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/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.Gluing
import Mathlib.CategoryTheory.Limits.Opposites
import Mathlib.AlgebraicGeometry.AffineScheme
import Mathlib.CategoryTheory.Limits.Shapes.Diagonal
#align_import algebraic_geometry.pullbacks from "leanprover-community/mathlib"@"7316286ff2942aa14e540add9058c6b0aa1c8070"
/-!
# Fibred products of schemes
In this file we construct the fibred product of schemes via gluing.
We roughly follow [har77] Theorem 3.3.
In particular, the main construction is to show that for an open cover `{ Uᵢ }` of `X`, if there
exist fibred products `Uᵢ ×[Z] Y` for each `i`, then there exists a fibred product `X ×[Z] Y`.
Then, for constructing the fibred product for arbitrary schemes `X, Y, Z`, we can use the
construction to reduce to the case where `X, Y, Z` are all affine, where fibred products are
constructed via tensor products.
-/
set_option linter.uppercaseLean3 false
universe v u
noncomputable section
open CategoryTheory CategoryTheory.Limits AlgebraicGeometry
namespace AlgebraicGeometry.Scheme
namespace Pullback
variable {C : Type u} [Category.{v} C]
variable {X Y Z : Scheme.{u}} (𝒰 : OpenCover.{u} X) (f : X ⟶ Z) (g : Y ⟶ Z)
variable [∀ i, HasPullback (𝒰.map i ≫ f) g]
/-- The intersection of `Uᵢ ×[Z] Y` and `Uⱼ ×[Z] Y` is given by (Uᵢ ×[Z] Y) ×[X] Uⱼ -/
def v (i j : 𝒰.J) : Scheme :=
pullback ((pullback.fst : pullback (𝒰.map i ≫ f) g ⟶ _) ≫ 𝒰.map i) (𝒰.map j)
#align algebraic_geometry.Scheme.pullback.V AlgebraicGeometry.Scheme.Pullback.v
/-- The canonical transition map `(Uᵢ ×[Z] Y) ×[X] Uⱼ ⟶ (Uⱼ ×[Z] Y) ×[X] Uᵢ` given by the fact
that pullbacks are associative and symmetric. -/
def t (i j : 𝒰.J) : v 𝒰 f g i j ⟶ v 𝒰 f g j i := by
have : HasPullback (pullback.snd ≫ 𝒰.map i ≫ f) g :=
hasPullback_assoc_symm (𝒰.map j) (𝒰.map i) (𝒰.map i ≫ f) g
have : HasPullback (pullback.snd ≫ 𝒰.map j ≫ f) g :=
hasPullback_assoc_symm (𝒰.map i) (𝒰.map j) (𝒰.map j ≫ f) g
refine (pullbackSymmetry ..).hom ≫ (pullbackAssoc ..).inv ≫ ?_
refine ?_ ≫ (pullbackAssoc ..).hom ≫ (pullbackSymmetry ..).hom
refine pullback.map _ _ _ _ (pullbackSymmetry _ _).hom (𝟙 _) (𝟙 _) ?_ ?_
· rw [pullbackSymmetry_hom_comp_snd_assoc, pullback.condition_assoc, Category.comp_id]
· rw [Category.comp_id, Category.id_comp]
#align algebraic_geometry.Scheme.pullback.t AlgebraicGeometry.Scheme.Pullback.t
@[simp, reassoc]
theorem t_fst_fst (i j : 𝒰.J) : t 𝒰 f g i j ≫ pullback.fst ≫ pullback.fst = pullback.snd := by
simp only [t, Category.assoc, pullbackSymmetry_hom_comp_fst_assoc, pullbackAssoc_hom_snd_fst,
pullback.lift_fst_assoc, pullbackSymmetry_hom_comp_snd, pullbackAssoc_inv_fst_fst,
pullbackSymmetry_hom_comp_fst]
#align algebraic_geometry.Scheme.pullback.t_fst_fst AlgebraicGeometry.Scheme.Pullback.t_fst_fst
@[simp, reassoc]
theorem t_fst_snd (i j : 𝒰.J) :
t 𝒰 f g i j ≫ pullback.fst ≫ pullback.snd = pullback.fst ≫ pullback.snd := by
simp only [t, Category.assoc, pullbackSymmetry_hom_comp_fst_assoc, pullbackAssoc_hom_snd_snd,
pullback.lift_snd, Category.comp_id, pullbackAssoc_inv_snd, pullbackSymmetry_hom_comp_snd_assoc]
#align algebraic_geometry.Scheme.pullback.t_fst_snd AlgebraicGeometry.Scheme.Pullback.t_fst_snd
@[simp, reassoc]
theorem t_snd (i j : 𝒰.J) : t 𝒰 f g i j ≫ pullback.snd = pullback.fst ≫ pullback.fst := by
simp only [t, Category.assoc, pullbackSymmetry_hom_comp_snd, pullbackAssoc_hom_fst,
pullback.lift_fst_assoc, pullbackSymmetry_hom_comp_fst, pullbackAssoc_inv_fst_snd,
pullbackSymmetry_hom_comp_snd_assoc]
#align algebraic_geometry.Scheme.pullback.t_snd AlgebraicGeometry.Scheme.Pullback.t_snd
theorem t_id (i : 𝒰.J) : t 𝒰 f g i i = 𝟙 _ := by
apply pullback.hom_ext <;> rw [Category.id_comp]
· apply pullback.hom_ext
· rw [← cancel_mono (𝒰.map i)]; simp only [pullback.condition, Category.assoc, t_fst_fst]
· simp only [Category.assoc, t_fst_snd]
· rw [← cancel_mono (𝒰.map i)]; simp only [pullback.condition, t_snd, Category.assoc]
#align algebraic_geometry.Scheme.pullback.t_id AlgebraicGeometry.Scheme.Pullback.t_id
/-- The inclusion map of `V i j = (Uᵢ ×[Z] Y) ×[X] Uⱼ ⟶ Uᵢ ×[Z] Y`-/
abbrev fV (i j : 𝒰.J) : v 𝒰 f g i j ⟶ pullback (𝒰.map i ≫ f) g :=
pullback.fst
#align algebraic_geometry.Scheme.pullback.fV AlgebraicGeometry.Scheme.Pullback.fV
/-- The map `((Xᵢ ×[Z] Y) ×[X] Xⱼ) ×[Xᵢ ×[Z] Y] ((Xᵢ ×[Z] Y) ×[X] Xₖ)` ⟶
`((Xⱼ ×[Z] Y) ×[X] Xₖ) ×[Xⱼ ×[Z] Y] ((Xⱼ ×[Z] Y) ×[X] Xᵢ)` needed for gluing -/
def t' (i j k : 𝒰.J) :
pullback (fV 𝒰 f g i j) (fV 𝒰 f g i k) ⟶ pullback (fV 𝒰 f g j k) (fV 𝒰 f g j i) := by
refine (pullbackRightPullbackFstIso ..).hom ≫ ?_
refine ?_ ≫ (pullbackSymmetry _ _).hom
refine ?_ ≫ (pullbackRightPullbackFstIso ..).inv
refine pullback.map _ _ _ _ (t 𝒰 f g i j) (𝟙 _) (𝟙 _) ?_ ?_
· simp_rw [Category.comp_id, t_fst_fst_assoc, ← pullback.condition]
· rw [Category.comp_id, Category.id_comp]
#align algebraic_geometry.Scheme.pullback.t' AlgebraicGeometry.Scheme.Pullback.t'
@[simp, reassoc]
theorem t'_fst_fst_fst (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.fst ≫ pullback.fst ≫ pullback.fst = pullback.fst ≫ pullback.snd := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_fst_assoc,
pullbackRightPullbackFstIso_inv_snd_fst_assoc, pullback.lift_fst_assoc, t_fst_fst,
pullbackRightPullbackFstIso_hom_fst_assoc]
#align algebraic_geometry.Scheme.pullback.t'_fst_fst_fst AlgebraicGeometry.Scheme.Pullback.t'_fst_fst_fst
@[simp, reassoc]
theorem t'_fst_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.fst ≫ pullback.fst ≫ pullback.snd =
pullback.fst ≫ pullback.fst ≫ pullback.snd := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_fst_assoc,
pullbackRightPullbackFstIso_inv_snd_fst_assoc, pullback.lift_fst_assoc, t_fst_snd,
pullbackRightPullbackFstIso_hom_fst_assoc]
#align algebraic_geometry.Scheme.pullback.t'_fst_fst_snd AlgebraicGeometry.Scheme.Pullback.t'_fst_fst_snd
@[simp, reassoc]
theorem t'_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.fst ≫ pullback.snd = pullback.snd ≫ pullback.snd := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_fst_assoc,
pullbackRightPullbackFstIso_inv_snd_snd, pullback.lift_snd, Category.comp_id,
pullbackRightPullbackFstIso_hom_snd]
#align algebraic_geometry.Scheme.pullback.t'_fst_snd AlgebraicGeometry.Scheme.Pullback.t'_fst_snd
@[simp, reassoc]
theorem t'_snd_fst_fst (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.snd ≫ pullback.fst ≫ pullback.fst = pullback.fst ≫ pullback.snd := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_snd_assoc,
pullbackRightPullbackFstIso_inv_fst_assoc, pullback.lift_fst_assoc, t_fst_fst,
pullbackRightPullbackFstIso_hom_fst_assoc]
#align algebraic_geometry.Scheme.pullback.t'_snd_fst_fst AlgebraicGeometry.Scheme.Pullback.t'_snd_fst_fst
@[simp, reassoc]
theorem t'_snd_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.snd ≫ pullback.fst ≫ pullback.snd =
pullback.fst ≫ pullback.fst ≫ pullback.snd := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_snd_assoc,
pullbackRightPullbackFstIso_inv_fst_assoc, pullback.lift_fst_assoc, t_fst_snd,
pullbackRightPullbackFstIso_hom_fst_assoc]
#align algebraic_geometry.Scheme.pullback.t'_snd_fst_snd AlgebraicGeometry.Scheme.Pullback.t'_snd_fst_snd
@[simp, reassoc]
theorem t'_snd_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ pullback.snd ≫ pullback.snd = pullback.fst ≫ pullback.fst ≫ pullback.fst := by
simp only [t', Category.assoc, pullbackSymmetry_hom_comp_snd_assoc,
pullbackRightPullbackFstIso_inv_fst_assoc, pullback.lift_fst_assoc, t_snd,
pullbackRightPullbackFstIso_hom_fst_assoc]
#align algebraic_geometry.Scheme.pullback.t'_snd_snd AlgebraicGeometry.Scheme.Pullback.t'_snd_snd
theorem cocycle_fst_fst_fst (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.fst ≫ pullback.fst ≫ pullback.fst =
pullback.fst ≫ pullback.fst ≫ pullback.fst := by
simp only [t'_fst_fst_fst, t'_fst_snd, t'_snd_snd]
#align algebraic_geometry.Scheme.pullback.cocycle_fst_fst_fst AlgebraicGeometry.Scheme.Pullback.cocycle_fst_fst_fst
theorem cocycle_fst_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.fst ≫ pullback.fst ≫ pullback.snd =
pullback.fst ≫ pullback.fst ≫ pullback.snd := by
simp only [t'_fst_fst_snd]
#align algebraic_geometry.Scheme.pullback.cocycle_fst_fst_snd AlgebraicGeometry.Scheme.Pullback.cocycle_fst_fst_snd
theorem cocycle_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.fst ≫ pullback.snd =
pullback.fst ≫ pullback.snd := by
simp only [t'_fst_snd, t'_snd_snd, t'_fst_fst_fst]
#align algebraic_geometry.Scheme.pullback.cocycle_fst_snd AlgebraicGeometry.Scheme.Pullback.cocycle_fst_snd
theorem cocycle_snd_fst_fst (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.snd ≫ pullback.fst ≫ pullback.fst =
pullback.snd ≫ pullback.fst ≫ pullback.fst := by
rw [← cancel_mono (𝒰.map i)]
simp only [pullback.condition_assoc, t'_snd_fst_fst, t'_fst_snd, t'_snd_snd]
#align algebraic_geometry.Scheme.pullback.cocycle_snd_fst_fst AlgebraicGeometry.Scheme.Pullback.cocycle_snd_fst_fst
theorem cocycle_snd_fst_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.snd ≫ pullback.fst ≫ pullback.snd =
pullback.snd ≫ pullback.fst ≫ pullback.snd := by
simp only [pullback.condition_assoc, t'_snd_fst_snd]
#align algebraic_geometry.Scheme.pullback.cocycle_snd_fst_snd AlgebraicGeometry.Scheme.Pullback.cocycle_snd_fst_snd
theorem cocycle_snd_snd (i j k : 𝒰.J) :
t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j ≫ pullback.snd ≫ pullback.snd =
pullback.snd ≫ pullback.snd := by
simp only [t'_snd_snd, t'_fst_fst_fst, t'_fst_snd]
#align algebraic_geometry.Scheme.pullback.cocycle_snd_snd AlgebraicGeometry.Scheme.Pullback.cocycle_snd_snd
-- `by tidy` should solve it, but it times out.
theorem cocycle (i j k : 𝒰.J) : t' 𝒰 f g i j k ≫ t' 𝒰 f g j k i ≫ t' 𝒰 f g k i j = 𝟙 _ := by
apply pullback.hom_ext <;> rw [Category.id_comp]
· apply pullback.hom_ext
· apply pullback.hom_ext
· simp_rw [Category.assoc, cocycle_fst_fst_fst 𝒰 f g i j k]
· simp_rw [Category.assoc, cocycle_fst_fst_snd 𝒰 f g i j k]
· simp_rw [Category.assoc, cocycle_fst_snd 𝒰 f g i j k]
· apply pullback.hom_ext
· apply pullback.hom_ext
· simp_rw [Category.assoc, cocycle_snd_fst_fst 𝒰 f g i j k]
· simp_rw [Category.assoc, cocycle_snd_fst_snd 𝒰 f g i j k]
· simp_rw [Category.assoc, cocycle_snd_snd 𝒰 f g i j k]
#align algebraic_geometry.Scheme.pullback.cocycle AlgebraicGeometry.Scheme.Pullback.cocycle
/-- Given `Uᵢ ×[Z] Y`, this is the glued fibered product `X ×[Z] Y`. -/
@[simps U V f t t', simps (config := .lemmasOnly) J]
def gluing : Scheme.GlueData.{u} where
J := 𝒰.J
U i := pullback (𝒰.map i ≫ f) g
V := fun ⟨i, j⟩ => v 𝒰 f g i j
-- `p⁻¹(Uᵢ ∩ Uⱼ)` where `p : Uᵢ ×[Z] Y ⟶ Uᵢ ⟶ X`.
f i j := pullback.fst
f_id i := inferInstance
f_open := inferInstance
t i j := t 𝒰 f g i j
t_id i := t_id 𝒰 f g i
t' i j k := t' 𝒰 f g i j k
t_fac i j k := by
apply pullback.hom_ext
on_goal 1 => apply pullback.hom_ext
all_goals
simp only [t'_snd_fst_fst, t'_snd_fst_snd, t'_snd_snd, t_fst_fst, t_fst_snd, t_snd,
Category.assoc]
cocycle i j k := cocycle 𝒰 f g i j k
#align algebraic_geometry.Scheme.pullback.gluing AlgebraicGeometry.Scheme.Pullback.gluing
@[simp]
lemma gluing_ι (j : 𝒰.J) :
(gluing 𝒰 f g).ι j = Multicoequalizer.π (gluing 𝒰 f g).diagram j := rfl
/-- The first projection from the glued scheme into `X`. -/
def p1 : (gluing 𝒰 f g).glued ⟶ X := by
apply Multicoequalizer.desc (gluing 𝒰 f g).diagram _ fun i ↦ pullback.fst ≫ 𝒰.map i
simp [t_fst_fst_assoc, ← pullback.condition]
#align algebraic_geometry.Scheme.pullback.p1 AlgebraicGeometry.Scheme.Pullback.p1
/-- The second projection from the glued scheme into `Y`. -/
def p2 : (gluing 𝒰 f g).glued ⟶ Y := by
apply Multicoequalizer.desc _ _ fun i ↦ pullback.snd
simp [t_fst_snd]
#align algebraic_geometry.Scheme.pullback.p2 AlgebraicGeometry.Scheme.Pullback.p2
theorem p_comm : p1 𝒰 f g ≫ f = p2 𝒰 f g ≫ g := by
apply Multicoequalizer.hom_ext
simp [p1, p2, pullback.condition]
#align algebraic_geometry.Scheme.pullback.p_comm AlgebraicGeometry.Scheme.Pullback.p_comm
variable (s : PullbackCone f g)
/-- (Implementation)
The canonical map `(s.X ×[X] Uᵢ) ×[s.X] (s.X ×[X] Uⱼ) ⟶ (Uᵢ ×[Z] Y) ×[X] Uⱼ`
This is used in `gluedLift`. -/
def gluedLiftPullbackMap (i j : 𝒰.J) :
pullback ((𝒰.pullbackCover s.fst).map i) ((𝒰.pullbackCover s.fst).map j) ⟶
(gluing 𝒰 f g).V ⟨i, j⟩ := by
refine (pullbackRightPullbackFstIso _ _ _).hom ≫ ?_
refine pullback.map _ _ _ _ ?_ (𝟙 _) (𝟙 _) ?_ ?_
· exact (pullbackSymmetry _ _).hom ≫
pullback.map _ _ _ _ (𝟙 _) s.snd f (Category.id_comp _).symm s.condition
· simpa using pullback.condition
· simp only [Category.comp_id, Category.id_comp]
#align algebraic_geometry.Scheme.pullback.glued_lift_pullback_map AlgebraicGeometry.Scheme.Pullback.gluedLiftPullbackMap
@[reassoc]
theorem gluedLiftPullbackMap_fst (i j : 𝒰.J) :
gluedLiftPullbackMap 𝒰 f g s i j ≫ pullback.fst =
pullback.fst ≫
(pullbackSymmetry _ _).hom ≫
pullback.map _ _ _ _ (𝟙 _) s.snd f (Category.id_comp _).symm s.condition := by
simp [gluedLiftPullbackMap]
#align algebraic_geometry.Scheme.pullback.glued_lift_pullback_map_fst AlgebraicGeometry.Scheme.Pullback.gluedLiftPullbackMap_fst
@[reassoc]
theorem gluedLiftPullbackMap_snd (i j : 𝒰.J) :
gluedLiftPullbackMap 𝒰 f g s i j ≫ pullback.snd = pullback.snd ≫ pullback.snd := by
simp [gluedLiftPullbackMap]
#align algebraic_geometry.Scheme.pullback.glued_lift_pullback_map_snd AlgebraicGeometry.Scheme.Pullback.gluedLiftPullbackMap_snd
/-- The lifted map `s.X ⟶ (gluing 𝒰 f g).glued` in order to show that `(gluing 𝒰 f g).glued` is
indeed the pullback.
Given a pullback cone `s`, we have the maps `s.fst ⁻¹' Uᵢ ⟶ Uᵢ` and
`s.fst ⁻¹' Uᵢ ⟶ s.X ⟶ Y` that we may lift to a map `s.fst ⁻¹' Uᵢ ⟶ Uᵢ ×[Z] Y`.
to glue these into a map `s.X ⟶ Uᵢ ×[Z] Y`, we need to show that the maps agree on
`(s.fst ⁻¹' Uᵢ) ×[s.X] (s.fst ⁻¹' Uⱼ) ⟶ Uᵢ ×[Z] Y`. This is achieved by showing that both of these
maps factors through `gluedLiftPullbackMap`.
-/
def gluedLift : s.pt ⟶ (gluing 𝒰 f g).glued := by
fapply (𝒰.pullbackCover s.fst).glueMorphisms
· exact fun i ↦ (pullbackSymmetry _ _).hom ≫
pullback.map _ _ _ _ (𝟙 _) s.snd f (Category.id_comp _).symm s.condition ≫ (gluing 𝒰 f g).ι i
intro i j
rw [← gluedLiftPullbackMap_fst_assoc, ← gluing_f, ← (gluing 𝒰 f g).glue_condition i j,
gluing_t, gluing_f]
simp_rw [← Category.assoc]
congr 1
apply pullback.hom_ext <;> simp_rw [Category.assoc]
· rw [t_fst_fst, gluedLiftPullbackMap_snd]
congr 1
rw [← Iso.inv_comp_eq, pullbackSymmetry_inv_comp_snd, pullback.lift_fst, Category.comp_id]
· rw [t_fst_snd, gluedLiftPullbackMap_fst_assoc, pullback.lift_snd, pullback.lift_snd]
simp_rw [pullbackSymmetry_hom_comp_snd_assoc]
exact pullback.condition_assoc _
#align algebraic_geometry.Scheme.pullback.glued_lift AlgebraicGeometry.Scheme.Pullback.gluedLift
theorem gluedLift_p1 : gluedLift 𝒰 f g s ≫ p1 𝒰 f g = s.fst := by
rw [← cancel_epi (𝒰.pullbackCover s.fst).fromGlued]
apply Multicoequalizer.hom_ext
intro b
simp_rw [OpenCover.fromGlued, Multicoequalizer.π_desc_assoc, gluedLift, ← Category.assoc]
simp_rw [(𝒰.pullbackCover s.fst).ι_glueMorphisms]
simp [p1, pullback.condition]
#align algebraic_geometry.Scheme.pullback.glued_lift_p1 AlgebraicGeometry.Scheme.Pullback.gluedLift_p1
theorem gluedLift_p2 : gluedLift 𝒰 f g s ≫ p2 𝒰 f g = s.snd := by
rw [← cancel_epi (𝒰.pullbackCover s.fst).fromGlued]
apply Multicoequalizer.hom_ext
intro b
simp_rw [OpenCover.fromGlued, Multicoequalizer.π_desc_assoc, gluedLift, ← Category.assoc]
simp_rw [(𝒰.pullbackCover s.fst).ι_glueMorphisms]
simp [p2, pullback.condition]
#align algebraic_geometry.Scheme.pullback.glued_lift_p2 AlgebraicGeometry.Scheme.Pullback.gluedLift_p2
/-- (Implementation)
The canonical map `(W ×[X] Uᵢ) ×[W] (Uⱼ ×[Z] Y) ⟶ (Uⱼ ×[Z] Y) ×[X] Uᵢ = V j i` where `W` is
the glued fibred product.
This is used in `lift_comp_ι`. -/
def pullbackFstιToV (i j : 𝒰.J) :
pullback (pullback.fst : pullback (p1 𝒰 f g) (𝒰.map i) ⟶ _) ((gluing 𝒰 f g).ι j) ⟶
v 𝒰 f g j i :=
(pullbackSymmetry _ _ ≪≫ pullbackRightPullbackFstIso (p1 𝒰 f g) (𝒰.map i) _).hom ≫
(pullback.congrHom (Multicoequalizer.π_desc ..) rfl).hom
#align algebraic_geometry.Scheme.pullback.pullback_fst_ι_to_V AlgebraicGeometry.Scheme.Pullback.pullbackFstιToV
@[simp, reassoc]
theorem pullbackFstιToV_fst (i j : 𝒰.J) :
pullbackFstιToV 𝒰 f g i j ≫ pullback.fst = pullback.snd := by
simp [pullbackFstιToV, p1]
#align algebraic_geometry.Scheme.pullback.pullback_fst_ι_to_V_fst AlgebraicGeometry.Scheme.Pullback.pullbackFstιToV_fst
@[simp, reassoc]
theorem pullbackFstιToV_snd (i j : 𝒰.J) :
pullbackFstιToV 𝒰 f g i j ≫ pullback.snd = pullback.fst ≫ pullback.snd := by
simp [pullbackFstιToV, p1]
#align algebraic_geometry.Scheme.pullback.pullback_fst_ι_to_V_snd AlgebraicGeometry.Scheme.Pullback.pullbackFstιToV_snd
/-- We show that the map `W ×[X] Uᵢ ⟶ Uᵢ ×[Z] Y ⟶ W` is the first projection, where the
first map is given by the lift of `W ×[X] Uᵢ ⟶ Uᵢ` and `W ×[X] Uᵢ ⟶ W ⟶ Y`.
It suffices to show that the two map agrees when restricted onto `Uⱼ ×[Z] Y`. In this case,
both maps factor through `V j i` via `pullback_fst_ι_to_V` -/
theorem lift_comp_ι (i : 𝒰.J) :
pullback.lift pullback.snd (pullback.fst ≫ p2 𝒰 f g)
(by rw [← pullback.condition_assoc, Category.assoc, p_comm]) ≫
(gluing 𝒰 f g).ι i =
(pullback.fst : pullback (p1 𝒰 f g) (𝒰.map i) ⟶ _) := by
apply ((gluing 𝒰 f g).openCover.pullbackCover pullback.fst).hom_ext
intro j
dsimp only [OpenCover.pullbackCover]
trans pullbackFstιToV 𝒰 f g i j ≫ fV 𝒰 f g j i ≫ (gluing 𝒰 f g).ι _
· rw [← show _ = fV 𝒰 f g j i ≫ _ from (gluing 𝒰 f g).glue_condition j i]
simp_rw [← Category.assoc]
congr 1
rw [gluing_f, gluing_t]
apply pullback.hom_ext <;> simp_rw [Category.assoc]
· simp_rw [t_fst_fst, pullback.lift_fst, pullbackFstιToV_snd, GlueData.openCover_map]
· simp_rw [t_fst_snd, pullback.lift_snd, pullbackFstιToV_fst_assoc, pullback.condition_assoc,
GlueData.openCover_map, p2]
simp
· rw [pullback.condition, ← Category.assoc]
simp_rw [pullbackFstιToV_fst, GlueData.openCover_map]
#align algebraic_geometry.Scheme.pullback.lift_comp_ι AlgebraicGeometry.Scheme.Pullback.lift_comp_ι
/-- The canonical isomorphism between `W ×[X] Uᵢ` and `Uᵢ ×[X] Y`. That is, the preimage of `Uᵢ` in
`W` along `p1` is indeed `Uᵢ ×[X] Y`. -/
def pullbackP1Iso (i : 𝒰.J) : pullback (p1 𝒰 f g) (𝒰.map i) ≅ pullback (𝒰.map i ≫ f) g := by
fconstructor
· exact
pullback.lift pullback.snd (pullback.fst ≫ p2 𝒰 f g)
(by rw [← pullback.condition_assoc, Category.assoc, p_comm])
· apply pullback.lift ((gluing 𝒰 f g).ι i) pullback.fst
rw [gluing_ι, p1, Multicoequalizer.π_desc]
· apply pullback.hom_ext
· simpa using lift_comp_ι 𝒰 f g i
· simp_rw [Category.assoc, pullback.lift_snd, pullback.lift_fst, Category.id_comp]
· apply pullback.hom_ext
· simp_rw [Category.assoc, pullback.lift_fst, pullback.lift_snd, Category.id_comp]
· simp [p2]
#align algebraic_geometry.Scheme.pullback.pullback_p1_iso AlgebraicGeometry.Scheme.Pullback.pullbackP1Iso
@[simp, reassoc]
| Mathlib/AlgebraicGeometry/Pullbacks.lean | 401 | 403 | theorem pullbackP1Iso_hom_fst (i : 𝒰.J) :
(pullbackP1Iso 𝒰 f g i).hom ≫ pullback.fst = pullback.snd := by |
simp_rw [pullbackP1Iso, pullback.lift_fst]
|
/-
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.VectorMeasure
import Mathlib.MeasureTheory.Function.AEEqOfIntegral
#align_import measure_theory.measure.with_density_vector_measure from "leanprover-community/mathlib"@"d1bd9c5df2867c1cb463bc6364446d57bdd9f7f1"
/-!
# Vector measure defined by an integral
Given a measure `μ` and an integrable function `f : α → E`, we can define a vector measure `v` such
that for all measurable set `s`, `v i = ∫ x in s, f x ∂μ`. This definition is useful for
the Radon-Nikodym theorem for signed measures.
## Main definitions
* `MeasureTheory.Measure.withDensityᵥ`: the vector measure formed by integrating a function `f`
with respect to a measure `μ` on some set if `f` is integrable, and `0` otherwise.
-/
noncomputable section
open scoped Classical MeasureTheory NNReal ENNReal
variable {α β : Type*} {m : MeasurableSpace α}
namespace MeasureTheory
open TopologicalSpace
variable {μ ν : Measure α}
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E]
/-- Given a measure `μ` and an integrable function `f`, `μ.withDensityᵥ f` is
the vector measure which maps the set `s` to `∫ₛ f ∂μ`. -/
def Measure.withDensityᵥ {m : MeasurableSpace α} (μ : Measure α) (f : α → E) : VectorMeasure α E :=
if hf : Integrable f μ then
{ measureOf' := fun s => if MeasurableSet s then ∫ x in s, f x ∂μ else 0
empty' := by simp
not_measurable' := fun s hs => if_neg hs
m_iUnion' := fun s hs₁ hs₂ => by
dsimp only
convert hasSum_integral_iUnion hs₁ hs₂ hf.integrableOn with n
· rw [if_pos (hs₁ n)]
· rw [if_pos (MeasurableSet.iUnion hs₁)] }
else 0
#align measure_theory.measure.with_densityᵥ MeasureTheory.Measure.withDensityᵥ
open Measure
variable {f g : α → E}
theorem withDensityᵥ_apply (hf : Integrable f μ) {s : Set α} (hs : MeasurableSet s) :
μ.withDensityᵥ f s = ∫ x in s, f x ∂μ := by rw [withDensityᵥ, dif_pos hf]; exact dif_pos hs
#align measure_theory.with_densityᵥ_apply MeasureTheory.withDensityᵥ_apply
@[simp]
theorem withDensityᵥ_zero : μ.withDensityᵥ (0 : α → E) = 0 := by
ext1 s hs; erw [withDensityᵥ_apply (integrable_zero α E μ) hs]; simp
#align measure_theory.with_densityᵥ_zero MeasureTheory.withDensityᵥ_zero
@[simp]
theorem withDensityᵥ_neg : μ.withDensityᵥ (-f) = -μ.withDensityᵥ f := by
by_cases hf : Integrable f μ
· ext1 i hi
rw [VectorMeasure.neg_apply, withDensityᵥ_apply hf hi, ← integral_neg,
withDensityᵥ_apply hf.neg hi]
rfl
· rw [withDensityᵥ, withDensityᵥ, dif_neg hf, dif_neg, neg_zero]
rwa [integrable_neg_iff]
#align measure_theory.with_densityᵥ_neg MeasureTheory.withDensityᵥ_neg
theorem withDensityᵥ_neg' : (μ.withDensityᵥ fun x => -f x) = -μ.withDensityᵥ f :=
withDensityᵥ_neg
#align measure_theory.with_densityᵥ_neg' MeasureTheory.withDensityᵥ_neg'
@[simp]
theorem withDensityᵥ_add (hf : Integrable f μ) (hg : Integrable g μ) :
μ.withDensityᵥ (f + g) = μ.withDensityᵥ f + μ.withDensityᵥ g := by
ext1 i hi
rw [withDensityᵥ_apply (hf.add hg) hi, VectorMeasure.add_apply, withDensityᵥ_apply hf hi,
withDensityᵥ_apply hg hi]
simp_rw [Pi.add_apply]
rw [integral_add] <;> rw [← integrableOn_univ]
· exact hf.integrableOn.restrict MeasurableSet.univ
· exact hg.integrableOn.restrict MeasurableSet.univ
#align measure_theory.with_densityᵥ_add MeasureTheory.withDensityᵥ_add
theorem withDensityᵥ_add' (hf : Integrable f μ) (hg : Integrable g μ) :
(μ.withDensityᵥ fun x => f x + g x) = μ.withDensityᵥ f + μ.withDensityᵥ g :=
withDensityᵥ_add hf hg
#align measure_theory.with_densityᵥ_add' MeasureTheory.withDensityᵥ_add'
@[simp]
| Mathlib/MeasureTheory/Measure/WithDensityVectorMeasure.lean | 101 | 103 | theorem withDensityᵥ_sub (hf : Integrable f μ) (hg : Integrable g μ) :
μ.withDensityᵥ (f - g) = μ.withDensityᵥ f - μ.withDensityᵥ g := by |
rw [sub_eq_add_neg, sub_eq_add_neg, withDensityᵥ_add hf hg.neg, withDensityᵥ_neg]
|
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky, Chris Hughes
-/
import Mathlib.Data.List.Nodup
#align_import data.list.duplicate from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e"
/-!
# List duplicates
## Main definitions
* `List.Duplicate x l : Prop` is an inductive property that holds when `x` is a duplicate in `l`
## Implementation details
In this file, `x ∈+ l` notation is shorthand for `List.Duplicate x l`.
-/
variable {α : Type*}
namespace List
/-- Property that an element `x : α` of `l : List α` can be found in the list more than once. -/
inductive Duplicate (x : α) : List α → Prop
| cons_mem {l : List α} : x ∈ l → Duplicate x (x :: l)
| cons_duplicate {y : α} {l : List α} : Duplicate x l → Duplicate x (y :: l)
#align list.duplicate List.Duplicate
local infixl:50 " ∈+ " => List.Duplicate
variable {l : List α} {x : α}
theorem Mem.duplicate_cons_self (h : x ∈ l) : x ∈+ x :: l :=
Duplicate.cons_mem h
#align list.mem.duplicate_cons_self List.Mem.duplicate_cons_self
theorem Duplicate.duplicate_cons (h : x ∈+ l) (y : α) : x ∈+ y :: l :=
Duplicate.cons_duplicate h
#align list.duplicate.duplicate_cons List.Duplicate.duplicate_cons
theorem Duplicate.mem (h : x ∈+ l) : x ∈ l := by
induction' h with l' _ y l' _ hm
· exact mem_cons_self _ _
· exact mem_cons_of_mem _ hm
#align list.duplicate.mem List.Duplicate.mem
theorem Duplicate.mem_cons_self (h : x ∈+ x :: l) : x ∈ l := by
cases' h with _ h _ _ h
· exact h
· exact h.mem
#align list.duplicate.mem_cons_self List.Duplicate.mem_cons_self
@[simp]
theorem duplicate_cons_self_iff : x ∈+ x :: l ↔ x ∈ l :=
⟨Duplicate.mem_cons_self, Mem.duplicate_cons_self⟩
#align list.duplicate_cons_self_iff List.duplicate_cons_self_iff
theorem Duplicate.ne_nil (h : x ∈+ l) : l ≠ [] := fun H => (mem_nil_iff x).mp (H ▸ h.mem)
#align list.duplicate.ne_nil List.Duplicate.ne_nil
@[simp]
theorem not_duplicate_nil (x : α) : ¬x ∈+ [] := fun H => H.ne_nil rfl
#align list.not_duplicate_nil List.not_duplicate_nil
| Mathlib/Data/List/Duplicate.lean | 70 | 73 | theorem Duplicate.ne_singleton (h : x ∈+ l) (y : α) : l ≠ [y] := by |
induction' h with l' h z l' h _
· simp [ne_nil_of_mem h]
· simp [ne_nil_of_mem h.mem]
|
/-
Copyright (c) 2018 Andreas Swerdlow. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andreas Swerdlow, Kexing Ying
-/
import Mathlib.Algebra.GroupWithZero.NonZeroDivisors
import Mathlib.LinearAlgebra.BilinearForm.Properties
/-!
# Bilinear form
This file defines orthogonal bilinear forms.
## Notations
Given any term `B` of type `BilinForm`, due to a coercion, can use
the notation `B x y` to refer to the function field, ie. `B x y = B.bilin x y`.
In this file we use the following type variables:
- `M`, `M'`, ... are modules over the commutative semiring `R`,
- `M₁`, `M₁'`, ... are modules over the commutative ring `R₁`,
- `V`, ... is a vector space over the field `K`.
## References
* <https://en.wikipedia.org/wiki/Bilinear_form>
## Tags
Bilinear form,
-/
open LinearMap (BilinForm)
universe u v w
variable {R : Type*} {M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M]
variable {R₁ : Type*} {M₁ : Type*} [CommRing R₁] [AddCommGroup M₁] [Module R₁ M₁]
variable {V : Type*} {K : Type*} [Field K] [AddCommGroup V] [Module K V]
variable {B : BilinForm R M} {B₁ : BilinForm R₁ M₁}
namespace LinearMap
namespace BilinForm
/-- The proposition that two elements of a bilinear form space are orthogonal. For orthogonality
of an indexed set of elements, use `BilinForm.iIsOrtho`. -/
def IsOrtho (B : BilinForm R M) (x y : M) : Prop :=
B x y = 0
#align bilin_form.is_ortho LinearMap.BilinForm.IsOrtho
theorem isOrtho_def {B : BilinForm R M} {x y : M} : B.IsOrtho x y ↔ B x y = 0 :=
Iff.rfl
#align bilin_form.is_ortho_def LinearMap.BilinForm.isOrtho_def
theorem isOrtho_zero_left (x : M) : IsOrtho B (0 : M) x := LinearMap.isOrtho_zero_left B x
#align bilin_form.is_ortho_zero_left LinearMap.BilinForm.isOrtho_zero_left
theorem isOrtho_zero_right (x : M) : IsOrtho B x (0 : M) :=
zero_right x
#align bilin_form.is_ortho_zero_right LinearMap.BilinForm.isOrtho_zero_right
theorem ne_zero_of_not_isOrtho_self {B : BilinForm K V} (x : V) (hx₁ : ¬B.IsOrtho x x) : x ≠ 0 :=
fun hx₂ => hx₁ (hx₂.symm ▸ isOrtho_zero_left _)
#align bilin_form.ne_zero_of_not_is_ortho_self LinearMap.BilinForm.ne_zero_of_not_isOrtho_self
theorem IsRefl.ortho_comm (H : B.IsRefl) {x y : M} : IsOrtho B x y ↔ IsOrtho B y x :=
⟨eq_zero H, eq_zero H⟩
#align bilin_form.is_refl.ortho_comm LinearMap.BilinForm.IsRefl.ortho_comm
theorem IsAlt.ortho_comm (H : B₁.IsAlt) {x y : M₁} : IsOrtho B₁ x y ↔ IsOrtho B₁ y x :=
LinearMap.IsAlt.ortho_comm H
#align bilin_form.is_alt.ortho_comm LinearMap.BilinForm.IsAlt.ortho_comm
theorem IsSymm.ortho_comm (H : B.IsSymm) {x y : M} : IsOrtho B x y ↔ IsOrtho B y x :=
LinearMap.IsSymm.ortho_comm H
#align bilin_form.is_symm.ortho_comm LinearMap.BilinForm.IsSymm.ortho_comm
/-- A set of vectors `v` is orthogonal with respect to some bilinear form `B` if and only
if for all `i ≠ j`, `B (v i) (v j) = 0`. For orthogonality between two elements, use
`BilinForm.IsOrtho` -/
def iIsOrtho {n : Type w} (B : BilinForm R M) (v : n → M) : Prop :=
B.IsOrthoᵢ v
set_option linter.uppercaseLean3 false in
#align bilin_form.is_Ortho LinearMap.BilinForm.iIsOrtho
theorem iIsOrtho_def {n : Type w} {B : BilinForm R M} {v : n → M} :
B.iIsOrtho v ↔ ∀ i j : n, i ≠ j → B (v i) (v j) = 0 :=
Iff.rfl
set_option linter.uppercaseLean3 false in
#align bilin_form.is_Ortho_def LinearMap.BilinForm.iIsOrtho_def
section
variable {R₄ M₄ : Type*} [CommRing R₄] [IsDomain R₄]
variable [AddCommGroup M₄] [Module R₄ M₄] {G : BilinForm R₄ M₄}
@[simp]
theorem isOrtho_smul_left {x y : M₄} {a : R₄} (ha : a ≠ 0) :
IsOrtho G (a • x) y ↔ IsOrtho G x y := by
dsimp only [IsOrtho]
rw [map_smul]
simp only [LinearMap.smul_apply, smul_eq_mul, mul_eq_zero, or_iff_right_iff_imp]
exact fun a ↦ (ha a).elim
#align bilin_form.is_ortho_smul_left LinearMap.BilinForm.isOrtho_smul_left
@[simp]
theorem isOrtho_smul_right {x y : M₄} {a : R₄} (ha : a ≠ 0) :
IsOrtho G x (a • y) ↔ IsOrtho G x y := by
dsimp only [IsOrtho]
rw [map_smul]
simp only [smul_eq_mul, mul_eq_zero, or_iff_right_iff_imp]
exact fun a ↦ (ha a).elim
#align bilin_form.is_ortho_smul_right LinearMap.BilinForm.isOrtho_smul_right
/-- A set of orthogonal vectors `v` with respect to some bilinear form `B` is linearly independent
if for all `i`, `B (v i) (v i) ≠ 0`. -/
theorem linearIndependent_of_iIsOrtho {n : Type w} {B : BilinForm K V} {v : n → V}
(hv₁ : B.iIsOrtho v) (hv₂ : ∀ i, ¬B.IsOrtho (v i) (v i)) : LinearIndependent K v := by
classical
rw [linearIndependent_iff']
intro s w hs i hi
have : B (s.sum fun i : n => w i • v i) (v i) = 0 := by rw [hs, zero_left]
have hsum : (s.sum fun j : n => w j * B (v j) (v i)) = w i * B (v i) (v i) := by
apply Finset.sum_eq_single_of_mem i hi
intro j _ hij
rw [iIsOrtho_def.1 hv₁ _ _ hij, mul_zero]
simp_rw [sum_left, smul_left, hsum] at this
exact eq_zero_of_ne_zero_of_mul_right_eq_zero (hv₂ i) this
set_option linter.uppercaseLean3 false in
#align bilin_form.linear_independent_of_is_Ortho LinearMap.BilinForm.linearIndependent_of_iIsOrtho
end
section Orthogonal
/-- The orthogonal complement of a submodule `N` with respect to some bilinear form is the set of
elements `x` which are orthogonal to all elements of `N`; i.e., for all `y` in `N`, `B x y = 0`.
Note that for general (neither symmetric nor antisymmetric) bilinear forms this definition has a
chirality; in addition to this "left" orthogonal complement one could define a "right" orthogonal
complement for which, for all `y` in `N`, `B y x = 0`. This variant definition is not currently
provided in mathlib. -/
def orthogonal (B : BilinForm R M) (N : Submodule R M) : Submodule R M where
carrier := { m | ∀ n ∈ N, IsOrtho B n m }
zero_mem' x _ := isOrtho_zero_right x
add_mem' {x y} hx hy n hn := by
rw [IsOrtho, add_right, show B n x = 0 from hx n hn, show B n y = 0 from hy n hn, zero_add]
smul_mem' c x hx n hn := by
rw [IsOrtho, smul_right, show B n x = 0 from hx n hn, mul_zero]
#align bilin_form.orthogonal LinearMap.BilinForm.orthogonal
variable {N L : Submodule R M}
@[simp]
theorem mem_orthogonal_iff {N : Submodule R M} {m : M} :
m ∈ B.orthogonal N ↔ ∀ n ∈ N, IsOrtho B n m :=
Iff.rfl
#align bilin_form.mem_orthogonal_iff LinearMap.BilinForm.mem_orthogonal_iff
@[simp] lemma orthogonal_bot : B.orthogonal ⊥ = ⊤ := by ext; simp [IsOrtho]
theorem orthogonal_le (h : N ≤ L) : B.orthogonal L ≤ B.orthogonal N := fun _ hn l hl => hn l (h hl)
#align bilin_form.orthogonal_le LinearMap.BilinForm.orthogonal_le
theorem le_orthogonal_orthogonal (b : B.IsRefl) : N ≤ B.orthogonal (B.orthogonal N) :=
fun n hn _ hm => b _ _ (hm n hn)
#align bilin_form.le_orthogonal_orthogonal LinearMap.BilinForm.le_orthogonal_orthogonal
lemma orthogonal_top (hB : B.Nondegenerate) (hB₀ : B.IsRefl) :
B.orthogonal ⊤ = ⊥ :=
(Submodule.eq_bot_iff _).mpr fun _ hx ↦ hB _ fun y ↦ hB₀ _ _ <| hx y Submodule.mem_top
-- ↓ This lemma only applies in fields as we require `a * b = 0 → a = 0 ∨ b = 0`
theorem span_singleton_inf_orthogonal_eq_bot {B : BilinForm K V} {x : V} (hx : ¬B.IsOrtho x x) :
(K ∙ x) ⊓ B.orthogonal (K ∙ x) = ⊥ := by
rw [← Finset.coe_singleton]
refine eq_bot_iff.2 fun y h => ?_
rcases mem_span_finset.1 h.1 with ⟨μ, rfl⟩
have := h.2 x ?_
· rw [Finset.sum_singleton] at this ⊢
suffices hμzero : μ x = 0 by rw [hμzero, zero_smul, Submodule.mem_bot]
change B x (μ x • x) = 0 at this
rw [smul_right] at this
exact eq_zero_of_ne_zero_of_mul_right_eq_zero hx this
· rw [Submodule.mem_span]
exact fun _ hp => hp <| Finset.mem_singleton_self _
#align bilin_form.span_singleton_inf_orthogonal_eq_bot LinearMap.BilinForm.span_singleton_inf_orthogonal_eq_bot
-- ↓ This lemma only applies in fields since we use the `mul_eq_zero`
theorem orthogonal_span_singleton_eq_toLin_ker {B : BilinForm K V} (x : V) :
B.orthogonal (K ∙ x) = LinearMap.ker (LinearMap.BilinForm.toLinHomAux₁ B x) := by
ext y
simp_rw [mem_orthogonal_iff, LinearMap.mem_ker, Submodule.mem_span_singleton]
constructor
· exact fun h => h x ⟨1, one_smul _ _⟩
· rintro h _ ⟨z, rfl⟩
rw [IsOrtho, smul_left, mul_eq_zero]
exact Or.intro_right _ h
#align bilin_form.orthogonal_span_singleton_eq_to_lin_ker LinearMap.BilinForm.orthogonal_span_singleton_eq_toLin_ker
theorem span_singleton_sup_orthogonal_eq_top {B : BilinForm K V} {x : V} (hx : ¬B.IsOrtho x x) :
(K ∙ x) ⊔ B.orthogonal (K ∙ x) = ⊤ := by
rw [orthogonal_span_singleton_eq_toLin_ker]
exact LinearMap.span_singleton_sup_ker_eq_top _ hx
#align bilin_form.span_singleton_sup_orthogonal_eq_top LinearMap.BilinForm.span_singleton_sup_orthogonal_eq_top
/-- Given a bilinear form `B` and some `x` such that `B x x ≠ 0`, the span of the singleton of `x`
is complement to its orthogonal complement. -/
theorem isCompl_span_singleton_orthogonal {B : BilinForm K V} {x : V} (hx : ¬B.IsOrtho x x) :
IsCompl (K ∙ x) (B.orthogonal <| K ∙ x) :=
{ disjoint := disjoint_iff.2 <| span_singleton_inf_orthogonal_eq_bot hx
codisjoint := codisjoint_iff.2 <| span_singleton_sup_orthogonal_eq_top hx }
#align bilin_form.is_compl_span_singleton_orthogonal LinearMap.BilinForm.isCompl_span_singleton_orthogonal
end Orthogonal
variable {M₂' : Type*}
variable [AddCommMonoid M₂'] [Module R M₂']
/-- The restriction of a reflexive bilinear form `B` onto a submodule `W` is
nondegenerate if `Disjoint W (B.orthogonal W)`. -/
theorem nondegenerate_restrict_of_disjoint_orthogonal (B : BilinForm R₁ M₁) (b : B.IsRefl)
{W : Submodule R₁ M₁} (hW : Disjoint W (B.orthogonal W)) : (B.restrict W).Nondegenerate := by
rintro ⟨x, hx⟩ b₁
rw [Submodule.mk_eq_zero, ← Submodule.mem_bot R₁]
refine hW.le_bot ⟨hx, fun y hy => ?_⟩
specialize b₁ ⟨y, hy⟩
simp only [restrict_apply, domRestrict_apply] at b₁
exact isOrtho_def.mpr (b x y b₁)
#align bilin_form.nondegenerate_restrict_of_disjoint_orthogonal LinearMap.BilinForm.nondegenerate_restrict_of_disjoint_orthogonal
@[deprecated (since := "2024-05-30")]
alias nondegenerateRestrictOfDisjointOrthogonal := nondegenerate_restrict_of_disjoint_orthogonal
/-- An orthogonal basis with respect to a nondegenerate bilinear form has no self-orthogonal
elements. -/
theorem iIsOrtho.not_isOrtho_basis_self_of_nondegenerate {n : Type w} [Nontrivial R]
{B : BilinForm R M} {v : Basis n R M} (h : B.iIsOrtho v) (hB : B.Nondegenerate) (i : n) :
¬B.IsOrtho (v i) (v i) := by
intro ho
refine v.ne_zero i (hB (v i) fun m => ?_)
obtain ⟨vi, rfl⟩ := v.repr.symm.surjective m
rw [Basis.repr_symm_apply, Finsupp.total_apply, Finsupp.sum, sum_right]
apply Finset.sum_eq_zero
rintro j -
rw [smul_right]
convert mul_zero (vi j) using 2
obtain rfl | hij := eq_or_ne i j
· exact ho
· exact h hij
set_option linter.uppercaseLean3 false in
#align bilin_form.is_Ortho.not_is_ortho_basis_self_of_nondegenerate LinearMap.BilinForm.iIsOrtho.not_isOrtho_basis_self_of_nondegenerate
/-- Given an orthogonal basis with respect to a bilinear form, the bilinear form is nondegenerate
iff the basis has no elements which are self-orthogonal. -/
theorem iIsOrtho.nondegenerate_iff_not_isOrtho_basis_self {n : Type w} [Nontrivial R]
[NoZeroDivisors R] (B : BilinForm R M) (v : Basis n R M) (hO : B.iIsOrtho v) :
B.Nondegenerate ↔ ∀ i, ¬B.IsOrtho (v i) (v i) := by
refine ⟨hO.not_isOrtho_basis_self_of_nondegenerate, fun ho m hB => ?_⟩
obtain ⟨vi, rfl⟩ := v.repr.symm.surjective m
rw [LinearEquiv.map_eq_zero_iff]
ext i
rw [Finsupp.zero_apply]
specialize hB (v i)
simp_rw [Basis.repr_symm_apply, Finsupp.total_apply, Finsupp.sum, sum_left, smul_left] at hB
rw [Finset.sum_eq_single i] at hB
· exact eq_zero_of_ne_zero_of_mul_right_eq_zero (ho i) hB
· intro j _ hij
convert mul_zero (vi j) using 2
exact hO hij
· intro hi
convert zero_mul (M₀ := R) _ using 2
exact Finsupp.not_mem_support_iff.mp hi
set_option linter.uppercaseLean3 false in
#align bilin_form.is_Ortho.nondegenerate_iff_not_is_ortho_basis_self LinearMap.BilinForm.iIsOrtho.nondegenerate_iff_not_isOrtho_basis_self
section
theorem toLin_restrict_ker_eq_inf_orthogonal (B : BilinForm K V) (W : Subspace K V) (b : B.IsRefl) :
(B.domRestrict W).ker.map W.subtype = (W ⊓ B.orthogonal ⊤ : Subspace K V) := by
ext x; constructor <;> intro hx
· rcases hx with ⟨⟨x, hx⟩, hker, rfl⟩
erw [LinearMap.mem_ker] at hker
constructor
· simp [hx]
· intro y _
rw [IsOrtho, b]
change (B.domRestrict W) ⟨x, hx⟩ y = 0
rw [hker]
rfl
· simp_rw [Submodule.mem_map, LinearMap.mem_ker]
refine ⟨⟨x, hx.1⟩, ?_, rfl⟩
ext y
change B x y = 0
rw [b]
exact hx.2 _ Submodule.mem_top
#align bilin_form.to_lin_restrict_ker_eq_inf_orthogonal LinearMap.BilinForm.toLin_restrict_ker_eq_inf_orthogonal
| Mathlib/LinearAlgebra/BilinearForm/Orthogonal.lean | 301 | 309 | theorem toLin_restrict_range_dualCoannihilator_eq_orthogonal (B : BilinForm K V)
(W : Subspace K V) : (B.domRestrict W).range.dualCoannihilator = B.orthogonal W := by |
ext x; constructor <;> rw [mem_orthogonal_iff] <;> intro hx
· intro y hy
rw [Submodule.mem_dualCoannihilator] at hx
exact hx (B.domRestrict W ⟨y, hy⟩) ⟨⟨y, hy⟩, rfl⟩
· rw [Submodule.mem_dualCoannihilator]
rintro _ ⟨⟨w, hw⟩, rfl⟩
exact hx w hw
|
/-
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.Map
#align_import linear_algebra.basic from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Kernel of a linear map
This file defines the kernel of a linear map.
## Main definitions
* `LinearMap.ker`: the kernel of a linear map as a submodule of the domain
## Notations
* We continue to use the notations `M →ₛₗ[σ] M₂` and `M →ₗ[R] M₂` for the type of semilinear
(resp. linear) maps from `M` to `M₂` over the ring homomorphism `σ` (resp. over the ring `R`).
## Tags
linear algebra, vector space, module
-/
open Function
open Pointwise
variable {R : Type*} {R₁ : Type*} {R₂ : Type*} {R₃ : Type*}
variable {K : Type*}
variable {M : Type*} {M₁ : Type*} {M₂ : Type*} {M₃ : Type*}
variable {V : Type*} {V₂ : Type*}
/-! ### Properties of linear maps -/
namespace LinearMap
section AddCommMonoid
variable [Semiring R] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃}
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable [Module R M] [Module R₂ M₂] [Module R₃ M₃]
open Submodule
variable {σ₂₁ : R₂ →+* R} {τ₁₂ : R →+* R₂} {τ₂₃ : R₂ →+* R₃} {τ₁₃ : R →+* R₃}
variable [RingHomCompTriple τ₁₂ τ₂₃ τ₁₃]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F τ₁₂ M M₂]
/-- The kernel of a linear map `f : M → M₂` is defined to be `comap f ⊥`. This is equivalent to the
set of `x : M` such that `f x = 0`. The kernel is a submodule of `M`. -/
def ker (f : F) : Submodule R M :=
comap f ⊥
#align linear_map.ker LinearMap.ker
@[simp]
theorem mem_ker {f : F} {y} : y ∈ ker f ↔ f y = 0 :=
mem_bot R₂
#align linear_map.mem_ker LinearMap.mem_ker
@[simp]
theorem ker_id : ker (LinearMap.id : M →ₗ[R] M) = ⊥ :=
rfl
#align linear_map.ker_id LinearMap.ker_id
@[simp]
theorem map_coe_ker (f : F) (x : ker f) : f x = 0 :=
mem_ker.1 x.2
#align linear_map.map_coe_ker LinearMap.map_coe_ker
theorem ker_toAddSubmonoid (f : M →ₛₗ[τ₁₂] M₂) : f.ker.toAddSubmonoid = (AddMonoidHom.mker f) :=
rfl
#align linear_map.ker_to_add_submonoid LinearMap.ker_toAddSubmonoid
theorem comp_ker_subtype (f : M →ₛₗ[τ₁₂] M₂) : f.comp f.ker.subtype = 0 :=
LinearMap.ext fun x => mem_ker.1 x.2
#align linear_map.comp_ker_subtype LinearMap.comp_ker_subtype
theorem ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker (g.comp f : M →ₛₗ[τ₁₃] M₃) = comap f (ker g) :=
rfl
#align linear_map.ker_comp LinearMap.ker_comp
theorem ker_le_ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker f ≤ ker (g.comp f : M →ₛₗ[τ₁₃] M₃) := by rw [ker_comp]; exact comap_mono bot_le
#align linear_map.ker_le_ker_comp LinearMap.ker_le_ker_comp
theorem ker_sup_ker_le_ker_comp_of_commute {f g : M →ₗ[R] M} (h : Commute f g) :
ker f ⊔ ker g ≤ ker (f ∘ₗ g) := by
refine sup_le_iff.mpr ⟨?_, ker_le_ker_comp g f⟩
rw [← mul_eq_comp, h.eq, mul_eq_comp]
exact ker_le_ker_comp f g
@[simp]
theorem ker_le_comap {p : Submodule R₂ M₂} (f : M →ₛₗ[τ₁₂] M₂) :
ker f ≤ p.comap f :=
fun x hx ↦ by simp [mem_ker.mp hx]
theorem disjoint_ker {f : F} {p : Submodule R M} :
Disjoint p (ker f) ↔ ∀ x ∈ p, f x = 0 → x = 0 := by
simp [disjoint_def]
#align linear_map.disjoint_ker LinearMap.disjoint_ker
theorem ker_eq_bot' {f : F} : ker f = ⊥ ↔ ∀ m, f m = 0 → m = 0 := by
simpa [disjoint_iff_inf_le] using disjoint_ker (f := f) (p := ⊤)
#align linear_map.ker_eq_bot' LinearMap.ker_eq_bot'
theorem ker_eq_bot_of_inverse {τ₂₁ : R₂ →+* R} [RingHomInvPair τ₁₂ τ₂₁] {f : M →ₛₗ[τ₁₂] M₂}
{g : M₂ →ₛₗ[τ₂₁] M} (h : (g.comp f : M →ₗ[R] M) = id) : ker f = ⊥ :=
ker_eq_bot'.2 fun m hm => by rw [← id_apply (R := R) m, ← h, comp_apply, hm, g.map_zero]
#align linear_map.ker_eq_bot_of_inverse LinearMap.ker_eq_bot_of_inverse
theorem le_ker_iff_map [RingHomSurjective τ₁₂] {f : F} {p : Submodule R M} :
p ≤ ker f ↔ map f p = ⊥ := by rw [ker, eq_bot_iff, map_le_iff_le_comap]
#align linear_map.le_ker_iff_map LinearMap.le_ker_iff_map
theorem ker_codRestrict {τ₂₁ : R₂ →+* R} (p : Submodule R M) (f : M₂ →ₛₗ[τ₂₁] M) (hf) :
ker (codRestrict p f hf) = ker f := by rw [ker, comap_codRestrict, Submodule.map_bot]; rfl
#align linear_map.ker_cod_restrict LinearMap.ker_codRestrict
theorem ker_restrict [AddCommMonoid M₁] [Module R M₁] {p : Submodule R M} {q : Submodule R M₁}
{f : M →ₗ[R] M₁} (hf : ∀ x : M, x ∈ p → f x ∈ q) :
ker (f.restrict hf) = LinearMap.ker (f.domRestrict p) := by
rw [restrict_eq_codRestrict_domRestrict, ker_codRestrict]
#align linear_map.ker_restrict LinearMap.ker_restrict
@[simp]
theorem ker_zero : ker (0 : M →ₛₗ[τ₁₂] M₂) = ⊤ :=
eq_top_iff'.2 fun x => by simp
#align linear_map.ker_zero LinearMap.ker_zero
theorem ker_eq_top {f : M →ₛₗ[τ₁₂] M₂} : ker f = ⊤ ↔ f = 0 :=
⟨fun h => ext fun _ => mem_ker.1 <| h.symm ▸ trivial, fun h => h.symm ▸ ker_zero⟩
#align linear_map.ker_eq_top LinearMap.ker_eq_top
@[simp]
theorem _root_.AddMonoidHom.coe_toIntLinearMap_ker {M M₂ : Type*} [AddCommGroup M] [AddCommGroup M₂]
(f : M →+ M₂) : LinearMap.ker f.toIntLinearMap = AddSubgroup.toIntSubmodule f.ker := rfl
theorem ker_eq_bot_of_injective {f : F} (hf : Injective f) : ker f = ⊥ := by
have : Disjoint ⊤ (ker f) := by
-- Porting note: `← map_zero f` should work here, but it needs to be directly applied to H.
rw [disjoint_ker]
intros _ _ H
rw [← map_zero f] at H
exact hf H
simpa [disjoint_iff_inf_le]
#align linear_map.ker_eq_bot_of_injective LinearMap.ker_eq_bot_of_injective
/-- The increasing sequence of submodules consisting of the kernels of the iterates of a linear map.
-/
@[simps]
def iterateKer (f : M →ₗ[R] M) : ℕ →o Submodule R M where
toFun n := ker (f ^ n)
monotone' n m w x h := by
obtain ⟨c, rfl⟩ := le_iff_exists_add.mp w
rw [LinearMap.mem_ker] at h
rw [LinearMap.mem_ker, add_comm, pow_add, LinearMap.mul_apply, h, LinearMap.map_zero]
#align linear_map.iterate_ker LinearMap.iterateKer
end AddCommMonoid
section Ring
variable [Ring R] [Ring R₂] [Ring R₃]
variable [AddCommGroup M] [AddCommGroup M₂] [AddCommGroup M₃]
variable [Module R M] [Module R₂ M₂] [Module R₃ M₃]
variable {τ₁₂ : R →+* R₂} {τ₂₃ : R₂ →+* R₃} {τ₁₃ : R →+* R₃}
variable [RingHomCompTriple τ₁₂ τ₂₃ τ₁₃]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F τ₁₂ M M₂]
variable {f : F}
open Submodule
theorem ker_toAddSubgroup (f : M →ₛₗ[τ₁₂] M₂) : (ker f).toAddSubgroup = f.toAddMonoidHom.ker :=
rfl
#align linear_map.ker_to_add_subgroup LinearMap.ker_toAddSubgroup
| Mathlib/Algebra/Module/Submodule/Ker.lean | 187 | 187 | theorem sub_mem_ker_iff {x y} : x - y ∈ ker f ↔ f x = f y := by | rw [mem_ker, map_sub, sub_eq_zero]
|
/-
Copyright (c) 2022 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.MeasureTheory.Integral.Layercake
#align_import measure_theory.integral.layercake from "leanprover-community/mathlib"@"08a4542bec7242a5c60f179e4e49de8c0d677b1b"
/-!
# The integral of the real power of a nonnegative function
In this file, we give a common application of the layer cake formula -
a representation of the integral of the p:th power of a nonnegative function f:
∫ f(ω)^p ∂μ(ω) = p * ∫ t^(p-1) * μ {ω | f(ω) ≥ t} dt .
A variant of the formula with measures of sets of the form {ω | f(ω) > t} instead of {ω | f(ω) ≥ t}
is also included.
## Main results
* `MeasureTheory.lintegral_rpow_eq_lintegral_meas_le_mul` and
`MeasureTheory.lintegral_rpow_eq_lintegral_meas_lt_mul`:
Other common special cases of the layer cake formulas, stating that for a nonnegative function f
and p > 0, we have ∫ f(ω)^p ∂μ(ω) = p * ∫ μ {ω | f(ω) ≥ t} * t^(p-1) dt and
∫ f(ω)^p ∂μ(ω) = p * ∫ μ {ω | f(ω) > t} * t^(p-1) dt, respectively.
## Tags
layer cake representation, Cavalieri's principle, tail probability formula
-/
open Set
namespace MeasureTheory
variable {α : Type*} [MeasurableSpace α] {f : α → ℝ} (μ : Measure α) (f_nn : 0 ≤ᵐ[μ] f)
(f_mble : AEMeasurable f μ) {p : ℝ} (p_pos : 0 < p)
section Layercake
/-- An application of the layer cake formula / Cavalieri's principle / tail probability formula:
For a nonnegative function `f` on a measure space, the Lebesgue integral of `f` can
be written (roughly speaking) as: `∫⁻ f^p ∂μ = p * ∫⁻ t in 0..∞, t^(p-1) * μ {ω | f(ω) ≥ t}`.
See `MeasureTheory.lintegral_rpow_eq_lintegral_meas_lt_mul` for a version with sets of the form
`{ω | f(ω) > t}` instead. -/
| Mathlib/Analysis/SpecialFunctions/Pow/Integral.lean | 50 | 72 | theorem lintegral_rpow_eq_lintegral_meas_le_mul :
∫⁻ ω, ENNReal.ofReal (f ω ^ p) ∂μ =
ENNReal.ofReal p * ∫⁻ t in Ioi 0, μ {a : α | t ≤ f a} * ENNReal.ofReal (t ^ (p - 1)) := by |
have one_lt_p : -1 < p - 1 := by linarith
have obs : ∀ x : ℝ, ∫ t : ℝ in (0)..x, t ^ (p - 1) = x ^ p / p := by
intro x
rw [integral_rpow (Or.inl one_lt_p)]
simp [Real.zero_rpow p_pos.ne.symm]
set g := fun t : ℝ => t ^ (p - 1)
have g_nn : ∀ᵐ t ∂volume.restrict (Ioi (0 : ℝ)), 0 ≤ g t := by
filter_upwards [self_mem_ae_restrict (measurableSet_Ioi : MeasurableSet (Ioi (0 : ℝ)))]
intro t t_pos
exact Real.rpow_nonneg (mem_Ioi.mp t_pos).le (p - 1)
have g_intble : ∀ t > 0, IntervalIntegrable g volume 0 t := fun _ _ =>
intervalIntegral.intervalIntegrable_rpow' one_lt_p
have key := lintegral_comp_eq_lintegral_meas_le_mul μ f_nn f_mble g_intble g_nn
rw [← key, ← lintegral_const_mul'' (ENNReal.ofReal p)] <;> simp_rw [obs]
· congr with ω
rw [← ENNReal.ofReal_mul p_pos.le, mul_div_cancel₀ (f ω ^ p) p_pos.ne.symm]
· have aux := (@measurable_const ℝ α (by infer_instance) (by infer_instance) p).aemeasurable
(μ := μ)
exact (Measurable.ennreal_ofReal (hf := measurable_id)).comp_aemeasurable
((f_mble.pow aux).div_const p)
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Eval
import Mathlib.RingTheory.Ideal.Quotient
#align_import linear_algebra.smodeq from "leanprover-community/mathlib"@"146d3d1fa59c091fedaad8a4afa09d6802886d24"
/-!
# modular equivalence for submodule
-/
open Submodule
open Polynomial
variable {R : Type*} [Ring R]
variable {A : Type*} [CommRing A]
variable {M : Type*} [AddCommGroup M] [Module R M] (U U₁ U₂ : Submodule R M)
variable {x x₁ x₂ y y₁ y₂ z z₁ z₂ : M}
variable {N : Type*} [AddCommGroup N] [Module R N] (V V₁ V₂ : Submodule R N)
set_option backward.isDefEq.lazyWhnfCore false in -- See https://github.com/leanprover-community/mathlib4/issues/12534
/-- A predicate saying two elements of a module are equivalent modulo a submodule. -/
def SModEq (x y : M) : Prop :=
(Submodule.Quotient.mk x : M ⧸ U) = Submodule.Quotient.mk y
#align smodeq SModEq
notation:50 x " ≡ " y " [SMOD " N "]" => SModEq N x y
variable {U U₁ U₂}
set_option backward.isDefEq.lazyWhnfCore false in -- See https://github.com/leanprover-community/mathlib4/issues/12534
protected theorem SModEq.def :
x ≡ y [SMOD U] ↔ (Submodule.Quotient.mk x : M ⧸ U) = Submodule.Quotient.mk y :=
Iff.rfl
#align smodeq.def SModEq.def
namespace SModEq
| Mathlib/LinearAlgebra/SModEq.lean | 44 | 44 | theorem sub_mem : x ≡ y [SMOD U] ↔ x - y ∈ U := by | rw [SModEq.def, Submodule.Quotient.eq]
|
/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel
-/
import Mathlib.Topology.EMetricSpace.Basic
import Mathlib.Topology.Bornology.Constructions
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.Topology.Order.DenselyOrdered
/-!
## Pseudo-metric spaces
This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the
condition `dist x y = 0 → x = y`.
Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform
spaces and topological spaces. For example: open and closed sets, compactness, completeness,
continuity and uniform continuity.
## Main definitions
* `Dist α`: Endows a space `α` with a function `dist a b`.
* `PseudoMetricSpace α`: A space endowed with a distance function, which can
be zero even if the two elements are non-equal.
* `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`.
* `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded.
* `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`.
Additional useful definitions:
* `nndist a b`: `dist` as a function to the non-negative reals.
* `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`.
* `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`.
TODO (anyone): Add "Main results" section.
## Tags
pseudo_metric, dist
-/
open Set Filter TopologicalSpace Bornology
open scoped ENNReal NNReal Uniformity Topology
universe u v w
variable {α : Type u} {β : Type v} {X ι : Type*}
theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε :=
⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩
/-- Construct a uniform structure from a distance function and metric space axioms -/
def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0)
(dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α :=
.ofFun dist dist_self dist_comm dist_triangle ofDist_aux
#align uniform_space_of_dist UniformSpace.ofDist
-- Porting note: dropped the `dist_self` argument
/-- Construct a bornology from a distance function and metric space axioms. -/
abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x)
(dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α :=
Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C }
⟨0, fun x hx y => hx.elim⟩ (fun s ⟨c, hc⟩ t h => ⟨c, fun x hx y hy => hc (h hx) (h hy)⟩)
(fun s hs t ht => by
rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· rwa [empty_union]
rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩
· rwa [union_empty]
rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C
· refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩
simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb)
rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩
refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim
(fun hz => (hs hx hz).trans (le_max_left _ _))
(fun hz => (dist_triangle x y z).trans <|
(add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩)
fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩
#align bornology.of_dist Bornology.ofDistₓ
/-- The distance function (given an ambient metric space on `α`), which returns
a nonnegative real number `dist x y` given `x y : α`. -/
@[ext]
class Dist (α : Type*) where
dist : α → α → ℝ
#align has_dist Dist
export Dist (dist)
-- the uniform structure and the emetric space structure are embedded in the metric space structure
-- to avoid instance diamond issues. See Note [forgetful inheritance].
/-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/
private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y :=
have : 0 ≤ 2 * dist x y :=
calc 0 = dist x x := (dist_self _).symm
_ ≤ dist x y + dist y x := dist_triangle _ _ _
_ = 2 * dist x y := by rw [two_mul, dist_comm]
nonneg_of_mul_nonneg_right this two_pos
#noalign pseudo_metric_space.edist_dist_tac -- Porting note (#11215): TODO: restore
/-- Pseudo metric and Metric spaces
A pseudo metric space is endowed with a distance for which the requirement `d(x,y)=0 → x = y` might
not hold. A metric space is a pseudo metric space such that `d(x,y)=0 → x = y`.
Each pseudo metric space induces a canonical `UniformSpace` and hence a canonical
`TopologicalSpace` This is enforced in the type class definition, by extending the `UniformSpace`
structure. When instantiating a `PseudoMetricSpace` structure, the uniformity fields are not
necessary, they will be filled in by default. In the same way, each (pseudo) metric space induces a
(pseudo) emetric space structure. It is included in the structure, but filled in by default.
-/
class PseudoMetricSpace (α : Type u) extends Dist α : Type u where
dist_self : ∀ x : α, dist x x = 0
dist_comm : ∀ x y : α, dist x y = dist y x
dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z
edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩
edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y)
-- Porting note (#11215): TODO: add := by _
toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle
uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl
toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets : (Bornology.cobounded α).sets =
{ s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl
#align pseudo_metric_space PseudoMetricSpace
/-- Two pseudo metric space structures with the same distance function coincide. -/
@[ext]
theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α}
(h : m.toDist = m'.toDist) : m = m' := by
cases' m with d _ _ _ ed hed U hU B hB
cases' m' with d' _ _ _ ed' hed' U' hU' B' hB'
obtain rfl : d = d' := h
congr
· ext x y : 2
rw [hed, hed']
· exact UniformSpace.ext (hU.trans hU'.symm)
· ext : 2
rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB']
#align pseudo_metric_space.ext PseudoMetricSpace.ext
variable [PseudoMetricSpace α]
attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology
-- see Note [lower instance priority]
instance (priority := 200) PseudoMetricSpace.toEDist : EDist α :=
⟨PseudoMetricSpace.edist⟩
#align pseudo_metric_space.to_has_edist PseudoMetricSpace.toEDist
/-- Construct a pseudo-metric space structure whose underlying topological space structure
(definitionally) agrees which a pre-existing topology which is compatible with a given distance
function. -/
def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z)
(H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) :
PseudoMetricSpace α :=
{ dist := dist
dist_self := dist_self
dist_comm := dist_comm
dist_triangle := dist_triangle
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
toUniformSpace :=
(UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <|
TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦
((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle
UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm
uniformity_dist := rfl
toBornology := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets := rfl }
#align pseudo_metric_space.of_dist_topology PseudoMetricSpace.ofDistTopology
@[simp]
theorem dist_self (x : α) : dist x x = 0 :=
PseudoMetricSpace.dist_self x
#align dist_self dist_self
theorem dist_comm (x y : α) : dist x y = dist y x :=
PseudoMetricSpace.dist_comm x y
#align dist_comm dist_comm
theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) :=
PseudoMetricSpace.edist_dist x y
#align edist_dist edist_dist
theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
PseudoMetricSpace.dist_triangle x y z
#align dist_triangle dist_triangle
theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by
rw [dist_comm z]; apply dist_triangle
#align dist_triangle_left dist_triangle_left
theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by
rw [dist_comm y]; apply dist_triangle
#align dist_triangle_right dist_triangle_right
theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w :=
calc
dist x w ≤ dist x z + dist z w := dist_triangle x z w
_ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _
#align dist_triangle4 dist_triangle4
theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) :
dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by
rw [add_left_comm, dist_comm x₁, ← add_assoc]
apply dist_triangle4
#align dist_triangle4_left dist_triangle4_left
theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) :
dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by
rw [add_right_comm, dist_comm y₁]
apply dist_triangle4
#align dist_triangle4_right dist_triangle4_right
/-- The triangle (polygon) inequality for sequences of points; `Finset.Ico` version. -/
theorem dist_le_Ico_sum_dist (f : ℕ → α) {m n} (h : m ≤ n) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, dist (f i) (f (i + 1)) := by
induction n, h using Nat.le_induction with
| base => rw [Finset.Ico_self, Finset.sum_empty, dist_self]
| succ n hle ihn =>
calc
dist (f m) (f (n + 1)) ≤ dist (f m) (f n) + dist (f n) (f (n + 1)) := dist_triangle _ _ _
_ ≤ (∑ i ∈ Finset.Ico m n, _) + _ := add_le_add ihn le_rfl
_ = ∑ i ∈ Finset.Ico m (n + 1), _ := by
{ rw [Nat.Ico_succ_right_eq_insert_Ico hle, Finset.sum_insert, add_comm]; simp }
#align dist_le_Ico_sum_dist dist_le_Ico_sum_dist
/-- The triangle (polygon) inequality for sequences of points; `Finset.range` version. -/
theorem dist_le_range_sum_dist (f : ℕ → α) (n : ℕ) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, dist (f i) (f (i + 1)) :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_dist f (Nat.zero_le n)
#align dist_le_range_sum_dist dist_le_range_sum_dist
/-- A version of `dist_le_Ico_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_Ico_sum_of_dist_le {f : ℕ → α} {m n} (hmn : m ≤ n) {d : ℕ → ℝ}
(hd : ∀ {k}, m ≤ k → k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, d i :=
le_trans (dist_le_Ico_sum_dist f hmn) <|
Finset.sum_le_sum fun _k hk => hd (Finset.mem_Ico.1 hk).1 (Finset.mem_Ico.1 hk).2
#align dist_le_Ico_sum_of_dist_le dist_le_Ico_sum_of_dist_le
/-- A version of `dist_le_range_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_range_sum_of_dist_le {f : ℕ → α} (n : ℕ) {d : ℕ → ℝ}
(hd : ∀ {k}, k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, d i :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_of_dist_le (zero_le n) fun _ => hd
#align dist_le_range_sum_of_dist_le dist_le_range_sum_of_dist_le
theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _
#align swap_dist swap_dist
theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y :=
abs_sub_le_iff.2
⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩
#align abs_dist_sub_le abs_dist_sub_le
theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
dist_nonneg' dist dist_self dist_comm dist_triangle
#align dist_nonneg dist_nonneg
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension for the `positivity` tactic: distances are nonnegative. -/
@[positivity Dist.dist _ _]
def evalDist : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) =>
let _inst ← synthInstanceQ q(PseudoMetricSpace $β)
assertInstancesCommute
pure (.nonnegative q(dist_nonneg))
| _, _, _ => throwError "not dist"
end Mathlib.Meta.Positivity
example {x y : α} : 0 ≤ dist x y := by positivity
@[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg
#align abs_dist abs_dist
/-- A version of `Dist` that takes value in `ℝ≥0`. -/
class NNDist (α : Type*) where
nndist : α → α → ℝ≥0
#align has_nndist NNDist
export NNDist (nndist)
-- see Note [lower instance priority]
/-- Distance as a nonnegative real number. -/
instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α :=
⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩
#align pseudo_metric_space.to_has_nndist PseudoMetricSpace.toNNDist
/-- Express `dist` in terms of `nndist`-/
theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl
#align dist_nndist dist_nndist
@[simp, norm_cast]
theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl
#align coe_nndist coe_nndist
/-- Express `edist` in terms of `nndist`-/
theorem edist_nndist (x y : α) : edist x y = nndist x y := by
rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal]
#align edist_nndist edist_nndist
/-- Express `nndist` in terms of `edist`-/
theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by
simp [edist_nndist]
#align nndist_edist nndist_edist
@[simp, norm_cast]
theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y :=
(edist_nndist x y).symm
#align coe_nnreal_ennreal_nndist coe_nnreal_ennreal_nndist
@[simp, norm_cast]
theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by
rw [edist_nndist, ENNReal.coe_lt_coe]
#align edist_lt_coe edist_lt_coe
@[simp, norm_cast]
theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by
rw [edist_nndist, ENNReal.coe_le_coe]
#align edist_le_coe edist_le_coe
/-- In a pseudometric space, the extended distance is always finite-/
theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ :=
(edist_dist x y).symm ▸ ENNReal.ofReal_lt_top
#align edist_lt_top edist_lt_top
/-- In a pseudometric space, the extended distance is always finite-/
theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ :=
(edist_lt_top x y).ne
#align edist_ne_top edist_ne_top
/-- `nndist x x` vanishes-/
@[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a)
#align nndist_self nndist_self
-- Porting note: `dist_nndist` and `coe_nndist` moved up
@[simp, norm_cast]
theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c :=
Iff.rfl
#align dist_lt_coe dist_lt_coe
@[simp, norm_cast]
theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c :=
Iff.rfl
#align dist_le_coe dist_le_coe
@[simp]
theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by
rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg]
#align edist_lt_of_real edist_lt_ofReal
@[simp]
theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) :
edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by
rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr]
#align edist_le_of_real edist_le_ofReal
/-- Express `nndist` in terms of `dist`-/
theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by
rw [dist_nndist, Real.toNNReal_coe]
#align nndist_dist nndist_dist
theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y
#align nndist_comm nndist_comm
/-- Triangle inequality for the nonnegative distance-/
theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z :=
dist_triangle _ _ _
#align nndist_triangle nndist_triangle
theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y :=
dist_triangle_left _ _ _
#align nndist_triangle_left nndist_triangle_left
theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z :=
dist_triangle_right _ _ _
#align nndist_triangle_right nndist_triangle_right
/-- Express `dist` in terms of `edist`-/
theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by
rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg]
#align dist_edist dist_edist
namespace Metric
-- instantiate pseudometric space as a topology
variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α}
/-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/
def ball (x : α) (ε : ℝ) : Set α :=
{ y | dist y x < ε }
#align metric.ball Metric.ball
@[simp]
theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε :=
Iff.rfl
#align metric.mem_ball Metric.mem_ball
theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball]
#align metric.mem_ball' Metric.mem_ball'
theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε :=
dist_nonneg.trans_lt hy
#align metric.pos_of_mem_ball Metric.pos_of_mem_ball
theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by
rwa [mem_ball, dist_self]
#align metric.mem_ball_self Metric.mem_ball_self
@[simp]
theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε :=
⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩
#align metric.nonempty_ball Metric.nonempty_ball
@[simp]
theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt]
#align metric.ball_eq_empty Metric.ball_eq_empty
@[simp]
theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty]
#align metric.ball_zero Metric.ball_zero
/-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also
contains it.
See also `exists_lt_subset_ball`. -/
| Mathlib/Topology/MetricSpace/PseudoMetric.lean | 440 | 442 | theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by |
simp only [mem_ball] at h ⊢
exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.ChartedSpace
#align_import geometry.manifold.local_invariant_properties from "leanprover-community/mathlib"@"431589bce478b2229eba14b14a283250428217db"
/-!
# Local properties invariant under a groupoid
We study properties of a triple `(g, s, x)` where `g` is a function between two spaces `H` and `H'`,
`s` is a subset of `H` and `x` is a point of `H`. Our goal is to register how such a property
should behave to make sense in charted spaces modelled on `H` and `H'`.
The main examples we have in mind are the properties "`g` is differentiable at `x` within `s`", or
"`g` is smooth at `x` within `s`". We want to develop general results that, when applied in these
specific situations, say that the notion of smooth function in a manifold behaves well under
restriction, intersection, is local, and so on.
## Main definitions
* `LocalInvariantProp G G' P` says that a property `P` of a triple `(g, s, x)` is local, and
invariant under composition by elements of the groupoids `G` and `G'` of `H` and `H'`
respectively.
* `ChartedSpace.LiftPropWithinAt` (resp. `LiftPropAt`, `LiftPropOn` and `LiftProp`):
given a property `P` of `(g, s, x)` where `g : H → H'`, define the corresponding property
for functions `M → M'` where `M` and `M'` are charted spaces modelled respectively on `H` and
`H'`. We define these properties within a set at a point, or at a point, or on a set, or in the
whole space. This lifting process (obtained by restricting to suitable chart domains) can always
be done, but it only behaves well under locality and invariance assumptions.
Given `hG : LocalInvariantProp G G' P`, we deduce many properties of the lifted property on the
charted spaces. For instance, `hG.liftPropWithinAt_inter` says that `P g s x` is equivalent to
`P g (s ∩ t) x` whenever `t` is a neighborhood of `x`.
## Implementation notes
We do not use dot notation for properties of the lifted property. For instance, we have
`hG.liftPropWithinAt_congr` saying that if `LiftPropWithinAt P g s x` holds, and `g` and `g'`
coincide on `s`, then `LiftPropWithinAt P g' s x` holds. We can't call it
`LiftPropWithinAt.congr` as it is in the namespace associated to `LocalInvariantProp`, not
in the one for `LiftPropWithinAt`.
-/
noncomputable section
open scoped Classical
open Manifold Topology
open Set Filter TopologicalSpace
variable {H M H' M' X : Type*}
variable [TopologicalSpace H] [TopologicalSpace M] [ChartedSpace H M]
variable [TopologicalSpace H'] [TopologicalSpace M'] [ChartedSpace H' M']
variable [TopologicalSpace X]
namespace StructureGroupoid
variable (G : StructureGroupoid H) (G' : StructureGroupoid H')
/-- Structure recording good behavior of a property of a triple `(f, s, x)` where `f` is a function,
`s` a set and `x` a point. Good behavior here means locality and invariance under given groupoids
(both in the source and in the target). Given such a good behavior, the lift of this property
to charted spaces admitting these groupoids will inherit the good behavior. -/
structure LocalInvariantProp (P : (H → H') → Set H → H → Prop) : Prop where
is_local : ∀ {s x u} {f : H → H'}, IsOpen u → x ∈ u → (P f s x ↔ P f (s ∩ u) x)
right_invariance' : ∀ {s x f} {e : PartialHomeomorph H H},
e ∈ G → x ∈ e.source → P f s x → P (f ∘ e.symm) (e.symm ⁻¹' s) (e x)
congr_of_forall : ∀ {s x} {f g : H → H'}, (∀ y ∈ s, f y = g y) → f x = g x → P f s x → P g s x
left_invariance' : ∀ {s x f} {e' : PartialHomeomorph H' H'},
e' ∈ G' → s ⊆ f ⁻¹' e'.source → f x ∈ e'.source → P f s x → P (e' ∘ f) s x
#align structure_groupoid.local_invariant_prop StructureGroupoid.LocalInvariantProp
variable {G G'} {P : (H → H') → Set H → H → Prop} {s t u : Set H} {x : H}
variable (hG : G.LocalInvariantProp G' P)
namespace LocalInvariantProp
theorem congr_set {s t : Set H} {x : H} {f : H → H'} (hu : s =ᶠ[𝓝 x] t) : P f s x ↔ P f t x := by
obtain ⟨o, host, ho, hxo⟩ := mem_nhds_iff.mp hu.mem_iff
simp_rw [subset_def, mem_setOf, ← and_congr_left_iff, ← mem_inter_iff, ← Set.ext_iff] at host
rw [hG.is_local ho hxo, host, ← hG.is_local ho hxo]
#align structure_groupoid.local_invariant_prop.congr_set StructureGroupoid.LocalInvariantProp.congr_set
theorem is_local_nhds {s u : Set H} {x : H} {f : H → H'} (hu : u ∈ 𝓝[s] x) :
P f s x ↔ P f (s ∩ u) x :=
hG.congr_set <| mem_nhdsWithin_iff_eventuallyEq.mp hu
#align structure_groupoid.local_invariant_prop.is_local_nhds StructureGroupoid.LocalInvariantProp.is_local_nhds
theorem congr_iff_nhdsWithin {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g)
(h2 : f x = g x) : P f s x ↔ P g s x := by
simp_rw [hG.is_local_nhds h1]
exact ⟨hG.congr_of_forall (fun y hy ↦ hy.2) h2, hG.congr_of_forall (fun y hy ↦ hy.2.symm) h2.symm⟩
#align structure_groupoid.local_invariant_prop.congr_iff_nhds_within StructureGroupoid.LocalInvariantProp.congr_iff_nhdsWithin
theorem congr_nhdsWithin {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g) (h2 : f x = g x)
(hP : P f s x) : P g s x :=
(hG.congr_iff_nhdsWithin h1 h2).mp hP
#align structure_groupoid.local_invariant_prop.congr_nhds_within StructureGroupoid.LocalInvariantProp.congr_nhdsWithin
theorem congr_nhdsWithin' {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g) (h2 : f x = g x)
(hP : P g s x) : P f s x :=
(hG.congr_iff_nhdsWithin h1 h2).mpr hP
#align structure_groupoid.local_invariant_prop.congr_nhds_within' StructureGroupoid.LocalInvariantProp.congr_nhdsWithin'
theorem congr_iff {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) : P f s x ↔ P g s x :=
hG.congr_iff_nhdsWithin (mem_nhdsWithin_of_mem_nhds h) (mem_of_mem_nhds h : _)
#align structure_groupoid.local_invariant_prop.congr_iff StructureGroupoid.LocalInvariantProp.congr_iff
theorem congr {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) (hP : P f s x) : P g s x :=
(hG.congr_iff h).mp hP
#align structure_groupoid.local_invariant_prop.congr StructureGroupoid.LocalInvariantProp.congr
theorem congr' {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) (hP : P g s x) : P f s x :=
hG.congr h.symm hP
#align structure_groupoid.local_invariant_prop.congr' StructureGroupoid.LocalInvariantProp.congr'
theorem left_invariance {s : Set H} {x : H} {f : H → H'} {e' : PartialHomeomorph H' H'}
(he' : e' ∈ G') (hfs : ContinuousWithinAt f s x) (hxe' : f x ∈ e'.source) :
P (e' ∘ f) s x ↔ P f s x := by
have h2f := hfs.preimage_mem_nhdsWithin (e'.open_source.mem_nhds hxe')
have h3f :=
((e'.continuousAt hxe').comp_continuousWithinAt hfs).preimage_mem_nhdsWithin <|
e'.symm.open_source.mem_nhds <| e'.mapsTo hxe'
constructor
· intro h
rw [hG.is_local_nhds h3f] at h
have h2 := hG.left_invariance' (G'.symm he') inter_subset_right (e'.mapsTo hxe') h
rw [← hG.is_local_nhds h3f] at h2
refine hG.congr_nhdsWithin ?_ (e'.left_inv hxe') h2
exact eventually_of_mem h2f fun x' ↦ e'.left_inv
· simp_rw [hG.is_local_nhds h2f]
exact hG.left_invariance' he' inter_subset_right hxe'
#align structure_groupoid.local_invariant_prop.left_invariance StructureGroupoid.LocalInvariantProp.left_invariance
theorem right_invariance {s : Set H} {x : H} {f : H → H'} {e : PartialHomeomorph H H} (he : e ∈ G)
(hxe : x ∈ e.source) : P (f ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P f s x := by
refine ⟨fun h ↦ ?_, hG.right_invariance' he hxe⟩
have := hG.right_invariance' (G.symm he) (e.mapsTo hxe) h
rw [e.symm_symm, e.left_inv hxe] at this
refine hG.congr ?_ ((hG.congr_set ?_).mp this)
· refine eventually_of_mem (e.open_source.mem_nhds hxe) fun x' hx' ↦ ?_
simp_rw [Function.comp_apply, e.left_inv hx']
· rw [eventuallyEq_set]
refine eventually_of_mem (e.open_source.mem_nhds hxe) fun x' hx' ↦ ?_
simp_rw [mem_preimage, e.left_inv hx']
#align structure_groupoid.local_invariant_prop.right_invariance StructureGroupoid.LocalInvariantProp.right_invariance
end LocalInvariantProp
end StructureGroupoid
namespace ChartedSpace
/-- Given a property of germs of functions and sets in the model space, then one defines
a corresponding property in a charted space, by requiring that it holds at the preferred chart at
this point. (When the property is local and invariant, it will in fact hold using any chart, see
`liftPropWithinAt_indep_chart`). We require continuity in the lifted property, as otherwise one
single chart might fail to capture the behavior of the function.
-/
@[mk_iff liftPropWithinAt_iff']
structure LiftPropWithinAt (P : (H → H') → Set H → H → Prop) (f : M → M') (s : Set M) (x : M) :
Prop where
continuousWithinAt : ContinuousWithinAt f s x
prop : P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) ((chartAt H x).symm ⁻¹' s) (chartAt H x x)
#align charted_space.lift_prop_within_at ChartedSpace.LiftPropWithinAt
/-- Given a property of germs of functions and sets in the model space, then one defines
a corresponding property of functions on sets in a charted space, by requiring that it holds
around each point of the set, in the preferred charts. -/
def LiftPropOn (P : (H → H') → Set H → H → Prop) (f : M → M') (s : Set M) :=
∀ x ∈ s, LiftPropWithinAt P f s x
#align charted_space.lift_prop_on ChartedSpace.LiftPropOn
/-- Given a property of germs of functions and sets in the model space, then one defines
a corresponding property of a function at a point in a charted space, by requiring that it holds
in the preferred chart. -/
def LiftPropAt (P : (H → H') → Set H → H → Prop) (f : M → M') (x : M) :=
LiftPropWithinAt P f univ x
#align charted_space.lift_prop_at ChartedSpace.LiftPropAt
theorem liftPropAt_iff {P : (H → H') → Set H → H → Prop} {f : M → M'} {x : M} :
LiftPropAt P f x ↔
ContinuousAt f x ∧ P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) univ (chartAt H x x) := by
rw [LiftPropAt, liftPropWithinAt_iff', continuousWithinAt_univ, preimage_univ]
#align charted_space.lift_prop_at_iff ChartedSpace.liftPropAt_iff
/-- Given a property of germs of functions and sets in the model space, then one defines
a corresponding property of a function in a charted space, by requiring that it holds
in the preferred chart around every point. -/
def LiftProp (P : (H → H') → Set H → H → Prop) (f : M → M') :=
∀ x, LiftPropAt P f x
#align charted_space.lift_prop ChartedSpace.LiftProp
theorem liftProp_iff {P : (H → H') → Set H → H → Prop} {f : M → M'} :
LiftProp P f ↔
Continuous f ∧ ∀ x, P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) univ (chartAt H x x) := by
simp_rw [LiftProp, liftPropAt_iff, forall_and, continuous_iff_continuousAt]
#align charted_space.lift_prop_iff ChartedSpace.liftProp_iff
end ChartedSpace
open ChartedSpace
namespace StructureGroupoid
variable {G : StructureGroupoid H} {G' : StructureGroupoid H'} {e e' : PartialHomeomorph M H}
{f f' : PartialHomeomorph M' H'} {P : (H → H') → Set H → H → Prop} {g g' : M → M'} {s t : Set M}
{x : M} {Q : (H → H) → Set H → H → Prop}
theorem liftPropWithinAt_univ : LiftPropWithinAt P g univ x ↔ LiftPropAt P g x := Iff.rfl
#align structure_groupoid.lift_prop_within_at_univ StructureGroupoid.liftPropWithinAt_univ
theorem liftPropOn_univ : LiftPropOn P g univ ↔ LiftProp P g := by
simp [LiftPropOn, LiftProp, LiftPropAt]
#align structure_groupoid.lift_prop_on_univ StructureGroupoid.liftPropOn_univ
theorem liftPropWithinAt_self {f : H → H'} {s : Set H} {x : H} :
LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P f s x :=
liftPropWithinAt_iff' ..
#align structure_groupoid.lift_prop_within_at_self StructureGroupoid.liftPropWithinAt_self
theorem liftPropWithinAt_self_source {f : H → M'} {s : Set H} {x : H} :
LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P (chartAt H' (f x) ∘ f) s x :=
liftPropWithinAt_iff' ..
#align structure_groupoid.lift_prop_within_at_self_source StructureGroupoid.liftPropWithinAt_self_source
theorem liftPropWithinAt_self_target {f : M → H'} :
LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧
P (f ∘ (chartAt H x).symm) ((chartAt H x).symm ⁻¹' s) (chartAt H x x) :=
liftPropWithinAt_iff' ..
#align structure_groupoid.lift_prop_within_at_self_target StructureGroupoid.liftPropWithinAt_self_target
namespace LocalInvariantProp
variable (hG : G.LocalInvariantProp G' P)
/-- `LiftPropWithinAt P f s x` is equivalent to a definition where we restrict the set we are
considering to the domain of the charts at `x` and `f x`. -/
theorem liftPropWithinAt_iff {f : M → M'} :
LiftPropWithinAt P f s x ↔
ContinuousWithinAt f s x ∧
P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm)
((chartAt H x).target ∩ (chartAt H x).symm ⁻¹' (s ∩ f ⁻¹' (chartAt H' (f x)).source))
(chartAt H x x) := by
rw [liftPropWithinAt_iff']
refine and_congr_right fun hf ↦ hG.congr_set ?_
exact PartialHomeomorph.preimage_eventuallyEq_target_inter_preimage_inter hf
(mem_chart_source H x) (chart_source_mem_nhds H' (f x))
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_iff StructureGroupoid.LocalInvariantProp.liftPropWithinAt_iff
theorem liftPropWithinAt_indep_chart_source_aux (g : M → H') (he : e ∈ G.maximalAtlas M)
(xe : x ∈ e.source) (he' : e' ∈ G.maximalAtlas M) (xe' : x ∈ e'.source) :
P (g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (g ∘ e'.symm) (e'.symm ⁻¹' s) (e' x) := by
rw [← hG.right_invariance (compatible_of_mem_maximalAtlas he he')]
swap; · simp only [xe, xe', mfld_simps]
simp_rw [PartialHomeomorph.trans_apply, e.left_inv xe]
rw [hG.congr_iff]
· refine hG.congr_set ?_
refine (eventually_of_mem ?_ fun y (hy : y ∈ e'.symm ⁻¹' e.source) ↦ ?_).set_eq
· refine (e'.symm.continuousAt <| e'.mapsTo xe').preimage_mem_nhds (e.open_source.mem_nhds ?_)
simp_rw [e'.left_inv xe', xe]
simp_rw [mem_preimage, PartialHomeomorph.coe_trans_symm, PartialHomeomorph.symm_symm,
Function.comp_apply, e.left_inv hy]
· refine ((e'.eventually_nhds' _ xe').mpr <| e.eventually_left_inverse xe).mono fun y hy ↦ ?_
simp only [mfld_simps]
rw [hy]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_source_aux StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_source_aux
theorem liftPropWithinAt_indep_chart_target_aux2 (g : H → M') {x : H} {s : Set H}
(hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) (hf' : f' ∈ G'.maximalAtlas M')
(xf' : g x ∈ f'.source) (hgs : ContinuousWithinAt g s x) : P (f ∘ g) s x ↔ P (f' ∘ g) s x := by
have hcont : ContinuousWithinAt (f ∘ g) s x := (f.continuousAt xf).comp_continuousWithinAt hgs
rw [← hG.left_invariance (compatible_of_mem_maximalAtlas hf hf') hcont
(by simp only [xf, xf', mfld_simps])]
refine hG.congr_iff_nhdsWithin ?_ (by simp only [xf, mfld_simps])
exact (hgs.eventually <| f.eventually_left_inverse xf).mono fun y ↦ congr_arg f'
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_target_aux2 StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_target_aux2
theorem liftPropWithinAt_indep_chart_target_aux {g : X → M'} {e : PartialHomeomorph X H} {x : X}
{s : Set X} (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source)
(hf' : f' ∈ G'.maximalAtlas M') (xf' : g x ∈ f'.source) (hgs : ContinuousWithinAt g s x) :
P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (f' ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by
rw [← e.left_inv xe] at xf xf' hgs
refine hG.liftPropWithinAt_indep_chart_target_aux2 (g ∘ e.symm) hf xf hf' xf' ?_
exact hgs.comp (e.symm.continuousAt <| e.mapsTo xe).continuousWithinAt Subset.rfl
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_target_aux StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_target_aux
/-- If a property of a germ of function `g` on a pointed set `(s, x)` is invariant under the
structure groupoid (by composition in the source space and in the target space), then
expressing it in charted spaces does not depend on the element of the maximal atlas one uses
both in the source and in the target manifolds, provided they are defined around `x` and `g x`
respectively, and provided `g` is continuous within `s` at `x` (otherwise, the local behavior
of `g` at `x` can not be captured with a chart in the target). -/
theorem liftPropWithinAt_indep_chart_aux (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source)
(he' : e' ∈ G.maximalAtlas M) (xe' : x ∈ e'.source) (hf : f ∈ G'.maximalAtlas M')
(xf : g x ∈ f.source) (hf' : f' ∈ G'.maximalAtlas M') (xf' : g x ∈ f'.source)
(hgs : ContinuousWithinAt g s x) :
P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (f' ∘ g ∘ e'.symm) (e'.symm ⁻¹' s) (e' x) := by
rw [← Function.comp.assoc, hG.liftPropWithinAt_indep_chart_source_aux (f ∘ g) he xe he' xe',
Function.comp.assoc, hG.liftPropWithinAt_indep_chart_target_aux xe' hf xf hf' xf' hgs]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_aux StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_aux
theorem liftPropWithinAt_indep_chart [HasGroupoid M G] [HasGroupoid M' G']
(he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M')
(xf : g x ∈ f.source) :
LiftPropWithinAt P g s x ↔
ContinuousWithinAt g s x ∧ P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by
simp only [liftPropWithinAt_iff']
exact and_congr_right <|
hG.liftPropWithinAt_indep_chart_aux (chart_mem_maximalAtlas _ _) (mem_chart_source _ _) he xe
(chart_mem_maximalAtlas _ _) (mem_chart_source _ _) hf xf
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart
/-- A version of `liftPropWithinAt_indep_chart`, only for the source. -/
theorem liftPropWithinAt_indep_chart_source [HasGroupoid M G] (he : e ∈ G.maximalAtlas M)
(xe : x ∈ e.source) :
LiftPropWithinAt P g s x ↔ LiftPropWithinAt P (g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by
rw [liftPropWithinAt_self_source, liftPropWithinAt_iff',
e.symm.continuousWithinAt_iff_continuousWithinAt_comp_right xe, e.symm_symm]
refine and_congr Iff.rfl ?_
rw [Function.comp_apply, e.left_inv xe, ← Function.comp.assoc,
hG.liftPropWithinAt_indep_chart_source_aux (chartAt _ (g x) ∘ g) (chart_mem_maximalAtlas G x)
(mem_chart_source _ x) he xe, Function.comp.assoc]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_source StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_source
/-- A version of `liftPropWithinAt_indep_chart`, only for the target. -/
theorem liftPropWithinAt_indep_chart_target [HasGroupoid M' G'] (hf : f ∈ G'.maximalAtlas M')
(xf : g x ∈ f.source) :
LiftPropWithinAt P g s x ↔ ContinuousWithinAt g s x ∧ LiftPropWithinAt P (f ∘ g) s x := by
rw [liftPropWithinAt_self_target, liftPropWithinAt_iff', and_congr_right_iff]
intro hg
simp_rw [(f.continuousAt xf).comp_continuousWithinAt hg, true_and_iff]
exact hG.liftPropWithinAt_indep_chart_target_aux (mem_chart_source _ _)
(chart_mem_maximalAtlas _ _) (mem_chart_source _ _) hf xf hg
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart_target StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart_target
/-- A version of `liftPropWithinAt_indep_chart`, that uses `LiftPropWithinAt` on both sides. -/
theorem liftPropWithinAt_indep_chart' [HasGroupoid M G] [HasGroupoid M' G']
(he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M')
(xf : g x ∈ f.source) :
LiftPropWithinAt P g s x ↔
ContinuousWithinAt g s x ∧ LiftPropWithinAt P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by
rw [hG.liftPropWithinAt_indep_chart he xe hf xf, liftPropWithinAt_self, and_left_comm,
Iff.comm, and_iff_right_iff_imp]
intro h
have h1 := (e.symm.continuousWithinAt_iff_continuousWithinAt_comp_right xe).mp h.1
have : ContinuousAt f ((g ∘ e.symm) (e x)) := by
simp_rw [Function.comp, e.left_inv xe, f.continuousAt xf]
exact this.comp_continuousWithinAt h1
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_indep_chart' StructureGroupoid.LocalInvariantProp.liftPropWithinAt_indep_chart'
theorem liftPropOn_indep_chart [HasGroupoid M G] [HasGroupoid M' G'] (he : e ∈ G.maximalAtlas M)
(hf : f ∈ G'.maximalAtlas M') (h : LiftPropOn P g s) {y : H}
(hy : y ∈ e.target ∩ e.symm ⁻¹' (s ∩ g ⁻¹' f.source)) :
P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) y := by
convert ((hG.liftPropWithinAt_indep_chart he (e.symm_mapsTo hy.1) hf hy.2.2).1 (h _ hy.2.1)).2
rw [e.right_inv hy.1]
#align structure_groupoid.local_invariant_prop.lift_prop_on_indep_chart StructureGroupoid.LocalInvariantProp.liftPropOn_indep_chart
theorem liftPropWithinAt_inter' (ht : t ∈ 𝓝[s] x) :
LiftPropWithinAt P g (s ∩ t) x ↔ LiftPropWithinAt P g s x := by
rw [liftPropWithinAt_iff', liftPropWithinAt_iff', continuousWithinAt_inter' ht, hG.congr_set]
simp_rw [eventuallyEq_set, mem_preimage,
(chartAt _ x).eventually_nhds' (fun x ↦ x ∈ s ∩ t ↔ x ∈ s) (mem_chart_source _ x)]
exact (mem_nhdsWithin_iff_eventuallyEq.mp ht).symm.mem_iff
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_inter' StructureGroupoid.LocalInvariantProp.liftPropWithinAt_inter'
theorem liftPropWithinAt_inter (ht : t ∈ 𝓝 x) :
LiftPropWithinAt P g (s ∩ t) x ↔ LiftPropWithinAt P g s x :=
hG.liftPropWithinAt_inter' (mem_nhdsWithin_of_mem_nhds ht)
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_inter StructureGroupoid.LocalInvariantProp.liftPropWithinAt_inter
theorem liftPropAt_of_liftPropWithinAt (h : LiftPropWithinAt P g s x) (hs : s ∈ 𝓝 x) :
LiftPropAt P g x := by
rwa [← univ_inter s, hG.liftPropWithinAt_inter hs] at h
#align structure_groupoid.local_invariant_prop.lift_prop_at_of_lift_prop_within_at StructureGroupoid.LocalInvariantProp.liftPropAt_of_liftPropWithinAt
theorem liftPropWithinAt_of_liftPropAt_of_mem_nhds (h : LiftPropAt P g x) (hs : s ∈ 𝓝 x) :
LiftPropWithinAt P g s x := by
rwa [← univ_inter s, hG.liftPropWithinAt_inter hs]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_of_lift_prop_at_of_mem_nhds StructureGroupoid.LocalInvariantProp.liftPropWithinAt_of_liftPropAt_of_mem_nhds
theorem liftPropOn_of_locally_liftPropOn
(h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ LiftPropOn P g (s ∩ u)) : LiftPropOn P g s := by
intro x hx
rcases h x hx with ⟨u, u_open, xu, hu⟩
have := hu x ⟨hx, xu⟩
rwa [hG.liftPropWithinAt_inter] at this
exact u_open.mem_nhds xu
#align structure_groupoid.local_invariant_prop.lift_prop_on_of_locally_lift_prop_on StructureGroupoid.LocalInvariantProp.liftPropOn_of_locally_liftPropOn
theorem liftProp_of_locally_liftPropOn (h : ∀ x, ∃ u, IsOpen u ∧ x ∈ u ∧ LiftPropOn P g u) :
LiftProp P g := by
rw [← liftPropOn_univ]
refine hG.liftPropOn_of_locally_liftPropOn fun x _ ↦ ?_
simp [h x]
#align structure_groupoid.local_invariant_prop.lift_prop_of_locally_lift_prop_on StructureGroupoid.LocalInvariantProp.liftProp_of_locally_liftPropOn
theorem liftPropWithinAt_congr_of_eventuallyEq (h : LiftPropWithinAt P g s x) (h₁ : g' =ᶠ[𝓝[s] x] g)
(hx : g' x = g x) : LiftPropWithinAt P g' s x := by
refine ⟨h.1.congr_of_eventuallyEq h₁ hx, ?_⟩
refine hG.congr_nhdsWithin' ?_
(by simp_rw [Function.comp_apply, (chartAt H x).left_inv (mem_chart_source H x), hx]) h.2
simp_rw [EventuallyEq, Function.comp_apply]
rw [(chartAt H x).eventually_nhdsWithin'
(fun y ↦ chartAt H' (g' x) (g' y) = chartAt H' (g x) (g y)) (mem_chart_source H x)]
exact h₁.mono fun y hy ↦ by rw [hx, hy]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_congr_of_eventually_eq StructureGroupoid.LocalInvariantProp.liftPropWithinAt_congr_of_eventuallyEq
theorem liftPropWithinAt_congr_iff_of_eventuallyEq (h₁ : g' =ᶠ[𝓝[s] x] g) (hx : g' x = g x) :
LiftPropWithinAt P g' s x ↔ LiftPropWithinAt P g s x :=
⟨fun h ↦ hG.liftPropWithinAt_congr_of_eventuallyEq h h₁.symm hx.symm,
fun h ↦ hG.liftPropWithinAt_congr_of_eventuallyEq h h₁ hx⟩
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_congr_iff_of_eventually_eq StructureGroupoid.LocalInvariantProp.liftPropWithinAt_congr_iff_of_eventuallyEq
theorem liftPropWithinAt_congr_iff (h₁ : ∀ y ∈ s, g' y = g y) (hx : g' x = g x) :
LiftPropWithinAt P g' s x ↔ LiftPropWithinAt P g s x :=
hG.liftPropWithinAt_congr_iff_of_eventuallyEq (eventually_nhdsWithin_of_forall h₁) hx
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_congr_iff StructureGroupoid.LocalInvariantProp.liftPropWithinAt_congr_iff
theorem liftPropWithinAt_congr (h : LiftPropWithinAt P g s x) (h₁ : ∀ y ∈ s, g' y = g y)
(hx : g' x = g x) : LiftPropWithinAt P g' s x :=
(hG.liftPropWithinAt_congr_iff h₁ hx).mpr h
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_congr StructureGroupoid.LocalInvariantProp.liftPropWithinAt_congr
theorem liftPropAt_congr_iff_of_eventuallyEq (h₁ : g' =ᶠ[𝓝 x] g) :
LiftPropAt P g' x ↔ LiftPropAt P g x :=
hG.liftPropWithinAt_congr_iff_of_eventuallyEq (by simp_rw [nhdsWithin_univ, h₁]) h₁.eq_of_nhds
#align structure_groupoid.local_invariant_prop.lift_prop_at_congr_iff_of_eventually_eq StructureGroupoid.LocalInvariantProp.liftPropAt_congr_iff_of_eventuallyEq
theorem liftPropAt_congr_of_eventuallyEq (h : LiftPropAt P g x) (h₁ : g' =ᶠ[𝓝 x] g) :
LiftPropAt P g' x :=
(hG.liftPropAt_congr_iff_of_eventuallyEq h₁).mpr h
#align structure_groupoid.local_invariant_prop.lift_prop_at_congr_of_eventually_eq StructureGroupoid.LocalInvariantProp.liftPropAt_congr_of_eventuallyEq
theorem liftPropOn_congr (h : LiftPropOn P g s) (h₁ : ∀ y ∈ s, g' y = g y) : LiftPropOn P g' s :=
fun x hx ↦ hG.liftPropWithinAt_congr (h x hx) h₁ (h₁ x hx)
#align structure_groupoid.local_invariant_prop.lift_prop_on_congr StructureGroupoid.LocalInvariantProp.liftPropOn_congr
theorem liftPropOn_congr_iff (h₁ : ∀ y ∈ s, g' y = g y) : LiftPropOn P g' s ↔ LiftPropOn P g s :=
⟨fun h ↦ hG.liftPropOn_congr h fun y hy ↦ (h₁ y hy).symm, fun h ↦ hG.liftPropOn_congr h h₁⟩
#align structure_groupoid.local_invariant_prop.lift_prop_on_congr_iff StructureGroupoid.LocalInvariantProp.liftPropOn_congr_iff
theorem liftPropWithinAt_mono_of_mem
(mono_of_mem : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, s ∈ 𝓝[t] x → P f s x → P f t x)
(h : LiftPropWithinAt P g s x) (hst : s ∈ 𝓝[t] x) : LiftPropWithinAt P g t x := by
simp only [liftPropWithinAt_iff'] at h ⊢
refine ⟨h.1.mono_of_mem hst, mono_of_mem ?_ h.2⟩
simp_rw [← mem_map, (chartAt H x).symm.map_nhdsWithin_preimage_eq (mem_chart_target H x),
(chartAt H x).left_inv (mem_chart_source H x), hst]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_mono_of_mem StructureGroupoid.LocalInvariantProp.liftPropWithinAt_mono_of_mem
theorem liftPropWithinAt_mono (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x)
(h : LiftPropWithinAt P g s x) (hts : t ⊆ s) : LiftPropWithinAt P g t x := by
refine ⟨h.1.mono hts, mono (fun y hy ↦ ?_) h.2⟩
simp only [mfld_simps] at hy
simp only [hy, hts _, mfld_simps]
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_mono StructureGroupoid.LocalInvariantProp.liftPropWithinAt_mono
theorem liftPropWithinAt_of_liftPropAt (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x)
(h : LiftPropAt P g x) : LiftPropWithinAt P g s x := by
rw [← liftPropWithinAt_univ] at h
exact liftPropWithinAt_mono mono h (subset_univ _)
#align structure_groupoid.local_invariant_prop.lift_prop_within_at_of_lift_prop_at StructureGroupoid.LocalInvariantProp.liftPropWithinAt_of_liftPropAt
theorem liftPropOn_mono (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x)
(h : LiftPropOn P g t) (hst : s ⊆ t) : LiftPropOn P g s :=
fun x hx ↦ liftPropWithinAt_mono mono (h x (hst hx)) hst
#align structure_groupoid.local_invariant_prop.lift_prop_on_mono StructureGroupoid.LocalInvariantProp.liftPropOn_mono
theorem liftPropOn_of_liftProp (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x)
(h : LiftProp P g) : LiftPropOn P g s := by
rw [← liftPropOn_univ] at h
exact liftPropOn_mono mono h (subset_univ _)
#align structure_groupoid.local_invariant_prop.lift_prop_on_of_lift_prop StructureGroupoid.LocalInvariantProp.liftPropOn_of_liftProp
theorem liftPropAt_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q)
(hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) (hx : x ∈ e.source) : LiftPropAt Q e x := by
simp_rw [LiftPropAt, hG.liftPropWithinAt_indep_chart he hx G.id_mem_maximalAtlas (mem_univ _),
(e.continuousAt hx).continuousWithinAt, true_and_iff]
exact hG.congr' (e.eventually_right_inverse' hx) (hQ _)
#align structure_groupoid.local_invariant_prop.lift_prop_at_of_mem_maximal_atlas StructureGroupoid.LocalInvariantProp.liftPropAt_of_mem_maximalAtlas
theorem liftPropOn_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q)
(hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) : LiftPropOn Q e e.source := by
intro x hx
apply hG.liftPropWithinAt_of_liftPropAt_of_mem_nhds (hG.liftPropAt_of_mem_maximalAtlas hQ he hx)
exact e.open_source.mem_nhds hx
#align structure_groupoid.local_invariant_prop.lift_prop_on_of_mem_maximal_atlas StructureGroupoid.LocalInvariantProp.liftPropOn_of_mem_maximalAtlas
theorem liftPropAt_symm_of_mem_maximalAtlas [HasGroupoid M G] {x : H}
(hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G)
(hx : x ∈ e.target) : LiftPropAt Q e.symm x := by
suffices h : Q (e ∘ e.symm) univ x by
have : e.symm x ∈ e.source := by simp only [hx, mfld_simps]
rw [LiftPropAt, hG.liftPropWithinAt_indep_chart G.id_mem_maximalAtlas (mem_univ _) he this]
refine ⟨(e.symm.continuousAt hx).continuousWithinAt, ?_⟩
simp only [h, mfld_simps]
exact hG.congr' (e.eventually_right_inverse hx) (hQ x)
#align structure_groupoid.local_invariant_prop.lift_prop_at_symm_of_mem_maximal_atlas StructureGroupoid.LocalInvariantProp.liftPropAt_symm_of_mem_maximalAtlas
theorem liftPropOn_symm_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q)
(hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) : LiftPropOn Q e.symm e.target := by
intro x hx
apply hG.liftPropWithinAt_of_liftPropAt_of_mem_nhds
(hG.liftPropAt_symm_of_mem_maximalAtlas hQ he hx)
exact e.open_target.mem_nhds hx
#align structure_groupoid.local_invariant_prop.lift_prop_on_symm_of_mem_maximal_atlas StructureGroupoid.LocalInvariantProp.liftPropOn_symm_of_mem_maximalAtlas
theorem liftPropAt_chart [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) :
LiftPropAt Q (chartAt (H := H) x) x :=
hG.liftPropAt_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) (mem_chart_source H x)
#align structure_groupoid.local_invariant_prop.lift_prop_at_chart StructureGroupoid.LocalInvariantProp.liftPropAt_chart
theorem liftPropOn_chart [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) :
LiftPropOn Q (chartAt (H := H) x) (chartAt (H := H) x).source :=
hG.liftPropOn_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x)
#align structure_groupoid.local_invariant_prop.lift_prop_on_chart StructureGroupoid.LocalInvariantProp.liftPropOn_chart
theorem liftPropAt_chart_symm [HasGroupoid M G] (hG : G.LocalInvariantProp G Q)
(hQ : ∀ y, Q id univ y) : LiftPropAt Q (chartAt (H := H) x).symm ((chartAt H x) x) :=
hG.liftPropAt_symm_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) (by simp)
#align structure_groupoid.local_invariant_prop.lift_prop_at_chart_symm StructureGroupoid.LocalInvariantProp.liftPropAt_chart_symm
theorem liftPropOn_chart_symm [HasGroupoid M G] (hG : G.LocalInvariantProp G Q)
(hQ : ∀ y, Q id univ y) : LiftPropOn Q (chartAt (H := H) x).symm (chartAt H x).target :=
hG.liftPropOn_symm_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x)
#align structure_groupoid.local_invariant_prop.lift_prop_on_chart_symm StructureGroupoid.LocalInvariantProp.liftPropOn_chart_symm
theorem liftPropAt_of_mem_groupoid (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y)
{f : PartialHomeomorph H H} (hf : f ∈ G) {x : H} (hx : x ∈ f.source) : LiftPropAt Q f x :=
liftPropAt_of_mem_maximalAtlas hG hQ (G.mem_maximalAtlas_of_mem_groupoid hf) hx
#align structure_groupoid.local_invariant_prop.lift_prop_at_of_mem_groupoid StructureGroupoid.LocalInvariantProp.liftPropAt_of_mem_groupoid
theorem liftPropOn_of_mem_groupoid (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y)
{f : PartialHomeomorph H H} (hf : f ∈ G) : LiftPropOn Q f f.source :=
liftPropOn_of_mem_maximalAtlas hG hQ (G.mem_maximalAtlas_of_mem_groupoid hf)
#align structure_groupoid.local_invariant_prop.lift_prop_on_of_mem_groupoid StructureGroupoid.LocalInvariantProp.liftPropOn_of_mem_groupoid
theorem liftProp_id (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) :
LiftProp Q (id : M → M) := by
simp_rw [liftProp_iff, continuous_id, true_and_iff]
exact fun x ↦ hG.congr' ((chartAt H x).eventually_right_inverse <| mem_chart_target H x) (hQ _)
#align structure_groupoid.local_invariant_prop.lift_prop_id StructureGroupoid.LocalInvariantProp.liftProp_id
theorem liftPropAt_iff_comp_subtype_val (hG : LocalInvariantProp G G' P) {U : Opens M}
(f : M → M') (x : U) :
LiftPropAt P f x ↔ LiftPropAt P (f ∘ Subtype.val) x := by
simp only [LiftPropAt, liftPropWithinAt_iff']
congrm ?_ ∧ ?_
· simp_rw [continuousWithinAt_univ, U.openEmbedding'.continuousAt_iff]
· apply hG.congr_iff
exact (U.chartAt_subtype_val_symm_eventuallyEq).fun_comp (chartAt H' (f x) ∘ f)
theorem liftPropAt_iff_comp_inclusion (hG : LocalInvariantProp G G' P) {U V : Opens M} (hUV : U ≤ V)
(f : V → M') (x : U) :
LiftPropAt P f (Set.inclusion hUV x) ↔ LiftPropAt P (f ∘ Set.inclusion hUV : U → M') x := by
simp only [LiftPropAt, liftPropWithinAt_iff']
congrm ?_ ∧ ?_
· simp_rw [continuousWithinAt_univ,
(TopologicalSpace.Opens.openEmbedding_of_le hUV).continuousAt_iff]
· apply hG.congr_iff
exact (TopologicalSpace.Opens.chartAt_inclusion_symm_eventuallyEq hUV).fun_comp
(chartAt H' (f (Set.inclusion hUV x)) ∘ f)
#align structure_groupoid.local_invariant_prop.lift_prop_at_iff_comp_inclusion StructureGroupoid.LocalInvariantProp.liftPropAt_iff_comp_inclusion
theorem liftProp_subtype_val {Q : (H → H) → Set H → H → Prop} (hG : LocalInvariantProp G G Q)
(hQ : ∀ y, Q id univ y) (U : Opens M) :
LiftProp Q (Subtype.val : U → M) := by
intro x
show LiftPropAt Q (id ∘ Subtype.val) x
rw [← hG.liftPropAt_iff_comp_subtype_val]
apply hG.liftProp_id hQ
theorem liftProp_inclusion {Q : (H → H) → Set H → H → Prop} (hG : LocalInvariantProp G G Q)
(hQ : ∀ y, Q id univ y) {U V : Opens M} (hUV : U ≤ V) :
LiftProp Q (Set.inclusion hUV : U → V) := by
intro x
show LiftPropAt Q (id ∘ inclusion hUV) x
rw [← hG.liftPropAt_iff_comp_inclusion hUV]
apply hG.liftProp_id hQ
#align structure_groupoid.local_invariant_prop.lift_prop_inclusion StructureGroupoid.LocalInvariantProp.liftProp_inclusion
end LocalInvariantProp
section LocalStructomorph
variable (G)
open PartialHomeomorph
/-- A function from a model space `H` to itself is a local structomorphism, with respect to a
structure groupoid `G` for `H`, relative to a set `s` in `H`, if for all points `x` in the set, the
function agrees with a `G`-structomorphism on `s` in a neighbourhood of `x`. -/
def IsLocalStructomorphWithinAt (f : H → H) (s : Set H) (x : H) : Prop :=
x ∈ s → ∃ e : PartialHomeomorph H H, e ∈ G ∧ EqOn f e.toFun (s ∩ e.source) ∧ x ∈ e.source
#align structure_groupoid.is_local_structomorph_within_at StructureGroupoid.IsLocalStructomorphWithinAt
/-- For a groupoid `G` which is `ClosedUnderRestriction`, being a local structomorphism is a local
invariant property. -/
theorem isLocalStructomorphWithinAt_localInvariantProp [ClosedUnderRestriction G] :
LocalInvariantProp G G (IsLocalStructomorphWithinAt G) :=
{ is_local := by
intro s x u f hu hux
constructor
· rintro h hx
rcases h hx.1 with ⟨e, heG, hef, hex⟩
have : s ∩ u ∩ e.source ⊆ s ∩ e.source := by mfld_set_tac
exact ⟨e, heG, hef.mono this, hex⟩
· rintro h hx
rcases h ⟨hx, hux⟩ with ⟨e, heG, hef, hex⟩
refine ⟨e.restr (interior u), ?_, ?_, ?_⟩
· exact closedUnderRestriction' heG isOpen_interior
· have : s ∩ u ∩ e.source = s ∩ (e.source ∩ u) := by mfld_set_tac
simpa only [this, interior_interior, hu.interior_eq, mfld_simps] using hef
· simp only [*, interior_interior, hu.interior_eq, mfld_simps]
right_invariance' := by
intro s x f e' he'G he'x h hx
have hxs : x ∈ s := by simpa only [e'.left_inv he'x, mfld_simps] using hx
rcases h hxs with ⟨e, heG, hef, hex⟩
refine ⟨e'.symm.trans e, G.trans (G.symm he'G) heG, ?_, ?_⟩
· intro y hy
simp only [mfld_simps] at hy
simp only [hef ⟨hy.1, hy.2.2⟩, mfld_simps]
· simp only [hex, he'x, mfld_simps]
congr_of_forall := by
intro s x f g hfgs _ h hx
rcases h hx with ⟨e, heG, hef, hex⟩
refine ⟨e, heG, ?_, hex⟩
intro y hy
rw [← hef hy, hfgs y hy.1]
left_invariance' := by
intro s x f e' he'G _ hfx h hx
rcases h hx with ⟨e, heG, hef, hex⟩
refine ⟨e.trans e', G.trans heG he'G, ?_, ?_⟩
· intro y hy
simp only [mfld_simps] at hy
simp only [hef ⟨hy.1, hy.2.1⟩, mfld_simps]
· simpa only [hex, hef ⟨hx, hex⟩, mfld_simps] using hfx }
#align structure_groupoid.is_local_structomorph_within_at_local_invariant_prop StructureGroupoid.isLocalStructomorphWithinAt_localInvariantProp
/-- A slight reformulation of `IsLocalStructomorphWithinAt` when `f` is a partial homeomorph.
This gives us an `e` that is defined on a subset of `f.source`. -/
theorem _root_.PartialHomeomorph.isLocalStructomorphWithinAt_iff {G : StructureGroupoid H}
[ClosedUnderRestriction G] (f : PartialHomeomorph H H) {s : Set H} {x : H}
(hx : x ∈ f.source ∪ sᶜ) :
G.IsLocalStructomorphWithinAt (⇑f) s x ↔
x ∈ s → ∃ e : PartialHomeomorph H H,
e ∈ G ∧ e.source ⊆ f.source ∧ EqOn f (⇑e) (s ∩ e.source) ∧ x ∈ e.source := by
constructor
· intro hf h2x
obtain ⟨e, he, hfe, hxe⟩ := hf h2x
refine ⟨e.restr f.source, closedUnderRestriction' he f.open_source, ?_, ?_, hxe, ?_⟩
· simp_rw [PartialHomeomorph.restr_source]
exact inter_subset_right.trans interior_subset
· intro x' hx'
exact hfe ⟨hx'.1, hx'.2.1⟩
· rw [f.open_source.interior_eq]
exact Or.resolve_right hx (not_not.mpr h2x)
· intro hf hx
obtain ⟨e, he, _, hfe, hxe⟩ := hf hx
exact ⟨e, he, hfe, hxe⟩
#align local_homeomorph.is_local_structomorph_within_at_iff PartialHomeomorph.isLocalStructomorphWithinAt_iff
/-- A slight reformulation of `IsLocalStructomorphWithinAt` when `f` is a partial homeomorph and
the set we're considering is a superset of `f.source`. -/
theorem _root_.PartialHomeomorph.isLocalStructomorphWithinAt_iff' {G : StructureGroupoid H}
[ClosedUnderRestriction G] (f : PartialHomeomorph H H) {s : Set H} {x : H} (hs : f.source ⊆ s)
(hx : x ∈ f.source ∪ sᶜ) :
G.IsLocalStructomorphWithinAt (⇑f) s x ↔
x ∈ s → ∃ e : PartialHomeomorph H H,
e ∈ G ∧ e.source ⊆ f.source ∧ EqOn f (⇑e) e.source ∧ x ∈ e.source := by
rw [f.isLocalStructomorphWithinAt_iff hx]
refine imp_congr_right fun _ ↦ exists_congr fun e ↦ and_congr_right fun _ ↦ ?_
refine and_congr_right fun h2e ↦ ?_
rw [inter_eq_right.mpr (h2e.trans hs)]
#align local_homeomorph.is_local_structomorph_within_at_iff' PartialHomeomorph.isLocalStructomorphWithinAt_iff'
/-- A slight reformulation of `IsLocalStructomorphWithinAt` when `f` is a partial homeomorph and
the set we're considering is `f.source`. -/
theorem _root_.PartialHomeomorph.isLocalStructomorphWithinAt_source_iff {G : StructureGroupoid H}
[ClosedUnderRestriction G] (f : PartialHomeomorph H H) {x : H} :
G.IsLocalStructomorphWithinAt (⇑f) f.source x ↔
x ∈ f.source → ∃ e : PartialHomeomorph H H,
e ∈ G ∧ e.source ⊆ f.source ∧ EqOn f (⇑e) e.source ∧ x ∈ e.source :=
haveI : x ∈ f.source ∪ f.sourceᶜ := by simp_rw [union_compl_self, mem_univ]
f.isLocalStructomorphWithinAt_iff' Subset.rfl this
#align local_homeomorph.is_local_structomorph_within_at_source_iff PartialHomeomorph.isLocalStructomorphWithinAt_source_iff
variable {H₁ : Type*} [TopologicalSpace H₁] {H₂ : Type*} [TopologicalSpace H₂] {H₃ : Type*}
[TopologicalSpace H₃] [ChartedSpace H₁ H₂] [ChartedSpace H₂ H₃] {G₁ : StructureGroupoid H₁}
[HasGroupoid H₂ G₁] [ClosedUnderRestriction G₁] (G₂ : StructureGroupoid H₂) [HasGroupoid H₃ G₂]
| Mathlib/Geometry/Manifold/LocalInvariantProperties.lean | 698 | 722 | theorem HasGroupoid.comp
(H : ∀ e ∈ G₂, LiftPropOn (IsLocalStructomorphWithinAt G₁) (e : H₂ → H₂) e.source) :
@HasGroupoid H₁ _ H₃ _ (ChartedSpace.comp H₁ H₂ H₃) G₁ :=
let _ := ChartedSpace.comp H₁ H₂ H₃ -- Porting note: need this to synthesize `ChartedSpace H₁ H₃`
{ compatible := by |
rintro _ _ ⟨e, he, f, hf, rfl⟩ ⟨e', he', f', hf', rfl⟩
apply G₁.locality
intro x hx
simp only [mfld_simps] at hx
have hxs : x ∈ f.symm ⁻¹' (e.symm ≫ₕ e').source := by simp only [hx, mfld_simps]
have hxs' : x ∈ f.target ∩ f.symm ⁻¹' ((e.symm ≫ₕ e').source ∩ e.symm ≫ₕ e' ⁻¹' f'.source) :=
by simp only [hx, mfld_simps]
obtain ⟨φ, hφG₁, hφ, hφ_dom⟩ := LocalInvariantProp.liftPropOn_indep_chart
(isLocalStructomorphWithinAt_localInvariantProp G₁) (G₁.subset_maximalAtlas hf)
(G₁.subset_maximalAtlas hf') (H _ (G₂.compatible he he')) hxs' hxs
simp_rw [← PartialHomeomorph.coe_trans, PartialHomeomorph.trans_assoc] at hφ
simp_rw [PartialHomeomorph.trans_symm_eq_symm_trans_symm, PartialHomeomorph.trans_assoc]
have hs : IsOpen (f.symm ≫ₕ e.symm ≫ₕ e' ≫ₕ f').source :=
(f.symm ≫ₕ e.symm ≫ₕ e' ≫ₕ f').open_source
refine ⟨_, hs.inter φ.open_source, ?_, ?_⟩
· simp only [hx, hφ_dom, mfld_simps]
· refine G₁.mem_of_eqOnSource (closedUnderRestriction' hφG₁ hs) ?_
rw [PartialHomeomorph.restr_source_inter]
refine PartialHomeomorph.Set.EqOn.restr_eqOn_source (hφ.mono ?_)
mfld_set_tac }
|
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Yuyang Zhao
-/
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Algebra.Order.Monoid.Unbundled.Defs
import Mathlib.Tactic.GCongr.Core
#align_import algebra.order.ring.lemmas from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Monotonicity of multiplication by positive elements
This file defines typeclasses to reason about monotonicity of the operations
* `b ↦ a * b`, "left multiplication"
* `a ↦ a * b`, "right multiplication"
We use eight typeclasses to encode the various properties we care about for those two operations.
These typeclasses are meant to be mostly internal to this file, to set up each lemma in the
appropriate generality.
Less granular typeclasses like `OrderedAddCommMonoid`, `LinearOrderedField` should be enough for
most purposes, and the system is set up so that they imply the correct granular typeclasses here.
If those are enough for you, you may stop reading here! Else, beware that what follows is a bit
technical.
## Definitions
In all that follows, `α` is an orders which has a `0` and a multiplication. Note however that we do
not use lawfulness of this action in most of the file. Hence `*` should be considered here as a
mostly arbitrary function `α → α → α`.
We use the following four typeclasses to reason about left multiplication (`b ↦ a * b`):
* `PosMulMono`: If `a ≥ 0`, then `b₁ ≤ b₂ → a * b₁ ≤ a * b₂`.
* `PosMulStrictMono`: If `a > 0`, then `b₁ < b₂ → a * b₁ < a * b₂`.
* `PosMulReflectLT`: If `a ≥ 0`, then `a * b₁ < a * b₂ → b₁ < b₂`.
* `PosMulReflectLE`: If `a > 0`, then `a * b₁ ≤ a * b₂ → b₁ ≤ b₂`.
We use the following four typeclasses to reason about right multiplication (`a ↦ a * b`):
* `MulPosMono`: If `b ≥ 0`, then `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b`.
* `MulPosStrictMono`: If `b > 0`, then `a₁ < a₂ → a₁ * b < a₂ * b`.
* `MulPosReflectLT`: If `b ≥ 0`, then `a₁ * b < a₂ * b → a₁ < a₂`.
* `MulPosReflectLE`: If `b > 0`, then `a₁ * b ≤ a₂ * b → a₁ ≤ a₂`.
## Implications
As `α` gets more and more structure, those typeclasses end up being equivalent. The commonly used
implications are:
* When `α` is a partial order:
* `PosMulStrictMono → PosMulMono`
* `MulPosStrictMono → MulPosMono`
* `PosMulReflectLE → PosMulReflectLT`
* `MulPosReflectLE → MulPosReflectLT`
* When `α` is a linear order:
* `PosMulStrictMono → PosMulReflectLE`
* `MulPosStrictMono → MulPosReflectLE` .
* When the multiplication of `α` is commutative:
* `PosMulMono → MulPosMono`
* `PosMulStrictMono → MulPosStrictMono`
* `PosMulReflectLE → MulPosReflectLE`
* `PosMulReflectLT → MulPosReflectLT`
Further, the bundled non-granular typeclasses imply the granular ones like so:
* `OrderedSemiring → PosMulMono`
* `OrderedSemiring → MulPosMono`
* `StrictOrderedSemiring → PosMulStrictMono`
* `StrictOrderedSemiring → MulPosStrictMono`
All these are registered as instances, which means that in practice you should not worry about these
implications. However, if you encounter a case where you think a statement is true but not covered
by the current implications, please bring it up on Zulip!
## Notation
The following is local notation in this file:
* `α≥0`: `{x : α // 0 ≤ x}`
* `α>0`: `{x : α // 0 < x}`
See https://leanprover.zulipchat.com/#narrow/stream/113488-general/topic/notation.20for.20positive.20elements
for a discussion about this notation, and whether to enable it globally (note that the notation is
currently global but broken, hence actually only works locally).
-/
variable (α : Type*)
set_option quotPrecheck false in
/-- Local notation for the nonnegative elements of a type `α`. TODO: actually make local. -/
notation "α≥0" => { x : α // 0 ≤ x }
set_option quotPrecheck false in
/-- Local notation for the positive elements of a type `α`. TODO: actually make local. -/
notation "α>0" => { x : α // 0 < x }
section Abbreviations
variable [Mul α] [Zero α] [Preorder α]
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the left,
namely `b₁ ≤ b₂ → a * b₁ ≤ a * b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev PosMulMono : Prop :=
CovariantClass α≥0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono PosMulMono
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the right,
namely `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev MulPosMono : Prop :=
CovariantClass α≥0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono MulPosMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the left,
namely `b₁ < b₂ → a * b₁ < a * b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev PosMulStrictMono : Prop :=
CovariantClass α>0 α (fun x y => x * y) (· < ·)
#align pos_mul_strict_mono PosMulStrictMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the right,
namely `a₁ < a₂ → a₁ * b < a₂ * b` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev MulPosStrictMono : Prop :=
CovariantClass α>0 α (fun x y => y * x) (· < ·)
#align mul_pos_strict_mono MulPosStrictMono
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the left, namely `a * b₁ < a * b₂ → b₁ < b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => x * y) (· < ·)
#align pos_mul_reflect_lt PosMulReflectLT
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the right, namely `a₁ * b < a₂ * b → a₁ < a₂` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => y * x) (· < ·)
#align mul_pos_reflect_lt MulPosReflectLT
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the left,
namely `a * b₁ ≤ a * b₂ → b₁ ≤ b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono_rev PosMulReflectLE
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the right,
namely `a₁ * b ≤ a₂ * b → a₁ ≤ a₂` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono_rev MulPosReflectLE
end Abbreviations
variable {α} {a b c d : α}
section MulZero
variable [Mul α] [Zero α]
section Preorder
variable [Preorder α]
instance PosMulMono.to_covariantClass_pos_mul_le [PosMulMono α] :
CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_mono.to_covariant_class_pos_mul_le PosMulMono.to_covariantClass_pos_mul_le
instance MulPosMono.to_covariantClass_pos_mul_le [MulPosMono α] :
CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_mono.to_covariant_class_pos_mul_le MulPosMono.to_covariantClass_pos_mul_le
instance PosMulReflectLT.to_contravariantClass_pos_mul_lt [PosMulReflectLT α] :
ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_reflect_lt.to_contravariant_class_pos_mul_lt PosMulReflectLT.to_contravariantClass_pos_mul_lt
instance MulPosReflectLT.to_contravariantClass_pos_mul_lt [MulPosReflectLT α] :
ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_reflect_lt.to_contravariant_class_pos_mul_lt MulPosReflectLT.to_contravariantClass_pos_mul_lt
@[gcongr]
theorem mul_le_mul_of_nonneg_left [PosMulMono α] (h : b ≤ c) (a0 : 0 ≤ a) : a * b ≤ a * c :=
@CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_left mul_le_mul_of_nonneg_left
@[gcongr]
theorem mul_le_mul_of_nonneg_right [MulPosMono α] (h : b ≤ c) (a0 : 0 ≤ a) : b * a ≤ c * a :=
@CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_right mul_le_mul_of_nonneg_right
@[gcongr]
theorem mul_lt_mul_of_pos_left [PosMulStrictMono α] (bc : b < c) (a0 : 0 < a) : a * b < a * c :=
@CovariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_left mul_lt_mul_of_pos_left
@[gcongr]
theorem mul_lt_mul_of_pos_right [MulPosStrictMono α] (bc : b < c) (a0 : 0 < a) : b * a < c * a :=
@CovariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_right mul_lt_mul_of_pos_right
theorem lt_of_mul_lt_mul_left [PosMulReflectLT α] (h : a * b < a * c) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_left lt_of_mul_lt_mul_left
theorem lt_of_mul_lt_mul_right [MulPosReflectLT α] (h : b * a < c * a) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_right lt_of_mul_lt_mul_right
theorem le_of_mul_le_mul_left [PosMulReflectLE α] (bc : a * b ≤ a * c) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_left le_of_mul_le_mul_left
theorem le_of_mul_le_mul_right [MulPosReflectLE α] (bc : b * a ≤ c * a) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_right le_of_mul_le_mul_right
alias lt_of_mul_lt_mul_of_nonneg_left := lt_of_mul_lt_mul_left
#align lt_of_mul_lt_mul_of_nonneg_left lt_of_mul_lt_mul_of_nonneg_left
alias lt_of_mul_lt_mul_of_nonneg_right := lt_of_mul_lt_mul_right
#align lt_of_mul_lt_mul_of_nonneg_right lt_of_mul_lt_mul_of_nonneg_right
alias le_of_mul_le_mul_of_pos_left := le_of_mul_le_mul_left
#align le_of_mul_le_mul_of_pos_left le_of_mul_le_mul_of_pos_left
alias le_of_mul_le_mul_of_pos_right := le_of_mul_le_mul_right
#align le_of_mul_le_mul_of_pos_right le_of_mul_le_mul_of_pos_right
@[simp]
theorem mul_lt_mul_left [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a * c ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_left mul_lt_mul_left
@[simp]
theorem mul_lt_mul_right [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
b * a < c * a ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_right mul_lt_mul_right
@[simp]
theorem mul_le_mul_left [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_left mul_le_mul_left
@[simp]
theorem mul_le_mul_right [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : b * a ≤ c * a ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_right mul_le_mul_right
alias mul_le_mul_iff_of_pos_left := mul_le_mul_left
alias mul_le_mul_iff_of_pos_right := mul_le_mul_right
alias mul_lt_mul_iff_of_pos_left := mul_lt_mul_left
alias mul_lt_mul_iff_of_pos_right := mul_lt_mul_right
theorem mul_lt_mul_of_pos_of_nonneg [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 ≤ d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans_le (mul_le_mul_of_nonneg_right h₁ d0)
#align mul_lt_mul_of_pos_of_nonneg mul_lt_mul_of_pos_of_nonneg
theorem mul_lt_mul_of_le_of_le' [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 ≤ c) : a * c < b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans_lt (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_le_of_le' mul_lt_mul_of_le_of_le'
theorem mul_lt_mul_of_nonneg_of_pos [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(a0 : 0 ≤ a) (d0 : 0 < d) : a * c < b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans_lt (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_nonneg_of_pos mul_lt_mul_of_nonneg_of_pos
theorem mul_lt_mul_of_le_of_lt' [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(b0 : 0 ≤ b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans_le (mul_le_mul_of_nonneg_left h₂ b0)
#align mul_lt_mul_of_le_of_lt' mul_lt_mul_of_le_of_lt'
theorem mul_lt_mul_of_pos_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 < d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_pos_of_pos mul_lt_mul_of_pos_of_pos
theorem mul_lt_mul_of_lt_of_lt' [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_lt_of_lt' mul_lt_mul_of_lt_of_lt'
theorem mul_lt_of_mul_lt_of_nonneg_left [PosMulMono α] (h : a * b < c) (hdb : d ≤ b) (ha : 0 ≤ a) :
a * d < c :=
(mul_le_mul_of_nonneg_left hdb ha).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_left mul_lt_of_mul_lt_of_nonneg_left
theorem lt_mul_of_lt_mul_of_nonneg_left [PosMulMono α] (h : a < b * c) (hcd : c ≤ d) (hb : 0 ≤ b) :
a < b * d :=
h.trans_le <| mul_le_mul_of_nonneg_left hcd hb
#align lt_mul_of_lt_mul_of_nonneg_left lt_mul_of_lt_mul_of_nonneg_left
theorem mul_lt_of_mul_lt_of_nonneg_right [MulPosMono α] (h : a * b < c) (hda : d ≤ a) (hb : 0 ≤ b) :
d * b < c :=
(mul_le_mul_of_nonneg_right hda hb).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_right mul_lt_of_mul_lt_of_nonneg_right
theorem lt_mul_of_lt_mul_of_nonneg_right [MulPosMono α] (h : a < b * c) (hbd : b ≤ d) (hc : 0 ≤ c) :
a < d * c :=
h.trans_le <| mul_le_mul_of_nonneg_right hbd hc
#align lt_mul_of_lt_mul_of_nonneg_right lt_mul_of_lt_mul_of_nonneg_right
end Preorder
section LinearOrder
variable [LinearOrder α]
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulReflectLE [PosMulStrictMono α] :
PosMulReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosReflectLE [MulPosStrictMono α] :
MulPosReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
theorem PosMulReflectLE.toPosMulStrictMono [PosMulReflectLE α] : PosMulStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_mono_rev.to_pos_mul_strict_mono PosMulReflectLE.toPosMulStrictMono
theorem MulPosReflectLE.toMulPosStrictMono [MulPosReflectLE α] : MulPosStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_mono_rev.to_mul_pos_strict_mono MulPosReflectLE.toMulPosStrictMono
theorem posMulStrictMono_iff_posMulReflectLE : PosMulStrictMono α ↔ PosMulReflectLE α :=
⟨@PosMulStrictMono.toPosMulReflectLE _ _ _ _, @PosMulReflectLE.toPosMulStrictMono _ _ _ _⟩
#align pos_mul_strict_mono_iff_pos_mul_mono_rev posMulStrictMono_iff_posMulReflectLE
theorem mulPosStrictMono_iff_mulPosReflectLE : MulPosStrictMono α ↔ MulPosReflectLE α :=
⟨@MulPosStrictMono.toMulPosReflectLE _ _ _ _, @MulPosReflectLE.toMulPosStrictMono _ _ _ _⟩
#align mul_pos_strict_mono_iff_mul_pos_mono_rev mulPosStrictMono_iff_mulPosReflectLE
theorem PosMulReflectLT.toPosMulMono [PosMulReflectLT α] : PosMulMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_reflect_lt.to_pos_mul_mono PosMulReflectLT.toPosMulMono
theorem MulPosReflectLT.toMulPosMono [MulPosReflectLT α] : MulPosMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_reflect_lt.to_mul_pos_mono MulPosReflectLT.toMulPosMono
theorem PosMulMono.toPosMulReflectLT [PosMulMono α] : PosMulReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align pos_mul_mono.to_pos_mul_reflect_lt PosMulMono.toPosMulReflectLT
theorem MulPosMono.toMulPosReflectLT [MulPosMono α] : MulPosReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align mul_pos_mono.to_mul_pos_reflect_lt MulPosMono.toMulPosReflectLT
/- TODO: Currently, only one in four of the above are made instances; we could consider making
both directions of `covariant_le_iff_contravariant_lt` and `covariant_lt_iff_contravariant_le`
instances, then all of the above become redundant instances, but there are performance issues. -/
theorem posMulMono_iff_posMulReflectLT : PosMulMono α ↔ PosMulReflectLT α :=
⟨@PosMulMono.toPosMulReflectLT _ _ _ _, @PosMulReflectLT.toPosMulMono _ _ _ _⟩
#align pos_mul_mono_iff_pos_mul_reflect_lt posMulMono_iff_posMulReflectLT
theorem mulPosMono_iff_mulPosReflectLT : MulPosMono α ↔ MulPosReflectLT α :=
⟨@MulPosMono.toMulPosReflectLT _ _ _ _, @MulPosReflectLT.toMulPosMono _ _ _ _⟩
#align mul_pos_mono_iff_mul_pos_reflect_lt mulPosMono_iff_mulPosReflectLT
end LinearOrder
end MulZero
section MulZeroClass
variable [MulZeroClass α]
section Preorder
variable [Preorder α]
/-- Assumes left covariance. -/
theorem Left.mul_pos [PosMulStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align left.mul_pos Left.mul_pos
alias mul_pos := Left.mul_pos
#align mul_pos mul_pos
theorem mul_neg_of_pos_of_neg [PosMulStrictMono α] (ha : 0 < a) (hb : b < 0) : a * b < 0 := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align mul_neg_of_pos_of_neg mul_neg_of_pos_of_neg
@[simp]
theorem mul_pos_iff_of_pos_left [PosMulStrictMono α] [PosMulReflectLT α] (h : 0 < a) :
0 < a * b ↔ 0 < b := by simpa using mul_lt_mul_left (b := 0) h
#align zero_lt_mul_left mul_pos_iff_of_pos_left
/-- Assumes right covariance. -/
theorem Right.mul_pos [MulPosStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align right.mul_pos Right.mul_pos
theorem mul_neg_of_neg_of_pos [MulPosStrictMono α] (ha : a < 0) (hb : 0 < b) : a * b < 0 := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align mul_neg_of_neg_of_pos mul_neg_of_neg_of_pos
@[simp]
theorem mul_pos_iff_of_pos_right [MulPosStrictMono α] [MulPosReflectLT α] (h : 0 < b) :
0 < a * b ↔ 0 < a := by simpa using mul_lt_mul_right (b := 0) h
#align zero_lt_mul_right mul_pos_iff_of_pos_right
/-- Assumes left covariance. -/
theorem Left.mul_nonneg [PosMulMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align left.mul_nonneg Left.mul_nonneg
alias mul_nonneg := Left.mul_nonneg
#align mul_nonneg mul_nonneg
theorem mul_nonpos_of_nonneg_of_nonpos [PosMulMono α] (ha : 0 ≤ a) (hb : b ≤ 0) : a * b ≤ 0 := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align mul_nonpos_of_nonneg_of_nonpos mul_nonpos_of_nonneg_of_nonpos
/-- Assumes right covariance. -/
theorem Right.mul_nonneg [MulPosMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align right.mul_nonneg Right.mul_nonneg
theorem mul_nonpos_of_nonpos_of_nonneg [MulPosMono α] (ha : a ≤ 0) (hb : 0 ≤ b) : a * b ≤ 0 := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align mul_nonpos_of_nonpos_of_nonneg mul_nonpos_of_nonpos_of_nonneg
theorem pos_of_mul_pos_right [PosMulReflectLT α] (h : 0 < a * b) (ha : 0 ≤ a) : 0 < b :=
lt_of_mul_lt_mul_left ((mul_zero a).symm ▸ h : a * 0 < a * b) ha
#align pos_of_mul_pos_right pos_of_mul_pos_right
theorem pos_of_mul_pos_left [MulPosReflectLT α] (h : 0 < a * b) (hb : 0 ≤ b) : 0 < a :=
lt_of_mul_lt_mul_right ((zero_mul b).symm ▸ h : 0 * b < a * b) hb
#align pos_of_mul_pos_left pos_of_mul_pos_left
theorem pos_iff_pos_of_mul_pos [PosMulReflectLT α] [MulPosReflectLT α] (hab : 0 < a * b) :
0 < a ↔ 0 < b :=
⟨pos_of_mul_pos_right hab ∘ le_of_lt, pos_of_mul_pos_left hab ∘ le_of_lt⟩
#align pos_iff_pos_of_mul_pos pos_iff_pos_of_mul_pos
theorem mul_le_mul_of_le_of_le [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (a0 : 0 ≤ a)
(d0 : 0 ≤ d) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans <| mul_le_mul_of_nonneg_right h₁ d0
#align mul_le_mul_of_le_of_le mul_le_mul_of_le_of_le
@[gcongr]
theorem mul_le_mul [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (c0 : 0 ≤ c)
(b0 : 0 ≤ b) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans <| mul_le_mul_of_nonneg_left h₂ b0
#align mul_le_mul mul_le_mul
theorem mul_self_le_mul_self [PosMulMono α] [MulPosMono α] (ha : 0 ≤ a) (hab : a ≤ b) :
a * a ≤ b * b :=
mul_le_mul hab hab ha <| ha.trans hab
#align mul_self_le_mul_self mul_self_le_mul_self
theorem mul_le_of_mul_le_of_nonneg_left [PosMulMono α] (h : a * b ≤ c) (hle : d ≤ b)
(a0 : 0 ≤ a) : a * d ≤ c :=
(mul_le_mul_of_nonneg_left hle a0).trans h
#align mul_le_of_mul_le_of_nonneg_left mul_le_of_mul_le_of_nonneg_left
theorem le_mul_of_le_mul_of_nonneg_left [PosMulMono α] (h : a ≤ b * c) (hle : c ≤ d)
(b0 : 0 ≤ b) : a ≤ b * d :=
h.trans (mul_le_mul_of_nonneg_left hle b0)
#align le_mul_of_le_mul_of_nonneg_left le_mul_of_le_mul_of_nonneg_left
theorem mul_le_of_mul_le_of_nonneg_right [MulPosMono α] (h : a * b ≤ c) (hle : d ≤ a)
(b0 : 0 ≤ b) : d * b ≤ c :=
(mul_le_mul_of_nonneg_right hle b0).trans h
#align mul_le_of_mul_le_of_nonneg_right mul_le_of_mul_le_of_nonneg_right
theorem le_mul_of_le_mul_of_nonneg_right [MulPosMono α] (h : a ≤ b * c) (hle : b ≤ d)
(c0 : 0 ≤ c) : a ≤ d * c :=
h.trans (mul_le_mul_of_nonneg_right hle c0)
#align le_mul_of_le_mul_of_nonneg_right le_mul_of_le_mul_of_nonneg_right
end Preorder
section PartialOrder
variable [PartialOrder α]
theorem posMulMono_iff_covariant_pos :
PosMulMono α ↔ CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨@PosMulMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_mono_iff_covariant_pos posMulMono_iff_covariant_pos
theorem mulPosMono_iff_covariant_pos :
MulPosMono α ↔ CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨@MulPosMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_mono_iff_covariant_pos mulPosMono_iff_covariant_pos
theorem posMulReflectLT_iff_contravariant_pos :
PosMulReflectLT α ↔ ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨@PosMulReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_reflect_lt_iff_contravariant_pos posMulReflectLT_iff_contravariant_pos
theorem mulPosReflectLT_iff_contravariant_pos :
MulPosReflectLT α ↔ ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨@MulPosReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_reflect_lt_iff_contravariant_pos mulPosReflectLT_iff_contravariant_pos
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulMono [PosMulStrictMono α] : PosMulMono α :=
posMulMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align pos_mul_strict_mono.to_pos_mul_mono PosMulStrictMono.toPosMulMono
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosMono [MulPosStrictMono α] : MulPosMono α :=
mulPosMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align mul_pos_strict_mono.to_mul_pos_mono MulPosStrictMono.toMulPosMono
-- see Note [lower instance priority]
instance (priority := 100) PosMulReflectLE.toPosMulReflectLT [PosMulReflectLE α] :
PosMulReflectLT α :=
posMulReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_left h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align pos_mul_mono_rev.to_pos_mul_reflect_lt PosMulReflectLE.toPosMulReflectLT
-- see Note [lower instance priority]
instance (priority := 100) MulPosReflectLE.toMulPosReflectLT [MulPosReflectLE α] :
MulPosReflectLT α :=
mulPosReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_right h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align mul_pos_mono_rev.to_mul_pos_reflect_lt MulPosReflectLE.toMulPosReflectLT
theorem mul_left_cancel_iff_of_pos [PosMulReflectLE α] (a0 : 0 < a) : a * b = a * c ↔ b = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_left h.le a0).antisymm <|
le_of_mul_le_mul_of_pos_left h.ge a0, congr_arg _⟩
#align mul_left_cancel_iff_of_pos mul_left_cancel_iff_of_pos
theorem mul_right_cancel_iff_of_pos [MulPosReflectLE α] (b0 : 0 < b) : a * b = c * b ↔ a = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_right h.le b0).antisymm <|
le_of_mul_le_mul_of_pos_right h.ge b0, congr_arg (· * b)⟩
#align mul_right_cancel_iff_of_pos mul_right_cancel_iff_of_pos
theorem mul_eq_mul_iff_eq_and_eq_of_pos [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (a0 : 0 < a) (d0 : 0 < d) :
a * c = b * d ↔ a = b ∧ c = d := by
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_le_mul_of_nonneg_left hcd a0.le).trans_lt (mul_lt_mul_of_pos_right hab d0)
· exact (mul_lt_mul_of_pos_left hcd a0).trans_le (mul_le_mul_of_nonneg_right hab d0.le)
#align mul_eq_mul_iff_eq_and_eq_of_pos mul_eq_mul_iff_eq_and_eq_of_pos
theorem mul_eq_mul_iff_eq_and_eq_of_pos' [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (b0 : 0 < b) (c0 : 0 < c) :
a * c = b * d ↔ a = b ∧ c = d := by
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_lt_mul_of_pos_right hab c0).trans_le (mul_le_mul_of_nonneg_left hcd b0.le)
· exact (mul_le_mul_of_nonneg_right hab c0.le).trans_lt (mul_lt_mul_of_pos_left hcd b0)
#align mul_eq_mul_iff_eq_and_eq_of_pos' mul_eq_mul_iff_eq_and_eq_of_pos'
end PartialOrder
section LinearOrder
variable [LinearOrder α]
theorem pos_and_pos_or_neg_and_neg_of_mul_pos [PosMulMono α] [MulPosMono α] (hab : 0 < a * b) :
0 < a ∧ 0 < b ∨ a < 0 ∧ b < 0 := by
rcases lt_trichotomy a 0 with (ha | rfl | ha)
· refine Or.inr ⟨ha, lt_imp_lt_of_le_imp_le (fun hb => ?_) hab⟩
exact mul_nonpos_of_nonpos_of_nonneg ha.le hb
· rw [zero_mul] at hab
exact hab.false.elim
· refine Or.inl ⟨ha, lt_imp_lt_of_le_imp_le (fun hb => ?_) hab⟩
exact mul_nonpos_of_nonneg_of_nonpos ha.le hb
#align pos_and_pos_or_neg_and_neg_of_mul_pos pos_and_pos_or_neg_and_neg_of_mul_pos
theorem neg_of_mul_pos_right [PosMulMono α] [MulPosMono α] (h : 0 < a * b) (ha : a ≤ 0) : b < 0 :=
((pos_and_pos_or_neg_and_neg_of_mul_pos h).resolve_left fun h => h.1.not_le ha).2
#align neg_of_mul_pos_right neg_of_mul_pos_right
theorem neg_of_mul_pos_left [PosMulMono α] [MulPosMono α] (h : 0 < a * b) (ha : b ≤ 0) : a < 0 :=
((pos_and_pos_or_neg_and_neg_of_mul_pos h).resolve_left fun h => h.2.not_le ha).1
#align neg_of_mul_pos_left neg_of_mul_pos_left
theorem neg_iff_neg_of_mul_pos [PosMulMono α] [MulPosMono α] (hab : 0 < a * b) : a < 0 ↔ b < 0 :=
⟨neg_of_mul_pos_right hab ∘ le_of_lt, neg_of_mul_pos_left hab ∘ le_of_lt⟩
#align neg_iff_neg_of_mul_pos neg_iff_neg_of_mul_pos
theorem Left.neg_of_mul_neg_left [PosMulMono α] (h : a * b < 0) (h1 : 0 ≤ a) : b < 0 :=
lt_of_not_ge fun h2 : b ≥ 0 => (Left.mul_nonneg h1 h2).not_lt h
#align left.neg_of_mul_neg_left Left.neg_of_mul_neg_left
theorem Right.neg_of_mul_neg_left [MulPosMono α] (h : a * b < 0) (h1 : 0 ≤ a) : b < 0 :=
lt_of_not_ge fun h2 : b ≥ 0 => (Right.mul_nonneg h1 h2).not_lt h
#align right.neg_of_mul_neg_left Right.neg_of_mul_neg_left
theorem Left.neg_of_mul_neg_right [PosMulMono α] (h : a * b < 0) (h1 : 0 ≤ b) : a < 0 :=
lt_of_not_ge fun h2 : a ≥ 0 => (Left.mul_nonneg h2 h1).not_lt h
#align left.neg_of_mul_neg_right Left.neg_of_mul_neg_right
theorem Right.neg_of_mul_neg_right [MulPosMono α] (h : a * b < 0) (h1 : 0 ≤ b) : a < 0 :=
lt_of_not_ge fun h2 : a ≥ 0 => (Right.mul_nonneg h2 h1).not_lt h
#align right.neg_of_mul_neg_right Right.neg_of_mul_neg_right
end LinearOrder
end MulZeroClass
section MulOneClass
variable [MulOneClass α] [Zero α]
section Preorder
variable [Preorder α]
/-! Lemmas of the form `a ≤ a * b ↔ 1 ≤ b` and `a * b ≤ a ↔ b ≤ 1`,
which assume left covariance. -/
@[simp]
lemma le_mul_iff_one_le_right [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a ≤ a * b ↔ 1 ≤ b :=
Iff.trans (by rw [mul_one]) (mul_le_mul_left a0)
#align le_mul_iff_one_le_right le_mul_iff_one_le_right
@[simp]
theorem lt_mul_iff_one_lt_right [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a < a * b ↔ 1 < b :=
Iff.trans (by rw [mul_one]) (mul_lt_mul_left a0)
#align lt_mul_iff_one_lt_right lt_mul_iff_one_lt_right
@[simp]
lemma mul_le_iff_le_one_right [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a ↔ b ≤ 1 :=
Iff.trans (by rw [mul_one]) (mul_le_mul_left a0)
#align mul_le_iff_le_one_right mul_le_iff_le_one_right
@[simp]
theorem mul_lt_iff_lt_one_right [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a ↔ b < 1 :=
Iff.trans (by rw [mul_one]) (mul_lt_mul_left a0)
#align mul_lt_iff_lt_one_right mul_lt_iff_lt_one_right
/-! Lemmas of the form `a ≤ b * a ↔ 1 ≤ b` and `a * b ≤ b ↔ a ≤ 1`,
which assume right covariance. -/
@[simp]
lemma le_mul_iff_one_le_left [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : a ≤ b * a ↔ 1 ≤ b :=
Iff.trans (by rw [one_mul]) (mul_le_mul_right a0)
#align le_mul_iff_one_le_left le_mul_iff_one_le_left
@[simp]
theorem lt_mul_iff_one_lt_left [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
a < b * a ↔ 1 < b :=
Iff.trans (by rw [one_mul]) (mul_lt_mul_right a0)
#align lt_mul_iff_one_lt_left lt_mul_iff_one_lt_left
@[simp]
lemma mul_le_iff_le_one_left [MulPosMono α] [MulPosReflectLE α] (b0 : 0 < b) : a * b ≤ b ↔ a ≤ 1 :=
Iff.trans (by rw [one_mul]) (mul_le_mul_right b0)
#align mul_le_iff_le_one_left mul_le_iff_le_one_left
@[simp]
theorem mul_lt_iff_lt_one_left [MulPosStrictMono α] [MulPosReflectLT α] (b0 : 0 < b) :
a * b < b ↔ a < 1 :=
Iff.trans (by rw [one_mul]) (mul_lt_mul_right b0)
#align mul_lt_iff_lt_one_left mul_lt_iff_lt_one_left
/-! Lemmas of the form `1 ≤ b → a ≤ a * b`.
Variants with `< 0` and `≤ 0` instead of `0 <` and `0 ≤` appear in `Mathlib/Algebra/Order/Ring/Defs`
(which imports this file) as they need additional results which are not yet available here. -/
theorem mul_le_of_le_one_left [MulPosMono α] (hb : 0 ≤ b) (h : a ≤ 1) : a * b ≤ b := by
simpa only [one_mul] using mul_le_mul_of_nonneg_right h hb
#align mul_le_of_le_one_left mul_le_of_le_one_left
theorem le_mul_of_one_le_left [MulPosMono α] (hb : 0 ≤ b) (h : 1 ≤ a) : b ≤ a * b := by
simpa only [one_mul] using mul_le_mul_of_nonneg_right h hb
#align le_mul_of_one_le_left le_mul_of_one_le_left
theorem mul_le_of_le_one_right [PosMulMono α] (ha : 0 ≤ a) (h : b ≤ 1) : a * b ≤ a := by
simpa only [mul_one] using mul_le_mul_of_nonneg_left h ha
#align mul_le_of_le_one_right mul_le_of_le_one_right
theorem le_mul_of_one_le_right [PosMulMono α] (ha : 0 ≤ a) (h : 1 ≤ b) : a ≤ a * b := by
simpa only [mul_one] using mul_le_mul_of_nonneg_left h ha
#align le_mul_of_one_le_right le_mul_of_one_le_right
| Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean | 740 | 741 | theorem mul_lt_of_lt_one_left [MulPosStrictMono α] (hb : 0 < b) (h : a < 1) : a * b < b := by |
simpa only [one_mul] using mul_lt_mul_of_pos_right h hb
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Chris Hughes, Floris van Doorn, Yaël Dillies
-/
import Mathlib.Data.Nat.Defs
import Mathlib.Tactic.GCongr.Core
import Mathlib.Tactic.Common
import Mathlib.Tactic.Monotonicity.Attr
#align_import data.nat.factorial.basic from "leanprover-community/mathlib"@"d012cd09a9b256d870751284dd6a29882b0be105"
/-!
# Factorial and variants
This file defines the factorial, along with the ascending and descending variants.
## Main declarations
* `Nat.factorial`: The factorial.
* `Nat.ascFactorial`: The ascending factorial. It is the product of natural numbers from `n` to
`n + k - 1`.
* `Nat.descFactorial`: The descending factorial. It is the product of natural numbers from
`n - k + 1` to `n`.
-/
namespace Nat
/-- `Nat.factorial n` is the factorial of `n`. -/
def factorial : ℕ → ℕ
| 0 => 1
| succ n => succ n * factorial n
#align nat.factorial Nat.factorial
/-- factorial notation `n!` -/
scoped notation:10000 n "!" => Nat.factorial n
section Factorial
variable {m n : ℕ}
@[simp] theorem factorial_zero : 0! = 1 :=
rfl
#align nat.factorial_zero Nat.factorial_zero
theorem factorial_succ (n : ℕ) : (n + 1)! = (n + 1) * n ! :=
rfl
#align nat.factorial_succ Nat.factorial_succ
@[simp] theorem factorial_one : 1! = 1 :=
rfl
#align nat.factorial_one Nat.factorial_one
@[simp] theorem factorial_two : 2! = 2 :=
rfl
#align nat.factorial_two Nat.factorial_two
theorem mul_factorial_pred (hn : 0 < n) : n * (n - 1)! = n ! :=
Nat.sub_add_cancel (Nat.succ_le_of_lt hn) ▸ rfl
#align nat.mul_factorial_pred Nat.mul_factorial_pred
theorem factorial_pos : ∀ n, 0 < n !
| 0 => Nat.zero_lt_one
| succ n => Nat.mul_pos (succ_pos _) (factorial_pos n)
#align nat.factorial_pos Nat.factorial_pos
theorem factorial_ne_zero (n : ℕ) : n ! ≠ 0 :=
ne_of_gt (factorial_pos _)
#align nat.factorial_ne_zero Nat.factorial_ne_zero
theorem factorial_dvd_factorial {m n} (h : m ≤ n) : m ! ∣ n ! := by
induction' h with n _ ih
· exact Nat.dvd_refl _
· exact Nat.dvd_trans ih (Nat.dvd_mul_left _ _)
#align nat.factorial_dvd_factorial Nat.factorial_dvd_factorial
theorem dvd_factorial : ∀ {m n}, 0 < m → m ≤ n → m ∣ n !
| succ _, _, _, h => Nat.dvd_trans (Nat.dvd_mul_right _ _) (factorial_dvd_factorial h)
#align nat.dvd_factorial Nat.dvd_factorial
@[mono, gcongr]
theorem factorial_le {m n} (h : m ≤ n) : m ! ≤ n ! :=
le_of_dvd (factorial_pos _) (factorial_dvd_factorial h)
#align nat.factorial_le Nat.factorial_le
theorem factorial_mul_pow_le_factorial : ∀ {m n : ℕ}, m ! * (m + 1) ^ n ≤ (m + n)!
| m, 0 => by simp
| m, n + 1 => by
rw [← Nat.add_assoc, factorial_succ, Nat.mul_comm (_ + 1), Nat.pow_succ, ← Nat.mul_assoc]
exact Nat.mul_le_mul factorial_mul_pow_le_factorial (succ_le_succ (le_add_right _ _))
#align nat.factorial_mul_pow_le_factorial Nat.factorial_mul_pow_le_factorial
theorem factorial_lt (hn : 0 < n) : n ! < m ! ↔ n < m := by
refine ⟨fun h => not_le.mp fun hmn => Nat.not_le_of_lt h (factorial_le hmn), fun h => ?_⟩
have : ∀ {n}, 0 < n → n ! < (n + 1)! := by
intro k hk
rw [factorial_succ, succ_mul, Nat.lt_add_left_iff_pos]
exact Nat.mul_pos hk k.factorial_pos
induction' h with k hnk ih generalizing hn
· exact this hn
· exact lt_trans (ih hn) $ this <| lt_trans hn <| lt_of_succ_le hnk
#align nat.factorial_lt Nat.factorial_lt
@[gcongr]
lemma factorial_lt_of_lt {m n : ℕ} (hn : 0 < n) (h : n < m) : n ! < m ! := (factorial_lt hn).mpr h
@[simp] lemma one_lt_factorial : 1 < n ! ↔ 1 < n := factorial_lt Nat.one_pos
#align nat.one_lt_factorial Nat.one_lt_factorial
@[simp]
theorem factorial_eq_one : n ! = 1 ↔ n ≤ 1 := by
constructor
· intro h
rw [← not_lt, ← one_lt_factorial, h]
apply lt_irrefl
· rintro (_|_|_) <;> rfl
#align nat.factorial_eq_one Nat.factorial_eq_one
| Mathlib/Data/Nat/Factorial/Basic.lean | 121 | 129 | theorem factorial_inj (hn : 1 < n) : n ! = m ! ↔ n = m := by |
refine ⟨fun h => ?_, congr_arg _⟩
obtain hnm | rfl | hnm := lt_trichotomy n m
· rw [← factorial_lt <| lt_of_succ_lt hn, h] at hnm
cases lt_irrefl _ hnm
· rfl
rw [← one_lt_factorial, h, one_lt_factorial] at hn
rw [← factorial_lt <| lt_of_succ_lt hn, h] at hnm
cases lt_irrefl _ hnm
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Julian Kuelshammer
-/
import Mathlib.Algebra.CharP.Defs
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Data.Int.ModEq
import Mathlib.Data.Set.Pointwise.Basic
import Mathlib.Dynamics.PeriodicPts
import Mathlib.GroupTheory.Index
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Order.Interval.Set.Infinite
#align_import group_theory.order_of_element from "leanprover-community/mathlib"@"d07245fd37786daa997af4f1a73a49fa3b748408"
/-!
# Order of an element
This file defines the order of an element of a finite group. For a finite group `G` the order of
`x ∈ G` is the minimal `n ≥ 1` such that `x ^ n = 1`.
## Main definitions
* `IsOfFinOrder` is a predicate on an element `x` of a monoid `G` saying that `x` is of finite
order.
* `IsOfFinAddOrder` is the additive analogue of `IsOfFinOrder`.
* `orderOf x` defines the order of an element `x` of a monoid `G`, by convention its value is `0`
if `x` has infinite order.
* `addOrderOf` is the additive analogue of `orderOf`.
## Tags
order of an element
-/
open Function Fintype Nat Pointwise Subgroup Submonoid
variable {G H A α β : Type*}
section Monoid
variable [Monoid G] {a b x y : G} {n m : ℕ}
section IsOfFinOrder
-- Porting note(#12129): additional beta reduction needed
@[to_additive]
theorem isPeriodicPt_mul_iff_pow_eq_one (x : G) : IsPeriodicPt (x * ·) n 1 ↔ x ^ n = 1 := by
rw [IsPeriodicPt, IsFixedPt, mul_left_iterate]; beta_reduce; rw [mul_one]
#align is_periodic_pt_mul_iff_pow_eq_one isPeriodicPt_mul_iff_pow_eq_one
#align is_periodic_pt_add_iff_nsmul_eq_zero isPeriodicPt_add_iff_nsmul_eq_zero
/-- `IsOfFinOrder` is a predicate on an element `x` of a monoid to be of finite order, i.e. there
exists `n ≥ 1` such that `x ^ n = 1`. -/
@[to_additive "`IsOfFinAddOrder` is a predicate on an element `a` of an
additive monoid to be of finite order, i.e. there exists `n ≥ 1` such that `n • a = 0`."]
def IsOfFinOrder (x : G) : Prop :=
(1 : G) ∈ periodicPts (x * ·)
#align is_of_fin_order IsOfFinOrder
#align is_of_fin_add_order IsOfFinAddOrder
theorem isOfFinAddOrder_ofMul_iff : IsOfFinAddOrder (Additive.ofMul x) ↔ IsOfFinOrder x :=
Iff.rfl
#align is_of_fin_add_order_of_mul_iff isOfFinAddOrder_ofMul_iff
theorem isOfFinOrder_ofAdd_iff {α : Type*} [AddMonoid α] {x : α} :
IsOfFinOrder (Multiplicative.ofAdd x) ↔ IsOfFinAddOrder x := Iff.rfl
#align is_of_fin_order_of_add_iff isOfFinOrder_ofAdd_iff
@[to_additive]
theorem isOfFinOrder_iff_pow_eq_one : IsOfFinOrder x ↔ ∃ n, 0 < n ∧ x ^ n = 1 := by
simp [IsOfFinOrder, mem_periodicPts, isPeriodicPt_mul_iff_pow_eq_one]
#align is_of_fin_order_iff_pow_eq_one isOfFinOrder_iff_pow_eq_one
#align is_of_fin_add_order_iff_nsmul_eq_zero isOfFinAddOrder_iff_nsmul_eq_zero
@[to_additive] alias ⟨IsOfFinOrder.exists_pow_eq_one, _⟩ := isOfFinOrder_iff_pow_eq_one
@[to_additive]
lemma isOfFinOrder_iff_zpow_eq_one {G} [Group G] {x : G} :
IsOfFinOrder x ↔ ∃ (n : ℤ), n ≠ 0 ∧ x ^ n = 1 := by
rw [isOfFinOrder_iff_pow_eq_one]
refine ⟨fun ⟨n, hn, hn'⟩ ↦ ⟨n, Int.natCast_ne_zero_iff_pos.mpr hn, zpow_natCast x n ▸ hn'⟩,
fun ⟨n, hn, hn'⟩ ↦ ⟨n.natAbs, Int.natAbs_pos.mpr hn, ?_⟩⟩
cases' (Int.natAbs_eq_iff (a := n)).mp rfl with h h
· rwa [h, zpow_natCast] at hn'
· rwa [h, zpow_neg, inv_eq_one, zpow_natCast] at hn'
/-- See also `injective_pow_iff_not_isOfFinOrder`. -/
@[to_additive "See also `injective_nsmul_iff_not_isOfFinAddOrder`."]
theorem not_isOfFinOrder_of_injective_pow {x : G} (h : Injective fun n : ℕ => x ^ n) :
¬IsOfFinOrder x := by
simp_rw [isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
intro n hn_pos hnx
rw [← pow_zero x] at hnx
rw [h hnx] at hn_pos
exact irrefl 0 hn_pos
#align not_is_of_fin_order_of_injective_pow not_isOfFinOrder_of_injective_pow
#align not_is_of_fin_add_order_of_injective_nsmul not_isOfFinAddOrder_of_injective_nsmul
lemma IsOfFinOrder.pow {n : ℕ} : IsOfFinOrder a → IsOfFinOrder (a ^ n) := by
simp_rw [isOfFinOrder_iff_pow_eq_one]
rintro ⟨m, hm, ha⟩
exact ⟨m, hm, by simp [pow_right_comm _ n, ha]⟩
/-- Elements of finite order are of finite order in submonoids. -/
@[to_additive "Elements of finite order are of finite order in submonoids."]
theorem Submonoid.isOfFinOrder_coe {H : Submonoid G} {x : H} :
IsOfFinOrder (x : G) ↔ IsOfFinOrder x := by
rw [isOfFinOrder_iff_pow_eq_one, isOfFinOrder_iff_pow_eq_one]
norm_cast
#align is_of_fin_order_iff_coe Submonoid.isOfFinOrder_coe
#align is_of_fin_add_order_iff_coe AddSubmonoid.isOfFinAddOrder_coe
/-- The image of an element of finite order has finite order. -/
@[to_additive "The image of an element of finite additive order has finite additive order."]
theorem MonoidHom.isOfFinOrder [Monoid H] (f : G →* H) {x : G} (h : IsOfFinOrder x) :
IsOfFinOrder <| f x :=
isOfFinOrder_iff_pow_eq_one.mpr <| by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact ⟨n, npos, by rw [← f.map_pow, hn, f.map_one]⟩
#align monoid_hom.is_of_fin_order MonoidHom.isOfFinOrder
#align add_monoid_hom.is_of_fin_order AddMonoidHom.isOfFinAddOrder
/-- If a direct product has finite order then so does each component. -/
@[to_additive "If a direct product has finite additive order then so does each component."]
theorem IsOfFinOrder.apply {η : Type*} {Gs : η → Type*} [∀ i, Monoid (Gs i)] {x : ∀ i, Gs i}
(h : IsOfFinOrder x) : ∀ i, IsOfFinOrder (x i) := by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact fun _ => isOfFinOrder_iff_pow_eq_one.mpr ⟨n, npos, (congr_fun hn.symm _).symm⟩
#align is_of_fin_order.apply IsOfFinOrder.apply
#align is_of_fin_add_order.apply IsOfFinAddOrder.apply
/-- 1 is of finite order in any monoid. -/
@[to_additive "0 is of finite order in any additive monoid."]
theorem isOfFinOrder_one : IsOfFinOrder (1 : G) :=
isOfFinOrder_iff_pow_eq_one.mpr ⟨1, Nat.one_pos, one_pow 1⟩
#align is_of_fin_order_one isOfFinOrder_one
#align is_of_fin_order_zero isOfFinAddOrder_zero
/-- The submonoid generated by an element is a group if that element has finite order. -/
@[to_additive "The additive submonoid generated by an element is
an additive group if that element has finite order."]
noncomputable abbrev IsOfFinOrder.groupPowers (hx : IsOfFinOrder x) :
Group (Submonoid.powers x) := by
obtain ⟨hpos, hx⟩ := hx.exists_pow_eq_one.choose_spec
exact Submonoid.groupPowers hpos hx
end IsOfFinOrder
/-- `orderOf x` is the order of the element `x`, i.e. the `n ≥ 1`, s.t. `x ^ n = 1` if it exists.
Otherwise, i.e. if `x` is of infinite order, then `orderOf x` is `0` by convention. -/
@[to_additive
"`addOrderOf a` is the order of the element `a`, i.e. the `n ≥ 1`, s.t. `n • a = 0` if it
exists. Otherwise, i.e. if `a` is of infinite order, then `addOrderOf a` is `0` by convention."]
noncomputable def orderOf (x : G) : ℕ :=
minimalPeriod (x * ·) 1
#align order_of orderOf
#align add_order_of addOrderOf
@[simp]
theorem addOrderOf_ofMul_eq_orderOf (x : G) : addOrderOf (Additive.ofMul x) = orderOf x :=
rfl
#align add_order_of_of_mul_eq_order_of addOrderOf_ofMul_eq_orderOf
@[simp]
lemma orderOf_ofAdd_eq_addOrderOf {α : Type*} [AddMonoid α] (a : α) :
orderOf (Multiplicative.ofAdd a) = addOrderOf a := rfl
#align order_of_of_add_eq_add_order_of orderOf_ofAdd_eq_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.orderOf_pos (h : IsOfFinOrder x) : 0 < orderOf x :=
minimalPeriod_pos_of_mem_periodicPts h
#align order_of_pos' IsOfFinOrder.orderOf_pos
#align add_order_of_pos' IsOfFinAddOrder.addOrderOf_pos
@[to_additive addOrderOf_nsmul_eq_zero]
theorem pow_orderOf_eq_one (x : G) : x ^ orderOf x = 1 := by
convert Eq.trans _ (isPeriodicPt_minimalPeriod (x * ·) 1)
-- Porting note(#12129): additional beta reduction needed in the middle of the rewrite
rw [orderOf, mul_left_iterate]; beta_reduce; rw [mul_one]
#align pow_order_of_eq_one pow_orderOf_eq_one
#align add_order_of_nsmul_eq_zero addOrderOf_nsmul_eq_zero
@[to_additive]
theorem orderOf_eq_zero (h : ¬IsOfFinOrder x) : orderOf x = 0 := by
rwa [orderOf, minimalPeriod, dif_neg]
#align order_of_eq_zero orderOf_eq_zero
#align add_order_of_eq_zero addOrderOf_eq_zero
@[to_additive]
theorem orderOf_eq_zero_iff : orderOf x = 0 ↔ ¬IsOfFinOrder x :=
⟨fun h H ↦ H.orderOf_pos.ne' h, orderOf_eq_zero⟩
#align order_of_eq_zero_iff orderOf_eq_zero_iff
#align add_order_of_eq_zero_iff addOrderOf_eq_zero_iff
@[to_additive]
theorem orderOf_eq_zero_iff' : orderOf x = 0 ↔ ∀ n : ℕ, 0 < n → x ^ n ≠ 1 := by
simp_rw [orderOf_eq_zero_iff, isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
#align order_of_eq_zero_iff' orderOf_eq_zero_iff'
#align add_order_of_eq_zero_iff' addOrderOf_eq_zero_iff'
@[to_additive]
theorem orderOf_eq_iff {n} (h : 0 < n) :
orderOf x = n ↔ x ^ n = 1 ∧ ∀ m, m < n → 0 < m → x ^ m ≠ 1 := by
simp_rw [Ne, ← isPeriodicPt_mul_iff_pow_eq_one, orderOf, minimalPeriod]
split_ifs with h1
· classical
rw [find_eq_iff]
simp only [h, true_and]
push_neg
rfl
· rw [iff_false_left h.ne]
rintro ⟨h', -⟩
exact h1 ⟨n, h, h'⟩
#align order_of_eq_iff orderOf_eq_iff
#align add_order_of_eq_iff addOrderOf_eq_iff
/-- A group element has finite order iff its order is positive. -/
@[to_additive
"A group element has finite additive order iff its order is positive."]
theorem orderOf_pos_iff : 0 < orderOf x ↔ IsOfFinOrder x := by
rw [iff_not_comm.mp orderOf_eq_zero_iff, pos_iff_ne_zero]
#align order_of_pos_iff orderOf_pos_iff
#align add_order_of_pos_iff addOrderOf_pos_iff
@[to_additive]
theorem IsOfFinOrder.mono [Monoid β] {y : β} (hx : IsOfFinOrder x) (h : orderOf y ∣ orderOf x) :
IsOfFinOrder y := by rw [← orderOf_pos_iff] at hx ⊢; exact Nat.pos_of_dvd_of_pos h hx
#align is_of_fin_order.mono IsOfFinOrder.mono
#align is_of_fin_add_order.mono IsOfFinAddOrder.mono
@[to_additive]
theorem pow_ne_one_of_lt_orderOf' (n0 : n ≠ 0) (h : n < orderOf x) : x ^ n ≠ 1 := fun j =>
not_isPeriodicPt_of_pos_of_lt_minimalPeriod n0 h ((isPeriodicPt_mul_iff_pow_eq_one x).mpr j)
#align pow_ne_one_of_lt_order_of' pow_ne_one_of_lt_orderOf'
#align nsmul_ne_zero_of_lt_add_order_of' nsmul_ne_zero_of_lt_addOrderOf'
@[to_additive]
theorem orderOf_le_of_pow_eq_one (hn : 0 < n) (h : x ^ n = 1) : orderOf x ≤ n :=
IsPeriodicPt.minimalPeriod_le hn (by rwa [isPeriodicPt_mul_iff_pow_eq_one])
#align order_of_le_of_pow_eq_one orderOf_le_of_pow_eq_one
#align add_order_of_le_of_nsmul_eq_zero addOrderOf_le_of_nsmul_eq_zero
@[to_additive (attr := simp)]
theorem orderOf_one : orderOf (1 : G) = 1 := by
rw [orderOf, ← minimalPeriod_id (x := (1:G)), ← one_mul_eq_id]
#align order_of_one orderOf_one
#align order_of_zero addOrderOf_zero
@[to_additive (attr := simp) AddMonoid.addOrderOf_eq_one_iff]
theorem orderOf_eq_one_iff : orderOf x = 1 ↔ x = 1 := by
rw [orderOf, minimalPeriod_eq_one_iff_isFixedPt, IsFixedPt, mul_one]
#align order_of_eq_one_iff orderOf_eq_one_iff
#align add_monoid.order_of_eq_one_iff AddMonoid.addOrderOf_eq_one_iff
@[to_additive (attr := simp) mod_addOrderOf_nsmul]
lemma pow_mod_orderOf (x : G) (n : ℕ) : x ^ (n % orderOf x) = x ^ n :=
calc
x ^ (n % orderOf x) = x ^ (n % orderOf x + orderOf x * (n / orderOf x)) := by
simp [pow_add, pow_mul, pow_orderOf_eq_one]
_ = x ^ n := by rw [Nat.mod_add_div]
#align pow_eq_mod_order_of pow_mod_orderOf
#align nsmul_eq_mod_add_order_of mod_addOrderOf_nsmul
@[to_additive]
theorem orderOf_dvd_of_pow_eq_one (h : x ^ n = 1) : orderOf x ∣ n :=
IsPeriodicPt.minimalPeriod_dvd ((isPeriodicPt_mul_iff_pow_eq_one _).mpr h)
#align order_of_dvd_of_pow_eq_one orderOf_dvd_of_pow_eq_one
#align add_order_of_dvd_of_nsmul_eq_zero addOrderOf_dvd_of_nsmul_eq_zero
@[to_additive]
theorem orderOf_dvd_iff_pow_eq_one {n : ℕ} : orderOf x ∣ n ↔ x ^ n = 1 :=
⟨fun h => by rw [← pow_mod_orderOf, Nat.mod_eq_zero_of_dvd h, _root_.pow_zero],
orderOf_dvd_of_pow_eq_one⟩
#align order_of_dvd_iff_pow_eq_one orderOf_dvd_iff_pow_eq_one
#align add_order_of_dvd_iff_nsmul_eq_zero addOrderOf_dvd_iff_nsmul_eq_zero
@[to_additive addOrderOf_smul_dvd]
theorem orderOf_pow_dvd (n : ℕ) : orderOf (x ^ n) ∣ orderOf x := by
rw [orderOf_dvd_iff_pow_eq_one, pow_right_comm, pow_orderOf_eq_one, one_pow]
#align order_of_pow_dvd orderOf_pow_dvd
#align add_order_of_smul_dvd addOrderOf_smul_dvd
@[to_additive]
lemma pow_injOn_Iio_orderOf : (Set.Iio <| orderOf x).InjOn (x ^ ·) := by
simpa only [mul_left_iterate, mul_one]
using iterate_injOn_Iio_minimalPeriod (f := (x * ·)) (x := 1)
#align pow_injective_of_lt_order_of pow_injOn_Iio_orderOf
#align nsmul_injective_of_lt_add_order_of nsmul_injOn_Iio_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.mem_powers_iff_mem_range_orderOf [DecidableEq G]
(hx : IsOfFinOrder x) :
y ∈ Submonoid.powers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
Finset.mem_range_iff_mem_finset_range_of_mod_eq' hx.orderOf_pos <| pow_mod_orderOf _
#align mem_powers_iff_mem_range_order_of' IsOfFinOrder.mem_powers_iff_mem_range_orderOf
#align mem_multiples_iff_mem_range_add_order_of' IsOfFinAddOrder.mem_multiples_iff_mem_range_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.powers_eq_image_range_orderOf [DecidableEq G] (hx : IsOfFinOrder x) :
(Submonoid.powers x : Set G) = (Finset.range (orderOf x)).image (x ^ ·) :=
Set.ext fun _ ↦ hx.mem_powers_iff_mem_range_orderOf
@[deprecated (since := "2024-02-21")]
alias IsOfFinAddOrder.powers_eq_image_range_orderOf :=
IsOfFinAddOrder.multiples_eq_image_range_addOrderOf
@[to_additive]
theorem pow_eq_one_iff_modEq : x ^ n = 1 ↔ n ≡ 0 [MOD orderOf x] := by
rw [modEq_zero_iff_dvd, orderOf_dvd_iff_pow_eq_one]
#align pow_eq_one_iff_modeq pow_eq_one_iff_modEq
#align nsmul_eq_zero_iff_modeq nsmul_eq_zero_iff_modEq
@[to_additive]
theorem orderOf_map_dvd {H : Type*} [Monoid H] (ψ : G →* H) (x : G) :
orderOf (ψ x) ∣ orderOf x := by
apply orderOf_dvd_of_pow_eq_one
rw [← map_pow, pow_orderOf_eq_one]
apply map_one
#align order_of_map_dvd orderOf_map_dvd
#align add_order_of_map_dvd addOrderOf_map_dvd
@[to_additive]
theorem exists_pow_eq_self_of_coprime (h : n.Coprime (orderOf x)) : ∃ m : ℕ, (x ^ n) ^ m = x := by
by_cases h0 : orderOf x = 0
· rw [h0, coprime_zero_right] at h
exact ⟨1, by rw [h, pow_one, pow_one]⟩
by_cases h1 : orderOf x = 1
· exact ⟨0, by rw [orderOf_eq_one_iff.mp h1, one_pow, one_pow]⟩
obtain ⟨m, h⟩ := exists_mul_emod_eq_one_of_coprime h (one_lt_iff_ne_zero_and_ne_one.mpr ⟨h0, h1⟩)
exact ⟨m, by rw [← pow_mul, ← pow_mod_orderOf, h, pow_one]⟩
#align exists_pow_eq_self_of_coprime exists_pow_eq_self_of_coprime
#align exists_nsmul_eq_self_of_coprime exists_nsmul_eq_self_of_coprime
/-- If `x^n = 1`, but `x^(n/p) ≠ 1` for all prime factors `p` of `n`,
then `x` has order `n` in `G`. -/
@[to_additive addOrderOf_eq_of_nsmul_and_div_prime_nsmul "If `n * x = 0`, but `n/p * x ≠ 0` for
all prime factors `p` of `n`, then `x` has order `n` in `G`."]
theorem orderOf_eq_of_pow_and_pow_div_prime (hn : 0 < n) (hx : x ^ n = 1)
(hd : ∀ p : ℕ, p.Prime → p ∣ n → x ^ (n / p) ≠ 1) : orderOf x = n := by
-- Let `a` be `n/(orderOf x)`, and show `a = 1`
cases' exists_eq_mul_right_of_dvd (orderOf_dvd_of_pow_eq_one hx) with a ha
suffices a = 1 by simp [this, ha]
-- Assume `a` is not one...
by_contra h
have a_min_fac_dvd_p_sub_one : a.minFac ∣ n := by
obtain ⟨b, hb⟩ : ∃ b : ℕ, a = b * a.minFac := exists_eq_mul_left_of_dvd a.minFac_dvd
rw [hb, ← mul_assoc] at ha
exact Dvd.intro_left (orderOf x * b) ha.symm
-- Use the minimum prime factor of `a` as `p`.
refine hd a.minFac (Nat.minFac_prime h) a_min_fac_dvd_p_sub_one ?_
rw [← orderOf_dvd_iff_pow_eq_one, Nat.dvd_div_iff a_min_fac_dvd_p_sub_one, ha, mul_comm,
Nat.mul_dvd_mul_iff_left (IsOfFinOrder.orderOf_pos _)]
· exact Nat.minFac_dvd a
· rw [isOfFinOrder_iff_pow_eq_one]
exact Exists.intro n (id ⟨hn, hx⟩)
#align order_of_eq_of_pow_and_pow_div_prime orderOf_eq_of_pow_and_pow_div_prime
#align add_order_of_eq_of_nsmul_and_div_prime_nsmul addOrderOf_eq_of_nsmul_and_div_prime_nsmul
@[to_additive]
theorem orderOf_eq_orderOf_iff {H : Type*} [Monoid H] {y : H} :
orderOf x = orderOf y ↔ ∀ n : ℕ, x ^ n = 1 ↔ y ^ n = 1 := by
simp_rw [← isPeriodicPt_mul_iff_pow_eq_one, ← minimalPeriod_eq_minimalPeriod_iff, orderOf]
#align order_of_eq_order_of_iff orderOf_eq_orderOf_iff
#align add_order_of_eq_add_order_of_iff addOrderOf_eq_addOrderOf_iff
/-- An injective homomorphism of monoids preserves orders of elements. -/
@[to_additive "An injective homomorphism of additive monoids preserves orders of elements."]
theorem orderOf_injective {H : Type*} [Monoid H] (f : G →* H) (hf : Function.Injective f) (x : G) :
orderOf (f x) = orderOf x := by
simp_rw [orderOf_eq_orderOf_iff, ← f.map_pow, ← f.map_one, hf.eq_iff, forall_const]
#align order_of_injective orderOf_injective
#align add_order_of_injective addOrderOf_injective
/-- A multiplicative equivalence preserves orders of elements. -/
@[to_additive (attr := simp) "An additive equivalence preserves orders of elements."]
lemma MulEquiv.orderOf_eq {H : Type*} [Monoid H] (e : G ≃* H) (x : G) :
orderOf (e x) = orderOf x :=
orderOf_injective e e.injective x
@[to_additive]
theorem Function.Injective.isOfFinOrder_iff [Monoid H] {f : G →* H} (hf : Injective f) :
IsOfFinOrder (f x) ↔ IsOfFinOrder x := by
rw [← orderOf_pos_iff, orderOf_injective f hf x, ← orderOf_pos_iff]
@[to_additive (attr := norm_cast, simp)]
theorem orderOf_submonoid {H : Submonoid G} (y : H) : orderOf (y : G) = orderOf y :=
orderOf_injective H.subtype Subtype.coe_injective y
#align order_of_submonoid orderOf_submonoid
#align order_of_add_submonoid addOrderOf_addSubmonoid
@[to_additive]
theorem orderOf_units {y : Gˣ} : orderOf (y : G) = orderOf y :=
orderOf_injective (Units.coeHom G) Units.ext y
#align order_of_units orderOf_units
#align order_of_add_units addOrderOf_addUnits
/-- If the order of `x` is finite, then `x` is a unit with inverse `x ^ (orderOf x - 1)`. -/
@[simps]
noncomputable
def IsOfFinOrder.unit {M} [Monoid M] {x : M} (hx : IsOfFinOrder x) : Mˣ :=
⟨x, x ^ (orderOf x - 1),
by rw [← _root_.pow_succ', tsub_add_cancel_of_le (by exact hx.orderOf_pos), pow_orderOf_eq_one],
by rw [← _root_.pow_succ, tsub_add_cancel_of_le (by exact hx.orderOf_pos), pow_orderOf_eq_one]⟩
lemma IsOfFinOrder.isUnit {M} [Monoid M] {x : M} (hx : IsOfFinOrder x) : IsUnit x := ⟨hx.unit, rfl⟩
variable (x)
@[to_additive]
theorem orderOf_pow' (h : n ≠ 0) : orderOf (x ^ n) = orderOf x / gcd (orderOf x) n := by
unfold orderOf
rw [← minimalPeriod_iterate_eq_div_gcd h, mul_left_iterate]
#align order_of_pow' orderOf_pow'
#align add_order_of_nsmul' addOrderOf_nsmul'
@[to_additive]
lemma orderOf_pow_of_dvd {x : G} {n : ℕ} (hn : n ≠ 0) (dvd : n ∣ orderOf x) :
orderOf (x ^ n) = orderOf x / n := by rw [orderOf_pow' _ hn, Nat.gcd_eq_right dvd]
@[to_additive]
lemma orderOf_pow_orderOf_div {x : G} {n : ℕ} (hx : orderOf x ≠ 0) (hn : n ∣ orderOf x) :
orderOf (x ^ (orderOf x / n)) = n := by
rw [orderOf_pow_of_dvd _ (Nat.div_dvd_of_dvd hn), Nat.div_div_self hn hx]
rw [← Nat.div_mul_cancel hn] at hx; exact left_ne_zero_of_mul hx
variable (n)
@[to_additive]
protected lemma IsOfFinOrder.orderOf_pow (h : IsOfFinOrder x) :
orderOf (x ^ n) = orderOf x / gcd (orderOf x) n := by
unfold orderOf
rw [← minimalPeriod_iterate_eq_div_gcd' h, mul_left_iterate]
#align order_of_pow'' IsOfFinOrder.orderOf_pow
#align add_order_of_nsmul'' IsOfFinAddOrder.addOrderOf_nsmul
@[to_additive]
lemma Nat.Coprime.orderOf_pow (h : (orderOf y).Coprime m) : orderOf (y ^ m) = orderOf y := by
by_cases hg : IsOfFinOrder y
· rw [hg.orderOf_pow y m , h.gcd_eq_one, Nat.div_one]
· rw [m.coprime_zero_left.1 (orderOf_eq_zero hg ▸ h), pow_one]
#align order_of_pow_coprime Nat.Coprime.orderOf_pow
#align add_order_of_nsmul_coprime Nat.Coprime.addOrderOf_nsmul
@[to_additive]
lemma IsOfFinOrder.natCard_powers_le_orderOf (ha : IsOfFinOrder a) :
Nat.card (powers a : Set G) ≤ orderOf a := by
classical
simpa [ha.powers_eq_image_range_orderOf, Finset.card_range, Nat.Iio_eq_range]
using Finset.card_image_le (s := Finset.range (orderOf a))
@[to_additive]
lemma IsOfFinOrder.finite_powers (ha : IsOfFinOrder a) : (powers a : Set G).Finite := by
classical rw [ha.powers_eq_image_range_orderOf]; exact Finset.finite_toSet _
namespace Commute
variable {x} (h : Commute x y)
@[to_additive]
theorem orderOf_mul_dvd_lcm : orderOf (x * y) ∣ Nat.lcm (orderOf x) (orderOf y) := by
rw [orderOf, ← comp_mul_left]
exact Function.Commute.minimalPeriod_of_comp_dvd_lcm h.function_commute_mul_left
#align commute.order_of_mul_dvd_lcm Commute.orderOf_mul_dvd_lcm
#align add_commute.order_of_add_dvd_lcm AddCommute.addOrderOf_add_dvd_lcm
@[to_additive]
theorem orderOf_dvd_lcm_mul : orderOf y ∣ Nat.lcm (orderOf x) (orderOf (x * y)) := by
by_cases h0 : orderOf x = 0
· rw [h0, lcm_zero_left]
apply dvd_zero
conv_lhs =>
rw [← one_mul y, ← pow_orderOf_eq_one x, ← succ_pred_eq_of_pos (Nat.pos_of_ne_zero h0),
_root_.pow_succ, mul_assoc]
exact
(((Commute.refl x).mul_right h).pow_left _).orderOf_mul_dvd_lcm.trans
(lcm_dvd_iff.2 ⟨(orderOf_pow_dvd _).trans (dvd_lcm_left _ _), dvd_lcm_right _ _⟩)
#align commute.order_of_dvd_lcm_mul Commute.orderOf_dvd_lcm_mul
#align add_commute.order_of_dvd_lcm_add AddCommute.addOrderOf_dvd_lcm_add
@[to_additive addOrderOf_add_dvd_mul_addOrderOf]
theorem orderOf_mul_dvd_mul_orderOf : orderOf (x * y) ∣ orderOf x * orderOf y :=
dvd_trans h.orderOf_mul_dvd_lcm (lcm_dvd_mul _ _)
#align commute.order_of_mul_dvd_mul_order_of Commute.orderOf_mul_dvd_mul_orderOf
#align add_commute.add_order_of_add_dvd_mul_add_order_of AddCommute.addOrderOf_add_dvd_mul_addOrderOf
@[to_additive addOrderOf_add_eq_mul_addOrderOf_of_coprime]
theorem orderOf_mul_eq_mul_orderOf_of_coprime (hco : (orderOf x).Coprime (orderOf y)) :
orderOf (x * y) = orderOf x * orderOf y := by
rw [orderOf, ← comp_mul_left]
exact h.function_commute_mul_left.minimalPeriod_of_comp_eq_mul_of_coprime hco
#align commute.order_of_mul_eq_mul_order_of_of_coprime Commute.orderOf_mul_eq_mul_orderOf_of_coprime
#align add_commute.add_order_of_add_eq_mul_add_order_of_of_coprime AddCommute.addOrderOf_add_eq_mul_addOrderOf_of_coprime
/-- Commuting elements of finite order are closed under multiplication. -/
@[to_additive "Commuting elements of finite additive order are closed under addition."]
theorem isOfFinOrder_mul (hx : IsOfFinOrder x) (hy : IsOfFinOrder y) : IsOfFinOrder (x * y) :=
orderOf_pos_iff.mp <|
pos_of_dvd_of_pos h.orderOf_mul_dvd_mul_orderOf <| mul_pos hx.orderOf_pos hy.orderOf_pos
#align commute.is_of_fin_order_mul Commute.isOfFinOrder_mul
#align add_commute.is_of_fin_order_add AddCommute.isOfFinAddOrder_add
/-- If each prime factor of `orderOf x` has higher multiplicity in `orderOf y`, and `x` commutes
with `y`, then `x * y` has the same order as `y`. -/
@[to_additive addOrderOf_add_eq_right_of_forall_prime_mul_dvd
"If each prime factor of
`addOrderOf x` has higher multiplicity in `addOrderOf y`, and `x` commutes with `y`,
then `x + y` has the same order as `y`."]
theorem orderOf_mul_eq_right_of_forall_prime_mul_dvd (hy : IsOfFinOrder y)
(hdvd : ∀ p : ℕ, p.Prime → p ∣ orderOf x → p * orderOf x ∣ orderOf y) :
orderOf (x * y) = orderOf y := by
have hoy := hy.orderOf_pos
have hxy := dvd_of_forall_prime_mul_dvd hdvd
apply orderOf_eq_of_pow_and_pow_div_prime hoy <;> simp only [Ne, ← orderOf_dvd_iff_pow_eq_one]
· exact h.orderOf_mul_dvd_lcm.trans (lcm_dvd hxy dvd_rfl)
refine fun p hp hpy hd => hp.ne_one ?_
rw [← Nat.dvd_one, ← mul_dvd_mul_iff_right hoy.ne', one_mul, ← dvd_div_iff hpy]
refine (orderOf_dvd_lcm_mul h).trans (lcm_dvd ((dvd_div_iff hpy).2 ?_) hd)
by_cases h : p ∣ orderOf x
exacts [hdvd p hp h, (hp.coprime_iff_not_dvd.2 h).mul_dvd_of_dvd_of_dvd hpy hxy]
#align commute.order_of_mul_eq_right_of_forall_prime_mul_dvd Commute.orderOf_mul_eq_right_of_forall_prime_mul_dvd
#align add_commute.add_order_of_add_eq_right_of_forall_prime_mul_dvd AddCommute.addOrderOf_add_eq_right_of_forall_prime_mul_dvd
end Commute
section PPrime
variable {x n} {p : ℕ} [hp : Fact p.Prime]
@[to_additive]
theorem orderOf_eq_prime (hg : x ^ p = 1) (hg1 : x ≠ 1) : orderOf x = p :=
minimalPeriod_eq_prime ((isPeriodicPt_mul_iff_pow_eq_one _).mpr hg)
(by rwa [IsFixedPt, mul_one])
#align order_of_eq_prime orderOf_eq_prime
#align add_order_of_eq_prime addOrderOf_eq_prime
@[to_additive addOrderOf_eq_prime_pow]
theorem orderOf_eq_prime_pow (hnot : ¬x ^ p ^ n = 1) (hfin : x ^ p ^ (n + 1) = 1) :
orderOf x = p ^ (n + 1) := by
apply minimalPeriod_eq_prime_pow <;> rwa [isPeriodicPt_mul_iff_pow_eq_one]
#align order_of_eq_prime_pow orderOf_eq_prime_pow
#align add_order_of_eq_prime_pow addOrderOf_eq_prime_pow
@[to_additive exists_addOrderOf_eq_prime_pow_iff]
theorem exists_orderOf_eq_prime_pow_iff :
(∃ k : ℕ, orderOf x = p ^ k) ↔ ∃ m : ℕ, x ^ (p : ℕ) ^ m = 1 :=
⟨fun ⟨k, hk⟩ => ⟨k, by rw [← hk, pow_orderOf_eq_one]⟩, fun ⟨_, hm⟩ => by
obtain ⟨k, _, hk⟩ := (Nat.dvd_prime_pow hp.elim).mp (orderOf_dvd_of_pow_eq_one hm)
exact ⟨k, hk⟩⟩
#align exists_order_of_eq_prime_pow_iff exists_orderOf_eq_prime_pow_iff
#align exists_add_order_of_eq_prime_pow_iff exists_addOrderOf_eq_prime_pow_iff
end PPrime
end Monoid
section CancelMonoid
variable [LeftCancelMonoid G] {x y : G} {a : G} {m n : ℕ}
@[to_additive]
theorem pow_eq_pow_iff_modEq : x ^ n = x ^ m ↔ n ≡ m [MOD orderOf x] := by
wlog hmn : m ≤ n generalizing m n
· rw [eq_comm, ModEq.comm, this (le_of_not_le hmn)]
obtain ⟨k, rfl⟩ := Nat.exists_eq_add_of_le hmn
rw [← mul_one (x ^ m), pow_add, mul_left_cancel_iff, pow_eq_one_iff_modEq]
exact ⟨fun h => Nat.ModEq.add_left _ h, fun h => Nat.ModEq.add_left_cancel' _ h⟩
#align pow_eq_pow_iff_modeq pow_eq_pow_iff_modEq
#align nsmul_eq_nsmul_iff_modeq nsmul_eq_nsmul_iff_modEq
@[to_additive (attr := simp)]
lemma injective_pow_iff_not_isOfFinOrder : Injective (fun n : ℕ ↦ x ^ n) ↔ ¬IsOfFinOrder x := by
refine ⟨fun h => not_isOfFinOrder_of_injective_pow h, fun h n m hnm => ?_⟩
rwa [pow_eq_pow_iff_modEq, orderOf_eq_zero_iff.mpr h, modEq_zero_iff] at hnm
#align injective_pow_iff_not_is_of_fin_order injective_pow_iff_not_isOfFinOrder
#align injective_nsmul_iff_not_is_of_fin_add_order injective_nsmul_iff_not_isOfFinAddOrder
@[to_additive]
lemma pow_inj_mod {n m : ℕ} : x ^ n = x ^ m ↔ n % orderOf x = m % orderOf x := pow_eq_pow_iff_modEq
#align pow_inj_mod pow_inj_mod
#align nsmul_inj_mod nsmul_inj_mod
@[to_additive]
theorem pow_inj_iff_of_orderOf_eq_zero (h : orderOf x = 0) {n m : ℕ} : x ^ n = x ^ m ↔ n = m := by
rw [pow_eq_pow_iff_modEq, h, modEq_zero_iff]
#align pow_inj_iff_of_order_of_eq_zero pow_inj_iff_of_orderOf_eq_zero
#align nsmul_inj_iff_of_add_order_of_eq_zero nsmul_inj_iff_of_addOrderOf_eq_zero
@[to_additive]
| Mathlib/GroupTheory/OrderOfElement.lean | 586 | 601 | theorem infinite_not_isOfFinOrder {x : G} (h : ¬IsOfFinOrder x) :
{ y : G | ¬IsOfFinOrder y }.Infinite := by |
let s := { n | 0 < n }.image fun n : ℕ => x ^ n
have hs : s ⊆ { y : G | ¬IsOfFinOrder y } := by
rintro - ⟨n, hn : 0 < n, rfl⟩ (contra : IsOfFinOrder (x ^ n))
apply h
rw [isOfFinOrder_iff_pow_eq_one] at contra ⊢
obtain ⟨m, hm, hm'⟩ := contra
exact ⟨n * m, mul_pos hn hm, by rwa [pow_mul]⟩
suffices s.Infinite by exact this.mono hs
contrapose! h
have : ¬Injective fun n : ℕ => x ^ n := by
have := Set.not_injOn_infinite_finite_image (Set.Ioi_infinite 0) (Set.not_infinite.mp h)
contrapose! this
exact Set.injOn_of_injective this
rwa [injective_pow_iff_not_isOfFinOrder, Classical.not_not] at this
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Bool.Set
import Mathlib.Data.Nat.Set
import Mathlib.Data.Set.Prod
import Mathlib.Data.ULift
import Mathlib.Order.Bounds.Basic
import Mathlib.Order.Hom.Set
import Mathlib.Order.SetNotation
#align_import order.complete_lattice from "leanprover-community/mathlib"@"5709b0d8725255e76f47debca6400c07b5c2d8e6"
/-!
# Theory of complete lattices
## Main definitions
* `sSup` and `sInf` are the supremum and the infimum of a set;
* `iSup (f : ι → α)` and `iInf (f : ι → α)` are indexed supremum and infimum of a function,
defined as `sSup` and `sInf` of the range of this function;
* class `CompleteLattice`: a bounded lattice such that `sSup s` is always the least upper boundary
of `s` and `sInf s` is always the greatest lower boundary of `s`;
* class `CompleteLinearOrder`: a linear ordered complete lattice.
## Naming conventions
In lemma names,
* `sSup` is called `sSup`
* `sInf` is called `sInf`
* `⨆ i, s i` is called `iSup`
* `⨅ i, s i` is called `iInf`
* `⨆ i j, s i j` is called `iSup₂`. This is an `iSup` inside an `iSup`.
* `⨅ i j, s i j` is called `iInf₂`. This is an `iInf` inside an `iInf`.
* `⨆ i ∈ s, t i` is called `biSup` for "bounded `iSup`". This is the special case of `iSup₂`
where `j : i ∈ s`.
* `⨅ i ∈ s, t i` is called `biInf` for "bounded `iInf`". This is the special case of `iInf₂`
where `j : i ∈ s`.
## Notation
* `⨆ i, f i` : `iSup f`, the supremum of the range of `f`;
* `⨅ i, f i` : `iInf f`, the infimum of the range of `f`.
-/
open Function OrderDual Set
variable {α β β₂ γ : Type*} {ι ι' : Sort*} {κ : ι → Sort*} {κ' : ι' → Sort*}
instance OrderDual.supSet (α) [InfSet α] : SupSet αᵒᵈ :=
⟨(sInf : Set α → α)⟩
instance OrderDual.infSet (α) [SupSet α] : InfSet αᵒᵈ :=
⟨(sSup : Set α → α)⟩
/-- Note that we rarely use `CompleteSemilatticeSup`
(in fact, any such object is always a `CompleteLattice`, so it's usually best to start there).
Nevertheless it is sometimes a useful intermediate step in constructions.
-/
class CompleteSemilatticeSup (α : Type*) extends PartialOrder α, SupSet α where
/-- Any element of a set is less than the set supremum. -/
le_sSup : ∀ s, ∀ a ∈ s, a ≤ sSup s
/-- Any upper bound is more than the set supremum. -/
sSup_le : ∀ s a, (∀ b ∈ s, b ≤ a) → sSup s ≤ a
#align complete_semilattice_Sup CompleteSemilatticeSup
section
variable [CompleteSemilatticeSup α] {s t : Set α} {a b : α}
theorem le_sSup : a ∈ s → a ≤ sSup s :=
CompleteSemilatticeSup.le_sSup s a
#align le_Sup le_sSup
theorem sSup_le : (∀ b ∈ s, b ≤ a) → sSup s ≤ a :=
CompleteSemilatticeSup.sSup_le s a
#align Sup_le sSup_le
theorem isLUB_sSup (s : Set α) : IsLUB s (sSup s) :=
⟨fun _ ↦ le_sSup, fun _ ↦ sSup_le⟩
#align is_lub_Sup isLUB_sSup
lemma isLUB_iff_sSup_eq : IsLUB s a ↔ sSup s = a :=
⟨(isLUB_sSup s).unique, by rintro rfl; exact isLUB_sSup _⟩
alias ⟨IsLUB.sSup_eq, _⟩ := isLUB_iff_sSup_eq
#align is_lub.Sup_eq IsLUB.sSup_eq
theorem le_sSup_of_le (hb : b ∈ s) (h : a ≤ b) : a ≤ sSup s :=
le_trans h (le_sSup hb)
#align le_Sup_of_le le_sSup_of_le
@[gcongr]
theorem sSup_le_sSup (h : s ⊆ t) : sSup s ≤ sSup t :=
(isLUB_sSup s).mono (isLUB_sSup t) h
#align Sup_le_Sup sSup_le_sSup
@[simp]
theorem sSup_le_iff : sSup s ≤ a ↔ ∀ b ∈ s, b ≤ a :=
isLUB_le_iff (isLUB_sSup s)
#align Sup_le_iff sSup_le_iff
theorem le_sSup_iff : a ≤ sSup s ↔ ∀ b ∈ upperBounds s, a ≤ b :=
⟨fun h _ hb => le_trans h (sSup_le hb), fun hb => hb _ fun _ => le_sSup⟩
#align le_Sup_iff le_sSup_iff
theorem le_iSup_iff {s : ι → α} : a ≤ iSup s ↔ ∀ b, (∀ i, s i ≤ b) → a ≤ b := by
simp [iSup, le_sSup_iff, upperBounds]
#align le_supr_iff le_iSup_iff
theorem sSup_le_sSup_of_forall_exists_le (h : ∀ x ∈ s, ∃ y ∈ t, x ≤ y) : sSup s ≤ sSup t :=
le_sSup_iff.2 fun _ hb =>
sSup_le fun a ha =>
let ⟨_, hct, hac⟩ := h a ha
hac.trans (hb hct)
#align Sup_le_Sup_of_forall_exists_le sSup_le_sSup_of_forall_exists_le
-- We will generalize this to conditionally complete lattices in `csSup_singleton`.
theorem sSup_singleton {a : α} : sSup {a} = a :=
isLUB_singleton.sSup_eq
#align Sup_singleton sSup_singleton
end
/-- Note that we rarely use `CompleteSemilatticeInf`
(in fact, any such object is always a `CompleteLattice`, so it's usually best to start there).
Nevertheless it is sometimes a useful intermediate step in constructions.
-/
class CompleteSemilatticeInf (α : Type*) extends PartialOrder α, InfSet α where
/-- Any element of a set is more than the set infimum. -/
sInf_le : ∀ s, ∀ a ∈ s, sInf s ≤ a
/-- Any lower bound is less than the set infimum. -/
le_sInf : ∀ s a, (∀ b ∈ s, a ≤ b) → a ≤ sInf s
#align complete_semilattice_Inf CompleteSemilatticeInf
section
variable [CompleteSemilatticeInf α] {s t : Set α} {a b : α}
theorem sInf_le : a ∈ s → sInf s ≤ a :=
CompleteSemilatticeInf.sInf_le s a
#align Inf_le sInf_le
theorem le_sInf : (∀ b ∈ s, a ≤ b) → a ≤ sInf s :=
CompleteSemilatticeInf.le_sInf s a
#align le_Inf le_sInf
theorem isGLB_sInf (s : Set α) : IsGLB s (sInf s) :=
⟨fun _ => sInf_le, fun _ => le_sInf⟩
#align is_glb_Inf isGLB_sInf
lemma isGLB_iff_sInf_eq : IsGLB s a ↔ sInf s = a :=
⟨(isGLB_sInf s).unique, by rintro rfl; exact isGLB_sInf _⟩
alias ⟨IsGLB.sInf_eq, _⟩ := isGLB_iff_sInf_eq
#align is_glb.Inf_eq IsGLB.sInf_eq
theorem sInf_le_of_le (hb : b ∈ s) (h : b ≤ a) : sInf s ≤ a :=
le_trans (sInf_le hb) h
#align Inf_le_of_le sInf_le_of_le
@[gcongr]
theorem sInf_le_sInf (h : s ⊆ t) : sInf t ≤ sInf s :=
(isGLB_sInf s).mono (isGLB_sInf t) h
#align Inf_le_Inf sInf_le_sInf
@[simp]
theorem le_sInf_iff : a ≤ sInf s ↔ ∀ b ∈ s, a ≤ b :=
le_isGLB_iff (isGLB_sInf s)
#align le_Inf_iff le_sInf_iff
theorem sInf_le_iff : sInf s ≤ a ↔ ∀ b ∈ lowerBounds s, b ≤ a :=
⟨fun h _ hb => le_trans (le_sInf hb) h, fun hb => hb _ fun _ => sInf_le⟩
#align Inf_le_iff sInf_le_iff
theorem iInf_le_iff {s : ι → α} : iInf s ≤ a ↔ ∀ b, (∀ i, b ≤ s i) → b ≤ a := by
simp [iInf, sInf_le_iff, lowerBounds]
#align infi_le_iff iInf_le_iff
theorem sInf_le_sInf_of_forall_exists_le (h : ∀ x ∈ s, ∃ y ∈ t, y ≤ x) : sInf t ≤ sInf s :=
le_sInf fun x hx ↦ let ⟨_y, hyt, hyx⟩ := h x hx; sInf_le_of_le hyt hyx
#align Inf_le_Inf_of_forall_exists_le sInf_le_sInf_of_forall_exists_le
-- We will generalize this to conditionally complete lattices in `csInf_singleton`.
theorem sInf_singleton {a : α} : sInf {a} = a :=
isGLB_singleton.sInf_eq
#align Inf_singleton sInf_singleton
end
/-- A complete lattice is a bounded lattice which has suprema and infima for every subset. -/
class CompleteLattice (α : Type*) extends Lattice α, CompleteSemilatticeSup α,
CompleteSemilatticeInf α, Top α, Bot α where
/-- Any element is less than the top one. -/
protected le_top : ∀ x : α, x ≤ ⊤
/-- Any element is more than the bottom one. -/
protected bot_le : ∀ x : α, ⊥ ≤ x
#align complete_lattice CompleteLattice
-- see Note [lower instance priority]
instance (priority := 100) CompleteLattice.toBoundedOrder [h : CompleteLattice α] :
BoundedOrder α :=
{ h with }
#align complete_lattice.to_bounded_order CompleteLattice.toBoundedOrder
/-- Create a `CompleteLattice` from a `PartialOrder` and `InfSet`
that returns the greatest lower bound of a set. Usually this constructor provides
poor definitional equalities. If other fields are known explicitly, they should be
provided; for example, if `inf` is known explicitly, construct the `CompleteLattice`
instance as
```
instance : CompleteLattice my_T where
inf := better_inf
le_inf := ...
inf_le_right := ...
inf_le_left := ...
-- don't care to fix sup, sSup, bot, top
__ := completeLatticeOfInf my_T _
```
-/
def completeLatticeOfInf (α : Type*) [H1 : PartialOrder α] [H2 : InfSet α]
(isGLB_sInf : ∀ s : Set α, IsGLB s (sInf s)) : CompleteLattice α where
__ := H1; __ := H2
bot := sInf univ
bot_le x := (isGLB_sInf univ).1 trivial
top := sInf ∅
le_top a := (isGLB_sInf ∅).2 <| by simp
sup a b := sInf { x : α | a ≤ x ∧ b ≤ x }
inf a b := sInf {a, b}
le_inf a b c hab hac := by
apply (isGLB_sInf _).2
simp [*]
inf_le_right a b := (isGLB_sInf _).1 <| mem_insert_of_mem _ <| mem_singleton _
inf_le_left a b := (isGLB_sInf _).1 <| mem_insert _ _
sup_le a b c hac hbc := (isGLB_sInf _).1 <| by simp [*]
le_sup_left a b := (isGLB_sInf _).2 fun x => And.left
le_sup_right a b := (isGLB_sInf _).2 fun x => And.right
le_sInf s a ha := (isGLB_sInf s).2 ha
sInf_le s a ha := (isGLB_sInf s).1 ha
sSup s := sInf (upperBounds s)
le_sSup s a ha := (isGLB_sInf (upperBounds s)).2 fun b hb => hb ha
sSup_le s a ha := (isGLB_sInf (upperBounds s)).1 ha
#align complete_lattice_of_Inf completeLatticeOfInf
/-- Any `CompleteSemilatticeInf` is in fact a `CompleteLattice`.
Note that this construction has bad definitional properties:
see the doc-string on `completeLatticeOfInf`.
-/
def completeLatticeOfCompleteSemilatticeInf (α : Type*) [CompleteSemilatticeInf α] :
CompleteLattice α :=
completeLatticeOfInf α fun s => isGLB_sInf s
#align complete_lattice_of_complete_semilattice_Inf completeLatticeOfCompleteSemilatticeInf
/-- Create a `CompleteLattice` from a `PartialOrder` and `SupSet`
that returns the least upper bound of a set. Usually this constructor provides
poor definitional equalities. If other fields are known explicitly, they should be
provided; for example, if `inf` is known explicitly, construct the `CompleteLattice`
instance as
```
instance : CompleteLattice my_T where
inf := better_inf
le_inf := ...
inf_le_right := ...
inf_le_left := ...
-- don't care to fix sup, sInf, bot, top
__ := completeLatticeOfSup my_T _
```
-/
def completeLatticeOfSup (α : Type*) [H1 : PartialOrder α] [H2 : SupSet α]
(isLUB_sSup : ∀ s : Set α, IsLUB s (sSup s)) : CompleteLattice α where
__ := H1; __ := H2
top := sSup univ
le_top x := (isLUB_sSup univ).1 trivial
bot := sSup ∅
bot_le x := (isLUB_sSup ∅).2 <| by simp
sup a b := sSup {a, b}
sup_le a b c hac hbc := (isLUB_sSup _).2 (by simp [*])
le_sup_left a b := (isLUB_sSup _).1 <| mem_insert _ _
le_sup_right a b := (isLUB_sSup _).1 <| mem_insert_of_mem _ <| mem_singleton _
inf a b := sSup { x | x ≤ a ∧ x ≤ b }
le_inf a b c hab hac := (isLUB_sSup _).1 <| by simp [*]
inf_le_left a b := (isLUB_sSup _).2 fun x => And.left
inf_le_right a b := (isLUB_sSup _).2 fun x => And.right
sInf s := sSup (lowerBounds s)
sSup_le s a ha := (isLUB_sSup s).2 ha
le_sSup s a ha := (isLUB_sSup s).1 ha
sInf_le s a ha := (isLUB_sSup (lowerBounds s)).2 fun b hb => hb ha
le_sInf s a ha := (isLUB_sSup (lowerBounds s)).1 ha
#align complete_lattice_of_Sup completeLatticeOfSup
/-- Any `CompleteSemilatticeSup` is in fact a `CompleteLattice`.
Note that this construction has bad definitional properties:
see the doc-string on `completeLatticeOfSup`.
-/
def completeLatticeOfCompleteSemilatticeSup (α : Type*) [CompleteSemilatticeSup α] :
CompleteLattice α :=
completeLatticeOfSup α fun s => isLUB_sSup s
#align complete_lattice_of_complete_semilattice_Sup completeLatticeOfCompleteSemilatticeSup
-- Porting note: as we cannot rename fields while extending,
-- `CompleteLinearOrder` does not directly extend `LinearOrder`.
-- Instead we add the fields by hand, and write a manual instance.
/-- A complete linear order is a linear order whose lattice structure is complete. -/
class CompleteLinearOrder (α : Type*) extends CompleteLattice α where
/-- A linear order is total. -/
le_total (a b : α) : a ≤ b ∨ b ≤ a
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableLE : DecidableRel (· ≤ · : α → α → Prop)
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableEq : DecidableEq α := @decidableEqOfDecidableLE _ _ decidableLE
/-- In a linearly ordered type, we assume the order relations are all decidable. -/
decidableLT : DecidableRel (· < · : α → α → Prop) :=
@decidableLTOfDecidableLE _ _ decidableLE
#align complete_linear_order CompleteLinearOrder
instance CompleteLinearOrder.toLinearOrder [i : CompleteLinearOrder α] : LinearOrder α where
__ := i
min := Inf.inf
max := Sup.sup
min_def a b := by
split_ifs with h
· simp [h]
· simp [(CompleteLinearOrder.le_total a b).resolve_left h]
max_def a b := by
split_ifs with h
· simp [h]
· simp [(CompleteLinearOrder.le_total a b).resolve_left h]
namespace OrderDual
instance instCompleteLattice [CompleteLattice α] : CompleteLattice αᵒᵈ where
__ := instBoundedOrder α
le_sSup := @CompleteLattice.sInf_le α _
sSup_le := @CompleteLattice.le_sInf α _
sInf_le := @CompleteLattice.le_sSup α _
le_sInf := @CompleteLattice.sSup_le α _
instance instCompleteLinearOrder [CompleteLinearOrder α] : CompleteLinearOrder αᵒᵈ where
__ := instCompleteLattice
__ := instLinearOrder α
end OrderDual
open OrderDual
section
variable [CompleteLattice α] {s t : Set α} {a b : α}
@[simp]
theorem toDual_sSup (s : Set α) : toDual (sSup s) = sInf (ofDual ⁻¹' s) :=
rfl
#align to_dual_Sup toDual_sSup
@[simp]
theorem toDual_sInf (s : Set α) : toDual (sInf s) = sSup (ofDual ⁻¹' s) :=
rfl
#align to_dual_Inf toDual_sInf
@[simp]
theorem ofDual_sSup (s : Set αᵒᵈ) : ofDual (sSup s) = sInf (toDual ⁻¹' s) :=
rfl
#align of_dual_Sup ofDual_sSup
@[simp]
theorem ofDual_sInf (s : Set αᵒᵈ) : ofDual (sInf s) = sSup (toDual ⁻¹' s) :=
rfl
#align of_dual_Inf ofDual_sInf
@[simp]
theorem toDual_iSup (f : ι → α) : toDual (⨆ i, f i) = ⨅ i, toDual (f i) :=
rfl
#align to_dual_supr toDual_iSup
@[simp]
theorem toDual_iInf (f : ι → α) : toDual (⨅ i, f i) = ⨆ i, toDual (f i) :=
rfl
#align to_dual_infi toDual_iInf
@[simp]
theorem ofDual_iSup (f : ι → αᵒᵈ) : ofDual (⨆ i, f i) = ⨅ i, ofDual (f i) :=
rfl
#align of_dual_supr ofDual_iSup
@[simp]
theorem ofDual_iInf (f : ι → αᵒᵈ) : ofDual (⨅ i, f i) = ⨆ i, ofDual (f i) :=
rfl
#align of_dual_infi ofDual_iInf
theorem sInf_le_sSup (hs : s.Nonempty) : sInf s ≤ sSup s :=
isGLB_le_isLUB (isGLB_sInf s) (isLUB_sSup s) hs
#align Inf_le_Sup sInf_le_sSup
theorem sSup_union {s t : Set α} : sSup (s ∪ t) = sSup s ⊔ sSup t :=
((isLUB_sSup s).union (isLUB_sSup t)).sSup_eq
#align Sup_union sSup_union
theorem sInf_union {s t : Set α} : sInf (s ∪ t) = sInf s ⊓ sInf t :=
((isGLB_sInf s).union (isGLB_sInf t)).sInf_eq
#align Inf_union sInf_union
theorem sSup_inter_le {s t : Set α} : sSup (s ∩ t) ≤ sSup s ⊓ sSup t :=
sSup_le fun _ hb => le_inf (le_sSup hb.1) (le_sSup hb.2)
#align Sup_inter_le sSup_inter_le
theorem le_sInf_inter {s t : Set α} : sInf s ⊔ sInf t ≤ sInf (s ∩ t) :=
@sSup_inter_le αᵒᵈ _ _ _
#align le_Inf_inter le_sInf_inter
@[simp]
theorem sSup_empty : sSup ∅ = (⊥ : α) :=
(@isLUB_empty α _ _).sSup_eq
#align Sup_empty sSup_empty
@[simp]
theorem sInf_empty : sInf ∅ = (⊤ : α) :=
(@isGLB_empty α _ _).sInf_eq
#align Inf_empty sInf_empty
@[simp]
theorem sSup_univ : sSup univ = (⊤ : α) :=
(@isLUB_univ α _ _).sSup_eq
#align Sup_univ sSup_univ
@[simp]
theorem sInf_univ : sInf univ = (⊥ : α) :=
(@isGLB_univ α _ _).sInf_eq
#align Inf_univ sInf_univ
-- TODO(Jeremy): get this automatically
@[simp]
theorem sSup_insert {a : α} {s : Set α} : sSup (insert a s) = a ⊔ sSup s :=
((isLUB_sSup s).insert a).sSup_eq
#align Sup_insert sSup_insert
@[simp]
theorem sInf_insert {a : α} {s : Set α} : sInf (insert a s) = a ⊓ sInf s :=
((isGLB_sInf s).insert a).sInf_eq
#align Inf_insert sInf_insert
theorem sSup_le_sSup_of_subset_insert_bot (h : s ⊆ insert ⊥ t) : sSup s ≤ sSup t :=
(sSup_le_sSup h).trans_eq (sSup_insert.trans (bot_sup_eq _))
#align Sup_le_Sup_of_subset_insert_bot sSup_le_sSup_of_subset_insert_bot
theorem sInf_le_sInf_of_subset_insert_top (h : s ⊆ insert ⊤ t) : sInf t ≤ sInf s :=
(sInf_le_sInf h).trans_eq' (sInf_insert.trans (top_inf_eq _)).symm
#align Inf_le_Inf_of_subset_insert_top sInf_le_sInf_of_subset_insert_top
@[simp]
theorem sSup_diff_singleton_bot (s : Set α) : sSup (s \ {⊥}) = sSup s :=
(sSup_le_sSup diff_subset).antisymm <|
sSup_le_sSup_of_subset_insert_bot <| subset_insert_diff_singleton _ _
#align Sup_diff_singleton_bot sSup_diff_singleton_bot
@[simp]
theorem sInf_diff_singleton_top (s : Set α) : sInf (s \ {⊤}) = sInf s :=
@sSup_diff_singleton_bot αᵒᵈ _ s
#align Inf_diff_singleton_top sInf_diff_singleton_top
theorem sSup_pair {a b : α} : sSup {a, b} = a ⊔ b :=
(@isLUB_pair α _ a b).sSup_eq
#align Sup_pair sSup_pair
theorem sInf_pair {a b : α} : sInf {a, b} = a ⊓ b :=
(@isGLB_pair α _ a b).sInf_eq
#align Inf_pair sInf_pair
@[simp]
theorem sSup_eq_bot : sSup s = ⊥ ↔ ∀ a ∈ s, a = ⊥ :=
⟨fun h _ ha => bot_unique <| h ▸ le_sSup ha, fun h =>
bot_unique <| sSup_le fun a ha => le_bot_iff.2 <| h a ha⟩
#align Sup_eq_bot sSup_eq_bot
@[simp]
theorem sInf_eq_top : sInf s = ⊤ ↔ ∀ a ∈ s, a = ⊤ :=
@sSup_eq_bot αᵒᵈ _ _
#align Inf_eq_top sInf_eq_top
theorem eq_singleton_bot_of_sSup_eq_bot_of_nonempty {s : Set α} (h_sup : sSup s = ⊥)
(hne : s.Nonempty) : s = {⊥} := by
rw [Set.eq_singleton_iff_nonempty_unique_mem]
rw [sSup_eq_bot] at h_sup
exact ⟨hne, h_sup⟩
#align eq_singleton_bot_of_Sup_eq_bot_of_nonempty eq_singleton_bot_of_sSup_eq_bot_of_nonempty
theorem eq_singleton_top_of_sInf_eq_top_of_nonempty : sInf s = ⊤ → s.Nonempty → s = {⊤} :=
@eq_singleton_bot_of_sSup_eq_bot_of_nonempty αᵒᵈ _ _
#align eq_singleton_top_of_Inf_eq_top_of_nonempty eq_singleton_top_of_sInf_eq_top_of_nonempty
/-- Introduction rule to prove that `b` is the supremum of `s`: it suffices to check that `b`
is larger than all elements of `s`, and that this is not the case of any `w < b`.
See `csSup_eq_of_forall_le_of_forall_lt_exists_gt` for a version in conditionally complete
lattices. -/
theorem sSup_eq_of_forall_le_of_forall_lt_exists_gt (h₁ : ∀ a ∈ s, a ≤ b)
(h₂ : ∀ w, w < b → ∃ a ∈ s, w < a) : sSup s = b :=
(sSup_le h₁).eq_of_not_lt fun h =>
let ⟨_, ha, ha'⟩ := h₂ _ h
((le_sSup ha).trans_lt ha').false
#align Sup_eq_of_forall_le_of_forall_lt_exists_gt sSup_eq_of_forall_le_of_forall_lt_exists_gt
/-- Introduction rule to prove that `b` is the infimum of `s`: it suffices to check that `b`
is smaller than all elements of `s`, and that this is not the case of any `w > b`.
See `csInf_eq_of_forall_ge_of_forall_gt_exists_lt` for a version in conditionally complete
lattices. -/
theorem sInf_eq_of_forall_ge_of_forall_gt_exists_lt :
(∀ a ∈ s, b ≤ a) → (∀ w, b < w → ∃ a ∈ s, a < w) → sInf s = b :=
@sSup_eq_of_forall_le_of_forall_lt_exists_gt αᵒᵈ _ _ _
#align Inf_eq_of_forall_ge_of_forall_gt_exists_lt sInf_eq_of_forall_ge_of_forall_gt_exists_lt
end
section CompleteLinearOrder
variable [CompleteLinearOrder α] {s t : Set α} {a b : α}
theorem lt_sSup_iff : b < sSup s ↔ ∃ a ∈ s, b < a :=
lt_isLUB_iff <| isLUB_sSup s
#align lt_Sup_iff lt_sSup_iff
theorem sInf_lt_iff : sInf s < b ↔ ∃ a ∈ s, a < b :=
isGLB_lt_iff <| isGLB_sInf s
#align Inf_lt_iff sInf_lt_iff
theorem sSup_eq_top : sSup s = ⊤ ↔ ∀ b < ⊤, ∃ a ∈ s, b < a :=
⟨fun h _ hb => lt_sSup_iff.1 <| hb.trans_eq h.symm, fun h =>
top_unique <|
le_of_not_gt fun h' =>
let ⟨_, ha, h⟩ := h _ h'
(h.trans_le <| le_sSup ha).false⟩
#align Sup_eq_top sSup_eq_top
theorem sInf_eq_bot : sInf s = ⊥ ↔ ∀ b > ⊥, ∃ a ∈ s, a < b :=
@sSup_eq_top αᵒᵈ _ _
#align Inf_eq_bot sInf_eq_bot
theorem lt_iSup_iff {f : ι → α} : a < iSup f ↔ ∃ i, a < f i :=
lt_sSup_iff.trans exists_range_iff
#align lt_supr_iff lt_iSup_iff
theorem iInf_lt_iff {f : ι → α} : iInf f < a ↔ ∃ i, f i < a :=
sInf_lt_iff.trans exists_range_iff
#align infi_lt_iff iInf_lt_iff
end CompleteLinearOrder
/-
### iSup & iInf
-/
section SupSet
variable [SupSet α] {f g : ι → α}
theorem sSup_range : sSup (range f) = iSup f :=
rfl
#align Sup_range sSup_range
theorem sSup_eq_iSup' (s : Set α) : sSup s = ⨆ a : s, (a : α) := by rw [iSup, Subtype.range_coe]
#align Sup_eq_supr' sSup_eq_iSup'
theorem iSup_congr (h : ∀ i, f i = g i) : ⨆ i, f i = ⨆ i, g i :=
congr_arg _ <| funext h
#align supr_congr iSup_congr
theorem biSup_congr {p : ι → Prop} (h : ∀ i, p i → f i = g i) :
⨆ (i) (_ : p i), f i = ⨆ (i) (_ : p i), g i :=
iSup_congr fun i ↦ iSup_congr (h i)
theorem biSup_congr' {p : ι → Prop} {f g : (i : ι) → p i → α}
(h : ∀ i (hi : p i), f i hi = g i hi) :
⨆ i, ⨆ (hi : p i), f i hi = ⨆ i, ⨆ (hi : p i), g i hi := by
congr; ext i; congr; ext hi; exact h i hi
theorem Function.Surjective.iSup_comp {f : ι → ι'} (hf : Surjective f) (g : ι' → α) :
⨆ x, g (f x) = ⨆ y, g y := by
simp only [iSup.eq_1]
congr
exact hf.range_comp g
#align function.surjective.supr_comp Function.Surjective.iSup_comp
theorem Equiv.iSup_comp {g : ι' → α} (e : ι ≃ ι') : ⨆ x, g (e x) = ⨆ y, g y :=
e.surjective.iSup_comp _
#align equiv.supr_comp Equiv.iSup_comp
protected theorem Function.Surjective.iSup_congr {g : ι' → α} (h : ι → ι') (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⨆ x, f x = ⨆ y, g y := by
convert h1.iSup_comp g
exact (h2 _).symm
#align function.surjective.supr_congr Function.Surjective.iSup_congr
protected theorem Equiv.iSup_congr {g : ι' → α} (e : ι ≃ ι') (h : ∀ x, g (e x) = f x) :
⨆ x, f x = ⨆ y, g y :=
e.surjective.iSup_congr _ h
#align equiv.supr_congr Equiv.iSup_congr
@[congr]
theorem iSup_congr_Prop {p q : Prop} {f₁ : p → α} {f₂ : q → α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iSup f₁ = iSup f₂ := by
obtain rfl := propext pq
congr with x
apply f
#align supr_congr_Prop iSup_congr_Prop
theorem iSup_plift_up (f : PLift ι → α) : ⨆ i, f (PLift.up i) = ⨆ i, f i :=
(PLift.up_surjective.iSup_congr _) fun _ => rfl
#align supr_plift_up iSup_plift_up
theorem iSup_plift_down (f : ι → α) : ⨆ i, f (PLift.down i) = ⨆ i, f i :=
(PLift.down_surjective.iSup_congr _) fun _ => rfl
#align supr_plift_down iSup_plift_down
theorem iSup_range' (g : β → α) (f : ι → β) : ⨆ b : range f, g b = ⨆ i, g (f i) := by
rw [iSup, iSup, ← image_eq_range, ← range_comp]
rfl
#align supr_range' iSup_range'
theorem sSup_image' {s : Set β} {f : β → α} : sSup (f '' s) = ⨆ a : s, f a := by
rw [iSup, image_eq_range]
#align Sup_image' sSup_image'
end SupSet
section InfSet
variable [InfSet α] {f g : ι → α}
theorem sInf_range : sInf (range f) = iInf f :=
rfl
#align Inf_range sInf_range
theorem sInf_eq_iInf' (s : Set α) : sInf s = ⨅ a : s, (a : α) :=
@sSup_eq_iSup' αᵒᵈ _ _
#align Inf_eq_infi' sInf_eq_iInf'
theorem iInf_congr (h : ∀ i, f i = g i) : ⨅ i, f i = ⨅ i, g i :=
congr_arg _ <| funext h
#align infi_congr iInf_congr
theorem biInf_congr {p : ι → Prop} (h : ∀ i, p i → f i = g i) :
⨅ (i) (_ : p i), f i = ⨅ (i) (_ : p i), g i :=
biSup_congr (α := αᵒᵈ) h
theorem biInf_congr' {p : ι → Prop} {f g : (i : ι) → p i → α}
(h : ∀ i (hi : p i), f i hi = g i hi) :
⨅ i, ⨅ (hi : p i), f i hi = ⨅ i, ⨅ (hi : p i), g i hi := by
congr; ext i; congr; ext hi; exact h i hi
theorem Function.Surjective.iInf_comp {f : ι → ι'} (hf : Surjective f) (g : ι' → α) :
⨅ x, g (f x) = ⨅ y, g y :=
@Function.Surjective.iSup_comp αᵒᵈ _ _ _ f hf g
#align function.surjective.infi_comp Function.Surjective.iInf_comp
theorem Equiv.iInf_comp {g : ι' → α} (e : ι ≃ ι') : ⨅ x, g (e x) = ⨅ y, g y :=
@Equiv.iSup_comp αᵒᵈ _ _ _ _ e
#align equiv.infi_comp Equiv.iInf_comp
protected theorem Function.Surjective.iInf_congr {g : ι' → α} (h : ι → ι') (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⨅ x, f x = ⨅ y, g y :=
@Function.Surjective.iSup_congr αᵒᵈ _ _ _ _ _ h h1 h2
#align function.surjective.infi_congr Function.Surjective.iInf_congr
protected theorem Equiv.iInf_congr {g : ι' → α} (e : ι ≃ ι') (h : ∀ x, g (e x) = f x) :
⨅ x, f x = ⨅ y, g y :=
@Equiv.iSup_congr αᵒᵈ _ _ _ _ _ e h
#align equiv.infi_congr Equiv.iInf_congr
@[congr]
theorem iInf_congr_Prop {p q : Prop} {f₁ : p → α} {f₂ : q → α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iInf f₁ = iInf f₂ :=
@iSup_congr_Prop αᵒᵈ _ p q f₁ f₂ pq f
#align infi_congr_Prop iInf_congr_Prop
theorem iInf_plift_up (f : PLift ι → α) : ⨅ i, f (PLift.up i) = ⨅ i, f i :=
(PLift.up_surjective.iInf_congr _) fun _ => rfl
#align infi_plift_up iInf_plift_up
theorem iInf_plift_down (f : ι → α) : ⨅ i, f (PLift.down i) = ⨅ i, f i :=
(PLift.down_surjective.iInf_congr _) fun _ => rfl
#align infi_plift_down iInf_plift_down
theorem iInf_range' (g : β → α) (f : ι → β) : ⨅ b : range f, g b = ⨅ i, g (f i) :=
@iSup_range' αᵒᵈ _ _ _ _ _
#align infi_range' iInf_range'
theorem sInf_image' {s : Set β} {f : β → α} : sInf (f '' s) = ⨅ a : s, f a :=
@sSup_image' αᵒᵈ _ _ _ _
#align Inf_image' sInf_image'
end InfSet
section
variable [CompleteLattice α] {f g s t : ι → α} {a b : α}
theorem le_iSup (f : ι → α) (i : ι) : f i ≤ iSup f :=
le_sSup ⟨i, rfl⟩
#align le_supr le_iSup
theorem iInf_le (f : ι → α) (i : ι) : iInf f ≤ f i :=
sInf_le ⟨i, rfl⟩
#align infi_le iInf_le
theorem le_iSup' (f : ι → α) (i : ι) : f i ≤ iSup f :=
le_sSup ⟨i, rfl⟩
#align le_supr' le_iSup'
theorem iInf_le' (f : ι → α) (i : ι) : iInf f ≤ f i :=
sInf_le ⟨i, rfl⟩
#align infi_le' iInf_le'
theorem isLUB_iSup : IsLUB (range f) (⨆ j, f j) :=
isLUB_sSup _
#align is_lub_supr isLUB_iSup
theorem isGLB_iInf : IsGLB (range f) (⨅ j, f j) :=
isGLB_sInf _
#align is_glb_infi isGLB_iInf
theorem IsLUB.iSup_eq (h : IsLUB (range f) a) : ⨆ j, f j = a :=
h.sSup_eq
#align is_lub.supr_eq IsLUB.iSup_eq
theorem IsGLB.iInf_eq (h : IsGLB (range f) a) : ⨅ j, f j = a :=
h.sInf_eq
#align is_glb.infi_eq IsGLB.iInf_eq
theorem le_iSup_of_le (i : ι) (h : a ≤ f i) : a ≤ iSup f :=
h.trans <| le_iSup _ i
#align le_supr_of_le le_iSup_of_le
theorem iInf_le_of_le (i : ι) (h : f i ≤ a) : iInf f ≤ a :=
(iInf_le _ i).trans h
#align infi_le_of_le iInf_le_of_le
theorem le_iSup₂ {f : ∀ i, κ i → α} (i : ι) (j : κ i) : f i j ≤ ⨆ (i) (j), f i j :=
le_iSup_of_le i <| le_iSup (f i) j
#align le_supr₂ le_iSup₂
theorem iInf₂_le {f : ∀ i, κ i → α} (i : ι) (j : κ i) : ⨅ (i) (j), f i j ≤ f i j :=
iInf_le_of_le i <| iInf_le (f i) j
#align infi₂_le iInf₂_le
theorem le_iSup₂_of_le {f : ∀ i, κ i → α} (i : ι) (j : κ i) (h : a ≤ f i j) :
a ≤ ⨆ (i) (j), f i j :=
h.trans <| le_iSup₂ i j
#align le_supr₂_of_le le_iSup₂_of_le
theorem iInf₂_le_of_le {f : ∀ i, κ i → α} (i : ι) (j : κ i) (h : f i j ≤ a) :
⨅ (i) (j), f i j ≤ a :=
(iInf₂_le i j).trans h
#align infi₂_le_of_le iInf₂_le_of_le
theorem iSup_le (h : ∀ i, f i ≤ a) : iSup f ≤ a :=
sSup_le fun _ ⟨i, Eq⟩ => Eq ▸ h i
#align supr_le iSup_le
theorem le_iInf (h : ∀ i, a ≤ f i) : a ≤ iInf f :=
le_sInf fun _ ⟨i, Eq⟩ => Eq ▸ h i
#align le_infi le_iInf
theorem iSup₂_le {f : ∀ i, κ i → α} (h : ∀ i j, f i j ≤ a) : ⨆ (i) (j), f i j ≤ a :=
iSup_le fun i => iSup_le <| h i
#align supr₂_le iSup₂_le
theorem le_iInf₂ {f : ∀ i, κ i → α} (h : ∀ i j, a ≤ f i j) : a ≤ ⨅ (i) (j), f i j :=
le_iInf fun i => le_iInf <| h i
#align le_infi₂ le_iInf₂
theorem iSup₂_le_iSup (κ : ι → Sort*) (f : ι → α) : ⨆ (i) (_ : κ i), f i ≤ ⨆ i, f i :=
iSup₂_le fun i _ => le_iSup f i
#align supr₂_le_supr iSup₂_le_iSup
theorem iInf_le_iInf₂ (κ : ι → Sort*) (f : ι → α) : ⨅ i, f i ≤ ⨅ (i) (_ : κ i), f i :=
le_iInf₂ fun i _ => iInf_le f i
#align infi_le_infi₂ iInf_le_iInf₂
@[gcongr]
theorem iSup_mono (h : ∀ i, f i ≤ g i) : iSup f ≤ iSup g :=
iSup_le fun i => le_iSup_of_le i <| h i
#align supr_mono iSup_mono
@[gcongr]
theorem iInf_mono (h : ∀ i, f i ≤ g i) : iInf f ≤ iInf g :=
le_iInf fun i => iInf_le_of_le i <| h i
#align infi_mono iInf_mono
theorem iSup₂_mono {f g : ∀ i, κ i → α} (h : ∀ i j, f i j ≤ g i j) :
⨆ (i) (j), f i j ≤ ⨆ (i) (j), g i j :=
iSup_mono fun i => iSup_mono <| h i
#align supr₂_mono iSup₂_mono
theorem iInf₂_mono {f g : ∀ i, κ i → α} (h : ∀ i j, f i j ≤ g i j) :
⨅ (i) (j), f i j ≤ ⨅ (i) (j), g i j :=
iInf_mono fun i => iInf_mono <| h i
#align infi₂_mono iInf₂_mono
theorem iSup_mono' {g : ι' → α} (h : ∀ i, ∃ i', f i ≤ g i') : iSup f ≤ iSup g :=
iSup_le fun i => Exists.elim (h i) le_iSup_of_le
#align supr_mono' iSup_mono'
theorem iInf_mono' {g : ι' → α} (h : ∀ i', ∃ i, f i ≤ g i') : iInf f ≤ iInf g :=
le_iInf fun i' => Exists.elim (h i') iInf_le_of_le
#align infi_mono' iInf_mono'
theorem iSup₂_mono' {f : ∀ i, κ i → α} {g : ∀ i', κ' i' → α} (h : ∀ i j, ∃ i' j', f i j ≤ g i' j') :
⨆ (i) (j), f i j ≤ ⨆ (i) (j), g i j :=
iSup₂_le fun i j =>
let ⟨i', j', h⟩ := h i j
le_iSup₂_of_le i' j' h
#align supr₂_mono' iSup₂_mono'
theorem iInf₂_mono' {f : ∀ i, κ i → α} {g : ∀ i', κ' i' → α} (h : ∀ i j, ∃ i' j', f i' j' ≤ g i j) :
⨅ (i) (j), f i j ≤ ⨅ (i) (j), g i j :=
le_iInf₂ fun i j =>
let ⟨i', j', h⟩ := h i j
iInf₂_le_of_le i' j' h
#align infi₂_mono' iInf₂_mono'
theorem iSup_const_mono (h : ι → ι') : ⨆ _ : ι, a ≤ ⨆ _ : ι', a :=
iSup_le <| le_iSup _ ∘ h
#align supr_const_mono iSup_const_mono
theorem iInf_const_mono (h : ι' → ι) : ⨅ _ : ι, a ≤ ⨅ _ : ι', a :=
le_iInf <| iInf_le _ ∘ h
#align infi_const_mono iInf_const_mono
theorem iSup_iInf_le_iInf_iSup (f : ι → ι' → α) : ⨆ i, ⨅ j, f i j ≤ ⨅ j, ⨆ i, f i j :=
iSup_le fun i => iInf_mono fun j => le_iSup (fun i => f i j) i
#align supr_infi_le_infi_supr iSup_iInf_le_iInf_iSup
theorem biSup_mono {p q : ι → Prop} (hpq : ∀ i, p i → q i) :
⨆ (i) (_ : p i), f i ≤ ⨆ (i) (_ : q i), f i :=
iSup_mono fun i => iSup_const_mono (hpq i)
#align bsupr_mono biSup_mono
theorem biInf_mono {p q : ι → Prop} (hpq : ∀ i, p i → q i) :
⨅ (i) (_ : q i), f i ≤ ⨅ (i) (_ : p i), f i :=
iInf_mono fun i => iInf_const_mono (hpq i)
#align binfi_mono biInf_mono
@[simp]
theorem iSup_le_iff : iSup f ≤ a ↔ ∀ i, f i ≤ a :=
(isLUB_le_iff isLUB_iSup).trans forall_mem_range
#align supr_le_iff iSup_le_iff
@[simp]
theorem le_iInf_iff : a ≤ iInf f ↔ ∀ i, a ≤ f i :=
(le_isGLB_iff isGLB_iInf).trans forall_mem_range
#align le_infi_iff le_iInf_iff
theorem iSup₂_le_iff {f : ∀ i, κ i → α} : ⨆ (i) (j), f i j ≤ a ↔ ∀ i j, f i j ≤ a := by
simp_rw [iSup_le_iff]
#align supr₂_le_iff iSup₂_le_iff
theorem le_iInf₂_iff {f : ∀ i, κ i → α} : (a ≤ ⨅ (i) (j), f i j) ↔ ∀ i j, a ≤ f i j := by
simp_rw [le_iInf_iff]
#align le_infi₂_iff le_iInf₂_iff
theorem iSup_lt_iff : iSup f < a ↔ ∃ b, b < a ∧ ∀ i, f i ≤ b :=
⟨fun h => ⟨iSup f, h, le_iSup f⟩, fun ⟨_, h, hb⟩ => (iSup_le hb).trans_lt h⟩
#align supr_lt_iff iSup_lt_iff
theorem lt_iInf_iff : a < iInf f ↔ ∃ b, a < b ∧ ∀ i, b ≤ f i :=
⟨fun h => ⟨iInf f, h, iInf_le f⟩, fun ⟨_, h, hb⟩ => h.trans_le <| le_iInf hb⟩
#align lt_infi_iff lt_iInf_iff
theorem sSup_eq_iSup {s : Set α} : sSup s = ⨆ a ∈ s, a :=
le_antisymm (sSup_le le_iSup₂) (iSup₂_le fun _ => le_sSup)
#align Sup_eq_supr sSup_eq_iSup
theorem sInf_eq_iInf {s : Set α} : sInf s = ⨅ a ∈ s, a :=
@sSup_eq_iSup αᵒᵈ _ _
#align Inf_eq_infi sInf_eq_iInf
theorem Monotone.le_map_iSup [CompleteLattice β] {f : α → β} (hf : Monotone f) :
⨆ i, f (s i) ≤ f (iSup s) :=
iSup_le fun _ => hf <| le_iSup _ _
#align monotone.le_map_supr Monotone.le_map_iSup
theorem Antitone.le_map_iInf [CompleteLattice β] {f : α → β} (hf : Antitone f) :
⨆ i, f (s i) ≤ f (iInf s) :=
hf.dual_left.le_map_iSup
#align antitone.le_map_infi Antitone.le_map_iInf
theorem Monotone.le_map_iSup₂ [CompleteLattice β] {f : α → β} (hf : Monotone f) (s : ∀ i, κ i → α) :
⨆ (i) (j), f (s i j) ≤ f (⨆ (i) (j), s i j) :=
iSup₂_le fun _ _ => hf <| le_iSup₂ _ _
#align monotone.le_map_supr₂ Monotone.le_map_iSup₂
theorem Antitone.le_map_iInf₂ [CompleteLattice β] {f : α → β} (hf : Antitone f) (s : ∀ i, κ i → α) :
⨆ (i) (j), f (s i j) ≤ f (⨅ (i) (j), s i j) :=
hf.dual_left.le_map_iSup₂ _
#align antitone.le_map_infi₂ Antitone.le_map_iInf₂
theorem Monotone.le_map_sSup [CompleteLattice β] {s : Set α} {f : α → β} (hf : Monotone f) :
⨆ a ∈ s, f a ≤ f (sSup s) := by rw [sSup_eq_iSup]; exact hf.le_map_iSup₂ _
#align monotone.le_map_Sup Monotone.le_map_sSup
theorem Antitone.le_map_sInf [CompleteLattice β] {s : Set α} {f : α → β} (hf : Antitone f) :
⨆ a ∈ s, f a ≤ f (sInf s) :=
hf.dual_left.le_map_sSup
#align antitone.le_map_Inf Antitone.le_map_sInf
theorem OrderIso.map_iSup [CompleteLattice β] (f : α ≃o β) (x : ι → α) :
f (⨆ i, x i) = ⨆ i, f (x i) :=
eq_of_forall_ge_iff <| f.surjective.forall.2
fun x => by simp only [f.le_iff_le, iSup_le_iff]
#align order_iso.map_supr OrderIso.map_iSup
theorem OrderIso.map_iInf [CompleteLattice β] (f : α ≃o β) (x : ι → α) :
f (⨅ i, x i) = ⨅ i, f (x i) :=
OrderIso.map_iSup f.dual _
#align order_iso.map_infi OrderIso.map_iInf
theorem OrderIso.map_sSup [CompleteLattice β] (f : α ≃o β) (s : Set α) :
f (sSup s) = ⨆ a ∈ s, f a := by
simp only [sSup_eq_iSup, OrderIso.map_iSup]
#align order_iso.map_Sup OrderIso.map_sSup
theorem OrderIso.map_sInf [CompleteLattice β] (f : α ≃o β) (s : Set α) :
f (sInf s) = ⨅ a ∈ s, f a :=
OrderIso.map_sSup f.dual _
#align order_iso.map_Inf OrderIso.map_sInf
theorem iSup_comp_le {ι' : Sort*} (f : ι' → α) (g : ι → ι') : ⨆ x, f (g x) ≤ ⨆ y, f y :=
iSup_mono' fun _ => ⟨_, le_rfl⟩
#align supr_comp_le iSup_comp_le
theorem le_iInf_comp {ι' : Sort*} (f : ι' → α) (g : ι → ι') : ⨅ y, f y ≤ ⨅ x, f (g x) :=
iInf_mono' fun _ => ⟨_, le_rfl⟩
#align le_infi_comp le_iInf_comp
theorem Monotone.iSup_comp_eq [Preorder β] {f : β → α} (hf : Monotone f) {s : ι → β}
(hs : ∀ x, ∃ i, x ≤ s i) : ⨆ x, f (s x) = ⨆ y, f y :=
le_antisymm (iSup_comp_le _ _) (iSup_mono' fun x => (hs x).imp fun _ hi => hf hi)
#align monotone.supr_comp_eq Monotone.iSup_comp_eq
theorem Monotone.iInf_comp_eq [Preorder β] {f : β → α} (hf : Monotone f) {s : ι → β}
(hs : ∀ x, ∃ i, s i ≤ x) : ⨅ x, f (s x) = ⨅ y, f y :=
le_antisymm (iInf_mono' fun x => (hs x).imp fun _ hi => hf hi) (le_iInf_comp _ _)
#align monotone.infi_comp_eq Monotone.iInf_comp_eq
theorem Antitone.map_iSup_le [CompleteLattice β] {f : α → β} (hf : Antitone f) :
f (iSup s) ≤ ⨅ i, f (s i) :=
le_iInf fun _ => hf <| le_iSup _ _
#align antitone.map_supr_le Antitone.map_iSup_le
theorem Monotone.map_iInf_le [CompleteLattice β] {f : α → β} (hf : Monotone f) :
f (iInf s) ≤ ⨅ i, f (s i) :=
hf.dual_left.map_iSup_le
#align monotone.map_infi_le Monotone.map_iInf_le
theorem Antitone.map_iSup₂_le [CompleteLattice β] {f : α → β} (hf : Antitone f) (s : ∀ i, κ i → α) :
f (⨆ (i) (j), s i j) ≤ ⨅ (i) (j), f (s i j) :=
hf.dual.le_map_iInf₂ _
#align antitone.map_supr₂_le Antitone.map_iSup₂_le
theorem Monotone.map_iInf₂_le [CompleteLattice β] {f : α → β} (hf : Monotone f) (s : ∀ i, κ i → α) :
f (⨅ (i) (j), s i j) ≤ ⨅ (i) (j), f (s i j) :=
hf.dual.le_map_iSup₂ _
#align monotone.map_infi₂_le Monotone.map_iInf₂_le
theorem Antitone.map_sSup_le [CompleteLattice β] {s : Set α} {f : α → β} (hf : Antitone f) :
f (sSup s) ≤ ⨅ a ∈ s, f a := by
rw [sSup_eq_iSup]
exact hf.map_iSup₂_le _
#align antitone.map_Sup_le Antitone.map_sSup_le
theorem Monotone.map_sInf_le [CompleteLattice β] {s : Set α} {f : α → β} (hf : Monotone f) :
f (sInf s) ≤ ⨅ a ∈ s, f a :=
hf.dual_left.map_sSup_le
#align monotone.map_Inf_le Monotone.map_sInf_le
theorem iSup_const_le : ⨆ _ : ι, a ≤ a :=
iSup_le fun _ => le_rfl
#align supr_const_le iSup_const_le
theorem le_iInf_const : a ≤ ⨅ _ : ι, a :=
le_iInf fun _ => le_rfl
#align le_infi_const le_iInf_const
-- We generalize this to conditionally complete lattices in `ciSup_const` and `ciInf_const`.
theorem iSup_const [Nonempty ι] : ⨆ _ : ι, a = a := by rw [iSup, range_const, sSup_singleton]
#align supr_const iSup_const
theorem iInf_const [Nonempty ι] : ⨅ _ : ι, a = a :=
@iSup_const αᵒᵈ _ _ a _
#align infi_const iInf_const
@[simp]
theorem iSup_bot : (⨆ _ : ι, ⊥ : α) = ⊥ :=
bot_unique iSup_const_le
#align supr_bot iSup_bot
@[simp]
theorem iInf_top : (⨅ _ : ι, ⊤ : α) = ⊤ :=
top_unique le_iInf_const
#align infi_top iInf_top
@[simp]
theorem iSup_eq_bot : iSup s = ⊥ ↔ ∀ i, s i = ⊥ :=
sSup_eq_bot.trans forall_mem_range
#align supr_eq_bot iSup_eq_bot
@[simp]
theorem iInf_eq_top : iInf s = ⊤ ↔ ∀ i, s i = ⊤ :=
sInf_eq_top.trans forall_mem_range
#align infi_eq_top iInf_eq_top
theorem iSup₂_eq_bot {f : ∀ i, κ i → α} : ⨆ (i) (j), f i j = ⊥ ↔ ∀ i j, f i j = ⊥ := by
simp
#align supr₂_eq_bot iSup₂_eq_bot
theorem iInf₂_eq_top {f : ∀ i, κ i → α} : ⨅ (i) (j), f i j = ⊤ ↔ ∀ i j, f i j = ⊤ := by
simp
#align infi₂_eq_top iInf₂_eq_top
@[simp]
theorem iSup_pos {p : Prop} {f : p → α} (hp : p) : ⨆ h : p, f h = f hp :=
le_antisymm (iSup_le fun _ => le_rfl) (le_iSup _ _)
#align supr_pos iSup_pos
@[simp]
theorem iInf_pos {p : Prop} {f : p → α} (hp : p) : ⨅ h : p, f h = f hp :=
le_antisymm (iInf_le _ _) (le_iInf fun _ => le_rfl)
#align infi_pos iInf_pos
@[simp]
theorem iSup_neg {p : Prop} {f : p → α} (hp : ¬p) : ⨆ h : p, f h = ⊥ :=
le_antisymm (iSup_le fun h => (hp h).elim) bot_le
#align supr_neg iSup_neg
@[simp]
theorem iInf_neg {p : Prop} {f : p → α} (hp : ¬p) : ⨅ h : p, f h = ⊤ :=
le_antisymm le_top <| le_iInf fun h => (hp h).elim
#align infi_neg iInf_neg
/-- Introduction rule to prove that `b` is the supremum of `f`: it suffices to check that `b`
is larger than `f i` for all `i`, and that this is not the case of any `w<b`.
See `ciSup_eq_of_forall_le_of_forall_lt_exists_gt` for a version in conditionally complete
lattices. -/
theorem iSup_eq_of_forall_le_of_forall_lt_exists_gt {f : ι → α} (h₁ : ∀ i, f i ≤ b)
(h₂ : ∀ w, w < b → ∃ i, w < f i) : ⨆ i : ι, f i = b :=
sSup_eq_of_forall_le_of_forall_lt_exists_gt (forall_mem_range.mpr h₁) fun w hw =>
exists_range_iff.mpr <| h₂ w hw
#align supr_eq_of_forall_le_of_forall_lt_exists_gt iSup_eq_of_forall_le_of_forall_lt_exists_gt
/-- Introduction rule to prove that `b` is the infimum of `f`: it suffices to check that `b`
is smaller than `f i` for all `i`, and that this is not the case of any `w>b`.
See `ciInf_eq_of_forall_ge_of_forall_gt_exists_lt` for a version in conditionally complete
lattices. -/
theorem iInf_eq_of_forall_ge_of_forall_gt_exists_lt :
(∀ i, b ≤ f i) → (∀ w, b < w → ∃ i, f i < w) → ⨅ i, f i = b :=
@iSup_eq_of_forall_le_of_forall_lt_exists_gt αᵒᵈ _ _ _ _
#align infi_eq_of_forall_ge_of_forall_gt_exists_lt iInf_eq_of_forall_ge_of_forall_gt_exists_lt
theorem iSup_eq_dif {p : Prop} [Decidable p] (a : p → α) :
⨆ h : p, a h = if h : p then a h else ⊥ := by by_cases h : p <;> simp [h]
#align supr_eq_dif iSup_eq_dif
theorem iSup_eq_if {p : Prop} [Decidable p] (a : α) : ⨆ _ : p, a = if p then a else ⊥ :=
iSup_eq_dif fun _ => a
#align supr_eq_if iSup_eq_if
theorem iInf_eq_dif {p : Prop} [Decidable p] (a : p → α) :
⨅ h : p, a h = if h : p then a h else ⊤ :=
@iSup_eq_dif αᵒᵈ _ _ _ _
#align infi_eq_dif iInf_eq_dif
theorem iInf_eq_if {p : Prop} [Decidable p] (a : α) : ⨅ _ : p, a = if p then a else ⊤ :=
iInf_eq_dif fun _ => a
#align infi_eq_if iInf_eq_if
theorem iSup_comm {f : ι → ι' → α} : ⨆ (i) (j), f i j = ⨆ (j) (i), f i j :=
le_antisymm (iSup_le fun i => iSup_mono fun j => le_iSup (fun i => f i j) i)
(iSup_le fun _ => iSup_mono fun _ => le_iSup _ _)
#align supr_comm iSup_comm
theorem iInf_comm {f : ι → ι' → α} : ⨅ (i) (j), f i j = ⨅ (j) (i), f i j :=
@iSup_comm αᵒᵈ _ _ _ _
#align infi_comm iInf_comm
theorem iSup₂_comm {ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*}
(f : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → α) :
⨆ (i₁) (j₁) (i₂) (j₂), f i₁ j₁ i₂ j₂ = ⨆ (i₂) (j₂) (i₁) (j₁), f i₁ j₁ i₂ j₂ := by
simp only [@iSup_comm _ (κ₁ _), @iSup_comm _ ι₁]
#align supr₂_comm iSup₂_comm
theorem iInf₂_comm {ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*}
(f : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → α) :
⨅ (i₁) (j₁) (i₂) (j₂), f i₁ j₁ i₂ j₂ = ⨅ (i₂) (j₂) (i₁) (j₁), f i₁ j₁ i₂ j₂ := by
simp only [@iInf_comm _ (κ₁ _), @iInf_comm _ ι₁]
#align infi₂_comm iInf₂_comm
/- TODO: this is strange. In the proof below, we get exactly the desired
among the equalities, but close does not get it.
begin
apply @le_antisymm,
simp, intros,
begin [smt]
ematch, ematch, ematch, trace_state, have := le_refl (f i_1 i),
trace_state, close
end
end
-/
@[simp]
theorem iSup_iSup_eq_left {b : β} {f : ∀ x : β, x = b → α} : ⨆ x, ⨆ h : x = b, f x h = f b rfl :=
(@le_iSup₂ _ _ _ _ f b rfl).antisymm'
(iSup_le fun c =>
iSup_le <| by
rintro rfl
rfl)
#align supr_supr_eq_left iSup_iSup_eq_left
@[simp]
theorem iInf_iInf_eq_left {b : β} {f : ∀ x : β, x = b → α} : ⨅ x, ⨅ h : x = b, f x h = f b rfl :=
@iSup_iSup_eq_left αᵒᵈ _ _ _ _
#align infi_infi_eq_left iInf_iInf_eq_left
@[simp]
theorem iSup_iSup_eq_right {b : β} {f : ∀ x : β, b = x → α} : ⨆ x, ⨆ h : b = x, f x h = f b rfl :=
(le_iSup₂ b rfl).antisymm'
(iSup₂_le fun c => by
rintro rfl
rfl)
#align supr_supr_eq_right iSup_iSup_eq_right
@[simp]
theorem iInf_iInf_eq_right {b : β} {f : ∀ x : β, b = x → α} : ⨅ x, ⨅ h : b = x, f x h = f b rfl :=
@iSup_iSup_eq_right αᵒᵈ _ _ _ _
#align infi_infi_eq_right iInf_iInf_eq_right
theorem iSup_subtype {p : ι → Prop} {f : Subtype p → α} : iSup f = ⨆ (i) (h : p i), f ⟨i, h⟩ :=
le_antisymm (iSup_le fun ⟨i, h⟩ => @le_iSup₂ _ _ p _ (fun i h => f ⟨i, h⟩) i h)
(iSup₂_le fun _ _ => le_iSup _ _)
#align supr_subtype iSup_subtype
theorem iInf_subtype : ∀ {p : ι → Prop} {f : Subtype p → α}, iInf f = ⨅ (i) (h : p i), f ⟨i, h⟩ :=
@iSup_subtype αᵒᵈ _ _
#align infi_subtype iInf_subtype
theorem iSup_subtype' {p : ι → Prop} {f : ∀ i, p i → α} :
⨆ (i) (h), f i h = ⨆ x : Subtype p, f x x.property :=
(@iSup_subtype _ _ _ p fun x => f x.val x.property).symm
#align supr_subtype' iSup_subtype'
theorem iInf_subtype' {p : ι → Prop} {f : ∀ i, p i → α} :
⨅ (i) (h : p i), f i h = ⨅ x : Subtype p, f x x.property :=
(@iInf_subtype _ _ _ p fun x => f x.val x.property).symm
#align infi_subtype' iInf_subtype'
theorem iSup_subtype'' {ι} (s : Set ι) (f : ι → α) : ⨆ i : s, f i = ⨆ (t : ι) (_ : t ∈ s), f t :=
iSup_subtype
#align supr_subtype'' iSup_subtype''
theorem iInf_subtype'' {ι} (s : Set ι) (f : ι → α) : ⨅ i : s, f i = ⨅ (t : ι) (_ : t ∈ s), f t :=
iInf_subtype
#align infi_subtype'' iInf_subtype''
theorem biSup_const {ι : Sort _} {a : α} {s : Set ι} (hs : s.Nonempty) : ⨆ i ∈ s, a = a := by
haveI : Nonempty s := Set.nonempty_coe_sort.mpr hs
rw [← iSup_subtype'', iSup_const]
#align bsupr_const biSup_const
theorem biInf_const {ι : Sort _} {a : α} {s : Set ι} (hs : s.Nonempty) : ⨅ i ∈ s, a = a :=
@biSup_const αᵒᵈ _ ι _ s hs
#align binfi_const biInf_const
theorem iSup_sup_eq : ⨆ x, f x ⊔ g x = (⨆ x, f x) ⊔ ⨆ x, g x :=
le_antisymm (iSup_le fun _ => sup_le_sup (le_iSup _ _) <| le_iSup _ _)
(sup_le (iSup_mono fun _ => le_sup_left) <| iSup_mono fun _ => le_sup_right)
#align supr_sup_eq iSup_sup_eq
theorem iInf_inf_eq : ⨅ x, f x ⊓ g x = (⨅ x, f x) ⊓ ⨅ x, g x :=
@iSup_sup_eq αᵒᵈ _ _ _ _
#align infi_inf_eq iInf_inf_eq
lemma Equiv.biSup_comp {ι ι' : Type*} {g : ι' → α} (e : ι ≃ ι') (s : Set ι') :
⨆ i ∈ e.symm '' s, g (e i) = ⨆ i ∈ s, g i := by
simpa only [iSup_subtype'] using (image e.symm s).symm.iSup_comp (g := g ∘ (↑))
lemma Equiv.biInf_comp {ι ι' : Type*} {g : ι' → α} (e : ι ≃ ι') (s : Set ι') :
⨅ i ∈ e.symm '' s, g (e i) = ⨅ i ∈ s, g i :=
e.biSup_comp s (α := αᵒᵈ)
lemma biInf_le {ι : Type*} {s : Set ι} (f : ι → α) {i : ι} (hi : i ∈ s) :
⨅ i ∈ s, f i ≤ f i := by
simpa only [iInf_subtype'] using iInf_le (ι := s) (f := f ∘ (↑)) ⟨i, hi⟩
lemma le_biSup {ι : Type*} {s : Set ι} (f : ι → α) {i : ι} (hi : i ∈ s) :
f i ≤ ⨆ i ∈ s, f i :=
biInf_le (α := αᵒᵈ) f hi
/- TODO: here is another example where more flexible pattern matching
might help.
begin
apply @le_antisymm,
safe, pose h := f a ⊓ g a, begin [smt] ematch, ematch end
end
-/
theorem iSup_sup [Nonempty ι] {f : ι → α} {a : α} : (⨆ x, f x) ⊔ a = ⨆ x, f x ⊔ a := by
rw [iSup_sup_eq, iSup_const]
#align supr_sup iSup_sup
theorem iInf_inf [Nonempty ι] {f : ι → α} {a : α} : (⨅ x, f x) ⊓ a = ⨅ x, f x ⊓ a := by
rw [iInf_inf_eq, iInf_const]
#align infi_inf iInf_inf
theorem sup_iSup [Nonempty ι] {f : ι → α} {a : α} : (a ⊔ ⨆ x, f x) = ⨆ x, a ⊔ f x := by
rw [iSup_sup_eq, iSup_const]
#align sup_supr sup_iSup
theorem inf_iInf [Nonempty ι] {f : ι → α} {a : α} : (a ⊓ ⨅ x, f x) = ⨅ x, a ⊓ f x := by
rw [iInf_inf_eq, iInf_const]
#align inf_infi inf_iInf
theorem biSup_sup {p : ι → Prop} {f : ∀ i, p i → α} {a : α} (h : ∃ i, p i) :
(⨆ (i) (h : p i), f i h) ⊔ a = ⨆ (i) (h : p i), f i h ⊔ a := by
haveI : Nonempty { i // p i } :=
let ⟨i, hi⟩ := h
⟨⟨i, hi⟩⟩
rw [iSup_subtype', iSup_subtype', iSup_sup]
#align bsupr_sup biSup_sup
theorem sup_biSup {p : ι → Prop} {f : ∀ i, p i → α} {a : α} (h : ∃ i, p i) :
(a ⊔ ⨆ (i) (h : p i), f i h) = ⨆ (i) (h : p i), a ⊔ f i h := by
simpa only [sup_comm] using @biSup_sup α _ _ p _ _ h
#align sup_bsupr sup_biSup
theorem biInf_inf {p : ι → Prop} {f : ∀ i, p i → α} {a : α} (h : ∃ i, p i) :
(⨅ (i) (h : p i), f i h) ⊓ a = ⨅ (i) (h : p i), f i h ⊓ a :=
@biSup_sup αᵒᵈ ι _ p f _ h
#align binfi_inf biInf_inf
theorem inf_biInf {p : ι → Prop} {f : ∀ i, p i → α} {a : α} (h : ∃ i, p i) :
(a ⊓ ⨅ (i) (h : p i), f i h) = ⨅ (i) (h : p i), a ⊓ f i h :=
@sup_biSup αᵒᵈ ι _ p f _ h
#align inf_binfi inf_biInf
/-! ### `iSup` and `iInf` under `Prop` -/
theorem iSup_false {s : False → α} : iSup s = ⊥ := by simp
#align supr_false iSup_false
theorem iInf_false {s : False → α} : iInf s = ⊤ := by simp
#align infi_false iInf_false
theorem iSup_true {s : True → α} : iSup s = s trivial :=
iSup_pos trivial
#align supr_true iSup_true
theorem iInf_true {s : True → α} : iInf s = s trivial :=
iInf_pos trivial
#align infi_true iInf_true
@[simp]
theorem iSup_exists {p : ι → Prop} {f : Exists p → α} : ⨆ x, f x = ⨆ (i) (h), f ⟨i, h⟩ :=
le_antisymm (iSup_le fun ⟨i, h⟩ => @le_iSup₂ _ _ _ _ (fun _ _ => _) i h)
(iSup₂_le fun _ _ => le_iSup _ _)
#align supr_exists iSup_exists
@[simp]
theorem iInf_exists {p : ι → Prop} {f : Exists p → α} : ⨅ x, f x = ⨅ (i) (h), f ⟨i, h⟩ :=
@iSup_exists αᵒᵈ _ _ _ _
#align infi_exists iInf_exists
theorem iSup_and {p q : Prop} {s : p ∧ q → α} : iSup s = ⨆ (h₁) (h₂), s ⟨h₁, h₂⟩ :=
le_antisymm (iSup_le fun ⟨i, h⟩ => @le_iSup₂ _ _ _ _ (fun _ _ => _) i h)
(iSup₂_le fun _ _ => le_iSup _ _)
#align supr_and iSup_and
theorem iInf_and {p q : Prop} {s : p ∧ q → α} : iInf s = ⨅ (h₁) (h₂), s ⟨h₁, h₂⟩ :=
@iSup_and αᵒᵈ _ _ _ _
#align infi_and iInf_and
/-- The symmetric case of `iSup_and`, useful for rewriting into a supremum over a conjunction -/
theorem iSup_and' {p q : Prop} {s : p → q → α} :
⨆ (h₁ : p) (h₂ : q), s h₁ h₂ = ⨆ h : p ∧ q, s h.1 h.2 :=
Eq.symm iSup_and
#align supr_and' iSup_and'
/-- The symmetric case of `iInf_and`, useful for rewriting into an infimum over a conjunction -/
theorem iInf_and' {p q : Prop} {s : p → q → α} :
⨅ (h₁ : p) (h₂ : q), s h₁ h₂ = ⨅ h : p ∧ q, s h.1 h.2 :=
Eq.symm iInf_and
#align infi_and' iInf_and'
theorem iSup_or {p q : Prop} {s : p ∨ q → α} :
⨆ x, s x = (⨆ i, s (Or.inl i)) ⊔ ⨆ j, s (Or.inr j) :=
le_antisymm
(iSup_le fun i =>
match i with
| Or.inl _ => le_sup_of_le_left <| le_iSup (fun _ => s _) _
| Or.inr _ => le_sup_of_le_right <| le_iSup (fun _ => s _) _)
(sup_le (iSup_comp_le _ _) (iSup_comp_le _ _))
#align supr_or iSup_or
theorem iInf_or {p q : Prop} {s : p ∨ q → α} :
⨅ x, s x = (⨅ i, s (Or.inl i)) ⊓ ⨅ j, s (Or.inr j) :=
@iSup_or αᵒᵈ _ _ _ _
#align infi_or iInf_or
section
variable (p : ι → Prop) [DecidablePred p]
theorem iSup_dite (f : ∀ i, p i → α) (g : ∀ i, ¬p i → α) :
⨆ i, (if h : p i then f i h else g i h) = (⨆ (i) (h : p i), f i h) ⊔ ⨆ (i) (h : ¬p i),
g i h := by
rw [← iSup_sup_eq]
congr 1 with i
split_ifs with h <;> simp [h]
#align supr_dite iSup_dite
theorem iInf_dite (f : ∀ i, p i → α) (g : ∀ i, ¬p i → α) :
⨅ i, (if h : p i then f i h else g i h) = (⨅ (i) (h : p i), f i h) ⊓ ⨅ (i) (h : ¬p i), g i h :=
iSup_dite p (show ∀ i, p i → αᵒᵈ from f) g
#align infi_dite iInf_dite
theorem iSup_ite (f g : ι → α) :
⨆ i, (if p i then f i else g i) = (⨆ (i) (_ : p i), f i) ⊔ ⨆ (i) (_ : ¬p i), g i :=
iSup_dite _ _ _
#align supr_ite iSup_ite
theorem iInf_ite (f g : ι → α) :
⨅ i, (if p i then f i else g i) = (⨅ (i) (_ : p i), f i) ⊓ ⨅ (i) (_ : ¬p i), g i :=
iInf_dite _ _ _
#align infi_ite iInf_ite
end
theorem iSup_range {g : β → α} {f : ι → β} : ⨆ b ∈ range f, g b = ⨆ i, g (f i) := by
rw [← iSup_subtype'', iSup_range']
#align supr_range iSup_range
theorem iInf_range : ∀ {g : β → α} {f : ι → β}, ⨅ b ∈ range f, g b = ⨅ i, g (f i) :=
@iSup_range αᵒᵈ _ _ _
#align infi_range iInf_range
theorem sSup_image {s : Set β} {f : β → α} : sSup (f '' s) = ⨆ a ∈ s, f a := by
rw [← iSup_subtype'', sSup_image']
#align Sup_image sSup_image
theorem sInf_image {s : Set β} {f : β → α} : sInf (f '' s) = ⨅ a ∈ s, f a :=
@sSup_image αᵒᵈ _ _ _ _
#align Inf_image sInf_image
theorem OrderIso.map_sSup_eq_sSup_symm_preimage [CompleteLattice β] (f : α ≃o β) (s : Set α) :
f (sSup s) = sSup (f.symm ⁻¹' s) := by
rw [map_sSup, ← sSup_image, f.image_eq_preimage]
theorem OrderIso.map_sInf_eq_sInf_symm_preimage [CompleteLattice β] (f : α ≃o β) (s : Set α) :
f (sInf s) = sInf (f.symm ⁻¹' s) := by
rw [map_sInf, ← sInf_image, f.image_eq_preimage]
/-
### iSup and iInf under set constructions
-/
theorem iSup_emptyset {f : β → α} : ⨆ x ∈ (∅ : Set β), f x = ⊥ := by simp
#align supr_emptyset iSup_emptyset
theorem iInf_emptyset {f : β → α} : ⨅ x ∈ (∅ : Set β), f x = ⊤ := by simp
#align infi_emptyset iInf_emptyset
theorem iSup_univ {f : β → α} : ⨆ x ∈ (univ : Set β), f x = ⨆ x, f x := by simp
#align supr_univ iSup_univ
theorem iInf_univ {f : β → α} : ⨅ x ∈ (univ : Set β), f x = ⨅ x, f x := by simp
#align infi_univ iInf_univ
theorem iSup_union {f : β → α} {s t : Set β} :
⨆ x ∈ s ∪ t, f x = (⨆ x ∈ s, f x) ⊔ ⨆ x ∈ t, f x := by
simp_rw [mem_union, iSup_or, iSup_sup_eq]
#align supr_union iSup_union
theorem iInf_union {f : β → α} {s t : Set β} : ⨅ x ∈ s ∪ t, f x = (⨅ x ∈ s, f x) ⊓ ⨅ x ∈ t, f x :=
@iSup_union αᵒᵈ _ _ _ _ _
#align infi_union iInf_union
theorem iSup_split (f : β → α) (p : β → Prop) :
⨆ i, f i = (⨆ (i) (_ : p i), f i) ⊔ ⨆ (i) (_ : ¬p i), f i := by
simpa [Classical.em] using @iSup_union _ _ _ f { i | p i } { i | ¬p i }
#align supr_split iSup_split
theorem iInf_split :
∀ (f : β → α) (p : β → Prop), ⨅ i, f i = (⨅ (i) (_ : p i), f i) ⊓ ⨅ (i) (_ : ¬p i), f i :=
@iSup_split αᵒᵈ _ _
#align infi_split iInf_split
theorem iSup_split_single (f : β → α) (i₀ : β) : ⨆ i, f i = f i₀ ⊔ ⨆ (i) (_ : i ≠ i₀), f i := by
convert iSup_split f (fun i => i = i₀)
simp
#align supr_split_single iSup_split_single
theorem iInf_split_single (f : β → α) (i₀ : β) : ⨅ i, f i = f i₀ ⊓ ⨅ (i) (_ : i ≠ i₀), f i :=
@iSup_split_single αᵒᵈ _ _ _ _
#align infi_split_single iInf_split_single
theorem iSup_le_iSup_of_subset {f : β → α} {s t : Set β} : s ⊆ t → ⨆ x ∈ s, f x ≤ ⨆ x ∈ t, f x :=
biSup_mono
#align supr_le_supr_of_subset iSup_le_iSup_of_subset
theorem iInf_le_iInf_of_subset {f : β → α} {s t : Set β} : s ⊆ t → ⨅ x ∈ t, f x ≤ ⨅ x ∈ s, f x :=
biInf_mono
#align infi_le_infi_of_subset iInf_le_iInf_of_subset
theorem iSup_insert {f : β → α} {s : Set β} {b : β} :
⨆ x ∈ insert b s, f x = f b ⊔ ⨆ x ∈ s, f x :=
Eq.trans iSup_union <| congr_arg (fun x => x ⊔ ⨆ x ∈ s, f x) iSup_iSup_eq_left
#align supr_insert iSup_insert
theorem iInf_insert {f : β → α} {s : Set β} {b : β} :
⨅ x ∈ insert b s, f x = f b ⊓ ⨅ x ∈ s, f x :=
Eq.trans iInf_union <| congr_arg (fun x => x ⊓ ⨅ x ∈ s, f x) iInf_iInf_eq_left
#align infi_insert iInf_insert
theorem iSup_singleton {f : β → α} {b : β} : ⨆ x ∈ (singleton b : Set β), f x = f b := by simp
#align supr_singleton iSup_singleton
theorem iInf_singleton {f : β → α} {b : β} : ⨅ x ∈ (singleton b : Set β), f x = f b := by simp
#align infi_singleton iInf_singleton
theorem iSup_pair {f : β → α} {a b : β} : ⨆ x ∈ ({a, b} : Set β), f x = f a ⊔ f b := by
rw [iSup_insert, iSup_singleton]
#align supr_pair iSup_pair
theorem iInf_pair {f : β → α} {a b : β} : ⨅ x ∈ ({a, b} : Set β), f x = f a ⊓ f b := by
rw [iInf_insert, iInf_singleton]
#align infi_pair iInf_pair
theorem iSup_image {γ} {f : β → γ} {g : γ → α} {t : Set β} :
⨆ c ∈ f '' t, g c = ⨆ b ∈ t, g (f b) := by rw [← sSup_image, ← sSup_image, ← image_comp]; rfl
#align supr_image iSup_image
theorem iInf_image :
∀ {γ} {f : β → γ} {g : γ → α} {t : Set β}, ⨅ c ∈ f '' t, g c = ⨅ b ∈ t, g (f b) :=
@iSup_image αᵒᵈ _ _
#align infi_image iInf_image
theorem iSup_extend_bot {e : ι → β} (he : Injective e) (f : ι → α) :
⨆ j, extend e f ⊥ j = ⨆ i, f i := by
rw [iSup_split _ fun j => ∃ i, e i = j]
simp (config := { contextual := true }) [he.extend_apply, extend_apply', @iSup_comm _ β ι]
#align supr_extend_bot iSup_extend_bot
theorem iInf_extend_top {e : ι → β} (he : Injective e) (f : ι → α) :
⨅ j, extend e f ⊤ j = iInf f :=
@iSup_extend_bot αᵒᵈ _ _ _ _ he _
#align infi_extend_top iInf_extend_top
/-!
### `iSup` and `iInf` under `Type`
-/
theorem iSup_of_empty' {α ι} [SupSet α] [IsEmpty ι] (f : ι → α) : iSup f = sSup (∅ : Set α) :=
congr_arg sSup (range_eq_empty f)
#align supr_of_empty' iSup_of_empty'
theorem iInf_of_isEmpty {α ι} [InfSet α] [IsEmpty ι] (f : ι → α) : iInf f = sInf (∅ : Set α) :=
congr_arg sInf (range_eq_empty f)
#align infi_of_empty' iInf_of_isEmpty
theorem iSup_of_empty [IsEmpty ι] (f : ι → α) : iSup f = ⊥ :=
(iSup_of_empty' f).trans sSup_empty
#align supr_of_empty iSup_of_empty
theorem iInf_of_empty [IsEmpty ι] (f : ι → α) : iInf f = ⊤ :=
@iSup_of_empty αᵒᵈ _ _ _ f
#align infi_of_empty iInf_of_empty
theorem iSup_bool_eq {f : Bool → α} : ⨆ b : Bool, f b = f true ⊔ f false := by
rw [iSup, Bool.range_eq, sSup_pair, sup_comm]
#align supr_bool_eq iSup_bool_eq
theorem iInf_bool_eq {f : Bool → α} : ⨅ b : Bool, f b = f true ⊓ f false :=
@iSup_bool_eq αᵒᵈ _ _
#align infi_bool_eq iInf_bool_eq
theorem sup_eq_iSup (x y : α) : x ⊔ y = ⨆ b : Bool, cond b x y := by
rw [iSup_bool_eq, Bool.cond_true, Bool.cond_false]
#align sup_eq_supr sup_eq_iSup
theorem inf_eq_iInf (x y : α) : x ⊓ y = ⨅ b : Bool, cond b x y :=
@sup_eq_iSup αᵒᵈ _ _ _
#align inf_eq_infi inf_eq_iInf
theorem isGLB_biInf {s : Set β} {f : β → α} : IsGLB (f '' s) (⨅ x ∈ s, f x) := by
simpa only [range_comp, Subtype.range_coe, iInf_subtype'] using
@isGLB_iInf α s _ (f ∘ fun x => (x : β))
#align is_glb_binfi isGLB_biInf
theorem isLUB_biSup {s : Set β} {f : β → α} : IsLUB (f '' s) (⨆ x ∈ s, f x) := by
simpa only [range_comp, Subtype.range_coe, iSup_subtype'] using
@isLUB_iSup α s _ (f ∘ fun x => (x : β))
#align is_lub_bsupr isLUB_biSup
theorem iSup_sigma {p : β → Type*} {f : Sigma p → α} : ⨆ x, f x = ⨆ (i) (j), f ⟨i, j⟩ :=
eq_of_forall_ge_iff fun c => by simp only [iSup_le_iff, Sigma.forall]
#align supr_sigma iSup_sigma
theorem iInf_sigma {p : β → Type*} {f : Sigma p → α} : ⨅ x, f x = ⨅ (i) (j), f ⟨i, j⟩ :=
@iSup_sigma αᵒᵈ _ _ _ _
#align infi_sigma iInf_sigma
lemma iSup_sigma' {κ : β → Type*} (f : ∀ i, κ i → α) :
(⨆ i, ⨆ j, f i j) = ⨆ x : Σ i, κ i, f x.1 x.2 :=
(iSup_sigma (f := fun x ↦ f x.1 x.2)).symm
lemma iInf_sigma' {κ : β → Type*} (f : ∀ i, κ i → α) :
(⨅ i, ⨅ j, f i j) = ⨅ x : Σ i, κ i, f x.1 x.2 :=
(iInf_sigma (f := fun x ↦ f x.1 x.2)).symm
theorem iSup_prod {f : β × γ → α} : ⨆ x, f x = ⨆ (i) (j), f (i, j) :=
eq_of_forall_ge_iff fun c => by simp only [iSup_le_iff, Prod.forall]
#align supr_prod iSup_prod
theorem iInf_prod {f : β × γ → α} : ⨅ x, f x = ⨅ (i) (j), f (i, j) :=
@iSup_prod αᵒᵈ _ _ _ _
#align infi_prod iInf_prod
lemma iSup_prod' (f : β → γ → α) : (⨆ i, ⨆ j, f i j) = ⨆ x : β × γ, f x.1 x.2 :=
(iSup_prod (f := fun x ↦ f x.1 x.2)).symm
lemma iInf_prod' (f : β → γ → α) : (⨅ i, ⨅ j, f i j) = ⨅ x : β × γ, f x.1 x.2 :=
(iInf_prod (f := fun x ↦ f x.1 x.2)).symm
theorem biSup_prod {f : β × γ → α} {s : Set β} {t : Set γ} :
⨆ x ∈ s ×ˢ t, f x = ⨆ (a ∈ s) (b ∈ t), f (a, b) := by
simp_rw [iSup_prod, mem_prod, iSup_and]
exact iSup_congr fun _ => iSup_comm
#align bsupr_prod biSup_prod
theorem biInf_prod {f : β × γ → α} {s : Set β} {t : Set γ} :
⨅ x ∈ s ×ˢ t, f x = ⨅ (a ∈ s) (b ∈ t), f (a, b) :=
@biSup_prod αᵒᵈ _ _ _ _ _ _
#align binfi_prod biInf_prod
theorem iSup_sum {f : Sum β γ → α} : ⨆ x, f x = (⨆ i, f (Sum.inl i)) ⊔ ⨆ j, f (Sum.inr j) :=
eq_of_forall_ge_iff fun c => by simp only [sup_le_iff, iSup_le_iff, Sum.forall]
#align supr_sum iSup_sum
theorem iInf_sum {f : Sum β γ → α} : ⨅ x, f x = (⨅ i, f (Sum.inl i)) ⊓ ⨅ j, f (Sum.inr j) :=
@iSup_sum αᵒᵈ _ _ _ _
#align infi_sum iInf_sum
theorem iSup_option (f : Option β → α) : ⨆ o, f o = f none ⊔ ⨆ b, f (Option.some b) :=
eq_of_forall_ge_iff fun c => by simp only [iSup_le_iff, sup_le_iff, Option.forall]
#align supr_option iSup_option
theorem iInf_option (f : Option β → α) : ⨅ o, f o = f none ⊓ ⨅ b, f (Option.some b) :=
@iSup_option αᵒᵈ _ _ _
#align infi_option iInf_option
/-- A version of `iSup_option` useful for rewriting right-to-left. -/
theorem iSup_option_elim (a : α) (f : β → α) : ⨆ o : Option β, o.elim a f = a ⊔ ⨆ b, f b := by
simp [iSup_option]
#align supr_option_elim iSup_option_elim
/-- A version of `iInf_option` useful for rewriting right-to-left. -/
theorem iInf_option_elim (a : α) (f : β → α) : ⨅ o : Option β, o.elim a f = a ⊓ ⨅ b, f b :=
@iSup_option_elim αᵒᵈ _ _ _ _
#align infi_option_elim iInf_option_elim
/-- When taking the supremum of `f : ι → α`, the elements of `ι` on which `f` gives `⊥` can be
dropped, without changing the result. -/
@[simp]
theorem iSup_ne_bot_subtype (f : ι → α) : ⨆ i : { i // f i ≠ ⊥ }, f i = ⨆ i, f i := by
by_cases htriv : ∀ i, f i = ⊥
· simp only [iSup_bot, (funext htriv : f = _)]
refine (iSup_comp_le f _).antisymm (iSup_mono' fun i => ?_)
by_cases hi : f i = ⊥
· rw [hi]
obtain ⟨i₀, hi₀⟩ := not_forall.mp htriv
exact ⟨⟨i₀, hi₀⟩, bot_le⟩
· exact ⟨⟨i, hi⟩, rfl.le⟩
#align supr_ne_bot_subtype iSup_ne_bot_subtype
/-- When taking the infimum of `f : ι → α`, the elements of `ι` on which `f` gives `⊤` can be
dropped, without changing the result. -/
theorem iInf_ne_top_subtype (f : ι → α) : ⨅ i : { i // f i ≠ ⊤ }, f i = ⨅ i, f i :=
@iSup_ne_bot_subtype αᵒᵈ ι _ f
#align infi_ne_top_subtype iInf_ne_top_subtype
theorem sSup_image2 {f : β → γ → α} {s : Set β} {t : Set γ} :
sSup (image2 f s t) = ⨆ (a ∈ s) (b ∈ t), f a b := by rw [← image_prod, sSup_image, biSup_prod]
#align Sup_image2 sSup_image2
theorem sInf_image2 {f : β → γ → α} {s : Set β} {t : Set γ} :
sInf (image2 f s t) = ⨅ (a ∈ s) (b ∈ t), f a b := by rw [← image_prod, sInf_image, biInf_prod]
#align Inf_image2 sInf_image2
/-!
### `iSup` and `iInf` under `ℕ`
-/
theorem iSup_ge_eq_iSup_nat_add (u : ℕ → α) (n : ℕ) : ⨆ i ≥ n, u i = ⨆ i, u (i + n) := by
apply le_antisymm <;> simp only [iSup_le_iff]
· refine fun i hi => le_sSup ⟨i - n, ?_⟩
dsimp only
rw [Nat.sub_add_cancel hi]
· exact fun i => le_sSup ⟨i + n, iSup_pos (Nat.le_add_left _ _)⟩
#align supr_ge_eq_supr_nat_add iSup_ge_eq_iSup_nat_add
theorem iInf_ge_eq_iInf_nat_add (u : ℕ → α) (n : ℕ) : ⨅ i ≥ n, u i = ⨅ i, u (i + n) :=
@iSup_ge_eq_iSup_nat_add αᵒᵈ _ _ _
#align infi_ge_eq_infi_nat_add iInf_ge_eq_iInf_nat_add
theorem Monotone.iSup_nat_add {f : ℕ → α} (hf : Monotone f) (k : ℕ) : ⨆ n, f (n + k) = ⨆ n, f n :=
le_antisymm (iSup_le fun i => le_iSup _ (i + k)) <| iSup_mono fun i => hf <| Nat.le_add_right i k
#align monotone.supr_nat_add Monotone.iSup_nat_add
theorem Antitone.iInf_nat_add {f : ℕ → α} (hf : Antitone f) (k : ℕ) : ⨅ n, f (n + k) = ⨅ n, f n :=
hf.dual_right.iSup_nat_add k
#align antitone.infi_nat_add Antitone.iInf_nat_add
-- Porting note: the linter doesn't like this being marked as `@[simp]`,
-- saying that it doesn't work when called on its LHS.
-- Mysteriously, it *does* work. Nevertheless, per
-- https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/complete_lattice.20and.20has_sup/near/316497982
-- "the subterm ?f (i + ?k) produces an ugly higher-order unification problem."
-- @[simp]
theorem iSup_iInf_ge_nat_add (f : ℕ → α) (k : ℕ) :
⨆ n, ⨅ i ≥ n, f (i + k) = ⨆ n, ⨅ i ≥ n, f i := by
have hf : Monotone fun n => ⨅ i ≥ n, f i := fun n m h => biInf_mono fun i => h.trans
rw [← Monotone.iSup_nat_add hf k]
· simp_rw [iInf_ge_eq_iInf_nat_add, ← Nat.add_assoc]
#align supr_infi_ge_nat_add iSup_iInf_ge_nat_add
-- Porting note: removing `@[simp]`, see discussion on `iSup_iInf_ge_nat_add`.
-- @[simp]
theorem iInf_iSup_ge_nat_add :
∀ (f : ℕ → α) (k : ℕ), ⨅ n, ⨆ i ≥ n, f (i + k) = ⨅ n, ⨆ i ≥ n, f i :=
@iSup_iInf_ge_nat_add αᵒᵈ _
#align infi_supr_ge_nat_add iInf_iSup_ge_nat_add
theorem sup_iSup_nat_succ (u : ℕ → α) : (u 0 ⊔ ⨆ i, u (i + 1)) = ⨆ i, u i :=
calc
(u 0 ⊔ ⨆ i, u (i + 1)) = ⨆ x ∈ {0} ∪ range Nat.succ, u x := by
{ rw [iSup_union, iSup_singleton, iSup_range] }
_ = ⨆ i, u i := by rw [Nat.zero_union_range_succ, iSup_univ]
#align sup_supr_nat_succ sup_iSup_nat_succ
theorem inf_iInf_nat_succ (u : ℕ → α) : (u 0 ⊓ ⨅ i, u (i + 1)) = ⨅ i, u i :=
@sup_iSup_nat_succ αᵒᵈ _ u
#align inf_infi_nat_succ inf_iInf_nat_succ
theorem iInf_nat_gt_zero_eq (f : ℕ → α) : ⨅ i > 0, f i = ⨅ i, f (i + 1) := by
rw [← iInf_range, Nat.range_succ]
simp
#align infi_nat_gt_zero_eq iInf_nat_gt_zero_eq
theorem iSup_nat_gt_zero_eq (f : ℕ → α) : ⨆ i > 0, f i = ⨆ i, f (i + 1) :=
@iInf_nat_gt_zero_eq αᵒᵈ _ f
#align supr_nat_gt_zero_eq iSup_nat_gt_zero_eq
end
section CompleteLinearOrder
variable [CompleteLinearOrder α]
theorem iSup_eq_top (f : ι → α) : iSup f = ⊤ ↔ ∀ b < ⊤, ∃ i, b < f i := by
simp only [← sSup_range, sSup_eq_top, Set.exists_range_iff]
#align supr_eq_top iSup_eq_top
theorem iInf_eq_bot (f : ι → α) : iInf f = ⊥ ↔ ∀ b > ⊥, ∃ i, f i < b := by
simp only [← sInf_range, sInf_eq_bot, Set.exists_range_iff]
#align infi_eq_bot iInf_eq_bot
end CompleteLinearOrder
/-!
### Instances
-/
instance Prop.instCompleteLattice : CompleteLattice Prop where
__ := Prop.instBoundedOrder
__ := Prop.instDistribLattice
sSup s := ∃ a ∈ s, a
le_sSup _ a h p := ⟨a, h, p⟩
sSup_le _ _ h := fun ⟨b, h', p⟩ => h b h' p
sInf s := ∀ a, a ∈ s → a
sInf_le _ a h p := p a h
le_sInf _ _ h p b hb := h b hb p
#align Prop.complete_lattice Prop.instCompleteLattice
noncomputable instance Prop.instCompleteLinearOrder : CompleteLinearOrder Prop where
__ := Prop.instCompleteLattice
__ := Prop.linearOrder
#align Prop.complete_linear_order Prop.instCompleteLinearOrder
@[simp]
theorem sSup_Prop_eq {s : Set Prop} : sSup s = ∃ p ∈ s, p :=
rfl
#align Sup_Prop_eq sSup_Prop_eq
@[simp]
theorem sInf_Prop_eq {s : Set Prop} : sInf s = ∀ p ∈ s, p :=
rfl
#align Inf_Prop_eq sInf_Prop_eq
@[simp]
theorem iSup_Prop_eq {p : ι → Prop} : ⨆ i, p i = ∃ i, p i :=
le_antisymm (fun ⟨_, ⟨i, (eq : p i = _)⟩, hq⟩ => ⟨i, eq.symm ▸ hq⟩) fun ⟨i, hi⟩ =>
⟨p i, ⟨i, rfl⟩, hi⟩
#align supr_Prop_eq iSup_Prop_eq
@[simp]
theorem iInf_Prop_eq {p : ι → Prop} : ⨅ i, p i = ∀ i, p i :=
le_antisymm (fun h i => h _ ⟨i, rfl⟩) fun h _ ⟨i, Eq⟩ => Eq ▸ h i
#align infi_Prop_eq iInf_Prop_eq
instance Pi.supSet {α : Type*} {β : α → Type*} [∀ i, SupSet (β i)] : SupSet (∀ i, β i) :=
⟨fun s i => ⨆ f : s, (f : ∀ i, β i) i⟩
#align pi.has_Sup Pi.supSet
instance Pi.infSet {α : Type*} {β : α → Type*} [∀ i, InfSet (β i)] : InfSet (∀ i, β i) :=
⟨fun s i => ⨅ f : s, (f : ∀ i, β i) i⟩
#align pi.has_Inf Pi.infSet
instance Pi.instCompleteLattice {α : Type*} {β : α → Type*} [∀ i, CompleteLattice (β i)] :
CompleteLattice (∀ i, β i) where
__ := instBoundedOrder
le_sSup s f hf := fun i => le_iSup (fun f : s => (f : ∀ i, β i) i) ⟨f, hf⟩
sInf_le s f hf := fun i => iInf_le (fun f : s => (f : ∀ i, β i) i) ⟨f, hf⟩
sSup_le _ _ hf := fun i => iSup_le fun g => hf g g.2 i
le_sInf _ _ hf := fun i => le_iInf fun g => hf g g.2 i
#align pi.complete_lattice Pi.instCompleteLattice
theorem sSup_apply {α : Type*} {β : α → Type*} [∀ i, SupSet (β i)] {s : Set (∀ a, β a)} {a : α} :
(sSup s) a = ⨆ f : s, (f : ∀ a, β a) a :=
rfl
#align Sup_apply sSup_apply
theorem sInf_apply {α : Type*} {β : α → Type*} [∀ i, InfSet (β i)] {s : Set (∀ a, β a)} {a : α} :
sInf s a = ⨅ f : s, (f : ∀ a, β a) a :=
rfl
#align Inf_apply sInf_apply
@[simp]
theorem iSup_apply {α : Type*} {β : α → Type*} {ι : Sort*} [∀ i, SupSet (β i)] {f : ι → ∀ a, β a}
{a : α} : (⨆ i, f i) a = ⨆ i, f i a := by
rw [iSup, sSup_apply, iSup, iSup, ← image_eq_range (fun f : ∀ i, β i => f a) (range f), ←
range_comp]; rfl
#align supr_apply iSup_apply
@[simp]
theorem iInf_apply {α : Type*} {β : α → Type*} {ι : Sort*} [∀ i, InfSet (β i)] {f : ι → ∀ a, β a}
{a : α} : (⨅ i, f i) a = ⨅ i, f i a :=
@iSup_apply α (fun i => (β i)ᵒᵈ) _ _ _ _
#align infi_apply iInf_apply
theorem unary_relation_sSup_iff {α : Type*} (s : Set (α → Prop)) {a : α} :
sSup s a ↔ ∃ r : α → Prop, r ∈ s ∧ r a := by
rw [sSup_apply]
simp [← eq_iff_iff]
#align unary_relation_Sup_iff unary_relation_sSup_iff
theorem unary_relation_sInf_iff {α : Type*} (s : Set (α → Prop)) {a : α} :
sInf s a ↔ ∀ r : α → Prop, r ∈ s → r a := by
rw [sInf_apply]
simp [← eq_iff_iff]
#align unary_relation_Inf_iff unary_relation_sInf_iff
theorem binary_relation_sSup_iff {α β : Type*} (s : Set (α → β → Prop)) {a : α} {b : β} :
sSup s a b ↔ ∃ r : α → β → Prop, r ∈ s ∧ r a b := by
rw [sSup_apply]
simp [← eq_iff_iff]
#align binary_relation_Sup_iff binary_relation_sSup_iff
| Mathlib/Order/CompleteLattice.lean | 1,782 | 1,785 | theorem binary_relation_sInf_iff {α β : Type*} (s : Set (α → β → Prop)) {a : α} {b : β} :
sInf s a b ↔ ∀ r : α → β → Prop, r ∈ s → r a b := by |
rw [sInf_apply]
simp [← eq_iff_iff]
|
/-
Copyright (c) 2023 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.Deriv.Comp
import Mathlib.Analysis.Calculus.Deriv.Add
import Mathlib.Analysis.Calculus.Deriv.Mul
import Mathlib.Analysis.Calculus.Deriv.Slope
/-!
# Line derivatives
We define the line derivative of a function `f : E → F`, at a point `x : E` along a vector `v : E`,
as the element `f' : F` such that `f (x + t • v) = f x + t • f' + o (t)` as `t` tends to `0` in
the scalar field `𝕜`, if it exists. It is denoted by `lineDeriv 𝕜 f x v`.
This notion is generally less well behaved than the full Fréchet derivative (for instance, the
composition of functions which are line-differentiable is not line-differentiable in general).
The Fréchet derivative should therefore be favored over this one in general, although the line
derivative may sometimes prove handy.
The line derivative in direction `v` is also called the Gateaux derivative in direction `v`,
although the term "Gateaux derivative" is sometimes reserved for the situation where there is
such a derivative in all directions, for the map `v ↦ lineDeriv 𝕜 f x v` (which doesn't have to be
linear in general).
## Main definition and results
We mimic the definitions and statements for the Fréchet derivative and the one-dimensional
derivative. We define in particular the following objects:
* `LineDifferentiableWithinAt 𝕜 f s x v`
* `LineDifferentiableAt 𝕜 f x v`
* `HasLineDerivWithinAt 𝕜 f f' s x v`
* `HasLineDerivAt 𝕜 f s x v`
* `lineDerivWithin 𝕜 f s x v`
* `lineDeriv 𝕜 f x v`
and develop about them a basic API inspired by the one for the Fréchet derivative.
We depart from the Fréchet derivative in two places, as the dependence of the following predicates
on the direction would make them barely usable:
* We do not define an analogue of the predicate `UniqueDiffOn`;
* We do not define `LineDifferentiableOn` nor `LineDifferentiable`.
-/
noncomputable section
open scoped Topology Filter ENNReal NNReal
open Filter Asymptotics Set
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
section Module
/-!
Results that do not rely on a topological structure on `E`
-/
variable (𝕜)
variable {E : Type*} [AddCommGroup E] [Module 𝕜 E]
/-- `f` has the derivative `f'` at the point `x` along the direction `v` in the set `s`.
That is, `f (x + t v) = f x + t • f' + o (t)` when `t` tends to `0` and `x + t v ∈ s`.
Note that this definition is less well behaved than the total Fréchet derivative, which
should generally be favored over this one. -/
def HasLineDerivWithinAt (f : E → F) (f' : F) (s : Set E) (x : E) (v : E) :=
HasDerivWithinAt (fun t ↦ f (x + t • v)) f' ((fun t ↦ x + t • v) ⁻¹' s) (0 : 𝕜)
/-- `f` has the derivative `f'` at the point `x` along the direction `v`.
That is, `f (x + t v) = f x + t • f' + o (t)` when `t` tends to `0`.
Note that this definition is less well behaved than the total Fréchet derivative, which
should generally be favored over this one. -/
def HasLineDerivAt (f : E → F) (f' : F) (x : E) (v : E) :=
HasDerivAt (fun t ↦ f (x + t • v)) f' (0 : 𝕜)
/-- `f` is line-differentiable at the point `x` in the direction `v` in the set `s` if there
exists `f'` such that `f (x + t v) = f x + t • f' + o (t)` when `t` tends to `0` and `x + t v ∈ s`.
-/
def LineDifferentiableWithinAt (f : E → F) (s : Set E) (x : E) (v : E) : Prop :=
DifferentiableWithinAt 𝕜 (fun t ↦ f (x + t • v)) ((fun t ↦ x + t • v) ⁻¹' s) (0 : 𝕜)
/-- `f` is line-differentiable at the point `x` in the direction `v` if there
exists `f'` such that `f (x + t v) = f x + t • f' + o (t)` when `t` tends to `0`. -/
def LineDifferentiableAt (f : E → F) (x : E) (v : E) : Prop :=
DifferentiableAt 𝕜 (fun t ↦ f (x + t • v)) (0 : 𝕜)
/-- Line derivative of `f` at the point `x` in the direction `v` within the set `s`, if it exists.
Zero otherwise.
If the line derivative exists (i.e., `∃ f', HasLineDerivWithinAt 𝕜 f f' s x v`), then
`f (x + t v) = f x + t lineDerivWithin 𝕜 f s x v + o (t)` when `t` tends to `0` and `x + t v ∈ s`.
-/
def lineDerivWithin (f : E → F) (s : Set E) (x : E) (v : E) : F :=
derivWithin (fun t ↦ f (x + t • v)) ((fun t ↦ x + t • v) ⁻¹' s) (0 : 𝕜)
/-- Line derivative of `f` at the point `x` in the direction `v`, if it exists. Zero otherwise.
If the line derivative exists (i.e., `∃ f', HasLineDerivAt 𝕜 f f' x v`), then
`f (x + t v) = f x + t lineDeriv 𝕜 f x v + o (t)` when `t` tends to `0`.
-/
def lineDeriv (f : E → F) (x : E) (v : E) : F :=
deriv (fun t ↦ f (x + t • v)) (0 : 𝕜)
variable {𝕜}
variable {f f₁ : E → F} {f' f₀' f₁' : F} {s t : Set E} {x v : E}
lemma HasLineDerivWithinAt.mono (hf : HasLineDerivWithinAt 𝕜 f f' s x v) (hst : t ⊆ s) :
HasLineDerivWithinAt 𝕜 f f' t x v :=
HasDerivWithinAt.mono hf (preimage_mono hst)
lemma HasLineDerivAt.hasLineDerivWithinAt (hf : HasLineDerivAt 𝕜 f f' x v) (s : Set E) :
HasLineDerivWithinAt 𝕜 f f' s x v :=
HasDerivAt.hasDerivWithinAt hf
lemma HasLineDerivWithinAt.lineDifferentiableWithinAt (hf : HasLineDerivWithinAt 𝕜 f f' s x v) :
LineDifferentiableWithinAt 𝕜 f s x v :=
HasDerivWithinAt.differentiableWithinAt hf
theorem HasLineDerivAt.lineDifferentiableAt (hf : HasLineDerivAt 𝕜 f f' x v) :
LineDifferentiableAt 𝕜 f x v :=
HasDerivAt.differentiableAt hf
theorem LineDifferentiableWithinAt.hasLineDerivWithinAt (h : LineDifferentiableWithinAt 𝕜 f s x v) :
HasLineDerivWithinAt 𝕜 f (lineDerivWithin 𝕜 f s x v) s x v :=
DifferentiableWithinAt.hasDerivWithinAt h
theorem LineDifferentiableAt.hasLineDerivAt (h : LineDifferentiableAt 𝕜 f x v) :
HasLineDerivAt 𝕜 f (lineDeriv 𝕜 f x v) x v :=
DifferentiableAt.hasDerivAt h
@[simp] lemma hasLineDerivWithinAt_univ :
HasLineDerivWithinAt 𝕜 f f' univ x v ↔ HasLineDerivAt 𝕜 f f' x v := by
simp only [HasLineDerivWithinAt, HasLineDerivAt, preimage_univ, hasDerivWithinAt_univ]
theorem lineDerivWithin_zero_of_not_lineDifferentiableWithinAt
(h : ¬LineDifferentiableWithinAt 𝕜 f s x v) :
lineDerivWithin 𝕜 f s x v = 0 :=
derivWithin_zero_of_not_differentiableWithinAt h
theorem lineDeriv_zero_of_not_lineDifferentiableAt (h : ¬LineDifferentiableAt 𝕜 f x v) :
lineDeriv 𝕜 f x v = 0 :=
deriv_zero_of_not_differentiableAt h
theorem hasLineDerivAt_iff_isLittleO_nhds_zero :
HasLineDerivAt 𝕜 f f' x v ↔
(fun t : 𝕜 => f (x + t • v) - f x - t • f') =o[𝓝 0] fun t => t := by
simp only [HasLineDerivAt, hasDerivAt_iff_isLittleO_nhds_zero, zero_add, zero_smul, add_zero]
theorem HasLineDerivAt.unique (h₀ : HasLineDerivAt 𝕜 f f₀' x v) (h₁ : HasLineDerivAt 𝕜 f f₁' x v) :
f₀' = f₁' :=
HasDerivAt.unique h₀ h₁
protected theorem HasLineDerivAt.lineDeriv (h : HasLineDerivAt 𝕜 f f' x v) :
lineDeriv 𝕜 f x v = f' := by
rw [h.unique h.lineDifferentiableAt.hasLineDerivAt]
theorem lineDifferentiableWithinAt_univ :
LineDifferentiableWithinAt 𝕜 f univ x v ↔ LineDifferentiableAt 𝕜 f x v := by
simp only [LineDifferentiableWithinAt, LineDifferentiableAt, preimage_univ,
differentiableWithinAt_univ]
theorem LineDifferentiableAt.lineDifferentiableWithinAt (h : LineDifferentiableAt 𝕜 f x v) :
LineDifferentiableWithinAt 𝕜 f s x v :=
(differentiableWithinAt_univ.2 h).mono (subset_univ _)
@[simp]
theorem lineDerivWithin_univ : lineDerivWithin 𝕜 f univ x v = lineDeriv 𝕜 f x v := by
simp [lineDerivWithin, lineDeriv]
theorem LineDifferentiableWithinAt.mono (h : LineDifferentiableWithinAt 𝕜 f t x v) (st : s ⊆ t) :
LineDifferentiableWithinAt 𝕜 f s x v :=
(h.hasLineDerivWithinAt.mono st).lineDifferentiableWithinAt
theorem HasLineDerivWithinAt.congr_mono (h : HasLineDerivWithinAt 𝕜 f f' s x v) (ht : EqOn f₁ f t)
(hx : f₁ x = f x) (h₁ : t ⊆ s) : HasLineDerivWithinAt 𝕜 f₁ f' t x v :=
HasDerivWithinAt.congr_mono h (fun y hy ↦ ht hy) (by simpa using hx) (preimage_mono h₁)
theorem HasLineDerivWithinAt.congr (h : HasLineDerivWithinAt 𝕜 f f' s x v) (hs : EqOn f₁ f s)
(hx : f₁ x = f x) : HasLineDerivWithinAt 𝕜 f₁ f' s x v :=
h.congr_mono hs hx (Subset.refl _)
theorem HasLineDerivWithinAt.congr' (h : HasLineDerivWithinAt 𝕜 f f' s x v)
(hs : EqOn f₁ f s) (hx : x ∈ s) :
HasLineDerivWithinAt 𝕜 f₁ f' s x v :=
h.congr hs (hs hx)
theorem LineDifferentiableWithinAt.congr_mono (h : LineDifferentiableWithinAt 𝕜 f s x v)
(ht : EqOn f₁ f t) (hx : f₁ x = f x) (h₁ : t ⊆ s) :
LineDifferentiableWithinAt 𝕜 f₁ t x v :=
(HasLineDerivWithinAt.congr_mono h.hasLineDerivWithinAt ht hx h₁).differentiableWithinAt
theorem LineDifferentiableWithinAt.congr (h : LineDifferentiableWithinAt 𝕜 f s x v)
(ht : ∀ x ∈ s, f₁ x = f x) (hx : f₁ x = f x) :
LineDifferentiableWithinAt 𝕜 f₁ s x v :=
LineDifferentiableWithinAt.congr_mono h ht hx (Subset.refl _)
theorem lineDerivWithin_congr (hs : EqOn f₁ f s) (hx : f₁ x = f x) :
lineDerivWithin 𝕜 f₁ s x v = lineDerivWithin 𝕜 f s x v :=
derivWithin_congr (fun y hy ↦ hs hy) (by simpa using hx)
theorem lineDerivWithin_congr' (hs : EqOn f₁ f s) (hx : x ∈ s) :
lineDerivWithin 𝕜 f₁ s x v = lineDerivWithin 𝕜 f s x v :=
lineDerivWithin_congr hs (hs hx)
theorem hasLineDerivAt_iff_tendsto_slope_zero :
HasLineDerivAt 𝕜 f f' x v ↔
Tendsto (fun (t : 𝕜) ↦ t⁻¹ • (f (x + t • v) - f x)) (𝓝[≠] 0) (𝓝 f') := by
simp only [HasLineDerivAt, hasDerivAt_iff_tendsto_slope_zero, zero_add,
zero_smul, add_zero]
alias ⟨HasLineDerivAt.tendsto_slope_zero, _⟩ := hasLineDerivAt_iff_tendsto_slope_zero
theorem HasLineDerivAt.tendsto_slope_zero_right [PartialOrder 𝕜] (h : HasLineDerivAt 𝕜 f f' x v) :
Tendsto (fun (t : 𝕜) ↦ t⁻¹ • (f (x + t • v) - f x)) (𝓝[>] 0) (𝓝 f') :=
h.tendsto_slope_zero.mono_left (nhds_right'_le_nhds_ne 0)
theorem HasLineDerivAt.tendsto_slope_zero_left [PartialOrder 𝕜] (h : HasLineDerivAt 𝕜 f f' x v) :
Tendsto (fun (t : 𝕜) ↦ t⁻¹ • (f (x + t • v) - f x)) (𝓝[<] 0) (𝓝 f') :=
h.tendsto_slope_zero.mono_left (nhds_left'_le_nhds_ne 0)
end Module
section NormedSpace
/-!
Results that need a normed space structure on `E`
-/
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
{f f₀ f₁ : E → F} {f' : F} {s t : Set E} {x v : E} {L : E →L[𝕜] F}
theorem HasLineDerivWithinAt.mono_of_mem
(h : HasLineDerivWithinAt 𝕜 f f' t x v) (hst : t ∈ 𝓝[s] x) :
HasLineDerivWithinAt 𝕜 f f' s x v := by
apply HasDerivWithinAt.mono_of_mem h
apply ContinuousWithinAt.preimage_mem_nhdsWithin'' _ hst (by simp)
apply Continuous.continuousWithinAt; continuity
theorem HasLineDerivWithinAt.hasLineDerivAt
(h : HasLineDerivWithinAt 𝕜 f f' s x v) (hs : s ∈ 𝓝 x) :
HasLineDerivAt 𝕜 f f' x v := by
rw [← hasLineDerivWithinAt_univ]
rw [← nhdsWithin_univ] at hs
exact h.mono_of_mem hs
theorem LineDifferentiableWithinAt.lineDifferentiableAt (h : LineDifferentiableWithinAt 𝕜 f s x v)
(hs : s ∈ 𝓝 x) : LineDifferentiableAt 𝕜 f x v :=
(h.hasLineDerivWithinAt.hasLineDerivAt hs).lineDifferentiableAt
lemma HasFDerivWithinAt.hasLineDerivWithinAt (hf : HasFDerivWithinAt f L s x) (v : E) :
HasLineDerivWithinAt 𝕜 f (L v) s x v := by
let F := fun (t : 𝕜) ↦ x + t • v
rw [show x = F (0 : 𝕜) by simp [F]] at hf
have A : HasDerivWithinAt F (0 + (1 : 𝕜) • v) (F ⁻¹' s) 0 :=
((hasDerivAt_const (0 : 𝕜) x).add ((hasDerivAt_id' (0 : 𝕜)).smul_const v)).hasDerivWithinAt
simp only [one_smul, zero_add] at A
exact hf.comp_hasDerivWithinAt (x := (0 : 𝕜)) A (mapsTo_preimage F s)
lemma HasFDerivAt.hasLineDerivAt (hf : HasFDerivAt f L x) (v : E) :
HasLineDerivAt 𝕜 f (L v) x v := by
rw [← hasLineDerivWithinAt_univ]
exact hf.hasFDerivWithinAt.hasLineDerivWithinAt v
lemma DifferentiableAt.lineDeriv_eq_fderiv (hf : DifferentiableAt 𝕜 f x) :
lineDeriv 𝕜 f x v = fderiv 𝕜 f x v :=
(hf.hasFDerivAt.hasLineDerivAt v).lineDeriv
theorem LineDifferentiableWithinAt.mono_of_mem (h : LineDifferentiableWithinAt 𝕜 f s x v)
(hst : s ∈ 𝓝[t] x) : LineDifferentiableWithinAt 𝕜 f t x v :=
(h.hasLineDerivWithinAt.mono_of_mem hst).lineDifferentiableWithinAt
theorem lineDerivWithin_of_mem_nhds (h : s ∈ 𝓝 x) :
lineDerivWithin 𝕜 f s x v = lineDeriv 𝕜 f x v := by
apply derivWithin_of_mem_nhds
apply (Continuous.continuousAt _).preimage_mem_nhds (by simpa using h)
continuity
theorem lineDerivWithin_of_isOpen (hs : IsOpen s) (hx : x ∈ s) :
lineDerivWithin 𝕜 f s x v = lineDeriv 𝕜 f x v :=
lineDerivWithin_of_mem_nhds (hs.mem_nhds hx)
theorem hasLineDerivWithinAt_congr_set (h : s =ᶠ[𝓝 x] t) :
HasLineDerivWithinAt 𝕜 f f' s x v ↔ HasLineDerivWithinAt 𝕜 f f' t x v := by
apply hasDerivWithinAt_congr_set
let F := fun (t : 𝕜) ↦ x + t • v
have B : ContinuousAt F 0 := by apply Continuous.continuousAt; continuity
have : s =ᶠ[𝓝 (F 0)] t := by convert h; simp [F]
exact B.preimage_mem_nhds this
theorem lineDifferentiableWithinAt_congr_set (h : s =ᶠ[𝓝 x] t) :
LineDifferentiableWithinAt 𝕜 f s x v ↔ LineDifferentiableWithinAt 𝕜 f t x v :=
⟨fun h' ↦ ((hasLineDerivWithinAt_congr_set h).1
h'.hasLineDerivWithinAt).lineDifferentiableWithinAt,
fun h' ↦ ((hasLineDerivWithinAt_congr_set h.symm).1
h'.hasLineDerivWithinAt).lineDifferentiableWithinAt⟩
theorem lineDerivWithin_congr_set (h : s =ᶠ[𝓝 x] t) :
lineDerivWithin 𝕜 f s x v = lineDerivWithin 𝕜 f t x v := by
apply derivWithin_congr_set
let F := fun (t : 𝕜) ↦ x + t • v
have B : ContinuousAt F 0 := by apply Continuous.continuousAt; continuity
have : s =ᶠ[𝓝 (F 0)] t := by convert h; simp [F]
exact B.preimage_mem_nhds this
theorem Filter.EventuallyEq.hasLineDerivAt_iff (h : f₀ =ᶠ[𝓝 x] f₁) :
HasLineDerivAt 𝕜 f₀ f' x v ↔ HasLineDerivAt 𝕜 f₁ f' x v := by
apply hasDerivAt_iff
let F := fun (t : 𝕜) ↦ x + t • v
have B : ContinuousAt F 0 := by apply Continuous.continuousAt; continuity
have : f₀ =ᶠ[𝓝 (F 0)] f₁ := by convert h; simp [F]
exact B.preimage_mem_nhds this
theorem Filter.EventuallyEq.lineDifferentiableAt_iff (h : f₀ =ᶠ[𝓝 x] f₁) :
LineDifferentiableAt 𝕜 f₀ x v ↔ LineDifferentiableAt 𝕜 f₁ x v :=
⟨fun h' ↦ (h.hasLineDerivAt_iff.1 h'.hasLineDerivAt).lineDifferentiableAt,
fun h' ↦ (h.hasLineDerivAt_iff.2 h'.hasLineDerivAt).lineDifferentiableAt⟩
theorem Filter.EventuallyEq.hasLineDerivWithinAt_iff (h : f₀ =ᶠ[𝓝[s] x] f₁) (hx : f₀ x = f₁ x) :
HasLineDerivWithinAt 𝕜 f₀ f' s x v ↔ HasLineDerivWithinAt 𝕜 f₁ f' s x v := by
apply hasDerivWithinAt_iff
· have A : Continuous (fun (t : 𝕜) ↦ x + t • v) := by continuity
exact A.continuousWithinAt.preimage_mem_nhdsWithin'' h (by simp)
· simpa using hx
theorem Filter.EventuallyEq.hasLineDerivWithinAt_iff_of_mem (h : f₀ =ᶠ[𝓝[s] x] f₁) (hx : x ∈ s) :
HasLineDerivWithinAt 𝕜 f₀ f' s x v ↔ HasLineDerivWithinAt 𝕜 f₁ f' s x v :=
h.hasLineDerivWithinAt_iff (h.eq_of_nhdsWithin hx)
theorem Filter.EventuallyEq.lineDifferentiableWithinAt_iff
(h : f₀ =ᶠ[𝓝[s] x] f₁) (hx : f₀ x = f₁ x) :
LineDifferentiableWithinAt 𝕜 f₀ s x v ↔ LineDifferentiableWithinAt 𝕜 f₁ s x v :=
⟨fun h' ↦ ((h.hasLineDerivWithinAt_iff hx).1 h'.hasLineDerivWithinAt).lineDifferentiableWithinAt,
fun h' ↦ ((h.hasLineDerivWithinAt_iff hx).2 h'.hasLineDerivWithinAt).lineDifferentiableWithinAt⟩
theorem Filter.EventuallyEq.lineDifferentiableWithinAt_iff_of_mem
(h : f₀ =ᶠ[𝓝[s] x] f₁) (hx : x ∈ s) :
LineDifferentiableWithinAt 𝕜 f₀ s x v ↔ LineDifferentiableWithinAt 𝕜 f₁ s x v :=
h.lineDifferentiableWithinAt_iff (h.eq_of_nhdsWithin hx)
lemma HasLineDerivWithinAt.congr_of_eventuallyEq (hf : HasLineDerivWithinAt 𝕜 f f' s x v)
(h'f : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : HasLineDerivWithinAt 𝕜 f₁ f' s x v := by
apply HasDerivWithinAt.congr_of_eventuallyEq hf _ (by simp [hx])
have A : Continuous (fun (t : 𝕜) ↦ x + t • v) := by continuity
exact A.continuousWithinAt.preimage_mem_nhdsWithin'' h'f (by simp)
theorem HasLineDerivAt.congr_of_eventuallyEq (h : HasLineDerivAt 𝕜 f f' x v) (h₁ : f₁ =ᶠ[𝓝 x] f) :
HasLineDerivAt 𝕜 f₁ f' x v := by
apply HasDerivAt.congr_of_eventuallyEq h
let F := fun (t : 𝕜) ↦ x + t • v
rw [show x = F 0 by simp [F]] at h₁
exact (Continuous.continuousAt (by continuity)).preimage_mem_nhds h₁
theorem LineDifferentiableWithinAt.congr_of_eventuallyEq (h : LineDifferentiableWithinAt 𝕜 f s x v)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : LineDifferentiableWithinAt 𝕜 f₁ s x v :=
(h.hasLineDerivWithinAt.congr_of_eventuallyEq h₁ hx).differentiableWithinAt
theorem LineDifferentiableAt.congr_of_eventuallyEq
(h : LineDifferentiableAt 𝕜 f x v) (hL : f₁ =ᶠ[𝓝 x] f) :
LineDifferentiableAt 𝕜 f₁ x v := by
apply DifferentiableAt.congr_of_eventuallyEq h
let F := fun (t : 𝕜) ↦ x + t • v
rw [show x = F 0 by simp [F]] at hL
exact (Continuous.continuousAt (by continuity)).preimage_mem_nhds hL
theorem Filter.EventuallyEq.lineDerivWithin_eq (hs : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) :
lineDerivWithin 𝕜 f₁ s x v = lineDerivWithin 𝕜 f s x v := by
apply derivWithin_eq ?_ (by simpa using hx)
have A : Continuous (fun (t : 𝕜) ↦ x + t • v) := by continuity
exact A.continuousWithinAt.preimage_mem_nhdsWithin'' hs (by simp)
theorem Filter.EventuallyEq.lineDerivWithin_eq_nhds (h : f₁ =ᶠ[𝓝 x] f) :
lineDerivWithin 𝕜 f₁ s x v = lineDerivWithin 𝕜 f s x v :=
(h.filter_mono nhdsWithin_le_nhds).lineDerivWithin_eq h.self_of_nhds
theorem Filter.EventuallyEq.lineDeriv_eq (h : f₁ =ᶠ[𝓝 x] f) :
lineDeriv 𝕜 f₁ x v = lineDeriv 𝕜 f x v := by
rw [← lineDerivWithin_univ, ← lineDerivWithin_univ, h.lineDerivWithin_eq_nhds]
/-- Converse to the mean value inequality: if `f` is line differentiable at `x₀` and `C`-lipschitz
on a neighborhood of `x₀` then its line derivative at `x₀` in the direction `v` has norm
bounded by `C * ‖v‖`. This version only assumes that `‖f x - f x₀‖ ≤ C * ‖x - x₀‖` in a
neighborhood of `x`. -/
| Mathlib/Analysis/Calculus/LineDeriv/Basic.lean | 386 | 394 | theorem HasLineDerivAt.le_of_lip' {f : E → F} {f' : F} {x₀ : E} (hf : HasLineDerivAt 𝕜 f f' x₀ v)
{C : ℝ} (hC₀ : 0 ≤ C) (hlip : ∀ᶠ x in 𝓝 x₀, ‖f x - f x₀‖ ≤ C * ‖x - x₀‖) :
‖f'‖ ≤ C * ‖v‖ := by |
apply HasDerivAt.le_of_lip' hf (by positivity)
have A : Continuous (fun (t : 𝕜) ↦ x₀ + t • v) := by continuity
have : ∀ᶠ x in 𝓝 (x₀ + (0 : 𝕜) • v), ‖f x - f x₀‖ ≤ C * ‖x - x₀‖ := by simpa using hlip
filter_upwards [(A.continuousAt (x := 0)).preimage_mem_nhds this] with t ht
simp only [preimage_setOf_eq, add_sub_cancel_left, norm_smul, mem_setOf_eq, mul_comm (‖t‖)] at ht
simpa [mul_assoc] using ht
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Monoid.Unbundled.Pow
import Mathlib.Data.Finset.Fold
import Mathlib.Data.Finset.Option
import Mathlib.Data.Finset.Pi
import Mathlib.Data.Finset.Prod
import Mathlib.Data.Multiset.Lattice
import Mathlib.Data.Set.Lattice
import Mathlib.Order.Hom.Lattice
import Mathlib.Order.Nat
#align_import data.finset.lattice from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Lattice operations on finsets
-/
-- TODO:
-- assert_not_exists OrderedCommMonoid
assert_not_exists MonoidWithZero
open Function Multiset OrderDual
variable {F α β γ ι κ : Type*}
namespace Finset
/-! ### sup -/
section Sup
-- TODO: define with just `[Bot α]` where some lemmas hold without requiring `[OrderBot α]`
variable [SemilatticeSup α] [OrderBot α]
/-- Supremum of a finite set: `sup {a, b, c} f = f a ⊔ f b ⊔ f c` -/
def sup (s : Finset β) (f : β → α) : α :=
s.fold (· ⊔ ·) ⊥ f
#align finset.sup Finset.sup
variable {s s₁ s₂ : Finset β} {f g : β → α} {a : α}
theorem sup_def : s.sup f = (s.1.map f).sup :=
rfl
#align finset.sup_def Finset.sup_def
@[simp]
theorem sup_empty : (∅ : Finset β).sup f = ⊥ :=
fold_empty
#align finset.sup_empty Finset.sup_empty
@[simp]
theorem sup_cons {b : β} (h : b ∉ s) : (cons b s h).sup f = f b ⊔ s.sup f :=
fold_cons h
#align finset.sup_cons Finset.sup_cons
@[simp]
theorem sup_insert [DecidableEq β] {b : β} : (insert b s : Finset β).sup f = f b ⊔ s.sup f :=
fold_insert_idem
#align finset.sup_insert Finset.sup_insert
@[simp]
theorem sup_image [DecidableEq β] (s : Finset γ) (f : γ → β) (g : β → α) :
(s.image f).sup g = s.sup (g ∘ f) :=
fold_image_idem
#align finset.sup_image Finset.sup_image
@[simp]
theorem sup_map (s : Finset γ) (f : γ ↪ β) (g : β → α) : (s.map f).sup g = s.sup (g ∘ f) :=
fold_map
#align finset.sup_map Finset.sup_map
@[simp]
theorem sup_singleton {b : β} : ({b} : Finset β).sup f = f b :=
Multiset.sup_singleton
#align finset.sup_singleton Finset.sup_singleton
theorem sup_sup : s.sup (f ⊔ g) = s.sup f ⊔ s.sup g := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, sup_empty, sup_empty, bot_sup_eq]
| cons _ _ _ ih =>
rw [sup_cons, sup_cons, sup_cons, ih]
exact sup_sup_sup_comm _ _ _ _
#align finset.sup_sup Finset.sup_sup
theorem sup_congr {f g : β → α} (hs : s₁ = s₂) (hfg : ∀ a ∈ s₂, f a = g a) :
s₁.sup f = s₂.sup g := by
subst hs
exact Finset.fold_congr hfg
#align finset.sup_congr Finset.sup_congr
@[simp]
theorem _root_.map_finset_sup [SemilatticeSup β] [OrderBot β]
[FunLike F α β] [SupBotHomClass F α β]
(f : F) (s : Finset ι) (g : ι → α) : f (s.sup g) = s.sup (f ∘ g) :=
Finset.cons_induction_on s (map_bot f) fun i s _ h => by
rw [sup_cons, sup_cons, map_sup, h, Function.comp_apply]
#align map_finset_sup map_finset_sup
@[simp]
protected theorem sup_le_iff {a : α} : s.sup f ≤ a ↔ ∀ b ∈ s, f b ≤ a := by
apply Iff.trans Multiset.sup_le
simp only [Multiset.mem_map, and_imp, exists_imp]
exact ⟨fun k b hb => k _ _ hb rfl, fun k a' b hb h => h ▸ k _ hb⟩
#align finset.sup_le_iff Finset.sup_le_iff
protected alias ⟨_, sup_le⟩ := Finset.sup_le_iff
#align finset.sup_le Finset.sup_le
theorem sup_const_le : (s.sup fun _ => a) ≤ a :=
Finset.sup_le fun _ _ => le_rfl
#align finset.sup_const_le Finset.sup_const_le
theorem le_sup {b : β} (hb : b ∈ s) : f b ≤ s.sup f :=
Finset.sup_le_iff.1 le_rfl _ hb
#align finset.le_sup Finset.le_sup
theorem le_sup_of_le {b : β} (hb : b ∈ s) (h : a ≤ f b) : a ≤ s.sup f := h.trans <| le_sup hb
#align finset.le_sup_of_le Finset.le_sup_of_le
theorem sup_union [DecidableEq β] : (s₁ ∪ s₂).sup f = s₁.sup f ⊔ s₂.sup f :=
eq_of_forall_ge_iff fun c => by simp [or_imp, forall_and]
#align finset.sup_union Finset.sup_union
@[simp]
theorem sup_biUnion [DecidableEq β] (s : Finset γ) (t : γ → Finset β) :
(s.biUnion t).sup f = s.sup fun x => (t x).sup f :=
eq_of_forall_ge_iff fun c => by simp [@forall_swap _ β]
#align finset.sup_bUnion Finset.sup_biUnion
theorem sup_const {s : Finset β} (h : s.Nonempty) (c : α) : (s.sup fun _ => c) = c :=
eq_of_forall_ge_iff (fun _ => Finset.sup_le_iff.trans h.forall_const)
#align finset.sup_const Finset.sup_const
@[simp]
theorem sup_bot (s : Finset β) : (s.sup fun _ => ⊥) = (⊥ : α) := by
obtain rfl | hs := s.eq_empty_or_nonempty
· exact sup_empty
· exact sup_const hs _
#align finset.sup_bot Finset.sup_bot
theorem sup_ite (p : β → Prop) [DecidablePred p] :
(s.sup fun i => ite (p i) (f i) (g i)) = (s.filter p).sup f ⊔ (s.filter fun i => ¬p i).sup g :=
fold_ite _
#align finset.sup_ite Finset.sup_ite
theorem sup_mono_fun {g : β → α} (h : ∀ b ∈ s, f b ≤ g b) : s.sup f ≤ s.sup g :=
Finset.sup_le fun b hb => le_trans (h b hb) (le_sup hb)
#align finset.sup_mono_fun Finset.sup_mono_fun
@[gcongr]
theorem sup_mono (h : s₁ ⊆ s₂) : s₁.sup f ≤ s₂.sup f :=
Finset.sup_le (fun _ hb => le_sup (h hb))
#align finset.sup_mono Finset.sup_mono
protected theorem sup_comm (s : Finset β) (t : Finset γ) (f : β → γ → α) :
(s.sup fun b => t.sup (f b)) = t.sup fun c => s.sup fun b => f b c :=
eq_of_forall_ge_iff fun a => by simpa using forall₂_swap
#align finset.sup_comm Finset.sup_comm
@[simp, nolint simpNF] -- Porting note: linter claims that LHS does not simplify
theorem sup_attach (s : Finset β) (f : β → α) : (s.attach.sup fun x => f x) = s.sup f :=
(s.attach.sup_map (Function.Embedding.subtype _) f).symm.trans <| congr_arg _ attach_map_val
#align finset.sup_attach Finset.sup_attach
/-- See also `Finset.product_biUnion`. -/
theorem sup_product_left (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).sup f = s.sup fun i => t.sup fun i' => f ⟨i, i'⟩ :=
eq_of_forall_ge_iff fun a => by simp [@forall_swap _ γ]
#align finset.sup_product_left Finset.sup_product_left
theorem sup_product_right (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).sup f = t.sup fun i' => s.sup fun i => f ⟨i, i'⟩ := by
rw [sup_product_left, Finset.sup_comm]
#align finset.sup_product_right Finset.sup_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeSup α] [SemilatticeSup β] [OrderBot α] [OrderBot β]
{s : Finset ι} {t : Finset κ}
@[simp] lemma sup_prodMap (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
sup (s ×ˢ t) (Prod.map f g) = (sup s f, sup t g) :=
eq_of_forall_ge_iff fun i ↦ by
obtain ⟨a, ha⟩ := hs
obtain ⟨b, hb⟩ := ht
simp only [Prod.map, Finset.sup_le_iff, mem_product, and_imp, Prod.forall, Prod.le_def]
exact ⟨fun h ↦ ⟨fun i hi ↦ (h _ _ hi hb).1, fun j hj ↦ (h _ _ ha hj).2⟩, by aesop⟩
end Prod
@[simp]
theorem sup_erase_bot [DecidableEq α] (s : Finset α) : (s.erase ⊥).sup id = s.sup id := by
refine (sup_mono (s.erase_subset _)).antisymm (Finset.sup_le_iff.2 fun a ha => ?_)
obtain rfl | ha' := eq_or_ne a ⊥
· exact bot_le
· exact le_sup (mem_erase.2 ⟨ha', ha⟩)
#align finset.sup_erase_bot Finset.sup_erase_bot
theorem sup_sdiff_right {α β : Type*} [GeneralizedBooleanAlgebra α] (s : Finset β) (f : β → α)
(a : α) : (s.sup fun b => f b \ a) = s.sup f \ a := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, sup_empty, bot_sdiff]
| cons _ _ _ h => rw [sup_cons, sup_cons, h, sup_sdiff]
#align finset.sup_sdiff_right Finset.sup_sdiff_right
theorem comp_sup_eq_sup_comp [SemilatticeSup γ] [OrderBot γ] {s : Finset β} {f : β → α} (g : α → γ)
(g_sup : ∀ x y, g (x ⊔ y) = g x ⊔ g y) (bot : g ⊥ = ⊥) : g (s.sup f) = s.sup (g ∘ f) :=
Finset.cons_induction_on s bot fun c t hc ih => by
rw [sup_cons, sup_cons, g_sup, ih, Function.comp_apply]
#align finset.comp_sup_eq_sup_comp Finset.comp_sup_eq_sup_comp
/-- Computing `sup` in a subtype (closed under `sup`) is the same as computing it in `α`. -/
theorem sup_coe {P : α → Prop} {Pbot : P ⊥} {Psup : ∀ ⦃x y⦄, P x → P y → P (x ⊔ y)} (t : Finset β)
(f : β → { x : α // P x }) :
(@sup { x // P x } _ (Subtype.semilatticeSup Psup) (Subtype.orderBot Pbot) t f : α) =
t.sup fun x => ↑(f x) := by
letI := Subtype.semilatticeSup Psup
letI := Subtype.orderBot Pbot
apply comp_sup_eq_sup_comp Subtype.val <;> intros <;> rfl
#align finset.sup_coe Finset.sup_coe
@[simp]
theorem sup_toFinset {α β} [DecidableEq β] (s : Finset α) (f : α → Multiset β) :
(s.sup f).toFinset = s.sup fun x => (f x).toFinset :=
comp_sup_eq_sup_comp Multiset.toFinset toFinset_union rfl
#align finset.sup_to_finset Finset.sup_toFinset
theorem _root_.List.foldr_sup_eq_sup_toFinset [DecidableEq α] (l : List α) :
l.foldr (· ⊔ ·) ⊥ = l.toFinset.sup id := by
rw [← coe_fold_r, ← Multiset.fold_dedup_idem, sup_def, ← List.toFinset_coe, toFinset_val,
Multiset.map_id]
rfl
#align list.foldr_sup_eq_sup_to_finset List.foldr_sup_eq_sup_toFinset
theorem subset_range_sup_succ (s : Finset ℕ) : s ⊆ range (s.sup id).succ := fun _ hn =>
mem_range.2 <| Nat.lt_succ_of_le <| @le_sup _ _ _ _ _ id _ hn
#align finset.subset_range_sup_succ Finset.subset_range_sup_succ
theorem exists_nat_subset_range (s : Finset ℕ) : ∃ n : ℕ, s ⊆ range n :=
⟨_, s.subset_range_sup_succ⟩
#align finset.exists_nat_subset_range Finset.exists_nat_subset_range
theorem sup_induction {p : α → Prop} (hb : p ⊥) (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊔ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.sup f) := by
induction s using Finset.cons_induction with
| empty => exact hb
| cons _ _ _ ih =>
simp only [sup_cons, forall_mem_cons] at hs ⊢
exact hp _ hs.1 _ (ih hs.2)
#align finset.sup_induction Finset.sup_induction
theorem sup_le_of_le_directed {α : Type*} [SemilatticeSup α] [OrderBot α] (s : Set α)
(hs : s.Nonempty) (hdir : DirectedOn (· ≤ ·) s) (t : Finset α) :
(∀ x ∈ t, ∃ y ∈ s, x ≤ y) → ∃ x ∈ s, t.sup id ≤ x := by
classical
induction' t using Finset.induction_on with a r _ ih h
· simpa only [forall_prop_of_true, and_true_iff, forall_prop_of_false, bot_le, not_false_iff,
sup_empty, forall_true_iff, not_mem_empty]
· intro h
have incs : (r : Set α) ⊆ ↑(insert a r) := by
rw [Finset.coe_subset]
apply Finset.subset_insert
-- x ∈ s is above the sup of r
obtain ⟨x, ⟨hxs, hsx_sup⟩⟩ := ih fun x hx => h x <| incs hx
-- y ∈ s is above a
obtain ⟨y, hys, hay⟩ := h a (Finset.mem_insert_self a r)
-- z ∈ s is above x and y
obtain ⟨z, hzs, ⟨hxz, hyz⟩⟩ := hdir x hxs y hys
use z, hzs
rw [sup_insert, id, sup_le_iff]
exact ⟨le_trans hay hyz, le_trans hsx_sup hxz⟩
#align finset.sup_le_of_le_directed Finset.sup_le_of_le_directed
-- If we acquire sublattices
-- the hypotheses should be reformulated as `s : SubsemilatticeSupBot`
theorem sup_mem (s : Set α) (w₁ : ⊥ ∈ s) (w₂ : ∀ᵉ (x ∈ s) (y ∈ s), x ⊔ y ∈ s)
{ι : Type*} (t : Finset ι) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.sup p ∈ s :=
@sup_induction _ _ _ _ _ _ (· ∈ s) w₁ w₂ h
#align finset.sup_mem Finset.sup_mem
@[simp]
protected theorem sup_eq_bot_iff (f : β → α) (S : Finset β) : S.sup f = ⊥ ↔ ∀ s ∈ S, f s = ⊥ := by
classical induction' S using Finset.induction with a S _ hi <;> simp [*]
#align finset.sup_eq_bot_iff Finset.sup_eq_bot_iff
end Sup
theorem sup_eq_iSup [CompleteLattice β] (s : Finset α) (f : α → β) : s.sup f = ⨆ a ∈ s, f a :=
le_antisymm
(Finset.sup_le (fun a ha => le_iSup_of_le a <| le_iSup (fun _ => f a) ha))
(iSup_le fun _ => iSup_le fun ha => le_sup ha)
#align finset.sup_eq_supr Finset.sup_eq_iSup
theorem sup_id_eq_sSup [CompleteLattice α] (s : Finset α) : s.sup id = sSup s := by
simp [sSup_eq_iSup, sup_eq_iSup]
#align finset.sup_id_eq_Sup Finset.sup_id_eq_sSup
theorem sup_id_set_eq_sUnion (s : Finset (Set α)) : s.sup id = ⋃₀ ↑s :=
sup_id_eq_sSup _
#align finset.sup_id_set_eq_sUnion Finset.sup_id_set_eq_sUnion
@[simp]
theorem sup_set_eq_biUnion (s : Finset α) (f : α → Set β) : s.sup f = ⋃ x ∈ s, f x :=
sup_eq_iSup _ _
#align finset.sup_set_eq_bUnion Finset.sup_set_eq_biUnion
theorem sup_eq_sSup_image [CompleteLattice β] (s : Finset α) (f : α → β) :
s.sup f = sSup (f '' s) := by
classical rw [← Finset.coe_image, ← sup_id_eq_sSup, sup_image, Function.id_comp]
#align finset.sup_eq_Sup_image Finset.sup_eq_sSup_image
/-! ### inf -/
section Inf
-- TODO: define with just `[Top α]` where some lemmas hold without requiring `[OrderTop α]`
variable [SemilatticeInf α] [OrderTop α]
/-- Infimum of a finite set: `inf {a, b, c} f = f a ⊓ f b ⊓ f c` -/
def inf (s : Finset β) (f : β → α) : α :=
s.fold (· ⊓ ·) ⊤ f
#align finset.inf Finset.inf
variable {s s₁ s₂ : Finset β} {f g : β → α} {a : α}
theorem inf_def : s.inf f = (s.1.map f).inf :=
rfl
#align finset.inf_def Finset.inf_def
@[simp]
theorem inf_empty : (∅ : Finset β).inf f = ⊤ :=
fold_empty
#align finset.inf_empty Finset.inf_empty
@[simp]
theorem inf_cons {b : β} (h : b ∉ s) : (cons b s h).inf f = f b ⊓ s.inf f :=
@sup_cons αᵒᵈ _ _ _ _ _ _ h
#align finset.inf_cons Finset.inf_cons
@[simp]
theorem inf_insert [DecidableEq β] {b : β} : (insert b s : Finset β).inf f = f b ⊓ s.inf f :=
fold_insert_idem
#align finset.inf_insert Finset.inf_insert
@[simp]
theorem inf_image [DecidableEq β] (s : Finset γ) (f : γ → β) (g : β → α) :
(s.image f).inf g = s.inf (g ∘ f) :=
fold_image_idem
#align finset.inf_image Finset.inf_image
@[simp]
theorem inf_map (s : Finset γ) (f : γ ↪ β) (g : β → α) : (s.map f).inf g = s.inf (g ∘ f) :=
fold_map
#align finset.inf_map Finset.inf_map
@[simp]
theorem inf_singleton {b : β} : ({b} : Finset β).inf f = f b :=
Multiset.inf_singleton
#align finset.inf_singleton Finset.inf_singleton
theorem inf_inf : s.inf (f ⊓ g) = s.inf f ⊓ s.inf g :=
@sup_sup αᵒᵈ _ _ _ _ _ _
#align finset.inf_inf Finset.inf_inf
theorem inf_congr {f g : β → α} (hs : s₁ = s₂) (hfg : ∀ a ∈ s₂, f a = g a) :
s₁.inf f = s₂.inf g := by
subst hs
exact Finset.fold_congr hfg
#align finset.inf_congr Finset.inf_congr
@[simp]
theorem _root_.map_finset_inf [SemilatticeInf β] [OrderTop β]
[FunLike F α β] [InfTopHomClass F α β]
(f : F) (s : Finset ι) (g : ι → α) : f (s.inf g) = s.inf (f ∘ g) :=
Finset.cons_induction_on s (map_top f) fun i s _ h => by
rw [inf_cons, inf_cons, map_inf, h, Function.comp_apply]
#align map_finset_inf map_finset_inf
@[simp] protected theorem le_inf_iff {a : α} : a ≤ s.inf f ↔ ∀ b ∈ s, a ≤ f b :=
@Finset.sup_le_iff αᵒᵈ _ _ _ _ _ _
#align finset.le_inf_iff Finset.le_inf_iff
protected alias ⟨_, le_inf⟩ := Finset.le_inf_iff
#align finset.le_inf Finset.le_inf
theorem le_inf_const_le : a ≤ s.inf fun _ => a :=
Finset.le_inf fun _ _ => le_rfl
#align finset.le_inf_const_le Finset.le_inf_const_le
theorem inf_le {b : β} (hb : b ∈ s) : s.inf f ≤ f b :=
Finset.le_inf_iff.1 le_rfl _ hb
#align finset.inf_le Finset.inf_le
theorem inf_le_of_le {b : β} (hb : b ∈ s) (h : f b ≤ a) : s.inf f ≤ a := (inf_le hb).trans h
#align finset.inf_le_of_le Finset.inf_le_of_le
theorem inf_union [DecidableEq β] : (s₁ ∪ s₂).inf f = s₁.inf f ⊓ s₂.inf f :=
eq_of_forall_le_iff fun c ↦ by simp [or_imp, forall_and]
#align finset.inf_union Finset.inf_union
@[simp] theorem inf_biUnion [DecidableEq β] (s : Finset γ) (t : γ → Finset β) :
(s.biUnion t).inf f = s.inf fun x => (t x).inf f :=
@sup_biUnion αᵒᵈ _ _ _ _ _ _ _ _
#align finset.inf_bUnion Finset.inf_biUnion
theorem inf_const (h : s.Nonempty) (c : α) : (s.inf fun _ => c) = c := @sup_const αᵒᵈ _ _ _ _ h _
#align finset.inf_const Finset.inf_const
@[simp] theorem inf_top (s : Finset β) : (s.inf fun _ => ⊤) = (⊤ : α) := @sup_bot αᵒᵈ _ _ _ _
#align finset.inf_top Finset.inf_top
theorem inf_ite (p : β → Prop) [DecidablePred p] :
(s.inf fun i ↦ ite (p i) (f i) (g i)) = (s.filter p).inf f ⊓ (s.filter fun i ↦ ¬ p i).inf g :=
fold_ite _
theorem inf_mono_fun {g : β → α} (h : ∀ b ∈ s, f b ≤ g b) : s.inf f ≤ s.inf g :=
Finset.le_inf fun b hb => le_trans (inf_le hb) (h b hb)
#align finset.inf_mono_fun Finset.inf_mono_fun
@[gcongr]
theorem inf_mono (h : s₁ ⊆ s₂) : s₂.inf f ≤ s₁.inf f :=
Finset.le_inf (fun _ hb => inf_le (h hb))
#align finset.inf_mono Finset.inf_mono
protected theorem inf_comm (s : Finset β) (t : Finset γ) (f : β → γ → α) :
(s.inf fun b => t.inf (f b)) = t.inf fun c => s.inf fun b => f b c :=
@Finset.sup_comm αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_comm Finset.inf_comm
theorem inf_attach (s : Finset β) (f : β → α) : (s.attach.inf fun x => f x) = s.inf f :=
@sup_attach αᵒᵈ _ _ _ _ _
#align finset.inf_attach Finset.inf_attach
theorem inf_product_left (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).inf f = s.inf fun i => t.inf fun i' => f ⟨i, i'⟩ :=
@sup_product_left αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_product_left Finset.inf_product_left
theorem inf_product_right (s : Finset β) (t : Finset γ) (f : β × γ → α) :
(s ×ˢ t).inf f = t.inf fun i' => s.inf fun i => f ⟨i, i'⟩ :=
@sup_product_right αᵒᵈ _ _ _ _ _ _ _
#align finset.inf_product_right Finset.inf_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeInf α] [SemilatticeInf β] [OrderTop α] [OrderTop β]
{s : Finset ι} {t : Finset κ}
@[simp] lemma inf_prodMap (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
inf (s ×ˢ t) (Prod.map f g) = (inf s f, inf t g) :=
sup_prodMap (α := αᵒᵈ) (β := βᵒᵈ) hs ht _ _
end Prod
@[simp]
theorem inf_erase_top [DecidableEq α] (s : Finset α) : (s.erase ⊤).inf id = s.inf id :=
@sup_erase_bot αᵒᵈ _ _ _ _
#align finset.inf_erase_top Finset.inf_erase_top
theorem comp_inf_eq_inf_comp [SemilatticeInf γ] [OrderTop γ] {s : Finset β} {f : β → α} (g : α → γ)
(g_inf : ∀ x y, g (x ⊓ y) = g x ⊓ g y) (top : g ⊤ = ⊤) : g (s.inf f) = s.inf (g ∘ f) :=
@comp_sup_eq_sup_comp αᵒᵈ _ γᵒᵈ _ _ _ _ _ _ _ g_inf top
#align finset.comp_inf_eq_inf_comp Finset.comp_inf_eq_inf_comp
/-- Computing `inf` in a subtype (closed under `inf`) is the same as computing it in `α`. -/
theorem inf_coe {P : α → Prop} {Ptop : P ⊤} {Pinf : ∀ ⦃x y⦄, P x → P y → P (x ⊓ y)} (t : Finset β)
(f : β → { x : α // P x }) :
(@inf { x // P x } _ (Subtype.semilatticeInf Pinf) (Subtype.orderTop Ptop) t f : α) =
t.inf fun x => ↑(f x) :=
@sup_coe αᵒᵈ _ _ _ _ Ptop Pinf t f
#align finset.inf_coe Finset.inf_coe
theorem _root_.List.foldr_inf_eq_inf_toFinset [DecidableEq α] (l : List α) :
l.foldr (· ⊓ ·) ⊤ = l.toFinset.inf id := by
rw [← coe_fold_r, ← Multiset.fold_dedup_idem, inf_def, ← List.toFinset_coe, toFinset_val,
Multiset.map_id]
rfl
#align list.foldr_inf_eq_inf_to_finset List.foldr_inf_eq_inf_toFinset
theorem inf_induction {p : α → Prop} (ht : p ⊤) (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊓ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.inf f) :=
@sup_induction αᵒᵈ _ _ _ _ _ _ ht hp hs
#align finset.inf_induction Finset.inf_induction
theorem inf_mem (s : Set α) (w₁ : ⊤ ∈ s) (w₂ : ∀ᵉ (x ∈ s) (y ∈ s), x ⊓ y ∈ s)
{ι : Type*} (t : Finset ι) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.inf p ∈ s :=
@inf_induction _ _ _ _ _ _ (· ∈ s) w₁ w₂ h
#align finset.inf_mem Finset.inf_mem
@[simp]
protected theorem inf_eq_top_iff (f : β → α) (S : Finset β) : S.inf f = ⊤ ↔ ∀ s ∈ S, f s = ⊤ :=
@Finset.sup_eq_bot_iff αᵒᵈ _ _ _ _ _
#align finset.inf_eq_top_iff Finset.inf_eq_top_iff
end Inf
@[simp]
theorem toDual_sup [SemilatticeSup α] [OrderBot α] (s : Finset β) (f : β → α) :
toDual (s.sup f) = s.inf (toDual ∘ f) :=
rfl
#align finset.to_dual_sup Finset.toDual_sup
@[simp]
theorem toDual_inf [SemilatticeInf α] [OrderTop α] (s : Finset β) (f : β → α) :
toDual (s.inf f) = s.sup (toDual ∘ f) :=
rfl
#align finset.to_dual_inf Finset.toDual_inf
@[simp]
theorem ofDual_sup [SemilatticeInf α] [OrderTop α] (s : Finset β) (f : β → αᵒᵈ) :
ofDual (s.sup f) = s.inf (ofDual ∘ f) :=
rfl
#align finset.of_dual_sup Finset.ofDual_sup
@[simp]
theorem ofDual_inf [SemilatticeSup α] [OrderBot α] (s : Finset β) (f : β → αᵒᵈ) :
ofDual (s.inf f) = s.sup (ofDual ∘ f) :=
rfl
#align finset.of_dual_inf Finset.ofDual_inf
section DistribLattice
variable [DistribLattice α]
section OrderBot
variable [OrderBot α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α} {a : α}
theorem sup_inf_distrib_left (s : Finset ι) (f : ι → α) (a : α) :
a ⊓ s.sup f = s.sup fun i => a ⊓ f i := by
induction s using Finset.cons_induction with
| empty => simp_rw [Finset.sup_empty, inf_bot_eq]
| cons _ _ _ h => rw [sup_cons, sup_cons, inf_sup_left, h]
#align finset.sup_inf_distrib_left Finset.sup_inf_distrib_left
theorem sup_inf_distrib_right (s : Finset ι) (f : ι → α) (a : α) :
s.sup f ⊓ a = s.sup fun i => f i ⊓ a := by
rw [_root_.inf_comm, s.sup_inf_distrib_left]
simp_rw [_root_.inf_comm]
#align finset.sup_inf_distrib_right Finset.sup_inf_distrib_right
protected theorem disjoint_sup_right : Disjoint a (s.sup f) ↔ ∀ ⦃i⦄, i ∈ s → Disjoint a (f i) := by
simp only [disjoint_iff, sup_inf_distrib_left, Finset.sup_eq_bot_iff]
#align finset.disjoint_sup_right Finset.disjoint_sup_right
protected theorem disjoint_sup_left : Disjoint (s.sup f) a ↔ ∀ ⦃i⦄, i ∈ s → Disjoint (f i) a := by
simp only [disjoint_iff, sup_inf_distrib_right, Finset.sup_eq_bot_iff]
#align finset.disjoint_sup_left Finset.disjoint_sup_left
theorem sup_inf_sup (s : Finset ι) (t : Finset κ) (f : ι → α) (g : κ → α) :
s.sup f ⊓ t.sup g = (s ×ˢ t).sup fun i => f i.1 ⊓ g i.2 := by
simp_rw [Finset.sup_inf_distrib_right, Finset.sup_inf_distrib_left, sup_product_left]
#align finset.sup_inf_sup Finset.sup_inf_sup
end OrderBot
section OrderTop
variable [OrderTop α] {f : ι → α} {g : κ → α} {s : Finset ι} {t : Finset κ} {a : α}
theorem inf_sup_distrib_left (s : Finset ι) (f : ι → α) (a : α) :
a ⊔ s.inf f = s.inf fun i => a ⊔ f i :=
@sup_inf_distrib_left αᵒᵈ _ _ _ _ _ _
#align finset.inf_sup_distrib_left Finset.inf_sup_distrib_left
theorem inf_sup_distrib_right (s : Finset ι) (f : ι → α) (a : α) :
s.inf f ⊔ a = s.inf fun i => f i ⊔ a :=
@sup_inf_distrib_right αᵒᵈ _ _ _ _ _ _
#align finset.inf_sup_distrib_right Finset.inf_sup_distrib_right
protected theorem codisjoint_inf_right :
Codisjoint a (s.inf f) ↔ ∀ ⦃i⦄, i ∈ s → Codisjoint a (f i) :=
@Finset.disjoint_sup_right αᵒᵈ _ _ _ _ _ _
#align finset.codisjoint_inf_right Finset.codisjoint_inf_right
protected theorem codisjoint_inf_left :
Codisjoint (s.inf f) a ↔ ∀ ⦃i⦄, i ∈ s → Codisjoint (f i) a :=
@Finset.disjoint_sup_left αᵒᵈ _ _ _ _ _ _
#align finset.codisjoint_inf_left Finset.codisjoint_inf_left
theorem inf_sup_inf (s : Finset ι) (t : Finset κ) (f : ι → α) (g : κ → α) :
s.inf f ⊔ t.inf g = (s ×ˢ t).inf fun i => f i.1 ⊔ g i.2 :=
@sup_inf_sup αᵒᵈ _ _ _ _ _ _ _ _
#align finset.inf_sup_inf Finset.inf_sup_inf
end OrderTop
section BoundedOrder
variable [BoundedOrder α] [DecidableEq ι]
--TODO: Extract out the obvious isomorphism `(insert i s).pi t ≃ t i ×ˢ s.pi t` from this proof
theorem inf_sup {κ : ι → Type*} (s : Finset ι) (t : ∀ i, Finset (κ i)) (f : ∀ i, κ i → α) :
(s.inf fun i => (t i).sup (f i)) =
(s.pi t).sup fun g => s.attach.inf fun i => f _ <| g _ i.2 := by
induction' s using Finset.induction with i s hi ih
· simp
rw [inf_insert, ih, attach_insert, sup_inf_sup]
refine eq_of_forall_ge_iff fun c => ?_
simp only [Finset.sup_le_iff, mem_product, mem_pi, and_imp, Prod.forall,
inf_insert, inf_image]
refine
⟨fun h g hg =>
h (g i <| mem_insert_self _ _) (fun j hj => g j <| mem_insert_of_mem hj)
(hg _ <| mem_insert_self _ _) fun j hj => hg _ <| mem_insert_of_mem hj,
fun h a g ha hg => ?_⟩
-- TODO: This `have` must be named to prevent it being shadowed by the internal `this` in `simpa`
have aux : ∀ j : { x // x ∈ s }, ↑j ≠ i := fun j : s => ne_of_mem_of_not_mem j.2 hi
-- Porting note: `simpa` doesn't support placeholders in proof terms
have := h (fun j hj => if hji : j = i then cast (congr_arg κ hji.symm) a
else g _ <| mem_of_mem_insert_of_ne hj hji) (fun j hj => ?_)
· simpa only [cast_eq, dif_pos, Function.comp, Subtype.coe_mk, dif_neg, aux] using this
rw [mem_insert] at hj
obtain (rfl | hj) := hj
· simpa
· simpa [ne_of_mem_of_not_mem hj hi] using hg _ _
#align finset.inf_sup Finset.inf_sup
theorem sup_inf {κ : ι → Type*} (s : Finset ι) (t : ∀ i, Finset (κ i)) (f : ∀ i, κ i → α) :
(s.sup fun i => (t i).inf (f i)) = (s.pi t).inf fun g => s.attach.sup fun i => f _ <| g _ i.2 :=
@inf_sup αᵒᵈ _ _ _ _ _ _ _ _
#align finset.sup_inf Finset.sup_inf
end BoundedOrder
end DistribLattice
section BooleanAlgebra
variable [BooleanAlgebra α] {s : Finset ι}
theorem sup_sdiff_left (s : Finset ι) (f : ι → α) (a : α) :
(s.sup fun b => a \ f b) = a \ s.inf f := by
induction s using Finset.cons_induction with
| empty => rw [sup_empty, inf_empty, sdiff_top]
| cons _ _ _ h => rw [sup_cons, inf_cons, h, sdiff_inf]
#align finset.sup_sdiff_left Finset.sup_sdiff_left
theorem inf_sdiff_left (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.inf fun b => a \ f b) = a \ s.sup f := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => rw [sup_singleton, inf_singleton]
| cons _ _ _ _ ih => rw [sup_cons, inf_cons, ih, sdiff_sup]
#align finset.inf_sdiff_left Finset.inf_sdiff_left
theorem inf_sdiff_right (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.inf fun b => f b \ a) = s.inf f \ a := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => rw [inf_singleton, inf_singleton]
| cons _ _ _ _ ih => rw [inf_cons, inf_cons, ih, inf_sdiff]
#align finset.inf_sdiff_right Finset.inf_sdiff_right
theorem inf_himp_right (s : Finset ι) (f : ι → α) (a : α) :
(s.inf fun b => f b ⇨ a) = s.sup f ⇨ a :=
@sup_sdiff_left αᵒᵈ _ _ _ _ _
#align finset.inf_himp_right Finset.inf_himp_right
theorem sup_himp_right (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.sup fun b => f b ⇨ a) = s.inf f ⇨ a :=
@inf_sdiff_left αᵒᵈ _ _ _ hs _ _
#align finset.sup_himp_right Finset.sup_himp_right
theorem sup_himp_left (hs : s.Nonempty) (f : ι → α) (a : α) :
(s.sup fun b => a ⇨ f b) = a ⇨ s.sup f :=
@inf_sdiff_right αᵒᵈ _ _ _ hs _ _
#align finset.sup_himp_left Finset.sup_himp_left
@[simp]
protected theorem compl_sup (s : Finset ι) (f : ι → α) : (s.sup f)ᶜ = s.inf fun i => (f i)ᶜ :=
map_finset_sup (OrderIso.compl α) _ _
#align finset.compl_sup Finset.compl_sup
@[simp]
protected theorem compl_inf (s : Finset ι) (f : ι → α) : (s.inf f)ᶜ = s.sup fun i => (f i)ᶜ :=
map_finset_inf (OrderIso.compl α) _ _
#align finset.compl_inf Finset.compl_inf
end BooleanAlgebra
section LinearOrder
variable [LinearOrder α]
section OrderBot
variable [OrderBot α] {s : Finset ι} {f : ι → α} {a : α}
theorem comp_sup_eq_sup_comp_of_is_total [SemilatticeSup β] [OrderBot β] (g : α → β)
(mono_g : Monotone g) (bot : g ⊥ = ⊥) : g (s.sup f) = s.sup (g ∘ f) :=
comp_sup_eq_sup_comp g mono_g.map_sup bot
#align finset.comp_sup_eq_sup_comp_of_is_total Finset.comp_sup_eq_sup_comp_of_is_total
@[simp]
protected theorem le_sup_iff (ha : ⊥ < a) : a ≤ s.sup f ↔ ∃ b ∈ s, a ≤ f b := by
apply Iff.intro
· induction s using cons_induction with
| empty => exact (absurd · (not_le_of_lt ha))
| cons c t hc ih =>
rw [sup_cons, le_sup_iff]
exact fun
| Or.inl h => ⟨c, mem_cons.2 (Or.inl rfl), h⟩
| Or.inr h => let ⟨b, hb, hle⟩ := ih h; ⟨b, mem_cons.2 (Or.inr hb), hle⟩
· exact fun ⟨b, hb, hle⟩ => le_trans hle (le_sup hb)
#align finset.le_sup_iff Finset.le_sup_iff
@[simp]
protected theorem lt_sup_iff : a < s.sup f ↔ ∃ b ∈ s, a < f b := by
apply Iff.intro
· induction s using cons_induction with
| empty => exact (absurd · not_lt_bot)
| cons c t hc ih =>
rw [sup_cons, lt_sup_iff]
exact fun
| Or.inl h => ⟨c, mem_cons.2 (Or.inl rfl), h⟩
| Or.inr h => let ⟨b, hb, hlt⟩ := ih h; ⟨b, mem_cons.2 (Or.inr hb), hlt⟩
· exact fun ⟨b, hb, hlt⟩ => lt_of_lt_of_le hlt (le_sup hb)
#align finset.lt_sup_iff Finset.lt_sup_iff
@[simp]
protected theorem sup_lt_iff (ha : ⊥ < a) : s.sup f < a ↔ ∀ b ∈ s, f b < a :=
⟨fun hs b hb => lt_of_le_of_lt (le_sup hb) hs,
Finset.cons_induction_on s (fun _ => ha) fun c t hc => by
simpa only [sup_cons, sup_lt_iff, mem_cons, forall_eq_or_imp] using And.imp_right⟩
#align finset.sup_lt_iff Finset.sup_lt_iff
end OrderBot
section OrderTop
variable [OrderTop α] {s : Finset ι} {f : ι → α} {a : α}
theorem comp_inf_eq_inf_comp_of_is_total [SemilatticeInf β] [OrderTop β] (g : α → β)
(mono_g : Monotone g) (top : g ⊤ = ⊤) : g (s.inf f) = s.inf (g ∘ f) :=
comp_inf_eq_inf_comp g mono_g.map_inf top
#align finset.comp_inf_eq_inf_comp_of_is_total Finset.comp_inf_eq_inf_comp_of_is_total
@[simp]
protected theorem inf_le_iff (ha : a < ⊤) : s.inf f ≤ a ↔ ∃ b ∈ s, f b ≤ a :=
@Finset.le_sup_iff αᵒᵈ _ _ _ _ _ _ ha
#align finset.inf_le_iff Finset.inf_le_iff
@[simp]
protected theorem inf_lt_iff : s.inf f < a ↔ ∃ b ∈ s, f b < a :=
@Finset.lt_sup_iff αᵒᵈ _ _ _ _ _ _
#align finset.inf_lt_iff Finset.inf_lt_iff
@[simp]
protected theorem lt_inf_iff (ha : a < ⊤) : a < s.inf f ↔ ∀ b ∈ s, a < f b :=
@Finset.sup_lt_iff αᵒᵈ _ _ _ _ _ _ ha
#align finset.lt_inf_iff Finset.lt_inf_iff
end OrderTop
end LinearOrder
theorem inf_eq_iInf [CompleteLattice β] (s : Finset α) (f : α → β) : s.inf f = ⨅ a ∈ s, f a :=
@sup_eq_iSup _ βᵒᵈ _ _ _
#align finset.inf_eq_infi Finset.inf_eq_iInf
theorem inf_id_eq_sInf [CompleteLattice α] (s : Finset α) : s.inf id = sInf s :=
@sup_id_eq_sSup αᵒᵈ _ _
#align finset.inf_id_eq_Inf Finset.inf_id_eq_sInf
theorem inf_id_set_eq_sInter (s : Finset (Set α)) : s.inf id = ⋂₀ ↑s :=
inf_id_eq_sInf _
#align finset.inf_id_set_eq_sInter Finset.inf_id_set_eq_sInter
@[simp]
theorem inf_set_eq_iInter (s : Finset α) (f : α → Set β) : s.inf f = ⋂ x ∈ s, f x :=
inf_eq_iInf _ _
#align finset.inf_set_eq_bInter Finset.inf_set_eq_iInter
theorem inf_eq_sInf_image [CompleteLattice β] (s : Finset α) (f : α → β) :
s.inf f = sInf (f '' s) :=
@sup_eq_sSup_image _ βᵒᵈ _ _ _
#align finset.inf_eq_Inf_image Finset.inf_eq_sInf_image
section Sup'
variable [SemilatticeSup α]
theorem sup_of_mem {s : Finset β} (f : β → α) {b : β} (h : b ∈ s) :
∃ a : α, s.sup ((↑) ∘ f : β → WithBot α) = ↑a :=
Exists.imp (fun _ => And.left) (@le_sup (WithBot α) _ _ _ _ _ _ h (f b) rfl)
#align finset.sup_of_mem Finset.sup_of_mem
/-- Given nonempty finset `s` then `s.sup' H f` is the supremum of its image under `f` in (possibly
unbounded) join-semilattice `α`, where `H` is a proof of nonemptiness. If `α` has a bottom element
you may instead use `Finset.sup` which does not require `s` nonempty. -/
def sup' (s : Finset β) (H : s.Nonempty) (f : β → α) : α :=
WithBot.unbot (s.sup ((↑) ∘ f)) (by simpa using H)
#align finset.sup' Finset.sup'
variable {s : Finset β} (H : s.Nonempty) (f : β → α)
@[simp]
theorem coe_sup' : ((s.sup' H f : α) : WithBot α) = s.sup ((↑) ∘ f) := by
rw [sup', WithBot.coe_unbot]
#align finset.coe_sup' Finset.coe_sup'
@[simp]
theorem sup'_cons {b : β} {hb : b ∉ s} :
(cons b s hb).sup' (nonempty_cons hb) f = f b ⊔ s.sup' H f := by
rw [← WithBot.coe_eq_coe]
simp [WithBot.coe_sup]
#align finset.sup'_cons Finset.sup'_cons
@[simp]
theorem sup'_insert [DecidableEq β] {b : β} :
(insert b s).sup' (insert_nonempty _ _) f = f b ⊔ s.sup' H f := by
rw [← WithBot.coe_eq_coe]
simp [WithBot.coe_sup]
#align finset.sup'_insert Finset.sup'_insert
@[simp]
theorem sup'_singleton {b : β} : ({b} : Finset β).sup' (singleton_nonempty _) f = f b :=
rfl
#align finset.sup'_singleton Finset.sup'_singleton
@[simp]
theorem sup'_le_iff {a : α} : s.sup' H f ≤ a ↔ ∀ b ∈ s, f b ≤ a := by
simp_rw [← @WithBot.coe_le_coe α, coe_sup', Finset.sup_le_iff]; rfl
#align finset.sup'_le_iff Finset.sup'_le_iff
alias ⟨_, sup'_le⟩ := sup'_le_iff
#align finset.sup'_le Finset.sup'_le
theorem le_sup' {b : β} (h : b ∈ s) : f b ≤ s.sup' ⟨b, h⟩ f :=
(sup'_le_iff ⟨b, h⟩ f).1 le_rfl b h
#align finset.le_sup' Finset.le_sup'
theorem le_sup'_of_le {a : α} {b : β} (hb : b ∈ s) (h : a ≤ f b) : a ≤ s.sup' ⟨b, hb⟩ f :=
h.trans <| le_sup' _ hb
#align finset.le_sup'_of_le Finset.le_sup'_of_le
@[simp]
theorem sup'_const (a : α) : s.sup' H (fun _ => a) = a := by
apply le_antisymm
· apply sup'_le
intros
exact le_rfl
· apply le_sup' (fun _ => a) H.choose_spec
#align finset.sup'_const Finset.sup'_const
theorem sup'_union [DecidableEq β] {s₁ s₂ : Finset β} (h₁ : s₁.Nonempty) (h₂ : s₂.Nonempty)
(f : β → α) :
(s₁ ∪ s₂).sup' (h₁.mono subset_union_left) f = s₁.sup' h₁ f ⊔ s₂.sup' h₂ f :=
eq_of_forall_ge_iff fun a => by simp [or_imp, forall_and]
#align finset.sup'_union Finset.sup'_union
theorem sup'_biUnion [DecidableEq β] {s : Finset γ} (Hs : s.Nonempty) {t : γ → Finset β}
(Ht : ∀ b, (t b).Nonempty) :
(s.biUnion t).sup' (Hs.biUnion fun b _ => Ht b) f = s.sup' Hs (fun b => (t b).sup' (Ht b) f) :=
eq_of_forall_ge_iff fun c => by simp [@forall_swap _ β]
#align finset.sup'_bUnion Finset.sup'_biUnion
protected theorem sup'_comm {t : Finset γ} (hs : s.Nonempty) (ht : t.Nonempty) (f : β → γ → α) :
(s.sup' hs fun b => t.sup' ht (f b)) = t.sup' ht fun c => s.sup' hs fun b => f b c :=
eq_of_forall_ge_iff fun a => by simpa using forall₂_swap
#align finset.sup'_comm Finset.sup'_comm
theorem sup'_product_left {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).sup' h f = s.sup' h.fst fun i => t.sup' h.snd fun i' => f ⟨i, i'⟩ :=
eq_of_forall_ge_iff fun a => by simp [@forall_swap _ γ]
#align finset.sup'_product_left Finset.sup'_product_left
theorem sup'_product_right {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).sup' h f = t.sup' h.snd fun i' => s.sup' h.fst fun i => f ⟨i, i'⟩ := by
rw [sup'_product_left, Finset.sup'_comm]
#align finset.sup'_product_right Finset.sup'_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeSup α] [SemilatticeSup β] {s : Finset ι} {t : Finset κ}
/-- See also `Finset.sup'_prodMap`. -/
lemma prodMk_sup'_sup' (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
(sup' s hs f, sup' t ht g) = sup' (s ×ˢ t) (hs.product ht) (Prod.map f g) :=
eq_of_forall_ge_iff fun i ↦ by
obtain ⟨a, ha⟩ := hs
obtain ⟨b, hb⟩ := ht
simp only [Prod.map, sup'_le_iff, mem_product, and_imp, Prod.forall, Prod.le_def]
exact ⟨by aesop, fun h ↦ ⟨fun i hi ↦ (h _ _ hi hb).1, fun j hj ↦ (h _ _ ha hj).2⟩⟩
/-- See also `Finset.prodMk_sup'_sup'`. -/
-- @[simp] -- TODO: Why does `Prod.map_apply` simplify the LHS?
lemma sup'_prodMap (hst : (s ×ˢ t).Nonempty) (f : ι → α) (g : κ → β) :
sup' (s ×ˢ t) hst (Prod.map f g) = (sup' s hst.fst f, sup' t hst.snd g) :=
(prodMk_sup'_sup' _ _ _ _).symm
end Prod
theorem sup'_induction {p : α → Prop} (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊔ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.sup' H f) := by
show @WithBot.recBotCoe α (fun _ => Prop) True p ↑(s.sup' H f)
rw [coe_sup']
refine sup_induction trivial (fun a₁ h₁ a₂ h₂ ↦ ?_) hs
match a₁, a₂ with
| ⊥, _ => rwa [bot_sup_eq]
| (a₁ : α), ⊥ => rwa [sup_bot_eq]
| (a₁ : α), (a₂ : α) => exact hp a₁ h₁ a₂ h₂
#align finset.sup'_induction Finset.sup'_induction
theorem sup'_mem (s : Set α) (w : ∀ᵉ (x ∈ s) (y ∈ s), x ⊔ y ∈ s) {ι : Type*}
(t : Finset ι) (H : t.Nonempty) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.sup' H p ∈ s :=
sup'_induction H p w h
#align finset.sup'_mem Finset.sup'_mem
@[congr]
theorem sup'_congr {t : Finset β} {f g : β → α} (h₁ : s = t) (h₂ : ∀ x ∈ s, f x = g x) :
s.sup' H f = t.sup' (h₁ ▸ H) g := by
subst s
refine eq_of_forall_ge_iff fun c => ?_
simp (config := { contextual := true }) only [sup'_le_iff, h₂]
#align finset.sup'_congr Finset.sup'_congr
theorem comp_sup'_eq_sup'_comp [SemilatticeSup γ] {s : Finset β} (H : s.Nonempty) {f : β → α}
(g : α → γ) (g_sup : ∀ x y, g (x ⊔ y) = g x ⊔ g y) : g (s.sup' H f) = s.sup' H (g ∘ f) := by
refine H.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align finset.comp_sup'_eq_sup'_comp Finset.comp_sup'_eq_sup'_comp
@[simp]
theorem _root_.map_finset_sup' [SemilatticeSup β] [FunLike F α β] [SupHomClass F α β]
(f : F) {s : Finset ι} (hs) (g : ι → α) :
f (s.sup' hs g) = s.sup' hs (f ∘ g) := by
refine hs.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align map_finset_sup' map_finset_sup'
lemma nsmul_sup' [LinearOrderedAddCommMonoid β] {s : Finset α}
(hs : s.Nonempty) (f : α → β) (n : ℕ) :
s.sup' hs (fun a => n • f a) = n • s.sup' hs f :=
let ns : SupHom β β := { toFun := (n • ·), map_sup' := fun _ _ => (nsmul_right_mono n).map_max }
(map_finset_sup' ns hs _).symm
/-- To rewrite from right to left, use `Finset.sup'_comp_eq_image`. -/
@[simp]
theorem sup'_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : (s.image f).Nonempty)
(g : β → α) :
(s.image f).sup' hs g = s.sup' hs.of_image (g ∘ f) := by
rw [← WithBot.coe_eq_coe]; simp only [coe_sup', sup_image, WithBot.coe_sup]; rfl
#align finset.sup'_image Finset.sup'_image
/-- A version of `Finset.sup'_image` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma sup'_comp_eq_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : s.Nonempty) (g : β → α) :
s.sup' hs (g ∘ f) = (s.image f).sup' (hs.image f) g :=
.symm <| sup'_image _ _
/-- To rewrite from right to left, use `Finset.sup'_comp_eq_map`. -/
@[simp]
theorem sup'_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : (s.map f).Nonempty) :
(s.map f).sup' hs g = s.sup' (map_nonempty.1 hs) (g ∘ f) := by
rw [← WithBot.coe_eq_coe, coe_sup', sup_map, coe_sup']
rfl
#align finset.sup'_map Finset.sup'_map
/-- A version of `Finset.sup'_map` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma sup'_comp_eq_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : s.Nonempty) :
s.sup' hs (g ∘ f) = (s.map f).sup' (map_nonempty.2 hs) g :=
.symm <| sup'_map _ _
theorem sup'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂) (h₁ : s₁.Nonempty):
s₁.sup' h₁ f ≤ s₂.sup' (h₁.mono h) f :=
Finset.sup'_le h₁ _ (fun _ hb => le_sup' _ (h hb))
/-- A version of `Finset.sup'_mono` acceptable for `@[gcongr]`.
Instead of deducing `s₂.Nonempty` from `s₁.Nonempty` and `s₁ ⊆ s₂`,
this version takes it as an argument. -/
@[gcongr]
lemma _root_.GCongr.finset_sup'_le {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂)
{h₁ : s₁.Nonempty} {h₂ : s₂.Nonempty} : s₁.sup' h₁ f ≤ s₂.sup' h₂ f :=
sup'_mono f h h₁
end Sup'
section Inf'
variable [SemilatticeInf α]
theorem inf_of_mem {s : Finset β} (f : β → α) {b : β} (h : b ∈ s) :
∃ a : α, s.inf ((↑) ∘ f : β → WithTop α) = ↑a :=
@sup_of_mem αᵒᵈ _ _ _ f _ h
#align finset.inf_of_mem Finset.inf_of_mem
/-- Given nonempty finset `s` then `s.inf' H f` is the infimum of its image under `f` in (possibly
unbounded) meet-semilattice `α`, where `H` is a proof of nonemptiness. If `α` has a top element you
may instead use `Finset.inf` which does not require `s` nonempty. -/
def inf' (s : Finset β) (H : s.Nonempty) (f : β → α) : α :=
WithTop.untop (s.inf ((↑) ∘ f)) (by simpa using H)
#align finset.inf' Finset.inf'
variable {s : Finset β} (H : s.Nonempty) (f : β → α)
@[simp]
theorem coe_inf' : ((s.inf' H f : α) : WithTop α) = s.inf ((↑) ∘ f) :=
@coe_sup' αᵒᵈ _ _ _ H f
#align finset.coe_inf' Finset.coe_inf'
@[simp]
theorem inf'_cons {b : β} {hb : b ∉ s} :
(cons b s hb).inf' (nonempty_cons hb) f = f b ⊓ s.inf' H f :=
@sup'_cons αᵒᵈ _ _ _ H f _ _
#align finset.inf'_cons Finset.inf'_cons
@[simp]
theorem inf'_insert [DecidableEq β] {b : β} :
(insert b s).inf' (insert_nonempty _ _) f = f b ⊓ s.inf' H f :=
@sup'_insert αᵒᵈ _ _ _ H f _ _
#align finset.inf'_insert Finset.inf'_insert
@[simp]
theorem inf'_singleton {b : β} : ({b} : Finset β).inf' (singleton_nonempty _) f = f b :=
rfl
#align finset.inf'_singleton Finset.inf'_singleton
@[simp]
theorem le_inf'_iff {a : α} : a ≤ s.inf' H f ↔ ∀ b ∈ s, a ≤ f b :=
sup'_le_iff (α := αᵒᵈ) H f
#align finset.le_inf'_iff Finset.le_inf'_iff
theorem le_inf' {a : α} (hs : ∀ b ∈ s, a ≤ f b) : a ≤ s.inf' H f :=
sup'_le (α := αᵒᵈ) H f hs
#align finset.le_inf' Finset.le_inf'
theorem inf'_le {b : β} (h : b ∈ s) : s.inf' ⟨b, h⟩ f ≤ f b :=
le_sup' (α := αᵒᵈ) f h
#align finset.inf'_le Finset.inf'_le
theorem inf'_le_of_le {a : α} {b : β} (hb : b ∈ s) (h : f b ≤ a) :
s.inf' ⟨b, hb⟩ f ≤ a := (inf'_le _ hb).trans h
#align finset.inf'_le_of_le Finset.inf'_le_of_le
@[simp]
theorem inf'_const (a : α) : (s.inf' H fun _ => a) = a :=
sup'_const (α := αᵒᵈ) H a
#align finset.inf'_const Finset.inf'_const
theorem inf'_union [DecidableEq β] {s₁ s₂ : Finset β} (h₁ : s₁.Nonempty) (h₂ : s₂.Nonempty)
(f : β → α) :
(s₁ ∪ s₂).inf' (h₁.mono subset_union_left) f = s₁.inf' h₁ f ⊓ s₂.inf' h₂ f :=
@sup'_union αᵒᵈ _ _ _ _ _ h₁ h₂ _
#align finset.inf'_union Finset.inf'_union
theorem inf'_biUnion [DecidableEq β] {s : Finset γ} (Hs : s.Nonempty) {t : γ → Finset β}
(Ht : ∀ b, (t b).Nonempty) :
(s.biUnion t).inf' (Hs.biUnion fun b _ => Ht b) f = s.inf' Hs (fun b => (t b).inf' (Ht b) f) :=
sup'_biUnion (α := αᵒᵈ) _ Hs Ht
#align finset.inf'_bUnion Finset.inf'_biUnion
protected theorem inf'_comm {t : Finset γ} (hs : s.Nonempty) (ht : t.Nonempty) (f : β → γ → α) :
(s.inf' hs fun b => t.inf' ht (f b)) = t.inf' ht fun c => s.inf' hs fun b => f b c :=
@Finset.sup'_comm αᵒᵈ _ _ _ _ _ hs ht _
#align finset.inf'_comm Finset.inf'_comm
theorem inf'_product_left {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).inf' h f = s.inf' h.fst fun i => t.inf' h.snd fun i' => f ⟨i, i'⟩ :=
sup'_product_left (α := αᵒᵈ) h f
#align finset.inf'_product_left Finset.inf'_product_left
theorem inf'_product_right {t : Finset γ} (h : (s ×ˢ t).Nonempty) (f : β × γ → α) :
(s ×ˢ t).inf' h f = t.inf' h.snd fun i' => s.inf' h.fst fun i => f ⟨i, i'⟩ :=
sup'_product_right (α := αᵒᵈ) h f
#align finset.inf'_product_right Finset.inf'_product_right
section Prod
variable {ι κ α β : Type*} [SemilatticeInf α] [SemilatticeInf β] {s : Finset ι} {t : Finset κ}
/-- See also `Finset.inf'_prodMap`. -/
lemma prodMk_inf'_inf' (hs : s.Nonempty) (ht : t.Nonempty) (f : ι → α) (g : κ → β) :
(inf' s hs f, inf' t ht g) = inf' (s ×ˢ t) (hs.product ht) (Prod.map f g) :=
prodMk_sup'_sup' (α := αᵒᵈ) (β := βᵒᵈ) hs ht _ _
/-- See also `Finset.prodMk_inf'_inf'`. -/
-- @[simp] -- TODO: Why does `Prod.map_apply` simplify the LHS?
lemma inf'_prodMap (hst : (s ×ˢ t).Nonempty) (f : ι → α) (g : κ → β) :
inf' (s ×ˢ t) hst (Prod.map f g) = (inf' s hst.fst f, inf' t hst.snd g) :=
(prodMk_inf'_inf' _ _ _ _).symm
end Prod
theorem comp_inf'_eq_inf'_comp [SemilatticeInf γ] {s : Finset β} (H : s.Nonempty) {f : β → α}
(g : α → γ) (g_inf : ∀ x y, g (x ⊓ y) = g x ⊓ g y) : g (s.inf' H f) = s.inf' H (g ∘ f) :=
comp_sup'_eq_sup'_comp (α := αᵒᵈ) (γ := γᵒᵈ) H g g_inf
#align finset.comp_inf'_eq_inf'_comp Finset.comp_inf'_eq_inf'_comp
theorem inf'_induction {p : α → Prop} (hp : ∀ a₁, p a₁ → ∀ a₂, p a₂ → p (a₁ ⊓ a₂))
(hs : ∀ b ∈ s, p (f b)) : p (s.inf' H f) :=
sup'_induction (α := αᵒᵈ) H f hp hs
#align finset.inf'_induction Finset.inf'_induction
theorem inf'_mem (s : Set α) (w : ∀ᵉ (x ∈ s) (y ∈ s), x ⊓ y ∈ s) {ι : Type*}
(t : Finset ι) (H : t.Nonempty) (p : ι → α) (h : ∀ i ∈ t, p i ∈ s) : t.inf' H p ∈ s :=
inf'_induction H p w h
#align finset.inf'_mem Finset.inf'_mem
@[congr]
theorem inf'_congr {t : Finset β} {f g : β → α} (h₁ : s = t) (h₂ : ∀ x ∈ s, f x = g x) :
s.inf' H f = t.inf' (h₁ ▸ H) g :=
sup'_congr (α := αᵒᵈ) H h₁ h₂
#align finset.inf'_congr Finset.inf'_congr
@[simp]
theorem _root_.map_finset_inf' [SemilatticeInf β] [FunLike F α β] [InfHomClass F α β]
(f : F) {s : Finset ι} (hs) (g : ι → α) :
f (s.inf' hs g) = s.inf' hs (f ∘ g) := by
refine hs.cons_induction ?_ ?_ <;> intros <;> simp [*]
#align map_finset_inf' map_finset_inf'
lemma nsmul_inf' [LinearOrderedAddCommMonoid β] {s : Finset α}
(hs : s.Nonempty) (f : α → β) (n : ℕ) :
s.inf' hs (fun a => n • f a) = n • s.inf' hs f :=
let ns : InfHom β β := { toFun := (n • ·), map_inf' := fun _ _ => (nsmul_right_mono n).map_min }
(map_finset_inf' ns hs _).symm
/-- To rewrite from right to left, use `Finset.inf'_comp_eq_image`. -/
@[simp]
theorem inf'_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : (s.image f).Nonempty)
(g : β → α) :
(s.image f).inf' hs g = s.inf' hs.of_image (g ∘ f) :=
@sup'_image αᵒᵈ _ _ _ _ _ _ hs _
#align finset.inf'_image Finset.inf'_image
/-- A version of `Finset.inf'_image` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma inf'_comp_eq_image [DecidableEq β] {s : Finset γ} {f : γ → β} (hs : s.Nonempty) (g : β → α) :
s.inf' hs (g ∘ f) = (s.image f).inf' (hs.image f) g :=
sup'_comp_eq_image (α := αᵒᵈ) hs g
/-- To rewrite from right to left, use `Finset.inf'_comp_eq_map`. -/
@[simp]
theorem inf'_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : (s.map f).Nonempty) :
(s.map f).inf' hs g = s.inf' (map_nonempty.1 hs) (g ∘ f) :=
sup'_map (α := αᵒᵈ) _ hs
#align finset.inf'_map Finset.inf'_map
/-- A version of `Finset.inf'_map` with LHS and RHS reversed.
Also, this lemma assumes that `s` is nonempty instead of assuming that its image is nonempty. -/
lemma inf'_comp_eq_map {s : Finset γ} {f : γ ↪ β} (g : β → α) (hs : s.Nonempty) :
s.inf' hs (g ∘ f) = (s.map f).inf' (map_nonempty.2 hs) g :=
sup'_comp_eq_map (α := αᵒᵈ) g hs
theorem inf'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂) (h₁ : s₁.Nonempty) :
s₂.inf' (h₁.mono h) f ≤ s₁.inf' h₁ f :=
Finset.le_inf' h₁ _ (fun _ hb => inf'_le _ (h hb))
/-- A version of `Finset.inf'_mono` acceptable for `@[gcongr]`.
Instead of deducing `s₂.Nonempty` from `s₁.Nonempty` and `s₁ ⊆ s₂`,
this version takes it as an argument. -/
@[gcongr]
lemma _root_.GCongr.finset_inf'_mono {s₁ s₂ : Finset β} (h : s₁ ⊆ s₂)
{h₁ : s₁.Nonempty} {h₂ : s₂.Nonempty} : s₂.inf' h₂ f ≤ s₁.inf' h₁ f :=
inf'_mono f h h₁
end Inf'
section Sup
variable [SemilatticeSup α] [OrderBot α]
theorem sup'_eq_sup {s : Finset β} (H : s.Nonempty) (f : β → α) : s.sup' H f = s.sup f :=
le_antisymm (sup'_le H f fun _ => le_sup) (Finset.sup_le fun _ => le_sup' f)
#align finset.sup'_eq_sup Finset.sup'_eq_sup
theorem coe_sup_of_nonempty {s : Finset β} (h : s.Nonempty) (f : β → α) :
(↑(s.sup f) : WithBot α) = s.sup ((↑) ∘ f) := by simp only [← sup'_eq_sup h, coe_sup' h]
#align finset.coe_sup_of_nonempty Finset.coe_sup_of_nonempty
end Sup
section Inf
variable [SemilatticeInf α] [OrderTop α]
theorem inf'_eq_inf {s : Finset β} (H : s.Nonempty) (f : β → α) : s.inf' H f = s.inf f :=
sup'_eq_sup (α := αᵒᵈ) H f
#align finset.inf'_eq_inf Finset.inf'_eq_inf
theorem coe_inf_of_nonempty {s : Finset β} (h : s.Nonempty) (f : β → α) :
(↑(s.inf f) : WithTop α) = s.inf ((↑) ∘ f) :=
coe_sup_of_nonempty (α := αᵒᵈ) h f
#align finset.coe_inf_of_nonempty Finset.coe_inf_of_nonempty
end Inf
@[simp]
protected theorem sup_apply {C : β → Type*} [∀ b : β, SemilatticeSup (C b)]
[∀ b : β, OrderBot (C b)] (s : Finset α) (f : α → ∀ b : β, C b) (b : β) :
s.sup f b = s.sup fun a => f a b :=
comp_sup_eq_sup_comp (fun x : ∀ b : β, C b => x b) (fun _ _ => rfl) rfl
#align finset.sup_apply Finset.sup_apply
@[simp]
protected theorem inf_apply {C : β → Type*} [∀ b : β, SemilatticeInf (C b)]
[∀ b : β, OrderTop (C b)] (s : Finset α) (f : α → ∀ b : β, C b) (b : β) :
s.inf f b = s.inf fun a => f a b :=
Finset.sup_apply (C := fun b => (C b)ᵒᵈ) s f b
#align finset.inf_apply Finset.inf_apply
@[simp]
protected theorem sup'_apply {C : β → Type*} [∀ b : β, SemilatticeSup (C b)]
{s : Finset α} (H : s.Nonempty) (f : α → ∀ b : β, C b) (b : β) :
s.sup' H f b = s.sup' H fun a => f a b :=
comp_sup'_eq_sup'_comp H (fun x : ∀ b : β, C b => x b) fun _ _ => rfl
#align finset.sup'_apply Finset.sup'_apply
@[simp]
protected theorem inf'_apply {C : β → Type*} [∀ b : β, SemilatticeInf (C b)]
{s : Finset α} (H : s.Nonempty) (f : α → ∀ b : β, C b) (b : β) :
s.inf' H f b = s.inf' H fun a => f a b :=
Finset.sup'_apply (C := fun b => (C b)ᵒᵈ) H f b
#align finset.inf'_apply Finset.inf'_apply
@[simp]
theorem toDual_sup' [SemilatticeSup α] {s : Finset ι} (hs : s.Nonempty) (f : ι → α) :
toDual (s.sup' hs f) = s.inf' hs (toDual ∘ f) :=
rfl
#align finset.to_dual_sup' Finset.toDual_sup'
@[simp]
theorem toDual_inf' [SemilatticeInf α] {s : Finset ι} (hs : s.Nonempty) (f : ι → α) :
toDual (s.inf' hs f) = s.sup' hs (toDual ∘ f) :=
rfl
#align finset.to_dual_inf' Finset.toDual_inf'
@[simp]
theorem ofDual_sup' [SemilatticeInf α] {s : Finset ι} (hs : s.Nonempty) (f : ι → αᵒᵈ) :
ofDual (s.sup' hs f) = s.inf' hs (ofDual ∘ f) :=
rfl
#align finset.of_dual_sup' Finset.ofDual_sup'
@[simp]
theorem ofDual_inf' [SemilatticeSup α] {s : Finset ι} (hs : s.Nonempty) (f : ι → αᵒᵈ) :
ofDual (s.inf' hs f) = s.sup' hs (ofDual ∘ f) :=
rfl
#align finset.of_dual_inf' Finset.ofDual_inf'
section DistribLattice
variable [DistribLattice α] {s : Finset ι} {t : Finset κ} (hs : s.Nonempty) (ht : t.Nonempty)
{f : ι → α} {g : κ → α} {a : α}
theorem sup'_inf_distrib_left (f : ι → α) (a : α) :
a ⊓ s.sup' hs f = s.sup' hs fun i ↦ a ⊓ f i := by
induction hs using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih => simp_rw [sup'_cons hs, inf_sup_left, ih]
#align finset.sup'_inf_distrib_left Finset.sup'_inf_distrib_left
theorem sup'_inf_distrib_right (f : ι → α) (a : α) :
s.sup' hs f ⊓ a = s.sup' hs fun i => f i ⊓ a := by
rw [inf_comm, sup'_inf_distrib_left]; simp_rw [inf_comm]
#align finset.sup'_inf_distrib_right Finset.sup'_inf_distrib_right
theorem sup'_inf_sup' (f : ι → α) (g : κ → α) :
s.sup' hs f ⊓ t.sup' ht g = (s ×ˢ t).sup' (hs.product ht) fun i => f i.1 ⊓ g i.2 := by
simp_rw [Finset.sup'_inf_distrib_right, Finset.sup'_inf_distrib_left, sup'_product_left]
#align finset.sup'_inf_sup' Finset.sup'_inf_sup'
theorem inf'_sup_distrib_left (f : ι → α) (a : α) : a ⊔ s.inf' hs f = s.inf' hs fun i => a ⊔ f i :=
@sup'_inf_distrib_left αᵒᵈ _ _ _ hs _ _
#align finset.inf'_sup_distrib_left Finset.inf'_sup_distrib_left
theorem inf'_sup_distrib_right (f : ι → α) (a : α) : s.inf' hs f ⊔ a = s.inf' hs fun i => f i ⊔ a :=
@sup'_inf_distrib_right αᵒᵈ _ _ _ hs _ _
#align finset.inf'_sup_distrib_right Finset.inf'_sup_distrib_right
theorem inf'_sup_inf' (f : ι → α) (g : κ → α) :
s.inf' hs f ⊔ t.inf' ht g = (s ×ˢ t).inf' (hs.product ht) fun i => f i.1 ⊔ g i.2 :=
@sup'_inf_sup' αᵒᵈ _ _ _ _ _ hs ht _ _
#align finset.inf'_sup_inf' Finset.inf'_sup_inf'
end DistribLattice
section LinearOrder
variable [LinearOrder α] {s : Finset ι} (H : s.Nonempty) {f : ι → α} {a : α}
@[simp]
theorem le_sup'_iff : a ≤ s.sup' H f ↔ ∃ b ∈ s, a ≤ f b := by
rw [← WithBot.coe_le_coe, coe_sup', Finset.le_sup_iff (WithBot.bot_lt_coe a)]
exact exists_congr (fun _ => and_congr_right' WithBot.coe_le_coe)
#align finset.le_sup'_iff Finset.le_sup'_iff
@[simp]
theorem lt_sup'_iff : a < s.sup' H f ↔ ∃ b ∈ s, a < f b := by
rw [← WithBot.coe_lt_coe, coe_sup', Finset.lt_sup_iff]
exact exists_congr (fun _ => and_congr_right' WithBot.coe_lt_coe)
#align finset.lt_sup'_iff Finset.lt_sup'_iff
@[simp]
theorem sup'_lt_iff : s.sup' H f < a ↔ ∀ i ∈ s, f i < a := by
rw [← WithBot.coe_lt_coe, coe_sup', Finset.sup_lt_iff (WithBot.bot_lt_coe a)]
exact forall₂_congr (fun _ _ => WithBot.coe_lt_coe)
#align finset.sup'_lt_iff Finset.sup'_lt_iff
@[simp]
theorem inf'_le_iff : s.inf' H f ≤ a ↔ ∃ i ∈ s, f i ≤ a :=
le_sup'_iff (α := αᵒᵈ) H
#align finset.inf'_le_iff Finset.inf'_le_iff
@[simp]
theorem inf'_lt_iff : s.inf' H f < a ↔ ∃ i ∈ s, f i < a :=
lt_sup'_iff (α := αᵒᵈ) H
#align finset.inf'_lt_iff Finset.inf'_lt_iff
@[simp]
theorem lt_inf'_iff : a < s.inf' H f ↔ ∀ i ∈ s, a < f i :=
sup'_lt_iff (α := αᵒᵈ) H
#align finset.lt_inf'_iff Finset.lt_inf'_iff
theorem exists_mem_eq_sup' (f : ι → α) : ∃ i, i ∈ s ∧ s.sup' H f = f i := by
induction H using Finset.Nonempty.cons_induction with
| singleton c => exact ⟨c, mem_singleton_self c, rfl⟩
| cons c s hcs hs ih =>
rcases ih with ⟨b, hb, h'⟩
rw [sup'_cons hs, h']
cases le_total (f b) (f c) with
| inl h => exact ⟨c, mem_cons.2 (Or.inl rfl), sup_eq_left.2 h⟩
| inr h => exact ⟨b, mem_cons.2 (Or.inr hb), sup_eq_right.2 h⟩
#align finset.exists_mem_eq_sup' Finset.exists_mem_eq_sup'
theorem exists_mem_eq_inf' (f : ι → α) : ∃ i, i ∈ s ∧ s.inf' H f = f i :=
exists_mem_eq_sup' (α := αᵒᵈ) H f
#align finset.exists_mem_eq_inf' Finset.exists_mem_eq_inf'
theorem exists_mem_eq_sup [OrderBot α] (s : Finset ι) (h : s.Nonempty) (f : ι → α) :
∃ i, i ∈ s ∧ s.sup f = f i :=
sup'_eq_sup h f ▸ exists_mem_eq_sup' h f
#align finset.exists_mem_eq_sup Finset.exists_mem_eq_sup
theorem exists_mem_eq_inf [OrderTop α] (s : Finset ι) (h : s.Nonempty) (f : ι → α) :
∃ i, i ∈ s ∧ s.inf f = f i :=
exists_mem_eq_sup (α := αᵒᵈ) s h f
#align finset.exists_mem_eq_inf Finset.exists_mem_eq_inf
end LinearOrder
/-! ### max and min of finite sets -/
section MaxMin
variable [LinearOrder α]
/-- Let `s` be a finset in a linear order. Then `s.max` is the maximum of `s` if `s` is not empty,
and `⊥` otherwise. It belongs to `WithBot α`. If you want to get an element of `α`, see
`s.max'`. -/
protected def max (s : Finset α) : WithBot α :=
sup s (↑)
#align finset.max Finset.max
theorem max_eq_sup_coe {s : Finset α} : s.max = s.sup (↑) :=
rfl
#align finset.max_eq_sup_coe Finset.max_eq_sup_coe
theorem max_eq_sup_withBot (s : Finset α) : s.max = sup s (↑) :=
rfl
#align finset.max_eq_sup_with_bot Finset.max_eq_sup_withBot
@[simp]
theorem max_empty : (∅ : Finset α).max = ⊥ :=
rfl
#align finset.max_empty Finset.max_empty
@[simp]
theorem max_insert {a : α} {s : Finset α} : (insert a s).max = max ↑a s.max :=
fold_insert_idem
#align finset.max_insert Finset.max_insert
@[simp]
theorem max_singleton {a : α} : Finset.max {a} = (a : WithBot α) := by
rw [← insert_emptyc_eq]
exact max_insert
#align finset.max_singleton Finset.max_singleton
theorem max_of_mem {s : Finset α} {a : α} (h : a ∈ s) : ∃ b : α, s.max = b := by
obtain ⟨b, h, _⟩ := le_sup (α := WithBot α) h _ rfl
exact ⟨b, h⟩
#align finset.max_of_mem Finset.max_of_mem
theorem max_of_nonempty {s : Finset α} (h : s.Nonempty) : ∃ a : α, s.max = a :=
let ⟨_, h⟩ := h
max_of_mem h
#align finset.max_of_nonempty Finset.max_of_nonempty
theorem max_eq_bot {s : Finset α} : s.max = ⊥ ↔ s = ∅ :=
⟨fun h ↦ s.eq_empty_or_nonempty.elim id fun H ↦ by
obtain ⟨a, ha⟩ := max_of_nonempty H
rw [h] at ha; cases ha; , -- the `;` is needed since the `cases` syntax allows `cases a, b`
fun h ↦ h.symm ▸ max_empty⟩
#align finset.max_eq_bot Finset.max_eq_bot
theorem mem_of_max {s : Finset α} : ∀ {a : α}, s.max = a → a ∈ s := by
induction' s using Finset.induction_on with b s _ ih
· intro _ H; cases H
· intro a h
by_cases p : b = a
· induction p
exact mem_insert_self b s
· cases' max_choice (↑b) s.max with q q <;> rw [max_insert, q] at h
· cases h
cases p rfl
· exact mem_insert_of_mem (ih h)
#align finset.mem_of_max Finset.mem_of_max
theorem le_max {a : α} {s : Finset α} (as : a ∈ s) : ↑a ≤ s.max :=
le_sup as
#align finset.le_max Finset.le_max
theorem not_mem_of_max_lt_coe {a : α} {s : Finset α} (h : s.max < a) : a ∉ s :=
mt le_max h.not_le
#align finset.not_mem_of_max_lt_coe Finset.not_mem_of_max_lt_coe
theorem le_max_of_eq {s : Finset α} {a b : α} (h₁ : a ∈ s) (h₂ : s.max = b) : a ≤ b :=
WithBot.coe_le_coe.mp <| (le_max h₁).trans h₂.le
#align finset.le_max_of_eq Finset.le_max_of_eq
theorem not_mem_of_max_lt {s : Finset α} {a b : α} (h₁ : b < a) (h₂ : s.max = ↑b) : a ∉ s :=
Finset.not_mem_of_max_lt_coe <| h₂.trans_lt <| WithBot.coe_lt_coe.mpr h₁
#align finset.not_mem_of_max_lt Finset.not_mem_of_max_lt
@[gcongr]
theorem max_mono {s t : Finset α} (st : s ⊆ t) : s.max ≤ t.max :=
sup_mono st
#align finset.max_mono Finset.max_mono
protected theorem max_le {M : WithBot α} {s : Finset α} (st : ∀ a ∈ s, (a : WithBot α) ≤ M) :
s.max ≤ M :=
Finset.sup_le st
#align finset.max_le Finset.max_le
/-- Let `s` be a finset in a linear order. Then `s.min` is the minimum of `s` if `s` is not empty,
and `⊤` otherwise. It belongs to `WithTop α`. If you want to get an element of `α`, see
`s.min'`. -/
protected def min (s : Finset α) : WithTop α :=
inf s (↑)
#align finset.min Finset.min
theorem min_eq_inf_withTop (s : Finset α) : s.min = inf s (↑) :=
rfl
#align finset.min_eq_inf_with_top Finset.min_eq_inf_withTop
@[simp]
theorem min_empty : (∅ : Finset α).min = ⊤ :=
rfl
#align finset.min_empty Finset.min_empty
@[simp]
theorem min_insert {a : α} {s : Finset α} : (insert a s).min = min (↑a) s.min :=
fold_insert_idem
#align finset.min_insert Finset.min_insert
@[simp]
theorem min_singleton {a : α} : Finset.min {a} = (a : WithTop α) := by
rw [← insert_emptyc_eq]
exact min_insert
#align finset.min_singleton Finset.min_singleton
theorem min_of_mem {s : Finset α} {a : α} (h : a ∈ s) : ∃ b : α, s.min = b := by
obtain ⟨b, h, _⟩ := inf_le (α := WithTop α) h _ rfl
exact ⟨b, h⟩
#align finset.min_of_mem Finset.min_of_mem
theorem min_of_nonempty {s : Finset α} (h : s.Nonempty) : ∃ a : α, s.min = a :=
let ⟨_, h⟩ := h
min_of_mem h
#align finset.min_of_nonempty Finset.min_of_nonempty
theorem min_eq_top {s : Finset α} : s.min = ⊤ ↔ s = ∅ :=
⟨fun h =>
s.eq_empty_or_nonempty.elim id fun H => by
let ⟨a, ha⟩ := min_of_nonempty H
rw [h] at ha; cases ha; , -- Porting note: error without `done`
fun h => h.symm ▸ min_empty⟩
#align finset.min_eq_top Finset.min_eq_top
theorem mem_of_min {s : Finset α} : ∀ {a : α}, s.min = a → a ∈ s :=
@mem_of_max αᵒᵈ _ s
#align finset.mem_of_min Finset.mem_of_min
theorem min_le {a : α} {s : Finset α} (as : a ∈ s) : s.min ≤ a :=
inf_le as
#align finset.min_le Finset.min_le
theorem not_mem_of_coe_lt_min {a : α} {s : Finset α} (h : ↑a < s.min) : a ∉ s :=
mt min_le h.not_le
#align finset.not_mem_of_coe_lt_min Finset.not_mem_of_coe_lt_min
theorem min_le_of_eq {s : Finset α} {a b : α} (h₁ : b ∈ s) (h₂ : s.min = a) : a ≤ b :=
WithTop.coe_le_coe.mp <| h₂.ge.trans (min_le h₁)
#align finset.min_le_of_eq Finset.min_le_of_eq
theorem not_mem_of_lt_min {s : Finset α} {a b : α} (h₁ : a < b) (h₂ : s.min = ↑b) : a ∉ s :=
Finset.not_mem_of_coe_lt_min <| (WithTop.coe_lt_coe.mpr h₁).trans_eq h₂.symm
#align finset.not_mem_of_lt_min Finset.not_mem_of_lt_min
@[gcongr]
theorem min_mono {s t : Finset α} (st : s ⊆ t) : t.min ≤ s.min :=
inf_mono st
#align finset.min_mono Finset.min_mono
protected theorem le_min {m : WithTop α} {s : Finset α} (st : ∀ a : α, a ∈ s → m ≤ a) : m ≤ s.min :=
Finset.le_inf st
#align finset.le_min Finset.le_min
/-- Given a nonempty finset `s` in a linear order `α`, then `s.min' h` is its minimum, as an
element of `α`, where `h` is a proof of nonemptiness. Without this assumption, use instead `s.min`,
taking values in `WithTop α`. -/
def min' (s : Finset α) (H : s.Nonempty) : α :=
inf' s H id
#align finset.min' Finset.min'
/-- Given a nonempty finset `s` in a linear order `α`, then `s.max' h` is its maximum, as an
element of `α`, where `h` is a proof of nonemptiness. Without this assumption, use instead `s.max`,
taking values in `WithBot α`. -/
def max' (s : Finset α) (H : s.Nonempty) : α :=
sup' s H id
#align finset.max' Finset.max'
variable (s : Finset α) (H : s.Nonempty) {x : α}
theorem min'_mem : s.min' H ∈ s :=
mem_of_min <| by simp only [Finset.min, min', id_eq, coe_inf']; rfl
#align finset.min'_mem Finset.min'_mem
theorem min'_le (x) (H2 : x ∈ s) : s.min' ⟨x, H2⟩ ≤ x :=
min_le_of_eq H2 (WithTop.coe_untop _ _).symm
#align finset.min'_le Finset.min'_le
theorem le_min' (x) (H2 : ∀ y ∈ s, x ≤ y) : x ≤ s.min' H :=
H2 _ <| min'_mem _ _
#align finset.le_min' Finset.le_min'
theorem isLeast_min' : IsLeast (↑s) (s.min' H) :=
⟨min'_mem _ _, min'_le _⟩
#align finset.is_least_min' Finset.isLeast_min'
@[simp]
theorem le_min'_iff {x} : x ≤ s.min' H ↔ ∀ y ∈ s, x ≤ y :=
le_isGLB_iff (isLeast_min' s H).isGLB
#align finset.le_min'_iff Finset.le_min'_iff
/-- `{a}.min' _` is `a`. -/
@[simp]
theorem min'_singleton (a : α) : ({a} : Finset α).min' (singleton_nonempty _) = a := by simp [min']
#align finset.min'_singleton Finset.min'_singleton
theorem max'_mem : s.max' H ∈ s :=
mem_of_max <| by simp only [max', Finset.max, id_eq, coe_sup']; rfl
#align finset.max'_mem Finset.max'_mem
theorem le_max' (x) (H2 : x ∈ s) : x ≤ s.max' ⟨x, H2⟩ :=
le_max_of_eq H2 (WithBot.coe_unbot _ _).symm
#align finset.le_max' Finset.le_max'
theorem max'_le (x) (H2 : ∀ y ∈ s, y ≤ x) : s.max' H ≤ x :=
H2 _ <| max'_mem _ _
#align finset.max'_le Finset.max'_le
theorem isGreatest_max' : IsGreatest (↑s) (s.max' H) :=
⟨max'_mem _ _, le_max' _⟩
#align finset.is_greatest_max' Finset.isGreatest_max'
@[simp]
theorem max'_le_iff {x} : s.max' H ≤ x ↔ ∀ y ∈ s, y ≤ x :=
isLUB_le_iff (isGreatest_max' s H).isLUB
#align finset.max'_le_iff Finset.max'_le_iff
@[simp]
theorem max'_lt_iff {x} : s.max' H < x ↔ ∀ y ∈ s, y < x :=
⟨fun Hlt y hy => (s.le_max' y hy).trans_lt Hlt, fun H => H _ <| s.max'_mem _⟩
#align finset.max'_lt_iff Finset.max'_lt_iff
@[simp]
theorem lt_min'_iff : x < s.min' H ↔ ∀ y ∈ s, x < y :=
@max'_lt_iff αᵒᵈ _ _ H _
#align finset.lt_min'_iff Finset.lt_min'_iff
theorem max'_eq_sup' : s.max' H = s.sup' H id :=
eq_of_forall_ge_iff fun _ => (max'_le_iff _ _).trans (sup'_le_iff _ _).symm
#align finset.max'_eq_sup' Finset.max'_eq_sup'
theorem min'_eq_inf' : s.min' H = s.inf' H id :=
@max'_eq_sup' αᵒᵈ _ s H
#align finset.min'_eq_inf' Finset.min'_eq_inf'
/-- `{a}.max' _` is `a`. -/
@[simp]
theorem max'_singleton (a : α) : ({a} : Finset α).max' (singleton_nonempty _) = a := by simp [max']
#align finset.max'_singleton Finset.max'_singleton
theorem min'_lt_max' {i j} (H1 : i ∈ s) (H2 : j ∈ s) (H3 : i ≠ j) :
s.min' ⟨i, H1⟩ < s.max' ⟨i, H1⟩ :=
isGLB_lt_isLUB_of_ne (s.isLeast_min' _).isGLB (s.isGreatest_max' _).isLUB H1 H2 H3
#align finset.min'_lt_max' Finset.min'_lt_max'
/-- If there's more than 1 element, the min' is less than the max'. An alternate version of
`min'_lt_max'` which is sometimes more convenient.
-/
theorem min'_lt_max'_of_card (h₂ : 1 < card s) :
s.min' (Finset.card_pos.1 <| by omega) < s.max' (Finset.card_pos.1 <| by omega) := by
rcases one_lt_card.1 h₂ with ⟨a, ha, b, hb, hab⟩
exact s.min'_lt_max' ha hb hab
#align finset.min'_lt_max'_of_card Finset.min'_lt_max'_of_card
theorem map_ofDual_min (s : Finset αᵒᵈ) : s.min.map ofDual = (s.image ofDual).max := by
rw [max_eq_sup_withBot, sup_image]
exact congr_fun Option.map_id _
#align finset.map_of_dual_min Finset.map_ofDual_min
theorem map_ofDual_max (s : Finset αᵒᵈ) : s.max.map ofDual = (s.image ofDual).min := by
rw [min_eq_inf_withTop, inf_image]
exact congr_fun Option.map_id _
#align finset.map_of_dual_max Finset.map_ofDual_max
theorem map_toDual_min (s : Finset α) : s.min.map toDual = (s.image toDual).max := by
rw [max_eq_sup_withBot, sup_image]
exact congr_fun Option.map_id _
#align finset.map_to_dual_min Finset.map_toDual_min
theorem map_toDual_max (s : Finset α) : s.max.map toDual = (s.image toDual).min := by
rw [min_eq_inf_withTop, inf_image]
exact congr_fun Option.map_id _
#align finset.map_to_dual_max Finset.map_toDual_max
-- Porting note: new proofs without `convert` for the next four theorems.
theorem ofDual_min' {s : Finset αᵒᵈ} (hs : s.Nonempty) :
ofDual (min' s hs) = max' (s.image ofDual) (hs.image _) := by
rw [← WithBot.coe_eq_coe]
simp only [min'_eq_inf', id_eq, ofDual_inf', Function.comp_apply, coe_sup', max'_eq_sup',
sup_image]
rfl
#align finset.of_dual_min' Finset.ofDual_min'
theorem ofDual_max' {s : Finset αᵒᵈ} (hs : s.Nonempty) :
ofDual (max' s hs) = min' (s.image ofDual) (hs.image _) := by
rw [← WithTop.coe_eq_coe]
simp only [max'_eq_sup', id_eq, ofDual_sup', Function.comp_apply, coe_inf', min'_eq_inf',
inf_image]
rfl
#align finset.of_dual_max' Finset.ofDual_max'
theorem toDual_min' {s : Finset α} (hs : s.Nonempty) :
toDual (min' s hs) = max' (s.image toDual) (hs.image _) := by
rw [← WithBot.coe_eq_coe]
simp only [min'_eq_inf', id_eq, toDual_inf', Function.comp_apply, coe_sup', max'_eq_sup',
sup_image]
rfl
#align finset.to_dual_min' Finset.toDual_min'
theorem toDual_max' {s : Finset α} (hs : s.Nonempty) :
toDual (max' s hs) = min' (s.image toDual) (hs.image _) := by
rw [← WithTop.coe_eq_coe]
simp only [max'_eq_sup', id_eq, toDual_sup', Function.comp_apply, coe_inf', min'_eq_inf',
inf_image]
rfl
#align finset.to_dual_max' Finset.toDual_max'
theorem max'_subset {s t : Finset α} (H : s.Nonempty) (hst : s ⊆ t) :
s.max' H ≤ t.max' (H.mono hst) :=
le_max' _ _ (hst (s.max'_mem H))
#align finset.max'_subset Finset.max'_subset
theorem min'_subset {s t : Finset α} (H : s.Nonempty) (hst : s ⊆ t) :
t.min' (H.mono hst) ≤ s.min' H :=
min'_le _ _ (hst (s.min'_mem H))
#align finset.min'_subset Finset.min'_subset
theorem max'_insert (a : α) (s : Finset α) (H : s.Nonempty) :
(insert a s).max' (s.insert_nonempty a) = max (s.max' H) a :=
(isGreatest_max' _ _).unique <| by
rw [coe_insert, max_comm]
exact (isGreatest_max' _ _).insert _
#align finset.max'_insert Finset.max'_insert
theorem min'_insert (a : α) (s : Finset α) (H : s.Nonempty) :
(insert a s).min' (s.insert_nonempty a) = min (s.min' H) a :=
(isLeast_min' _ _).unique <| by
rw [coe_insert, min_comm]
exact (isLeast_min' _ _).insert _
#align finset.min'_insert Finset.min'_insert
theorem lt_max'_of_mem_erase_max' [DecidableEq α] {a : α} (ha : a ∈ s.erase (s.max' H)) :
a < s.max' H :=
lt_of_le_of_ne (le_max' _ _ (mem_of_mem_erase ha)) <| ne_of_mem_of_not_mem ha <| not_mem_erase _ _
#align finset.lt_max'_of_mem_erase_max' Finset.lt_max'_of_mem_erase_max'
theorem min'_lt_of_mem_erase_min' [DecidableEq α] {a : α} (ha : a ∈ s.erase (s.min' H)) :
s.min' H < a :=
@lt_max'_of_mem_erase_max' αᵒᵈ _ s H _ a ha
#align finset.min'_lt_of_mem_erase_min' Finset.min'_lt_of_mem_erase_min'
/-- To rewrite from right to left, use `Monotone.map_finset_max'`. -/
@[simp]
theorem max'_image [LinearOrder β] {f : α → β} (hf : Monotone f) (s : Finset α)
(h : (s.image f).Nonempty) : (s.image f).max' h = f (s.max' h.of_image) := by
simp only [max', sup'_image]
exact .symm <| comp_sup'_eq_sup'_comp _ _ fun _ _ ↦ hf.map_max
#align finset.max'_image Finset.max'_image
/-- A version of `Finset.max'_image` with LHS and RHS reversed.
Also, this version assumes that `s` is nonempty, not its image. -/
lemma _root_.Monotone.map_finset_max' [LinearOrder β] {f : α → β} (hf : Monotone f) {s : Finset α}
(h : s.Nonempty) : f (s.max' h) = (s.image f).max' (h.image f) :=
.symm <| max'_image hf ..
/-- To rewrite from right to left, use `Monotone.map_finset_min'`. -/
@[simp]
theorem min'_image [LinearOrder β] {f : α → β} (hf : Monotone f) (s : Finset α)
(h : (s.image f).Nonempty) : (s.image f).min' h = f (s.min' h.of_image) := by
simp only [min', inf'_image]
exact .symm <| comp_inf'_eq_inf'_comp _ _ fun _ _ ↦ hf.map_min
#align finset.min'_image Finset.min'_image
/-- A version of `Finset.min'_image` with LHS and RHS reversed.
Also, this version assumes that `s` is nonempty, not its image. -/
lemma _root_.Monotone.map_finset_min' [LinearOrder β] {f : α → β} (hf : Monotone f) {s : Finset α}
(h : s.Nonempty) : f (s.min' h) = (s.image f).min' (h.image f) :=
.symm <| min'_image hf ..
theorem coe_max' {s : Finset α} (hs : s.Nonempty) : ↑(s.max' hs) = s.max :=
coe_sup' hs id
#align finset.coe_max' Finset.coe_max'
theorem coe_min' {s : Finset α} (hs : s.Nonempty) : ↑(s.min' hs) = s.min :=
coe_inf' hs id
#align finset.coe_min' Finset.coe_min'
theorem max_mem_image_coe {s : Finset α} (hs : s.Nonempty) :
s.max ∈ (s.image (↑) : Finset (WithBot α)) :=
mem_image.2 ⟨max' s hs, max'_mem _ _, coe_max' hs⟩
#align finset.max_mem_image_coe Finset.max_mem_image_coe
theorem min_mem_image_coe {s : Finset α} (hs : s.Nonempty) :
s.min ∈ (s.image (↑) : Finset (WithTop α)) :=
mem_image.2 ⟨min' s hs, min'_mem _ _, coe_min' hs⟩
#align finset.min_mem_image_coe Finset.min_mem_image_coe
theorem max_mem_insert_bot_image_coe (s : Finset α) :
s.max ∈ (insert ⊥ (s.image (↑)) : Finset (WithBot α)) :=
mem_insert.2 <| s.eq_empty_or_nonempty.imp max_eq_bot.2 max_mem_image_coe
#align finset.max_mem_insert_bot_image_coe Finset.max_mem_insert_bot_image_coe
theorem min_mem_insert_top_image_coe (s : Finset α) :
s.min ∈ (insert ⊤ (s.image (↑)) : Finset (WithTop α)) :=
mem_insert.2 <| s.eq_empty_or_nonempty.imp min_eq_top.2 min_mem_image_coe
#align finset.min_mem_insert_top_image_coe Finset.min_mem_insert_top_image_coe
theorem max'_erase_ne_self {s : Finset α} (s0 : (s.erase x).Nonempty) : (s.erase x).max' s0 ≠ x :=
ne_of_mem_erase (max'_mem _ s0)
#align finset.max'_erase_ne_self Finset.max'_erase_ne_self
theorem min'_erase_ne_self {s : Finset α} (s0 : (s.erase x).Nonempty) : (s.erase x).min' s0 ≠ x :=
ne_of_mem_erase (min'_mem _ s0)
#align finset.min'_erase_ne_self Finset.min'_erase_ne_self
theorem max_erase_ne_self {s : Finset α} : (s.erase x).max ≠ x := by
by_cases s0 : (s.erase x).Nonempty
· refine ne_of_eq_of_ne (coe_max' s0).symm ?_
exact WithBot.coe_eq_coe.not.mpr (max'_erase_ne_self _)
· rw [not_nonempty_iff_eq_empty.mp s0, max_empty]
exact WithBot.bot_ne_coe
#align finset.max_erase_ne_self Finset.max_erase_ne_self
theorem min_erase_ne_self {s : Finset α} : (s.erase x).min ≠ x := by
-- Porting note: old proof `convert @max_erase_ne_self αᵒᵈ _ _ _`
convert @max_erase_ne_self αᵒᵈ _ (toDual x) (s.map toDual.toEmbedding) using 1
apply congr_arg -- Porting note: forces unfolding to see `Finset.min` is `Finset.max`
congr!
ext; simp only [mem_map_equiv]; exact Iff.rfl
#align finset.min_erase_ne_self Finset.min_erase_ne_self
theorem exists_next_right {x : α} {s : Finset α} (h : ∃ y ∈ s, x < y) :
∃ y ∈ s, x < y ∧ ∀ z ∈ s, x < z → y ≤ z :=
have Hne : (s.filter (x < ·)).Nonempty := h.imp fun y hy => mem_filter.2 (by simpa)
have aux := mem_filter.1 (min'_mem _ Hne)
⟨min' _ Hne, aux.1, by simp, fun z hzs hz => min'_le _ _ <| mem_filter.2 ⟨hzs, by simpa⟩⟩
#align finset.exists_next_right Finset.exists_next_right
theorem exists_next_left {x : α} {s : Finset α} (h : ∃ y ∈ s, y < x) :
∃ y ∈ s, y < x ∧ ∀ z ∈ s, z < x → z ≤ y :=
@exists_next_right αᵒᵈ _ x s h
#align finset.exists_next_left Finset.exists_next_left
/-- If finsets `s` and `t` are interleaved, then `Finset.card s ≤ Finset.card t + 1`. -/
theorem card_le_of_interleaved {s t : Finset α}
(h : ∀ᵉ (x ∈ s) (y ∈ s),
x < y → (∀ z ∈ s, z ∉ Set.Ioo x y) → ∃ z ∈ t, x < z ∧ z < y) :
s.card ≤ t.card + 1 := by
replace h : ∀ᵉ (x ∈ s) (y ∈ s), x < y → ∃ z ∈ t, x < z ∧ z < y := by
intro x hx y hy hxy
rcases exists_next_right ⟨y, hy, hxy⟩ with ⟨a, has, hxa, ha⟩
rcases h x hx a has hxa fun z hzs hz => hz.2.not_le <| ha _ hzs hz.1 with ⟨b, hbt, hxb, hba⟩
exact ⟨b, hbt, hxb, hba.trans_le <| ha _ hy hxy⟩
set f : α → WithTop α := fun x => (t.filter fun y => x < y).min
have f_mono : StrictMonoOn f s := by
intro x hx y hy hxy
rcases h x hx y hy hxy with ⟨a, hat, hxa, hay⟩
calc
f x ≤ a := min_le (mem_filter.2 ⟨hat, by simpa⟩)
_ < f y :=
(Finset.lt_inf_iff <| WithTop.coe_lt_top a).2 fun b hb =>
WithTop.coe_lt_coe.2 <| hay.trans (by simpa using (mem_filter.1 hb).2)
calc
s.card = (s.image f).card := (card_image_of_injOn f_mono.injOn).symm
_ ≤ (insert ⊤ (t.image (↑)) : Finset (WithTop α)).card :=
card_mono <| image_subset_iff.2 fun x _ =>
insert_subset_insert _ (image_subset_image <| filter_subset _ _)
(min_mem_insert_top_image_coe _)
_ ≤ t.card + 1 := (card_insert_le _ _).trans (Nat.add_le_add_right card_image_le _)
#align finset.card_le_of_interleaved Finset.card_le_of_interleaved
/-- If finsets `s` and `t` are interleaved, then `Finset.card s ≤ Finset.card (t \ s) + 1`. -/
theorem card_le_diff_of_interleaved {s t : Finset α}
(h :
∀ᵉ (x ∈ s) (y ∈ s),
x < y → (∀ z ∈ s, z ∉ Set.Ioo x y) → ∃ z ∈ t, x < z ∧ z < y) :
s.card ≤ (t \ s).card + 1 :=
card_le_of_interleaved fun x hx y hy hxy hs =>
let ⟨z, hzt, hxz, hzy⟩ := h x hx y hy hxy hs
⟨z, mem_sdiff.2 ⟨hzt, fun hzs => hs z hzs ⟨hxz, hzy⟩⟩, hxz, hzy⟩
#align finset.card_le_diff_of_interleaved Finset.card_le_diff_of_interleaved
/-- Induction principle for `Finset`s in a linearly ordered type: a predicate is true on all
`s : Finset α` provided that:
* it is true on the empty `Finset`,
* for every `s : Finset α` and an element `a` strictly greater than all elements of `s`, `p s`
implies `p (insert a s)`. -/
@[elab_as_elim]
theorem induction_on_max [DecidableEq α] {p : Finset α → Prop} (s : Finset α) (h0 : p ∅)
(step : ∀ a s, (∀ x ∈ s, x < a) → p s → p (insert a s)) : p s := by
induction' s using Finset.strongInductionOn with s ihs
rcases s.eq_empty_or_nonempty with (rfl | hne)
· exact h0
· have H : s.max' hne ∈ s := max'_mem s hne
rw [← insert_erase H]
exact step _ _ (fun x => s.lt_max'_of_mem_erase_max' hne) (ihs _ <| erase_ssubset H)
#align finset.induction_on_max Finset.induction_on_max
/-- Induction principle for `Finset`s in a linearly ordered type: a predicate is true on all
`s : Finset α` provided that:
* it is true on the empty `Finset`,
* for every `s : Finset α` and an element `a` strictly less than all elements of `s`, `p s`
implies `p (insert a s)`. -/
@[elab_as_elim]
theorem induction_on_min [DecidableEq α] {p : Finset α → Prop} (s : Finset α) (h0 : p ∅)
(step : ∀ a s, (∀ x ∈ s, a < x) → p s → p (insert a s)) : p s :=
@induction_on_max αᵒᵈ _ _ _ s h0 step
#align finset.induction_on_min Finset.induction_on_min
end MaxMin
section MaxMinInductionValue
variable [LinearOrder α] [LinearOrder β]
/-- Induction principle for `Finset`s in any type from which a given function `f` maps to a linearly
ordered type : a predicate is true on all `s : Finset α` provided that:
* it is true on the empty `Finset`,
* for every `s : Finset α` and an element `a` such that for elements of `s` denoted by `x` we have
`f x ≤ f a`, `p s` implies `p (insert a s)`. -/
@[elab_as_elim]
theorem induction_on_max_value [DecidableEq ι] (f : ι → α) {p : Finset ι → Prop} (s : Finset ι)
(h0 : p ∅) (step : ∀ a s, a ∉ s → (∀ x ∈ s, f x ≤ f a) → p s → p (insert a s)) : p s := by
induction' s using Finset.strongInductionOn with s ihs
rcases (s.image f).eq_empty_or_nonempty with (hne | hne)
· simp only [image_eq_empty] at hne
simp only [hne, h0]
· have H : (s.image f).max' hne ∈ s.image f := max'_mem (s.image f) hne
simp only [mem_image, exists_prop] at H
rcases H with ⟨a, has, hfa⟩
rw [← insert_erase has]
refine step _ _ (not_mem_erase a s) (fun x hx => ?_) (ihs _ <| erase_ssubset has)
rw [hfa]
exact le_max' _ _ (mem_image_of_mem _ <| mem_of_mem_erase hx)
#align finset.induction_on_max_value Finset.induction_on_max_value
/-- Induction principle for `Finset`s in any type from which a given function `f` maps to a linearly
ordered type : a predicate is true on all `s : Finset α` provided that:
* it is true on the empty `Finset`,
* for every `s : Finset α` and an element `a` such that for elements of `s` denoted by `x` we have
`f a ≤ f x`, `p s` implies `p (insert a s)`. -/
@[elab_as_elim]
theorem induction_on_min_value [DecidableEq ι] (f : ι → α) {p : Finset ι → Prop} (s : Finset ι)
(h0 : p ∅) (step : ∀ a s, a ∉ s → (∀ x ∈ s, f a ≤ f x) → p s → p (insert a s)) : p s :=
@induction_on_max_value αᵒᵈ ι _ _ _ _ s h0 step
#align finset.induction_on_min_value Finset.induction_on_min_value
end MaxMinInductionValue
section ExistsMaxMin
variable [LinearOrder α]
theorem exists_max_image (s : Finset β) (f : β → α) (h : s.Nonempty) :
∃ x ∈ s, ∀ x' ∈ s, f x' ≤ f x := by
cases' max_of_nonempty (h.image f) with y hy
rcases mem_image.mp (mem_of_max hy) with ⟨x, hx, rfl⟩
exact ⟨x, hx, fun x' hx' => le_max_of_eq (mem_image_of_mem f hx') hy⟩
#align finset.exists_max_image Finset.exists_max_image
theorem exists_min_image (s : Finset β) (f : β → α) (h : s.Nonempty) :
∃ x ∈ s, ∀ x' ∈ s, f x ≤ f x' :=
@exists_max_image αᵒᵈ β _ s f h
#align finset.exists_min_image Finset.exists_min_image
end ExistsMaxMin
theorem isGLB_iff_isLeast [LinearOrder α] (i : α) (s : Finset α) (hs : s.Nonempty) :
IsGLB (s : Set α) i ↔ IsLeast (↑s) i := by
refine ⟨fun his => ?_, IsLeast.isGLB⟩
suffices i = min' s hs by
rw [this]
exact isLeast_min' s hs
rw [IsGLB, IsGreatest, mem_lowerBounds, mem_upperBounds] at his
exact le_antisymm (his.1 (Finset.min' s hs) (Finset.min'_mem s hs)) (his.2 _ (Finset.min'_le s))
#align finset.is_glb_iff_is_least Finset.isGLB_iff_isLeast
theorem isLUB_iff_isGreatest [LinearOrder α] (i : α) (s : Finset α) (hs : s.Nonempty) :
IsLUB (s : Set α) i ↔ IsGreatest (↑s) i :=
@isGLB_iff_isLeast αᵒᵈ _ i s hs
#align finset.is_lub_iff_is_greatest Finset.isLUB_iff_isGreatest
theorem isGLB_mem [LinearOrder α] {i : α} (s : Finset α) (his : IsGLB (s : Set α) i)
(hs : s.Nonempty) : i ∈ s := by
rw [← mem_coe]
exact ((isGLB_iff_isLeast i s hs).mp his).1
#align finset.is_glb_mem Finset.isGLB_mem
theorem isLUB_mem [LinearOrder α] {i : α} (s : Finset α) (his : IsLUB (s : Set α) i)
(hs : s.Nonempty) : i ∈ s :=
@isGLB_mem αᵒᵈ _ i s his hs
#align finset.is_lub_mem Finset.isLUB_mem
end Finset
namespace Multiset
theorem map_finset_sup [DecidableEq α] [DecidableEq β] (s : Finset γ) (f : γ → Multiset β)
(g : β → α) (hg : Function.Injective g) : map g (s.sup f) = s.sup (map g ∘ f) :=
Finset.comp_sup_eq_sup_comp _ (fun _ _ => map_union hg) (map_zero _)
#align multiset.map_finset_sup Multiset.map_finset_sup
theorem count_finset_sup [DecidableEq β] (s : Finset α) (f : α → Multiset β) (b : β) :
count b (s.sup f) = s.sup fun a => count b (f a) := by
letI := Classical.decEq α
refine s.induction ?_ ?_
· exact count_zero _
· intro i s _ ih
rw [Finset.sup_insert, sup_eq_union, count_union, Finset.sup_insert, ih]
rfl
#align multiset.count_finset_sup Multiset.count_finset_sup
theorem mem_sup {α β} [DecidableEq β] {s : Finset α} {f : α → Multiset β} {x : β} :
x ∈ s.sup f ↔ ∃ v ∈ s, x ∈ f v := by
induction s using Finset.cons_induction <;> simp [*]
#align multiset.mem_sup Multiset.mem_sup
end Multiset
namespace Finset
theorem mem_sup {α β} [DecidableEq β] {s : Finset α} {f : α → Finset β} {x : β} :
x ∈ s.sup f ↔ ∃ v ∈ s, x ∈ f v := by
change _ ↔ ∃ v ∈ s, x ∈ (f v).val
rw [← Multiset.mem_sup, ← Multiset.mem_toFinset, sup_toFinset]
simp_rw [val_toFinset]
#align finset.mem_sup Finset.mem_sup
theorem sup_eq_biUnion {α β} [DecidableEq β] (s : Finset α) (t : α → Finset β) :
s.sup t = s.biUnion t := by
ext
rw [mem_sup, mem_biUnion]
#align finset.sup_eq_bUnion Finset.sup_eq_biUnion
@[simp]
theorem sup_singleton'' [DecidableEq α] (s : Finset β) (f : β → α) :
(s.sup fun b => {f b}) = s.image f := by
ext a
rw [mem_sup, mem_image]
simp only [mem_singleton, eq_comm]
#align finset.sup_singleton'' Finset.sup_singleton''
@[simp]
theorem sup_singleton' [DecidableEq α] (s : Finset α) : s.sup singleton = s :=
(s.sup_singleton'' _).trans image_id
#align finset.sup_singleton' Finset.sup_singleton'
end Finset
section Lattice
variable {ι' : Sort*} [CompleteLattice α]
/-- Supremum of `s i`, `i : ι`, is equal to the supremum over `t : Finset ι` of suprema
`⨆ i ∈ t, s i`. This version assumes `ι` is a `Type*`. See `iSup_eq_iSup_finset'` for a version
that works for `ι : Sort*`. -/
theorem iSup_eq_iSup_finset (s : ι → α) : ⨆ i, s i = ⨆ t : Finset ι, ⨆ i ∈ t, s i := by
classical
refine le_antisymm ?_ ?_
· exact iSup_le fun b => le_iSup_of_le {b} <| le_iSup_of_le b <| le_iSup_of_le (by simp) <| le_rfl
· exact iSup_le fun t => iSup_le fun b => iSup_le fun _ => le_iSup _ _
#align supr_eq_supr_finset iSup_eq_iSup_finset
/-- Supremum of `s i`, `i : ι`, is equal to the supremum over `t : Finset ι` of suprema
`⨆ i ∈ t, s i`. This version works for `ι : Sort*`. See `iSup_eq_iSup_finset` for a version
that assumes `ι : Type*` but has no `PLift`s. -/
theorem iSup_eq_iSup_finset' (s : ι' → α) :
⨆ i, s i = ⨆ t : Finset (PLift ι'), ⨆ i ∈ t, s (PLift.down i) := by
rw [← iSup_eq_iSup_finset, ← Equiv.plift.surjective.iSup_comp]; rfl
#align supr_eq_supr_finset' iSup_eq_iSup_finset'
/-- Infimum of `s i`, `i : ι`, is equal to the infimum over `t : Finset ι` of infima
`⨅ i ∈ t, s i`. This version assumes `ι` is a `Type*`. See `iInf_eq_iInf_finset'` for a version
that works for `ι : Sort*`. -/
theorem iInf_eq_iInf_finset (s : ι → α) : ⨅ i, s i = ⨅ (t : Finset ι) (i ∈ t), s i :=
@iSup_eq_iSup_finset αᵒᵈ _ _ _
#align infi_eq_infi_finset iInf_eq_iInf_finset
/-- Infimum of `s i`, `i : ι`, is equal to the infimum over `t : Finset ι` of infima
`⨅ i ∈ t, s i`. This version works for `ι : Sort*`. See `iInf_eq_iInf_finset` for a version
that assumes `ι : Type*` but has no `PLift`s. -/
theorem iInf_eq_iInf_finset' (s : ι' → α) :
⨅ i, s i = ⨅ t : Finset (PLift ι'), ⨅ i ∈ t, s (PLift.down i) :=
@iSup_eq_iSup_finset' αᵒᵈ _ _ _
#align infi_eq_infi_finset' iInf_eq_iInf_finset'
end Lattice
namespace Set
variable {ι' : Sort*}
/-- Union of an indexed family of sets `s : ι → Set α` is equal to the union of the unions
of finite subfamilies. This version assumes `ι : Type*`. See also `iUnion_eq_iUnion_finset'` for
a version that works for `ι : Sort*`. -/
theorem iUnion_eq_iUnion_finset (s : ι → Set α) : ⋃ i, s i = ⋃ t : Finset ι, ⋃ i ∈ t, s i :=
iSup_eq_iSup_finset s
#align set.Union_eq_Union_finset Set.iUnion_eq_iUnion_finset
/-- Union of an indexed family of sets `s : ι → Set α` is equal to the union of the unions
of finite subfamilies. This version works for `ι : Sort*`. See also `iUnion_eq_iUnion_finset` for
a version that assumes `ι : Type*` but avoids `PLift`s in the right hand side. -/
theorem iUnion_eq_iUnion_finset' (s : ι' → Set α) :
⋃ i, s i = ⋃ t : Finset (PLift ι'), ⋃ i ∈ t, s (PLift.down i) :=
iSup_eq_iSup_finset' s
#align set.Union_eq_Union_finset' Set.iUnion_eq_iUnion_finset'
/-- Intersection of an indexed family of sets `s : ι → Set α` is equal to the intersection of the
intersections of finite subfamilies. This version assumes `ι : Type*`. See also
`iInter_eq_iInter_finset'` for a version that works for `ι : Sort*`. -/
theorem iInter_eq_iInter_finset (s : ι → Set α) : ⋂ i, s i = ⋂ t : Finset ι, ⋂ i ∈ t, s i :=
iInf_eq_iInf_finset s
#align set.Inter_eq_Inter_finset Set.iInter_eq_iInter_finset
/-- Intersection of an indexed family of sets `s : ι → Set α` is equal to the intersection of the
intersections of finite subfamilies. This version works for `ι : Sort*`. See also
`iInter_eq_iInter_finset` for a version that assumes `ι : Type*` but avoids `PLift`s in the right
hand side. -/
theorem iInter_eq_iInter_finset' (s : ι' → Set α) :
⋂ i, s i = ⋂ t : Finset (PLift ι'), ⋂ i ∈ t, s (PLift.down i) :=
iInf_eq_iInf_finset' s
#align set.Inter_eq_Inter_finset' Set.iInter_eq_iInter_finset'
end Set
namespace Finset
/-! ### Interaction with big lattice/set operations -/
section Lattice
theorem iSup_coe [SupSet β] (f : α → β) (s : Finset α) : ⨆ x ∈ (↑s : Set α), f x = ⨆ x ∈ s, f x :=
rfl
#align finset.supr_coe Finset.iSup_coe
theorem iInf_coe [InfSet β] (f : α → β) (s : Finset α) : ⨅ x ∈ (↑s : Set α), f x = ⨅ x ∈ s, f x :=
rfl
#align finset.infi_coe Finset.iInf_coe
variable [CompleteLattice β]
theorem iSup_singleton (a : α) (s : α → β) : ⨆ x ∈ ({a} : Finset α), s x = s a := by simp
#align finset.supr_singleton Finset.iSup_singleton
theorem iInf_singleton (a : α) (s : α → β) : ⨅ x ∈ ({a} : Finset α), s x = s a := by simp
#align finset.infi_singleton Finset.iInf_singleton
theorem iSup_option_toFinset (o : Option α) (f : α → β) : ⨆ x ∈ o.toFinset, f x = ⨆ x ∈ o, f x := by
simp
#align finset.supr_option_to_finset Finset.iSup_option_toFinset
theorem iInf_option_toFinset (o : Option α) (f : α → β) : ⨅ x ∈ o.toFinset, f x = ⨅ x ∈ o, f x :=
@iSup_option_toFinset _ βᵒᵈ _ _ _
#align finset.infi_option_to_finset Finset.iInf_option_toFinset
variable [DecidableEq α]
theorem iSup_union {f : α → β} {s t : Finset α} :
⨆ x ∈ s ∪ t, f x = (⨆ x ∈ s, f x) ⊔ ⨆ x ∈ t, f x := by simp [iSup_or, iSup_sup_eq]
#align finset.supr_union Finset.iSup_union
theorem iInf_union {f : α → β} {s t : Finset α} :
⨅ x ∈ s ∪ t, f x = (⨅ x ∈ s, f x) ⊓ ⨅ x ∈ t, f x :=
@iSup_union α βᵒᵈ _ _ _ _ _
#align finset.infi_union Finset.iInf_union
| Mathlib/Data/Finset/Lattice.lean | 2,118 | 2,121 | theorem iSup_insert (a : α) (s : Finset α) (t : α → β) :
⨆ x ∈ insert a s, t x = t a ⊔ ⨆ x ∈ s, t x := by |
rw [insert_eq]
simp only [iSup_union, Finset.iSup_singleton]
|
/-
Copyright (c) 2020 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Measure.GiryMonad
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.MeasureTheory.Integral.Lebesgue
import Mathlib.MeasureTheory.Measure.OpenPos
#align_import measure_theory.constructions.prod.basic from "leanprover-community/mathlib"@"00abe0695d8767201e6d008afa22393978bb324d"
/-!
# The product measure
In this file we define and prove properties about the binary product measure. If `α` and `β` have
s-finite measures `μ` resp. `ν` then `α × β` can be equipped with a s-finite measure `μ.prod ν` that
satisfies `(μ.prod ν) s = ∫⁻ x, ν {y | (x, y) ∈ s} ∂μ`.
We also have `(μ.prod ν) (s ×ˢ t) = μ s * ν t`, i.e. the measure of a rectangle is the product of
the measures of the sides.
We also prove Tonelli's theorem.
## Main definition
* `MeasureTheory.Measure.prod`: The product of two measures.
## Main results
* `MeasureTheory.Measure.prod_apply` states `μ.prod ν s = ∫⁻ x, ν {y | (x, y) ∈ s} ∂μ`
for measurable `s`. `MeasureTheory.Measure.prod_apply_symm` is the reversed version.
* `MeasureTheory.Measure.prod_prod` states `μ.prod ν (s ×ˢ t) = μ s * ν t` for measurable sets
`s` and `t`.
* `MeasureTheory.lintegral_prod`: Tonelli's theorem. It states that for a measurable function
`α × β → ℝ≥0∞` we have `∫⁻ z, f z ∂(μ.prod ν) = ∫⁻ x, ∫⁻ y, f (x, y) ∂ν ∂μ`. The version
for functions `α → β → ℝ≥0∞` is reversed, and called `lintegral_lintegral`. Both versions have
a variant with `_symm` appended, where the order of integration is reversed.
The lemma `Measurable.lintegral_prod_right'` states that the inner integral of the right-hand side
is measurable.
## Implementation Notes
Many results are proven twice, once for functions in curried form (`α → β → γ`) and one for
functions in uncurried form (`α × β → γ`). The former often has an assumption
`Measurable (uncurry f)`, which could be inconvenient to discharge, but for the latter it is more
common that the function has to be given explicitly, since Lean cannot synthesize the function by
itself. We name the lemmas about the uncurried form with a prime.
Tonelli's theorem has a different naming scheme, since the version for the uncurried version is
reversed.
## Tags
product measure, Tonelli's theorem, Fubini-Tonelli theorem
-/
noncomputable section
open scoped Classical
open Topology ENNReal MeasureTheory
open Set Function Real ENNReal
open MeasureTheory MeasurableSpace MeasureTheory.Measure
open TopologicalSpace hiding generateFrom
open Filter hiding prod_eq map
variable {α α' β β' γ E : Type*}
/-- Rectangles formed by π-systems form a π-system. -/
theorem IsPiSystem.prod {C : Set (Set α)} {D : Set (Set β)} (hC : IsPiSystem C)
(hD : IsPiSystem D) : IsPiSystem (image2 (· ×ˢ ·) C D) := by
rintro _ ⟨s₁, hs₁, t₁, ht₁, rfl⟩ _ ⟨s₂, hs₂, t₂, ht₂, rfl⟩ hst
rw [prod_inter_prod] at hst ⊢; rw [prod_nonempty_iff] at hst
exact mem_image2_of_mem (hC _ hs₁ _ hs₂ hst.1) (hD _ ht₁ _ ht₂ hst.2)
#align is_pi_system.prod IsPiSystem.prod
/-- Rectangles of countably spanning sets are countably spanning. -/
theorem IsCountablySpanning.prod {C : Set (Set α)} {D : Set (Set β)} (hC : IsCountablySpanning C)
(hD : IsCountablySpanning D) : IsCountablySpanning (image2 (· ×ˢ ·) C D) := by
rcases hC, hD with ⟨⟨s, h1s, h2s⟩, t, h1t, h2t⟩
refine ⟨fun n => s n.unpair.1 ×ˢ t n.unpair.2, fun n => mem_image2_of_mem (h1s _) (h1t _), ?_⟩
rw [iUnion_unpair_prod, h2s, h2t, univ_prod_univ]
#align is_countably_spanning.prod IsCountablySpanning.prod
variable [MeasurableSpace α] [MeasurableSpace α'] [MeasurableSpace β] [MeasurableSpace β']
variable [MeasurableSpace γ]
variable {μ μ' : Measure α} {ν ν' : Measure β} {τ : Measure γ}
variable [NormedAddCommGroup E]
/-! ### Measurability
Before we define the product measure, we can talk about the measurability of operations on binary
functions. We show that if `f` is a binary measurable function, then the function that integrates
along one of the variables (using either the Lebesgue or Bochner integral) is measurable.
-/
/-- The product of generated σ-algebras is the one generated by rectangles, if both generating sets
are countably spanning. -/
theorem generateFrom_prod_eq {α β} {C : Set (Set α)} {D : Set (Set β)} (hC : IsCountablySpanning C)
(hD : IsCountablySpanning D) :
@Prod.instMeasurableSpace _ _ (generateFrom C) (generateFrom D) =
generateFrom (image2 (· ×ˢ ·) C D) := by
apply le_antisymm
· refine sup_le ?_ ?_ <;> rw [comap_generateFrom] <;> apply generateFrom_le <;>
rintro _ ⟨s, hs, rfl⟩
· rcases hD with ⟨t, h1t, h2t⟩
rw [← prod_univ, ← h2t, prod_iUnion]
apply MeasurableSet.iUnion
intro n
apply measurableSet_generateFrom
exact ⟨s, hs, t n, h1t n, rfl⟩
· rcases hC with ⟨t, h1t, h2t⟩
rw [← univ_prod, ← h2t, iUnion_prod_const]
apply MeasurableSet.iUnion
rintro n
apply measurableSet_generateFrom
exact mem_image2_of_mem (h1t n) hs
· apply generateFrom_le
rintro _ ⟨s, hs, t, ht, rfl⟩
dsimp only
rw [prod_eq]
apply (measurable_fst _).inter (measurable_snd _)
· exact measurableSet_generateFrom hs
· exact measurableSet_generateFrom ht
#align generate_from_prod_eq generateFrom_prod_eq
/-- If `C` and `D` generate the σ-algebras on `α` resp. `β`, then rectangles formed by `C` and `D`
generate the σ-algebra on `α × β`. -/
theorem generateFrom_eq_prod {C : Set (Set α)} {D : Set (Set β)} (hC : generateFrom C = ‹_›)
(hD : generateFrom D = ‹_›) (h2C : IsCountablySpanning C) (h2D : IsCountablySpanning D) :
generateFrom (image2 (· ×ˢ ·) C D) = Prod.instMeasurableSpace := by
rw [← hC, ← hD, generateFrom_prod_eq h2C h2D]
#align generate_from_eq_prod generateFrom_eq_prod
/-- The product σ-algebra is generated from boxes, i.e. `s ×ˢ t` for sets `s : Set α` and
`t : Set β`. -/
theorem generateFrom_prod :
generateFrom (image2 (· ×ˢ ·) { s : Set α | MeasurableSet s } { t : Set β | MeasurableSet t }) =
Prod.instMeasurableSpace :=
generateFrom_eq_prod generateFrom_measurableSet generateFrom_measurableSet
isCountablySpanning_measurableSet isCountablySpanning_measurableSet
#align generate_from_prod generateFrom_prod
/-- Rectangles form a π-system. -/
theorem isPiSystem_prod :
IsPiSystem (image2 (· ×ˢ ·) { s : Set α | MeasurableSet s } { t : Set β | MeasurableSet t }) :=
isPiSystem_measurableSet.prod isPiSystem_measurableSet
#align is_pi_system_prod isPiSystem_prod
/-- If `ν` is a finite measure, and `s ⊆ α × β` is measurable, then `x ↦ ν { y | (x, y) ∈ s }` is
a measurable function. `measurable_measure_prod_mk_left` is strictly more general. -/
theorem measurable_measure_prod_mk_left_finite [IsFiniteMeasure ν] {s : Set (α × β)}
(hs : MeasurableSet s) : Measurable fun x => ν (Prod.mk x ⁻¹' s) := by
refine induction_on_inter (C := fun s => Measurable fun x => ν (Prod.mk x ⁻¹' s))
generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ hs
· simp
· rintro _ ⟨s, hs, t, _, rfl⟩
simp only [mk_preimage_prod_right_eq_if, measure_if]
exact measurable_const.indicator hs
· intro t ht h2t
simp_rw [preimage_compl, measure_compl (measurable_prod_mk_left ht) (measure_ne_top ν _)]
exact h2t.const_sub _
· intro f h1f h2f h3f
simp_rw [preimage_iUnion]
have : ∀ b, ν (⋃ i, Prod.mk b ⁻¹' f i) = ∑' i, ν (Prod.mk b ⁻¹' f i) := fun b =>
measure_iUnion (fun i j hij => Disjoint.preimage _ (h1f hij)) fun i =>
measurable_prod_mk_left (h2f i)
simp_rw [this]
apply Measurable.ennreal_tsum h3f
#align measurable_measure_prod_mk_left_finite measurable_measure_prod_mk_left_finite
/-- If `ν` is an s-finite measure, and `s ⊆ α × β` is measurable, then `x ↦ ν { y | (x, y) ∈ s }`
is a measurable function. -/
theorem measurable_measure_prod_mk_left [SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
Measurable fun x => ν (Prod.mk x ⁻¹' s) := by
rw [← sum_sFiniteSeq ν]
simp_rw [Measure.sum_apply_of_countable]
exact Measurable.ennreal_tsum (fun i ↦ measurable_measure_prod_mk_left_finite hs)
#align measurable_measure_prod_mk_left measurable_measure_prod_mk_left
/-- If `μ` is a σ-finite measure, and `s ⊆ α × β` is measurable, then `y ↦ μ { x | (x, y) ∈ s }` is
a measurable function. -/
theorem measurable_measure_prod_mk_right {μ : Measure α} [SFinite μ] {s : Set (α × β)}
(hs : MeasurableSet s) : Measurable fun y => μ ((fun x => (x, y)) ⁻¹' s) :=
measurable_measure_prod_mk_left (measurableSet_swap_iff.mpr hs)
#align measurable_measure_prod_mk_right measurable_measure_prod_mk_right
theorem Measurable.map_prod_mk_left [SFinite ν] :
Measurable fun x : α => map (Prod.mk x) ν := by
apply measurable_of_measurable_coe; intro s hs
simp_rw [map_apply measurable_prod_mk_left hs]
exact measurable_measure_prod_mk_left hs
#align measurable.map_prod_mk_left Measurable.map_prod_mk_left
theorem Measurable.map_prod_mk_right {μ : Measure α} [SFinite μ] :
Measurable fun y : β => map (fun x : α => (x, y)) μ := by
apply measurable_of_measurable_coe; intro s hs
simp_rw [map_apply measurable_prod_mk_right hs]
exact measurable_measure_prod_mk_right hs
#align measurable.map_prod_mk_right Measurable.map_prod_mk_right
theorem MeasurableEmbedding.prod_mk {α β γ δ : Type*} {mα : MeasurableSpace α}
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} {mδ : MeasurableSpace δ} {f : α → β}
{g : γ → δ} (hg : MeasurableEmbedding g) (hf : MeasurableEmbedding f) :
MeasurableEmbedding fun x : γ × α => (g x.1, f x.2) := by
have h_inj : Function.Injective fun x : γ × α => (g x.fst, f x.snd) := by
intro x y hxy
rw [← @Prod.mk.eta _ _ x, ← @Prod.mk.eta _ _ y]
simp only [Prod.mk.inj_iff] at hxy ⊢
exact ⟨hg.injective hxy.1, hf.injective hxy.2⟩
refine ⟨h_inj, ?_, ?_⟩
· exact (hg.measurable.comp measurable_fst).prod_mk (hf.measurable.comp measurable_snd)
· -- Induction using the π-system of rectangles
refine fun s hs =>
@MeasurableSpace.induction_on_inter _
(fun s => MeasurableSet ((fun x : γ × α => (g x.fst, f x.snd)) '' s)) _ _
generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ _ hs
· simp only [Set.image_empty, MeasurableSet.empty]
· rintro t ⟨t₁, ht₁, t₂, ht₂, rfl⟩
rw [← Set.prod_image_image_eq]
exact (hg.measurableSet_image.mpr ht₁).prod (hf.measurableSet_image.mpr ht₂)
· intro t _ ht_m
rw [← Set.range_diff_image h_inj, ← Set.prod_range_range_eq]
exact
MeasurableSet.diff (MeasurableSet.prod hg.measurableSet_range hf.measurableSet_range) ht_m
· intro g _ _ hg
simp_rw [Set.image_iUnion]
exact MeasurableSet.iUnion hg
#align measurable_embedding.prod_mk MeasurableEmbedding.prod_mk
lemma MeasurableEmbedding.prod_mk_left {β γ : Type*} [MeasurableSingletonClass α]
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ}
(x : α) {f : γ → β} (hf : MeasurableEmbedding f) :
MeasurableEmbedding (fun y ↦ (x, f y)) where
injective := by
intro y y'
simp only [Prod.mk.injEq, true_and]
exact fun h ↦ hf.injective h
measurable := Measurable.prod_mk measurable_const hf.measurable
measurableSet_image' := by
intro s hs
convert (MeasurableSet.singleton x).prod (hf.measurableSet_image.mpr hs)
ext x
simp
lemma measurableEmbedding_prod_mk_left [MeasurableSingletonClass α] (x : α) :
MeasurableEmbedding (Prod.mk x : β → α × β) :=
MeasurableEmbedding.prod_mk_left x MeasurableEmbedding.id
lemma MeasurableEmbedding.prod_mk_right {β γ : Type*} [MeasurableSingletonClass α]
{mβ : MeasurableSpace β} {mγ : MeasurableSpace γ}
{f : γ → β} (hf : MeasurableEmbedding f) (x : α) :
MeasurableEmbedding (fun y ↦ (f y, x)) where
injective := by
intro y y'
simp only [Prod.mk.injEq, and_true]
exact fun h ↦ hf.injective h
measurable := Measurable.prod_mk hf.measurable measurable_const
measurableSet_image' := by
intro s hs
convert (hf.measurableSet_image.mpr hs).prod (MeasurableSet.singleton x)
ext x
simp
lemma measurableEmbedding_prod_mk_right [MeasurableSingletonClass α] (x : α) :
MeasurableEmbedding (fun y ↦ (y, x) : β → β × α) :=
MeasurableEmbedding.prod_mk_right MeasurableEmbedding.id x
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
Tonelli's theorem is measurable. -/
theorem Measurable.lintegral_prod_right' [SFinite ν] :
∀ {f : α × β → ℝ≥0∞}, Measurable f → Measurable fun x => ∫⁻ y, f (x, y) ∂ν := by
have m := @measurable_prod_mk_left
refine Measurable.ennreal_induction (P := fun f => Measurable fun (x : α) => ∫⁻ y, f (x, y) ∂ν)
?_ ?_ ?_
· intro c s hs
simp only [← indicator_comp_right]
suffices Measurable fun x => c * ν (Prod.mk x ⁻¹' s) by simpa [lintegral_indicator _ (m hs)]
exact (measurable_measure_prod_mk_left hs).const_mul _
· rintro f g - hf - h2f h2g
simp only [Pi.add_apply]
conv => enter [1, x]; erw [lintegral_add_left (hf.comp m)]
exact h2f.add h2g
· intro f hf h2f h3f
have := measurable_iSup h3f
have : ∀ x, Monotone fun n y => f n (x, y) := fun x i j hij y => h2f hij (x, y)
conv => enter [1, x]; erw [lintegral_iSup (fun n => (hf n).comp m) (this x)]
assumption
#align measurable.lintegral_prod_right' Measurable.lintegral_prod_right'
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
Tonelli's theorem is measurable.
This version has the argument `f` in curried form. -/
theorem Measurable.lintegral_prod_right [SFinite ν] {f : α → β → ℝ≥0∞}
(hf : Measurable (uncurry f)) : Measurable fun x => ∫⁻ y, f x y ∂ν :=
hf.lintegral_prod_right'
#align measurable.lintegral_prod_right Measurable.lintegral_prod_right
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Tonelli's theorem is measurable. -/
theorem Measurable.lintegral_prod_left' [SFinite μ] {f : α × β → ℝ≥0∞} (hf : Measurable f) :
Measurable fun y => ∫⁻ x, f (x, y) ∂μ :=
(measurable_swap_iff.mpr hf).lintegral_prod_right'
#align measurable.lintegral_prod_left' Measurable.lintegral_prod_left'
/-- The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Tonelli's theorem is measurable.
This version has the argument `f` in curried form. -/
theorem Measurable.lintegral_prod_left [SFinite μ] {f : α → β → ℝ≥0∞}
(hf : Measurable (uncurry f)) : Measurable fun y => ∫⁻ x, f x y ∂μ :=
hf.lintegral_prod_left'
#align measurable.lintegral_prod_left Measurable.lintegral_prod_left
/-! ### The product measure -/
namespace MeasureTheory
namespace Measure
/-- The binary product of measures. They are defined for arbitrary measures, but we basically
prove all properties under the assumption that at least one of them is s-finite. -/
protected irreducible_def prod (μ : Measure α) (ν : Measure β) : Measure (α × β) :=
bind μ fun x : α => map (Prod.mk x) ν
#align measure_theory.measure.prod MeasureTheory.Measure.prod
instance prod.measureSpace {α β} [MeasureSpace α] [MeasureSpace β] : MeasureSpace (α × β) where
volume := volume.prod volume
#align measure_theory.measure.prod.measure_space MeasureTheory.Measure.prod.measureSpace
theorem volume_eq_prod (α β) [MeasureSpace α] [MeasureSpace β] :
(volume : Measure (α × β)) = (volume : Measure α).prod (volume : Measure β) :=
rfl
#align measure_theory.measure.volume_eq_prod MeasureTheory.Measure.volume_eq_prod
variable [SFinite ν]
theorem prod_apply {s : Set (α × β)} (hs : MeasurableSet s) :
μ.prod ν s = ∫⁻ x, ν (Prod.mk x ⁻¹' s) ∂μ := by
simp_rw [Measure.prod, bind_apply hs (Measurable.map_prod_mk_left (ν := ν)),
map_apply measurable_prod_mk_left hs]
#align measure_theory.measure.prod_apply MeasureTheory.Measure.prod_apply
/-- The product measure of the product of two sets is the product of their measures. Note that we
do not need the sets to be measurable. -/
@[simp]
theorem prod_prod (s : Set α) (t : Set β) : μ.prod ν (s ×ˢ t) = μ s * ν t := by
apply le_antisymm
· set S := toMeasurable μ s
set T := toMeasurable ν t
have hSTm : MeasurableSet (S ×ˢ T) :=
(measurableSet_toMeasurable _ _).prod (measurableSet_toMeasurable _ _)
calc
μ.prod ν (s ×ˢ t) ≤ μ.prod ν (S ×ˢ T) := by gcongr <;> apply subset_toMeasurable
_ = μ S * ν T := by
rw [prod_apply hSTm]
simp_rw [mk_preimage_prod_right_eq_if, measure_if,
lintegral_indicator _ (measurableSet_toMeasurable _ _), lintegral_const,
restrict_apply_univ, mul_comm]
_ = μ s * ν t := by rw [measure_toMeasurable, measure_toMeasurable]
· -- Formalization is based on https://mathoverflow.net/a/254134/136589
set ST := toMeasurable (μ.prod ν) (s ×ˢ t)
have hSTm : MeasurableSet ST := measurableSet_toMeasurable _ _
have hST : s ×ˢ t ⊆ ST := subset_toMeasurable _ _
set f : α → ℝ≥0∞ := fun x => ν (Prod.mk x ⁻¹' ST)
have hfm : Measurable f := measurable_measure_prod_mk_left hSTm
set s' : Set α := { x | ν t ≤ f x }
have hss' : s ⊆ s' := fun x hx => measure_mono fun y hy => hST <| mk_mem_prod hx hy
calc
μ s * ν t ≤ μ s' * ν t := by gcongr
_ = ∫⁻ _ in s', ν t ∂μ := by rw [set_lintegral_const, mul_comm]
_ ≤ ∫⁻ x in s', f x ∂μ := set_lintegral_mono measurable_const hfm fun x => id
_ ≤ ∫⁻ x, f x ∂μ := lintegral_mono' restrict_le_self le_rfl
_ = μ.prod ν ST := (prod_apply hSTm).symm
_ = μ.prod ν (s ×ˢ t) := measure_toMeasurable _
#align measure_theory.measure.prod_prod MeasureTheory.Measure.prod_prod
@[simp] lemma map_fst_prod : Measure.map Prod.fst (μ.prod ν) = (ν univ) • μ := by
ext s hs
simp [Measure.map_apply measurable_fst hs, ← prod_univ, mul_comm]
@[simp] lemma map_snd_prod : Measure.map Prod.snd (μ.prod ν) = (μ univ) • ν := by
ext s hs
simp [Measure.map_apply measurable_snd hs, ← univ_prod]
instance prod.instIsOpenPosMeasure {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y]
{m : MeasurableSpace X} {μ : Measure X} [IsOpenPosMeasure μ] {m' : MeasurableSpace Y}
{ν : Measure Y} [IsOpenPosMeasure ν] [SFinite ν] : IsOpenPosMeasure (μ.prod ν) := by
constructor
rintro U U_open ⟨⟨x, y⟩, hxy⟩
rcases isOpen_prod_iff.1 U_open x y hxy with ⟨u, v, u_open, v_open, xu, yv, huv⟩
refine ne_of_gt (lt_of_lt_of_le ?_ (measure_mono huv))
simp only [prod_prod, CanonicallyOrderedCommSemiring.mul_pos]
constructor
· exact u_open.measure_pos μ ⟨x, xu⟩
· exact v_open.measure_pos ν ⟨y, yv⟩
#align measure_theory.measure.prod.is_open_pos_measure MeasureTheory.Measure.prod.instIsOpenPosMeasure
instance {X Y : Type*}
[TopologicalSpace X] [MeasureSpace X] [IsOpenPosMeasure (volume : Measure X)]
[TopologicalSpace Y] [MeasureSpace Y] [IsOpenPosMeasure (volume : Measure Y)]
[SFinite (volume : Measure Y)] : IsOpenPosMeasure (volume : Measure (X × Y)) :=
prod.instIsOpenPosMeasure
instance prod.instIsFiniteMeasure {α β : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β}
(μ : Measure α) (ν : Measure β) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
IsFiniteMeasure (μ.prod ν) := by
constructor
rw [← univ_prod_univ, prod_prod]
exact mul_lt_top (measure_lt_top _ _).ne (measure_lt_top _ _).ne
#align measure_theory.measure.prod.measure_theory.is_finite_measure MeasureTheory.Measure.prod.instIsFiniteMeasure
instance {α β : Type*} [MeasureSpace α] [MeasureSpace β] [IsFiniteMeasure (volume : Measure α)]
[IsFiniteMeasure (volume : Measure β)] : IsFiniteMeasure (volume : Measure (α × β)) :=
prod.instIsFiniteMeasure _ _
instance prod.instIsProbabilityMeasure {α β : Type*} {mα : MeasurableSpace α}
{mβ : MeasurableSpace β} (μ : Measure α) (ν : Measure β) [IsProbabilityMeasure μ]
[IsProbabilityMeasure ν] : IsProbabilityMeasure (μ.prod ν) :=
⟨by rw [← univ_prod_univ, prod_prod, measure_univ, measure_univ, mul_one]⟩
#align measure_theory.measure.prod.measure_theory.is_probability_measure MeasureTheory.Measure.prod.instIsProbabilityMeasure
instance {α β : Type*} [MeasureSpace α] [MeasureSpace β]
[IsProbabilityMeasure (volume : Measure α)] [IsProbabilityMeasure (volume : Measure β)] :
IsProbabilityMeasure (volume : Measure (α × β)) :=
prod.instIsProbabilityMeasure _ _
instance prod.instIsFiniteMeasureOnCompacts {α β : Type*} [TopologicalSpace α] [TopologicalSpace β]
{mα : MeasurableSpace α} {mβ : MeasurableSpace β} (μ : Measure α) (ν : Measure β)
[IsFiniteMeasureOnCompacts μ] [IsFiniteMeasureOnCompacts ν] [SFinite ν] :
IsFiniteMeasureOnCompacts (μ.prod ν) := by
refine ⟨fun K hK => ?_⟩
set L := (Prod.fst '' K) ×ˢ (Prod.snd '' K) with hL
have : K ⊆ L := by
rintro ⟨x, y⟩ hxy
simp only [L, prod_mk_mem_set_prod_eq, mem_image, Prod.exists, exists_and_right,
exists_eq_right]
exact ⟨⟨y, hxy⟩, ⟨x, hxy⟩⟩
apply lt_of_le_of_lt (measure_mono this)
rw [hL, prod_prod]
exact
mul_lt_top (IsCompact.measure_lt_top (hK.image continuous_fst)).ne
(IsCompact.measure_lt_top (hK.image continuous_snd)).ne
#align measure_theory.measure.prod.measure_theory.is_finite_measure_on_compacts MeasureTheory.Measure.prod.instIsFiniteMeasureOnCompacts
instance {X Y : Type*}
[TopologicalSpace X] [MeasureSpace X] [IsFiniteMeasureOnCompacts (volume : Measure X)]
[TopologicalSpace Y] [MeasureSpace Y] [IsFiniteMeasureOnCompacts (volume : Measure Y)]
[SFinite (volume : Measure Y)] : IsFiniteMeasureOnCompacts (volume : Measure (X × Y)) :=
prod.instIsFiniteMeasureOnCompacts _ _
instance prod.instNoAtoms_fst [NoAtoms μ] :
NoAtoms (Measure.prod μ ν) := by
refine NoAtoms.mk (fun x => ?_)
rw [← Set.singleton_prod_singleton, Measure.prod_prod, measure_singleton, zero_mul]
instance prod.instNoAtoms_snd [NoAtoms ν] :
NoAtoms (Measure.prod μ ν) := by
refine NoAtoms.mk (fun x => ?_)
rw [← Set.singleton_prod_singleton, Measure.prod_prod, measure_singleton (μ := ν), mul_zero]
| Mathlib/MeasureTheory/Constructions/Prod/Basic.lean | 465 | 468 | theorem ae_measure_lt_top {s : Set (α × β)} (hs : MeasurableSet s) (h2s : (μ.prod ν) s ≠ ∞) :
∀ᵐ x ∂μ, ν (Prod.mk x ⁻¹' s) < ∞ := by |
rw [prod_apply hs] at h2s
exact ae_lt_top (measurable_measure_prod_mk_left hs) h2s
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Devon Tuma
-/
import Mathlib.Algebra.GroupWithZero.NonZeroDivisors
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.RingTheory.Coprime.Basic
import Mathlib.Tactic.AdaptationNote
#align_import ring_theory.polynomial.scale_roots from "leanprover-community/mathlib"@"40ac1b258344e0c2b4568dc37bfad937ec35a727"
/-!
# Scaling the roots of a polynomial
This file defines `scaleRoots p s` for a polynomial `p` in one variable and a ring element `s` to
be the polynomial with root `r * s` for each root `r` of `p` and proves some basic results about it.
-/
variable {R S A K : Type*}
namespace Polynomial
open Polynomial
section Semiring
variable [Semiring R] [Semiring S]
/-- `scaleRoots p s` is a polynomial with root `r * s` for each root `r` of `p`. -/
noncomputable def scaleRoots (p : R[X]) (s : R) : R[X] :=
∑ i ∈ p.support, monomial i (p.coeff i * s ^ (p.natDegree - i))
#align polynomial.scale_roots Polynomial.scaleRoots
@[simp]
theorem coeff_scaleRoots (p : R[X]) (s : R) (i : ℕ) :
(scaleRoots p s).coeff i = coeff p i * s ^ (p.natDegree - i) := by
simp (config := { contextual := true }) [scaleRoots, coeff_monomial]
#align polynomial.coeff_scale_roots Polynomial.coeff_scaleRoots
theorem coeff_scaleRoots_natDegree (p : R[X]) (s : R) :
(scaleRoots p s).coeff p.natDegree = p.leadingCoeff := by
rw [leadingCoeff, coeff_scaleRoots, tsub_self, pow_zero, mul_one]
#align polynomial.coeff_scale_roots_nat_degree Polynomial.coeff_scaleRoots_natDegree
@[simp]
theorem zero_scaleRoots (s : R) : scaleRoots 0 s = 0 := by
ext
simp
#align polynomial.zero_scale_roots Polynomial.zero_scaleRoots
theorem scaleRoots_ne_zero {p : R[X]} (hp : p ≠ 0) (s : R) : scaleRoots p s ≠ 0 := by
intro h
have : p.coeff p.natDegree ≠ 0 := mt leadingCoeff_eq_zero.mp hp
have : (scaleRoots p s).coeff p.natDegree = 0 :=
congr_fun (congr_arg (coeff : R[X] → ℕ → R) h) p.natDegree
rw [coeff_scaleRoots_natDegree] at this
contradiction
#align polynomial.scale_roots_ne_zero Polynomial.scaleRoots_ne_zero
| Mathlib/RingTheory/Polynomial/ScaleRoots.lean | 62 | 64 | theorem support_scaleRoots_le (p : R[X]) (s : R) : (scaleRoots p s).support ≤ p.support := by |
intro
simpa using left_ne_zero_of_mul
|
/-
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, Matthew Robert Ballard
-/
import Mathlib.NumberTheory.Divisors
import Mathlib.Data.Nat.Digits
import Mathlib.Data.Nat.MaxPowDiv
import Mathlib.Data.Nat.Multiplicity
import Mathlib.Tactic.IntervalCases
#align_import number_theory.padics.padic_val from "leanprover-community/mathlib"@"60fa54e778c9e85d930efae172435f42fb0d71f7"
/-!
# `p`-adic Valuation
This file defines the `p`-adic valuation on `ℕ`, `ℤ`, and `ℚ`.
The `p`-adic valuation on `ℚ` is the difference of the multiplicities of `p` in the numerator and
denominator of `q`. This function obeys the standard properties of a valuation, with the appropriate
assumptions on `p`. The `p`-adic valuations on `ℕ` and `ℤ` agree with that on `ℚ`.
The valuation induces a norm on `ℚ`. This norm is defined in padicNorm.lean.
## Notations
This file uses the local notation `/.` for `Rat.mk`.
## 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.
## Calculations with `p`-adic valuations
* `padicValNat_factorial`: Legendre's Theorem. The `p`-adic valuation of `n!` is the sum of the
quotients `n / p ^ i`. This sum is expressed over the finset `Ico 1 b` where `b` is any bound
greater than `log p n`. See `Nat.Prime.multiplicity_factorial` for the same result but stated in the
language of prime multiplicity.
* `sub_one_mul_padicValNat_factorial`: Legendre's Theorem. Taking (`p - 1`) times
the `p`-adic valuation of `n!` equals `n` minus the sum of base `p` digits of `n`.
* `padicValNat_choose`: Kummer's Theorem. The `p`-adic valuation of `n.choose k` is the number
of carries when `k` and `n - k` are added in base `p`. This sum is expressed over the finset
`Ico 1 b` where `b` is any bound greater than `log p n`. See `Nat.Prime.multiplicity_choose` for the
same result but stated in the language of prime multiplicity.
* `sub_one_mul_padicValNat_choose_eq_sub_sum_digits`: Kummer's Theorem. Taking (`p - 1`) times the
`p`-adic valuation of the binomial `n` over `k` equals the sum of the digits of `k` plus the sum of
the digits of `n - k` minus the sum of digits of `n`, all base `p`.
## References
* [F. Q. Gouvêa, *p-adic numbers*][gouvea1997]
* [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]
* <https://en.wikipedia.org/wiki/P-adic_number>
## Tags
p-adic, p adic, padic, norm, valuation
-/
universe u
open Nat
open Rat
open multiplicity
/-- For `p ≠ 1`, the `p`-adic valuation of a natural `n ≠ 0` is the largest natural number `k` such
that `p^k` divides `n`. If `n = 0` or `p = 1`, then `padicValNat p q` defaults to `0`. -/
def padicValNat (p : ℕ) (n : ℕ) : ℕ :=
if h : p ≠ 1 ∧ 0 < n then (multiplicity p n).get (multiplicity.finite_nat_iff.2 h) else 0
#align padic_val_nat padicValNat
namespace padicValNat
open multiplicity
variable {p : ℕ}
/-- `padicValNat p 0` is `0` for any `p`. -/
@[simp]
protected theorem zero : padicValNat p 0 = 0 := by simp [padicValNat]
#align padic_val_nat.zero padicValNat.zero
/-- `padicValNat p 1` is `0` for any `p`. -/
@[simp]
protected theorem one : padicValNat p 1 = 0 := by
unfold padicValNat
split_ifs
· simp
· rfl
#align padic_val_nat.one padicValNat.one
/-- If `p ≠ 0` and `p ≠ 1`, then `padicValNat p p` is `1`. -/
@[simp]
theorem self (hp : 1 < p) : padicValNat p p = 1 := by
have neq_one : ¬p = 1 ↔ True := iff_of_true hp.ne' trivial
have eq_zero_false : p = 0 ↔ False := iff_false_intro (zero_lt_one.trans hp).ne'
simp [padicValNat, neq_one, eq_zero_false]
#align padic_val_nat.self padicValNat.self
@[simp]
theorem eq_zero_iff {n : ℕ} : padicValNat p n = 0 ↔ p = 1 ∨ n = 0 ∨ ¬p ∣ n := by
simp only [padicValNat, dite_eq_right_iff, PartENat.get_eq_iff_eq_coe, Nat.cast_zero,
multiplicity_eq_zero, and_imp, pos_iff_ne_zero, Ne, ← or_iff_not_imp_left]
#align padic_val_nat.eq_zero_iff padicValNat.eq_zero_iff
theorem eq_zero_of_not_dvd {n : ℕ} (h : ¬p ∣ n) : padicValNat p n = 0 :=
eq_zero_iff.2 <| Or.inr <| Or.inr h
#align padic_val_nat.eq_zero_of_not_dvd padicValNat.eq_zero_of_not_dvd
open Nat.maxPowDiv
theorem maxPowDiv_eq_multiplicity {p n : ℕ} (hp : 1 < p) (hn : 0 < n) :
p.maxPowDiv n = multiplicity p n := by
apply multiplicity.unique <| pow_dvd p n
intro h
apply Nat.not_lt.mpr <| le_of_dvd hp hn h
simp
theorem maxPowDiv_eq_multiplicity_get {p n : ℕ} (hp : 1 < p) (hn : 0 < n) (h : Finite p n) :
p.maxPowDiv n = (multiplicity p n).get h := by
rw [PartENat.get_eq_iff_eq_coe.mpr]
apply maxPowDiv_eq_multiplicity hp hn|>.symm
/-- Allows for more efficient code for `padicValNat` -/
@[csimp]
theorem padicValNat_eq_maxPowDiv : @padicValNat = @maxPowDiv := by
ext p n
by_cases h : 1 < p ∧ 0 < n
· dsimp [padicValNat]
rw [dif_pos ⟨Nat.ne_of_gt h.1,h.2⟩, maxPowDiv_eq_multiplicity_get h.1 h.2]
· simp only [not_and_or,not_gt_eq,Nat.le_zero] at h
apply h.elim
· intro h
interval_cases p
· simp [Classical.em]
· dsimp [padicValNat, maxPowDiv]
rw [go, if_neg, dif_neg] <;> simp
· intro h
simp [h]
end padicValNat
/-- For `p ≠ 1`, the `p`-adic valuation of an integer `z ≠ 0` is the largest natural number `k` such
that `p^k` divides `z`. If `x = 0` or `p = 1`, then `padicValInt p q` defaults to `0`. -/
def padicValInt (p : ℕ) (z : ℤ) : ℕ :=
padicValNat p z.natAbs
#align padic_val_int padicValInt
namespace padicValInt
open multiplicity
variable {p : ℕ}
theorem of_ne_one_ne_zero {z : ℤ} (hp : p ≠ 1) (hz : z ≠ 0) :
padicValInt p z =
(multiplicity (p : ℤ) z).get
(by
apply multiplicity.finite_int_iff.2
simp [hp, hz]) := by
rw [padicValInt, padicValNat, dif_pos (And.intro hp (Int.natAbs_pos.mpr hz))]
simp only [multiplicity.Int.natAbs p z]
#align padic_val_int.of_ne_one_ne_zero padicValInt.of_ne_one_ne_zero
/-- `padicValInt p 0` is `0` for any `p`. -/
@[simp]
protected theorem zero : padicValInt p 0 = 0 := by simp [padicValInt]
#align padic_val_int.zero padicValInt.zero
/-- `padicValInt p 1` is `0` for any `p`. -/
@[simp]
protected theorem one : padicValInt p 1 = 0 := by simp [padicValInt]
#align padic_val_int.one padicValInt.one
/-- The `p`-adic value of a natural is its `p`-adic value as an integer. -/
@[simp]
theorem of_nat {n : ℕ} : padicValInt p n = padicValNat p n := by simp [padicValInt]
#align padic_val_int.of_nat padicValInt.of_nat
/-- If `p ≠ 0` and `p ≠ 1`, then `padicValInt p p` is `1`. -/
theorem self (hp : 1 < p) : padicValInt p p = 1 := by simp [padicValNat.self hp]
#align padic_val_int.self padicValInt.self
theorem eq_zero_of_not_dvd {z : ℤ} (h : ¬(p : ℤ) ∣ z) : padicValInt p z = 0 := by
rw [padicValInt, padicValNat]
split_ifs <;> simp [multiplicity.Int.natAbs, multiplicity_eq_zero.2 h]
#align padic_val_int.eq_zero_of_not_dvd padicValInt.eq_zero_of_not_dvd
end padicValInt
/-- `padicValRat` defines the valuation of a rational `q` to be the valuation of `q.num` minus the
valuation of `q.den`. If `q = 0` or `p = 1`, then `padicValRat p q` defaults to `0`. -/
def padicValRat (p : ℕ) (q : ℚ) : ℤ :=
padicValInt p q.num - padicValNat p q.den
#align padic_val_rat padicValRat
lemma padicValRat_def (p : ℕ) (q : ℚ) :
padicValRat p q = padicValInt p q.num - padicValNat p q.den :=
rfl
namespace padicValRat
open multiplicity
variable {p : ℕ}
/-- `padicValRat p q` is symmetric in `q`. -/
@[simp]
protected theorem neg (q : ℚ) : padicValRat p (-q) = padicValRat p q := by
simp [padicValRat, padicValInt]
#align padic_val_rat.neg padicValRat.neg
/-- `padicValRat p 0` is `0` for any `p`. -/
@[simp]
protected theorem zero : padicValRat p 0 = 0 := by simp [padicValRat]
#align padic_val_rat.zero padicValRat.zero
/-- `padicValRat p 1` is `0` for any `p`. -/
@[simp]
protected theorem one : padicValRat p 1 = 0 := by simp [padicValRat]
#align padic_val_rat.one padicValRat.one
/-- The `p`-adic value of an integer `z ≠ 0` is its `p`-adic_value as a rational. -/
@[simp]
theorem of_int {z : ℤ} : padicValRat p z = padicValInt p z := by simp [padicValRat]
#align padic_val_rat.of_int padicValRat.of_int
/-- The `p`-adic value of an integer `z ≠ 0` is the multiplicity of `p` in `z`. -/
theorem of_int_multiplicity {z : ℤ} (hp : p ≠ 1) (hz : z ≠ 0) :
padicValRat p (z : ℚ) = (multiplicity (p : ℤ) z).get (finite_int_iff.2 ⟨hp, hz⟩) := by
rw [of_int, padicValInt.of_ne_one_ne_zero hp hz]
#align padic_val_rat.of_int_multiplicity padicValRat.of_int_multiplicity
theorem multiplicity_sub_multiplicity {q : ℚ} (hp : p ≠ 1) (hq : q ≠ 0) :
padicValRat p q =
(multiplicity (p : ℤ) q.num).get (finite_int_iff.2 ⟨hp, Rat.num_ne_zero.2 hq⟩) -
(multiplicity p q.den).get
(by
rw [← finite_iff_dom, finite_nat_iff]
exact ⟨hp, q.pos⟩) := by
rw [padicValRat, padicValInt.of_ne_one_ne_zero hp, padicValNat, dif_pos]
· exact ⟨hp, q.pos⟩
· exact Rat.num_ne_zero.2 hq
#align padic_val_rat.multiplicity_sub_multiplicity padicValRat.multiplicity_sub_multiplicity
/-- The `p`-adic value of an integer `z ≠ 0` is its `p`-adic value as a rational. -/
@[simp]
theorem of_nat {n : ℕ} : padicValRat p n = padicValNat p n := by simp [padicValRat]
#align padic_val_rat.of_nat padicValRat.of_nat
/-- If `p ≠ 0` and `p ≠ 1`, then `padicValRat p p` is `1`. -/
theorem self (hp : 1 < p) : padicValRat p p = 1 := by simp [hp]
#align padic_val_rat.self padicValRat.self
end padicValRat
section padicValNat
variable {p : ℕ}
theorem zero_le_padicValRat_of_nat (n : ℕ) : 0 ≤ padicValRat p n := by simp
#align zero_le_padic_val_rat_of_nat zero_le_padicValRat_of_nat
/-- `padicValRat` coincides with `padicValNat`. -/
@[norm_cast]
theorem padicValRat_of_nat (n : ℕ) : ↑(padicValNat p n) = padicValRat p n := by simp
#align padic_val_rat_of_nat padicValRat_of_nat
/-- A simplification of `padicValNat` when one input is prime, by analogy with
`padicValRat_def`. -/
theorem padicValNat_def [hp : Fact p.Prime] {n : ℕ} (hn : 0 < n) :
padicValNat p n = (multiplicity p n).get (multiplicity.finite_nat_iff.2 ⟨hp.out.ne_one, hn⟩) :=
dif_pos ⟨hp.out.ne_one, hn⟩
#align padic_val_nat_def padicValNat_def
theorem padicValNat_def' {n : ℕ} (hp : p ≠ 1) (hn : 0 < n) :
↑(padicValNat p n) = multiplicity p n := by simp [padicValNat, hp, hn]
#align padic_val_nat_def' padicValNat_def'
@[simp]
theorem padicValNat_self [Fact p.Prime] : padicValNat p p = 1 := by
rw [padicValNat_def (@Fact.out p.Prime).pos]
simp
#align padic_val_nat_self padicValNat_self
theorem one_le_padicValNat_of_dvd {n : ℕ} [hp : Fact p.Prime] (hn : 0 < n) (div : p ∣ n) :
1 ≤ padicValNat p n := by
rwa [← PartENat.coe_le_coe, padicValNat_def' hp.out.ne_one hn, ← pow_dvd_iff_le_multiplicity,
pow_one]
#align one_le_padic_val_nat_of_dvd one_le_padicValNat_of_dvd
theorem dvd_iff_padicValNat_ne_zero {p n : ℕ} [Fact p.Prime] (hn0 : n ≠ 0) :
p ∣ n ↔ padicValNat p n ≠ 0 :=
⟨fun h => one_le_iff_ne_zero.mp (one_le_padicValNat_of_dvd hn0.bot_lt h), fun h =>
Classical.not_not.1 (mt padicValNat.eq_zero_of_not_dvd h)⟩
#align dvd_iff_padic_val_nat_ne_zero dvd_iff_padicValNat_ne_zero
open List
theorem le_multiplicity_iff_replicate_subperm_factors {a b : ℕ} {n : ℕ} (ha : a.Prime)
(hb : b ≠ 0) :
↑n ≤ multiplicity a b ↔ replicate n a <+~ b.factors :=
(replicate_subperm_factors_iff ha hb).trans multiplicity.pow_dvd_iff_le_multiplicity |>.symm
theorem le_padicValNat_iff_replicate_subperm_factors {a b : ℕ} {n : ℕ} (ha : a.Prime)
(hb : b ≠ 0) :
n ≤ padicValNat a b ↔ replicate n a <+~ b.factors := by
rw [← le_multiplicity_iff_replicate_subperm_factors ha hb,
← padicValNat_def' ha.ne_one (Nat.pos_of_ne_zero hb), Nat.cast_le]
end padicValNat
namespace padicValRat
open multiplicity
variable {p : ℕ} [hp : Fact p.Prime]
/-- The multiplicity of `p : ℕ` in `a : ℤ` is finite exactly when `a ≠ 0`. -/
theorem finite_int_prime_iff {a : ℤ} : Finite (p : ℤ) a ↔ a ≠ 0 := by
simp [finite_int_iff, hp.1.ne_one]
#align padic_val_rat.finite_int_prime_iff padicValRat.finite_int_prime_iff
/-- A rewrite lemma for `padicValRat p q` when `q` is expressed in terms of `Rat.mk`. -/
protected theorem defn (p : ℕ) [hp : Fact p.Prime] {q : ℚ} {n d : ℤ} (hqz : q ≠ 0)
(qdf : q = n /. d) :
padicValRat p q =
(multiplicity (p : ℤ) n).get
(finite_int_iff.2 ⟨hp.1.ne_one, fun hn => by simp_all⟩) -
(multiplicity (p : ℤ) d).get
(finite_int_iff.2 ⟨hp.1.ne_one, fun hd => by simp_all⟩) := by
have hd : d ≠ 0 := Rat.mk_denom_ne_zero_of_ne_zero hqz qdf
let ⟨c, hc1, hc2⟩ := Rat.num_den_mk hd qdf
rw [padicValRat.multiplicity_sub_multiplicity hp.1.ne_one hqz]
simp only [Nat.isUnit_iff, hc1, hc2]
rw [multiplicity.mul' (Nat.prime_iff_prime_int.1 hp.1),
multiplicity.mul' (Nat.prime_iff_prime_int.1 hp.1)]
rw [Nat.cast_add, Nat.cast_add]
simp_rw [Int.natCast_multiplicity p q.den]
ring
-- Porting note: was
-- simp only [hc1, hc2, multiplicity.mul' (Nat.prime_iff_prime_int.1 hp.1),
-- hp.1.ne_one, hqz, pos_iff_ne_zero, Int.natCast_multiplicity p q.den
#align padic_val_rat.defn padicValRat.defn
/-- A rewrite lemma for `padicValRat p (q * r)` with conditions `q ≠ 0`, `r ≠ 0`. -/
protected theorem mul {q r : ℚ} (hq : q ≠ 0) (hr : r ≠ 0) :
padicValRat p (q * r) = padicValRat p q + padicValRat p r := by
have : q * r = (q.num * r.num) /. (q.den * r.den) := by
rw [Rat.mul_eq_mkRat, Rat.mkRat_eq_divInt, Nat.cast_mul]
have hq' : q.num /. q.den ≠ 0 := by rwa [Rat.num_divInt_den]
have hr' : r.num /. r.den ≠ 0 := by rwa [Rat.num_divInt_den]
have hp' : Prime (p : ℤ) := Nat.prime_iff_prime_int.1 hp.1
rw [padicValRat.defn p (mul_ne_zero hq hr) this]
conv_rhs =>
rw [← q.num_divInt_den, padicValRat.defn p hq', ← r.num_divInt_den, padicValRat.defn p hr']
rw [multiplicity.mul' hp', multiplicity.mul' hp', Nat.cast_add, Nat.cast_add]
ring
-- Porting note: was
-- simp [add_comm, add_left_comm, sub_eq_add_neg]
#align padic_val_rat.mul padicValRat.mul
/-- A rewrite lemma for `padicValRat p (q^k)` with condition `q ≠ 0`. -/
protected theorem pow {q : ℚ} (hq : q ≠ 0) {k : ℕ} :
padicValRat p (q ^ k) = k * padicValRat p q := by
induction k <;>
simp [*, padicValRat.mul hq (pow_ne_zero _ hq), _root_.pow_succ', add_mul, add_comm]
#align padic_val_rat.pow padicValRat.pow
/-- A rewrite lemma for `padicValRat p (q⁻¹)` with condition `q ≠ 0`. -/
protected theorem inv (q : ℚ) : padicValRat p q⁻¹ = -padicValRat p q := by
by_cases hq : q = 0
· simp [hq]
· rw [eq_neg_iff_add_eq_zero, ← padicValRat.mul (inv_ne_zero hq) hq, inv_mul_cancel hq,
padicValRat.one]
#align padic_val_rat.inv padicValRat.inv
/-- A rewrite lemma for `padicValRat p (q / r)` with conditions `q ≠ 0`, `r ≠ 0`. -/
protected theorem div {q r : ℚ} (hq : q ≠ 0) (hr : r ≠ 0) :
padicValRat p (q / r) = padicValRat p q - padicValRat p r := by
rw [div_eq_mul_inv, padicValRat.mul hq (inv_ne_zero hr), padicValRat.inv r, sub_eq_add_neg]
#align padic_val_rat.div padicValRat.div
/-- A condition for `padicValRat p (n₁ / d₁) ≤ padicValRat p (n₂ / d₂)`, in terms of
divisibility by `p^n`. -/
theorem padicValRat_le_padicValRat_iff {n₁ n₂ d₁ d₂ : ℤ} (hn₁ : n₁ ≠ 0) (hn₂ : n₂ ≠ 0)
(hd₁ : d₁ ≠ 0) (hd₂ : d₂ ≠ 0) :
padicValRat p (n₁ /. d₁) ≤ padicValRat p (n₂ /. d₂) ↔
∀ n : ℕ, (p : ℤ) ^ n ∣ n₁ * d₂ → (p : ℤ) ^ n ∣ n₂ * d₁ := by
have hf1 : Finite (p : ℤ) (n₁ * d₂) := finite_int_prime_iff.2 (mul_ne_zero hn₁ hd₂)
have hf2 : Finite (p : ℤ) (n₂ * d₁) := finite_int_prime_iff.2 (mul_ne_zero hn₂ hd₁)
conv =>
lhs
rw [padicValRat.defn p (Rat.divInt_ne_zero_of_ne_zero hn₁ hd₁) rfl,
padicValRat.defn p (Rat.divInt_ne_zero_of_ne_zero hn₂ hd₂) rfl, sub_le_iff_le_add', ←
add_sub_assoc, _root_.le_sub_iff_add_le]
norm_cast
rw [← multiplicity.mul' (Nat.prime_iff_prime_int.1 hp.1) hf1, add_comm, ←
multiplicity.mul' (Nat.prime_iff_prime_int.1 hp.1) hf2, PartENat.get_le_get,
multiplicity_le_multiplicity_iff]
#align padic_val_rat.padic_val_rat_le_padic_val_rat_iff padicValRat.padicValRat_le_padicValRat_iff
/-- Sufficient conditions to show that the `p`-adic valuation of `q` is less than or equal to the
`p`-adic valuation of `q + r`. -/
theorem le_padicValRat_add_of_le {q r : ℚ} (hqr : q + r ≠ 0)
(h : padicValRat p q ≤ padicValRat p r) : padicValRat p q ≤ padicValRat p (q + r) :=
if hq : q = 0 then by simpa [hq] using h
else
if hr : r = 0 then by simp [hr]
else by
have hqn : q.num ≠ 0 := Rat.num_ne_zero.2 hq
have hqd : (q.den : ℤ) ≠ 0 := mod_cast Rat.den_nz _
have hrn : r.num ≠ 0 := Rat.num_ne_zero.2 hr
have hrd : (r.den : ℤ) ≠ 0 := mod_cast Rat.den_nz _
have hqreq : q + r = (q.num * r.den + q.den * r.num) /. (q.den * r.den) := Rat.add_num_den _ _
have hqrd : q.num * r.den + q.den * r.num ≠ 0 := Rat.mk_num_ne_zero_of_ne_zero hqr hqreq
conv_lhs => rw [← q.num_divInt_den]
rw [hqreq, padicValRat_le_padicValRat_iff hqn hqrd hqd (mul_ne_zero hqd hrd), ←
multiplicity_le_multiplicity_iff, mul_left_comm,
multiplicity.mul (Nat.prime_iff_prime_int.1 hp.1), add_mul]
rw [← q.num_divInt_den, ← r.num_divInt_den, padicValRat_le_padicValRat_iff hqn hrn hqd hrd, ←
multiplicity_le_multiplicity_iff] at h
calc
_ ≤
min (multiplicity (↑p) (q.num * r.den * q.den))
(multiplicity (↑p) (↑q.den * r.num * ↑q.den)) :=
le_min
(by rw [@multiplicity.mul _ _ _ _ (_ * _) _ (Nat.prime_iff_prime_int.1 hp.1), add_comm])
(by
rw [mul_assoc,
@multiplicity.mul _ _ _ _ (q.den : ℤ) (_ * _)
(Nat.prime_iff_prime_int.1 hp.1)]
exact add_le_add_left h _)
_ ≤ _ := min_le_multiplicity_add
#align padic_val_rat.le_padic_val_rat_add_of_le padicValRat.le_padicValRat_add_of_le
/-- The minimum of the valuations of `q` and `r` is at most the valuation of `q + r`. -/
theorem min_le_padicValRat_add {q r : ℚ} (hqr : q + r ≠ 0) :
min (padicValRat p q) (padicValRat p r) ≤ padicValRat p (q + r) :=
(le_total (padicValRat p q) (padicValRat p r)).elim
(fun h => by rw [min_eq_left h]; exact le_padicValRat_add_of_le hqr h)
(fun h => by rw [min_eq_right h, add_comm]; exact le_padicValRat_add_of_le (by rwa [add_comm]) h)
#align padic_val_rat.min_le_padic_val_rat_add padicValRat.min_le_padicValRat_add
/-- Ultrametric property of a p-adic valuation. -/
lemma add_eq_min {q r : ℚ} (hqr : q + r ≠ 0) (hq : q ≠ 0) (hr : r ≠ 0)
(hval : padicValRat p q ≠ padicValRat p r) :
padicValRat p (q + r) = min (padicValRat p q) (padicValRat p r) := by
have h1 := min_le_padicValRat_add (p := p) hqr
have h2 := min_le_padicValRat_add (p := p) (ne_of_eq_of_ne (add_neg_cancel_right q r) hq)
have h3 := min_le_padicValRat_add (p := p) (ne_of_eq_of_ne (add_neg_cancel_right r q) hr)
rw [add_neg_cancel_right, padicValRat.neg] at h2 h3
rw [add_comm] at h3
refine le_antisymm (le_min ?_ ?_) h1
· contrapose! h2
rw [min_eq_right h2.le] at h3
exact lt_min h2 (lt_of_le_of_ne h3 hval)
· contrapose! h3
rw [min_eq_right h3.le] at h2
exact lt_min h3 (lt_of_le_of_ne h2 hval.symm)
lemma add_eq_of_lt {q r : ℚ} (hqr : q + r ≠ 0)
(hq : q ≠ 0) (hr : r ≠ 0) (hval : padicValRat p q < padicValRat p r) :
padicValRat p (q + r) = padicValRat p q := by
rw [add_eq_min hqr hq hr (ne_of_lt hval), min_eq_left (le_of_lt hval)]
lemma lt_add_of_lt {q r₁ r₂ : ℚ} (hqr : r₁ + r₂ ≠ 0)
(hval₁ : padicValRat p q < padicValRat p r₁) (hval₂ : padicValRat p q < padicValRat p r₂) :
padicValRat p q < padicValRat p (r₁ + r₂) :=
lt_of_lt_of_le (lt_min hval₁ hval₂) (padicValRat.min_le_padicValRat_add hqr)
@[simp]
lemma self_pow_inv (r : ℕ) : padicValRat p ((p : ℚ) ^ r)⁻¹ = -r := by
rw [padicValRat.inv, neg_inj, padicValRat.pow (Nat.cast_ne_zero.mpr hp.elim.ne_zero),
padicValRat.self hp.elim.one_lt, mul_one]
/-- A finite sum of rationals with positive `p`-adic valuation has positive `p`-adic valuation
(if the sum is non-zero). -/
theorem sum_pos_of_pos {n : ℕ} {F : ℕ → ℚ} (hF : ∀ i, i < n → 0 < padicValRat p (F i))
(hn0 : ∑ i ∈ Finset.range n, F i ≠ 0) : 0 < padicValRat p (∑ i ∈ Finset.range n, F i) := by
induction' n with d hd
· exact False.elim (hn0 rfl)
· rw [Finset.sum_range_succ] at hn0 ⊢
by_cases h : ∑ x ∈ Finset.range d, F x = 0
· rw [h, zero_add]
exact hF d (lt_add_one _)
· refine lt_of_lt_of_le ?_ (min_le_padicValRat_add hn0)
refine lt_min (hd (fun i hi => ?_) h) (hF d (lt_add_one _))
exact hF _ (lt_trans hi (lt_add_one _))
#align padic_val_rat.sum_pos_of_pos padicValRat.sum_pos_of_pos
/-- If the p-adic valuation of a finite set of positive rationals is greater than a given rational
number, then the p-adic valuation of their sum is also greater than the same rational number. -/
theorem lt_sum_of_lt {p j : ℕ} [hp : Fact (Nat.Prime p)] {F : ℕ → ℚ} {S : Finset ℕ}
(hS : S.Nonempty) (hF : ∀ i, i ∈ S → padicValRat p (F j) < padicValRat p (F i))
(hn1 : ∀ i : ℕ, 0 < F i) : padicValRat p (F j) < padicValRat p (∑ i ∈ S, F i) := by
induction' hS using Finset.Nonempty.cons_induction with k s S' Hnot Hne Hind
· rw [Finset.sum_singleton]
exact hF k (by simp)
· rw [Finset.cons_eq_insert, Finset.sum_insert Hnot]
exact padicValRat.lt_add_of_lt
(ne_of_gt (add_pos (hn1 s) (Finset.sum_pos (fun i _ => hn1 i) Hne)))
(hF _ (by simp [Finset.mem_insert, true_or]))
(Hind (fun i hi => hF _ (by rw [Finset.cons_eq_insert,Finset.mem_insert]; exact Or.inr hi)))
end padicValRat
namespace padicValNat
variable {p a b : ℕ} [hp : Fact p.Prime]
/-- A rewrite lemma for `padicValNat p (a * b)` with conditions `a ≠ 0`, `b ≠ 0`. -/
protected theorem mul : a ≠ 0 → b ≠ 0 → padicValNat p (a * b) = padicValNat p a + padicValNat p b :=
mod_cast @padicValRat.mul p _ a b
#align padic_val_nat.mul padicValNat.mul
protected theorem div_of_dvd (h : b ∣ a) :
padicValNat p (a / b) = padicValNat p a - padicValNat p b := by
rcases eq_or_ne a 0 with (rfl | ha)
· simp
obtain ⟨k, rfl⟩ := h
obtain ⟨hb, hk⟩ := mul_ne_zero_iff.mp ha
rw [mul_comm, k.mul_div_cancel hb.bot_lt, padicValNat.mul hk hb, Nat.add_sub_cancel]
#align padic_val_nat.div_of_dvd padicValNat.div_of_dvd
/-- Dividing out by a prime factor reduces the `padicValNat` by `1`. -/
protected theorem div (dvd : p ∣ b) : padicValNat p (b / p) = padicValNat p b - 1 := by
rw [padicValNat.div_of_dvd dvd, padicValNat_self]
#align padic_val_nat.div padicValNat.div
/-- A version of `padicValRat.pow` for `padicValNat`. -/
protected theorem pow (n : ℕ) (ha : a ≠ 0) : padicValNat p (a ^ n) = n * padicValNat p a := by
simpa only [← @Nat.cast_inj ℤ, push_cast] using padicValRat.pow (Nat.cast_ne_zero.mpr ha)
#align padic_val_nat.pow padicValNat.pow
@[simp]
protected theorem prime_pow (n : ℕ) : padicValNat p (p ^ n) = n := by
rw [padicValNat.pow _ (@Fact.out p.Prime).ne_zero, padicValNat_self, mul_one]
#align padic_val_nat.prime_pow padicValNat.prime_pow
protected theorem div_pow (dvd : p ^ a ∣ b) : padicValNat p (b / p ^ a) = padicValNat p b - a := by
rw [padicValNat.div_of_dvd dvd, padicValNat.prime_pow]
#align padic_val_nat.div_pow padicValNat.div_pow
protected theorem div' {m : ℕ} (cpm : Coprime p m) {b : ℕ} (dvd : m ∣ b) :
padicValNat p (b / m) = padicValNat p b := by
rw [padicValNat.div_of_dvd dvd, eq_zero_of_not_dvd (hp.out.coprime_iff_not_dvd.mp cpm),
Nat.sub_zero]
#align padic_val_nat.div' padicValNat.div'
end padicValNat
section padicValNat
variable {p : ℕ}
theorem dvd_of_one_le_padicValNat {n : ℕ} (hp : 1 ≤ padicValNat p n) : p ∣ n := by
by_contra h
rw [padicValNat.eq_zero_of_not_dvd h] at hp
exact lt_irrefl 0 (lt_of_lt_of_le zero_lt_one hp)
#align dvd_of_one_le_padic_val_nat dvd_of_one_le_padicValNat
theorem pow_padicValNat_dvd {n : ℕ} : p ^ padicValNat p n ∣ n := by
rcases n.eq_zero_or_pos with (rfl | hn); · simp
rcases eq_or_ne p 1 with (rfl | hp); · simp
rw [multiplicity.pow_dvd_iff_le_multiplicity, padicValNat_def'] <;> assumption
#align pow_padic_val_nat_dvd pow_padicValNat_dvd
theorem padicValNat_dvd_iff_le [hp : Fact p.Prime] {a n : ℕ} (ha : a ≠ 0) :
p ^ n ∣ a ↔ n ≤ padicValNat p a := by
rw [pow_dvd_iff_le_multiplicity, ← padicValNat_def' hp.out.ne_one ha.bot_lt, PartENat.coe_le_coe]
#align padic_val_nat_dvd_iff_le padicValNat_dvd_iff_le
| Mathlib/NumberTheory/Padics/PadicVal.lean | 581 | 585 | theorem padicValNat_dvd_iff (n : ℕ) [hp : Fact p.Prime] (a : ℕ) :
p ^ n ∣ a ↔ a = 0 ∨ n ≤ padicValNat p a := by |
rcases eq_or_ne a 0 with (rfl | ha)
· exact iff_of_true (dvd_zero _) (Or.inl rfl)
· rw [padicValNat_dvd_iff_le ha, or_iff_right ha]
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Fabian Glöckle, Kyle Miller
-/
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.FreeModule.Finite.Basic
import Mathlib.LinearAlgebra.FreeModule.StrongRankCondition
import Mathlib.LinearAlgebra.Projection
import Mathlib.LinearAlgebra.SesquilinearForm
import Mathlib.RingTheory.TensorProduct.Basic
import Mathlib.RingTheory.Ideal.LocalRing
#align_import linear_algebra.dual from "leanprover-community/mathlib"@"b1c017582e9f18d8494e5c18602a8cb4a6f843ac"
/-!
# Dual vector spaces
The dual space of an $R$-module $M$ is the $R$-module of $R$-linear maps $M \to R$.
## Main definitions
* Duals and transposes:
* `Module.Dual R M` defines the dual space of the `R`-module `M`, as `M →ₗ[R] R`.
* `Module.dualPairing R M` is the canonical pairing between `Dual R M` and `M`.
* `Module.Dual.eval R M : M →ₗ[R] Dual R (Dual R)` is the canonical map to the double dual.
* `Module.Dual.transpose` is the linear map from `M →ₗ[R] M'` to `Dual R M' →ₗ[R] Dual R M`.
* `LinearMap.dualMap` is `Module.Dual.transpose` of a given linear map, for dot notation.
* `LinearEquiv.dualMap` is for the dual of an equivalence.
* Bases:
* `Basis.toDual` produces the map `M →ₗ[R] Dual R M` associated to a basis for an `R`-module `M`.
* `Basis.toDual_equiv` is the equivalence `M ≃ₗ[R] Dual R M` associated to a finite basis.
* `Basis.dualBasis` is a basis for `Dual R M` given a finite basis for `M`.
* `Module.dual_bases e ε` is the proposition that the families `e` of vectors and `ε` of dual
vectors have the characteristic properties of a basis and a dual.
* Submodules:
* `Submodule.dualRestrict W` is the transpose `Dual R M →ₗ[R] Dual R W` of the inclusion map.
* `Submodule.dualAnnihilator W` is the kernel of `W.dualRestrict`. That is, it is the submodule
of `dual R M` whose elements all annihilate `W`.
* `Submodule.dualRestrict_comap W'` is the dual annihilator of `W' : Submodule R (Dual R M)`,
pulled back along `Module.Dual.eval R M`.
* `Submodule.dualCopairing W` is the canonical pairing between `W.dualAnnihilator` and `M ⧸ W`.
It is nondegenerate for vector spaces (`subspace.dualCopairing_nondegenerate`).
* `Submodule.dualPairing W` is the canonical pairing between `Dual R M ⧸ W.dualAnnihilator`
and `W`. It is nondegenerate for vector spaces (`Subspace.dualPairing_nondegenerate`).
* Vector spaces:
* `Subspace.dualLift W` is an arbitrary section (using choice) of `Submodule.dualRestrict W`.
## Main results
* Bases:
* `Module.dualBasis.basis` and `Module.dualBasis.coe_basis`: if `e` and `ε` form a dual pair,
then `e` is a basis.
* `Module.dualBasis.coe_dualBasis`: if `e` and `ε` form a dual pair,
then `ε` is a basis.
* Annihilators:
* `Module.dualAnnihilator_gc R M` is the antitone Galois correspondence between
`Submodule.dualAnnihilator` and `Submodule.dualConnihilator`.
* `LinearMap.ker_dual_map_eq_dualAnnihilator_range` says that
`f.dual_map.ker = f.range.dualAnnihilator`
* `LinearMap.range_dual_map_eq_dualAnnihilator_ker_of_subtype_range_surjective` says that
`f.dual_map.range = f.ker.dualAnnihilator`; this is specialized to vector spaces in
`LinearMap.range_dual_map_eq_dualAnnihilator_ker`.
* `Submodule.dualQuotEquivDualAnnihilator` is the equivalence
`Dual R (M ⧸ W) ≃ₗ[R] W.dualAnnihilator`
* `Submodule.quotDualCoannihilatorToDual` is the nondegenerate pairing
`M ⧸ W.dualCoannihilator →ₗ[R] Dual R W`.
It is an perfect pairing when `R` is a field and `W` is finite-dimensional.
* Vector spaces:
* `Subspace.dualAnnihilator_dualConnihilator_eq` says that the double dual annihilator,
pulled back ground `Module.Dual.eval`, is the original submodule.
* `Subspace.dualAnnihilator_gci` says that `module.dualAnnihilator_gc R M` is an
antitone Galois coinsertion.
* `Subspace.quotAnnihilatorEquiv` is the equivalence
`Dual K V ⧸ W.dualAnnihilator ≃ₗ[K] Dual K W`.
* `LinearMap.dualPairing_nondegenerate` says that `Module.dualPairing` is nondegenerate.
* `Subspace.is_compl_dualAnnihilator` says that the dual annihilator carries complementary
subspaces to complementary subspaces.
* Finite-dimensional vector spaces:
* `Module.evalEquiv` is the equivalence `V ≃ₗ[K] Dual K (Dual K V)`
* `Module.mapEvalEquiv` is the order isomorphism between subspaces of `V` and
subspaces of `Dual K (Dual K V)`.
* `Subspace.orderIsoFiniteCodimDim` is the antitone order isomorphism between
finite-codimensional subspaces of `V` and finite-dimensional subspaces of `Dual K V`.
* `Subspace.orderIsoFiniteDimensional` is the antitone order isomorphism between
subspaces of a finite-dimensional vector space `V` and subspaces of its dual.
* `Subspace.quotDualEquivAnnihilator W` is the equivalence
`(Dual K V ⧸ W.dualLift.range) ≃ₗ[K] W.dualAnnihilator`, where `W.dualLift.range` is a copy
of `Dual K W` inside `Dual K V`.
* `Subspace.quotEquivAnnihilator W` is the equivalence `(V ⧸ W) ≃ₗ[K] W.dualAnnihilator`
* `Subspace.dualQuotDistrib W` is an equivalence
`Dual K (V₁ ⧸ W) ≃ₗ[K] Dual K V₁ ⧸ W.dualLift.range` from an arbitrary choice of
splitting of `V₁`.
-/
noncomputable section
namespace Module
-- Porting note: max u v universe issues so name and specific below
universe uR uA uM uM' uM''
variable (R : Type uR) (A : Type uA) (M : Type uM)
variable [CommSemiring R] [AddCommMonoid M] [Module R M]
/-- The dual space of an R-module M is the R-module of linear maps `M → R`. -/
abbrev Dual :=
M →ₗ[R] R
#align module.dual Module.Dual
/-- The canonical pairing of a vector space and its algebraic dual. -/
def dualPairing (R M) [CommSemiring R] [AddCommMonoid M] [Module R M] :
Module.Dual R M →ₗ[R] M →ₗ[R] R :=
LinearMap.id
#align module.dual_pairing Module.dualPairing
@[simp]
theorem dualPairing_apply (v x) : dualPairing R M v x = v x :=
rfl
#align module.dual_pairing_apply Module.dualPairing_apply
namespace Dual
instance : Inhabited (Dual R M) := ⟨0⟩
/-- Maps a module M to the dual of the dual of M. See `Module.erange_coe` and
`Module.evalEquiv`. -/
def eval : M →ₗ[R] Dual R (Dual R M) :=
LinearMap.flip LinearMap.id
#align module.dual.eval Module.Dual.eval
@[simp]
theorem eval_apply (v : M) (a : Dual R M) : eval R M v a = a v :=
rfl
#align module.dual.eval_apply Module.Dual.eval_apply
variable {R M} {M' : Type uM'}
variable [AddCommMonoid M'] [Module R M']
/-- The transposition of linear maps, as a linear map from `M →ₗ[R] M'` to
`Dual R M' →ₗ[R] Dual R M`. -/
def transpose : (M →ₗ[R] M') →ₗ[R] Dual R M' →ₗ[R] Dual R M :=
(LinearMap.llcomp R M M' R).flip
#align module.dual.transpose Module.Dual.transpose
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem transpose_apply (u : M →ₗ[R] M') (l : Dual R M') : transpose (R := R) u l = l.comp u :=
rfl
#align module.dual.transpose_apply Module.Dual.transpose_apply
variable {M'' : Type uM''} [AddCommMonoid M''] [Module R M'']
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem transpose_comp (u : M' →ₗ[R] M'') (v : M →ₗ[R] M') :
transpose (R := R) (u.comp v) = (transpose (R := R) v).comp (transpose (R := R) u) :=
rfl
#align module.dual.transpose_comp Module.Dual.transpose_comp
end Dual
section Prod
variable (M' : Type uM') [AddCommMonoid M'] [Module R M']
/-- Taking duals distributes over products. -/
@[simps!]
def dualProdDualEquivDual : (Module.Dual R M × Module.Dual R M') ≃ₗ[R] Module.Dual R (M × M') :=
LinearMap.coprodEquiv R
#align module.dual_prod_dual_equiv_dual Module.dualProdDualEquivDual
@[simp]
theorem dualProdDualEquivDual_apply (φ : Module.Dual R M) (ψ : Module.Dual R M') :
dualProdDualEquivDual R M M' (φ, ψ) = φ.coprod ψ :=
rfl
#align module.dual_prod_dual_equiv_dual_apply Module.dualProdDualEquivDual_apply
end Prod
end Module
section DualMap
open Module
universe u v v'
variable {R : Type u} [CommSemiring R] {M₁ : Type v} {M₂ : Type v'}
variable [AddCommMonoid M₁] [Module R M₁] [AddCommMonoid M₂] [Module R M₂]
/-- Given a linear map `f : M₁ →ₗ[R] M₂`, `f.dualMap` is the linear map between the dual of
`M₂` and `M₁` such that it maps the functional `φ` to `φ ∘ f`. -/
def LinearMap.dualMap (f : M₁ →ₗ[R] M₂) : Dual R M₂ →ₗ[R] Dual R M₁ :=
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
Module.Dual.transpose (R := R) f
#align linear_map.dual_map LinearMap.dualMap
lemma LinearMap.dualMap_eq_lcomp (f : M₁ →ₗ[R] M₂) : f.dualMap = f.lcomp R := rfl
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem LinearMap.dualMap_def (f : M₁ →ₗ[R] M₂) : f.dualMap = Module.Dual.transpose (R := R) f :=
rfl
#align linear_map.dual_map_def LinearMap.dualMap_def
theorem LinearMap.dualMap_apply' (f : M₁ →ₗ[R] M₂) (g : Dual R M₂) : f.dualMap g = g.comp f :=
rfl
#align linear_map.dual_map_apply' LinearMap.dualMap_apply'
@[simp]
theorem LinearMap.dualMap_apply (f : M₁ →ₗ[R] M₂) (g : Dual R M₂) (x : M₁) :
f.dualMap g x = g (f x) :=
rfl
#align linear_map.dual_map_apply LinearMap.dualMap_apply
@[simp]
theorem LinearMap.dualMap_id : (LinearMap.id : M₁ →ₗ[R] M₁).dualMap = LinearMap.id := by
ext
rfl
#align linear_map.dual_map_id LinearMap.dualMap_id
theorem LinearMap.dualMap_comp_dualMap {M₃ : Type*} [AddCommGroup M₃] [Module R M₃]
(f : M₁ →ₗ[R] M₂) (g : M₂ →ₗ[R] M₃) : f.dualMap.comp g.dualMap = (g.comp f).dualMap :=
rfl
#align linear_map.dual_map_comp_dual_map LinearMap.dualMap_comp_dualMap
/-- If a linear map is surjective, then its dual is injective. -/
theorem LinearMap.dualMap_injective_of_surjective {f : M₁ →ₗ[R] M₂} (hf : Function.Surjective f) :
Function.Injective f.dualMap := by
intro φ ψ h
ext x
obtain ⟨y, rfl⟩ := hf x
exact congr_arg (fun g : Module.Dual R M₁ => g y) h
#align linear_map.dual_map_injective_of_surjective LinearMap.dualMap_injective_of_surjective
/-- The `Linear_equiv` version of `LinearMap.dualMap`. -/
def LinearEquiv.dualMap (f : M₁ ≃ₗ[R] M₂) : Dual R M₂ ≃ₗ[R] Dual R M₁ where
__ := f.toLinearMap.dualMap
invFun := f.symm.toLinearMap.dualMap
left_inv φ := LinearMap.ext fun x ↦ congr_arg φ (f.right_inv x)
right_inv φ := LinearMap.ext fun x ↦ congr_arg φ (f.left_inv x)
#align linear_equiv.dual_map LinearEquiv.dualMap
@[simp]
theorem LinearEquiv.dualMap_apply (f : M₁ ≃ₗ[R] M₂) (g : Dual R M₂) (x : M₁) :
f.dualMap g x = g (f x) :=
rfl
#align linear_equiv.dual_map_apply LinearEquiv.dualMap_apply
@[simp]
theorem LinearEquiv.dualMap_refl :
(LinearEquiv.refl R M₁).dualMap = LinearEquiv.refl R (Dual R M₁) := by
ext
rfl
#align linear_equiv.dual_map_refl LinearEquiv.dualMap_refl
@[simp]
theorem LinearEquiv.dualMap_symm {f : M₁ ≃ₗ[R] M₂} :
(LinearEquiv.dualMap f).symm = LinearEquiv.dualMap f.symm :=
rfl
#align linear_equiv.dual_map_symm LinearEquiv.dualMap_symm
theorem LinearEquiv.dualMap_trans {M₃ : Type*} [AddCommGroup M₃] [Module R M₃] (f : M₁ ≃ₗ[R] M₂)
(g : M₂ ≃ₗ[R] M₃) : g.dualMap.trans f.dualMap = (f.trans g).dualMap :=
rfl
#align linear_equiv.dual_map_trans LinearEquiv.dualMap_trans
@[simp]
lemma Dual.apply_one_mul_eq (f : Dual R R) (r : R) :
f 1 * r = f r := by
conv_rhs => rw [← mul_one r, ← smul_eq_mul]
rw [map_smul, smul_eq_mul, mul_comm]
@[simp]
lemma LinearMap.range_dualMap_dual_eq_span_singleton (f : Dual R M₁) :
range f.dualMap = R ∙ f := by
ext m
rw [Submodule.mem_span_singleton]
refine ⟨fun ⟨r, hr⟩ ↦ ⟨r 1, ?_⟩, fun ⟨r, hr⟩ ↦ ⟨r • LinearMap.id, ?_⟩⟩
· ext; simp [dualMap_apply', ← hr]
· ext; simp [dualMap_apply', ← hr]
end DualMap
namespace Basis
universe u v w
open Module Module.Dual Submodule LinearMap Cardinal Function
universe uR uM uK uV uι
variable {R : Type uR} {M : Type uM} {K : Type uK} {V : Type uV} {ι : Type uι}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [DecidableEq ι]
variable (b : Basis ι R M)
/-- The linear map from a vector space equipped with basis to its dual vector space,
taking basis elements to corresponding dual basis elements. -/
def toDual : M →ₗ[R] Module.Dual R M :=
b.constr ℕ fun v => b.constr ℕ fun w => if w = v then (1 : R) else 0
#align basis.to_dual Basis.toDual
theorem toDual_apply (i j : ι) : b.toDual (b i) (b j) = if i = j then 1 else 0 := by
erw [constr_basis b, constr_basis b]
simp only [eq_comm]
#align basis.to_dual_apply Basis.toDual_apply
@[simp]
theorem toDual_total_left (f : ι →₀ R) (i : ι) :
b.toDual (Finsupp.total ι M R b f) (b i) = f i := by
rw [Finsupp.total_apply, Finsupp.sum, _root_.map_sum, LinearMap.sum_apply]
simp_rw [LinearMap.map_smul, LinearMap.smul_apply, toDual_apply, smul_eq_mul, mul_boole,
Finset.sum_ite_eq']
split_ifs with h
· rfl
· rw [Finsupp.not_mem_support_iff.mp h]
#align basis.to_dual_total_left Basis.toDual_total_left
@[simp]
theorem toDual_total_right (f : ι →₀ R) (i : ι) :
b.toDual (b i) (Finsupp.total ι M R b f) = f i := by
rw [Finsupp.total_apply, Finsupp.sum, _root_.map_sum]
simp_rw [LinearMap.map_smul, toDual_apply, smul_eq_mul, mul_boole, Finset.sum_ite_eq]
split_ifs with h
· rfl
· rw [Finsupp.not_mem_support_iff.mp h]
#align basis.to_dual_total_right Basis.toDual_total_right
theorem toDual_apply_left (m : M) (i : ι) : b.toDual m (b i) = b.repr m i := by
rw [← b.toDual_total_left, b.total_repr]
#align basis.to_dual_apply_left Basis.toDual_apply_left
theorem toDual_apply_right (i : ι) (m : M) : b.toDual (b i) m = b.repr m i := by
rw [← b.toDual_total_right, b.total_repr]
#align basis.to_dual_apply_right Basis.toDual_apply_right
theorem coe_toDual_self (i : ι) : b.toDual (b i) = b.coord i := by
ext
apply toDual_apply_right
#align basis.coe_to_dual_self Basis.coe_toDual_self
/-- `h.toDual_flip v` is the linear map sending `w` to `h.toDual w v`. -/
def toDualFlip (m : M) : M →ₗ[R] R :=
b.toDual.flip m
#align basis.to_dual_flip Basis.toDualFlip
theorem toDualFlip_apply (m₁ m₂ : M) : b.toDualFlip m₁ m₂ = b.toDual m₂ m₁ :=
rfl
#align basis.to_dual_flip_apply Basis.toDualFlip_apply
theorem toDual_eq_repr (m : M) (i : ι) : b.toDual m (b i) = b.repr m i :=
b.toDual_apply_left m i
#align basis.to_dual_eq_repr Basis.toDual_eq_repr
theorem toDual_eq_equivFun [Finite ι] (m : M) (i : ι) : b.toDual m (b i) = b.equivFun m i := by
rw [b.equivFun_apply, toDual_eq_repr]
#align basis.to_dual_eq_equiv_fun Basis.toDual_eq_equivFun
theorem toDual_injective : Injective b.toDual := fun x y h ↦ b.ext_elem_iff.mpr fun i ↦ by
simp_rw [← toDual_eq_repr]; exact DFunLike.congr_fun h _
theorem toDual_inj (m : M) (a : b.toDual m = 0) : m = 0 :=
b.toDual_injective (by rwa [_root_.map_zero])
#align basis.to_dual_inj Basis.toDual_inj
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
theorem toDual_ker : LinearMap.ker b.toDual = ⊥ :=
ker_eq_bot'.mpr b.toDual_inj
#align basis.to_dual_ker Basis.toDual_ker
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem toDual_range [Finite ι] : LinearMap.range b.toDual = ⊤ := by
refine eq_top_iff'.2 fun f => ?_
let lin_comb : ι →₀ R := Finsupp.equivFunOnFinite.symm fun i => f (b i)
refine ⟨Finsupp.total ι M R b lin_comb, b.ext fun i => ?_⟩
rw [b.toDual_eq_repr _ i, repr_total b]
rfl
#align basis.to_dual_range Basis.toDual_range
end CommSemiring
section
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [Fintype ι]
variable (b : Basis ι R M)
@[simp]
theorem sum_dual_apply_smul_coord (f : Module.Dual R M) :
(∑ x, f (b x) • b.coord x) = f := by
ext m
simp_rw [LinearMap.sum_apply, LinearMap.smul_apply, smul_eq_mul, mul_comm (f _), ← smul_eq_mul, ←
f.map_smul, ← _root_.map_sum, Basis.coord_apply, Basis.sum_repr]
#align basis.sum_dual_apply_smul_coord Basis.sum_dual_apply_smul_coord
end
section CommRing
variable [CommRing R] [AddCommGroup M] [Module R M] [DecidableEq ι]
variable (b : Basis ι R M)
section Finite
variable [Finite ι]
/-- A vector space is linearly equivalent to its dual space. -/
def toDualEquiv : M ≃ₗ[R] Dual R M :=
LinearEquiv.ofBijective b.toDual ⟨ker_eq_bot.mp b.toDual_ker, range_eq_top.mp b.toDual_range⟩
#align basis.to_dual_equiv Basis.toDualEquiv
-- `simps` times out when generating this
@[simp]
theorem toDualEquiv_apply (m : M) : b.toDualEquiv m = b.toDual m :=
rfl
#align basis.to_dual_equiv_apply Basis.toDualEquiv_apply
-- Not sure whether this is true for free modules over a commutative ring
/-- A vector space over a field is isomorphic to its dual if and only if it is finite-dimensional:
a consequence of the Erdős-Kaplansky theorem. -/
theorem linearEquiv_dual_iff_finiteDimensional [Field K] [AddCommGroup V] [Module K V] :
Nonempty (V ≃ₗ[K] Dual K V) ↔ FiniteDimensional K V := by
refine ⟨fun ⟨e⟩ ↦ ?_, fun h ↦ ⟨(Module.Free.chooseBasis K V).toDualEquiv⟩⟩
rw [FiniteDimensional, ← Module.rank_lt_alpeh0_iff]
by_contra!
apply (lift_rank_lt_rank_dual this).ne
have := e.lift_rank_eq
rwa [lift_umax.{uV,uK}, lift_id'.{uV,uK}] at this
/-- Maps a basis for `V` to a basis for the dual space. -/
def dualBasis : Basis ι R (Dual R M) :=
b.map b.toDualEquiv
#align basis.dual_basis Basis.dualBasis
-- We use `j = i` to match `Basis.repr_self`
theorem dualBasis_apply_self (i j : ι) : b.dualBasis i (b j) =
if j = i then 1 else 0 := by
convert b.toDual_apply i j using 2
rw [@eq_comm _ j i]
#align basis.dual_basis_apply_self Basis.dualBasis_apply_self
theorem total_dualBasis (f : ι →₀ R) (i : ι) :
Finsupp.total ι (Dual R M) R b.dualBasis f (b i) = f i := by
cases nonempty_fintype ι
rw [Finsupp.total_apply, Finsupp.sum_fintype, LinearMap.sum_apply]
· simp_rw [LinearMap.smul_apply, smul_eq_mul, dualBasis_apply_self, mul_boole,
Finset.sum_ite_eq, if_pos (Finset.mem_univ i)]
· intro
rw [zero_smul]
#align basis.total_dual_basis Basis.total_dualBasis
theorem dualBasis_repr (l : Dual R M) (i : ι) : b.dualBasis.repr l i = l (b i) := by
rw [← total_dualBasis b, Basis.total_repr b.dualBasis l]
#align basis.dual_basis_repr Basis.dualBasis_repr
theorem dualBasis_apply (i : ι) (m : M) : b.dualBasis i m = b.repr m i :=
b.toDual_apply_right i m
#align basis.dual_basis_apply Basis.dualBasis_apply
@[simp]
theorem coe_dualBasis : ⇑b.dualBasis = b.coord := by
ext i x
apply dualBasis_apply
#align basis.coe_dual_basis Basis.coe_dualBasis
@[simp]
theorem toDual_toDual : b.dualBasis.toDual.comp b.toDual = Dual.eval R M := by
refine b.ext fun i => b.dualBasis.ext fun j => ?_
rw [LinearMap.comp_apply, toDual_apply_left, coe_toDual_self, ← coe_dualBasis,
Dual.eval_apply, Basis.repr_self, Finsupp.single_apply, dualBasis_apply_self]
#align basis.to_dual_to_dual Basis.toDual_toDual
end Finite
theorem dualBasis_equivFun [Finite ι] (l : Dual R M) (i : ι) :
b.dualBasis.equivFun l i = l (b i) := by rw [Basis.equivFun_apply, dualBasis_repr]
#align basis.dual_basis_equiv_fun Basis.dualBasis_equivFun
theorem eval_ker {ι : Type*} (b : Basis ι R M) :
LinearMap.ker (Dual.eval R M) = ⊥ := by
rw [ker_eq_bot']
intro m hm
simp_rw [LinearMap.ext_iff, Dual.eval_apply, zero_apply] at hm
exact (Basis.forall_coord_eq_zero_iff _).mp fun i => hm (b.coord i)
#align basis.eval_ker Basis.eval_ker
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem eval_range {ι : Type*} [Finite ι] (b : Basis ι R M) :
LinearMap.range (Dual.eval R M) = ⊤ := by
classical
cases nonempty_fintype ι
rw [← b.toDual_toDual, range_comp, b.toDual_range, Submodule.map_top, toDual_range _]
#align basis.eval_range Basis.eval_range
section
variable [Finite R M] [Free R M]
instance dual_free : Free R (Dual R M) :=
Free.of_basis (Free.chooseBasis R M).dualBasis
#align basis.dual_free Basis.dual_free
instance dual_finite : Finite R (Dual R M) :=
Finite.of_basis (Free.chooseBasis R M).dualBasis
#align basis.dual_finite Basis.dual_finite
end
end CommRing
/-- `simp` normal form version of `total_dualBasis` -/
@[simp]
theorem total_coord [CommRing R] [AddCommGroup M] [Module R M] [Finite ι] (b : Basis ι R M)
(f : ι →₀ R) (i : ι) : Finsupp.total ι (Dual R M) R b.coord f (b i) = f i := by
haveI := Classical.decEq ι
rw [← coe_dualBasis, total_dualBasis]
#align basis.total_coord Basis.total_coord
theorem dual_rank_eq [CommRing K] [AddCommGroup V] [Module K V] [Finite ι] (b : Basis ι K V) :
Cardinal.lift.{uK,uV} (Module.rank K V) = Module.rank K (Dual K V) := by
classical rw [← lift_umax.{uV,uK}, b.toDualEquiv.lift_rank_eq, lift_id'.{uV,uK}]
#align basis.dual_rank_eq Basis.dual_rank_eq
end Basis
namespace Module
universe uK uV
variable {K : Type uK} {V : Type uV}
variable [CommRing K] [AddCommGroup V] [Module K V] [Module.Free K V]
open Module Module.Dual Submodule LinearMap Cardinal Basis FiniteDimensional
section
variable (K) (V)
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
theorem eval_ker : LinearMap.ker (eval K V) = ⊥ := by
classical exact (Module.Free.chooseBasis K V).eval_ker
#align module.eval_ker Module.eval_ker
theorem map_eval_injective : (Submodule.map (eval K V)).Injective := by
apply Submodule.map_injective_of_injective
rw [← LinearMap.ker_eq_bot]
exact eval_ker K V
#align module.map_eval_injective Module.map_eval_injective
theorem comap_eval_surjective : (Submodule.comap (eval K V)).Surjective := by
apply Submodule.comap_surjective_of_injective
rw [← LinearMap.ker_eq_bot]
exact eval_ker K V
#align module.comap_eval_surjective Module.comap_eval_surjective
end
section
variable (K)
theorem eval_apply_eq_zero_iff (v : V) : (eval K V) v = 0 ↔ v = 0 := by
simpa only using SetLike.ext_iff.mp (eval_ker K V) v
#align module.eval_apply_eq_zero_iff Module.eval_apply_eq_zero_iff
theorem eval_apply_injective : Function.Injective (eval K V) :=
(injective_iff_map_eq_zero' (eval K V)).mpr (eval_apply_eq_zero_iff K)
#align module.eval_apply_injective Module.eval_apply_injective
theorem forall_dual_apply_eq_zero_iff (v : V) : (∀ φ : Module.Dual K V, φ v = 0) ↔ v = 0 := by
rw [← eval_apply_eq_zero_iff K v, LinearMap.ext_iff]
rfl
#align module.forall_dual_apply_eq_zero_iff Module.forall_dual_apply_eq_zero_iff
@[simp]
theorem subsingleton_dual_iff :
Subsingleton (Dual K V) ↔ Subsingleton V := by
refine ⟨fun h ↦ ⟨fun v w ↦ ?_⟩, fun h ↦ ⟨fun f g ↦ ?_⟩⟩
· rw [← sub_eq_zero, ← forall_dual_apply_eq_zero_iff K (v - w)]
intros f
simp [Subsingleton.elim f 0]
· ext v
simp [Subsingleton.elim v 0]
instance instSubsingletonDual [Subsingleton V] : Subsingleton (Dual K V) :=
(subsingleton_dual_iff K).mp inferInstance
@[simp]
theorem nontrivial_dual_iff :
Nontrivial (Dual K V) ↔ Nontrivial V := by
rw [← not_iff_not, not_nontrivial_iff_subsingleton, not_nontrivial_iff_subsingleton,
subsingleton_dual_iff]
instance instNontrivialDual [Nontrivial V] : Nontrivial (Dual K V) :=
(nontrivial_dual_iff K).mpr inferInstance
theorem finite_dual_iff : Finite K (Dual K V) ↔ Finite K V := by
constructor <;> intro h
· obtain ⟨⟨ι, b⟩⟩ := Module.Free.exists_basis (R := K) (M := V)
nontriviality K
obtain ⟨⟨s, span_s⟩⟩ := h
classical
haveI := (b.linearIndependent.map' _ b.toDual_ker).finite_of_le_span_finite _ s ?_
· exact Finite.of_basis b
· rw [span_s]; apply le_top
· infer_instance
end
theorem dual_rank_eq [Module.Finite K V] :
Cardinal.lift.{uK,uV} (Module.rank K V) = Module.rank K (Dual K V) :=
(Module.Free.chooseBasis K V).dual_rank_eq
#align module.dual_rank_eq Module.dual_rank_eq
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem erange_coe [Module.Finite K V] : LinearMap.range (eval K V) = ⊤ :=
(Module.Free.chooseBasis K V).eval_range
#align module.erange_coe Module.erange_coe
section IsReflexive
open Function
variable (R M N : Type*) [CommRing R] [AddCommGroup M] [AddCommGroup N] [Module R M] [Module R N]
/-- A reflexive module is one for which the natural map to its double dual is a bijection.
Any finitely-generated free module (and thus any finite-dimensional vector space) is reflexive.
See `Module.IsReflexive.of_finite_of_free`. -/
class IsReflexive : Prop where
/-- A reflexive module is one for which the natural map to its double dual is a bijection. -/
bijective_dual_eval' : Bijective (Dual.eval R M)
lemma bijective_dual_eval [IsReflexive R M] : Bijective (Dual.eval R M) :=
IsReflexive.bijective_dual_eval'
instance IsReflexive.of_finite_of_free [Finite R M] [Free R M] : IsReflexive R M where
bijective_dual_eval' := ⟨LinearMap.ker_eq_bot.mp (Free.chooseBasis R M).eval_ker,
LinearMap.range_eq_top.mp (Free.chooseBasis R M).eval_range⟩
variable [IsReflexive R M]
/-- The bijection between a reflexive module and its double dual, bundled as a `LinearEquiv`. -/
def evalEquiv : M ≃ₗ[R] Dual R (Dual R M) :=
LinearEquiv.ofBijective _ (bijective_dual_eval R M)
#align module.eval_equiv Module.evalEquiv
@[simp] lemma evalEquiv_toLinearMap : evalEquiv R M = Dual.eval R M := rfl
#align module.eval_equiv_to_linear_map Module.evalEquiv_toLinearMap
@[simp] lemma evalEquiv_apply (m : M) : evalEquiv R M m = Dual.eval R M m := rfl
@[simp] lemma apply_evalEquiv_symm_apply (f : Dual R M) (g : Dual R (Dual R M)) :
f ((evalEquiv R M).symm g) = g f := by
set m := (evalEquiv R M).symm g
rw [← (evalEquiv R M).apply_symm_apply g, evalEquiv_apply, Dual.eval_apply]
@[simp] lemma symm_dualMap_evalEquiv :
(evalEquiv R M).symm.dualMap = Dual.eval R (Dual R M) := by
ext; simp
/-- The dual of a reflexive module is reflexive. -/
instance Dual.instIsReflecive : IsReflexive R (Dual R M) :=
⟨by simpa only [← symm_dualMap_evalEquiv] using (evalEquiv R M).dualMap.symm.bijective⟩
/-- The isomorphism `Module.evalEquiv` induces an order isomorphism on subspaces. -/
def mapEvalEquiv : Submodule R M ≃o Submodule R (Dual R (Dual R M)) :=
Submodule.orderIsoMapComap (evalEquiv R M)
#align module.map_eval_equiv Module.mapEvalEquiv
@[simp]
theorem mapEvalEquiv_apply (W : Submodule R M) :
mapEvalEquiv R M W = W.map (Dual.eval R M) :=
rfl
#align module.map_eval_equiv_apply Module.mapEvalEquiv_apply
@[simp]
theorem mapEvalEquiv_symm_apply (W'' : Submodule R (Dual R (Dual R M))) :
(mapEvalEquiv R M).symm W'' = W''.comap (Dual.eval R M) :=
rfl
#align module.map_eval_equiv_symm_apply Module.mapEvalEquiv_symm_apply
instance _root_.Prod.instModuleIsReflexive [IsReflexive R N] :
IsReflexive R (M × N) where
bijective_dual_eval' := by
let e : Dual R (Dual R (M × N)) ≃ₗ[R] Dual R (Dual R M) × Dual R (Dual R N) :=
(dualProdDualEquivDual R M N).dualMap.trans
(dualProdDualEquivDual R (Dual R M) (Dual R N)).symm
have : Dual.eval R (M × N) = e.symm.comp ((Dual.eval R M).prodMap (Dual.eval R N)) := by
ext m f <;> simp [e]
simp only [this, LinearEquiv.trans_symm, LinearEquiv.symm_symm, LinearEquiv.dualMap_symm,
coe_comp, LinearEquiv.coe_coe, EquivLike.comp_bijective]
exact (bijective_dual_eval R M).prodMap (bijective_dual_eval R N)
variable {R M N} in
lemma equiv (e : M ≃ₗ[R] N) : IsReflexive R N where
bijective_dual_eval' := by
let ed : Dual R (Dual R N) ≃ₗ[R] Dual R (Dual R M) := e.symm.dualMap.dualMap
have : Dual.eval R N = ed.symm.comp ((Dual.eval R M).comp e.symm.toLinearMap) := by
ext m f
exact DFunLike.congr_arg f (e.apply_symm_apply m).symm
simp only [this, LinearEquiv.trans_symm, LinearEquiv.symm_symm, LinearEquiv.dualMap_symm,
coe_comp, LinearEquiv.coe_coe, EquivLike.comp_bijective]
exact Bijective.comp (bijective_dual_eval R M) (LinearEquiv.bijective _)
instance _root_.MulOpposite.instModuleIsReflexive : IsReflexive R (MulOpposite M) :=
equiv <| MulOpposite.opLinearEquiv _
instance _root_.ULift.instModuleIsReflexive.{w} : IsReflexive R (ULift.{w} M) :=
equiv ULift.moduleEquiv.symm
end IsReflexive
end Module
namespace Submodule
open Module
variable {R M : Type*} [CommRing R] [AddCommGroup M] [Module R M] {p : Submodule R M}
theorem exists_dual_map_eq_bot_of_nmem {x : M} (hx : x ∉ p) (hp' : Free R (M ⧸ p)) :
∃ f : Dual R M, f x ≠ 0 ∧ p.map f = ⊥ := by
suffices ∃ f : Dual R (M ⧸ p), f (p.mkQ x) ≠ 0 by
obtain ⟨f, hf⟩ := this; exact ⟨f.comp p.mkQ, hf, by simp [Submodule.map_comp]⟩
rwa [← Submodule.Quotient.mk_eq_zero, ← Submodule.mkQ_apply,
← forall_dual_apply_eq_zero_iff (K := R), not_forall] at hx
theorem exists_dual_map_eq_bot_of_lt_top (hp : p < ⊤) (hp' : Free R (M ⧸ p)) :
∃ f : Dual R M, f ≠ 0 ∧ p.map f = ⊥ := by
obtain ⟨x, hx⟩ : ∃ x : M, x ∉ p := by rw [lt_top_iff_ne_top] at hp; contrapose! hp; ext; simp [hp]
obtain ⟨f, hf, hf'⟩ := p.exists_dual_map_eq_bot_of_nmem hx hp'
exact ⟨f, by aesop, hf'⟩
end Submodule
section DualBases
open Module
variable {R M ι : Type*}
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [DecidableEq ι]
-- Porting note: replace use_finite_instance tactic
open Lean.Elab.Tactic in
/-- Try using `Set.to_finite` to dispatch a `Set.finite` goal. -/
def evalUseFiniteInstance : TacticM Unit := do
evalTactic (← `(tactic| intros; apply Set.toFinite))
elab "use_finite_instance" : tactic => evalUseFiniteInstance
/-- `e` and `ε` have characteristic properties of a basis and its dual -/
-- @[nolint has_nonempty_instance] Porting note (#5171): removed
structure Module.DualBases (e : ι → M) (ε : ι → Dual R M) : Prop where
eval : ∀ i j : ι, ε i (e j) = if i = j then 1 else 0
protected total : ∀ {m : M}, (∀ i, ε i m = 0) → m = 0
protected finite : ∀ m : M, { i | ε i m ≠ 0 }.Finite := by
use_finite_instance
#align module.dual_bases Module.DualBases
end DualBases
namespace Module.DualBases
open Module Module.Dual LinearMap Function
variable {R M ι : Type*}
variable [CommRing R] [AddCommGroup M] [Module R M]
variable {e : ι → M} {ε : ι → Dual R M}
/-- The coefficients of `v` on the basis `e` -/
def coeffs [DecidableEq ι] (h : DualBases e ε) (m : M) : ι →₀ R where
toFun i := ε i m
support := (h.finite m).toFinset
mem_support_toFun i := by rw [Set.Finite.mem_toFinset, Set.mem_setOf_eq]
#align module.dual_bases.coeffs Module.DualBases.coeffs
@[simp]
theorem coeffs_apply [DecidableEq ι] (h : DualBases e ε) (m : M) (i : ι) : h.coeffs m i = ε i m :=
rfl
#align module.dual_bases.coeffs_apply Module.DualBases.coeffs_apply
/-- linear combinations of elements of `e`.
This is a convenient abbreviation for `Finsupp.total _ M R e l` -/
def lc {ι} (e : ι → M) (l : ι →₀ R) : M :=
l.sum fun (i : ι) (a : R) => a • e i
#align module.dual_bases.lc Module.DualBases.lc
theorem lc_def (e : ι → M) (l : ι →₀ R) : lc e l = Finsupp.total _ _ R e l :=
rfl
#align module.dual_bases.lc_def Module.DualBases.lc_def
open Module
variable [DecidableEq ι] (h : DualBases e ε)
theorem dual_lc (l : ι →₀ R) (i : ι) : ε i (DualBases.lc e l) = l i := by
rw [lc, _root_.map_finsupp_sum, Finsupp.sum_eq_single i (g := fun a b ↦ (ε i) (b • e a))]
-- Porting note: cannot get at •
-- simp only [h.eval, map_smul, smul_eq_mul]
· simp [h.eval, smul_eq_mul]
· intro q _ q_ne
simp [q_ne.symm, h.eval, smul_eq_mul]
· simp
#align module.dual_bases.dual_lc Module.DualBases.dual_lc
@[simp]
theorem coeffs_lc (l : ι →₀ R) : h.coeffs (DualBases.lc e l) = l := by
ext i
rw [h.coeffs_apply, h.dual_lc]
#align module.dual_bases.coeffs_lc Module.DualBases.coeffs_lc
/-- For any m : M n, \sum_{p ∈ Q n} (ε p m) • e p = m -/
@[simp]
theorem lc_coeffs (m : M) : DualBases.lc e (h.coeffs m) = m := by
refine eq_of_sub_eq_zero <| h.total fun i ↦ ?_
simp [LinearMap.map_sub, h.dual_lc, sub_eq_zero]
#align module.dual_bases.lc_coeffs Module.DualBases.lc_coeffs
/-- `(h : DualBases e ε).basis` shows the family of vectors `e` forms a basis. -/
@[simps]
def basis : Basis ι R M :=
Basis.ofRepr
{ toFun := coeffs h
invFun := lc e
left_inv := lc_coeffs h
right_inv := coeffs_lc h
map_add' := fun v w => by
ext i
exact (ε i).map_add v w
map_smul' := fun c v => by
ext i
exact (ε i).map_smul c v }
#align module.dual_bases.basis Module.DualBases.basis
-- Porting note: from simpNF the LHS simplifies; it yields lc_def.symm
-- probably not a useful simp lemma; nolint simpNF since it cannot see this removal
attribute [-simp, nolint simpNF] basis_repr_symm_apply
@[simp]
theorem coe_basis : ⇑h.basis = e := by
ext i
rw [Basis.apply_eq_iff]
ext j
rw [h.basis_repr_apply, coeffs_apply, h.eval, Finsupp.single_apply]
convert if_congr (eq_comm (a := j) (b := i)) rfl rfl
#align module.dual_bases.coe_basis Module.DualBases.coe_basis
-- `convert` to get rid of a `DecidableEq` mismatch
theorem mem_of_mem_span {H : Set ι} {x : M} (hmem : x ∈ Submodule.span R (e '' H)) :
∀ i : ι, ε i x ≠ 0 → i ∈ H := by
intro i hi
rcases (Finsupp.mem_span_image_iff_total _).mp hmem with ⟨l, supp_l, rfl⟩
apply not_imp_comm.mp ((Finsupp.mem_supported' _ _).mp supp_l i)
rwa [← lc_def, h.dual_lc] at hi
#align module.dual_bases.mem_of_mem_span Module.DualBases.mem_of_mem_span
theorem coe_dualBasis [_root_.Finite ι] : ⇑h.basis.dualBasis = ε :=
funext fun i =>
h.basis.ext fun j => by
rw [h.basis.dualBasis_apply_self, h.coe_basis, h.eval, if_congr eq_comm rfl rfl]
#align module.dual_bases.coe_dual_basis Module.DualBases.coe_dualBasis
end Module.DualBases
namespace Submodule
universe u v w
variable {R : Type u} {M : Type v} [CommSemiring R] [AddCommMonoid M] [Module R M]
variable {W : Submodule R M}
/-- The `dualRestrict` of a submodule `W` of `M` is the linear map from the
dual of `M` to the dual of `W` such that the domain of each linear map is
restricted to `W`. -/
def dualRestrict (W : Submodule R M) : Module.Dual R M →ₗ[R] Module.Dual R W :=
LinearMap.domRestrict' W
#align submodule.dual_restrict Submodule.dualRestrict
theorem dualRestrict_def (W : Submodule R M) : W.dualRestrict = W.subtype.dualMap :=
rfl
#align submodule.dual_restrict_def Submodule.dualRestrict_def
@[simp]
theorem dualRestrict_apply (W : Submodule R M) (φ : Module.Dual R M) (x : W) :
W.dualRestrict φ x = φ (x : M) :=
rfl
#align submodule.dual_restrict_apply Submodule.dualRestrict_apply
/-- The `dualAnnihilator` of a submodule `W` is the set of linear maps `φ` such
that `φ w = 0` for all `w ∈ W`. -/
def dualAnnihilator {R : Type u} {M : Type v} [CommSemiring R] [AddCommMonoid M] [Module R M]
(W : Submodule R M) : Submodule R <| Module.Dual R M :=
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
LinearMap.ker W.dualRestrict
#align submodule.dual_annihilator Submodule.dualAnnihilator
@[simp]
theorem mem_dualAnnihilator (φ : Module.Dual R M) : φ ∈ W.dualAnnihilator ↔ ∀ w ∈ W, φ w = 0 := by
refine LinearMap.mem_ker.trans ?_
simp_rw [LinearMap.ext_iff, dualRestrict_apply]
exact ⟨fun h w hw => h ⟨w, hw⟩, fun h w => h w.1 w.2⟩
#align submodule.mem_dual_annihilator Submodule.mem_dualAnnihilator
/-- That $\operatorname{ker}(\iota^* : V^* \to W^*) = \operatorname{ann}(W)$.
This is the definition of the dual annihilator of the submodule $W$. -/
theorem dualRestrict_ker_eq_dualAnnihilator (W : Submodule R M) :
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
LinearMap.ker W.dualRestrict = W.dualAnnihilator :=
rfl
#align submodule.dual_restrict_ker_eq_dual_annihilator Submodule.dualRestrict_ker_eq_dualAnnihilator
/-- The `dualAnnihilator` of a submodule of the dual space pulled back along the evaluation map
`Module.Dual.eval`. -/
def dualCoannihilator (Φ : Submodule R (Module.Dual R M)) : Submodule R M :=
Φ.dualAnnihilator.comap (Module.Dual.eval R M)
#align submodule.dual_coannihilator Submodule.dualCoannihilator
@[simp]
theorem mem_dualCoannihilator {Φ : Submodule R (Module.Dual R M)} (x : M) :
x ∈ Φ.dualCoannihilator ↔ ∀ φ ∈ Φ, (φ x : R) = 0 := by
simp_rw [dualCoannihilator, mem_comap, mem_dualAnnihilator, Module.Dual.eval_apply]
#align submodule.mem_dual_coannihilator Submodule.mem_dualCoannihilator
theorem comap_dualAnnihilator (Φ : Submodule R (Module.Dual R M)) :
Φ.dualAnnihilator.comap (Module.Dual.eval R M) = Φ.dualCoannihilator := rfl
theorem map_dualCoannihilator_le (Φ : Submodule R (Module.Dual R M)) :
Φ.dualCoannihilator.map (Module.Dual.eval R M) ≤ Φ.dualAnnihilator :=
map_le_iff_le_comap.mpr (comap_dualAnnihilator Φ).le
variable (R M) in
theorem dualAnnihilator_gc :
GaloisConnection
(OrderDual.toDual ∘ (dualAnnihilator : Submodule R M → Submodule R (Module.Dual R M)))
(dualCoannihilator ∘ OrderDual.ofDual) := by
intro a b
induction b using OrderDual.rec
simp only [Function.comp_apply, OrderDual.toDual_le_toDual, OrderDual.ofDual_toDual]
constructor <;>
· intro h x hx
simp only [mem_dualAnnihilator, mem_dualCoannihilator]
intro y hy
have := h hy
simp only [mem_dualAnnihilator, mem_dualCoannihilator] at this
exact this x hx
#align submodule.dual_annihilator_gc Submodule.dualAnnihilator_gc
theorem le_dualAnnihilator_iff_le_dualCoannihilator {U : Submodule R (Module.Dual R M)}
{V : Submodule R M} : U ≤ V.dualAnnihilator ↔ V ≤ U.dualCoannihilator :=
(dualAnnihilator_gc R M).le_iff_le
#align submodule.le_dual_annihilator_iff_le_dual_coannihilator Submodule.le_dualAnnihilator_iff_le_dualCoannihilator
@[simp]
theorem dualAnnihilator_bot : (⊥ : Submodule R M).dualAnnihilator = ⊤ :=
(dualAnnihilator_gc R M).l_bot
#align submodule.dual_annihilator_bot Submodule.dualAnnihilator_bot
@[simp]
theorem dualAnnihilator_top : (⊤ : Submodule R M).dualAnnihilator = ⊥ := by
rw [eq_bot_iff]
intro v
simp_rw [mem_dualAnnihilator, mem_bot, mem_top, forall_true_left]
exact fun h => LinearMap.ext h
#align submodule.dual_annihilator_top Submodule.dualAnnihilator_top
@[simp]
theorem dualCoannihilator_bot : (⊥ : Submodule R (Module.Dual R M)).dualCoannihilator = ⊤ :=
(dualAnnihilator_gc R M).u_top
#align submodule.dual_coannihilator_bot Submodule.dualCoannihilator_bot
@[mono]
theorem dualAnnihilator_anti {U V : Submodule R M} (hUV : U ≤ V) :
V.dualAnnihilator ≤ U.dualAnnihilator :=
(dualAnnihilator_gc R M).monotone_l hUV
#align submodule.dual_annihilator_anti Submodule.dualAnnihilator_anti
@[mono]
theorem dualCoannihilator_anti {U V : Submodule R (Module.Dual R M)} (hUV : U ≤ V) :
V.dualCoannihilator ≤ U.dualCoannihilator :=
(dualAnnihilator_gc R M).monotone_u hUV
#align submodule.dual_coannihilator_anti Submodule.dualCoannihilator_anti
theorem le_dualAnnihilator_dualCoannihilator (U : Submodule R M) :
U ≤ U.dualAnnihilator.dualCoannihilator :=
(dualAnnihilator_gc R M).le_u_l U
#align submodule.le_dual_annihilator_dual_coannihilator Submodule.le_dualAnnihilator_dualCoannihilator
theorem le_dualCoannihilator_dualAnnihilator (U : Submodule R (Module.Dual R M)) :
U ≤ U.dualCoannihilator.dualAnnihilator :=
(dualAnnihilator_gc R M).l_u_le U
#align submodule.le_dual_coannihilator_dual_annihilator Submodule.le_dualCoannihilator_dualAnnihilator
theorem dualAnnihilator_dualCoannihilator_dualAnnihilator (U : Submodule R M) :
U.dualAnnihilator.dualCoannihilator.dualAnnihilator = U.dualAnnihilator :=
(dualAnnihilator_gc R M).l_u_l_eq_l U
#align submodule.dual_annihilator_dual_coannihilator_dual_annihilator Submodule.dualAnnihilator_dualCoannihilator_dualAnnihilator
theorem dualCoannihilator_dualAnnihilator_dualCoannihilator (U : Submodule R (Module.Dual R M)) :
U.dualCoannihilator.dualAnnihilator.dualCoannihilator = U.dualCoannihilator :=
(dualAnnihilator_gc R M).u_l_u_eq_u U
#align submodule.dual_coannihilator_dual_annihilator_dual_coannihilator Submodule.dualCoannihilator_dualAnnihilator_dualCoannihilator
theorem dualAnnihilator_sup_eq (U V : Submodule R M) :
(U ⊔ V).dualAnnihilator = U.dualAnnihilator ⊓ V.dualAnnihilator :=
(dualAnnihilator_gc R M).l_sup
#align submodule.dual_annihilator_sup_eq Submodule.dualAnnihilator_sup_eq
theorem dualCoannihilator_sup_eq (U V : Submodule R (Module.Dual R M)) :
(U ⊔ V).dualCoannihilator = U.dualCoannihilator ⊓ V.dualCoannihilator :=
(dualAnnihilator_gc R M).u_inf
#align submodule.dual_coannihilator_sup_eq Submodule.dualCoannihilator_sup_eq
theorem dualAnnihilator_iSup_eq {ι : Sort*} (U : ι → Submodule R M) :
(⨆ i : ι, U i).dualAnnihilator = ⨅ i : ι, (U i).dualAnnihilator :=
(dualAnnihilator_gc R M).l_iSup
#align submodule.dual_annihilator_supr_eq Submodule.dualAnnihilator_iSup_eq
theorem dualCoannihilator_iSup_eq {ι : Sort*} (U : ι → Submodule R (Module.Dual R M)) :
(⨆ i : ι, U i).dualCoannihilator = ⨅ i : ι, (U i).dualCoannihilator :=
(dualAnnihilator_gc R M).u_iInf
#align submodule.dual_coannihilator_supr_eq Submodule.dualCoannihilator_iSup_eq
/-- See also `Subspace.dualAnnihilator_inf_eq` for vector subspaces. -/
theorem sup_dualAnnihilator_le_inf (U V : Submodule R M) :
U.dualAnnihilator ⊔ V.dualAnnihilator ≤ (U ⊓ V).dualAnnihilator := by
rw [le_dualAnnihilator_iff_le_dualCoannihilator, dualCoannihilator_sup_eq]
apply inf_le_inf <;> exact le_dualAnnihilator_dualCoannihilator _
#align submodule.sup_dual_annihilator_le_inf Submodule.sup_dualAnnihilator_le_inf
/-- See also `Subspace.dualAnnihilator_iInf_eq` for vector subspaces when `ι` is finite. -/
theorem iSup_dualAnnihilator_le_iInf {ι : Sort*} (U : ι → Submodule R M) :
⨆ i : ι, (U i).dualAnnihilator ≤ (⨅ i : ι, U i).dualAnnihilator := by
rw [le_dualAnnihilator_iff_le_dualCoannihilator, dualCoannihilator_iSup_eq]
apply iInf_mono
exact fun i : ι => le_dualAnnihilator_dualCoannihilator (U i)
#align submodule.supr_dual_annihilator_le_infi Submodule.iSup_dualAnnihilator_le_iInf
end Submodule
namespace Subspace
open Submodule LinearMap
universe u v w
-- We work in vector spaces because `exists_is_compl` only hold for vector spaces
variable {K : Type u} {V : Type v} [Field K] [AddCommGroup V] [Module K V]
@[simp]
theorem dualCoannihilator_top (W : Subspace K V) :
(⊤ : Subspace K (Module.Dual K W)).dualCoannihilator = ⊥ := by
rw [dualCoannihilator, dualAnnihilator_top, comap_bot, Module.eval_ker]
#align subspace.dual_coannihilator_top Subspace.dualCoannihilator_top
@[simp]
theorem dualAnnihilator_dualCoannihilator_eq {W : Subspace K V} :
W.dualAnnihilator.dualCoannihilator = W := by
refine le_antisymm (fun v ↦ Function.mtr ?_) (le_dualAnnihilator_dualCoannihilator _)
simp only [mem_dualAnnihilator, mem_dualCoannihilator]
rw [← Quotient.mk_eq_zero W, ← Module.forall_dual_apply_eq_zero_iff K]
push_neg
refine fun ⟨φ, hφ⟩ ↦ ⟨φ.comp W.mkQ, fun w hw ↦ ?_, hφ⟩
rw [comp_apply, mkQ_apply, (Quotient.mk_eq_zero W).mpr hw, φ.map_zero]
#align subspace.dual_annihilator_dual_coannihilator_eq Subspace.dualAnnihilator_dualCoannihilator_eq
-- exact elaborates slowly
theorem forall_mem_dualAnnihilator_apply_eq_zero_iff (W : Subspace K V) (v : V) :
(∀ φ : Module.Dual K V, φ ∈ W.dualAnnihilator → φ v = 0) ↔ v ∈ W := by
rw [← SetLike.ext_iff.mp dualAnnihilator_dualCoannihilator_eq v, mem_dualCoannihilator]
#align subspace.forall_mem_dual_annihilator_apply_eq_zero_iff Subspace.forall_mem_dualAnnihilator_apply_eq_zero_iff
theorem comap_dualAnnihilator_dualAnnihilator (W : Subspace K V) :
W.dualAnnihilator.dualAnnihilator.comap (Module.Dual.eval K V) = W := by
ext; rw [Iff.comm, ← forall_mem_dualAnnihilator_apply_eq_zero_iff]; simp
theorem map_le_dualAnnihilator_dualAnnihilator (W : Subspace K V) :
W.map (Module.Dual.eval K V) ≤ W.dualAnnihilator.dualAnnihilator :=
map_le_iff_le_comap.mpr (comap_dualAnnihilator_dualAnnihilator W).ge
/-- `Submodule.dualAnnihilator` and `Submodule.dualCoannihilator` form a Galois coinsertion. -/
def dualAnnihilatorGci (K V : Type*) [Field K] [AddCommGroup V] [Module K V] :
GaloisCoinsertion
(OrderDual.toDual ∘ (dualAnnihilator : Subspace K V → Subspace K (Module.Dual K V)))
(dualCoannihilator ∘ OrderDual.ofDual) where
choice W _ := dualCoannihilator W
gc := dualAnnihilator_gc K V
u_l_le _ := dualAnnihilator_dualCoannihilator_eq.le
choice_eq _ _ := rfl
#align subspace.dual_annihilator_gci Subspace.dualAnnihilatorGci
theorem dualAnnihilator_le_dualAnnihilator_iff {W W' : Subspace K V} :
W.dualAnnihilator ≤ W'.dualAnnihilator ↔ W' ≤ W :=
(dualAnnihilatorGci K V).l_le_l_iff
#align subspace.dual_annihilator_le_dual_annihilator_iff Subspace.dualAnnihilator_le_dualAnnihilator_iff
theorem dualAnnihilator_inj {W W' : Subspace K V} :
W.dualAnnihilator = W'.dualAnnihilator ↔ W = W' :=
⟨fun h ↦ (dualAnnihilatorGci K V).l_injective h, congr_arg _⟩
#align subspace.dual_annihilator_inj Subspace.dualAnnihilator_inj
/-- Given a subspace `W` of `V` and an element of its dual `φ`, `dualLift W φ` is
an arbitrary extension of `φ` to an element of the dual of `V`.
That is, `dualLift W φ` sends `w ∈ W` to `φ x` and `x` in a chosen complement of `W` to `0`. -/
noncomputable def dualLift (W : Subspace K V) : Module.Dual K W →ₗ[K] Module.Dual K V :=
(Classical.choose <| W.subtype.exists_leftInverse_of_injective W.ker_subtype).dualMap
#align subspace.dual_lift Subspace.dualLift
variable {W : Subspace K V}
@[simp]
theorem dualLift_of_subtype {φ : Module.Dual K W} (w : W) : W.dualLift φ (w : V) = φ w :=
congr_arg φ <| DFunLike.congr_fun
(Classical.choose_spec <| W.subtype.exists_leftInverse_of_injective W.ker_subtype) w
#align subspace.dual_lift_of_subtype Subspace.dualLift_of_subtype
theorem dualLift_of_mem {φ : Module.Dual K W} {w : V} (hw : w ∈ W) : W.dualLift φ w = φ ⟨w, hw⟩ :=
dualLift_of_subtype ⟨w, hw⟩
#align subspace.dual_lift_of_mem Subspace.dualLift_of_mem
@[simp]
theorem dualRestrict_comp_dualLift (W : Subspace K V) : W.dualRestrict.comp W.dualLift = 1 := by
ext φ x
simp
#align subspace.dual_restrict_comp_dual_lift Subspace.dualRestrict_comp_dualLift
theorem dualRestrict_leftInverse (W : Subspace K V) :
Function.LeftInverse W.dualRestrict W.dualLift := fun x =>
show W.dualRestrict.comp W.dualLift x = x by
rw [dualRestrict_comp_dualLift]
rfl
#align subspace.dual_restrict_left_inverse Subspace.dualRestrict_leftInverse
theorem dualLift_rightInverse (W : Subspace K V) :
Function.RightInverse W.dualLift W.dualRestrict :=
W.dualRestrict_leftInverse
#align subspace.dual_lift_right_inverse Subspace.dualLift_rightInverse
theorem dualRestrict_surjective : Function.Surjective W.dualRestrict :=
W.dualLift_rightInverse.surjective
#align subspace.dual_restrict_surjective Subspace.dualRestrict_surjective
theorem dualLift_injective : Function.Injective W.dualLift :=
W.dualRestrict_leftInverse.injective
#align subspace.dual_lift_injective Subspace.dualLift_injective
/-- The quotient by the `dualAnnihilator` of a subspace is isomorphic to the
dual of that subspace. -/
noncomputable def quotAnnihilatorEquiv (W : Subspace K V) :
(Module.Dual K V ⧸ W.dualAnnihilator) ≃ₗ[K] Module.Dual K W :=
(quotEquivOfEq _ _ W.dualRestrict_ker_eq_dualAnnihilator).symm.trans <|
W.dualRestrict.quotKerEquivOfSurjective dualRestrict_surjective
#align subspace.quot_annihilator_equiv Subspace.quotAnnihilatorEquiv
@[simp]
theorem quotAnnihilatorEquiv_apply (W : Subspace K V) (φ : Module.Dual K V) :
W.quotAnnihilatorEquiv (Submodule.Quotient.mk φ) = W.dualRestrict φ := by
ext
rfl
#align subspace.quot_annihilator_equiv_apply Subspace.quotAnnihilatorEquiv_apply
/-- The natural isomorphism from the dual of a subspace `W` to `W.dualLift.range`. -/
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
noncomputable def dualEquivDual (W : Subspace K V) :
Module.Dual K W ≃ₗ[K] LinearMap.range W.dualLift :=
LinearEquiv.ofInjective _ dualLift_injective
#align subspace.dual_equiv_dual Subspace.dualEquivDual
theorem dualEquivDual_def (W : Subspace K V) :
W.dualEquivDual.toLinearMap = W.dualLift.rangeRestrict :=
rfl
#align subspace.dual_equiv_dual_def Subspace.dualEquivDual_def
@[simp]
theorem dualEquivDual_apply (φ : Module.Dual K W) :
W.dualEquivDual φ = ⟨W.dualLift φ, mem_range.2 ⟨φ, rfl⟩⟩ :=
rfl
#align subspace.dual_equiv_dual_apply Subspace.dualEquivDual_apply
section
open FiniteDimensional
instance instModuleDualFiniteDimensional [FiniteDimensional K V] :
FiniteDimensional K (Module.Dual K V) := by
infer_instance
#align subspace.module.dual.finite_dimensional Subspace.instModuleDualFiniteDimensional
@[simp]
theorem dual_finrank_eq : finrank K (Module.Dual K V) = finrank K V := by
by_cases h : FiniteDimensional K V
· classical exact LinearEquiv.finrank_eq (Basis.ofVectorSpace K V).toDualEquiv.symm
rw [finrank_eq_zero_of_basis_imp_false, finrank_eq_zero_of_basis_imp_false]
· exact fun _ b ↦ h (Module.Finite.of_basis b)
· exact fun _ b ↦ h ((Module.finite_dual_iff K).mp <| Module.Finite.of_basis b)
#align subspace.dual_finrank_eq Subspace.dual_finrank_eq
variable [FiniteDimensional K V]
| Mathlib/LinearAlgebra/Dual.lean | 1,198 | 1,202 | theorem dualAnnihilator_dualAnnihilator_eq (W : Subspace K V) :
W.dualAnnihilator.dualAnnihilator = Module.mapEvalEquiv K V W := by |
have : _ = W := Subspace.dualAnnihilator_dualCoannihilator_eq
rw [dualCoannihilator, ← Module.mapEvalEquiv_symm_apply] at this
rwa [← OrderIso.symm_apply_eq]
|
/-
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.Order.Filter.Interval
import Mathlib.Order.Interval.Set.Pi
import Mathlib.Tactic.TFAE
import Mathlib.Tactic.NormNum
import Mathlib.Topology.Order.LeftRight
import Mathlib.Topology.Order.OrderClosed
#align_import topology.order.basic from "leanprover-community/mathlib"@"3efd324a3a31eaa40c9d5bfc669c4fafee5f9423"
/-!
# Theory of topology on ordered spaces
## Main definitions
The order topology on an ordered space is the topology generated by all open intervals (or
equivalently by those of the form `(-∞, a)` and `(b, +∞)`). We define it as `Preorder.topology α`.
However, we do *not* register it as an instance (as many existing ordered types already have
topologies, which would be equal but not definitionally equal to `Preorder.topology α`). Instead,
we introduce a class `OrderTopology α` (which is a `Prop`, also known as a mixin) saying that on
the type `α` having already a topological space structure and a preorder structure, the topological
structure is equal to the order topology.
We prove many basic properties of such topologies.
## Main statements
This file contains the proofs of the following facts. For exact requirements
(`OrderClosedTopology` vs `OrderTopology`, `Preorder` vs `PartialOrder` vs `LinearOrder` etc)
see their statements.
* `exists_Ioc_subset_of_mem_nhds`, `exists_Ico_subset_of_mem_nhds` : if `x < y`, then any
neighborhood of `x` includes an interval `[x, z)` for some `z ∈ (x, y]`, and any neighborhood
of `y` includes an interval `(z, y]` for some `z ∈ [x, y)`.
* `tendsto_of_tendsto_of_tendsto_of_le_of_le` : theorem known as squeeze theorem,
sandwich theorem, theorem of Carabinieri, and two policemen (and a drunk) theorem; if `g` and `h`
both converge to `a`, and eventually `g x ≤ f x ≤ h x`, then `f` converges to `a`.
## Implementation notes
We do _not_ register the order topology as an instance on a preorder (or even on a linear order).
Indeed, on many such spaces, a topology has already been constructed in a different way (think
of the discrete spaces `ℕ` or `ℤ`, or `ℝ` that could inherit a topology as the completion of `ℚ`),
and is in general not defeq to the one generated by the intervals. We make it available as a
definition `Preorder.topology α` though, that can be registered as an instance when necessary, or
for specific types.
-/
open Set Filter TopologicalSpace Topology Function
open OrderDual (toDual ofDual)
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
-- Porting note (#11215): TODO: define `Preorder.topology` before `OrderTopology` and reuse the def
/-- The order topology on an ordered type is the topology generated by open intervals. We register
it on a preorder, but it is mostly interesting in linear orders, where it is also order-closed.
We define it as a mixin. If you want to introduce the order topology on a preorder, use
`Preorder.topology`. -/
class OrderTopology (α : Type*) [t : TopologicalSpace α] [Preorder α] : Prop where
/-- The topology is generated by open intervals `Set.Ioi _` and `Set.Iio _`. -/
topology_eq_generate_intervals : t = generateFrom { s | ∃ a, s = Ioi a ∨ s = Iio a }
#align order_topology OrderTopology
/-- (Order) topology on a partial order `α` generated by the subbase of open intervals
`(a, ∞) = { x ∣ a < x }, (-∞ , b) = {x ∣ x < b}` for all `a, b` in `α`. We do not register it as an
instance as many ordered sets are already endowed with the same topology, most often in a non-defeq
way though. Register as a local instance when necessary. -/
def Preorder.topology (α : Type*) [Preorder α] : TopologicalSpace α :=
generateFrom { s : Set α | ∃ a : α, s = { b : α | a < b } ∨ s = { b : α | b < a } }
#align preorder.topology Preorder.topology
section OrderTopology
section Preorder
variable [TopologicalSpace α] [Preorder α] [t : OrderTopology α]
instance : OrderTopology αᵒᵈ :=
⟨by
convert OrderTopology.topology_eq_generate_intervals (α := α) using 6
apply or_comm⟩
theorem isOpen_iff_generate_intervals {s : Set α} :
IsOpen s ↔ GenerateOpen { s | ∃ a, s = Ioi a ∨ s = Iio a } s := by
rw [t.topology_eq_generate_intervals]; rfl
#align is_open_iff_generate_intervals isOpen_iff_generate_intervals
theorem isOpen_lt' (a : α) : IsOpen { b : α | a < b } :=
isOpen_iff_generate_intervals.2 <| .basic _ ⟨a, .inl rfl⟩
#align is_open_lt' isOpen_lt'
theorem isOpen_gt' (a : α) : IsOpen { b : α | b < a } :=
isOpen_iff_generate_intervals.2 <| .basic _ ⟨a, .inr rfl⟩
#align is_open_gt' isOpen_gt'
theorem lt_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 b, a < x :=
(isOpen_lt' _).mem_nhds h
#align lt_mem_nhds lt_mem_nhds
theorem le_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 b, a ≤ x :=
(lt_mem_nhds h).mono fun _ => le_of_lt
#align le_mem_nhds le_mem_nhds
theorem gt_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 a, x < b :=
(isOpen_gt' _).mem_nhds h
#align gt_mem_nhds gt_mem_nhds
theorem ge_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 a, x ≤ b :=
(gt_mem_nhds h).mono fun _ => le_of_lt
#align ge_mem_nhds ge_mem_nhds
theorem nhds_eq_order (a : α) : 𝓝 a = (⨅ b ∈ Iio a, 𝓟 (Ioi b)) ⊓ ⨅ b ∈ Ioi a, 𝓟 (Iio b) := by
rw [t.topology_eq_generate_intervals, nhds_generateFrom]
simp_rw [mem_setOf_eq, @and_comm (a ∈ _), exists_or, or_and_right, iInf_or, iInf_and, iInf_exists,
iInf_inf_eq, iInf_comm (ι := Set α), iInf_iInf_eq_left, mem_Ioi, mem_Iio]
#align nhds_eq_order nhds_eq_order
theorem tendsto_order {f : β → α} {a : α} {x : Filter β} :
Tendsto f x (𝓝 a) ↔ (∀ a' < a, ∀ᶠ b in x, a' < f b) ∧ ∀ a' > a, ∀ᶠ b in x, f b < a' := by
simp only [nhds_eq_order a, tendsto_inf, tendsto_iInf, tendsto_principal]; rfl
#align tendsto_order tendsto_order
instance tendstoIccClassNhds (a : α) : TendstoIxxClass Icc (𝓝 a) (𝓝 a) := by
simp only [nhds_eq_order, iInf_subtype']
refine
((hasBasis_iInf_principal_finite _).inf (hasBasis_iInf_principal_finite _)).tendstoIxxClass
fun s _ => ?_
refine ((ordConnected_biInter ?_).inter (ordConnected_biInter ?_)).out <;> intro _ _
exacts [ordConnected_Ioi, ordConnected_Iio]
#align tendsto_Icc_class_nhds tendstoIccClassNhds
instance tendstoIcoClassNhds (a : α) : TendstoIxxClass Ico (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ico_subset_Icc_self
#align tendsto_Ico_class_nhds tendstoIcoClassNhds
instance tendstoIocClassNhds (a : α) : TendstoIxxClass Ioc (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ioc_subset_Icc_self
#align tendsto_Ioc_class_nhds tendstoIocClassNhds
instance tendstoIooClassNhds (a : α) : TendstoIxxClass Ioo (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ioo_subset_Icc_self
#align tendsto_Ioo_class_nhds tendstoIooClassNhds
/-- **Squeeze theorem** (also known as **sandwich theorem**). This version assumes that inequalities
hold eventually for the filter. -/
theorem tendsto_of_tendsto_of_tendsto_of_le_of_le' {f g h : β → α} {b : Filter β} {a : α}
(hg : Tendsto g b (𝓝 a)) (hh : Tendsto h b (𝓝 a)) (hgf : ∀ᶠ b in b, g b ≤ f b)
(hfh : ∀ᶠ b in b, f b ≤ h b) : Tendsto f b (𝓝 a) :=
(hg.Icc hh).of_smallSets <| hgf.and hfh
#align tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_of_tendsto_of_tendsto_of_le_of_le'
/-- **Squeeze theorem** (also known as **sandwich theorem**). This version assumes that inequalities
hold everywhere. -/
theorem tendsto_of_tendsto_of_tendsto_of_le_of_le {f g h : β → α} {b : Filter β} {a : α}
(hg : Tendsto g b (𝓝 a)) (hh : Tendsto h b (𝓝 a)) (hgf : g ≤ f) (hfh : f ≤ h) :
Tendsto f b (𝓝 a) :=
tendsto_of_tendsto_of_tendsto_of_le_of_le' hg hh (eventually_of_forall hgf)
(eventually_of_forall hfh)
#align tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_of_tendsto_of_tendsto_of_le_of_le
theorem nhds_order_unbounded {a : α} (hu : ∃ u, a < u) (hl : ∃ l, l < a) :
𝓝 a = ⨅ (l) (_ : l < a) (u) (_ : a < u), 𝓟 (Ioo l u) := by
simp only [nhds_eq_order, ← inf_biInf, ← biInf_inf, *, ← inf_principal, ← Ioi_inter_Iio]; rfl
#align nhds_order_unbounded nhds_order_unbounded
theorem tendsto_order_unbounded {f : β → α} {a : α} {x : Filter β} (hu : ∃ u, a < u)
(hl : ∃ l, l < a) (h : ∀ l u, l < a → a < u → ∀ᶠ b in x, l < f b ∧ f b < u) :
Tendsto f x (𝓝 a) := by
simp only [nhds_order_unbounded hu hl, tendsto_iInf, tendsto_principal]
exact fun l hl u => h l u hl
#align tendsto_order_unbounded tendsto_order_unbounded
end Preorder
instance tendstoIxxNhdsWithin {α : Type*} [TopologicalSpace α] (a : α) {s t : Set α}
{Ixx} [TendstoIxxClass Ixx (𝓝 a) (𝓝 a)] [TendstoIxxClass Ixx (𝓟 s) (𝓟 t)] :
TendstoIxxClass Ixx (𝓝[s] a) (𝓝[t] a) :=
Filter.tendstoIxxClass_inf
#align tendsto_Ixx_nhds_within tendstoIxxNhdsWithin
instance tendstoIccClassNhdsPi {ι : Type*} {α : ι → Type*} [∀ i, Preorder (α i)]
[∀ i, TopologicalSpace (α i)] [∀ i, OrderTopology (α i)] (f : ∀ i, α i) :
TendstoIxxClass Icc (𝓝 f) (𝓝 f) := by
constructor
conv in (𝓝 f).smallSets => rw [nhds_pi, Filter.pi]
simp only [smallSets_iInf, smallSets_comap_eq_comap_image, tendsto_iInf, tendsto_comap_iff]
intro i
have : Tendsto (fun g : ∀ i, α i => g i) (𝓝 f) (𝓝 (f i)) := (continuous_apply i).tendsto f
refine (this.comp tendsto_fst).Icc (this.comp tendsto_snd) |>.smallSets_mono ?_
filter_upwards [] using fun ⟨f, g⟩ ↦ image_subset_iff.mpr fun p hp ↦ ⟨hp.1 i, hp.2 i⟩
#align tendsto_Icc_class_nhds_pi tendstoIccClassNhdsPi
-- Porting note (#10756): new lemma
theorem induced_topology_le_preorder [Preorder α] [Preorder β] [TopologicalSpace β]
[OrderTopology β] {f : α → β} (hf : ∀ {x y}, f x < f y ↔ x < y) :
induced f ‹TopologicalSpace β› ≤ Preorder.topology α := by
let _ := Preorder.topology α; have : OrderTopology α := ⟨rfl⟩
refine le_of_nhds_le_nhds fun x => ?_
simp only [nhds_eq_order, nhds_induced, comap_inf, comap_iInf, comap_principal, Ioi, Iio, ← hf]
refine inf_le_inf (le_iInf₂ fun a ha => ?_) (le_iInf₂ fun a ha => ?_)
exacts [iInf₂_le (f a) ha, iInf₂_le (f a) ha]
-- Porting note (#10756): new lemma
theorem induced_topology_eq_preorder [Preorder α] [Preorder β] [TopologicalSpace β]
[OrderTopology β] {f : α → β} (hf : ∀ {x y}, f x < f y ↔ x < y)
(H₁ : ∀ {a b x}, b < f a → ¬(b < f x) → ∃ y, y < a ∧ b ≤ f y)
(H₂ : ∀ {a b x}, f a < b → ¬(f x < b) → ∃ y, a < y ∧ f y ≤ b) :
induced f ‹TopologicalSpace β› = Preorder.topology α := by
let _ := Preorder.topology α; have : OrderTopology α := ⟨rfl⟩
refine le_antisymm (induced_topology_le_preorder hf) ?_
refine le_of_nhds_le_nhds fun a => ?_
simp only [nhds_eq_order, nhds_induced, comap_inf, comap_iInf, comap_principal]
refine inf_le_inf (le_iInf₂ fun b hb => ?_) (le_iInf₂ fun b hb => ?_)
· rcases em (∃ x, ¬(b < f x)) with (⟨x, hx⟩ | hb)
· rcases H₁ hb hx with ⟨y, hya, hyb⟩
exact iInf₂_le_of_le y hya (principal_mono.2 fun z hz => hyb.trans_lt (hf.2 hz))
· push_neg at hb
exact le_principal_iff.2 (univ_mem' hb)
· rcases em (∃ x, ¬(f x < b)) with (⟨x, hx⟩ | hb)
· rcases H₂ hb hx with ⟨y, hya, hyb⟩
exact iInf₂_le_of_le y hya (principal_mono.2 fun z hz => (hf.2 hz).trans_le hyb)
· push_neg at hb
exact le_principal_iff.2 (univ_mem' hb)
theorem induced_orderTopology' {α : Type u} {β : Type v} [Preorder α] [ta : TopologicalSpace β]
[Preorder β] [OrderTopology β] (f : α → β) (hf : ∀ {x y}, f x < f y ↔ x < y)
(H₁ : ∀ {a x}, x < f a → ∃ b < a, x ≤ f b) (H₂ : ∀ {a x}, f a < x → ∃ b > a, f b ≤ x) :
@OrderTopology _ (induced f ta) _ :=
let _ := induced f ta
⟨induced_topology_eq_preorder hf (fun h _ => H₁ h) (fun h _ => H₂ h)⟩
#align induced_order_topology' induced_orderTopology'
theorem induced_orderTopology {α : Type u} {β : Type v} [Preorder α] [ta : TopologicalSpace β]
[Preorder β] [OrderTopology β] (f : α → β) (hf : ∀ {x y}, f x < f y ↔ x < y)
(H : ∀ {x y}, x < y → ∃ a, x < f a ∧ f a < y) : @OrderTopology _ (induced f ta) _ :=
induced_orderTopology' f (hf)
(fun xa => let ⟨b, xb, ba⟩ := H xa; ⟨b, hf.1 ba, le_of_lt xb⟩)
fun ax => let ⟨b, ab, bx⟩ := H ax; ⟨b, hf.1 ab, le_of_lt bx⟩
#align induced_order_topology induced_orderTopology
/-- The topology induced by a strictly monotone function with order-connected range is the preorder
topology. -/
nonrec theorem StrictMono.induced_topology_eq_preorder {α β : Type*} [LinearOrder α]
[LinearOrder β] [t : TopologicalSpace β] [OrderTopology β] {f : α → β}
(hf : StrictMono f) (hc : OrdConnected (range f)) : t.induced f = Preorder.topology α := by
refine induced_topology_eq_preorder hf.lt_iff_lt (fun h₁ h₂ => ?_) fun h₁ h₂ => ?_
· rcases hc.out (mem_range_self _) (mem_range_self _) ⟨not_lt.1 h₂, h₁.le⟩ with ⟨y, rfl⟩
exact ⟨y, hf.lt_iff_lt.1 h₁, le_rfl⟩
· rcases hc.out (mem_range_self _) (mem_range_self _) ⟨h₁.le, not_lt.1 h₂⟩ with ⟨y, rfl⟩
exact ⟨y, hf.lt_iff_lt.1 h₁, le_rfl⟩
/-- A strictly monotone function between linear orders with order topology is a topological
embedding provided that the range of `f` is order-connected. -/
theorem StrictMono.embedding_of_ordConnected {α β : Type*} [LinearOrder α] [LinearOrder β]
[TopologicalSpace α] [h : OrderTopology α] [TopologicalSpace β] [OrderTopology β] {f : α → β}
(hf : StrictMono f) (hc : OrdConnected (range f)) : Embedding f :=
⟨⟨h.1.trans <| Eq.symm <| hf.induced_topology_eq_preorder hc⟩, hf.injective⟩
/-- On a `Set.OrdConnected` subset of a linear order, the order topology for the restriction of the
order is the same as the restriction to the subset of the order topology. -/
instance orderTopology_of_ordConnected {α : Type u} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] {t : Set α} [ht : OrdConnected t] : OrderTopology t :=
⟨(Subtype.strictMono_coe t).induced_topology_eq_preorder <| by
rwa [← @Subtype.range_val _ t] at ht⟩
#align order_topology_of_ord_connected orderTopology_of_ordConnected
theorem nhdsWithin_Ici_eq'' [TopologicalSpace α] [Preorder α] [OrderTopology α] (a : α) :
𝓝[≥] a = (⨅ (u) (_ : a < u), 𝓟 (Iio u)) ⊓ 𝓟 (Ici a) := by
rw [nhdsWithin, nhds_eq_order]
refine le_antisymm (inf_le_inf_right _ inf_le_right) (le_inf (le_inf ?_ inf_le_left) inf_le_right)
exact inf_le_right.trans (le_iInf₂ fun l hl => principal_mono.2 <| Ici_subset_Ioi.2 hl)
#align nhds_within_Ici_eq'' nhdsWithin_Ici_eq''
theorem nhdsWithin_Iic_eq'' [TopologicalSpace α] [Preorder α] [OrderTopology α] (a : α) :
𝓝[≤] a = (⨅ l < a, 𝓟 (Ioi l)) ⊓ 𝓟 (Iic a) :=
nhdsWithin_Ici_eq'' (toDual a)
#align nhds_within_Iic_eq'' nhdsWithin_Iic_eq''
theorem nhdsWithin_Ici_eq' [TopologicalSpace α] [Preorder α] [OrderTopology α] {a : α}
(ha : ∃ u, a < u) : 𝓝[≥] a = ⨅ (u) (_ : a < u), 𝓟 (Ico a u) := by
simp only [nhdsWithin_Ici_eq'', biInf_inf ha, inf_principal, Iio_inter_Ici]
#align nhds_within_Ici_eq' nhdsWithin_Ici_eq'
theorem nhdsWithin_Iic_eq' [TopologicalSpace α] [Preorder α] [OrderTopology α] {a : α}
(ha : ∃ l, l < a) : 𝓝[≤] a = ⨅ l < a, 𝓟 (Ioc l a) := by
simp only [nhdsWithin_Iic_eq'', biInf_inf ha, inf_principal, Ioi_inter_Iic]
#align nhds_within_Iic_eq' nhdsWithin_Iic_eq'
theorem nhdsWithin_Ici_basis' [TopologicalSpace α] [LinearOrder α] [OrderTopology α] {a : α}
(ha : ∃ u, a < u) : (𝓝[≥] a).HasBasis (fun u => a < u) fun u => Ico a u :=
(nhdsWithin_Ici_eq' ha).symm ▸
hasBasis_biInf_principal
(fun b hb c hc => ⟨min b c, lt_min hb hc, Ico_subset_Ico_right (min_le_left _ _),
Ico_subset_Ico_right (min_le_right _ _)⟩)
ha
#align nhds_within_Ici_basis' nhdsWithin_Ici_basis'
theorem nhdsWithin_Iic_basis' [TopologicalSpace α] [LinearOrder α] [OrderTopology α] {a : α}
(ha : ∃ l, l < a) : (𝓝[≤] a).HasBasis (fun l => l < a) fun l => Ioc l a := by
convert nhdsWithin_Ici_basis' (α := αᵒᵈ) ha using 2
exact dual_Ico.symm
#align nhds_within_Iic_basis' nhdsWithin_Iic_basis'
theorem nhdsWithin_Ici_basis [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [NoMaxOrder α]
(a : α) : (𝓝[≥] a).HasBasis (fun u => a < u) fun u => Ico a u :=
nhdsWithin_Ici_basis' (exists_gt a)
#align nhds_within_Ici_basis nhdsWithin_Ici_basis
theorem nhdsWithin_Iic_basis [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [NoMinOrder α]
(a : α) : (𝓝[≤] a).HasBasis (fun l => l < a) fun l => Ioc l a :=
nhdsWithin_Iic_basis' (exists_lt a)
#align nhds_within_Iic_basis nhdsWithin_Iic_basis
theorem nhds_top_order [TopologicalSpace α] [Preorder α] [OrderTop α] [OrderTopology α] :
𝓝 (⊤ : α) = ⨅ (l) (h₂ : l < ⊤), 𝓟 (Ioi l) := by simp [nhds_eq_order (⊤ : α)]
#align nhds_top_order nhds_top_order
theorem nhds_bot_order [TopologicalSpace α] [Preorder α] [OrderBot α] [OrderTopology α] :
𝓝 (⊥ : α) = ⨅ (l) (h₂ : ⊥ < l), 𝓟 (Iio l) := by simp [nhds_eq_order (⊥ : α)]
#align nhds_bot_order nhds_bot_order
| Mathlib/Topology/Order/Basic.lean | 330 | 333 | theorem nhds_top_basis [TopologicalSpace α] [LinearOrder α] [OrderTop α] [OrderTopology α]
[Nontrivial α] : (𝓝 ⊤).HasBasis (fun a : α => a < ⊤) fun a : α => Ioi a := by |
have : ∃ x : α, x < ⊤ := (exists_ne ⊤).imp fun x hx => hx.lt_top
simpa only [Iic_top, nhdsWithin_univ, Ioc_top] using nhdsWithin_Iic_basis' this
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jan-David Salchow, Sébastien Gouëzel, Jean Lo, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Topology.Algebra.Ring.Basic
import Mathlib.Topology.Algebra.MulAction
import Mathlib.Topology.Algebra.UniformGroup
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Topology.UniformSpace.UniformEmbedding
import Mathlib.Algebra.Algebra.Defs
import Mathlib.LinearAlgebra.Projection
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Finsupp
#align_import topology.algebra.module.basic from "leanprover-community/mathlib"@"6285167a053ad0990fc88e56c48ccd9fae6550eb"
/-!
# Theory of topological modules and continuous linear maps.
We use the class `ContinuousSMul` for topological (semi) modules and topological vector spaces.
In this file we define continuous (semi-)linear maps, as semilinear maps between topological
modules which are continuous. The set of continuous semilinear maps between the topological
`R₁`-module `M` and `R₂`-module `M₂` with respect to the `RingHom` `σ` is denoted by `M →SL[σ] M₂`.
Plain linear maps are denoted by `M →L[R] M₂` and star-linear maps by `M →L⋆[R] M₂`.
The corresponding notation for equivalences is `M ≃SL[σ] M₂`, `M ≃L[R] M₂` and `M ≃L⋆[R] M₂`.
-/
open LinearMap (ker range)
open Topology Filter Pointwise
universe u v w u'
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [Module R M]
theorem ContinuousSMul.of_nhds_zero [TopologicalRing R] [TopologicalAddGroup M]
(hmul : Tendsto (fun p : R × M => p.1 • p.2) (𝓝 0 ×ˢ 𝓝 0) (𝓝 0))
(hmulleft : ∀ m : M, Tendsto (fun a : R => a • m) (𝓝 0) (𝓝 0))
(hmulright : ∀ a : R, Tendsto (fun m : M => a • m) (𝓝 0) (𝓝 0)) : ContinuousSMul R M where
continuous_smul := by
refine continuous_of_continuousAt_zero₂ (AddMonoidHom.smul : R →+ M →+ M) ?_ ?_ ?_ <;>
simpa [ContinuousAt, nhds_prod_eq]
#align has_continuous_smul.of_nhds_zero ContinuousSMul.of_nhds_zero
end
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [ContinuousAdd M] [Module R M] [ContinuousSMul R M]
/-- If `M` is a topological module over `R` and `0` is a limit of invertible elements of `R`, then
`⊤` is the only submodule of `M` with a nonempty interior.
This is the case, e.g., if `R` is a nontrivially normed field. -/
theorem Submodule.eq_top_of_nonempty_interior' [NeBot (𝓝[{ x : R | IsUnit x }] 0)]
(s : Submodule R M) (hs : (interior (s : Set M)).Nonempty) : s = ⊤ := by
rcases hs with ⟨y, hy⟩
refine Submodule.eq_top_iff'.2 fun x => ?_
rw [mem_interior_iff_mem_nhds] at hy
have : Tendsto (fun c : R => y + c • x) (𝓝[{ x : R | IsUnit x }] 0) (𝓝 (y + (0 : R) • x)) :=
tendsto_const_nhds.add ((tendsto_nhdsWithin_of_tendsto_nhds tendsto_id).smul tendsto_const_nhds)
rw [zero_smul, add_zero] at this
obtain ⟨_, hu : y + _ • _ ∈ s, u, rfl⟩ :=
nonempty_of_mem (inter_mem (Filter.mem_map.1 (this hy)) self_mem_nhdsWithin)
have hy' : y ∈ ↑s := mem_of_mem_nhds hy
rwa [s.add_mem_iff_right hy', ← Units.smul_def, s.smul_mem_iff' u] at hu
#align submodule.eq_top_of_nonempty_interior' Submodule.eq_top_of_nonempty_interior'
variable (R M)
/-- Let `R` be a topological ring such that zero is not an isolated point (e.g., a nontrivially
normed field, see `NormedField.punctured_nhds_neBot`). Let `M` be a nontrivial module over `R`
such that `c • x = 0` implies `c = 0 ∨ x = 0`. Then `M` has no isolated points. We formulate this
using `NeBot (𝓝[≠] x)`.
This lemma is not an instance because Lean would need to find `[ContinuousSMul ?m_1 M]` with
unknown `?m_1`. We register this as an instance for `R = ℝ` in `Real.punctured_nhds_module_neBot`.
One can also use `haveI := Module.punctured_nhds_neBot R M` in a proof.
-/
theorem Module.punctured_nhds_neBot [Nontrivial M] [NeBot (𝓝[≠] (0 : R))] [NoZeroSMulDivisors R M]
(x : M) : NeBot (𝓝[≠] x) := by
rcases exists_ne (0 : M) with ⟨y, hy⟩
suffices Tendsto (fun c : R => x + c • y) (𝓝[≠] 0) (𝓝[≠] x) from this.neBot
refine Tendsto.inf ?_ (tendsto_principal_principal.2 <| ?_)
· convert tendsto_const_nhds.add ((@tendsto_id R _).smul_const y)
rw [zero_smul, add_zero]
· intro c hc
simpa [hy] using hc
#align module.punctured_nhds_ne_bot Module.punctured_nhds_neBot
end
section LatticeOps
variable {ι R M₁ M₂ : Type*} [Semiring R] [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁]
[Module R M₂] [u : TopologicalSpace R] {t : TopologicalSpace M₂} [ContinuousSMul R M₂]
(f : M₁ →ₗ[R] M₂)
theorem continuousSMul_induced : @ContinuousSMul R M₁ _ u (t.induced f) :=
let _ : TopologicalSpace M₁ := t.induced f
Inducing.continuousSMul ⟨rfl⟩ continuous_id (map_smul f _ _)
#align has_continuous_smul_induced continuousSMul_induced
end LatticeOps
/-- The span of a separable subset with respect to a separable scalar ring is again separable. -/
lemma TopologicalSpace.IsSeparable.span {R M : Type*} [AddCommMonoid M] [Semiring R] [Module R M]
[TopologicalSpace M] [TopologicalSpace R] [SeparableSpace R]
[ContinuousAdd M] [ContinuousSMul R M] {s : Set M} (hs : IsSeparable s) :
IsSeparable (Submodule.span R s : Set M) := by
rw [span_eq_iUnion_nat]
refine .iUnion fun n ↦ .image ?_ ?_
· have : IsSeparable {f : Fin n → R × M | ∀ (i : Fin n), f i ∈ Set.univ ×ˢ s} := by
apply isSeparable_pi (fun i ↦ .prod (.of_separableSpace Set.univ) hs)
rwa [Set.univ_prod] at this
· apply continuous_finset_sum _ (fun i _ ↦ ?_)
exact (continuous_fst.comp (continuous_apply i)).smul (continuous_snd.comp (continuous_apply i))
namespace Submodule
variable {α β : Type*} [TopologicalSpace β]
#align submodule.has_continuous_smul SMulMemClass.continuousSMul
instance topologicalAddGroup [Ring α] [AddCommGroup β] [Module α β] [TopologicalAddGroup β]
(S : Submodule α β) : TopologicalAddGroup S :=
inferInstanceAs (TopologicalAddGroup S.toAddSubgroup)
#align submodule.topological_add_group Submodule.topologicalAddGroup
end Submodule
section closure
variable {R R' : Type u} {M M' : Type v} [Semiring R] [Ring R']
[TopologicalSpace M] [AddCommMonoid M] [TopologicalSpace M'] [AddCommGroup M'] [Module R M]
[ContinuousConstSMul R M] [Module R' M'] [ContinuousConstSMul R' M']
theorem Submodule.mapsTo_smul_closure (s : Submodule R M) (c : R) :
Set.MapsTo (c • ·) (closure s : Set M) (closure s) :=
have : Set.MapsTo (c • ·) (s : Set M) s := fun _ h ↦ s.smul_mem c h
this.closure (continuous_const_smul c)
theorem Submodule.smul_closure_subset (s : Submodule R M) (c : R) :
c • closure (s : Set M) ⊆ closure (s : Set M) :=
(s.mapsTo_smul_closure c).image_subset
variable [ContinuousAdd M]
/-- The (topological-space) closure of a submodule of a topological `R`-module `M` is itself
a submodule. -/
def Submodule.topologicalClosure (s : Submodule R M) : Submodule R M :=
{ s.toAddSubmonoid.topologicalClosure with
smul_mem' := s.mapsTo_smul_closure }
#align submodule.topological_closure Submodule.topologicalClosure
@[simp]
theorem Submodule.topologicalClosure_coe (s : Submodule R M) :
(s.topologicalClosure : Set M) = closure (s : Set M) :=
rfl
#align submodule.topological_closure_coe Submodule.topologicalClosure_coe
theorem Submodule.le_topologicalClosure (s : Submodule R M) : s ≤ s.topologicalClosure :=
subset_closure
#align submodule.le_topological_closure Submodule.le_topologicalClosure
theorem Submodule.closure_subset_topologicalClosure_span (s : Set M) :
closure s ⊆ (span R s).topologicalClosure := by
rw [Submodule.topologicalClosure_coe]
exact closure_mono subset_span
theorem Submodule.isClosed_topologicalClosure (s : Submodule R M) :
IsClosed (s.topologicalClosure : Set M) := isClosed_closure
#align submodule.is_closed_topological_closure Submodule.isClosed_topologicalClosure
theorem Submodule.topologicalClosure_minimal (s : Submodule R M) {t : Submodule R M} (h : s ≤ t)
(ht : IsClosed (t : Set M)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
#align submodule.topological_closure_minimal Submodule.topologicalClosure_minimal
theorem Submodule.topologicalClosure_mono {s : Submodule R M} {t : Submodule R M} (h : s ≤ t) :
s.topologicalClosure ≤ t.topologicalClosure :=
closure_mono h
#align submodule.topological_closure_mono Submodule.topologicalClosure_mono
/-- The topological closure of a closed submodule `s` is equal to `s`. -/
theorem IsClosed.submodule_topologicalClosure_eq {s : Submodule R M} (hs : IsClosed (s : Set M)) :
s.topologicalClosure = s :=
SetLike.ext' hs.closure_eq
#align is_closed.submodule_topological_closure_eq IsClosed.submodule_topologicalClosure_eq
/-- A subspace is dense iff its topological closure is the entire space. -/
theorem Submodule.dense_iff_topologicalClosure_eq_top {s : Submodule R M} :
Dense (s : Set M) ↔ s.topologicalClosure = ⊤ := by
rw [← SetLike.coe_set_eq, dense_iff_closure_eq]
simp
#align submodule.dense_iff_topological_closure_eq_top Submodule.dense_iff_topologicalClosure_eq_top
instance Submodule.topologicalClosure.completeSpace {M' : Type*} [AddCommMonoid M'] [Module R M']
[UniformSpace M'] [ContinuousAdd M'] [ContinuousConstSMul R M'] [CompleteSpace M']
(U : Submodule R M') : CompleteSpace U.topologicalClosure :=
isClosed_closure.completeSpace_coe
#align submodule.topological_closure.complete_space Submodule.topologicalClosure.completeSpace
/-- A maximal proper subspace of a topological module (i.e a `Submodule` satisfying `IsCoatom`)
is either closed or dense. -/
theorem Submodule.isClosed_or_dense_of_isCoatom (s : Submodule R M) (hs : IsCoatom s) :
IsClosed (s : Set M) ∨ Dense (s : Set M) := by
refine (hs.le_iff.mp s.le_topologicalClosure).symm.imp ?_ dense_iff_topologicalClosure_eq_top.mpr
exact fun h ↦ h ▸ isClosed_closure
#align submodule.is_closed_or_dense_of_is_coatom Submodule.isClosed_or_dense_of_isCoatom
end closure
section Pi
theorem LinearMap.continuous_on_pi {ι : Type*} {R : Type*} {M : Type*} [Finite ι] [Semiring R]
[TopologicalSpace R] [AddCommMonoid M] [Module R M] [TopologicalSpace M] [ContinuousAdd M]
[ContinuousSMul R M] (f : (ι → R) →ₗ[R] M) : Continuous f := by
cases nonempty_fintype ι
classical
-- for the proof, write `f` in the standard basis, and use that each coordinate is a continuous
-- function.
have : (f : (ι → R) → M) = fun x => ∑ i : ι, x i • f fun j => if i = j then 1 else 0 := by
ext x
exact f.pi_apply_eq_sum_univ x
rw [this]
refine continuous_finset_sum _ fun i _ => ?_
exact (continuous_apply i).smul continuous_const
#align linear_map.continuous_on_pi LinearMap.continuous_on_pi
end Pi
/-- Continuous linear maps between modules. We only put the type classes that are necessary for the
definition, although in applications `M` and `M₂` will be topological modules over the topological
ring `R`. -/
structure ContinuousLinearMap {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
(M : Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂]
[AddCommMonoid M₂] [Module R M] [Module S M₂] extends M →ₛₗ[σ] M₂ where
cont : Continuous toFun := by continuity
#align continuous_linear_map ContinuousLinearMap
attribute [inherit_doc ContinuousLinearMap] ContinuousLinearMap.cont
@[inherit_doc]
notation:25 M " →SL[" σ "] " M₂ => ContinuousLinearMap σ M M₂
@[inherit_doc]
notation:25 M " →L[" R "] " M₂ => ContinuousLinearMap (RingHom.id R) M M₂
@[inherit_doc]
notation:25 M " →L⋆[" R "] " M₂ => ContinuousLinearMap (starRingEnd R) M M₂
/-- `ContinuousSemilinearMapClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear maps `M → M₂`. See also `ContinuousLinearMapClass F R M M₂` for the case where
`σ` is the identity map on `R`. A map `f` between an `R`-module and an `S`-module over a ring
homomorphism `σ : R →+* S` is semilinear if it satisfies the two properties `f (x + y) = f x + f y`
and `f (c • x) = (σ c) • f x`. -/
class ContinuousSemilinearMapClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam <| R →+* S) (M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [FunLike F M M₂]
extends SemilinearMapClass F σ M M₂, ContinuousMapClass F M M₂ : Prop
#align continuous_semilinear_map_class ContinuousSemilinearMapClass
-- `σ`, `R` and `S` become metavariables, but they are all outparams so it's OK
-- Porting note(#12094): removed nolint; dangerous_instance linter not ported yet
-- attribute [nolint dangerous_instance] ContinuousSemilinearMapClass.toContinuousMapClass
/-- `ContinuousLinearMapClass F R M M₂` asserts `F` is a type of bundled continuous
`R`-linear maps `M → M₂`. This is an abbreviation for
`ContinuousSemilinearMapClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearMapClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [FunLike F M M₂] :=
ContinuousSemilinearMapClass F (RingHom.id R) M M₂
#align continuous_linear_map_class ContinuousLinearMapClass
/-- Continuous linear equivalences between modules. We only put the type classes that are necessary
for the definition, although in applications `M` and `M₂` will be topological modules over the
topological semiring `R`. -/
-- Porting note (#5171): linter not ported yet; was @[nolint has_nonempty_instance]
structure ContinuousLinearEquiv {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] extends M ≃ₛₗ[σ] M₂ where
continuous_toFun : Continuous toFun := by continuity
continuous_invFun : Continuous invFun := by continuity
#align continuous_linear_equiv ContinuousLinearEquiv
attribute [inherit_doc ContinuousLinearEquiv] ContinuousLinearEquiv.continuous_toFun
ContinuousLinearEquiv.continuous_invFun
@[inherit_doc]
notation:50 M " ≃SL[" σ "] " M₂ => ContinuousLinearEquiv σ M M₂
@[inherit_doc]
notation:50 M " ≃L[" R "] " M₂ => ContinuousLinearEquiv (RingHom.id R) M M₂
@[inherit_doc]
notation:50 M " ≃L⋆[" R "] " M₂ => ContinuousLinearEquiv (starRingEnd R) M M₂
/-- `ContinuousSemilinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear equivs `M → M₂`. See also `ContinuousLinearEquivClass F R M M₂` for the case
where `σ` is the identity map on `R`. A map `f` between an `R`-module and an `S`-module over a ring
homomorphism `σ : R →+* S` is semilinear if it satisfies the two properties `f (x + y) = f x + f y`
and `f (c • x) = (σ c) • f x`. -/
class ContinuousSemilinearEquivClass (F : Type*) {R : outParam Type*} {S : outParam Type*}
[Semiring R] [Semiring S] (σ : outParam <| R →+* S) {σ' : outParam <| S →+* R}
[RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : outParam Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [EquivLike F M M₂] extends SemilinearEquivClass F σ M M₂ : Prop where
map_continuous : ∀ f : F, Continuous f := by continuity
inv_continuous : ∀ f : F, Continuous (EquivLike.inv f) := by continuity
#align continuous_semilinear_equiv_class ContinuousSemilinearEquivClass
attribute [inherit_doc ContinuousSemilinearEquivClass]
ContinuousSemilinearEquivClass.map_continuous
ContinuousSemilinearEquivClass.inv_continuous
/-- `ContinuousLinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`R`-linear equivs `M → M₂`. This is an abbreviation for
`ContinuousSemilinearEquivClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearEquivClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [EquivLike F M M₂] :=
ContinuousSemilinearEquivClass F (RingHom.id R) M M₂
#align continuous_linear_equiv_class ContinuousLinearEquivClass
namespace ContinuousSemilinearEquivClass
variable (F : Type*) {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
(M : Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂]
[Module R M] [Module S M₂]
-- `σ'` becomes a metavariable, but it's OK since it's an outparam
instance (priority := 100) continuousSemilinearMapClass [EquivLike F M M₂]
[s : ContinuousSemilinearEquivClass F σ M M₂] : ContinuousSemilinearMapClass F σ M M₂ :=
{ s with }
#align continuous_semilinear_equiv_class.continuous_semilinear_map_class ContinuousSemilinearEquivClass.continuousSemilinearMapClass
end ContinuousSemilinearEquivClass
section PointwiseLimits
variable {M₁ M₂ α R S : Type*} [TopologicalSpace M₂] [T2Space M₂] [Semiring R] [Semiring S]
[AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module S M₂] [ContinuousConstSMul S M₂]
variable [ContinuousAdd M₂] {σ : R →+* S} {l : Filter α}
/-- Constructs a bundled linear map from a function and a proof that this function belongs to the
closure of the set of linear maps. -/
@[simps (config := .asFn)]
def linearMapOfMemClosureRangeCoe (f : M₁ → M₂)
(hf : f ∈ closure (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂))) : M₁ →ₛₗ[σ] M₂ :=
{ addMonoidHomOfMemClosureRangeCoe f hf with
map_smul' := (isClosed_setOf_map_smul M₁ M₂ σ).closure_subset_iff.2
(Set.range_subset_iff.2 LinearMap.map_smulₛₗ) hf }
#align linear_map_of_mem_closure_range_coe linearMapOfMemClosureRangeCoe
#align linear_map_of_mem_closure_range_coe_apply linearMapOfMemClosureRangeCoe_apply
/-- Construct a bundled linear map from a pointwise limit of linear maps -/
@[simps! (config := .asFn)]
def linearMapOfTendsto (f : M₁ → M₂) (g : α → M₁ →ₛₗ[σ] M₂) [l.NeBot]
(h : Tendsto (fun a x => g a x) l (𝓝 f)) : M₁ →ₛₗ[σ] M₂ :=
linearMapOfMemClosureRangeCoe f <|
mem_closure_of_tendsto h <| eventually_of_forall fun _ => Set.mem_range_self _
#align linear_map_of_tendsto linearMapOfTendsto
#align linear_map_of_tendsto_apply linearMapOfTendsto_apply
variable (M₁ M₂ σ)
theorem LinearMap.isClosed_range_coe : IsClosed (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂)) :=
isClosed_of_closure_subset fun f hf => ⟨linearMapOfMemClosureRangeCoe f hf, rfl⟩
#align linear_map.is_closed_range_coe LinearMap.isClosed_range_coe
end PointwiseLimits
namespace ContinuousLinearMap
section Semiring
/-!
### Properties that hold for non-necessarily commutative semirings.
-/
variable {R₁ : Type*} {R₂ : Type*} {R₃ : Type*} [Semiring R₁] [Semiring R₂] [Semiring R₃]
{σ₁₂ : R₁ →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R₁ →+* R₃} {M₁ : Type*} [TopologicalSpace M₁]
[AddCommMonoid M₁] {M'₁ : Type*} [TopologicalSpace M'₁] [AddCommMonoid M'₁] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommMonoid M₂] {M₃ : Type*} [TopologicalSpace M₃] [AddCommMonoid M₃]
{M₄ : Type*} [TopologicalSpace M₄] [AddCommMonoid M₄] [Module R₁ M₁] [Module R₁ M'₁]
[Module R₂ M₂] [Module R₃ M₃]
attribute [coe] ContinuousLinearMap.toLinearMap
/-- Coerce continuous linear maps to linear maps. -/
instance LinearMap.coe : Coe (M₁ →SL[σ₁₂] M₂) (M₁ →ₛₗ[σ₁₂] M₂) := ⟨toLinearMap⟩
#align continuous_linear_map.linear_map.has_coe ContinuousLinearMap.LinearMap.coe
#noalign continuous_linear_map.to_linear_map_eq_coe
theorem coe_injective : Function.Injective ((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂) := by
intro f g H
cases f
cases g
congr
#align continuous_linear_map.coe_injective ContinuousLinearMap.coe_injective
instance funLike : FunLike (M₁ →SL[σ₁₂] M₂) M₁ M₂ where
coe f := f.toLinearMap
coe_injective' _ _ h := coe_injective (DFunLike.coe_injective h)
instance continuousSemilinearMapClass :
ContinuousSemilinearMapClass (M₁ →SL[σ₁₂] M₂) σ₁₂ M₁ M₂ where
map_add f := map_add f.toLinearMap
map_continuous f := f.2
map_smulₛₗ f := f.toLinearMap.map_smul'
#align continuous_linear_map.continuous_semilinear_map_class ContinuousLinearMap.continuousSemilinearMapClass
-- see Note [function coercion]
/-- Coerce continuous linear maps to functions. -/
--instance toFun' : CoeFun (M₁ →SL[σ₁₂] M₂) fun _ => M₁ → M₂ := ⟨DFunLike.coe⟩
-- porting note (#10618): was `simp`, now `simp only` proves it
theorem coe_mk (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_mk ContinuousLinearMap.coe_mk
@[simp]
theorem coe_mk' (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ → M₂) = f :=
rfl
#align continuous_linear_map.coe_mk' ContinuousLinearMap.coe_mk'
@[continuity]
protected theorem continuous (f : M₁ →SL[σ₁₂] M₂) : Continuous f :=
f.2
#align continuous_linear_map.continuous ContinuousLinearMap.continuous
protected theorem uniformContinuous {E₁ E₂ : Type*} [UniformSpace E₁] [UniformSpace E₂]
[AddCommGroup E₁] [AddCommGroup E₂] [Module R₁ E₁] [Module R₂ E₂] [UniformAddGroup E₁]
[UniformAddGroup E₂] (f : E₁ →SL[σ₁₂] E₂) : UniformContinuous f :=
uniformContinuous_addMonoidHom_of_continuous f.continuous
#align continuous_linear_map.uniform_continuous ContinuousLinearMap.uniformContinuous
@[simp, norm_cast]
theorem coe_inj {f g : M₁ →SL[σ₁₂] M₂} : (f : M₁ →ₛₗ[σ₁₂] M₂) = g ↔ f = g :=
coe_injective.eq_iff
#align continuous_linear_map.coe_inj ContinuousLinearMap.coe_inj
theorem coeFn_injective : @Function.Injective (M₁ →SL[σ₁₂] M₂) (M₁ → M₂) (↑) :=
DFunLike.coe_injective
#align continuous_linear_map.coe_fn_injective ContinuousLinearMap.coeFn_injective
/-- See Note [custom simps projection]. We need to specify this projection explicitly in this case,
because it is a composition of multiple projections. -/
def Simps.apply (h : M₁ →SL[σ₁₂] M₂) : M₁ → M₂ :=
h
#align continuous_linear_map.simps.apply ContinuousLinearMap.Simps.apply
/-- See Note [custom simps projection]. -/
def Simps.coe (h : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂ :=
h
#align continuous_linear_map.simps.coe ContinuousLinearMap.Simps.coe
initialize_simps_projections ContinuousLinearMap (toLinearMap_toFun → apply, toLinearMap → coe)
@[ext]
theorem ext {f g : M₁ →SL[σ₁₂] M₂} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align continuous_linear_map.ext ContinuousLinearMap.ext
theorem ext_iff {f g : M₁ →SL[σ₁₂] M₂} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align continuous_linear_map.ext_iff ContinuousLinearMap.ext_iff
/-- Copy of a `ContinuousLinearMap` with a new `toFun` equal to the old one. Useful to fix
definitional equalities. -/
protected def copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : M₁ →SL[σ₁₂] M₂ where
toLinearMap := f.toLinearMap.copy f' h
cont := show Continuous f' from h.symm ▸ f.continuous
#align continuous_linear_map.copy ContinuousLinearMap.copy
@[simp]
theorem coe_copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : ⇑(f.copy f' h) = f' :=
rfl
#align continuous_linear_map.coe_copy ContinuousLinearMap.coe_copy
theorem copy_eq (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : f.copy f' h = f :=
DFunLike.ext' h
#align continuous_linear_map.copy_eq ContinuousLinearMap.copy_eq
-- make some straightforward lemmas available to `simp`.
protected theorem map_zero (f : M₁ →SL[σ₁₂] M₂) : f (0 : M₁) = 0 :=
map_zero f
#align continuous_linear_map.map_zero ContinuousLinearMap.map_zero
protected theorem map_add (f : M₁ →SL[σ₁₂] M₂) (x y : M₁) : f (x + y) = f x + f y :=
map_add f x y
#align continuous_linear_map.map_add ContinuousLinearMap.map_add
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smulₛₗ (f : M₁ →SL[σ₁₂] M₂) (c : R₁) (x : M₁) : f (c • x) = σ₁₂ c • f x :=
(toLinearMap _).map_smulₛₗ _ _
#align continuous_linear_map.map_smulₛₗ ContinuousLinearMap.map_smulₛₗ
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smul [Module R₁ M₂] (f : M₁ →L[R₁] M₂) (c : R₁) (x : M₁) :
f (c • x) = c • f x := by simp only [RingHom.id_apply, ContinuousLinearMap.map_smulₛₗ]
#align continuous_linear_map.map_smul ContinuousLinearMap.map_smul
@[simp]
theorem map_smul_of_tower {R S : Type*} [Semiring S] [SMul R M₁] [Module S M₁] [SMul R M₂]
[Module S M₂] [LinearMap.CompatibleSMul M₁ M₂ R S] (f : M₁ →L[S] M₂) (c : R) (x : M₁) :
f (c • x) = c • f x :=
LinearMap.CompatibleSMul.map_smul (f : M₁ →ₗ[S] M₂) c x
#align continuous_linear_map.map_smul_of_tower ContinuousLinearMap.map_smul_of_tower
@[deprecated _root_.map_sum]
protected theorem map_sum {ι : Type*} (f : M₁ →SL[σ₁₂] M₂) (s : Finset ι) (g : ι → M₁) :
f (∑ i ∈ s, g i) = ∑ i ∈ s, f (g i) :=
map_sum ..
#align continuous_linear_map.map_sum ContinuousLinearMap.map_sum
@[simp, norm_cast]
theorem coe_coe (f : M₁ →SL[σ₁₂] M₂) : ⇑(f : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_coe ContinuousLinearMap.coe_coe
@[ext]
theorem ext_ring [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} (h : f 1 = g 1) : f = g :=
coe_inj.1 <| LinearMap.ext_ring h
#align continuous_linear_map.ext_ring ContinuousLinearMap.ext_ring
theorem ext_ring_iff [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} : f = g ↔ f 1 = g 1 :=
⟨fun h => h ▸ rfl, ext_ring⟩
#align continuous_linear_map.ext_ring_iff ContinuousLinearMap.ext_ring_iff
/-- If two continuous linear maps are equal on a set `s`, then they are equal on the closure
of the `Submodule.span` of this set. -/
theorem eqOn_closure_span [T2Space M₂] {s : Set M₁} {f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) :
Set.EqOn f g (closure (Submodule.span R₁ s : Set M₁)) :=
(LinearMap.eqOn_span' h).closure f.continuous g.continuous
#align continuous_linear_map.eq_on_closure_span ContinuousLinearMap.eqOn_closure_span
/-- If the submodule generated by a set `s` is dense in the ambient module, then two continuous
linear maps equal on `s` are equal. -/
theorem ext_on [T2Space M₂] {s : Set M₁} (hs : Dense (Submodule.span R₁ s : Set M₁))
{f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) : f = g :=
ext fun x => eqOn_closure_span h (hs x)
#align continuous_linear_map.ext_on ContinuousLinearMap.ext_on
/-- Under a continuous linear map, the image of the `TopologicalClosure` of a submodule is
contained in the `TopologicalClosure` of its image. -/
theorem _root_.Submodule.topologicalClosure_map [RingHomSurjective σ₁₂] [TopologicalSpace R₁]
[TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁] [ContinuousSMul R₂ M₂]
[ContinuousAdd M₂] (f : M₁ →SL[σ₁₂] M₂) (s : Submodule R₁ M₁) :
s.topologicalClosure.map (f : M₁ →ₛₗ[σ₁₂] M₂) ≤
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure :=
image_closure_subset_closure_image f.continuous
#align submodule.topological_closure_map Submodule.topologicalClosure_map
/-- Under a dense continuous linear map, a submodule whose `TopologicalClosure` is `⊤` is sent to
another such submodule. That is, the image of a dense set under a map with dense range is dense.
-/
theorem _root_.DenseRange.topologicalClosure_map_submodule [RingHomSurjective σ₁₂]
[TopologicalSpace R₁] [TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁]
[ContinuousSMul R₂ M₂] [ContinuousAdd M₂] {f : M₁ →SL[σ₁₂] M₂} (hf' : DenseRange f)
{s : Submodule R₁ M₁} (hs : s.topologicalClosure = ⊤) :
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure = ⊤ := by
rw [SetLike.ext'_iff] at hs ⊢
simp only [Submodule.topologicalClosure_coe, Submodule.top_coe, ← dense_iff_closure_eq] at hs ⊢
exact hf'.dense_image f.continuous hs
#align dense_range.topological_closure_map_submodule DenseRange.topologicalClosure_map_submodule
section SMulMonoid
variable {S₂ T₂ : Type*} [Monoid S₂] [Monoid T₂]
variable [DistribMulAction S₂ M₂] [SMulCommClass R₂ S₂ M₂] [ContinuousConstSMul S₂ M₂]
variable [DistribMulAction T₂ M₂] [SMulCommClass R₂ T₂ M₂] [ContinuousConstSMul T₂ M₂]
instance instSMul : SMul S₂ (M₁ →SL[σ₁₂] M₂) where
smul c f := ⟨c • (f : M₁ →ₛₗ[σ₁₂] M₂), (f.2.const_smul _ : Continuous fun x => c • f x)⟩
instance mulAction : MulAction S₂ (M₁ →SL[σ₁₂] M₂) where
one_smul _f := ext fun _x => one_smul _ _
mul_smul _a _b _f := ext fun _x => mul_smul _ _ _
#align continuous_linear_map.mul_action ContinuousLinearMap.mulAction
theorem smul_apply (c : S₂) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (c • f) x = c • f x :=
rfl
#align continuous_linear_map.smul_apply ContinuousLinearMap.smul_apply
@[simp, norm_cast]
theorem coe_smul (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_smul ContinuousLinearMap.coe_smul
@[simp, norm_cast]
theorem coe_smul' (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ → M₂) :=
rfl
#align continuous_linear_map.coe_smul' ContinuousLinearMap.coe_smul'
instance isScalarTower [SMul S₂ T₂] [IsScalarTower S₂ T₂ M₂] :
IsScalarTower S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_assoc a b (f x)⟩
#align continuous_linear_map.is_scalar_tower ContinuousLinearMap.isScalarTower
instance smulCommClass [SMulCommClass S₂ T₂ M₂] : SMulCommClass S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_comm a b (f x)⟩
#align continuous_linear_map.smul_comm_class ContinuousLinearMap.smulCommClass
end SMulMonoid
/-- The continuous map that is constantly zero. -/
instance zero : Zero (M₁ →SL[σ₁₂] M₂) :=
⟨⟨0, continuous_zero⟩⟩
#align continuous_linear_map.has_zero ContinuousLinearMap.zero
instance inhabited : Inhabited (M₁ →SL[σ₁₂] M₂) :=
⟨0⟩
#align continuous_linear_map.inhabited ContinuousLinearMap.inhabited
@[simp]
theorem default_def : (default : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.default_def ContinuousLinearMap.default_def
@[simp]
theorem zero_apply (x : M₁) : (0 : M₁ →SL[σ₁₂] M₂) x = 0 :=
rfl
#align continuous_linear_map.zero_apply ContinuousLinearMap.zero_apply
@[simp, norm_cast]
theorem coe_zero : ((0 : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero ContinuousLinearMap.coe_zero
/- no simp attribute on the next line as simp does not always simplify `0 x` to `0`
when `0` is the zero function, while it does for the zero continuous linear map,
and this is the most important property we care about. -/
@[norm_cast]
theorem coe_zero' : ⇑(0 : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero' ContinuousLinearMap.coe_zero'
instance uniqueOfLeft [Subsingleton M₁] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_left ContinuousLinearMap.uniqueOfLeft
instance uniqueOfRight [Subsingleton M₂] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_right ContinuousLinearMap.uniqueOfRight
theorem exists_ne_zero {f : M₁ →SL[σ₁₂] M₂} (hf : f ≠ 0) : ∃ x, f x ≠ 0 := by
by_contra! h
exact hf (ContinuousLinearMap.ext h)
#align continuous_linear_map.exists_ne_zero ContinuousLinearMap.exists_ne_zero
section
variable (R₁ M₁)
/-- the identity map as a continuous linear map. -/
def id : M₁ →L[R₁] M₁ :=
⟨LinearMap.id, continuous_id⟩
#align continuous_linear_map.id ContinuousLinearMap.id
end
instance one : One (M₁ →L[R₁] M₁) :=
⟨id R₁ M₁⟩
#align continuous_linear_map.has_one ContinuousLinearMap.one
theorem one_def : (1 : M₁ →L[R₁] M₁) = id R₁ M₁ :=
rfl
#align continuous_linear_map.one_def ContinuousLinearMap.one_def
theorem id_apply (x : M₁) : id R₁ M₁ x = x :=
rfl
#align continuous_linear_map.id_apply ContinuousLinearMap.id_apply
@[simp, norm_cast]
theorem coe_id : (id R₁ M₁ : M₁ →ₗ[R₁] M₁) = LinearMap.id :=
rfl
#align continuous_linear_map.coe_id ContinuousLinearMap.coe_id
@[simp, norm_cast]
theorem coe_id' : ⇑(id R₁ M₁) = _root_.id :=
rfl
#align continuous_linear_map.coe_id' ContinuousLinearMap.coe_id'
@[simp, norm_cast]
theorem coe_eq_id {f : M₁ →L[R₁] M₁} : (f : M₁ →ₗ[R₁] M₁) = LinearMap.id ↔ f = id _ _ := by
rw [← coe_id, coe_inj]
#align continuous_linear_map.coe_eq_id ContinuousLinearMap.coe_eq_id
@[simp]
theorem one_apply (x : M₁) : (1 : M₁ →L[R₁] M₁) x = x :=
rfl
#align continuous_linear_map.one_apply ContinuousLinearMap.one_apply
instance [Nontrivial M₁] : Nontrivial (M₁ →L[R₁] M₁) :=
⟨0, 1, fun e ↦
have ⟨x, hx⟩ := exists_ne (0 : M₁); hx (by simpa using DFunLike.congr_fun e.symm x)⟩
section Add
variable [ContinuousAdd M₂]
instance add : Add (M₁ →SL[σ₁₂] M₂) :=
⟨fun f g => ⟨f + g, f.2.add g.2⟩⟩
#align continuous_linear_map.has_add ContinuousLinearMap.add
@[simp]
theorem add_apply (f g : M₁ →SL[σ₁₂] M₂) (x : M₁) : (f + g) x = f x + g x :=
rfl
#align continuous_linear_map.add_apply ContinuousLinearMap.add_apply
@[simp, norm_cast]
theorem coe_add (f g : M₁ →SL[σ₁₂] M₂) : (↑(f + g) : M₁ →ₛₗ[σ₁₂] M₂) = f + g :=
rfl
#align continuous_linear_map.coe_add ContinuousLinearMap.coe_add
@[norm_cast]
theorem coe_add' (f g : M₁ →SL[σ₁₂] M₂) : ⇑(f + g) = f + g :=
rfl
#align continuous_linear_map.coe_add' ContinuousLinearMap.coe_add'
instance addCommMonoid : AddCommMonoid (M₁ →SL[σ₁₂] M₂) where
zero_add := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_zero := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_comm := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_assoc := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
nsmul := (· • ·)
nsmul_zero f := by
ext
simp
nsmul_succ n f := by
ext
simp [add_smul]
#align continuous_linear_map.add_comm_monoid ContinuousLinearMap.addCommMonoid
@[simp, norm_cast]
theorem coe_sum {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
↑(∑ d ∈ t, f d) = (∑ d ∈ t, f d : M₁ →ₛₗ[σ₁₂] M₂) :=
map_sum (AddMonoidHom.mk ⟨((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂), rfl⟩ fun _ _ => rfl) _ _
#align continuous_linear_map.coe_sum ContinuousLinearMap.coe_sum
@[simp, norm_cast]
theorem coe_sum' {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
⇑(∑ d ∈ t, f d) = ∑ d ∈ t, ⇑(f d) := by simp only [← coe_coe, coe_sum, LinearMap.coeFn_sum]
#align continuous_linear_map.coe_sum' ContinuousLinearMap.coe_sum'
theorem sum_apply {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) (b : M₁) :
(∑ d ∈ t, f d) b = ∑ d ∈ t, f d b := by simp only [coe_sum', Finset.sum_apply]
#align continuous_linear_map.sum_apply ContinuousLinearMap.sum_apply
end Add
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
/-- Composition of bounded linear maps. -/
def comp (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : M₁ →SL[σ₁₃] M₃ :=
⟨(g : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂), g.2.comp f.2⟩
#align continuous_linear_map.comp ContinuousLinearMap.comp
@[inherit_doc comp]
infixr:80 " ∘L " =>
@ContinuousLinearMap.comp _ _ _ _ _ _ (RingHom.id _) (RingHom.id _) (RingHom.id _) _ _ _ _ _ _ _ _
_ _ _ _ RingHomCompTriple.ids
@[simp, norm_cast]
theorem coe_comp (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(h.comp f : M₁ →ₛₗ[σ₁₃] M₃) = (h : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_comp ContinuousLinearMap.coe_comp
@[simp, norm_cast]
theorem coe_comp' (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : ⇑(h.comp f) = h ∘ f :=
rfl
#align continuous_linear_map.coe_comp' ContinuousLinearMap.coe_comp'
theorem comp_apply (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (g.comp f) x = g (f x) :=
rfl
#align continuous_linear_map.comp_apply ContinuousLinearMap.comp_apply
@[simp]
theorem comp_id (f : M₁ →SL[σ₁₂] M₂) : f.comp (id R₁ M₁) = f :=
ext fun _x => rfl
#align continuous_linear_map.comp_id ContinuousLinearMap.comp_id
@[simp]
theorem id_comp (f : M₁ →SL[σ₁₂] M₂) : (id R₂ M₂).comp f = f :=
ext fun _x => rfl
#align continuous_linear_map.id_comp ContinuousLinearMap.id_comp
@[simp]
| Mathlib/Topology/Algebra/Module/Basic.lean | 818 | 820 | theorem comp_zero (g : M₂ →SL[σ₂₃] M₃) : g.comp (0 : M₁ →SL[σ₁₂] M₂) = 0 := by |
ext
simp
|
/-
Copyright (c) 2020 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Data.Finset.Prod
import Mathlib.Data.Sym.Basic
import Mathlib.Data.Sym.Sym2.Init
import Mathlib.Data.SetLike.Basic
#align_import data.sym.sym2 from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1"
/-!
# The symmetric square
This file defines the symmetric square, which is `α × α` modulo
swapping. This is also known as the type of unordered pairs.
More generally, the symmetric square is the second symmetric power
(see `Data.Sym.Basic`). The equivalence is `Sym2.equivSym`.
From the point of view that an unordered pair is equivalent to a
multiset of cardinality two (see `Sym2.equivMultiset`), there is a
`Mem` instance `Sym2.Mem`, which is a `Prop`-valued membership
test. Given `h : a ∈ z` for `z : Sym2 α`, then `Mem.other h` is the other
element of the pair, defined using `Classical.choice`. If `α` has
decidable equality, then `h.other'` computably gives the other element.
The universal property of `Sym2` is provided as `Sym2.lift`, which
states that functions from `Sym2 α` are equivalent to symmetric
two-argument functions from `α`.
Recall that an undirected graph (allowing self loops, but no multiple
edges) is equivalent to a symmetric relation on the vertex type `α`.
Given a symmetric relation on `α`, the corresponding edge set is
constructed by `Sym2.fromRel` which is a special case of `Sym2.lift`.
## Notation
The element `Sym2.mk (a, b)` can be written as `s(a, b)` for short.
## Tags
symmetric square, unordered pairs, symmetric powers
-/
assert_not_exists MonoidWithZero
open Finset Function Sym
universe u
variable {α β γ : Type*}
namespace Sym2
/-- This is the relation capturing the notion of pairs equivalent up to permutations. -/
@[aesop (rule_sets := [Sym2]) [safe [constructors, cases], norm]]
inductive Rel (α : Type u) : α × α → α × α → Prop
| refl (x y : α) : Rel _ (x, y) (x, y)
| swap (x y : α) : Rel _ (x, y) (y, x)
#align sym2.rel Sym2.Rel
#align sym2.rel.refl Sym2.Rel.refl
#align sym2.rel.swap Sym2.Rel.swap
attribute [refl] Rel.refl
@[symm]
theorem Rel.symm {x y : α × α} : Rel α x y → Rel α y x := by aesop (rule_sets := [Sym2])
#align sym2.rel.symm Sym2.Rel.symm
@[trans]
theorem Rel.trans {x y z : α × α} (a : Rel α x y) (b : Rel α y z) : Rel α x z := by
aesop (rule_sets := [Sym2])
#align sym2.rel.trans Sym2.Rel.trans
theorem Rel.is_equivalence : Equivalence (Rel α) :=
{ refl := fun (x, y) ↦ Rel.refl x y, symm := Rel.symm, trans := Rel.trans }
#align sym2.rel.is_equivalence Sym2.Rel.is_equivalence
/-- One can use `attribute [local instance] Sym2.Rel.setoid` to temporarily
make `Quotient` functionality work for `α × α`. -/
def Rel.setoid (α : Type u) : Setoid (α × α) :=
⟨Rel α, Rel.is_equivalence⟩
#align sym2.rel.setoid Sym2.Rel.setoid
@[simp]
theorem rel_iff' {p q : α × α} : Rel α p q ↔ p = q ∨ p = q.swap := by
aesop (rule_sets := [Sym2])
theorem rel_iff {x y z w : α} : Rel α (x, y) (z, w) ↔ x = z ∧ y = w ∨ x = w ∧ y = z := by
simp
#align sym2.rel_iff Sym2.rel_iff
end Sym2
/-- `Sym2 α` is the symmetric square of `α`, which, in other words, is the
type of unordered pairs.
It is equivalent in a natural way to multisets of cardinality 2 (see
`Sym2.equivMultiset`).
-/
abbrev Sym2 (α : Type u) := Quot (Sym2.Rel α)
#align sym2 Sym2
/-- Constructor for `Sym2`. This is the quotient map `α × α → Sym2 α`. -/
protected abbrev Sym2.mk {α : Type*} (p : α × α) : Sym2 α := Quot.mk (Sym2.Rel α) p
/-- `s(x, y)` is an unordered pair,
which is to say a pair modulo the action of the symmetric group.
It is equal to `Sym2.mk (x, y)`. -/
notation3 "s(" x ", " y ")" => Sym2.mk (x, y)
namespace Sym2
protected theorem sound {p p' : α × α} (h : Sym2.Rel α p p') : Sym2.mk p = Sym2.mk p' :=
Quot.sound h
protected theorem exact {p p' : α × α} (h : Sym2.mk p = Sym2.mk p') : Sym2.Rel α p p' :=
Quotient.exact (s := Sym2.Rel.setoid α) h
@[simp]
protected theorem eq {p p' : α × α} : Sym2.mk p = Sym2.mk p' ↔ Sym2.Rel α p p' :=
Quotient.eq' (s₁ := Sym2.Rel.setoid α)
@[elab_as_elim]
protected theorem ind {f : Sym2 α → Prop} (h : ∀ x y, f s(x, y)) : ∀ i, f i :=
Quot.ind <| Prod.rec <| h
#align sym2.ind Sym2.ind
@[elab_as_elim]
protected theorem inductionOn {f : Sym2 α → Prop} (i : Sym2 α) (hf : ∀ x y, f s(x, y)) : f i :=
i.ind hf
#align sym2.induction_on Sym2.inductionOn
@[elab_as_elim]
protected theorem inductionOn₂ {f : Sym2 α → Sym2 β → Prop} (i : Sym2 α) (j : Sym2 β)
(hf : ∀ a₁ a₂ b₁ b₂, f s(a₁, a₂) s(b₁, b₂)) : f i j :=
Quot.induction_on₂ i j <| by
intro ⟨a₁, a₂⟩ ⟨b₁, b₂⟩
exact hf _ _ _ _
#align sym2.induction_on₂ Sym2.inductionOn₂
/-- Dependent recursion principal for `Sym2`. See `Quot.rec`. -/
@[elab_as_elim]
protected def rec {motive : Sym2 α → Sort*}
(f : (p : α × α) → motive (Sym2.mk p))
(h : (p q : α × α) → (h : Sym2.Rel α p q) → Eq.ndrec (f p) (Sym2.sound h) = f q)
(z : Sym2 α) : motive z :=
Quot.rec f h z
/-- Dependent recursion principal for `Sym2` when the target is a `Subsingleton` type.
See `Quot.recOnSubsingleton`. -/
@[elab_as_elim]
protected abbrev recOnSubsingleton {motive : Sym2 α → Sort*}
[(p : α × α) → Subsingleton (motive (Sym2.mk p))]
(z : Sym2 α) (f : (p : α × α) → motive (Sym2.mk p)) : motive z :=
Quot.recOnSubsingleton z f
protected theorem «exists» {α : Sort _} {f : Sym2 α → Prop} :
(∃ x : Sym2 α, f x) ↔ ∃ x y, f s(x, y) :=
(surjective_quot_mk _).exists.trans Prod.exists
#align sym2.exists Sym2.exists
protected theorem «forall» {α : Sort _} {f : Sym2 α → Prop} :
(∀ x : Sym2 α, f x) ↔ ∀ x y, f s(x, y) :=
(surjective_quot_mk _).forall.trans Prod.forall
#align sym2.forall Sym2.forall
theorem eq_swap {a b : α} : s(a, b) = s(b, a) := Quot.sound (Rel.swap _ _)
#align sym2.eq_swap Sym2.eq_swap
@[simp]
theorem mk_prod_swap_eq {p : α × α} : Sym2.mk p.swap = Sym2.mk p := by
cases p
exact eq_swap
#align sym2.mk_prod_swap_eq Sym2.mk_prod_swap_eq
theorem congr_right {a b c : α} : s(a, b) = s(a, c) ↔ b = c := by
simp (config := {contextual := true})
#align sym2.congr_right Sym2.congr_right
theorem congr_left {a b c : α} : s(b, a) = s(c, a) ↔ b = c := by
simp (config := {contextual := true})
#align sym2.congr_left Sym2.congr_left
theorem eq_iff {x y z w : α} : s(x, y) = s(z, w) ↔ x = z ∧ y = w ∨ x = w ∧ y = z := by
simp
#align sym2.eq_iff Sym2.eq_iff
theorem mk_eq_mk_iff {p q : α × α} : Sym2.mk p = Sym2.mk q ↔ p = q ∨ p = q.swap := by
cases p
cases q
simp only [eq_iff, Prod.mk.inj_iff, Prod.swap_prod_mk]
#align sym2.mk_eq_mk_iff Sym2.mk_eq_mk_iff
/-- The universal property of `Sym2`; symmetric functions of two arguments are equivalent to
functions from `Sym2`. Note that when `β` is `Prop`, it can sometimes be more convenient to use
`Sym2.fromRel` instead. -/
def lift : { f : α → α → β // ∀ a₁ a₂, f a₁ a₂ = f a₂ a₁ } ≃ (Sym2 α → β) where
toFun f :=
Quot.lift (uncurry ↑f) <| by
rintro _ _ ⟨⟩
exacts [rfl, f.prop _ _]
invFun F := ⟨curry (F ∘ Sym2.mk), fun a₁ a₂ => congr_arg F eq_swap⟩
left_inv f := Subtype.ext rfl
right_inv F := funext <| Sym2.ind fun x y => rfl
#align sym2.lift Sym2.lift
@[simp]
theorem lift_mk (f : { f : α → α → β // ∀ a₁ a₂, f a₁ a₂ = f a₂ a₁ }) (a₁ a₂ : α) :
lift f s(a₁, a₂) = (f : α → α → β) a₁ a₂ :=
rfl
#align sym2.lift_mk Sym2.lift_mk
@[simp]
theorem coe_lift_symm_apply (F : Sym2 α → β) (a₁ a₂ : α) :
(lift.symm F : α → α → β) a₁ a₂ = F s(a₁, a₂) :=
rfl
#align sym2.coe_lift_symm_apply Sym2.coe_lift_symm_apply
/-- A two-argument version of `Sym2.lift`. -/
def lift₂ :
{ f : α → α → β → β → γ //
∀ a₁ a₂ b₁ b₂, f a₁ a₂ b₁ b₂ = f a₂ a₁ b₁ b₂ ∧ f a₁ a₂ b₁ b₂ = f a₁ a₂ b₂ b₁ } ≃
(Sym2 α → Sym2 β → γ) where
toFun f :=
Quotient.lift₂ (s₁ := Sym2.Rel.setoid α) (s₂ := Sym2.Rel.setoid β)
(fun (a : α × α) (b : β × β) => f.1 a.1 a.2 b.1 b.2)
(by
rintro _ _ _ _ ⟨⟩ ⟨⟩
exacts [rfl, (f.2 _ _ _ _).2, (f.2 _ _ _ _).1, (f.2 _ _ _ _).1.trans (f.2 _ _ _ _).2])
invFun F :=
⟨fun a₁ a₂ b₁ b₂ => F s(a₁, a₂) s(b₁, b₂), fun a₁ a₂ b₁ b₂ => by
constructor
exacts [congr_arg₂ F eq_swap rfl, congr_arg₂ F rfl eq_swap]⟩
left_inv f := Subtype.ext rfl
right_inv F := funext₂ fun a b => Sym2.inductionOn₂ a b fun _ _ _ _ => rfl
#align sym2.lift₂ Sym2.lift₂
@[simp]
theorem lift₂_mk
(f :
{ f : α → α → β → β → γ //
∀ a₁ a₂ b₁ b₂, f a₁ a₂ b₁ b₂ = f a₂ a₁ b₁ b₂ ∧ f a₁ a₂ b₁ b₂ = f a₁ a₂ b₂ b₁ })
(a₁ a₂ : α) (b₁ b₂ : β) : lift₂ f s(a₁, a₂) s(b₁, b₂) = (f : α → α → β → β → γ) a₁ a₂ b₁ b₂ :=
rfl
#align sym2.lift₂_mk Sym2.lift₂_mk
@[simp]
theorem coe_lift₂_symm_apply (F : Sym2 α → Sym2 β → γ) (a₁ a₂ : α) (b₁ b₂ : β) :
(lift₂.symm F : α → α → β → β → γ) a₁ a₂ b₁ b₂ = F s(a₁, a₂) s(b₁, b₂) :=
rfl
#align sym2.coe_lift₂_symm_apply Sym2.coe_lift₂_symm_apply
/-- The functor `Sym2` is functorial, and this function constructs the induced maps.
-/
def map (f : α → β) : Sym2 α → Sym2 β :=
Quot.map (Prod.map f f)
(by intro _ _ h; cases h <;> constructor)
#align sym2.map Sym2.map
@[simp]
theorem map_id : map (@id α) = id := by
ext ⟨⟨x, y⟩⟩
rfl
#align sym2.map_id Sym2.map_id
theorem map_comp {g : β → γ} {f : α → β} : Sym2.map (g ∘ f) = Sym2.map g ∘ Sym2.map f := by
ext ⟨⟨x, y⟩⟩
rfl
#align sym2.map_comp Sym2.map_comp
theorem map_map {g : β → γ} {f : α → β} (x : Sym2 α) : map g (map f x) = map (g ∘ f) x := by
revert x; apply Sym2.ind; aesop
#align sym2.map_map Sym2.map_map
@[simp]
theorem map_pair_eq (f : α → β) (x y : α) : map f s(x, y) = s(f x, f y) :=
rfl
#align sym2.map_pair_eq Sym2.map_pair_eq
theorem map.injective {f : α → β} (hinj : Injective f) : Injective (map f) := by
intro z z'
refine Sym2.inductionOn₂ z z' (fun x y x' y' => ?_)
simp [hinj.eq_iff]
#align sym2.map.injective Sym2.map.injective
section Membership
/-! ### Membership and set coercion -/
/-- This is a predicate that determines whether a given term is a member of a term of the
symmetric square. From this point of view, the symmetric square is the subtype of
cardinality-two multisets on `α`.
-/
protected def Mem (x : α) (z : Sym2 α) : Prop :=
∃ y : α, z = s(x, y)
#align sym2.mem Sym2.Mem
@[aesop norm (rule_sets := [Sym2])]
theorem mem_iff' {a b c : α} : Sym2.Mem a s(b, c) ↔ a = b ∨ a = c :=
{ mp := by
rintro ⟨_, h⟩
rw [eq_iff] at h
aesop
mpr := by
rintro (rfl | rfl)
· exact ⟨_, rfl⟩
rw [eq_swap]
exact ⟨_, rfl⟩ }
#align sym2.mem_iff' Sym2.mem_iff'
instance : SetLike (Sym2 α) α where
coe z := { x | z.Mem x }
coe_injective' z z' h := by
simp only [Set.ext_iff, Set.mem_setOf_eq] at h
induction' z using Sym2.ind with x y
induction' z' using Sym2.ind with x' y'
have hx := h x; have hy := h y; have hx' := h x'; have hy' := h y'
simp only [mem_iff', eq_self_iff_true, or_true_iff, iff_true_iff,
true_or_iff, true_iff_iff] at hx hy hx' hy'
aesop
@[simp]
theorem mem_iff_mem {x : α} {z : Sym2 α} : Sym2.Mem x z ↔ x ∈ z :=
Iff.rfl
#align sym2.mem_iff_mem Sym2.mem_iff_mem
theorem mem_iff_exists {x : α} {z : Sym2 α} : x ∈ z ↔ ∃ y : α, z = s(x, y) :=
Iff.rfl
#align sym2.mem_iff_exists Sym2.mem_iff_exists
@[ext]
theorem ext {p q : Sym2 α} (h : ∀ x, x ∈ p ↔ x ∈ q) : p = q :=
SetLike.ext h
#align sym2.ext Sym2.ext
theorem mem_mk_left (x y : α) : x ∈ s(x, y) :=
⟨y, rfl⟩
#align sym2.mem_mk_left Sym2.mem_mk_left
theorem mem_mk_right (x y : α) : y ∈ s(x, y) :=
eq_swap.subst <| mem_mk_left y x
#align sym2.mem_mk_right Sym2.mem_mk_right
@[simp, aesop norm (rule_sets := [Sym2])]
theorem mem_iff {a b c : α} : a ∈ s(b, c) ↔ a = b ∨ a = c :=
mem_iff'
#align sym2.mem_iff Sym2.mem_iff
theorem out_fst_mem (e : Sym2 α) : e.out.1 ∈ e :=
⟨e.out.2, by rw [Sym2.mk, e.out_eq]⟩
#align sym2.out_fst_mem Sym2.out_fst_mem
theorem out_snd_mem (e : Sym2 α) : e.out.2 ∈ e :=
⟨e.out.1, by rw [eq_swap, Sym2.mk, e.out_eq]⟩
#align sym2.out_snd_mem Sym2.out_snd_mem
theorem ball {p : α → Prop} {a b : α} : (∀ c ∈ s(a, b), p c) ↔ p a ∧ p b := by
refine ⟨fun h => ⟨h _ <| mem_mk_left _ _, h _ <| mem_mk_right _ _⟩, fun h c hc => ?_⟩
obtain rfl | rfl := Sym2.mem_iff.1 hc
· exact h.1
· exact h.2
#align sym2.ball Sym2.ball
/-- Given an element of the unordered pair, give the other element using `Classical.choose`.
See also `Mem.other'` for the computable version.
-/
noncomputable def Mem.other {a : α} {z : Sym2 α} (h : a ∈ z) : α :=
Classical.choose h
#align sym2.mem.other Sym2.Mem.other
@[simp]
theorem other_spec {a : α} {z : Sym2 α} (h : a ∈ z) : s(a, Mem.other h) = z := by
erw [← Classical.choose_spec h]
#align sym2.other_spec Sym2.other_spec
theorem other_mem {a : α} {z : Sym2 α} (h : a ∈ z) : Mem.other h ∈ z := by
convert mem_mk_right a <| Mem.other h
rw [other_spec h]
#align sym2.other_mem Sym2.other_mem
theorem mem_and_mem_iff {x y : α} {z : Sym2 α} (hne : x ≠ y) : x ∈ z ∧ y ∈ z ↔ z = s(x, y) := by
constructor
· induction' z using Sym2.ind with x' y'
rw [mem_iff, mem_iff]
aesop
· rintro rfl
simp
#align sym2.mem_and_mem_iff Sym2.mem_and_mem_iff
theorem eq_of_ne_mem {x y : α} {z z' : Sym2 α} (h : x ≠ y) (h1 : x ∈ z) (h2 : y ∈ z) (h3 : x ∈ z')
(h4 : y ∈ z') : z = z' :=
((mem_and_mem_iff h).mp ⟨h1, h2⟩).trans ((mem_and_mem_iff h).mp ⟨h3, h4⟩).symm
#align sym2.eq_of_ne_mem Sym2.eq_of_ne_mem
instance Mem.decidable [DecidableEq α] (x : α) (z : Sym2 α) : Decidable (x ∈ z) :=
z.recOnSubsingleton fun ⟨_, _⟩ => decidable_of_iff' _ mem_iff
#align sym2.mem.decidable Sym2.Mem.decidable
end Membership
@[simp]
theorem mem_map {f : α → β} {b : β} {z : Sym2 α} : b ∈ Sym2.map f z ↔ ∃ a, a ∈ z ∧ f a = b := by
induction' z using Sym2.ind with x y
simp only [map_pair_eq, mem_iff, exists_eq_or_imp, exists_eq_left]
aesop
#align sym2.mem_map Sym2.mem_map
@[congr]
theorem map_congr {f g : α → β} {s : Sym2 α} (h : ∀ x ∈ s, f x = g x) : map f s = map g s := by
ext y
simp only [mem_map]
constructor <;>
· rintro ⟨w, hw, rfl⟩
exact ⟨w, hw, by simp [hw, h]⟩
#align sym2.map_congr Sym2.map_congr
/-- Note: `Sym2.map_id` will not simplify `Sym2.map id z` due to `Sym2.map_congr`. -/
@[simp]
theorem map_id' : (map fun x : α => x) = id :=
map_id
#align sym2.map_id' Sym2.map_id'
/-! ### Diagonal -/
variable {e : Sym2 α} {f : α → β}
/-- A type `α` is naturally included in the diagonal of `α × α`, and this function gives the image
of this diagonal in `Sym2 α`.
-/
def diag (x : α) : Sym2 α := s(x, x)
#align sym2.diag Sym2.diag
theorem diag_injective : Function.Injective (Sym2.diag : α → Sym2 α) := fun x y h => by
cases Sym2.exact h <;> rfl
#align sym2.diag_injective Sym2.diag_injective
/-- A predicate for testing whether an element of `Sym2 α` is on the diagonal.
-/
def IsDiag : Sym2 α → Prop :=
lift ⟨Eq, fun _ _ => propext eq_comm⟩
#align sym2.is_diag Sym2.IsDiag
theorem mk_isDiag_iff {x y : α} : IsDiag s(x, y) ↔ x = y :=
Iff.rfl
#align sym2.mk_is_diag_iff Sym2.mk_isDiag_iff
@[simp]
theorem isDiag_iff_proj_eq (z : α × α) : IsDiag (Sym2.mk z) ↔ z.1 = z.2 :=
Prod.recOn z fun _ _ => mk_isDiag_iff
#align sym2.is_diag_iff_proj_eq Sym2.isDiag_iff_proj_eq
protected lemma IsDiag.map : e.IsDiag → (e.map f).IsDiag := Sym2.ind (fun _ _ ↦ congr_arg f) e
lemma isDiag_map (hf : Injective f) : (e.map f).IsDiag ↔ e.IsDiag :=
Sym2.ind (fun _ _ ↦ hf.eq_iff) e
@[simp]
theorem diag_isDiag (a : α) : IsDiag (diag a) :=
Eq.refl a
#align sym2.diag_is_diag Sym2.diag_isDiag
| Mathlib/Data/Sym/Sym2.lean | 467 | 470 | theorem IsDiag.mem_range_diag {z : Sym2 α} : IsDiag z → z ∈ Set.range (@diag α) := by |
induction' z using Sym2.ind with x y
rintro (rfl : x = y)
exact ⟨_, rfl⟩
|
/-
Copyright (c) 2022 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Batteries.Data.RBMap.Alter
import Batteries.Data.List.Lemmas
/-!
# Additional lemmas for Red-black trees
-/
namespace Batteries
namespace RBNode
open RBColor
attribute [simp] fold foldl foldr Any forM foldlM Ordered
@[simp] theorem min?_reverse (t : RBNode α) : t.reverse.min? = t.max? := by
unfold RBNode.max?; split <;> simp [RBNode.min?]
unfold RBNode.min?; rw [min?.match_1.eq_3]
· apply min?_reverse
· simpa [reverse_eq_iff]
@[simp] theorem max?_reverse (t : RBNode α) : t.reverse.max? = t.min? := by
rw [← min?_reverse, reverse_reverse]
@[simp] theorem mem_nil {x} : ¬x ∈ (.nil : RBNode α) := by simp [(·∈·), EMem]
@[simp] theorem mem_node {y c a x b} :
y ∈ (.node c a x b : RBNode α) ↔ y = x ∨ y ∈ a ∨ y ∈ b := by simp [(·∈·), EMem]
theorem All_def {t : RBNode α} : t.All p ↔ ∀ x ∈ t, p x := by
induction t <;> simp [or_imp, forall_and, *]
theorem Any_def {t : RBNode α} : t.Any p ↔ ∃ x ∈ t, p x := by
induction t <;> simp [or_and_right, exists_or, *]
theorem memP_def : MemP cut t ↔ ∃ x ∈ t, cut x = .eq := Any_def
theorem mem_def : Mem cmp x t ↔ ∃ y ∈ t, cmp x y = .eq := Any_def
theorem mem_congr [@TransCmp α cmp] {t : RBNode α} (h : cmp x y = .eq) :
Mem cmp x t ↔ Mem cmp y t := by simp [Mem, TransCmp.cmp_congr_left' h]
theorem isOrdered_iff' [@TransCmp α cmp] {t : RBNode α} :
isOrdered cmp t L R ↔
(∀ a ∈ L, t.All (cmpLT cmp a ·)) ∧
(∀ a ∈ R, t.All (cmpLT cmp · a)) ∧
(∀ a ∈ L, ∀ b ∈ R, cmpLT cmp a b) ∧
Ordered cmp t := by
induction t generalizing L R with
| nil =>
simp [isOrdered]; split <;> simp [cmpLT_iff]
next h => intro _ ha _ hb; cases h _ _ ha hb
| node _ l v r =>
simp [isOrdered, *]
exact ⟨
fun ⟨⟨Ll, lv, Lv, ol⟩, ⟨vr, rR, vR, or⟩⟩ => ⟨
fun _ h => ⟨Lv _ h, Ll _ h, (Lv _ h).trans_l vr⟩,
fun _ h => ⟨vR _ h, (vR _ h).trans_r lv, rR _ h⟩,
fun _ hL _ hR => (Lv _ hL).trans (vR _ hR),
lv, vr, ol, or⟩,
fun ⟨hL, hR, _, lv, vr, ol, or⟩ => ⟨
⟨fun _ h => (hL _ h).2.1, lv, fun _ h => (hL _ h).1, ol⟩,
⟨vr, fun _ h => (hR _ h).2.2, fun _ h => (hR _ h).1, or⟩⟩⟩
theorem isOrdered_iff [@TransCmp α cmp] {t : RBNode α} :
isOrdered cmp t ↔ Ordered cmp t := by simp [isOrdered_iff']
instance (cmp) [@TransCmp α cmp] (t) : Decidable (Ordered cmp t) := decidable_of_iff _ isOrdered_iff
/--
A cut is like a homomorphism of orderings: it is a monotonic predicate with respect to `cmp`,
but it can make things that are distinguished by `cmp` equal.
This is sufficient for `find?` to locate an element on which `cut` returns `.eq`,
but there may be other elements, not returned by `find?`, on which `cut` also returns `.eq`.
-/
class IsCut (cmp : α → α → Ordering) (cut : α → Ordering) : Prop where
/-- The set `{x | cut x = .lt}` is downward-closed. -/
le_lt_trans [TransCmp cmp] : cmp x y ≠ .gt → cut x = .lt → cut y = .lt
/-- The set `{x | cut x = .gt}` is upward-closed. -/
le_gt_trans [TransCmp cmp] : cmp x y ≠ .gt → cut y = .gt → cut x = .gt
theorem IsCut.lt_trans [IsCut cmp cut] [TransCmp cmp]
(H : cmp x y = .lt) : cut x = .lt → cut y = .lt :=
IsCut.le_lt_trans <| TransCmp.gt_asymm <| OrientedCmp.cmp_eq_gt.2 H
theorem IsCut.gt_trans [IsCut cmp cut] [TransCmp cmp]
(H : cmp x y = .lt) : cut y = .gt → cut x = .gt :=
IsCut.le_gt_trans <| TransCmp.gt_asymm <| OrientedCmp.cmp_eq_gt.2 H
theorem IsCut.congr [IsCut cmp cut] [TransCmp cmp] (H : cmp x y = .eq) : cut x = cut y := by
cases ey : cut y
· exact IsCut.le_lt_trans (fun h => nomatch H.symm.trans <| OrientedCmp.cmp_eq_gt.1 h) ey
· cases ex : cut x
· exact IsCut.le_lt_trans (fun h => nomatch H.symm.trans h) ex |>.symm.trans ey
· rfl
· refine IsCut.le_gt_trans (cmp := cmp) (fun h => ?_) ex |>.symm.trans ey
cases H.symm.trans <| OrientedCmp.cmp_eq_gt.1 h
· exact IsCut.le_gt_trans (fun h => nomatch H.symm.trans h) ey
instance (cmp cut) [@IsCut α cmp cut] : IsCut (flip cmp) (cut · |>.swap) where
le_lt_trans h₁ h₂ := by
have : TransCmp cmp := inferInstanceAs (TransCmp (flip (flip cmp)))
rw [IsCut.le_gt_trans (cmp := cmp) h₁ (Ordering.swap_inj.1 h₂)]; rfl
le_gt_trans h₁ h₂ := by
have : TransCmp cmp := inferInstanceAs (TransCmp (flip (flip cmp)))
rw [IsCut.le_lt_trans (cmp := cmp) h₁ (Ordering.swap_inj.1 h₂)]; rfl
/--
`IsStrictCut` upgrades the `IsCut` property to ensure that at most one element of the tree
can match the cut, and hence `find?` will return the unique such element if one exists.
-/
class IsStrictCut (cmp : α → α → Ordering) (cut : α → Ordering) extends IsCut cmp cut : Prop where
/-- If `cut = x`, then `cut` and `x` have compare the same with respect to other elements. -/
exact [TransCmp cmp] : cut x = .eq → cmp x y = cut y
/-- A "representable cut" is one generated by `cmp a` for some `a`. This is always a valid cut. -/
instance (cmp) (a : α) : IsStrictCut cmp (cmp a) where
le_lt_trans h₁ h₂ := TransCmp.lt_le_trans h₂ h₁
le_gt_trans h₁ := Decidable.not_imp_not.1 (TransCmp.le_trans · h₁)
exact h := (TransCmp.cmp_congr_left h).symm
instance (cmp cut) [@IsStrictCut α cmp cut] : IsStrictCut (flip cmp) (cut · |>.swap) where
exact h := by
have : TransCmp cmp := inferInstanceAs (TransCmp (flip (flip cmp)))
rw [← IsStrictCut.exact (cmp := cmp) (Ordering.swap_inj.1 h), OrientedCmp.symm]; rfl
section fold
theorem foldr_cons (t : RBNode α) (l) : t.foldr (·::·) l = t.toList ++ l := by
unfold toList
induction t generalizing l with
| nil => rfl
| node _ a _ b iha ihb => rw [foldr, foldr, iha, iha (_::_), ihb]; simp
@[simp] theorem toList_nil : (.nil : RBNode α).toList = [] := rfl
@[simp] theorem toList_node : (.node c a x b : RBNode α).toList = a.toList ++ x :: b.toList := by
rw [toList, foldr, foldr_cons]; rfl
@[simp] theorem toList_reverse (t : RBNode α) : t.reverse.toList = t.toList.reverse := by
induction t <;> simp [*]
@[simp] theorem mem_toList {t : RBNode α} : x ∈ t.toList ↔ x ∈ t := by
induction t <;> simp [*, or_left_comm]
@[simp] theorem mem_reverse {t : RBNode α} : a ∈ t.reverse ↔ a ∈ t := by rw [← mem_toList]; simp
theorem min?_eq_toList_head? {t : RBNode α} : t.min? = t.toList.head? := by
induction t with
| nil => rfl
| node _ l _ _ ih =>
cases l <;> simp [RBNode.min?, ih]
next ll _ _ => cases toList ll <;> rfl
theorem max?_eq_toList_getLast? {t : RBNode α} : t.max? = t.toList.getLast? := by
rw [← min?_reverse, min?_eq_toList_head?]; simp
theorem foldr_eq_foldr_toList {t : RBNode α} : t.foldr f init = t.toList.foldr f init := by
induction t generalizing init <;> simp [*]
theorem foldl_eq_foldl_toList {t : RBNode α} : t.foldl f init = t.toList.foldl f init := by
induction t generalizing init <;> simp [*]
theorem foldl_reverse {α β : Type _} {t : RBNode α} {f : β → α → β} {init : β} :
t.reverse.foldl f init = t.foldr (flip f) init := by
simp (config := {unfoldPartialApp := true})
[foldr_eq_foldr_toList, foldl_eq_foldl_toList, flip]
theorem foldr_reverse {α β : Type _} {t : RBNode α} {f : α → β → β} {init : β} :
t.reverse.foldr f init = t.foldl (flip f) init :=
foldl_reverse.symm.trans (by simp; rfl)
theorem forM_eq_forM_toList [Monad m] [LawfulMonad m] {t : RBNode α} :
t.forM (m := m) f = t.toList.forM f := by induction t <;> simp [*]
theorem foldlM_eq_foldlM_toList [Monad m] [LawfulMonad m] {t : RBNode α} :
t.foldlM (m := m) f init = t.toList.foldlM f init := by
induction t generalizing init <;> simp [*]
theorem forIn_visit_eq_bindList [Monad m] [LawfulMonad m] {t : RBNode α} :
forIn.visit (m := m) f t init = (ForInStep.yield init).bindList f t.toList := by
induction t generalizing init <;> simp [*, forIn.visit]
theorem forIn_eq_forIn_toList [Monad m] [LawfulMonad m] {t : RBNode α} :
forIn (m := m) t init f = forIn t.toList init f := by
conv => lhs; simp only [forIn, RBNode.forIn]
rw [List.forIn_eq_bindList, forIn_visit_eq_bindList]
end fold
namespace Stream
attribute [simp] foldl foldr
theorem foldr_cons (t : RBNode.Stream α) (l) : t.foldr (·::·) l = t.toList ++ l := by
unfold toList; apply Eq.symm; induction t <;> simp [*, foldr, RBNode.foldr_cons]
@[simp] theorem toList_nil : (.nil : RBNode.Stream α).toList = [] := rfl
@[simp] theorem toList_cons :
(.cons x r s : RBNode.Stream α).toList = x :: r.toList ++ s.toList := by
rw [toList, toList, foldr, RBNode.foldr_cons]; rfl
theorem foldr_eq_foldr_toList {s : RBNode.Stream α} : s.foldr f init = s.toList.foldr f init := by
induction s <;> simp [*, RBNode.foldr_eq_foldr_toList]
theorem foldl_eq_foldl_toList {t : RBNode.Stream α} : t.foldl f init = t.toList.foldl f init := by
induction t generalizing init <;> simp [*, RBNode.foldl_eq_foldl_toList]
theorem forIn_eq_forIn_toList [Monad m] [LawfulMonad m] {t : RBNode α} :
forIn (m := m) t init f = forIn t.toList init f := by
conv => lhs; simp only [forIn, RBNode.forIn]
rw [List.forIn_eq_bindList, forIn_visit_eq_bindList]
end Stream
theorem toStream_toList' {t : RBNode α} {s} : (t.toStream s).toList = t.toList ++ s.toList := by
induction t generalizing s <;> simp [*, toStream]
@[simp] theorem toStream_toList {t : RBNode α} : t.toStream.toList = t.toList := by
simp [toStream_toList']
theorem Stream.next?_toList {s : RBNode.Stream α} :
(s.next?.map fun (a, b) => (a, b.toList)) = s.toList.next? := by
cases s <;> simp [next?, toStream_toList']
theorem ordered_iff {t : RBNode α} :
t.Ordered cmp ↔ t.toList.Pairwise (cmpLT cmp) := by
induction t with
| nil => simp
| node c l v r ihl ihr =>
simp [*, List.pairwise_append, Ordered, All_def,
and_assoc, and_left_comm, and_comm, imp_and, forall_and]
exact fun _ _ hl hr a ha b hb => (hl _ ha).trans (hr _ hb)
theorem Ordered.toList_sorted {t : RBNode α} : t.Ordered cmp → t.toList.Pairwise (cmpLT cmp) :=
ordered_iff.1
| .lake/packages/batteries/Batteries/Data/RBMap/Lemmas.lean | 241 | 244 | theorem min?_mem {t : RBNode α} (h : t.min? = some a) : a ∈ t := by |
rw [min?_eq_toList_head?] at h
rw [← mem_toList]
revert h; cases toList t <;> rintro ⟨⟩; constructor
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot, Yury Kudryashov, Rémy Degenne
-/
import Mathlib.Algebra.Order.Group.Abs
import Mathlib.Algebra.Order.Group.Basic
import Mathlib.Algebra.Order.Group.OrderIso
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Order.Interval.Set.Basic
import Mathlib.Logic.Pairwise
#align_import data.set.intervals.group from "leanprover-community/mathlib"@"c227d107bbada5d0d9d20287e3282c0a7f1651a0"
/-! ### Lemmas about arithmetic operations and intervals. -/
variable {α : Type*}
namespace Set
section OrderedCommGroup
variable [OrderedCommGroup α] {a b c d : α}
/-! `inv_mem_Ixx_iff`, `sub_mem_Ixx_iff` -/
@[to_additive]
theorem inv_mem_Icc_iff : a⁻¹ ∈ Set.Icc c d ↔ a ∈ Set.Icc d⁻¹ c⁻¹ :=
and_comm.trans <| and_congr inv_le' le_inv'
#align set.inv_mem_Icc_iff Set.inv_mem_Icc_iff
#align set.neg_mem_Icc_iff Set.neg_mem_Icc_iff
@[to_additive]
theorem inv_mem_Ico_iff : a⁻¹ ∈ Set.Ico c d ↔ a ∈ Set.Ioc d⁻¹ c⁻¹ :=
and_comm.trans <| and_congr inv_lt' le_inv'
#align set.inv_mem_Ico_iff Set.inv_mem_Ico_iff
#align set.neg_mem_Ico_iff Set.neg_mem_Ico_iff
@[to_additive]
theorem inv_mem_Ioc_iff : a⁻¹ ∈ Set.Ioc c d ↔ a ∈ Set.Ico d⁻¹ c⁻¹ :=
and_comm.trans <| and_congr inv_le' lt_inv'
#align set.inv_mem_Ioc_iff Set.inv_mem_Ioc_iff
#align set.neg_mem_Ioc_iff Set.neg_mem_Ioc_iff
@[to_additive]
theorem inv_mem_Ioo_iff : a⁻¹ ∈ Set.Ioo c d ↔ a ∈ Set.Ioo d⁻¹ c⁻¹ :=
and_comm.trans <| and_congr inv_lt' lt_inv'
#align set.inv_mem_Ioo_iff Set.inv_mem_Ioo_iff
#align set.neg_mem_Ioo_iff Set.neg_mem_Ioo_iff
end OrderedCommGroup
section OrderedAddCommGroup
variable [OrderedAddCommGroup α] {a b c d : α}
/-! `add_mem_Ixx_iff_left` -/
-- Porting note: instance search needs help `(α := α)`
theorem add_mem_Icc_iff_left : a + b ∈ Set.Icc c d ↔ a ∈ Set.Icc (c - b) (d - b) :=
(and_congr (sub_le_iff_le_add (α := α)) (le_sub_iff_add_le (α := α))).symm
#align set.add_mem_Icc_iff_left Set.add_mem_Icc_iff_left
theorem add_mem_Ico_iff_left : a + b ∈ Set.Ico c d ↔ a ∈ Set.Ico (c - b) (d - b) :=
(and_congr (sub_le_iff_le_add (α := α)) (lt_sub_iff_add_lt (α := α))).symm
#align set.add_mem_Ico_iff_left Set.add_mem_Ico_iff_left
theorem add_mem_Ioc_iff_left : a + b ∈ Set.Ioc c d ↔ a ∈ Set.Ioc (c - b) (d - b) :=
(and_congr (sub_lt_iff_lt_add (α := α)) (le_sub_iff_add_le (α := α))).symm
#align set.add_mem_Ioc_iff_left Set.add_mem_Ioc_iff_left
theorem add_mem_Ioo_iff_left : a + b ∈ Set.Ioo c d ↔ a ∈ Set.Ioo (c - b) (d - b) :=
(and_congr (sub_lt_iff_lt_add (α := α)) (lt_sub_iff_add_lt (α := α))).symm
#align set.add_mem_Ioo_iff_left Set.add_mem_Ioo_iff_left
/-! `add_mem_Ixx_iff_right` -/
theorem add_mem_Icc_iff_right : a + b ∈ Set.Icc c d ↔ b ∈ Set.Icc (c - a) (d - a) :=
(and_congr sub_le_iff_le_add' le_sub_iff_add_le').symm
#align set.add_mem_Icc_iff_right Set.add_mem_Icc_iff_right
theorem add_mem_Ico_iff_right : a + b ∈ Set.Ico c d ↔ b ∈ Set.Ico (c - a) (d - a) :=
(and_congr sub_le_iff_le_add' lt_sub_iff_add_lt').symm
#align set.add_mem_Ico_iff_right Set.add_mem_Ico_iff_right
theorem add_mem_Ioc_iff_right : a + b ∈ Set.Ioc c d ↔ b ∈ Set.Ioc (c - a) (d - a) :=
(and_congr sub_lt_iff_lt_add' le_sub_iff_add_le').symm
#align set.add_mem_Ioc_iff_right Set.add_mem_Ioc_iff_right
theorem add_mem_Ioo_iff_right : a + b ∈ Set.Ioo c d ↔ b ∈ Set.Ioo (c - a) (d - a) :=
(and_congr sub_lt_iff_lt_add' lt_sub_iff_add_lt').symm
#align set.add_mem_Ioo_iff_right Set.add_mem_Ioo_iff_right
/-! `sub_mem_Ixx_iff_left` -/
theorem sub_mem_Icc_iff_left : a - b ∈ Set.Icc c d ↔ a ∈ Set.Icc (c + b) (d + b) :=
and_congr le_sub_iff_add_le sub_le_iff_le_add
#align set.sub_mem_Icc_iff_left Set.sub_mem_Icc_iff_left
theorem sub_mem_Ico_iff_left : a - b ∈ Set.Ico c d ↔ a ∈ Set.Ico (c + b) (d + b) :=
and_congr le_sub_iff_add_le sub_lt_iff_lt_add
#align set.sub_mem_Ico_iff_left Set.sub_mem_Ico_iff_left
theorem sub_mem_Ioc_iff_left : a - b ∈ Set.Ioc c d ↔ a ∈ Set.Ioc (c + b) (d + b) :=
and_congr lt_sub_iff_add_lt sub_le_iff_le_add
#align set.sub_mem_Ioc_iff_left Set.sub_mem_Ioc_iff_left
theorem sub_mem_Ioo_iff_left : a - b ∈ Set.Ioo c d ↔ a ∈ Set.Ioo (c + b) (d + b) :=
and_congr lt_sub_iff_add_lt sub_lt_iff_lt_add
#align set.sub_mem_Ioo_iff_left Set.sub_mem_Ioo_iff_left
/-! `sub_mem_Ixx_iff_right` -/
theorem sub_mem_Icc_iff_right : a - b ∈ Set.Icc c d ↔ b ∈ Set.Icc (a - d) (a - c) :=
and_comm.trans <| and_congr sub_le_comm le_sub_comm
#align set.sub_mem_Icc_iff_right Set.sub_mem_Icc_iff_right
theorem sub_mem_Ico_iff_right : a - b ∈ Set.Ico c d ↔ b ∈ Set.Ioc (a - d) (a - c) :=
and_comm.trans <| and_congr sub_lt_comm le_sub_comm
#align set.sub_mem_Ico_iff_right Set.sub_mem_Ico_iff_right
theorem sub_mem_Ioc_iff_right : a - b ∈ Set.Ioc c d ↔ b ∈ Set.Ico (a - d) (a - c) :=
and_comm.trans <| and_congr sub_le_comm lt_sub_comm
#align set.sub_mem_Ioc_iff_right Set.sub_mem_Ioc_iff_right
theorem sub_mem_Ioo_iff_right : a - b ∈ Set.Ioo c d ↔ b ∈ Set.Ioo (a - d) (a - c) :=
and_comm.trans <| and_congr sub_lt_comm lt_sub_comm
#align set.sub_mem_Ioo_iff_right Set.sub_mem_Ioo_iff_right
-- I think that symmetric intervals deserve attention and API: they arise all the time,
-- for instance when considering metric balls in `ℝ`.
theorem mem_Icc_iff_abs_le {R : Type*} [LinearOrderedAddCommGroup R] {x y z : R} :
|x - y| ≤ z ↔ y ∈ Icc (x - z) (x + z) :=
abs_le.trans <| and_comm.trans <| and_congr sub_le_comm neg_le_sub_iff_le_add
#align set.mem_Icc_iff_abs_le Set.mem_Icc_iff_abs_le
end OrderedAddCommGroup
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α]
/-- If we remove a smaller interval from a larger, the result is nonempty -/
theorem nonempty_Ico_sdiff {x dx y dy : α} (h : dy < dx) (hx : 0 < dx) :
Nonempty ↑(Ico x (x + dx) \ Ico y (y + dy)) := by
cases' lt_or_le x y with h' h'
· use x
simp [*, not_le.2 h']
· use max x (x + dy)
simp [*, le_refl]
#align set.nonempty_Ico_sdiff Set.nonempty_Ico_sdiff
end LinearOrderedAddCommGroup
/-! ### Lemmas about disjointness of translates of intervals -/
section PairwiseDisjoint
section OrderedCommGroup
variable [OrderedCommGroup α] (a b : α)
@[to_additive]
theorem pairwise_disjoint_Ioc_mul_zpow :
Pairwise (Disjoint on fun n : ℤ => Ioc (a * b ^ n) (a * b ^ (n + 1))) := by
simp (config := { unfoldPartialApp := true }) only [Function.onFun]
simp_rw [Set.disjoint_iff]
intro m n hmn x hx
apply hmn
have hb : 1 < b := by
have : a * b ^ m < a * b ^ (m + 1) := hx.1.1.trans_le hx.1.2
rwa [mul_lt_mul_iff_left, ← mul_one (b ^ m), zpow_add_one, mul_lt_mul_iff_left] at this
have i1 := hx.1.1.trans_le hx.2.2
have i2 := hx.2.1.trans_le hx.1.2
rw [mul_lt_mul_iff_left, zpow_lt_zpow_iff hb, Int.lt_add_one_iff] at i1 i2
exact le_antisymm i1 i2
#align set.pairwise_disjoint_Ioc_mul_zpow Set.pairwise_disjoint_Ioc_mul_zpow
#align set.pairwise_disjoint_Ioc_add_zsmul Set.pairwise_disjoint_Ioc_add_zsmul
@[to_additive]
theorem pairwise_disjoint_Ico_mul_zpow :
Pairwise (Disjoint on fun n : ℤ => Ico (a * b ^ n) (a * b ^ (n + 1))) := by
simp (config := { unfoldPartialApp := true }) only [Function.onFun]
simp_rw [Set.disjoint_iff]
intro m n hmn x hx
apply hmn
have hb : 1 < b := by
have : a * b ^ m < a * b ^ (m + 1) := hx.1.1.trans_lt hx.1.2
rwa [mul_lt_mul_iff_left, ← mul_one (b ^ m), zpow_add_one, mul_lt_mul_iff_left] at this
have i1 := hx.1.1.trans_lt hx.2.2
have i2 := hx.2.1.trans_lt hx.1.2
rw [mul_lt_mul_iff_left, zpow_lt_zpow_iff hb, Int.lt_add_one_iff] at i1 i2
exact le_antisymm i1 i2
#align set.pairwise_disjoint_Ico_mul_zpow Set.pairwise_disjoint_Ico_mul_zpow
#align set.pairwise_disjoint_Ico_add_zsmul Set.pairwise_disjoint_Ico_add_zsmul
@[to_additive]
theorem pairwise_disjoint_Ioo_mul_zpow :
Pairwise (Disjoint on fun n : ℤ => Ioo (a * b ^ n) (a * b ^ (n + 1))) := fun _ _ hmn =>
(pairwise_disjoint_Ioc_mul_zpow a b hmn).mono Ioo_subset_Ioc_self Ioo_subset_Ioc_self
#align set.pairwise_disjoint_Ioo_mul_zpow Set.pairwise_disjoint_Ioo_mul_zpow
#align set.pairwise_disjoint_Ioo_add_zsmul Set.pairwise_disjoint_Ioo_add_zsmul
@[to_additive]
theorem pairwise_disjoint_Ioc_zpow :
Pairwise (Disjoint on fun n : ℤ => Ioc (b ^ n) (b ^ (n + 1))) := by
simpa only [one_mul] using pairwise_disjoint_Ioc_mul_zpow 1 b
#align set.pairwise_disjoint_Ioc_zpow Set.pairwise_disjoint_Ioc_zpow
#align set.pairwise_disjoint_Ioc_zsmul Set.pairwise_disjoint_Ioc_zsmul
@[to_additive]
theorem pairwise_disjoint_Ico_zpow :
Pairwise (Disjoint on fun n : ℤ => Ico (b ^ n) (b ^ (n + 1))) := by
simpa only [one_mul] using pairwise_disjoint_Ico_mul_zpow 1 b
#align set.pairwise_disjoint_Ico_zpow Set.pairwise_disjoint_Ico_zpow
#align set.pairwise_disjoint_Ico_zsmul Set.pairwise_disjoint_Ico_zsmul
@[to_additive]
| Mathlib/Algebra/Order/Interval/Set/Group.lean | 226 | 228 | theorem pairwise_disjoint_Ioo_zpow :
Pairwise (Disjoint on fun n : ℤ => Ioo (b ^ n) (b ^ (n + 1))) := by |
simpa only [one_mul] using pairwise_disjoint_Ioo_mul_zpow 1 b
|
/-
Copyright (c) 2019 Amelia Livingston. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Amelia Livingston
-/
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Group.Units
import Mathlib.Algebra.Regular.Basic
import Mathlib.GroupTheory.Congruence.Basic
import Mathlib.Init.Data.Prod
import Mathlib.RingTheory.OreLocalization.Basic
#align_import group_theory.monoid_localization from "leanprover-community/mathlib"@"10ee941346c27bdb5e87bb3535100c0b1f08ac41"
/-!
# Localizations of commutative monoids
Localizing a commutative ring at one of its submonoids does not rely on the ring's addition, so
we can generalize localizations to commutative monoids.
We characterize the localization of a commutative monoid `M` at a submonoid `S` up to
isomorphism; that is, a commutative monoid `N` is the localization of `M` at `S` iff we can find a
monoid homomorphism `f : M →* N` satisfying 3 properties:
1. For all `y ∈ S`, `f y` is a unit;
2. For all `z : N`, there exists `(x, y) : M × S` such that `z * f y = f x`;
3. For all `x, y : M` such that `f x = f y`, there exists `c ∈ S` such that `x * c = y * c`.
(The converse is a consequence of 1.)
Given such a localization map `f : M →* N`, we can define the surjection
`Submonoid.LocalizationMap.mk'` sending `(x, y) : M × S` to `f x * (f y)⁻¹`, and
`Submonoid.LocalizationMap.lift`, the homomorphism from `N` induced by a homomorphism from `M` which
maps elements of `S` to invertible elements of the codomain. Similarly, given commutative monoids
`P, Q`, a submonoid `T` of `P` and a localization map for `T` from `P` to `Q`, then a homomorphism
`g : M →* P` such that `g(S) ⊆ T` induces a homomorphism of localizations, `LocalizationMap.map`,
from `N` to `Q`. We treat the special case of localizing away from an element in the sections
`AwayMap` and `Away`.
We also define the quotient of `M × S` by the unique congruence relation (equivalence relation
preserving a binary operation) `r` such that for any other congruence relation `s` on `M × S`
satisfying '`∀ y ∈ S`, `(1, 1) ∼ (y, y)` under `s`', we have that `(x₁, y₁) ∼ (x₂, y₂)` by `s`
whenever `(x₁, y₁) ∼ (x₂, y₂)` by `r`. We show this relation is equivalent to the standard
localization relation.
This defines the localization as a quotient type, `Localization`, but the majority of
subsequent lemmas in the file are given in terms of localizations up to isomorphism, using maps
which satisfy the characteristic predicate.
The Grothendieck group construction corresponds to localizing at the top submonoid, namely making
every element invertible.
## Implementation notes
In maths it is natural to reason up to isomorphism, but in Lean we cannot naturally `rewrite` one
structure with an isomorphic one; one way around this is to isolate a predicate characterizing
a structure up to isomorphism, and reason about things that satisfy the predicate.
The infimum form of the localization congruence relation is chosen as 'canonical' here, since it
shortens some proofs.
To apply a localization map `f` as a function, we use `f.toMap`, as coercions don't work well for
this structure.
To reason about the localization as a quotient type, use `mk_eq_monoidOf_mk'` and associated
lemmas. These show the quotient map `mk : M → S → Localization S` equals the
surjection `LocalizationMap.mk'` induced by the map
`Localization.monoidOf : Submonoid.LocalizationMap S (Localization S)` (where `of` establishes the
localization as a quotient type satisfies the characteristic predicate). The lemma
`mk_eq_monoidOf_mk'` hence gives you access to the results in the rest of the file, which are about
the `LocalizationMap.mk'` induced by any localization map.
## TODO
* Show that the localization at the top monoid is a group.
* Generalise to (nonempty) subsemigroups.
* If we acquire more bundlings, we can make `Localization.mkOrderEmbedding` be an ordered monoid
embedding.
## Tags
localization, monoid localization, quotient monoid, congruence relation, characteristic predicate,
commutative monoid, grothendieck group
-/
open Function
namespace AddSubmonoid
variable {M : Type*} [AddCommMonoid M] (S : AddSubmonoid M) (N : Type*) [AddCommMonoid N]
/-- The type of AddMonoid homomorphisms satisfying the characteristic predicate: if `f : M →+ N`
satisfies this predicate, then `N` is isomorphic to the localization of `M` at `S`. -/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
structure LocalizationMap extends AddMonoidHom M N where
map_add_units' : ∀ y : S, IsAddUnit (toFun y)
surj' : ∀ z : N, ∃ x : M × S, z + toFun x.2 = toFun x.1
exists_of_eq : ∀ x y, toFun x = toFun y → ∃ c : S, ↑c + x = ↑c + y
#align add_submonoid.localization_map AddSubmonoid.LocalizationMap
-- Porting note: no docstrings for AddSubmonoid.LocalizationMap
attribute [nolint docBlame] AddSubmonoid.LocalizationMap.map_add_units'
AddSubmonoid.LocalizationMap.surj' AddSubmonoid.LocalizationMap.exists_of_eq
/-- The AddMonoidHom underlying a `LocalizationMap` of `AddCommMonoid`s. -/
add_decl_doc LocalizationMap.toAddMonoidHom
end AddSubmonoid
section CommMonoid
variable {M : Type*} [CommMonoid M] (S : Submonoid M) (N : Type*) [CommMonoid N] {P : Type*}
[CommMonoid P]
namespace Submonoid
/-- The type of monoid homomorphisms satisfying the characteristic predicate: if `f : M →* N`
satisfies this predicate, then `N` is isomorphic to the localization of `M` at `S`. -/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
structure LocalizationMap extends MonoidHom M N where
map_units' : ∀ y : S, IsUnit (toFun y)
surj' : ∀ z : N, ∃ x : M × S, z * toFun x.2 = toFun x.1
exists_of_eq : ∀ x y, toFun x = toFun y → ∃ c : S, ↑c * x = c * y
#align submonoid.localization_map Submonoid.LocalizationMap
-- Porting note: no docstrings for Submonoid.LocalizationMap
attribute [nolint docBlame] Submonoid.LocalizationMap.map_units' Submonoid.LocalizationMap.surj'
Submonoid.LocalizationMap.exists_of_eq
attribute [to_additive] Submonoid.LocalizationMap
-- Porting note: this translation already exists
-- attribute [to_additive] Submonoid.LocalizationMap.toMonoidHom
/-- The monoid hom underlying a `LocalizationMap`. -/
add_decl_doc LocalizationMap.toMonoidHom
end Submonoid
namespace Localization
-- Porting note: this does not work so it is done explicitly instead
-- run_cmd to_additive.map_namespace `Localization `AddLocalization
-- run_cmd Elab.Command.liftCoreM <| ToAdditive.insertTranslation `Localization `AddLocalization
/-- The congruence relation on `M × S`, `M` a `CommMonoid` and `S` a submonoid of `M`, whose
quotient is the localization of `M` at `S`, defined as the unique congruence relation on
`M × S` such that for any other congruence relation `s` on `M × S` where for all `y ∈ S`,
`(1, 1) ∼ (y, y)` under `s`, we have that `(x₁, y₁) ∼ (x₂, y₂)` by `r` implies
`(x₁, y₁) ∼ (x₂, y₂)` by `s`. -/
@[to_additive AddLocalization.r
"The congruence relation on `M × S`, `M` an `AddCommMonoid` and `S` an `AddSubmonoid` of `M`,
whose quotient is the localization of `M` at `S`, defined as the unique congruence relation on
`M × S` such that for any other congruence relation `s` on `M × S` where for all `y ∈ S`,
`(0, 0) ∼ (y, y)` under `s`, we have that `(x₁, y₁) ∼ (x₂, y₂)` by `r` implies
`(x₁, y₁) ∼ (x₂, y₂)` by `s`."]
def r (S : Submonoid M) : Con (M × S) :=
sInf { c | ∀ y : S, c 1 (y, y) }
#align localization.r Localization.r
#align add_localization.r AddLocalization.r
/-- An alternate form of the congruence relation on `M × S`, `M` a `CommMonoid` and `S` a
submonoid of `M`, whose quotient is the localization of `M` at `S`. -/
@[to_additive AddLocalization.r'
"An alternate form of the congruence relation on `M × S`, `M` a `CommMonoid` and `S` a
submonoid of `M`, whose quotient is the localization of `M` at `S`."]
def r' : Con (M × S) := by
-- note we multiply by `c` on the left so that we can later generalize to `•`
refine
{ r := fun a b : M × S ↦ ∃ c : S, ↑c * (↑b.2 * a.1) = c * (a.2 * b.1)
iseqv := ⟨fun a ↦ ⟨1, rfl⟩, fun ⟨c, hc⟩ ↦ ⟨c, hc.symm⟩, ?_⟩
mul' := ?_ }
· rintro a b c ⟨t₁, ht₁⟩ ⟨t₂, ht₂⟩
use t₂ * t₁ * b.2
simp only [Submonoid.coe_mul]
calc
(t₂ * t₁ * b.2 : M) * (c.2 * a.1) = t₂ * c.2 * (t₁ * (b.2 * a.1)) := by ac_rfl
_ = t₁ * a.2 * (t₂ * (c.2 * b.1)) := by rw [ht₁]; ac_rfl
_ = t₂ * t₁ * b.2 * (a.2 * c.1) := by rw [ht₂]; ac_rfl
· rintro a b c d ⟨t₁, ht₁⟩ ⟨t₂, ht₂⟩
use t₂ * t₁
calc
(t₂ * t₁ : M) * (b.2 * d.2 * (a.1 * c.1)) = t₂ * (d.2 * c.1) * (t₁ * (b.2 * a.1)) := by ac_rfl
_ = (t₂ * t₁ : M) * (a.2 * c.2 * (b.1 * d.1)) := by rw [ht₁, ht₂]; ac_rfl
#align localization.r' Localization.r'
#align add_localization.r' AddLocalization.r'
/-- The congruence relation used to localize a `CommMonoid` at a submonoid can be expressed
equivalently as an infimum (see `Localization.r`) or explicitly
(see `Localization.r'`). -/
@[to_additive AddLocalization.r_eq_r'
"The additive congruence relation used to localize an `AddCommMonoid` at a submonoid can be
expressed equivalently as an infimum (see `AddLocalization.r`) or explicitly
(see `AddLocalization.r'`)."]
theorem r_eq_r' : r S = r' S :=
le_antisymm (sInf_le fun _ ↦ ⟨1, by simp⟩) <|
le_sInf fun b H ⟨p, q⟩ ⟨x, y⟩ ⟨t, ht⟩ ↦ by
rw [← one_mul (p, q), ← one_mul (x, y)]
refine b.trans (b.mul (H (t * y)) (b.refl _)) ?_
convert b.symm (b.mul (H (t * q)) (b.refl (x, y))) using 1
dsimp only [Prod.mk_mul_mk, Submonoid.coe_mul] at ht ⊢
simp_rw [mul_assoc, ht, mul_comm y q]
#align localization.r_eq_r' Localization.r_eq_r'
#align add_localization.r_eq_r' AddLocalization.r_eq_r'
variable {S}
@[to_additive AddLocalization.r_iff_exists]
theorem r_iff_exists {x y : M × S} : r S x y ↔ ∃ c : S, ↑c * (↑y.2 * x.1) = c * (x.2 * y.1) := by
rw [r_eq_r' S]; rfl
#align localization.r_iff_exists Localization.r_iff_exists
#align add_localization.r_iff_exists AddLocalization.r_iff_exists
end Localization
/-- The localization of a `CommMonoid` at one of its submonoids (as a quotient type). -/
@[to_additive AddLocalization
"The localization of an `AddCommMonoid` at one of its submonoids (as a quotient type)."]
def Localization := (Localization.r S).Quotient
#align localization Localization
#align add_localization AddLocalization
namespace Localization
@[to_additive]
instance inhabited : Inhabited (Localization S) := Con.Quotient.inhabited
#align localization.inhabited Localization.inhabited
#align add_localization.inhabited AddLocalization.inhabited
/-- Multiplication in a `Localization` is defined as `⟨a, b⟩ * ⟨c, d⟩ = ⟨a * c, b * d⟩`. -/
@[to_additive "Addition in an `AddLocalization` is defined as `⟨a, b⟩ + ⟨c, d⟩ = ⟨a + c, b + d⟩`.
Should not be confused with the ring localization counterpart `Localization.add`, which maps
`⟨a, b⟩ + ⟨c, d⟩` to `⟨d * a + b * c, b * d⟩`."]
protected irreducible_def mul : Localization S → Localization S → Localization S :=
(r S).commMonoid.mul
#align localization.mul Localization.mul
#align add_localization.add AddLocalization.add
@[to_additive]
instance : Mul (Localization S) := ⟨Localization.mul S⟩
/-- The identity element of a `Localization` is defined as `⟨1, 1⟩`. -/
@[to_additive "The identity element of an `AddLocalization` is defined as `⟨0, 0⟩`.
Should not be confused with the ring localization counterpart `Localization.zero`,
which is defined as `⟨0, 1⟩`."]
protected irreducible_def one : Localization S := (r S).commMonoid.one
#align localization.one Localization.one
#align add_localization.zero AddLocalization.zero
@[to_additive]
instance : One (Localization S) := ⟨Localization.one S⟩
/-- Exponentiation in a `Localization` is defined as `⟨a, b⟩ ^ n = ⟨a ^ n, b ^ n⟩`.
This is a separate `irreducible` def to ensure the elaborator doesn't waste its time
trying to unify some huge recursive definition with itself, but unfolded one step less.
-/
@[to_additive "Multiplication with a natural in an `AddLocalization` is defined as
`n • ⟨a, b⟩ = ⟨n • a, n • b⟩`.
This is a separate `irreducible` def to ensure the elaborator doesn't waste its time
trying to unify some huge recursive definition with itself, but unfolded one step less."]
protected irreducible_def npow : ℕ → Localization S → Localization S := (r S).commMonoid.npow
#align localization.npow Localization.npow
#align add_localization.nsmul AddLocalization.nsmul
@[to_additive]
instance commMonoid : CommMonoid (Localization S) where
mul := (· * ·)
one := 1
mul_assoc x y z := show (x.mul S y).mul S z = x.mul S (y.mul S z) by
rw [Localization.mul]; apply (r S).commMonoid.mul_assoc
mul_comm x y := show x.mul S y = y.mul S x by
rw [Localization.mul]; apply (r S).commMonoid.mul_comm
mul_one x := show x.mul S (.one S) = x by
rw [Localization.mul, Localization.one]; apply (r S).commMonoid.mul_one
one_mul x := show (Localization.one S).mul S x = x by
rw [Localization.mul, Localization.one]; apply (r S).commMonoid.one_mul
npow := Localization.npow S
npow_zero x := show Localization.npow S 0 x = .one S by
rw [Localization.npow, Localization.one]; apply (r S).commMonoid.npow_zero
npow_succ n x := show Localization.npow S n.succ x = (Localization.npow S n x).mul S x by
rw [Localization.npow, Localization.mul]; apply (r S).commMonoid.npow_succ
variable {S}
/-- Given a `CommMonoid` `M` and submonoid `S`, `mk` sends `x : M`, `y ∈ S` to the equivalence
class of `(x, y)` in the localization of `M` at `S`. -/
@[to_additive
"Given an `AddCommMonoid` `M` and submonoid `S`, `mk` sends `x : M`, `y ∈ S` to
the equivalence class of `(x, y)` in the localization of `M` at `S`."]
def mk (x : M) (y : S) : Localization S := (r S).mk' (x, y)
#align localization.mk Localization.mk
#align add_localization.mk AddLocalization.mk
@[to_additive]
theorem mk_eq_mk_iff {a c : M} {b d : S} : mk a b = mk c d ↔ r S ⟨a, b⟩ ⟨c, d⟩ := (r S).eq
#align localization.mk_eq_mk_iff Localization.mk_eq_mk_iff
#align add_localization.mk_eq_mk_iff AddLocalization.mk_eq_mk_iff
universe u
/-- Dependent recursion principle for `Localizations`: given elements `f a b : p (mk a b)`
for all `a b`, such that `r S (a, b) (c, d)` implies `f a b = f c d` (with the correct coercions),
then `f` is defined on the whole `Localization S`. -/
@[to_additive (attr := elab_as_elim)
"Dependent recursion principle for `AddLocalizations`: given elements `f a b : p (mk a b)`
for all `a b`, such that `r S (a, b) (c, d)` implies `f a b = f c d` (with the correct coercions),
then `f` is defined on the whole `AddLocalization S`."]
def rec {p : Localization S → Sort u} (f : ∀ (a : M) (b : S), p (mk a b))
(H : ∀ {a c : M} {b d : S} (h : r S (a, b) (c, d)),
(Eq.ndrec (f a b) (mk_eq_mk_iff.mpr h) : p (mk c d)) = f c d) (x) : p x :=
Quot.rec (fun y ↦ Eq.ndrec (f y.1 y.2) (by rfl)) (fun y z h ↦ by cases y; cases z; exact H h) x
#align localization.rec Localization.rec
#align add_localization.rec AddLocalization.rec
/-- Copy of `Quotient.recOnSubsingleton₂` for `Localization` -/
@[to_additive (attr := elab_as_elim) "Copy of `Quotient.recOnSubsingleton₂` for `AddLocalization`"]
def recOnSubsingleton₂ {r : Localization S → Localization S → Sort u}
[h : ∀ (a c : M) (b d : S), Subsingleton (r (mk a b) (mk c d))] (x y : Localization S)
(f : ∀ (a c : M) (b d : S), r (mk a b) (mk c d)) : r x y :=
@Quotient.recOnSubsingleton₂' _ _ _ _ r (Prod.rec fun _ _ => Prod.rec fun _ _ => h _ _ _ _) x y
(Prod.rec fun _ _ => Prod.rec fun _ _ => f _ _ _ _)
#align localization.rec_on_subsingleton₂ Localization.recOnSubsingleton₂
#align add_localization.rec_on_subsingleton₂ AddLocalization.recOnSubsingleton₂
@[to_additive]
theorem mk_mul (a c : M) (b d : S) : mk a b * mk c d = mk (a * c) (b * d) :=
show Localization.mul S _ _ = _ by rw [Localization.mul]; rfl
#align localization.mk_mul Localization.mk_mul
#align add_localization.mk_add AddLocalization.mk_add
@[to_additive]
theorem mk_one : mk 1 (1 : S) = 1 :=
show mk _ _ = .one S by rw [Localization.one]; rfl
#align localization.mk_one Localization.mk_one
#align add_localization.mk_zero AddLocalization.mk_zero
@[to_additive]
theorem mk_pow (n : ℕ) (a : M) (b : S) : mk a b ^ n = mk (a ^ n) (b ^ n) :=
show Localization.npow S _ _ = _ by rw [Localization.npow]; rfl
#align localization.mk_pow Localization.mk_pow
#align add_localization.mk_nsmul AddLocalization.mk_nsmul
-- Porting note: mathport translated `rec` to `ndrec` in the name of this lemma
@[to_additive (attr := simp)]
theorem ndrec_mk {p : Localization S → Sort u} (f : ∀ (a : M) (b : S), p (mk a b)) (H) (a : M)
(b : S) : (rec f H (mk a b) : p (mk a b)) = f a b := rfl
#align localization.rec_mk Localization.ndrec_mk
#align add_localization.rec_mk AddLocalization.ndrec_mk
/-- Non-dependent recursion principle for localizations: given elements `f a b : p`
for all `a b`, such that `r S (a, b) (c, d)` implies `f a b = f c d`,
then `f` is defined on the whole `Localization S`. -/
-- Porting note: the attribute `elab_as_elim` fails with `unexpected eliminator resulting type p`
-- @[to_additive (attr := elab_as_elim)
@[to_additive
"Non-dependent recursion principle for `AddLocalization`s: given elements `f a b : p`
for all `a b`, such that `r S (a, b) (c, d)` implies `f a b = f c d`,
then `f` is defined on the whole `Localization S`."]
def liftOn {p : Sort u} (x : Localization S) (f : M → S → p)
(H : ∀ {a c : M} {b d : S}, r S (a, b) (c, d) → f a b = f c d) : p :=
rec f (fun h ↦ (by simpa only [eq_rec_constant] using H h)) x
#align localization.lift_on Localization.liftOn
#align add_localization.lift_on AddLocalization.liftOn
@[to_additive]
theorem liftOn_mk {p : Sort u} (f : M → S → p) (H) (a : M) (b : S) :
liftOn (mk a b) f H = f a b := rfl
#align localization.lift_on_mk Localization.liftOn_mk
#align add_localization.lift_on_mk AddLocalization.liftOn_mk
@[to_additive (attr := elab_as_elim)]
theorem ind {p : Localization S → Prop} (H : ∀ y : M × S, p (mk y.1 y.2)) (x) : p x :=
rec (fun a b ↦ H (a, b)) (fun _ ↦ rfl) x
#align localization.ind Localization.ind
#align add_localization.ind AddLocalization.ind
@[to_additive (attr := elab_as_elim)]
theorem induction_on {p : Localization S → Prop} (x) (H : ∀ y : M × S, p (mk y.1 y.2)) : p x :=
ind H x
#align localization.induction_on Localization.induction_on
#align add_localization.induction_on AddLocalization.induction_on
/-- Non-dependent recursion principle for localizations: given elements `f x y : p`
for all `x` and `y`, such that `r S x x'` and `r S y y'` implies `f x y = f x' y'`,
then `f` is defined on the whole `Localization S`. -/
-- Porting note: the attribute `elab_as_elim` fails with `unexpected eliminator resulting type p`
-- @[to_additive (attr := elab_as_elim)
@[to_additive
"Non-dependent recursion principle for localizations: given elements `f x y : p`
for all `x` and `y`, such that `r S x x'` and `r S y y'` implies `f x y = f x' y'`,
then `f` is defined on the whole `Localization S`."]
def liftOn₂ {p : Sort u} (x y : Localization S) (f : M → S → M → S → p)
(H : ∀ {a a' b b' c c' d d'}, r S (a, b) (a', b') → r S (c, d) (c', d') →
f a b c d = f a' b' c' d') : p :=
liftOn x (fun a b ↦ liftOn y (f a b) fun hy ↦ H ((r S).refl _) hy) fun hx ↦
induction_on y fun ⟨_, _⟩ ↦ H hx ((r S).refl _)
#align localization.lift_on₂ Localization.liftOn₂
#align add_localization.lift_on₂ AddLocalization.liftOn₂
@[to_additive]
theorem liftOn₂_mk {p : Sort*} (f : M → S → M → S → p) (H) (a c : M) (b d : S) :
liftOn₂ (mk a b) (mk c d) f H = f a b c d := rfl
#align localization.lift_on₂_mk Localization.liftOn₂_mk
#align add_localization.lift_on₂_mk AddLocalization.liftOn₂_mk
@[to_additive (attr := elab_as_elim)]
theorem induction_on₂ {p : Localization S → Localization S → Prop} (x y)
(H : ∀ x y : M × S, p (mk x.1 x.2) (mk y.1 y.2)) : p x y :=
induction_on x fun x ↦ induction_on y <| H x
#align localization.induction_on₂ Localization.induction_on₂
#align add_localization.induction_on₂ AddLocalization.induction_on₂
@[to_additive (attr := elab_as_elim)]
theorem induction_on₃ {p : Localization S → Localization S → Localization S → Prop} (x y z)
(H : ∀ x y z : M × S, p (mk x.1 x.2) (mk y.1 y.2) (mk z.1 z.2)) : p x y z :=
induction_on₂ x y fun x y ↦ induction_on z <| H x y
#align localization.induction_on₃ Localization.induction_on₃
#align add_localization.induction_on₃ AddLocalization.induction_on₃
@[to_additive]
theorem one_rel (y : S) : r S 1 (y, y) := fun _ hb ↦ hb y
#align localization.one_rel Localization.one_rel
#align add_localization.zero_rel AddLocalization.zero_rel
@[to_additive]
theorem r_of_eq {x y : M × S} (h : ↑y.2 * x.1 = ↑x.2 * y.1) : r S x y :=
r_iff_exists.2 ⟨1, by rw [h]⟩
#align localization.r_of_eq Localization.r_of_eq
#align add_localization.r_of_eq AddLocalization.r_of_eq
@[to_additive]
theorem mk_self (a : S) : mk (a : M) a = 1 := by
symm
rw [← mk_one, mk_eq_mk_iff]
exact one_rel a
#align localization.mk_self Localization.mk_self
#align add_localization.mk_self AddLocalization.mk_self
section Scalar
variable {R R₁ R₂ : Type*}
/-- Scalar multiplication in a monoid localization is defined as `c • ⟨a, b⟩ = ⟨c • a, b⟩`. -/
protected irreducible_def smul [SMul R M] [IsScalarTower R M M] (c : R) (z : Localization S) :
Localization S :=
Localization.liftOn z (fun a b ↦ mk (c • a) b)
(fun {a a' b b'} h ↦ mk_eq_mk_iff.2 (by
let ⟨b, hb⟩ := b
let ⟨b', hb'⟩ := b'
rw [r_eq_r'] at h ⊢
let ⟨t, ht⟩ := h
use t
dsimp only [Subtype.coe_mk] at ht ⊢
-- TODO: this definition should take `SMulCommClass R M M` instead of `IsScalarTower R M M` if
-- we ever want to generalize to the non-commutative case.
haveI : SMulCommClass R M M :=
⟨fun r m₁ m₂ ↦ by simp_rw [smul_eq_mul, mul_comm m₁, smul_mul_assoc]⟩
simp only [mul_smul_comm, ht]))
#align localization.smul Localization.smul
instance instSMulLocalization [SMul R M] [IsScalarTower R M M] : SMul R (Localization S) where
smul := Localization.smul
theorem smul_mk [SMul R M] [IsScalarTower R M M] (c : R) (a b) :
c • (mk a b : Localization S) = mk (c • a) b := by
simp only [HSMul.hSMul, instHSMul, SMul.smul, instSMulLocalization, Localization.smul]
show liftOn (mk a b) (fun a b => mk (c • a) b) _ = _
exact liftOn_mk (fun a b => mk (c • a) b) _ a b
#align localization.smul_mk Localization.smul_mk
instance [SMul R₁ M] [SMul R₂ M] [IsScalarTower R₁ M M] [IsScalarTower R₂ M M]
[SMulCommClass R₁ R₂ M] : SMulCommClass R₁ R₂ (Localization S) where
smul_comm s t := Localization.ind <| Prod.rec fun r x ↦ by simp only [smul_mk, smul_comm s t r]
instance [SMul R₁ M] [SMul R₂ M] [IsScalarTower R₁ M M] [IsScalarTower R₂ M M] [SMul R₁ R₂]
[IsScalarTower R₁ R₂ M] : IsScalarTower R₁ R₂ (Localization S) where
smul_assoc s t := Localization.ind <| Prod.rec fun r x ↦ by simp only [smul_mk, smul_assoc s t r]
instance smulCommClass_right {R : Type*} [SMul R M] [IsScalarTower R M M] :
SMulCommClass R (Localization S) (Localization S) where
smul_comm s :=
Localization.ind <|
Prod.rec fun r₁ x₁ ↦
Localization.ind <|
Prod.rec fun r₂ x₂ ↦ by
simp only [smul_mk, smul_eq_mul, mk_mul, mul_comm r₁, smul_mul_assoc]
#align localization.smul_comm_class_right Localization.smulCommClass_right
instance isScalarTower_right {R : Type*} [SMul R M] [IsScalarTower R M M] :
IsScalarTower R (Localization S) (Localization S) where
smul_assoc s :=
Localization.ind <|
Prod.rec fun r₁ x₁ ↦
Localization.ind <|
Prod.rec fun r₂ x₂ ↦ by simp only [smul_mk, smul_eq_mul, mk_mul, smul_mul_assoc]
#align localization.is_scalar_tower_right Localization.isScalarTower_right
instance [SMul R M] [SMul Rᵐᵒᵖ M] [IsScalarTower R M M] [IsScalarTower Rᵐᵒᵖ M M]
[IsCentralScalar R M] : IsCentralScalar R (Localization S) where
op_smul_eq_smul s :=
Localization.ind <| Prod.rec fun r x ↦ by simp only [smul_mk, op_smul_eq_smul]
instance [Monoid R] [MulAction R M] [IsScalarTower R M M] : MulAction R (Localization S) where
one_smul :=
Localization.ind <|
Prod.rec <| by
intros
simp only [Localization.smul_mk, one_smul]
mul_smul s₁ s₂ :=
Localization.ind <|
Prod.rec <| by
intros
simp only [Localization.smul_mk, mul_smul]
instance [Monoid R] [MulDistribMulAction R M] [IsScalarTower R M M] :
MulDistribMulAction R (Localization S) where
smul_one s := by simp only [← Localization.mk_one, Localization.smul_mk, smul_one]
smul_mul s x y :=
Localization.induction_on₂ x y <|
Prod.rec fun r₁ x₁ ↦
Prod.rec fun r₂ x₂ ↦ by simp only [Localization.smul_mk, Localization.mk_mul, smul_mul']
end Scalar
end Localization
variable {S N}
namespace MonoidHom
/-- Makes a localization map from a `CommMonoid` hom satisfying the characteristic predicate. -/
@[to_additive
"Makes a localization map from an `AddCommMonoid` hom satisfying the characteristic predicate."]
def toLocalizationMap (f : M →* N) (H1 : ∀ y : S, IsUnit (f y))
(H2 : ∀ z, ∃ x : M × S, z * f x.2 = f x.1) (H3 : ∀ x y, f x = f y → ∃ c : S, ↑c * x = ↑c * y) :
Submonoid.LocalizationMap S N :=
{ f with
map_units' := H1
surj' := H2
exists_of_eq := H3 }
#align monoid_hom.to_localization_map MonoidHom.toLocalizationMap
#align add_monoid_hom.to_localization_map AddMonoidHom.toLocalizationMap
end MonoidHom
namespace Submonoid
namespace LocalizationMap
/-- Short for `toMonoidHom`; used to apply a localization map as a function. -/
@[to_additive "Short for `toAddMonoidHom`; used to apply a localization map as a function."]
abbrev toMap (f : LocalizationMap S N) := f.toMonoidHom
#align submonoid.localization_map.to_map Submonoid.LocalizationMap.toMap
#align add_submonoid.localization_map.to_map AddSubmonoid.LocalizationMap.toMap
@[to_additive (attr := ext)]
theorem ext {f g : LocalizationMap S N} (h : ∀ x, f.toMap x = g.toMap x) : f = g := by
rcases f with ⟨⟨⟩⟩
rcases g with ⟨⟨⟩⟩
simp only [mk.injEq, MonoidHom.mk.injEq]
exact OneHom.ext h
#align submonoid.localization_map.ext Submonoid.LocalizationMap.ext
#align add_submonoid.localization_map.ext AddSubmonoid.LocalizationMap.ext
@[to_additive]
theorem ext_iff {f g : LocalizationMap S N} : f = g ↔ ∀ x, f.toMap x = g.toMap x :=
⟨fun h _ ↦ h ▸ rfl, ext⟩
#align submonoid.localization_map.ext_iff Submonoid.LocalizationMap.ext_iff
#align add_submonoid.localization_map.ext_iff AddSubmonoid.LocalizationMap.ext_iff
@[to_additive]
theorem toMap_injective : Function.Injective (@LocalizationMap.toMap _ _ S N _) :=
fun _ _ h ↦ ext <| DFunLike.ext_iff.1 h
#align submonoid.localization_map.to_map_injective Submonoid.LocalizationMap.toMap_injective
#align add_submonoid.localization_map.to_map_injective AddSubmonoid.LocalizationMap.toMap_injective
@[to_additive]
theorem map_units (f : LocalizationMap S N) (y : S) : IsUnit (f.toMap y) :=
f.2 y
#align submonoid.localization_map.map_units Submonoid.LocalizationMap.map_units
#align add_submonoid.localization_map.map_add_units AddSubmonoid.LocalizationMap.map_addUnits
@[to_additive]
theorem surj (f : LocalizationMap S N) (z : N) : ∃ x : M × S, z * f.toMap x.2 = f.toMap x.1 :=
f.3 z
#align submonoid.localization_map.surj Submonoid.LocalizationMap.surj
#align add_submonoid.localization_map.surj AddSubmonoid.LocalizationMap.surj
/-- Given a localization map `f : M →* N`, and `z w : N`, there exist `z' w' : M` and `d : S`
such that `f z' / f d = z` and `f w' / f d = w`. -/
@[to_additive
"Given a localization map `f : M →+ N`, and `z w : N`, there exist `z' w' : M` and `d : S`
such that `f z' - f d = z` and `f w' - f d = w`."]
theorem surj₂ (f : LocalizationMap S N) (z w : N) : ∃ z' w' : M, ∃ d : S,
(z * f.toMap d = f.toMap z') ∧ (w * f.toMap d = f.toMap w') := by
let ⟨a, ha⟩ := surj f z
let ⟨b, hb⟩ := surj f w
refine ⟨a.1 * b.2, a.2 * b.1, a.2 * b.2, ?_, ?_⟩
· simp_rw [mul_def, map_mul, ← ha]
exact (mul_assoc z _ _).symm
· simp_rw [mul_def, map_mul, ← hb]
exact mul_left_comm w _ _
@[to_additive]
theorem eq_iff_exists (f : LocalizationMap S N) {x y} :
f.toMap x = f.toMap y ↔ ∃ c : S, ↑c * x = c * y := Iff.intro (f.4 x y)
fun ⟨c, h⟩ ↦ by
replace h := congr_arg f.toMap h
rw [map_mul, map_mul] at h
exact (f.map_units c).mul_right_inj.mp h
#align submonoid.localization_map.eq_iff_exists Submonoid.LocalizationMap.eq_iff_exists
#align add_submonoid.localization_map.eq_iff_exists AddSubmonoid.LocalizationMap.eq_iff_exists
/-- Given a localization map `f : M →* N`, a section function sending `z : N` to some
`(x, y) : M × S` such that `f x * (f y)⁻¹ = z`. -/
@[to_additive
"Given a localization map `f : M →+ N`, a section function sending `z : N`
to some `(x, y) : M × S` such that `f x - f y = z`."]
noncomputable def sec (f : LocalizationMap S N) (z : N) : M × S := Classical.choose <| f.surj z
#align submonoid.localization_map.sec Submonoid.LocalizationMap.sec
#align add_submonoid.localization_map.sec AddSubmonoid.LocalizationMap.sec
@[to_additive]
theorem sec_spec {f : LocalizationMap S N} (z : N) :
z * f.toMap (f.sec z).2 = f.toMap (f.sec z).1 := Classical.choose_spec <| f.surj z
#align submonoid.localization_map.sec_spec Submonoid.LocalizationMap.sec_spec
#align add_submonoid.localization_map.sec_spec AddSubmonoid.LocalizationMap.sec_spec
@[to_additive]
theorem sec_spec' {f : LocalizationMap S N} (z : N) :
f.toMap (f.sec z).1 = f.toMap (f.sec z).2 * z := by rw [mul_comm, sec_spec]
#align submonoid.localization_map.sec_spec' Submonoid.LocalizationMap.sec_spec'
#align add_submonoid.localization_map.sec_spec' AddSubmonoid.LocalizationMap.sec_spec'
/-- Given a MonoidHom `f : M →* N` and Submonoid `S ⊆ M` such that `f(S) ⊆ Nˣ`, for all
`w, z : N` and `y ∈ S`, we have `w * (f y)⁻¹ = z ↔ w = f y * z`. -/
@[to_additive
"Given an AddMonoidHom `f : M →+ N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ AddUnits N`, for all `w, z : N` and `y ∈ S`, we have `w - f y = z ↔ w = f y + z`."]
theorem mul_inv_left {f : M →* N} (h : ∀ y : S, IsUnit (f y)) (y : S) (w z : N) :
w * (IsUnit.liftRight (f.restrict S) h y)⁻¹ = z ↔ w = f y * z := by
rw [mul_comm]
exact Units.inv_mul_eq_iff_eq_mul (IsUnit.liftRight (f.restrict S) h y)
#align submonoid.localization_map.mul_inv_left Submonoid.LocalizationMap.mul_inv_left
#align add_submonoid.localization_map.add_neg_left AddSubmonoid.LocalizationMap.add_neg_left
/-- Given a MonoidHom `f : M →* N` and Submonoid `S ⊆ M` such that `f(S) ⊆ Nˣ`, for all
`w, z : N` and `y ∈ S`, we have `z = w * (f y)⁻¹ ↔ z * f y = w`. -/
@[to_additive
"Given an AddMonoidHom `f : M →+ N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ AddUnits N`, for all `w, z : N` and `y ∈ S`, we have `z = w - f y ↔ z + f y = w`."]
theorem mul_inv_right {f : M →* N} (h : ∀ y : S, IsUnit (f y)) (y : S) (w z : N) :
z = w * (IsUnit.liftRight (f.restrict S) h y)⁻¹ ↔ z * f y = w := by
rw [eq_comm, mul_inv_left h, mul_comm, eq_comm]
#align submonoid.localization_map.mul_inv_right Submonoid.LocalizationMap.mul_inv_right
#align add_submonoid.localization_map.add_neg_right AddSubmonoid.LocalizationMap.add_neg_right
/-- Given a MonoidHom `f : M →* N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ Nˣ`, for all `x₁ x₂ : M` and `y₁, y₂ ∈ S`, we have
`f x₁ * (f y₁)⁻¹ = f x₂ * (f y₂)⁻¹ ↔ f (x₁ * y₂) = f (x₂ * y₁)`. -/
@[to_additive (attr := simp)
"Given an AddMonoidHom `f : M →+ N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ AddUnits N`, for all `x₁ x₂ : M` and `y₁, y₂ ∈ S`, we have
`f x₁ - f y₁ = f x₂ - f y₂ ↔ f (x₁ + y₂) = f (x₂ + y₁)`."]
theorem mul_inv {f : M →* N} (h : ∀ y : S, IsUnit (f y)) {x₁ x₂} {y₁ y₂ : S} :
f x₁ * (IsUnit.liftRight (f.restrict S) h y₁)⁻¹ =
f x₂ * (IsUnit.liftRight (f.restrict S) h y₂)⁻¹ ↔
f (x₁ * y₂) = f (x₂ * y₁) := by
rw [mul_inv_right h, mul_assoc, mul_comm _ (f y₂), ← mul_assoc, mul_inv_left h, mul_comm x₂,
f.map_mul, f.map_mul]
#align submonoid.localization_map.mul_inv Submonoid.LocalizationMap.mul_inv
#align add_submonoid.localization_map.add_neg AddSubmonoid.LocalizationMap.add_neg
/-- Given a MonoidHom `f : M →* N` and Submonoid `S ⊆ M` such that `f(S) ⊆ Nˣ`, for all
`y, z ∈ S`, we have `(f y)⁻¹ = (f z)⁻¹ → f y = f z`. -/
@[to_additive
"Given an AddMonoidHom `f : M →+ N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ AddUnits N`, for all `y, z ∈ S`, we have `- (f y) = - (f z) → f y = f z`."]
theorem inv_inj {f : M →* N} (hf : ∀ y : S, IsUnit (f y)) {y z : S}
(h : (IsUnit.liftRight (f.restrict S) hf y)⁻¹ = (IsUnit.liftRight (f.restrict S) hf z)⁻¹) :
f y = f z := by
rw [← mul_one (f y), eq_comm, ← mul_inv_left hf y (f z) 1, h]
exact Units.inv_mul (IsUnit.liftRight (f.restrict S) hf z)⁻¹
#align submonoid.localization_map.inv_inj Submonoid.LocalizationMap.inv_inj
#align add_submonoid.localization_map.neg_inj AddSubmonoid.LocalizationMap.neg_inj
/-- Given a MonoidHom `f : M →* N` and Submonoid `S ⊆ M` such that `f(S) ⊆ Nˣ`, for all
`y ∈ S`, `(f y)⁻¹` is unique. -/
@[to_additive
"Given an AddMonoidHom `f : M →+ N` and Submonoid `S ⊆ M` such that
`f(S) ⊆ AddUnits N`, for all `y ∈ S`, `- (f y)` is unique."]
theorem inv_unique {f : M →* N} (h : ∀ y : S, IsUnit (f y)) {y : S} {z : N} (H : f y * z = 1) :
(IsUnit.liftRight (f.restrict S) h y)⁻¹ = z := by
rw [← one_mul _⁻¹, Units.val_mul, mul_inv_left]
exact H.symm
#align submonoid.localization_map.inv_unique Submonoid.LocalizationMap.inv_unique
#align add_submonoid.localization_map.neg_unique AddSubmonoid.LocalizationMap.neg_unique
variable (f : LocalizationMap S N)
@[to_additive]
theorem map_right_cancel {x y} {c : S} (h : f.toMap (c * x) = f.toMap (c * y)) :
f.toMap x = f.toMap y := by
rw [f.toMap.map_mul, f.toMap.map_mul] at h
let ⟨u, hu⟩ := f.map_units c
rw [← hu] at h
exact (Units.mul_right_inj u).1 h
#align submonoid.localization_map.map_right_cancel Submonoid.LocalizationMap.map_right_cancel
#align add_submonoid.localization_map.map_right_cancel AddSubmonoid.LocalizationMap.map_right_cancel
@[to_additive]
theorem map_left_cancel {x y} {c : S} (h : f.toMap (x * c) = f.toMap (y * c)) :
f.toMap x = f.toMap y :=
f.map_right_cancel <| by rw [mul_comm _ x, mul_comm _ y, h]
#align submonoid.localization_map.map_left_cancel Submonoid.LocalizationMap.map_left_cancel
#align add_submonoid.localization_map.map_left_cancel AddSubmonoid.LocalizationMap.map_left_cancel
/-- Given a localization map `f : M →* N`, the surjection sending `(x, y) : M × S` to
`f x * (f y)⁻¹`. -/
@[to_additive
"Given a localization map `f : M →+ N`, the surjection sending `(x, y) : M × S`
to `f x - f y`."]
noncomputable def mk' (f : LocalizationMap S N) (x : M) (y : S) : N :=
f.toMap x * ↑(IsUnit.liftRight (f.toMap.restrict S) f.map_units y)⁻¹
#align submonoid.localization_map.mk' Submonoid.LocalizationMap.mk'
#align add_submonoid.localization_map.mk' AddSubmonoid.LocalizationMap.mk'
@[to_additive]
theorem mk'_mul (x₁ x₂ : M) (y₁ y₂ : S) : f.mk' (x₁ * x₂) (y₁ * y₂) = f.mk' x₁ y₁ * f.mk' x₂ y₂ :=
(mul_inv_left f.map_units _ _ _).2 <|
show _ = _ * (_ * _ * (_ * _)) by
rw [← mul_assoc, ← mul_assoc, mul_inv_right f.map_units, mul_assoc, mul_assoc,
mul_comm _ (f.toMap x₂), ← mul_assoc, ← mul_assoc, mul_inv_right f.map_units,
Submonoid.coe_mul, f.toMap.map_mul, f.toMap.map_mul]
ac_rfl
#align submonoid.localization_map.mk'_mul Submonoid.LocalizationMap.mk'_mul
#align add_submonoid.localization_map.mk'_add AddSubmonoid.LocalizationMap.mk'_add
@[to_additive]
theorem mk'_one (x) : f.mk' x (1 : S) = f.toMap x := by
rw [mk', MonoidHom.map_one]
exact mul_one _
#align submonoid.localization_map.mk'_one Submonoid.LocalizationMap.mk'_one
#align add_submonoid.localization_map.mk'_zero AddSubmonoid.LocalizationMap.mk'_zero
/-- Given a localization map `f : M →* N` for a submonoid `S ⊆ M`, for all `z : N` we have that if
`x : M, y ∈ S` are such that `z * f y = f x`, then `f x * (f y)⁻¹ = z`. -/
@[to_additive (attr := simp)
"Given a localization map `f : M →+ N` for a Submonoid `S ⊆ M`, for all `z : N`
we have that if `x : M, y ∈ S` are such that `z + f y = f x`, then `f x - f y = z`."]
theorem mk'_sec (z : N) : f.mk' (f.sec z).1 (f.sec z).2 = z :=
show _ * _ = _ by rw [← sec_spec, mul_inv_left, mul_comm]
#align submonoid.localization_map.mk'_sec Submonoid.LocalizationMap.mk'_sec
#align add_submonoid.localization_map.mk'_sec AddSubmonoid.LocalizationMap.mk'_sec
@[to_additive]
theorem mk'_surjective (z : N) : ∃ (x : _) (y : S), f.mk' x y = z :=
⟨(f.sec z).1, (f.sec z).2, f.mk'_sec z⟩
#align submonoid.localization_map.mk'_surjective Submonoid.LocalizationMap.mk'_surjective
#align add_submonoid.localization_map.mk'_surjective AddSubmonoid.LocalizationMap.mk'_surjective
@[to_additive]
theorem mk'_spec (x) (y : S) : f.mk' x y * f.toMap y = f.toMap x :=
show _ * _ * _ = _ by rw [mul_assoc, mul_comm _ (f.toMap y), ← mul_assoc, mul_inv_left, mul_comm]
#align submonoid.localization_map.mk'_spec Submonoid.LocalizationMap.mk'_spec
#align add_submonoid.localization_map.mk'_spec AddSubmonoid.LocalizationMap.mk'_spec
@[to_additive]
theorem mk'_spec' (x) (y : S) : f.toMap y * f.mk' x y = f.toMap x := by rw [mul_comm, mk'_spec]
#align submonoid.localization_map.mk'_spec' Submonoid.LocalizationMap.mk'_spec'
#align add_submonoid.localization_map.mk'_spec' AddSubmonoid.LocalizationMap.mk'_spec'
@[to_additive]
theorem eq_mk'_iff_mul_eq {x} {y : S} {z} : z = f.mk' x y ↔ z * f.toMap y = f.toMap x :=
⟨fun H ↦ by rw [H, mk'_spec], fun H ↦ by erw [mul_inv_right, H]⟩
#align submonoid.localization_map.eq_mk'_iff_mul_eq Submonoid.LocalizationMap.eq_mk'_iff_mul_eq
#align add_submonoid.localization_map.eq_mk'_iff_add_eq AddSubmonoid.LocalizationMap.eq_mk'_iff_add_eq
@[to_additive]
theorem mk'_eq_iff_eq_mul {x} {y : S} {z} : f.mk' x y = z ↔ f.toMap x = z * f.toMap y := by
rw [eq_comm, eq_mk'_iff_mul_eq, eq_comm]
#align submonoid.localization_map.mk'_eq_iff_eq_mul Submonoid.LocalizationMap.mk'_eq_iff_eq_mul
#align add_submonoid.localization_map.mk'_eq_iff_eq_add AddSubmonoid.LocalizationMap.mk'_eq_iff_eq_add
@[to_additive]
theorem mk'_eq_iff_eq {x₁ x₂} {y₁ y₂ : S} :
f.mk' x₁ y₁ = f.mk' x₂ y₂ ↔ f.toMap (y₂ * x₁) = f.toMap (y₁ * x₂) :=
⟨fun H ↦ by
rw [f.toMap.map_mul, f.toMap.map_mul, f.mk'_eq_iff_eq_mul.1 H,← mul_assoc, mk'_spec',
mul_comm ((toMap f) x₂) _],
fun H ↦ by
rw [mk'_eq_iff_eq_mul, mk', mul_assoc, mul_comm _ (f.toMap y₁), ← mul_assoc, ←
f.toMap.map_mul, mul_comm x₂, ← H, ← mul_comm x₁, f.toMap.map_mul,
mul_inv_right f.map_units]⟩
#align submonoid.localization_map.mk'_eq_iff_eq Submonoid.LocalizationMap.mk'_eq_iff_eq
#align add_submonoid.localization_map.mk'_eq_iff_eq AddSubmonoid.LocalizationMap.mk'_eq_iff_eq
@[to_additive]
theorem mk'_eq_iff_eq' {x₁ x₂} {y₁ y₂ : S} :
f.mk' x₁ y₁ = f.mk' x₂ y₂ ↔ f.toMap (x₁ * y₂) = f.toMap (x₂ * y₁) := by
simp only [f.mk'_eq_iff_eq, mul_comm]
#align submonoid.localization_map.mk'_eq_iff_eq' Submonoid.LocalizationMap.mk'_eq_iff_eq'
#align add_submonoid.localization_map.mk'_eq_iff_eq' AddSubmonoid.LocalizationMap.mk'_eq_iff_eq'
@[to_additive]
protected theorem eq {a₁ b₁} {a₂ b₂ : S} :
f.mk' a₁ a₂ = f.mk' b₁ b₂ ↔ ∃ c : S, ↑c * (↑b₂ * a₁) = c * (a₂ * b₁) :=
f.mk'_eq_iff_eq.trans <| f.eq_iff_exists
#align submonoid.localization_map.eq Submonoid.LocalizationMap.eq
#align add_submonoid.localization_map.eq AddSubmonoid.LocalizationMap.eq
@[to_additive]
protected theorem eq' {a₁ b₁} {a₂ b₂ : S} :
f.mk' a₁ a₂ = f.mk' b₁ b₂ ↔ Localization.r S (a₁, a₂) (b₁, b₂) := by
rw [f.eq, Localization.r_iff_exists]
#align submonoid.localization_map.eq' Submonoid.LocalizationMap.eq'
#align add_submonoid.localization_map.eq' AddSubmonoid.LocalizationMap.eq'
@[to_additive]
theorem eq_iff_eq (g : LocalizationMap S P) {x y} : f.toMap x = f.toMap y ↔ g.toMap x = g.toMap y :=
f.eq_iff_exists.trans g.eq_iff_exists.symm
#align submonoid.localization_map.eq_iff_eq Submonoid.LocalizationMap.eq_iff_eq
#align add_submonoid.localization_map.eq_iff_eq AddSubmonoid.LocalizationMap.eq_iff_eq
@[to_additive]
theorem mk'_eq_iff_mk'_eq (g : LocalizationMap S P) {x₁ x₂} {y₁ y₂ : S} :
f.mk' x₁ y₁ = f.mk' x₂ y₂ ↔ g.mk' x₁ y₁ = g.mk' x₂ y₂ :=
f.eq'.trans g.eq'.symm
#align submonoid.localization_map.mk'_eq_iff_mk'_eq Submonoid.LocalizationMap.mk'_eq_iff_mk'_eq
#align add_submonoid.localization_map.mk'_eq_iff_mk'_eq AddSubmonoid.LocalizationMap.mk'_eq_iff_mk'_eq
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M`, for all `x₁ : M` and `y₁ ∈ S`,
if `x₂ : M, y₂ ∈ S` are such that `f x₁ * (f y₁)⁻¹ * f y₂ = f x₂`, then there exists `c ∈ S`
such that `x₁ * y₂ * c = x₂ * y₁ * c`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M`, for all `x₁ : M`
and `y₁ ∈ S`, if `x₂ : M, y₂ ∈ S` are such that `(f x₁ - f y₁) + f y₂ = f x₂`, then there exists
`c ∈ S` such that `x₁ + y₂ + c = x₂ + y₁ + c`."]
theorem exists_of_sec_mk' (x) (y : S) :
∃ c : S, ↑c * (↑(f.sec <| f.mk' x y).2 * x) = c * (y * (f.sec <| f.mk' x y).1) :=
f.eq_iff_exists.1 <| f.mk'_eq_iff_eq.1 <| (mk'_sec _ _).symm
#align submonoid.localization_map.exists_of_sec_mk' Submonoid.LocalizationMap.exists_of_sec_mk'
#align add_submonoid.localization_map.exists_of_sec_mk' AddSubmonoid.LocalizationMap.exists_of_sec_mk'
@[to_additive]
theorem mk'_eq_of_eq {a₁ b₁ : M} {a₂ b₂ : S} (H : ↑a₂ * b₁ = ↑b₂ * a₁) :
f.mk' a₁ a₂ = f.mk' b₁ b₂ :=
f.mk'_eq_iff_eq.2 <| H ▸ rfl
#align submonoid.localization_map.mk'_eq_of_eq Submonoid.LocalizationMap.mk'_eq_of_eq
#align add_submonoid.localization_map.mk'_eq_of_eq AddSubmonoid.LocalizationMap.mk'_eq_of_eq
@[to_additive]
theorem mk'_eq_of_eq' {a₁ b₁ : M} {a₂ b₂ : S} (H : b₁ * ↑a₂ = a₁ * ↑b₂) :
f.mk' a₁ a₂ = f.mk' b₁ b₂ :=
f.mk'_eq_of_eq <| by simpa only [mul_comm] using H
#align submonoid.localization_map.mk'_eq_of_eq' Submonoid.LocalizationMap.mk'_eq_of_eq'
#align add_submonoid.localization_map.mk'_eq_of_eq' AddSubmonoid.LocalizationMap.mk'_eq_of_eq'
@[to_additive]
theorem mk'_cancel (a : M) (b c : S) :
f.mk' (a * c) (b * c) = f.mk' a b :=
mk'_eq_of_eq' f (by rw [Submonoid.coe_mul, mul_comm (b:M), mul_assoc])
@[to_additive]
theorem mk'_eq_of_same {a b} {d : S} :
f.mk' a d = f.mk' b d ↔ ∃ c : S, c * a = c * b := by
rw [mk'_eq_iff_eq', map_mul, map_mul, ← eq_iff_exists f]
exact (map_units f d).mul_left_inj
@[to_additive (attr := simp)]
theorem mk'_self' (y : S) : f.mk' (y : M) y = 1 :=
show _ * _ = _ by rw [mul_inv_left, mul_one]
#align submonoid.localization_map.mk'_self' Submonoid.LocalizationMap.mk'_self'
#align add_submonoid.localization_map.mk'_self' AddSubmonoid.LocalizationMap.mk'_self'
@[to_additive (attr := simp)]
theorem mk'_self (x) (H : x ∈ S) : f.mk' x ⟨x, H⟩ = 1 := mk'_self' f ⟨x, H⟩
#align submonoid.localization_map.mk'_self Submonoid.LocalizationMap.mk'_self
#align add_submonoid.localization_map.mk'_self AddSubmonoid.LocalizationMap.mk'_self
@[to_additive]
theorem mul_mk'_eq_mk'_of_mul (x₁ x₂) (y : S) : f.toMap x₁ * f.mk' x₂ y = f.mk' (x₁ * x₂) y := by
rw [← mk'_one, ← mk'_mul, one_mul]
#align submonoid.localization_map.mul_mk'_eq_mk'_of_mul Submonoid.LocalizationMap.mul_mk'_eq_mk'_of_mul
#align add_submonoid.localization_map.add_mk'_eq_mk'_of_add AddSubmonoid.LocalizationMap.add_mk'_eq_mk'_of_add
@[to_additive]
theorem mk'_mul_eq_mk'_of_mul (x₁ x₂) (y : S) : f.mk' x₂ y * f.toMap x₁ = f.mk' (x₁ * x₂) y := by
rw [mul_comm, mul_mk'_eq_mk'_of_mul]
#align submonoid.localization_map.mk'_mul_eq_mk'_of_mul Submonoid.LocalizationMap.mk'_mul_eq_mk'_of_mul
#align add_submonoid.localization_map.mk'_add_eq_mk'_of_add AddSubmonoid.LocalizationMap.mk'_add_eq_mk'_of_add
@[to_additive]
theorem mul_mk'_one_eq_mk' (x) (y : S) : f.toMap x * f.mk' 1 y = f.mk' x y := by
rw [mul_mk'_eq_mk'_of_mul, mul_one]
#align submonoid.localization_map.mul_mk'_one_eq_mk' Submonoid.LocalizationMap.mul_mk'_one_eq_mk'
#align add_submonoid.localization_map.add_mk'_zero_eq_mk' AddSubmonoid.LocalizationMap.add_mk'_zero_eq_mk'
@[to_additive (attr := simp)]
theorem mk'_mul_cancel_right (x : M) (y : S) : f.mk' (x * y) y = f.toMap x := by
rw [← mul_mk'_one_eq_mk', f.toMap.map_mul, mul_assoc, mul_mk'_one_eq_mk', mk'_self', mul_one]
#align submonoid.localization_map.mk'_mul_cancel_right Submonoid.LocalizationMap.mk'_mul_cancel_right
#align add_submonoid.localization_map.mk'_add_cancel_right AddSubmonoid.LocalizationMap.mk'_add_cancel_right
@[to_additive]
theorem mk'_mul_cancel_left (x) (y : S) : f.mk' ((y : M) * x) y = f.toMap x := by
rw [mul_comm, mk'_mul_cancel_right]
#align submonoid.localization_map.mk'_mul_cancel_left Submonoid.LocalizationMap.mk'_mul_cancel_left
#align add_submonoid.localization_map.mk'_add_cancel_left AddSubmonoid.LocalizationMap.mk'_add_cancel_left
@[to_additive]
theorem isUnit_comp (j : N →* P) (y : S) : IsUnit (j.comp f.toMap y) :=
⟨Units.map j <| IsUnit.liftRight (f.toMap.restrict S) f.map_units y,
show j _ = j _ from congr_arg j <| IsUnit.coe_liftRight (f.toMap.restrict S) f.map_units _⟩
#align submonoid.localization_map.is_unit_comp Submonoid.LocalizationMap.isUnit_comp
#align add_submonoid.localization_map.is_add_unit_comp AddSubmonoid.LocalizationMap.isAddUnit_comp
variable {g : M →* P}
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M` and a map of `CommMonoid`s
`g : M →* P` such that `g(S) ⊆ Units P`, `f x = f y → g x = g y` for all `x y : M`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M` and a map of
`AddCommMonoid`s `g : M →+ P` such that `g(S) ⊆ AddUnits P`, `f x = f y → g x = g y`
for all `x y : M`."]
theorem eq_of_eq (hg : ∀ y : S, IsUnit (g y)) {x y} (h : f.toMap x = f.toMap y) : g x = g y := by
obtain ⟨c, hc⟩ := f.eq_iff_exists.1 h
rw [← one_mul (g x), ← IsUnit.liftRight_inv_mul (g.restrict S) hg c]
show _ * g c * _ = _
rw [mul_assoc, ← g.map_mul, hc, mul_comm, mul_inv_left hg, g.map_mul]
#align submonoid.localization_map.eq_of_eq Submonoid.LocalizationMap.eq_of_eq
#align add_submonoid.localization_map.eq_of_eq AddSubmonoid.LocalizationMap.eq_of_eq
/-- Given `CommMonoid`s `M, P`, Localization maps `f : M →* N, k : P →* Q` for Submonoids
`S, T` respectively, and `g : M →* P` such that `g(S) ⊆ T`, `f x = f y` implies
`k (g x) = k (g y)`. -/
@[to_additive
"Given `AddCommMonoid`s `M, P`, Localization maps `f : M →+ N, k : P →+ Q` for Submonoids
`S, T` respectively, and `g : M →+ P` such that `g(S) ⊆ T`, `f x = f y`
implies `k (g x) = k (g y)`."]
theorem comp_eq_of_eq {T : Submonoid P} {Q : Type*} [CommMonoid Q] (hg : ∀ y : S, g y ∈ T)
(k : LocalizationMap T Q) {x y} (h : f.toMap x = f.toMap y) : k.toMap (g x) = k.toMap (g y) :=
f.eq_of_eq (fun y : S ↦ show IsUnit (k.toMap.comp g y) from k.map_units ⟨g y, hg y⟩) h
#align submonoid.localization_map.comp_eq_of_eq Submonoid.LocalizationMap.comp_eq_of_eq
#align add_submonoid.localization_map.comp_eq_of_eq AddSubmonoid.LocalizationMap.comp_eq_of_eq
variable (hg : ∀ y : S, IsUnit (g y))
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M` and a map of `CommMonoid`s
`g : M →* P` such that `g y` is invertible for all `y : S`, the homomorphism induced from
`N` to `P` sending `z : N` to `g x * (g y)⁻¹`, where `(x, y) : M × S` are such that
`z = f x * (f y)⁻¹`. -/
@[to_additive
"Given a localization map `f : M →+ N` for a submonoid `S ⊆ M` and a map of
`AddCommMonoid`s `g : M →+ P` such that `g y` is invertible for all `y : S`, the homomorphism
induced from `N` to `P` sending `z : N` to `g x - g y`, where `(x, y) : M × S` are such that
`z = f x - f y`."]
noncomputable def lift : N →* P where
toFun z := g (f.sec z).1 * (IsUnit.liftRight (g.restrict S) hg (f.sec z).2)⁻¹
map_one' := by rw [mul_inv_left, mul_one]; exact f.eq_of_eq hg (by rw [← sec_spec, one_mul])
map_mul' x y := by
dsimp only
rw [mul_inv_left hg, ← mul_assoc, ← mul_assoc, mul_inv_right hg, mul_comm _ (g (f.sec y).1), ←
mul_assoc, ← mul_assoc, mul_inv_right hg]
repeat rw [← g.map_mul]
exact f.eq_of_eq hg (by simp_rw [f.toMap.map_mul, sec_spec']; ac_rfl)
#align submonoid.localization_map.lift Submonoid.LocalizationMap.lift
#align add_submonoid.localization_map.lift AddSubmonoid.LocalizationMap.lift
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M` and a map of `CommMonoid`s
`g : M →* P` such that `g y` is invertible for all `y : S`, the homomorphism induced from
`N` to `P` maps `f x * (f y)⁻¹` to `g x * (g y)⁻¹` for all `x : M, y ∈ S`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M` and a map of
`AddCommMonoid`s `g : M →+ P` such that `g y` is invertible for all `y : S`, the homomorphism
induced from `N` to `P` maps `f x - f y` to `g x - g y` for all `x : M, y ∈ S`."]
theorem lift_mk' (x y) : f.lift hg (f.mk' x y) = g x * (IsUnit.liftRight (g.restrict S) hg y)⁻¹ :=
(mul_inv hg).2 <|
f.eq_of_eq hg <| by
simp_rw [f.toMap.map_mul, sec_spec', mul_assoc, f.mk'_spec, mul_comm]
#align submonoid.localization_map.lift_mk' Submonoid.LocalizationMap.lift_mk'
#align add_submonoid.localization_map.lift_mk' AddSubmonoid.LocalizationMap.lift_mk'
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M`, if a `CommMonoid` map
`g : M →* P` induces a map `f.lift hg : N →* P` then for all `z : N, v : P`, we have
`f.lift hg z = v ↔ g x = g y * v`, where `x : M, y ∈ S` are such that `z * f y = f x`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M`, if an
`AddCommMonoid` map `g : M →+ P` induces a map `f.lift hg : N →+ P` then for all
`z : N, v : P`, we have `f.lift hg z = v ↔ g x = g y + v`, where `x : M, y ∈ S` are such that
`z + f y = f x`."]
theorem lift_spec (z v) : f.lift hg z = v ↔ g (f.sec z).1 = g (f.sec z).2 * v :=
mul_inv_left hg _ _ v
#align submonoid.localization_map.lift_spec Submonoid.LocalizationMap.lift_spec
#align add_submonoid.localization_map.lift_spec AddSubmonoid.LocalizationMap.lift_spec
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M`, if a `CommMonoid` map
`g : M →* P` induces a map `f.lift hg : N →* P` then for all `z : N, v w : P`, we have
`f.lift hg z * w = v ↔ g x * w = g y * v`, where `x : M, y ∈ S` are such that
`z * f y = f x`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M`, if an `AddCommMonoid` map
`g : M →+ P` induces a map `f.lift hg : N →+ P` then for all
`z : N, v w : P`, we have `f.lift hg z + w = v ↔ g x + w = g y + v`, where `x : M, y ∈ S` are such
that `z + f y = f x`."]
theorem lift_spec_mul (z w v) : f.lift hg z * w = v ↔ g (f.sec z).1 * w = g (f.sec z).2 * v := by
erw [mul_comm, ← mul_assoc, mul_inv_left hg, mul_comm]
#align submonoid.localization_map.lift_spec_mul Submonoid.LocalizationMap.lift_spec_mul
#align add_submonoid.localization_map.lift_spec_add AddSubmonoid.LocalizationMap.lift_spec_add
@[to_additive]
theorem lift_mk'_spec (x v) (y : S) : f.lift hg (f.mk' x y) = v ↔ g x = g y * v := by
rw [f.lift_mk' hg]; exact mul_inv_left hg _ _ _
#align submonoid.localization_map.lift_mk'_spec Submonoid.LocalizationMap.lift_mk'_spec
#align add_submonoid.localization_map.lift_mk'_spec AddSubmonoid.LocalizationMap.lift_mk'_spec
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M`, if a `CommMonoid` map
`g : M →* P` induces a map `f.lift hg : N →* P` then for all `z : N`, we have
`f.lift hg z * g y = g x`, where `x : M, y ∈ S` are such that `z * f y = f x`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M`, if an `AddCommMonoid`
map `g : M →+ P` induces a map `f.lift hg : N →+ P` then for all `z : N`, we have
`f.lift hg z + g y = g x`, where `x : M, y ∈ S` are such that `z + f y = f x`."]
theorem lift_mul_right (z) : f.lift hg z * g (f.sec z).2 = g (f.sec z).1 := by
erw [mul_assoc, IsUnit.liftRight_inv_mul, mul_one]
#align submonoid.localization_map.lift_mul_right Submonoid.LocalizationMap.lift_mul_right
#align add_submonoid.localization_map.lift_add_right AddSubmonoid.LocalizationMap.lift_add_right
/-- Given a Localization map `f : M →* N` for a Submonoid `S ⊆ M`, if a `CommMonoid` map
`g : M →* P` induces a map `f.lift hg : N →* P` then for all `z : N`, we have
`g y * f.lift hg z = g x`, where `x : M, y ∈ S` are such that `z * f y = f x`. -/
@[to_additive
"Given a Localization map `f : M →+ N` for a Submonoid `S ⊆ M`, if an `AddCommMonoid` map
`g : M →+ P` induces a map `f.lift hg : N →+ P` then for all `z : N`, we have
`g y + f.lift hg z = g x`, where `x : M, y ∈ S` are such that `z + f y = f x`."]
theorem lift_mul_left (z) : g (f.sec z).2 * f.lift hg z = g (f.sec z).1 := by
rw [mul_comm, lift_mul_right]
#align submonoid.localization_map.lift_mul_left Submonoid.LocalizationMap.lift_mul_left
#align add_submonoid.localization_map.lift_add_left AddSubmonoid.LocalizationMap.lift_add_left
@[to_additive (attr := simp)]
theorem lift_eq (x : M) : f.lift hg (f.toMap x) = g x := by
rw [lift_spec, ← g.map_mul]; exact f.eq_of_eq hg (by rw [sec_spec', f.toMap.map_mul])
#align submonoid.localization_map.lift_eq Submonoid.LocalizationMap.lift_eq
#align add_submonoid.localization_map.lift_eq AddSubmonoid.LocalizationMap.lift_eq
@[to_additive]
theorem lift_eq_iff {x y : M × S} :
f.lift hg (f.mk' x.1 x.2) = f.lift hg (f.mk' y.1 y.2) ↔ g (x.1 * y.2) = g (y.1 * x.2) := by
rw [lift_mk', lift_mk', mul_inv hg]
#align submonoid.localization_map.lift_eq_iff Submonoid.LocalizationMap.lift_eq_iff
#align add_submonoid.localization_map.lift_eq_iff AddSubmonoid.LocalizationMap.lift_eq_iff
@[to_additive (attr := simp)]
theorem lift_comp : (f.lift hg).comp f.toMap = g := by ext; exact f.lift_eq hg _
#align submonoid.localization_map.lift_comp Submonoid.LocalizationMap.lift_comp
#align add_submonoid.localization_map.lift_comp AddSubmonoid.LocalizationMap.lift_comp
@[to_additive (attr := simp)]
theorem lift_of_comp (j : N →* P) : f.lift (f.isUnit_comp j) = j := by
ext
rw [lift_spec]
show j _ = j _ * _
erw [← j.map_mul, sec_spec']
#align submonoid.localization_map.lift_of_comp Submonoid.LocalizationMap.lift_of_comp
#align add_submonoid.localization_map.lift_of_comp AddSubmonoid.LocalizationMap.lift_of_comp
@[to_additive]
theorem epic_of_localizationMap {j k : N →* P} (h : ∀ a, j.comp f.toMap a = k.comp f.toMap a) :
j = k := by
rw [← f.lift_of_comp j, ← f.lift_of_comp k]
congr 1 with x; exact h x
#align submonoid.localization_map.epic_of_localization_map Submonoid.LocalizationMap.epic_of_localizationMap
#align add_submonoid.localization_map.epic_of_localization_map AddSubmonoid.LocalizationMap.epic_of_localizationMap
@[to_additive]
theorem lift_unique {j : N →* P} (hj : ∀ x, j (f.toMap x) = g x) : f.lift hg = j := by
ext
rw [lift_spec, ← hj, ← hj, ← j.map_mul]
apply congr_arg
rw [← sec_spec']
#align submonoid.localization_map.lift_unique Submonoid.LocalizationMap.lift_unique
#align add_submonoid.localization_map.lift_unique AddSubmonoid.LocalizationMap.lift_unique
@[to_additive (attr := simp)]
theorem lift_id (x) : f.lift f.map_units x = x :=
DFunLike.ext_iff.1 (f.lift_of_comp <| MonoidHom.id N) x
#align submonoid.localization_map.lift_id Submonoid.LocalizationMap.lift_id
#align add_submonoid.localization_map.lift_id AddSubmonoid.LocalizationMap.lift_id
/-- Given Localization maps `f : M →* N` for a Submonoid `S ⊆ M` and
`k : M →* Q` for a Submonoid `T ⊆ M`, such that `S ≤ T`, and we have
`l : M →* A`, the composition of the induced map `f.lift` for `k` with
the induced map `k.lift` for `l` is equal to the induced map `f.lift` for `l`. -/
@[to_additive
"Given Localization maps `f : M →+ N` for a Submonoid `S ⊆ M` and
`k : M →+ Q` for a Submonoid `T ⊆ M`, such that `S ≤ T`, and we have
`l : M →+ A`, the composition of the induced map `f.lift` for `k` with
the induced map `k.lift` for `l` is equal to the induced map `f.lift` for `l`"]
theorem lift_comp_lift {T : Submonoid M} (hST : S ≤ T) {Q : Type*} [CommMonoid Q]
(k : LocalizationMap T Q) {A : Type*} [CommMonoid A] {l : M →* A}
(hl : ∀ w : T, IsUnit (l w)) :
(k.lift hl).comp (f.lift (map_units k ⟨_, hST ·.2⟩)) =
f.lift (hl ⟨_, hST ·.2⟩) := .symm <|
lift_unique _ _ fun x ↦ by rw [← MonoidHom.comp_apply,
MonoidHom.comp_assoc, lift_comp, lift_comp]
@[to_additive]
theorem lift_comp_lift_eq {Q : Type*} [CommMonoid Q] (k : LocalizationMap S Q)
{A : Type*} [CommMonoid A] {l : M →* A} (hl : ∀ w : S, IsUnit (l w)) :
(k.lift hl).comp (f.lift k.map_units) = f.lift hl :=
lift_comp_lift f le_rfl k hl
/-- Given two Localization maps `f : M →* N, k : M →* P` for a Submonoid `S ⊆ M`, the hom
from `P` to `N` induced by `f` is left inverse to the hom from `N` to `P` induced by `k`. -/
@[to_additive (attr := simp)
"Given two Localization maps `f : M →+ N, k : M →+ P` for a Submonoid `S ⊆ M`, the hom
from `P` to `N` induced by `f` is left inverse to the hom from `N` to `P` induced by `k`."]
theorem lift_left_inverse {k : LocalizationMap S P} (z : N) :
k.lift f.map_units (f.lift k.map_units z) = z :=
(DFunLike.congr_fun (lift_comp_lift_eq f k f.map_units) z).trans (lift_id f z)
#align submonoid.localization_map.lift_left_inverse Submonoid.LocalizationMap.lift_left_inverse
#align add_submonoid.localization_map.lift_left_inverse AddSubmonoid.LocalizationMap.lift_left_inverse
@[to_additive]
theorem lift_surjective_iff :
Function.Surjective (f.lift hg) ↔ ∀ v : P, ∃ x : M × S, v * g x.2 = g x.1 := by
constructor
· intro H v
obtain ⟨z, hz⟩ := H v
obtain ⟨x, hx⟩ := f.surj z
use x
rw [← hz, f.eq_mk'_iff_mul_eq.2 hx, lift_mk', mul_assoc, mul_comm _ (g ↑x.2)]
erw [IsUnit.mul_liftRight_inv (g.restrict S) hg, mul_one]
· intro H v
obtain ⟨x, hx⟩ := H v
use f.mk' x.1 x.2
rw [lift_mk', mul_inv_left hg, mul_comm, ← hx]
#align submonoid.localization_map.lift_surjective_iff Submonoid.LocalizationMap.lift_surjective_iff
#align add_submonoid.localization_map.lift_surjective_iff AddSubmonoid.LocalizationMap.lift_surjective_iff
@[to_additive]
theorem lift_injective_iff :
Function.Injective (f.lift hg) ↔ ∀ x y, f.toMap x = f.toMap y ↔ g x = g y := by
constructor
· intro H x y
constructor
· exact f.eq_of_eq hg
· intro h
rw [← f.lift_eq hg, ← f.lift_eq hg] at h
exact H h
· intro H z w h
obtain ⟨_, _⟩ := f.surj z
obtain ⟨_, _⟩ := f.surj w
rw [← f.mk'_sec z, ← f.mk'_sec w]
exact (mul_inv f.map_units).2 ((H _ _).2 <| (mul_inv hg).1 h)
#align submonoid.localization_map.lift_injective_iff Submonoid.LocalizationMap.lift_injective_iff
#align add_submonoid.localization_map.lift_injective_iff AddSubmonoid.LocalizationMap.lift_injective_iff
variable {T : Submonoid P} (hy : ∀ y : S, g y ∈ T) {Q : Type*} [CommMonoid Q]
(k : LocalizationMap T Q)
/-- Given a `CommMonoid` homomorphism `g : M →* P` where for Submonoids `S ⊆ M, T ⊆ P` we have
`g(S) ⊆ T`, the induced Monoid homomorphism from the Localization of `M` at `S` to the
Localization of `P` at `T`: if `f : M →* N` and `k : P →* Q` are Localization maps for `S` and
`T` respectively, we send `z : N` to `k (g x) * (k (g y))⁻¹`, where `(x, y) : M × S` are such
that `z = f x * (f y)⁻¹`. -/
@[to_additive
"Given an `AddCommMonoid` homomorphism `g : M →+ P` where for Submonoids `S ⊆ M, T ⊆ P` we have
`g(S) ⊆ T`, the induced AddMonoid homomorphism from the Localization of `M` at `S` to the
Localization of `P` at `T`: if `f : M →+ N` and `k : P →+ Q` are Localization maps for `S` and
`T` respectively, we send `z : N` to `k (g x) - k (g y)`, where `(x, y) : M × S` are such
that `z = f x - f y`."]
noncomputable def map : N →* Q :=
@lift _ _ _ _ _ _ _ f (k.toMap.comp g) fun y ↦ k.map_units ⟨g y, hy y⟩
#align submonoid.localization_map.map Submonoid.LocalizationMap.map
#align add_submonoid.localization_map.map AddSubmonoid.LocalizationMap.map
variable {k}
@[to_additive]
theorem map_eq (x) : f.map hy k (f.toMap x) = k.toMap (g x) :=
f.lift_eq (fun y ↦ k.map_units ⟨g y, hy y⟩) x
#align submonoid.localization_map.map_eq Submonoid.LocalizationMap.map_eq
#align add_submonoid.localization_map.map_eq AddSubmonoid.LocalizationMap.map_eq
@[to_additive (attr := simp)]
theorem map_comp : (f.map hy k).comp f.toMap = k.toMap.comp g :=
f.lift_comp fun y ↦ k.map_units ⟨g y, hy y⟩
#align submonoid.localization_map.map_comp Submonoid.LocalizationMap.map_comp
#align add_submonoid.localization_map.map_comp AddSubmonoid.LocalizationMap.map_comp
@[to_additive]
theorem map_mk' (x) (y : S) : f.map hy k (f.mk' x y) = k.mk' (g x) ⟨g y, hy y⟩ := by
rw [map, lift_mk', mul_inv_left]
show k.toMap (g x) = k.toMap (g y) * _
rw [mul_mk'_eq_mk'_of_mul]
exact (k.mk'_mul_cancel_left (g x) ⟨g y, hy y⟩).symm
#align submonoid.localization_map.map_mk' Submonoid.LocalizationMap.map_mk'
#align add_submonoid.localization_map.map_mk' AddSubmonoid.LocalizationMap.map_mk'
/-- Given Localization maps `f : M →* N, k : P →* Q` for Submonoids `S, T` respectively, if a
`CommMonoid` homomorphism `g : M →* P` induces a `f.map hy k : N →* Q`, then for all `z : N`,
`u : Q`, we have `f.map hy k z = u ↔ k (g x) = k (g y) * u` where `x : M, y ∈ S` are such that
`z * f y = f x`. -/
@[to_additive
"Given Localization maps `f : M →+ N, k : P →+ Q` for Submonoids `S, T` respectively, if an
`AddCommMonoid` homomorphism `g : M →+ P` induces a `f.map hy k : N →+ Q`, then for all `z : N`,
`u : Q`, we have `f.map hy k z = u ↔ k (g x) = k (g y) + u` where `x : M, y ∈ S` are such that
`z + f y = f x`."]
theorem map_spec (z u) : f.map hy k z = u ↔ k.toMap (g (f.sec z).1) = k.toMap (g (f.sec z).2) * u :=
f.lift_spec (fun y ↦ k.map_units ⟨g y, hy y⟩) _ _
#align submonoid.localization_map.map_spec Submonoid.LocalizationMap.map_spec
#align add_submonoid.localization_map.map_spec AddSubmonoid.LocalizationMap.map_spec
/-- Given Localization maps `f : M →* N, k : P →* Q` for Submonoids `S, T` respectively, if a
`CommMonoid` homomorphism `g : M →* P` induces a `f.map hy k : N →* Q`, then for all `z : N`,
we have `f.map hy k z * k (g y) = k (g x)` where `x : M, y ∈ S` are such that
`z * f y = f x`. -/
@[to_additive
"Given Localization maps `f : M →+ N, k : P →+ Q` for Submonoids `S, T` respectively, if an
`AddCommMonoid` homomorphism `g : M →+ P` induces a `f.map hy k : N →+ Q`, then for all `z : N`,
we have `f.map hy k z + k (g y) = k (g x)` where `x : M, y ∈ S` are such that
`z + f y = f x`."]
theorem map_mul_right (z) : f.map hy k z * k.toMap (g (f.sec z).2) = k.toMap (g (f.sec z).1) :=
f.lift_mul_right (fun y ↦ k.map_units ⟨g y, hy y⟩) _
#align submonoid.localization_map.map_mul_right Submonoid.LocalizationMap.map_mul_right
#align add_submonoid.localization_map.map_add_right AddSubmonoid.LocalizationMap.map_add_right
/-- Given Localization maps `f : M →* N, k : P →* Q` for Submonoids `S, T` respectively, if a
`CommMonoid` homomorphism `g : M →* P` induces a `f.map hy k : N →* Q`, then for all `z : N`,
we have `k (g y) * f.map hy k z = k (g x)` where `x : M, y ∈ S` are such that
`z * f y = f x`. -/
@[to_additive
"Given Localization maps `f : M →+ N, k : P →+ Q` for Submonoids `S, T` respectively if an
`AddCommMonoid` homomorphism `g : M →+ P` induces a `f.map hy k : N →+ Q`, then for all `z : N`,
we have `k (g y) + f.map hy k z = k (g x)` where `x : M, y ∈ S` are such that
`z + f y = f x`."]
theorem map_mul_left (z) : k.toMap (g (f.sec z).2) * f.map hy k z = k.toMap (g (f.sec z).1) := by
rw [mul_comm, f.map_mul_right]
#align submonoid.localization_map.map_mul_left Submonoid.LocalizationMap.map_mul_left
#align add_submonoid.localization_map.map_add_left AddSubmonoid.LocalizationMap.map_add_left
@[to_additive (attr := simp)]
theorem map_id (z : N) : f.map (fun y ↦ show MonoidHom.id M y ∈ S from y.2) f z = z :=
f.lift_id z
#align submonoid.localization_map.map_id Submonoid.LocalizationMap.map_id
#align add_submonoid.localization_map.map_id AddSubmonoid.LocalizationMap.map_id
/-- If `CommMonoid` homs `g : M →* P, l : P →* A` induce maps of localizations, the composition
of the induced maps equals the map of localizations induced by `l ∘ g`. -/
@[to_additive
"If `AddCommMonoid` homs `g : M →+ P, l : P →+ A` induce maps of localizations, the composition
of the induced maps equals the map of localizations induced by `l ∘ g`."]
| Mathlib/GroupTheory/MonoidLocalization.lean | 1,255 | 1,266 | theorem map_comp_map {A : Type*} [CommMonoid A] {U : Submonoid A} {R} [CommMonoid R]
(j : LocalizationMap U R) {l : P →* A} (hl : ∀ w : T, l w ∈ U) :
(k.map hl j).comp (f.map hy k) =
f.map (fun x ↦ show l.comp g x ∈ U from hl ⟨g x, hy x⟩) j := by |
ext z
show j.toMap _ * _ = j.toMap (l _) * _
rw [mul_inv_left, ← mul_assoc, mul_inv_right]
show j.toMap _ * j.toMap (l (g _)) = j.toMap (l _) * _
rw [← j.toMap.map_mul, ← j.toMap.map_mul, ← l.map_mul, ← l.map_mul]
exact
k.comp_eq_of_eq hl j
(by rw [k.toMap.map_mul, k.toMap.map_mul, sec_spec', mul_assoc, map_mul_right])
|
/-
Copyright (c) 2021 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Subgraph
import Mathlib.Data.List.Rotate
#align_import combinatorics.simple_graph.connectivity from "leanprover-community/mathlib"@"b99e2d58a5e6861833fa8de11e51a81144258db4"
/-!
# Graph connectivity
In a simple graph,
* A *walk* is a finite sequence of adjacent vertices, and can be
thought of equally well as a sequence of directed edges.
* A *trail* is a walk whose edges each appear no more than once.
* A *path* is a trail whose vertices appear no more than once.
* A *cycle* is a nonempty trail whose first and last vertices are the
same and whose vertices except for the first appear no more than once.
**Warning:** graph theorists mean something different by "path" than
do homotopy theorists. A "walk" in graph theory is a "path" in
homotopy theory. Another warning: some graph theorists use "path" and
"simple path" for "walk" and "path."
Some definitions and theorems have inspiration from multigraph
counterparts in [Chou1994].
## Main definitions
* `SimpleGraph.Walk` (with accompanying pattern definitions
`SimpleGraph.Walk.nil'` and `SimpleGraph.Walk.cons'`)
* `SimpleGraph.Walk.IsTrail`, `SimpleGraph.Walk.IsPath`, and `SimpleGraph.Walk.IsCycle`.
* `SimpleGraph.Path`
* `SimpleGraph.Walk.map` and `SimpleGraph.Path.map` for the induced map on walks,
given an (injective) graph homomorphism.
* `SimpleGraph.Reachable` for the relation of whether there exists
a walk between a given pair of vertices
* `SimpleGraph.Preconnected` and `SimpleGraph.Connected` are predicates
on simple graphs for whether every vertex can be reached from every other,
and in the latter case, whether the vertex type is nonempty.
* `SimpleGraph.ConnectedComponent` is the type of connected components of
a given graph.
* `SimpleGraph.IsBridge` for whether an edge is a bridge edge
## Main statements
* `SimpleGraph.isBridge_iff_mem_and_forall_cycle_not_mem` characterizes bridge edges in terms of
there being no cycle containing them.
## Tags
walks, trails, paths, circuits, cycles, bridge edges
-/
open Function
universe u v w
namespace SimpleGraph
variable {V : Type u} {V' : Type v} {V'' : Type w}
variable (G : SimpleGraph V) (G' : SimpleGraph V') (G'' : SimpleGraph V'')
/-- A walk is a sequence of adjacent vertices. For vertices `u v : V`,
the type `walk u v` consists of all walks starting at `u` and ending at `v`.
We say that a walk *visits* the vertices it contains. The set of vertices a
walk visits is `SimpleGraph.Walk.support`.
See `SimpleGraph.Walk.nil'` and `SimpleGraph.Walk.cons'` for patterns that
can be useful in definitions since they make the vertices explicit. -/
inductive Walk : V → V → Type u
| nil {u : V} : Walk u u
| cons {u v w : V} (h : G.Adj u v) (p : Walk v w) : Walk u w
deriving DecidableEq
#align simple_graph.walk SimpleGraph.Walk
attribute [refl] Walk.nil
@[simps]
instance Walk.instInhabited (v : V) : Inhabited (G.Walk v v) := ⟨Walk.nil⟩
#align simple_graph.walk.inhabited SimpleGraph.Walk.instInhabited
/-- The one-edge walk associated to a pair of adjacent vertices. -/
@[match_pattern, reducible]
def Adj.toWalk {G : SimpleGraph V} {u v : V} (h : G.Adj u v) : G.Walk u v :=
Walk.cons h Walk.nil
#align simple_graph.adj.to_walk SimpleGraph.Adj.toWalk
namespace Walk
variable {G}
/-- Pattern to get `Walk.nil` with the vertex as an explicit argument. -/
@[match_pattern]
abbrev nil' (u : V) : G.Walk u u := Walk.nil
#align simple_graph.walk.nil' SimpleGraph.Walk.nil'
/-- Pattern to get `Walk.cons` with the vertices as explicit arguments. -/
@[match_pattern]
abbrev cons' (u v w : V) (h : G.Adj u v) (p : G.Walk v w) : G.Walk u w := Walk.cons h p
#align simple_graph.walk.cons' SimpleGraph.Walk.cons'
/-- Change the endpoints of a walk using equalities. This is helpful for relaxing
definitional equality constraints and to be able to state otherwise difficult-to-state
lemmas. While this is a simple wrapper around `Eq.rec`, it gives a canonical way to write it.
The simp-normal form is for the `copy` to be pushed outward. That way calculations can
occur within the "copy context." -/
protected def copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') : G.Walk u' v' :=
hu ▸ hv ▸ p
#align simple_graph.walk.copy SimpleGraph.Walk.copy
@[simp]
theorem copy_rfl_rfl {u v} (p : G.Walk u v) : p.copy rfl rfl = p := rfl
#align simple_graph.walk.copy_rfl_rfl SimpleGraph.Walk.copy_rfl_rfl
@[simp]
theorem copy_copy {u v u' v' u'' v''} (p : G.Walk u v)
(hu : u = u') (hv : v = v') (hu' : u' = u'') (hv' : v' = v'') :
(p.copy hu hv).copy hu' hv' = p.copy (hu.trans hu') (hv.trans hv') := by
subst_vars
rfl
#align simple_graph.walk.copy_copy SimpleGraph.Walk.copy_copy
@[simp]
theorem copy_nil {u u'} (hu : u = u') : (Walk.nil : G.Walk u u).copy hu hu = Walk.nil := by
subst_vars
rfl
#align simple_graph.walk.copy_nil SimpleGraph.Walk.copy_nil
theorem copy_cons {u v w u' w'} (h : G.Adj u v) (p : G.Walk v w) (hu : u = u') (hw : w = w') :
(Walk.cons h p).copy hu hw = Walk.cons (hu ▸ h) (p.copy rfl hw) := by
subst_vars
rfl
#align simple_graph.walk.copy_cons SimpleGraph.Walk.copy_cons
@[simp]
theorem cons_copy {u v w v' w'} (h : G.Adj u v) (p : G.Walk v' w') (hv : v' = v) (hw : w' = w) :
Walk.cons h (p.copy hv hw) = (Walk.cons (hv ▸ h) p).copy rfl hw := by
subst_vars
rfl
#align simple_graph.walk.cons_copy SimpleGraph.Walk.cons_copy
theorem exists_eq_cons_of_ne {u v : V} (hne : u ≠ v) :
∀ (p : G.Walk u v), ∃ (w : V) (h : G.Adj u w) (p' : G.Walk w v), p = cons h p'
| nil => (hne rfl).elim
| cons h p' => ⟨_, h, p', rfl⟩
#align simple_graph.walk.exists_eq_cons_of_ne SimpleGraph.Walk.exists_eq_cons_of_ne
/-- The length of a walk is the number of edges/darts along it. -/
def length {u v : V} : G.Walk u v → ℕ
| nil => 0
| cons _ q => q.length.succ
#align simple_graph.walk.length SimpleGraph.Walk.length
/-- The concatenation of two compatible walks. -/
@[trans]
def append {u v w : V} : G.Walk u v → G.Walk v w → G.Walk u w
| nil, q => q
| cons h p, q => cons h (p.append q)
#align simple_graph.walk.append SimpleGraph.Walk.append
/-- The reversed version of `SimpleGraph.Walk.cons`, concatenating an edge to
the end of a walk. -/
def concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) : G.Walk u w := p.append (cons h nil)
#align simple_graph.walk.concat SimpleGraph.Walk.concat
theorem concat_eq_append {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
p.concat h = p.append (cons h nil) := rfl
#align simple_graph.walk.concat_eq_append SimpleGraph.Walk.concat_eq_append
/-- The concatenation of the reverse of the first walk with the second walk. -/
protected def reverseAux {u v w : V} : G.Walk u v → G.Walk u w → G.Walk v w
| nil, q => q
| cons h p, q => Walk.reverseAux p (cons (G.symm h) q)
#align simple_graph.walk.reverse_aux SimpleGraph.Walk.reverseAux
/-- The walk in reverse. -/
@[symm]
def reverse {u v : V} (w : G.Walk u v) : G.Walk v u := w.reverseAux nil
#align simple_graph.walk.reverse SimpleGraph.Walk.reverse
/-- Get the `n`th vertex from a walk, where `n` is generally expected to be
between `0` and `p.length`, inclusive.
If `n` is greater than or equal to `p.length`, the result is the path's endpoint. -/
def getVert {u v : V} : G.Walk u v → ℕ → V
| nil, _ => u
| cons _ _, 0 => u
| cons _ q, n + 1 => q.getVert n
#align simple_graph.walk.get_vert SimpleGraph.Walk.getVert
@[simp]
theorem getVert_zero {u v} (w : G.Walk u v) : w.getVert 0 = u := by cases w <;> rfl
#align simple_graph.walk.get_vert_zero SimpleGraph.Walk.getVert_zero
theorem getVert_of_length_le {u v} (w : G.Walk u v) {i : ℕ} (hi : w.length ≤ i) :
w.getVert i = v := by
induction w generalizing i with
| nil => rfl
| cons _ _ ih =>
cases i
· cases hi
· exact ih (Nat.succ_le_succ_iff.1 hi)
#align simple_graph.walk.get_vert_of_length_le SimpleGraph.Walk.getVert_of_length_le
@[simp]
theorem getVert_length {u v} (w : G.Walk u v) : w.getVert w.length = v :=
w.getVert_of_length_le rfl.le
#align simple_graph.walk.get_vert_length SimpleGraph.Walk.getVert_length
theorem adj_getVert_succ {u v} (w : G.Walk u v) {i : ℕ} (hi : i < w.length) :
G.Adj (w.getVert i) (w.getVert (i + 1)) := by
induction w generalizing i with
| nil => cases hi
| cons hxy _ ih =>
cases i
· simp [getVert, hxy]
· exact ih (Nat.succ_lt_succ_iff.1 hi)
#align simple_graph.walk.adj_get_vert_succ SimpleGraph.Walk.adj_getVert_succ
@[simp]
theorem cons_append {u v w x : V} (h : G.Adj u v) (p : G.Walk v w) (q : G.Walk w x) :
(cons h p).append q = cons h (p.append q) := rfl
#align simple_graph.walk.cons_append SimpleGraph.Walk.cons_append
@[simp]
theorem cons_nil_append {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h nil).append p = cons h p := rfl
#align simple_graph.walk.cons_nil_append SimpleGraph.Walk.cons_nil_append
@[simp]
theorem append_nil {u v : V} (p : G.Walk u v) : p.append nil = p := by
induction p with
| nil => rfl
| cons _ _ ih => rw [cons_append, ih]
#align simple_graph.walk.append_nil SimpleGraph.Walk.append_nil
@[simp]
theorem nil_append {u v : V} (p : G.Walk u v) : nil.append p = p :=
rfl
#align simple_graph.walk.nil_append SimpleGraph.Walk.nil_append
theorem append_assoc {u v w x : V} (p : G.Walk u v) (q : G.Walk v w) (r : G.Walk w x) :
p.append (q.append r) = (p.append q).append r := by
induction p with
| nil => rfl
| cons h p' ih =>
dsimp only [append]
rw [ih]
#align simple_graph.walk.append_assoc SimpleGraph.Walk.append_assoc
@[simp]
theorem append_copy_copy {u v w u' v' w'} (p : G.Walk u v) (q : G.Walk v w)
(hu : u = u') (hv : v = v') (hw : w = w') :
(p.copy hu hv).append (q.copy hv hw) = (p.append q).copy hu hw := by
subst_vars
rfl
#align simple_graph.walk.append_copy_copy SimpleGraph.Walk.append_copy_copy
theorem concat_nil {u v : V} (h : G.Adj u v) : nil.concat h = cons h nil := rfl
#align simple_graph.walk.concat_nil SimpleGraph.Walk.concat_nil
@[simp]
theorem concat_cons {u v w x : V} (h : G.Adj u v) (p : G.Walk v w) (h' : G.Adj w x) :
(cons h p).concat h' = cons h (p.concat h') := rfl
#align simple_graph.walk.concat_cons SimpleGraph.Walk.concat_cons
theorem append_concat {u v w x : V} (p : G.Walk u v) (q : G.Walk v w) (h : G.Adj w x) :
p.append (q.concat h) = (p.append q).concat h := append_assoc _ _ _
#align simple_graph.walk.append_concat SimpleGraph.Walk.append_concat
theorem concat_append {u v w x : V} (p : G.Walk u v) (h : G.Adj v w) (q : G.Walk w x) :
(p.concat h).append q = p.append (cons h q) := by
rw [concat_eq_append, ← append_assoc, cons_nil_append]
#align simple_graph.walk.concat_append SimpleGraph.Walk.concat_append
/-- A non-trivial `cons` walk is representable as a `concat` walk. -/
theorem exists_cons_eq_concat {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
∃ (x : V) (q : G.Walk u x) (h' : G.Adj x w), cons h p = q.concat h' := by
induction p generalizing u with
| nil => exact ⟨_, nil, h, rfl⟩
| cons h' p ih =>
obtain ⟨y, q, h'', hc⟩ := ih h'
refine ⟨y, cons h q, h'', ?_⟩
rw [concat_cons, hc]
#align simple_graph.walk.exists_cons_eq_concat SimpleGraph.Walk.exists_cons_eq_concat
/-- A non-trivial `concat` walk is representable as a `cons` walk. -/
theorem exists_concat_eq_cons {u v w : V} :
∀ (p : G.Walk u v) (h : G.Adj v w),
∃ (x : V) (h' : G.Adj u x) (q : G.Walk x w), p.concat h = cons h' q
| nil, h => ⟨_, h, nil, rfl⟩
| cons h' p, h => ⟨_, h', Walk.concat p h, concat_cons _ _ _⟩
#align simple_graph.walk.exists_concat_eq_cons SimpleGraph.Walk.exists_concat_eq_cons
@[simp]
theorem reverse_nil {u : V} : (nil : G.Walk u u).reverse = nil := rfl
#align simple_graph.walk.reverse_nil SimpleGraph.Walk.reverse_nil
theorem reverse_singleton {u v : V} (h : G.Adj u v) : (cons h nil).reverse = cons (G.symm h) nil :=
rfl
#align simple_graph.walk.reverse_singleton SimpleGraph.Walk.reverse_singleton
@[simp]
theorem cons_reverseAux {u v w x : V} (p : G.Walk u v) (q : G.Walk w x) (h : G.Adj w u) :
(cons h p).reverseAux q = p.reverseAux (cons (G.symm h) q) := rfl
#align simple_graph.walk.cons_reverse_aux SimpleGraph.Walk.cons_reverseAux
@[simp]
protected theorem append_reverseAux {u v w x : V}
(p : G.Walk u v) (q : G.Walk v w) (r : G.Walk u x) :
(p.append q).reverseAux r = q.reverseAux (p.reverseAux r) := by
induction p with
| nil => rfl
| cons h _ ih => exact ih q (cons (G.symm h) r)
#align simple_graph.walk.append_reverse_aux SimpleGraph.Walk.append_reverseAux
@[simp]
protected theorem reverseAux_append {u v w x : V}
(p : G.Walk u v) (q : G.Walk u w) (r : G.Walk w x) :
(p.reverseAux q).append r = p.reverseAux (q.append r) := by
induction p with
| nil => rfl
| cons h _ ih => simp [ih (cons (G.symm h) q)]
#align simple_graph.walk.reverse_aux_append SimpleGraph.Walk.reverseAux_append
protected theorem reverseAux_eq_reverse_append {u v w : V} (p : G.Walk u v) (q : G.Walk u w) :
p.reverseAux q = p.reverse.append q := by simp [reverse]
#align simple_graph.walk.reverse_aux_eq_reverse_append SimpleGraph.Walk.reverseAux_eq_reverse_append
@[simp]
theorem reverse_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).reverse = p.reverse.append (cons (G.symm h) nil) := by simp [reverse]
#align simple_graph.walk.reverse_cons SimpleGraph.Walk.reverse_cons
@[simp]
theorem reverse_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).reverse = p.reverse.copy hv hu := by
subst_vars
rfl
#align simple_graph.walk.reverse_copy SimpleGraph.Walk.reverse_copy
@[simp]
theorem reverse_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).reverse = q.reverse.append p.reverse := by simp [reverse]
#align simple_graph.walk.reverse_append SimpleGraph.Walk.reverse_append
@[simp]
theorem reverse_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).reverse = cons (G.symm h) p.reverse := by simp [concat_eq_append]
#align simple_graph.walk.reverse_concat SimpleGraph.Walk.reverse_concat
@[simp]
theorem reverse_reverse {u v : V} (p : G.Walk u v) : p.reverse.reverse = p := by
induction p with
| nil => rfl
| cons _ _ ih => simp [ih]
#align simple_graph.walk.reverse_reverse SimpleGraph.Walk.reverse_reverse
@[simp]
theorem length_nil {u : V} : (nil : G.Walk u u).length = 0 := rfl
#align simple_graph.walk.length_nil SimpleGraph.Walk.length_nil
@[simp]
theorem length_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).length = p.length + 1 := rfl
#align simple_graph.walk.length_cons SimpleGraph.Walk.length_cons
@[simp]
theorem length_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).length = p.length := by
subst_vars
rfl
#align simple_graph.walk.length_copy SimpleGraph.Walk.length_copy
@[simp]
theorem length_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).length = p.length + q.length := by
induction p with
| nil => simp
| cons _ _ ih => simp [ih, add_comm, add_left_comm, add_assoc]
#align simple_graph.walk.length_append SimpleGraph.Walk.length_append
@[simp]
theorem length_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).length = p.length + 1 := length_append _ _
#align simple_graph.walk.length_concat SimpleGraph.Walk.length_concat
@[simp]
protected theorem length_reverseAux {u v w : V} (p : G.Walk u v) (q : G.Walk u w) :
(p.reverseAux q).length = p.length + q.length := by
induction p with
| nil => simp!
| cons _ _ ih => simp [ih, Nat.succ_add, Nat.add_assoc]
#align simple_graph.walk.length_reverse_aux SimpleGraph.Walk.length_reverseAux
@[simp]
theorem length_reverse {u v : V} (p : G.Walk u v) : p.reverse.length = p.length := by simp [reverse]
#align simple_graph.walk.length_reverse SimpleGraph.Walk.length_reverse
theorem eq_of_length_eq_zero {u v : V} : ∀ {p : G.Walk u v}, p.length = 0 → u = v
| nil, _ => rfl
#align simple_graph.walk.eq_of_length_eq_zero SimpleGraph.Walk.eq_of_length_eq_zero
theorem adj_of_length_eq_one {u v : V} : ∀ {p : G.Walk u v}, p.length = 1 → G.Adj u v
| cons h nil, _ => h
@[simp]
theorem exists_length_eq_zero_iff {u v : V} : (∃ p : G.Walk u v, p.length = 0) ↔ u = v := by
constructor
· rintro ⟨p, hp⟩
exact eq_of_length_eq_zero hp
· rintro rfl
exact ⟨nil, rfl⟩
#align simple_graph.walk.exists_length_eq_zero_iff SimpleGraph.Walk.exists_length_eq_zero_iff
@[simp]
theorem length_eq_zero_iff {u : V} {p : G.Walk u u} : p.length = 0 ↔ p = nil := by cases p <;> simp
#align simple_graph.walk.length_eq_zero_iff SimpleGraph.Walk.length_eq_zero_iff
theorem getVert_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) (i : ℕ) :
(p.append q).getVert i = if i < p.length then p.getVert i else q.getVert (i - p.length) := by
induction p generalizing i with
| nil => simp
| cons h p ih => cases i <;> simp [getVert, ih, Nat.succ_lt_succ_iff]
theorem getVert_reverse {u v : V} (p : G.Walk u v) (i : ℕ) :
p.reverse.getVert i = p.getVert (p.length - i) := by
induction p with
| nil => rfl
| cons h p ih =>
simp only [reverse_cons, getVert_append, length_reverse, ih, length_cons]
split_ifs
next hi =>
rw [Nat.succ_sub hi.le]
simp [getVert]
next hi =>
obtain rfl | hi' := Nat.eq_or_lt_of_not_lt hi
· simp [getVert]
· rw [Nat.eq_add_of_sub_eq (Nat.sub_pos_of_lt hi') rfl, Nat.sub_eq_zero_of_le hi']
simp [getVert]
section ConcatRec
variable {motive : ∀ u v : V, G.Walk u v → Sort*} (Hnil : ∀ {u : V}, motive u u nil)
(Hconcat : ∀ {u v w : V} (p : G.Walk u v) (h : G.Adj v w), motive u v p → motive u w (p.concat h))
/-- Auxiliary definition for `SimpleGraph.Walk.concatRec` -/
def concatRecAux {u v : V} : (p : G.Walk u v) → motive v u p.reverse
| nil => Hnil
| cons h p => reverse_cons h p ▸ Hconcat p.reverse h.symm (concatRecAux p)
#align simple_graph.walk.concat_rec_aux SimpleGraph.Walk.concatRecAux
/-- Recursor on walks by inducting on `SimpleGraph.Walk.concat`.
This is inducting from the opposite end of the walk compared
to `SimpleGraph.Walk.rec`, which inducts on `SimpleGraph.Walk.cons`. -/
@[elab_as_elim]
def concatRec {u v : V} (p : G.Walk u v) : motive u v p :=
reverse_reverse p ▸ concatRecAux @Hnil @Hconcat p.reverse
#align simple_graph.walk.concat_rec SimpleGraph.Walk.concatRec
@[simp]
theorem concatRec_nil (u : V) :
@concatRec _ _ motive @Hnil @Hconcat _ _ (nil : G.Walk u u) = Hnil := rfl
#align simple_graph.walk.concat_rec_nil SimpleGraph.Walk.concatRec_nil
@[simp]
theorem concatRec_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
@concatRec _ _ motive @Hnil @Hconcat _ _ (p.concat h) =
Hconcat p h (concatRec @Hnil @Hconcat p) := by
simp only [concatRec]
apply eq_of_heq
apply rec_heq_of_heq
trans concatRecAux @Hnil @Hconcat (cons h.symm p.reverse)
· congr
simp
· rw [concatRecAux, rec_heq_iff_heq]
congr <;> simp [heq_rec_iff_heq]
#align simple_graph.walk.concat_rec_concat SimpleGraph.Walk.concatRec_concat
end ConcatRec
theorem concat_ne_nil {u v : V} (p : G.Walk u v) (h : G.Adj v u) : p.concat h ≠ nil := by
cases p <;> simp [concat]
#align simple_graph.walk.concat_ne_nil SimpleGraph.Walk.concat_ne_nil
theorem concat_inj {u v v' w : V} {p : G.Walk u v} {h : G.Adj v w} {p' : G.Walk u v'}
{h' : G.Adj v' w} (he : p.concat h = p'.concat h') : ∃ hv : v = v', p.copy rfl hv = p' := by
induction p with
| nil =>
cases p'
· exact ⟨rfl, rfl⟩
· exfalso
simp only [concat_nil, concat_cons, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
simp only [heq_iff_eq] at he
exact concat_ne_nil _ _ he.symm
| cons _ _ ih =>
rw [concat_cons] at he
cases p'
· exfalso
simp only [concat_nil, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
rw [heq_iff_eq] at he
exact concat_ne_nil _ _ he
· rw [concat_cons, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
rw [heq_iff_eq] at he
obtain ⟨rfl, rfl⟩ := ih he
exact ⟨rfl, rfl⟩
#align simple_graph.walk.concat_inj SimpleGraph.Walk.concat_inj
/-- The `support` of a walk is the list of vertices it visits in order. -/
def support {u v : V} : G.Walk u v → List V
| nil => [u]
| cons _ p => u :: p.support
#align simple_graph.walk.support SimpleGraph.Walk.support
/-- The `darts` of a walk is the list of darts it visits in order. -/
def darts {u v : V} : G.Walk u v → List G.Dart
| nil => []
| cons h p => ⟨(u, _), h⟩ :: p.darts
#align simple_graph.walk.darts SimpleGraph.Walk.darts
/-- The `edges` of a walk is the list of edges it visits in order.
This is defined to be the list of edges underlying `SimpleGraph.Walk.darts`. -/
def edges {u v : V} (p : G.Walk u v) : List (Sym2 V) := p.darts.map Dart.edge
#align simple_graph.walk.edges SimpleGraph.Walk.edges
@[simp]
theorem support_nil {u : V} : (nil : G.Walk u u).support = [u] := rfl
#align simple_graph.walk.support_nil SimpleGraph.Walk.support_nil
@[simp]
theorem support_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).support = u :: p.support := rfl
#align simple_graph.walk.support_cons SimpleGraph.Walk.support_cons
@[simp]
theorem support_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).support = p.support.concat w := by
induction p <;> simp [*, concat_nil]
#align simple_graph.walk.support_concat SimpleGraph.Walk.support_concat
@[simp]
theorem support_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).support = p.support := by
subst_vars
rfl
#align simple_graph.walk.support_copy SimpleGraph.Walk.support_copy
theorem support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').support = p.support ++ p'.support.tail := by
induction p <;> cases p' <;> simp [*]
#align simple_graph.walk.support_append SimpleGraph.Walk.support_append
@[simp]
theorem support_reverse {u v : V} (p : G.Walk u v) : p.reverse.support = p.support.reverse := by
induction p <;> simp [support_append, *]
#align simple_graph.walk.support_reverse SimpleGraph.Walk.support_reverse
@[simp]
theorem support_ne_nil {u v : V} (p : G.Walk u v) : p.support ≠ [] := by cases p <;> simp
#align simple_graph.walk.support_ne_nil SimpleGraph.Walk.support_ne_nil
theorem tail_support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').support.tail = p.support.tail ++ p'.support.tail := by
rw [support_append, List.tail_append_of_ne_nil _ _ (support_ne_nil _)]
#align simple_graph.walk.tail_support_append SimpleGraph.Walk.tail_support_append
theorem support_eq_cons {u v : V} (p : G.Walk u v) : p.support = u :: p.support.tail := by
cases p <;> simp
#align simple_graph.walk.support_eq_cons SimpleGraph.Walk.support_eq_cons
@[simp]
theorem start_mem_support {u v : V} (p : G.Walk u v) : u ∈ p.support := by cases p <;> simp
#align simple_graph.walk.start_mem_support SimpleGraph.Walk.start_mem_support
@[simp]
theorem end_mem_support {u v : V} (p : G.Walk u v) : v ∈ p.support := by induction p <;> simp [*]
#align simple_graph.walk.end_mem_support SimpleGraph.Walk.end_mem_support
@[simp]
theorem support_nonempty {u v : V} (p : G.Walk u v) : { w | w ∈ p.support }.Nonempty :=
⟨u, by simp⟩
#align simple_graph.walk.support_nonempty SimpleGraph.Walk.support_nonempty
theorem mem_support_iff {u v w : V} (p : G.Walk u v) :
w ∈ p.support ↔ w = u ∨ w ∈ p.support.tail := by cases p <;> simp
#align simple_graph.walk.mem_support_iff SimpleGraph.Walk.mem_support_iff
theorem mem_support_nil_iff {u v : V} : u ∈ (nil : G.Walk v v).support ↔ u = v := by simp
#align simple_graph.walk.mem_support_nil_iff SimpleGraph.Walk.mem_support_nil_iff
@[simp]
theorem mem_tail_support_append_iff {t u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
t ∈ (p.append p').support.tail ↔ t ∈ p.support.tail ∨ t ∈ p'.support.tail := by
rw [tail_support_append, List.mem_append]
#align simple_graph.walk.mem_tail_support_append_iff SimpleGraph.Walk.mem_tail_support_append_iff
@[simp]
theorem end_mem_tail_support_of_ne {u v : V} (h : u ≠ v) (p : G.Walk u v) : v ∈ p.support.tail := by
obtain ⟨_, _, _, rfl⟩ := exists_eq_cons_of_ne h p
simp
#align simple_graph.walk.end_mem_tail_support_of_ne SimpleGraph.Walk.end_mem_tail_support_of_ne
@[simp, nolint unusedHavesSuffices]
theorem mem_support_append_iff {t u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
t ∈ (p.append p').support ↔ t ∈ p.support ∨ t ∈ p'.support := by
simp only [mem_support_iff, mem_tail_support_append_iff]
obtain rfl | h := eq_or_ne t v <;> obtain rfl | h' := eq_or_ne t u <;>
-- this `have` triggers the unusedHavesSuffices linter:
(try have := h'.symm) <;> simp [*]
#align simple_graph.walk.mem_support_append_iff SimpleGraph.Walk.mem_support_append_iff
@[simp]
theorem subset_support_append_left {V : Type u} {G : SimpleGraph V} {u v w : V}
(p : G.Walk u v) (q : G.Walk v w) : p.support ⊆ (p.append q).support := by
simp only [Walk.support_append, List.subset_append_left]
#align simple_graph.walk.subset_support_append_left SimpleGraph.Walk.subset_support_append_left
@[simp]
theorem subset_support_append_right {V : Type u} {G : SimpleGraph V} {u v w : V}
(p : G.Walk u v) (q : G.Walk v w) : q.support ⊆ (p.append q).support := by
intro h
simp (config := { contextual := true }) only [mem_support_append_iff, or_true_iff, imp_true_iff]
#align simple_graph.walk.subset_support_append_right SimpleGraph.Walk.subset_support_append_right
theorem coe_support {u v : V} (p : G.Walk u v) :
(p.support : Multiset V) = {u} + p.support.tail := by cases p <;> rfl
#align simple_graph.walk.coe_support SimpleGraph.Walk.coe_support
theorem coe_support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
((p.append p').support : Multiset V) = {u} + p.support.tail + p'.support.tail := by
rw [support_append, ← Multiset.coe_add, coe_support]
#align simple_graph.walk.coe_support_append SimpleGraph.Walk.coe_support_append
theorem coe_support_append' [DecidableEq V] {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
((p.append p').support : Multiset V) = p.support + p'.support - {v} := by
rw [support_append, ← Multiset.coe_add]
simp only [coe_support]
rw [add_comm ({v} : Multiset V)]
simp only [← add_assoc, add_tsub_cancel_right]
#align simple_graph.walk.coe_support_append' SimpleGraph.Walk.coe_support_append'
theorem chain_adj_support {u v w : V} (h : G.Adj u v) :
∀ (p : G.Walk v w), List.Chain G.Adj u p.support
| nil => List.Chain.cons h List.Chain.nil
| cons h' p => List.Chain.cons h (chain_adj_support h' p)
#align simple_graph.walk.chain_adj_support SimpleGraph.Walk.chain_adj_support
theorem chain'_adj_support {u v : V} : ∀ (p : G.Walk u v), List.Chain' G.Adj p.support
| nil => List.Chain.nil
| cons h p => chain_adj_support h p
#align simple_graph.walk.chain'_adj_support SimpleGraph.Walk.chain'_adj_support
theorem chain_dartAdj_darts {d : G.Dart} {v w : V} (h : d.snd = v) (p : G.Walk v w) :
List.Chain G.DartAdj d p.darts := by
induction p generalizing d with
| nil => exact List.Chain.nil
-- Porting note: needed to defer `h` and `rfl` to help elaboration
| cons h' p ih => exact List.Chain.cons (by exact h) (ih (by rfl))
#align simple_graph.walk.chain_dart_adj_darts SimpleGraph.Walk.chain_dartAdj_darts
theorem chain'_dartAdj_darts {u v : V} : ∀ (p : G.Walk u v), List.Chain' G.DartAdj p.darts
| nil => trivial
-- Porting note: needed to defer `rfl` to help elaboration
| cons h p => chain_dartAdj_darts (by rfl) p
#align simple_graph.walk.chain'_dart_adj_darts SimpleGraph.Walk.chain'_dartAdj_darts
/-- Every edge in a walk's edge list is an edge of the graph.
It is written in this form (rather than using `⊆`) to avoid unsightly coercions. -/
theorem edges_subset_edgeSet {u v : V} :
∀ (p : G.Walk u v) ⦃e : Sym2 V⦄, e ∈ p.edges → e ∈ G.edgeSet
| cons h' p', e, h => by
cases h
· exact h'
next h' => exact edges_subset_edgeSet p' h'
#align simple_graph.walk.edges_subset_edge_set SimpleGraph.Walk.edges_subset_edgeSet
theorem adj_of_mem_edges {u v x y : V} (p : G.Walk u v) (h : s(x, y) ∈ p.edges) : G.Adj x y :=
edges_subset_edgeSet p h
#align simple_graph.walk.adj_of_mem_edges SimpleGraph.Walk.adj_of_mem_edges
@[simp]
theorem darts_nil {u : V} : (nil : G.Walk u u).darts = [] := rfl
#align simple_graph.walk.darts_nil SimpleGraph.Walk.darts_nil
@[simp]
theorem darts_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).darts = ⟨(u, v), h⟩ :: p.darts := rfl
#align simple_graph.walk.darts_cons SimpleGraph.Walk.darts_cons
@[simp]
theorem darts_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).darts = p.darts.concat ⟨(v, w), h⟩ := by
induction p <;> simp [*, concat_nil]
#align simple_graph.walk.darts_concat SimpleGraph.Walk.darts_concat
@[simp]
theorem darts_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).darts = p.darts := by
subst_vars
rfl
#align simple_graph.walk.darts_copy SimpleGraph.Walk.darts_copy
@[simp]
theorem darts_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').darts = p.darts ++ p'.darts := by
induction p <;> simp [*]
#align simple_graph.walk.darts_append SimpleGraph.Walk.darts_append
@[simp]
theorem darts_reverse {u v : V} (p : G.Walk u v) :
p.reverse.darts = (p.darts.map Dart.symm).reverse := by
induction p <;> simp [*, Sym2.eq_swap]
#align simple_graph.walk.darts_reverse SimpleGraph.Walk.darts_reverse
theorem mem_darts_reverse {u v : V} {d : G.Dart} {p : G.Walk u v} :
d ∈ p.reverse.darts ↔ d.symm ∈ p.darts := by simp
#align simple_graph.walk.mem_darts_reverse SimpleGraph.Walk.mem_darts_reverse
theorem cons_map_snd_darts {u v : V} (p : G.Walk u v) : (u :: p.darts.map (·.snd)) = p.support := by
induction p <;> simp! [*]
#align simple_graph.walk.cons_map_snd_darts SimpleGraph.Walk.cons_map_snd_darts
theorem map_snd_darts {u v : V} (p : G.Walk u v) : p.darts.map (·.snd) = p.support.tail := by
simpa using congr_arg List.tail (cons_map_snd_darts p)
#align simple_graph.walk.map_snd_darts SimpleGraph.Walk.map_snd_darts
theorem map_fst_darts_append {u v : V} (p : G.Walk u v) :
p.darts.map (·.fst) ++ [v] = p.support := by
induction p <;> simp! [*]
#align simple_graph.walk.map_fst_darts_append SimpleGraph.Walk.map_fst_darts_append
theorem map_fst_darts {u v : V} (p : G.Walk u v) : p.darts.map (·.fst) = p.support.dropLast := by
simpa! using congr_arg List.dropLast (map_fst_darts_append p)
#align simple_graph.walk.map_fst_darts SimpleGraph.Walk.map_fst_darts
@[simp]
theorem edges_nil {u : V} : (nil : G.Walk u u).edges = [] := rfl
#align simple_graph.walk.edges_nil SimpleGraph.Walk.edges_nil
@[simp]
theorem edges_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).edges = s(u, v) :: p.edges := rfl
#align simple_graph.walk.edges_cons SimpleGraph.Walk.edges_cons
@[simp]
theorem edges_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).edges = p.edges.concat s(v, w) := by simp [edges]
#align simple_graph.walk.edges_concat SimpleGraph.Walk.edges_concat
@[simp]
theorem edges_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).edges = p.edges := by
subst_vars
rfl
#align simple_graph.walk.edges_copy SimpleGraph.Walk.edges_copy
@[simp]
theorem edges_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').edges = p.edges ++ p'.edges := by simp [edges]
#align simple_graph.walk.edges_append SimpleGraph.Walk.edges_append
@[simp]
theorem edges_reverse {u v : V} (p : G.Walk u v) : p.reverse.edges = p.edges.reverse := by
simp [edges, List.map_reverse]
#align simple_graph.walk.edges_reverse SimpleGraph.Walk.edges_reverse
@[simp]
theorem length_support {u v : V} (p : G.Walk u v) : p.support.length = p.length + 1 := by
induction p <;> simp [*]
#align simple_graph.walk.length_support SimpleGraph.Walk.length_support
@[simp]
theorem length_darts {u v : V} (p : G.Walk u v) : p.darts.length = p.length := by
induction p <;> simp [*]
#align simple_graph.walk.length_darts SimpleGraph.Walk.length_darts
@[simp]
theorem length_edges {u v : V} (p : G.Walk u v) : p.edges.length = p.length := by simp [edges]
#align simple_graph.walk.length_edges SimpleGraph.Walk.length_edges
theorem dart_fst_mem_support_of_mem_darts {u v : V} :
∀ (p : G.Walk u v) {d : G.Dart}, d ∈ p.darts → d.fst ∈ p.support
| cons h p', d, hd => by
simp only [support_cons, darts_cons, List.mem_cons] at hd ⊢
rcases hd with (rfl | hd)
· exact Or.inl rfl
· exact Or.inr (dart_fst_mem_support_of_mem_darts _ hd)
#align simple_graph.walk.dart_fst_mem_support_of_mem_darts SimpleGraph.Walk.dart_fst_mem_support_of_mem_darts
theorem dart_snd_mem_support_of_mem_darts {u v : V} (p : G.Walk u v) {d : G.Dart}
(h : d ∈ p.darts) : d.snd ∈ p.support := by
simpa using p.reverse.dart_fst_mem_support_of_mem_darts (by simp [h] : d.symm ∈ p.reverse.darts)
#align simple_graph.walk.dart_snd_mem_support_of_mem_darts SimpleGraph.Walk.dart_snd_mem_support_of_mem_darts
theorem fst_mem_support_of_mem_edges {t u v w : V} (p : G.Walk v w) (he : s(t, u) ∈ p.edges) :
t ∈ p.support := by
obtain ⟨d, hd, he⟩ := List.mem_map.mp he
rw [dart_edge_eq_mk'_iff'] at he
rcases he with (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩)
· exact dart_fst_mem_support_of_mem_darts _ hd
· exact dart_snd_mem_support_of_mem_darts _ hd
#align simple_graph.walk.fst_mem_support_of_mem_edges SimpleGraph.Walk.fst_mem_support_of_mem_edges
theorem snd_mem_support_of_mem_edges {t u v w : V} (p : G.Walk v w) (he : s(t, u) ∈ p.edges) :
u ∈ p.support := by
rw [Sym2.eq_swap] at he
exact p.fst_mem_support_of_mem_edges he
#align simple_graph.walk.snd_mem_support_of_mem_edges SimpleGraph.Walk.snd_mem_support_of_mem_edges
theorem darts_nodup_of_support_nodup {u v : V} {p : G.Walk u v} (h : p.support.Nodup) :
p.darts.Nodup := by
induction p with
| nil => simp
| cons _ p' ih =>
simp only [darts_cons, support_cons, List.nodup_cons] at h ⊢
exact ⟨fun h' => h.1 (dart_fst_mem_support_of_mem_darts p' h'), ih h.2⟩
#align simple_graph.walk.darts_nodup_of_support_nodup SimpleGraph.Walk.darts_nodup_of_support_nodup
theorem edges_nodup_of_support_nodup {u v : V} {p : G.Walk u v} (h : p.support.Nodup) :
p.edges.Nodup := by
induction p with
| nil => simp
| cons _ p' ih =>
simp only [edges_cons, support_cons, List.nodup_cons] at h ⊢
exact ⟨fun h' => h.1 (fst_mem_support_of_mem_edges p' h'), ih h.2⟩
#align simple_graph.walk.edges_nodup_of_support_nodup SimpleGraph.Walk.edges_nodup_of_support_nodup
/-- Predicate for the empty walk.
Solves the dependent type problem where `p = G.Walk.nil` typechecks
only if `p` has defeq endpoints. -/
inductive Nil : {v w : V} → G.Walk v w → Prop
| nil {u : V} : Nil (nil : G.Walk u u)
variable {u v w : V}
@[simp] lemma nil_nil : (nil : G.Walk u u).Nil := Nil.nil
@[simp] lemma not_nil_cons {h : G.Adj u v} {p : G.Walk v w} : ¬ (cons h p).Nil := nofun
instance (p : G.Walk v w) : Decidable p.Nil :=
match p with
| nil => isTrue .nil
| cons _ _ => isFalse nofun
protected lemma Nil.eq {p : G.Walk v w} : p.Nil → v = w | .nil => rfl
lemma not_nil_of_ne {p : G.Walk v w} : v ≠ w → ¬ p.Nil := mt Nil.eq
lemma nil_iff_support_eq {p : G.Walk v w} : p.Nil ↔ p.support = [v] := by
cases p <;> simp
lemma nil_iff_length_eq {p : G.Walk v w} : p.Nil ↔ p.length = 0 := by
cases p <;> simp
lemma not_nil_iff {p : G.Walk v w} :
¬ p.Nil ↔ ∃ (u : V) (h : G.Adj v u) (q : G.Walk u w), p = cons h q := by
cases p <;> simp [*]
/-- A walk with its endpoints defeq is `Nil` if and only if it is equal to `nil`. -/
lemma nil_iff_eq_nil : ∀ {p : G.Walk v v}, p.Nil ↔ p = nil
| .nil | .cons _ _ => by simp
alias ⟨Nil.eq_nil, _⟩ := nil_iff_eq_nil
@[elab_as_elim]
def notNilRec {motive : {u w : V} → (p : G.Walk u w) → (h : ¬ p.Nil) → Sort*}
(cons : {u v w : V} → (h : G.Adj u v) → (q : G.Walk v w) → motive (cons h q) not_nil_cons)
(p : G.Walk u w) : (hp : ¬ p.Nil) → motive p hp :=
match p with
| nil => fun hp => absurd .nil hp
| .cons h q => fun _ => cons h q
/-- The second vertex along a non-nil walk. -/
def sndOfNotNil (p : G.Walk v w) (hp : ¬ p.Nil) : V :=
p.notNilRec (@fun _ u _ _ _ => u) hp
@[simp] lemma adj_sndOfNotNil {p : G.Walk v w} (hp : ¬ p.Nil) :
G.Adj v (p.sndOfNotNil hp) :=
p.notNilRec (fun h _ => h) hp
/-- The walk obtained by removing the first dart of a non-nil walk. -/
def tail (p : G.Walk u v) (hp : ¬ p.Nil) : G.Walk (p.sndOfNotNil hp) v :=
p.notNilRec (fun _ q => q) hp
/-- The first dart of a walk. -/
@[simps]
def firstDart (p : G.Walk v w) (hp : ¬ p.Nil) : G.Dart where
fst := v
snd := p.sndOfNotNil hp
adj := p.adj_sndOfNotNil hp
lemma edge_firstDart (p : G.Walk v w) (hp : ¬ p.Nil) :
(p.firstDart hp).edge = s(v, p.sndOfNotNil hp) := rfl
variable {x y : V} -- TODO: rename to u, v, w instead?
@[simp] lemma cons_tail_eq (p : G.Walk x y) (hp : ¬ p.Nil) :
cons (p.adj_sndOfNotNil hp) (p.tail hp) = p :=
p.notNilRec (fun _ _ => rfl) hp
@[simp] lemma cons_support_tail (p : G.Walk x y) (hp : ¬p.Nil) :
x :: (p.tail hp).support = p.support := by
rw [← support_cons, cons_tail_eq]
@[simp] lemma length_tail_add_one {p : G.Walk x y} (hp : ¬ p.Nil) :
(p.tail hp).length + 1 = p.length := by
rw [← length_cons, cons_tail_eq]
@[simp] lemma nil_copy {x' y' : V} {p : G.Walk x y} (hx : x = x') (hy : y = y') :
(p.copy hx hy).Nil = p.Nil := by
subst_vars; rfl
@[simp] lemma support_tail (p : G.Walk v v) (hp) :
(p.tail hp).support = p.support.tail := by
rw [← cons_support_tail p hp, List.tail_cons]
/-! ### Trails, paths, circuits, cycles -/
/-- A *trail* is a walk with no repeating edges. -/
@[mk_iff isTrail_def]
structure IsTrail {u v : V} (p : G.Walk u v) : Prop where
edges_nodup : p.edges.Nodup
#align simple_graph.walk.is_trail SimpleGraph.Walk.IsTrail
#align simple_graph.walk.is_trail_def SimpleGraph.Walk.isTrail_def
/-- A *path* is a walk with no repeating vertices.
Use `SimpleGraph.Walk.IsPath.mk'` for a simpler constructor. -/
structure IsPath {u v : V} (p : G.Walk u v) extends IsTrail p : Prop where
support_nodup : p.support.Nodup
#align simple_graph.walk.is_path SimpleGraph.Walk.IsPath
-- Porting note: used to use `extends to_trail : is_trail p` in structure
protected lemma IsPath.isTrail {p : Walk G u v}(h : IsPath p) : IsTrail p := h.toIsTrail
#align simple_graph.walk.is_path.to_trail SimpleGraph.Walk.IsPath.isTrail
/-- A *circuit* at `u : V` is a nonempty trail beginning and ending at `u`. -/
@[mk_iff isCircuit_def]
structure IsCircuit {u : V} (p : G.Walk u u) extends IsTrail p : Prop where
ne_nil : p ≠ nil
#align simple_graph.walk.is_circuit SimpleGraph.Walk.IsCircuit
#align simple_graph.walk.is_circuit_def SimpleGraph.Walk.isCircuit_def
-- Porting note: used to use `extends to_trail : is_trail p` in structure
protected lemma IsCircuit.isTrail {p : Walk G u u} (h : IsCircuit p) : IsTrail p := h.toIsTrail
#align simple_graph.walk.is_circuit.to_trail SimpleGraph.Walk.IsCircuit.isTrail
/-- A *cycle* at `u : V` is a circuit at `u` whose only repeating vertex
is `u` (which appears exactly twice). -/
structure IsCycle {u : V} (p : G.Walk u u) extends IsCircuit p : Prop where
support_nodup : p.support.tail.Nodup
#align simple_graph.walk.is_cycle SimpleGraph.Walk.IsCycle
-- Porting note: used to use `extends to_circuit : is_circuit p` in structure
protected lemma IsCycle.isCircuit {p : Walk G u u} (h : IsCycle p) : IsCircuit p := h.toIsCircuit
#align simple_graph.walk.is_cycle.to_circuit SimpleGraph.Walk.IsCycle.isCircuit
@[simp]
theorem isTrail_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).IsTrail ↔ p.IsTrail := by
subst_vars
rfl
#align simple_graph.walk.is_trail_copy SimpleGraph.Walk.isTrail_copy
theorem IsPath.mk' {u v : V} {p : G.Walk u v} (h : p.support.Nodup) : p.IsPath :=
⟨⟨edges_nodup_of_support_nodup h⟩, h⟩
#align simple_graph.walk.is_path.mk' SimpleGraph.Walk.IsPath.mk'
theorem isPath_def {u v : V} (p : G.Walk u v) : p.IsPath ↔ p.support.Nodup :=
⟨IsPath.support_nodup, IsPath.mk'⟩
#align simple_graph.walk.is_path_def SimpleGraph.Walk.isPath_def
@[simp]
theorem isPath_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).IsPath ↔ p.IsPath := by
subst_vars
rfl
#align simple_graph.walk.is_path_copy SimpleGraph.Walk.isPath_copy
@[simp]
theorem isCircuit_copy {u u'} (p : G.Walk u u) (hu : u = u') :
(p.copy hu hu).IsCircuit ↔ p.IsCircuit := by
subst_vars
rfl
#align simple_graph.walk.is_circuit_copy SimpleGraph.Walk.isCircuit_copy
lemma IsCircuit.not_nil {p : G.Walk v v} (hp : IsCircuit p) : ¬ p.Nil := (hp.ne_nil ·.eq_nil)
theorem isCycle_def {u : V} (p : G.Walk u u) :
p.IsCycle ↔ p.IsTrail ∧ p ≠ nil ∧ p.support.tail.Nodup :=
Iff.intro (fun h => ⟨h.1.1, h.1.2, h.2⟩) fun h => ⟨⟨h.1, h.2.1⟩, h.2.2⟩
#align simple_graph.walk.is_cycle_def SimpleGraph.Walk.isCycle_def
@[simp]
theorem isCycle_copy {u u'} (p : G.Walk u u) (hu : u = u') :
(p.copy hu hu).IsCycle ↔ p.IsCycle := by
subst_vars
rfl
#align simple_graph.walk.is_cycle_copy SimpleGraph.Walk.isCycle_copy
lemma IsCycle.not_nil {p : G.Walk v v} (hp : IsCycle p) : ¬ p.Nil := (hp.ne_nil ·.eq_nil)
@[simp]
theorem IsTrail.nil {u : V} : (nil : G.Walk u u).IsTrail :=
⟨by simp [edges]⟩
#align simple_graph.walk.is_trail.nil SimpleGraph.Walk.IsTrail.nil
theorem IsTrail.of_cons {u v w : V} {h : G.Adj u v} {p : G.Walk v w} :
(cons h p).IsTrail → p.IsTrail := by simp [isTrail_def]
#align simple_graph.walk.is_trail.of_cons SimpleGraph.Walk.IsTrail.of_cons
@[simp]
theorem cons_isTrail_iff {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).IsTrail ↔ p.IsTrail ∧ s(u, v) ∉ p.edges := by simp [isTrail_def, and_comm]
#align simple_graph.walk.cons_is_trail_iff SimpleGraph.Walk.cons_isTrail_iff
theorem IsTrail.reverse {u v : V} (p : G.Walk u v) (h : p.IsTrail) : p.reverse.IsTrail := by
simpa [isTrail_def] using h
#align simple_graph.walk.is_trail.reverse SimpleGraph.Walk.IsTrail.reverse
@[simp]
theorem reverse_isTrail_iff {u v : V} (p : G.Walk u v) : p.reverse.IsTrail ↔ p.IsTrail := by
constructor <;>
· intro h
convert h.reverse _
try rw [reverse_reverse]
#align simple_graph.walk.reverse_is_trail_iff SimpleGraph.Walk.reverse_isTrail_iff
theorem IsTrail.of_append_left {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsTrail) : p.IsTrail := by
rw [isTrail_def, edges_append, List.nodup_append] at h
exact ⟨h.1⟩
#align simple_graph.walk.is_trail.of_append_left SimpleGraph.Walk.IsTrail.of_append_left
theorem IsTrail.of_append_right {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsTrail) : q.IsTrail := by
rw [isTrail_def, edges_append, List.nodup_append] at h
exact ⟨h.2.1⟩
#align simple_graph.walk.is_trail.of_append_right SimpleGraph.Walk.IsTrail.of_append_right
theorem IsTrail.count_edges_le_one [DecidableEq V] {u v : V} {p : G.Walk u v} (h : p.IsTrail)
(e : Sym2 V) : p.edges.count e ≤ 1 :=
List.nodup_iff_count_le_one.mp h.edges_nodup e
#align simple_graph.walk.is_trail.count_edges_le_one SimpleGraph.Walk.IsTrail.count_edges_le_one
theorem IsTrail.count_edges_eq_one [DecidableEq V] {u v : V} {p : G.Walk u v} (h : p.IsTrail)
{e : Sym2 V} (he : e ∈ p.edges) : p.edges.count e = 1 :=
List.count_eq_one_of_mem h.edges_nodup he
#align simple_graph.walk.is_trail.count_edges_eq_one SimpleGraph.Walk.IsTrail.count_edges_eq_one
theorem IsPath.nil {u : V} : (nil : G.Walk u u).IsPath := by constructor <;> simp
#align simple_graph.walk.is_path.nil SimpleGraph.Walk.IsPath.nil
theorem IsPath.of_cons {u v w : V} {h : G.Adj u v} {p : G.Walk v w} :
(cons h p).IsPath → p.IsPath := by simp [isPath_def]
#align simple_graph.walk.is_path.of_cons SimpleGraph.Walk.IsPath.of_cons
@[simp]
theorem cons_isPath_iff {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).IsPath ↔ p.IsPath ∧ u ∉ p.support := by
constructor <;> simp (config := { contextual := true }) [isPath_def]
#align simple_graph.walk.cons_is_path_iff SimpleGraph.Walk.cons_isPath_iff
protected lemma IsPath.cons {p : Walk G v w} (hp : p.IsPath) (hu : u ∉ p.support) {h : G.Adj u v} :
(cons h p).IsPath :=
(cons_isPath_iff _ _).2 ⟨hp, hu⟩
@[simp]
theorem isPath_iff_eq_nil {u : V} (p : G.Walk u u) : p.IsPath ↔ p = nil := by
cases p <;> simp [IsPath.nil]
#align simple_graph.walk.is_path_iff_eq_nil SimpleGraph.Walk.isPath_iff_eq_nil
theorem IsPath.reverse {u v : V} {p : G.Walk u v} (h : p.IsPath) : p.reverse.IsPath := by
simpa [isPath_def] using h
#align simple_graph.walk.is_path.reverse SimpleGraph.Walk.IsPath.reverse
@[simp]
theorem isPath_reverse_iff {u v : V} (p : G.Walk u v) : p.reverse.IsPath ↔ p.IsPath := by
constructor <;> intro h <;> convert h.reverse; simp
#align simple_graph.walk.is_path_reverse_iff SimpleGraph.Walk.isPath_reverse_iff
theorem IsPath.of_append_left {u v w : V} {p : G.Walk u v} {q : G.Walk v w} :
(p.append q).IsPath → p.IsPath := by
simp only [isPath_def, support_append]
exact List.Nodup.of_append_left
#align simple_graph.walk.is_path.of_append_left SimpleGraph.Walk.IsPath.of_append_left
theorem IsPath.of_append_right {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsPath) : q.IsPath := by
rw [← isPath_reverse_iff] at h ⊢
rw [reverse_append] at h
apply h.of_append_left
#align simple_graph.walk.is_path.of_append_right SimpleGraph.Walk.IsPath.of_append_right
@[simp]
theorem IsCycle.not_of_nil {u : V} : ¬(nil : G.Walk u u).IsCycle := fun h => h.ne_nil rfl
#align simple_graph.walk.is_cycle.not_of_nil SimpleGraph.Walk.IsCycle.not_of_nil
lemma IsCycle.ne_bot : ∀ {p : G.Walk u u}, p.IsCycle → G ≠ ⊥
| nil, hp => by cases hp.ne_nil rfl
| cons h _, hp => by rintro rfl; exact h
lemma IsCycle.three_le_length {v : V} {p : G.Walk v v} (hp : p.IsCycle) : 3 ≤ p.length := by
have ⟨⟨hp, hp'⟩, _⟩ := hp
match p with
| .nil => simp at hp'
| .cons h .nil => simp at h
| .cons _ (.cons _ .nil) => simp at hp
| .cons _ (.cons _ (.cons _ _)) => simp_rw [SimpleGraph.Walk.length_cons]; omega
theorem cons_isCycle_iff {u v : V} (p : G.Walk v u) (h : G.Adj u v) :
(Walk.cons h p).IsCycle ↔ p.IsPath ∧ ¬s(u, v) ∈ p.edges := by
simp only [Walk.isCycle_def, Walk.isPath_def, Walk.isTrail_def, edges_cons, List.nodup_cons,
support_cons, List.tail_cons]
have : p.support.Nodup → p.edges.Nodup := edges_nodup_of_support_nodup
tauto
#align simple_graph.walk.cons_is_cycle_iff SimpleGraph.Walk.cons_isCycle_iff
lemma IsPath.tail {p : G.Walk u v} (hp : p.IsPath) (hp' : ¬ p.Nil) : (p.tail hp').IsPath := by
rw [Walk.isPath_def] at hp ⊢
rw [← cons_support_tail _ hp', List.nodup_cons] at hp
exact hp.2
/-! ### About paths -/
instance [DecidableEq V] {u v : V} (p : G.Walk u v) : Decidable p.IsPath := by
rw [isPath_def]
infer_instance
theorem IsPath.length_lt [Fintype V] {u v : V} {p : G.Walk u v} (hp : p.IsPath) :
p.length < Fintype.card V := by
rw [Nat.lt_iff_add_one_le, ← length_support]
exact hp.support_nodup.length_le_card
#align simple_graph.walk.is_path.length_lt SimpleGraph.Walk.IsPath.length_lt
/-! ### Walk decompositions -/
section WalkDecomp
variable [DecidableEq V]
/-- Given a vertex in the support of a path, give the path up until (and including) that vertex. -/
def takeUntil {v w : V} : ∀ (p : G.Walk v w) (u : V), u ∈ p.support → G.Walk v u
| nil, u, h => by rw [mem_support_nil_iff.mp h]
| cons r p, u, h =>
if hx : v = u then
by subst u; exact Walk.nil
else
cons r (takeUntil p u <| by
cases h
· exact (hx rfl).elim
· assumption)
#align simple_graph.walk.take_until SimpleGraph.Walk.takeUntil
/-- Given a vertex in the support of a path, give the path from (and including) that vertex to
the end. In other words, drop vertices from the front of a path until (and not including)
that vertex. -/
def dropUntil {v w : V} : ∀ (p : G.Walk v w) (u : V), u ∈ p.support → G.Walk u w
| nil, u, h => by rw [mem_support_nil_iff.mp h]
| cons r p, u, h =>
if hx : v = u then by
subst u
exact cons r p
else dropUntil p u <| by
cases h
· exact (hx rfl).elim
· assumption
#align simple_graph.walk.drop_until SimpleGraph.Walk.dropUntil
/-- The `takeUntil` and `dropUntil` functions split a walk into two pieces.
The lemma `SimpleGraph.Walk.count_support_takeUntil_eq_one` specifies where this split occurs. -/
@[simp]
theorem take_spec {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).append (p.dropUntil u h) = p := by
induction p
· rw [mem_support_nil_iff] at h
subst u
rfl
· cases h
· simp!
· simp! only
split_ifs with h' <;> subst_vars <;> simp [*]
#align simple_graph.walk.take_spec SimpleGraph.Walk.take_spec
theorem mem_support_iff_exists_append {V : Type u} {G : SimpleGraph V} {u v w : V}
{p : G.Walk u v} : w ∈ p.support ↔ ∃ (q : G.Walk u w) (r : G.Walk w v), p = q.append r := by
classical
constructor
· exact fun h => ⟨_, _, (p.take_spec h).symm⟩
· rintro ⟨q, r, rfl⟩
simp only [mem_support_append_iff, end_mem_support, start_mem_support, or_self_iff]
#align simple_graph.walk.mem_support_iff_exists_append SimpleGraph.Walk.mem_support_iff_exists_append
@[simp]
theorem count_support_takeUntil_eq_one {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).support.count u = 1 := by
induction p
· rw [mem_support_nil_iff] at h
subst u
simp!
· cases h
· simp!
· simp! only
split_ifs with h' <;> rw [eq_comm] at h' <;> subst_vars <;> simp! [*, List.count_cons]
#align simple_graph.walk.count_support_take_until_eq_one SimpleGraph.Walk.count_support_takeUntil_eq_one
theorem count_edges_takeUntil_le_one {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) (x : V) :
(p.takeUntil u h).edges.count s(u, x) ≤ 1 := by
induction' p with u' u' v' w' ha p' ih
· rw [mem_support_nil_iff] at h
subst u
simp!
· cases h
· simp!
· simp! only
split_ifs with h'
· subst h'
simp
· rw [edges_cons, List.count_cons]
split_ifs with h''
· rw [Sym2.eq_iff] at h''
obtain ⟨rfl, rfl⟩ | ⟨rfl, rfl⟩ := h''
· exact (h' rfl).elim
· cases p' <;> simp!
· apply ih
#align simple_graph.walk.count_edges_take_until_le_one SimpleGraph.Walk.count_edges_takeUntil_le_one
@[simp]
theorem takeUntil_copy {u v w v' w'} (p : G.Walk v w) (hv : v = v') (hw : w = w')
(h : u ∈ (p.copy hv hw).support) :
(p.copy hv hw).takeUntil u h = (p.takeUntil u (by subst_vars; exact h)).copy hv rfl := by
subst_vars
rfl
#align simple_graph.walk.take_until_copy SimpleGraph.Walk.takeUntil_copy
@[simp]
theorem dropUntil_copy {u v w v' w'} (p : G.Walk v w) (hv : v = v') (hw : w = w')
(h : u ∈ (p.copy hv hw).support) :
(p.copy hv hw).dropUntil u h = (p.dropUntil u (by subst_vars; exact h)).copy rfl hw := by
subst_vars
rfl
#align simple_graph.walk.drop_until_copy SimpleGraph.Walk.dropUntil_copy
theorem support_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).support ⊆ p.support := fun x hx => by
rw [← take_spec p h, mem_support_append_iff]
exact Or.inl hx
#align simple_graph.walk.support_take_until_subset SimpleGraph.Walk.support_takeUntil_subset
theorem support_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).support ⊆ p.support := fun x hx => by
rw [← take_spec p h, mem_support_append_iff]
exact Or.inr hx
#align simple_graph.walk.support_drop_until_subset SimpleGraph.Walk.support_dropUntil_subset
theorem darts_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).darts ⊆ p.darts := fun x hx => by
rw [← take_spec p h, darts_append, List.mem_append]
exact Or.inl hx
#align simple_graph.walk.darts_take_until_subset SimpleGraph.Walk.darts_takeUntil_subset
theorem darts_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).darts ⊆ p.darts := fun x hx => by
rw [← take_spec p h, darts_append, List.mem_append]
exact Or.inr hx
#align simple_graph.walk.darts_drop_until_subset SimpleGraph.Walk.darts_dropUntil_subset
theorem edges_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).edges ⊆ p.edges :=
List.map_subset _ (p.darts_takeUntil_subset h)
#align simple_graph.walk.edges_take_until_subset SimpleGraph.Walk.edges_takeUntil_subset
theorem edges_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).edges ⊆ p.edges :=
List.map_subset _ (p.darts_dropUntil_subset h)
#align simple_graph.walk.edges_drop_until_subset SimpleGraph.Walk.edges_dropUntil_subset
theorem length_takeUntil_le {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).length ≤ p.length := by
have := congr_arg Walk.length (p.take_spec h)
rw [length_append] at this
exact Nat.le.intro this
#align simple_graph.walk.length_take_until_le SimpleGraph.Walk.length_takeUntil_le
theorem length_dropUntil_le {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).length ≤ p.length := by
have := congr_arg Walk.length (p.take_spec h)
rw [length_append, add_comm] at this
exact Nat.le.intro this
#align simple_graph.walk.length_drop_until_le SimpleGraph.Walk.length_dropUntil_le
protected theorem IsTrail.takeUntil {u v w : V} {p : G.Walk v w} (hc : p.IsTrail)
(h : u ∈ p.support) : (p.takeUntil u h).IsTrail :=
IsTrail.of_append_left (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_trail.take_until SimpleGraph.Walk.IsTrail.takeUntil
protected theorem IsTrail.dropUntil {u v w : V} {p : G.Walk v w} (hc : p.IsTrail)
(h : u ∈ p.support) : (p.dropUntil u h).IsTrail :=
IsTrail.of_append_right (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_trail.drop_until SimpleGraph.Walk.IsTrail.dropUntil
protected theorem IsPath.takeUntil {u v w : V} {p : G.Walk v w} (hc : p.IsPath)
(h : u ∈ p.support) : (p.takeUntil u h).IsPath :=
IsPath.of_append_left (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_path.take_until SimpleGraph.Walk.IsPath.takeUntil
-- Porting note: p was previously accidentally an explicit argument
protected theorem IsPath.dropUntil {u v w : V} {p : G.Walk v w} (hc : p.IsPath)
(h : u ∈ p.support) : (p.dropUntil u h).IsPath :=
IsPath.of_append_right (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_path.drop_until SimpleGraph.Walk.IsPath.dropUntil
/-- Rotate a loop walk such that it is centered at the given vertex. -/
def rotate {u v : V} (c : G.Walk v v) (h : u ∈ c.support) : G.Walk u u :=
(c.dropUntil u h).append (c.takeUntil u h)
#align simple_graph.walk.rotate SimpleGraph.Walk.rotate
@[simp]
theorem support_rotate {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).support.tail ~r c.support.tail := by
simp only [rotate, tail_support_append]
apply List.IsRotated.trans List.isRotated_append
rw [← tail_support_append, take_spec]
#align simple_graph.walk.support_rotate SimpleGraph.Walk.support_rotate
theorem rotate_darts {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).darts ~r c.darts := by
simp only [rotate, darts_append]
apply List.IsRotated.trans List.isRotated_append
rw [← darts_append, take_spec]
#align simple_graph.walk.rotate_darts SimpleGraph.Walk.rotate_darts
theorem rotate_edges {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).edges ~r c.edges :=
(rotate_darts c h).map _
#align simple_graph.walk.rotate_edges SimpleGraph.Walk.rotate_edges
protected theorem IsTrail.rotate {u v : V} {c : G.Walk v v} (hc : c.IsTrail) (h : u ∈ c.support) :
(c.rotate h).IsTrail := by
rw [isTrail_def, (c.rotate_edges h).perm.nodup_iff]
exact hc.edges_nodup
#align simple_graph.walk.is_trail.rotate SimpleGraph.Walk.IsTrail.rotate
protected theorem IsCircuit.rotate {u v : V} {c : G.Walk v v} (hc : c.IsCircuit)
(h : u ∈ c.support) : (c.rotate h).IsCircuit := by
refine ⟨hc.isTrail.rotate _, ?_⟩
cases c
· exact (hc.ne_nil rfl).elim
· intro hn
have hn' := congr_arg length hn
rw [rotate, length_append, add_comm, ← length_append, take_spec] at hn'
simp at hn'
#align simple_graph.walk.is_circuit.rotate SimpleGraph.Walk.IsCircuit.rotate
protected theorem IsCycle.rotate {u v : V} {c : G.Walk v v} (hc : c.IsCycle) (h : u ∈ c.support) :
(c.rotate h).IsCycle := by
refine ⟨hc.isCircuit.rotate _, ?_⟩
rw [List.IsRotated.nodup_iff (support_rotate _ _)]
exact hc.support_nodup
#align simple_graph.walk.is_cycle.rotate SimpleGraph.Walk.IsCycle.rotate
end WalkDecomp
/-- Given a set `S` and a walk `w` from `u` to `v` such that `u ∈ S` but `v ∉ S`,
there exists a dart in the walk whose start is in `S` but whose end is not. -/
theorem exists_boundary_dart {u v : V} (p : G.Walk u v) (S : Set V) (uS : u ∈ S) (vS : v ∉ S) :
∃ d : G.Dart, d ∈ p.darts ∧ d.fst ∈ S ∧ d.snd ∉ S := by
induction' p with _ x y w a p' ih
· cases vS uS
· by_cases h : y ∈ S
· obtain ⟨d, hd, hcd⟩ := ih h vS
exact ⟨d, List.Mem.tail _ hd, hcd⟩
· exact ⟨⟨(x, y), a⟩, List.Mem.head _, uS, h⟩
#align simple_graph.walk.exists_boundary_dart SimpleGraph.Walk.exists_boundary_dart
end Walk
/-! ### Type of paths -/
/-- The type for paths between two vertices. -/
abbrev Path (u v : V) := { p : G.Walk u v // p.IsPath }
#align simple_graph.path SimpleGraph.Path
namespace Path
variable {G G'}
@[simp]
protected theorem isPath {u v : V} (p : G.Path u v) : (p : G.Walk u v).IsPath := p.property
#align simple_graph.path.is_path SimpleGraph.Path.isPath
@[simp]
protected theorem isTrail {u v : V} (p : G.Path u v) : (p : G.Walk u v).IsTrail :=
p.property.isTrail
#align simple_graph.path.is_trail SimpleGraph.Path.isTrail
/-- The length-0 path at a vertex. -/
@[refl, simps]
protected def nil {u : V} : G.Path u u :=
⟨Walk.nil, Walk.IsPath.nil⟩
#align simple_graph.path.nil SimpleGraph.Path.nil
/-- The length-1 path between a pair of adjacent vertices. -/
@[simps]
def singleton {u v : V} (h : G.Adj u v) : G.Path u v :=
⟨Walk.cons h Walk.nil, by simp [h.ne]⟩
#align simple_graph.path.singleton SimpleGraph.Path.singleton
theorem mk'_mem_edges_singleton {u v : V} (h : G.Adj u v) :
s(u, v) ∈ (singleton h : G.Walk u v).edges := by simp [singleton]
#align simple_graph.path.mk_mem_edges_singleton SimpleGraph.Path.mk'_mem_edges_singleton
/-- The reverse of a path is another path. See also `SimpleGraph.Walk.reverse`. -/
@[symm, simps]
def reverse {u v : V} (p : G.Path u v) : G.Path v u :=
⟨Walk.reverse p, p.property.reverse⟩
#align simple_graph.path.reverse SimpleGraph.Path.reverse
theorem count_support_eq_one [DecidableEq V] {u v w : V} {p : G.Path u v}
(hw : w ∈ (p : G.Walk u v).support) : (p : G.Walk u v).support.count w = 1 :=
List.count_eq_one_of_mem p.property.support_nodup hw
#align simple_graph.path.count_support_eq_one SimpleGraph.Path.count_support_eq_one
theorem count_edges_eq_one [DecidableEq V] {u v : V} {p : G.Path u v} (e : Sym2 V)
(hw : e ∈ (p : G.Walk u v).edges) : (p : G.Walk u v).edges.count e = 1 :=
List.count_eq_one_of_mem p.property.isTrail.edges_nodup hw
#align simple_graph.path.count_edges_eq_one SimpleGraph.Path.count_edges_eq_one
@[simp]
theorem nodup_support {u v : V} (p : G.Path u v) : (p : G.Walk u v).support.Nodup :=
(Walk.isPath_def _).mp p.property
#align simple_graph.path.nodup_support SimpleGraph.Path.nodup_support
theorem loop_eq {v : V} (p : G.Path v v) : p = Path.nil := by
obtain ⟨_ | _, h⟩ := p
· rfl
· simp at h
#align simple_graph.path.loop_eq SimpleGraph.Path.loop_eq
theorem not_mem_edges_of_loop {v : V} {e : Sym2 V} {p : G.Path v v} :
¬e ∈ (p : G.Walk v v).edges := by simp [p.loop_eq]
#align simple_graph.path.not_mem_edges_of_loop SimpleGraph.Path.not_mem_edges_of_loop
theorem cons_isCycle {u v : V} (p : G.Path v u) (h : G.Adj u v)
(he : ¬s(u, v) ∈ (p : G.Walk v u).edges) : (Walk.cons h ↑p).IsCycle := by
simp [Walk.isCycle_def, Walk.cons_isTrail_iff, he]
#align simple_graph.path.cons_is_cycle SimpleGraph.Path.cons_isCycle
end Path
/-! ### Walks to paths -/
namespace Walk
variable {G} [DecidableEq V]
/-- Given a walk, produces a walk from it by bypassing subwalks between repeated vertices.
The result is a path, as shown in `SimpleGraph.Walk.bypass_isPath`.
This is packaged up in `SimpleGraph.Walk.toPath`. -/
def bypass {u v : V} : G.Walk u v → G.Walk u v
| nil => nil
| cons ha p =>
let p' := p.bypass
if hs : u ∈ p'.support then
p'.dropUntil u hs
else
cons ha p'
#align simple_graph.walk.bypass SimpleGraph.Walk.bypass
@[simp]
theorem bypass_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).bypass = p.bypass.copy hu hv := by
subst_vars
rfl
#align simple_graph.walk.bypass_copy SimpleGraph.Walk.bypass_copy
theorem bypass_isPath {u v : V} (p : G.Walk u v) : p.bypass.IsPath := by
induction p with
| nil => simp!
| cons _ p' ih =>
simp only [bypass]
split_ifs with hs
· exact ih.dropUntil hs
· simp [*, cons_isPath_iff]
#align simple_graph.walk.bypass_is_path SimpleGraph.Walk.bypass_isPath
theorem length_bypass_le {u v : V} (p : G.Walk u v) : p.bypass.length ≤ p.length := by
induction p with
| nil => rfl
| cons _ _ ih =>
simp only [bypass]
split_ifs
· trans
· apply length_dropUntil_le
rw [length_cons]
omega
· rw [length_cons, length_cons]
exact Nat.add_le_add_right ih 1
#align simple_graph.walk.length_bypass_le SimpleGraph.Walk.length_bypass_le
lemma bypass_eq_self_of_length_le {u v : V} (p : G.Walk u v) (h : p.length ≤ p.bypass.length) :
p.bypass = p := by
induction p with
| nil => rfl
| cons h p ih =>
simp only [Walk.bypass]
split_ifs with hb
· exfalso
simp only [hb, Walk.bypass, Walk.length_cons, dif_pos] at h
apply Nat.not_succ_le_self p.length
calc p.length + 1
_ ≤ (p.bypass.dropUntil _ _).length := h
_ ≤ p.bypass.length := Walk.length_dropUntil_le p.bypass hb
_ ≤ p.length := Walk.length_bypass_le _
· simp only [hb, Walk.bypass, Walk.length_cons, not_false_iff, dif_neg,
Nat.add_le_add_iff_right] at h
rw [ih h]
/-- Given a walk, produces a path with the same endpoints using `SimpleGraph.Walk.bypass`. -/
def toPath {u v : V} (p : G.Walk u v) : G.Path u v :=
⟨p.bypass, p.bypass_isPath⟩
#align simple_graph.walk.to_path SimpleGraph.Walk.toPath
theorem support_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.support ⊆ p.support := by
induction p with
| nil => simp!
| cons _ _ ih =>
simp! only
split_ifs
· apply List.Subset.trans (support_dropUntil_subset _ _)
apply List.subset_cons_of_subset
assumption
· rw [support_cons]
apply List.cons_subset_cons
assumption
#align simple_graph.walk.support_bypass_subset SimpleGraph.Walk.support_bypass_subset
theorem support_toPath_subset {u v : V} (p : G.Walk u v) :
(p.toPath : G.Walk u v).support ⊆ p.support :=
support_bypass_subset _
#align simple_graph.walk.support_to_path_subset SimpleGraph.Walk.support_toPath_subset
theorem darts_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.darts ⊆ p.darts := by
induction p with
| nil => simp!
| cons _ _ ih =>
simp! only
split_ifs
· apply List.Subset.trans (darts_dropUntil_subset _ _)
apply List.subset_cons_of_subset _ ih
· rw [darts_cons]
exact List.cons_subset_cons _ ih
#align simple_graph.walk.darts_bypass_subset SimpleGraph.Walk.darts_bypass_subset
theorem edges_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.edges ⊆ p.edges :=
List.map_subset _ p.darts_bypass_subset
#align simple_graph.walk.edges_bypass_subset SimpleGraph.Walk.edges_bypass_subset
theorem darts_toPath_subset {u v : V} (p : G.Walk u v) : (p.toPath : G.Walk u v).darts ⊆ p.darts :=
darts_bypass_subset _
#align simple_graph.walk.darts_to_path_subset SimpleGraph.Walk.darts_toPath_subset
theorem edges_toPath_subset {u v : V} (p : G.Walk u v) : (p.toPath : G.Walk u v).edges ⊆ p.edges :=
edges_bypass_subset _
#align simple_graph.walk.edges_to_path_subset SimpleGraph.Walk.edges_toPath_subset
end Walk
/-! ### Mapping paths -/
namespace Walk
variable {G G' G''}
/-- Given a graph homomorphism, map walks to walks. -/
protected def map (f : G →g G') {u v : V} : G.Walk u v → G'.Walk (f u) (f v)
| nil => nil
| cons h p => cons (f.map_adj h) (p.map f)
#align simple_graph.walk.map SimpleGraph.Walk.map
variable (f : G →g G') (f' : G' →g G'') {u v u' v' : V} (p : G.Walk u v)
@[simp]
theorem map_nil : (nil : G.Walk u u).map f = nil := rfl
#align simple_graph.walk.map_nil SimpleGraph.Walk.map_nil
@[simp]
theorem map_cons {w : V} (h : G.Adj w u) : (cons h p).map f = cons (f.map_adj h) (p.map f) := rfl
#align simple_graph.walk.map_cons SimpleGraph.Walk.map_cons
@[simp]
theorem map_copy (hu : u = u') (hv : v = v') :
(p.copy hu hv).map f = (p.map f).copy (hu ▸ rfl) (hv ▸ rfl) := by
subst_vars
rfl
#align simple_graph.walk.map_copy SimpleGraph.Walk.map_copy
@[simp]
theorem map_id (p : G.Walk u v) : p.map Hom.id = p := by
induction p with
| nil => rfl
| cons _ p' ih => simp [ih p']
#align simple_graph.walk.map_id SimpleGraph.Walk.map_id
@[simp]
theorem map_map : (p.map f).map f' = p.map (f'.comp f) := by
induction p with
| nil => rfl
| cons _ _ ih => simp [ih]
#align simple_graph.walk.map_map SimpleGraph.Walk.map_map
/-- Unlike categories, for graphs vertex equality is an important notion, so needing to be able to
work with equality of graph homomorphisms is a necessary evil. -/
theorem map_eq_of_eq {f : G →g G'} (f' : G →g G') (h : f = f') :
p.map f = (p.map f').copy (h ▸ rfl) (h ▸ rfl) := by
subst_vars
rfl
#align simple_graph.walk.map_eq_of_eq SimpleGraph.Walk.map_eq_of_eq
@[simp]
theorem map_eq_nil_iff {p : G.Walk u u} : p.map f = nil ↔ p = nil := by cases p <;> simp
#align simple_graph.walk.map_eq_nil_iff SimpleGraph.Walk.map_eq_nil_iff
@[simp]
theorem length_map : (p.map f).length = p.length := by induction p <;> simp [*]
#align simple_graph.walk.length_map SimpleGraph.Walk.length_map
theorem map_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).map f = (p.map f).append (q.map f) := by induction p <;> simp [*]
#align simple_graph.walk.map_append SimpleGraph.Walk.map_append
@[simp]
theorem reverse_map : (p.map f).reverse = p.reverse.map f := by induction p <;> simp [map_append, *]
#align simple_graph.walk.reverse_map SimpleGraph.Walk.reverse_map
@[simp]
theorem support_map : (p.map f).support = p.support.map f := by induction p <;> simp [*]
#align simple_graph.walk.support_map SimpleGraph.Walk.support_map
@[simp]
theorem darts_map : (p.map f).darts = p.darts.map f.mapDart := by induction p <;> simp [*]
#align simple_graph.walk.darts_map SimpleGraph.Walk.darts_map
@[simp]
theorem edges_map : (p.map f).edges = p.edges.map (Sym2.map f) := by
induction p with
| nil => rfl
| cons _ _ ih =>
simp only [Walk.map_cons, edges_cons, List.map_cons, Sym2.map_pair_eq, List.cons.injEq,
true_and, ih]
#align simple_graph.walk.edges_map SimpleGraph.Walk.edges_map
variable {p f}
theorem map_isPath_of_injective (hinj : Function.Injective f) (hp : p.IsPath) :
(p.map f).IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [Walk.cons_isPath_iff] at hp
simp only [map_cons, cons_isPath_iff, ih hp.1, support_map, List.mem_map, not_exists, not_and,
true_and]
intro x hx hf
cases hinj hf
exact hp.2 hx
#align simple_graph.walk.map_is_path_of_injective SimpleGraph.Walk.map_isPath_of_injective
protected theorem IsPath.of_map {f : G →g G'} (hp : (p.map f).IsPath) : p.IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [map_cons, Walk.cons_isPath_iff, support_map] at hp
rw [Walk.cons_isPath_iff]
cases' hp with hp1 hp2
refine ⟨ih hp1, ?_⟩
contrapose! hp2
exact List.mem_map_of_mem f hp2
#align simple_graph.walk.is_path.of_map SimpleGraph.Walk.IsPath.of_map
theorem map_isPath_iff_of_injective (hinj : Function.Injective f) : (p.map f).IsPath ↔ p.IsPath :=
⟨IsPath.of_map, map_isPath_of_injective hinj⟩
#align simple_graph.walk.map_is_path_iff_of_injective SimpleGraph.Walk.map_isPath_iff_of_injective
theorem map_isTrail_iff_of_injective (hinj : Function.Injective f) :
(p.map f).IsTrail ↔ p.IsTrail := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [map_cons, cons_isTrail_iff, ih, cons_isTrail_iff]
apply and_congr_right'
rw [← Sym2.map_pair_eq, edges_map, ← List.mem_map_of_injective (Sym2.map.injective hinj)]
#align simple_graph.walk.map_is_trail_iff_of_injective SimpleGraph.Walk.map_isTrail_iff_of_injective
alias ⟨_, map_isTrail_of_injective⟩ := map_isTrail_iff_of_injective
#align simple_graph.walk.map_is_trail_of_injective SimpleGraph.Walk.map_isTrail_of_injective
theorem map_isCycle_iff_of_injective {p : G.Walk u u} (hinj : Function.Injective f) :
(p.map f).IsCycle ↔ p.IsCycle := by
rw [isCycle_def, isCycle_def, map_isTrail_iff_of_injective hinj, Ne, map_eq_nil_iff,
support_map, ← List.map_tail, List.nodup_map_iff hinj]
#align simple_graph.walk.map_is_cycle_iff_of_injective SimpleGraph.Walk.map_isCycle_iff_of_injective
alias ⟨_, IsCycle.map⟩ := map_isCycle_iff_of_injective
#align simple_graph.walk.map_is_cycle_of_injective SimpleGraph.Walk.IsCycle.map
variable (p f)
theorem map_injective_of_injective {f : G →g G'} (hinj : Function.Injective f) (u v : V) :
Function.Injective (Walk.map f : G.Walk u v → G'.Walk (f u) (f v)) := by
intro p p' h
induction p with
| nil =>
cases p'
· rfl
· simp at h
| cons _ _ ih =>
cases p' with
| nil => simp at h
| cons _ _ =>
simp only [map_cons, cons.injEq] at h
cases hinj h.1
simp only [cons.injEq, heq_iff_eq, true_and_iff]
apply ih
simpa using h.2
#align simple_graph.walk.map_injective_of_injective SimpleGraph.Walk.map_injective_of_injective
/-- The specialization of `SimpleGraph.Walk.map` for mapping walks to supergraphs. -/
abbrev mapLe {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} (p : G.Walk u v) : G'.Walk u v :=
p.map (Hom.mapSpanningSubgraphs h)
#align simple_graph.walk.map_le SimpleGraph.Walk.mapLe
@[simp]
theorem mapLe_isTrail {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} {p : G.Walk u v} :
(p.mapLe h).IsTrail ↔ p.IsTrail :=
map_isTrail_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_trail SimpleGraph.Walk.mapLe_isTrail
alias ⟨IsTrail.of_mapLe, IsTrail.mapLe⟩ := mapLe_isTrail
#align simple_graph.walk.is_trail.of_map_le SimpleGraph.Walk.IsTrail.of_mapLe
#align simple_graph.walk.is_trail.map_le SimpleGraph.Walk.IsTrail.mapLe
@[simp]
theorem mapLe_isPath {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} {p : G.Walk u v} :
(p.mapLe h).IsPath ↔ p.IsPath :=
map_isPath_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_path SimpleGraph.Walk.mapLe_isPath
alias ⟨IsPath.of_mapLe, IsPath.mapLe⟩ := mapLe_isPath
#align simple_graph.walk.is_path.of_map_le SimpleGraph.Walk.IsPath.of_mapLe
#align simple_graph.walk.is_path.map_le SimpleGraph.Walk.IsPath.mapLe
@[simp]
theorem mapLe_isCycle {G G' : SimpleGraph V} (h : G ≤ G') {u : V} {p : G.Walk u u} :
(p.mapLe h).IsCycle ↔ p.IsCycle :=
map_isCycle_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_cycle SimpleGraph.Walk.mapLe_isCycle
alias ⟨IsCycle.of_mapLe, IsCycle.mapLe⟩ := mapLe_isCycle
#align simple_graph.walk.is_cycle.of_map_le SimpleGraph.Walk.IsCycle.of_mapLe
#align simple_graph.walk.is_cycle.map_le SimpleGraph.Walk.IsCycle.mapLe
end Walk
namespace Path
variable {G G'}
/-- Given an injective graph homomorphism, map paths to paths. -/
@[simps]
protected def map (f : G →g G') (hinj : Function.Injective f) {u v : V} (p : G.Path u v) :
G'.Path (f u) (f v) :=
⟨Walk.map f p, Walk.map_isPath_of_injective hinj p.2⟩
#align simple_graph.path.map SimpleGraph.Path.map
theorem map_injective {f : G →g G'} (hinj : Function.Injective f) (u v : V) :
Function.Injective (Path.map f hinj : G.Path u v → G'.Path (f u) (f v)) := by
rintro ⟨p, hp⟩ ⟨p', hp'⟩ h
simp only [Path.map, Subtype.coe_mk, Subtype.mk.injEq] at h
simp [Walk.map_injective_of_injective hinj u v h]
#align simple_graph.path.map_injective SimpleGraph.Path.map_injective
/-- Given a graph embedding, map paths to paths. -/
@[simps!]
protected def mapEmbedding (f : G ↪g G') {u v : V} (p : G.Path u v) : G'.Path (f u) (f v) :=
Path.map f.toHom f.injective p
#align simple_graph.path.map_embedding SimpleGraph.Path.mapEmbedding
theorem mapEmbedding_injective (f : G ↪g G') (u v : V) :
Function.Injective (Path.mapEmbedding f : G.Path u v → G'.Path (f u) (f v)) :=
map_injective f.injective u v
#align simple_graph.path.map_embedding_injective SimpleGraph.Path.mapEmbedding_injective
end Path
/-! ### Transferring between graphs -/
namespace Walk
variable {G}
/-- The walk `p` transferred to lie in `H`, given that `H` contains its edges. -/
@[simp]
protected def transfer {u v : V} (p : G.Walk u v)
(H : SimpleGraph V) (h : ∀ e, e ∈ p.edges → e ∈ H.edgeSet) : H.Walk u v :=
match p with
| nil => nil
| cons' u v w _ p =>
cons (h s(u, v) (by simp)) (p.transfer H fun e he => h e (by simp [he]))
#align simple_graph.walk.transfer SimpleGraph.Walk.transfer
variable {u v : V} (p : G.Walk u v)
theorem transfer_self : p.transfer G p.edges_subset_edgeSet = p := by
induction p <;> simp [*]
#align simple_graph.walk.transfer_self SimpleGraph.Walk.transfer_self
variable {H : SimpleGraph V}
theorem transfer_eq_map_of_le (hp) (GH : G ≤ H) :
p.transfer H hp = p.map (SimpleGraph.Hom.mapSpanningSubgraphs GH) := by
induction p <;> simp [*]
#align simple_graph.walk.transfer_eq_map_of_le SimpleGraph.Walk.transfer_eq_map_of_le
@[simp]
theorem edges_transfer (hp) : (p.transfer H hp).edges = p.edges := by
induction p <;> simp [*]
#align simple_graph.walk.edges_transfer SimpleGraph.Walk.edges_transfer
@[simp]
theorem support_transfer (hp) : (p.transfer H hp).support = p.support := by
induction p <;> simp [*]
#align simple_graph.walk.support_transfer SimpleGraph.Walk.support_transfer
@[simp]
theorem length_transfer (hp) : (p.transfer H hp).length = p.length := by
induction p <;> simp [*]
#align simple_graph.walk.length_transfer SimpleGraph.Walk.length_transfer
variable {p}
protected theorem IsPath.transfer (hp) (pp : p.IsPath) :
(p.transfer H hp).IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
simp only [Walk.transfer, cons_isPath_iff, support_transfer _ ] at pp ⊢
exact ⟨ih _ pp.1, pp.2⟩
#align simple_graph.walk.is_path.transfer SimpleGraph.Walk.IsPath.transfer
protected theorem IsCycle.transfer {q : G.Walk u u} (qc : q.IsCycle) (hq) :
(q.transfer H hq).IsCycle := by
cases q with
| nil => simp at qc
| cons _ q =>
simp only [edges_cons, List.find?, List.mem_cons, forall_eq_or_imp, mem_edgeSet] at hq
simp only [Walk.transfer, cons_isCycle_iff, edges_transfer q hq.2] at qc ⊢
exact ⟨qc.1.transfer hq.2, qc.2⟩
#align simple_graph.walk.is_cycle.transfer SimpleGraph.Walk.IsCycle.transfer
variable (p)
-- Porting note: this failed the simpNF linter since it was originally of the form
-- `(p.transfer H hp).transfer K hp' = p.transfer K hp''` with `hp'` a function of `hp` and `hp'`.
-- This was a mistake and it's corrected here.
@[simp]
theorem transfer_transfer (hp) {K : SimpleGraph V} (hp') :
(p.transfer H hp).transfer K hp' = p.transfer K (p.edges_transfer hp ▸ hp') := by
induction p with
| nil => simp
| cons _ _ ih =>
simp only [Walk.transfer, cons.injEq, heq_eq_eq, true_and]
apply ih
#align simple_graph.walk.transfer_transfer SimpleGraph.Walk.transfer_transfer
@[simp]
theorem transfer_append {w : V} (q : G.Walk v w) (hpq) :
(p.append q).transfer H hpq =
(p.transfer H fun e he => hpq _ (by simp [he])).append
(q.transfer H fun e he => hpq _ (by simp [he])) := by
induction p with
| nil => simp
| cons _ _ ih => simp only [Walk.transfer, cons_append, cons.injEq, heq_eq_eq, true_and, ih]
#align simple_graph.walk.transfer_append SimpleGraph.Walk.transfer_append
@[simp]
theorem reverse_transfer (hp) :
(p.transfer H hp).reverse =
p.reverse.transfer H (by simp only [edges_reverse, List.mem_reverse]; exact hp) := by
induction p with
| nil => simp
| cons _ _ ih => simp only [transfer_append, Walk.transfer, reverse_nil, reverse_cons, ih]
#align simple_graph.walk.reverse_transfer SimpleGraph.Walk.reverse_transfer
end Walk
/-! ## Deleting edges -/
namespace Walk
variable {G}
/-- Given a walk that avoids a set of edges, produce a walk in the graph
with those edges deleted. -/
abbrev toDeleteEdges (s : Set (Sym2 V)) {v w : V} (p : G.Walk v w)
(hp : ∀ e, e ∈ p.edges → ¬e ∈ s) : (G.deleteEdges s).Walk v w :=
p.transfer _ <| by
simp only [edgeSet_deleteEdges, Set.mem_diff]
exact fun e ep => ⟨edges_subset_edgeSet p ep, hp e ep⟩
#align simple_graph.walk.to_delete_edges SimpleGraph.Walk.toDeleteEdges
@[simp]
theorem toDeleteEdges_nil (s : Set (Sym2 V)) {v : V} (hp) :
(Walk.nil : G.Walk v v).toDeleteEdges s hp = Walk.nil := rfl
#align simple_graph.walk.to_delete_edges_nil SimpleGraph.Walk.toDeleteEdges_nil
@[simp]
theorem toDeleteEdges_cons (s : Set (Sym2 V)) {u v w : V} (h : G.Adj u v) (p : G.Walk v w) (hp) :
(Walk.cons h p).toDeleteEdges s hp =
Walk.cons (deleteEdges_adj.mpr ⟨h, hp _ (List.Mem.head _)⟩)
(p.toDeleteEdges s fun _ he => hp _ <| List.Mem.tail _ he) :=
rfl
#align simple_graph.walk.to_delete_edges_cons SimpleGraph.Walk.toDeleteEdges_cons
variable {v w : V}
/-- Given a walk that avoids an edge, create a walk in the subgraph with that edge deleted.
This is an abbreviation for `SimpleGraph.Walk.toDeleteEdges`. -/
abbrev toDeleteEdge (e : Sym2 V) (p : G.Walk v w) (hp : e ∉ p.edges) :
(G.deleteEdges {e}).Walk v w :=
p.toDeleteEdges {e} (fun e' => by contrapose!; simp (config := { contextual := true }) [hp])
#align simple_graph.walk.to_delete_edge SimpleGraph.Walk.toDeleteEdge
@[simp]
theorem map_toDeleteEdges_eq (s : Set (Sym2 V)) {p : G.Walk v w} (hp) :
Walk.map (Hom.mapSpanningSubgraphs (G.deleteEdges_le s)) (p.toDeleteEdges s hp) = p := by
rw [← transfer_eq_map_of_le, transfer_transfer, transfer_self]
intros e
rw [edges_transfer]
apply edges_subset_edgeSet p
#align simple_graph.walk.map_to_delete_edges_eq SimpleGraph.Walk.map_toDeleteEdges_eq
protected theorem IsPath.toDeleteEdges (s : Set (Sym2 V))
{p : G.Walk v w} (h : p.IsPath) (hp) : (p.toDeleteEdges s hp).IsPath :=
h.transfer _
#align simple_graph.walk.is_path.to_delete_edges SimpleGraph.Walk.IsPath.toDeleteEdges
protected theorem IsCycle.toDeleteEdges (s : Set (Sym2 V))
{p : G.Walk v v} (h : p.IsCycle) (hp) : (p.toDeleteEdges s hp).IsCycle :=
h.transfer _
#align simple_graph.walk.is_cycle.to_delete_edges SimpleGraph.Walk.IsCycle.toDeleteEdges
@[simp]
theorem toDeleteEdges_copy {v u u' v' : V} (s : Set (Sym2 V))
(p : G.Walk u v) (hu : u = u') (hv : v = v') (h) :
(p.copy hu hv).toDeleteEdges s h =
(p.toDeleteEdges s (by subst_vars; exact h)).copy hu hv := by
subst_vars
rfl
#align simple_graph.walk.to_delete_edges_copy SimpleGraph.Walk.toDeleteEdges_copy
end Walk
/-! ## `Reachable` and `Connected` -/
/-- Two vertices are *reachable* if there is a walk between them.
This is equivalent to `Relation.ReflTransGen` of `G.Adj`.
See `SimpleGraph.reachable_iff_reflTransGen`. -/
def Reachable (u v : V) : Prop := Nonempty (G.Walk u v)
#align simple_graph.reachable SimpleGraph.Reachable
variable {G}
theorem reachable_iff_nonempty_univ {u v : V} :
G.Reachable u v ↔ (Set.univ : Set (G.Walk u v)).Nonempty :=
Set.nonempty_iff_univ_nonempty
#align simple_graph.reachable_iff_nonempty_univ SimpleGraph.reachable_iff_nonempty_univ
protected theorem Reachable.elim {p : Prop} {u v : V} (h : G.Reachable u v)
(hp : G.Walk u v → p) : p :=
Nonempty.elim h hp
#align simple_graph.reachable.elim SimpleGraph.Reachable.elim
protected theorem Reachable.elim_path {p : Prop} {u v : V} (h : G.Reachable u v)
(hp : G.Path u v → p) : p := by classical exact h.elim fun q => hp q.toPath
#align simple_graph.reachable.elim_path SimpleGraph.Reachable.elim_path
protected theorem Walk.reachable {G : SimpleGraph V} {u v : V} (p : G.Walk u v) : G.Reachable u v :=
⟨p⟩
#align simple_graph.walk.reachable SimpleGraph.Walk.reachable
protected theorem Adj.reachable {u v : V} (h : G.Adj u v) : G.Reachable u v :=
h.toWalk.reachable
#align simple_graph.adj.reachable SimpleGraph.Adj.reachable
@[refl]
protected theorem Reachable.refl (u : V) : G.Reachable u u := ⟨Walk.nil⟩
#align simple_graph.reachable.refl SimpleGraph.Reachable.refl
protected theorem Reachable.rfl {u : V} : G.Reachable u u := Reachable.refl _
#align simple_graph.reachable.rfl SimpleGraph.Reachable.rfl
@[symm]
protected theorem Reachable.symm {u v : V} (huv : G.Reachable u v) : G.Reachable v u :=
huv.elim fun p => ⟨p.reverse⟩
#align simple_graph.reachable.symm SimpleGraph.Reachable.symm
theorem reachable_comm {u v : V} : G.Reachable u v ↔ G.Reachable v u :=
⟨Reachable.symm, Reachable.symm⟩
#align simple_graph.reachable_comm SimpleGraph.reachable_comm
@[trans]
protected theorem Reachable.trans {u v w : V} (huv : G.Reachable u v) (hvw : G.Reachable v w) :
G.Reachable u w :=
huv.elim fun puv => hvw.elim fun pvw => ⟨puv.append pvw⟩
#align simple_graph.reachable.trans SimpleGraph.Reachable.trans
theorem reachable_iff_reflTransGen (u v : V) :
G.Reachable u v ↔ Relation.ReflTransGen G.Adj u v := by
constructor
· rintro ⟨h⟩
induction h with
| nil => rfl
| cons h' _ ih => exact (Relation.ReflTransGen.single h').trans ih
· intro h
induction h with
| refl => rfl
| tail _ ha hr => exact Reachable.trans hr ⟨Walk.cons ha Walk.nil⟩
#align simple_graph.reachable_iff_refl_trans_gen SimpleGraph.reachable_iff_reflTransGen
protected theorem Reachable.map {u v : V} {G : SimpleGraph V} {G' : SimpleGraph V'} (f : G →g G')
(h : G.Reachable u v) : G'.Reachable (f u) (f v) :=
h.elim fun p => ⟨p.map f⟩
#align simple_graph.reachable.map SimpleGraph.Reachable.map
@[mono]
protected lemma Reachable.mono {u v : V} {G G' : SimpleGraph V}
(h : G ≤ G') (Guv : G.Reachable u v) : G'.Reachable u v :=
Guv.map (SimpleGraph.Hom.mapSpanningSubgraphs h)
theorem Iso.reachable_iff {G : SimpleGraph V} {G' : SimpleGraph V'} {φ : G ≃g G'} {u v : V} :
G'.Reachable (φ u) (φ v) ↔ G.Reachable u v :=
⟨fun r => φ.left_inv u ▸ φ.left_inv v ▸ r.map φ.symm.toHom, Reachable.map φ.toHom⟩
#align simple_graph.iso.reachable_iff SimpleGraph.Iso.reachable_iff
theorem Iso.symm_apply_reachable {G : SimpleGraph V} {G' : SimpleGraph V'} {φ : G ≃g G'} {u : V}
{v : V'} : G.Reachable (φ.symm v) u ↔ G'.Reachable v (φ u) := by
rw [← Iso.reachable_iff, RelIso.apply_symm_apply]
#align simple_graph.iso.symm_apply_reachable SimpleGraph.Iso.symm_apply_reachable
variable (G)
theorem reachable_is_equivalence : Equivalence G.Reachable :=
Equivalence.mk (@Reachable.refl _ G) (@Reachable.symm _ G) (@Reachable.trans _ G)
#align simple_graph.reachable_is_equivalence SimpleGraph.reachable_is_equivalence
/-- The equivalence relation on vertices given by `SimpleGraph.Reachable`. -/
def reachableSetoid : Setoid V := Setoid.mk _ G.reachable_is_equivalence
#align simple_graph.reachable_setoid SimpleGraph.reachableSetoid
/-- A graph is preconnected if every pair of vertices is reachable from one another. -/
def Preconnected : Prop := ∀ u v : V, G.Reachable u v
#align simple_graph.preconnected SimpleGraph.Preconnected
theorem Preconnected.map {G : SimpleGraph V} {H : SimpleGraph V'} (f : G →g H) (hf : Surjective f)
(hG : G.Preconnected) : H.Preconnected :=
hf.forall₂.2 fun _ _ => Nonempty.map (Walk.map _) <| hG _ _
#align simple_graph.preconnected.map SimpleGraph.Preconnected.map
@[mono]
protected lemma Preconnected.mono {G G' : SimpleGraph V} (h : G ≤ G') (hG : G.Preconnected) :
G'.Preconnected := fun u v => (hG u v).mono h
lemma top_preconnected : (⊤ : SimpleGraph V).Preconnected := fun x y => by
if h : x = y then rw [h] else exact Adj.reachable h
theorem Iso.preconnected_iff {G : SimpleGraph V} {H : SimpleGraph V'} (e : G ≃g H) :
G.Preconnected ↔ H.Preconnected :=
⟨Preconnected.map e.toHom e.toEquiv.surjective,
Preconnected.map e.symm.toHom e.symm.toEquiv.surjective⟩
#align simple_graph.iso.preconnected_iff SimpleGraph.Iso.preconnected_iff
/-- A graph is connected if it's preconnected and contains at least one vertex.
This follows the convention observed by mathlib that something is connected iff it has
exactly one connected component.
There is a `CoeFun` instance so that `h u v` can be used instead of `h.Preconnected u v`. -/
@[mk_iff]
structure Connected : Prop where
protected preconnected : G.Preconnected
protected [nonempty : Nonempty V]
#align simple_graph.connected SimpleGraph.Connected
lemma connected_iff_exists_forall_reachable : G.Connected ↔ ∃ v, ∀ w, G.Reachable v w := by
rw [connected_iff]
constructor
· rintro ⟨hp, ⟨v⟩⟩
exact ⟨v, fun w => hp v w⟩
· rintro ⟨v, h⟩
exact ⟨fun u w => (h u).symm.trans (h w), ⟨v⟩⟩
instance : CoeFun G.Connected fun _ => ∀ u v : V, G.Reachable u v := ⟨fun h => h.preconnected⟩
theorem Connected.map {G : SimpleGraph V} {H : SimpleGraph V'} (f : G →g H) (hf : Surjective f)
(hG : G.Connected) : H.Connected :=
haveI := hG.nonempty.map f
⟨hG.preconnected.map f hf⟩
#align simple_graph.connected.map SimpleGraph.Connected.map
@[mono]
protected lemma Connected.mono {G G' : SimpleGraph V} (h : G ≤ G')
(hG : G.Connected) : G'.Connected where
preconnected := hG.preconnected.mono h
nonempty := hG.nonempty
lemma top_connected [Nonempty V] : (⊤ : SimpleGraph V).Connected where
preconnected := top_preconnected
theorem Iso.connected_iff {G : SimpleGraph V} {H : SimpleGraph V'} (e : G ≃g H) :
G.Connected ↔ H.Connected :=
⟨Connected.map e.toHom e.toEquiv.surjective, Connected.map e.symm.toHom e.symm.toEquiv.surjective⟩
#align simple_graph.iso.connected_iff SimpleGraph.Iso.connected_iff
/-- The quotient of `V` by the `SimpleGraph.Reachable` relation gives the connected
components of a graph. -/
def ConnectedComponent := Quot G.Reachable
#align simple_graph.connected_component SimpleGraph.ConnectedComponent
/-- Gives the connected component containing a particular vertex. -/
def connectedComponentMk (v : V) : G.ConnectedComponent := Quot.mk G.Reachable v
#align simple_graph.connected_component_mk SimpleGraph.connectedComponentMk
variable {G G' G''}
namespace ConnectedComponent
@[simps]
instance inhabited [Inhabited V] : Inhabited G.ConnectedComponent :=
⟨G.connectedComponentMk default⟩
#align simple_graph.connected_component.inhabited SimpleGraph.ConnectedComponent.inhabited
@[elab_as_elim]
protected theorem ind {β : G.ConnectedComponent → Prop}
(h : ∀ v : V, β (G.connectedComponentMk v)) (c : G.ConnectedComponent) : β c :=
Quot.ind h c
#align simple_graph.connected_component.ind SimpleGraph.ConnectedComponent.ind
@[elab_as_elim]
protected theorem ind₂ {β : G.ConnectedComponent → G.ConnectedComponent → Prop}
(h : ∀ v w : V, β (G.connectedComponentMk v) (G.connectedComponentMk w))
(c d : G.ConnectedComponent) : β c d :=
Quot.induction_on₂ c d h
#align simple_graph.connected_component.ind₂ SimpleGraph.ConnectedComponent.ind₂
protected theorem sound {v w : V} :
G.Reachable v w → G.connectedComponentMk v = G.connectedComponentMk w :=
Quot.sound
#align simple_graph.connected_component.sound SimpleGraph.ConnectedComponent.sound
protected theorem exact {v w : V} :
G.connectedComponentMk v = G.connectedComponentMk w → G.Reachable v w :=
@Quotient.exact _ G.reachableSetoid _ _
#align simple_graph.connected_component.exact SimpleGraph.ConnectedComponent.exact
@[simp]
protected theorem eq {v w : V} :
G.connectedComponentMk v = G.connectedComponentMk w ↔ G.Reachable v w :=
@Quotient.eq' _ G.reachableSetoid _ _
#align simple_graph.connected_component.eq SimpleGraph.ConnectedComponent.eq
theorem connectedComponentMk_eq_of_adj {v w : V} (a : G.Adj v w) :
G.connectedComponentMk v = G.connectedComponentMk w :=
ConnectedComponent.sound a.reachable
#align simple_graph.connected_component.connected_component_mk_eq_of_adj SimpleGraph.ConnectedComponent.connectedComponentMk_eq_of_adj
/-- The `ConnectedComponent` specialization of `Quot.lift`. Provides the stronger
assumption that the vertices are connected by a path. -/
protected def lift {β : Sort*} (f : V → β)
(h : ∀ (v w : V) (p : G.Walk v w), p.IsPath → f v = f w) : G.ConnectedComponent → β :=
Quot.lift f fun v w (h' : G.Reachable v w) => h'.elim_path fun hp => h v w hp hp.2
#align simple_graph.connected_component.lift SimpleGraph.ConnectedComponent.lift
@[simp]
protected theorem lift_mk {β : Sort*} {f : V → β}
{h : ∀ (v w : V) (p : G.Walk v w), p.IsPath → f v = f w} {v : V} :
ConnectedComponent.lift f h (G.connectedComponentMk v) = f v :=
rfl
#align simple_graph.connected_component.lift_mk SimpleGraph.ConnectedComponent.lift_mk
protected theorem «exists» {p : G.ConnectedComponent → Prop} :
(∃ c : G.ConnectedComponent, p c) ↔ ∃ v, p (G.connectedComponentMk v) :=
(surjective_quot_mk G.Reachable).exists
#align simple_graph.connected_component.exists SimpleGraph.ConnectedComponent.exists
protected theorem «forall» {p : G.ConnectedComponent → Prop} :
(∀ c : G.ConnectedComponent, p c) ↔ ∀ v, p (G.connectedComponentMk v) :=
(surjective_quot_mk G.Reachable).forall
#align simple_graph.connected_component.forall SimpleGraph.ConnectedComponent.forall
theorem _root_.SimpleGraph.Preconnected.subsingleton_connectedComponent (h : G.Preconnected) :
Subsingleton G.ConnectedComponent :=
⟨ConnectedComponent.ind₂ fun v w => ConnectedComponent.sound (h v w)⟩
#align simple_graph.preconnected.subsingleton_connected_component SimpleGraph.Preconnected.subsingleton_connectedComponent
/-- The map on connected components induced by a graph homomorphism. -/
def map (φ : G →g G') (C : G.ConnectedComponent) : G'.ConnectedComponent :=
C.lift (fun v => G'.connectedComponentMk (φ v)) fun _ _ p _ =>
ConnectedComponent.eq.mpr (p.map φ).reachable
#align simple_graph.connected_component.map SimpleGraph.ConnectedComponent.map
@[simp]
theorem map_mk (φ : G →g G') (v : V) :
(G.connectedComponentMk v).map φ = G'.connectedComponentMk (φ v) :=
rfl
#align simple_graph.connected_component.map_mk SimpleGraph.ConnectedComponent.map_mk
@[simp]
theorem map_id (C : ConnectedComponent G) : C.map Hom.id = C := by
refine C.ind ?_
exact fun _ => rfl
#align simple_graph.connected_component.map_id SimpleGraph.ConnectedComponent.map_id
@[simp]
theorem map_comp (C : G.ConnectedComponent) (φ : G →g G') (ψ : G' →g G'') :
(C.map φ).map ψ = C.map (ψ.comp φ) := by
refine C.ind ?_
exact fun _ => rfl
#align simple_graph.connected_component.map_comp SimpleGraph.ConnectedComponent.map_comp
variable {φ : G ≃g G'} {v : V} {v' : V'}
@[simp]
theorem iso_image_comp_eq_map_iff_eq_comp {C : G.ConnectedComponent} :
G'.connectedComponentMk (φ v) = C.map ↑(↑φ : G ↪g G') ↔ G.connectedComponentMk v = C := by
refine C.ind fun u => ?_
simp only [Iso.reachable_iff, ConnectedComponent.map_mk, RelEmbedding.coe_toRelHom,
RelIso.coe_toRelEmbedding, ConnectedComponent.eq]
#align simple_graph.connected_component.iso_image_comp_eq_map_iff_eq_comp SimpleGraph.ConnectedComponent.iso_image_comp_eq_map_iff_eq_comp
@[simp]
theorem iso_inv_image_comp_eq_iff_eq_map {C : G.ConnectedComponent} :
G.connectedComponentMk (φ.symm v') = C ↔ G'.connectedComponentMk v' = C.map φ := by
refine C.ind fun u => ?_
simp only [Iso.symm_apply_reachable, ConnectedComponent.eq, ConnectedComponent.map_mk,
RelEmbedding.coe_toRelHom, RelIso.coe_toRelEmbedding]
#align simple_graph.connected_component.iso_inv_image_comp_eq_iff_eq_map SimpleGraph.ConnectedComponent.iso_inv_image_comp_eq_iff_eq_map
end ConnectedComponent
namespace Iso
/-- An isomorphism of graphs induces a bijection of connected components. -/
@[simps]
def connectedComponentEquiv (φ : G ≃g G') : G.ConnectedComponent ≃ G'.ConnectedComponent where
toFun := ConnectedComponent.map φ
invFun := ConnectedComponent.map φ.symm
left_inv C := ConnectedComponent.ind
(fun v => congr_arg G.connectedComponentMk (Equiv.left_inv φ.toEquiv v)) C
right_inv C := ConnectedComponent.ind
(fun v => congr_arg G'.connectedComponentMk (Equiv.right_inv φ.toEquiv v)) C
#align simple_graph.iso.connected_component_equiv SimpleGraph.Iso.connectedComponentEquiv
@[simp]
theorem connectedComponentEquiv_refl :
(Iso.refl : G ≃g G).connectedComponentEquiv = Equiv.refl _ := by
ext ⟨v⟩
rfl
#align simple_graph.iso.connected_component_equiv_refl SimpleGraph.Iso.connectedComponentEquiv_refl
@[simp]
theorem connectedComponentEquiv_symm (φ : G ≃g G') :
φ.symm.connectedComponentEquiv = φ.connectedComponentEquiv.symm := by
ext ⟨_⟩
rfl
#align simple_graph.iso.connected_component_equiv_symm SimpleGraph.Iso.connectedComponentEquiv_symm
@[simp]
theorem connectedComponentEquiv_trans (φ : G ≃g G') (φ' : G' ≃g G'') :
connectedComponentEquiv (φ.trans φ') =
φ.connectedComponentEquiv.trans φ'.connectedComponentEquiv := by
ext ⟨_⟩
rfl
#align simple_graph.iso.connected_component_equiv_trans SimpleGraph.Iso.connectedComponentEquiv_trans
end Iso
namespace ConnectedComponent
/-- The set of vertices in a connected component of a graph. -/
def supp (C : G.ConnectedComponent) :=
{ v | G.connectedComponentMk v = C }
#align simple_graph.connected_component.supp SimpleGraph.ConnectedComponent.supp
@[ext]
theorem supp_injective :
Function.Injective (ConnectedComponent.supp : G.ConnectedComponent → Set V) := by
refine ConnectedComponent.ind₂ ?_
intro v w
simp only [ConnectedComponent.supp, Set.ext_iff, ConnectedComponent.eq, Set.mem_setOf_eq]
intro h
rw [reachable_comm, h]
#align simple_graph.connected_component.supp_injective SimpleGraph.ConnectedComponent.supp_injective
@[simp]
theorem supp_inj {C D : G.ConnectedComponent} : C.supp = D.supp ↔ C = D :=
ConnectedComponent.supp_injective.eq_iff
#align simple_graph.connected_component.supp_inj SimpleGraph.ConnectedComponent.supp_inj
instance : SetLike G.ConnectedComponent V where
coe := ConnectedComponent.supp
coe_injective' := ConnectedComponent.supp_injective
@[simp]
theorem mem_supp_iff (C : G.ConnectedComponent) (v : V) :
v ∈ C.supp ↔ G.connectedComponentMk v = C :=
Iff.rfl
#align simple_graph.connected_component.mem_supp_iff SimpleGraph.ConnectedComponent.mem_supp_iff
theorem connectedComponentMk_mem {v : V} : v ∈ G.connectedComponentMk v :=
rfl
#align simple_graph.connected_component.connected_component_mk_mem SimpleGraph.ConnectedComponent.connectedComponentMk_mem
/-- The equivalence between connected components, induced by an isomorphism of graphs,
itself defines an equivalence on the supports of each connected component.
-/
def isoEquivSupp (φ : G ≃g G') (C : G.ConnectedComponent) :
C.supp ≃ (φ.connectedComponentEquiv C).supp where
toFun v := ⟨φ v, ConnectedComponent.iso_image_comp_eq_map_iff_eq_comp.mpr v.prop⟩
invFun v' := ⟨φ.symm v', ConnectedComponent.iso_inv_image_comp_eq_iff_eq_map.mpr v'.prop⟩
left_inv v := Subtype.ext_val (φ.toEquiv.left_inv ↑v)
right_inv v := Subtype.ext_val (φ.toEquiv.right_inv ↑v)
#align simple_graph.connected_component.iso_equiv_supp SimpleGraph.ConnectedComponent.isoEquivSupp
end ConnectedComponent
theorem Preconnected.set_univ_walk_nonempty (hconn : G.Preconnected) (u v : V) :
(Set.univ : Set (G.Walk u v)).Nonempty := by
rw [← Set.nonempty_iff_univ_nonempty]
exact hconn u v
#align simple_graph.preconnected.set_univ_walk_nonempty SimpleGraph.Preconnected.set_univ_walk_nonempty
theorem Connected.set_univ_walk_nonempty (hconn : G.Connected) (u v : V) :
(Set.univ : Set (G.Walk u v)).Nonempty :=
hconn.preconnected.set_univ_walk_nonempty u v
#align simple_graph.connected.set_univ_walk_nonempty SimpleGraph.Connected.set_univ_walk_nonempty
/-! ### Walks as subgraphs -/
namespace Walk
variable {u v w : V}
/-- The subgraph consisting of the vertices and edges of the walk. -/
@[simp]
protected def toSubgraph {u v : V} : G.Walk u v → G.Subgraph
| nil => G.singletonSubgraph u
| cons h p => G.subgraphOfAdj h ⊔ p.toSubgraph
#align simple_graph.walk.to_subgraph SimpleGraph.Walk.toSubgraph
theorem toSubgraph_cons_nil_eq_subgraphOfAdj (h : G.Adj u v) :
(cons h nil).toSubgraph = G.subgraphOfAdj h := by simp
#align simple_graph.walk.to_subgraph_cons_nil_eq_subgraph_of_adj SimpleGraph.Walk.toSubgraph_cons_nil_eq_subgraphOfAdj
theorem mem_verts_toSubgraph (p : G.Walk u v) : w ∈ p.toSubgraph.verts ↔ w ∈ p.support := by
induction' p with _ x y z h p' ih
· simp
· have : w = y ∨ w ∈ p'.support ↔ w ∈ p'.support :=
⟨by rintro (rfl | h) <;> simp [*], by simp (config := { contextual := true })⟩
simp [ih, or_assoc, this]
#align simple_graph.walk.mem_verts_to_subgraph SimpleGraph.Walk.mem_verts_toSubgraph
lemma start_mem_verts_toSubgraph (p : G.Walk u v) : u ∈ p.toSubgraph.verts := by
simp [mem_verts_toSubgraph]
lemma end_mem_verts_toSubgraph (p : G.Walk u v) : v ∈ p.toSubgraph.verts := by
simp [mem_verts_toSubgraph]
@[simp]
theorem verts_toSubgraph (p : G.Walk u v) : p.toSubgraph.verts = { w | w ∈ p.support } :=
Set.ext fun _ => p.mem_verts_toSubgraph
#align simple_graph.walk.verts_to_subgraph SimpleGraph.Walk.verts_toSubgraph
theorem mem_edges_toSubgraph (p : G.Walk u v) {e : Sym2 V} :
e ∈ p.toSubgraph.edgeSet ↔ e ∈ p.edges := by induction p <;> simp [*]
#align simple_graph.walk.mem_edges_to_subgraph SimpleGraph.Walk.mem_edges_toSubgraph
@[simp]
theorem edgeSet_toSubgraph (p : G.Walk u v) : p.toSubgraph.edgeSet = { e | e ∈ p.edges } :=
Set.ext fun _ => p.mem_edges_toSubgraph
#align simple_graph.walk.edge_set_to_subgraph SimpleGraph.Walk.edgeSet_toSubgraph
@[simp]
theorem toSubgraph_append (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).toSubgraph = p.toSubgraph ⊔ q.toSubgraph := by induction p <;> simp [*, sup_assoc]
#align simple_graph.walk.to_subgraph_append SimpleGraph.Walk.toSubgraph_append
@[simp]
theorem toSubgraph_reverse (p : G.Walk u v) : p.reverse.toSubgraph = p.toSubgraph := by
induction p with
| nil => simp
| cons _ _ _ =>
simp only [*, Walk.toSubgraph, reverse_cons, toSubgraph_append, subgraphOfAdj_symm]
rw [sup_comm]
congr
ext <;> simp [-Set.bot_eq_empty]
#align simple_graph.walk.to_subgraph_reverse SimpleGraph.Walk.toSubgraph_reverse
@[simp]
theorem toSubgraph_rotate [DecidableEq V] (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).toSubgraph = c.toSubgraph := by
rw [rotate, toSubgraph_append, sup_comm, ← toSubgraph_append, take_spec]
#align simple_graph.walk.to_subgraph_rotate SimpleGraph.Walk.toSubgraph_rotate
@[simp]
theorem toSubgraph_map (f : G →g G') (p : G.Walk u v) :
(p.map f).toSubgraph = p.toSubgraph.map f := by induction p <;> simp [*, Subgraph.map_sup]
#align simple_graph.walk.to_subgraph_map SimpleGraph.Walk.toSubgraph_map
@[simp]
theorem finite_neighborSet_toSubgraph (p : G.Walk u v) : (p.toSubgraph.neighborSet w).Finite := by
induction p with
| nil =>
rw [Walk.toSubgraph, neighborSet_singletonSubgraph]
apply Set.toFinite
| cons ha _ ih =>
rw [Walk.toSubgraph, Subgraph.neighborSet_sup]
refine Set.Finite.union ?_ ih
refine Set.Finite.subset ?_ (neighborSet_subgraphOfAdj_subset ha)
apply Set.toFinite
#align simple_graph.walk.finite_neighbor_set_to_subgraph SimpleGraph.Walk.finite_neighborSet_toSubgraph
lemma toSubgraph_le_induce_support (p : G.Walk u v) :
p.toSubgraph ≤ (⊤ : G.Subgraph).induce {v | v ∈ p.support} := by
convert Subgraph.le_induce_top_verts
exact p.verts_toSubgraph.symm
end Walk
/-! ### Walks of a given length -/
section WalkCounting
theorem set_walk_self_length_zero_eq (u : V) : {p : G.Walk u u | p.length = 0} = {Walk.nil} := by
ext p
simp
#align simple_graph.set_walk_self_length_zero_eq SimpleGraph.set_walk_self_length_zero_eq
theorem set_walk_length_zero_eq_of_ne {u v : V} (h : u ≠ v) :
{p : G.Walk u v | p.length = 0} = ∅ := by
ext p
simp only [Set.mem_setOf_eq, Set.mem_empty_iff_false, iff_false_iff]
exact fun h' => absurd (Walk.eq_of_length_eq_zero h') h
#align simple_graph.set_walk_length_zero_eq_of_ne SimpleGraph.set_walk_length_zero_eq_of_ne
theorem set_walk_length_succ_eq (u v : V) (n : ℕ) :
{p : G.Walk u v | p.length = n.succ} =
⋃ (w : V) (h : G.Adj u w), Walk.cons h '' {p' : G.Walk w v | p'.length = n} := by
ext p
cases' p with _ _ w _ huw pwv
· simp [eq_comm]
· simp only [Nat.succ_eq_add_one, Set.mem_setOf_eq, Walk.length_cons, add_left_inj,
Set.mem_iUnion, Set.mem_image, exists_prop]
constructor
· rintro rfl
exact ⟨w, huw, pwv, rfl, rfl⟩
· rintro ⟨w, huw, pwv, rfl, rfl, rfl⟩
rfl
#align simple_graph.set_walk_length_succ_eq SimpleGraph.set_walk_length_succ_eq
variable (G) [DecidableEq V]
/-- Walks of length two from `u` to `v` correspond bijectively to common neighbours of `u` and `v`.
Note that `u` and `v` may be the same. -/
@[simps]
def walkLengthTwoEquivCommonNeighbors (u v : V) :
{p : G.Walk u v // p.length = 2} ≃ G.commonNeighbors u v where
toFun p := ⟨p.val.getVert 1, match p with
| ⟨.cons _ (.cons _ .nil), hp⟩ => ⟨‹G.Adj u _›, ‹G.Adj _ v›.symm⟩⟩
invFun w := ⟨w.prop.1.toWalk.concat w.prop.2.symm, rfl⟩
left_inv | ⟨.cons _ (.cons _ .nil), hp⟩ => by rfl
right_inv _ := rfl
section LocallyFinite
variable [LocallyFinite G]
/-- The `Finset` of length-`n` walks from `u` to `v`.
This is used to give `{p : G.walk u v | p.length = n}` a `Fintype` instance, and it
can also be useful as a recursive description of this set when `V` is finite.
See `SimpleGraph.coe_finsetWalkLength_eq` for the relationship between this `Finset` and
the set of length-`n` walks. -/
def finsetWalkLength (n : ℕ) (u v : V) : Finset (G.Walk u v) :=
match n with
| 0 =>
if h : u = v then by
subst u
exact {Walk.nil}
else ∅
| n + 1 =>
Finset.univ.biUnion fun (w : G.neighborSet u) =>
(finsetWalkLength n w v).map ⟨fun p => Walk.cons w.property p, fun _ _ => by simp⟩
#align simple_graph.finset_walk_length SimpleGraph.finsetWalkLength
theorem coe_finsetWalkLength_eq (n : ℕ) (u v : V) :
(G.finsetWalkLength n u v : Set (G.Walk u v)) = {p : G.Walk u v | p.length = n} := by
induction' n with n ih generalizing u v
· obtain rfl | huv := eq_or_ne u v <;> simp [finsetWalkLength, set_walk_length_zero_eq_of_ne, *]
· simp only [finsetWalkLength, set_walk_length_succ_eq, Finset.coe_biUnion, Finset.mem_coe,
Finset.mem_univ, Set.iUnion_true]
ext p
simp only [mem_neighborSet, Finset.coe_map, Embedding.coeFn_mk, Set.iUnion_coe_set,
Set.mem_iUnion, Set.mem_image, Finset.mem_coe, Set.mem_setOf_eq]
congr!
rename_i w _ q
have := Set.ext_iff.mp (ih w v) q
simp only [Finset.mem_coe, Set.mem_setOf_eq] at this
rw [← this]
#align simple_graph.coe_finset_walk_length_eq SimpleGraph.coe_finsetWalkLength_eq
variable {G}
theorem Walk.mem_finsetWalkLength_iff_length_eq {n : ℕ} {u v : V} (p : G.Walk u v) :
p ∈ G.finsetWalkLength n u v ↔ p.length = n :=
Set.ext_iff.mp (G.coe_finsetWalkLength_eq n u v) p
#align simple_graph.walk.mem_finset_walk_length_iff_length_eq SimpleGraph.Walk.mem_finsetWalkLength_iff_length_eq
variable (G)
instance fintypeSetWalkLength (u v : V) (n : ℕ) : Fintype {p : G.Walk u v | p.length = n} :=
Fintype.ofFinset (G.finsetWalkLength n u v) fun p => by
rw [← Finset.mem_coe, coe_finsetWalkLength_eq]
#align simple_graph.fintype_set_walk_length SimpleGraph.fintypeSetWalkLength
instance fintypeSubtypeWalkLength (u v : V) (n : ℕ) : Fintype {p : G.Walk u v // p.length = n} :=
fintypeSetWalkLength G u v n
| Mathlib/Combinatorics/SimpleGraph/Connectivity.lean | 2,565 | 2,568 | theorem set_walk_length_toFinset_eq (n : ℕ) (u v : V) :
{p : G.Walk u v | p.length = n}.toFinset = G.finsetWalkLength n u v := by |
ext p
simp [← coe_finsetWalkLength_eq]
|
/-
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.TensorProduct.Basic
import Mathlib.Algebra.Module.ULift
#align_import ring_theory.is_tensor_product from "leanprover-community/mathlib"@"c4926d76bb9c5a4a62ed2f03d998081786132105"
/-!
# The characteristic predicate of tensor product
## Main definitions
- `IsTensorProduct`: A predicate on `f : M₁ →ₗ[R] M₂ →ₗ[R] M` expressing that `f` realizes `M` as
the tensor product of `M₁ ⊗[R] M₂`. This is defined by requiring the lift `M₁ ⊗[R] M₂ → M` to be
bijective.
- `IsBaseChange`: A predicate on an `R`-algebra `S` and a map `f : M →ₗ[R] N` with `N` being an
`S`-module, expressing that `f` realizes `N` as the base change of `M` along `R → S`.
- `Algebra.IsPushout`: A predicate on the following diagram of scalar towers
```
R → S
↓ ↓
R' → S'
```
asserting that is a pushout diagram (i.e. `S' = S ⊗[R] R'`)
## Main results
- `TensorProduct.isBaseChange`: `S ⊗[R] M` is the base change of `M` along `R → S`.
-/
universe u v₁ v₂ v₃ v₄
open TensorProduct
section IsTensorProduct
variable {R : Type*} [CommSemiring R]
variable {M₁ M₂ M M' : Type*}
variable [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M] [AddCommMonoid M']
variable [Module R M₁] [Module R M₂] [Module R M] [Module R M']
variable (f : M₁ →ₗ[R] M₂ →ₗ[R] M)
variable {N₁ N₂ N : Type*} [AddCommMonoid N₁] [AddCommMonoid N₂] [AddCommMonoid N]
variable [Module R N₁] [Module R N₂] [Module R N]
variable {g : N₁ →ₗ[R] N₂ →ₗ[R] N}
/-- Given a bilinear map `f : M₁ →ₗ[R] M₂ →ₗ[R] M`, `IsTensorProduct f` means that
`M` is the tensor product of `M₁` and `M₂` via `f`.
This is defined by requiring the lift `M₁ ⊗[R] M₂ → M` to be bijective.
-/
def IsTensorProduct : Prop :=
Function.Bijective (TensorProduct.lift f)
#align is_tensor_product IsTensorProduct
variable (R M N) {f}
theorem TensorProduct.isTensorProduct : IsTensorProduct (TensorProduct.mk R M N) := by
delta IsTensorProduct
convert_to Function.Bijective (LinearMap.id : M ⊗[R] N →ₗ[R] M ⊗[R] N) using 2
· apply TensorProduct.ext'
simp
· exact Function.bijective_id
#align tensor_product.is_tensor_product TensorProduct.isTensorProduct
variable {R M N}
/-- If `M` is the tensor product of `M₁` and `M₂`, it is linearly equivalent to `M₁ ⊗[R] M₂`. -/
@[simps! apply]
noncomputable def IsTensorProduct.equiv (h : IsTensorProduct f) : M₁ ⊗[R] M₂ ≃ₗ[R] M :=
LinearEquiv.ofBijective _ h
#align is_tensor_product.equiv IsTensorProduct.equiv
@[simp]
theorem IsTensorProduct.equiv_toLinearMap (h : IsTensorProduct f) :
h.equiv.toLinearMap = TensorProduct.lift f :=
rfl
#align is_tensor_product.equiv_to_linear_map IsTensorProduct.equiv_toLinearMap
@[simp]
theorem IsTensorProduct.equiv_symm_apply (h : IsTensorProduct f) (x₁ : M₁) (x₂ : M₂) :
h.equiv.symm (f x₁ x₂) = x₁ ⊗ₜ x₂ := by
apply h.equiv.injective
refine (h.equiv.apply_symm_apply _).trans ?_
simp
#align is_tensor_product.equiv_symm_apply IsTensorProduct.equiv_symm_apply
/-- If `M` is the tensor product of `M₁` and `M₂`, we may lift a bilinear map `M₁ →ₗ[R] M₂ →ₗ[R] M'`
to a `M →ₗ[R] M'`. -/
noncomputable def IsTensorProduct.lift (h : IsTensorProduct f) (f' : M₁ →ₗ[R] M₂ →ₗ[R] M') :
M →ₗ[R] M' :=
(TensorProduct.lift f').comp h.equiv.symm.toLinearMap
#align is_tensor_product.lift IsTensorProduct.lift
theorem IsTensorProduct.lift_eq (h : IsTensorProduct f) (f' : M₁ →ₗ[R] M₂ →ₗ[R] M') (x₁ : M₁)
(x₂ : M₂) : h.lift f' (f x₁ x₂) = f' x₁ x₂ := by
delta IsTensorProduct.lift
simp
#align is_tensor_product.lift_eq IsTensorProduct.lift_eq
/-- The tensor product of a pair of linear maps between modules. -/
noncomputable def IsTensorProduct.map (hf : IsTensorProduct f) (hg : IsTensorProduct g)
(i₁ : M₁ →ₗ[R] N₁) (i₂ : M₂ →ₗ[R] N₂) : M →ₗ[R] N :=
hg.equiv.toLinearMap.comp ((TensorProduct.map i₁ i₂).comp hf.equiv.symm.toLinearMap)
#align is_tensor_product.map IsTensorProduct.map
theorem IsTensorProduct.map_eq (hf : IsTensorProduct f) (hg : IsTensorProduct g) (i₁ : M₁ →ₗ[R] N₁)
(i₂ : M₂ →ₗ[R] N₂) (x₁ : M₁) (x₂ : M₂) : hf.map hg i₁ i₂ (f x₁ x₂) = g (i₁ x₁) (i₂ x₂) := by
delta IsTensorProduct.map
simp
#align is_tensor_product.map_eq IsTensorProduct.map_eq
theorem IsTensorProduct.inductionOn (h : IsTensorProduct f) {C : M → Prop} (m : M) (h0 : C 0)
(htmul : ∀ x y, C (f x y)) (hadd : ∀ x y, C x → C y → C (x + y)) : C m := by
rw [← h.equiv.right_inv m]
generalize h.equiv.invFun m = y
change C (TensorProduct.lift f y)
induction y using TensorProduct.induction_on with
| zero => rwa [map_zero]
| tmul _ _ =>
rw [TensorProduct.lift.tmul]
apply htmul
| add _ _ _ _ =>
rw [map_add]
apply hadd <;> assumption
#align is_tensor_product.induction_on IsTensorProduct.inductionOn
end IsTensorProduct
section IsBaseChange
variable {R : Type*} {M : Type v₁} {N : Type v₂} (S : Type v₃)
variable [AddCommMonoid M] [AddCommMonoid N] [CommSemiring R]
variable [CommSemiring S] [Algebra R S] [Module R M] [Module R N] [Module S N] [IsScalarTower R S N]
variable (f : M →ₗ[R] N)
/-- Given an `R`-algebra `S` and an `R`-module `M`, an `S`-module `N` together with a map
`f : M →ₗ[R] N` is the base change of `M` to `S` if the map `S × M → N, (s, m) ↦ s • f m` is the
tensor product. -/
def IsBaseChange : Prop :=
IsTensorProduct
(((Algebra.linearMap S <| Module.End S (M →ₗ[R] N)).flip f).restrictScalars R)
#align is_base_change IsBaseChange
-- Porting note: split `variable`
variable {S f}
variable (h : IsBaseChange S f)
variable {P Q : Type*} [AddCommMonoid P] [Module R P]
variable [AddCommMonoid Q] [Module S Q]
section
variable [Module R Q] [IsScalarTower R S Q]
/-- Suppose `f : M →ₗ[R] N` is the base change of `M` along `R → S`. Then any `R`-linear map from
`M` to an `S`-module factors through `f`. -/
noncomputable nonrec def IsBaseChange.lift (g : M →ₗ[R] Q) : N →ₗ[S] Q :=
{ h.lift
(((Algebra.linearMap S <| Module.End S (M →ₗ[R] Q)).flip g).restrictScalars R) with
map_smul' := fun r x => by
let F := ((Algebra.linearMap S <| Module.End S (M →ₗ[R] Q)).flip g).restrictScalars R
have hF : ∀ (s : S) (m : M), h.lift F (s • f m) = s • g m := h.lift_eq F
change h.lift F (r • x) = r • h.lift F x
apply h.inductionOn x
· rw [smul_zero, map_zero, smul_zero]
· intro s m
change h.lift F (r • s • f m) = r • h.lift F (s • f m)
rw [← mul_smul, hF, hF, mul_smul]
· intro x₁ x₂ e₁ e₂
rw [map_add, smul_add, map_add, smul_add, e₁, e₂] }
#align is_base_change.lift IsBaseChange.lift
nonrec theorem IsBaseChange.lift_eq (g : M →ₗ[R] Q) (x : M) : h.lift g (f x) = g x := by
have hF : ∀ (s : S) (m : M), h.lift g (s • f m) = s • g m := h.lift_eq _
convert hF 1 x <;> rw [one_smul]
#align is_base_change.lift_eq IsBaseChange.lift_eq
theorem IsBaseChange.lift_comp (g : M →ₗ[R] Q) : ((h.lift g).restrictScalars R).comp f = g :=
LinearMap.ext (h.lift_eq g)
#align is_base_change.lift_comp IsBaseChange.lift_comp
end
@[elab_as_elim]
nonrec theorem IsBaseChange.inductionOn (x : N) (P : N → Prop) (h₁ : P 0) (h₂ : ∀ m : M, P (f m))
(h₃ : ∀ (s : S) (n), P n → P (s • n)) (h₄ : ∀ n₁ n₂, P n₁ → P n₂ → P (n₁ + n₂)) : P x :=
h.inductionOn x h₁ (fun _ _ => h₃ _ _ (h₂ _)) h₄
#align is_base_change.induction_on IsBaseChange.inductionOn
theorem IsBaseChange.algHom_ext (g₁ g₂ : N →ₗ[S] Q) (e : ∀ x, g₁ (f x) = g₂ (f x)) : g₁ = g₂ := by
ext x
refine h.inductionOn x ?_ ?_ ?_ ?_
· rw [map_zero, map_zero]
· assumption
· intro s n e'
rw [g₁.map_smul, g₂.map_smul, e']
· intro x y e₁ e₂
rw [map_add, map_add, e₁, e₂]
#align is_base_change.alg_hom_ext IsBaseChange.algHom_ext
theorem IsBaseChange.algHom_ext' [Module R Q] [IsScalarTower R S Q] (g₁ g₂ : N →ₗ[S] Q)
(e : (g₁.restrictScalars R).comp f = (g₂.restrictScalars R).comp f) : g₁ = g₂ :=
h.algHom_ext g₁ g₂ (LinearMap.congr_fun e)
#align is_base_change.alg_hom_ext' IsBaseChange.algHom_ext'
variable (R M N S)
theorem TensorProduct.isBaseChange : IsBaseChange S (TensorProduct.mk R S M 1) := by
delta IsBaseChange
convert TensorProduct.isTensorProduct R S M using 1
ext s x
change s • (1 : S) ⊗ₜ[R] x = s ⊗ₜ[R] x
rw [TensorProduct.smul_tmul']
congr 1
exact mul_one _
#align tensor_product.is_base_change TensorProduct.isBaseChange
variable {R M N S}
/-- The base change of `M` along `R → S` is linearly equivalent to `S ⊗[R] M`. -/
noncomputable nonrec def IsBaseChange.equiv : S ⊗[R] M ≃ₗ[S] N :=
{ h.equiv with
map_smul' := fun r x => by
change h.equiv (r • x) = r • h.equiv x
refine TensorProduct.induction_on x ?_ ?_ ?_
· rw [smul_zero, map_zero, smul_zero]
· intro x y
-- porting note (#10745): was simp [smul_tmul', Algebra.ofId_apply]
simp only [Algebra.linearMap_apply, lift.tmul, smul_eq_mul,
LinearMap.mul_apply, LinearMap.smul_apply, IsTensorProduct.equiv_apply,
Module.algebraMap_end_apply, _root_.map_mul, smul_tmul', eq_self_iff_true,
LinearMap.coe_restrictScalars, LinearMap.flip_apply]
· intro x y hx hy
rw [map_add, smul_add, map_add, smul_add, hx, hy] }
#align is_base_change.equiv IsBaseChange.equiv
theorem IsBaseChange.equiv_tmul (s : S) (m : M) : h.equiv (s ⊗ₜ m) = s • f m :=
TensorProduct.lift.tmul s m
#align is_base_change.equiv_tmul IsBaseChange.equiv_tmul
theorem IsBaseChange.equiv_symm_apply (m : M) : h.equiv.symm (f m) = 1 ⊗ₜ m := by
rw [h.equiv.symm_apply_eq, h.equiv_tmul, one_smul]
#align is_base_change.equiv_symm_apply IsBaseChange.equiv_symm_apply
variable (f)
| Mathlib/RingTheory/IsTensorProduct.lean | 249 | 280 | theorem IsBaseChange.of_lift_unique
(h : ∀ (Q : Type max v₁ v₂ v₃) [AddCommMonoid Q],
∀ [Module R Q] [Module S Q], ∀ [IsScalarTower R S Q],
∀ g : M →ₗ[R] Q, ∃! g' : N →ₗ[S] Q, (g'.restrictScalars R).comp f = g) :
IsBaseChange S f := by |
obtain ⟨g, hg, -⟩ :=
h (ULift.{v₂} <| S ⊗[R] M)
(ULift.moduleEquiv.symm.toLinearMap.comp <| TensorProduct.mk R S M 1)
let f' : S ⊗[R] M →ₗ[R] N :=
TensorProduct.lift (((LinearMap.flip (AlgHom.toLinearMap (Algebra.ofId S
(Module.End S (M →ₗ[R] N))))) f).restrictScalars R)
change Function.Bijective f'
let f'' : S ⊗[R] M →ₗ[S] N := by
refine
{ f' with
map_smul' := fun s x =>
TensorProduct.induction_on x ?_ (fun s' y => smul_assoc s s' _) fun x y hx hy => ?_ }
· dsimp; rw [map_zero, smul_zero, map_zero, smul_zero]
· dsimp at *; rw [smul_add, map_add, map_add, smul_add, hx, hy]
simp_rw [DFunLike.ext_iff, LinearMap.comp_apply, LinearMap.restrictScalars_apply] at hg
let fe : S ⊗[R] M ≃ₗ[S] N :=
LinearEquiv.ofLinear f'' (ULift.moduleEquiv.toLinearMap.comp g) ?_ ?_
· exact fe.bijective
· rw [← LinearMap.cancel_left (ULift.moduleEquiv : ULift.{max v₁ v₃} N ≃ₗ[S] N).symm.injective]
refine (h (ULift.{max v₁ v₃} N) <| ULift.moduleEquiv.symm.toLinearMap.comp f).unique ?_ rfl
ext x
simp only [LinearMap.comp_apply, LinearMap.restrictScalars_apply, hg]
apply one_smul
· ext x
change (g <| (1 : S) • f x).down = _
rw [one_smul, hg]
rfl
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jens Wagemaker, Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Associated
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Data.Nat.Factors
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Multiplicity
#align_import ring_theory.unique_factorization_domain from "leanprover-community/mathlib"@"570e9f4877079b3a923135b3027ac3be8695ab8c"
/-!
# Unique factorization
## Main Definitions
* `WfDvdMonoid` holds for `Monoid`s for which a strict divisibility relation is
well-founded.
* `UniqueFactorizationMonoid` holds for `WfDvdMonoid`s where
`Irreducible` is equivalent to `Prime`
## To do
* set up the complete lattice structure on `FactorSet`.
-/
variable {α : Type*}
local infixl:50 " ~ᵤ " => Associated
/-- Well-foundedness of the strict version of |, which is equivalent to the descending chain
condition on divisibility and to the ascending chain condition on
principal ideals in an integral domain.
-/
class WfDvdMonoid (α : Type*) [CommMonoidWithZero α] : Prop where
wellFounded_dvdNotUnit : WellFounded (@DvdNotUnit α _)
#align wf_dvd_monoid WfDvdMonoid
export WfDvdMonoid (wellFounded_dvdNotUnit)
-- see Note [lower instance priority]
instance (priority := 100) IsNoetherianRing.wfDvdMonoid [CommRing α] [IsDomain α]
[IsNoetherianRing α] : WfDvdMonoid α :=
⟨by
convert InvImage.wf (fun a => Ideal.span ({a} : Set α)) (wellFounded_submodule_gt _ _)
ext
exact Ideal.span_singleton_lt_span_singleton.symm⟩
#align is_noetherian_ring.wf_dvd_monoid IsNoetherianRing.wfDvdMonoid
namespace WfDvdMonoid
variable [CommMonoidWithZero α]
open Associates Nat
theorem of_wfDvdMonoid_associates (_ : WfDvdMonoid (Associates α)) : WfDvdMonoid α :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).2 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.of_wf_dvd_monoid_associates WfDvdMonoid.of_wfDvdMonoid_associates
variable [WfDvdMonoid α]
instance wfDvdMonoid_associates : WfDvdMonoid (Associates α) :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).1 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.wf_dvd_monoid_associates WfDvdMonoid.wfDvdMonoid_associates
theorem wellFounded_associates : WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
Subrelation.wf dvdNotUnit_of_lt wellFounded_dvdNotUnit
#align wf_dvd_monoid.well_founded_associates WfDvdMonoid.wellFounded_associates
-- Porting note: elab_as_elim can only be global and cannot be changed on an imported decl
-- attribute [local elab_as_elim] WellFounded.fix
theorem exists_irreducible_factor {a : α} (ha : ¬IsUnit a) (ha0 : a ≠ 0) :
∃ i, Irreducible i ∧ i ∣ a :=
let ⟨b, hs, hr⟩ := wellFounded_dvdNotUnit.has_min { b | b ∣ a ∧ ¬IsUnit b } ⟨a, dvd_rfl, ha⟩
⟨b,
⟨hs.2, fun c d he =>
let h := dvd_trans ⟨d, he⟩ hs.1
or_iff_not_imp_left.2 fun hc =>
of_not_not fun hd => hr c ⟨h, hc⟩ ⟨ne_zero_of_dvd_ne_zero ha0 h, d, hd, he⟩⟩,
hs.1⟩
#align wf_dvd_monoid.exists_irreducible_factor WfDvdMonoid.exists_irreducible_factor
@[elab_as_elim]
theorem induction_on_irreducible {P : α → Prop} (a : α) (h0 : P 0) (hu : ∀ u : α, IsUnit u → P u)
(hi : ∀ a i : α, a ≠ 0 → Irreducible i → P a → P (i * a)) : P a :=
haveI := Classical.dec
wellFounded_dvdNotUnit.fix
(fun a ih =>
if ha0 : a = 0 then ha0.substr h0
else
if hau : IsUnit a then hu a hau
else
let ⟨i, hii, b, hb⟩ := exists_irreducible_factor hau ha0
let hb0 : b ≠ 0 := ne_zero_of_dvd_ne_zero ha0 ⟨i, mul_comm i b ▸ hb⟩
hb.symm ▸ hi b i hb0 hii <| ih b ⟨hb0, i, hii.1, mul_comm i b ▸ hb⟩)
a
#align wf_dvd_monoid.induction_on_irreducible WfDvdMonoid.induction_on_irreducible
theorem exists_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ Associated f.prod a :=
induction_on_irreducible a (fun h => (h rfl).elim)
(fun u hu _ => ⟨0, fun _ h => False.elim (Multiset.not_mem_zero _ h), hu.unit, one_mul _⟩)
fun a i ha0 hi ih _ =>
let ⟨s, hs⟩ := ih ha0
⟨i ::ₘ s, fun b H => (Multiset.mem_cons.1 H).elim (fun h => h.symm ▸ hi) (hs.1 b), by
rw [s.prod_cons i]
exact hs.2.mul_left i⟩
#align wf_dvd_monoid.exists_factors WfDvdMonoid.exists_factors
theorem not_unit_iff_exists_factors_eq (a : α) (hn0 : a ≠ 0) :
¬IsUnit a ↔ ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod = a ∧ f ≠ ∅ :=
⟨fun hnu => by
obtain ⟨f, hi, u, rfl⟩ := exists_factors a hn0
obtain ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero fun h : f = 0 => hnu <| by simp [h]
classical
refine ⟨(f.erase b).cons (b * u), fun a ha => ?_, ?_, Multiset.cons_ne_zero⟩
· obtain rfl | ha := Multiset.mem_cons.1 ha
exacts [Associated.irreducible ⟨u, rfl⟩ (hi b h), hi a (Multiset.mem_of_mem_erase ha)]
· rw [Multiset.prod_cons, mul_comm b, mul_assoc, Multiset.prod_erase h, mul_comm],
fun ⟨f, hi, he, hne⟩ =>
let ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero hne
not_isUnit_of_not_isUnit_dvd (hi b h).not_unit <| he ▸ Multiset.dvd_prod h⟩
#align wf_dvd_monoid.not_unit_iff_exists_factors_eq WfDvdMonoid.not_unit_iff_exists_factors_eq
theorem isRelPrime_of_no_irreducible_factors {x y : α} (nonzero : ¬(x = 0 ∧ y = 0))
(H : ∀ z : α, Irreducible z → z ∣ x → ¬z ∣ y) : IsRelPrime x y :=
isRelPrime_of_no_nonunits_factors nonzero fun _z znu znz zx zy ↦
have ⟨i, h1, h2⟩ := exists_irreducible_factor znu znz
H i h1 (h2.trans zx) (h2.trans zy)
end WfDvdMonoid
theorem WfDvdMonoid.of_wellFounded_associates [CancelCommMonoidWithZero α]
(h : WellFounded ((· < ·) : Associates α → Associates α → Prop)) : WfDvdMonoid α :=
WfDvdMonoid.of_wfDvdMonoid_associates
⟨by
convert h
ext
exact Associates.dvdNotUnit_iff_lt⟩
#align wf_dvd_monoid.of_well_founded_associates WfDvdMonoid.of_wellFounded_associates
theorem WfDvdMonoid.iff_wellFounded_associates [CancelCommMonoidWithZero α] :
WfDvdMonoid α ↔ WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
⟨by apply WfDvdMonoid.wellFounded_associates, WfDvdMonoid.of_wellFounded_associates⟩
#align wf_dvd_monoid.iff_well_founded_associates WfDvdMonoid.iff_wellFounded_associates
theorem WfDvdMonoid.max_power_factor' [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : ¬IsUnit x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a := by
obtain ⟨a, ⟨n, rfl⟩, hm⟩ := wellFounded_dvdNotUnit.has_min
{a | ∃ n, x ^ n * a = a₀} ⟨a₀, 0, by rw [pow_zero, one_mul]⟩
refine ⟨n, a, ?_, rfl⟩; rintro ⟨d, rfl⟩
exact hm d ⟨n + 1, by rw [pow_succ, mul_assoc]⟩
⟨(right_ne_zero_of_mul <| right_ne_zero_of_mul h), x, hx, mul_comm _ _⟩
theorem WfDvdMonoid.max_power_factor [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : Irreducible x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a :=
max_power_factor' h hx.not_unit
theorem multiplicity.finite_of_not_isUnit [CancelCommMonoidWithZero α] [WfDvdMonoid α]
{a b : α} (ha : ¬IsUnit a) (hb : b ≠ 0) : multiplicity.Finite a b := by
obtain ⟨n, c, ndvd, rfl⟩ := WfDvdMonoid.max_power_factor' hb ha
exact ⟨n, by rwa [pow_succ, mul_dvd_mul_iff_left (left_ne_zero_of_mul hb)]⟩
section Prio
-- set_option default_priority 100
-- see Note [default priority]
/-- unique factorization monoids.
These are defined as `CancelCommMonoidWithZero`s with well-founded strict divisibility
relations, but this is equivalent to more familiar definitions:
Each element (except zero) is uniquely represented as a multiset of irreducible factors.
Uniqueness is only up to associated elements.
Each element (except zero) is non-uniquely represented as a multiset
of prime factors.
To define a UFD using the definition in terms of multisets
of irreducible factors, use the definition `of_exists_unique_irreducible_factors`
To define a UFD using the definition in terms of multisets
of prime factors, use the definition `of_exists_prime_factors`
-/
class UniqueFactorizationMonoid (α : Type*) [CancelCommMonoidWithZero α] extends WfDvdMonoid α :
Prop where
protected irreducible_iff_prime : ∀ {a : α}, Irreducible a ↔ Prime a
#align unique_factorization_monoid UniqueFactorizationMonoid
/-- Can't be an instance because it would cause a loop `ufm → WfDvdMonoid → ufm → ...`. -/
theorem ufm_of_decomposition_of_wfDvdMonoid [CancelCommMonoidWithZero α] [WfDvdMonoid α]
[DecompositionMonoid α] : UniqueFactorizationMonoid α :=
{ ‹WfDvdMonoid α› with irreducible_iff_prime := irreducible_iff_prime }
#align ufm_of_gcd_of_wf_dvd_monoid ufm_of_decomposition_of_wfDvdMonoid
@[deprecated] alias ufm_of_gcd_of_wfDvdMonoid := ufm_of_decomposition_of_wfDvdMonoid
instance Associates.ufm [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α] :
UniqueFactorizationMonoid (Associates α) :=
{ (WfDvdMonoid.wfDvdMonoid_associates : WfDvdMonoid (Associates α)) with
irreducible_iff_prime := by
rw [← Associates.irreducible_iff_prime_iff]
apply UniqueFactorizationMonoid.irreducible_iff_prime }
#align associates.ufm Associates.ufm
end Prio
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem exists_prime_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime]
apply WfDvdMonoid.exists_factors a
#align unique_factorization_monoid.exists_prime_factors UniqueFactorizationMonoid.exists_prime_factors
instance : DecompositionMonoid α where
primal a := by
obtain rfl | ha := eq_or_ne a 0; · exact isPrimal_zero
obtain ⟨f, hf, u, rfl⟩ := exists_prime_factors a ha
exact ((Submonoid.isPrimal α).multiset_prod_mem f (hf · ·|>.isPrimal)).mul u.isUnit.isPrimal
lemma exists_prime_iff :
(∃ (p : α), Prime p) ↔ ∃ (x : α), x ≠ 0 ∧ ¬ IsUnit x := by
refine ⟨fun ⟨p, hp⟩ ↦ ⟨p, hp.ne_zero, hp.not_unit⟩, fun ⟨x, hx₀, hxu⟩ ↦ ?_⟩
obtain ⟨f, hf, -⟩ := WfDvdMonoid.exists_irreducible_factor hxu hx₀
exact ⟨f, UniqueFactorizationMonoid.irreducible_iff_prime.mp hf⟩
@[elab_as_elim]
theorem induction_on_prime {P : α → Prop} (a : α) (h₁ : P 0) (h₂ : ∀ x : α, IsUnit x → P x)
(h₃ : ∀ a p : α, a ≠ 0 → Prime p → P a → P (p * a)) : P a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime] at h₃
exact WfDvdMonoid.induction_on_irreducible a h₁ h₂ h₃
#align unique_factorization_monoid.induction_on_prime UniqueFactorizationMonoid.induction_on_prime
end UniqueFactorizationMonoid
theorem prime_factors_unique [CancelCommMonoidWithZero α] :
∀ {f g : Multiset α},
(∀ x ∈ f, Prime x) → (∀ x ∈ g, Prime x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g := by
classical
intro f
induction' f using Multiset.induction_on with p f ih
· intros g _ hg h
exact Multiset.rel_zero_left.2 <|
Multiset.eq_zero_of_forall_not_mem fun x hx =>
have : IsUnit g.prod := by simpa [associated_one_iff_isUnit] using h.symm
(hg x hx).not_unit <|
isUnit_iff_dvd_one.2 <| (Multiset.dvd_prod hx).trans (isUnit_iff_dvd_one.1 this)
· intros g hf hg hfg
let ⟨b, hbg, hb⟩ :=
(exists_associated_mem_of_dvd_prod (hf p (by simp)) fun q hq => hg _ hq) <|
hfg.dvd_iff_dvd_right.1 (show p ∣ (p ::ₘ f).prod by simp)
haveI := Classical.decEq α
rw [← Multiset.cons_erase hbg]
exact
Multiset.Rel.cons hb
(ih (fun q hq => hf _ (by simp [hq]))
(fun {q} (hq : q ∈ g.erase b) => hg q (Multiset.mem_of_mem_erase hq))
(Associated.of_mul_left
(by rwa [← Multiset.prod_cons, ← Multiset.prod_cons, Multiset.cons_erase hbg]) hb
(hf p (by simp)).ne_zero))
#align prime_factors_unique prime_factors_unique
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem factors_unique {f g : Multiset α} (hf : ∀ x ∈ f, Irreducible x)
(hg : ∀ x ∈ g, Irreducible x) (h : f.prod ~ᵤ g.prod) : Multiset.Rel Associated f g :=
prime_factors_unique (fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hf x hx))
(fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hg x hx)) h
#align unique_factorization_monoid.factors_unique UniqueFactorizationMonoid.factors_unique
end UniqueFactorizationMonoid
/-- If an irreducible has a prime factorization,
then it is an associate of one of its prime factors. -/
theorem prime_factors_irreducible [CancelCommMonoidWithZero α] {a : α} {f : Multiset α}
(ha : Irreducible a) (pfa : (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a) : ∃ p, a ~ᵤ p ∧ f = {p} := by
haveI := Classical.decEq α
refine @Multiset.induction_on _
(fun g => (g.prod ~ᵤ a) → (∀ b ∈ g, Prime b) → ∃ p, a ~ᵤ p ∧ g = {p}) f ?_ ?_ pfa.2 pfa.1
· intro h; exact (ha.not_unit (associated_one_iff_isUnit.1 (Associated.symm h))).elim
· rintro p s _ ⟨u, hu⟩ hs
use p
have hs0 : s = 0 := by
by_contra hs0
obtain ⟨q, hq⟩ := Multiset.exists_mem_of_ne_zero hs0
apply (hs q (by simp [hq])).2.1
refine (ha.isUnit_or_isUnit (?_ : _ = p * ↑u * (s.erase q).prod * _)).resolve_left ?_
· rw [mul_right_comm _ _ q, mul_assoc, ← Multiset.prod_cons, Multiset.cons_erase hq, ← hu,
mul_comm, mul_comm p _, mul_assoc]
simp
apply mt isUnit_of_mul_isUnit_left (mt isUnit_of_mul_isUnit_left _)
apply (hs p (Multiset.mem_cons_self _ _)).2.1
simp only [mul_one, Multiset.prod_cons, Multiset.prod_zero, hs0] at *
exact ⟨Associated.symm ⟨u, hu⟩, rfl⟩
#align prime_factors_irreducible prime_factors_irreducible
section ExistsPrimeFactors
variable [CancelCommMonoidWithZero α]
variable (pf : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a)
theorem WfDvdMonoid.of_exists_prime_factors : WfDvdMonoid α :=
⟨by
classical
refine RelHomClass.wellFounded
(RelHom.mk ?_ ?_ : (DvdNotUnit : α → α → Prop) →r ((· < ·) : ℕ∞ → ℕ∞ → Prop)) wellFounded_lt
· intro a
by_cases h : a = 0
· exact ⊤
exact ↑(Multiset.card (Classical.choose (pf a h)))
rintro a b ⟨ane0, ⟨c, hc, b_eq⟩⟩
rw [dif_neg ane0]
by_cases h : b = 0
· simp [h, lt_top_iff_ne_top]
· rw [dif_neg h]
erw [WithTop.coe_lt_coe]
have cne0 : c ≠ 0 := by
refine mt (fun con => ?_) h
rw [b_eq, con, mul_zero]
calc
Multiset.card (Classical.choose (pf a ane0)) <
_ + Multiset.card (Classical.choose (pf c cne0)) :=
lt_add_of_pos_right _
(Multiset.card_pos.mpr fun con => hc (associated_one_iff_isUnit.mp ?_))
_ = Multiset.card (Classical.choose (pf a ane0) + Classical.choose (pf c cne0)) :=
(Multiset.card_add _ _).symm
_ = Multiset.card (Classical.choose (pf b h)) :=
Multiset.card_eq_card_of_rel
(prime_factors_unique ?_ (Classical.choose_spec (pf _ h)).1 ?_)
· convert (Classical.choose_spec (pf c cne0)).2.symm
rw [con, Multiset.prod_zero]
· intro x hadd
rw [Multiset.mem_add] at hadd
cases' hadd with h h <;> apply (Classical.choose_spec (pf _ _)).1 _ h <;> assumption
· rw [Multiset.prod_add]
trans a * c
· apply Associated.mul_mul <;> apply (Classical.choose_spec (pf _ _)).2 <;> assumption
· rw [← b_eq]
apply (Classical.choose_spec (pf _ _)).2.symm; assumption⟩
#align wf_dvd_monoid.of_exists_prime_factors WfDvdMonoid.of_exists_prime_factors
theorem irreducible_iff_prime_of_exists_prime_factors {p : α} : Irreducible p ↔ Prime p := by
by_cases hp0 : p = 0
· simp [hp0]
refine ⟨fun h => ?_, Prime.irreducible⟩
obtain ⟨f, hf⟩ := pf p hp0
obtain ⟨q, hq, rfl⟩ := prime_factors_irreducible h hf
rw [hq.prime_iff]
exact hf.1 q (Multiset.mem_singleton_self _)
#align irreducible_iff_prime_of_exists_prime_factors irreducible_iff_prime_of_exists_prime_factors
theorem UniqueFactorizationMonoid.of_exists_prime_factors : UniqueFactorizationMonoid α :=
{ WfDvdMonoid.of_exists_prime_factors pf with
irreducible_iff_prime := irreducible_iff_prime_of_exists_prime_factors pf }
#align unique_factorization_monoid.of_exists_prime_factors UniqueFactorizationMonoid.of_exists_prime_factors
end ExistsPrimeFactors
theorem UniqueFactorizationMonoid.iff_exists_prime_factors [CancelCommMonoidWithZero α] :
UniqueFactorizationMonoid α ↔
∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a :=
⟨fun h => @UniqueFactorizationMonoid.exists_prime_factors _ _ h,
UniqueFactorizationMonoid.of_exists_prime_factors⟩
#align unique_factorization_monoid.iff_exists_prime_factors UniqueFactorizationMonoid.iff_exists_prime_factors
section
variable {β : Type*} [CancelCommMonoidWithZero α] [CancelCommMonoidWithZero β]
theorem MulEquiv.uniqueFactorizationMonoid (e : α ≃* β) (hα : UniqueFactorizationMonoid α) :
UniqueFactorizationMonoid β := by
rw [UniqueFactorizationMonoid.iff_exists_prime_factors] at hα ⊢
intro a ha
obtain ⟨w, hp, u, h⟩ :=
hα (e.symm a) fun h =>
ha <| by
convert← map_zero e
simp [← h]
exact
⟨w.map e, fun b hb =>
let ⟨c, hc, he⟩ := Multiset.mem_map.1 hb
he ▸ e.prime_iff.1 (hp c hc),
Units.map e.toMonoidHom u,
by
erw [Multiset.prod_hom, ← e.map_mul, h]
simp⟩
#align mul_equiv.unique_factorization_monoid MulEquiv.uniqueFactorizationMonoid
theorem MulEquiv.uniqueFactorizationMonoid_iff (e : α ≃* β) :
UniqueFactorizationMonoid α ↔ UniqueFactorizationMonoid β :=
⟨e.uniqueFactorizationMonoid, e.symm.uniqueFactorizationMonoid⟩
#align mul_equiv.unique_factorization_monoid_iff MulEquiv.uniqueFactorizationMonoid_iff
end
theorem irreducible_iff_prime_of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g)
(p : α) : Irreducible p ↔ Prime p :=
letI := Classical.decEq α
⟨ fun hpi =>
⟨hpi.ne_zero, hpi.1, fun a b ⟨x, hx⟩ =>
if hab0 : a * b = 0 then
(eq_zero_or_eq_zero_of_mul_eq_zero hab0).elim (fun ha0 => by simp [ha0]) fun hb0 => by
simp [hb0]
else by
have hx0 : x ≠ 0 := fun hx0 => by simp_all
have ha0 : a ≠ 0 := left_ne_zero_of_mul hab0
have hb0 : b ≠ 0 := right_ne_zero_of_mul hab0
cases' eif x hx0 with fx hfx
cases' eif a ha0 with fa hfa
cases' eif b hb0 with fb hfb
have h : Multiset.Rel Associated (p ::ₘ fx) (fa + fb) := by
apply uif
· exact fun i hi => (Multiset.mem_cons.1 hi).elim (fun hip => hip.symm ▸ hpi) (hfx.1 _)
· exact fun i hi => (Multiset.mem_add.1 hi).elim (hfa.1 _) (hfb.1 _)
calc
Multiset.prod (p ::ₘ fx) ~ᵤ a * b := by
rw [hx, Multiset.prod_cons]; exact hfx.2.mul_left _
_ ~ᵤ fa.prod * fb.prod := hfa.2.symm.mul_mul hfb.2.symm
_ = _ := by rw [Multiset.prod_add]
exact
let ⟨q, hqf, hq⟩ := Multiset.exists_mem_of_rel_of_mem h (Multiset.mem_cons_self p _)
(Multiset.mem_add.1 hqf).elim
(fun hqa =>
Or.inl <| hq.dvd_iff_dvd_left.2 <| hfa.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqa))
fun hqb =>
Or.inr <| hq.dvd_iff_dvd_left.2 <| hfb.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqb)⟩,
Prime.irreducible⟩
#align irreducible_iff_prime_of_exists_unique_irreducible_factors irreducible_iff_prime_of_exists_unique_irreducible_factors
theorem UniqueFactorizationMonoid.of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g) :
UniqueFactorizationMonoid α :=
UniqueFactorizationMonoid.of_exists_prime_factors
(by
convert eif using 7
simp_rw [irreducible_iff_prime_of_exists_unique_irreducible_factors eif uif])
#align unique_factorization_monoid.of_exists_unique_irreducible_factors UniqueFactorizationMonoid.of_exists_unique_irreducible_factors
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α]
variable [UniqueFactorizationMonoid α]
open Classical in
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def factors (a : α) : Multiset α :=
if h : a = 0 then 0 else Classical.choose (UniqueFactorizationMonoid.exists_prime_factors a h)
#align unique_factorization_monoid.factors UniqueFactorizationMonoid.factors
theorem factors_prod {a : α} (ane0 : a ≠ 0) : Associated (factors a).prod a := by
rw [factors, dif_neg ane0]
exact (Classical.choose_spec (exists_prime_factors a ane0)).2
#align unique_factorization_monoid.factors_prod UniqueFactorizationMonoid.factors_prod
@[simp]
theorem factors_zero : factors (0 : α) = 0 := by simp [factors]
#align unique_factorization_monoid.factors_zero UniqueFactorizationMonoid.factors_zero
theorem ne_zero_of_mem_factors {p a : α} (h : p ∈ factors a) : a ≠ 0 := by
rintro rfl
simp at h
#align unique_factorization_monoid.ne_zero_of_mem_factors UniqueFactorizationMonoid.ne_zero_of_mem_factors
theorem dvd_of_mem_factors {p a : α} (h : p ∈ factors a) : p ∣ a :=
dvd_trans (Multiset.dvd_prod h) (Associated.dvd (factors_prod (ne_zero_of_mem_factors h)))
#align unique_factorization_monoid.dvd_of_mem_factors UniqueFactorizationMonoid.dvd_of_mem_factors
theorem prime_of_factor {a : α} (x : α) (hx : x ∈ factors a) : Prime x := by
have ane0 := ne_zero_of_mem_factors hx
rw [factors, dif_neg ane0] at hx
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 x hx
#align unique_factorization_monoid.prime_of_factor UniqueFactorizationMonoid.prime_of_factor
theorem irreducible_of_factor {a : α} : ∀ x : α, x ∈ factors a → Irreducible x := fun x h =>
(prime_of_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_factor UniqueFactorizationMonoid.irreducible_of_factor
@[simp]
theorem factors_one : factors (1 : α) = 0 := by
nontriviality α using factors
rw [← Multiset.rel_zero_right]
refine factors_unique irreducible_of_factor (fun x hx => (Multiset.not_mem_zero x hx).elim) ?_
rw [Multiset.prod_zero]
exact factors_prod one_ne_zero
#align unique_factorization_monoid.factors_one UniqueFactorizationMonoid.factors_one
theorem exists_mem_factors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ factors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ factors b) (factors a) :=
factors_unique
(fun x hx => (Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_factor _))
irreducible_of_factor
(Associated.symm <|
calc
Multiset.prod (factors a) ~ᵤ a := factors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ factors b) := by
rw [Multiset.prod_cons]; exact (factors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_factors_of_dvd UniqueFactorizationMonoid.exists_mem_factors_of_dvd
theorem exists_mem_factors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) : ∃ p, p ∈ factors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_factors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_factors UniqueFactorizationMonoid.exists_mem_factors
open Classical in
theorem factors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
Multiset.Rel Associated (factors (x * y)) (factors x + factors y) := by
refine
factors_unique irreducible_of_factor
(fun a ha =>
(Multiset.mem_add.mp ha).by_cases (irreducible_of_factor _) (irreducible_of_factor _))
((factors_prod (mul_ne_zero hx hy)).trans ?_)
rw [Multiset.prod_add]
exact (Associated.mul_mul (factors_prod hx) (factors_prod hy)).symm
#align unique_factorization_monoid.factors_mul UniqueFactorizationMonoid.factors_mul
theorem factors_pow {x : α} (n : ℕ) :
Multiset.Rel Associated (factors (x ^ n)) (n • factors x) := by
match n with
| 0 => rw [zero_smul, pow_zero, factors_one, Multiset.rel_zero_right]
| n+1 =>
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
· rw [pow_succ', succ_nsmul']
refine Multiset.Rel.trans _ (factors_mul h0 (pow_ne_zero n h0)) ?_
refine Multiset.Rel.add ?_ <| factors_pow n
exact Multiset.rel_refl_of_refl_on fun y _ => Associated.refl _
#align unique_factorization_monoid.factors_pow UniqueFactorizationMonoid.factors_pow
@[simp]
theorem factors_pos (x : α) (hx : x ≠ 0) : 0 < factors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact (prime_of_factor _ hp).not_unit (isUnit_of_dvd_unit (dvd_of_mem_factors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_factors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.factors_pos UniqueFactorizationMonoid.factors_pos
open Multiset in
theorem factors_pow_count_prod [DecidableEq α] {x : α} (hx : x ≠ 0) :
(∏ p ∈ (factors x).toFinset, p ^ (factors x).count p) ~ᵤ x :=
calc
_ = prod (∑ a ∈ toFinset (factors x), count a (factors x) • {a}) := by
simp only [prod_sum, prod_nsmul, prod_singleton]
_ = prod (factors x) := by rw [toFinset_sum_count_nsmul_eq (factors x)]
_ ~ᵤ x := factors_prod hx
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [NormalizationMonoid α]
variable [UniqueFactorizationMonoid α]
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def normalizedFactors (a : α) : Multiset α :=
Multiset.map normalize <| factors a
#align unique_factorization_monoid.normalized_factors UniqueFactorizationMonoid.normalizedFactors
/-- An arbitrary choice of factors of `x : M` is exactly the (unique) normalized set of factors,
if `M` has a trivial group of units. -/
@[simp]
theorem factors_eq_normalizedFactors {M : Type*} [CancelCommMonoidWithZero M]
[UniqueFactorizationMonoid M] [Unique Mˣ] (x : M) : factors x = normalizedFactors x := by
unfold normalizedFactors
convert (Multiset.map_id (factors x)).symm
ext p
exact normalize_eq p
#align unique_factorization_monoid.factors_eq_normalized_factors UniqueFactorizationMonoid.factors_eq_normalizedFactors
theorem normalizedFactors_prod {a : α} (ane0 : a ≠ 0) :
Associated (normalizedFactors a).prod a := by
rw [normalizedFactors, factors, dif_neg ane0]
refine Associated.trans ?_ (Classical.choose_spec (exists_prime_factors a ane0)).2
rw [← Associates.mk_eq_mk_iff_associated, ← Associates.prod_mk, ← Associates.prod_mk,
Multiset.map_map]
congr 2
ext
rw [Function.comp_apply, Associates.mk_normalize]
#align unique_factorization_monoid.normalized_factors_prod UniqueFactorizationMonoid.normalizedFactors_prod
theorem prime_of_normalized_factor {a : α} : ∀ x : α, x ∈ normalizedFactors a → Prime x := by
rw [normalizedFactors, factors]
split_ifs with ane0; · simp
intro x hx; rcases Multiset.mem_map.1 hx with ⟨y, ⟨hy, rfl⟩⟩
rw [(normalize_associated _).prime_iff]
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 y hy
#align unique_factorization_monoid.prime_of_normalized_factor UniqueFactorizationMonoid.prime_of_normalized_factor
theorem irreducible_of_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → Irreducible x := fun x h =>
(prime_of_normalized_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_normalized_factor UniqueFactorizationMonoid.irreducible_of_normalized_factor
theorem normalize_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → normalize x = x := by
rw [normalizedFactors, factors]
split_ifs with h; · simp
intro x hx
obtain ⟨y, _, rfl⟩ := Multiset.mem_map.1 hx
apply normalize_idem
#align unique_factorization_monoid.normalize_normalized_factor UniqueFactorizationMonoid.normalize_normalized_factor
theorem normalizedFactors_irreducible {a : α} (ha : Irreducible a) :
normalizedFactors a = {normalize a} := by
obtain ⟨p, a_assoc, hp⟩ :=
prime_factors_irreducible ha ⟨prime_of_normalized_factor, normalizedFactors_prod ha.ne_zero⟩
have p_mem : p ∈ normalizedFactors a := by
rw [hp]
exact Multiset.mem_singleton_self _
convert hp
rwa [← normalize_normalized_factor p p_mem, normalize_eq_normalize_iff, dvd_dvd_iff_associated]
#align unique_factorization_monoid.normalized_factors_irreducible UniqueFactorizationMonoid.normalizedFactors_irreducible
theorem normalizedFactors_eq_of_dvd (a : α) :
∀ᵉ (p ∈ normalizedFactors a) (q ∈ normalizedFactors a), p ∣ q → p = q := by
intro p hp q hq hdvd
convert normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd) <;>
apply (normalize_normalized_factor _ ‹_›).symm
#align unique_factorization_monoid.normalized_factors_eq_of_dvd UniqueFactorizationMonoid.normalizedFactors_eq_of_dvd
theorem exists_mem_normalizedFactors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ normalizedFactors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ normalizedFactors b) (normalizedFactors a) :=
factors_unique
(fun x hx =>
(Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_normalized_factor _))
irreducible_of_normalized_factor
(Associated.symm <|
calc
Multiset.prod (normalizedFactors a) ~ᵤ a := normalizedFactors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ normalizedFactors b) := by
rw [Multiset.prod_cons]
exact (normalizedFactors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_normalized_factors_of_dvd UniqueFactorizationMonoid.exists_mem_normalizedFactors_of_dvd
theorem exists_mem_normalizedFactors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) :
∃ p, p ∈ normalizedFactors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_normalizedFactors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_normalized_factors UniqueFactorizationMonoid.exists_mem_normalizedFactors
@[simp]
theorem normalizedFactors_zero : normalizedFactors (0 : α) = 0 := by
simp [normalizedFactors, factors]
#align unique_factorization_monoid.normalized_factors_zero UniqueFactorizationMonoid.normalizedFactors_zero
@[simp]
theorem normalizedFactors_one : normalizedFactors (1 : α) = 0 := by
cases' subsingleton_or_nontrivial α with h h
· dsimp [normalizedFactors, factors]
simp [Subsingleton.elim (1:α) 0]
· rw [← Multiset.rel_zero_right]
apply factors_unique irreducible_of_normalized_factor
· intro x hx
exfalso
apply Multiset.not_mem_zero x hx
· apply normalizedFactors_prod one_ne_zero
#align unique_factorization_monoid.normalized_factors_one UniqueFactorizationMonoid.normalizedFactors_one
@[simp]
theorem normalizedFactors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
normalizedFactors (x * y) = normalizedFactors x + normalizedFactors y := by
have h : (normalize : α → α) = Associates.out ∘ Associates.mk := by
ext
rw [Function.comp_apply, Associates.out_mk]
rw [← Multiset.map_id' (normalizedFactors (x * y)), ← Multiset.map_id' (normalizedFactors x), ←
Multiset.map_id' (normalizedFactors y), ← Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ← Multiset.map_add, h, ←
Multiset.map_map Associates.out, eq_comm, ← Multiset.map_map Associates.out]
refine congr rfl ?_
apply Multiset.map_mk_eq_map_mk_of_rel
apply factors_unique
· intro x hx
rcases Multiset.mem_add.1 hx with (hx | hx) <;> exact irreducible_of_normalized_factor x hx
· exact irreducible_of_normalized_factor
· rw [Multiset.prod_add]
exact
((normalizedFactors_prod hx).mul_mul (normalizedFactors_prod hy)).trans
(normalizedFactors_prod (mul_ne_zero hx hy)).symm
#align unique_factorization_monoid.normalized_factors_mul UniqueFactorizationMonoid.normalizedFactors_mul
@[simp]
theorem normalizedFactors_pow {x : α} (n : ℕ) :
normalizedFactors (x ^ n) = n • normalizedFactors x := by
induction' n with n ih
· simp
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
rw [pow_succ', succ_nsmul', normalizedFactors_mul h0 (pow_ne_zero _ h0), ih]
#align unique_factorization_monoid.normalized_factors_pow UniqueFactorizationMonoid.normalizedFactors_pow
theorem _root_.Irreducible.normalizedFactors_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [UniqueFactorizationMonoid.normalizedFactors_pow, normalizedFactors_irreducible hp,
Multiset.nsmul_singleton]
#align irreducible.normalized_factors_pow Irreducible.normalizedFactors_pow
theorem normalizedFactors_prod_eq (s : Multiset α) (hs : ∀ a ∈ s, Irreducible a) :
normalizedFactors s.prod = s.map normalize := by
induction' s using Multiset.induction with a s ih
· rw [Multiset.prod_zero, normalizedFactors_one, Multiset.map_zero]
· have ia := hs a (Multiset.mem_cons_self a _)
have ib := fun b h => hs b (Multiset.mem_cons_of_mem h)
obtain rfl | ⟨b, hb⟩ := s.empty_or_exists_mem
· rw [Multiset.cons_zero, Multiset.prod_singleton, Multiset.map_singleton,
normalizedFactors_irreducible ia]
haveI := nontrivial_of_ne b 0 (ib b hb).ne_zero
rw [Multiset.prod_cons, Multiset.map_cons,
normalizedFactors_mul ia.ne_zero (Multiset.prod_ne_zero fun h => (ib 0 h).ne_zero rfl),
normalizedFactors_irreducible ia, ih ib, Multiset.singleton_add]
#align unique_factorization_monoid.normalized_factors_prod_eq UniqueFactorizationMonoid.normalizedFactors_prod_eq
theorem dvd_iff_normalizedFactors_le_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ∣ y ↔ normalizedFactors x ≤ normalizedFactors y := by
constructor
· rintro ⟨c, rfl⟩
simp [hx, right_ne_zero_of_mul hy]
· rw [← (normalizedFactors_prod hx).dvd_iff_dvd_left, ←
(normalizedFactors_prod hy).dvd_iff_dvd_right]
apply Multiset.prod_dvd_prod_of_le
#align unique_factorization_monoid.dvd_iff_normalized_factors_le_normalized_factors UniqueFactorizationMonoid.dvd_iff_normalizedFactors_le_normalizedFactors
theorem associated_iff_normalizedFactors_eq_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ~ᵤ y ↔ normalizedFactors x = normalizedFactors y := by
refine
⟨fun h => ?_, fun h =>
(normalizedFactors_prod hx).symm.trans (_root_.trans (by rw [h]) (normalizedFactors_prod hy))⟩
apply le_antisymm <;> rw [← dvd_iff_normalizedFactors_le_normalizedFactors]
all_goals simp [*, h.dvd, h.symm.dvd]
#align unique_factorization_monoid.associated_iff_normalized_factors_eq_normalized_factors UniqueFactorizationMonoid.associated_iff_normalizedFactors_eq_normalizedFactors
theorem normalizedFactors_of_irreducible_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [normalizedFactors_pow, normalizedFactors_irreducible hp, Multiset.nsmul_singleton]
#align unique_factorization_monoid.normalized_factors_of_irreducible_pow UniqueFactorizationMonoid.normalizedFactors_of_irreducible_pow
theorem zero_not_mem_normalizedFactors (x : α) : (0 : α) ∉ normalizedFactors x := fun h =>
Prime.ne_zero (prime_of_normalized_factor _ h) rfl
#align unique_factorization_monoid.zero_not_mem_normalized_factors UniqueFactorizationMonoid.zero_not_mem_normalizedFactors
theorem dvd_of_mem_normalizedFactors {a p : α} (H : p ∈ normalizedFactors a) : p ∣ a := by
by_cases hcases : a = 0
· rw [hcases]
exact dvd_zero p
· exact dvd_trans (Multiset.dvd_prod H) (Associated.dvd (normalizedFactors_prod hcases))
#align unique_factorization_monoid.dvd_of_mem_normalized_factors UniqueFactorizationMonoid.dvd_of_mem_normalizedFactors
theorem mem_normalizedFactors_iff [Unique αˣ] {p x : α} (hx : x ≠ 0) :
p ∈ normalizedFactors x ↔ Prime p ∧ p ∣ x := by
constructor
· intro h
exact ⟨prime_of_normalized_factor p h, dvd_of_mem_normalizedFactors h⟩
· rintro ⟨hprime, hdvd⟩
obtain ⟨q, hqmem, hqeq⟩ := exists_mem_normalizedFactors_of_dvd hx hprime.irreducible hdvd
rw [associated_iff_eq] at hqeq
exact hqeq ▸ hqmem
theorem exists_associated_prime_pow_of_unique_normalized_factor {p r : α}
(h : ∀ {m}, m ∈ normalizedFactors r → m = p) (hr : r ≠ 0) : ∃ i : ℕ, Associated (p ^ i) r := by
use Multiset.card.toFun (normalizedFactors r)
have := UniqueFactorizationMonoid.normalizedFactors_prod hr
rwa [Multiset.eq_replicate_of_mem fun b => h, Multiset.prod_replicate] at this
#align unique_factorization_monoid.exists_associated_prime_pow_of_unique_normalized_factor UniqueFactorizationMonoid.exists_associated_prime_pow_of_unique_normalized_factor
theorem normalizedFactors_prod_of_prime [Nontrivial α] [Unique αˣ] {m : Multiset α}
(h : ∀ p ∈ m, Prime p) : normalizedFactors m.prod = m := by
simpa only [← Multiset.rel_eq, ← associated_eq_eq] using
prime_factors_unique prime_of_normalized_factor h
(normalizedFactors_prod (m.prod_ne_zero_of_prime h))
#align unique_factorization_monoid.normalized_factors_prod_of_prime UniqueFactorizationMonoid.normalizedFactors_prod_of_prime
theorem mem_normalizedFactors_eq_of_associated {a b c : α} (ha : a ∈ normalizedFactors c)
(hb : b ∈ normalizedFactors c) (h : Associated a b) : a = b := by
rw [← normalize_normalized_factor a ha, ← normalize_normalized_factor b hb,
normalize_eq_normalize_iff]
exact Associated.dvd_dvd h
#align unique_factorization_monoid.mem_normalized_factors_eq_of_associated UniqueFactorizationMonoid.mem_normalizedFactors_eq_of_associated
@[simp]
theorem normalizedFactors_pos (x : α) (hx : x ≠ 0) : 0 < normalizedFactors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact
(prime_of_normalized_factor _ hp).not_unit
(isUnit_of_dvd_unit (dvd_of_mem_normalizedFactors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_normalizedFactors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.normalized_factors_pos UniqueFactorizationMonoid.normalizedFactors_pos
theorem dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
DvdNotUnit x y ↔ normalizedFactors x < normalizedFactors y := by
constructor
· rintro ⟨_, c, hc, rfl⟩
simp only [hx, right_ne_zero_of_mul hy, normalizedFactors_mul, Ne, not_false_iff,
lt_add_iff_pos_right, normalizedFactors_pos, hc]
· intro h
exact
dvdNotUnit_of_dvd_of_not_dvd
((dvd_iff_normalizedFactors_le_normalizedFactors hx hy).mpr h.le)
(mt (dvd_iff_normalizedFactors_le_normalizedFactors hy hx).mp h.not_le)
#align unique_factorization_monoid.dvd_not_unit_iff_normalized_factors_lt_normalized_factors UniqueFactorizationMonoid.dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors
theorem normalizedFactors_multiset_prod (s : Multiset α) (hs : 0 ∉ s) :
normalizedFactors (s.prod) = (s.map normalizedFactors).sum := by
cases subsingleton_or_nontrivial α
· obtain rfl : s = 0 := by
apply Multiset.eq_zero_of_forall_not_mem
intro _
convert hs
simp
induction s using Multiset.induction with
| empty => simp
| cons _ _ IH =>
rw [Multiset.prod_cons, Multiset.map_cons, Multiset.sum_cons, normalizedFactors_mul, IH]
· exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
· exact fun h ↦ hs (h ▸ Multiset.mem_cons_self _ _)
· apply Multiset.prod_ne_zero
exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
open scoped Classical
open Multiset Associates
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
/-- Noncomputably defines a `normalizationMonoid` structure on a `UniqueFactorizationMonoid`. -/
protected noncomputable def normalizationMonoid : NormalizationMonoid α :=
normalizationMonoidOfMonoidHomRightInverse
{ toFun := fun a : Associates α =>
if a = 0 then 0
else
((normalizedFactors a).map
(Classical.choose mk_surjective.hasRightInverse : Associates α → α)).prod
map_one' := by nontriviality α; simp
map_mul' := fun x y => by
by_cases hx : x = 0
· simp [hx]
by_cases hy : y = 0
· simp [hy]
simp [hx, hy] }
(by
intro x
dsimp
by_cases hx : x = 0
· simp [hx]
have h : Associates.mkMonoidHom ∘ Classical.choose mk_surjective.hasRightInverse =
(id : Associates α → Associates α) := by
ext x
rw [Function.comp_apply, mkMonoidHom_apply,
Classical.choose_spec mk_surjective.hasRightInverse x]
rfl
rw [if_neg hx, ← mkMonoidHom_apply, MonoidHom.map_multiset_prod, map_map, h, map_id, ←
associated_iff_eq]
apply normalizedFactors_prod hx)
#align unique_factorization_monoid.normalization_monoid UniqueFactorizationMonoid.normalizationMonoid
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable {R : Type*} [CancelCommMonoidWithZero R] [UniqueFactorizationMonoid R]
theorem isRelPrime_iff_no_prime_factors {a b : R} (ha : a ≠ 0) :
IsRelPrime a b ↔ ∀ ⦃d⦄, d ∣ a → d ∣ b → ¬Prime d :=
⟨fun h _ ha hb ↦ (·.not_unit <| h ha hb), fun h ↦ WfDvdMonoid.isRelPrime_of_no_irreducible_factors
(ha ·.1) fun _ irr ha hb ↦ h ha hb (UniqueFactorizationMonoid.irreducible_iff_prime.mp irr)⟩
#align unique_factorization_monoid.no_factors_of_no_prime_factors UniqueFactorizationMonoid.isRelPrime_iff_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `c` have no common prime factors, `a ∣ b`.
Compare `IsCoprime.dvd_of_dvd_mul_left`. -/
theorem dvd_of_dvd_mul_left_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(h : ∀ ⦃d⦄, d ∣ a → d ∣ c → ¬Prime d) : a ∣ b * c → a ∣ b :=
((isRelPrime_iff_no_prime_factors ha).mpr h).dvd_of_dvd_mul_right
#align unique_factorization_monoid.dvd_of_dvd_mul_left_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_left_of_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `b` have no common prime factors, `a ∣ c`.
Compare `IsCoprime.dvd_of_dvd_mul_right`. -/
theorem dvd_of_dvd_mul_right_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(no_factors : ∀ {d}, d ∣ a → d ∣ b → ¬Prime d) : a ∣ b * c → a ∣ c := by
simpa [mul_comm b c] using dvd_of_dvd_mul_left_of_no_prime_factors ha @no_factors
#align unique_factorization_monoid.dvd_of_dvd_mul_right_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_right_of_no_prime_factors
/-- If `a ≠ 0, b` are elements of a unique factorization domain, then dividing
out their common factor `c'` gives `a'` and `b'` with no factors in common. -/
theorem exists_reduced_factors :
∀ a ≠ (0 : R), ∀ b,
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b := by
intro a
refine induction_on_prime a ?_ ?_ ?_
· intros
contradiction
· intro a a_unit _ b
use a, b, 1
constructor
· intro p p_dvd_a _
exact isUnit_of_dvd_unit p_dvd_a a_unit
· simp
· intro a p a_ne_zero p_prime ih_a pa_ne_zero b
by_cases h : p ∣ b
· rcases h with ⟨b, rfl⟩
obtain ⟨a', b', c', no_factor, ha', hb'⟩ := ih_a a_ne_zero b
refine ⟨a', b', p * c', @no_factor, ?_, ?_⟩
· rw [mul_assoc, ha']
· rw [mul_assoc, hb']
· obtain ⟨a', b', c', coprime, rfl, rfl⟩ := ih_a a_ne_zero b
refine ⟨p * a', b', c', ?_, mul_left_comm _ _ _, rfl⟩
intro q q_dvd_pa' q_dvd_b'
cases' p_prime.left_dvd_or_dvd_right_of_dvd_mul q_dvd_pa' with p_dvd_q q_dvd_a'
· have : p ∣ c' * b' := dvd_mul_of_dvd_right (p_dvd_q.trans q_dvd_b') _
contradiction
exact coprime q_dvd_a' q_dvd_b'
#align unique_factorization_monoid.exists_reduced_factors UniqueFactorizationMonoid.exists_reduced_factors
theorem exists_reduced_factors' (a b : R) (hb : b ≠ 0) :
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b :=
let ⟨b', a', c', no_factor, hb, ha⟩ := exists_reduced_factors b hb a
⟨a', b', c', fun _ hpb hpa => no_factor hpa hpb, ha, hb⟩
#align unique_factorization_monoid.exists_reduced_factors' UniqueFactorizationMonoid.exists_reduced_factors'
theorem pow_right_injective {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) :
Function.Injective (a ^ · : ℕ → R) := by
letI := Classical.decEq R
intro i j hij
letI : Nontrivial R := ⟨⟨a, 0, ha0⟩⟩
letI : NormalizationMonoid R := UniqueFactorizationMonoid.normalizationMonoid
obtain ⟨p', hp', dvd'⟩ := WfDvdMonoid.exists_irreducible_factor ha1 ha0
obtain ⟨p, mem, _⟩ := exists_mem_normalizedFactors_of_dvd ha0 hp' dvd'
have := congr_arg (fun x => Multiset.count p (normalizedFactors x)) hij
simp only [normalizedFactors_pow, Multiset.count_nsmul] at this
exact mul_right_cancel₀ (Multiset.count_ne_zero.mpr mem) this
#align unique_factorization_monoid.pow_right_injective UniqueFactorizationMonoid.pow_right_injective
theorem pow_eq_pow_iff {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) {i j : ℕ} : a ^ i = a ^ j ↔ i = j :=
(pow_right_injective ha0 ha1).eq_iff
#align unique_factorization_monoid.pow_eq_pow_iff UniqueFactorizationMonoid.pow_eq_pow_iff
section multiplicity
variable [NormalizationMonoid R]
variable [DecidableRel (Dvd.dvd : R → R → Prop)]
open multiplicity Multiset
theorem le_multiplicity_iff_replicate_le_normalizedFactors {a b : R} {n : ℕ} (ha : Irreducible a)
(hb : b ≠ 0) :
↑n ≤ multiplicity a b ↔ replicate n (normalize a) ≤ normalizedFactors b := by
rw [← pow_dvd_iff_le_multiplicity]
revert b
induction' n with n ih; · simp
intro b hb
constructor
· rintro ⟨c, rfl⟩
rw [Ne, pow_succ', mul_assoc, mul_eq_zero, not_or] at hb
rw [pow_succ', mul_assoc, normalizedFactors_mul hb.1 hb.2, replicate_succ,
normalizedFactors_irreducible ha, singleton_add, cons_le_cons_iff, ← ih hb.2]
apply Dvd.intro _ rfl
· rw [Multiset.le_iff_exists_add]
rintro ⟨u, hu⟩
rw [← (normalizedFactors_prod hb).dvd_iff_dvd_right, hu, prod_add, prod_replicate]
exact (Associated.pow_pow <| associated_normalize a).dvd.trans (Dvd.intro u.prod rfl)
#align unique_factorization_monoid.le_multiplicity_iff_replicate_le_normalized_factors UniqueFactorizationMonoid.le_multiplicity_iff_replicate_le_normalizedFactors
/-- The multiplicity of an irreducible factor of a nonzero element is exactly the number of times
the normalized factor occurs in the `normalizedFactors`.
See also `count_normalizedFactors_eq` which expands the definition of `multiplicity`
to produce a specification for `count (normalizedFactors _) _`..
-/
theorem multiplicity_eq_count_normalizedFactors [DecidableEq R] {a b : R} (ha : Irreducible a)
(hb : b ≠ 0) : multiplicity a b = (normalizedFactors b).count (normalize a) := by
apply le_antisymm
· apply PartENat.le_of_lt_add_one
rw [← Nat.cast_one, ← Nat.cast_add, lt_iff_not_ge, ge_iff_le,
le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
simp
rw [le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
#align unique_factorization_monoid.multiplicity_eq_count_normalized_factors UniqueFactorizationMonoid.multiplicity_eq_count_normalizedFactors
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq [DecidableEq R] {p x : R} (hp : Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
letI : DecidableRel ((· ∣ ·) : R → R → Prop) := fun _ _ => Classical.propDecidable _
by_cases hx0 : x = 0
· simp [hx0] at hlt
rw [← PartENat.natCast_inj]
convert (multiplicity_eq_count_normalizedFactors hp hx0).symm
· exact hnorm.symm
exact (multiplicity.eq_coe_iff.mpr ⟨hle, hlt⟩).symm
#align unique_factorization_monoid.count_normalized_factors_eq UniqueFactorizationMonoid.count_normalizedFactors_eq
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`. This is a slightly more general version of
`UniqueFactorizationMonoid.count_normalizedFactors_eq` that allows `p = 0`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq' [DecidableEq R] {p x : R} (hp : p = 0 ∨ Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
rcases hp with (rfl | hp)
· cases n
· exact count_eq_zero.2 (zero_not_mem_normalizedFactors _)
· rw [zero_pow (Nat.succ_ne_zero _)] at hle hlt
exact absurd hle hlt
· exact count_normalizedFactors_eq hp hnorm hle hlt
#align unique_factorization_monoid.count_normalized_factors_eq' UniqueFactorizationMonoid.count_normalizedFactors_eq'
/-- Deprecated. Use `WfDvdMonoid.max_power_factor` instead. -/
@[deprecated WfDvdMonoid.max_power_factor]
theorem max_power_factor {a₀ x : R} (h : a₀ ≠ 0) (hx : Irreducible x) :
∃ n : ℕ, ∃ a : R, ¬x ∣ a ∧ a₀ = x ^ n * a := WfDvdMonoid.max_power_factor h hx
#align unique_factorization_monoid.max_power_factor UniqueFactorizationMonoid.max_power_factor
end multiplicity
section Multiplicative
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
variable {β : Type*} [CancelCommMonoidWithZero β]
theorem prime_pow_coprime_prod_of_coprime_insert [DecidableEq α] {s : Finset α} (i : α → ℕ) (p : α)
(hps : p ∉ s) (is_prime : ∀ q ∈ insert p s, Prime q)
(is_coprime : ∀ᵉ (q ∈ insert p s) (q' ∈ insert p s), q ∣ q' → q = q') :
IsRelPrime (p ^ i p) (∏ p' ∈ s, p' ^ i p') := by
have hp := is_prime _ (Finset.mem_insert_self _ _)
refine (isRelPrime_iff_no_prime_factors <| pow_ne_zero _ hp.ne_zero).mpr ?_
intro d hdp hdprod hd
apply hps
replace hdp := hd.dvd_of_dvd_pow hdp
obtain ⟨q, q_mem', hdq⟩ := hd.exists_mem_multiset_dvd hdprod
obtain ⟨q, q_mem, rfl⟩ := Multiset.mem_map.mp q_mem'
replace hdq := hd.dvd_of_dvd_pow hdq
have : p ∣ q := dvd_trans (hd.irreducible.dvd_symm hp.irreducible hdp) hdq
convert q_mem
rw [Finset.mem_val,
is_coprime _ (Finset.mem_insert_self p s) _ (Finset.mem_insert_of_mem q_mem) this]
#align unique_factorization_monoid.prime_pow_coprime_prod_of_coprime_insert UniqueFactorizationMonoid.prime_pow_coprime_prod_of_coprime_insert
/-- If `P` holds for units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on a product of powers of distinct primes. -/
-- @[elab_as_elim] Porting note: commented out
theorem induction_on_prime_power {P : α → Prop} (s : Finset α) (i : α → ℕ)
(is_prime : ∀ p ∈ s, Prime p) (is_coprime : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q)
(h1 : ∀ {x}, IsUnit x → P x) (hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) :
P (∏ p ∈ s, p ^ i p) := by
letI := Classical.decEq α
induction' s using Finset.induction_on with p f' hpf' ih
· simpa using h1 isUnit_one
rw [Finset.prod_insert hpf']
exact
hcp (prime_pow_coprime_prod_of_coprime_insert i p hpf' is_prime is_coprime)
(hpr (i p) (is_prime _ (Finset.mem_insert_self _ _)))
(ih (fun q hq => is_prime _ (Finset.mem_insert_of_mem hq)) fun q hq q' hq' =>
is_coprime _ (Finset.mem_insert_of_mem hq) _ (Finset.mem_insert_of_mem hq'))
#align unique_factorization_monoid.induction_on_prime_power UniqueFactorizationMonoid.induction_on_prime_power
/-- If `P` holds for `0`, units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on all `a : α`. -/
@[elab_as_elim]
theorem induction_on_coprime {P : α → Prop} (a : α) (h0 : P 0) (h1 : ∀ {x}, IsUnit x → P x)
(hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) : P a := by
letI := Classical.decEq α
have P_of_associated : ∀ {x y}, Associated x y → P x → P y := by
rintro x y ⟨u, rfl⟩ hx
exact hcp (fun p _ hpx => isUnit_of_dvd_unit hpx u.isUnit) hx (h1 u.isUnit)
by_cases ha0 : a = 0
· rwa [ha0]
haveI : Nontrivial α := ⟨⟨_, _, ha0⟩⟩
letI : NormalizationMonoid α := UniqueFactorizationMonoid.normalizationMonoid
refine P_of_associated (normalizedFactors_prod ha0) ?_
rw [← (normalizedFactors a).map_id, Finset.prod_multiset_map_count]
refine induction_on_prime_power _ _ ?_ ?_ @h1 @hpr @hcp <;> simp only [Multiset.mem_toFinset]
· apply prime_of_normalized_factor
· apply normalizedFactors_eq_of_dvd
#align unique_factorization_monoid.induction_on_coprime UniqueFactorizationMonoid.induction_on_coprime
/-- If `f` maps `p ^ i` to `(f p) ^ i` for primes `p`, and `f`
is multiplicative on coprime elements, then `f` is multiplicative on all products of primes. -/
-- @[elab_as_elim] Porting note: commented out
theorem multiplicative_prime_power {f : α → β} (s : Finset α) (i j : α → ℕ)
(is_prime : ∀ p ∈ s, Prime p) (is_coprime : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q)
(h1 : ∀ {x y}, IsUnit y → f (x * y) = f x * f y)
(hpr : ∀ {p} (i : ℕ), Prime p → f (p ^ i) = f p ^ i)
(hcp : ∀ {x y}, IsRelPrime x y → f (x * y) = f x * f y) :
f (∏ p ∈ s, p ^ (i p + j p)) = f (∏ p ∈ s, p ^ i p) * f (∏ p ∈ s, p ^ j p) := by
letI := Classical.decEq α
induction' s using Finset.induction_on with p s hps ih
· simpa using h1 isUnit_one
have hpr_p := is_prime _ (Finset.mem_insert_self _ _)
have hpr_s : ∀ p ∈ s, Prime p := fun p hp => is_prime _ (Finset.mem_insert_of_mem hp)
have hcp_p := fun i => prime_pow_coprime_prod_of_coprime_insert i p hps is_prime is_coprime
have hcp_s : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q := fun p hp q hq =>
is_coprime p (Finset.mem_insert_of_mem hp) q (Finset.mem_insert_of_mem hq)
rw [Finset.prod_insert hps, Finset.prod_insert hps, Finset.prod_insert hps, hcp (hcp_p _),
hpr _ hpr_p, hcp (hcp_p _), hpr _ hpr_p, hcp (hcp_p (fun p => i p + j p)), hpr _ hpr_p,
ih hpr_s hcp_s, pow_add, mul_assoc, mul_left_comm (f p ^ j p), mul_assoc]
#align unique_factorization_monoid.multiplicative_prime_power UniqueFactorizationMonoid.multiplicative_prime_power
/-- If `f` maps `p ^ i` to `(f p) ^ i` for primes `p`, and `f`
is multiplicative on coprime elements, then `f` is multiplicative everywhere. -/
theorem multiplicative_of_coprime (f : α → β) (a b : α) (h0 : f 0 = 0)
(h1 : ∀ {x y}, IsUnit y → f (x * y) = f x * f y)
(hpr : ∀ {p} (i : ℕ), Prime p → f (p ^ i) = f p ^ i)
(hcp : ∀ {x y}, IsRelPrime x y → f (x * y) = f x * f y) :
f (a * b) = f a * f b := by
letI := Classical.decEq α
by_cases ha0 : a = 0
· rw [ha0, zero_mul, h0, zero_mul]
by_cases hb0 : b = 0
· rw [hb0, mul_zero, h0, mul_zero]
by_cases hf1 : f 1 = 0
· calc
f (a * b) = f (a * b * 1) := by rw [mul_one]
_ = 0 := by simp only [h1 isUnit_one, hf1, mul_zero]
_ = f a * f (b * 1) := by simp only [h1 isUnit_one, hf1, mul_zero]
_ = f a * f b := by rw [mul_one]
haveI : Nontrivial α := ⟨⟨_, _, ha0⟩⟩
letI : NormalizationMonoid α := UniqueFactorizationMonoid.normalizationMonoid
suffices
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ ((normalizedFactors a).count p + (normalizedFactors b).count p)) =
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ (normalizedFactors a).count p) *
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ (normalizedFactors b).count p) by
obtain ⟨ua, a_eq⟩ := normalizedFactors_prod ha0
obtain ⟨ub, b_eq⟩ := normalizedFactors_prod hb0
rw [← a_eq, ← b_eq, mul_right_comm (Multiset.prod (normalizedFactors a)) ua
(Multiset.prod (normalizedFactors b) * ub), h1 ua.isUnit, h1 ub.isUnit, h1 ua.isUnit, ←
mul_assoc, h1 ub.isUnit, mul_right_comm _ (f ua), ← mul_assoc]
congr
rw [← (normalizedFactors a).map_id, ← (normalizedFactors b).map_id,
Finset.prod_multiset_map_count, Finset.prod_multiset_map_count,
Finset.prod_subset (Finset.subset_union_left (s₂:=(normalizedFactors b).toFinset)),
Finset.prod_subset (Finset.subset_union_right (s₂:=(normalizedFactors b).toFinset)), ←
Finset.prod_mul_distrib]
· simp_rw [id, ← pow_add, this]
all_goals simp only [Multiset.mem_toFinset]
· intro p _ hpb
simp [hpb]
· intro p _ hpa
simp [hpa]
refine multiplicative_prime_power _ _ _ ?_ ?_ @h1 @hpr @hcp
all_goals simp only [Multiset.mem_toFinset, Finset.mem_union]
· rintro p (hpa | hpb) <;> apply prime_of_normalized_factor <;> assumption
· rintro p (hp | hp) q (hq | hq) hdvd <;>
rw [← normalize_normalized_factor _ hp, ← normalize_normalized_factor _ hq] <;>
exact
normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd)
#align unique_factorization_monoid.multiplicative_of_coprime UniqueFactorizationMonoid.multiplicative_of_coprime
end Multiplicative
end UniqueFactorizationMonoid
namespace Associates
open UniqueFactorizationMonoid Associated Multiset
variable [CancelCommMonoidWithZero α]
/-- `FactorSet α` representation elements of unique factorization domain as multisets.
`Multiset α` produced by `normalizedFactors` are only unique up to associated elements, while the
multisets in `FactorSet α` are unique by equality and restricted to irreducible elements. This
gives us a representation of each element as a unique multisets (or the added ⊤ for 0), which has a
complete lattice structure. Infimum is the greatest common divisor and supremum is the least common
multiple.
-/
abbrev FactorSet.{u} (α : Type u) [CancelCommMonoidWithZero α] : Type u :=
WithTop (Multiset { a : Associates α // Irreducible a })
#align associates.factor_set Associates.FactorSet
attribute [local instance] Associated.setoid
theorem FactorSet.coe_add {a b : Multiset { a : Associates α // Irreducible a }} :
(↑(a + b) : FactorSet α) = a + b := by norm_cast
#align associates.factor_set.coe_add Associates.FactorSet.coe_add
theorem FactorSet.sup_add_inf_eq_add [DecidableEq (Associates α)] :
∀ a b : FactorSet α, a ⊔ b + a ⊓ b = a + b
| ⊤, b => show ⊤ ⊔ b + ⊤ ⊓ b = ⊤ + b by simp
| a, ⊤ => show a ⊔ ⊤ + a ⊓ ⊤ = a + ⊤ by simp
| WithTop.some a, WithTop.some b =>
show (a : FactorSet α) ⊔ b + (a : FactorSet α) ⊓ b = a + b by
rw [← WithTop.coe_sup, ← WithTop.coe_inf, ← WithTop.coe_add, ← WithTop.coe_add,
WithTop.coe_eq_coe]
exact Multiset.union_add_inter _ _
#align associates.factor_set.sup_add_inf_eq_add Associates.FactorSet.sup_add_inf_eq_add
/-- Evaluates the product of a `FactorSet` to be the product of the corresponding multiset,
or `0` if there is none. -/
def FactorSet.prod : FactorSet α → Associates α
| ⊤ => 0
| WithTop.some s => (s.map (↑)).prod
#align associates.factor_set.prod Associates.FactorSet.prod
@[simp]
theorem prod_top : (⊤ : FactorSet α).prod = 0 :=
rfl
#align associates.prod_top Associates.prod_top
@[simp]
theorem prod_coe {s : Multiset { a : Associates α // Irreducible a }} :
FactorSet.prod (s : FactorSet α) = (s.map (↑)).prod :=
rfl
#align associates.prod_coe Associates.prod_coe
@[simp]
theorem prod_add : ∀ a b : FactorSet α, (a + b).prod = a.prod * b.prod
| ⊤, b => show (⊤ + b).prod = (⊤ : FactorSet α).prod * b.prod by simp
| a, ⊤ => show (a + ⊤).prod = a.prod * (⊤ : FactorSet α).prod by simp
| WithTop.some a, WithTop.some b => by
rw [← FactorSet.coe_add, prod_coe, prod_coe, prod_coe, Multiset.map_add, Multiset.prod_add]
#align associates.prod_add Associates.prod_add
@[gcongr]
theorem prod_mono : ∀ {a b : FactorSet α}, a ≤ b → a.prod ≤ b.prod
| ⊤, b, h => by
have : b = ⊤ := top_unique h
rw [this, prod_top]
| a, ⊤, _ => show a.prod ≤ (⊤ : FactorSet α).prod by simp
| WithTop.some a, WithTop.some b, h =>
prod_le_prod <| Multiset.map_le_map <| WithTop.coe_le_coe.1 <| h
#align associates.prod_mono Associates.prod_mono
theorem FactorSet.prod_eq_zero_iff [Nontrivial α] (p : FactorSet α) : p.prod = 0 ↔ p = ⊤ := by
unfold FactorSet at p
induction p -- TODO: `induction_eliminator` doesn't work with `abbrev`
· simp only [iff_self_iff, eq_self_iff_true, Associates.prod_top]
· rw [prod_coe, Multiset.prod_eq_zero_iff, Multiset.mem_map, eq_false WithTop.coe_ne_top,
iff_false_iff, not_exists]
exact fun a => not_and_of_not_right _ a.prop.ne_zero
#align associates.factor_set.prod_eq_zero_iff Associates.FactorSet.prod_eq_zero_iff
section count
variable [DecidableEq (Associates α)]
/-- `bcount p s` is the multiplicity of `p` in the FactorSet `s` (with bundled `p`)-/
def bcount (p : { a : Associates α // Irreducible a }) :
FactorSet α → ℕ
| ⊤ => 0
| WithTop.some s => s.count p
#align associates.bcount Associates.bcount
variable [∀ p : Associates α, Decidable (Irreducible p)] {p : Associates α}
/-- `count p s` is the multiplicity of the irreducible `p` in the FactorSet `s`.
If `p` is not irreducible, `count p s` is defined to be `0`. -/
def count (p : Associates α) : FactorSet α → ℕ :=
if hp : Irreducible p then bcount ⟨p, hp⟩ else 0
#align associates.count Associates.count
@[simp]
theorem count_some (hp : Irreducible p) (s : Multiset _) :
count p (WithTop.some s) = s.count ⟨p, hp⟩ := by
simp only [count, dif_pos hp, bcount]
#align associates.count_some Associates.count_some
@[simp]
theorem count_zero (hp : Irreducible p) : count p (0 : FactorSet α) = 0 := by
simp only [count, dif_pos hp, bcount, Multiset.count_zero]
#align associates.count_zero Associates.count_zero
theorem count_reducible (hp : ¬Irreducible p) : count p = 0 := dif_neg hp
#align associates.count_reducible Associates.count_reducible
end count
section Mem
/-- membership in a FactorSet (bundled version) -/
def BfactorSetMem : { a : Associates α // Irreducible a } → FactorSet α → Prop
| _, ⊤ => True
| p, some l => p ∈ l
#align associates.bfactor_set_mem Associates.BfactorSetMem
/-- `FactorSetMem p s` is the predicate that the irreducible `p` is a member of
`s : FactorSet α`.
If `p` is not irreducible, `p` is not a member of any `FactorSet`. -/
def FactorSetMem (p : Associates α) (s : FactorSet α) : Prop :=
letI : Decidable (Irreducible p) := Classical.dec _
if hp : Irreducible p then BfactorSetMem ⟨p, hp⟩ s else False
#align associates.factor_set_mem Associates.FactorSetMem
instance : Membership (Associates α) (FactorSet α) :=
⟨FactorSetMem⟩
@[simp]
theorem factorSetMem_eq_mem (p : Associates α) (s : FactorSet α) : FactorSetMem p s = (p ∈ s) :=
rfl
#align associates.factor_set_mem_eq_mem Associates.factorSetMem_eq_mem
theorem mem_factorSet_top {p : Associates α} {hp : Irreducible p} : p ∈ (⊤ : FactorSet α) := by
dsimp only [Membership.mem]; dsimp only [FactorSetMem]; split_ifs; exact trivial
#align associates.mem_factor_set_top Associates.mem_factorSet_top
theorem mem_factorSet_some {p : Associates α} {hp : Irreducible p}
{l : Multiset { a : Associates α // Irreducible a }} :
p ∈ (l : FactorSet α) ↔ Subtype.mk p hp ∈ l := by
dsimp only [Membership.mem]; dsimp only [FactorSetMem]; split_ifs; rfl
#align associates.mem_factor_set_some Associates.mem_factorSet_some
theorem reducible_not_mem_factorSet {p : Associates α} (hp : ¬Irreducible p) (s : FactorSet α) :
¬p ∈ s := fun h ↦ by
rwa [← factorSetMem_eq_mem, FactorSetMem, dif_neg hp] at h
#align associates.reducible_not_mem_factor_set Associates.reducible_not_mem_factorSet
theorem irreducible_of_mem_factorSet {p : Associates α} {s : FactorSet α} (h : p ∈ s) :
Irreducible p :=
by_contra fun hp ↦ reducible_not_mem_factorSet hp s h
end Mem
variable [UniqueFactorizationMonoid α]
theorem unique' {p q : Multiset (Associates α)} :
(∀ a ∈ p, Irreducible a) → (∀ a ∈ q, Irreducible a) → p.prod = q.prod → p = q := by
apply Multiset.induction_on_multiset_quot p
apply Multiset.induction_on_multiset_quot q
intro s t hs ht eq
refine Multiset.map_mk_eq_map_mk_of_rel (UniqueFactorizationMonoid.factors_unique ?_ ?_ ?_)
· exact fun a ha => irreducible_mk.1 <| hs _ <| Multiset.mem_map_of_mem _ ha
· exact fun a ha => irreducible_mk.1 <| ht _ <| Multiset.mem_map_of_mem _ ha
have eq' : (Quot.mk Setoid.r : α → Associates α) = Associates.mk := funext quot_mk_eq_mk
rwa [eq', prod_mk, prod_mk, mk_eq_mk_iff_associated] at eq
#align associates.unique' Associates.unique'
theorem FactorSet.unique [Nontrivial α] {p q : FactorSet α} (h : p.prod = q.prod) : p = q := by
-- TODO: `induction_eliminator` doesn't work with `abbrev`
unfold FactorSet at p q
induction p <;> induction q
· rfl
· rw [eq_comm, ← FactorSet.prod_eq_zero_iff, ← h, Associates.prod_top]
· rw [← FactorSet.prod_eq_zero_iff, h, Associates.prod_top]
· congr 1
rw [← Multiset.map_eq_map Subtype.coe_injective]
apply unique' _ _ h <;>
· intro a ha
obtain ⟨⟨a', irred⟩, -, rfl⟩ := Multiset.mem_map.mp ha
rwa [Subtype.coe_mk]
#align associates.factor_set.unique Associates.FactorSet.unique
theorem prod_le_prod_iff_le [Nontrivial α] {p q : Multiset (Associates α)}
(hp : ∀ a ∈ p, Irreducible a) (hq : ∀ a ∈ q, Irreducible a) : p.prod ≤ q.prod ↔ p ≤ q := by
refine ⟨?_, prod_le_prod⟩
rintro ⟨c, eqc⟩
refine Multiset.le_iff_exists_add.2 ⟨factors c, unique' hq (fun x hx ↦ ?_) ?_⟩
· obtain h | h := Multiset.mem_add.1 hx
· exact hp x h
· exact irreducible_of_factor _ h
· rw [eqc, Multiset.prod_add]
congr
refine associated_iff_eq.mp (factors_prod fun hc => ?_).symm
refine not_irreducible_zero (hq _ ?_)
rw [← prod_eq_zero_iff, eqc, hc, mul_zero]
#align associates.prod_le_prod_iff_le Associates.prod_le_prod_iff_le
/-- This returns the multiset of irreducible factors as a `FactorSet`,
a multiset of irreducible associates `WithTop`. -/
noncomputable def factors' (a : α) : Multiset { a : Associates α // Irreducible a } :=
(factors a).pmap (fun a ha => ⟨Associates.mk a, irreducible_mk.2 ha⟩) irreducible_of_factor
#align associates.factors' Associates.factors'
@[simp]
theorem map_subtype_coe_factors' {a : α} :
(factors' a).map (↑) = (factors a).map Associates.mk := by
simp [factors', Multiset.map_pmap, Multiset.pmap_eq_map]
#align associates.map_subtype_coe_factors' Associates.map_subtype_coe_factors'
theorem factors'_cong {a b : α} (h : a ~ᵤ b) : factors' a = factors' b := by
obtain rfl | hb := eq_or_ne b 0
· rw [associated_zero_iff_eq_zero] at h
rw [h]
have ha : a ≠ 0 := by
contrapose! hb with ha
rw [← associated_zero_iff_eq_zero, ← ha]
exact h.symm
rw [← Multiset.map_eq_map Subtype.coe_injective, map_subtype_coe_factors',
map_subtype_coe_factors', ← rel_associated_iff_map_eq_map]
exact
factors_unique irreducible_of_factor irreducible_of_factor
((factors_prod ha).trans <| h.trans <| (factors_prod hb).symm)
#align associates.factors'_cong Associates.factors'_cong
/-- This returns the multiset of irreducible factors of an associate as a `FactorSet`,
a multiset of irreducible associates `WithTop`. -/
noncomputable def factors (a : Associates α) : FactorSet α := by
classical refine if h : a = 0 then ⊤ else Quotient.hrecOn a (fun x _ => factors' x) ?_ h
intro a b hab
apply Function.hfunext
· have : a ~ᵤ 0 ↔ b ~ᵤ 0 := Iff.intro (fun ha0 => hab.symm.trans ha0) fun hb0 => hab.trans hb0
simp only [associated_zero_iff_eq_zero] at this
simp only [quotient_mk_eq_mk, this, mk_eq_zero]
exact fun ha hb _ => heq_of_eq <| congr_arg some <| factors'_cong hab
#align associates.factors Associates.factors
@[simp]
theorem factors_zero : (0 : Associates α).factors = ⊤ :=
dif_pos rfl
#align associates.factors_0 Associates.factors_zero
@[deprecated (since := "2024-03-16")] alias factors_0 := factors_zero
@[simp]
| Mathlib/RingTheory/UniqueFactorizationDomain.lean | 1,468 | 1,471 | theorem factors_mk (a : α) (h : a ≠ 0) : (Associates.mk a).factors = factors' a := by |
classical
apply dif_neg
apply mt mk_eq_zero.1 h
|
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.Geometry.RingedSpace.OpenImmersion
import Mathlib.AlgebraicGeometry.Scheme
import Mathlib.CategoryTheory.Limits.Shapes.CommSq
#align_import algebraic_geometry.open_immersion.Scheme from "leanprover-community/mathlib"@"533f62f4dd62a5aad24a04326e6e787c8f7e98b1"
/-!
# Open immersions of schemes
-/
-- Explicit universe annotations were used in this file to improve perfomance #12737
set_option linter.uppercaseLean3 false
noncomputable section
open TopologicalSpace CategoryTheory Opposite
open CategoryTheory.Limits
namespace AlgebraicGeometry
universe v v₁ v₂ u
variable {C : Type u} [Category.{v} C]
/-- A morphism of Schemes is an open immersion if it is an open immersion as a morphism
of LocallyRingedSpaces
-/
abbrev IsOpenImmersion {X Y : Scheme.{u}} (f : X ⟶ Y) : Prop :=
LocallyRingedSpace.IsOpenImmersion f
#align algebraic_geometry.IsOpenImmersion AlgebraicGeometry.IsOpenImmersion
instance IsOpenImmersion.comp {X Y Z : Scheme.{u}} (f : X ⟶ Y) (g : Y ⟶ Z)
[IsOpenImmersion f] [IsOpenImmersion g] : IsOpenImmersion (f ≫ g) :=
LocallyRingedSpace.IsOpenImmersion.comp f g
namespace LocallyRingedSpace.IsOpenImmersion
/-- To show that a locally ringed space is a scheme, it suffices to show that it has a jointly
surjective family of open immersions from affine schemes. -/
protected def scheme (X : LocallyRingedSpace.{u})
(h :
∀ x : X,
∃ (R : CommRingCat) (f : Spec.toLocallyRingedSpace.obj (op R) ⟶ X),
(x ∈ Set.range f.1.base : _) ∧ LocallyRingedSpace.IsOpenImmersion f) :
Scheme where
toLocallyRingedSpace := X
local_affine := by
intro x
obtain ⟨R, f, h₁, h₂⟩ := h x
refine ⟨⟨⟨_, h₂.base_open.isOpen_range⟩, h₁⟩, R, ⟨?_⟩⟩
apply LocallyRingedSpace.isoOfSheafedSpaceIso
refine SheafedSpace.forgetToPresheafedSpace.preimageIso ?_
apply PresheafedSpace.IsOpenImmersion.isoOfRangeEq (PresheafedSpace.ofRestrict _ _) f.1
· exact Subtype.range_coe_subtype
· exact Opens.openEmbedding _ -- Porting note (#11187): was `infer_instance`
#align algebraic_geometry.LocallyRingedSpace.IsOpenImmersion.Scheme AlgebraicGeometry.LocallyRingedSpace.IsOpenImmersion.scheme
end LocallyRingedSpace.IsOpenImmersion
theorem IsOpenImmersion.isOpen_range {X Y : Scheme.{u}} (f : X ⟶ Y) [H : IsOpenImmersion f] :
IsOpen (Set.range f.1.base) :=
H.base_open.isOpen_range
#align algebraic_geometry.IsOpenImmersion.open_range AlgebraicGeometry.IsOpenImmersion.isOpen_range
@[deprecated (since := "2024-03-17")]
alias IsOpenImmersion.open_range := IsOpenImmersion.isOpen_range
section OpenCover
namespace Scheme
-- TODO: provide API to and from a presieve.
/-- An open cover of `X` consists of a family of open immersions into `X`,
and for each `x : X` an open immersion (indexed by `f x`) that covers `x`.
This is merely a coverage in the Zariski pretopology, and it would be optimal
if we could reuse the existing API about pretopologies, However, the definitions of sieves and
grothendieck topologies uses `Prop`s, so that the actual open sets and immersions are hard to
obtain. Also, since such a coverage in the pretopology usually contains a proper class of
immersions, it is quite hard to glue them, reason about finite covers, etc.
-/
structure OpenCover (X : Scheme.{u}) where
/-- index set of an open cover of a scheme `X` -/
J : Type v
/-- the subschemes of an open cover -/
obj : J → Scheme
/-- the embedding of subschemes to `X` -/
map : ∀ j : J, obj j ⟶ X
/-- given a point of `x : X`, `f x` is the index of the subscheme which contains `x` -/
f : X.carrier → J
/-- the subschemes covers `X` -/
Covers : ∀ x, x ∈ Set.range (map (f x)).1.base
/-- the embedding of subschemes are open immersions -/
IsOpen : ∀ x, IsOpenImmersion (map x) := by infer_instance
#align algebraic_geometry.Scheme.open_cover AlgebraicGeometry.Scheme.OpenCover
attribute [instance] OpenCover.IsOpen
variable {X Y Z : Scheme.{u}} (𝒰 : OpenCover X) (f : X ⟶ Z) (g : Y ⟶ Z)
variable [∀ x, HasPullback (𝒰.map x ≫ f) g]
/-- The affine cover of a scheme. -/
def affineCover (X : Scheme.{u}) : OpenCover X where
J := X.carrier
obj x := Spec.obj <| Opposite.op (X.local_affine x).choose_spec.choose
map x :=
((X.local_affine x).choose_spec.choose_spec.some.inv ≫ X.toLocallyRingedSpace.ofRestrict _ : _)
f x := x
IsOpen x := by
apply (config := { allowSynthFailures := true }) PresheafedSpace.IsOpenImmersion.comp
apply PresheafedSpace.IsOpenImmersion.ofRestrict
Covers := by
intro x
erw [TopCat.coe_comp] -- now `erw` after #13170
rw [Set.range_comp, Set.range_iff_surjective.mpr, Set.image_univ]
· erw [Subtype.range_coe_subtype]
exact (X.local_affine x).choose.2
erw [← TopCat.epi_iff_surjective] -- now `erw` after #13170
change Epi ((SheafedSpace.forget _).map (LocallyRingedSpace.forgetToSheafedSpace.map _))
infer_instance
#align algebraic_geometry.Scheme.affine_cover AlgebraicGeometry.Scheme.affineCover
instance : Inhabited X.OpenCover :=
⟨X.affineCover⟩
/-- Given an open cover `{ Uᵢ }` of `X`, and for each `Uᵢ` an open cover, we may combine these
open covers to form an open cover of `X`. -/
@[simps! J obj map]
def OpenCover.bind (f : ∀ x : 𝒰.J, OpenCover (𝒰.obj x)) : OpenCover X where
J := Σ i : 𝒰.J, (f i).J
obj x := (f x.1).obj x.2
map x := (f x.1).map x.2 ≫ 𝒰.map x.1
f x := ⟨_, (f _).f (𝒰.Covers x).choose⟩
Covers x := by
let y := (𝒰.Covers x).choose
have hy : (𝒰.map (𝒰.f x)).val.base y = x := (𝒰.Covers x).choose_spec
rcases (f (𝒰.f x)).Covers y with ⟨z, hz⟩
change x ∈ Set.range ((f (𝒰.f x)).map ((f (𝒰.f x)).f y) ≫ 𝒰.map (𝒰.f x)).1.base
use z
erw [comp_apply]
erw [hz, hy] -- now `erw` after #13170
-- Porting note: weirdly, even though no input is needed, `inferInstance` does not work
-- `PresheafedSpace.IsOpenImmersion.comp` is marked as `instance`
IsOpen x := PresheafedSpace.IsOpenImmersion.comp _ _
#align algebraic_geometry.Scheme.open_cover.bind AlgebraicGeometry.Scheme.OpenCover.bind
/-- An isomorphism `X ⟶ Y` is an open cover of `Y`. -/
@[simps J obj map]
def openCoverOfIsIso {X Y : Scheme.{u}} (f : X ⟶ Y) [IsIso f] : OpenCover Y where
J := PUnit.{v + 1}
obj _ := X
map _ := f
f _ := PUnit.unit
Covers x := by
rw [Set.range_iff_surjective.mpr]
all_goals try trivial
rw [← TopCat.epi_iff_surjective]
infer_instance
#align algebraic_geometry.Scheme.open_cover_of_is_iso AlgebraicGeometry.Scheme.openCoverOfIsIso
/-- We construct an open cover from another, by providing the needed fields and showing that the
provided fields are isomorphic with the original open cover. -/
@[simps J obj map]
def OpenCover.copy {X : Scheme.{u}} (𝒰 : OpenCover X) (J : Type*) (obj : J → Scheme)
(map : ∀ i, obj i ⟶ X) (e₁ : J ≃ 𝒰.J) (e₂ : ∀ i, obj i ≅ 𝒰.obj (e₁ i))
(e₂ : ∀ i, map i = (e₂ i).hom ≫ 𝒰.map (e₁ i)) : OpenCover X :=
{ J, obj, map
f := fun x => e₁.symm (𝒰.f x)
Covers := fun x => by
rw [e₂, Scheme.comp_val_base, TopCat.coe_comp, Set.range_comp, Set.range_iff_surjective.mpr,
Set.image_univ, e₁.rightInverse_symm]
· exact 𝒰.Covers x
· erw [← TopCat.epi_iff_surjective]; infer_instance -- now `erw` after #13170
-- Porting note: weirdly, even though no input is needed, `inferInstance` does not work
-- `PresheafedSpace.IsOpenImmersion.comp` is marked as `instance`
IsOpen := fun i => by rw [e₂]; exact PresheafedSpace.IsOpenImmersion.comp _ _ }
#align algebraic_geometry.Scheme.open_cover.copy AlgebraicGeometry.Scheme.OpenCover.copy
-- Porting note: need more hint on universe level
/-- The pushforward of an open cover along an isomorphism. -/
@[simps! J obj map]
def OpenCover.pushforwardIso {X Y : Scheme.{u}} (𝒰 : OpenCover.{v} X) (f : X ⟶ Y) [IsIso f] :
OpenCover.{v} Y :=
((openCoverOfIsIso.{v, u} f).bind fun _ => 𝒰).copy 𝒰.J _ _
((Equiv.punitProd _).symm.trans (Equiv.sigmaEquivProd PUnit 𝒰.J).symm) (fun _ => Iso.refl _)
fun _ => (Category.id_comp _).symm
#align algebraic_geometry.Scheme.open_cover.pushforward_iso AlgebraicGeometry.Scheme.OpenCover.pushforwardIso
/-- Adding an open immersion into an open cover gives another open cover. -/
@[simps]
def OpenCover.add {X Y : Scheme.{u}} (𝒰 : X.OpenCover) (f : Y ⟶ X) [IsOpenImmersion f] :
X.OpenCover where
J := Option 𝒰.J
obj i := Option.rec Y 𝒰.obj i
map i := Option.rec f 𝒰.map i
f x := some (𝒰.f x)
Covers := 𝒰.Covers
IsOpen := by rintro (_ | _) <;> dsimp <;> infer_instance
#align algebraic_geometry.Scheme.open_cover.add AlgebraicGeometry.Scheme.OpenCover.add
-- Related result : `open_cover.pullback_cover`, where we pullback an open cover on `X` along a
-- morphism `W ⟶ X`. This is provided at the end of the file since it needs some more results
-- about open immersion (which in turn needs the open cover API).
-- attribute [local reducible] CommRingCat.of CommRingCat.ofHom
instance val_base_isIso {X Y : Scheme.{u}} (f : X ⟶ Y) [IsIso f] : IsIso f.1.base :=
Scheme.forgetToTop.map_isIso f
#align algebraic_geometry.Scheme.val_base_is_iso AlgebraicGeometry.Scheme.val_base_isIso
instance basic_open_isOpenImmersion {R : CommRingCat.{u}} (f : R) :
AlgebraicGeometry.IsOpenImmersion
(Scheme.Spec.map (CommRingCat.ofHom (algebraMap R (Localization.Away f))).op) := by
apply SheafedSpace.IsOpenImmersion.of_stalk_iso (H := ?_)
· exact (PrimeSpectrum.localization_away_openEmbedding (Localization.Away f) f : _)
· intro x
exact Spec_map_localization_isIso R (Submonoid.powers f) x
#align algebraic_geometry.Scheme.basic_open_IsOpenImmersion AlgebraicGeometry.Scheme.basic_open_isOpenImmersion
/-- The basic open sets form an affine open cover of `Spec R`. -/
def affineBasisCoverOfAffine (R : CommRingCat.{u}) : OpenCover (Spec.obj (Opposite.op R)) where
J := R
obj r := Spec.obj (Opposite.op <| CommRingCat.of <| Localization.Away r)
map r := Spec.map (Quiver.Hom.op (algebraMap R (Localization.Away r) : _))
f _ := 1
Covers r := by
rw [Set.range_iff_surjective.mpr ((TopCat.epi_iff_surjective _).mp _)]
· exact trivial
· -- Porting note: need more hand holding here because Lean knows that
-- `CommRing.ofHom ...` is iso, but without `ofHom` Lean does not know what to do
change Epi (Spec.map (CommRingCat.ofHom (algebraMap _ _)).op).1.base
infer_instance
IsOpen x := AlgebraicGeometry.Scheme.basic_open_isOpenImmersion x
#align algebraic_geometry.Scheme.affine_basis_cover_of_affine AlgebraicGeometry.Scheme.affineBasisCoverOfAffine
/-- We may bind the basic open sets of an open affine cover to form an affine cover that is also
a basis. -/
def affineBasisCover (X : Scheme.{u}) : OpenCover X :=
X.affineCover.bind fun _ => affineBasisCoverOfAffine _
#align algebraic_geometry.Scheme.affine_basis_cover AlgebraicGeometry.Scheme.affineBasisCover
/-- The coordinate ring of a component in the `affine_basis_cover`. -/
def affineBasisCoverRing (X : Scheme.{u}) (i : X.affineBasisCover.J) : CommRingCat :=
CommRingCat.of <| @Localization.Away (X.local_affine i.1).choose_spec.choose _ i.2
#align algebraic_geometry.Scheme.affine_basis_cover_ring AlgebraicGeometry.Scheme.affineBasisCoverRing
theorem affineBasisCover_obj (X : Scheme.{u}) (i : X.affineBasisCover.J) :
X.affineBasisCover.obj i = Spec.obj (op <| X.affineBasisCoverRing i) :=
rfl
#align algebraic_geometry.Scheme.affine_basis_cover_obj AlgebraicGeometry.Scheme.affineBasisCover_obj
theorem affineBasisCover_map_range (X : Scheme.{u}) (x : X)
(r : (X.local_affine x).choose_spec.choose) :
Set.range (X.affineBasisCover.map ⟨x, r⟩).1.base =
(X.affineCover.map x).1.base '' (PrimeSpectrum.basicOpen r).1 := by
erw [coe_comp, Set.range_comp]
-- Porting note: `congr` fails to see the goal is comparing image of the same function
refine congr_arg (_ '' ·) ?_
exact (PrimeSpectrum.localization_away_comap_range (Localization.Away r) r : _)
#align algebraic_geometry.Scheme.affine_basis_cover_map_range AlgebraicGeometry.Scheme.affineBasisCover_map_range
theorem affineBasisCover_is_basis (X : Scheme.{u}) :
TopologicalSpace.IsTopologicalBasis
{x : Set X |
∃ a : X.affineBasisCover.J, x = Set.range (X.affineBasisCover.map a).1.base} := by
apply TopologicalSpace.isTopologicalBasis_of_isOpen_of_nhds
· rintro _ ⟨a, rfl⟩
exact IsOpenImmersion.isOpen_range (X.affineBasisCover.map a)
· rintro a U haU hU
rcases X.affineCover.Covers a with ⟨x, e⟩
let U' := (X.affineCover.map (X.affineCover.f a)).1.base ⁻¹' U
have hxU' : x ∈ U' := by rw [← e] at haU; exact haU
rcases PrimeSpectrum.isBasis_basic_opens.exists_subset_of_mem_open hxU'
((X.affineCover.map (X.affineCover.f a)).1.base.continuous_toFun.isOpen_preimage _
hU) with
⟨_, ⟨_, ⟨s, rfl⟩, rfl⟩, hxV, hVU⟩
refine ⟨_, ⟨⟨_, s⟩, rfl⟩, ?_, ?_⟩ <;> erw [affineBasisCover_map_range]
· exact ⟨x, hxV, e⟩
· rw [Set.image_subset_iff]; exact hVU
#align algebraic_geometry.Scheme.affine_basis_cover_is_basis AlgebraicGeometry.Scheme.affineBasisCover_is_basis
/-- Every open cover of a quasi-compact scheme can be refined into a finite subcover.
-/
@[simps! obj map]
def OpenCover.finiteSubcover {X : Scheme.{u}} (𝒰 : OpenCover X) [H : CompactSpace X] :
OpenCover X := by
have :=
@CompactSpace.elim_nhds_subcover _ _ H (fun x : X => Set.range (𝒰.map (𝒰.f x)).1.base)
fun x => (IsOpenImmersion.isOpen_range (𝒰.map (𝒰.f x))).mem_nhds (𝒰.Covers x)
let t := this.choose
have h : ∀ x : X, ∃ y : t, x ∈ Set.range (𝒰.map (𝒰.f y)).1.base := by
intro x
have h' : x ∈ (⊤ : Set X) := trivial
rw [← Classical.choose_spec this, Set.mem_iUnion] at h'
rcases h' with ⟨y, _, ⟨hy, rfl⟩, hy'⟩
exact ⟨⟨y, hy⟩, hy'⟩
exact
{ J := t
obj := fun x => 𝒰.obj (𝒰.f x.1)
map := fun x => 𝒰.map (𝒰.f x.1)
f := fun x => (h x).choose
Covers := fun x => (h x).choose_spec }
#align algebraic_geometry.Scheme.open_cover.finite_subcover AlgebraicGeometry.Scheme.OpenCover.finiteSubcover
instance [H : CompactSpace X] : Fintype 𝒰.finiteSubcover.J := by
delta OpenCover.finiteSubcover; infer_instance
end Scheme
end OpenCover
namespace PresheafedSpace.IsOpenImmersion
section ToScheme
variable {X : PresheafedSpace CommRingCat.{u}} (Y : Scheme.{u})
variable (f : X ⟶ Y.toPresheafedSpace) [H : PresheafedSpace.IsOpenImmersion f]
/-- If `X ⟶ Y` is an open immersion, and `Y` is a scheme, then so is `X`. -/
def toScheme : Scheme := by
apply LocallyRingedSpace.IsOpenImmersion.scheme (toLocallyRingedSpace _ f)
intro x
obtain ⟨_, ⟨i, rfl⟩, hx, hi⟩ :=
Y.affineBasisCover_is_basis.exists_subset_of_mem_open (Set.mem_range_self x)
H.base_open.isOpen_range
use Y.affineBasisCoverRing i
use LocallyRingedSpace.IsOpenImmersion.lift (toLocallyRingedSpaceHom _ f) _ hi
constructor
· rw [LocallyRingedSpace.IsOpenImmersion.lift_range]; exact hx
· delta LocallyRingedSpace.IsOpenImmersion.lift; infer_instance
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toScheme
@[simp]
theorem toScheme_toLocallyRingedSpace :
(toScheme Y f).toLocallyRingedSpace = toLocallyRingedSpace Y.1 f :=
rfl
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_to_LocallyRingedSpace AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toScheme_toLocallyRingedSpace
/-- If `X ⟶ Y` is an open immersion of PresheafedSpaces, and `Y` is a Scheme, we can
upgrade it into a morphism of Schemes.
-/
def toSchemeHom : toScheme Y f ⟶ Y :=
toLocallyRingedSpaceHom _ f
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom
@[simp]
theorem toSchemeHom_val : (toSchemeHom Y f).val = f :=
rfl
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom_val AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom_val
instance toSchemeHom_isOpenImmersion : AlgebraicGeometry.IsOpenImmersion (toSchemeHom Y f) :=
H
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom_IsOpenImmersion AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom_isOpenImmersionₓ
theorem scheme_eq_of_locallyRingedSpace_eq {X Y : Scheme.{u}}
(H : X.toLocallyRingedSpace = Y.toLocallyRingedSpace) : X = Y := by
cases X; cases Y; congr
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.Scheme_eq_of_LocallyRingedSpace_eq AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.scheme_eq_of_locallyRingedSpace_eq
theorem scheme_toScheme {X Y : Scheme.{u}} (f : X ⟶ Y) [AlgebraicGeometry.IsOpenImmersion f] :
toScheme Y f.1 = X := by
apply scheme_eq_of_locallyRingedSpace_eq
exact locallyRingedSpace_toLocallyRingedSpace f
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.Scheme_to_Scheme AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.scheme_toScheme
end ToScheme
end PresheafedSpace.IsOpenImmersion
/-- The restriction of a Scheme along an open embedding. -/
@[simps! (config := .lemmasOnly) carrier, simps! presheaf_map presheaf_obj]
def Scheme.restrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X} (h : OpenEmbedding f) :
Scheme :=
{ PresheafedSpace.IsOpenImmersion.toScheme X (X.toPresheafedSpace.ofRestrict h) with
toPresheafedSpace := X.toPresheafedSpace.restrict h }
#align algebraic_geometry.Scheme.restrict AlgebraicGeometry.Scheme.restrict
lemma Scheme.restrict_toPresheafedSpace
{U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X} (h : OpenEmbedding f) :
(X.restrict h).toPresheafedSpace = X.toPresheafedSpace.restrict h := rfl
/-- The canonical map from the restriction to the subspace. -/
@[simps!]
def Scheme.ofRestrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X}
(h : OpenEmbedding f) : X.restrict h ⟶ X :=
X.toLocallyRingedSpace.ofRestrict h
#align algebraic_geometry.Scheme.ofRestrict AlgebraicGeometry.Scheme.ofRestrict
instance IsOpenImmersion.ofRestrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X}
(h : OpenEmbedding f) : IsOpenImmersion (X.ofRestrict h) :=
show PresheafedSpace.IsOpenImmersion (X.toPresheafedSpace.ofRestrict h) by infer_instance
#align algebraic_geometry.IsOpenImmersion.ofRestrict AlgebraicGeometry.IsOpenImmersion.ofRestrict
namespace IsOpenImmersion
variable {X Y Z : Scheme.{u}} (f : X ⟶ Z) (g : Y ⟶ Z)
variable [H : IsOpenImmersion f]
instance (priority := 100) of_isIso [IsIso g] : IsOpenImmersion g :=
@LocallyRingedSpace.IsOpenImmersion.of_isIso _ _ _
(show IsIso ((inducedFunctor _).map g) by infer_instance)
#align algebraic_geometry.IsOpenImmersion.of_is_iso AlgebraicGeometry.IsOpenImmersion.of_isIso
theorem to_iso {X Y : Scheme.{u}} (f : X ⟶ Y) [h : IsOpenImmersion f] [Epi f.1.base] : IsIso f :=
@isIso_of_reflects_iso _ _ _ _ _ _ f
(Scheme.forgetToLocallyRingedSpace ⋙
LocallyRingedSpace.forgetToSheafedSpace ⋙ SheafedSpace.forgetToPresheafedSpace)
(@PresheafedSpace.IsOpenImmersion.to_iso _ _ _ _ f.1 h _) _
#align algebraic_geometry.IsOpenImmersion.to_iso AlgebraicGeometry.IsOpenImmersion.to_iso
theorem of_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) (hf : OpenEmbedding f.1.base)
[∀ x, IsIso (PresheafedSpace.stalkMap f.1 x)] : IsOpenImmersion f :=
SheafedSpace.IsOpenImmersion.of_stalk_iso f.1 hf
#align algebraic_geometry.IsOpenImmersion.of_stalk_iso AlgebraicGeometry.IsOpenImmersion.of_stalk_iso
theorem iff_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsOpenImmersion f ↔ OpenEmbedding f.1.base ∧ ∀ x, IsIso (PresheafedSpace.stalkMap f.1 x) :=
⟨fun H => ⟨H.1, inferInstance⟩, fun ⟨h₁, h₂⟩ => @IsOpenImmersion.of_stalk_iso _ _ f h₁ h₂⟩
#align algebraic_geometry.IsOpenImmersion.iff_stalk_iso AlgebraicGeometry.IsOpenImmersion.iff_stalk_iso
theorem _root_.AlgebraicGeometry.isIso_iff_isOpenImmersion {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsIso f ↔ IsOpenImmersion f ∧ Epi f.1.base :=
⟨fun _ => ⟨inferInstance, inferInstance⟩, fun ⟨h₁, h₂⟩ => @IsOpenImmersion.to_iso _ _ f h₁ h₂⟩
#align algebraic_geometry.is_iso_iff_IsOpenImmersion AlgebraicGeometry.isIso_iff_isOpenImmersion
theorem _root_.AlgebraicGeometry.isIso_iff_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsIso f ↔ IsIso f.1.base ∧ ∀ x, IsIso (PresheafedSpace.stalkMap f.1 x) := by
rw [isIso_iff_isOpenImmersion, IsOpenImmersion.iff_stalk_iso, and_comm, ← and_assoc]
refine and_congr ⟨?_, ?_⟩ Iff.rfl
· rintro ⟨h₁, h₂⟩
convert_to
IsIso
(TopCat.isoOfHomeo
(Homeomorph.homeomorphOfContinuousOpen
(Equiv.ofBijective _ ⟨h₂.inj, (TopCat.epi_iff_surjective _).mp h₁⟩) h₂.continuous
h₂.isOpenMap)).hom
infer_instance
· intro H; exact ⟨inferInstance, (TopCat.homeoOfIso (asIso f.1.base)).openEmbedding⟩
#align algebraic_geometry.is_iso_iff_stalk_iso AlgebraicGeometry.isIso_iff_stalk_iso
/-- An open immersion induces an isomorphism from the domain onto the image -/
def isoRestrict : X ≅ (Z.restrict H.base_open : _) :=
⟨(LocallyRingedSpace.IsOpenImmersion.isoRestrict H).hom,
(LocallyRingedSpace.IsOpenImmersion.isoRestrict H).inv,
(LocallyRingedSpace.IsOpenImmersion.isoRestrict H).hom_inv_id,
(LocallyRingedSpace.IsOpenImmersion.isoRestrict H).inv_hom_id⟩
#align algebraic_geometry.IsOpenImmersion.iso_restrict AlgebraicGeometry.IsOpenImmersion.isoRestrict
local notation "forget" => Scheme.forgetToLocallyRingedSpace
instance mono : Mono f :=
(inducedFunctor _).mono_of_mono_map (show @Mono LocallyRingedSpace _ _ _ f by infer_instance)
#align algebraic_geometry.IsOpenImmersion.mono AlgebraicGeometry.IsOpenImmersion.mono
instance forget_map_isOpenImmersion : LocallyRingedSpace.IsOpenImmersion ((forget).map f) :=
⟨H.base_open, H.c_iso⟩
#align algebraic_geometry.IsOpenImmersion.forget_map_IsOpenImmersion AlgebraicGeometry.IsOpenImmersion.forget_map_isOpenImmersion
instance hasLimit_cospan_forget_of_left :
HasLimit (cospan f g ⋙ Scheme.forgetToLocallyRingedSpace) := by
apply @hasLimitOfIso _ _ _ _ _ _ ?_ (diagramIsoCospan.{u} _).symm
change HasLimit (cospan ((forget).map f) ((forget).map g))
infer_instance
#align algebraic_geometry.IsOpenImmersion.has_limit_cospan_forget_of_left AlgebraicGeometry.IsOpenImmersion.hasLimit_cospan_forget_of_left
open CategoryTheory.Limits.WalkingCospan
instance hasLimit_cospan_forget_of_left' :
HasLimit (cospan ((cospan f g ⋙ forget).map Hom.inl) ((cospan f g ⋙ forget).map Hom.inr)) :=
show HasLimit (cospan ((forget).map f) ((forget).map g)) from inferInstance
#align algebraic_geometry.IsOpenImmersion.has_limit_cospan_forget_of_left' AlgebraicGeometry.IsOpenImmersion.hasLimit_cospan_forget_of_left'
instance hasLimit_cospan_forget_of_right : HasLimit (cospan g f ⋙ forget) := by
apply @hasLimitOfIso _ _ _ _ _ _ ?_ (diagramIsoCospan.{u} _).symm
change HasLimit (cospan ((forget).map g) ((forget).map f))
infer_instance
#align algebraic_geometry.IsOpenImmersion.has_limit_cospan_forget_of_right AlgebraicGeometry.IsOpenImmersion.hasLimit_cospan_forget_of_right
instance hasLimit_cospan_forget_of_right' :
HasLimit (cospan ((cospan g f ⋙ forget).map Hom.inl) ((cospan g f ⋙ forget).map Hom.inr)) :=
show HasLimit (cospan ((forget).map g) ((forget).map f)) from inferInstance
#align algebraic_geometry.IsOpenImmersion.has_limit_cospan_forget_of_right' AlgebraicGeometry.IsOpenImmersion.hasLimit_cospan_forget_of_right'
instance forgetCreatesPullbackOfLeft : CreatesLimit (cospan f g) forget :=
createsLimitOfFullyFaithfulOfIso
(PresheafedSpace.IsOpenImmersion.toScheme Y (@pullback.snd LocallyRingedSpace _ _ _ _ f g _).1)
(eqToIso (by simp) ≪≫ HasLimit.isoOfNatIso (diagramIsoCospan _).symm)
#align algebraic_geometry.IsOpenImmersion.forget_creates_pullback_of_left AlgebraicGeometry.IsOpenImmersion.forgetCreatesPullbackOfLeft
instance forgetCreatesPullbackOfRight : CreatesLimit (cospan g f) forget :=
createsLimitOfFullyFaithfulOfIso
(PresheafedSpace.IsOpenImmersion.toScheme Y (@pullback.fst LocallyRingedSpace _ _ _ _ g f _).1)
(eqToIso (by simp) ≪≫ HasLimit.isoOfNatIso (diagramIsoCospan _).symm)
#align algebraic_geometry.IsOpenImmersion.forget_creates_pullback_of_right AlgebraicGeometry.IsOpenImmersion.forgetCreatesPullbackOfRight
instance forgetPreservesOfLeft : PreservesLimit (cospan f g) forget :=
CategoryTheory.preservesLimitOfCreatesLimitAndHasLimit _ _
#align algebraic_geometry.IsOpenImmersion.forget_preserves_of_left AlgebraicGeometry.IsOpenImmersion.forgetPreservesOfLeft
instance forgetPreservesOfRight : PreservesLimit (cospan g f) forget :=
preservesPullbackSymmetry _ _ _
#align algebraic_geometry.IsOpenImmersion.forget_preserves_of_right AlgebraicGeometry.IsOpenImmersion.forgetPreservesOfRight
instance hasPullback_of_left : HasPullback f g :=
hasLimit_of_created (cospan f g) forget
#align algebraic_geometry.IsOpenImmersion.has_pullback_of_left AlgebraicGeometry.IsOpenImmersion.hasPullback_of_left
instance hasPullback_of_right : HasPullback g f :=
hasLimit_of_created (cospan g f) forget
#align algebraic_geometry.IsOpenImmersion.has_pullback_of_right AlgebraicGeometry.IsOpenImmersion.hasPullback_of_right
instance pullback_snd_of_left : IsOpenImmersion (pullback.snd : pullback f g ⟶ _) := by
have := PreservesPullback.iso_hom_snd forget f g
dsimp only [Scheme.forgetToLocallyRingedSpace, inducedFunctor_map] at this
rw [← this]
change LocallyRingedSpace.IsOpenImmersion _
infer_instance
#align algebraic_geometry.IsOpenImmersion.pullback_snd_of_left AlgebraicGeometry.IsOpenImmersion.pullback_snd_of_left
instance pullback_fst_of_right : IsOpenImmersion (pullback.fst : pullback g f ⟶ _) := by
rw [← pullbackSymmetry_hom_comp_snd]
-- Porting note: was just `infer_instance`, it is a bit weird that no explicit class instance is
-- provided but still class inference fail to find this
exact LocallyRingedSpace.IsOpenImmersion.comp (H := inferInstance) _
#align algebraic_geometry.IsOpenImmersion.pullback_fst_of_right AlgebraicGeometry.IsOpenImmersion.pullback_fst_of_right
instance pullback_to_base [IsOpenImmersion g] :
IsOpenImmersion (limit.π (cospan f g) WalkingCospan.one) := by
rw [← limit.w (cospan f g) WalkingCospan.Hom.inl]
change IsOpenImmersion (_ ≫ f)
-- Porting note: was just `infer_instance`, it is a bit weird that no explicit class instance is
-- provided but still class inference fail to find this
exact LocallyRingedSpace.IsOpenImmersion.comp (H := inferInstance) _
#align algebraic_geometry.IsOpenImmersion.pullback_to_base AlgebraicGeometry.IsOpenImmersion.pullback_to_base
instance forgetToTopPreservesOfLeft : PreservesLimit (cospan f g) Scheme.forgetToTop := by
delta Scheme.forgetToTop
apply @Limits.compPreservesLimit (K := cospan f g) (F := forget)
(G := LocallyRingedSpace.forgetToTop) ?_ ?_
· infer_instance
apply @preservesLimitOfIsoDiagram (F := _) _ _ _ _ _ _ (diagramIsoCospan.{u} _).symm ?_
dsimp [LocallyRingedSpace.forgetToTop]
infer_instance
#align algebraic_geometry.IsOpenImmersion.forget_to_Top_preserves_of_left AlgebraicGeometry.IsOpenImmersion.forgetToTopPreservesOfLeft
instance forgetToTopPreservesOfRight : PreservesLimit (cospan g f) Scheme.forgetToTop :=
preservesPullbackSymmetry _ _ _
#align algebraic_geometry.IsOpenImmersion.forget_to_Top_preserves_of_right AlgebraicGeometry.IsOpenImmersion.forgetToTopPreservesOfRight
theorem range_pullback_snd_of_left :
Set.range (pullback.snd : pullback f g ⟶ Y).1.base =
((Opens.map g.1.base).obj ⟨Set.range f.1.base, H.base_open.isOpen_range⟩).1 := by
rw [← show _ = (pullback.snd : pullback f g ⟶ _).1.base from
PreservesPullback.iso_hom_snd Scheme.forgetToTop f g]
-- Porting note (#10691): was `rw`
erw [coe_comp]
rw [Set.range_comp, Set.range_iff_surjective.mpr, ←
@Set.preimage_univ _ _ (pullback.fst : pullback f.1.base g.1.base ⟶ _)]
-- Porting note (#10691): was `rw`
· erw [TopCat.pullback_snd_image_fst_preimage]
rw [Set.image_univ]
rfl
erw [← TopCat.epi_iff_surjective] -- now `erw` after #13170
infer_instance
#align algebraic_geometry.IsOpenImmersion.range_pullback_snd_of_left AlgebraicGeometry.IsOpenImmersion.range_pullback_snd_of_left
theorem range_pullback_fst_of_right :
Set.range (pullback.fst : pullback g f ⟶ Y).1.base =
((Opens.map g.1.base).obj ⟨Set.range f.1.base, H.base_open.isOpen_range⟩).1 := by
rw [← show _ = (pullback.fst : pullback g f ⟶ _).1.base from
PreservesPullback.iso_hom_fst Scheme.forgetToTop g f]
-- Porting note (#10691): was `rw`
erw [coe_comp]
rw [Set.range_comp, Set.range_iff_surjective.mpr, ←
@Set.preimage_univ _ _ (pullback.snd : pullback g.1.base f.1.base ⟶ _)]
-- Porting note (#10691): was `rw`
· erw [TopCat.pullback_fst_image_snd_preimage]
rw [Set.image_univ]
rfl
erw [← TopCat.epi_iff_surjective] -- now `erw` after #13170
infer_instance
#align algebraic_geometry.IsOpenImmersion.range_pullback_fst_of_right AlgebraicGeometry.IsOpenImmersion.range_pullback_fst_of_right
theorem range_pullback_to_base_of_left :
Set.range (pullback.fst ≫ f : pullback f g ⟶ Z).1.base =
Set.range f.1.base ∩ Set.range g.1.base := by
rw [pullback.condition, Scheme.comp_val_base, TopCat.coe_comp, Set.range_comp,
range_pullback_snd_of_left, Opens.carrier_eq_coe,
Opens.map_obj, Opens.coe_mk, Set.image_preimage_eq_inter_range]
#align algebraic_geometry.IsOpenImmersion.range_pullback_to_base_of_left AlgebraicGeometry.IsOpenImmersion.range_pullback_to_base_of_left
| Mathlib/AlgebraicGeometry/OpenImmersion.lean | 599 | 604 | theorem range_pullback_to_base_of_right :
Set.range (pullback.fst ≫ g : pullback g f ⟶ Z).1.base =
Set.range g.1.base ∩ Set.range f.1.base := by |
rw [Scheme.comp_val_base, TopCat.coe_comp, Set.range_comp, range_pullback_fst_of_right,
Opens.map_obj, Opens.carrier_eq_coe, Opens.coe_mk, Set.image_preimage_eq_inter_range,
Set.inter_comm]
|
/-
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
-/
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.LinearAlgebra.Span
#align_import linear_algebra.quotient from "leanprover-community/mathlib"@"48085f140e684306f9e7da907cd5932056d1aded"
/-!
# Quotients by submodules
* If `p` is a submodule of `M`, `M ⧸ p` is the quotient of `M` with respect to `p`:
that is, elements of `M` are identified if their difference is in `p`. This is itself a module.
-/
-- For most of this file we work over a noncommutative ring
section Ring
namespace Submodule
variable {R M : Type*} {r : R} {x y : M} [Ring R] [AddCommGroup M] [Module R M]
variable (p p' : Submodule R M)
open LinearMap QuotientAddGroup
/-- The equivalence relation associated to a submodule `p`, defined by `x ≈ y` iff `-x + y ∈ p`.
Note this is equivalent to `y - x ∈ p`, but defined this way to be defeq to the `AddSubgroup`
version, where commutativity can't be assumed. -/
def quotientRel : Setoid M :=
QuotientAddGroup.leftRel p.toAddSubgroup
#align submodule.quotient_rel Submodule.quotientRel
theorem quotientRel_r_def {x y : M} : @Setoid.r _ p.quotientRel x y ↔ x - y ∈ p :=
Iff.trans
(by
rw [leftRel_apply, sub_eq_add_neg, neg_add, neg_neg]
rfl)
neg_mem_iff
#align submodule.quotient_rel_r_def Submodule.quotientRel_r_def
/-- The quotient of a module `M` by a submodule `p ⊆ M`. -/
instance hasQuotient : HasQuotient M (Submodule R M) :=
⟨fun p => Quotient (quotientRel p)⟩
#align submodule.has_quotient Submodule.hasQuotient
namespace Quotient
/-- Map associating to an element of `M` the corresponding element of `M/p`,
when `p` is a submodule of `M`. -/
def mk {p : Submodule R M} : M → M ⧸ p :=
Quotient.mk''
#align submodule.quotient.mk Submodule.Quotient.mk
/- porting note: here and throughout elaboration is sped up *tremendously* (in some cases even
avoiding timeouts) by providing type ascriptions to `mk` (or `mk x`) and its variants. Lean 3
didn't need this help. -/
@[simp]
theorem mk'_eq_mk' {p : Submodule R M} (x : M) :
@Quotient.mk' _ (quotientRel p) x = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.mk_eq_mk Submodule.Quotient.mk'_eq_mk'
@[simp]
theorem mk''_eq_mk {p : Submodule R M} (x : M) : (Quotient.mk'' x : M ⧸ p) = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.mk'_eq_mk Submodule.Quotient.mk''_eq_mk
@[simp]
theorem quot_mk_eq_mk {p : Submodule R M} (x : M) : (Quot.mk _ x : M ⧸ p) = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.quot_mk_eq_mk Submodule.Quotient.quot_mk_eq_mk
protected theorem eq' {x y : M} : (mk x : M ⧸ p) = (mk : M → M ⧸ p) y ↔ -x + y ∈ p :=
QuotientAddGroup.eq
#align submodule.quotient.eq' Submodule.Quotient.eq'
protected theorem eq {x y : M} : (mk x : M ⧸ p) = (mk y : M ⧸ p) ↔ x - y ∈ p :=
(Submodule.Quotient.eq' p).trans (leftRel_apply.symm.trans p.quotientRel_r_def)
#align submodule.quotient.eq Submodule.Quotient.eq
instance : Zero (M ⧸ p) where
-- Use Quotient.mk'' instead of mk here because mk is not reducible.
-- This would lead to non-defeq diamonds.
-- See also the same comment at the One instance for Con.
zero := Quotient.mk'' 0
instance : Inhabited (M ⧸ p) :=
⟨0⟩
@[simp]
theorem mk_zero : mk 0 = (0 : M ⧸ p) :=
rfl
#align submodule.quotient.mk_zero Submodule.Quotient.mk_zero
@[simp]
theorem mk_eq_zero : (mk x : M ⧸ p) = 0 ↔ x ∈ p := by simpa using (Quotient.eq' p : mk x = 0 ↔ _)
#align submodule.quotient.mk_eq_zero Submodule.Quotient.mk_eq_zero
instance addCommGroup : AddCommGroup (M ⧸ p) :=
QuotientAddGroup.Quotient.addCommGroup p.toAddSubgroup
#align submodule.quotient.add_comm_group Submodule.Quotient.addCommGroup
@[simp]
theorem mk_add : (mk (x + y) : M ⧸ p) = (mk x : M ⧸ p) + (mk y : M ⧸ p) :=
rfl
#align submodule.quotient.mk_add Submodule.Quotient.mk_add
@[simp]
theorem mk_neg : (mk (-x) : M ⧸ p) = -(mk x : M ⧸ p) :=
rfl
#align submodule.quotient.mk_neg Submodule.Quotient.mk_neg
@[simp]
theorem mk_sub : (mk (x - y) : M ⧸ p) = (mk x : M ⧸ p) - (mk y : M ⧸ p) :=
rfl
#align submodule.quotient.mk_sub Submodule.Quotient.mk_sub
section SMul
variable {S : Type*} [SMul S R] [SMul S M] [IsScalarTower S R M] (P : Submodule R M)
instance instSMul' : SMul S (M ⧸ P) :=
⟨fun a =>
Quotient.map' (a • ·) fun x y h =>
leftRel_apply.mpr <| by simpa using Submodule.smul_mem P (a • (1 : R)) (leftRel_apply.mp h)⟩
#align submodule.quotient.has_smul' Submodule.Quotient.instSMul'
-- Porting note: should this be marked as a `@[default_instance]`?
/-- Shortcut to help the elaborator in the common case. -/
instance instSMul : SMul R (M ⧸ P) :=
Quotient.instSMul' P
#align submodule.quotient.has_smul Submodule.Quotient.instSMul
@[simp]
theorem mk_smul (r : S) (x : M) : (mk (r • x) : M ⧸ p) = r • mk x :=
rfl
#align submodule.quotient.mk_smul Submodule.Quotient.mk_smul
instance smulCommClass (T : Type*) [SMul T R] [SMul T M] [IsScalarTower T R M]
[SMulCommClass S T M] : SMulCommClass S T (M ⧸ P) where
smul_comm _x _y := Quotient.ind' fun _z => congr_arg mk (smul_comm _ _ _)
#align submodule.quotient.smul_comm_class Submodule.Quotient.smulCommClass
instance isScalarTower (T : Type*) [SMul T R] [SMul T M] [IsScalarTower T R M] [SMul S T]
[IsScalarTower S T M] : IsScalarTower S T (M ⧸ P) where
smul_assoc _x _y := Quotient.ind' fun _z => congr_arg mk (smul_assoc _ _ _)
#align submodule.quotient.is_scalar_tower Submodule.Quotient.isScalarTower
instance isCentralScalar [SMul Sᵐᵒᵖ R] [SMul Sᵐᵒᵖ M] [IsScalarTower Sᵐᵒᵖ R M]
[IsCentralScalar S M] : IsCentralScalar S (M ⧸ P) where
op_smul_eq_smul _x := Quotient.ind' fun _z => congr_arg mk <| op_smul_eq_smul _ _
#align submodule.quotient.is_central_scalar Submodule.Quotient.isCentralScalar
end SMul
section Module
variable {S : Type*}
-- Performance of `Function.Surjective.mulAction` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance mulAction' [Monoid S] [SMul S R] [MulAction S M] [IsScalarTower S R M]
(P : Submodule R M) : MulAction S (M ⧸ P) :=
{ Function.Surjective.mulAction mk (surjective_quot_mk _) <| Submodule.Quotient.mk_smul P with
toSMul := instSMul' _ }
#align submodule.quotient.mul_action' Submodule.Quotient.mulAction'
-- Porting note: should this be marked as a `@[default_instance]`?
instance mulAction (P : Submodule R M) : MulAction R (M ⧸ P) :=
Quotient.mulAction' P
#align submodule.quotient.mul_action Submodule.Quotient.mulAction
instance smulZeroClass' [SMul S R] [SMulZeroClass S M] [IsScalarTower S R M] (P : Submodule R M) :
SMulZeroClass S (M ⧸ P) :=
ZeroHom.smulZeroClass ⟨mk, mk_zero _⟩ <| Submodule.Quotient.mk_smul P
#align submodule.quotient.smul_zero_class' Submodule.Quotient.smulZeroClass'
-- Porting note: should this be marked as a `@[default_instance]`?
instance smulZeroClass (P : Submodule R M) : SMulZeroClass R (M ⧸ P) :=
Quotient.smulZeroClass' P
#align submodule.quotient.smul_zero_class Submodule.Quotient.smulZeroClass
-- Performance of `Function.Surjective.distribSMul` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance distribSMul' [SMul S R] [DistribSMul S M] [IsScalarTower S R M] (P : Submodule R M) :
DistribSMul S (M ⧸ P) :=
{ Function.Surjective.distribSMul {toFun := mk, map_zero' := rfl, map_add' := fun _ _ => rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toSMulZeroClass := smulZeroClass' _ }
#align submodule.quotient.distrib_smul' Submodule.Quotient.distribSMul'
-- Porting note: should this be marked as a `@[default_instance]`?
instance distribSMul (P : Submodule R M) : DistribSMul R (M ⧸ P) :=
Quotient.distribSMul' P
#align submodule.quotient.distrib_smul Submodule.Quotient.distribSMul
-- Performance of `Function.Surjective.distribMulAction` is worse since it has to unify data
-- TODO: leanprover-community/mathlib4#7432
instance distribMulAction' [Monoid S] [SMul S R] [DistribMulAction S M] [IsScalarTower S R M]
(P : Submodule R M) : DistribMulAction S (M ⧸ P) :=
{ Function.Surjective.distribMulAction {toFun := mk, map_zero' := rfl, map_add' := fun _ _ => rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toMulAction := mulAction' _ }
#align submodule.quotient.distrib_mul_action' Submodule.Quotient.distribMulAction'
-- Porting note: should this be marked as a `@[default_instance]`?
instance distribMulAction (P : Submodule R M) : DistribMulAction R (M ⧸ P) :=
Quotient.distribMulAction' P
#align submodule.quotient.distrib_mul_action Submodule.Quotient.distribMulAction
-- Performance of `Function.Surjective.module` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance module' [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] (P : Submodule R M) :
Module S (M ⧸ P) :=
{ Function.Surjective.module _ {toFun := mk, map_zero' := by rfl, map_add' := fun _ _ => by rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toDistribMulAction := distribMulAction' _ }
#align submodule.quotient.module' Submodule.Quotient.module'
-- Porting note: should this be marked as a `@[default_instance]`?
instance module (P : Submodule R M) : Module R (M ⧸ P) :=
Quotient.module' P
#align submodule.quotient.module Submodule.Quotient.module
variable (S)
/-- The quotient of `P` as an `S`-submodule is the same as the quotient of `P` as an `R`-submodule,
where `P : Submodule R M`.
-/
def restrictScalarsEquiv [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) : (M ⧸ P.restrictScalars S) ≃ₗ[S] M ⧸ P :=
{ Quotient.congrRight fun _ _ => Iff.rfl with
map_add' := fun x y => Quotient.inductionOn₂' x y fun _x' _y' => rfl
map_smul' := fun _c x => Quotient.inductionOn' x fun _x' => rfl }
#align submodule.quotient.restrict_scalars_equiv Submodule.Quotient.restrictScalarsEquiv
@[simp]
theorem restrictScalarsEquiv_mk [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) (x : M) :
restrictScalarsEquiv S P (mk x : M ⧸ P) = (mk x : M ⧸ P) :=
rfl
#align submodule.quotient.restrict_scalars_equiv_mk Submodule.Quotient.restrictScalarsEquiv_mk
@[simp]
theorem restrictScalarsEquiv_symm_mk [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) (x : M) :
(restrictScalarsEquiv S P).symm ((mk : M → M ⧸ P) x) = (mk : M → M ⧸ P) x :=
rfl
#align submodule.quotient.restrict_scalars_equiv_symm_mk Submodule.Quotient.restrictScalarsEquiv_symm_mk
end Module
theorem mk_surjective : Function.Surjective (@mk _ _ _ _ _ p) := by
rintro ⟨x⟩
exact ⟨x, rfl⟩
#align submodule.quotient.mk_surjective Submodule.Quotient.mk_surjective
theorem nontrivial_of_lt_top (h : p < ⊤) : Nontrivial (M ⧸ p) := by
obtain ⟨x, _, not_mem_s⟩ := SetLike.exists_of_lt h
refine ⟨⟨mk x, 0, ?_⟩⟩
simpa using not_mem_s
#align submodule.quotient.nontrivial_of_lt_top Submodule.Quotient.nontrivial_of_lt_top
end Quotient
instance QuotientBot.infinite [Infinite M] : Infinite (M ⧸ (⊥ : Submodule R M)) :=
Infinite.of_injective Submodule.Quotient.mk fun _x _y h =>
sub_eq_zero.mp <| (Submodule.Quotient.eq ⊥).mp h
#align submodule.quotient_bot.infinite Submodule.QuotientBot.infinite
instance QuotientTop.unique : Unique (M ⧸ (⊤ : Submodule R M)) where
default := 0
uniq x := Quotient.inductionOn' x fun _x => (Submodule.Quotient.eq ⊤).mpr Submodule.mem_top
#align submodule.quotient_top.unique Submodule.QuotientTop.unique
instance QuotientTop.fintype : Fintype (M ⧸ (⊤ : Submodule R M)) :=
Fintype.ofSubsingleton 0
#align submodule.quotient_top.fintype Submodule.QuotientTop.fintype
variable {p}
theorem subsingleton_quotient_iff_eq_top : Subsingleton (M ⧸ p) ↔ p = ⊤ := by
constructor
· rintro h
refine eq_top_iff.mpr fun x _ => ?_
have : x - 0 ∈ p := (Submodule.Quotient.eq p).mp (Subsingleton.elim _ _)
rwa [sub_zero] at this
· rintro rfl
infer_instance
#align submodule.subsingleton_quotient_iff_eq_top Submodule.subsingleton_quotient_iff_eq_top
theorem unique_quotient_iff_eq_top : Nonempty (Unique (M ⧸ p)) ↔ p = ⊤ :=
⟨fun ⟨h⟩ => subsingleton_quotient_iff_eq_top.mp (@Unique.instSubsingleton _ h),
by rintro rfl; exact ⟨QuotientTop.unique⟩⟩
#align submodule.unique_quotient_iff_eq_top Submodule.unique_quotient_iff_eq_top
variable (p)
noncomputable instance Quotient.fintype [Fintype M] (S : Submodule R M) : Fintype (M ⧸ S) :=
@_root_.Quotient.fintype _ _ _ fun _ _ => Classical.dec _
#align submodule.quotient.fintype Submodule.Quotient.fintype
theorem card_eq_card_quotient_mul_card [Fintype M] (S : Submodule R M) [DecidablePred (· ∈ S)] :
Fintype.card M = Fintype.card S * Fintype.card (M ⧸ S) := by
rw [mul_comm, ← Fintype.card_prod]
exact Fintype.card_congr AddSubgroup.addGroupEquivQuotientProdAddSubgroup
#align submodule.card_eq_card_quotient_mul_card Submodule.card_eq_card_quotient_mul_card
section
variable {M₂ : Type*} [AddCommGroup M₂] [Module R M₂]
theorem quot_hom_ext (f g : (M ⧸ p) →ₗ[R] M₂) (h : ∀ x : M, f (Quotient.mk x) = g (Quotient.mk x)) :
f = g :=
LinearMap.ext fun x => Quotient.inductionOn' x h
#align submodule.quot_hom_ext Submodule.quot_hom_ext
/-- The map from a module `M` to the quotient of `M` by a submodule `p` as a linear map. -/
def mkQ : M →ₗ[R] M ⧸ p where
toFun := Quotient.mk
map_add' := by simp
map_smul' := by simp
#align submodule.mkq Submodule.mkQ
@[simp]
theorem mkQ_apply (x : M) : p.mkQ x = (Quotient.mk x : M ⧸ p) :=
rfl
#align submodule.mkq_apply Submodule.mkQ_apply
theorem mkQ_surjective (A : Submodule R M) : Function.Surjective A.mkQ := by
rintro ⟨x⟩; exact ⟨x, rfl⟩
#align submodule.mkq_surjective Submodule.mkQ_surjective
end
variable {R₂ M₂ : Type*} [Ring R₂] [AddCommGroup M₂] [Module R₂ M₂] {τ₁₂ : R →+* R₂}
/-- Two `LinearMap`s from a quotient module are equal if their compositions with
`submodule.mkQ` are equal.
See note [partially-applied ext lemmas]. -/
@[ext 1100] -- Porting note: increase priority so this applies before `LinearMap.ext`
theorem linearMap_qext ⦃f g : M ⧸ p →ₛₗ[τ₁₂] M₂⦄ (h : f.comp p.mkQ = g.comp p.mkQ) : f = g :=
LinearMap.ext fun x => Quotient.inductionOn' x <| (LinearMap.congr_fun h : _)
#align submodule.linear_map_qext Submodule.linearMap_qext
/-- The map from the quotient of `M` by a submodule `p` to `M₂` induced by a linear map `f : M → M₂`
vanishing on `p`, as a linear map. -/
def liftQ (f : M →ₛₗ[τ₁₂] M₂) (h : p ≤ ker f) : M ⧸ p →ₛₗ[τ₁₂] M₂ :=
{ QuotientAddGroup.lift p.toAddSubgroup f.toAddMonoidHom h with
map_smul' := by rintro a ⟨x⟩; exact f.map_smulₛₗ a x }
#align submodule.liftq Submodule.liftQ
@[simp]
theorem liftQ_apply (f : M →ₛₗ[τ₁₂] M₂) {h} (x : M) : p.liftQ f h (Quotient.mk x) = f x :=
rfl
#align submodule.liftq_apply Submodule.liftQ_apply
@[simp]
theorem liftQ_mkQ (f : M →ₛₗ[τ₁₂] M₂) (h) : (p.liftQ f h).comp p.mkQ = f := by ext; rfl
#align submodule.liftq_mkq Submodule.liftQ_mkQ
/-- Special case of `submodule.liftQ` when `p` is the span of `x`. In this case, the condition on
`f` simply becomes vanishing at `x`. -/
def liftQSpanSingleton (x : M) (f : M →ₛₗ[τ₁₂] M₂) (h : f x = 0) : (M ⧸ R ∙ x) →ₛₗ[τ₁₂] M₂ :=
(R ∙ x).liftQ f <| by rw [span_singleton_le_iff_mem, LinearMap.mem_ker, h]
#align submodule.liftq_span_singleton Submodule.liftQSpanSingleton
@[simp]
theorem liftQSpanSingleton_apply (x : M) (f : M →ₛₗ[τ₁₂] M₂) (h : f x = 0) (y : M) :
liftQSpanSingleton x f h (Quotient.mk y) = f y :=
rfl
#align submodule.liftq_span_singleton_apply Submodule.liftQSpanSingleton_apply
@[simp]
theorem range_mkQ : range p.mkQ = ⊤ :=
eq_top_iff'.2 <| by rintro ⟨x⟩; exact ⟨x, rfl⟩
#align submodule.range_mkq Submodule.range_mkQ
@[simp]
theorem ker_mkQ : ker p.mkQ = p := by ext; simp
#align submodule.ker_mkq Submodule.ker_mkQ
theorem le_comap_mkQ (p' : Submodule R (M ⧸ p)) : p ≤ comap p.mkQ p' := by
simpa using (comap_mono bot_le : ker p.mkQ ≤ comap p.mkQ p')
#align submodule.le_comap_mkq Submodule.le_comap_mkQ
@[simp]
| Mathlib/LinearAlgebra/Quotient.lean | 393 | 394 | theorem mkQ_map_self : map p.mkQ p = ⊥ := by |
rw [eq_bot_iff, map_le_iff_le_comap, comap_bot, ker_mkQ]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.FDeriv.Equiv
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
#align_import analysis.calculus.cont_diff_def from "leanprover-community/mathlib"@"3a69562db5a458db8322b190ec8d9a8bbd8a5b14"
/-!
# Higher differentiability
A function is `C^1` on a domain if it is differentiable there, and its derivative is continuous.
By induction, it is `C^n` if it is `C^{n-1}` and its (n-1)-th derivative is `C^1` there or,
equivalently, if it is `C^1` and its derivative is `C^{n-1}`.
Finally, it is `C^∞` if it is `C^n` for all n.
We formalize these notions by defining iteratively the `n+1`-th derivative of a function as the
derivative of the `n`-th derivative. It is called `iteratedFDeriv 𝕜 n f x` where `𝕜` is the
field, `n` is the number of iterations, `f` is the function and `x` is the point, and it is given
as an `n`-multilinear map. We also define a version `iteratedFDerivWithin` relative to a domain,
as well as predicates `ContDiffWithinAt`, `ContDiffAt`, `ContDiffOn` and
`ContDiff` saying that the function is `C^n` within a set at a point, at a point, on a set
and on the whole space respectively.
To avoid the issue of choice when choosing a derivative in sets where the derivative is not
necessarily unique, `ContDiffOn` is not defined directly in terms of the
regularity of the specific choice `iteratedFDerivWithin 𝕜 n f s` inside `s`, but in terms of the
existence of a nice sequence of derivatives, expressed with a predicate
`HasFTaylorSeriesUpToOn`.
We prove basic properties of these notions.
## Main definitions and results
Let `f : E → F` be a map between normed vector spaces over a nontrivially normed field `𝕜`.
* `HasFTaylorSeriesUpTo n f p`: expresses that the formal multilinear series `p` is a sequence
of iterated derivatives of `f`, up to the `n`-th term (where `n` is a natural number or `∞`).
* `HasFTaylorSeriesUpToOn n f p s`: same thing, but inside a set `s`. The notion of derivative
is now taken inside `s`. In particular, derivatives don't have to be unique.
* `ContDiff 𝕜 n f`: expresses that `f` is `C^n`, i.e., it admits a Taylor series up to
rank `n`.
* `ContDiffOn 𝕜 n f s`: expresses that `f` is `C^n` in `s`.
* `ContDiffAt 𝕜 n f x`: expresses that `f` is `C^n` around `x`.
* `ContDiffWithinAt 𝕜 n f s x`: expresses that `f` is `C^n` around `x` within the set `s`.
* `iteratedFDerivWithin 𝕜 n f s x` is an `n`-th derivative of `f` over the field `𝕜` on the
set `s` at the point `x`. It is a continuous multilinear map from `E^n` to `F`, defined as a
derivative within `s` of `iteratedFDerivWithin 𝕜 (n-1) f s` if one exists, and `0` otherwise.
* `iteratedFDeriv 𝕜 n f x` is the `n`-th derivative of `f` over the field `𝕜` at the point `x`.
It is a continuous multilinear map from `E^n` to `F`, defined as a derivative of
`iteratedFDeriv 𝕜 (n-1) f` if one exists, and `0` otherwise.
In sets of unique differentiability, `ContDiffOn 𝕜 n f s` can be expressed in terms of the
properties of `iteratedFDerivWithin 𝕜 m f s` for `m ≤ n`. In the whole space,
`ContDiff 𝕜 n f` can be expressed in terms of the properties of `iteratedFDeriv 𝕜 m f`
for `m ≤ n`.
## Implementation notes
The definitions in this file are designed to work on any field `𝕜`. They are sometimes slightly more
complicated than the naive definitions one would guess from the intuition over the real or complex
numbers, but they are designed to circumvent the lack of gluing properties and partitions of unity
in general. In the usual situations, they coincide with the usual definitions.
### Definition of `C^n` functions in domains
One could define `C^n` functions in a domain `s` by fixing an arbitrary choice of derivatives (this
is what we do with `iteratedFDerivWithin`) and requiring that all these derivatives up to `n` are
continuous. If the derivative is not unique, this could lead to strange behavior like two `C^n`
functions `f` and `g` on `s` whose sum is not `C^n`. A better definition is thus to say that a
function is `C^n` inside `s` if it admits a sequence of derivatives up to `n` inside `s`.
This definition still has the problem that a function which is locally `C^n` would not need to
be `C^n`, as different choices of sequences of derivatives around different points might possibly
not be glued together to give a globally defined sequence of derivatives. (Note that this issue
can not happen over reals, thanks to partition of unity, but the behavior over a general field is
not so clear, and we want a definition for general fields). Also, there are locality
problems for the order parameter: one could image a function which, for each `n`, has a nice
sequence of derivatives up to order `n`, but they do not coincide for varying `n` and can therefore
not be glued to give rise to an infinite sequence of derivatives. This would give a function
which is `C^n` for all `n`, but not `C^∞`. We solve this issue by putting locality conditions
in space and order in our definition of `ContDiffWithinAt` and `ContDiffOn`.
The resulting definition is slightly more complicated to work with (in fact not so much), but it
gives rise to completely satisfactory theorems.
For instance, with this definition, a real function which is `C^m` (but not better) on `(-1/m, 1/m)`
for each natural `m` is by definition `C^∞` at `0`.
There is another issue with the definition of `ContDiffWithinAt 𝕜 n f s x`. We can
require the existence and good behavior of derivatives up to order `n` on a neighborhood of `x`
within `s`. However, this does not imply continuity or differentiability within `s` of the function
at `x` when `x` does not belong to `s`. Therefore, we require such existence and good behavior on
a neighborhood of `x` within `s ∪ {x}` (which appears as `insert x s` in this file).
### Side of the composition, and universe issues
With a naïve direct definition, the `n`-th derivative of a function belongs to the space
`E →L[𝕜] (E →L[𝕜] (E ... F)...)))` where there are n iterations of `E →L[𝕜]`. This space
may also be seen as the space of continuous multilinear functions on `n` copies of `E` with
values in `F`, by uncurrying. This is the point of view that is usually adopted in textbooks,
and that we also use. This means that the definition and the first proofs are slightly involved,
as one has to keep track of the uncurrying operation. The uncurrying can be done from the
left or from the right, amounting to defining the `n+1`-th derivative either as the derivative of
the `n`-th derivative, or as the `n`-th derivative of the derivative.
For proofs, it would be more convenient to use the latter approach (from the right),
as it means to prove things at the `n+1`-th step we only need to understand well enough the
derivative in `E →L[𝕜] F` (contrary to the approach from the left, where one would need to know
enough on the `n`-th derivative to deduce things on the `n+1`-th derivative).
However, the definition from the right leads to a universe polymorphism problem: if we define
`iteratedFDeriv 𝕜 (n + 1) f x = iteratedFDeriv 𝕜 n (fderiv 𝕜 f) x` by induction, we need to
generalize over all spaces (as `f` and `fderiv 𝕜 f` don't take values in the same space). It is
only possible to generalize over all spaces in some fixed universe in an inductive definition.
For `f : E → F`, then `fderiv 𝕜 f` is a map `E → (E →L[𝕜] F)`. Therefore, the definition will only
work if `F` and `E →L[𝕜] F` are in the same universe.
This issue does not appear with the definition from the left, where one does not need to generalize
over all spaces. Therefore, we use the definition from the left. This means some proofs later on
become a little bit more complicated: to prove that a function is `C^n`, the most efficient approach
is to exhibit a formula for its `n`-th derivative and prove it is continuous (contrary to the
inductive approach where one would prove smoothness statements without giving a formula for the
derivative). In the end, this approach is still satisfactory as it is good to have formulas for the
iterated derivatives in various constructions.
One point where we depart from this explicit approach is in the proof of smoothness of a
composition: there is a formula for the `n`-th derivative of a composition (Faà di Bruno's formula),
but it is very complicated and barely usable, while the inductive proof is very simple. Thus, we
give the inductive proof. As explained above, it works by generalizing over the target space, hence
it only works well if all spaces belong to the same universe. To get the general version, we lift
things to a common universe using a trick.
### Variables management
The textbook definitions and proofs use various identifications and abuse of notations, for instance
when saying that the natural space in which the derivative lives, i.e.,
`E →L[𝕜] (E →L[𝕜] ( ... →L[𝕜] F))`, is the same as a space of multilinear maps. When doing things
formally, we need to provide explicit maps for these identifications, and chase some diagrams to see
everything is compatible with the identifications. In particular, one needs to check that taking the
derivative and then doing the identification, or first doing the identification and then taking the
derivative, gives the same result. The key point for this is that taking the derivative commutes
with continuous linear equivalences. Therefore, we need to implement all our identifications with
continuous linear equivs.
## 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
open NNReal Topology Filter
local notation "∞" => (⊤ : ℕ∞)
/-
Porting note: These lines are not required in Mathlib4.
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup NormedSpace.toModule' AddCommGroup.toAddCommMonoid
-/
open Set Fin Filter Function
universe u uE uF uG uX
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type uE} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {F : Type uF} [NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG}
[NormedAddCommGroup G] [NormedSpace 𝕜 G] {X : Type uX} [NormedAddCommGroup X] [NormedSpace 𝕜 X]
{s s₁ t u : Set E} {f f₁ : E → F} {g : F → G} {x x₀ : E} {c : F} {m n : ℕ∞}
{p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Functions with a Taylor series on a domain -/
/-- `HasFTaylorSeriesUpToOn n f p s` registers the fact that `p 0 = f` and `p (m+1)` is a
derivative of `p m` for `m < n`, and is continuous for `m ≤ n`. This is a predicate analogous to
`HasFDerivWithinAt` but for higher order derivatives.
Notice that `p` does not sum up to `f` on the diagonal (`FormalMultilinearSeries.sum`), even if
`f` is analytic and `n = ∞`: an additional `1/m!` factor on the `m`th term is necessary for that. -/
structure HasFTaylorSeriesUpToOn (n : ℕ∞) (f : E → F) (p : E → FormalMultilinearSeries 𝕜 E F)
(s : Set E) : Prop where
zero_eq : ∀ x ∈ s, (p x 0).uncurry0 = f x
protected fderivWithin : ∀ m : ℕ, (m : ℕ∞) < n → ∀ x ∈ s,
HasFDerivWithinAt (p · m) (p x m.succ).curryLeft s x
cont : ∀ m : ℕ, (m : ℕ∞) ≤ n → ContinuousOn (p · m) s
#align has_ftaylor_series_up_to_on HasFTaylorSeriesUpToOn
theorem HasFTaylorSeriesUpToOn.zero_eq' (h : HasFTaylorSeriesUpToOn n f p s) {x : E} (hx : x ∈ s) :
p x 0 = (continuousMultilinearCurryFin0 𝕜 E F).symm (f x) := by
rw [← h.zero_eq x hx]
exact (p x 0).uncurry0_curry0.symm
#align has_ftaylor_series_up_to_on.zero_eq' HasFTaylorSeriesUpToOn.zero_eq'
/-- If two functions coincide on a set `s`, then a Taylor series for the first one is as well a
Taylor series for the second one. -/
theorem HasFTaylorSeriesUpToOn.congr (h : HasFTaylorSeriesUpToOn n f p s)
(h₁ : ∀ x ∈ s, f₁ x = f x) : HasFTaylorSeriesUpToOn n f₁ p s := by
refine ⟨fun x hx => ?_, h.fderivWithin, h.cont⟩
rw [h₁ x hx]
exact h.zero_eq x hx
#align has_ftaylor_series_up_to_on.congr HasFTaylorSeriesUpToOn.congr
theorem HasFTaylorSeriesUpToOn.mono (h : HasFTaylorSeriesUpToOn n f p s) {t : Set E} (hst : t ⊆ s) :
HasFTaylorSeriesUpToOn n f p t :=
⟨fun x hx => h.zero_eq x (hst hx), fun m hm x hx => (h.fderivWithin m hm x (hst hx)).mono hst,
fun m hm => (h.cont m hm).mono hst⟩
#align has_ftaylor_series_up_to_on.mono HasFTaylorSeriesUpToOn.mono
theorem HasFTaylorSeriesUpToOn.of_le (h : HasFTaylorSeriesUpToOn n f p s) (hmn : m ≤ n) :
HasFTaylorSeriesUpToOn m f p s :=
⟨h.zero_eq, fun k hk x hx => h.fderivWithin k (lt_of_lt_of_le hk hmn) x hx, fun k hk =>
h.cont k (le_trans hk hmn)⟩
#align has_ftaylor_series_up_to_on.of_le HasFTaylorSeriesUpToOn.of_le
theorem HasFTaylorSeriesUpToOn.continuousOn (h : HasFTaylorSeriesUpToOn n f p s) :
ContinuousOn f s := by
have := (h.cont 0 bot_le).congr fun x hx => (h.zero_eq' hx).symm
rwa [← (continuousMultilinearCurryFin0 𝕜 E F).symm.comp_continuousOn_iff]
#align has_ftaylor_series_up_to_on.continuous_on HasFTaylorSeriesUpToOn.continuousOn
theorem hasFTaylorSeriesUpToOn_zero_iff :
HasFTaylorSeriesUpToOn 0 f p s ↔ ContinuousOn f s ∧ ∀ x ∈ s, (p x 0).uncurry0 = f x := by
refine ⟨fun H => ⟨H.continuousOn, H.zero_eq⟩, fun H =>
⟨H.2, fun m hm => False.elim (not_le.2 hm bot_le), fun m hm ↦ ?_⟩⟩
obtain rfl : m = 0 := mod_cast hm.antisymm (zero_le _)
have : EqOn (p · 0) ((continuousMultilinearCurryFin0 𝕜 E F).symm ∘ f) s := fun x hx ↦
(continuousMultilinearCurryFin0 𝕜 E F).eq_symm_apply.2 (H.2 x hx)
rw [continuousOn_congr this, LinearIsometryEquiv.comp_continuousOn_iff]
exact H.1
#align has_ftaylor_series_up_to_on_zero_iff hasFTaylorSeriesUpToOn_zero_iff
theorem hasFTaylorSeriesUpToOn_top_iff :
HasFTaylorSeriesUpToOn ∞ f p s ↔ ∀ n : ℕ, HasFTaylorSeriesUpToOn n f p s := by
constructor
· intro H n; exact H.of_le le_top
· intro H
constructor
· exact (H 0).zero_eq
· intro m _
apply (H m.succ).fderivWithin m (WithTop.coe_lt_coe.2 (lt_add_one m))
· intro m _
apply (H m).cont m le_rfl
#align has_ftaylor_series_up_to_on_top_iff hasFTaylorSeriesUpToOn_top_iff
/-- In the case that `n = ∞` we don't need the continuity assumption in
`HasFTaylorSeriesUpToOn`. -/
theorem hasFTaylorSeriesUpToOn_top_iff' :
HasFTaylorSeriesUpToOn ∞ f p s ↔
(∀ x ∈ s, (p x 0).uncurry0 = f x) ∧
∀ m : ℕ, ∀ x ∈ s, HasFDerivWithinAt (fun y => p y m) (p x m.succ).curryLeft s x :=
-- Everything except for the continuity is trivial:
⟨fun h => ⟨h.1, fun m => h.2 m (WithTop.coe_lt_top m)⟩, fun h =>
⟨h.1, fun m _ => h.2 m, fun m _ x hx =>
-- The continuity follows from the existence of a derivative:
(h.2 m x hx).continuousWithinAt⟩⟩
#align has_ftaylor_series_up_to_on_top_iff' hasFTaylorSeriesUpToOn_top_iff'
/-- If a function has a Taylor series at order at least `1`, then the term of order `1` of this
series is a derivative of `f`. -/
theorem HasFTaylorSeriesUpToOn.hasFDerivWithinAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : x ∈ s) : HasFDerivWithinAt f (continuousMultilinearCurryFin1 𝕜 E F (p x 1)) s x := by
have A : ∀ y ∈ s, f y = (continuousMultilinearCurryFin0 𝕜 E F) (p y 0) := fun y hy ↦
(h.zero_eq y hy).symm
suffices H : HasFDerivWithinAt (continuousMultilinearCurryFin0 𝕜 E F ∘ (p · 0))
(continuousMultilinearCurryFin1 𝕜 E F (p x 1)) s x from H.congr A (A x hx)
rw [LinearIsometryEquiv.comp_hasFDerivWithinAt_iff']
have : ((0 : ℕ) : ℕ∞) < n := zero_lt_one.trans_le hn
convert h.fderivWithin _ this x hx
ext y v
change (p x 1) (snoc 0 y) = (p x 1) (cons y v)
congr with i
rw [Unique.eq_default (α := Fin 1) i]
rfl
#align has_ftaylor_series_up_to_on.has_fderiv_within_at HasFTaylorSeriesUpToOn.hasFDerivWithinAt
theorem HasFTaylorSeriesUpToOn.differentiableOn (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n) :
DifferentiableOn 𝕜 f s := fun _x hx => (h.hasFDerivWithinAt hn hx).differentiableWithinAt
#align has_ftaylor_series_up_to_on.differentiable_on HasFTaylorSeriesUpToOn.differentiableOn
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then the term
of order `1` of this series is a derivative of `f` at `x`. -/
theorem HasFTaylorSeriesUpToOn.hasFDerivAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : s ∈ 𝓝 x) : HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p x 1)) x :=
(h.hasFDerivWithinAt hn (mem_of_mem_nhds hx)).hasFDerivAt hx
#align has_ftaylor_series_up_to_on.has_fderiv_at HasFTaylorSeriesUpToOn.hasFDerivAt
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then
in a neighborhood of `x`, the term of order `1` of this series is a derivative of `f`. -/
theorem HasFTaylorSeriesUpToOn.eventually_hasFDerivAt (h : HasFTaylorSeriesUpToOn n f p s)
(hn : 1 ≤ n) (hx : s ∈ 𝓝 x) :
∀ᶠ y in 𝓝 x, HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p y 1)) y :=
(eventually_eventually_nhds.2 hx).mono fun _y hy => h.hasFDerivAt hn hy
#align has_ftaylor_series_up_to_on.eventually_has_fderiv_at HasFTaylorSeriesUpToOn.eventually_hasFDerivAt
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then
it is differentiable at `x`. -/
theorem HasFTaylorSeriesUpToOn.differentiableAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : s ∈ 𝓝 x) : DifferentiableAt 𝕜 f x :=
(h.hasFDerivAt hn hx).differentiableAt
#align has_ftaylor_series_up_to_on.differentiable_at HasFTaylorSeriesUpToOn.differentiableAt
/-- `p` is a Taylor series of `f` up to `n+1` if and only if `p` is a Taylor series up to `n`, and
`p (n + 1)` is a derivative of `p n`. -/
theorem hasFTaylorSeriesUpToOn_succ_iff_left {n : ℕ} :
HasFTaylorSeriesUpToOn (n + 1) f p s ↔
HasFTaylorSeriesUpToOn n f p s ∧
(∀ x ∈ s, HasFDerivWithinAt (fun y => p y n) (p x n.succ).curryLeft s x) ∧
ContinuousOn (fun x => p x (n + 1)) s := by
constructor
· exact fun h ↦ ⟨h.of_le (WithTop.coe_le_coe.2 (Nat.le_succ n)),
h.fderivWithin _ (WithTop.coe_lt_coe.2 (lt_add_one n)), h.cont (n + 1) le_rfl⟩
· intro h
constructor
· exact h.1.zero_eq
· intro m hm
by_cases h' : m < n
· exact h.1.fderivWithin m (WithTop.coe_lt_coe.2 h')
· have : m = n := Nat.eq_of_lt_succ_of_not_lt (WithTop.coe_lt_coe.1 hm) h'
rw [this]
exact h.2.1
· intro m hm
by_cases h' : m ≤ n
· apply h.1.cont m (WithTop.coe_le_coe.2 h')
· have : m = n + 1 := le_antisymm (WithTop.coe_le_coe.1 hm) (not_le.1 h')
rw [this]
exact h.2.2
#align has_ftaylor_series_up_to_on_succ_iff_left hasFTaylorSeriesUpToOn_succ_iff_left
#adaptation_note
/--
After https://github.com/leanprover/lean4/pull/4119,
without `set_option maxSynthPendingDepth 2` this proof needs substantial repair.
-/
set_option maxSynthPendingDepth 2 in
-- Porting note: this was split out from `hasFTaylorSeriesUpToOn_succ_iff_right` to avoid a timeout.
theorem HasFTaylorSeriesUpToOn.shift_of_succ
{n : ℕ} (H : HasFTaylorSeriesUpToOn (n + 1 : ℕ) f p s) :
(HasFTaylorSeriesUpToOn n (fun x => continuousMultilinearCurryFin1 𝕜 E F (p x 1))
(fun x => (p x).shift)) s := by
constructor
· intro x _
rfl
· intro m (hm : (m : ℕ∞) < n) x (hx : x ∈ s)
have A : (m.succ : ℕ∞) < n.succ := by
rw [Nat.cast_lt] at hm ⊢
exact Nat.succ_lt_succ hm
change HasFDerivWithinAt ((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm ∘ (p · m.succ))
(p x m.succ.succ).curryRight.curryLeft s x
rw [((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm).comp_hasFDerivWithinAt_iff']
convert H.fderivWithin _ A x hx
ext y v
change p x (m + 2) (snoc (cons y (init v)) (v (last _))) = p x (m + 2) (cons y v)
rw [← cons_snoc_eq_snoc_cons, snoc_init_self]
· intro m (hm : (m : ℕ∞) ≤ n)
suffices A : ContinuousOn (p · (m + 1)) s from
((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm).continuous.comp_continuousOn A
refine H.cont _ ?_
rw [Nat.cast_le] at hm ⊢
exact Nat.succ_le_succ hm
/-- `p` is a Taylor series of `f` up to `n+1` if and only if `p.shift` is a Taylor series up to `n`
for `p 1`, which is a derivative of `f`. -/
theorem hasFTaylorSeriesUpToOn_succ_iff_right {n : ℕ} :
HasFTaylorSeriesUpToOn (n + 1 : ℕ) f p s ↔
(∀ x ∈ s, (p x 0).uncurry0 = f x) ∧
(∀ x ∈ s, HasFDerivWithinAt (fun y => p y 0) (p x 1).curryLeft s x) ∧
HasFTaylorSeriesUpToOn n (fun x => continuousMultilinearCurryFin1 𝕜 E F (p x 1))
(fun x => (p x).shift) s := by
constructor
· intro H
refine ⟨H.zero_eq, H.fderivWithin 0 (Nat.cast_lt.2 (Nat.succ_pos n)), ?_⟩
exact H.shift_of_succ
· rintro ⟨Hzero_eq, Hfderiv_zero, Htaylor⟩
constructor
· exact Hzero_eq
· intro m (hm : (m : ℕ∞) < n.succ) x (hx : x ∈ s)
cases' m with m
· exact Hfderiv_zero x hx
· have A : (m : ℕ∞) < n := by
rw [Nat.cast_lt] at hm ⊢
exact Nat.lt_of_succ_lt_succ hm
have :
HasFDerivWithinAt ((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm ∘ (p · m.succ))
((p x).shift m.succ).curryLeft s x := Htaylor.fderivWithin _ A x hx
rw [LinearIsometryEquiv.comp_hasFDerivWithinAt_iff'] at this
convert this
ext y v
change
(p x (Nat.succ (Nat.succ m))) (cons y v) =
(p x m.succ.succ) (snoc (cons y (init v)) (v (last _)))
rw [← cons_snoc_eq_snoc_cons, snoc_init_self]
· intro m (hm : (m : ℕ∞) ≤ n.succ)
cases' m with m
· have : DifferentiableOn 𝕜 (fun x => p x 0) s := fun x hx =>
(Hfderiv_zero x hx).differentiableWithinAt
exact this.continuousOn
· refine (continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm.comp_continuousOn_iff.mp ?_
refine Htaylor.cont _ ?_
rw [Nat.cast_le] at hm ⊢
exact Nat.lt_succ_iff.mp hm
#align has_ftaylor_series_up_to_on_succ_iff_right hasFTaylorSeriesUpToOn_succ_iff_right
/-! ### Smooth functions within a set around a point -/
variable (𝕜)
/-- A function is continuously differentiable up to order `n` within a set `s` at a point `x` if
it admits continuous derivatives up to order `n` in a neighborhood of `x` in `s ∪ {x}`.
For `n = ∞`, we only require that this holds up to any finite order (where the neighborhood may
depend on the finite order we consider).
For instance, a real function which is `C^m` on `(-1/m, 1/m)` for each natural `m`, but not
better, is `C^∞` at `0` within `univ`.
-/
def ContDiffWithinAt (n : ℕ∞) (f : E → F) (s : Set E) (x : E) : Prop :=
∀ m : ℕ, (m : ℕ∞) ≤ n → ∃ u ∈ 𝓝[insert x s] x,
∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn m f p u
#align cont_diff_within_at ContDiffWithinAt
variable {𝕜}
theorem contDiffWithinAt_nat {n : ℕ} :
ContDiffWithinAt 𝕜 n f s x ↔ ∃ u ∈ 𝓝[insert x s] x,
∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn n f p u :=
⟨fun H => H n le_rfl, fun ⟨u, hu, p, hp⟩ _m hm => ⟨u, hu, p, hp.of_le hm⟩⟩
#align cont_diff_within_at_nat contDiffWithinAt_nat
theorem ContDiffWithinAt.of_le (h : ContDiffWithinAt 𝕜 n f s x) (hmn : m ≤ n) :
ContDiffWithinAt 𝕜 m f s x := fun k hk => h k (le_trans hk hmn)
#align cont_diff_within_at.of_le ContDiffWithinAt.of_le
theorem contDiffWithinAt_iff_forall_nat_le :
ContDiffWithinAt 𝕜 n f s x ↔ ∀ m : ℕ, ↑m ≤ n → ContDiffWithinAt 𝕜 m f s x :=
⟨fun H _m hm => H.of_le hm, fun H m hm => H m hm _ le_rfl⟩
#align cont_diff_within_at_iff_forall_nat_le contDiffWithinAt_iff_forall_nat_le
theorem contDiffWithinAt_top : ContDiffWithinAt 𝕜 ∞ f s x ↔ ∀ n : ℕ, ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAt_iff_forall_nat_le.trans <| by simp only [forall_prop_of_true, le_top]
#align cont_diff_within_at_top contDiffWithinAt_top
theorem ContDiffWithinAt.continuousWithinAt (h : ContDiffWithinAt 𝕜 n f s x) :
ContinuousWithinAt f s x := by
rcases h 0 bot_le with ⟨u, hu, p, H⟩
rw [mem_nhdsWithin_insert] at hu
exact (H.continuousOn.continuousWithinAt hu.1).mono_of_mem hu.2
#align cont_diff_within_at.continuous_within_at ContDiffWithinAt.continuousWithinAt
theorem ContDiffWithinAt.congr_of_eventuallyEq (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x := fun m hm =>
let ⟨u, hu, p, H⟩ := h m hm
⟨{ x ∈ u | f₁ x = f x }, Filter.inter_mem hu (mem_nhdsWithin_insert.2 ⟨hx, h₁⟩), p,
(H.mono (sep_subset _ _)).congr fun _ => And.right⟩
#align cont_diff_within_at.congr_of_eventually_eq ContDiffWithinAt.congr_of_eventuallyEq
theorem ContDiffWithinAt.congr_of_eventuallyEq_insert (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[insert x s] x] f) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq (nhdsWithin_mono x (subset_insert x s) h₁)
(mem_of_mem_nhdsWithin (mem_insert x s) h₁ : _)
#align cont_diff_within_at.congr_of_eventually_eq_insert ContDiffWithinAt.congr_of_eventuallyEq_insert
theorem ContDiffWithinAt.congr_of_eventually_eq' (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq h₁ <| h₁.self_of_nhdsWithin hx
#align cont_diff_within_at.congr_of_eventually_eq' ContDiffWithinAt.congr_of_eventually_eq'
theorem Filter.EventuallyEq.contDiffWithinAt_iff (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) :
ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x :=
⟨fun H => ContDiffWithinAt.congr_of_eventuallyEq H h₁.symm hx.symm, fun H =>
H.congr_of_eventuallyEq h₁ hx⟩
#align filter.eventually_eq.cont_diff_within_at_iff Filter.EventuallyEq.contDiffWithinAt_iff
theorem ContDiffWithinAt.congr (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y)
(hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq (Filter.eventuallyEq_of_mem self_mem_nhdsWithin h₁) hx
#align cont_diff_within_at.congr ContDiffWithinAt.congr
theorem ContDiffWithinAt.congr' (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y)
(hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr h₁ (h₁ _ hx)
#align cont_diff_within_at.congr' ContDiffWithinAt.congr'
theorem ContDiffWithinAt.mono_of_mem (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E}
(hst : s ∈ 𝓝[t] x) : ContDiffWithinAt 𝕜 n f t x := by
intro m hm
rcases h m hm with ⟨u, hu, p, H⟩
exact ⟨u, nhdsWithin_le_of_mem (insert_mem_nhdsWithin_insert hst) hu, p, H⟩
#align cont_diff_within_at.mono_of_mem ContDiffWithinAt.mono_of_mem
theorem ContDiffWithinAt.mono (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E} (hst : t ⊆ s) :
ContDiffWithinAt 𝕜 n f t x :=
h.mono_of_mem <| Filter.mem_of_superset self_mem_nhdsWithin hst
#align cont_diff_within_at.mono ContDiffWithinAt.mono
theorem ContDiffWithinAt.congr_nhds (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E}
(hst : 𝓝[s] x = 𝓝[t] x) : ContDiffWithinAt 𝕜 n f t x :=
h.mono_of_mem <| hst ▸ self_mem_nhdsWithin
#align cont_diff_within_at.congr_nhds ContDiffWithinAt.congr_nhds
theorem contDiffWithinAt_congr_nhds {t : Set E} (hst : 𝓝[s] x = 𝓝[t] x) :
ContDiffWithinAt 𝕜 n f s x ↔ ContDiffWithinAt 𝕜 n f t x :=
⟨fun h => h.congr_nhds hst, fun h => h.congr_nhds hst.symm⟩
#align cont_diff_within_at_congr_nhds contDiffWithinAt_congr_nhds
theorem contDiffWithinAt_inter' (h : t ∈ 𝓝[s] x) :
ContDiffWithinAt 𝕜 n f (s ∩ t) x ↔ ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAt_congr_nhds <| Eq.symm <| nhdsWithin_restrict'' _ h
#align cont_diff_within_at_inter' contDiffWithinAt_inter'
theorem contDiffWithinAt_inter (h : t ∈ 𝓝 x) :
ContDiffWithinAt 𝕜 n f (s ∩ t) x ↔ ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAt_inter' (mem_nhdsWithin_of_mem_nhds h)
#align cont_diff_within_at_inter contDiffWithinAt_inter
theorem contDiffWithinAt_insert_self :
ContDiffWithinAt 𝕜 n f (insert x s) x ↔ ContDiffWithinAt 𝕜 n f s x := by
simp_rw [ContDiffWithinAt, insert_idem]
theorem contDiffWithinAt_insert {y : E} :
ContDiffWithinAt 𝕜 n f (insert y s) x ↔ ContDiffWithinAt 𝕜 n f s x := by
rcases eq_or_ne x y with (rfl | h)
· exact contDiffWithinAt_insert_self
simp_rw [ContDiffWithinAt, insert_comm x y, nhdsWithin_insert_of_ne h]
#align cont_diff_within_at_insert contDiffWithinAt_insert
alias ⟨ContDiffWithinAt.of_insert, ContDiffWithinAt.insert'⟩ := contDiffWithinAt_insert
#align cont_diff_within_at.of_insert ContDiffWithinAt.of_insert
#align cont_diff_within_at.insert' ContDiffWithinAt.insert'
protected theorem ContDiffWithinAt.insert (h : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n f (insert x s) x :=
h.insert'
#align cont_diff_within_at.insert ContDiffWithinAt.insert
/-- If a function is `C^n` within a set at a point, with `n ≥ 1`, then it is differentiable
within this set at this point. -/
theorem ContDiffWithinAt.differentiable_within_at' (h : ContDiffWithinAt 𝕜 n f s x) (hn : 1 ≤ n) :
DifferentiableWithinAt 𝕜 f (insert x s) x := by
rcases h 1 hn with ⟨u, hu, p, H⟩
rcases mem_nhdsWithin.1 hu with ⟨t, t_open, xt, tu⟩
rw [inter_comm] at tu
have := ((H.mono tu).differentiableOn le_rfl) x ⟨mem_insert x s, xt⟩
exact (differentiableWithinAt_inter (IsOpen.mem_nhds t_open xt)).1 this
#align cont_diff_within_at.differentiable_within_at' ContDiffWithinAt.differentiable_within_at'
theorem ContDiffWithinAt.differentiableWithinAt (h : ContDiffWithinAt 𝕜 n f s x) (hn : 1 ≤ n) :
DifferentiableWithinAt 𝕜 f s x :=
(h.differentiable_within_at' hn).mono (subset_insert x s)
#align cont_diff_within_at.differentiable_within_at ContDiffWithinAt.differentiableWithinAt
/-- A function is `C^(n + 1)` on a domain iff locally, it has a derivative which is `C^n`. -/
theorem contDiffWithinAt_succ_iff_hasFDerivWithinAt {n : ℕ} :
ContDiffWithinAt 𝕜 (n + 1 : ℕ) f s x ↔ ∃ u ∈ 𝓝[insert x s] x, ∃ f' : E → E →L[𝕜] F,
(∀ x ∈ u, HasFDerivWithinAt f (f' x) u x) ∧ ContDiffWithinAt 𝕜 n f' u x := by
constructor
· intro h
rcases h n.succ le_rfl with ⟨u, hu, p, Hp⟩
refine
⟨u, hu, fun y => (continuousMultilinearCurryFin1 𝕜 E F) (p y 1), fun y hy =>
Hp.hasFDerivWithinAt (WithTop.coe_le_coe.2 (Nat.le_add_left 1 n)) hy, ?_⟩
intro m hm
refine ⟨u, ?_, fun y : E => (p y).shift, ?_⟩
· -- Porting note: without the explicit argument Lean is not sure of the type.
convert @self_mem_nhdsWithin _ _ x u
have : x ∈ insert x s := by simp
exact insert_eq_of_mem (mem_of_mem_nhdsWithin this hu)
· rw [hasFTaylorSeriesUpToOn_succ_iff_right] at Hp
exact Hp.2.2.of_le hm
· rintro ⟨u, hu, f', f'_eq_deriv, Hf'⟩
rw [contDiffWithinAt_nat]
rcases Hf' n le_rfl with ⟨v, hv, p', Hp'⟩
refine ⟨v ∩ u, ?_, fun x => (p' x).unshift (f x), ?_⟩
· apply Filter.inter_mem _ hu
apply nhdsWithin_le_of_mem hu
exact nhdsWithin_mono _ (subset_insert x u) hv
· rw [hasFTaylorSeriesUpToOn_succ_iff_right]
refine ⟨fun y _ => rfl, fun y hy => ?_, ?_⟩
· change
HasFDerivWithinAt (fun z => (continuousMultilinearCurryFin0 𝕜 E F).symm (f z))
(FormalMultilinearSeries.unshift (p' y) (f y) 1).curryLeft (v ∩ u) y
-- Porting note: needed `erw` here.
-- https://github.com/leanprover-community/mathlib4/issues/5164
erw [LinearIsometryEquiv.comp_hasFDerivWithinAt_iff']
convert (f'_eq_deriv y hy.2).mono inter_subset_right
rw [← Hp'.zero_eq y hy.1]
ext z
change ((p' y 0) (init (@cons 0 (fun _ => E) z 0))) (@cons 0 (fun _ => E) z 0 (last 0)) =
((p' y 0) 0) z
congr
norm_num [eq_iff_true_of_subsingleton]
· convert (Hp'.mono inter_subset_left).congr fun x hx => Hp'.zero_eq x hx.1 using 1
· ext x y
change p' x 0 (init (@snoc 0 (fun _ : Fin 1 => E) 0 y)) y = p' x 0 0 y
rw [init_snoc]
· ext x k v y
change p' x k (init (@snoc k (fun _ : Fin k.succ => E) v y))
(@snoc k (fun _ : Fin k.succ => E) v y (last k)) = p' x k v y
rw [snoc_last, init_snoc]
#align cont_diff_within_at_succ_iff_has_fderiv_within_at contDiffWithinAt_succ_iff_hasFDerivWithinAt
/-- A version of `contDiffWithinAt_succ_iff_hasFDerivWithinAt` where all derivatives
are taken within the same set. -/
theorem contDiffWithinAt_succ_iff_hasFDerivWithinAt' {n : ℕ} :
ContDiffWithinAt 𝕜 (n + 1 : ℕ) f s x ↔
∃ u ∈ 𝓝[insert x s] x, u ⊆ insert x s ∧ ∃ f' : E → E →L[𝕜] F,
(∀ x ∈ u, HasFDerivWithinAt f (f' x) s x) ∧ ContDiffWithinAt 𝕜 n f' s x := by
refine ⟨fun hf => ?_, ?_⟩
· obtain ⟨u, hu, f', huf', hf'⟩ := contDiffWithinAt_succ_iff_hasFDerivWithinAt.mp hf
obtain ⟨w, hw, hxw, hwu⟩ := mem_nhdsWithin.mp hu
rw [inter_comm] at hwu
refine ⟨insert x s ∩ w, inter_mem_nhdsWithin _ (hw.mem_nhds hxw), inter_subset_left, f',
fun y hy => ?_, ?_⟩
· refine ((huf' y <| hwu hy).mono hwu).mono_of_mem ?_
refine mem_of_superset ?_ (inter_subset_inter_left _ (subset_insert _ _))
exact inter_mem_nhdsWithin _ (hw.mem_nhds hy.2)
· exact hf'.mono_of_mem (nhdsWithin_mono _ (subset_insert _ _) hu)
· rw [← contDiffWithinAt_insert, contDiffWithinAt_succ_iff_hasFDerivWithinAt,
insert_eq_of_mem (mem_insert _ _)]
rintro ⟨u, hu, hus, f', huf', hf'⟩
exact ⟨u, hu, f', fun y hy => (huf' y hy).insert'.mono hus, hf'.insert.mono hus⟩
#align cont_diff_within_at_succ_iff_has_fderiv_within_at' contDiffWithinAt_succ_iff_hasFDerivWithinAt'
/-! ### Smooth functions within a set -/
variable (𝕜)
/-- A function is continuously differentiable up to `n` on `s` if, for any point `x` in `s`, it
admits continuous derivatives up to order `n` on a neighborhood of `x` in `s`.
For `n = ∞`, we only require that this holds up to any finite order (where the neighborhood may
depend on the finite order we consider).
-/
def ContDiffOn (n : ℕ∞) (f : E → F) (s : Set E) : Prop :=
∀ x ∈ s, ContDiffWithinAt 𝕜 n f s x
#align cont_diff_on ContDiffOn
variable {𝕜}
theorem HasFTaylorSeriesUpToOn.contDiffOn {f' : E → FormalMultilinearSeries 𝕜 E F}
(hf : HasFTaylorSeriesUpToOn n f f' s) : ContDiffOn 𝕜 n f s := by
intro x hx m hm
use s
simp only [Set.insert_eq_of_mem hx, self_mem_nhdsWithin, true_and_iff]
exact ⟨f', hf.of_le hm⟩
#align has_ftaylor_series_up_to_on.cont_diff_on HasFTaylorSeriesUpToOn.contDiffOn
theorem ContDiffOn.contDiffWithinAt (h : ContDiffOn 𝕜 n f s) (hx : x ∈ s) :
ContDiffWithinAt 𝕜 n f s x :=
h x hx
#align cont_diff_on.cont_diff_within_at ContDiffOn.contDiffWithinAt
theorem ContDiffWithinAt.contDiffOn' {m : ℕ} (hm : (m : ℕ∞) ≤ n)
(h : ContDiffWithinAt 𝕜 n f s x) :
∃ u, IsOpen u ∧ x ∈ u ∧ ContDiffOn 𝕜 m f (insert x s ∩ u) := by
rcases h m hm with ⟨t, ht, p, hp⟩
rcases mem_nhdsWithin.1 ht with ⟨u, huo, hxu, hut⟩
rw [inter_comm] at hut
exact ⟨u, huo, hxu, (hp.mono hut).contDiffOn⟩
#align cont_diff_within_at.cont_diff_on' ContDiffWithinAt.contDiffOn'
theorem ContDiffWithinAt.contDiffOn {m : ℕ} (hm : (m : ℕ∞) ≤ n) (h : ContDiffWithinAt 𝕜 n f s x) :
∃ u ∈ 𝓝[insert x s] x, u ⊆ insert x s ∧ ContDiffOn 𝕜 m f u :=
let ⟨_u, uo, xu, h⟩ := h.contDiffOn' hm
⟨_, inter_mem_nhdsWithin _ (uo.mem_nhds xu), inter_subset_left, h⟩
#align cont_diff_within_at.cont_diff_on ContDiffWithinAt.contDiffOn
protected theorem ContDiffWithinAt.eventually {n : ℕ} (h : ContDiffWithinAt 𝕜 n f s x) :
∀ᶠ y in 𝓝[insert x s] x, ContDiffWithinAt 𝕜 n f s y := by
rcases h.contDiffOn le_rfl with ⟨u, hu, _, hd⟩
have : ∀ᶠ y : E in 𝓝[insert x s] x, u ∈ 𝓝[insert x s] y ∧ y ∈ u :=
(eventually_nhdsWithin_nhdsWithin.2 hu).and hu
refine this.mono fun y hy => (hd y hy.2).mono_of_mem ?_
exact nhdsWithin_mono y (subset_insert _ _) hy.1
#align cont_diff_within_at.eventually ContDiffWithinAt.eventually
theorem ContDiffOn.of_le (h : ContDiffOn 𝕜 n f s) (hmn : m ≤ n) : ContDiffOn 𝕜 m f s := fun x hx =>
(h x hx).of_le hmn
#align cont_diff_on.of_le ContDiffOn.of_le
theorem ContDiffOn.of_succ {n : ℕ} (h : ContDiffOn 𝕜 (n + 1) f s) : ContDiffOn 𝕜 n f s :=
h.of_le <| WithTop.coe_le_coe.mpr le_self_add
#align cont_diff_on.of_succ ContDiffOn.of_succ
theorem ContDiffOn.one_of_succ {n : ℕ} (h : ContDiffOn 𝕜 (n + 1) f s) : ContDiffOn 𝕜 1 f s :=
h.of_le <| WithTop.coe_le_coe.mpr le_add_self
#align cont_diff_on.one_of_succ ContDiffOn.one_of_succ
theorem contDiffOn_iff_forall_nat_le : ContDiffOn 𝕜 n f s ↔ ∀ m : ℕ, ↑m ≤ n → ContDiffOn 𝕜 m f s :=
⟨fun H _ hm => H.of_le hm, fun H x hx m hm => H m hm x hx m le_rfl⟩
#align cont_diff_on_iff_forall_nat_le contDiffOn_iff_forall_nat_le
theorem contDiffOn_top : ContDiffOn 𝕜 ∞ f s ↔ ∀ n : ℕ, ContDiffOn 𝕜 n f s :=
contDiffOn_iff_forall_nat_le.trans <| by simp only [le_top, forall_prop_of_true]
#align cont_diff_on_top contDiffOn_top
theorem contDiffOn_all_iff_nat : (∀ n, ContDiffOn 𝕜 n f s) ↔ ∀ n : ℕ, ContDiffOn 𝕜 n f s := by
refine ⟨fun H n => H n, ?_⟩
rintro H (_ | n)
exacts [contDiffOn_top.2 H, H n]
#align cont_diff_on_all_iff_nat contDiffOn_all_iff_nat
theorem ContDiffOn.continuousOn (h : ContDiffOn 𝕜 n f s) : ContinuousOn f s := fun x hx =>
(h x hx).continuousWithinAt
#align cont_diff_on.continuous_on ContDiffOn.continuousOn
theorem ContDiffOn.congr (h : ContDiffOn 𝕜 n f s) (h₁ : ∀ x ∈ s, f₁ x = f x) :
ContDiffOn 𝕜 n f₁ s := fun x hx => (h x hx).congr h₁ (h₁ x hx)
#align cont_diff_on.congr ContDiffOn.congr
theorem contDiffOn_congr (h₁ : ∀ x ∈ s, f₁ x = f x) : ContDiffOn 𝕜 n f₁ s ↔ ContDiffOn 𝕜 n f s :=
⟨fun H => H.congr fun x hx => (h₁ x hx).symm, fun H => H.congr h₁⟩
#align cont_diff_on_congr contDiffOn_congr
theorem ContDiffOn.mono (h : ContDiffOn 𝕜 n f s) {t : Set E} (hst : t ⊆ s) : ContDiffOn 𝕜 n f t :=
fun x hx => (h x (hst hx)).mono hst
#align cont_diff_on.mono ContDiffOn.mono
theorem ContDiffOn.congr_mono (hf : ContDiffOn 𝕜 n f s) (h₁ : ∀ x ∈ s₁, f₁ x = f x) (hs : s₁ ⊆ s) :
ContDiffOn 𝕜 n f₁ s₁ :=
(hf.mono hs).congr h₁
#align cont_diff_on.congr_mono ContDiffOn.congr_mono
/-- If a function is `C^n` on a set with `n ≥ 1`, then it is differentiable there. -/
theorem ContDiffOn.differentiableOn (h : ContDiffOn 𝕜 n f s) (hn : 1 ≤ n) :
DifferentiableOn 𝕜 f s := fun x hx => (h x hx).differentiableWithinAt hn
#align cont_diff_on.differentiable_on ContDiffOn.differentiableOn
/-- If a function is `C^n` around each point in a set, then it is `C^n` on the set. -/
theorem contDiffOn_of_locally_contDiffOn
(h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ ContDiffOn 𝕜 n f (s ∩ u)) : ContDiffOn 𝕜 n f s := by
intro x xs
rcases h x xs with ⟨u, u_open, xu, hu⟩
apply (contDiffWithinAt_inter _).1 (hu x ⟨xs, xu⟩)
exact IsOpen.mem_nhds u_open xu
#align cont_diff_on_of_locally_cont_diff_on contDiffOn_of_locally_contDiffOn
/-- A function is `C^(n + 1)` on a domain iff locally, it has a derivative which is `C^n`. -/
theorem contDiffOn_succ_iff_hasFDerivWithinAt {n : ℕ} :
ContDiffOn 𝕜 (n + 1 : ℕ) f s ↔
∀ x ∈ s, ∃ u ∈ 𝓝[insert x s] x, ∃ f' : E → E →L[𝕜] F,
(∀ x ∈ u, HasFDerivWithinAt f (f' x) u x) ∧ ContDiffOn 𝕜 n f' u := by
constructor
· intro h x hx
rcases (h x hx) n.succ le_rfl with ⟨u, hu, p, Hp⟩
refine
⟨u, hu, fun y => (continuousMultilinearCurryFin1 𝕜 E F) (p y 1), fun y hy =>
Hp.hasFDerivWithinAt (WithTop.coe_le_coe.2 (Nat.le_add_left 1 n)) hy, ?_⟩
rw [hasFTaylorSeriesUpToOn_succ_iff_right] at Hp
intro z hz m hm
refine ⟨u, ?_, fun x : E => (p x).shift, Hp.2.2.of_le hm⟩
-- Porting note: without the explicit arguments `convert` can not determine the type.
convert @self_mem_nhdsWithin _ _ z u
exact insert_eq_of_mem hz
· intro h x hx
rw [contDiffWithinAt_succ_iff_hasFDerivWithinAt]
rcases h x hx with ⟨u, u_nhbd, f', hu, hf'⟩
have : x ∈ u := mem_of_mem_nhdsWithin (mem_insert _ _) u_nhbd
exact ⟨u, u_nhbd, f', hu, hf' x this⟩
#align cont_diff_on_succ_iff_has_fderiv_within_at contDiffOn_succ_iff_hasFDerivWithinAt
/-! ### Iterated derivative within a set -/
variable (𝕜)
/-- The `n`-th derivative of a function along a set, defined inductively by saying that the `n+1`-th
derivative of `f` is the derivative of the `n`-th derivative of `f` along this set, together with
an uncurrying step to see it as a multilinear map in `n+1` variables..
-/
noncomputable def iteratedFDerivWithin (n : ℕ) (f : E → F) (s : Set E) : E → E[×n]→L[𝕜] F :=
Nat.recOn n (fun x => ContinuousMultilinearMap.curry0 𝕜 E (f x)) fun _ rec x =>
ContinuousLinearMap.uncurryLeft (fderivWithin 𝕜 rec s x)
#align iterated_fderiv_within iteratedFDerivWithin
/-- Formal Taylor series associated to a function within a set. -/
def ftaylorSeriesWithin (f : E → F) (s : Set E) (x : E) : FormalMultilinearSeries 𝕜 E F := fun n =>
iteratedFDerivWithin 𝕜 n f s x
#align ftaylor_series_within ftaylorSeriesWithin
variable {𝕜}
@[simp]
theorem iteratedFDerivWithin_zero_apply (m : Fin 0 → E) :
(iteratedFDerivWithin 𝕜 0 f s x : (Fin 0 → E) → F) m = f x :=
rfl
#align iterated_fderiv_within_zero_apply iteratedFDerivWithin_zero_apply
theorem iteratedFDerivWithin_zero_eq_comp :
iteratedFDerivWithin 𝕜 0 f s = (continuousMultilinearCurryFin0 𝕜 E F).symm ∘ f :=
rfl
#align iterated_fderiv_within_zero_eq_comp iteratedFDerivWithin_zero_eq_comp
@[simp]
theorem norm_iteratedFDerivWithin_zero : ‖iteratedFDerivWithin 𝕜 0 f s x‖ = ‖f x‖ := by
-- Porting note: added `comp_apply`.
rw [iteratedFDerivWithin_zero_eq_comp, comp_apply, LinearIsometryEquiv.norm_map]
#align norm_iterated_fderiv_within_zero norm_iteratedFDerivWithin_zero
theorem iteratedFDerivWithin_succ_apply_left {n : ℕ} (m : Fin (n + 1) → E) :
(iteratedFDerivWithin 𝕜 (n + 1) f s x : (Fin (n + 1) → E) → F) m =
(fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n f s) s x : E → E[×n]→L[𝕜] F) (m 0) (tail m) :=
rfl
#align iterated_fderiv_within_succ_apply_left iteratedFDerivWithin_succ_apply_left
/-- Writing explicitly the `n+1`-th derivative as the composition of a currying linear equiv,
and the derivative of the `n`-th derivative. -/
theorem iteratedFDerivWithin_succ_eq_comp_left {n : ℕ} :
iteratedFDerivWithin 𝕜 (n + 1) f s =
(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (n + 1) => E) F :
(E →L[𝕜] (E [×n]→L[𝕜] F)) → (E [×n.succ]→L[𝕜] F)) ∘
fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n f s) s :=
rfl
#align iterated_fderiv_within_succ_eq_comp_left iteratedFDerivWithin_succ_eq_comp_left
theorem fderivWithin_iteratedFDerivWithin {s : Set E} {n : ℕ} :
fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n f s) s =
(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (n + 1) => E) F).symm ∘
iteratedFDerivWithin 𝕜 (n + 1) f s := by
rw [iteratedFDerivWithin_succ_eq_comp_left]
ext1 x
simp only [Function.comp_apply, LinearIsometryEquiv.symm_apply_apply]
theorem norm_fderivWithin_iteratedFDerivWithin {n : ℕ} :
‖fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n f s) s x‖ =
‖iteratedFDerivWithin 𝕜 (n + 1) f s x‖ := by
-- Porting note: added `comp_apply`.
rw [iteratedFDerivWithin_succ_eq_comp_left, comp_apply, LinearIsometryEquiv.norm_map]
#align norm_fderiv_within_iterated_fderiv_within norm_fderivWithin_iteratedFDerivWithin
theorem iteratedFDerivWithin_succ_apply_right {n : ℕ} (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s)
(m : Fin (n + 1) → E) :
(iteratedFDerivWithin 𝕜 (n + 1) f s x : (Fin (n + 1) → E) → F) m =
iteratedFDerivWithin 𝕜 n (fun y => fderivWithin 𝕜 f s y) s x (init m) (m (last n)) := by
induction' n with n IH generalizing x
· rw [iteratedFDerivWithin_succ_eq_comp_left, iteratedFDerivWithin_zero_eq_comp,
iteratedFDerivWithin_zero_apply, Function.comp_apply,
LinearIsometryEquiv.comp_fderivWithin _ (hs x hx)]
rfl
· let I := continuousMultilinearCurryRightEquiv' 𝕜 n E F
have A : ∀ y ∈ s, iteratedFDerivWithin 𝕜 n.succ f s y =
(I ∘ iteratedFDerivWithin 𝕜 n (fun y => fderivWithin 𝕜 f s y) s) y := fun y hy ↦ by
ext m
rw [@IH y hy m]
rfl
calc
(iteratedFDerivWithin 𝕜 (n + 2) f s x : (Fin (n + 2) → E) → F) m =
(fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n.succ f s) s x : E → E[×n + 1]→L[𝕜] F) (m 0)
(tail m) :=
rfl
_ = (fderivWithin 𝕜 (I ∘ iteratedFDerivWithin 𝕜 n (fderivWithin 𝕜 f s) s) s x :
E → E[×n + 1]→L[𝕜] F) (m 0) (tail m) := by
rw [fderivWithin_congr A (A x hx)]
_ = (I ∘ fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n (fderivWithin 𝕜 f s) s) s x :
E → E[×n + 1]→L[𝕜] F) (m 0) (tail m) := by
#adaptation_note
/--
After https://github.com/leanprover/lean4/pull/4119 we need to either use
`set_option maxSynthPendingDepth 2 in`
or fill in an explicit argument as
```
simp only [LinearIsometryEquiv.comp_fderivWithin _
(f := iteratedFDerivWithin 𝕜 n (fderivWithin 𝕜 f s) s) (hs x hx)]
```
-/
set_option maxSynthPendingDepth 2 in
simp only [LinearIsometryEquiv.comp_fderivWithin _ (hs x hx)]
rfl
_ = (fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 n (fun y => fderivWithin 𝕜 f s y) s) s x :
E → E[×n]→L[𝕜] E →L[𝕜] F) (m 0) (init (tail m)) ((tail m) (last n)) := rfl
_ = iteratedFDerivWithin 𝕜 (Nat.succ n) (fun y => fderivWithin 𝕜 f s y) s x (init m)
(m (last (n + 1))) := by
rw [iteratedFDerivWithin_succ_apply_left, tail_init_eq_init_tail]
rfl
#align iterated_fderiv_within_succ_apply_right iteratedFDerivWithin_succ_apply_right
/-- Writing explicitly the `n+1`-th derivative as the composition of a currying linear equiv,
and the `n`-th derivative of the derivative. -/
theorem iteratedFDerivWithin_succ_eq_comp_right {n : ℕ} (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
iteratedFDerivWithin 𝕜 (n + 1) f s x =
(continuousMultilinearCurryRightEquiv' 𝕜 n E F ∘
iteratedFDerivWithin 𝕜 n (fun y => fderivWithin 𝕜 f s y) s)
x := by
ext m; rw [iteratedFDerivWithin_succ_apply_right hs hx]; rfl
#align iterated_fderiv_within_succ_eq_comp_right iteratedFDerivWithin_succ_eq_comp_right
theorem norm_iteratedFDerivWithin_fderivWithin {n : ℕ} (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
‖iteratedFDerivWithin 𝕜 n (fderivWithin 𝕜 f s) s x‖ =
‖iteratedFDerivWithin 𝕜 (n + 1) f s x‖ := by
-- Porting note: added `comp_apply`.
rw [iteratedFDerivWithin_succ_eq_comp_right hs hx, comp_apply, LinearIsometryEquiv.norm_map]
#align norm_iterated_fderiv_within_fderiv_within norm_iteratedFDerivWithin_fderivWithin
@[simp]
theorem iteratedFDerivWithin_one_apply (h : UniqueDiffWithinAt 𝕜 s x) (m : Fin 1 → E) :
iteratedFDerivWithin 𝕜 1 f s x m = fderivWithin 𝕜 f s x (m 0) := by
simp only [iteratedFDerivWithin_succ_apply_left, iteratedFDerivWithin_zero_eq_comp,
(continuousMultilinearCurryFin0 𝕜 E F).symm.comp_fderivWithin h]
rfl
#align iterated_fderiv_within_one_apply iteratedFDerivWithin_one_apply
/-- On a set of unique differentiability, the second derivative is obtained by taking the
derivative of the derivative. -/
lemma iteratedFDerivWithin_two_apply (f : E → F) {z : E} (hs : UniqueDiffOn 𝕜 s) (hz : z ∈ s)
(m : Fin 2 → E) :
iteratedFDerivWithin 𝕜 2 f s z m = fderivWithin 𝕜 (fderivWithin 𝕜 f s) s z (m 0) (m 1) := by
simp only [iteratedFDerivWithin_succ_apply_right hs hz]
rfl
theorem Filter.EventuallyEq.iteratedFDerivWithin' (h : f₁ =ᶠ[𝓝[s] x] f) (ht : t ⊆ s) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f₁ t =ᶠ[𝓝[s] x] iteratedFDerivWithin 𝕜 n f t := by
induction' n with n ihn
· exact h.mono fun y hy => DFunLike.ext _ _ fun _ => hy
· have : fderivWithin 𝕜 _ t =ᶠ[𝓝[s] x] fderivWithin 𝕜 _ t := ihn.fderivWithin' ht
apply this.mono
intro y hy
simp only [iteratedFDerivWithin_succ_eq_comp_left, hy, (· ∘ ·)]
#align filter.eventually_eq.iterated_fderiv_within' Filter.EventuallyEq.iteratedFDerivWithin'
protected theorem Filter.EventuallyEq.iteratedFDerivWithin (h : f₁ =ᶠ[𝓝[s] x] f) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f₁ s =ᶠ[𝓝[s] x] iteratedFDerivWithin 𝕜 n f s :=
h.iteratedFDerivWithin' Subset.rfl n
#align filter.eventually_eq.iterated_fderiv_within Filter.EventuallyEq.iteratedFDerivWithin
/-- If two functions coincide in a neighborhood of `x` within a set `s` and at `x`, then their
iterated differentials within this set at `x` coincide. -/
theorem Filter.EventuallyEq.iteratedFDerivWithin_eq (h : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x)
(n : ℕ) : iteratedFDerivWithin 𝕜 n f₁ s x = iteratedFDerivWithin 𝕜 n f s x :=
have : f₁ =ᶠ[𝓝[insert x s] x] f := by simpa [EventuallyEq, hx]
(this.iteratedFDerivWithin' (subset_insert _ _) n).self_of_nhdsWithin (mem_insert _ _)
#align filter.eventually_eq.iterated_fderiv_within_eq Filter.EventuallyEq.iteratedFDerivWithin_eq
/-- If two functions coincide on a set `s`, then their iterated differentials within this set
coincide. See also `Filter.EventuallyEq.iteratedFDerivWithin_eq` and
`Filter.EventuallyEq.iteratedFDerivWithin`. -/
theorem iteratedFDerivWithin_congr (hs : EqOn f₁ f s) (hx : x ∈ s) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f₁ s x = iteratedFDerivWithin 𝕜 n f s x :=
(hs.eventuallyEq.filter_mono inf_le_right).iteratedFDerivWithin_eq (hs hx) _
#align iterated_fderiv_within_congr iteratedFDerivWithin_congr
/-- If two functions coincide on a set `s`, then their iterated differentials within this set
coincide. See also `Filter.EventuallyEq.iteratedFDerivWithin_eq` and
`Filter.EventuallyEq.iteratedFDerivWithin`. -/
protected theorem Set.EqOn.iteratedFDerivWithin (hs : EqOn f₁ f s) (n : ℕ) :
EqOn (iteratedFDerivWithin 𝕜 n f₁ s) (iteratedFDerivWithin 𝕜 n f s) s := fun _x hx =>
iteratedFDerivWithin_congr hs hx n
#align set.eq_on.iterated_fderiv_within Set.EqOn.iteratedFDerivWithin
theorem iteratedFDerivWithin_eventually_congr_set' (y : E) (h : s =ᶠ[𝓝[{y}ᶜ] x] t) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f s =ᶠ[𝓝 x] iteratedFDerivWithin 𝕜 n f t := by
induction' n with n ihn generalizing x
· rfl
· refine (eventually_nhds_nhdsWithin.2 h).mono fun y hy => ?_
simp only [iteratedFDerivWithin_succ_eq_comp_left, (· ∘ ·)]
rw [(ihn hy).fderivWithin_eq_nhds, fderivWithin_congr_set' _ hy]
#align iterated_fderiv_within_eventually_congr_set' iteratedFDerivWithin_eventually_congr_set'
theorem iteratedFDerivWithin_eventually_congr_set (h : s =ᶠ[𝓝 x] t) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f s =ᶠ[𝓝 x] iteratedFDerivWithin 𝕜 n f t :=
iteratedFDerivWithin_eventually_congr_set' x (h.filter_mono inf_le_left) n
#align iterated_fderiv_within_eventually_congr_set iteratedFDerivWithin_eventually_congr_set
theorem iteratedFDerivWithin_congr_set (h : s =ᶠ[𝓝 x] t) (n : ℕ) :
iteratedFDerivWithin 𝕜 n f s x = iteratedFDerivWithin 𝕜 n f t x :=
(iteratedFDerivWithin_eventually_congr_set h n).self_of_nhds
#align iterated_fderiv_within_congr_set iteratedFDerivWithin_congr_set
/-- The iterated differential within a set `s` at a point `x` is not modified if one intersects
`s` with a neighborhood of `x` within `s`. -/
theorem iteratedFDerivWithin_inter' {n : ℕ} (hu : u ∈ 𝓝[s] x) :
iteratedFDerivWithin 𝕜 n f (s ∩ u) x = iteratedFDerivWithin 𝕜 n f s x :=
iteratedFDerivWithin_congr_set (nhdsWithin_eq_iff_eventuallyEq.1 <| nhdsWithin_inter_of_mem' hu) _
#align iterated_fderiv_within_inter' iteratedFDerivWithin_inter'
/-- The iterated differential within a set `s` at a point `x` is not modified if one intersects
`s` with a neighborhood of `x`. -/
theorem iteratedFDerivWithin_inter {n : ℕ} (hu : u ∈ 𝓝 x) :
iteratedFDerivWithin 𝕜 n f (s ∩ u) x = iteratedFDerivWithin 𝕜 n f s x :=
iteratedFDerivWithin_inter' (mem_nhdsWithin_of_mem_nhds hu)
#align iterated_fderiv_within_inter iteratedFDerivWithin_inter
/-- The iterated differential within a set `s` at a point `x` is not modified if one intersects
`s` with an open set containing `x`. -/
theorem iteratedFDerivWithin_inter_open {n : ℕ} (hu : IsOpen u) (hx : x ∈ u) :
iteratedFDerivWithin 𝕜 n f (s ∩ u) x = iteratedFDerivWithin 𝕜 n f s x :=
iteratedFDerivWithin_inter (hu.mem_nhds hx)
#align iterated_fderiv_within_inter_open iteratedFDerivWithin_inter_open
@[simp]
theorem contDiffOn_zero : ContDiffOn 𝕜 0 f s ↔ ContinuousOn f s := by
refine ⟨fun H => H.continuousOn, fun H => ?_⟩
intro x hx m hm
have : (m : ℕ∞) = 0 := le_antisymm hm bot_le
rw [this]
refine ⟨insert x s, self_mem_nhdsWithin, ftaylorSeriesWithin 𝕜 f s, ?_⟩
rw [hasFTaylorSeriesUpToOn_zero_iff]
exact ⟨by rwa [insert_eq_of_mem hx], fun x _ => by simp [ftaylorSeriesWithin]⟩
#align cont_diff_on_zero contDiffOn_zero
theorem contDiffWithinAt_zero (hx : x ∈ s) :
ContDiffWithinAt 𝕜 0 f s x ↔ ∃ u ∈ 𝓝[s] x, ContinuousOn f (s ∩ u) := by
constructor
· intro h
obtain ⟨u, H, p, hp⟩ := h 0 le_rfl
refine ⟨u, ?_, ?_⟩
· simpa [hx] using H
· simp only [Nat.cast_zero, hasFTaylorSeriesUpToOn_zero_iff] at hp
exact hp.1.mono inter_subset_right
· rintro ⟨u, H, hu⟩
rw [← contDiffWithinAt_inter' H]
have h' : x ∈ s ∩ u := ⟨hx, mem_of_mem_nhdsWithin hx H⟩
exact (contDiffOn_zero.mpr hu).contDiffWithinAt h'
#align cont_diff_within_at_zero contDiffWithinAt_zero
/-- On a set with unique differentiability, any choice of iterated differential has to coincide
with the one we have chosen in `iteratedFDerivWithin 𝕜 m f s`. -/
theorem HasFTaylorSeriesUpToOn.eq_iteratedFDerivWithin_of_uniqueDiffOn
(h : HasFTaylorSeriesUpToOn n f p s) {m : ℕ} (hmn : (m : ℕ∞) ≤ n) (hs : UniqueDiffOn 𝕜 s)
(hx : x ∈ s) : p x m = iteratedFDerivWithin 𝕜 m f s x := by
induction' m with m IH generalizing x
· rw [h.zero_eq' hx, iteratedFDerivWithin_zero_eq_comp]; rfl
· have A : (m : ℕ∞) < n := lt_of_lt_of_le (WithTop.coe_lt_coe.2 (lt_add_one m)) hmn
have :
HasFDerivWithinAt (fun y : E => iteratedFDerivWithin 𝕜 m f s y)
(ContinuousMultilinearMap.curryLeft (p x (Nat.succ m))) s x :=
(h.fderivWithin m A x hx).congr (fun y hy => (IH (le_of_lt A) hy).symm)
(IH (le_of_lt A) hx).symm
rw [iteratedFDerivWithin_succ_eq_comp_left, Function.comp_apply, this.fderivWithin (hs x hx)]
exact (ContinuousMultilinearMap.uncurry_curryLeft _).symm
#align has_ftaylor_series_up_to_on.eq_ftaylor_series_of_unique_diff_on HasFTaylorSeriesUpToOn.eq_iteratedFDerivWithin_of_uniqueDiffOn
@[deprecated] alias HasFTaylorSeriesUpToOn.eq_ftaylor_series_of_uniqueDiffOn :=
HasFTaylorSeriesUpToOn.eq_iteratedFDerivWithin_of_uniqueDiffOn -- 2024-03-28
/-- When a function is `C^n` in a set `s` of unique differentiability, it admits
`ftaylorSeriesWithin 𝕜 f s` as a Taylor series up to order `n` in `s`. -/
protected theorem ContDiffOn.ftaylorSeriesWithin (h : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) :
HasFTaylorSeriesUpToOn n f (ftaylorSeriesWithin 𝕜 f s) s := by
constructor
· intro x _
simp only [ftaylorSeriesWithin, ContinuousMultilinearMap.uncurry0_apply,
iteratedFDerivWithin_zero_apply]
· intro m hm x hx
rcases (h x hx) m.succ (ENat.add_one_le_of_lt hm) with ⟨u, hu, p, Hp⟩
rw [insert_eq_of_mem hx] at hu
rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩
rw [inter_comm] at ho
have : p x m.succ = ftaylorSeriesWithin 𝕜 f s x m.succ := by
change p x m.succ = iteratedFDerivWithin 𝕜 m.succ f s x
rw [← iteratedFDerivWithin_inter_open o_open xo]
exact (Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter o_open) ⟨hx, xo⟩
rw [← this, ← hasFDerivWithinAt_inter (IsOpen.mem_nhds o_open xo)]
have A : ∀ y ∈ s ∩ o, p y m = ftaylorSeriesWithin 𝕜 f s y m := by
rintro y ⟨hy, yo⟩
change p y m = iteratedFDerivWithin 𝕜 m f s y
rw [← iteratedFDerivWithin_inter_open o_open yo]
exact
(Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn (WithTop.coe_le_coe.2 (Nat.le_succ m))
(hs.inter o_open) ⟨hy, yo⟩
exact
((Hp.mono ho).fderivWithin m (WithTop.coe_lt_coe.2 (lt_add_one m)) x ⟨hx, xo⟩).congr
(fun y hy => (A y hy).symm) (A x ⟨hx, xo⟩).symm
· intro m hm
apply continuousOn_of_locally_continuousOn
intro x hx
rcases h x hx m hm with ⟨u, hu, p, Hp⟩
rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩
rw [insert_eq_of_mem hx] at ho
rw [inter_comm] at ho
refine ⟨o, o_open, xo, ?_⟩
have A : ∀ y ∈ s ∩ o, p y m = ftaylorSeriesWithin 𝕜 f s y m := by
rintro y ⟨hy, yo⟩
change p y m = iteratedFDerivWithin 𝕜 m f s y
rw [← iteratedFDerivWithin_inter_open o_open yo]
exact (Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter o_open) ⟨hy, yo⟩
exact ((Hp.mono ho).cont m le_rfl).congr fun y hy => (A y hy).symm
#align cont_diff_on.ftaylor_series_within ContDiffOn.ftaylorSeriesWithin
theorem contDiffOn_of_continuousOn_differentiableOn
(Hcont : ∀ m : ℕ, (m : ℕ∞) ≤ n → ContinuousOn (fun x => iteratedFDerivWithin 𝕜 m f s x) s)
(Hdiff : ∀ m : ℕ, (m : ℕ∞) < n →
DifferentiableOn 𝕜 (fun x => iteratedFDerivWithin 𝕜 m f s x) s) :
ContDiffOn 𝕜 n f s := by
intro x hx m hm
rw [insert_eq_of_mem hx]
refine ⟨s, self_mem_nhdsWithin, ftaylorSeriesWithin 𝕜 f s, ?_⟩
constructor
· intro y _
simp only [ftaylorSeriesWithin, ContinuousMultilinearMap.uncurry0_apply,
iteratedFDerivWithin_zero_apply]
· intro k hk y hy
convert (Hdiff k (lt_of_lt_of_le hk hm) y hy).hasFDerivWithinAt
· intro k hk
exact Hcont k (le_trans hk hm)
#align cont_diff_on_of_continuous_on_differentiable_on contDiffOn_of_continuousOn_differentiableOn
theorem contDiffOn_of_differentiableOn
(h : ∀ m : ℕ, (m : ℕ∞) ≤ n → DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 m f s) s) :
ContDiffOn 𝕜 n f s :=
contDiffOn_of_continuousOn_differentiableOn (fun m hm => (h m hm).continuousOn) fun m hm =>
h m (le_of_lt hm)
#align cont_diff_on_of_differentiable_on contDiffOn_of_differentiableOn
theorem ContDiffOn.continuousOn_iteratedFDerivWithin {m : ℕ} (h : ContDiffOn 𝕜 n f s)
(hmn : (m : ℕ∞) ≤ n) (hs : UniqueDiffOn 𝕜 s) : ContinuousOn (iteratedFDerivWithin 𝕜 m f s) s :=
(h.ftaylorSeriesWithin hs).cont m hmn
#align cont_diff_on.continuous_on_iterated_fderiv_within ContDiffOn.continuousOn_iteratedFDerivWithin
theorem ContDiffOn.differentiableOn_iteratedFDerivWithin {m : ℕ} (h : ContDiffOn 𝕜 n f s)
(hmn : (m : ℕ∞) < n) (hs : UniqueDiffOn 𝕜 s) :
DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 m f s) s := fun x hx =>
((h.ftaylorSeriesWithin hs).fderivWithin m hmn x hx).differentiableWithinAt
#align cont_diff_on.differentiable_on_iterated_fderiv_within ContDiffOn.differentiableOn_iteratedFDerivWithin
theorem ContDiffWithinAt.differentiableWithinAt_iteratedFDerivWithin {m : ℕ}
(h : ContDiffWithinAt 𝕜 n f s x) (hmn : (m : ℕ∞) < n) (hs : UniqueDiffOn 𝕜 (insert x s)) :
DifferentiableWithinAt 𝕜 (iteratedFDerivWithin 𝕜 m f s) s x := by
rcases h.contDiffOn' (ENat.add_one_le_of_lt hmn) with ⟨u, uo, xu, hu⟩
set t := insert x s ∩ u
have A : t =ᶠ[𝓝[≠] x] s := by
simp only [set_eventuallyEq_iff_inf_principal, ← nhdsWithin_inter']
rw [← inter_assoc, nhdsWithin_inter_of_mem', ← diff_eq_compl_inter, insert_diff_of_mem,
diff_eq_compl_inter]
exacts [rfl, mem_nhdsWithin_of_mem_nhds (uo.mem_nhds xu)]
have B : iteratedFDerivWithin 𝕜 m f s =ᶠ[𝓝 x] iteratedFDerivWithin 𝕜 m f t :=
iteratedFDerivWithin_eventually_congr_set' _ A.symm _
have C : DifferentiableWithinAt 𝕜 (iteratedFDerivWithin 𝕜 m f t) t x :=
hu.differentiableOn_iteratedFDerivWithin (Nat.cast_lt.2 m.lt_succ_self) (hs.inter uo) x
⟨mem_insert _ _, xu⟩
rw [differentiableWithinAt_congr_set' _ A] at C
exact C.congr_of_eventuallyEq (B.filter_mono inf_le_left) B.self_of_nhds
#align cont_diff_within_at.differentiable_within_at_iterated_fderiv_within ContDiffWithinAt.differentiableWithinAt_iteratedFDerivWithin
theorem contDiffOn_iff_continuousOn_differentiableOn (hs : UniqueDiffOn 𝕜 s) :
ContDiffOn 𝕜 n f s ↔
(∀ m : ℕ, (m : ℕ∞) ≤ n → ContinuousOn (fun x => iteratedFDerivWithin 𝕜 m f s x) s) ∧
∀ m : ℕ, (m : ℕ∞) < n → DifferentiableOn 𝕜 (fun x => iteratedFDerivWithin 𝕜 m f s x) s :=
⟨fun h => ⟨fun _m hm => h.continuousOn_iteratedFDerivWithin hm hs, fun _m hm =>
h.differentiableOn_iteratedFDerivWithin hm hs⟩,
fun h => contDiffOn_of_continuousOn_differentiableOn h.1 h.2⟩
#align cont_diff_on_iff_continuous_on_differentiable_on contDiffOn_iff_continuousOn_differentiableOn
theorem contDiffOn_succ_of_fderivWithin {n : ℕ} (hf : DifferentiableOn 𝕜 f s)
(h : ContDiffOn 𝕜 n (fun y => fderivWithin 𝕜 f s y) s) : ContDiffOn 𝕜 (n + 1 : ℕ) f s := by
intro x hx
rw [contDiffWithinAt_succ_iff_hasFDerivWithinAt, insert_eq_of_mem hx]
exact
⟨s, self_mem_nhdsWithin, fderivWithin 𝕜 f s, fun y hy => (hf y hy).hasFDerivWithinAt, h x hx⟩
#align cont_diff_on_succ_of_fderiv_within contDiffOn_succ_of_fderivWithin
/-- A function is `C^(n + 1)` on a domain with unique derivatives if and only if it is
differentiable there, and its derivative (expressed with `fderivWithin`) is `C^n`. -/
| Mathlib/Analysis/Calculus/ContDiff/Defs.lean | 1,159 | 1,175 | theorem contDiffOn_succ_iff_fderivWithin {n : ℕ} (hs : UniqueDiffOn 𝕜 s) :
ContDiffOn 𝕜 (n + 1 : ℕ) f s ↔
DifferentiableOn 𝕜 f s ∧ ContDiffOn 𝕜 n (fun y => fderivWithin 𝕜 f s y) s := by |
refine ⟨fun H => ?_, fun h => contDiffOn_succ_of_fderivWithin h.1 h.2⟩
refine ⟨H.differentiableOn (WithTop.coe_le_coe.2 (Nat.le_add_left 1 n)), fun x hx => ?_⟩
rcases contDiffWithinAt_succ_iff_hasFDerivWithinAt.1 (H x hx) with ⟨u, hu, f', hff', hf'⟩
rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩
rw [inter_comm, insert_eq_of_mem hx] at ho
have := hf'.mono ho
rw [contDiffWithinAt_inter' (mem_nhdsWithin_of_mem_nhds (IsOpen.mem_nhds o_open xo))] at this
apply this.congr_of_eventually_eq' _ hx
have : o ∩ s ∈ 𝓝[s] x := mem_nhdsWithin.2 ⟨o, o_open, xo, Subset.refl _⟩
rw [inter_comm] at this
refine Filter.eventuallyEq_of_mem this fun y hy => ?_
have A : fderivWithin 𝕜 f (s ∩ o) y = f' y :=
((hff' y (ho hy)).mono ho).fderivWithin (hs.inter o_open y hy)
rwa [fderivWithin_inter (o_open.mem_nhds hy.2)] at A
|
/-
Copyright (c) 2021 Yourong Zang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yourong Zang, Yury Kudryashov
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Topology.Separation
import Mathlib.Topology.Sets.Opens
#align_import topology.alexandroff from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# The OnePoint Compactification
We construct the OnePoint compactification (the one-point compactification) of an arbitrary
topological space `X` and prove some properties inherited from `X`.
## Main definitions
* `OnePoint`: the OnePoint compactification, we use coercion for the canonical embedding
`X → OnePoint X`; when `X` is already compact, the compactification adds an isolated point
to the space.
* `OnePoint.infty`: the extra point
## Main results
* The topological structure of `OnePoint X`
* The connectedness of `OnePoint X` for a noncompact, preconnected `X`
* `OnePoint X` is `T₀` for a T₀ space `X`
* `OnePoint X` is `T₁` for a T₁ space `X`
* `OnePoint X` is normal if `X` is a locally compact Hausdorff space
## Tags
one-point compactification, compactness
-/
open Set Filter Topology
/-!
### Definition and basic properties
In this section we define `OnePoint X` to be the disjoint union of `X` and `∞`, implemented as
`Option X`. Then we restate some lemmas about `Option X` for `OnePoint X`.
-/
variable {X : Type*}
/-- The OnePoint extension of an arbitrary topological space `X` -/
def OnePoint (X : Type*) :=
Option X
#align alexandroff OnePoint
/-- The repr uses the notation from the `OnePoint` locale. -/
instance [Repr X] : Repr (OnePoint X) :=
⟨fun o _ =>
match o with
| none => "∞"
| some a => "↑" ++ repr a⟩
namespace OnePoint
/-- The point at infinity -/
@[match_pattern] def infty : OnePoint X := none
#align alexandroff.infty OnePoint.infty
@[inherit_doc]
scoped notation "∞" => OnePoint.infty
/-- Coercion from `X` to `OnePoint X`. -/
@[coe, match_pattern] def some : X → OnePoint X := Option.some
instance : CoeTC X (OnePoint X) := ⟨some⟩
instance : Inhabited (OnePoint X) := ⟨∞⟩
instance [Fintype X] : Fintype (OnePoint X) :=
inferInstanceAs (Fintype (Option X))
instance infinite [Infinite X] : Infinite (OnePoint X) :=
inferInstanceAs (Infinite (Option X))
#align alexandroff.infinite OnePoint.infinite
theorem coe_injective : Function.Injective ((↑) : X → OnePoint X) :=
Option.some_injective X
#align alexandroff.coe_injective OnePoint.coe_injective
@[norm_cast]
theorem coe_eq_coe {x y : X} : (x : OnePoint X) = y ↔ x = y :=
coe_injective.eq_iff
#align alexandroff.coe_eq_coe OnePoint.coe_eq_coe
@[simp]
theorem coe_ne_infty (x : X) : (x : OnePoint X) ≠ ∞ :=
nofun
#align alexandroff.coe_ne_infty OnePoint.coe_ne_infty
@[simp]
theorem infty_ne_coe (x : X) : ∞ ≠ (x : OnePoint X) :=
nofun
#align alexandroff.infty_ne_coe OnePoint.infty_ne_coe
/-- Recursor for `OnePoint` using the preferred forms `∞` and `↑x`. -/
@[elab_as_elim]
protected def rec {C : OnePoint X → Sort*} (h₁ : C ∞) (h₂ : ∀ x : X, C x) :
∀ z : OnePoint X, C z
| ∞ => h₁
| (x : X) => h₂ x
#align alexandroff.rec OnePoint.rec
theorem isCompl_range_coe_infty : IsCompl (range ((↑) : X → OnePoint X)) {∞} :=
isCompl_range_some_none X
#align alexandroff.is_compl_range_coe_infty OnePoint.isCompl_range_coe_infty
-- Porting note: moved @[simp] to a new lemma
theorem range_coe_union_infty : range ((↑) : X → OnePoint X) ∪ {∞} = univ :=
range_some_union_none X
#align alexandroff.range_coe_union_infty OnePoint.range_coe_union_infty
@[simp]
theorem insert_infty_range_coe : insert ∞ (range (@some X)) = univ :=
insert_none_range_some _
@[simp]
theorem range_coe_inter_infty : range ((↑) : X → OnePoint X) ∩ {∞} = ∅ :=
range_some_inter_none X
#align alexandroff.range_coe_inter_infty OnePoint.range_coe_inter_infty
@[simp]
theorem compl_range_coe : (range ((↑) : X → OnePoint X))ᶜ = {∞} :=
compl_range_some X
#align alexandroff.compl_range_coe OnePoint.compl_range_coe
theorem compl_infty : ({∞}ᶜ : Set (OnePoint X)) = range ((↑) : X → OnePoint X) :=
(@isCompl_range_coe_infty X).symm.compl_eq
#align alexandroff.compl_infty OnePoint.compl_infty
theorem compl_image_coe (s : Set X) : ((↑) '' s : Set (OnePoint X))ᶜ = (↑) '' sᶜ ∪ {∞} := by
rw [coe_injective.compl_image_eq, compl_range_coe]
#align alexandroff.compl_image_coe OnePoint.compl_image_coe
theorem ne_infty_iff_exists {x : OnePoint X} : x ≠ ∞ ↔ ∃ y : X, (y : OnePoint X) = x := by
induction x using OnePoint.rec <;> simp
#align alexandroff.ne_infty_iff_exists OnePoint.ne_infty_iff_exists
instance canLift : CanLift (OnePoint X) X (↑) fun x => x ≠ ∞ :=
WithTop.canLift
#align alexandroff.can_lift OnePoint.canLift
theorem not_mem_range_coe_iff {x : OnePoint X} : x ∉ range some ↔ x = ∞ := by
rw [← mem_compl_iff, compl_range_coe, mem_singleton_iff]
#align alexandroff.not_mem_range_coe_iff OnePoint.not_mem_range_coe_iff
theorem infty_not_mem_range_coe : ∞ ∉ range ((↑) : X → OnePoint X) :=
not_mem_range_coe_iff.2 rfl
#align alexandroff.infty_not_mem_range_coe OnePoint.infty_not_mem_range_coe
theorem infty_not_mem_image_coe {s : Set X} : ∞ ∉ ((↑) : X → OnePoint X) '' s :=
not_mem_subset (image_subset_range _ _) infty_not_mem_range_coe
#align alexandroff.infty_not_mem_image_coe OnePoint.infty_not_mem_image_coe
@[simp]
theorem coe_preimage_infty : ((↑) : X → OnePoint X) ⁻¹' {∞} = ∅ := by
ext
simp
#align alexandroff.coe_preimage_infty OnePoint.coe_preimage_infty
/-!
### Topological space structure on `OnePoint X`
We define a topological space structure on `OnePoint X` so that `s` is open if and only if
* `(↑) ⁻¹' s` is open in `X`;
* if `∞ ∈ s`, then `((↑) ⁻¹' s)ᶜ` is compact.
Then we reformulate this definition in a few different ways, and prove that
`(↑) : X → OnePoint X` is an open embedding. If `X` is not a compact space, then we also prove
that `(↑)` has dense range, so it is a dense embedding.
-/
variable [TopologicalSpace X]
instance : TopologicalSpace (OnePoint X) where
IsOpen s := (∞ ∈ s → IsCompact (((↑) : X → OnePoint X) ⁻¹' s)ᶜ) ∧
IsOpen (((↑) : X → OnePoint X) ⁻¹' s)
isOpen_univ := by simp
isOpen_inter s t := by
rintro ⟨hms, hs⟩ ⟨hmt, ht⟩
refine ⟨?_, hs.inter ht⟩
rintro ⟨hms', hmt'⟩
simpa [compl_inter] using (hms hms').union (hmt hmt')
isOpen_sUnion S ho := by
suffices IsOpen ((↑) ⁻¹' ⋃₀ S : Set X) by
refine ⟨?_, this⟩
rintro ⟨s, hsS : s ∈ S, hs : ∞ ∈ s⟩
refine IsCompact.of_isClosed_subset ((ho s hsS).1 hs) this.isClosed_compl ?_
exact compl_subset_compl.mpr (preimage_mono <| subset_sUnion_of_mem hsS)
rw [preimage_sUnion]
exact isOpen_biUnion fun s hs => (ho s hs).2
variable {s : Set (OnePoint X)} {t : Set X}
theorem isOpen_def :
IsOpen s ↔ (∞ ∈ s → IsCompact ((↑) ⁻¹' s : Set X)ᶜ) ∧ IsOpen ((↑) ⁻¹' s : Set X) :=
Iff.rfl
#align alexandroff.is_open_def OnePoint.isOpen_def
theorem isOpen_iff_of_mem' (h : ∞ ∈ s) :
IsOpen s ↔ IsCompact ((↑) ⁻¹' s : Set X)ᶜ ∧ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
#align alexandroff.is_open_iff_of_mem' OnePoint.isOpen_iff_of_mem'
theorem isOpen_iff_of_mem (h : ∞ ∈ s) :
IsOpen s ↔ IsClosed ((↑) ⁻¹' s : Set X)ᶜ ∧ IsCompact ((↑) ⁻¹' s : Set X)ᶜ := by
simp only [isOpen_iff_of_mem' h, isClosed_compl_iff, and_comm]
#align alexandroff.is_open_iff_of_mem OnePoint.isOpen_iff_of_mem
theorem isOpen_iff_of_not_mem (h : ∞ ∉ s) : IsOpen s ↔ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
#align alexandroff.is_open_iff_of_not_mem OnePoint.isOpen_iff_of_not_mem
| Mathlib/Topology/Compactification/OnePoint.lean | 225 | 227 | theorem isClosed_iff_of_mem (h : ∞ ∈ s) : IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) := by |
have : ∞ ∉ sᶜ := fun H => H h
rw [← isOpen_compl_iff, isOpen_iff_of_not_mem this, ← isOpen_compl_iff, preimage_compl]
|
/-
Copyright (c) 2018 Ellen Arlt. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ellen Arlt, Blair Shi, Sean Leather, Mario Carneiro, Johan Commelin, Lu-Ming Zhang
-/
import Mathlib.Algebra.Algebra.Opposite
import Mathlib.Algebra.Algebra.Pi
import Mathlib.Algebra.BigOperators.Pi
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Algebra.BigOperators.RingEquiv
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.Algebra.Module.Pi
import Mathlib.Algebra.Star.BigOperators
import Mathlib.Algebra.Star.Module
import Mathlib.Algebra.Star.Pi
import Mathlib.Data.Fintype.BigOperators
import Mathlib.GroupTheory.GroupAction.BigOperators
#align_import data.matrix.basic from "leanprover-community/mathlib"@"eba5bb3155cab51d80af00e8d7d69fa271b1302b"
/-!
# Matrices
This file defines basic properties of matrices.
Matrices with rows indexed by `m`, columns indexed by `n`, and entries of type `α` are represented
with `Matrix m n α`. For the typical approach of counting rows and columns,
`Matrix (Fin m) (Fin n) α` can be used.
## Notation
The locale `Matrix` gives the following notation:
* `⬝ᵥ` for `Matrix.dotProduct`
* `*ᵥ` for `Matrix.mulVec`
* `ᵥ*` for `Matrix.vecMul`
* `ᵀ` for `Matrix.transpose`
* `ᴴ` for `Matrix.conjTranspose`
## Implementation notes
For convenience, `Matrix m n α` is defined as `m → n → α`, as this allows elements of the matrix
to be accessed with `A i j`. However, it is not advisable to _construct_ matrices using terms of the
form `fun i j ↦ _` or even `(fun i j ↦ _ : Matrix m n α)`, as these are not recognized by Lean
as having the right type. Instead, `Matrix.of` should be used.
## TODO
Under various conditions, multiplication of infinite matrices makes sense.
These have not yet been implemented.
-/
universe u u' v w
/-- `Matrix m n R` is the type of matrices with entries in `R`, whose rows are indexed by `m`
and whose columns are indexed by `n`. -/
def Matrix (m : Type u) (n : Type u') (α : Type v) : Type max u u' v :=
m → n → α
#align matrix Matrix
variable {l m n o : Type*} {m' : o → Type*} {n' : o → Type*}
variable {R : Type*} {S : Type*} {α : Type v} {β : Type w} {γ : Type*}
namespace Matrix
section Ext
variable {M N : Matrix m n α}
theorem ext_iff : (∀ i j, M i j = N i j) ↔ M = N :=
⟨fun h => funext fun i => funext <| h i, fun h => by simp [h]⟩
#align matrix.ext_iff Matrix.ext_iff
@[ext]
theorem ext : (∀ i j, M i j = N i j) → M = N :=
ext_iff.mp
#align matrix.ext Matrix.ext
end Ext
/-- Cast a function into a matrix.
The two sides of the equivalence are definitionally equal types. We want to use an explicit cast
to distinguish the types because `Matrix` has different instances to pi types (such as `Pi.mul`,
which performs elementwise multiplication, vs `Matrix.mul`).
If you are defining a matrix, in terms of its entries, use `of (fun i j ↦ _)`. The
purpose of this approach is to ensure that terms of the form `(fun i j ↦ _) * (fun i j ↦ _)` do not
appear, as the type of `*` can be misleading.
Porting note: In Lean 3, it is also safe to use pattern matching in a definition as `| i j := _`,
which can only be unfolded when fully-applied. leanprover/lean4#2042 means this does not
(currently) work in Lean 4.
-/
def of : (m → n → α) ≃ Matrix m n α :=
Equiv.refl _
#align matrix.of Matrix.of
@[simp]
theorem of_apply (f : m → n → α) (i j) : of f i j = f i j :=
rfl
#align matrix.of_apply Matrix.of_apply
@[simp]
theorem of_symm_apply (f : Matrix m n α) (i j) : of.symm f i j = f i j :=
rfl
#align matrix.of_symm_apply Matrix.of_symm_apply
/-- `M.map f` is the matrix obtained by applying `f` to each entry of the matrix `M`.
This is available in bundled forms as:
* `AddMonoidHom.mapMatrix`
* `LinearMap.mapMatrix`
* `RingHom.mapMatrix`
* `AlgHom.mapMatrix`
* `Equiv.mapMatrix`
* `AddEquiv.mapMatrix`
* `LinearEquiv.mapMatrix`
* `RingEquiv.mapMatrix`
* `AlgEquiv.mapMatrix`
-/
def map (M : Matrix m n α) (f : α → β) : Matrix m n β :=
of fun i j => f (M i j)
#align matrix.map Matrix.map
@[simp]
theorem map_apply {M : Matrix m n α} {f : α → β} {i : m} {j : n} : M.map f i j = f (M i j) :=
rfl
#align matrix.map_apply Matrix.map_apply
@[simp]
theorem map_id (M : Matrix m n α) : M.map id = M := by
ext
rfl
#align matrix.map_id Matrix.map_id
@[simp]
theorem map_id' (M : Matrix m n α) : M.map (·) = M := map_id M
@[simp]
theorem map_map {M : Matrix m n α} {β γ : Type*} {f : α → β} {g : β → γ} :
(M.map f).map g = M.map (g ∘ f) := by
ext
rfl
#align matrix.map_map Matrix.map_map
theorem map_injective {f : α → β} (hf : Function.Injective f) :
Function.Injective fun M : Matrix m n α => M.map f := fun _ _ h =>
ext fun i j => hf <| ext_iff.mpr h i j
#align matrix.map_injective Matrix.map_injective
/-- The transpose of a matrix. -/
def transpose (M : Matrix m n α) : Matrix n m α :=
of fun x y => M y x
#align matrix.transpose Matrix.transpose
-- TODO: set as an equation lemma for `transpose`, see mathlib4#3024
@[simp]
theorem transpose_apply (M : Matrix m n α) (i j) : transpose M i j = M j i :=
rfl
#align matrix.transpose_apply Matrix.transpose_apply
@[inherit_doc]
scoped postfix:1024 "ᵀ" => Matrix.transpose
/-- The conjugate transpose of a matrix defined in term of `star`. -/
def conjTranspose [Star α] (M : Matrix m n α) : Matrix n m α :=
M.transpose.map star
#align matrix.conj_transpose Matrix.conjTranspose
@[inherit_doc]
scoped postfix:1024 "ᴴ" => Matrix.conjTranspose
instance inhabited [Inhabited α] : Inhabited (Matrix m n α) :=
inferInstanceAs <| Inhabited <| m → n → α
-- Porting note: new, Lean3 found this automatically
instance decidableEq [DecidableEq α] [Fintype m] [Fintype n] : DecidableEq (Matrix m n α) :=
Fintype.decidablePiFintype
instance {n m} [Fintype m] [DecidableEq m] [Fintype n] [DecidableEq n] (α) [Fintype α] :
Fintype (Matrix m n α) := inferInstanceAs (Fintype (m → n → α))
instance {n m} [Finite m] [Finite n] (α) [Finite α] :
Finite (Matrix m n α) := inferInstanceAs (Finite (m → n → α))
instance add [Add α] : Add (Matrix m n α) :=
Pi.instAdd
instance addSemigroup [AddSemigroup α] : AddSemigroup (Matrix m n α) :=
Pi.addSemigroup
instance addCommSemigroup [AddCommSemigroup α] : AddCommSemigroup (Matrix m n α) :=
Pi.addCommSemigroup
instance zero [Zero α] : Zero (Matrix m n α) :=
Pi.instZero
instance addZeroClass [AddZeroClass α] : AddZeroClass (Matrix m n α) :=
Pi.addZeroClass
instance addMonoid [AddMonoid α] : AddMonoid (Matrix m n α) :=
Pi.addMonoid
instance addCommMonoid [AddCommMonoid α] : AddCommMonoid (Matrix m n α) :=
Pi.addCommMonoid
instance neg [Neg α] : Neg (Matrix m n α) :=
Pi.instNeg
instance sub [Sub α] : Sub (Matrix m n α) :=
Pi.instSub
instance addGroup [AddGroup α] : AddGroup (Matrix m n α) :=
Pi.addGroup
instance addCommGroup [AddCommGroup α] : AddCommGroup (Matrix m n α) :=
Pi.addCommGroup
instance unique [Unique α] : Unique (Matrix m n α) :=
Pi.unique
instance subsingleton [Subsingleton α] : Subsingleton (Matrix m n α) :=
inferInstanceAs <| Subsingleton <| m → n → α
instance nonempty [Nonempty m] [Nonempty n] [Nontrivial α] : Nontrivial (Matrix m n α) :=
Function.nontrivial
instance smul [SMul R α] : SMul R (Matrix m n α) :=
Pi.instSMul
instance smulCommClass [SMul R α] [SMul S α] [SMulCommClass R S α] :
SMulCommClass R S (Matrix m n α) :=
Pi.smulCommClass
instance isScalarTower [SMul R S] [SMul R α] [SMul S α] [IsScalarTower R S α] :
IsScalarTower R S (Matrix m n α) :=
Pi.isScalarTower
instance isCentralScalar [SMul R α] [SMul Rᵐᵒᵖ α] [IsCentralScalar R α] :
IsCentralScalar R (Matrix m n α) :=
Pi.isCentralScalar
instance mulAction [Monoid R] [MulAction R α] : MulAction R (Matrix m n α) :=
Pi.mulAction _
instance distribMulAction [Monoid R] [AddMonoid α] [DistribMulAction R α] :
DistribMulAction R (Matrix m n α) :=
Pi.distribMulAction _
instance module [Semiring R] [AddCommMonoid α] [Module R α] : Module R (Matrix m n α) :=
Pi.module _ _ _
-- Porting note (#10756): added the following section with simp lemmas because `simp` fails
-- to apply the corresponding lemmas in the namespace `Pi`.
-- (e.g. `Pi.zero_apply` used on `OfNat.ofNat 0 i j`)
section
@[simp]
theorem zero_apply [Zero α] (i : m) (j : n) : (0 : Matrix m n α) i j = 0 := rfl
@[simp]
theorem add_apply [Add α] (A B : Matrix m n α) (i : m) (j : n) :
(A + B) i j = (A i j) + (B i j) := rfl
@[simp]
theorem smul_apply [SMul β α] (r : β) (A : Matrix m n α) (i : m) (j : n) :
(r • A) i j = r • (A i j) := rfl
@[simp]
theorem sub_apply [Sub α] (A B : Matrix m n α) (i : m) (j : n) :
(A - B) i j = (A i j) - (B i j) := rfl
@[simp]
theorem neg_apply [Neg α] (A : Matrix m n α) (i : m) (j : n) :
(-A) i j = -(A i j) := rfl
end
/-! simp-normal form pulls `of` to the outside. -/
@[simp]
theorem of_zero [Zero α] : of (0 : m → n → α) = 0 :=
rfl
#align matrix.of_zero Matrix.of_zero
@[simp]
theorem of_add_of [Add α] (f g : m → n → α) : of f + of g = of (f + g) :=
rfl
#align matrix.of_add_of Matrix.of_add_of
@[simp]
theorem of_sub_of [Sub α] (f g : m → n → α) : of f - of g = of (f - g) :=
rfl
#align matrix.of_sub_of Matrix.of_sub_of
@[simp]
theorem neg_of [Neg α] (f : m → n → α) : -of f = of (-f) :=
rfl
#align matrix.neg_of Matrix.neg_of
@[simp]
theorem smul_of [SMul R α] (r : R) (f : m → n → α) : r • of f = of (r • f) :=
rfl
#align matrix.smul_of Matrix.smul_of
@[simp]
protected theorem map_zero [Zero α] [Zero β] (f : α → β) (h : f 0 = 0) :
(0 : Matrix m n α).map f = 0 := by
ext
simp [h]
#align matrix.map_zero Matrix.map_zero
protected theorem map_add [Add α] [Add β] (f : α → β) (hf : ∀ a₁ a₂, f (a₁ + a₂) = f a₁ + f a₂)
(M N : Matrix m n α) : (M + N).map f = M.map f + N.map f :=
ext fun _ _ => hf _ _
#align matrix.map_add Matrix.map_add
protected theorem map_sub [Sub α] [Sub β] (f : α → β) (hf : ∀ a₁ a₂, f (a₁ - a₂) = f a₁ - f a₂)
(M N : Matrix m n α) : (M - N).map f = M.map f - N.map f :=
ext fun _ _ => hf _ _
#align matrix.map_sub Matrix.map_sub
theorem map_smul [SMul R α] [SMul R β] (f : α → β) (r : R) (hf : ∀ a, f (r • a) = r • f a)
(M : Matrix m n α) : (r • M).map f = r • M.map f :=
ext fun _ _ => hf _
#align matrix.map_smul Matrix.map_smul
/-- The scalar action via `Mul.toSMul` is transformed by the same map as the elements
of the matrix, when `f` preserves multiplication. -/
theorem map_smul' [Mul α] [Mul β] (f : α → β) (r : α) (A : Matrix n n α)
(hf : ∀ a₁ a₂, f (a₁ * a₂) = f a₁ * f a₂) : (r • A).map f = f r • A.map f :=
ext fun _ _ => hf _ _
#align matrix.map_smul' Matrix.map_smul'
/-- The scalar action via `mul.toOppositeSMul` is transformed by the same map as the
elements of the matrix, when `f` preserves multiplication. -/
theorem map_op_smul' [Mul α] [Mul β] (f : α → β) (r : α) (A : Matrix n n α)
(hf : ∀ a₁ a₂, f (a₁ * a₂) = f a₁ * f a₂) :
(MulOpposite.op r • A).map f = MulOpposite.op (f r) • A.map f :=
ext fun _ _ => hf _ _
#align matrix.map_op_smul' Matrix.map_op_smul'
theorem _root_.IsSMulRegular.matrix [SMul R S] {k : R} (hk : IsSMulRegular S k) :
IsSMulRegular (Matrix m n S) k :=
IsSMulRegular.pi fun _ => IsSMulRegular.pi fun _ => hk
#align is_smul_regular.matrix IsSMulRegular.matrix
theorem _root_.IsLeftRegular.matrix [Mul α] {k : α} (hk : IsLeftRegular k) :
IsSMulRegular (Matrix m n α) k :=
hk.isSMulRegular.matrix
#align is_left_regular.matrix IsLeftRegular.matrix
instance subsingleton_of_empty_left [IsEmpty m] : Subsingleton (Matrix m n α) :=
⟨fun M N => by
ext i
exact isEmptyElim i⟩
#align matrix.subsingleton_of_empty_left Matrix.subsingleton_of_empty_left
instance subsingleton_of_empty_right [IsEmpty n] : Subsingleton (Matrix m n α) :=
⟨fun M N => by
ext i j
exact isEmptyElim j⟩
#align matrix.subsingleton_of_empty_right Matrix.subsingleton_of_empty_right
end Matrix
open Matrix
namespace Matrix
section Diagonal
variable [DecidableEq n]
/-- `diagonal d` is the square matrix such that `(diagonal d) i i = d i` and `(diagonal d) i j = 0`
if `i ≠ j`.
Note that bundled versions exist as:
* `Matrix.diagonalAddMonoidHom`
* `Matrix.diagonalLinearMap`
* `Matrix.diagonalRingHom`
* `Matrix.diagonalAlgHom`
-/
def diagonal [Zero α] (d : n → α) : Matrix n n α :=
of fun i j => if i = j then d i else 0
#align matrix.diagonal Matrix.diagonal
-- TODO: set as an equation lemma for `diagonal`, see mathlib4#3024
theorem diagonal_apply [Zero α] (d : n → α) (i j) : diagonal d i j = if i = j then d i else 0 :=
rfl
#align matrix.diagonal_apply Matrix.diagonal_apply
@[simp]
theorem diagonal_apply_eq [Zero α] (d : n → α) (i : n) : (diagonal d) i i = d i := by
simp [diagonal]
#align matrix.diagonal_apply_eq Matrix.diagonal_apply_eq
@[simp]
theorem diagonal_apply_ne [Zero α] (d : n → α) {i j : n} (h : i ≠ j) : (diagonal d) i j = 0 := by
simp [diagonal, h]
#align matrix.diagonal_apply_ne Matrix.diagonal_apply_ne
theorem diagonal_apply_ne' [Zero α] (d : n → α) {i j : n} (h : j ≠ i) : (diagonal d) i j = 0 :=
diagonal_apply_ne d h.symm
#align matrix.diagonal_apply_ne' Matrix.diagonal_apply_ne'
@[simp]
theorem diagonal_eq_diagonal_iff [Zero α] {d₁ d₂ : n → α} :
diagonal d₁ = diagonal d₂ ↔ ∀ i, d₁ i = d₂ i :=
⟨fun h i => by simpa using congr_arg (fun m : Matrix n n α => m i i) h, fun h => by
rw [show d₁ = d₂ from funext h]⟩
#align matrix.diagonal_eq_diagonal_iff Matrix.diagonal_eq_diagonal_iff
theorem diagonal_injective [Zero α] : Function.Injective (diagonal : (n → α) → Matrix n n α) :=
fun d₁ d₂ h => funext fun i => by simpa using Matrix.ext_iff.mpr h i i
#align matrix.diagonal_injective Matrix.diagonal_injective
@[simp]
theorem diagonal_zero [Zero α] : (diagonal fun _ => 0 : Matrix n n α) = 0 := by
ext
simp [diagonal]
#align matrix.diagonal_zero Matrix.diagonal_zero
@[simp]
theorem diagonal_transpose [Zero α] (v : n → α) : (diagonal v)ᵀ = diagonal v := by
ext i j
by_cases h : i = j
· simp [h, transpose]
· simp [h, transpose, diagonal_apply_ne' _ h]
#align matrix.diagonal_transpose Matrix.diagonal_transpose
@[simp]
theorem diagonal_add [AddZeroClass α] (d₁ d₂ : n → α) :
diagonal d₁ + diagonal d₂ = diagonal fun i => d₁ i + d₂ i := by
ext i j
by_cases h : i = j <;>
simp [h]
#align matrix.diagonal_add Matrix.diagonal_add
@[simp]
theorem diagonal_smul [Zero α] [SMulZeroClass R α] (r : R) (d : n → α) :
diagonal (r • d) = r • diagonal d := by
ext i j
by_cases h : i = j <;> simp [h]
#align matrix.diagonal_smul Matrix.diagonal_smul
@[simp]
theorem diagonal_neg [NegZeroClass α] (d : n → α) :
-diagonal d = diagonal fun i => -d i := by
ext i j
by_cases h : i = j <;>
simp [h]
#align matrix.diagonal_neg Matrix.diagonal_neg
@[simp]
theorem diagonal_sub [SubNegZeroMonoid α] (d₁ d₂ : n → α) :
diagonal d₁ - diagonal d₂ = diagonal fun i => d₁ i - d₂ i := by
ext i j
by_cases h : i = j <;>
simp [h]
instance [Zero α] [NatCast α] : NatCast (Matrix n n α) where
natCast m := diagonal fun _ => m
@[norm_cast]
theorem diagonal_natCast [Zero α] [NatCast α] (m : ℕ) : diagonal (fun _ : n => (m : α)) = m := rfl
@[norm_cast]
theorem diagonal_natCast' [Zero α] [NatCast α] (m : ℕ) : diagonal ((m : n → α)) = m := rfl
-- See note [no_index around OfNat.ofNat]
theorem diagonal_ofNat [Zero α] [NatCast α] (m : ℕ) [m.AtLeastTwo] :
diagonal (fun _ : n => no_index (OfNat.ofNat m : α)) = OfNat.ofNat m := rfl
-- See note [no_index around OfNat.ofNat]
theorem diagonal_ofNat' [Zero α] [NatCast α] (m : ℕ) [m.AtLeastTwo] :
diagonal (no_index (OfNat.ofNat m : n → α)) = OfNat.ofNat m := rfl
instance [Zero α] [IntCast α] : IntCast (Matrix n n α) where
intCast m := diagonal fun _ => m
@[norm_cast]
theorem diagonal_intCast [Zero α] [IntCast α] (m : ℤ) : diagonal (fun _ : n => (m : α)) = m := rfl
@[norm_cast]
theorem diagonal_intCast' [Zero α] [IntCast α] (m : ℤ) : diagonal ((m : n → α)) = m := rfl
variable (n α)
/-- `Matrix.diagonal` as an `AddMonoidHom`. -/
@[simps]
def diagonalAddMonoidHom [AddZeroClass α] : (n → α) →+ Matrix n n α where
toFun := diagonal
map_zero' := diagonal_zero
map_add' x y := (diagonal_add x y).symm
#align matrix.diagonal_add_monoid_hom Matrix.diagonalAddMonoidHom
variable (R)
/-- `Matrix.diagonal` as a `LinearMap`. -/
@[simps]
def diagonalLinearMap [Semiring R] [AddCommMonoid α] [Module R α] : (n → α) →ₗ[R] Matrix n n α :=
{ diagonalAddMonoidHom n α with map_smul' := diagonal_smul }
#align matrix.diagonal_linear_map Matrix.diagonalLinearMap
variable {n α R}
@[simp]
| Mathlib/Data/Matrix/Basic.lean | 511 | 515 | theorem diagonal_map [Zero α] [Zero β] {f : α → β} (h : f 0 = 0) {d : n → α} :
(diagonal d).map f = diagonal fun m => f (d m) := by |
ext
simp only [diagonal_apply, map_apply]
split_ifs <;> simp [h]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Bool.Basic
import Mathlib.Init.Order.Defs
import Mathlib.Order.Monotone.Basic
import Mathlib.Order.ULift
import Mathlib.Tactic.GCongr.Core
#align_import order.lattice from "leanprover-community/mathlib"@"3ba15165bd6927679be7c22d6091a87337e3cd0c"
/-!
# (Semi-)lattices
Semilattices are partially ordered sets with join (least upper bound, or `sup`) or meet (greatest
lower bound, or `inf`) operations. Lattices are posets that are both join-semilattices and
meet-semilattices.
Distributive lattices are lattices which satisfy any of four equivalent distributivity properties,
of `sup` over `inf`, on the left or on the right.
## Main declarations
* `SemilatticeSup`: a type class for join semilattices
* `SemilatticeSup.mk'`: an alternative constructor for `SemilatticeSup` via proofs that `⊔` is
commutative, associative and idempotent.
* `SemilatticeInf`: a type class for meet semilattices
* `SemilatticeSup.mk'`: an alternative constructor for `SemilatticeInf` via proofs that `⊓` is
commutative, associative and idempotent.
* `Lattice`: a type class for lattices
* `Lattice.mk'`: an alternative constructor for `Lattice` via proofs that `⊔` and `⊓` are
commutative, associative and satisfy a pair of "absorption laws".
* `DistribLattice`: a type class for distributive lattices.
## Notations
* `a ⊔ b`: the supremum or join of `a` and `b`
* `a ⊓ b`: the infimum or meet of `a` and `b`
## TODO
* (Semi-)lattice homomorphisms
* Alternative constructors for distributive lattices from the other distributive properties
## Tags
semilattice, lattice
-/
/-- See if the term is `a ⊂ b` and the goal is `a ⊆ b`. -/
@[gcongr_forward] def exactSubsetOfSSubset : Mathlib.Tactic.GCongr.ForwardExt where
eval h goal := do goal.assignIfDefeq (← Lean.Meta.mkAppM ``subset_of_ssubset #[h])
universe u v w
variable {α : Type u} {β : Type v}
#align le_antisymm' le_antisymm
/-!
### Join-semilattices
-/
-- TODO: automatic construction of dual definitions / theorems
/-- A `SemilatticeSup` is a join-semilattice, that is, a partial order
with a join (a.k.a. lub / least upper bound, sup / supremum) operation
`⊔` which is the least element larger than both factors. -/
class SemilatticeSup (α : Type u) extends Sup α, PartialOrder α where
/-- The supremum is an upper bound on the first argument -/
protected le_sup_left : ∀ a b : α, a ≤ a ⊔ b
/-- The supremum is an upper bound on the second argument -/
protected le_sup_right : ∀ a b : α, b ≤ a ⊔ b
/-- The supremum is the *least* upper bound -/
protected sup_le : ∀ a b c : α, a ≤ c → b ≤ c → a ⊔ b ≤ c
#align semilattice_sup SemilatticeSup
/--
A type with a commutative, associative and idempotent binary `sup` operation has the structure of a
join-semilattice.
The partial order is defined so that `a ≤ b` unfolds to `a ⊔ b = b`; cf. `sup_eq_right`.
-/
def SemilatticeSup.mk' {α : Type*} [Sup α] (sup_comm : ∀ a b : α, a ⊔ b = b ⊔ a)
(sup_assoc : ∀ a b c : α, a ⊔ b ⊔ c = a ⊔ (b ⊔ c)) (sup_idem : ∀ a : α, a ⊔ a = a) :
SemilatticeSup α where
sup := (· ⊔ ·)
le a b := a ⊔ b = b
le_refl := sup_idem
le_trans a b c hab hbc := by dsimp; rw [← hbc, ← sup_assoc, hab]
le_antisymm a b hab hba := by rwa [← hba, sup_comm]
le_sup_left a b := by dsimp; rw [← sup_assoc, sup_idem]
le_sup_right a b := by dsimp; rw [sup_comm, sup_assoc, sup_idem]
sup_le a b c hac hbc := by dsimp; rwa [sup_assoc, hbc]
#align semilattice_sup.mk' SemilatticeSup.mk'
instance OrderDual.instSup (α : Type*) [Inf α] : Sup αᵒᵈ :=
⟨((· ⊓ ·) : α → α → α)⟩
instance OrderDual.instInf (α : Type*) [Sup α] : Inf αᵒᵈ :=
⟨((· ⊔ ·) : α → α → α)⟩
section SemilatticeSup
variable [SemilatticeSup α] {a b c d : α}
@[simp]
theorem le_sup_left : a ≤ a ⊔ b :=
SemilatticeSup.le_sup_left a b
#align le_sup_left le_sup_left
#align le_sup_left' le_sup_left
@[deprecated (since := "2024-06-04")] alias le_sup_left' := le_sup_left
@[simp]
theorem le_sup_right : b ≤ a ⊔ b :=
SemilatticeSup.le_sup_right a b
#align le_sup_right le_sup_right
#align le_sup_right' le_sup_right
@[deprecated (since := "2024-06-04")] alias le_sup_right' := le_sup_right
theorem le_sup_of_le_left (h : c ≤ a) : c ≤ a ⊔ b :=
le_trans h le_sup_left
#align le_sup_of_le_left le_sup_of_le_left
theorem le_sup_of_le_right (h : c ≤ b) : c ≤ a ⊔ b :=
le_trans h le_sup_right
#align le_sup_of_le_right le_sup_of_le_right
theorem lt_sup_of_lt_left (h : c < a) : c < a ⊔ b :=
h.trans_le le_sup_left
#align lt_sup_of_lt_left lt_sup_of_lt_left
theorem lt_sup_of_lt_right (h : c < b) : c < a ⊔ b :=
h.trans_le le_sup_right
#align lt_sup_of_lt_right lt_sup_of_lt_right
theorem sup_le : a ≤ c → b ≤ c → a ⊔ b ≤ c :=
SemilatticeSup.sup_le a b c
#align sup_le sup_le
@[simp]
theorem sup_le_iff : a ⊔ b ≤ c ↔ a ≤ c ∧ b ≤ c :=
⟨fun h : a ⊔ b ≤ c => ⟨le_trans le_sup_left h, le_trans le_sup_right h⟩,
fun ⟨h₁, h₂⟩ => sup_le h₁ h₂⟩
#align sup_le_iff sup_le_iff
@[simp]
theorem sup_eq_left : a ⊔ b = a ↔ b ≤ a :=
le_antisymm_iff.trans <| by simp [le_rfl]
#align sup_eq_left sup_eq_left
@[simp]
theorem sup_eq_right : a ⊔ b = b ↔ a ≤ b :=
le_antisymm_iff.trans <| by simp [le_rfl]
#align sup_eq_right sup_eq_right
@[simp]
theorem left_eq_sup : a = a ⊔ b ↔ b ≤ a :=
eq_comm.trans sup_eq_left
#align left_eq_sup left_eq_sup
@[simp]
theorem right_eq_sup : b = a ⊔ b ↔ a ≤ b :=
eq_comm.trans sup_eq_right
#align right_eq_sup right_eq_sup
alias ⟨_, sup_of_le_left⟩ := sup_eq_left
#align sup_of_le_left sup_of_le_left
alias ⟨le_of_sup_eq, sup_of_le_right⟩ := sup_eq_right
#align sup_of_le_right sup_of_le_right
#align le_of_sup_eq le_of_sup_eq
attribute [simp] sup_of_le_left sup_of_le_right
@[simp]
theorem left_lt_sup : a < a ⊔ b ↔ ¬b ≤ a :=
le_sup_left.lt_iff_ne.trans <| not_congr left_eq_sup
#align left_lt_sup left_lt_sup
@[simp]
theorem right_lt_sup : b < a ⊔ b ↔ ¬a ≤ b :=
le_sup_right.lt_iff_ne.trans <| not_congr right_eq_sup
#align right_lt_sup right_lt_sup
theorem left_or_right_lt_sup (h : a ≠ b) : a < a ⊔ b ∨ b < a ⊔ b :=
h.not_le_or_not_le.symm.imp left_lt_sup.2 right_lt_sup.2
#align left_or_right_lt_sup left_or_right_lt_sup
theorem le_iff_exists_sup : a ≤ b ↔ ∃ c, b = a ⊔ c := by
constructor
· intro h
exact ⟨b, (sup_eq_right.mpr h).symm⟩
· rintro ⟨c, rfl : _ = _ ⊔ _⟩
exact le_sup_left
#align le_iff_exists_sup le_iff_exists_sup
@[gcongr]
theorem sup_le_sup (h₁ : a ≤ b) (h₂ : c ≤ d) : a ⊔ c ≤ b ⊔ d :=
sup_le (le_sup_of_le_left h₁) (le_sup_of_le_right h₂)
#align sup_le_sup sup_le_sup
@[gcongr]
theorem sup_le_sup_left (h₁ : a ≤ b) (c) : c ⊔ a ≤ c ⊔ b :=
sup_le_sup le_rfl h₁
#align sup_le_sup_left sup_le_sup_left
@[gcongr]
theorem sup_le_sup_right (h₁ : a ≤ b) (c) : a ⊔ c ≤ b ⊔ c :=
sup_le_sup h₁ le_rfl
#align sup_le_sup_right sup_le_sup_right
theorem sup_idem (a : α) : a ⊔ a = a := by simp
#align sup_idem sup_idem
instance : Std.IdempotentOp (α := α) (· ⊔ ·) := ⟨sup_idem⟩
theorem sup_comm (a b : α) : a ⊔ b = b ⊔ a := by apply le_antisymm <;> simp
#align sup_comm sup_comm
instance : Std.Commutative (α := α) (· ⊔ ·) := ⟨sup_comm⟩
theorem sup_assoc (a b c : α) : a ⊔ b ⊔ c = a ⊔ (b ⊔ c) :=
eq_of_forall_ge_iff fun x => by simp only [sup_le_iff]; rw [and_assoc]
#align sup_assoc sup_assoc
instance : Std.Associative (α := α) (· ⊔ ·) := ⟨sup_assoc⟩
theorem sup_left_right_swap (a b c : α) : a ⊔ b ⊔ c = c ⊔ b ⊔ a := by
rw [sup_comm, sup_comm a, sup_assoc]
#align sup_left_right_swap sup_left_right_swap
theorem sup_left_idem (a b : α) : a ⊔ (a ⊔ b) = a ⊔ b := by simp
#align sup_left_idem sup_left_idem
theorem sup_right_idem (a b : α) : a ⊔ b ⊔ b = a ⊔ b := by simp
#align sup_right_idem sup_right_idem
theorem sup_left_comm (a b c : α) : a ⊔ (b ⊔ c) = b ⊔ (a ⊔ c) := by
rw [← sup_assoc, ← sup_assoc, @sup_comm α _ a]
#align sup_left_comm sup_left_comm
theorem sup_right_comm (a b c : α) : a ⊔ b ⊔ c = a ⊔ c ⊔ b := by
rw [sup_assoc, sup_assoc, sup_comm b]
#align sup_right_comm sup_right_comm
theorem sup_sup_sup_comm (a b c d : α) : a ⊔ b ⊔ (c ⊔ d) = a ⊔ c ⊔ (b ⊔ d) := by
rw [sup_assoc, sup_left_comm b, ← sup_assoc]
#align sup_sup_sup_comm sup_sup_sup_comm
theorem sup_sup_distrib_left (a b c : α) : a ⊔ (b ⊔ c) = a ⊔ b ⊔ (a ⊔ c) := by
rw [sup_sup_sup_comm, sup_idem]
#align sup_sup_distrib_left sup_sup_distrib_left
theorem sup_sup_distrib_right (a b c : α) : a ⊔ b ⊔ c = a ⊔ c ⊔ (b ⊔ c) := by
rw [sup_sup_sup_comm, sup_idem]
#align sup_sup_distrib_right sup_sup_distrib_right
theorem sup_congr_left (hb : b ≤ a ⊔ c) (hc : c ≤ a ⊔ b) : a ⊔ b = a ⊔ c :=
(sup_le le_sup_left hb).antisymm <| sup_le le_sup_left hc
#align sup_congr_left sup_congr_left
theorem sup_congr_right (ha : a ≤ b ⊔ c) (hb : b ≤ a ⊔ c) : a ⊔ c = b ⊔ c :=
(sup_le ha le_sup_right).antisymm <| sup_le hb le_sup_right
#align sup_congr_right sup_congr_right
theorem sup_eq_sup_iff_left : a ⊔ b = a ⊔ c ↔ b ≤ a ⊔ c ∧ c ≤ a ⊔ b :=
⟨fun h => ⟨h ▸ le_sup_right, h.symm ▸ le_sup_right⟩, fun h => sup_congr_left h.1 h.2⟩
#align sup_eq_sup_iff_left sup_eq_sup_iff_left
theorem sup_eq_sup_iff_right : a ⊔ c = b ⊔ c ↔ a ≤ b ⊔ c ∧ b ≤ a ⊔ c :=
⟨fun h => ⟨h ▸ le_sup_left, h.symm ▸ le_sup_left⟩, fun h => sup_congr_right h.1 h.2⟩
#align sup_eq_sup_iff_right sup_eq_sup_iff_right
theorem Ne.lt_sup_or_lt_sup (hab : a ≠ b) : a < a ⊔ b ∨ b < a ⊔ b :=
hab.symm.not_le_or_not_le.imp left_lt_sup.2 right_lt_sup.2
#align ne.lt_sup_or_lt_sup Ne.lt_sup_or_lt_sup
/-- If `f` is monotone, `g` is antitone, and `f ≤ g`, then for all `a`, `b` we have `f a ≤ g b`. -/
theorem Monotone.forall_le_of_antitone {β : Type*} [Preorder β] {f g : α → β} (hf : Monotone f)
(hg : Antitone g) (h : f ≤ g) (m n : α) : f m ≤ g n :=
calc
f m ≤ f (m ⊔ n) := hf le_sup_left
_ ≤ g (m ⊔ n) := h _
_ ≤ g n := hg le_sup_right
#align monotone.forall_le_of_antitone Monotone.forall_le_of_antitone
theorem SemilatticeSup.ext_sup {α} {A B : SemilatticeSup α}
(H : ∀ x y : α, (haveI := A; x ≤ y) ↔ x ≤ y)
(x y : α) :
(haveI := A; x ⊔ y) = x ⊔ y :=
eq_of_forall_ge_iff fun c => by simp only [sup_le_iff]; rw [← H, @sup_le_iff α A, H, H]
#align semilattice_sup.ext_sup SemilatticeSup.ext_sup
theorem SemilatticeSup.ext {α} {A B : SemilatticeSup α}
(H : ∀ x y : α, (haveI := A; x ≤ y) ↔ x ≤ y) :
A = B := by
have ss : A.toSup = B.toSup := by ext; apply SemilatticeSup.ext_sup H
cases A
cases B
cases PartialOrder.ext H
congr
#align semilattice_sup.ext SemilatticeSup.ext
theorem ite_le_sup (s s' : α) (P : Prop) [Decidable P] : ite P s s' ≤ s ⊔ s' :=
if h : P then (if_pos h).trans_le le_sup_left else (if_neg h).trans_le le_sup_right
#align ite_le_sup ite_le_sup
end SemilatticeSup
/-!
### Meet-semilattices
-/
/-- A `SemilatticeInf` is a meet-semilattice, that is, a partial order
with a meet (a.k.a. glb / greatest lower bound, inf / infimum) operation
`⊓` which is the greatest element smaller than both factors. -/
class SemilatticeInf (α : Type u) extends Inf α, PartialOrder α where
/-- The infimum is a lower bound on the first argument -/
protected inf_le_left : ∀ a b : α, a ⊓ b ≤ a
/-- The infimum is a lower bound on the second argument -/
protected inf_le_right : ∀ a b : α, a ⊓ b ≤ b
/-- The infimum is the *greatest* lower bound -/
protected le_inf : ∀ a b c : α, a ≤ b → a ≤ c → a ≤ b ⊓ c
#align semilattice_inf SemilatticeInf
instance OrderDual.instSemilatticeSup (α) [SemilatticeInf α] : SemilatticeSup αᵒᵈ where
__ := inferInstanceAs (PartialOrder αᵒᵈ)
__ := inferInstanceAs (Sup αᵒᵈ)
le_sup_left := @SemilatticeInf.inf_le_left α _
le_sup_right := @SemilatticeInf.inf_le_right α _
sup_le := fun _ _ _ hca hcb => @SemilatticeInf.le_inf α _ _ _ _ hca hcb
instance OrderDual.instSemilatticeInf (α) [SemilatticeSup α] : SemilatticeInf αᵒᵈ where
__ := inferInstanceAs (PartialOrder αᵒᵈ)
__ := inferInstanceAs (Inf αᵒᵈ)
inf_le_left := @le_sup_left α _
inf_le_right := @le_sup_right α _
le_inf := fun _ _ _ hca hcb => @sup_le α _ _ _ _ hca hcb
theorem SemilatticeSup.dual_dual (α : Type*) [H : SemilatticeSup α] :
OrderDual.instSemilatticeSup αᵒᵈ = H :=
SemilatticeSup.ext fun _ _ => Iff.rfl
#align semilattice_sup.dual_dual SemilatticeSup.dual_dual
section SemilatticeInf
variable [SemilatticeInf α] {a b c d : α}
@[simp]
theorem inf_le_left : a ⊓ b ≤ a :=
SemilatticeInf.inf_le_left a b
#align inf_le_left inf_le_left
#align inf_le_left' inf_le_left
@[deprecated (since := "2024-06-04")] alias inf_le_left' := inf_le_left
@[simp]
theorem inf_le_right : a ⊓ b ≤ b :=
SemilatticeInf.inf_le_right a b
#align inf_le_right inf_le_right
#align inf_le_right' inf_le_right
@[deprecated (since := "2024-06-04")] alias inf_le_right' := inf_le_right
theorem le_inf : a ≤ b → a ≤ c → a ≤ b ⊓ c :=
SemilatticeInf.le_inf a b c
#align le_inf le_inf
theorem inf_le_of_left_le (h : a ≤ c) : a ⊓ b ≤ c :=
le_trans inf_le_left h
#align inf_le_of_left_le inf_le_of_left_le
theorem inf_le_of_right_le (h : b ≤ c) : a ⊓ b ≤ c :=
le_trans inf_le_right h
#align inf_le_of_right_le inf_le_of_right_le
theorem inf_lt_of_left_lt (h : a < c) : a ⊓ b < c :=
lt_of_le_of_lt inf_le_left h
#align inf_lt_of_left_lt inf_lt_of_left_lt
theorem inf_lt_of_right_lt (h : b < c) : a ⊓ b < c :=
lt_of_le_of_lt inf_le_right h
#align inf_lt_of_right_lt inf_lt_of_right_lt
@[simp]
theorem le_inf_iff : a ≤ b ⊓ c ↔ a ≤ b ∧ a ≤ c :=
@sup_le_iff αᵒᵈ _ _ _ _
#align le_inf_iff le_inf_iff
@[simp]
theorem inf_eq_left : a ⊓ b = a ↔ a ≤ b :=
le_antisymm_iff.trans <| by simp [le_rfl]
#align inf_eq_left inf_eq_left
@[simp]
theorem inf_eq_right : a ⊓ b = b ↔ b ≤ a :=
le_antisymm_iff.trans <| by simp [le_rfl]
#align inf_eq_right inf_eq_right
@[simp]
theorem left_eq_inf : a = a ⊓ b ↔ a ≤ b :=
eq_comm.trans inf_eq_left
#align left_eq_inf left_eq_inf
@[simp]
theorem right_eq_inf : b = a ⊓ b ↔ b ≤ a :=
eq_comm.trans inf_eq_right
#align right_eq_inf right_eq_inf
alias ⟨le_of_inf_eq, inf_of_le_left⟩ := inf_eq_left
#align inf_of_le_left inf_of_le_left
#align le_of_inf_eq le_of_inf_eq
alias ⟨_, inf_of_le_right⟩ := inf_eq_right
#align inf_of_le_right inf_of_le_right
attribute [simp] inf_of_le_left inf_of_le_right
@[simp]
theorem inf_lt_left : a ⊓ b < a ↔ ¬a ≤ b :=
@left_lt_sup αᵒᵈ _ _ _
#align inf_lt_left inf_lt_left
@[simp]
theorem inf_lt_right : a ⊓ b < b ↔ ¬b ≤ a :=
@right_lt_sup αᵒᵈ _ _ _
#align inf_lt_right inf_lt_right
theorem inf_lt_left_or_right (h : a ≠ b) : a ⊓ b < a ∨ a ⊓ b < b :=
@left_or_right_lt_sup αᵒᵈ _ _ _ h
#align inf_lt_left_or_right inf_lt_left_or_right
@[gcongr]
theorem inf_le_inf (h₁ : a ≤ b) (h₂ : c ≤ d) : a ⊓ c ≤ b ⊓ d :=
@sup_le_sup αᵒᵈ _ _ _ _ _ h₁ h₂
#align inf_le_inf inf_le_inf
@[gcongr]
theorem inf_le_inf_right (a : α) {b c : α} (h : b ≤ c) : b ⊓ a ≤ c ⊓ a :=
inf_le_inf h le_rfl
#align inf_le_inf_right inf_le_inf_right
@[gcongr]
theorem inf_le_inf_left (a : α) {b c : α} (h : b ≤ c) : a ⊓ b ≤ a ⊓ c :=
inf_le_inf le_rfl h
#align inf_le_inf_left inf_le_inf_left
theorem inf_idem (a : α) : a ⊓ a = a := by simp
#align inf_idem inf_idem
instance : Std.IdempotentOp (α := α) (· ⊓ ·) := ⟨inf_idem⟩
theorem inf_comm (a b : α) : a ⊓ b = b ⊓ a := @sup_comm αᵒᵈ _ _ _
#align inf_comm inf_comm
instance : Std.Commutative (α := α) (· ⊓ ·) := ⟨inf_comm⟩
theorem inf_assoc (a b c : α) : a ⊓ b ⊓ c = a ⊓ (b ⊓ c) := @sup_assoc αᵒᵈ _ _ _ _
#align inf_assoc inf_assoc
instance : Std.Associative (α := α) (· ⊓ ·) := ⟨inf_assoc⟩
theorem inf_left_right_swap (a b c : α) : a ⊓ b ⊓ c = c ⊓ b ⊓ a :=
@sup_left_right_swap αᵒᵈ _ _ _ _
#align inf_left_right_swap inf_left_right_swap
theorem inf_left_idem (a b : α) : a ⊓ (a ⊓ b) = a ⊓ b := by simp
#align inf_left_idem inf_left_idem
theorem inf_right_idem (a b : α) : a ⊓ b ⊓ b = a ⊓ b := by simp
#align inf_right_idem inf_right_idem
theorem inf_left_comm (a b c : α) : a ⊓ (b ⊓ c) = b ⊓ (a ⊓ c) :=
@sup_left_comm αᵒᵈ _ a b c
#align inf_left_comm inf_left_comm
theorem inf_right_comm (a b c : α) : a ⊓ b ⊓ c = a ⊓ c ⊓ b :=
@sup_right_comm αᵒᵈ _ a b c
#align inf_right_comm inf_right_comm
theorem inf_inf_inf_comm (a b c d : α) : a ⊓ b ⊓ (c ⊓ d) = a ⊓ c ⊓ (b ⊓ d) :=
@sup_sup_sup_comm αᵒᵈ _ _ _ _ _
#align inf_inf_inf_comm inf_inf_inf_comm
theorem inf_inf_distrib_left (a b c : α) : a ⊓ (b ⊓ c) = a ⊓ b ⊓ (a ⊓ c) :=
@sup_sup_distrib_left αᵒᵈ _ _ _ _
#align inf_inf_distrib_left inf_inf_distrib_left
theorem inf_inf_distrib_right (a b c : α) : a ⊓ b ⊓ c = a ⊓ c ⊓ (b ⊓ c) :=
@sup_sup_distrib_right αᵒᵈ _ _ _ _
#align inf_inf_distrib_right inf_inf_distrib_right
theorem inf_congr_left (hb : a ⊓ c ≤ b) (hc : a ⊓ b ≤ c) : a ⊓ b = a ⊓ c :=
@sup_congr_left αᵒᵈ _ _ _ _ hb hc
#align inf_congr_left inf_congr_left
theorem inf_congr_right (h1 : b ⊓ c ≤ a) (h2 : a ⊓ c ≤ b) : a ⊓ c = b ⊓ c :=
@sup_congr_right αᵒᵈ _ _ _ _ h1 h2
#align inf_congr_right inf_congr_right
theorem inf_eq_inf_iff_left : a ⊓ b = a ⊓ c ↔ a ⊓ c ≤ b ∧ a ⊓ b ≤ c :=
@sup_eq_sup_iff_left αᵒᵈ _ _ _ _
#align inf_eq_inf_iff_left inf_eq_inf_iff_left
theorem inf_eq_inf_iff_right : a ⊓ c = b ⊓ c ↔ b ⊓ c ≤ a ∧ a ⊓ c ≤ b :=
@sup_eq_sup_iff_right αᵒᵈ _ _ _ _
#align inf_eq_inf_iff_right inf_eq_inf_iff_right
theorem Ne.inf_lt_or_inf_lt : a ≠ b → a ⊓ b < a ∨ a ⊓ b < b :=
@Ne.lt_sup_or_lt_sup αᵒᵈ _ _ _
#align ne.inf_lt_or_inf_lt Ne.inf_lt_or_inf_lt
theorem SemilatticeInf.ext_inf {α} {A B : SemilatticeInf α}
(H : ∀ x y : α, (haveI := A; x ≤ y) ↔ x ≤ y)
(x y : α) :
(haveI := A; x ⊓ y) = x ⊓ y :=
eq_of_forall_le_iff fun c => by simp only [le_inf_iff]; rw [← H, @le_inf_iff α A, H, H]
#align semilattice_inf.ext_inf SemilatticeInf.ext_inf
theorem SemilatticeInf.ext {α} {A B : SemilatticeInf α}
(H : ∀ x y : α, (haveI := A; x ≤ y) ↔ x ≤ y) :
A = B := by
have ss : A.toInf = B.toInf := by ext; apply SemilatticeInf.ext_inf H
cases A
cases B
cases PartialOrder.ext H
congr
#align semilattice_inf.ext SemilatticeInf.ext
theorem SemilatticeInf.dual_dual (α : Type*) [H : SemilatticeInf α] :
OrderDual.instSemilatticeInf αᵒᵈ = H :=
SemilatticeInf.ext fun _ _ => Iff.rfl
#align semilattice_inf.dual_dual SemilatticeInf.dual_dual
theorem inf_le_ite (s s' : α) (P : Prop) [Decidable P] : s ⊓ s' ≤ ite P s s' :=
@ite_le_sup αᵒᵈ _ _ _ _ _
#align inf_le_ite inf_le_ite
end SemilatticeInf
/--
A type with a commutative, associative and idempotent binary `inf` operation has the structure of a
meet-semilattice.
The partial order is defined so that `a ≤ b` unfolds to `b ⊓ a = a`; cf. `inf_eq_right`.
-/
def SemilatticeInf.mk' {α : Type*} [Inf α] (inf_comm : ∀ a b : α, a ⊓ b = b ⊓ a)
(inf_assoc : ∀ a b c : α, a ⊓ b ⊓ c = a ⊓ (b ⊓ c)) (inf_idem : ∀ a : α, a ⊓ a = a) :
SemilatticeInf α := by
haveI : SemilatticeSup αᵒᵈ := SemilatticeSup.mk' inf_comm inf_assoc inf_idem
haveI i := OrderDual.instSemilatticeInf αᵒᵈ
exact i
#align semilattice_inf.mk' SemilatticeInf.mk'
/-!
### Lattices
-/
/-- A lattice is a join-semilattice which is also a meet-semilattice. -/
class Lattice (α : Type u) extends SemilatticeSup α, SemilatticeInf α
#align lattice Lattice
instance OrderDual.instLattice (α) [Lattice α] : Lattice αᵒᵈ where
__ := OrderDual.instSemilatticeSup α
__ := OrderDual.instSemilatticeInf α
/-- The partial orders from `SemilatticeSup_mk'` and `SemilatticeInf_mk'` agree
if `sup` and `inf` satisfy the lattice absorption laws `sup_inf_self` (`a ⊔ a ⊓ b = a`)
and `inf_sup_self` (`a ⊓ (a ⊔ b) = a`). -/
theorem semilatticeSup_mk'_partialOrder_eq_semilatticeInf_mk'_partialOrder
{α : Type*} [Sup α] [Inf α]
(sup_comm : ∀ a b : α, a ⊔ b = b ⊔ a) (sup_assoc : ∀ a b c : α, a ⊔ b ⊔ c = a ⊔ (b ⊔ c))
(sup_idem : ∀ a : α, a ⊔ a = a) (inf_comm : ∀ a b : α, a ⊓ b = b ⊓ a)
(inf_assoc : ∀ a b c : α, a ⊓ b ⊓ c = a ⊓ (b ⊓ c)) (inf_idem : ∀ a : α, a ⊓ a = a)
(sup_inf_self : ∀ a b : α, a ⊔ a ⊓ b = a) (inf_sup_self : ∀ a b : α, a ⊓ (a ⊔ b) = a) :
@SemilatticeSup.toPartialOrder _ (SemilatticeSup.mk' sup_comm sup_assoc sup_idem) =
@SemilatticeInf.toPartialOrder _ (SemilatticeInf.mk' inf_comm inf_assoc inf_idem) :=
PartialOrder.ext fun a b =>
show a ⊔ b = b ↔ b ⊓ a = a from
⟨fun h => by rw [← h, inf_comm, inf_sup_self], fun h => by rw [← h, sup_comm, sup_inf_self]⟩
#align semilattice_sup_mk'_partial_order_eq_semilattice_inf_mk'_partial_order semilatticeSup_mk'_partialOrder_eq_semilatticeInf_mk'_partialOrder
/-- A type with a pair of commutative and associative binary operations which satisfy two absorption
laws relating the two operations has the structure of a lattice.
The partial order is defined so that `a ≤ b` unfolds to `a ⊔ b = b`; cf. `sup_eq_right`.
-/
def Lattice.mk' {α : Type*} [Sup α] [Inf α] (sup_comm : ∀ a b : α, a ⊔ b = b ⊔ a)
(sup_assoc : ∀ a b c : α, a ⊔ b ⊔ c = a ⊔ (b ⊔ c)) (inf_comm : ∀ a b : α, a ⊓ b = b ⊓ a)
(inf_assoc : ∀ a b c : α, a ⊓ b ⊓ c = a ⊓ (b ⊓ c)) (sup_inf_self : ∀ a b : α, a ⊔ a ⊓ b = a)
(inf_sup_self : ∀ a b : α, a ⊓ (a ⊔ b) = a) : Lattice α :=
have sup_idem : ∀ b : α, b ⊔ b = b := fun b =>
calc
b ⊔ b = b ⊔ b ⊓ (b ⊔ b) := by rw [inf_sup_self]
_ = b := by rw [sup_inf_self]
have inf_idem : ∀ b : α, b ⊓ b = b := fun b =>
calc
b ⊓ b = b ⊓ (b ⊔ b ⊓ b) := by rw [sup_inf_self]
_ = b := by rw [inf_sup_self]
let semilatt_inf_inst := SemilatticeInf.mk' inf_comm inf_assoc inf_idem
let semilatt_sup_inst := SemilatticeSup.mk' sup_comm sup_assoc sup_idem
have partial_order_eq : @SemilatticeSup.toPartialOrder _ semilatt_sup_inst =
@SemilatticeInf.toPartialOrder _ semilatt_inf_inst :=
semilatticeSup_mk'_partialOrder_eq_semilatticeInf_mk'_partialOrder _ _ _ _ _ _
sup_inf_self inf_sup_self
{ semilatt_sup_inst, semilatt_inf_inst with
inf_le_left := fun a b => by
rw [partial_order_eq]
apply inf_le_left,
inf_le_right := fun a b => by
rw [partial_order_eq]
apply inf_le_right,
le_inf := fun a b c => by
rw [partial_order_eq]
apply le_inf }
#align lattice.mk' Lattice.mk'
section Lattice
variable [Lattice α] {a b c d : α}
theorem inf_le_sup : a ⊓ b ≤ a ⊔ b :=
inf_le_left.trans le_sup_left
#align inf_le_sup inf_le_sup
theorem sup_le_inf : a ⊔ b ≤ a ⊓ b ↔ a = b := by simp [le_antisymm_iff, and_comm]
#align sup_le_inf sup_le_inf
@[simp] lemma inf_eq_sup : a ⊓ b = a ⊔ b ↔ a = b := by rw [← inf_le_sup.ge_iff_eq, sup_le_inf]
#align inf_eq_sup inf_eq_sup
@[simp] lemma sup_eq_inf : a ⊔ b = a ⊓ b ↔ a = b := eq_comm.trans inf_eq_sup
#align sup_eq_inf sup_eq_inf
@[simp] lemma inf_lt_sup : a ⊓ b < a ⊔ b ↔ a ≠ b := by rw [inf_le_sup.lt_iff_ne, Ne, inf_eq_sup]
#align inf_lt_sup inf_lt_sup
lemma inf_eq_and_sup_eq_iff : a ⊓ b = c ∧ a ⊔ b = c ↔ a = c ∧ b = c := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain rfl := sup_eq_inf.1 (h.2.trans h.1.symm)
simpa using h
· rintro ⟨rfl, rfl⟩
exact ⟨inf_idem _, sup_idem _⟩
#align inf_eq_and_sup_eq_iff inf_eq_and_sup_eq_iff
/-!
#### Distributivity laws
-/
-- TODO: better names?
theorem sup_inf_le : a ⊔ b ⊓ c ≤ (a ⊔ b) ⊓ (a ⊔ c) :=
le_inf (sup_le_sup_left inf_le_left _) (sup_le_sup_left inf_le_right _)
#align sup_inf_le sup_inf_le
theorem le_inf_sup : a ⊓ b ⊔ a ⊓ c ≤ a ⊓ (b ⊔ c) :=
sup_le (inf_le_inf_left _ le_sup_left) (inf_le_inf_left _ le_sup_right)
#align le_inf_sup le_inf_sup
theorem inf_sup_self : a ⊓ (a ⊔ b) = a := by simp
#align inf_sup_self inf_sup_self
theorem sup_inf_self : a ⊔ a ⊓ b = a := by simp
#align sup_inf_self sup_inf_self
theorem sup_eq_iff_inf_eq : a ⊔ b = b ↔ a ⊓ b = a := by rw [sup_eq_right, ← inf_eq_left]
#align sup_eq_iff_inf_eq sup_eq_iff_inf_eq
theorem Lattice.ext {α} {A B : Lattice α} (H : ∀ x y : α, (haveI := A; x ≤ y) ↔ x ≤ y) :
A = B := by
cases A
cases B
cases SemilatticeSup.ext H
cases SemilatticeInf.ext H
congr
#align lattice.ext Lattice.ext
end Lattice
/-!
### Distributive lattices
-/
/-- A distributive lattice is a lattice that satisfies any of four
equivalent distributive properties (of `sup` over `inf` or `inf` over `sup`,
on the left or right).
The definition here chooses `le_sup_inf`: `(x ⊔ y) ⊓ (x ⊔ z) ≤ x ⊔ (y ⊓ z)`. To prove distributivity
from the dual law, use `DistribLattice.of_inf_sup_le`.
A classic example of a distributive lattice
is the lattice of subsets of a set, and in fact this example is
generic in the sense that every distributive lattice is realizable
as a sublattice of a powerset lattice. -/
class DistribLattice (α) extends Lattice α where
/-- The infimum distributes over the supremum -/
protected le_sup_inf : ∀ x y z : α, (x ⊔ y) ⊓ (x ⊔ z) ≤ x ⊔ y ⊓ z
#align distrib_lattice DistribLattice
section DistribLattice
variable [DistribLattice α] {x y z : α}
theorem le_sup_inf : ∀ {x y z : α}, (x ⊔ y) ⊓ (x ⊔ z) ≤ x ⊔ y ⊓ z :=
fun {x y z} => DistribLattice.le_sup_inf x y z
#align le_sup_inf le_sup_inf
theorem sup_inf_left (a b c : α) : a ⊔ b ⊓ c = (a ⊔ b) ⊓ (a ⊔ c) :=
le_antisymm sup_inf_le le_sup_inf
#align sup_inf_left sup_inf_left
theorem sup_inf_right (a b c : α) : a ⊓ b ⊔ c = (a ⊔ c) ⊓ (b ⊔ c) := by
simp only [sup_inf_left, sup_comm _ c, eq_self_iff_true]
#align sup_inf_right sup_inf_right
theorem inf_sup_left (a b c : α) : a ⊓ (b ⊔ c) = a ⊓ b ⊔ a ⊓ c :=
calc
a ⊓ (b ⊔ c) = a ⊓ (a ⊔ c) ⊓ (b ⊔ c) := by rw [inf_sup_self]
_ = a ⊓ (a ⊓ b ⊔ c) := by simp only [inf_assoc, sup_inf_right, eq_self_iff_true]
_ = (a ⊔ a ⊓ b) ⊓ (a ⊓ b ⊔ c) := by rw [sup_inf_self]
_ = (a ⊓ b ⊔ a) ⊓ (a ⊓ b ⊔ c) := by rw [sup_comm]
_ = a ⊓ b ⊔ a ⊓ c := by rw [sup_inf_left]
#align inf_sup_left inf_sup_left
instance OrderDual.instDistribLattice (α : Type*) [DistribLattice α] : DistribLattice αᵒᵈ where
__ := inferInstanceAs (Lattice αᵒᵈ)
le_sup_inf _ _ _ := (inf_sup_left _ _ _).le
theorem inf_sup_right (a b c : α) : (a ⊔ b) ⊓ c = a ⊓ c ⊔ b ⊓ c := by
simp only [inf_sup_left, inf_comm _ c, eq_self_iff_true]
#align inf_sup_right inf_sup_right
theorem le_of_inf_le_sup_le (h₁ : x ⊓ z ≤ y ⊓ z) (h₂ : x ⊔ z ≤ y ⊔ z) : x ≤ y :=
calc
x ≤ y ⊓ z ⊔ x := le_sup_right
_ = (y ⊔ x) ⊓ (x ⊔ z) := by rw [sup_inf_right, sup_comm x]
_ ≤ (y ⊔ x) ⊓ (y ⊔ z) := inf_le_inf_left _ h₂
_ = y ⊔ x ⊓ z := by rw [← sup_inf_left]
_ ≤ y ⊔ y ⊓ z := sup_le_sup_left h₁ _
_ ≤ _ := sup_le (le_refl y) inf_le_left
#align le_of_inf_le_sup_le le_of_inf_le_sup_le
theorem eq_of_inf_eq_sup_eq {a b c : α} (h₁ : b ⊓ a = c ⊓ a) (h₂ : b ⊔ a = c ⊔ a) : b = c :=
le_antisymm (le_of_inf_le_sup_le (le_of_eq h₁) (le_of_eq h₂))
(le_of_inf_le_sup_le (le_of_eq h₁.symm) (le_of_eq h₂.symm))
#align eq_of_inf_eq_sup_eq eq_of_inf_eq_sup_eq
end DistribLattice
-- See note [reducible non-instances]
/-- Prove distributivity of an existing lattice from the dual distributive law. -/
abbrev DistribLattice.ofInfSupLe
[Lattice α] (inf_sup_le : ∀ a b c : α, a ⊓ (b ⊔ c) ≤ a ⊓ b ⊔ a ⊓ c) : DistribLattice α where
le_sup_inf := (@OrderDual.instDistribLattice αᵒᵈ {inferInstanceAs (Lattice αᵒᵈ) with
le_sup_inf := inf_sup_le}).le_sup_inf
#align distrib_lattice.of_inf_sup_le DistribLattice.ofInfSupLe
/-!
### Lattices derived from linear orders
-/
-- see Note [lower instance priority]
instance (priority := 100) LinearOrder.toLattice {α : Type u} [o : LinearOrder α] : Lattice α where
__ := o
sup := max
le_sup_left := le_max_left; le_sup_right := le_max_right; sup_le _ _ _ := max_le
inf := min
inf_le_left := min_le_left; inf_le_right := min_le_right; le_inf _ _ _ := le_min
section LinearOrder
variable [LinearOrder α] {a b c d : α}
theorem sup_eq_max : a ⊔ b = max a b :=
rfl
#align sup_eq_max sup_eq_max
theorem inf_eq_min : a ⊓ b = min a b :=
rfl
#align inf_eq_min inf_eq_min
theorem sup_ind (a b : α) {p : α → Prop} (ha : p a) (hb : p b) : p (a ⊔ b) :=
(IsTotal.total a b).elim (fun h : a ≤ b => by rwa [sup_eq_right.2 h]) fun h => by
rwa [sup_eq_left.2 h]
#align sup_ind sup_ind
@[simp]
| Mathlib/Order/Lattice.lean | 799 | 804 | theorem le_sup_iff : a ≤ b ⊔ c ↔ a ≤ b ∨ a ≤ c := by |
exact ⟨fun h =>
(le_total c b).imp
(fun bc => by rwa [sup_eq_left.2 bc] at h)
(fun bc => by rwa [sup_eq_right.2 bc] at h),
fun h => h.elim le_sup_of_le_left le_sup_of_le_right⟩
|
/-
Copyright (c) 2021 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker, Bhavik Mehta
-/
import Mathlib.Analysis.Calculus.Deriv.Support
import Mathlib.Analysis.SpecialFunctions.Pow.Deriv
import Mathlib.MeasureTheory.Integral.FundThmCalculus
import Mathlib.Order.Filter.AtTopBot
import Mathlib.MeasureTheory.Function.Jacobian
import Mathlib.MeasureTheory.Measure.Haar.NormedSpace
import Mathlib.MeasureTheory.Measure.Haar.Unique
#align_import measure_theory.integral.integral_eq_improper from "leanprover-community/mathlib"@"b84aee748341da06a6d78491367e2c0e9f15e8a5"
/-!
# Links between an integral and its "improper" version
In its current state, mathlib only knows how to talk about definite ("proper") integrals,
in the sense that it treats integrals over `[x, +∞)` the same as it treats integrals over
`[y, z]`. For example, the integral over `[1, +∞)` is **not** defined to be the limit of
the integral over `[1, x]` as `x` tends to `+∞`, which is known as an **improper integral**.
Indeed, the "proper" definition is stronger than the "improper" one. The usual counterexample
is `x ↦ sin(x)/x`, which has an improper integral over `[1, +∞)` but no definite integral.
Although definite integrals have better properties, they are hardly usable when it comes to
computing integrals on unbounded sets, which is much easier using limits. Thus, in this file,
we prove various ways of studying the proper integral by studying the improper one.
## Definitions
The main definition of this file is `MeasureTheory.AECover`. It is a rather technical definition
whose sole purpose is generalizing and factoring proofs. Given an index type `ι`, a countably
generated filter `l` over `ι`, and an `ι`-indexed family `φ` of subsets of a measurable space `α`
equipped with a measure `μ`, one should think of a hypothesis `hφ : MeasureTheory.AECover μ l φ` as
a sufficient condition for being able to interpret `∫ x, f x ∂μ` (if it exists) as the limit of `∫ x
in φ i, f x ∂μ` as `i` tends to `l`.
When using this definition with a measure restricted to a set `s`, which happens fairly often, one
should not try too hard to use a `MeasureTheory.AECover` of subsets of `s`, as it often makes proofs
more complicated than necessary. See for example the proof of
`MeasureTheory.integrableOn_Iic_of_intervalIntegral_norm_tendsto` where we use `(fun x ↦ oi x)` as a
`MeasureTheory.AECover` w.r.t. `μ.restrict (Iic b)`, instead of using `(fun x ↦ Ioc x b)`.
## Main statements
- `MeasureTheory.AECover.lintegral_tendsto_of_countably_generated` : if `φ` is a
`MeasureTheory.AECover μ l`, where `l` is a countably generated filter, and if `f` is a measurable
`ENNReal`-valued function, then `∫⁻ x in φ n, f x ∂μ` tends to `∫⁻ x, f x ∂μ` as `n` tends to `l`
- `MeasureTheory.AECover.integrable_of_integral_norm_tendsto` : if `φ` is a
`MeasureTheory.AECover μ l`, where `l` is a countably generated filter, if `f` is measurable and
integrable on each `φ n`, and if `∫ x in φ n, ‖f x‖ ∂μ` tends to some `I : ℝ` as n tends to `l`,
then `f` is integrable
- `MeasureTheory.AECover.integral_tendsto_of_countably_generated` : if `φ` is a
`MeasureTheory.AECover μ l`, where `l` is a countably generated filter, and if `f` is measurable
and integrable (globally), then `∫ x in φ n, f x ∂μ` tends to `∫ x, f x ∂μ` as `n` tends to `+∞`.
We then specialize these lemmas to various use cases involving intervals, which are frequent
in analysis. In particular,
- `MeasureTheory.integral_Ioi_of_hasDerivAt_of_tendsto` is a version of FTC-2 on the interval
`(a, +∞)`, giving the formula `∫ x in (a, +∞), g' x = l - g a` if `g'` is integrable and
`g` tends to `l` at `+∞`.
- `MeasureTheory.integral_Ioi_of_hasDerivAt_of_nonneg` gives the same result assuming that
`g'` is nonnegative instead of integrable. Its automatic integrability in this context is proved
in `MeasureTheory.integrableOn_Ioi_deriv_of_nonneg`.
- `MeasureTheory.integral_comp_smul_deriv_Ioi` is a version of the change of variables formula
on semi-infinite intervals.
- `MeasureTheory.tendsto_limUnder_of_hasDerivAt_of_integrableOn_Ioi` shows that a function whose
derivative is integrable on `(a, +∞)` has a limit at `+∞`.
- `MeasureTheory.tendsto_zero_of_hasDerivAt_of_integrableOn_Ioi` shows that an integrable function
whose derivative is integrable on `(a, +∞)` tends to `0` at `+∞`.
Versions of these results are also given on the intervals `(-∞, a]` and `(-∞, +∞)`, as well as
the corresponding versions of integration by parts.
-/
open MeasureTheory Filter Set TopologicalSpace
open scoped ENNReal NNReal Topology
namespace MeasureTheory
section AECover
variable {α ι : Type*} [MeasurableSpace α] (μ : Measure α) (l : Filter ι)
/-- A sequence `φ` of subsets of `α` is a `MeasureTheory.AECover` w.r.t. a measure `μ` and a filter
`l` if almost every point (w.r.t. `μ`) of `α` eventually belongs to `φ n` (w.r.t. `l`), and if
each `φ n` is measurable. This definition is a technical way to avoid duplicating a lot of
proofs. It should be thought of as a sufficient condition for being able to interpret
`∫ x, f x ∂μ` (if it exists) as the limit of `∫ x in φ n, f x ∂μ` as `n` tends to `l`.
See for example `MeasureTheory.AECover.lintegral_tendsto_of_countably_generated`,
`MeasureTheory.AECover.integrable_of_integral_norm_tendsto` and
`MeasureTheory.AECover.integral_tendsto_of_countably_generated`. -/
structure AECover (φ : ι → Set α) : Prop where
ae_eventually_mem : ∀ᵐ x ∂μ, ∀ᶠ i in l, x ∈ φ i
protected measurableSet : ∀ i, MeasurableSet <| φ i
#align measure_theory.ae_cover MeasureTheory.AECover
#align measure_theory.ae_cover.ae_eventually_mem MeasureTheory.AECover.ae_eventually_mem
#align measure_theory.ae_cover.measurable MeasureTheory.AECover.measurableSet
variable {μ} {l}
namespace AECover
/-!
## Operations on `AECover`s
Porting note: this is a new section.
-/
/-- Elementwise intersection of two `AECover`s is an `AECover`. -/
theorem inter {φ ψ : ι → Set α} (hφ : AECover μ l φ) (hψ : AECover μ l ψ) :
AECover μ l (fun i ↦ φ i ∩ ψ i) where
ae_eventually_mem := hψ.1.mp <| hφ.1.mono fun _ ↦ Eventually.and
measurableSet _ := (hφ.2 _).inter (hψ.2 _)
theorem superset {φ ψ : ι → Set α} (hφ : AECover μ l φ) (hsub : ∀ i, φ i ⊆ ψ i)
(hmeas : ∀ i, MeasurableSet (ψ i)) : AECover μ l ψ :=
⟨hφ.1.mono fun _x hx ↦ hx.mono fun i hi ↦ hsub i hi, hmeas⟩
theorem mono_ac {ν : Measure α} {φ : ι → Set α} (hφ : AECover μ l φ) (hle : ν ≪ μ) :
AECover ν l φ := ⟨hle hφ.1, hφ.2⟩
theorem mono {ν : Measure α} {φ : ι → Set α} (hφ : AECover μ l φ) (hle : ν ≤ μ) :
AECover ν l φ := hφ.mono_ac hle.absolutelyContinuous
end AECover
section MetricSpace
variable [PseudoMetricSpace α] [OpensMeasurableSpace α]
theorem aecover_ball {x : α} {r : ι → ℝ} (hr : Tendsto r l atTop) :
AECover μ l (fun i ↦ Metric.ball x (r i)) where
measurableSet _ := Metric.isOpen_ball.measurableSet
ae_eventually_mem := by
filter_upwards with y
filter_upwards [hr (Ioi_mem_atTop (dist x y))] with a ha using by simpa [dist_comm] using ha
| Mathlib/MeasureTheory/Integral/IntegralEqImproper.lean | 146 | 151 | theorem aecover_closedBall {x : α} {r : ι → ℝ} (hr : Tendsto r l atTop) :
AECover μ l (fun i ↦ Metric.closedBall x (r i)) where
measurableSet _ := Metric.isClosed_ball.measurableSet
ae_eventually_mem := by |
filter_upwards with y
filter_upwards [hr (Ici_mem_atTop (dist x y))] with a ha using by simpa [dist_comm] using ha
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudryashov
-/
import Mathlib.Analysis.Convex.Combination
import Mathlib.Analysis.Convex.Strict
import Mathlib.Topology.Connected.PathConnected
import Mathlib.Topology.Algebra.Affine
import Mathlib.Topology.Algebra.Module.Basic
#align_import analysis.convex.topology from "leanprover-community/mathlib"@"0e3aacdc98d25e0afe035c452d876d28cbffaa7e"
/-!
# Topological properties of convex sets
We prove the following facts:
* `Convex.interior` : interior of a convex set is convex;
* `Convex.closure` : closure of a convex set is convex;
* `Set.Finite.isCompact_convexHull` : convex hull of a finite set is compact;
* `Set.Finite.isClosed_convexHull` : convex hull of a finite set is closed.
-/
assert_not_exists Norm
open Metric Bornology Set Pointwise Convex
variable {ι 𝕜 E : Type*}
theorem Real.convex_iff_isPreconnected {s : Set ℝ} : Convex ℝ s ↔ IsPreconnected s :=
convex_iff_ordConnected.trans isPreconnected_iff_ordConnected.symm
#align real.convex_iff_is_preconnected Real.convex_iff_isPreconnected
alias ⟨_, IsPreconnected.convex⟩ := Real.convex_iff_isPreconnected
#align is_preconnected.convex IsPreconnected.convex
/-! ### Standard simplex -/
section stdSimplex
variable [Fintype ι]
/-- Every vector in `stdSimplex 𝕜 ι` has `max`-norm at most `1`. -/
theorem stdSimplex_subset_closedBall : stdSimplex ℝ ι ⊆ Metric.closedBall 0 1 := fun f hf ↦ by
rw [Metric.mem_closedBall, dist_pi_le_iff zero_le_one]
intro x
rw [Pi.zero_apply, Real.dist_0_eq_abs, abs_of_nonneg <| hf.1 x]
exact (mem_Icc_of_mem_stdSimplex hf x).2
#align std_simplex_subset_closed_ball stdSimplex_subset_closedBall
variable (ι)
/-- `stdSimplex ℝ ι` is bounded. -/
theorem bounded_stdSimplex : IsBounded (stdSimplex ℝ ι) :=
(Metric.isBounded_iff_subset_closedBall 0).2 ⟨1, stdSimplex_subset_closedBall⟩
#align bounded_std_simplex bounded_stdSimplex
/-- `stdSimplex ℝ ι` is closed. -/
theorem isClosed_stdSimplex : IsClosed (stdSimplex ℝ ι) :=
(stdSimplex_eq_inter ℝ ι).symm ▸
IsClosed.inter (isClosed_iInter fun i => isClosed_le continuous_const (continuous_apply i))
(isClosed_eq (continuous_finset_sum _ fun x _ => continuous_apply x) continuous_const)
#align is_closed_std_simplex isClosed_stdSimplex
/-- `stdSimplex ℝ ι` is compact. -/
theorem isCompact_stdSimplex : IsCompact (stdSimplex ℝ ι) :=
Metric.isCompact_iff_isClosed_bounded.2 ⟨isClosed_stdSimplex ι, bounded_stdSimplex ι⟩
#align is_compact_std_simplex isCompact_stdSimplex
instance stdSimplex.instCompactSpace_coe : CompactSpace ↥(stdSimplex ℝ ι) :=
isCompact_iff_compactSpace.mp <| isCompact_stdSimplex _
/-- The standard one-dimensional simplex in `ℝ² = Fin 2 → ℝ`
is homeomorphic to the unit interval. -/
@[simps! (config := .asFn)]
def stdSimplexHomeomorphUnitInterval : stdSimplex ℝ (Fin 2) ≃ₜ unitInterval where
toEquiv := stdSimplexEquivIcc ℝ
continuous_toFun := .subtype_mk ((continuous_apply 0).comp continuous_subtype_val) _
continuous_invFun := by
apply Continuous.subtype_mk
exact (continuous_pi <| Fin.forall_fin_two.2
⟨continuous_subtype_val, continuous_const.sub continuous_subtype_val⟩)
end stdSimplex
/-! ### Topological vector spaces -/
section TopologicalSpace
variable [LinearOrderedRing 𝕜] [DenselyOrdered 𝕜] [TopologicalSpace 𝕜] [OrderTopology 𝕜]
[AddCommGroup E] [TopologicalSpace E] [ContinuousAdd E] [Module 𝕜 E] [ContinuousSMul 𝕜 E]
{x y : E}
theorem segment_subset_closure_openSegment : [x -[𝕜] y] ⊆ closure (openSegment 𝕜 x y) := by
rw [segment_eq_image, openSegment_eq_image, ← closure_Ioo (zero_ne_one' 𝕜)]
exact image_closure_subset_closure_image (by continuity)
#align segment_subset_closure_open_segment segment_subset_closure_openSegment
end TopologicalSpace
section PseudoMetricSpace
variable [LinearOrderedRing 𝕜] [DenselyOrdered 𝕜] [PseudoMetricSpace 𝕜] [OrderTopology 𝕜]
[ProperSpace 𝕜] [CompactIccSpace 𝕜] [AddCommGroup E] [TopologicalSpace E] [T2Space E]
[ContinuousAdd E] [Module 𝕜 E] [ContinuousSMul 𝕜 E]
@[simp]
theorem closure_openSegment (x y : E) : closure (openSegment 𝕜 x y) = [x -[𝕜] y] := by
rw [segment_eq_image, openSegment_eq_image, ← closure_Ioo (zero_ne_one' 𝕜)]
exact (image_closure_of_isCompact (isBounded_Ioo _ _).isCompact_closure <|
Continuous.continuousOn <| by continuity).symm
#align closure_open_segment closure_openSegment
end PseudoMetricSpace
section ContinuousConstSMul
variable [LinearOrderedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E]
[TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
/-- If `s` is a convex set, then `a • interior s + b • closure s ⊆ interior s` for all `0 < a`,
`0 ≤ b`, `a + b = 1`. See also `Convex.combo_interior_self_subset_interior` for a weaker version. -/
theorem Convex.combo_interior_closure_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) : a • interior s + b • closure s ⊆ interior s :=
interior_smul₀ ha.ne' s ▸
calc
interior (a • s) + b • closure s ⊆ interior (a • s) + closure (b • s) :=
add_subset_add Subset.rfl (smul_closure_subset b s)
_ = interior (a • s) + b • s := by rw [isOpen_interior.add_closure (b • s)]
_ ⊆ interior (a • s + b • s) := subset_interior_add_left
_ ⊆ interior s := interior_mono <| hs.set_combo_subset ha.le hb hab
#align convex.combo_interior_closure_subset_interior Convex.combo_interior_closure_subset_interior
/-- If `s` is a convex set, then `a • interior s + b • s ⊆ interior s` for all `0 < a`, `0 ≤ b`,
`a + b = 1`. See also `Convex.combo_interior_closure_subset_interior` for a stronger version. -/
theorem Convex.combo_interior_self_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) : a • interior s + b • s ⊆ interior s :=
calc
a • interior s + b • s ⊆ a • interior s + b • closure s :=
add_subset_add Subset.rfl <| image_subset _ subset_closure
_ ⊆ interior s := hs.combo_interior_closure_subset_interior ha hb hab
#align convex.combo_interior_self_subset_interior Convex.combo_interior_self_subset_interior
/-- If `s` is a convex set, then `a • closure s + b • interior s ⊆ interior s` for all `0 ≤ a`,
`0 < b`, `a + b = 1`. See also `Convex.combo_self_interior_subset_interior` for a weaker version. -/
theorem Convex.combo_closure_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) : a • closure s + b • interior s ⊆ interior s := by
rw [add_comm]
exact hs.combo_interior_closure_subset_interior hb ha (add_comm a b ▸ hab)
#align convex.combo_closure_interior_subset_interior Convex.combo_closure_interior_subset_interior
/-- If `s` is a convex set, then `a • s + b • interior s ⊆ interior s` for all `0 ≤ a`, `0 < b`,
`a + b = 1`. See also `Convex.combo_closure_interior_subset_interior` for a stronger version. -/
theorem Convex.combo_self_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) : a • s + b • interior s ⊆ interior s := by
rw [add_comm]
exact hs.combo_interior_self_subset_interior hb ha (add_comm a b ▸ hab)
#align convex.combo_self_interior_subset_interior Convex.combo_self_interior_subset_interior
theorem Convex.combo_interior_closure_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ closure s) {a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b)
(hab : a + b = 1) : a • x + b • y ∈ interior s :=
hs.combo_interior_closure_subset_interior ha hb hab <|
add_mem_add (smul_mem_smul_set hx) (smul_mem_smul_set hy)
#align convex.combo_interior_closure_mem_interior Convex.combo_interior_closure_mem_interior
theorem Convex.combo_interior_self_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ s) {a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) :
a • x + b • y ∈ interior s :=
hs.combo_interior_closure_mem_interior hx (subset_closure hy) ha hb hab
#align convex.combo_interior_self_mem_interior Convex.combo_interior_self_mem_interior
theorem Convex.combo_closure_interior_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ closure s) (hy : y ∈ interior s) {a b : 𝕜} (ha : 0 ≤ a) (hb : 0 < b)
(hab : a + b = 1) : a • x + b • y ∈ interior s :=
hs.combo_closure_interior_subset_interior ha hb hab <|
add_mem_add (smul_mem_smul_set hx) (smul_mem_smul_set hy)
#align convex.combo_closure_interior_mem_interior Convex.combo_closure_interior_mem_interior
theorem Convex.combo_self_interior_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ s)
(hy : y ∈ interior s) {a b : 𝕜} (ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) :
a • x + b • y ∈ interior s :=
hs.combo_closure_interior_mem_interior (subset_closure hx) hy ha hb hab
#align convex.combo_self_interior_mem_interior Convex.combo_self_interior_mem_interior
theorem Convex.openSegment_interior_closure_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ closure s) : openSegment 𝕜 x y ⊆ interior s := by
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
exact hs.combo_interior_closure_mem_interior hx hy ha hb.le hab
#align convex.open_segment_interior_closure_subset_interior Convex.openSegment_interior_closure_subset_interior
theorem Convex.openSegment_interior_self_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ s) : openSegment 𝕜 x y ⊆ interior s :=
hs.openSegment_interior_closure_subset_interior hx (subset_closure hy)
#align convex.open_segment_interior_self_subset_interior Convex.openSegment_interior_self_subset_interior
theorem Convex.openSegment_closure_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ closure s) (hy : y ∈ interior s) : openSegment 𝕜 x y ⊆ interior s := by
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
exact hs.combo_closure_interior_mem_interior hx hy ha.le hb hab
#align convex.open_segment_closure_interior_subset_interior Convex.openSegment_closure_interior_subset_interior
theorem Convex.openSegment_self_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ s) (hy : y ∈ interior s) : openSegment 𝕜 x y ⊆ interior s :=
hs.openSegment_closure_interior_subset_interior (subset_closure hx) hy
#align convex.open_segment_self_interior_subset_interior Convex.openSegment_self_interior_subset_interior
/-- If `x ∈ closure s` and `y ∈ interior s`, then the segment `(x, y]` is included in `interior s`.
-/
theorem Convex.add_smul_sub_mem_interior' {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ closure s) (hy : y ∈ interior s) {t : 𝕜} (ht : t ∈ Ioc (0 : 𝕜) 1) :
x + t • (y - x) ∈ interior s := by
simpa only [sub_smul, smul_sub, one_smul, add_sub, add_comm] using
hs.combo_interior_closure_mem_interior hy hx ht.1 (sub_nonneg.mpr ht.2)
(add_sub_cancel _ _)
#align convex.add_smul_sub_mem_interior' Convex.add_smul_sub_mem_interior'
/-- If `x ∈ s` and `y ∈ interior s`, then the segment `(x, y]` is included in `interior s`. -/
theorem Convex.add_smul_sub_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ s)
(hy : y ∈ interior s) {t : 𝕜} (ht : t ∈ Ioc (0 : 𝕜) 1) : x + t • (y - x) ∈ interior s :=
hs.add_smul_sub_mem_interior' (subset_closure hx) hy ht
#align convex.add_smul_sub_mem_interior Convex.add_smul_sub_mem_interior
/-- If `x ∈ closure s` and `x + y ∈ interior s`, then `x + t y ∈ interior s` for `t ∈ (0, 1]`. -/
theorem Convex.add_smul_mem_interior' {s : Set E} (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ closure s)
(hy : x + y ∈ interior s) {t : 𝕜} (ht : t ∈ Ioc (0 : 𝕜) 1) : x + t • y ∈ interior s := by
simpa only [add_sub_cancel_left] using hs.add_smul_sub_mem_interior' hx hy ht
#align convex.add_smul_mem_interior' Convex.add_smul_mem_interior'
/-- If `x ∈ s` and `x + y ∈ interior s`, then `x + t y ∈ interior s` for `t ∈ (0, 1]`. -/
theorem Convex.add_smul_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ s)
(hy : x + y ∈ interior s) {t : 𝕜} (ht : t ∈ Ioc (0 : 𝕜) 1) : x + t • y ∈ interior s :=
hs.add_smul_mem_interior' (subset_closure hx) hy ht
#align convex.add_smul_mem_interior Convex.add_smul_mem_interior
/-- In a topological vector space, the interior of a convex set is convex. -/
protected theorem Convex.interior {s : Set E} (hs : Convex 𝕜 s) : Convex 𝕜 (interior s) :=
convex_iff_openSegment_subset.mpr fun _ hx _ hy =>
hs.openSegment_closure_interior_subset_interior (interior_subset_closure hx) hy
#align convex.interior Convex.interior
/-- In a topological vector space, the closure of a convex set is convex. -/
protected theorem Convex.closure {s : Set E} (hs : Convex 𝕜 s) : Convex 𝕜 (closure s) :=
fun x hx y hy a b ha hb hab =>
let f : E → E → E := fun x' y' => a • x' + b • y'
have hf : Continuous (Function.uncurry f) :=
(continuous_fst.const_smul _).add (continuous_snd.const_smul _)
show f x y ∈ closure s from map_mem_closure₂ hf hx hy fun _ hx' _ hy' => hs hx' hy' ha hb hab
#align convex.closure Convex.closure
open AffineMap
/-- A convex set `s` is strictly convex provided that for any two distinct points of
`s \ interior s`, the line passing through these points has nonempty intersection with
`interior s`. -/
protected theorem Convex.strictConvex' {s : Set E} (hs : Convex 𝕜 s)
(h : (s \ interior s).Pairwise fun x y => ∃ c : 𝕜, lineMap x y c ∈ interior s) :
StrictConvex 𝕜 s := by
refine strictConvex_iff_openSegment_subset.2 ?_
intro x hx y hy hne
by_cases hx' : x ∈ interior s
· exact hs.openSegment_interior_self_subset_interior hx' hy
by_cases hy' : y ∈ interior s
· exact hs.openSegment_self_interior_subset_interior hx hy'
rcases h ⟨hx, hx'⟩ ⟨hy, hy'⟩ hne with ⟨c, hc⟩
refine (openSegment_subset_union x y ⟨c, rfl⟩).trans
(insert_subset_iff.2 ⟨hc, union_subset ?_ ?_⟩)
exacts [hs.openSegment_self_interior_subset_interior hx hc,
hs.openSegment_interior_self_subset_interior hc hy]
#align convex.strict_convex' Convex.strictConvex'
/-- A convex set `s` is strictly convex provided that for any two distinct points `x`, `y` of
`s \ interior s`, the segment with endpoints `x`, `y` has nonempty intersection with
`interior s`. -/
protected theorem Convex.strictConvex {s : Set E} (hs : Convex 𝕜 s)
(h : (s \ interior s).Pairwise fun x y => ([x -[𝕜] y] \ frontier s).Nonempty) :
StrictConvex 𝕜 s := by
refine hs.strictConvex' <| h.imp_on fun x hx y hy _ => ?_
simp only [segment_eq_image_lineMap, ← self_diff_frontier]
rintro ⟨_, ⟨⟨c, hc, rfl⟩, hcs⟩⟩
refine ⟨c, hs.segment_subset hx.1 hy.1 ?_, hcs⟩
exact (segment_eq_image_lineMap 𝕜 x y).symm ▸ mem_image_of_mem _ hc
#align convex.strict_convex Convex.strictConvex
end ContinuousConstSMul
section ContinuousSMul
variable [AddCommGroup E] [Module ℝ E] [TopologicalSpace E] [TopologicalAddGroup E]
[ContinuousSMul ℝ E]
/-- Convex hull of a finite set is compact. -/
| Mathlib/Analysis/Convex/Topology.lean | 296 | 301 | theorem Set.Finite.isCompact_convexHull {s : Set E} (hs : s.Finite) :
IsCompact (convexHull ℝ s) := by |
rw [hs.convexHull_eq_image]
apply (@isCompact_stdSimplex _ hs.fintype).image
haveI := hs.fintype
apply LinearMap.continuous_on_pi
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Geometry.Euclidean.Angle.Oriented.Affine
import Mathlib.Geometry.Euclidean.Angle.Unoriented.RightAngle
#align_import geometry.euclidean.angle.oriented.right_angle from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Oriented angles in right-angled triangles.
This file proves basic geometrical results about distances and oriented angles in (possibly
degenerate) right-angled triangles in real inner product spaces and Euclidean affine spaces.
-/
noncomputable section
open scoped EuclideanGeometry
open scoped Real
open scoped RealInnerProductSpace
namespace Orientation
open FiniteDimensional
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable [hd2 : Fact (finrank ℝ V = 2)] (o : Orientation ℝ V (Fin 2))
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arccos (‖x‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arccos_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arccos (‖y‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arcsin (‖y‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arcsin_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arcsin (‖x‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arctan (‖y‖ / ‖x‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arctan_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h) (o.left_ne_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arctan (‖x‖ / ‖y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle x (x + y)) = ‖x‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle (x + y) y) = ‖y‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle x (x + y)) = ‖y‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle (x + y) y) = ‖x‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle x (x + y)) = ‖y‖ / ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle (x + y) y) = ‖x‖ / ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle x (x + y)) * ‖x + y‖ = ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle (x + y) y) * ‖x + y‖ = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle x (x + y)) * ‖x + y‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle (x + y) y) * ‖x + y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle x (x + y)) * ‖x‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle (x + y) y) * ‖y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.cos (o.oangle x (x + y)) = ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.norm_div_cos_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.cos (o.oangle (x + y) y) = ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.sin (o.oangle x (x + y)) = ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.norm_div_sin_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.sin (o.oangle (x + y) y) = ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.tan (o.oangle x (x + y)) = ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.norm_div_tan_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.tan (o.oangle (x + y) y) = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arccos (‖y‖ / ‖y - x‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arccos_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arccos (‖x‖ / ‖x - y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two h
#align orientation.oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arcsin (‖x‖ / ‖y - x‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arcsin_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
theorem oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arcsin (‖y‖ / ‖x - y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two h
#align orientation.oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arctan (‖x‖ / ‖y‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arctan_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h) (o.right_ne_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, version subtracting vectors. -/
| Mathlib/Geometry/Euclidean/Angle/Oriented/RightAngle.lean | 312 | 315 | theorem oangle_sub_left_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arctan (‖y‖ / ‖x‖) := by |
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two h
|
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.RingTheory.FiniteType
import Mathlib.RingTheory.Localization.AtPrime
import Mathlib.RingTheory.Localization.Away.Basic
import Mathlib.RingTheory.Localization.Integer
import Mathlib.RingTheory.Localization.Submodule
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.RingTheory.RingHomProperties
import Mathlib.Data.Set.Subsingleton
#align_import ring_theory.local_properties from "leanprover-community/mathlib"@"a7c017d750512a352b623b1824d75da5998457d0"
/-!
# Local properties of commutative rings
In this file, we provide the proofs of various local properties.
## Naming Conventions
* `localization_P` : `P` holds for `S⁻¹R` if `P` holds for `R`.
* `P_of_localization_maximal` : `P` holds for `R` if `P` holds for `Rₘ` for all maximal `m`.
* `P_of_localization_prime` : `P` holds for `R` if `P` holds for `Rₘ` for all prime `m`.
* `P_ofLocalizationSpan` : `P` holds for `R` if given a spanning set `{fᵢ}`, `P` holds for all
`R_{fᵢ}`.
## Main results
The following properties are covered:
* The triviality of an ideal or an element:
`ideal_eq_bot_of_localization`, `eq_zero_of_localization`
* `isReduced` : `localization_isReduced`, `isReduced_of_localization_maximal`.
* `finite`: `localization_finite`, `finite_ofLocalizationSpan`
* `finiteType`: `localization_finiteType`, `finiteType_ofLocalizationSpan`
-/
open scoped Pointwise Classical
universe u
variable {R S : Type u} [CommRing R] [CommRing S] (M : Submonoid R)
variable (N : Submonoid S) (R' S' : Type u) [CommRing R'] [CommRing S'] (f : R →+* S)
variable [Algebra R R'] [Algebra S S']
section Properties
section CommRing
variable (P : ∀ (R : Type u) [CommRing R], Prop)
/-- A property `P` of comm rings is said to be preserved by localization
if `P` holds for `M⁻¹R` whenever `P` holds for `R`. -/
def LocalizationPreserves : Prop :=
∀ {R : Type u} [hR : CommRing R] (M : Submonoid R) (S : Type u) [hS : CommRing S] [Algebra R S]
[IsLocalization M S], @P R hR → @P S hS
#align localization_preserves LocalizationPreserves
/-- A property `P` of comm rings satisfies `OfLocalizationMaximal`
if `P` holds for `R` whenever `P` holds for `Rₘ` for all maximal ideal `m`. -/
def OfLocalizationMaximal : Prop :=
∀ (R : Type u) [CommRing R],
(∀ (J : Ideal R) (_ : J.IsMaximal), P (Localization.AtPrime J)) → P R
#align of_localization_maximal OfLocalizationMaximal
end CommRing
section RingHom
variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S] (_ : R →+* S), Prop)
/-- A property `P` of ring homs is said to be preserved by localization
if `P` holds for `M⁻¹R →+* M⁻¹S` whenever `P` holds for `R →+* S`. -/
def RingHom.LocalizationPreserves :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S) (M : Submonoid R) (R' S' : Type u)
[CommRing R'] [CommRing S'] [Algebra R R'] [Algebra S S'] [IsLocalization M R']
[IsLocalization (M.map f) S'],
P f → P (IsLocalization.map S' f (Submonoid.le_comap_map M) : R' →+* S')
#align ring_hom.localization_preserves RingHom.LocalizationPreserves
/-- A property `P` of ring homs satisfies `RingHom.OfLocalizationFiniteSpan`
if `P` holds for `R →+* S` whenever there exists a finite set `{ r }` that spans `R` such that
`P` holds for `Rᵣ →+* Sᵣ`.
Note that this is equivalent to `RingHom.OfLocalizationSpan` via
`RingHom.ofLocalizationSpan_iff_finite`, but this is easier to prove. -/
def RingHom.OfLocalizationFiniteSpan :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S) (s : Finset R)
(_ : Ideal.span (s : Set R) = ⊤) (_ : ∀ r : s, P (Localization.awayMap f r)), P f
#align ring_hom.of_localization_finite_span RingHom.OfLocalizationFiniteSpan
/-- A property `P` of ring homs satisfies `RingHom.OfLocalizationFiniteSpan`
if `P` holds for `R →+* S` whenever there exists a set `{ r }` that spans `R` such that
`P` holds for `Rᵣ →+* Sᵣ`.
Note that this is equivalent to `RingHom.OfLocalizationFiniteSpan` via
`RingHom.ofLocalizationSpan_iff_finite`, but this has less restrictions when applying. -/
def RingHom.OfLocalizationSpan :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S) (s : Set R) (_ : Ideal.span s = ⊤)
(_ : ∀ r : s, P (Localization.awayMap f r)), P f
#align ring_hom.of_localization_span RingHom.OfLocalizationSpan
/-- A property `P` of ring homs satisfies `RingHom.HoldsForLocalizationAway`
if `P` holds for each localization map `R →+* Rᵣ`. -/
def RingHom.HoldsForLocalizationAway : Prop :=
∀ ⦃R : Type u⦄ (S : Type u) [CommRing R] [CommRing S] [Algebra R S] (r : R)
[IsLocalization.Away r S], P (algebraMap R S)
#align ring_hom.holds_for_localization_away RingHom.HoldsForLocalizationAway
/-- A property `P` of ring homs satisfies `RingHom.OfLocalizationFiniteSpanTarget`
if `P` holds for `R →+* S` whenever there exists a finite set `{ r }` that spans `S` such that
`P` holds for `R →+* Sᵣ`.
Note that this is equivalent to `RingHom.OfLocalizationSpanTarget` via
`RingHom.ofLocalizationSpanTarget_iff_finite`, but this is easier to prove. -/
def RingHom.OfLocalizationFiniteSpanTarget : Prop :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S) (s : Finset S)
(_ : Ideal.span (s : Set S) = ⊤)
(_ : ∀ r : s, P ((algebraMap S (Localization.Away (r : S))).comp f)), P f
#align ring_hom.of_localization_finite_span_target RingHom.OfLocalizationFiniteSpanTarget
/-- A property `P` of ring homs satisfies `RingHom.OfLocalizationSpanTarget`
if `P` holds for `R →+* S` whenever there exists a set `{ r }` that spans `S` such that
`P` holds for `R →+* Sᵣ`.
Note that this is equivalent to `RingHom.OfLocalizationFiniteSpanTarget` via
`RingHom.ofLocalizationSpanTarget_iff_finite`, but this has less restrictions when applying. -/
def RingHom.OfLocalizationSpanTarget : Prop :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S) (s : Set S) (_ : Ideal.span s = ⊤)
(_ : ∀ r : s, P ((algebraMap S (Localization.Away (r : S))).comp f)), P f
#align ring_hom.of_localization_span_target RingHom.OfLocalizationSpanTarget
/-- A property `P` of ring homs satisfies `RingHom.OfLocalizationPrime`
if `P` holds for `R` whenever `P` holds for `Rₘ` for all prime ideals `p`. -/
def RingHom.OfLocalizationPrime : Prop :=
∀ ⦃R S : Type u⦄ [CommRing R] [CommRing S] (f : R →+* S),
(∀ (J : Ideal S) (_ : J.IsPrime), P (Localization.localRingHom _ J f rfl)) → P f
#align ring_hom.of_localization_prime RingHom.OfLocalizationPrime
/-- A property of ring homs is local if it is preserved by localizations and compositions, and for
each `{ r }` that spans `S`, we have `P (R →+* S) ↔ ∀ r, P (R →+* Sᵣ)`. -/
structure RingHom.PropertyIsLocal : Prop where
LocalizationPreserves : RingHom.LocalizationPreserves @P
OfLocalizationSpanTarget : RingHom.OfLocalizationSpanTarget @P
StableUnderComposition : RingHom.StableUnderComposition @P
HoldsForLocalizationAway : RingHom.HoldsForLocalizationAway @P
#align ring_hom.property_is_local RingHom.PropertyIsLocal
theorem RingHom.ofLocalizationSpan_iff_finite :
RingHom.OfLocalizationSpan @P ↔ RingHom.OfLocalizationFiniteSpan @P := by
delta RingHom.OfLocalizationSpan RingHom.OfLocalizationFiniteSpan
apply forall₅_congr
-- TODO: Using `refine` here breaks `resetI`.
intros
constructor
· intro h s; exact h s
· intro h s hs hs'
obtain ⟨s', h₁, h₂⟩ := (Ideal.span_eq_top_iff_finite s).mp hs
exact h s' h₂ fun x => hs' ⟨_, h₁ x.prop⟩
#align ring_hom.of_localization_span_iff_finite RingHom.ofLocalizationSpan_iff_finite
theorem RingHom.ofLocalizationSpanTarget_iff_finite :
RingHom.OfLocalizationSpanTarget @P ↔ RingHom.OfLocalizationFiniteSpanTarget @P := by
delta RingHom.OfLocalizationSpanTarget RingHom.OfLocalizationFiniteSpanTarget
apply forall₅_congr
-- TODO: Using `refine` here breaks `resetI`.
intros
constructor
· intro h s; exact h s
· intro h s hs hs'
obtain ⟨s', h₁, h₂⟩ := (Ideal.span_eq_top_iff_finite s).mp hs
exact h s' h₂ fun x => hs' ⟨_, h₁ x.prop⟩
#align ring_hom.of_localization_span_target_iff_finite RingHom.ofLocalizationSpanTarget_iff_finite
variable {P f R' S'}
theorem RingHom.PropertyIsLocal.respectsIso (hP : RingHom.PropertyIsLocal @P) :
RingHom.RespectsIso @P := by
apply hP.StableUnderComposition.respectsIso
introv
letI := e.toRingHom.toAlgebra
-- Porting note: was `apply_with hP.holds_for_localization_away { instances := ff }`
have : IsLocalization.Away (1 : R) S := by
apply IsLocalization.away_of_isUnit_of_bijective _ isUnit_one e.bijective
exact RingHom.PropertyIsLocal.HoldsForLocalizationAway hP S (1 : R)
#align ring_hom.property_is_local.respects_iso RingHom.PropertyIsLocal.respectsIso
-- Almost all arguments are implicit since this is not intended to use mid-proof.
theorem RingHom.LocalizationPreserves.away (H : RingHom.LocalizationPreserves @P) (r : R)
[IsLocalization.Away r R'] [IsLocalization.Away (f r) S'] (hf : P f) :
P (IsLocalization.Away.map R' S' f r) := by
have : IsLocalization ((Submonoid.powers r).map f) S' := by rw [Submonoid.map_powers]; assumption
exact H f (Submonoid.powers r) R' S' hf
#align ring_hom.localization_preserves.away RingHom.LocalizationPreserves.away
theorem RingHom.PropertyIsLocal.ofLocalizationSpan (hP : RingHom.PropertyIsLocal @P) :
RingHom.OfLocalizationSpan @P := by
introv R hs hs'
apply_fun Ideal.map f at hs
rw [Ideal.map_span, Ideal.map_top] at hs
apply hP.OfLocalizationSpanTarget _ _ hs
rintro ⟨_, r, hr, rfl⟩
convert hP.StableUnderComposition
_ _ (hP.HoldsForLocalizationAway (Localization.Away r) r) (hs' ⟨r, hr⟩) using 1
exact (IsLocalization.map_comp _).symm
#align ring_hom.property_is_local.of_localization_span RingHom.PropertyIsLocal.ofLocalizationSpan
lemma RingHom.OfLocalizationSpanTarget.ofIsLocalization
(hP : RingHom.OfLocalizationSpanTarget P) (hP' : RingHom.RespectsIso P)
{R S : Type u} [CommRing R] [CommRing S] (f : R →+* S) (s : Set S) (hs : Ideal.span s = ⊤)
(hT : ∀ r : s, ∃ (T : Type u) (_ : CommRing T) (_ : Algebra S T)
(_ : IsLocalization.Away (r : S) T), P ((algebraMap S T).comp f)) : P f := by
apply hP _ s hs
intros r
obtain ⟨T, _, _, _, hT⟩ := hT r
convert hP'.1 _
(Localization.algEquiv (R := S) (Submonoid.powers (r : S)) T).symm.toRingEquiv hT
rw [← RingHom.comp_assoc, RingEquiv.toRingHom_eq_coe, AlgEquiv.toRingEquiv_eq_coe,
AlgEquiv.toRingEquiv_toRingHom, Localization.coe_algEquiv_symm, IsLocalization.map_comp,
RingHom.comp_id]
end RingHom
end Properties
section Ideal
open scoped nonZeroDivisors
/-- Let `I J : Ideal R`. If the localization of `I` at each maximal ideal `P` is included in
the localization of `J` at `P`, then `I ≤ J`. -/
theorem Ideal.le_of_localization_maximal {I J : Ideal R}
(h : ∀ (P : Ideal R) (hP : P.IsMaximal),
Ideal.map (algebraMap R (Localization.AtPrime P)) I ≤
Ideal.map (algebraMap R (Localization.AtPrime P)) J) :
I ≤ J := by
intro x hx
suffices J.colon (Ideal.span {x}) = ⊤ by
simpa using Submodule.mem_colon.mp
(show (1 : R) ∈ J.colon (Ideal.span {x}) from this.symm ▸ Submodule.mem_top) x
(Ideal.mem_span_singleton_self x)
refine Not.imp_symm (J.colon (Ideal.span {x})).exists_le_maximal ?_
push_neg
intro P hP le
obtain ⟨⟨⟨a, ha⟩, ⟨s, hs⟩⟩, eq⟩ :=
(IsLocalization.mem_map_algebraMap_iff P.primeCompl _).mp (h P hP (Ideal.mem_map_of_mem _ hx))
rw [← _root_.map_mul, ← sub_eq_zero, ← map_sub] at eq
obtain ⟨⟨m, hm⟩, eq⟩ := (IsLocalization.map_eq_zero_iff P.primeCompl _ _).mp eq
refine hs ((hP.isPrime.mem_or_mem (le (Ideal.mem_colon_singleton.mpr ?_))).resolve_right hm)
simp only [Subtype.coe_mk, mul_sub, sub_eq_zero, mul_comm x s, mul_left_comm] at eq
simpa only [mul_assoc, eq] using J.mul_mem_left m ha
#align ideal.le_of_localization_maximal Ideal.le_of_localization_maximal
/-- Let `I J : Ideal R`. If the localization of `I` at each maximal ideal `P` is equal to
the localization of `J` at `P`, then `I = J`. -/
theorem Ideal.eq_of_localization_maximal {I J : Ideal R}
(h : ∀ (P : Ideal R) (_ : P.IsMaximal),
Ideal.map (algebraMap R (Localization.AtPrime P)) I =
Ideal.map (algebraMap R (Localization.AtPrime P)) J) :
I = J :=
le_antisymm (Ideal.le_of_localization_maximal fun P hP => (h P hP).le)
(Ideal.le_of_localization_maximal fun P hP => (h P hP).ge)
#align ideal.eq_of_localization_maximal Ideal.eq_of_localization_maximal
/-- An ideal is trivial if its localization at every maximal ideal is trivial. -/
theorem ideal_eq_bot_of_localization' (I : Ideal R)
(h : ∀ (J : Ideal R) (hJ : J.IsMaximal),
Ideal.map (algebraMap R (Localization.AtPrime J)) I = ⊥) :
I = ⊥ :=
Ideal.eq_of_localization_maximal fun P hP => by simpa using h P hP
#align ideal_eq_bot_of_localization' ideal_eq_bot_of_localization'
-- TODO: This proof should work for all modules, once we have enough material on submodules of
-- localized modules.
/-- An ideal is trivial if its localization at every maximal ideal is trivial. -/
theorem ideal_eq_bot_of_localization (I : Ideal R)
(h : ∀ (J : Ideal R) (hJ : J.IsMaximal),
IsLocalization.coeSubmodule (Localization.AtPrime J) I = ⊥) :
I = ⊥ :=
ideal_eq_bot_of_localization' _ fun P hP =>
(Ideal.map_eq_bot_iff_le_ker _).mpr fun x hx => by
rw [RingHom.mem_ker, ← Submodule.mem_bot R, ← h P hP, IsLocalization.mem_coeSubmodule]
exact ⟨x, hx, rfl⟩
#align ideal_eq_bot_of_localization ideal_eq_bot_of_localization
theorem eq_zero_of_localization (r : R)
(h : ∀ (J : Ideal R) (hJ : J.IsMaximal), algebraMap R (Localization.AtPrime J) r = 0) :
r = 0 := by
rw [← Ideal.span_singleton_eq_bot]
apply ideal_eq_bot_of_localization
intro J hJ
delta IsLocalization.coeSubmodule
erw [Submodule.map_span, Submodule.span_eq_bot]
rintro _ ⟨_, h', rfl⟩
cases Set.mem_singleton_iff.mpr h'
exact h J hJ
#align eq_zero_of_localization eq_zero_of_localization
end Ideal
section Reduced
theorem localization_isReduced : LocalizationPreserves fun R hR => IsReduced R := by
introv R _ _
constructor
rintro x ⟨_ | n, e⟩
· simpa using congr_arg (· * x) e
obtain ⟨⟨y, m⟩, hx⟩ := IsLocalization.surj M x
dsimp only at hx
let hx' := congr_arg (· ^ n.succ) hx
simp only [mul_pow, e, zero_mul, ← RingHom.map_pow] at hx'
rw [← (algebraMap R S).map_zero] at hx'
obtain ⟨m', hm'⟩ := (IsLocalization.eq_iff_exists M S).mp hx'
apply_fun (· * (m' : R) ^ n) at hm'
simp only [mul_assoc, zero_mul, mul_zero] at hm'
rw [← mul_left_comm, ← pow_succ', ← mul_pow] at hm'
replace hm' := IsNilpotent.eq_zero ⟨_, hm'.symm⟩
rw [← (IsLocalization.map_units S m).mul_left_inj, hx, zero_mul,
IsLocalization.map_eq_zero_iff M]
exact ⟨m', by rw [← hm', mul_comm]⟩
#align localization_is_reduced localization_isReduced
instance [IsReduced R] : IsReduced (Localization M) :=
localization_isReduced M _ inferInstance
theorem isReduced_ofLocalizationMaximal : OfLocalizationMaximal fun R hR => IsReduced R := by
introv R h
constructor
intro x hx
apply eq_zero_of_localization
intro J hJ
specialize h J hJ
exact (hx.map <| algebraMap R <| Localization.AtPrime J).eq_zero
#align is_reduced_of_localization_maximal isReduced_ofLocalizationMaximal
end Reduced
section Surjective
theorem localizationPreserves_surjective :
RingHom.LocalizationPreserves fun {R S} _ _ f => Function.Surjective f := by
introv R H x
obtain ⟨x, ⟨_, s, hs, rfl⟩, rfl⟩ := IsLocalization.mk'_surjective (M.map f) x
obtain ⟨y, rfl⟩ := H x
use IsLocalization.mk' R' y ⟨s, hs⟩
rw [IsLocalization.map_mk']
#align localization_preserves_surjective localizationPreserves_surjective
theorem surjective_ofLocalizationSpan :
RingHom.OfLocalizationSpan fun {R S} _ _ f => Function.Surjective f := by
introv R e H
rw [← Set.range_iff_surjective, Set.eq_univ_iff_forall]
letI := f.toAlgebra
intro x
apply Submodule.mem_of_span_eq_top_of_smul_pow_mem
(LinearMap.range (Algebra.linearMap R S)) s e
intro r
obtain ⟨a, e'⟩ := H r (algebraMap _ _ x)
obtain ⟨b, ⟨_, n, rfl⟩, rfl⟩ := IsLocalization.mk'_surjective (Submonoid.powers (r : R)) a
erw [IsLocalization.map_mk'] at e'
rw [eq_comm, IsLocalization.eq_mk'_iff_mul_eq, Subtype.coe_mk, Subtype.coe_mk, ← map_mul] at e'
obtain ⟨⟨_, n', rfl⟩, e''⟩ := (IsLocalization.eq_iff_exists (Submonoid.powers (f r)) _).mp e'
dsimp only at e''
rw [mul_comm x, ← mul_assoc, ← map_pow, ← map_mul, ← map_mul, ← pow_add] at e''
exact ⟨n' + n, _, e''.symm⟩
#align surjective_of_localization_span surjective_ofLocalizationSpan
/-- A surjective ring homomorphism `R →+* S` induces a surjective homomorphism `R_{f⁻¹(P)} →+* S_P`
for every prime ideal `P` of `S`. -/
theorem surjective_localRingHom_of_surjective (h : Function.Surjective f) (P : Ideal S)
[P.IsPrime] : Function.Surjective (Localization.localRingHom (P.comap f) P f rfl) :=
have : IsLocalization (Submonoid.map f (Ideal.comap f P).primeCompl) (Localization.AtPrime P) :=
(Submonoid.map_comap_eq_of_surjective h P.primeCompl).symm ▸ Localization.isLocalization
localizationPreserves_surjective _ _ _ _ h
end Surjective
section Finite
lemma Module.Finite_of_isLocalization (R S Rₚ Sₚ) [CommSemiring R] [CommRing S] [CommRing Rₚ]
[CommRing Sₚ] [Algebra R S] [Algebra R Rₚ] [Algebra R Sₚ] [Algebra S Sₚ] [Algebra Rₚ Sₚ]
[IsScalarTower R S Sₚ] [IsScalarTower R Rₚ Sₚ] (M : Submonoid R) [IsLocalization M Rₚ]
[IsLocalization (Algebra.algebraMapSubmonoid S M) Sₚ] [hRS : Module.Finite R S] :
Module.Finite Rₚ Sₚ := by
classical
have : algebraMap Rₚ Sₚ = IsLocalization.map (T := Algebra.algebraMapSubmonoid S M) Sₚ
(algebraMap R S) (Submonoid.le_comap_map M) := by
apply IsLocalization.ringHom_ext M
simp only [IsLocalization.map_comp, ← IsScalarTower.algebraMap_eq]
-- We claim that if `S` is generated by `T` as an `R`-module,
-- then `S'` is generated by `T` as an `R'`-module.
obtain ⟨T, hT⟩ := hRS
use T.image (algebraMap S Sₚ)
rw [eq_top_iff]
rintro x -
-- By the hypotheses, for each `x : S'`, we have `x = y / (f r)` for some `y : S` and `r : M`.
-- Since `S` is generated by `T`, the image of `y` should fall in the span of the image of `T`.
obtain ⟨y, ⟨_, ⟨r, hr, rfl⟩⟩, rfl⟩ :=
IsLocalization.mk'_surjective (Algebra.algebraMapSubmonoid S M) x
rw [IsLocalization.mk'_eq_mul_mk'_one, mul_comm, Finset.coe_image]
have hy : y ∈ Submodule.span R ↑T := by rw [hT]; trivial
replace hy : algebraMap S Sₚ y ∈ Submodule.map (IsScalarTower.toAlgHom R S Sₚ).toLinearMap
(Submodule.span R (T : Set S)) := Submodule.mem_map_of_mem
-- -- Note: #8386 had to specify the value of `f` below
(f := (IsScalarTower.toAlgHom R S Sₚ).toLinearMap) hy
rw [Submodule.map_span (IsScalarTower.toAlgHom R S Sₚ).toLinearMap T] at hy
have H : Submodule.span R (algebraMap S Sₚ '' T) ≤
(Submodule.span Rₚ (algebraMap S Sₚ '' T)).restrictScalars R := by
rw [Submodule.span_le]; exact Submodule.subset_span
-- Now, since `y ∈ span T`, and `(f r)⁻¹ ∈ R'`, `x / (f r)` is in `span T` as well.
convert (Submodule.span Rₚ (algebraMap S Sₚ '' T)).smul_mem
(IsLocalization.mk' Rₚ (1 : R) ⟨r, hr⟩) (H hy) using 1
rw [Algebra.smul_def, this, IsLocalization.map_mk', map_one]
/-- If `S` is a finite `R`-algebra, then `S' = M⁻¹S` is a finite `R' = M⁻¹R`-algebra. -/
theorem localization_finite : RingHom.LocalizationPreserves @RingHom.Finite := by
introv R hf
letI := f.toAlgebra
letI := ((algebraMap S S').comp f).toAlgebra
let f' : R' →+* S' := IsLocalization.map S' f (Submonoid.le_comap_map M)
letI := f'.toAlgebra
have : IsScalarTower R R' S' := IsScalarTower.of_algebraMap_eq'
(IsLocalization.map_comp M.le_comap_map).symm
have : IsScalarTower R S S' := IsScalarTower.of_algebraMap_eq' rfl
have : IsLocalization (Algebra.algebraMapSubmonoid S M) S' := by
rwa [Algebra.algebraMapSubmonoid, RingHom.algebraMap_toAlgebra]
have : Module.Finite R S := hf
apply Module.Finite_of_isLocalization R S R' S' M
#align localization_finite localization_finite
theorem localization_away_map_finite (r : R) [IsLocalization.Away r R']
[IsLocalization.Away (f r) S'] (hf : f.Finite) : (IsLocalization.Away.map R' S' f r).Finite :=
localization_finite.away r hf
#align localization_away_map_finite localization_away_map_finite
/-- Let `S` be an `R`-algebra, `M` a submonoid of `R`, and `S' = M⁻¹S`.
If the image of some `x : S` falls in the span of some finite `s ⊆ S'` over `R`,
then there exists some `m : M` such that `m • x` falls in the
span of `IsLocalization.finsetIntegerMultiple _ s` over `R`.
-/
theorem IsLocalization.smul_mem_finsetIntegerMultiple_span [Algebra R S] [Algebra R S']
[IsScalarTower R S S'] [IsLocalization (M.map (algebraMap R S)) S'] (x : S) (s : Finset S')
(hx : algebraMap S S' x ∈ Submodule.span R (s : Set S')) :
∃ m : M, m • x ∈
Submodule.span R
(IsLocalization.finsetIntegerMultiple (M.map (algebraMap R S)) s : Set S) := by
let g : S →ₐ[R] S' :=
AlgHom.mk' (algebraMap S S') fun c x => by simp [Algebra.algebraMap_eq_smul_one]
-- We first obtain the `y' ∈ M` such that `s' = y' • s` is falls in the image of `S` in `S'`.
let y := IsLocalization.commonDenomOfFinset (M.map (algebraMap R S)) s
have hx₁ : (y : S) • (s : Set S') = g '' _ :=
(IsLocalization.finsetIntegerMultiple_image _ s).symm
obtain ⟨y', hy', e : algebraMap R S y' = y⟩ := y.prop
have : algebraMap R S y' • (s : Set S') = y' • (s : Set S') := by
simp_rw [Algebra.algebraMap_eq_smul_one, smul_assoc, one_smul]
rw [← e, this] at hx₁
replace hx₁ := congr_arg (Submodule.span R) hx₁
rw [Submodule.span_smul] at hx₁
replace hx : _ ∈ y' • Submodule.span R (s : Set S') := Set.smul_mem_smul_set hx
rw [hx₁] at hx
erw [← g.map_smul, ← Submodule.map_span (g : S →ₗ[R] S')] at hx
-- Since `x` falls in the span of `s` in `S'`, `y' • x : S` falls in the span of `s'` in `S'`.
-- That is, there exists some `x' : S` in the span of `s'` in `S` and `x' = y' • x` in `S'`.
-- Thus `a • (y' • x) = a • x' ∈ span s'` in `S` for some `a ∈ M`.
obtain ⟨x', hx', hx'' : algebraMap _ _ _ = _⟩ := hx
obtain ⟨⟨_, a, ha₁, rfl⟩, ha₂⟩ :=
(IsLocalization.eq_iff_exists (M.map (algebraMap R S)) S').mp hx''
use (⟨a, ha₁⟩ : M) * (⟨y', hy'⟩ : M)
convert (Submodule.span R
(IsLocalization.finsetIntegerMultiple (Submonoid.map (algebraMap R S) M) s : Set S)).smul_mem
a hx' using 1
convert ha₂.symm using 1
· rw [Subtype.coe_mk, Submonoid.smul_def, Submonoid.coe_mul, ← smul_smul]
exact Algebra.smul_def _ _
· exact Algebra.smul_def _ _
#align is_localization.smul_mem_finset_integer_multiple_span IsLocalization.smul_mem_finsetIntegerMultiple_span
/-- If `S` is an `R' = M⁻¹R` algebra, and `x ∈ span R' s`,
then `t • x ∈ span R s` for some `t : M`. -/
| Mathlib/RingTheory/LocalProperties.lean | 484 | 504 | theorem multiple_mem_span_of_mem_localization_span [Algebra R' S] [Algebra R S]
[IsScalarTower R R' S] [IsLocalization M R'] (s : Set S) (x : S)
(hx : x ∈ Submodule.span R' s) : ∃ t : M, t • x ∈ Submodule.span R s := by |
obtain ⟨s', hss', hs'⟩ := Submodule.mem_span_finite_of_mem_span hx
rsuffices ⟨t, ht⟩ : ∃ t : M, t • x ∈ Submodule.span R (s' : Set S)
· exact ⟨t, Submodule.span_mono hss' ht⟩
clear hx hss' s
induction s' using Finset.induction_on generalizing x
· use 1; simpa using hs'
rename_i a s _ hs
simp only [Finset.coe_insert, Finset.image_insert, Finset.coe_image, Subtype.coe_mk,
Submodule.mem_span_insert] at hs' ⊢
rcases hs' with ⟨y, z, hz, rfl⟩
rcases IsLocalization.surj M y with ⟨⟨y', s'⟩, e⟩
replace e : _ * a = _ * a := (congr_arg (fun x => algebraMap R' S x * a) e : _)
simp_rw [RingHom.map_mul, ← IsScalarTower.algebraMap_apply, mul_comm (algebraMap R' S y),
mul_assoc, ← Algebra.smul_def] at e
rcases hs _ hz with ⟨t, ht⟩
refine ⟨t * s', t * y', _, (Submodule.span R (s : Set S)).smul_mem s' ht, ?_⟩
rw [smul_add, ← smul_smul, mul_comm, ← smul_smul, ← smul_smul, ← e]
rfl
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Algebra.Constructions
import Mathlib.Topology.Bases
import Mathlib.Topology.UniformSpace.Basic
#align_import topology.uniform_space.cauchy from "leanprover-community/mathlib"@"22131150f88a2d125713ffa0f4693e3355b1eb49"
/-!
# Theory of Cauchy filters in uniform spaces. Complete uniform spaces. Totally bounded subsets.
-/
universe u v
open scoped Classical
open Filter TopologicalSpace Set UniformSpace Function
open scoped Classical
open Uniformity Topology Filter
variable {α : Type u} {β : Type v} [uniformSpace : UniformSpace α]
/-- A filter `f` is Cauchy if for every entourage `r`, there exists an
`s ∈ f` such that `s × s ⊆ r`. This is a generalization of Cauchy
sequences, because if `a : ℕ → α` then the filter of sets containing
cofinitely many of the `a n` is Cauchy iff `a` is a Cauchy sequence. -/
def Cauchy (f : Filter α) :=
NeBot f ∧ f ×ˢ f ≤ 𝓤 α
#align cauchy Cauchy
/-- A set `s` is called *complete*, if any Cauchy filter `f` such that `s ∈ f`
has a limit in `s` (formally, it satisfies `f ≤ 𝓝 x` for some `x ∈ s`). -/
def IsComplete (s : Set α) :=
∀ f, Cauchy f → f ≤ 𝓟 s → ∃ x ∈ s, f ≤ 𝓝 x
#align is_complete IsComplete
theorem Filter.HasBasis.cauchy_iff {ι} {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s)
{f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ i, p i → ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s i :=
and_congr Iff.rfl <|
(f.basis_sets.prod_self.le_basis_iff h).trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
#align filter.has_basis.cauchy_iff Filter.HasBasis.cauchy_iff
theorem cauchy_iff' {f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s :=
(𝓤 α).basis_sets.cauchy_iff
#align cauchy_iff' cauchy_iff'
theorem cauchy_iff {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s :=
cauchy_iff'.trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
#align cauchy_iff cauchy_iff
lemma cauchy_iff_le {l : Filter α} [hl : l.NeBot] :
Cauchy l ↔ l ×ˢ l ≤ 𝓤 α := by
simp only [Cauchy, hl, true_and]
theorem Cauchy.ultrafilter_of {l : Filter α} (h : Cauchy l) :
Cauchy (@Ultrafilter.of _ l h.1 : Filter α) := by
haveI := h.1
have := Ultrafilter.of_le l
exact ⟨Ultrafilter.neBot _, (Filter.prod_mono this this).trans h.2⟩
#align cauchy.ultrafilter_of Cauchy.ultrafilter_of
theorem cauchy_map_iff {l : Filter β} {f : β → α} :
Cauchy (l.map f) ↔ NeBot l ∧ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) := by
rw [Cauchy, map_neBot_iff, prod_map_map_eq, Tendsto]
#align cauchy_map_iff cauchy_map_iff
theorem cauchy_map_iff' {l : Filter β} [hl : NeBot l] {f : β → α} :
Cauchy (l.map f) ↔ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) :=
cauchy_map_iff.trans <| and_iff_right hl
#align cauchy_map_iff' cauchy_map_iff'
theorem Cauchy.mono {f g : Filter α} [hg : NeBot g] (h_c : Cauchy f) (h_le : g ≤ f) : Cauchy g :=
⟨hg, le_trans (Filter.prod_mono h_le h_le) h_c.right⟩
#align cauchy.mono Cauchy.mono
theorem Cauchy.mono' {f g : Filter α} (h_c : Cauchy f) (_ : NeBot g) (h_le : g ≤ f) : Cauchy g :=
h_c.mono h_le
#align cauchy.mono' Cauchy.mono'
theorem cauchy_nhds {a : α} : Cauchy (𝓝 a) :=
⟨nhds_neBot, nhds_prod_eq.symm.trans_le (nhds_le_uniformity a)⟩
#align cauchy_nhds cauchy_nhds
theorem cauchy_pure {a : α} : Cauchy (pure a) :=
cauchy_nhds.mono (pure_le_nhds a)
#align cauchy_pure cauchy_pure
theorem Filter.Tendsto.cauchy_map {l : Filter β} [NeBot l] {f : β → α} {a : α}
(h : Tendsto f l (𝓝 a)) : Cauchy (map f l) :=
cauchy_nhds.mono h
#align filter.tendsto.cauchy_map Filter.Tendsto.cauchy_map
lemma Cauchy.mono_uniformSpace {u v : UniformSpace β} {F : Filter β} (huv : u ≤ v)
(hF : Cauchy (uniformSpace := u) F) : Cauchy (uniformSpace := v) F :=
⟨hF.1, hF.2.trans huv⟩
lemma cauchy_inf_uniformSpace {u v : UniformSpace β} {F : Filter β} :
Cauchy (uniformSpace := u ⊓ v) F ↔
Cauchy (uniformSpace := u) F ∧ Cauchy (uniformSpace := v) F := by
unfold Cauchy
rw [inf_uniformity (u := u), le_inf_iff, and_and_left]
lemma cauchy_iInf_uniformSpace {ι : Sort*} [Nonempty ι] {u : ι → UniformSpace β}
{l : Filter β} :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
unfold Cauchy
rw [iInf_uniformity, le_iInf_iff, forall_and, forall_const]
lemma cauchy_iInf_uniformSpace' {ι : Sort*} {u : ι → UniformSpace β}
{l : Filter β} [l.NeBot] :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
simp_rw [cauchy_iff_le (uniformSpace := _), iInf_uniformity, le_iInf_iff]
lemma cauchy_comap_uniformSpace {u : UniformSpace β} {f : α → β} {l : Filter α} :
Cauchy (uniformSpace := comap f u) l ↔ Cauchy (map f l) := by
simp only [Cauchy, map_neBot_iff, prod_map_map_eq, map_le_iff_le_comap]
rfl
lemma cauchy_prod_iff [UniformSpace β] {F : Filter (α × β)} :
Cauchy F ↔ Cauchy (map Prod.fst F) ∧ Cauchy (map Prod.snd F) := by
simp_rw [instUniformSpaceProd, ← cauchy_comap_uniformSpace, ← cauchy_inf_uniformSpace]
theorem Cauchy.prod [UniformSpace β] {f : Filter α} {g : Filter β} (hf : Cauchy f) (hg : Cauchy g) :
Cauchy (f ×ˢ g) := by
have := hf.1; have := hg.1
simpa [cauchy_prod_iff, hf.1] using ⟨hf, hg⟩
#align cauchy.prod Cauchy.prod
/-- The common part of the proofs of `le_nhds_of_cauchy_adhp` and
`SequentiallyComplete.le_nhds_of_seq_tendsto_nhds`: if for any entourage `s`
one can choose a set `t ∈ f` of diameter `s` such that it contains a point `y`
with `(x, y) ∈ s`, then `f` converges to `x`. -/
theorem le_nhds_of_cauchy_adhp_aux {f : Filter α} {x : α}
(adhs : ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s ∧ ∃ y, (x, y) ∈ s ∧ y ∈ t) : f ≤ 𝓝 x := by
-- Consider a neighborhood `s` of `x`
intro s hs
-- Take an entourage twice smaller than `s`
rcases comp_mem_uniformity_sets (mem_nhds_uniformity_iff_right.1 hs) with ⟨U, U_mem, hU⟩
-- Take a set `t ∈ f`, `t × t ⊆ U`, and a point `y ∈ t` such that `(x, y) ∈ U`
rcases adhs U U_mem with ⟨t, t_mem, ht, y, hxy, hy⟩
apply mem_of_superset t_mem
-- Given a point `z ∈ t`, we have `(x, y) ∈ U` and `(y, z) ∈ t × t ⊆ U`, hence `z ∈ s`
exact fun z hz => hU (prod_mk_mem_compRel hxy (ht <| mk_mem_prod hy hz)) rfl
#align le_nhds_of_cauchy_adhp_aux le_nhds_of_cauchy_adhp_aux
/-- If `x` is an adherent (cluster) point for a Cauchy filter `f`, then it is a limit point
for `f`. -/
theorem le_nhds_of_cauchy_adhp {f : Filter α} {x : α} (hf : Cauchy f) (adhs : ClusterPt x f) :
f ≤ 𝓝 x :=
le_nhds_of_cauchy_adhp_aux
(fun s hs => by
obtain ⟨t, t_mem, ht⟩ : ∃ t ∈ f, t ×ˢ t ⊆ s := (cauchy_iff.1 hf).2 s hs
use t, t_mem, ht
exact forall_mem_nonempty_iff_neBot.2 adhs _ (inter_mem_inf (mem_nhds_left x hs) t_mem))
#align le_nhds_of_cauchy_adhp le_nhds_of_cauchy_adhp
theorem le_nhds_iff_adhp_of_cauchy {f : Filter α} {x : α} (hf : Cauchy f) :
f ≤ 𝓝 x ↔ ClusterPt x f :=
⟨fun h => ClusterPt.of_le_nhds' h hf.1, le_nhds_of_cauchy_adhp hf⟩
#align le_nhds_iff_adhp_of_cauchy le_nhds_iff_adhp_of_cauchy
nonrec theorem Cauchy.map [UniformSpace β] {f : Filter α} {m : α → β} (hf : Cauchy f)
(hm : UniformContinuous m) : Cauchy (map m f) :=
⟨hf.1.map _,
calc
map m f ×ˢ map m f = map (Prod.map m m) (f ×ˢ f) := Filter.prod_map_map_eq
_ ≤ Filter.map (Prod.map m m) (𝓤 α) := map_mono hf.right
_ ≤ 𝓤 β := hm⟩
#align cauchy.map Cauchy.map
nonrec theorem Cauchy.comap [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f)
(hm : comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α) [NeBot (comap m f)] :
Cauchy (comap m f) :=
⟨‹_›,
calc
comap m f ×ˢ comap m f = comap (Prod.map m m) (f ×ˢ f) := prod_comap_comap_eq
_ ≤ comap (Prod.map m m) (𝓤 β) := comap_mono hf.right
_ ≤ 𝓤 α := hm⟩
#align cauchy.comap Cauchy.comap
theorem Cauchy.comap' [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f)
(hm : Filter.comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α)
(_ : NeBot (Filter.comap m f)) : Cauchy (Filter.comap m f) :=
hf.comap hm
#align cauchy.comap' Cauchy.comap'
/-- Cauchy sequences. Usually defined on ℕ, but often it is also useful to say that a function
defined on ℝ is Cauchy at +∞ to deduce convergence. Therefore, we define it in a type class that
is general enough to cover both ℕ and ℝ, which are the main motivating examples. -/
def CauchySeq [Preorder β] (u : β → α) :=
Cauchy (atTop.map u)
#align cauchy_seq CauchySeq
theorem CauchySeq.tendsto_uniformity [Preorder β] {u : β → α} (h : CauchySeq u) :
Tendsto (Prod.map u u) atTop (𝓤 α) := by
simpa only [Tendsto, prod_map_map_eq', prod_atTop_atTop_eq] using h.right
#align cauchy_seq.tendsto_uniformity CauchySeq.tendsto_uniformity
theorem CauchySeq.nonempty [Preorder β] {u : β → α} (hu : CauchySeq u) : Nonempty β :=
@nonempty_of_neBot _ _ <| (map_neBot_iff _).1 hu.1
#align cauchy_seq.nonempty CauchySeq.nonempty
theorem CauchySeq.mem_entourage {β : Type*} [SemilatticeSup β] {u : β → α} (h : CauchySeq u)
{V : Set (α × α)} (hV : V ∈ 𝓤 α) : ∃ k₀, ∀ i j, k₀ ≤ i → k₀ ≤ j → (u i, u j) ∈ V := by
haveI := h.nonempty
have := h.tendsto_uniformity; rw [← prod_atTop_atTop_eq] at this
simpa [MapsTo] using atTop_basis.prod_self.tendsto_left_iff.1 this V hV
#align cauchy_seq.mem_entourage CauchySeq.mem_entourage
theorem Filter.Tendsto.cauchySeq [SemilatticeSup β] [Nonempty β] {f : β → α} {x}
(hx : Tendsto f atTop (𝓝 x)) : CauchySeq f :=
hx.cauchy_map
#align filter.tendsto.cauchy_seq Filter.Tendsto.cauchySeq
theorem cauchySeq_const [SemilatticeSup β] [Nonempty β] (x : α) : CauchySeq fun _ : β => x :=
tendsto_const_nhds.cauchySeq
#align cauchy_seq_const cauchySeq_const
theorem cauchySeq_iff_tendsto [Nonempty β] [SemilatticeSup β] {u : β → α} :
CauchySeq u ↔ Tendsto (Prod.map u u) atTop (𝓤 α) :=
cauchy_map_iff'.trans <| by simp only [prod_atTop_atTop_eq, Prod.map_def]
#align cauchy_seq_iff_tendsto cauchySeq_iff_tendsto
theorem CauchySeq.comp_tendsto {γ} [Preorder β] [SemilatticeSup γ] [Nonempty γ] {f : β → α}
(hf : CauchySeq f) {g : γ → β} (hg : Tendsto g atTop atTop) : CauchySeq (f ∘ g) :=
⟨inferInstance, le_trans (prod_le_prod.mpr ⟨Tendsto.comp le_rfl hg, Tendsto.comp le_rfl hg⟩) hf.2⟩
#align cauchy_seq.comp_tendsto CauchySeq.comp_tendsto
theorem CauchySeq.comp_injective [SemilatticeSup β] [NoMaxOrder β] [Nonempty β] {u : ℕ → α}
(hu : CauchySeq u) {f : β → ℕ} (hf : Injective f) : CauchySeq (u ∘ f) :=
hu.comp_tendsto <| Nat.cofinite_eq_atTop ▸ hf.tendsto_cofinite.mono_left atTop_le_cofinite
#align cauchy_seq.comp_injective CauchySeq.comp_injective
theorem Function.Bijective.cauchySeq_comp_iff {f : ℕ → ℕ} (hf : Bijective f) (u : ℕ → α) :
CauchySeq (u ∘ f) ↔ CauchySeq u := by
refine ⟨fun H => ?_, fun H => H.comp_injective hf.injective⟩
lift f to ℕ ≃ ℕ using hf
simpa only [(· ∘ ·), f.apply_symm_apply] using H.comp_injective f.symm.injective
#align function.bijective.cauchy_seq_comp_iff Function.Bijective.cauchySeq_comp_iff
| Mathlib/Topology/UniformSpace/Cauchy.lean | 249 | 253 | theorem CauchySeq.subseq_subseq_mem {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α}
(hu : CauchySeq u) {f g : ℕ → ℕ} (hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, ((u ∘ f ∘ φ) n, (u ∘ g ∘ φ) n) ∈ V n := by |
rw [cauchySeq_iff_tendsto] at hu
exact ((hu.comp <| hf.prod_atTop hg).comp tendsto_atTop_diagonal).subseq_mem hV
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Algebra.Operations
import Mathlib.Data.Fintype.Lattice
import Mathlib.RingTheory.Coprime.Lemmas
#align_import ring_theory.ideal.operations from "leanprover-community/mathlib"@"e7f0ddbf65bd7181a85edb74b64bdc35ba4bdc74"
/-!
# More operations on modules and ideals
-/
assert_not_exists Basis -- See `RingTheory.Ideal.Basis`
assert_not_exists Submodule.hasQuotient -- See `RingTheory.Ideal.QuotientOperations`
universe u v w x
open Pointwise
namespace Submodule
variable {R : Type u} {M : Type v} {M' F G : Type*}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
open Pointwise
instance hasSMul' : SMul (Ideal R) (Submodule R M) :=
⟨Submodule.map₂ (LinearMap.lsmul R M)⟩
#align submodule.has_smul' Submodule.hasSMul'
/-- This duplicates the global `smul_eq_mul`, but doesn't have to unfold anywhere near as much to
apply. -/
protected theorem _root_.Ideal.smul_eq_mul (I J : Ideal R) : I • J = I * J :=
rfl
#align ideal.smul_eq_mul Ideal.smul_eq_mul
variable (R M) in
/-- `Module.annihilator R M` is the ideal of all elements `r : R` such that `r • M = 0`. -/
def _root_.Module.annihilator : Ideal R := LinearMap.ker (LinearMap.lsmul R M)
theorem _root_.Module.mem_annihilator {r} : r ∈ Module.annihilator R M ↔ ∀ m : M, r • m = 0 :=
⟨fun h ↦ (congr($h ·)), (LinearMap.ext ·)⟩
theorem _root_.LinearMap.annihilator_le_of_injective (f : M →ₗ[R] M') (hf : Function.Injective f) :
Module.annihilator R M' ≤ Module.annihilator R M := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢; exact fun m ↦ hf (by rw [map_smul, h, f.map_zero])
theorem _root_.LinearMap.annihilator_le_of_surjective (f : M →ₗ[R] M')
(hf : Function.Surjective f) : Module.annihilator R M ≤ Module.annihilator R M' := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢
intro m; obtain ⟨m, rfl⟩ := hf m
rw [← map_smul, h, f.map_zero]
theorem _root_.LinearEquiv.annihilator_eq (e : M ≃ₗ[R] M') :
Module.annihilator R M = Module.annihilator R M' :=
(e.annihilator_le_of_surjective e.surjective).antisymm (e.annihilator_le_of_injective e.injective)
/-- `N.annihilator` is the ideal of all elements `r : R` such that `r • N = 0`. -/
abbrev annihilator (N : Submodule R M) : Ideal R :=
Module.annihilator R N
#align submodule.annihilator Submodule.annihilator
theorem annihilator_top : (⊤ : Submodule R M).annihilator = Module.annihilator R M :=
topEquiv.annihilator_eq
variable {I J : Ideal R} {N P : Submodule R M}
theorem mem_annihilator {r} : r ∈ N.annihilator ↔ ∀ n ∈ N, r • n = (0 : M) := by
simp_rw [annihilator, Module.mem_annihilator, Subtype.forall, Subtype.ext_iff]; rfl
#align submodule.mem_annihilator Submodule.mem_annihilator
theorem mem_annihilator' {r} : r ∈ N.annihilator ↔ N ≤ comap (r • (LinearMap.id : M →ₗ[R] M)) ⊥ :=
mem_annihilator.trans ⟨fun H n hn => (mem_bot R).2 <| H n hn, fun H _ hn => (mem_bot R).1 <| H hn⟩
#align submodule.mem_annihilator' Submodule.mem_annihilator'
theorem mem_annihilator_span (s : Set M) (r : R) :
r ∈ (Submodule.span R s).annihilator ↔ ∀ n : s, r • (n : M) = 0 := by
rw [Submodule.mem_annihilator]
constructor
· intro h n
exact h _ (Submodule.subset_span n.prop)
· intro h n hn
refine Submodule.span_induction hn ?_ ?_ ?_ ?_
· intro x hx
exact h ⟨x, hx⟩
· exact smul_zero _
· intro x y hx hy
rw [smul_add, hx, hy, zero_add]
· intro a x hx
rw [smul_comm, hx, smul_zero]
#align submodule.mem_annihilator_span Submodule.mem_annihilator_span
theorem mem_annihilator_span_singleton (g : M) (r : R) :
r ∈ (Submodule.span R ({g} : Set M)).annihilator ↔ r • g = 0 := by simp [mem_annihilator_span]
#align submodule.mem_annihilator_span_singleton Submodule.mem_annihilator_span_singleton
theorem annihilator_bot : (⊥ : Submodule R M).annihilator = ⊤ :=
(Ideal.eq_top_iff_one _).2 <| mem_annihilator'.2 bot_le
#align submodule.annihilator_bot Submodule.annihilator_bot
theorem annihilator_eq_top_iff : N.annihilator = ⊤ ↔ N = ⊥ :=
⟨fun H =>
eq_bot_iff.2 fun (n : M) hn =>
(mem_bot R).2 <| one_smul R n ▸ mem_annihilator.1 ((Ideal.eq_top_iff_one _).1 H) n hn,
fun H => H.symm ▸ annihilator_bot⟩
#align submodule.annihilator_eq_top_iff Submodule.annihilator_eq_top_iff
theorem annihilator_mono (h : N ≤ P) : P.annihilator ≤ N.annihilator := fun _ hrp =>
mem_annihilator.2 fun n hn => mem_annihilator.1 hrp n <| h hn
#align submodule.annihilator_mono Submodule.annihilator_mono
theorem annihilator_iSup (ι : Sort w) (f : ι → Submodule R M) :
annihilator (⨆ i, f i) = ⨅ i, annihilator (f i) :=
le_antisymm (le_iInf fun _ => annihilator_mono <| le_iSup _ _) fun _ H =>
mem_annihilator'.2 <|
iSup_le fun i =>
have := (mem_iInf _).1 H i
mem_annihilator'.1 this
#align submodule.annihilator_supr Submodule.annihilator_iSup
theorem smul_mem_smul {r} {n} (hr : r ∈ I) (hn : n ∈ N) : r • n ∈ I • N :=
apply_mem_map₂ _ hr hn
#align submodule.smul_mem_smul Submodule.smul_mem_smul
theorem smul_le {P : Submodule R M} : I • N ≤ P ↔ ∀ r ∈ I, ∀ n ∈ N, r • n ∈ P :=
map₂_le
#align submodule.smul_le Submodule.smul_le
@[simp, norm_cast]
lemma coe_set_smul : (I : Set R) • N = I • N :=
Submodule.set_smul_eq_of_le _ _ _
(fun _ _ hr hx => smul_mem_smul hr hx)
(smul_le.mpr fun _ hr _ hx => mem_set_smul_of_mem_mem hr hx)
@[elab_as_elim]
theorem smul_induction_on {p : M → Prop} {x} (H : x ∈ I • N) (smul : ∀ r ∈ I, ∀ n ∈ N, p (r • n))
(add : ∀ x y, p x → p y → p (x + y)) : p x := by
have H0 : p 0 := by simpa only [zero_smul] using smul 0 I.zero_mem 0 N.zero_mem
refine Submodule.iSup_induction (x := x) _ H ?_ H0 add
rintro ⟨i, hi⟩ m ⟨j, hj, hj'⟩
rw [← hj']
exact smul _ hi _ hj
#align submodule.smul_induction_on Submodule.smul_induction_on
/-- Dependent version of `Submodule.smul_induction_on`. -/
@[elab_as_elim]
theorem smul_induction_on' {x : M} (hx : x ∈ I • N) {p : ∀ x, x ∈ I • N → Prop}
(smul : ∀ (r : R) (hr : r ∈ I) (n : M) (hn : n ∈ N), p (r • n) (smul_mem_smul hr hn))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›)) : p x hx := by
refine Exists.elim ?_ fun (h : x ∈ I • N) (H : p x h) => H
exact
smul_induction_on hx (fun a ha x hx => ⟨_, smul _ ha _ hx⟩) fun x y ⟨_, hx⟩ ⟨_, hy⟩ =>
⟨_, add _ _ _ _ hx hy⟩
#align submodule.smul_induction_on' Submodule.smul_induction_on'
theorem mem_smul_span_singleton {I : Ideal R} {m : M} {x : M} :
x ∈ I • span R ({m} : Set M) ↔ ∃ y ∈ I, y • m = x :=
⟨fun hx =>
smul_induction_on hx
(fun r hri n hnm =>
let ⟨s, hs⟩ := mem_span_singleton.1 hnm
⟨r * s, I.mul_mem_right _ hri, hs ▸ mul_smul r s m⟩)
fun m1 m2 ⟨y1, hyi1, hy1⟩ ⟨y2, hyi2, hy2⟩ =>
⟨y1 + y2, I.add_mem hyi1 hyi2, by rw [add_smul, hy1, hy2]⟩,
fun ⟨y, hyi, hy⟩ => hy ▸ smul_mem_smul hyi (subset_span <| Set.mem_singleton m)⟩
#align submodule.mem_smul_span_singleton Submodule.mem_smul_span_singleton
theorem smul_le_right : I • N ≤ N :=
smul_le.2 fun r _ _ => N.smul_mem r
#align submodule.smul_le_right Submodule.smul_le_right
theorem smul_mono (hij : I ≤ J) (hnp : N ≤ P) : I • N ≤ J • P :=
map₂_le_map₂ hij hnp
#align submodule.smul_mono Submodule.smul_mono
theorem smul_mono_left (h : I ≤ J) : I • N ≤ J • N :=
map₂_le_map₂_left h
#align submodule.smul_mono_left Submodule.smul_mono_left
instance : CovariantClass (Ideal R) (Submodule R M) HSMul.hSMul LE.le :=
⟨fun _ _ => map₂_le_map₂_right⟩
@[deprecated smul_mono_right (since := "2024-03-31")]
protected theorem smul_mono_right (h : N ≤ P) : I • N ≤ I • P :=
_root_.smul_mono_right I h
#align submodule.smul_mono_right Submodule.smul_mono_right
theorem map_le_smul_top (I : Ideal R) (f : R →ₗ[R] M) :
Submodule.map f I ≤ I • (⊤ : Submodule R M) := by
rintro _ ⟨y, hy, rfl⟩
rw [← mul_one y, ← smul_eq_mul, f.map_smul]
exact smul_mem_smul hy mem_top
#align submodule.map_le_smul_top Submodule.map_le_smul_top
@[simp]
theorem annihilator_smul (N : Submodule R M) : annihilator N • N = ⊥ :=
eq_bot_iff.2 (smul_le.2 fun _ => mem_annihilator.1)
#align submodule.annihilator_smul Submodule.annihilator_smul
@[simp]
theorem annihilator_mul (I : Ideal R) : annihilator I * I = ⊥ :=
annihilator_smul I
#align submodule.annihilator_mul Submodule.annihilator_mul
@[simp]
theorem mul_annihilator (I : Ideal R) : I * annihilator I = ⊥ := by rw [mul_comm, annihilator_mul]
#align submodule.mul_annihilator Submodule.mul_annihilator
variable (I J N P)
@[simp]
theorem smul_bot : I • (⊥ : Submodule R M) = ⊥ :=
map₂_bot_right _ _
#align submodule.smul_bot Submodule.smul_bot
@[simp]
theorem bot_smul : (⊥ : Ideal R) • N = ⊥ :=
map₂_bot_left _ _
#align submodule.bot_smul Submodule.bot_smul
@[simp]
theorem top_smul : (⊤ : Ideal R) • N = N :=
le_antisymm smul_le_right fun r hri => one_smul R r ▸ smul_mem_smul mem_top hri
#align submodule.top_smul Submodule.top_smul
theorem smul_sup : I • (N ⊔ P) = I • N ⊔ I • P :=
map₂_sup_right _ _ _ _
#align submodule.smul_sup Submodule.smul_sup
theorem sup_smul : (I ⊔ J) • N = I • N ⊔ J • N :=
map₂_sup_left _ _ _ _
#align submodule.sup_smul Submodule.sup_smul
protected theorem smul_assoc : (I • J) • N = I • J • N :=
le_antisymm
(smul_le.2 fun _ hrsij t htn =>
smul_induction_on hrsij
(fun r hr s hs =>
(@smul_eq_mul R _ r s).symm ▸ smul_smul r s t ▸ smul_mem_smul hr (smul_mem_smul hs htn))
fun x y => (add_smul x y t).symm ▸ Submodule.add_mem _)
(smul_le.2 fun r hr _ hsn =>
suffices J • N ≤ Submodule.comap (r • (LinearMap.id : M →ₗ[R] M)) ((I • J) • N) from this hsn
smul_le.2 fun s hs n hn =>
show r • s • n ∈ (I • J) • N from mul_smul r s n ▸ smul_mem_smul (smul_mem_smul hr hs) hn)
#align submodule.smul_assoc Submodule.smul_assoc
@[deprecated smul_inf_le (since := "2024-03-31")]
protected theorem smul_inf_le (M₁ M₂ : Submodule R M) :
I • (M₁ ⊓ M₂) ≤ I • M₁ ⊓ I • M₂ := smul_inf_le _ _ _
#align submodule.smul_inf_le Submodule.smul_inf_le
theorem smul_iSup {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} : I • iSup t = ⨆ i, I • t i :=
map₂_iSup_right _ _ _
#align submodule.smul_supr Submodule.smul_iSup
@[deprecated smul_iInf_le (since := "2024-03-31")]
protected theorem smul_iInf_le {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} :
I • iInf t ≤ ⨅ i, I • t i :=
smul_iInf_le
#align submodule.smul_infi_le Submodule.smul_iInf_le
variable (S : Set R) (T : Set M)
theorem span_smul_span : Ideal.span S • span R T = span R (⋃ (s ∈ S) (t ∈ T), {s • t}) :=
(map₂_span_span _ _ _ _).trans <| congr_arg _ <| Set.image2_eq_iUnion _ _ _
#align submodule.span_smul_span Submodule.span_smul_span
theorem ideal_span_singleton_smul (r : R) (N : Submodule R M) :
(Ideal.span {r} : Ideal R) • N = r • N := by
have : span R (⋃ (t : M) (_ : t ∈ N), {r • t}) = r • N := by
convert span_eq (r • N)
exact (Set.image_eq_iUnion _ (N : Set M)).symm
conv_lhs => rw [← span_eq N, span_smul_span]
simpa
#align submodule.ideal_span_singleton_smul Submodule.ideal_span_singleton_smul
theorem mem_of_span_top_of_smul_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤) (x : M)
(H : ∀ r : s, (r : R) • x ∈ M') : x ∈ M' := by
suffices (⊤ : Ideal R) • span R ({x} : Set M) ≤ M' by
rw [top_smul] at this
exact this (subset_span (Set.mem_singleton x))
rw [← hs, span_smul_span, span_le]
simpa using H
#align submodule.mem_of_span_top_of_smul_mem Submodule.mem_of_span_top_of_smul_mem
/-- Given `s`, a generating set of `R`, to check that an `x : M` falls in a
submodule `M'` of `x`, we only need to show that `r ^ n • x ∈ M'` for some `n` for each `r : s`. -/
theorem mem_of_span_eq_top_of_smul_pow_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤)
(x : M) (H : ∀ r : s, ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M') : x ∈ M' := by
obtain ⟨s', hs₁, hs₂⟩ := (Ideal.span_eq_top_iff_finite _).mp hs
replace H : ∀ r : s', ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M' := fun r => H ⟨_, hs₁ r.2⟩
choose n₁ n₂ using H
let N := s'.attach.sup n₁
have hs' := Ideal.span_pow_eq_top (s' : Set R) hs₂ N
apply M'.mem_of_span_top_of_smul_mem _ hs'
rintro ⟨_, r, hr, rfl⟩
convert M'.smul_mem (r ^ (N - n₁ ⟨r, hr⟩)) (n₂ ⟨r, hr⟩) using 1
simp only [Subtype.coe_mk, smul_smul, ← pow_add]
rw [tsub_add_cancel_of_le (Finset.le_sup (s'.mem_attach _) : n₁ ⟨r, hr⟩ ≤ N)]
#align submodule.mem_of_span_eq_top_of_smul_pow_mem Submodule.mem_of_span_eq_top_of_smul_pow_mem
variable {M' : Type w} [AddCommMonoid M'] [Module R M']
@[simp]
theorem map_smul'' (f : M →ₗ[R] M') : (I • N).map f = I • N.map f :=
le_antisymm
(map_le_iff_le_comap.2 <|
smul_le.2 fun r hr n hn =>
show f (r • n) ∈ I • N.map f from
(f.map_smul r n).symm ▸ smul_mem_smul hr (mem_map_of_mem hn)) <|
smul_le.2 fun r hr _ hn =>
let ⟨p, hp, hfp⟩ := mem_map.1 hn
hfp ▸ f.map_smul r p ▸ mem_map_of_mem (smul_mem_smul hr hp)
#align submodule.map_smul'' Submodule.map_smul''
open Pointwise in
@[simp]
theorem map_pointwise_smul (r : R) (N : Submodule R M) (f : M →ₗ[R] M') :
(r • N).map f = r • N.map f := by
simp_rw [← ideal_span_singleton_smul, map_smul'']
variable {I}
theorem mem_smul_span {s : Set M} {x : M} :
x ∈ I • Submodule.span R s ↔ x ∈ Submodule.span R (⋃ (a ∈ I) (b ∈ s), ({a • b} : Set M)) := by
rw [← I.span_eq, Submodule.span_smul_span, I.span_eq]
rfl
#align submodule.mem_smul_span Submodule.mem_smul_span
variable (I)
/-- If `x` is an `I`-multiple of the submodule spanned by `f '' s`,
then we can write `x` as an `I`-linear combination of the elements of `f '' s`. -/
theorem mem_ideal_smul_span_iff_exists_sum {ι : Type*} (f : ι → M) (x : M) :
x ∈ I • span R (Set.range f) ↔
∃ (a : ι →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
constructor; swap
· rintro ⟨a, ha, rfl⟩
exact Submodule.sum_mem _ fun c _ => smul_mem_smul (ha c) <| subset_span <| Set.mem_range_self _
refine fun hx => span_induction (mem_smul_span.mp hx) ?_ ?_ ?_ ?_
· simp only [Set.mem_iUnion, Set.mem_range, Set.mem_singleton_iff]
rintro x ⟨y, hy, x, ⟨i, rfl⟩, rfl⟩
refine ⟨Finsupp.single i y, fun j => ?_, ?_⟩
· letI := Classical.decEq ι
rw [Finsupp.single_apply]
split_ifs
· assumption
· exact I.zero_mem
refine @Finsupp.sum_single_index ι R M _ _ i _ (fun i y => y • f i) ?_
simp
· exact ⟨0, fun _ => I.zero_mem, Finsupp.sum_zero_index⟩
· rintro x y ⟨ax, hax, rfl⟩ ⟨ay, hay, rfl⟩
refine ⟨ax + ay, fun i => I.add_mem (hax i) (hay i), Finsupp.sum_add_index' ?_ ?_⟩ <;>
intros <;> simp only [zero_smul, add_smul]
· rintro c x ⟨a, ha, rfl⟩
refine ⟨c • a, fun i => I.mul_mem_left c (ha i), ?_⟩
rw [Finsupp.sum_smul_index, Finsupp.smul_sum] <;> intros <;> simp only [zero_smul, mul_smul]
#align submodule.mem_ideal_smul_span_iff_exists_sum Submodule.mem_ideal_smul_span_iff_exists_sum
theorem mem_ideal_smul_span_iff_exists_sum' {ι : Type*} (s : Set ι) (f : ι → M) (x : M) :
x ∈ I • span R (f '' s) ↔
∃ (a : s →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
rw [← Submodule.mem_ideal_smul_span_iff_exists_sum, ← Set.image_eq_range]
#align submodule.mem_ideal_smul_span_iff_exists_sum' Submodule.mem_ideal_smul_span_iff_exists_sum'
theorem mem_smul_top_iff (N : Submodule R M) (x : N) :
x ∈ I • (⊤ : Submodule R N) ↔ (x : M) ∈ I • N := by
change _ ↔ N.subtype x ∈ I • N
have : Submodule.map N.subtype (I • ⊤) = I • N := by
rw [Submodule.map_smul'', Submodule.map_top, Submodule.range_subtype]
rw [← this]
exact (Function.Injective.mem_set_image N.injective_subtype).symm
#align submodule.mem_smul_top_iff Submodule.mem_smul_top_iff
@[simp]
theorem smul_comap_le_comap_smul (f : M →ₗ[R] M') (S : Submodule R M') (I : Ideal R) :
I • S.comap f ≤ (I • S).comap f := by
refine Submodule.smul_le.mpr fun r hr x hx => ?_
rw [Submodule.mem_comap] at hx ⊢
rw [f.map_smul]
exact Submodule.smul_mem_smul hr hx
#align submodule.smul_comap_le_comap_smul Submodule.smul_comap_le_comap_smul
end CommSemiring
end Submodule
namespace Ideal
section Add
variable {R : Type u} [Semiring R]
@[simp]
theorem add_eq_sup {I J : Ideal R} : I + J = I ⊔ J :=
rfl
#align ideal.add_eq_sup Ideal.add_eq_sup
@[simp]
theorem zero_eq_bot : (0 : Ideal R) = ⊥ :=
rfl
#align ideal.zero_eq_bot Ideal.zero_eq_bot
@[simp]
theorem sum_eq_sup {ι : Type*} (s : Finset ι) (f : ι → Ideal R) : s.sum f = s.sup f :=
rfl
#align ideal.sum_eq_sup Ideal.sum_eq_sup
end Add
section MulAndRadical
variable {R : Type u} {ι : Type*} [CommSemiring R]
variable {I J K L : Ideal R}
instance : Mul (Ideal R) :=
⟨(· • ·)⟩
@[simp]
theorem one_eq_top : (1 : Ideal R) = ⊤ := by erw [Submodule.one_eq_range, LinearMap.range_id]
#align ideal.one_eq_top Ideal.one_eq_top
theorem add_eq_one_iff : I + J = 1 ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [one_eq_top, eq_top_iff_one, add_eq_sup, Submodule.mem_sup]
theorem mul_mem_mul {r s} (hr : r ∈ I) (hs : s ∈ J) : r * s ∈ I * J :=
Submodule.smul_mem_smul hr hs
#align ideal.mul_mem_mul Ideal.mul_mem_mul
theorem mul_mem_mul_rev {r s} (hr : r ∈ I) (hs : s ∈ J) : s * r ∈ I * J :=
mul_comm r s ▸ mul_mem_mul hr hs
#align ideal.mul_mem_mul_rev Ideal.mul_mem_mul_rev
theorem pow_mem_pow {x : R} (hx : x ∈ I) (n : ℕ) : x ^ n ∈ I ^ n :=
Submodule.pow_mem_pow _ hx _
#align ideal.pow_mem_pow Ideal.pow_mem_pow
theorem prod_mem_prod {ι : Type*} {s : Finset ι} {I : ι → Ideal R} {x : ι → R} :
(∀ i ∈ s, x i ∈ I i) → (∏ i ∈ s, x i) ∈ ∏ i ∈ s, I i := by
classical
refine Finset.induction_on s ?_ ?_
· intro
rw [Finset.prod_empty, Finset.prod_empty, one_eq_top]
exact Submodule.mem_top
· intro a s ha IH h
rw [Finset.prod_insert ha, Finset.prod_insert ha]
exact
mul_mem_mul (h a <| Finset.mem_insert_self a s)
(IH fun i hi => h i <| Finset.mem_insert_of_mem hi)
#align ideal.prod_mem_prod Ideal.prod_mem_prod
theorem mul_le : I * J ≤ K ↔ ∀ r ∈ I, ∀ s ∈ J, r * s ∈ K :=
Submodule.smul_le
#align ideal.mul_le Ideal.mul_le
theorem mul_le_left : I * J ≤ J :=
Ideal.mul_le.2 fun _ _ _ => J.mul_mem_left _
#align ideal.mul_le_left Ideal.mul_le_left
theorem mul_le_right : I * J ≤ I :=
Ideal.mul_le.2 fun _ hr _ _ => I.mul_mem_right _ hr
#align ideal.mul_le_right Ideal.mul_le_right
@[simp]
theorem sup_mul_right_self : I ⊔ I * J = I :=
sup_eq_left.2 Ideal.mul_le_right
#align ideal.sup_mul_right_self Ideal.sup_mul_right_self
@[simp]
theorem sup_mul_left_self : I ⊔ J * I = I :=
sup_eq_left.2 Ideal.mul_le_left
#align ideal.sup_mul_left_self Ideal.sup_mul_left_self
@[simp]
theorem mul_right_self_sup : I * J ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_right
#align ideal.mul_right_self_sup Ideal.mul_right_self_sup
@[simp]
theorem mul_left_self_sup : J * I ⊔ I = I :=
sup_eq_right.2 Ideal.mul_le_left
#align ideal.mul_left_self_sup Ideal.mul_left_self_sup
variable (I J K)
protected theorem mul_comm : I * J = J * I :=
le_antisymm (mul_le.2 fun _ hrI _ hsJ => mul_mem_mul_rev hsJ hrI)
(mul_le.2 fun _ hrJ _ hsI => mul_mem_mul_rev hsI hrJ)
#align ideal.mul_comm Ideal.mul_comm
protected theorem mul_assoc : I * J * K = I * (J * K) :=
Submodule.smul_assoc I J K
#align ideal.mul_assoc Ideal.mul_assoc
theorem span_mul_span (S T : Set R) : span S * span T = span (⋃ (s ∈ S) (t ∈ T), {s * t}) :=
Submodule.span_smul_span S T
#align ideal.span_mul_span Ideal.span_mul_span
variable {I J K}
theorem span_mul_span' (S T : Set R) : span S * span T = span (S * T) := by
unfold span
rw [Submodule.span_mul_span]
#align ideal.span_mul_span' Ideal.span_mul_span'
theorem span_singleton_mul_span_singleton (r s : R) :
span {r} * span {s} = (span {r * s} : Ideal R) := by
unfold span
rw [Submodule.span_mul_span, Set.singleton_mul_singleton]
#align ideal.span_singleton_mul_span_singleton Ideal.span_singleton_mul_span_singleton
theorem span_singleton_pow (s : R) (n : ℕ) : span {s} ^ n = (span {s ^ n} : Ideal R) := by
induction' n with n ih; · simp [Set.singleton_one]
simp only [pow_succ, ih, span_singleton_mul_span_singleton]
#align ideal.span_singleton_pow Ideal.span_singleton_pow
theorem mem_mul_span_singleton {x y : R} {I : Ideal R} : x ∈ I * span {y} ↔ ∃ z ∈ I, z * y = x :=
Submodule.mem_smul_span_singleton
#align ideal.mem_mul_span_singleton Ideal.mem_mul_span_singleton
theorem mem_span_singleton_mul {x y : R} {I : Ideal R} : x ∈ span {y} * I ↔ ∃ z ∈ I, y * z = x := by
simp only [mul_comm, mem_mul_span_singleton]
#align ideal.mem_span_singleton_mul Ideal.mem_span_singleton_mul
theorem le_span_singleton_mul_iff {x : R} {I J : Ideal R} :
I ≤ span {x} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI :=
show (∀ {zI} (_ : zI ∈ I), zI ∈ span {x} * J) ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI by
simp only [mem_span_singleton_mul]
#align ideal.le_span_singleton_mul_iff Ideal.le_span_singleton_mul_iff
theorem span_singleton_mul_le_iff {x : R} {I J : Ideal R} :
span {x} * I ≤ J ↔ ∀ z ∈ I, x * z ∈ J := by
simp only [mul_le, mem_span_singleton_mul, mem_span_singleton]
constructor
· intro h zI hzI
exact h x (dvd_refl x) zI hzI
· rintro h _ ⟨z, rfl⟩ zI hzI
rw [mul_comm x z, mul_assoc]
exact J.mul_mem_left _ (h zI hzI)
#align ideal.span_singleton_mul_le_iff Ideal.span_singleton_mul_le_iff
theorem span_singleton_mul_le_span_singleton_mul {x y : R} {I J : Ideal R} :
span {x} * I ≤ span {y} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ := by
simp only [span_singleton_mul_le_iff, mem_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_le_span_singleton_mul Ideal.span_singleton_mul_le_span_singleton_mul
theorem span_singleton_mul_right_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I ≤ span {x} * J ↔ I ≤ J := by
simp_rw [span_singleton_mul_le_span_singleton_mul, mul_right_inj' hx,
exists_eq_right', SetLike.le_def]
#align ideal.span_singleton_mul_right_mono Ideal.span_singleton_mul_right_mono
theorem span_singleton_mul_left_mono [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} ≤ J * span {x} ↔ I ≤ J := by
simpa only [mul_comm I, mul_comm J] using span_singleton_mul_right_mono hx
#align ideal.span_singleton_mul_left_mono Ideal.span_singleton_mul_left_mono
theorem span_singleton_mul_right_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
span {x} * I = span {x} * J ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_right_mono hx]
#align ideal.span_singleton_mul_right_inj Ideal.span_singleton_mul_right_inj
theorem span_singleton_mul_left_inj [IsDomain R] {x : R} (hx : x ≠ 0) :
I * span {x} = J * span {x} ↔ I = J := by
simp only [le_antisymm_iff, span_singleton_mul_left_mono hx]
#align ideal.span_singleton_mul_left_inj Ideal.span_singleton_mul_left_inj
theorem span_singleton_mul_right_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective ((span {x} : Ideal R) * ·) := fun _ _ =>
(span_singleton_mul_right_inj hx).mp
#align ideal.span_singleton_mul_right_injective Ideal.span_singleton_mul_right_injective
theorem span_singleton_mul_left_injective [IsDomain R] {x : R} (hx : x ≠ 0) :
Function.Injective fun I : Ideal R => I * span {x} := fun _ _ =>
(span_singleton_mul_left_inj hx).mp
#align ideal.span_singleton_mul_left_injective Ideal.span_singleton_mul_left_injective
theorem eq_span_singleton_mul {x : R} (I J : Ideal R) :
I = span {x} * J ↔ (∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI) ∧ ∀ z ∈ J, x * z ∈ I := by
simp only [le_antisymm_iff, le_span_singleton_mul_iff, span_singleton_mul_le_iff]
#align ideal.eq_span_singleton_mul Ideal.eq_span_singleton_mul
theorem span_singleton_mul_eq_span_singleton_mul {x y : R} (I J : Ideal R) :
span {x} * I = span {y} * J ↔
(∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ) ∧ ∀ zJ ∈ J, ∃ zI ∈ I, x * zI = y * zJ := by
simp only [le_antisymm_iff, span_singleton_mul_le_span_singleton_mul, eq_comm]
#align ideal.span_singleton_mul_eq_span_singleton_mul Ideal.span_singleton_mul_eq_span_singleton_mul
theorem prod_span {ι : Type*} (s : Finset ι) (I : ι → Set R) :
(∏ i ∈ s, Ideal.span (I i)) = Ideal.span (∏ i ∈ s, I i) :=
Submodule.prod_span s I
#align ideal.prod_span Ideal.prod_span
theorem prod_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R) :
(∏ i ∈ s, Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} :=
Submodule.prod_span_singleton s I
#align ideal.prod_span_singleton Ideal.prod_span_singleton
@[simp]
theorem multiset_prod_span_singleton (m : Multiset R) :
(m.map fun x => Ideal.span {x}).prod = Ideal.span ({Multiset.prod m} : Set R) :=
Multiset.induction_on m (by simp) fun a m ih => by
simp only [Multiset.map_cons, Multiset.prod_cons, ih, ← Ideal.span_singleton_mul_span_singleton]
#align ideal.multiset_prod_span_singleton Ideal.multiset_prod_span_singleton
theorem finset_inf_span_singleton {ι : Type*} (s : Finset ι) (I : ι → R)
(hI : Set.Pairwise (↑s) (IsCoprime on I)) :
(s.inf fun i => Ideal.span ({I i} : Set R)) = Ideal.span {∏ i ∈ s, I i} := by
ext x
simp only [Submodule.mem_finset_inf, Ideal.mem_span_singleton]
exact ⟨Finset.prod_dvd_of_coprime hI, fun h i hi => (Finset.dvd_prod_of_mem _ hi).trans h⟩
#align ideal.finset_inf_span_singleton Ideal.finset_inf_span_singleton
theorem iInf_span_singleton {ι : Type*} [Fintype ι] {I : ι → R}
(hI : ∀ (i j) (_ : i ≠ j), IsCoprime (I i) (I j)) :
⨅ i, span ({I i} : Set R) = span {∏ i, I i} := by
rw [← Finset.inf_univ_eq_iInf, finset_inf_span_singleton]
rwa [Finset.coe_univ, Set.pairwise_univ]
#align ideal.infi_span_singleton Ideal.iInf_span_singleton
theorem iInf_span_singleton_natCast {R : Type*} [CommRing R] {ι : Type*} [Fintype ι]
{I : ι → ℕ} (hI : Pairwise fun i j => (I i).Coprime (I j)) :
⨅ (i : ι), span {(I i : R)} = span {((∏ i : ι, I i : ℕ) : R)} := by
rw [iInf_span_singleton, Nat.cast_prod]
exact fun i j h ↦ (hI h).cast
theorem sup_eq_top_iff_isCoprime {R : Type*} [CommSemiring R] (x y : R) :
span ({x} : Set R) ⊔ span {y} = ⊤ ↔ IsCoprime x y := by
rw [eq_top_iff_one, Submodule.mem_sup]
constructor
· rintro ⟨u, hu, v, hv, h1⟩
rw [mem_span_singleton'] at hu hv
rw [← hu.choose_spec, ← hv.choose_spec] at h1
exact ⟨_, _, h1⟩
· exact fun ⟨u, v, h1⟩ =>
⟨_, mem_span_singleton'.mpr ⟨_, rfl⟩, _, mem_span_singleton'.mpr ⟨_, rfl⟩, h1⟩
#align ideal.sup_eq_top_iff_is_coprime Ideal.sup_eq_top_iff_isCoprime
theorem mul_le_inf : I * J ≤ I ⊓ J :=
mul_le.2 fun r hri s hsj => ⟨I.mul_mem_right s hri, J.mul_mem_left r hsj⟩
#align ideal.mul_le_inf Ideal.mul_le_inf
theorem multiset_prod_le_inf {s : Multiset (Ideal R)} : s.prod ≤ s.inf := by
classical
refine s.induction_on ?_ ?_
· rw [Multiset.inf_zero]
exact le_top
intro a s ih
rw [Multiset.prod_cons, Multiset.inf_cons]
exact le_trans mul_le_inf (inf_le_inf le_rfl ih)
#align ideal.multiset_prod_le_inf Ideal.multiset_prod_le_inf
theorem prod_le_inf {s : Finset ι} {f : ι → Ideal R} : s.prod f ≤ s.inf f :=
multiset_prod_le_inf
#align ideal.prod_le_inf Ideal.prod_le_inf
theorem mul_eq_inf_of_coprime (h : I ⊔ J = ⊤) : I * J = I ⊓ J :=
le_antisymm mul_le_inf fun r ⟨hri, hrj⟩ =>
let ⟨s, hsi, t, htj, hst⟩ := Submodule.mem_sup.1 ((eq_top_iff_one _).1 h)
mul_one r ▸
hst ▸
(mul_add r s t).symm ▸ Ideal.add_mem (I * J) (mul_mem_mul_rev hsi hrj) (mul_mem_mul hri htj)
#align ideal.mul_eq_inf_of_coprime Ideal.mul_eq_inf_of_coprime
theorem sup_mul_eq_of_coprime_left (h : I ⊔ J = ⊤) : I ⊔ J * K = I ⊔ K :=
le_antisymm (sup_le_sup_left mul_le_left _) fun i hi => by
rw [eq_top_iff_one] at h; rw [Submodule.mem_sup] at h hi ⊢
obtain ⟨i1, hi1, j, hj, h⟩ := h; obtain ⟨i', hi', k, hk, hi⟩ := hi
refine ⟨_, add_mem hi' (mul_mem_right k _ hi1), _, mul_mem_mul hj hk, ?_⟩
rw [add_assoc, ← add_mul, h, one_mul, hi]
#align ideal.sup_mul_eq_of_coprime_left Ideal.sup_mul_eq_of_coprime_left
theorem sup_mul_eq_of_coprime_right (h : I ⊔ K = ⊤) : I ⊔ J * K = I ⊔ J := by
rw [mul_comm]
exact sup_mul_eq_of_coprime_left h
#align ideal.sup_mul_eq_of_coprime_right Ideal.sup_mul_eq_of_coprime_right
theorem mul_sup_eq_of_coprime_left (h : I ⊔ J = ⊤) : I * K ⊔ J = K ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_left h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_left Ideal.mul_sup_eq_of_coprime_left
theorem mul_sup_eq_of_coprime_right (h : K ⊔ J = ⊤) : I * K ⊔ J = I ⊔ J := by
rw [sup_comm] at h
rw [sup_comm, sup_mul_eq_of_coprime_right h, sup_comm]
#align ideal.mul_sup_eq_of_coprime_right Ideal.mul_sup_eq_of_coprime_right
theorem sup_prod_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ∏ i ∈ s, J i) = ⊤ :=
Finset.prod_induction _ (fun J => I ⊔ J = ⊤)
(fun J K hJ hK => (sup_mul_eq_of_coprime_left hJ).trans hK)
(by simp_rw [one_eq_top, sup_top_eq]) h
#align ideal.sup_prod_eq_top Ideal.sup_prod_eq_top
theorem sup_iInf_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → I ⊔ J i = ⊤) :
(I ⊔ ⨅ i ∈ s, J i) = ⊤ :=
eq_top_iff.mpr <|
le_of_eq_of_le (sup_prod_eq_top h).symm <|
sup_le_sup_left (le_of_le_of_eq prod_le_inf <| Finset.inf_eq_iInf _ _) _
#align ideal.sup_infi_eq_top Ideal.sup_iInf_eq_top
| Mathlib/RingTheory/Ideal/Operations.lean | 708 | 709 | theorem prod_sup_eq_top {s : Finset ι} {J : ι → Ideal R} (h : ∀ i, i ∈ s → J i ⊔ I = ⊤) :
(∏ i ∈ s, J i) ⊔ I = ⊤ := by | rw [sup_comm, sup_prod_eq_top]; intro i hi; rw [sup_comm, h i hi]
|
/-
Copyright (c) 2022 Julian Kuelshammer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Julian Kuelshammer
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.BigOperators.NatAntidiagonal
import Mathlib.Algebra.CharZero.Lemmas
import Mathlib.Data.Finset.NatAntidiagonal
import Mathlib.Data.Nat.Choose.Central
import Mathlib.Data.Tree.Basic
import Mathlib.Tactic.FieldSimp
import Mathlib.Tactic.GCongr
import Mathlib.Tactic.Positivity
#align_import combinatorics.catalan from "leanprover-community/mathlib"@"26b40791e4a5772a4e53d0e28e4df092119dc7da"
/-!
# Catalan numbers
The Catalan numbers (http://oeis.org/A000108) are probably the most ubiquitous sequence of integers
in mathematics. They enumerate several important objects like binary trees, Dyck paths, and
triangulations of convex polygons.
## Main definitions
* `catalan n`: the `n`th Catalan number, defined recursively as
`catalan (n + 1) = ∑ i : Fin n.succ, catalan i * catalan (n - i)`.
## Main results
* `catalan_eq_centralBinom_div`: The explicit formula for the Catalan number using the central
binomial coefficient, `catalan n = Nat.centralBinom n / (n + 1)`.
* `treesOfNodesEq_card_eq_catalan`: The number of binary trees with `n` internal nodes
is `catalan n`
## Implementation details
The proof of `catalan_eq_centralBinom_div` follows https://math.stackexchange.com/questions/3304415
## TODO
* Prove that the Catalan numbers enumerate many interesting objects.
* Provide the many variants of Catalan numbers, e.g. associated to complex reflection groups,
Fuss-Catalan, etc.
-/
open Finset
open Finset.antidiagonal (fst_le snd_le)
/-- The recursive definition of the sequence of Catalan numbers:
`catalan (n + 1) = ∑ i : Fin n.succ, catalan i * catalan (n - i)` -/
def catalan : ℕ → ℕ
| 0 => 1
| n + 1 =>
∑ i : Fin n.succ,
catalan i * catalan (n - i)
#align catalan catalan
@[simp]
theorem catalan_zero : catalan 0 = 1 := by rw [catalan]
#align catalan_zero catalan_zero
| Mathlib/Combinatorics/Enumerative/Catalan.lean | 68 | 69 | theorem catalan_succ (n : ℕ) : catalan (n + 1) = ∑ i : Fin n.succ, catalan i * catalan (n - i) := by |
rw [catalan]
|
/-
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.Polynomial.FieldDivision
import Mathlib.Algebra.Polynomial.Lifts
import Mathlib.Data.List.Prime
#align_import data.polynomial.splits from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e"
/-!
# Split polynomials
A polynomial `f : K[X]` splits over a field extension `L` of `K` if it is zero or all of its
irreducible factors over `L` have degree `1`.
## Main definitions
* `Polynomial.Splits i f`: A predicate on a homomorphism `i : K →+* L` from a commutative ring to a
field and a polynomial `f` saying that `f.map i` is zero or all of its irreducible factors over
`L` have degree `1`.
-/
noncomputable section
open Polynomial
universe u v w
variable {R : Type*} {F : Type u} {K : Type v} {L : Type w}
namespace Polynomial
open Polynomial
section Splits
section CommRing
variable [CommRing K] [Field L] [Field F]
variable (i : K →+* L)
/-- A polynomial `Splits` iff it is zero or all of its irreducible factors have `degree` 1. -/
def Splits (f : K[X]) : Prop :=
f.map i = 0 ∨ ∀ {g : L[X]}, Irreducible g → g ∣ f.map i → degree g = 1
#align polynomial.splits Polynomial.Splits
@[simp]
theorem splits_zero : Splits i (0 : K[X]) :=
Or.inl (Polynomial.map_zero i)
#align polynomial.splits_zero Polynomial.splits_zero
theorem splits_of_map_eq_C {f : K[X]} {a : L} (h : f.map i = C a) : Splits i f :=
letI := Classical.decEq L
if ha : a = 0 then Or.inl (h.trans (ha.symm ▸ C_0))
else
Or.inr fun hg ⟨p, hp⟩ =>
absurd hg.1 <|
Classical.not_not.2 <|
isUnit_iff_degree_eq_zero.2 <| by
have := congr_arg degree hp
rw [h, degree_C ha, degree_mul, @eq_comm (WithBot ℕ) 0,
Nat.WithBot.add_eq_zero_iff] at this
exact this.1
set_option linter.uppercaseLean3 false in
#align polynomial.splits_of_map_eq_C Polynomial.splits_of_map_eq_C
@[simp]
theorem splits_C (a : K) : Splits i (C a) :=
splits_of_map_eq_C i (map_C i)
set_option linter.uppercaseLean3 false in
#align polynomial.splits_C Polynomial.splits_C
theorem splits_of_map_degree_eq_one {f : K[X]} (hf : degree (f.map i) = 1) : Splits i f :=
Or.inr fun hg ⟨p, hp⟩ => by
have := congr_arg degree hp
simp [Nat.WithBot.add_eq_one_iff, hf, @eq_comm (WithBot ℕ) 1,
mt isUnit_iff_degree_eq_zero.2 hg.1] at this
tauto
#align polynomial.splits_of_map_degree_eq_one Polynomial.splits_of_map_degree_eq_one
theorem splits_of_degree_le_one {f : K[X]} (hf : degree f ≤ 1) : Splits i f :=
if hif : degree (f.map i) ≤ 0 then splits_of_map_eq_C i (degree_le_zero_iff.mp hif)
else by
push_neg at hif
rw [← Order.succ_le_iff, ← WithBot.coe_zero, WithBot.succ_coe, Nat.succ_eq_succ] at hif
exact splits_of_map_degree_eq_one i (le_antisymm ((degree_map_le i _).trans hf) hif)
#align polynomial.splits_of_degree_le_one Polynomial.splits_of_degree_le_one
theorem splits_of_degree_eq_one {f : K[X]} (hf : degree f = 1) : Splits i f :=
splits_of_degree_le_one i hf.le
#align polynomial.splits_of_degree_eq_one Polynomial.splits_of_degree_eq_one
theorem splits_of_natDegree_le_one {f : K[X]} (hf : natDegree f ≤ 1) : Splits i f :=
splits_of_degree_le_one i (degree_le_of_natDegree_le hf)
#align polynomial.splits_of_nat_degree_le_one Polynomial.splits_of_natDegree_le_one
theorem splits_of_natDegree_eq_one {f : K[X]} (hf : natDegree f = 1) : Splits i f :=
splits_of_natDegree_le_one i (le_of_eq hf)
#align polynomial.splits_of_nat_degree_eq_one Polynomial.splits_of_natDegree_eq_one
theorem splits_mul {f g : K[X]} (hf : Splits i f) (hg : Splits i g) : Splits i (f * g) :=
letI := Classical.decEq L
if h : (f * g).map i = 0 then Or.inl h
else
Or.inr @fun p hp hpf =>
((irreducible_iff_prime.1 hp).2.2 _ _
(show p ∣ map i f * map i g by convert hpf; rw [Polynomial.map_mul])).elim
(hf.resolve_left (fun hf => by simp [hf] at h) hp)
(hg.resolve_left (fun hg => by simp [hg] at h) hp)
#align polynomial.splits_mul Polynomial.splits_mul
theorem splits_of_splits_mul' {f g : K[X]} (hfg : (f * g).map i ≠ 0) (h : Splits i (f * g)) :
Splits i f ∧ Splits i g :=
⟨Or.inr @fun g hgi hg =>
Or.resolve_left h hfg hgi (by rw [Polynomial.map_mul]; exact hg.trans (dvd_mul_right _ _)),
Or.inr @fun g hgi hg =>
Or.resolve_left h hfg hgi (by rw [Polynomial.map_mul]; exact hg.trans (dvd_mul_left _ _))⟩
#align polynomial.splits_of_splits_mul' Polynomial.splits_of_splits_mul'
theorem splits_map_iff (j : L →+* F) {f : K[X]} : Splits j (f.map i) ↔ Splits (j.comp i) f := by
simp [Splits, Polynomial.map_map]
#align polynomial.splits_map_iff Polynomial.splits_map_iff
theorem splits_one : Splits i 1 :=
splits_C i 1
#align polynomial.splits_one Polynomial.splits_one
theorem splits_of_isUnit [IsDomain K] {u : K[X]} (hu : IsUnit u) : u.Splits i :=
(isUnit_iff.mp hu).choose_spec.2 ▸ splits_C _ _
#align polynomial.splits_of_is_unit Polynomial.splits_of_isUnit
theorem splits_X_sub_C {x : K} : (X - C x).Splits i :=
splits_of_degree_le_one _ <| degree_X_sub_C_le _
set_option linter.uppercaseLean3 false in
#align polynomial.splits_X_sub_C Polynomial.splits_X_sub_C
theorem splits_X : X.Splits i :=
splits_of_degree_le_one _ degree_X_le
set_option linter.uppercaseLean3 false in
#align polynomial.splits_X Polynomial.splits_X
theorem splits_prod {ι : Type u} {s : ι → K[X]} {t : Finset ι} :
(∀ j ∈ t, (s j).Splits i) → (∏ x ∈ t, s x).Splits i := by
classical
refine Finset.induction_on t (fun _ => splits_one i) fun a t hat ih ht => ?_
rw [Finset.forall_mem_insert] at ht; rw [Finset.prod_insert hat]
exact splits_mul i ht.1 (ih ht.2)
#align polynomial.splits_prod Polynomial.splits_prod
theorem splits_pow {f : K[X]} (hf : f.Splits i) (n : ℕ) : (f ^ n).Splits i := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact splits_prod i fun j _ => hf
#align polynomial.splits_pow Polynomial.splits_pow
theorem splits_X_pow (n : ℕ) : (X ^ n).Splits i :=
splits_pow i (splits_X i) n
set_option linter.uppercaseLean3 false in
#align polynomial.splits_X_pow Polynomial.splits_X_pow
theorem splits_id_iff_splits {f : K[X]} : (f.map i).Splits (RingHom.id L) ↔ f.Splits i := by
rw [splits_map_iff, RingHom.id_comp]
#align polynomial.splits_id_iff_splits Polynomial.splits_id_iff_splits
theorem exists_root_of_splits' {f : K[X]} (hs : Splits i f) (hf0 : degree (f.map i) ≠ 0) :
∃ x, eval₂ i x f = 0 :=
letI := Classical.decEq L
if hf0' : f.map i = 0 then by simp [eval₂_eq_eval_map, hf0']
else
let ⟨g, hg⟩ :=
WfDvdMonoid.exists_irreducible_factor
(show ¬IsUnit (f.map i) from mt isUnit_iff_degree_eq_zero.1 hf0) hf0'
let ⟨x, hx⟩ := exists_root_of_degree_eq_one (hs.resolve_left hf0' hg.1 hg.2)
let ⟨i, hi⟩ := hg.2
⟨x, by rw [← eval_map, hi, eval_mul, show _ = _ from hx, zero_mul]⟩
#align polynomial.exists_root_of_splits' Polynomial.exists_root_of_splits'
theorem roots_ne_zero_of_splits' {f : K[X]} (hs : Splits i f) (hf0 : natDegree (f.map i) ≠ 0) :
(f.map i).roots ≠ 0 :=
let ⟨x, hx⟩ := exists_root_of_splits' i hs fun h => hf0 <| natDegree_eq_of_degree_eq_some h
fun h => by
rw [← eval_map] at hx
have : f.map i ≠ 0 := by intro; simp_all
cases h.subst ((mem_roots this).2 hx)
#align polynomial.roots_ne_zero_of_splits' Polynomial.roots_ne_zero_of_splits'
/-- Pick a root of a polynomial that splits. See `rootOfSplits` for polynomials over a field
which has simpler assumptions. -/
def rootOfSplits' {f : K[X]} (hf : f.Splits i) (hfd : (f.map i).degree ≠ 0) : L :=
Classical.choose <| exists_root_of_splits' i hf hfd
#align polynomial.root_of_splits' Polynomial.rootOfSplits'
theorem map_rootOfSplits' {f : K[X]} (hf : f.Splits i) (hfd) :
f.eval₂ i (rootOfSplits' i hf hfd) = 0 :=
Classical.choose_spec <| exists_root_of_splits' i hf hfd
#align polynomial.map_root_of_splits' Polynomial.map_rootOfSplits'
theorem natDegree_eq_card_roots' {p : K[X]} {i : K →+* L} (hsplit : Splits i p) :
(p.map i).natDegree = Multiset.card (p.map i).roots := by
by_cases hp : p.map i = 0
· rw [hp, natDegree_zero, roots_zero, Multiset.card_zero]
obtain ⟨q, he, hd, hr⟩ := exists_prod_multiset_X_sub_C_mul (p.map i)
rw [← splits_id_iff_splits, ← he] at hsplit
rw [← he] at hp
have hq : q ≠ 0 := fun h => hp (by rw [h, mul_zero])
rw [← hd, add_right_eq_self]
by_contra h
have h' : (map (RingHom.id L) q).natDegree ≠ 0 := by simp [h]
have := roots_ne_zero_of_splits' (RingHom.id L) (splits_of_splits_mul' _ ?_ hsplit).2 h'
· rw [map_id] at this
exact this hr
· rw [map_id]
exact mul_ne_zero monic_prod_multiset_X_sub_C.ne_zero hq
#align polynomial.nat_degree_eq_card_roots' Polynomial.natDegree_eq_card_roots'
theorem degree_eq_card_roots' {p : K[X]} {i : K →+* L} (p_ne_zero : p.map i ≠ 0)
(hsplit : Splits i p) : (p.map i).degree = Multiset.card (p.map i).roots := by
simp [degree_eq_natDegree p_ne_zero, natDegree_eq_card_roots' hsplit]
#align polynomial.degree_eq_card_roots' Polynomial.degree_eq_card_roots'
end CommRing
variable [CommRing R] [Field K] [Field L] [Field F]
variable (i : K →+* L)
/-- This lemma is for polynomials over a field. -/
theorem splits_iff (f : K[X]) :
Splits i f ↔ f = 0 ∨ ∀ {g : L[X]}, Irreducible g → g ∣ f.map i → degree g = 1 := by
rw [Splits, map_eq_zero]
#align polynomial.splits_iff Polynomial.splits_iff
/-- This lemma is for polynomials over a field. -/
theorem Splits.def {i : K →+* L} {f : K[X]} (h : Splits i f) :
f = 0 ∨ ∀ {g : L[X]}, Irreducible g → g ∣ f.map i → degree g = 1 :=
(splits_iff i f).mp h
#align polynomial.splits.def Polynomial.Splits.def
theorem splits_of_splits_mul {f g : K[X]} (hfg : f * g ≠ 0) (h : Splits i (f * g)) :
Splits i f ∧ Splits i g :=
splits_of_splits_mul' i (map_ne_zero hfg) h
#align polynomial.splits_of_splits_mul Polynomial.splits_of_splits_mul
theorem splits_of_splits_of_dvd {f g : K[X]} (hf0 : f ≠ 0) (hf : Splits i f) (hgf : g ∣ f) :
Splits i g := by
obtain ⟨f, rfl⟩ := hgf
exact (splits_of_splits_mul i hf0 hf).1
#align polynomial.splits_of_splits_of_dvd Polynomial.splits_of_splits_of_dvd
theorem splits_of_splits_gcd_left [DecidableEq K] {f g : K[X]} (hf0 : f ≠ 0) (hf : Splits i f) :
Splits i (EuclideanDomain.gcd f g) :=
Polynomial.splits_of_splits_of_dvd i hf0 hf (EuclideanDomain.gcd_dvd_left f g)
#align polynomial.splits_of_splits_gcd_left Polynomial.splits_of_splits_gcd_left
theorem splits_of_splits_gcd_right [DecidableEq K] {f g : K[X]} (hg0 : g ≠ 0) (hg : Splits i g) :
Splits i (EuclideanDomain.gcd f g) :=
Polynomial.splits_of_splits_of_dvd i hg0 hg (EuclideanDomain.gcd_dvd_right f g)
#align polynomial.splits_of_splits_gcd_right Polynomial.splits_of_splits_gcd_right
theorem splits_mul_iff {f g : K[X]} (hf : f ≠ 0) (hg : g ≠ 0) :
(f * g).Splits i ↔ f.Splits i ∧ g.Splits i :=
⟨splits_of_splits_mul i (mul_ne_zero hf hg), fun ⟨hfs, hgs⟩ => splits_mul i hfs hgs⟩
#align polynomial.splits_mul_iff Polynomial.splits_mul_iff
theorem splits_prod_iff {ι : Type u} {s : ι → K[X]} {t : Finset ι} :
(∀ j ∈ t, s j ≠ 0) → ((∏ x ∈ t, s x).Splits i ↔ ∀ j ∈ t, (s j).Splits i) := by
classical
refine
Finset.induction_on t (fun _ =>
⟨fun _ _ h => by simp only [Finset.not_mem_empty] at h, fun _ => splits_one i⟩)
fun a t hat ih ht => ?_
rw [Finset.forall_mem_insert] at ht ⊢
rw [Finset.prod_insert hat, splits_mul_iff i ht.1 (Finset.prod_ne_zero_iff.2 ht.2), ih ht.2]
#align polynomial.splits_prod_iff Polynomial.splits_prod_iff
theorem degree_eq_one_of_irreducible_of_splits {p : K[X]} (hp : Irreducible p)
(hp_splits : Splits (RingHom.id K) p) : p.degree = 1 := by
rcases hp_splits with ⟨⟩ | hp_splits
· exfalso
simp_all
· apply hp_splits hp
simp
#align polynomial.degree_eq_one_of_irreducible_of_splits Polynomial.degree_eq_one_of_irreducible_of_splits
theorem exists_root_of_splits {f : K[X]} (hs : Splits i f) (hf0 : degree f ≠ 0) :
∃ x, eval₂ i x f = 0 :=
exists_root_of_splits' i hs ((f.degree_map i).symm ▸ hf0)
#align polynomial.exists_root_of_splits Polynomial.exists_root_of_splits
theorem roots_ne_zero_of_splits {f : K[X]} (hs : Splits i f) (hf0 : natDegree f ≠ 0) :
(f.map i).roots ≠ 0 :=
roots_ne_zero_of_splits' i hs (ne_of_eq_of_ne (natDegree_map i) hf0)
#align polynomial.roots_ne_zero_of_splits Polynomial.roots_ne_zero_of_splits
/-- Pick a root of a polynomial that splits. This version is for polynomials over a field and has
simpler assumptions. -/
def rootOfSplits {f : K[X]} (hf : f.Splits i) (hfd : f.degree ≠ 0) : L :=
rootOfSplits' i hf ((f.degree_map i).symm ▸ hfd)
#align polynomial.root_of_splits Polynomial.rootOfSplits
/-- `rootOfSplits'` is definitionally equal to `rootOfSplits`. -/
theorem rootOfSplits'_eq_rootOfSplits {f : K[X]} (hf : f.Splits i) (hfd) :
rootOfSplits' i hf hfd = rootOfSplits i hf (f.degree_map i ▸ hfd) :=
rfl
#align polynomial.root_of_splits'_eq_root_of_splits Polynomial.rootOfSplits'_eq_rootOfSplits
theorem map_rootOfSplits {f : K[X]} (hf : f.Splits i) (hfd) :
f.eval₂ i (rootOfSplits i hf hfd) = 0 :=
map_rootOfSplits' i hf (ne_of_eq_of_ne (degree_map f i) hfd)
#align polynomial.map_root_of_splits Polynomial.map_rootOfSplits
theorem natDegree_eq_card_roots {p : K[X]} {i : K →+* L} (hsplit : Splits i p) :
p.natDegree = Multiset.card (p.map i).roots :=
(natDegree_map i).symm.trans <| natDegree_eq_card_roots' hsplit
#align polynomial.nat_degree_eq_card_roots Polynomial.natDegree_eq_card_roots
theorem degree_eq_card_roots {p : K[X]} {i : K →+* L} (p_ne_zero : p ≠ 0) (hsplit : Splits i p) :
p.degree = Multiset.card (p.map i).roots := by
rw [degree_eq_natDegree p_ne_zero, natDegree_eq_card_roots hsplit]
#align polynomial.degree_eq_card_roots Polynomial.degree_eq_card_roots
theorem roots_map {f : K[X]} (hf : f.Splits <| RingHom.id K) : (f.map i).roots = f.roots.map i :=
(roots_map_of_injective_of_card_eq_natDegree i.injective <| by
convert (natDegree_eq_card_roots hf).symm
rw [map_id]).symm
#align polynomial.roots_map Polynomial.roots_map
theorem image_rootSet [Algebra R K] [Algebra R L] {p : R[X]} (h : p.Splits (algebraMap R K))
(f : K →ₐ[R] L) : f '' p.rootSet K = p.rootSet L := by
classical
rw [rootSet, ← Finset.coe_image, ← Multiset.toFinset_map, ← f.coe_toRingHom,
← roots_map _ ((splits_id_iff_splits (algebraMap R K)).mpr h), map_map, f.comp_algebraMap,
← rootSet]
#align polynomial.image_root_set Polynomial.image_rootSet
theorem adjoin_rootSet_eq_range [Algebra R K] [Algebra R L] {p : R[X]}
(h : p.Splits (algebraMap R K)) (f : K →ₐ[R] L) :
Algebra.adjoin R (p.rootSet L) = f.range ↔ Algebra.adjoin R (p.rootSet K) = ⊤ := by
rw [← image_rootSet h f, Algebra.adjoin_image, ← Algebra.map_top]
exact (Subalgebra.map_injective f.toRingHom.injective).eq_iff
#align polynomial.adjoin_root_set_eq_range Polynomial.adjoin_rootSet_eq_range
theorem eq_prod_roots_of_splits {p : K[X]} {i : K →+* L} (hsplit : Splits i p) :
p.map i = C (i p.leadingCoeff) * ((p.map i).roots.map fun a => X - C a).prod := by
rw [← leadingCoeff_map]; symm
apply C_leadingCoeff_mul_prod_multiset_X_sub_C
rw [natDegree_map]; exact (natDegree_eq_card_roots hsplit).symm
#align polynomial.eq_prod_roots_of_splits Polynomial.eq_prod_roots_of_splits
theorem eq_prod_roots_of_splits_id {p : K[X]} (hsplit : Splits (RingHom.id K) p) :
p = C p.leadingCoeff * (p.roots.map fun a => X - C a).prod := by
simpa using eq_prod_roots_of_splits hsplit
#align polynomial.eq_prod_roots_of_splits_id Polynomial.eq_prod_roots_of_splits_id
theorem eq_prod_roots_of_monic_of_splits_id {p : K[X]} (m : Monic p)
(hsplit : Splits (RingHom.id K) p) : p = (p.roots.map fun a => X - C a).prod := by
convert eq_prod_roots_of_splits_id hsplit
simp [m]
#align polynomial.eq_prod_roots_of_monic_of_splits_id Polynomial.eq_prod_roots_of_monic_of_splits_id
theorem eq_X_sub_C_of_splits_of_single_root {x : K} {h : K[X]} (h_splits : Splits i h)
(h_roots : (h.map i).roots = {i x}) : h = C h.leadingCoeff * (X - C x) := by
apply Polynomial.map_injective _ i.injective
rw [eq_prod_roots_of_splits h_splits, h_roots]
simp
set_option linter.uppercaseLean3 false in
#align polynomial.eq_X_sub_C_of_splits_of_single_root Polynomial.eq_X_sub_C_of_splits_of_single_root
variable (R) in
theorem mem_lift_of_splits_of_roots_mem_range [Algebra R K] {f : K[X]}
(hs : f.Splits (RingHom.id K)) (hm : f.Monic) (hr : ∀ a ∈ f.roots, a ∈ (algebraMap R K).range) :
f ∈ Polynomial.lifts (algebraMap R K) := by
rw [eq_prod_roots_of_monic_of_splits_id hm hs, lifts_iff_liftsRing]
refine Subring.multiset_prod_mem _ _ fun P hP => ?_
obtain ⟨b, hb, rfl⟩ := Multiset.mem_map.1 hP
exact Subring.sub_mem _ (X_mem_lifts _) (C'_mem_lifts (hr _ hb))
#align polynomial.mem_lift_of_splits_of_roots_mem_range Polynomial.mem_lift_of_splits_of_roots_mem_range
section UFD
attribute [local instance] PrincipalIdealRing.to_uniqueFactorizationMonoid
local infixl:50 " ~ᵤ " => Associated
open UniqueFactorizationMonoid Associates
theorem splits_of_exists_multiset {f : K[X]} {s : Multiset L}
(hs : f.map i = C (i f.leadingCoeff) * (s.map fun a : L => X - C a).prod) : Splits i f :=
letI := Classical.decEq K
if hf0 : f = 0 then hf0.symm ▸ splits_zero i
else
Or.inr @fun p hp hdp => by
rw [irreducible_iff_prime] at hp
rw [hs, ← Multiset.prod_toList] at hdp
obtain hd | hd := hp.2.2 _ _ hdp
· refine (hp.2.1 <| isUnit_of_dvd_unit hd ?_).elim
exact isUnit_C.2 ((leadingCoeff_ne_zero.2 hf0).isUnit.map i)
· obtain ⟨q, hq, hd⟩ := hp.dvd_prod_iff.1 hd
obtain ⟨a, _, rfl⟩ := Multiset.mem_map.1 (Multiset.mem_toList.1 hq)
rw [degree_eq_degree_of_associated ((hp.dvd_prime_iff_associated <| prime_X_sub_C a).1 hd)]
exact degree_X_sub_C a
#align polynomial.splits_of_exists_multiset Polynomial.splits_of_exists_multiset
theorem splits_of_splits_id {f : K[X]} : Splits (RingHom.id K) f → Splits i f :=
UniqueFactorizationMonoid.induction_on_prime f (fun _ => splits_zero _)
(fun _ hu _ => splits_of_degree_le_one _ ((isUnit_iff_degree_eq_zero.1 hu).symm ▸ by decide))
fun a p ha0 hp ih hfi =>
splits_mul _
(splits_of_degree_eq_one _
((splits_of_splits_mul _ (mul_ne_zero hp.1 ha0) hfi).1.def.resolve_left hp.1 hp.irreducible
(by rw [map_id])))
(ih (splits_of_splits_mul _ (mul_ne_zero hp.1 ha0) hfi).2)
#align polynomial.splits_of_splits_id Polynomial.splits_of_splits_id
end UFD
theorem splits_iff_exists_multiset {f : K[X]} :
Splits i f ↔
∃ s : Multiset L, f.map i = C (i f.leadingCoeff) * (s.map fun a : L => X - C a).prod :=
⟨fun hf => ⟨(f.map i).roots, eq_prod_roots_of_splits hf⟩, fun ⟨_, hs⟩ =>
splits_of_exists_multiset i hs⟩
#align polynomial.splits_iff_exists_multiset Polynomial.splits_iff_exists_multiset
theorem splits_of_comp (j : L →+* F) {f : K[X]} (h : Splits (j.comp i) f)
(roots_mem_range : ∀ a ∈ (f.map (j.comp i)).roots, a ∈ j.range) : Splits i f := by
choose lift lift_eq using roots_mem_range
rw [splits_iff_exists_multiset]
refine ⟨(f.map (j.comp i)).roots.pmap lift fun _ ↦ id, map_injective _ j.injective ?_⟩
conv_lhs => rw [Polynomial.map_map, eq_prod_roots_of_splits h]
simp_rw [Polynomial.map_mul, Polynomial.map_multiset_prod, Multiset.map_pmap, Polynomial.map_sub,
map_C, map_X, lift_eq, Multiset.pmap_eq_map]
rfl
theorem splits_id_of_splits {f : K[X]} (h : Splits i f)
(roots_mem_range : ∀ a ∈ (f.map i).roots, a ∈ i.range) : Splits (RingHom.id K) f :=
splits_of_comp (RingHom.id K) i h roots_mem_range
theorem splits_comp_of_splits (i : R →+* K) (j : K →+* L) {f : R[X]} (h : Splits i f) :
Splits (j.comp i) f :=
(splits_map_iff i j).mp (splits_of_splits_id _ <| (splits_map_iff i <| .id K).mpr h)
#align polynomial.splits_comp_of_splits Polynomial.splits_comp_of_splits
variable [Algebra R K] [Algebra R L]
theorem splits_of_algHom {f : R[X]} (h : Splits (algebraMap R K) f) (e : K →ₐ[R] L) :
Splits (algebraMap R L) f := by
rw [← e.comp_algebraMap_of_tower R]; exact splits_comp_of_splits _ _ h
variable (L) in
theorem splits_of_isScalarTower {f : R[X]} [Algebra K L] [IsScalarTower R K L]
(h : Splits (algebraMap R K) f) : Splits (algebraMap R L) f :=
splits_of_algHom h (IsScalarTower.toAlgHom R K L)
/-- A polynomial splits if and only if it has as many roots as its degree. -/
theorem splits_iff_card_roots {p : K[X]} :
Splits (RingHom.id K) p ↔ Multiset.card p.roots = p.natDegree := by
constructor
· intro H
rw [natDegree_eq_card_roots H, map_id]
· intro hroots
rw [splits_iff_exists_multiset (RingHom.id K)]
use p.roots
simp only [RingHom.id_apply, map_id]
exact (C_leadingCoeff_mul_prod_multiset_X_sub_C hroots).symm
#align polynomial.splits_iff_card_roots Polynomial.splits_iff_card_roots
theorem aeval_root_derivative_of_splits [Algebra K L] [DecidableEq L] {P : K[X]} (hmo : P.Monic)
(hP : P.Splits (algebraMap K L)) {r : L} (hr : r ∈ P.aroots L) :
aeval r (Polynomial.derivative P) =
(((P.aroots L).erase r).map fun a => r - a).prod := by
replace hmo := hmo.map (algebraMap K L)
replace hP := (splits_id_iff_splits (algebraMap K L)).2 hP
rw [aeval_def, ← eval_map, ← derivative_map]
nth_rw 1 [eq_prod_roots_of_monic_of_splits_id hmo hP]
rw [eval_multiset_prod_X_sub_C_derivative hr]
#align polynomial.aeval_root_derivative_of_splits Polynomial.aeval_root_derivative_of_splits
/-- If `P` is a monic polynomial that splits, then `coeff P 0` equals the product of the roots. -/
theorem prod_roots_eq_coeff_zero_of_monic_of_split {P : K[X]} (hmo : P.Monic)
(hP : P.Splits (RingHom.id K)) : coeff P 0 = (-1) ^ P.natDegree * P.roots.prod := by
nth_rw 1 [eq_prod_roots_of_monic_of_splits_id hmo hP]
rw [coeff_zero_eq_eval_zero, eval_multiset_prod, Multiset.map_map]
simp_rw [Function.comp_apply, eval_sub, eval_X, zero_sub, eval_C]
conv_lhs =>
congr
congr
ext
rw [neg_eq_neg_one_mul]
simp only [splits_iff_card_roots.1 hP, neg_mul, one_mul, Multiset.prod_map_neg]
#align polynomial.prod_roots_eq_coeff_zero_of_monic_of_split Polynomial.prod_roots_eq_coeff_zero_of_monic_of_split
/-- If `P` is a monic polynomial that splits, then `P.nextCoeff` equals the sum of the roots. -/
| Mathlib/Algebra/Polynomial/Splits.lean | 495 | 500 | theorem sum_roots_eq_nextCoeff_of_monic_of_split {P : K[X]} (hmo : P.Monic)
(hP : P.Splits (RingHom.id K)) : P.nextCoeff = -P.roots.sum := by |
nth_rw 1 [eq_prod_roots_of_monic_of_splits_id hmo hP]
rw [Monic.nextCoeff_multiset_prod _ _ fun a ha => _]
· simp_rw [nextCoeff_X_sub_C, Multiset.sum_map_neg']
· simp only [monic_X_sub_C, implies_true]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Compactness.SigmaCompact
import Mathlib.Topology.Connected.TotallyDisconnected
import Mathlib.Topology.Inseparable
#align_import topology.separation from "leanprover-community/mathlib"@"d91e7f7a7f1c7e9f0e18fdb6bde4f652004c735d"
/-!
# Separation properties of topological spaces.
This file defines the predicate `SeparatedNhds`, and common separation axioms
(under the Kolmogorov classification).
## Main definitions
* `SeparatedNhds`: Two `Set`s are separated by neighbourhoods if they are contained in disjoint
open sets.
* `T0Space`: A T₀/Kolmogorov space is a space where, for every two points `x ≠ y`,
there is an open set that contains one, but not the other.
* `R0Space`: An R₀ space (sometimes called a *symmetric space*) is a topological space
such that the `Specializes` relation is symmetric.
* `T1Space`: A T₁/Fréchet space is a space where every singleton set is closed.
This is equivalent to, for every pair `x ≠ y`, there existing an open set containing `x`
but not `y` (`t1Space_iff_exists_open` shows that these conditions are equivalent.)
T₁ implies T₀ and R₀.
* `R1Space`: An R₁/preregular space is a space where any two topologically distinguishable points
have disjoint neighbourhoods. R₁ implies R₀.
* `T2Space`: A T₂/Hausdorff space is a space where, for every two points `x ≠ y`,
there is two disjoint open sets, one containing `x`, and the other `y`. T₂ implies T₁ and R₁.
* `T25Space`: A T₂.₅/Urysohn space is a space where, for every two points `x ≠ y`,
there is two open sets, one containing `x`, and the other `y`, whose closures are disjoint.
T₂.₅ implies T₂.
* `RegularSpace`: A regular space is one where, given any closed `C` and `x ∉ C`,
there are disjoint open sets containing `x` and `C` respectively. Such a space is not necessarily
Hausdorff.
* `T3Space`: A T₃ space is a regular T₀ space. T₃ implies T₂.₅.
* `NormalSpace`: A normal space, is one where given two disjoint closed sets,
we can find two open sets that separate them. Such a space is not necessarily Hausdorff, even if
it is T₀.
* `T4Space`: A T₄ space is a normal T₁ space. T₄ implies T₃.
* `CompletelyNormalSpace`: A completely normal space is one in which for any two sets `s`, `t`
such that if both `closure s` is disjoint with `t`, and `s` is disjoint with `closure t`,
then there exist disjoint neighbourhoods of `s` and `t`. `Embedding.completelyNormalSpace` allows
us to conclude that this is equivalent to all subspaces being normal. Such a space is not
necessarily Hausdorff or regular, even if it is T₀.
* `T5Space`: A T₅ space is a completely normal T₁ space. T₅ implies T₄.
Note that `mathlib` adopts the modern convention that `m ≤ n` if and only if `T_m → T_n`, but
occasionally the literature swaps definitions for e.g. T₃ and regular.
## Main results
### T₀ spaces
* `IsClosed.exists_closed_singleton`: Given a closed set `S` in a compact T₀ space,
there is some `x ∈ S` such that `{x}` is closed.
* `exists_isOpen_singleton_of_isOpen_finite`: Given an open finite set `S` in a T₀ space,
there is some `x ∈ S` such that `{x}` is open.
### T₁ spaces
* `isClosedMap_const`: The constant map is a closed map.
* `discrete_of_t1_of_finite`: A finite T₁ space must have the discrete topology.
### T₂ spaces
* `t2_iff_nhds`: A space is T₂ iff the neighbourhoods of distinct points generate the bottom filter.
* `t2_iff_isClosed_diagonal`: A space is T₂ iff the `diagonal` of `X` (that is, the set of all
points of the form `(a, a) : X × X`) is closed under the product topology.
* `separatedNhds_of_finset_finset`: Any two disjoint finsets are `SeparatedNhds`.
* Most topological constructions preserve Hausdorffness;
these results are part of the typeclass inference system (e.g. `Embedding.t2Space`)
* `Set.EqOn.closure`: If two functions are equal on some set `s`, they are equal on its closure.
* `IsCompact.isClosed`: All compact sets are closed.
* `WeaklyLocallyCompactSpace.locallyCompactSpace`: If a topological space is both
weakly locally compact (i.e., each point has a compact neighbourhood)
and is T₂, then it is locally compact.
* `totallySeparatedSpace_of_t1_of_basis_clopen`: If `X` has a clopen basis, then
it is a `TotallySeparatedSpace`.
* `loc_compact_t2_tot_disc_iff_tot_sep`: A locally compact T₂ space is totally disconnected iff
it is totally separated.
* `t2Quotient`: the largest T2 quotient of a given topological space.
If the space is also compact:
* `normalOfCompactT2`: A compact T₂ space is a `NormalSpace`.
* `connectedComponent_eq_iInter_isClopen`: The connected component of a point
is the intersection of all its clopen neighbourhoods.
* `compact_t2_tot_disc_iff_tot_sep`: Being a `TotallyDisconnectedSpace`
is equivalent to being a `TotallySeparatedSpace`.
* `ConnectedComponents.t2`: `ConnectedComponents X` is T₂ for `X` T₂ and compact.
### T₃ spaces
* `disjoint_nested_nhds`: Given two points `x ≠ y`, we can find neighbourhoods `x ∈ V₁ ⊆ U₁` and
`y ∈ V₂ ⊆ U₂`, with the `Vₖ` closed and the `Uₖ` open, such that the `Uₖ` are disjoint.
## References
https://en.wikipedia.org/wiki/Separation_axiom
-/
open Function Set Filter Topology TopologicalSpace
open scoped Classical
universe u v
variable {X : Type*} {Y : Type*} [TopologicalSpace X]
section Separation
/--
`SeparatedNhds` is a predicate on pairs of sub`Set`s of a topological space. It holds if the two
sub`Set`s are contained in disjoint open sets.
-/
def SeparatedNhds : Set X → Set X → Prop := fun s t : Set X =>
∃ U V : Set X, IsOpen U ∧ IsOpen V ∧ s ⊆ U ∧ t ⊆ V ∧ Disjoint U V
#align separated_nhds SeparatedNhds
theorem separatedNhds_iff_disjoint {s t : Set X} : SeparatedNhds s t ↔ Disjoint (𝓝ˢ s) (𝓝ˢ t) := by
simp only [(hasBasis_nhdsSet s).disjoint_iff (hasBasis_nhdsSet t), SeparatedNhds, exists_prop, ←
exists_and_left, and_assoc, and_comm, and_left_comm]
#align separated_nhds_iff_disjoint separatedNhds_iff_disjoint
alias ⟨SeparatedNhds.disjoint_nhdsSet, _⟩ := separatedNhds_iff_disjoint
namespace SeparatedNhds
variable {s s₁ s₂ t t₁ t₂ u : Set X}
@[symm]
theorem symm : SeparatedNhds s t → SeparatedNhds t s := fun ⟨U, V, oU, oV, aU, bV, UV⟩ =>
⟨V, U, oV, oU, bV, aU, Disjoint.symm UV⟩
#align separated_nhds.symm SeparatedNhds.symm
theorem comm (s t : Set X) : SeparatedNhds s t ↔ SeparatedNhds t s :=
⟨symm, symm⟩
#align separated_nhds.comm SeparatedNhds.comm
theorem preimage [TopologicalSpace Y] {f : X → Y} {s t : Set Y} (h : SeparatedNhds s t)
(hf : Continuous f) : SeparatedNhds (f ⁻¹' s) (f ⁻¹' t) :=
let ⟨U, V, oU, oV, sU, tV, UV⟩ := h
⟨f ⁻¹' U, f ⁻¹' V, oU.preimage hf, oV.preimage hf, preimage_mono sU, preimage_mono tV,
UV.preimage f⟩
#align separated_nhds.preimage SeparatedNhds.preimage
protected theorem disjoint (h : SeparatedNhds s t) : Disjoint s t :=
let ⟨_, _, _, _, hsU, htV, hd⟩ := h; hd.mono hsU htV
#align separated_nhds.disjoint SeparatedNhds.disjoint
theorem disjoint_closure_left (h : SeparatedNhds s t) : Disjoint (closure s) t :=
let ⟨_U, _V, _, hV, hsU, htV, hd⟩ := h
(hd.closure_left hV).mono (closure_mono hsU) htV
#align separated_nhds.disjoint_closure_left SeparatedNhds.disjoint_closure_left
theorem disjoint_closure_right (h : SeparatedNhds s t) : Disjoint s (closure t) :=
h.symm.disjoint_closure_left.symm
#align separated_nhds.disjoint_closure_right SeparatedNhds.disjoint_closure_right
@[simp] theorem empty_right (s : Set X) : SeparatedNhds s ∅ :=
⟨_, _, isOpen_univ, isOpen_empty, fun a _ => mem_univ a, Subset.rfl, disjoint_empty _⟩
#align separated_nhds.empty_right SeparatedNhds.empty_right
@[simp] theorem empty_left (s : Set X) : SeparatedNhds ∅ s :=
(empty_right _).symm
#align separated_nhds.empty_left SeparatedNhds.empty_left
theorem mono (h : SeparatedNhds s₂ t₂) (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) : SeparatedNhds s₁ t₁ :=
let ⟨U, V, hU, hV, hsU, htV, hd⟩ := h
⟨U, V, hU, hV, hs.trans hsU, ht.trans htV, hd⟩
#align separated_nhds.mono SeparatedNhds.mono
theorem union_left : SeparatedNhds s u → SeparatedNhds t u → SeparatedNhds (s ∪ t) u := by
simpa only [separatedNhds_iff_disjoint, nhdsSet_union, disjoint_sup_left] using And.intro
#align separated_nhds.union_left SeparatedNhds.union_left
theorem union_right (ht : SeparatedNhds s t) (hu : SeparatedNhds s u) : SeparatedNhds s (t ∪ u) :=
(ht.symm.union_left hu.symm).symm
#align separated_nhds.union_right SeparatedNhds.union_right
end SeparatedNhds
/-- A T₀ space, also known as a Kolmogorov space, is a topological space such that for every pair
`x ≠ y`, there is an open set containing one but not the other. We formulate the definition in terms
of the `Inseparable` relation. -/
class T0Space (X : Type u) [TopologicalSpace X] : Prop where
/-- Two inseparable points in a T₀ space are equal. -/
t0 : ∀ ⦃x y : X⦄, Inseparable x y → x = y
#align t0_space T0Space
theorem t0Space_iff_inseparable (X : Type u) [TopologicalSpace X] :
T0Space X ↔ ∀ x y : X, Inseparable x y → x = y :=
⟨fun ⟨h⟩ => h, fun h => ⟨h⟩⟩
#align t0_space_iff_inseparable t0Space_iff_inseparable
theorem t0Space_iff_not_inseparable (X : Type u) [TopologicalSpace X] :
T0Space X ↔ Pairwise fun x y : X => ¬Inseparable x y := by
simp only [t0Space_iff_inseparable, Ne, not_imp_not, Pairwise]
#align t0_space_iff_not_inseparable t0Space_iff_not_inseparable
theorem Inseparable.eq [T0Space X] {x y : X} (h : Inseparable x y) : x = y :=
T0Space.t0 h
#align inseparable.eq Inseparable.eq
/-- A topology `Inducing` map from a T₀ space is injective. -/
protected theorem Inducing.injective [TopologicalSpace Y] [T0Space X] {f : X → Y}
(hf : Inducing f) : Injective f := fun _ _ h =>
(hf.inseparable_iff.1 <| .of_eq h).eq
#align inducing.injective Inducing.injective
/-- A topology `Inducing` map from a T₀ space is a topological embedding. -/
protected theorem Inducing.embedding [TopologicalSpace Y] [T0Space X] {f : X → Y}
(hf : Inducing f) : Embedding f :=
⟨hf, hf.injective⟩
#align inducing.embedding Inducing.embedding
lemma embedding_iff_inducing [TopologicalSpace Y] [T0Space X] {f : X → Y} :
Embedding f ↔ Inducing f :=
⟨Embedding.toInducing, Inducing.embedding⟩
#align embedding_iff_inducing embedding_iff_inducing
theorem t0Space_iff_nhds_injective (X : Type u) [TopologicalSpace X] :
T0Space X ↔ Injective (𝓝 : X → Filter X) :=
t0Space_iff_inseparable X
#align t0_space_iff_nhds_injective t0Space_iff_nhds_injective
theorem nhds_injective [T0Space X] : Injective (𝓝 : X → Filter X) :=
(t0Space_iff_nhds_injective X).1 ‹_›
#align nhds_injective nhds_injective
theorem inseparable_iff_eq [T0Space X] {x y : X} : Inseparable x y ↔ x = y :=
nhds_injective.eq_iff
#align inseparable_iff_eq inseparable_iff_eq
@[simp]
theorem nhds_eq_nhds_iff [T0Space X] {a b : X} : 𝓝 a = 𝓝 b ↔ a = b :=
nhds_injective.eq_iff
#align nhds_eq_nhds_iff nhds_eq_nhds_iff
@[simp]
theorem inseparable_eq_eq [T0Space X] : Inseparable = @Eq X :=
funext₂ fun _ _ => propext inseparable_iff_eq
#align inseparable_eq_eq inseparable_eq_eq
theorem TopologicalSpace.IsTopologicalBasis.inseparable_iff {b : Set (Set X)}
(hb : IsTopologicalBasis b) {x y : X} : Inseparable x y ↔ ∀ s ∈ b, (x ∈ s ↔ y ∈ s) :=
⟨fun h s hs ↦ inseparable_iff_forall_open.1 h _ (hb.isOpen hs),
fun h ↦ hb.nhds_hasBasis.eq_of_same_basis <| by
convert hb.nhds_hasBasis using 2
exact and_congr_right (h _)⟩
theorem TopologicalSpace.IsTopologicalBasis.eq_iff [T0Space X] {b : Set (Set X)}
(hb : IsTopologicalBasis b) {x y : X} : x = y ↔ ∀ s ∈ b, (x ∈ s ↔ y ∈ s) :=
inseparable_iff_eq.symm.trans hb.inseparable_iff
theorem t0Space_iff_exists_isOpen_xor'_mem (X : Type u) [TopologicalSpace X] :
T0Space X ↔ Pairwise fun x y => ∃ U : Set X, IsOpen U ∧ Xor' (x ∈ U) (y ∈ U) := by
simp only [t0Space_iff_not_inseparable, xor_iff_not_iff, not_forall, exists_prop,
inseparable_iff_forall_open, Pairwise]
#align t0_space_iff_exists_is_open_xor_mem t0Space_iff_exists_isOpen_xor'_mem
theorem exists_isOpen_xor'_mem [T0Space X] {x y : X} (h : x ≠ y) :
∃ U : Set X, IsOpen U ∧ Xor' (x ∈ U) (y ∈ U) :=
(t0Space_iff_exists_isOpen_xor'_mem X).1 ‹_› h
#align exists_is_open_xor_mem exists_isOpen_xor'_mem
/-- Specialization forms a partial order on a t0 topological space. -/
def specializationOrder (X) [TopologicalSpace X] [T0Space X] : PartialOrder X :=
{ specializationPreorder X, PartialOrder.lift (OrderDual.toDual ∘ 𝓝) nhds_injective with }
#align specialization_order specializationOrder
instance SeparationQuotient.instT0Space : T0Space (SeparationQuotient X) :=
⟨fun x y => Quotient.inductionOn₂' x y fun _ _ h =>
SeparationQuotient.mk_eq_mk.2 <| SeparationQuotient.inducing_mk.inseparable_iff.1 h⟩
theorem minimal_nonempty_closed_subsingleton [T0Space X] {s : Set X} (hs : IsClosed s)
(hmin : ∀ t, t ⊆ s → t.Nonempty → IsClosed t → t = s) : s.Subsingleton := by
clear Y -- Porting note: added
refine fun x hx y hy => of_not_not fun hxy => ?_
rcases exists_isOpen_xor'_mem hxy with ⟨U, hUo, hU⟩
wlog h : x ∈ U ∧ y ∉ U
· refine this hs hmin y hy x hx (Ne.symm hxy) U hUo hU.symm (hU.resolve_left h)
cases' h with hxU hyU
have : s \ U = s := hmin (s \ U) diff_subset ⟨y, hy, hyU⟩ (hs.sdiff hUo)
exact (this.symm.subset hx).2 hxU
#align minimal_nonempty_closed_subsingleton minimal_nonempty_closed_subsingleton
theorem minimal_nonempty_closed_eq_singleton [T0Space X] {s : Set X} (hs : IsClosed s)
(hne : s.Nonempty) (hmin : ∀ t, t ⊆ s → t.Nonempty → IsClosed t → t = s) : ∃ x, s = {x} :=
exists_eq_singleton_iff_nonempty_subsingleton.2
⟨hne, minimal_nonempty_closed_subsingleton hs hmin⟩
#align minimal_nonempty_closed_eq_singleton minimal_nonempty_closed_eq_singleton
/-- Given a closed set `S` in a compact T₀ space, there is some `x ∈ S` such that `{x}` is
closed. -/
| Mathlib/Topology/Separation.lean | 301 | 305 | theorem IsClosed.exists_closed_singleton [T0Space X] [CompactSpace X] {S : Set X}
(hS : IsClosed S) (hne : S.Nonempty) : ∃ x : X, x ∈ S ∧ IsClosed ({x} : Set X) := by |
obtain ⟨V, Vsub, Vne, Vcls, hV⟩ := hS.exists_minimal_nonempty_closed_subset hne
rcases minimal_nonempty_closed_eq_singleton Vcls Vne hV with ⟨x, rfl⟩
exact ⟨x, Vsub (mem_singleton x), Vcls⟩
|
/-
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]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 1,015 | 1,031 | 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
|
/-
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.Decomposition.RadonNikodym
import Mathlib.MeasureTheory.Measure.Haar.OfBasis
import Mathlib.Probability.Independence.Basic
#align_import probability.density from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Probability density function
This file defines the probability density function of random variables, by which we mean
measurable functions taking values in a Borel space. The probability density function is defined
as the Radon–Nikodym derivative of the law of `X`. In particular, a measurable function `f`
is said to the probability density function of a random variable `X` if for all measurable
sets `S`, `ℙ(X ∈ S) = ∫ x in S, f x dx`. Probability density functions are one way of describing
the distribution of a random variable, and are useful for calculating probabilities and
finding moments (although the latter is better achieved with moment generating functions).
This file also defines the continuous uniform distribution and proves some properties about
random variables with this distribution.
## Main definitions
* `MeasureTheory.HasPDF` : A random variable `X : Ω → E` is said to `HasPDF` with
respect to the measure `ℙ` on `Ω` and `μ` on `E` if the push-forward measure of `ℙ` along `X`
is absolutely continuous with respect to `μ` and they `HaveLebesgueDecomposition`.
* `MeasureTheory.pdf` : If `X` is a random variable that `HasPDF X ℙ μ`, then `pdf X`
is the Radon–Nikodym derivative of the push-forward measure of `ℙ` along `X` with respect to `μ`.
* `MeasureTheory.pdf.IsUniform` : A random variable `X` is said to follow the uniform
distribution if it has a constant probability density function with a compact, non-null support.
## Main results
* `MeasureTheory.pdf.integral_pdf_smul` : Law of the unconscious statistician,
i.e. if a random variable `X : Ω → E` has pdf `f`, then `𝔼(g(X)) = ∫ x, f x • g x dx` for
all measurable `g : E → F`.
* `MeasureTheory.pdf.integral_mul_eq_integral` : A real-valued random variable `X` with
pdf `f` has expectation `∫ x, x * f x dx`.
* `MeasureTheory.pdf.IsUniform.integral_eq` : If `X` follows the uniform distribution with
its pdf having support `s`, then `X` has expectation `(λ s)⁻¹ * ∫ x in s, x dx` where `λ`
is the Lebesgue measure.
## TODOs
Ultimately, we would also like to define characteristic functions to describe distributions as
it exists for all random variables. However, to define this, we will need Fourier transforms
which we currently do not have.
-/
open scoped Classical MeasureTheory NNReal ENNReal
open TopologicalSpace MeasureTheory.Measure
noncomputable section
namespace MeasureTheory
variable {Ω E : Type*} [MeasurableSpace E]
/-- A random variable `X : Ω → E` is said to `HasPDF` with respect to the measure `ℙ` on `Ω` and
`μ` on `E` if the push-forward measure of `ℙ` along `X` is absolutely continuous with respect to
`μ` and they `HaveLebesgueDecomposition`. -/
class HasPDF {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω)
(μ : Measure E := by volume_tac) : Prop where
pdf' : AEMeasurable X ℙ ∧ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ
#align measure_theory.has_pdf MeasureTheory.HasPDF
section HasPDF
variable {_ : MeasurableSpace Ω}
theorem hasPDF_iff {X : Ω → E} {ℙ : Measure Ω} {μ : Measure E} :
HasPDF X ℙ μ ↔ AEMeasurable X ℙ ∧ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ :=
⟨@HasPDF.pdf' _ _ _ _ _ _ _, HasPDF.mk⟩
#align measure_theory.pdf.has_pdf_iff MeasureTheory.hasPDF_iff
theorem hasPDF_iff_of_aemeasurable {X : Ω → E} {ℙ : Measure Ω}
{μ : Measure E} (hX : AEMeasurable X ℙ) :
HasPDF X ℙ μ ↔ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ := by
rw [hasPDF_iff]
simp only [hX, true_and]
#align measure_theory.pdf.has_pdf_iff_of_measurable MeasureTheory.hasPDF_iff_of_aemeasurable
@[measurability]
theorem HasPDF.aemeasurable (X : Ω → E) (ℙ : Measure Ω)
(μ : Measure E) [hX : HasPDF X ℙ μ] : AEMeasurable X ℙ :=
hX.pdf'.1
#align measure_theory.has_pdf.measurable MeasureTheory.HasPDF.aemeasurable
instance HasPDF.haveLebesgueDecomposition {X : Ω → E} {ℙ : Measure Ω}
{μ : Measure E} [hX : HasPDF X ℙ μ] : (map X ℙ).HaveLebesgueDecomposition μ :=
hX.pdf'.2.1
#align measure_theory.pdf.have_lebesgue_decomposition_of_has_pdf MeasureTheory.HasPDF.haveLebesgueDecomposition
theorem HasPDF.absolutelyContinuous {X : Ω → E} {ℙ : Measure Ω} {μ : Measure E}
[hX : HasPDF X ℙ μ] : map X ℙ ≪ μ :=
hX.pdf'.2.2
#align measure_theory.pdf.map_absolutely_continuous MeasureTheory.HasPDF.absolutelyContinuous
/-- A random variable that `HasPDF` is quasi-measure preserving. -/
theorem HasPDF.quasiMeasurePreserving_of_measurable (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E)
[HasPDF X ℙ μ] (h : Measurable X) : QuasiMeasurePreserving X ℙ μ :=
{ measurable := h
absolutelyContinuous := HasPDF.absolutelyContinuous }
#align measure_theory.pdf.to_quasi_measure_preserving MeasureTheory.HasPDF.quasiMeasurePreserving_of_measurable
theorem HasPDF.congr {X Y : Ω → E} {ℙ : Measure Ω} {μ : Measure E} (hXY : X =ᵐ[ℙ] Y)
[hX : HasPDF X ℙ μ] : HasPDF Y ℙ μ :=
⟨(HasPDF.aemeasurable X ℙ μ).congr hXY, ℙ.map_congr hXY ▸ hX.haveLebesgueDecomposition,
ℙ.map_congr hXY ▸ hX.absolutelyContinuous⟩
theorem HasPDF.congr' {X Y : Ω → E} {ℙ : Measure Ω} {μ : Measure E} (hXY : X =ᵐ[ℙ] Y) :
HasPDF X ℙ μ ↔ HasPDF Y ℙ μ :=
⟨fun _ ↦ HasPDF.congr hXY, fun _ ↦ HasPDF.congr hXY.symm⟩
/-- X `HasPDF` if there is a pdf `f` such that `map X ℙ = μ.withDensity f`. -/
theorem hasPDF_of_map_eq_withDensity {X : Ω → E} {ℙ : Measure Ω} {μ : Measure E}
(hX : AEMeasurable X ℙ) (f : E → ℝ≥0∞) (hf : AEMeasurable f μ) (h : map X ℙ = μ.withDensity f) :
HasPDF X ℙ μ := by
refine ⟨hX, ?_, ?_⟩ <;> rw [h]
· rw [withDensity_congr_ae hf.ae_eq_mk]
exact haveLebesgueDecomposition_withDensity μ hf.measurable_mk
· exact withDensity_absolutelyContinuous μ f
end HasPDF
/-- If `X` is a random variable, then `pdf X` is the Radon–Nikodym derivative of the push-forward
measure of `ℙ` along `X` with respect to `μ`. -/
def pdf {_ : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) :
E → ℝ≥0∞ :=
(map X ℙ).rnDeriv μ
#align measure_theory.pdf MeasureTheory.pdf
theorem pdf_def {_ : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E} :
pdf X ℙ μ = (map X ℙ).rnDeriv μ := rfl
theorem pdf_of_not_aemeasurable {_ : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E}
{X : Ω → E} (hX : ¬AEMeasurable X ℙ) : pdf X ℙ μ =ᵐ[μ] 0 := by
rw [pdf_def, map_of_not_aemeasurable hX]
exact rnDeriv_zero μ
#align measure_theory.pdf_eq_zero_of_not_measurable MeasureTheory.pdf_of_not_aemeasurable
theorem pdf_of_not_haveLebesgueDecomposition {_ : MeasurableSpace Ω} {ℙ : Measure Ω}
{μ : Measure E} {X : Ω → E} (h : ¬(map X ℙ).HaveLebesgueDecomposition μ) : pdf X ℙ μ = 0 :=
rnDeriv_of_not_haveLebesgueDecomposition h
theorem aemeasurable_of_pdf_ne_zero {m : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E}
(X : Ω → E) (h : ¬pdf X ℙ μ =ᵐ[μ] 0) : AEMeasurable X ℙ := by
contrapose! h
exact pdf_of_not_aemeasurable h
#align measure_theory.measurable_of_pdf_ne_zero MeasureTheory.aemeasurable_of_pdf_ne_zero
theorem hasPDF_of_pdf_ne_zero {m : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E}
(hac : map X ℙ ≪ μ) (hpdf : ¬pdf X ℙ μ =ᵐ[μ] 0) : HasPDF X ℙ μ := by
refine ⟨?_, ?_, hac⟩
· exact aemeasurable_of_pdf_ne_zero X hpdf
· contrapose! hpdf
have := pdf_of_not_haveLebesgueDecomposition hpdf
filter_upwards using congrFun this
#align measure_theory.has_pdf_of_pdf_ne_zero MeasureTheory.hasPDF_of_pdf_ne_zero
@[measurability]
| Mathlib/Probability/Density.lean | 168 | 170 | theorem measurable_pdf {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω)
(μ : Measure E := by | volume_tac) : Measurable (pdf X ℙ μ) := by
exact measurable_rnDeriv _ _
|
/-
Copyright (c) 2023 Xavier Généreux. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Généreux, Patrick Massot
-/
import Mathlib.Analysis.SpecificLimits.Basic
import Mathlib.Analysis.RCLike.Basic
/-!
# A collection of specific limit computations for `RCLike`
-/
open Set Algebra Filter
open scoped Topology
variable (𝕜 : Type*) [RCLike 𝕜]
| Mathlib/Analysis/SpecificLimits/RCLike.lean | 19 | 22 | theorem RCLike.tendsto_inverse_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ => (n : 𝕜)⁻¹) atTop (𝓝 0) := by |
convert tendsto_algebraMap_inverse_atTop_nhds_zero_nat 𝕜
simp
|
/-
Copyright (c) 2022 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.AlgebraicTopology.DoldKan.FunctorN
#align_import algebraic_topology.dold_kan.normalized from "leanprover-community/mathlib"@"32a7e535287f9c73f2e4d2aef306a39190f0b504"
/-!
# Comparison with the normalized Moore complex functor
In this file, we show that when the category `A` is abelian,
there is an isomorphism `N₁_iso_normalizedMooreComplex_comp_toKaroubi` between
the functor `N₁ : SimplicialObject A ⥤ Karoubi (ChainComplex A ℕ)`
defined in `FunctorN.lean` and the composition of
`normalizedMooreComplex A` with the inclusion
`ChainComplex A ℕ ⥤ Karoubi (ChainComplex A ℕ)`.
This isomorphism shall be used in `Equivalence.lean` in order to obtain
the Dold-Kan equivalence
`CategoryTheory.Abelian.DoldKan.equivalence : SimplicialObject A ≌ ChainComplex A ℕ`
with a functor (definitionally) equal to `normalizedMooreComplex A`.
(See `Equivalence.lean` for the general strategy of proof of the Dold-Kan equivalence.)
-/
open CategoryTheory CategoryTheory.Category CategoryTheory.Limits
CategoryTheory.Subobject CategoryTheory.Idempotents DoldKan
noncomputable section
namespace AlgebraicTopology
namespace DoldKan
universe v
variable {A : Type*} [Category A] [Abelian A] {X : SimplicialObject A}
theorem HigherFacesVanish.inclusionOfMooreComplexMap (n : ℕ) :
HigherFacesVanish (n + 1) ((inclusionOfMooreComplexMap X).f (n + 1)) := fun j _ => by
dsimp [AlgebraicTopology.inclusionOfMooreComplexMap, NormalizedMooreComplex.objX]
rw [← factorThru_arrow _ _ (finset_inf_arrow_factors Finset.univ _ j
(by simp only [Finset.mem_univ])), assoc, kernelSubobject_arrow_comp, comp_zero]
set_option linter.uppercaseLean3 false in
#align algebraic_topology.dold_kan.higher_faces_vanish.inclusion_of_Moore_complex_map AlgebraicTopology.DoldKan.HigherFacesVanish.inclusionOfMooreComplexMap
| Mathlib/AlgebraicTopology/DoldKan/Normalized.lean | 52 | 59 | theorem factors_normalizedMooreComplex_PInfty (n : ℕ) :
Subobject.Factors (NormalizedMooreComplex.objX X n) (PInfty.f n) := by |
rcases n with _|n
· apply top_factors
· rw [PInfty_f, NormalizedMooreComplex.objX, finset_inf_factors]
intro i _
apply kernelSubobject_factors
exact (HigherFacesVanish.of_P (n + 1) n) i le_add_self
|
/-
Copyright (c) 2021 Bryan Gin-ge Chen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bryan Gin-ge Chen, Yury Kudryashov
-/
import Mathlib.Algebra.Group.Hom.Defs
#align_import algebra.group.ext from "leanprover-community/mathlib"@"e574b1a4e891376b0ef974b926da39e05da12a06"
/-!
# Extensionality lemmas for monoid and group structures
In this file we prove extensionality lemmas for `Monoid` and higher algebraic structures with one
binary operation. Extensionality lemmas for structures that are lower in the hierarchy can be found
in `Algebra.Group.Defs`.
## Implementation details
To get equality of `npow` etc, we define a monoid homomorphism between two monoid structures on the
same type, then apply lemmas like `MonoidHom.map_div`, `MonoidHom.map_pow` etc.
To refer to the `*` operator of a particular instance `i`, we use
`(letI := i; HMul.hMul : M → M → M)` instead of `i.mul` (which elaborates to `Mul.mul`), as the
former uses `HMul.hMul` which is the canonical spelling.
## Tags
monoid, group, extensionality
-/
assert_not_exists MonoidWithZero
assert_not_exists DenselyOrdered
open Function
universe u
@[to_additive (attr := ext)]
theorem Monoid.ext {M : Type u} ⦃m₁ m₂ : Monoid M⦄
(h_mul : (letI := m₁; HMul.hMul : M → M → M) = (letI := m₂; HMul.hMul : M → M → M)) :
m₁ = m₂ := by
have : m₁.toMulOneClass = m₂.toMulOneClass := MulOneClass.ext h_mul
have h₁ : m₁.one = m₂.one := congr_arg (·.one) this
let f : @MonoidHom M M m₁.toMulOneClass m₂.toMulOneClass :=
@MonoidHom.mk _ _ (_) _ (@OneHom.mk _ _ (_) _ id h₁)
(fun x y => congr_fun (congr_fun h_mul x) y)
have : m₁.npow = m₂.npow := by
ext n x
exact @MonoidHom.map_pow M M m₁ m₂ f x n
rcases m₁ with @⟨@⟨⟨_⟩⟩, ⟨_⟩⟩
rcases m₂ with @⟨@⟨⟨_⟩⟩, ⟨_⟩⟩
congr
#align monoid.ext Monoid.ext
#align add_monoid.ext AddMonoid.ext
@[to_additive]
theorem CommMonoid.toMonoid_injective {M : Type u} :
Function.Injective (@CommMonoid.toMonoid M) := by
rintro ⟨⟩ ⟨⟩ h
congr
#align comm_monoid.to_monoid_injective CommMonoid.toMonoid_injective
#align add_comm_monoid.to_add_monoid_injective AddCommMonoid.toAddMonoid_injective
@[to_additive (attr := ext)]
theorem CommMonoid.ext {M : Type*} ⦃m₁ m₂ : CommMonoid M⦄
(h_mul : (letI := m₁; HMul.hMul : M → M → M) = (letI := m₂; HMul.hMul : M → M → M)) : m₁ = m₂ :=
CommMonoid.toMonoid_injective <| Monoid.ext h_mul
#align comm_monoid.ext CommMonoid.ext
#align add_comm_monoid.ext AddCommMonoid.ext
@[to_additive]
| Mathlib/Algebra/Group/Ext.lean | 71 | 74 | theorem LeftCancelMonoid.toMonoid_injective {M : Type u} :
Function.Injective (@LeftCancelMonoid.toMonoid M) := by |
rintro @⟨@⟨⟩⟩ @⟨@⟨⟩⟩ h
congr <;> injection h
|
/-
Copyright (c) 2022 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.Balanced
import Mathlib.CategoryTheory.Limits.EssentiallySmall
import Mathlib.CategoryTheory.Limits.Opposites
import Mathlib.CategoryTheory.Limits.Shapes.ZeroMorphisms
import Mathlib.CategoryTheory.Subobject.Lattice
import Mathlib.CategoryTheory.Subobject.WellPowered
import Mathlib.Data.Set.Opposite
import Mathlib.Data.Set.Subsingleton
#align_import category_theory.generator from "leanprover-community/mathlib"@"f187f1074fa1857c94589cc653c786cadc4c35ff"
/-!
# Separating and detecting sets
There are several non-equivalent notions of a generator of a category. Here, we consider two of
them:
* We say that `𝒢` is a separating set if the functors `C(G, -)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `h ≫ f = h ≫ g` for all `h` with domain in `𝒢` implies `f = g`.
* We say that `𝒢` is a detecting set if the functors `C(G, -)` collectively reflect isomorphisms,
i.e., if any `h` with domain in `𝒢` uniquely factors through `f`, then `f` is an isomorphism.
There are, of course, also the dual notions of coseparating and codetecting sets.
## Main results
We
* define predicates `IsSeparating`, `IsCoseparating`, `IsDetecting` and `IsCodetecting` on
sets of objects;
* show that separating and coseparating are dual notions;
* show that detecting and codetecting are dual notions;
* show that if `C` has equalizers, then detecting implies separating;
* show that if `C` has coequalizers, then codetecting implies separating;
* show that if `C` is balanced, then separating implies detecting and coseparating implies
codetecting;
* show that `∅` is separating if and only if `∅` is coseparating if and only if `C` is thin;
* show that `∅` is detecting if and only if `∅` is codetecting if and only if `C` is a groupoid;
* define predicates `IsSeparator`, `IsCoseparator`, `IsDetector` and `IsCodetector` as the
singleton counterparts to the definitions for sets above and restate the above results in this
situation;
* show that `G` is a separator if and only if `coyoneda.obj (op G)` is faithful (and the dual);
* show that `G` is a detector if and only if `coyoneda.obj (op G)` reflects isomorphisms (and the
dual).
## Future work
* We currently don't have any examples yet.
* We will want typeclasses `HasSeparator C` and similar.
-/
universe w v₁ v₂ u₁ u₂
open CategoryTheory.Limits Opposite
namespace CategoryTheory
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D]
/-- We say that `𝒢` is a separating set if the functors `C(G, -)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `h ≫ f = h ≫ g` for all `h` with domain in `𝒢` implies `f = g`. -/
def IsSeparating (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : G ⟶ X), h ≫ f = h ≫ g) → f = g
#align category_theory.is_separating CategoryTheory.IsSeparating
/-- We say that `𝒢` is a coseparating set if the functors `C(-, G)` for `G ∈ 𝒢` are collectively
faithful, i.e., if `f ≫ h = g ≫ h` for all `h` with codomain in `𝒢` implies `f = g`. -/
def IsCoseparating (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : Y ⟶ G), f ≫ h = g ≫ h) → f = g
#align category_theory.is_coseparating CategoryTheory.IsCoseparating
/-- We say that `𝒢` is a detecting set if the functors `C(G, -)` collectively reflect isomorphisms,
i.e., if any `h` with domain in `𝒢` uniquely factors through `f`, then `f` is an isomorphism. -/
def IsDetecting (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : G ⟶ Y), ∃! h' : G ⟶ X, h' ≫ f = h) → IsIso f
#align category_theory.is_detecting CategoryTheory.IsDetecting
/-- We say that `𝒢` is a codetecting set if the functors `C(-, G)` collectively reflect
isomorphisms, i.e., if any `h` with codomain in `G` uniquely factors through `f`, then `f` is
an isomorphism. -/
def IsCodetecting (𝒢 : Set C) : Prop :=
∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : X ⟶ G), ∃! h' : Y ⟶ G, f ≫ h' = h) → IsIso f
#align category_theory.is_codetecting CategoryTheory.IsCodetecting
section Dual
theorem isSeparating_op_iff (𝒢 : Set C) : IsSeparating 𝒢.op ↔ IsCoseparating 𝒢 := by
refine ⟨fun h𝒢 X Y f g hfg => ?_, fun h𝒢 X Y f g hfg => ?_⟩
· refine Quiver.Hom.op_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.unop_inj ?_)
simpa only [unop_comp, Quiver.Hom.unop_op] using hfg _ (Set.mem_op.1 hG) _
· refine Quiver.Hom.unop_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.op_inj ?_)
simpa only [op_comp, Quiver.Hom.op_unop] using hfg _ (Set.op_mem_op.2 hG) _
#align category_theory.is_separating_op_iff CategoryTheory.isSeparating_op_iff
theorem isCoseparating_op_iff (𝒢 : Set C) : IsCoseparating 𝒢.op ↔ IsSeparating 𝒢 := by
refine ⟨fun h𝒢 X Y f g hfg => ?_, fun h𝒢 X Y f g hfg => ?_⟩
· refine Quiver.Hom.op_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.unop_inj ?_)
simpa only [unop_comp, Quiver.Hom.unop_op] using hfg _ (Set.mem_op.1 hG) _
· refine Quiver.Hom.unop_inj (h𝒢 _ _ fun G hG h => Quiver.Hom.op_inj ?_)
simpa only [op_comp, Quiver.Hom.op_unop] using hfg _ (Set.op_mem_op.2 hG) _
#align category_theory.is_coseparating_op_iff CategoryTheory.isCoseparating_op_iff
theorem isCoseparating_unop_iff (𝒢 : Set Cᵒᵖ) : IsCoseparating 𝒢.unop ↔ IsSeparating 𝒢 := by
rw [← isSeparating_op_iff, Set.unop_op]
#align category_theory.is_coseparating_unop_iff CategoryTheory.isCoseparating_unop_iff
theorem isSeparating_unop_iff (𝒢 : Set Cᵒᵖ) : IsSeparating 𝒢.unop ↔ IsCoseparating 𝒢 := by
rw [← isCoseparating_op_iff, Set.unop_op]
#align category_theory.is_separating_unop_iff CategoryTheory.isSeparating_unop_iff
theorem isDetecting_op_iff (𝒢 : Set C) : IsDetecting 𝒢.op ↔ IsCodetecting 𝒢 := by
refine ⟨fun h𝒢 X Y f hf => ?_, fun h𝒢 X Y f hf => ?_⟩
· refine (isIso_op_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (unop G) (Set.mem_op.1 hG) h.unop
exact
⟨t.op, Quiver.Hom.unop_inj ht, fun y hy => Quiver.Hom.unop_inj (ht' _ (Quiver.Hom.op_inj hy))⟩
· refine (isIso_unop_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (op G) (Set.op_mem_op.2 hG) h.op
refine ⟨t.unop, Quiver.Hom.op_inj ht, fun y hy => Quiver.Hom.op_inj (ht' _ ?_)⟩
exact Quiver.Hom.unop_inj (by simpa only using hy)
#align category_theory.is_detecting_op_iff CategoryTheory.isDetecting_op_iff
theorem isCodetecting_op_iff (𝒢 : Set C) : IsCodetecting 𝒢.op ↔ IsDetecting 𝒢 := by
refine ⟨fun h𝒢 X Y f hf => ?_, fun h𝒢 X Y f hf => ?_⟩
· refine (isIso_op_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (unop G) (Set.mem_op.1 hG) h.unop
exact
⟨t.op, Quiver.Hom.unop_inj ht, fun y hy => Quiver.Hom.unop_inj (ht' _ (Quiver.Hom.op_inj hy))⟩
· refine (isIso_unop_iff _).1 (h𝒢 _ fun G hG h => ?_)
obtain ⟨t, ht, ht'⟩ := hf (op G) (Set.op_mem_op.2 hG) h.op
refine ⟨t.unop, Quiver.Hom.op_inj ht, fun y hy => Quiver.Hom.op_inj (ht' _ ?_)⟩
exact Quiver.Hom.unop_inj (by simpa only using hy)
#align category_theory.is_codetecting_op_iff CategoryTheory.isCodetecting_op_iff
theorem isDetecting_unop_iff (𝒢 : Set Cᵒᵖ) : IsDetecting 𝒢.unop ↔ IsCodetecting 𝒢 := by
rw [← isCodetecting_op_iff, Set.unop_op]
#align category_theory.is_detecting_unop_iff CategoryTheory.isDetecting_unop_iff
theorem isCodetecting_unop_iff {𝒢 : Set Cᵒᵖ} : IsCodetecting 𝒢.unop ↔ IsDetecting 𝒢 := by
rw [← isDetecting_op_iff, Set.unop_op]
#align category_theory.is_codetecting_unop_iff CategoryTheory.isCodetecting_unop_iff
end Dual
theorem IsDetecting.isSeparating [HasEqualizers C] {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) :
IsSeparating 𝒢 := fun _ _ f g hfg =>
have : IsIso (equalizer.ι f g) := h𝒢 _ fun _ hG _ => equalizer.existsUnique _ (hfg _ hG _)
eq_of_epi_equalizer
#align category_theory.is_detecting.is_separating CategoryTheory.IsDetecting.isSeparating
section
theorem IsCodetecting.isCoseparating [HasCoequalizers C] {𝒢 : Set C} :
IsCodetecting 𝒢 → IsCoseparating 𝒢 := by
simpa only [← isSeparating_op_iff, ← isDetecting_op_iff] using IsDetecting.isSeparating
#align category_theory.is_codetecting.is_coseparating CategoryTheory.IsCodetecting.isCoseparating
end
theorem IsSeparating.isDetecting [Balanced C] {𝒢 : Set C} (h𝒢 : IsSeparating 𝒢) :
IsDetecting 𝒢 := by
intro X Y f hf
refine
(isIso_iff_mono_and_epi _).2 ⟨⟨fun g h hgh => h𝒢 _ _ fun G hG i => ?_⟩, ⟨fun g h hgh => ?_⟩⟩
· obtain ⟨t, -, ht⟩ := hf G hG (i ≫ g ≫ f)
rw [ht (i ≫ g) (Category.assoc _ _ _), ht (i ≫ h) (hgh.symm ▸ Category.assoc _ _ _)]
· refine h𝒢 _ _ fun G hG i => ?_
obtain ⟨t, rfl, -⟩ := hf G hG i
rw [Category.assoc, hgh, Category.assoc]
#align category_theory.is_separating.is_detecting CategoryTheory.IsSeparating.isDetecting
section
attribute [local instance] balanced_opposite
theorem IsCoseparating.isCodetecting [Balanced C] {𝒢 : Set C} :
IsCoseparating 𝒢 → IsCodetecting 𝒢 := by
simpa only [← isDetecting_op_iff, ← isSeparating_op_iff] using IsSeparating.isDetecting
#align category_theory.is_coseparating.is_codetecting CategoryTheory.IsCoseparating.isCodetecting
end
theorem isDetecting_iff_isSeparating [HasEqualizers C] [Balanced C] (𝒢 : Set C) :
IsDetecting 𝒢 ↔ IsSeparating 𝒢 :=
⟨IsDetecting.isSeparating, IsSeparating.isDetecting⟩
#align category_theory.is_detecting_iff_is_separating CategoryTheory.isDetecting_iff_isSeparating
theorem isCodetecting_iff_isCoseparating [HasCoequalizers C] [Balanced C] {𝒢 : Set C} :
IsCodetecting 𝒢 ↔ IsCoseparating 𝒢 :=
⟨IsCodetecting.isCoseparating, IsCoseparating.isCodetecting⟩
#align category_theory.is_codetecting_iff_is_coseparating CategoryTheory.isCodetecting_iff_isCoseparating
section Mono
theorem IsSeparating.mono {𝒢 : Set C} (h𝒢 : IsSeparating 𝒢) {ℋ : Set C} (h𝒢ℋ : 𝒢 ⊆ ℋ) :
IsSeparating ℋ := fun _ _ _ _ hfg => h𝒢 _ _ fun _ hG _ => hfg _ (h𝒢ℋ hG) _
#align category_theory.is_separating.mono CategoryTheory.IsSeparating.mono
theorem IsCoseparating.mono {𝒢 : Set C} (h𝒢 : IsCoseparating 𝒢) {ℋ : Set C} (h𝒢ℋ : 𝒢 ⊆ ℋ) :
IsCoseparating ℋ := fun _ _ _ _ hfg => h𝒢 _ _ fun _ hG _ => hfg _ (h𝒢ℋ hG) _
#align category_theory.is_coseparating.mono CategoryTheory.IsCoseparating.mono
theorem IsDetecting.mono {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) {ℋ : Set C} (h𝒢ℋ : 𝒢 ⊆ ℋ) :
IsDetecting ℋ := fun _ _ _ hf => h𝒢 _ fun _ hG _ => hf _ (h𝒢ℋ hG) _
#align category_theory.is_detecting.mono CategoryTheory.IsDetecting.mono
theorem IsCodetecting.mono {𝒢 : Set C} (h𝒢 : IsCodetecting 𝒢) {ℋ : Set C} (h𝒢ℋ : 𝒢 ⊆ ℋ) :
IsCodetecting ℋ := fun _ _ _ hf => h𝒢 _ fun _ hG _ => hf _ (h𝒢ℋ hG) _
#align category_theory.is_codetecting.mono CategoryTheory.IsCodetecting.mono
end Mono
section Empty
theorem thin_of_isSeparating_empty (h : IsSeparating (∅ : Set C)) : Quiver.IsThin C := fun _ _ =>
⟨fun _ _ => h _ _ fun _ => False.elim⟩
#align category_theory.thin_of_is_separating_empty CategoryTheory.thin_of_isSeparating_empty
theorem isSeparating_empty_of_thin [Quiver.IsThin C] : IsSeparating (∅ : Set C) :=
fun _ _ _ _ _ => Subsingleton.elim _ _
#align category_theory.is_separating_empty_of_thin CategoryTheory.isSeparating_empty_of_thin
theorem thin_of_isCoseparating_empty (h : IsCoseparating (∅ : Set C)) : Quiver.IsThin C :=
fun _ _ => ⟨fun _ _ => h _ _ fun _ => False.elim⟩
#align category_theory.thin_of_is_coseparating_empty CategoryTheory.thin_of_isCoseparating_empty
theorem isCoseparating_empty_of_thin [Quiver.IsThin C] : IsCoseparating (∅ : Set C) :=
fun _ _ _ _ _ => Subsingleton.elim _ _
#align category_theory.is_coseparating_empty_of_thin CategoryTheory.isCoseparating_empty_of_thin
theorem groupoid_of_isDetecting_empty (h : IsDetecting (∅ : Set C)) {X Y : C} (f : X ⟶ Y) :
IsIso f :=
h _ fun _ => False.elim
#align category_theory.groupoid_of_is_detecting_empty CategoryTheory.groupoid_of_isDetecting_empty
theorem isDetecting_empty_of_groupoid [∀ {X Y : C} (f : X ⟶ Y), IsIso f] :
IsDetecting (∅ : Set C) := fun _ _ _ _ => inferInstance
#align category_theory.is_detecting_empty_of_groupoid CategoryTheory.isDetecting_empty_of_groupoid
theorem groupoid_of_isCodetecting_empty (h : IsCodetecting (∅ : Set C)) {X Y : C} (f : X ⟶ Y) :
IsIso f :=
h _ fun _ => False.elim
#align category_theory.groupoid_of_is_codetecting_empty CategoryTheory.groupoid_of_isCodetecting_empty
theorem isCodetecting_empty_of_groupoid [∀ {X Y : C} (f : X ⟶ Y), IsIso f] :
IsCodetecting (∅ : Set C) := fun _ _ _ _ => inferInstance
#align category_theory.is_codetecting_empty_of_groupoid CategoryTheory.isCodetecting_empty_of_groupoid
end Empty
theorem isSeparating_iff_epi (𝒢 : Set C)
[∀ A : C, HasCoproduct fun f : ΣG : 𝒢, (G : C) ⟶ A => (f.1 : C)] :
IsSeparating 𝒢 ↔ ∀ A : C, Epi (Sigma.desc (@Sigma.snd 𝒢 fun G => (G : C) ⟶ A)) := by
refine ⟨fun h A => ⟨fun u v huv => h _ _ fun G hG f => ?_⟩, fun h X Y f g hh => ?_⟩
· simpa using Sigma.ι (fun f : ΣG : 𝒢, (G : C) ⟶ A => (f.1 : C)) ⟨⟨G, hG⟩, f⟩ ≫= huv
· haveI := h X
refine
(cancel_epi (Sigma.desc (@Sigma.snd 𝒢 fun G => (G : C) ⟶ X))).1 (colimit.hom_ext fun j => ?_)
simpa using hh j.as.1.1 j.as.1.2 j.as.2
#align category_theory.is_separating_iff_epi CategoryTheory.isSeparating_iff_epi
theorem isCoseparating_iff_mono (𝒢 : Set C)
[∀ A : C, HasProduct fun f : ΣG : 𝒢, A ⟶ (G : C) => (f.1 : C)] :
IsCoseparating 𝒢 ↔ ∀ A : C, Mono (Pi.lift (@Sigma.snd 𝒢 fun G => A ⟶ (G : C))) := by
refine ⟨fun h A => ⟨fun u v huv => h _ _ fun G hG f => ?_⟩, fun h X Y f g hh => ?_⟩
· simpa using huv =≫ Pi.π (fun f : ΣG : 𝒢, A ⟶ (G : C) => (f.1 : C)) ⟨⟨G, hG⟩, f⟩
· haveI := h Y
refine (cancel_mono (Pi.lift (@Sigma.snd 𝒢 fun G => Y ⟶ (G : C)))).1 (limit.hom_ext fun j => ?_)
simpa using hh j.as.1.1 j.as.1.2 j.as.2
#align category_theory.is_coseparating_iff_mono CategoryTheory.isCoseparating_iff_mono
/-- An ingredient of the proof of the Special Adjoint Functor Theorem: a complete well-powered
category with a small coseparating set has an initial object.
In fact, it follows from the Special Adjoint Functor Theorem that `C` is already cocomplete,
see `hasColimits_of_hasLimits_of_isCoseparating`. -/
theorem hasInitial_of_isCoseparating [WellPowered C] [HasLimits C] {𝒢 : Set C} [Small.{v₁} 𝒢]
(h𝒢 : IsCoseparating 𝒢) : HasInitial C := by
haveI : HasProductsOfShape 𝒢 C := hasProductsOfShape_of_small C 𝒢
haveI := fun A => hasProductsOfShape_of_small.{v₁} C (ΣG : 𝒢, A ⟶ (G : C))
letI := completeLatticeOfCompleteSemilatticeInf (Subobject (piObj (Subtype.val : 𝒢 → C)))
suffices ∀ A : C, Unique (((⊥ : Subobject (piObj (Subtype.val : 𝒢 → C))) : C) ⟶ A) by
exact hasInitial_of_unique ((⊥ : Subobject (piObj (Subtype.val : 𝒢 → C))) : C)
refine fun A => ⟨⟨?_⟩, fun f => ?_⟩
· let s := Pi.lift fun f : ΣG : 𝒢, A ⟶ (G : C) => id (Pi.π (Subtype.val : 𝒢 → C)) f.1
let t := Pi.lift (@Sigma.snd 𝒢 fun G => A ⟶ (G : C))
haveI : Mono t := (isCoseparating_iff_mono 𝒢).1 h𝒢 A
exact Subobject.ofLEMk _ (pullback.fst : pullback s t ⟶ _) bot_le ≫ pullback.snd
· suffices ∀ (g : Subobject.underlying.obj ⊥ ⟶ A), f = g by
apply this
intro g
suffices IsSplitEpi (equalizer.ι f g) by exact eq_of_epi_equalizer
exact IsSplitEpi.mk' ⟨Subobject.ofLEMk _ (equalizer.ι f g ≫ Subobject.arrow _) bot_le, by
ext
simp⟩
#align category_theory.has_initial_of_is_coseparating CategoryTheory.hasInitial_of_isCoseparating
/-- An ingredient of the proof of the Special Adjoint Functor Theorem: a cocomplete well-copowered
category with a small separating set has a terminal object.
In fact, it follows from the Special Adjoint Functor Theorem that `C` is already complete, see
`hasLimits_of_hasColimits_of_isSeparating`. -/
theorem hasTerminal_of_isSeparating [WellPowered Cᵒᵖ] [HasColimits C] {𝒢 : Set C} [Small.{v₁} 𝒢]
(h𝒢 : IsSeparating 𝒢) : HasTerminal C := by
haveI : Small.{v₁} 𝒢.op := small_of_injective (Set.opEquiv_self 𝒢).injective
haveI : HasInitial Cᵒᵖ := hasInitial_of_isCoseparating ((isCoseparating_op_iff _).2 h𝒢)
exact hasTerminal_of_hasInitial_op
#align category_theory.has_terminal_of_is_separating CategoryTheory.hasTerminal_of_isSeparating
section WellPowered
namespace Subobject
theorem eq_of_le_of_isDetecting {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) {X : C} (P Q : Subobject X)
(h₁ : P ≤ Q) (h₂ : ∀ G ∈ 𝒢, ∀ {f : G ⟶ X}, Q.Factors f → P.Factors f) : P = Q := by
suffices IsIso (ofLE _ _ h₁) by exact le_antisymm h₁ (le_of_comm (inv (ofLE _ _ h₁)) (by simp))
refine h𝒢 _ fun G hG f => ?_
have : P.Factors (f ≫ Q.arrow) := h₂ _ hG ((factors_iff _ _).2 ⟨_, rfl⟩)
refine ⟨factorThru _ _ this, ?_, fun g (hg : g ≫ _ = f) => ?_⟩
· simp only [← cancel_mono Q.arrow, Category.assoc, ofLE_arrow, factorThru_arrow]
· simp only [← cancel_mono (Subobject.ofLE _ _ h₁), ← cancel_mono Q.arrow, hg, Category.assoc,
ofLE_arrow, factorThru_arrow]
#align category_theory.subobject.eq_of_le_of_is_detecting CategoryTheory.Subobject.eq_of_le_of_isDetecting
theorem inf_eq_of_isDetecting [HasPullbacks C] {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) {X : C}
(P Q : Subobject X) (h : ∀ G ∈ 𝒢, ∀ {f : G ⟶ X}, P.Factors f → Q.Factors f) : P ⊓ Q = P :=
eq_of_le_of_isDetecting h𝒢 _ _ _root_.inf_le_left
fun _ hG _ hf => (inf_factors _).2 ⟨hf, h _ hG hf⟩
#align category_theory.subobject.inf_eq_of_is_detecting CategoryTheory.Subobject.inf_eq_of_isDetecting
theorem eq_of_isDetecting [HasPullbacks C] {𝒢 : Set C} (h𝒢 : IsDetecting 𝒢) {X : C}
(P Q : Subobject X) (h : ∀ G ∈ 𝒢, ∀ {f : G ⟶ X}, P.Factors f ↔ Q.Factors f) : P = Q :=
calc
P = P ⊓ Q := Eq.symm <| inf_eq_of_isDetecting h𝒢 _ _ fun G hG _ hf => (h G hG).1 hf
_ = Q ⊓ P := inf_comm ..
_ = Q := inf_eq_of_isDetecting h𝒢 _ _ fun G hG _ hf => (h G hG).2 hf
#align category_theory.subobject.eq_of_is_detecting CategoryTheory.Subobject.eq_of_isDetecting
end Subobject
/-- A category with pullbacks and a small detecting set is well-powered. -/
theorem wellPowered_of_isDetecting [HasPullbacks C] {𝒢 : Set C} [Small.{v₁} 𝒢]
(h𝒢 : IsDetecting 𝒢) : WellPowered C :=
⟨fun X =>
@small_of_injective _ _ _ (fun P : Subobject X => { f : ΣG : 𝒢, G.1 ⟶ X | P.Factors f.2 })
fun P Q h => Subobject.eq_of_isDetecting h𝒢 _ _ (by simpa [Set.ext_iff] using h)⟩
#align category_theory.well_powered_of_is_detecting CategoryTheory.wellPowered_of_isDetecting
end WellPowered
namespace StructuredArrow
variable (S : D) (T : C ⥤ D)
theorem isCoseparating_proj_preimage {𝒢 : Set C} (h𝒢 : IsCoseparating 𝒢) :
IsCoseparating ((proj S T).obj ⁻¹' 𝒢) := by
refine fun X Y f g hfg => ext _ _ (h𝒢 _ _ fun G hG h => ?_)
exact congr_arg CommaMorphism.right (hfg (mk (Y.hom ≫ T.map h)) hG (homMk h rfl))
#align category_theory.structured_arrow.is_coseparating_proj_preimage CategoryTheory.StructuredArrow.isCoseparating_proj_preimage
end StructuredArrow
namespace CostructuredArrow
variable (S : C ⥤ D) (T : D)
theorem isSeparating_proj_preimage {𝒢 : Set C} (h𝒢 : IsSeparating 𝒢) :
IsSeparating ((proj S T).obj ⁻¹' 𝒢) := by
refine fun X Y f g hfg => ext _ _ (h𝒢 _ _ fun G hG h => ?_)
exact congr_arg CommaMorphism.left (hfg (mk (S.map h ≫ X.hom)) hG (homMk h rfl))
#align category_theory.costructured_arrow.is_separating_proj_preimage CategoryTheory.CostructuredArrow.isSeparating_proj_preimage
end CostructuredArrow
/-- We say that `G` is a separator if the functor `C(G, -)` is faithful. -/
def IsSeparator (G : C) : Prop :=
IsSeparating ({G} : Set C)
#align category_theory.is_separator CategoryTheory.IsSeparator
/-- We say that `G` is a coseparator if the functor `C(-, G)` is faithful. -/
def IsCoseparator (G : C) : Prop :=
IsCoseparating ({G} : Set C)
#align category_theory.is_coseparator CategoryTheory.IsCoseparator
/-- We say that `G` is a detector if the functor `C(G, -)` reflects isomorphisms. -/
def IsDetector (G : C) : Prop :=
IsDetecting ({G} : Set C)
#align category_theory.is_detector CategoryTheory.IsDetector
/-- We say that `G` is a codetector if the functor `C(-, G)` reflects isomorphisms. -/
def IsCodetector (G : C) : Prop :=
IsCodetecting ({G} : Set C)
#align category_theory.is_codetector CategoryTheory.IsCodetector
section Dual
theorem isSeparator_op_iff (G : C) : IsSeparator (op G) ↔ IsCoseparator G := by
rw [IsSeparator, IsCoseparator, ← isSeparating_op_iff, Set.singleton_op]
#align category_theory.is_separator_op_iff CategoryTheory.isSeparator_op_iff
theorem isCoseparator_op_iff (G : C) : IsCoseparator (op G) ↔ IsSeparator G := by
rw [IsSeparator, IsCoseparator, ← isCoseparating_op_iff, Set.singleton_op]
#align category_theory.is_coseparator_op_iff CategoryTheory.isCoseparator_op_iff
theorem isCoseparator_unop_iff (G : Cᵒᵖ) : IsCoseparator (unop G) ↔ IsSeparator G := by
rw [IsSeparator, IsCoseparator, ← isCoseparating_unop_iff, Set.singleton_unop]
#align category_theory.is_coseparator_unop_iff CategoryTheory.isCoseparator_unop_iff
theorem isSeparator_unop_iff (G : Cᵒᵖ) : IsSeparator (unop G) ↔ IsCoseparator G := by
rw [IsSeparator, IsCoseparator, ← isSeparating_unop_iff, Set.singleton_unop]
#align category_theory.is_separator_unop_iff CategoryTheory.isSeparator_unop_iff
theorem isDetector_op_iff (G : C) : IsDetector (op G) ↔ IsCodetector G := by
rw [IsDetector, IsCodetector, ← isDetecting_op_iff, Set.singleton_op]
#align category_theory.is_detector_op_iff CategoryTheory.isDetector_op_iff
theorem isCodetector_op_iff (G : C) : IsCodetector (op G) ↔ IsDetector G := by
rw [IsDetector, IsCodetector, ← isCodetecting_op_iff, Set.singleton_op]
#align category_theory.is_codetector_op_iff CategoryTheory.isCodetector_op_iff
theorem isCodetector_unop_iff (G : Cᵒᵖ) : IsCodetector (unop G) ↔ IsDetector G := by
rw [IsDetector, IsCodetector, ← isCodetecting_unop_iff, Set.singleton_unop]
#align category_theory.is_codetector_unop_iff CategoryTheory.isCodetector_unop_iff
theorem isDetector_unop_iff (G : Cᵒᵖ) : IsDetector (unop G) ↔ IsCodetector G := by
rw [IsDetector, IsCodetector, ← isDetecting_unop_iff, Set.singleton_unop]
#align category_theory.is_detector_unop_iff CategoryTheory.isDetector_unop_iff
end Dual
theorem IsDetector.isSeparator [HasEqualizers C] {G : C} : IsDetector G → IsSeparator G :=
IsDetecting.isSeparating
#align category_theory.is_detector.is_separator CategoryTheory.IsDetector.isSeparator
theorem IsCodetector.isCoseparator [HasCoequalizers C] {G : C} : IsCodetector G → IsCoseparator G :=
IsCodetecting.isCoseparating
#align category_theory.is_codetector.is_coseparator CategoryTheory.IsCodetector.isCoseparator
theorem IsSeparator.isDetector [Balanced C] {G : C} : IsSeparator G → IsDetector G :=
IsSeparating.isDetecting
#align category_theory.is_separator.is_detector CategoryTheory.IsSeparator.isDetector
theorem IsCospearator.isCodetector [Balanced C] {G : C} : IsCoseparator G → IsCodetector G :=
IsCoseparating.isCodetecting
#align category_theory.is_cospearator.is_codetector CategoryTheory.IsCospearator.isCodetector
theorem isSeparator_def (G : C) :
IsSeparator G ↔ ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ h : G ⟶ X, h ≫ f = h ≫ g) → f = g :=
⟨fun hG X Y f g hfg =>
hG _ _ fun H hH h => by
obtain rfl := Set.mem_singleton_iff.1 hH
exact hfg h,
fun hG X Y f g hfg => hG _ _ fun h => hfg _ (Set.mem_singleton _) _⟩
#align category_theory.is_separator_def CategoryTheory.isSeparator_def
theorem IsSeparator.def {G : C} :
IsSeparator G → ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ h : G ⟶ X, h ≫ f = h ≫ g) → f = g :=
(isSeparator_def _).1
#align category_theory.is_separator.def CategoryTheory.IsSeparator.def
theorem isCoseparator_def (G : C) :
IsCoseparator G ↔ ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ h : Y ⟶ G, f ≫ h = g ≫ h) → f = g :=
⟨fun hG X Y f g hfg =>
hG _ _ fun H hH h => by
obtain rfl := Set.mem_singleton_iff.1 hH
exact hfg h,
fun hG X Y f g hfg => hG _ _ fun h => hfg _ (Set.mem_singleton _) _⟩
#align category_theory.is_coseparator_def CategoryTheory.isCoseparator_def
theorem IsCoseparator.def {G : C} :
IsCoseparator G → ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), (∀ h : Y ⟶ G, f ≫ h = g ≫ h) → f = g :=
(isCoseparator_def _).1
#align category_theory.is_coseparator.def CategoryTheory.IsCoseparator.def
theorem isDetector_def (G : C) :
IsDetector G ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : G ⟶ Y, ∃! h', h' ≫ f = h) → IsIso f :=
⟨fun hG X Y f hf =>
hG _ fun H hH h => by
obtain rfl := Set.mem_singleton_iff.1 hH
exact hf h,
fun hG X Y f hf => hG _ fun h => hf _ (Set.mem_singleton _) _⟩
#align category_theory.is_detector_def CategoryTheory.isDetector_def
theorem IsDetector.def {G : C} :
IsDetector G → ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : G ⟶ Y, ∃! h', h' ≫ f = h) → IsIso f :=
(isDetector_def _).1
#align category_theory.is_detector.def CategoryTheory.IsDetector.def
theorem isCodetector_def (G : C) :
IsCodetector G ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : X ⟶ G, ∃! h', f ≫ h' = h) → IsIso f :=
⟨fun hG X Y f hf =>
hG _ fun H hH h => by
obtain rfl := Set.mem_singleton_iff.1 hH
exact hf h,
fun hG X Y f hf => hG _ fun h => hf _ (Set.mem_singleton _) _⟩
#align category_theory.is_codetector_def CategoryTheory.isCodetector_def
theorem IsCodetector.def {G : C} :
IsCodetector G → ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : X ⟶ G, ∃! h', f ≫ h' = h) → IsIso f :=
(isCodetector_def _).1
#align category_theory.is_codetector.def CategoryTheory.IsCodetector.def
theorem isSeparator_iff_faithful_coyoneda_obj (G : C) :
IsSeparator G ↔ (coyoneda.obj (op G)).Faithful :=
⟨fun hG => ⟨fun hfg => hG.def _ _ (congr_fun hfg)⟩, fun _ =>
(isSeparator_def _).2 fun _ _ _ _ hfg => (coyoneda.obj (op G)).map_injective (funext hfg)⟩
#align category_theory.is_separator_iff_faithful_coyoneda_obj CategoryTheory.isSeparator_iff_faithful_coyoneda_obj
theorem isCoseparator_iff_faithful_yoneda_obj (G : C) : IsCoseparator G ↔ (yoneda.obj G).Faithful :=
⟨fun hG => ⟨fun hfg => Quiver.Hom.unop_inj (hG.def _ _ (congr_fun hfg))⟩, fun _ =>
(isCoseparator_def _).2 fun _ _ _ _ hfg =>
Quiver.Hom.op_inj <| (yoneda.obj G).map_injective (funext hfg)⟩
#align category_theory.is_coseparator_iff_faithful_yoneda_obj CategoryTheory.isCoseparator_iff_faithful_yoneda_obj
theorem isSeparator_iff_epi (G : C) [∀ A : C, HasCoproduct fun _ : G ⟶ A => G] :
IsSeparator G ↔ ∀ A : C, Epi (Sigma.desc fun f : G ⟶ A => f) := by
rw [isSeparator_def]
refine ⟨fun h A => ⟨fun u v huv => h _ _ fun i => ?_⟩, fun h X Y f g hh => ?_⟩
· simpa using Sigma.ι _ i ≫= huv
· haveI := h X
refine (cancel_epi (Sigma.desc fun f : G ⟶ X => f)).1 (colimit.hom_ext fun j => ?_)
simpa using hh j.as
#align category_theory.is_separator_iff_epi CategoryTheory.isSeparator_iff_epi
theorem isCoseparator_iff_mono (G : C) [∀ A : C, HasProduct fun _ : A ⟶ G => G] :
IsCoseparator G ↔ ∀ A : C, Mono (Pi.lift fun f : A ⟶ G => f) := by
rw [isCoseparator_def]
refine ⟨fun h A => ⟨fun u v huv => h _ _ fun i => ?_⟩, fun h X Y f g hh => ?_⟩
· simpa using huv =≫ Pi.π _ i
· haveI := h Y
refine (cancel_mono (Pi.lift fun f : Y ⟶ G => f)).1 (limit.hom_ext fun j => ?_)
simpa using hh j.as
#align category_theory.is_coseparator_iff_mono CategoryTheory.isCoseparator_iff_mono
section ZeroMorphisms
variable [HasZeroMorphisms C]
theorem isSeparator_coprod (G H : C) [HasBinaryCoproduct G H] :
IsSeparator (G ⨿ H) ↔ IsSeparating ({G, H} : Set C) := by
refine
⟨fun h X Y u v huv => ?_, fun h =>
(isSeparator_def _).2 fun X Y u v huv => h _ _ fun Z hZ g => ?_⟩
· refine h.def _ _ fun g => coprod.hom_ext ?_ ?_
· simpa using huv G (by simp) (coprod.inl ≫ g)
· simpa using huv H (by simp) (coprod.inr ≫ g)
· simp only [Set.mem_insert_iff, Set.mem_singleton_iff] at hZ
rcases hZ with (rfl | rfl)
· simpa using coprod.inl ≫= huv (coprod.desc g 0)
· simpa using coprod.inr ≫= huv (coprod.desc 0 g)
#align category_theory.is_separator_coprod CategoryTheory.isSeparator_coprod
theorem isSeparator_coprod_of_isSeparator_left (G H : C) [HasBinaryCoproduct G H]
(hG : IsSeparator G) : IsSeparator (G ⨿ H) :=
(isSeparator_coprod _ _).2 <| IsSeparating.mono hG <| by simp
#align category_theory.is_separator_coprod_of_is_separator_left CategoryTheory.isSeparator_coprod_of_isSeparator_left
theorem isSeparator_coprod_of_isSeparator_right (G H : C) [HasBinaryCoproduct G H]
(hH : IsSeparator H) : IsSeparator (G ⨿ H) :=
(isSeparator_coprod _ _).2 <| IsSeparating.mono hH <| by simp
#align category_theory.is_separator_coprod_of_is_separator_right CategoryTheory.isSeparator_coprod_of_isSeparator_right
theorem isSeparator_sigma {β : Type w} (f : β → C) [HasCoproduct f] :
IsSeparator (∐ f) ↔ IsSeparating (Set.range f) := by
refine
⟨fun h X Y u v huv => ?_, fun h =>
(isSeparator_def _).2 fun X Y u v huv => h _ _ fun Z hZ g => ?_⟩
· refine h.def _ _ fun g => colimit.hom_ext fun b => ?_
simpa using huv (f b.as) (by simp) (colimit.ι (Discrete.functor f) _ ≫ g)
· obtain ⟨b, rfl⟩ := Set.mem_range.1 hZ
classical simpa using Sigma.ι f b ≫= huv (Sigma.desc (Pi.single b g))
#align category_theory.is_separator_sigma CategoryTheory.isSeparator_sigma
theorem isSeparator_sigma_of_isSeparator {β : Type w} (f : β → C) [HasCoproduct f] (b : β)
(hb : IsSeparator (f b)) : IsSeparator (∐ f) :=
(isSeparator_sigma _).2 <| IsSeparating.mono hb <| by simp
#align category_theory.is_separator_sigma_of_is_separator CategoryTheory.isSeparator_sigma_of_isSeparator
| Mathlib/CategoryTheory/Generator.lean | 586 | 597 | theorem isCoseparator_prod (G H : C) [HasBinaryProduct G H] :
IsCoseparator (G ⨯ H) ↔ IsCoseparating ({G, H} : Set C) := by |
refine
⟨fun h X Y u v huv => ?_, fun h =>
(isCoseparator_def _).2 fun X Y u v huv => h _ _ fun Z hZ g => ?_⟩
· refine h.def _ _ fun g => prod.hom_ext ?_ ?_
· simpa using huv G (by simp) (g ≫ Limits.prod.fst)
· simpa using huv H (by simp) (g ≫ Limits.prod.snd)
· simp only [Set.mem_insert_iff, Set.mem_singleton_iff] at hZ
rcases hZ with (rfl | rfl)
· simpa using huv (prod.lift g 0) =≫ Limits.prod.fst
· simpa using huv (prod.lift 0 g) =≫ Limits.prod.snd
|
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.LinearAlgebra.Dimension.Free
import Mathlib.Algebra.Homology.ShortComplex.ModuleCat
/-!
# Exact sequences with free modules
This file proves results about linear independence and span in exact sequences of modules.
## Main theorems
* `linearIndependent_shortExact`: Given a short exact sequence `0 ⟶ X₁ ⟶ X₂ ⟶ X₃ ⟶ 0` of
`R`-modules and linearly independent families `v : ι → X₁` and `w : ι' → X₃`, we get a linearly
independent family `ι ⊕ ι' → X₂`
* `span_rightExact`: Given an exact sequence `X₁ ⟶ X₂ ⟶ X₃ ⟶ 0` of `R`-modules and spanning
families `v : ι → X₁` and `w : ι' → X₃`, we get a spanning family `ι ⊕ ι' → X₂`
* Using `linearIndependent_shortExact` and `span_rightExact`, we prove `free_shortExact`: In a
short exact sequence `0 ⟶ X₁ ⟶ X₂ ⟶ X₃ ⟶ 0` where `X₁` and `X₃` are free, `X₂` is free as well.
## Tags
linear algebra, module, free
-/
open CategoryTheory
namespace ModuleCat
variable {ι ι' R : Type*} [Ring R] {S : ShortComplex (ModuleCat R)}
(hS : S.Exact) (hS' : S.ShortExact) {v : ι → S.X₁}
open CategoryTheory Submodule Set
section LinearIndependent
variable (hv : LinearIndependent R v) {u : ι ⊕ ι' → S.X₂}
(hw : LinearIndependent R (S.g ∘ u ∘ Sum.inr))
(hm : Mono S.f) (huv : u ∘ Sum.inl = S.f ∘ v)
| Mathlib/Algebra/Category/ModuleCat/Free.lean | 44 | 49 | theorem disjoint_span_sum : Disjoint (span R (range (u ∘ Sum.inl)))
(span R (range (u ∘ Sum.inr))) := by |
rw [huv, disjoint_comm]
refine Disjoint.mono_right (span_mono (range_comp_subset_range _ _)) ?_
rw [← LinearMap.range_coe, span_eq (LinearMap.range S.f), hS.moduleCat_range_eq_ker]
exact range_ker_disjoint hw
|
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Group.Commute.Hom
import Mathlib.Data.Fintype.Card
#align_import data.finset.noncomm_prod from "leanprover-community/mathlib"@"509de852e1de55e1efa8eacfa11df0823f26f226"
/-!
# Products (respectively, sums) over a finset or a multiset.
The regular `Finset.prod` and `Multiset.prod` require `[CommMonoid α]`.
Often, there are collections `s : Finset α` where `[Monoid α]` and we know,
in a dependent fashion, that for all the terms `∀ (x ∈ s) (y ∈ s), Commute x y`.
This allows to still have a well-defined product over `s`.
## Main definitions
- `Finset.noncommProd`, requiring a proof of commutativity of held terms
- `Multiset.noncommProd`, requiring a proof of commutativity of held terms
## Implementation details
While `List.prod` is defined via `List.foldl`, `noncommProd` is defined via
`Multiset.foldr` for neater proofs and definitions. By the commutativity assumption,
the two must be equal.
TODO: Tidy up this file by using the fact that the submonoid generated by commuting
elements is commutative and using the `Finset.prod` versions of lemmas to prove the `noncommProd`
version.
-/
variable {F ι α β γ : Type*} (f : α → β → β) (op : α → α → α)
namespace Multiset
/-- Fold of a `s : Multiset α` with `f : α → β → β`, given a proof that `LeftCommutative f`
on all elements `x ∈ s`. -/
def noncommFoldr (s : Multiset α)
(comm : { x | x ∈ s }.Pairwise fun x y => ∀ b, f x (f y b) = f y (f x b)) (b : β) : β :=
s.attach.foldr (f ∘ Subtype.val)
(fun ⟨_, hx⟩ ⟨_, hy⟩ =>
haveI : IsRefl α fun x y => ∀ b, f x (f y b) = f y (f x b) := ⟨fun _ _ => rfl⟩
comm.of_refl hx hy)
b
#align multiset.noncomm_foldr Multiset.noncommFoldr
@[simp]
theorem noncommFoldr_coe (l : List α) (comm) (b : β) :
noncommFoldr f (l : Multiset α) comm b = l.foldr f b := by
simp only [noncommFoldr, coe_foldr, coe_attach, List.attach, List.attachWith, Function.comp]
rw [← List.foldr_map]
simp [List.map_pmap]
#align multiset.noncomm_foldr_coe Multiset.noncommFoldr_coe
@[simp]
theorem noncommFoldr_empty (h) (b : β) : noncommFoldr f (0 : Multiset α) h b = b :=
rfl
#align multiset.noncomm_foldr_empty Multiset.noncommFoldr_empty
theorem noncommFoldr_cons (s : Multiset α) (a : α) (h h') (b : β) :
noncommFoldr f (a ::ₘ s) h b = f a (noncommFoldr f s h' b) := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_foldr_cons Multiset.noncommFoldr_cons
theorem noncommFoldr_eq_foldr (s : Multiset α) (h : LeftCommutative f) (b : β) :
noncommFoldr f s (fun x _ y _ _ => h x y) b = foldr f h b s := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_foldr_eq_foldr Multiset.noncommFoldr_eq_foldr
section assoc
variable [assoc : Std.Associative op]
/-- Fold of a `s : Multiset α` with an associative `op : α → α → α`, given a proofs that `op`
is commutative on all elements `x ∈ s`. -/
def noncommFold (s : Multiset α) (comm : { x | x ∈ s }.Pairwise fun x y => op x y = op y x) :
α → α :=
noncommFoldr op s fun x hx y hy h b => by rw [← assoc.assoc, comm hx hy h, assoc.assoc]
#align multiset.noncomm_fold Multiset.noncommFold
@[simp]
theorem noncommFold_coe (l : List α) (comm) (a : α) :
noncommFold op (l : Multiset α) comm a = l.foldr op a := by simp [noncommFold]
#align multiset.noncomm_fold_coe Multiset.noncommFold_coe
@[simp]
theorem noncommFold_empty (h) (a : α) : noncommFold op (0 : Multiset α) h a = a :=
rfl
#align multiset.noncomm_fold_empty Multiset.noncommFold_empty
theorem noncommFold_cons (s : Multiset α) (a : α) (h h') (x : α) :
noncommFold op (a ::ₘ s) h x = op a (noncommFold op s h' x) := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_fold_cons Multiset.noncommFold_cons
theorem noncommFold_eq_fold (s : Multiset α) [Std.Commutative op] (a : α) :
noncommFold op s (fun x _ y _ _ => Std.Commutative.comm x y) a = fold op a s := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_fold_eq_fold Multiset.noncommFold_eq_fold
end assoc
variable [Monoid α] [Monoid β]
/-- Product of a `s : Multiset α` with `[Monoid α]`, given a proof that `*` commutes
on all elements `x ∈ s`. -/
@[to_additive
"Sum of a `s : Multiset α` with `[AddMonoid α]`, given a proof that `+` commutes
on all elements `x ∈ s`."]
def noncommProd (s : Multiset α) (comm : { x | x ∈ s }.Pairwise Commute) : α :=
s.noncommFold (· * ·) comm 1
#align multiset.noncomm_prod Multiset.noncommProd
#align multiset.noncomm_sum Multiset.noncommSum
@[to_additive (attr := simp)]
theorem noncommProd_coe (l : List α) (comm) : noncommProd (l : Multiset α) comm = l.prod := by
rw [noncommProd]
simp only [noncommFold_coe]
induction' l with hd tl hl
· simp
· rw [List.prod_cons, List.foldr, hl]
intro x hx y hy
exact comm (List.mem_cons_of_mem _ hx) (List.mem_cons_of_mem _ hy)
#align multiset.noncomm_prod_coe Multiset.noncommProd_coe
#align multiset.noncomm_sum_coe Multiset.noncommSum_coe
@[to_additive (attr := simp)]
theorem noncommProd_empty (h) : noncommProd (0 : Multiset α) h = 1 :=
rfl
#align multiset.noncomm_prod_empty Multiset.noncommProd_empty
#align multiset.noncomm_sum_empty Multiset.noncommSum_empty
@[to_additive (attr := simp)]
theorem noncommProd_cons (s : Multiset α) (a : α) (comm) :
noncommProd (a ::ₘ s) comm = a * noncommProd s (comm.mono fun _ => mem_cons_of_mem) := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_prod_cons Multiset.noncommProd_cons
#align multiset.noncomm_sum_cons Multiset.noncommSum_cons
@[to_additive]
theorem noncommProd_cons' (s : Multiset α) (a : α) (comm) :
noncommProd (a ::ₘ s) comm = noncommProd s (comm.mono fun _ => mem_cons_of_mem) * a := by
induction' s using Quotient.inductionOn with s
simp only [quot_mk_to_coe, cons_coe, noncommProd_coe, List.prod_cons]
induction' s with hd tl IH
· simp
· rw [List.prod_cons, mul_assoc, ← IH, ← mul_assoc, ← mul_assoc]
· congr 1
apply comm.of_refl <;> simp
· intro x hx y hy
simp only [quot_mk_to_coe, List.mem_cons, mem_coe, cons_coe] at hx hy
apply comm
· cases hx <;> simp [*]
· cases hy <;> simp [*]
#align multiset.noncomm_prod_cons' Multiset.noncommProd_cons'
#align multiset.noncomm_sum_cons' Multiset.noncommSum_cons'
@[to_additive]
theorem noncommProd_add (s t : Multiset α) (comm) :
noncommProd (s + t) comm =
noncommProd s (comm.mono <| subset_of_le <| s.le_add_right t) *
noncommProd t (comm.mono <| subset_of_le <| t.le_add_left s) := by
rcases s with ⟨⟩
rcases t with ⟨⟩
simp
#align multiset.noncomm_prod_add Multiset.noncommProd_add
#align multiset.noncomm_sum_add Multiset.noncommSum_add
@[to_additive]
lemma noncommProd_induction (s : Multiset α) (comm)
(p : α → Prop) (hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p x) :
p (s.noncommProd comm) := by
induction' s using Quotient.inductionOn with l
simp only [quot_mk_to_coe, noncommProd_coe, mem_coe] at base ⊢
exact l.prod_induction p hom unit base
variable [FunLike F α β]
@[to_additive]
protected theorem noncommProd_map_aux [MonoidHomClass F α β] (s : Multiset α)
(comm : { x | x ∈ s }.Pairwise Commute) (f : F) : { x | x ∈ s.map f }.Pairwise Commute := by
simp only [Multiset.mem_map]
rintro _ ⟨x, hx, rfl⟩ _ ⟨y, hy, rfl⟩ _
exact (comm.of_refl hx hy).map f
#align multiset.noncomm_prod_map_aux Multiset.noncommProd_map_aux
#align multiset.noncomm_sum_map_aux Multiset.noncommSum_map_aux
@[to_additive]
theorem noncommProd_map [MonoidHomClass F α β] (s : Multiset α) (comm) (f : F) :
f (s.noncommProd comm) = (s.map f).noncommProd (Multiset.noncommProd_map_aux s comm f) := by
induction s using Quotient.inductionOn
simpa using map_list_prod f _
#align multiset.noncomm_prod_map Multiset.noncommProd_map
#align multiset.noncomm_sum_map Multiset.noncommSum_map
@[to_additive noncommSum_eq_card_nsmul]
theorem noncommProd_eq_pow_card (s : Multiset α) (comm) (m : α) (h : ∀ x ∈ s, x = m) :
s.noncommProd comm = m ^ Multiset.card s := by
induction s using Quotient.inductionOn
simp only [quot_mk_to_coe, noncommProd_coe, coe_card, mem_coe] at *
exact List.prod_eq_pow_card _ m h
#align multiset.noncomm_prod_eq_pow_card Multiset.noncommProd_eq_pow_card
#align multiset.noncomm_sum_eq_card_nsmul Multiset.noncommSum_eq_card_nsmul
@[to_additive]
theorem noncommProd_eq_prod {α : Type*} [CommMonoid α] (s : Multiset α) :
(noncommProd s fun _ _ _ _ _ => Commute.all _ _) = prod s := by
induction s using Quotient.inductionOn
simp
#align multiset.noncomm_prod_eq_prod Multiset.noncommProd_eq_prod
#align multiset.noncomm_sum_eq_sum Multiset.noncommSum_eq_sum
@[to_additive]
theorem noncommProd_commute (s : Multiset α) (comm) (y : α) (h : ∀ x ∈ s, Commute y x) :
Commute y (s.noncommProd comm) := by
induction s using Quotient.inductionOn
simp only [quot_mk_to_coe, noncommProd_coe]
exact Commute.list_prod_right _ _ h
#align multiset.noncomm_prod_commute Multiset.noncommProd_commute
#align multiset.noncomm_sum_add_commute Multiset.noncommSum_addCommute
theorem mul_noncommProd_erase [DecidableEq α] (s : Multiset α) {a : α} (h : a ∈ s) (comm)
(comm' := fun x hx y hy hxy ↦ comm (s.mem_of_mem_erase hx) (s.mem_of_mem_erase hy) hxy) :
a * (s.erase a).noncommProd comm' = s.noncommProd comm := by
induction' s using Quotient.inductionOn with l
simp only [quot_mk_to_coe, mem_coe, coe_erase, noncommProd_coe] at comm h ⊢
suffices ∀ x ∈ l, ∀ y ∈ l, x * y = y * x by rw [List.prod_erase_of_comm h this]
intro x hx y hy
rcases eq_or_ne x y with rfl | hxy
· rfl
exact comm hx hy hxy
theorem noncommProd_erase_mul [DecidableEq α] (s : Multiset α) {a : α} (h : a ∈ s) (comm)
(comm' := fun x hx y hy hxy ↦ comm (s.mem_of_mem_erase hx) (s.mem_of_mem_erase hy) hxy) :
(s.erase a).noncommProd comm' * a = s.noncommProd comm := by
suffices ∀ b ∈ erase s a, Commute a b by
rw [← (noncommProd_commute (s.erase a) comm' a this).eq, mul_noncommProd_erase s h comm comm']
intro b hb
rcases eq_or_ne a b with rfl | hab
· rfl
exact comm h (mem_of_mem_erase hb) hab
end Multiset
namespace Finset
variable [Monoid β] [Monoid γ]
/-- Proof used in definition of `Finset.noncommProd` -/
@[to_additive]
theorem noncommProd_lemma (s : Finset α) (f : α → β)
(comm : (s : Set α).Pairwise fun a b => Commute (f a) (f b)) :
Set.Pairwise { x | x ∈ Multiset.map f s.val } Commute := by
simp_rw [Multiset.mem_map]
rintro _ ⟨a, ha, rfl⟩ _ ⟨b, hb, rfl⟩ _
exact comm.of_refl ha hb
/-- Product of a `s : Finset α` mapped with `f : α → β` with `[Monoid β]`,
given a proof that `*` commutes on all elements `f x` for `x ∈ s`. -/
@[to_additive
"Sum of a `s : Finset α` mapped with `f : α → β` with `[AddMonoid β]`,
given a proof that `+` commutes on all elements `f x` for `x ∈ s`."]
def noncommProd (s : Finset α) (f : α → β)
(comm : (s : Set α).Pairwise fun a b => Commute (f a) (f b)) : β :=
(s.1.map f).noncommProd <| noncommProd_lemma s f comm
#align finset.noncomm_prod Finset.noncommProd
#align finset.noncomm_sum Finset.noncommSum
@[to_additive]
lemma noncommProd_induction (s : Finset α) (f : α → β) (comm)
(p : β → Prop) (hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p (f x)) :
p (s.noncommProd f comm) := by
refine Multiset.noncommProd_induction _ _ _ hom unit fun b hb ↦ ?_
obtain (⟨a, ha : a ∈ s, rfl : f a = b⟩) := by simpa using hb
exact base a ha
@[to_additive (attr := congr)]
theorem noncommProd_congr {s₁ s₂ : Finset α} {f g : α → β} (h₁ : s₁ = s₂)
(h₂ : ∀ x ∈ s₂, f x = g x) (comm) :
noncommProd s₁ f comm =
noncommProd s₂ g fun x hx y hy h => by
dsimp only
rw [← h₂ _ hx, ← h₂ _ hy]
subst h₁
exact comm hx hy h := by
simp_rw [noncommProd, Multiset.map_congr (congr_arg _ h₁) h₂]
#align finset.noncomm_prod_congr Finset.noncommProd_congr
#align finset.noncomm_sum_congr Finset.noncommSum_congr
@[to_additive (attr := simp)]
theorem noncommProd_toFinset [DecidableEq α] (l : List α) (f : α → β) (comm) (hl : l.Nodup) :
noncommProd l.toFinset f comm = (l.map f).prod := by
rw [← List.dedup_eq_self] at hl
simp [noncommProd, hl]
#align finset.noncomm_prod_to_finset Finset.noncommProd_toFinset
#align finset.noncomm_sum_to_finset Finset.noncommSum_toFinset
@[to_additive (attr := simp)]
theorem noncommProd_empty (f : α → β) (h) : noncommProd (∅ : Finset α) f h = 1 :=
rfl
#align finset.noncomm_prod_empty Finset.noncommProd_empty
#align finset.noncomm_sum_empty Finset.noncommSum_empty
@[to_additive (attr := simp)]
theorem noncommProd_cons (s : Finset α) (a : α) (f : α → β)
(ha : a ∉ s) (comm) :
noncommProd (cons a s ha) f comm =
f a * noncommProd s f (comm.mono fun _ => Finset.mem_cons.2 ∘ .inr) := by
simp_rw [noncommProd, Finset.cons_val, Multiset.map_cons, Multiset.noncommProd_cons]
@[to_additive]
theorem noncommProd_cons' (s : Finset α) (a : α) (f : α → β)
(ha : a ∉ s) (comm) :
noncommProd (cons a s ha) f comm =
noncommProd s f (comm.mono fun _ => Finset.mem_cons.2 ∘ .inr) * f a := by
simp_rw [noncommProd, Finset.cons_val, Multiset.map_cons, Multiset.noncommProd_cons']
@[to_additive (attr := simp)]
| Mathlib/Data/Finset/NoncommProd.lean | 329 | 333 | theorem noncommProd_insert_of_not_mem [DecidableEq α] (s : Finset α) (a : α) (f : α → β) (comm)
(ha : a ∉ s) :
noncommProd (insert a s) f comm =
f a * noncommProd s f (comm.mono fun _ => mem_insert_of_mem) := by |
simp only [← cons_eq_insert _ _ ha, noncommProd_cons]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johannes Hölzl, Yury G. Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.GeomSum
import Mathlib.Order.Filter.Archimedean
import Mathlib.Order.Iterate
import Mathlib.Topology.Algebra.Algebra
import Mathlib.Topology.Algebra.InfiniteSum.Real
#align_import analysis.specific_limits.basic from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2"
/-!
# A collection of specific limit computations
This file, by design, is independent of `NormedSpace` in the import hierarchy. It contains
important specific limit computations in metric spaces, in ordered rings/fields, and in specific
instances of these such as `ℝ`, `ℝ≥0` and `ℝ≥0∞`.
-/
noncomputable section
open scoped Classical
open Set Function Filter Finset Metric
open scoped Classical
open Topology Nat uniformity NNReal ENNReal
variable {α : Type*} {β : Type*} {ι : Type*}
theorem tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
tendsto_inv_atTop_zero.comp tendsto_natCast_atTop_atTop
#align tendsto_inverse_at_top_nhds_0_nat tendsto_inverse_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_inverse_atTop_nhds_0_nat := tendsto_inverse_atTop_nhds_zero_nat
theorem tendsto_const_div_atTop_nhds_zero_nat (C : ℝ) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa only [mul_zero] using tendsto_const_nhds.mul tendsto_inverse_atTop_nhds_zero_nat
#align tendsto_const_div_at_top_nhds_0_nat tendsto_const_div_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_const_div_atTop_nhds_0_nat := tendsto_const_div_atTop_nhds_zero_nat
theorem tendsto_one_div_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ 1/(n : ℝ)) atTop (𝓝 0) :=
tendsto_const_div_atTop_nhds_zero_nat 1
@[deprecated (since := "2024-01-31")]
alias tendsto_one_div_atTop_nhds_0_nat := tendsto_one_div_atTop_nhds_zero_nat
theorem NNReal.tendsto_inverse_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
rw [← NNReal.tendsto_coe]
exact _root_.tendsto_inverse_atTop_nhds_zero_nat
#align nnreal.tendsto_inverse_at_top_nhds_0_nat NNReal.tendsto_inverse_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_inverse_atTop_nhds_0_nat := NNReal.tendsto_inverse_atTop_nhds_zero_nat
theorem NNReal.tendsto_const_div_atTop_nhds_zero_nat (C : ℝ≥0) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa using tendsto_const_nhds.mul NNReal.tendsto_inverse_atTop_nhds_zero_nat
#align nnreal.tendsto_const_div_at_top_nhds_0_nat NNReal.tendsto_const_div_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_const_div_atTop_nhds_0_nat := NNReal.tendsto_const_div_atTop_nhds_zero_nat
theorem tendsto_one_div_add_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ 1 / ((n : ℝ) + 1)) atTop (𝓝 0) :=
suffices Tendsto (fun n : ℕ ↦ 1 / (↑(n + 1) : ℝ)) atTop (𝓝 0) by simpa
(tendsto_add_atTop_iff_nat 1).2 (_root_.tendsto_const_div_atTop_nhds_zero_nat 1)
#align tendsto_one_div_add_at_top_nhds_0_nat tendsto_one_div_add_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_one_div_add_atTop_nhds_0_nat := tendsto_one_div_add_atTop_nhds_zero_nat
theorem NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜]
[Algebra ℝ≥0 𝕜] [TopologicalSpace 𝕜] [ContinuousSMul ℝ≥0 𝕜] :
Tendsto (algebraMap ℝ≥0 𝕜 ∘ fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
convert (continuous_algebraMap ℝ≥0 𝕜).continuousAt.tendsto.comp
tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero]
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_algebraMap_inverse_atTop_nhds_0_nat :=
NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat
theorem tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜] [Algebra ℝ 𝕜]
[TopologicalSpace 𝕜] [ContinuousSMul ℝ 𝕜] :
Tendsto (algebraMap ℝ 𝕜 ∘ fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat 𝕜
@[deprecated (since := "2024-01-31")]
alias tendsto_algebraMap_inverse_atTop_nhds_0_nat :=
_root_.tendsto_algebraMap_inverse_atTop_nhds_zero_nat
/-- The limit of `n / (n + x)` is 1, for any constant `x` (valid in `ℝ` or any topological division
algebra over `ℝ`, e.g., `ℂ`).
TODO: introduce a typeclass saying that `1 / n` tends to 0 at top, making it possible to get this
statement simultaneously on `ℚ`, `ℝ` and `ℂ`. -/
theorem tendsto_natCast_div_add_atTop {𝕜 : Type*} [DivisionRing 𝕜] [TopologicalSpace 𝕜]
[CharZero 𝕜] [Algebra ℝ 𝕜] [ContinuousSMul ℝ 𝕜] [TopologicalDivisionRing 𝕜] (x : 𝕜) :
Tendsto (fun n : ℕ ↦ (n : 𝕜) / (n + x)) atTop (𝓝 1) := by
convert Tendsto.congr' ((eventually_ne_atTop 0).mp (eventually_of_forall fun n hn ↦ _)) _
· exact fun n : ℕ ↦ 1 / (1 + x / n)
· field_simp [Nat.cast_ne_zero.mpr hn]
· have : 𝓝 (1 : 𝕜) = 𝓝 (1 / (1 + x * (0 : 𝕜))) := by
rw [mul_zero, add_zero, div_one]
rw [this]
refine tendsto_const_nhds.div (tendsto_const_nhds.add ?_) (by simp)
simp_rw [div_eq_mul_inv]
refine tendsto_const_nhds.mul ?_
have := ((continuous_algebraMap ℝ 𝕜).tendsto _).comp tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero, Filter.tendsto_atTop'] at this
refine Iff.mpr tendsto_atTop' ?_
intros
simp_all only [comp_apply, map_inv₀, map_natCast]
#align tendsto_coe_nat_div_add_at_top tendsto_natCast_div_add_atTop
/-! ### Powers -/
theorem tendsto_add_one_pow_atTop_atTop_of_pos [LinearOrderedSemiring α] [Archimedean α] {r : α}
(h : 0 < r) : Tendsto (fun n : ℕ ↦ (r + 1) ^ n) atTop atTop :=
tendsto_atTop_atTop_of_monotone' (fun _ _ ↦ pow_le_pow_right <| le_add_of_nonneg_left h.le) <|
not_bddAbove_iff.2 fun _ ↦ Set.exists_range_iff.2 <| add_one_pow_unbounded_of_pos _ h
#align tendsto_add_one_pow_at_top_at_top_of_pos tendsto_add_one_pow_atTop_atTop_of_pos
theorem tendsto_pow_atTop_atTop_of_one_lt [LinearOrderedRing α] [Archimedean α] {r : α}
(h : 1 < r) : Tendsto (fun n : ℕ ↦ r ^ n) atTop atTop :=
sub_add_cancel r 1 ▸ tendsto_add_one_pow_atTop_atTop_of_pos (sub_pos.2 h)
#align tendsto_pow_at_top_at_top_of_one_lt tendsto_pow_atTop_atTop_of_one_lt
theorem Nat.tendsto_pow_atTop_atTop_of_one_lt {m : ℕ} (h : 1 < m) :
Tendsto (fun n : ℕ ↦ m ^ n) atTop atTop :=
tsub_add_cancel_of_le (le_of_lt h) ▸ tendsto_add_one_pow_atTop_atTop_of_pos (tsub_pos_of_lt h)
#align nat.tendsto_pow_at_top_at_top_of_one_lt Nat.tendsto_pow_atTop_atTop_of_one_lt
theorem tendsto_pow_atTop_nhds_zero_of_lt_one {𝕜 : Type*} [LinearOrderedField 𝕜] [Archimedean 𝕜]
[TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} (h₁ : 0 ≤ r) (h₂ : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) :=
h₁.eq_or_lt.elim
(fun hr ↦ (tendsto_add_atTop_iff_nat 1).mp <| by
simp [_root_.pow_succ, ← hr, tendsto_const_nhds])
(fun hr ↦
have := one_lt_inv hr h₂ |> tendsto_pow_atTop_atTop_of_one_lt
(tendsto_inv_atTop_zero.comp this).congr fun n ↦ by simp)
#align tendsto_pow_at_top_nhds_0_of_lt_1 tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_of_lt_1 := tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp] theorem tendsto_pow_atTop_nhds_zero_iff {𝕜 : Type*} [LinearOrderedField 𝕜] [Archimedean 𝕜]
[TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) ↔ |r| < 1 := by
rw [tendsto_zero_iff_abs_tendsto_zero]
refine ⟨fun h ↦ by_contra (fun hr_le ↦ ?_), fun h ↦ ?_⟩
· by_cases hr : 1 = |r|
· replace h : Tendsto (fun n : ℕ ↦ |r|^n) atTop (𝓝 0) := by simpa only [← abs_pow, h]
simp only [hr.symm, one_pow] at h
exact zero_ne_one <| tendsto_nhds_unique h tendsto_const_nhds
· apply @not_tendsto_nhds_of_tendsto_atTop 𝕜 ℕ _ _ _ _ atTop _ (fun n ↦ |r| ^ n) _ 0 _
· refine (pow_right_strictMono <| lt_of_le_of_ne (le_of_not_lt hr_le)
hr).monotone.tendsto_atTop_atTop (fun b ↦ ?_)
obtain ⟨n, hn⟩ := (pow_unbounded_of_one_lt b (lt_of_le_of_ne (le_of_not_lt hr_le) hr))
exact ⟨n, le_of_lt hn⟩
· simpa only [← abs_pow]
· simpa only [← abs_pow] using (tendsto_pow_atTop_nhds_zero_of_lt_one (abs_nonneg r)) h
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhds_0_iff := tendsto_pow_atTop_nhds_zero_iff
theorem tendsto_pow_atTop_nhdsWithin_zero_of_lt_one {𝕜 : Type*} [LinearOrderedField 𝕜]
[Archimedean 𝕜] [TopologicalSpace 𝕜] [OrderTopology 𝕜] {r : 𝕜} (h₁ : 0 < r) (h₂ : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝[>] 0) :=
tendsto_inf.2
⟨tendsto_pow_atTop_nhds_zero_of_lt_one h₁.le h₂,
tendsto_principal.2 <| eventually_of_forall fun _ ↦ pow_pos h₁ _⟩
#align tendsto_pow_at_top_nhds_within_0_of_lt_1 tendsto_pow_atTop_nhdsWithin_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias tendsto_pow_atTop_nhdsWithin_0_of_lt_1 := tendsto_pow_atTop_nhdsWithin_zero_of_lt_one
theorem uniformity_basis_dist_pow_of_lt_one {α : Type*} [PseudoMetricSpace α] {r : ℝ} (h₀ : 0 < r)
(h₁ : r < 1) :
(uniformity α).HasBasis (fun _ : ℕ ↦ True) fun k ↦ { p : α × α | dist p.1 p.2 < r ^ k } :=
Metric.mk_uniformity_basis (fun _ _ ↦ pow_pos h₀ _) fun _ ε0 ↦
(exists_pow_lt_of_lt_one ε0 h₁).imp fun _ hk ↦ ⟨trivial, hk.le⟩
#align uniformity_basis_dist_pow_of_lt_1 uniformity_basis_dist_pow_of_lt_one
@[deprecated (since := "2024-01-31")]
alias uniformity_basis_dist_pow_of_lt_1 := uniformity_basis_dist_pow_of_lt_one
theorem geom_lt {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) {n : ℕ} (hn : 0 < n)
(h : ∀ k < n, c * u k < u (k + 1)) : c ^ n * u 0 < u n := by
apply (monotone_mul_left_of_nonneg hc).seq_pos_lt_seq_of_le_of_lt hn _ _ h
· simp
· simp [_root_.pow_succ', mul_assoc, le_refl]
#align geom_lt geom_lt
theorem geom_le {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) (n : ℕ) (h : ∀ k < n, c * u k ≤ u (k + 1)) :
c ^ n * u 0 ≤ u n := by
apply (monotone_mul_left_of_nonneg hc).seq_le_seq n _ _ h <;>
simp [_root_.pow_succ', mul_assoc, le_refl]
#align geom_le geom_le
theorem lt_geom {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) {n : ℕ} (hn : 0 < n)
(h : ∀ k < n, u (k + 1) < c * u k) : u n < c ^ n * u 0 := by
apply (monotone_mul_left_of_nonneg hc).seq_pos_lt_seq_of_lt_of_le hn _ h _
· simp
· simp [_root_.pow_succ', mul_assoc, le_refl]
#align lt_geom lt_geom
theorem le_geom {u : ℕ → ℝ} {c : ℝ} (hc : 0 ≤ c) (n : ℕ) (h : ∀ k < n, u (k + 1) ≤ c * u k) :
u n ≤ c ^ n * u 0 := by
apply (monotone_mul_left_of_nonneg hc).seq_le_seq n _ h _ <;>
simp [_root_.pow_succ', mul_assoc, le_refl]
#align le_geom le_geom
/-- If a sequence `v` of real numbers satisfies `k * v n ≤ v (n+1)` with `1 < k`,
then it goes to +∞. -/
theorem tendsto_atTop_of_geom_le {v : ℕ → ℝ} {c : ℝ} (h₀ : 0 < v 0) (hc : 1 < c)
(hu : ∀ n, c * v n ≤ v (n + 1)) : Tendsto v atTop atTop :=
(tendsto_atTop_mono fun n ↦ geom_le (zero_le_one.trans hc.le) n fun k _ ↦ hu k) <|
(tendsto_pow_atTop_atTop_of_one_lt hc).atTop_mul_const h₀
#align tendsto_at_top_of_geom_le tendsto_atTop_of_geom_le
theorem NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one {r : ℝ≥0} (hr : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) :=
NNReal.tendsto_coe.1 <| by
simp only [NNReal.coe_pow, NNReal.coe_zero,
_root_.tendsto_pow_atTop_nhds_zero_of_lt_one r.coe_nonneg hr]
#align nnreal.tendsto_pow_at_top_nhds_0_of_lt_1 NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias NNReal.tendsto_pow_atTop_nhds_0_of_lt_1 := NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp]
protected theorem NNReal.tendsto_pow_atTop_nhds_zero_iff {r : ℝ≥0} :
Tendsto (fun n : ℕ => r ^ n) atTop (𝓝 0) ↔ r < 1 :=
⟨fun h => by simpa [coe_pow, coe_zero, abs_eq, coe_lt_one, val_eq_coe] using
tendsto_pow_atTop_nhds_zero_iff.mp <| tendsto_coe.mpr h, tendsto_pow_atTop_nhds_zero_of_lt_one⟩
theorem ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one {r : ℝ≥0∞} (hr : r < 1) :
Tendsto (fun n : ℕ ↦ r ^ n) atTop (𝓝 0) := by
rcases ENNReal.lt_iff_exists_coe.1 hr with ⟨r, rfl, hr'⟩
rw [← ENNReal.coe_zero]
norm_cast at *
apply NNReal.tendsto_pow_atTop_nhds_zero_of_lt_one hr
#align ennreal.tendsto_pow_at_top_nhds_0_of_lt_1 ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[deprecated (since := "2024-01-31")]
alias ENNReal.tendsto_pow_atTop_nhds_0_of_lt_1 := ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one
@[simp]
protected theorem ENNReal.tendsto_pow_atTop_nhds_zero_iff {r : ℝ≥0∞} :
Tendsto (fun n : ℕ => r ^ n) atTop (𝓝 0) ↔ r < 1 := by
refine ⟨fun h ↦ ?_, tendsto_pow_atTop_nhds_zero_of_lt_one⟩
lift r to NNReal
· refine fun hr ↦ top_ne_zero (tendsto_nhds_unique (EventuallyEq.tendsto ?_) (hr ▸ h))
exact eventually_atTop.mpr ⟨1, fun _ hn ↦ pow_eq_top_iff.mpr ⟨rfl, Nat.pos_iff_ne_zero.mp hn⟩⟩
rw [← coe_zero] at h
norm_cast at h ⊢
exact NNReal.tendsto_pow_atTop_nhds_zero_iff.mp h
/-! ### Geometric series-/
section Geometric
theorem hasSum_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) :
HasSum (fun n : ℕ ↦ r ^ n) (1 - r)⁻¹ :=
have : r ≠ 1 := ne_of_lt h₂
have : Tendsto (fun n ↦ (r ^ n - 1) * (r - 1)⁻¹) atTop (𝓝 ((0 - 1) * (r - 1)⁻¹)) :=
((tendsto_pow_atTop_nhds_zero_of_lt_one h₁ h₂).sub tendsto_const_nhds).mul tendsto_const_nhds
(hasSum_iff_tendsto_nat_of_nonneg (pow_nonneg h₁) _).mpr <| by
simp_all [neg_inv, geom_sum_eq, div_eq_mul_inv]
#align has_sum_geometric_of_lt_1 hasSum_geometric_of_lt_one
@[deprecated (since := "2024-01-31")] alias hasSum_geometric_of_lt_1 := hasSum_geometric_of_lt_one
theorem summable_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) :
Summable fun n : ℕ ↦ r ^ n :=
⟨_, hasSum_geometric_of_lt_one h₁ h₂⟩
#align summable_geometric_of_lt_1 summable_geometric_of_lt_one
@[deprecated (since := "2024-01-31")]
alias summable_geometric_of_lt_1 := summable_geometric_of_lt_one
theorem tsum_geometric_of_lt_one {r : ℝ} (h₁ : 0 ≤ r) (h₂ : r < 1) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ :=
(hasSum_geometric_of_lt_one h₁ h₂).tsum_eq
#align tsum_geometric_of_lt_1 tsum_geometric_of_lt_one
@[deprecated (since := "2024-01-31")] alias tsum_geometric_of_lt_1 := tsum_geometric_of_lt_one
theorem hasSum_geometric_two : HasSum (fun n : ℕ ↦ ((1 : ℝ) / 2) ^ n) 2 := by
convert hasSum_geometric_of_lt_one _ _ <;> norm_num
#align has_sum_geometric_two hasSum_geometric_two
theorem summable_geometric_two : Summable fun n : ℕ ↦ ((1 : ℝ) / 2) ^ n :=
⟨_, hasSum_geometric_two⟩
#align summable_geometric_two summable_geometric_two
theorem summable_geometric_two_encode {ι : Type*} [Encodable ι] :
Summable fun i : ι ↦ (1 / 2 : ℝ) ^ Encodable.encode i :=
summable_geometric_two.comp_injective Encodable.encode_injective
#align summable_geometric_two_encode summable_geometric_two_encode
theorem tsum_geometric_two : (∑' n : ℕ, ((1 : ℝ) / 2) ^ n) = 2 :=
hasSum_geometric_two.tsum_eq
#align tsum_geometric_two tsum_geometric_two
theorem sum_geometric_two_le (n : ℕ) : (∑ i ∈ range n, (1 / (2 : ℝ)) ^ i) ≤ 2 := by
have : ∀ i, 0 ≤ (1 / (2 : ℝ)) ^ i := by
intro i
apply pow_nonneg
norm_num
convert sum_le_tsum (range n) (fun i _ ↦ this i) summable_geometric_two
exact tsum_geometric_two.symm
#align sum_geometric_two_le sum_geometric_two_le
theorem tsum_geometric_inv_two : (∑' n : ℕ, (2 : ℝ)⁻¹ ^ n) = 2 :=
(inv_eq_one_div (2 : ℝ)).symm ▸ tsum_geometric_two
#align tsum_geometric_inv_two tsum_geometric_inv_two
/-- The sum of `2⁻¹ ^ i` for `n ≤ i` equals `2 * 2⁻¹ ^ n`. -/
theorem tsum_geometric_inv_two_ge (n : ℕ) :
(∑' i, ite (n ≤ i) ((2 : ℝ)⁻¹ ^ i) 0) = 2 * 2⁻¹ ^ n := by
have A : Summable fun i : ℕ ↦ ite (n ≤ i) ((2⁻¹ : ℝ) ^ i) 0 := by
simpa only [← piecewise_eq_indicator, one_div]
using summable_geometric_two.indicator {i | n ≤ i}
have B : ((Finset.range n).sum fun i : ℕ ↦ ite (n ≤ i) ((2⁻¹ : ℝ) ^ i) 0) = 0 :=
Finset.sum_eq_zero fun i hi ↦
ite_eq_right_iff.2 fun h ↦ (lt_irrefl _ ((Finset.mem_range.1 hi).trans_le h)).elim
simp only [← _root_.sum_add_tsum_nat_add n A, B, if_true, zero_add, zero_le',
le_add_iff_nonneg_left, pow_add, _root_.tsum_mul_right, tsum_geometric_inv_two]
#align tsum_geometric_inv_two_ge tsum_geometric_inv_two_ge
theorem hasSum_geometric_two' (a : ℝ) : HasSum (fun n : ℕ ↦ a / 2 / 2 ^ n) a := by
convert HasSum.mul_left (a / 2)
(hasSum_geometric_of_lt_one (le_of_lt one_half_pos) one_half_lt_one) using 1
· funext n
simp only [one_div, inv_pow]
rfl
· norm_num
#align has_sum_geometric_two' hasSum_geometric_two'
theorem summable_geometric_two' (a : ℝ) : Summable fun n : ℕ ↦ a / 2 / 2 ^ n :=
⟨a, hasSum_geometric_two' a⟩
#align summable_geometric_two' summable_geometric_two'
theorem tsum_geometric_two' (a : ℝ) : ∑' n : ℕ, a / 2 / 2 ^ n = a :=
(hasSum_geometric_two' a).tsum_eq
#align tsum_geometric_two' tsum_geometric_two'
/-- **Sum of a Geometric Series** -/
theorem NNReal.hasSum_geometric {r : ℝ≥0} (hr : r < 1) : HasSum (fun n : ℕ ↦ r ^ n) (1 - r)⁻¹ := by
apply NNReal.hasSum_coe.1
push_cast
rw [NNReal.coe_sub (le_of_lt hr)]
exact hasSum_geometric_of_lt_one r.coe_nonneg hr
#align nnreal.has_sum_geometric NNReal.hasSum_geometric
theorem NNReal.summable_geometric {r : ℝ≥0} (hr : r < 1) : Summable fun n : ℕ ↦ r ^ n :=
⟨_, NNReal.hasSum_geometric hr⟩
#align nnreal.summable_geometric NNReal.summable_geometric
theorem tsum_geometric_nnreal {r : ℝ≥0} (hr : r < 1) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ :=
(NNReal.hasSum_geometric hr).tsum_eq
#align tsum_geometric_nnreal tsum_geometric_nnreal
/-- The series `pow r` converges to `(1-r)⁻¹`. For `r < 1` the RHS is a finite number,
and for `1 ≤ r` the RHS equals `∞`. -/
@[simp]
theorem ENNReal.tsum_geometric (r : ℝ≥0∞) : ∑' n : ℕ, r ^ n = (1 - r)⁻¹ := by
cases' lt_or_le r 1 with hr hr
· rcases ENNReal.lt_iff_exists_coe.1 hr with ⟨r, rfl, hr'⟩
norm_cast at *
convert ENNReal.tsum_coe_eq (NNReal.hasSum_geometric hr)
rw [ENNReal.coe_inv <| ne_of_gt <| tsub_pos_iff_lt.2 hr, coe_sub, coe_one]
· rw [tsub_eq_zero_iff_le.mpr hr, ENNReal.inv_zero, ENNReal.tsum_eq_iSup_nat, iSup_eq_top]
refine fun a ha ↦
(ENNReal.exists_nat_gt (lt_top_iff_ne_top.1 ha)).imp fun n hn ↦ lt_of_lt_of_le hn ?_
calc
(n : ℝ≥0∞) = ∑ i ∈ range n, 1 := by rw [sum_const, nsmul_one, card_range]
_ ≤ ∑ i ∈ range n, r ^ i := by gcongr; apply one_le_pow_of_one_le' hr
#align ennreal.tsum_geometric ENNReal.tsum_geometric
theorem ENNReal.tsum_geometric_add_one (r : ℝ≥0∞) : ∑' n : ℕ, r ^ (n + 1) = r * (1 - r)⁻¹ := by
simp only [_root_.pow_succ', ENNReal.tsum_mul_left, ENNReal.tsum_geometric]
end Geometric
/-!
### Sequences with geometrically decaying distance in metric spaces
In this paragraph, we discuss sequences in metric spaces or emetric spaces for which the distance
between two consecutive terms decays geometrically. We show that such sequences are Cauchy
sequences, and bound their distances to the limit. We also discuss series with geometrically
decaying terms.
-/
section EdistLeGeometric
variable [PseudoEMetricSpace α] (r C : ℝ≥0∞) (hr : r < 1) (hC : C ≠ ⊤) {f : ℕ → α}
(hu : ∀ n, edist (f n) (f (n + 1)) ≤ C * r ^ n)
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, `C ≠ ∞`, `r < 1`,
then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_edist_le_geometric : CauchySeq f := by
refine cauchySeq_of_edist_le_of_tsum_ne_top _ hu ?_
rw [ENNReal.tsum_mul_left, ENNReal.tsum_geometric]
refine ENNReal.mul_ne_top hC (ENNReal.inv_ne_top.2 ?_)
exact (tsub_pos_iff_lt.2 hr).ne'
#align cauchy_seq_of_edist_le_geometric cauchySeq_of_edist_le_geometric
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, then the distance from
`f n` to the limit of `f` is bounded above by `C * r^n / (1 - r)`. -/
theorem edist_le_of_edist_le_geometric_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
edist (f n) a ≤ C * r ^ n / (1 - r) := by
convert edist_le_tsum_of_edist_le_of_tendsto _ hu ha _
simp only [pow_add, ENNReal.tsum_mul_left, ENNReal.tsum_geometric, div_eq_mul_inv, mul_assoc]
#align edist_le_of_edist_le_geometric_of_tendsto edist_le_of_edist_le_geometric_of_tendsto
/-- If `edist (f n) (f (n+1))` is bounded by `C * r^n`, then the distance from
`f 0` to the limit of `f` is bounded above by `C / (1 - r)`. -/
theorem edist_le_of_edist_le_geometric_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
edist (f 0) a ≤ C / (1 - r) := by
simpa only [_root_.pow_zero, mul_one] using edist_le_of_edist_le_geometric_of_tendsto r C hu ha 0
#align edist_le_of_edist_le_geometric_of_tendsto₀ edist_le_of_edist_le_geometric_of_tendsto₀
end EdistLeGeometric
section EdistLeGeometricTwo
variable [PseudoEMetricSpace α] (C : ℝ≥0∞) (hC : C ≠ ⊤) {f : ℕ → α}
(hu : ∀ n, edist (f n) (f (n + 1)) ≤ C / 2 ^ n) {a : α} (ha : Tendsto f atTop (𝓝 a))
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_edist_le_geometric_two : CauchySeq f := by
simp only [div_eq_mul_inv, ENNReal.inv_pow] at hu
refine cauchySeq_of_edist_le_geometric 2⁻¹ C ?_ hC hu
simp [ENNReal.one_lt_two]
#align cauchy_seq_of_edist_le_geometric_two cauchySeq_of_edist_le_geometric_two
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then the distance from
`f n` to the limit of `f` is bounded above by `2 * C * 2^-n`. -/
theorem edist_le_of_edist_le_geometric_two_of_tendsto (n : ℕ) : edist (f n) a ≤ 2 * C / 2 ^ n := by
simp only [div_eq_mul_inv, ENNReal.inv_pow] at *
rw [mul_assoc, mul_comm]
convert edist_le_of_edist_le_geometric_of_tendsto 2⁻¹ C hu ha n using 1
rw [ENNReal.one_sub_inv_two, div_eq_mul_inv, inv_inv]
#align edist_le_of_edist_le_geometric_two_of_tendsto edist_le_of_edist_le_geometric_two_of_tendsto
/-- If `edist (f n) (f (n+1))` is bounded by `C * 2^-n`, then the distance from
`f 0` to the limit of `f` is bounded above by `2 * C`. -/
theorem edist_le_of_edist_le_geometric_two_of_tendsto₀ : edist (f 0) a ≤ 2 * C := by
simpa only [_root_.pow_zero, div_eq_mul_inv, inv_one, mul_one] using
edist_le_of_edist_le_geometric_two_of_tendsto C hu ha 0
#align edist_le_of_edist_le_geometric_two_of_tendsto₀ edist_le_of_edist_le_geometric_two_of_tendsto₀
end EdistLeGeometricTwo
section LeGeometric
variable [PseudoMetricSpace α] {r C : ℝ} (hr : r < 1) {f : ℕ → α}
(hu : ∀ n, dist (f n) (f (n + 1)) ≤ C * r ^ n)
theorem aux_hasSum_of_le_geometric : HasSum (fun n : ℕ ↦ C * r ^ n) (C / (1 - r)) := by
rcases sign_cases_of_C_mul_pow_nonneg fun n ↦ dist_nonneg.trans (hu n) with (rfl | ⟨_, r₀⟩)
· simp [hasSum_zero]
· refine HasSum.mul_left C ?_
simpa using hasSum_geometric_of_lt_one r₀ hr
#align aux_has_sum_of_le_geometric aux_hasSum_of_le_geometric
variable (r C)
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then `f` is a Cauchy sequence.
Note that this lemma does not assume `0 ≤ C` or `0 ≤ r`. -/
theorem cauchySeq_of_le_geometric : CauchySeq f :=
cauchySeq_of_dist_le_of_summable _ hu ⟨_, aux_hasSum_of_le_geometric hr hu⟩
#align cauchy_seq_of_le_geometric cauchySeq_of_le_geometric
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then the distance from
`f n` to the limit of `f` is bounded above by `C * r^n / (1 - r)`. -/
theorem dist_le_of_le_geometric_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
dist (f 0) a ≤ C / (1 - r) :=
(aux_hasSum_of_le_geometric hr hu).tsum_eq ▸
dist_le_tsum_of_dist_le_of_tendsto₀ _ hu ⟨_, aux_hasSum_of_le_geometric hr hu⟩ ha
#align dist_le_of_le_geometric_of_tendsto₀ dist_le_of_le_geometric_of_tendsto₀
/-- If `dist (f n) (f (n+1))` is bounded by `C * r^n`, `r < 1`, then the distance from
`f 0` to the limit of `f` is bounded above by `C / (1 - r)`. -/
theorem dist_le_of_le_geometric_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
dist (f n) a ≤ C * r ^ n / (1 - r) := by
have := aux_hasSum_of_le_geometric hr hu
convert dist_le_tsum_of_dist_le_of_tendsto _ hu ⟨_, this⟩ ha n
simp only [pow_add, mul_left_comm C, mul_div_right_comm]
rw [mul_comm]
exact (this.mul_left _).tsum_eq.symm
#align dist_le_of_le_geometric_of_tendsto dist_le_of_le_geometric_of_tendsto
variable (hu₂ : ∀ n, dist (f n) (f (n + 1)) ≤ C / 2 / 2 ^ n)
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then `f` is a Cauchy sequence. -/
theorem cauchySeq_of_le_geometric_two : CauchySeq f :=
cauchySeq_of_dist_le_of_summable _ hu₂ <| ⟨_, hasSum_geometric_two' C⟩
#align cauchy_seq_of_le_geometric_two cauchySeq_of_le_geometric_two
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then the distance from
`f 0` to the limit of `f` is bounded above by `C`. -/
theorem dist_le_of_le_geometric_two_of_tendsto₀ {a : α} (ha : Tendsto f atTop (𝓝 a)) :
dist (f 0) a ≤ C :=
tsum_geometric_two' C ▸ dist_le_tsum_of_dist_le_of_tendsto₀ _ hu₂ (summable_geometric_two' C) ha
#align dist_le_of_le_geometric_two_of_tendsto₀ dist_le_of_le_geometric_two_of_tendsto₀
/-- If `dist (f n) (f (n+1))` is bounded by `(C / 2) / 2^n`, then the distance from
`f n` to the limit of `f` is bounded above by `C / 2^n`. -/
theorem dist_le_of_le_geometric_two_of_tendsto {a : α} (ha : Tendsto f atTop (𝓝 a)) (n : ℕ) :
dist (f n) a ≤ C / 2 ^ n := by
convert dist_le_tsum_of_dist_le_of_tendsto _ hu₂ (summable_geometric_two' C) ha n
simp only [add_comm n, pow_add, ← div_div]
symm
exact ((hasSum_geometric_two' C).div_const _).tsum_eq
#align dist_le_of_le_geometric_two_of_tendsto dist_le_of_le_geometric_two_of_tendsto
end LeGeometric
/-! ### Summability tests based on comparison with geometric series -/
/-- A series whose terms are bounded by the terms of a converging geometric series converges. -/
theorem summable_one_div_pow_of_le {m : ℝ} {f : ℕ → ℕ} (hm : 1 < m) (fi : ∀ i, i ≤ f i) :
Summable fun i ↦ 1 / m ^ f i := by
refine .of_nonneg_of_le (fun a ↦ by positivity) (fun a ↦ ?_)
(summable_geometric_of_lt_one (one_div_nonneg.mpr (zero_le_one.trans hm.le))
((one_div_lt (zero_lt_one.trans hm) zero_lt_one).mpr (one_div_one.le.trans_lt hm)))
rw [div_pow, one_pow]
refine (one_div_le_one_div ?_ ?_).mpr (pow_le_pow_right hm.le (fi a)) <;>
exact pow_pos (zero_lt_one.trans hm) _
#align summable_one_div_pow_of_le summable_one_div_pow_of_le
/-! ### Positive sequences with small sums on countable types -/
/-- For any positive `ε`, define on an encodable type a positive sequence with sum less than `ε` -/
def posSumOfEncodable {ε : ℝ} (hε : 0 < ε) (ι) [Encodable ι] :
{ ε' : ι → ℝ // (∀ i, 0 < ε' i) ∧ ∃ c, HasSum ε' c ∧ c ≤ ε } := by
let f n := ε / 2 / 2 ^ n
have hf : HasSum f ε := hasSum_geometric_two' _
have f0 : ∀ n, 0 < f n := fun n ↦ div_pos (half_pos hε) (pow_pos zero_lt_two _)
refine ⟨f ∘ Encodable.encode, fun i ↦ f0 _, ?_⟩
rcases hf.summable.comp_injective (@Encodable.encode_injective ι _) with ⟨c, hg⟩
refine ⟨c, hg, hasSum_le_inj _ (@Encodable.encode_injective ι _) ?_ ?_ hg hf⟩
· intro i _
exact le_of_lt (f0 _)
· intro n
exact le_rfl
#align pos_sum_of_encodable posSumOfEncodable
theorem Set.Countable.exists_pos_hasSum_le {ι : Type*} {s : Set ι} (hs : s.Countable) {ε : ℝ}
(hε : 0 < ε) : ∃ ε' : ι → ℝ, (∀ i, 0 < ε' i) ∧ ∃ c, HasSum (fun i : s ↦ ε' i) c ∧ c ≤ ε := by
haveI := hs.toEncodable
rcases posSumOfEncodable hε s with ⟨f, hf0, ⟨c, hfc, hcε⟩⟩
refine ⟨fun i ↦ if h : i ∈ s then f ⟨i, h⟩ else 1, fun i ↦ ?_, ⟨c, ?_, hcε⟩⟩
· conv_rhs => simp
split_ifs
exacts [hf0 _, zero_lt_one]
· simpa only [Subtype.coe_prop, dif_pos, Subtype.coe_eta]
#align set.countable.exists_pos_has_sum_le Set.Countable.exists_pos_hasSum_le
theorem Set.Countable.exists_pos_forall_sum_le {ι : Type*} {s : Set ι} (hs : s.Countable) {ε : ℝ}
(hε : 0 < ε) : ∃ ε' : ι → ℝ,
(∀ i, 0 < ε' i) ∧ ∀ t : Finset ι, ↑t ⊆ s → ∑ i ∈ t, ε' i ≤ ε := by
rcases hs.exists_pos_hasSum_le hε with ⟨ε', hpos, c, hε'c, hcε⟩
refine ⟨ε', hpos, fun t ht ↦ ?_⟩
rw [← sum_subtype_of_mem _ ht]
refine (sum_le_hasSum _ ?_ hε'c).trans hcε
exact fun _ _ ↦ (hpos _).le
#align set.countable.exists_pos_forall_sum_le Set.Countable.exists_pos_forall_sum_le
namespace NNReal
theorem exists_pos_sum_of_countable {ε : ℝ≥0} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0, (∀ i, 0 < ε' i) ∧ ∃ c, HasSum ε' c ∧ c < ε := by
cases nonempty_encodable ι
obtain ⟨a, a0, aε⟩ := exists_between (pos_iff_ne_zero.2 hε)
obtain ⟨ε', hε', c, hc, hcε⟩ := posSumOfEncodable a0 ι
exact
⟨fun i ↦ ⟨ε' i, (hε' i).le⟩, fun i ↦ NNReal.coe_lt_coe.1 <| hε' i,
⟨c, hasSum_le (fun i ↦ (hε' i).le) hasSum_zero hc⟩, NNReal.hasSum_coe.1 hc,
aε.trans_le' <| NNReal.coe_le_coe.1 hcε⟩
#align nnreal.exists_pos_sum_of_countable NNReal.exists_pos_sum_of_countable
end NNReal
namespace ENNReal
theorem exists_pos_sum_of_countable {ε : ℝ≥0∞} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0, (∀ i, 0 < ε' i) ∧ (∑' i, (ε' i : ℝ≥0∞)) < ε := by
rcases exists_between (pos_iff_ne_zero.2 hε) with ⟨r, h0r, hrε⟩
rcases lt_iff_exists_coe.1 hrε with ⟨x, rfl, _⟩
rcases NNReal.exists_pos_sum_of_countable (coe_pos.1 h0r).ne' ι with ⟨ε', hp, c, hc, hcr⟩
exact ⟨ε', hp, (ENNReal.tsum_coe_eq hc).symm ▸ lt_trans (coe_lt_coe.2 hcr) hrε⟩
#align ennreal.exists_pos_sum_of_countable ENNReal.exists_pos_sum_of_countable
theorem exists_pos_sum_of_countable' {ε : ℝ≥0∞} (hε : ε ≠ 0) (ι) [Countable ι] :
∃ ε' : ι → ℝ≥0∞, (∀ i, 0 < ε' i) ∧ ∑' i, ε' i < ε :=
let ⟨δ, δpos, hδ⟩ := exists_pos_sum_of_countable hε ι
⟨fun i ↦ δ i, fun i ↦ ENNReal.coe_pos.2 (δpos i), hδ⟩
#align ennreal.exists_pos_sum_of_countable' ENNReal.exists_pos_sum_of_countable'
| Mathlib/Analysis/SpecificLimits/Basic.lean | 604 | 613 | theorem exists_pos_tsum_mul_lt_of_countable {ε : ℝ≥0∞} (hε : ε ≠ 0) {ι} [Countable ι] (w : ι → ℝ≥0∞)
(hw : ∀ i, w i ≠ ∞) : ∃ δ : ι → ℝ≥0, (∀ i, 0 < δ i) ∧ (∑' i, (w i * δ i : ℝ≥0∞)) < ε := by |
lift w to ι → ℝ≥0 using hw
rcases exists_pos_sum_of_countable hε ι with ⟨δ', Hpos, Hsum⟩
have : ∀ i, 0 < max 1 (w i) := fun i ↦ zero_lt_one.trans_le (le_max_left _ _)
refine ⟨fun i ↦ δ' i / max 1 (w i), fun i ↦ div_pos (Hpos _) (this i), ?_⟩
refine lt_of_le_of_lt (ENNReal.tsum_le_tsum fun i ↦ ?_) Hsum
rw [coe_div (this i).ne']
refine mul_le_of_le_div' (mul_le_mul_left' (ENNReal.inv_le_inv.2 ?_) _)
exact coe_le_coe.2 (le_max_right _ _)
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Finsupp.Encodable
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Span
import Mathlib.Data.Set.Countable
#align_import linear_algebra.finsupp from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Properties of the module `α →₀ M`
Given an `R`-module `M`, the `R`-module structure on `α →₀ M` is defined in
`Data.Finsupp.Basic`.
In this file we define `Finsupp.supported s` to be the set `{f : α →₀ M | f.support ⊆ s}`
interpreted as a submodule of `α →₀ M`. We also define `LinearMap` versions of various maps:
* `Finsupp.lsingle a : M →ₗ[R] ι →₀ M`: `Finsupp.single a` as a linear map;
* `Finsupp.lapply a : (ι →₀ M) →ₗ[R] M`: the map `fun f ↦ f a` as a linear map;
* `Finsupp.lsubtypeDomain (s : Set α) : (α →₀ M) →ₗ[R] (s →₀ M)`: restriction to a subtype as a
linear map;
* `Finsupp.restrictDom`: `Finsupp.filter` as a linear map to `Finsupp.supported s`;
* `Finsupp.lsum`: `Finsupp.sum` or `Finsupp.liftAddHom` as a `LinearMap`;
* `Finsupp.total α M R (v : ι → M)`: sends `l : ι → R` to the linear combination of `v i` with
coefficients `l i`;
* `Finsupp.totalOn`: a restricted version of `Finsupp.total` with domain `Finsupp.supported R R s`
and codomain `Submodule.span R (v '' s)`;
* `Finsupp.supportedEquivFinsupp`: a linear equivalence between the functions `α →₀ M` supported
on `s` and the functions `s →₀ M`;
* `Finsupp.lmapDomain`: a linear map version of `Finsupp.mapDomain`;
* `Finsupp.domLCongr`: a `LinearEquiv` version of `Finsupp.domCongr`;
* `Finsupp.congr`: if the sets `s` and `t` are equivalent, then `supported M R s` is equivalent to
`supported M R t`;
* `Finsupp.lcongr`: a `LinearEquiv`alence between `α →₀ M` and `β →₀ N` constructed using
`e : α ≃ β` and `e' : M ≃ₗ[R] N`.
## Tags
function with finite support, module, linear algebra
-/
noncomputable section
open Set LinearMap Submodule
namespace Finsupp
section SMul
variable {α : Type*} {β : Type*} {R : Type*} {M : Type*} {M₂ : Type*}
theorem smul_sum [Zero β] [AddCommMonoid M] [DistribSMul R M] {v : α →₀ β} {c : R} {h : α → β → M} :
c • v.sum h = v.sum fun a b => c • h a b :=
Finset.smul_sum
#align finsupp.smul_sum Finsupp.smul_sum
@[simp]
theorem sum_smul_index_linearMap' [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂]
[Module R M₂] {v : α →₀ M} {c : R} {h : α → M →ₗ[R] M₂} :
((c • v).sum fun a => h a) = c • v.sum fun a => h a := by
rw [Finsupp.sum_smul_index', Finsupp.smul_sum]
· simp only [map_smul]
· intro i
exact (h i).map_zero
#align finsupp.sum_smul_index_linear_map' Finsupp.sum_smul_index_linearMap'
end SMul
section LinearEquivFunOnFinite
variable (R : Type*) {S : Type*} (M : Type*) (α : Type*)
variable [Finite α] [AddCommMonoid M] [Semiring R] [Module R M]
/-- Given `Finite α`, `linearEquivFunOnFinite R` is the natural `R`-linear equivalence between
`α →₀ β` and `α → β`. -/
@[simps apply]
noncomputable def linearEquivFunOnFinite : (α →₀ M) ≃ₗ[R] α → M :=
{ equivFunOnFinite with
toFun := (⇑)
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv_fun_on_finite Finsupp.linearEquivFunOnFinite
@[simp]
theorem linearEquivFunOnFinite_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α) (single x m) = Pi.single x m :=
equivFunOnFinite_single x m
#align finsupp.linear_equiv_fun_on_finite_single Finsupp.linearEquivFunOnFinite_single
@[simp]
theorem linearEquivFunOnFinite_symm_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α).symm (Pi.single x m) = single x m :=
equivFunOnFinite_symm_single x m
#align finsupp.linear_equiv_fun_on_finite_symm_single Finsupp.linearEquivFunOnFinite_symm_single
@[simp]
theorem linearEquivFunOnFinite_symm_coe (f : α →₀ M) : (linearEquivFunOnFinite R M α).symm f = f :=
(linearEquivFunOnFinite R M α).symm_apply_apply f
#align finsupp.linear_equiv_fun_on_finite_symm_coe Finsupp.linearEquivFunOnFinite_symm_coe
end LinearEquivFunOnFinite
section LinearEquiv.finsuppUnique
variable (R : Type*) {S : Type*} (M : Type*)
variable [AddCommMonoid M] [Semiring R] [Module R M]
variable (α : Type*) [Unique α]
/-- If `α` has a unique term, then the type of finitely supported functions `α →₀ M` is
`R`-linearly equivalent to `M`. -/
noncomputable def LinearEquiv.finsuppUnique : (α →₀ M) ≃ₗ[R] M :=
{ Finsupp.equivFunOnFinite.trans (Equiv.funUnique α M) with
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv.finsupp_unique Finsupp.LinearEquiv.finsuppUnique
variable {R M}
@[simp]
theorem LinearEquiv.finsuppUnique_apply (f : α →₀ M) :
LinearEquiv.finsuppUnique R M α f = f default :=
rfl
#align finsupp.linear_equiv.finsupp_unique_apply Finsupp.LinearEquiv.finsuppUnique_apply
variable {α}
@[simp]
theorem LinearEquiv.finsuppUnique_symm_apply [Unique α] (m : M) :
(LinearEquiv.finsuppUnique R M α).symm m = Finsupp.single default m := by
ext; simp [LinearEquiv.finsuppUnique, Equiv.funUnique, single, Pi.single,
equivFunOnFinite, Function.update]
#align finsupp.linear_equiv.finsupp_unique_symm_apply Finsupp.LinearEquiv.finsuppUnique_symm_apply
end LinearEquiv.finsuppUnique
variable {α : Type*} {M : Type*} {N : Type*} {P : Type*} {R : Type*} {S : Type*}
variable [Semiring R] [Semiring S] [AddCommMonoid M] [Module R M]
variable [AddCommMonoid N] [Module R N]
variable [AddCommMonoid P] [Module R P]
/-- Interpret `Finsupp.single a` as a linear map. -/
def lsingle (a : α) : M →ₗ[R] α →₀ M :=
{ Finsupp.singleAddHom a with map_smul' := fun _ _ => (smul_single _ _ _).symm }
#align finsupp.lsingle Finsupp.lsingle
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a b, φ (single a b) = ψ (single a b)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align finsupp.lhom_ext Finsupp.lhom_ext
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere.
We formulate this fact using equality of linear maps `φ.comp (lsingle a)` and `ψ.comp (lsingle a)`
so that the `ext` tactic can apply a type-specific extensionality lemma to prove equality of these
maps. E.g., if `M = R`, then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
-- Porting note: The priority should be higher than `LinearMap.ext`.
@[ext high]
theorem lhom_ext' ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a, φ.comp (lsingle a) = ψ.comp (lsingle a)) :
φ = ψ :=
lhom_ext fun a => LinearMap.congr_fun (h a)
#align finsupp.lhom_ext' Finsupp.lhom_ext'
/-- Interpret `fun f : α →₀ M ↦ f a` as a linear map. -/
def lapply (a : α) : (α →₀ M) →ₗ[R] M :=
{ Finsupp.applyAddHom a with map_smul' := fun _ _ => rfl }
#align finsupp.lapply Finsupp.lapply
section CompatibleSMul
variable (R S M N ι : Type*)
variable [Semiring S] [AddCommMonoid M] [AddCommMonoid N] [Module S M] [Module S N]
instance _root_.LinearMap.CompatibleSMul.finsupp_dom [SMulZeroClass R M] [DistribSMul R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul (ι →₀ M) N R S where
map_smul f r m := by
conv_rhs => rw [← sum_single m, map_finsupp_sum, smul_sum]
erw [← sum_single (r • m), sum_mapRange_index single_zero, map_finsupp_sum]
congr; ext i m; exact (f.comp <| lsingle i).map_smul_of_tower r m
instance _root_.LinearMap.CompatibleSMul.finsupp_cod [SMul R M] [SMulZeroClass R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul M (ι →₀ N) R S where
map_smul f r m := by ext i; apply ((lapply i).comp f).map_smul_of_tower
end CompatibleSMul
/-- Forget that a function is finitely supported.
This is the linear version of `Finsupp.toFun`. -/
@[simps]
def lcoeFun : (α →₀ M) →ₗ[R] α → M where
toFun := (⇑)
map_add' x y := by
ext
simp
map_smul' x y := by
ext
simp
#align finsupp.lcoe_fun Finsupp.lcoeFun
section LSubtypeDomain
variable (s : Set α)
/-- Interpret `Finsupp.subtypeDomain s` as a linear map. -/
def lsubtypeDomain : (α →₀ M) →ₗ[R] s →₀ M where
toFun := subtypeDomain fun x => x ∈ s
map_add' _ _ := subtypeDomain_add
map_smul' _ _ := ext fun _ => rfl
#align finsupp.lsubtype_domain Finsupp.lsubtypeDomain
theorem lsubtypeDomain_apply (f : α →₀ M) :
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M) f = subtypeDomain (fun x => x ∈ s) f :=
rfl
#align finsupp.lsubtype_domain_apply Finsupp.lsubtypeDomain_apply
end LSubtypeDomain
@[simp]
theorem lsingle_apply (a : α) (b : M) : (lsingle a : M →ₗ[R] α →₀ M) b = single a b :=
rfl
#align finsupp.lsingle_apply Finsupp.lsingle_apply
@[simp]
theorem lapply_apply (a : α) (f : α →₀ M) : (lapply a : (α →₀ M) →ₗ[R] M) f = f a :=
rfl
#align finsupp.lapply_apply Finsupp.lapply_apply
@[simp]
theorem lapply_comp_lsingle_same (a : α) : lapply a ∘ₗ lsingle a = (.id : M →ₗ[R] M) := by ext; simp
@[simp]
| Mathlib/LinearAlgebra/Finsupp.lean | 237 | 238 | theorem lapply_comp_lsingle_of_ne (a a' : α) (h : a ≠ a') :
lapply a ∘ₗ lsingle a' = (0 : M →ₗ[R] M) := by | ext; simp [h.symm]
|
/-
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.Map
#align_import linear_algebra.basic from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Kernel of a linear map
This file defines the kernel of a linear map.
## Main definitions
* `LinearMap.ker`: the kernel of a linear map as a submodule of the domain
## Notations
* We continue to use the notations `M →ₛₗ[σ] M₂` and `M →ₗ[R] M₂` for the type of semilinear
(resp. linear) maps from `M` to `M₂` over the ring homomorphism `σ` (resp. over the ring `R`).
## Tags
linear algebra, vector space, module
-/
open Function
open Pointwise
variable {R : Type*} {R₁ : Type*} {R₂ : Type*} {R₃ : Type*}
variable {K : Type*}
variable {M : Type*} {M₁ : Type*} {M₂ : Type*} {M₃ : Type*}
variable {V : Type*} {V₂ : Type*}
/-! ### Properties of linear maps -/
namespace LinearMap
section AddCommMonoid
variable [Semiring R] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃}
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable [Module R M] [Module R₂ M₂] [Module R₃ M₃]
open Submodule
variable {σ₂₁ : R₂ →+* R} {τ₁₂ : R →+* R₂} {τ₂₃ : R₂ →+* R₃} {τ₁₃ : R →+* R₃}
variable [RingHomCompTriple τ₁₂ τ₂₃ τ₁₃]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F τ₁₂ M M₂]
/-- The kernel of a linear map `f : M → M₂` is defined to be `comap f ⊥`. This is equivalent to the
set of `x : M` such that `f x = 0`. The kernel is a submodule of `M`. -/
def ker (f : F) : Submodule R M :=
comap f ⊥
#align linear_map.ker LinearMap.ker
@[simp]
theorem mem_ker {f : F} {y} : y ∈ ker f ↔ f y = 0 :=
mem_bot R₂
#align linear_map.mem_ker LinearMap.mem_ker
@[simp]
theorem ker_id : ker (LinearMap.id : M →ₗ[R] M) = ⊥ :=
rfl
#align linear_map.ker_id LinearMap.ker_id
@[simp]
theorem map_coe_ker (f : F) (x : ker f) : f x = 0 :=
mem_ker.1 x.2
#align linear_map.map_coe_ker LinearMap.map_coe_ker
theorem ker_toAddSubmonoid (f : M →ₛₗ[τ₁₂] M₂) : f.ker.toAddSubmonoid = (AddMonoidHom.mker f) :=
rfl
#align linear_map.ker_to_add_submonoid LinearMap.ker_toAddSubmonoid
theorem comp_ker_subtype (f : M →ₛₗ[τ₁₂] M₂) : f.comp f.ker.subtype = 0 :=
LinearMap.ext fun x => mem_ker.1 x.2
#align linear_map.comp_ker_subtype LinearMap.comp_ker_subtype
theorem ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker (g.comp f : M →ₛₗ[τ₁₃] M₃) = comap f (ker g) :=
rfl
#align linear_map.ker_comp LinearMap.ker_comp
theorem ker_le_ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker f ≤ ker (g.comp f : M →ₛₗ[τ₁₃] M₃) := by rw [ker_comp]; exact comap_mono bot_le
#align linear_map.ker_le_ker_comp LinearMap.ker_le_ker_comp
theorem ker_sup_ker_le_ker_comp_of_commute {f g : M →ₗ[R] M} (h : Commute f g) :
ker f ⊔ ker g ≤ ker (f ∘ₗ g) := by
refine sup_le_iff.mpr ⟨?_, ker_le_ker_comp g f⟩
rw [← mul_eq_comp, h.eq, mul_eq_comp]
exact ker_le_ker_comp f g
@[simp]
theorem ker_le_comap {p : Submodule R₂ M₂} (f : M →ₛₗ[τ₁₂] M₂) :
ker f ≤ p.comap f :=
fun x hx ↦ by simp [mem_ker.mp hx]
theorem disjoint_ker {f : F} {p : Submodule R M} :
Disjoint p (ker f) ↔ ∀ x ∈ p, f x = 0 → x = 0 := by
simp [disjoint_def]
#align linear_map.disjoint_ker LinearMap.disjoint_ker
theorem ker_eq_bot' {f : F} : ker f = ⊥ ↔ ∀ m, f m = 0 → m = 0 := by
simpa [disjoint_iff_inf_le] using disjoint_ker (f := f) (p := ⊤)
#align linear_map.ker_eq_bot' LinearMap.ker_eq_bot'
theorem ker_eq_bot_of_inverse {τ₂₁ : R₂ →+* R} [RingHomInvPair τ₁₂ τ₂₁] {f : M →ₛₗ[τ₁₂] M₂}
{g : M₂ →ₛₗ[τ₂₁] M} (h : (g.comp f : M →ₗ[R] M) = id) : ker f = ⊥ :=
ker_eq_bot'.2 fun m hm => by rw [← id_apply (R := R) m, ← h, comp_apply, hm, g.map_zero]
#align linear_map.ker_eq_bot_of_inverse LinearMap.ker_eq_bot_of_inverse
theorem le_ker_iff_map [RingHomSurjective τ₁₂] {f : F} {p : Submodule R M} :
p ≤ ker f ↔ map f p = ⊥ := by rw [ker, eq_bot_iff, map_le_iff_le_comap]
#align linear_map.le_ker_iff_map LinearMap.le_ker_iff_map
| Mathlib/Algebra/Module/Submodule/Ker.lean | 125 | 126 | theorem ker_codRestrict {τ₂₁ : R₂ →+* R} (p : Submodule R M) (f : M₂ →ₛₗ[τ₂₁] M) (hf) :
ker (codRestrict p f hf) = ker f := by | rw [ker, comap_codRestrict, Submodule.map_bot]; rfl
|
/-
Copyright (c) 2019 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Isabel Longbottom, Scott Morrison, Apurva Nakade
-/
import Mathlib.Algebra.Ring.Int
import Mathlib.SetTheory.Game.PGame
import Mathlib.Tactic.Abel
#align_import set_theory.game.basic from "leanprover-community/mathlib"@"8900d545017cd21961daa2a1734bb658ef52c618"
/-!
# Combinatorial games.
In this file we construct an instance `OrderedAddCommGroup SetTheory.Game`.
## Multiplication on pre-games
We define the operations of multiplication and inverse on pre-games, and prove a few basic theorems
about them. Multiplication is not well-behaved under equivalence of pre-games i.e. `x ≈ y` does not
imply `x * z ≈ y * z`. Hence, multiplication is not a well-defined operation on games. Nevertheless,
the abelian group structure on games allows us to simplify many proofs for pre-games.
-/
-- Porting note: many definitions here are noncomputable as the compiler does not support PGame.rec
noncomputable section
namespace SetTheory
open Function PGame
open PGame
universe u
-- Porting note: moved the setoid instance to PGame.lean
/-- The type of combinatorial games. In ZFC, a combinatorial game is constructed from
two sets of combinatorial games that have been constructed at an earlier
stage. To do this in type theory, we say that a combinatorial pre-game is built
inductively from two families of combinatorial games indexed over any type
in Type u. The resulting type `PGame.{u}` lives in `Type (u+1)`,
reflecting that it is a proper class in ZFC.
A combinatorial game is then constructed by quotienting by the equivalence
`x ≈ y ↔ x ≤ y ∧ y ≤ x`. -/
abbrev Game :=
Quotient PGame.setoid
#align game SetTheory.Game
namespace Game
-- Porting note (#11445): added this definition
/-- Negation of games. -/
instance : Neg Game where
neg := Quot.map Neg.neg <| fun _ _ => (neg_equiv_neg_iff).2
instance : Zero Game where zero := ⟦0⟧
instance : Add Game where
add := Quotient.map₂ HAdd.hAdd <| fun _ _ hx _ _ hy => PGame.add_congr hx hy
instance instAddCommGroupWithOneGame : AddCommGroupWithOne Game where
zero := ⟦0⟧
one := ⟦1⟧
add_zero := by
rintro ⟨x⟩
exact Quot.sound (add_zero_equiv x)
zero_add := by
rintro ⟨x⟩
exact Quot.sound (zero_add_equiv x)
add_assoc := by
rintro ⟨x⟩ ⟨y⟩ ⟨z⟩
exact Quot.sound add_assoc_equiv
add_left_neg := Quotient.ind <| fun x => Quot.sound (add_left_neg_equiv x)
add_comm := by
rintro ⟨x⟩ ⟨y⟩
exact Quot.sound add_comm_equiv
nsmul := nsmulRec
zsmul := zsmulRec
instance : Inhabited Game :=
⟨0⟩
instance instPartialOrderGame : PartialOrder Game where
le := Quotient.lift₂ (· ≤ ·) fun x₁ y₁ x₂ y₂ hx hy => propext (le_congr hx hy)
le_refl := by
rintro ⟨x⟩
exact le_refl x
le_trans := by
rintro ⟨x⟩ ⟨y⟩ ⟨z⟩
exact @le_trans _ _ x y z
le_antisymm := by
rintro ⟨x⟩ ⟨y⟩ h₁ h₂
apply Quot.sound
exact ⟨h₁, h₂⟩
lt := Quotient.lift₂ (· < ·) fun x₁ y₁ x₂ y₂ hx hy => propext (lt_congr hx hy)
lt_iff_le_not_le := by
rintro ⟨x⟩ ⟨y⟩
exact @lt_iff_le_not_le _ _ x y
/-- The less or fuzzy relation on games.
If `0 ⧏ x` (less or fuzzy with), then Left can win `x` as the first player. -/
def LF : Game → Game → Prop :=
Quotient.lift₂ PGame.LF fun _ _ _ _ hx hy => propext (lf_congr hx hy)
#align game.lf SetTheory.Game.LF
local infixl:50 " ⧏ " => LF
/-- On `Game`, simp-normal inequalities should use as few negations as possible. -/
@[simp]
| Mathlib/SetTheory/Game/Basic.lean | 111 | 113 | theorem not_le : ∀ {x y : Game}, ¬x ≤ y ↔ y ⧏ x := by |
rintro ⟨x⟩ ⟨y⟩
exact PGame.not_le
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Antoine Chambert-Loir
-/
import Mathlib.Algebra.DirectSum.Finsupp
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.DirectSum.TensorProduct
#align_import linear_algebra.direct_sum.finsupp from "leanprover-community/mathlib"@"9b9d125b7be0930f564a68f1d73ace10cf46064d"
/-!
# Results on finitely supported functions.
* `TensorProduct.finsuppLeft`, the tensor product of `ι →₀ M` and `N`
is linearly equivalent to `ι →₀ M ⊗[R] N`
* `TensorProduct.finsuppScalarLeft`, the tensor product of `ι →₀ R` and `N`
is linearly equivalent to `ι →₀ N`
* `TensorProduct.finsuppRight`, the tensor product of `M` and `ι →₀ N`
is linearly equivalent to `ι →₀ M ⊗[R] N`
* `TensorProduct.finsuppScalarRight`, the tensor product of `M` and `ι →₀ R`
is linearly equivalent to `ι →₀ N`
* `TensorProduct.finsuppLeft'`, if `M` is an `S`-module,
then the tensor product of `ι →₀ M` and `N` is `S`-linearly equivalent
to `ι →₀ M ⊗[R] N`
* `finsuppTensorFinsupp`, the tensor product of `ι →₀ M` and `κ →₀ N`
is linearly equivalent to `(ι × κ) →₀ (M ⊗ N)`.
## Case of MvPolynomial
These functions apply to `MvPolynomial`, one can define
```
noncomputable def MvPolynomial.rTensor' :
MvPolynomial σ S ⊗[R] N ≃ₗ[S] (σ →₀ ℕ) →₀ (S ⊗[R] N) :=
TensorProduct.finsuppLeft'
noncomputable def MvPolynomial.rTensor :
MvPolynomial σ R ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ N :=
TensorProduct.finsuppScalarLeft
```
However, to be actually usable, these definitions need lemmas to be given in companion PR.
## Case of `Polynomial`
`Polynomial` is a structure containing a `Finsupp`, so these functions
can't be applied directly to `Polynomial`.
Some linear equivs need to be added to mathlib for that.
This belongs to a companion PR.
## TODO
* generalize to `MonoidAlgebra`, `AlgHom `
* reprove `TensorProduct.finsuppLeft'` using existing heterobasic version of `TensorProduct.congr`
-/
noncomputable section
open DirectSum TensorProduct
open Set LinearMap Submodule
section TensorProduct
variable (R : Type*) [CommSemiring R]
(M : Type*) [AddCommMonoid M] [Module R M]
(N : Type*) [AddCommMonoid N] [Module R N]
namespace TensorProduct
variable (ι : Type*) [DecidableEq ι]
/-- The tensor product of `ι →₀ M` and `N` is linearly equivalent to `ι →₀ M ⊗[R] N` -/
noncomputable def finsuppLeft :
(ι →₀ M) ⊗[R] N ≃ₗ[R] ι →₀ M ⊗[R] N :=
congr (finsuppLEquivDirectSum R M ι) (.refl R N) ≪≫ₗ
directSumLeft R (fun _ ↦ M) N ≪≫ₗ (finsuppLEquivDirectSum R _ ι).symm
variable {R M N ι}
lemma finsuppLeft_apply_tmul (p : ι →₀ M) (n : N) :
finsuppLeft R M N ι (p ⊗ₜ[R] n) = p.sum fun i m ↦ Finsupp.single i (m ⊗ₜ[R] n) := by
apply p.induction_linear
· simp
· intros f g hf hg; simp [add_tmul, map_add, hf, hg, Finsupp.sum_add_index]
· simp [finsuppLeft]
@[simp]
lemma finsuppLeft_apply_tmul_apply (p : ι →₀ M) (n : N) (i : ι) :
finsuppLeft R M N ι (p ⊗ₜ[R] n) i = p i ⊗ₜ[R] n := by
rw [finsuppLeft_apply_tmul, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
theorem finsuppLeft_apply (t : (ι →₀ M) ⊗[R] N) (i : ι) :
finsuppLeft R M N ι t i = rTensor N (Finsupp.lapply i) t := by
induction t using TensorProduct.induction_on with
| zero => simp
| tmul f n => simp only [finsuppLeft_apply_tmul_apply, rTensor_tmul, Finsupp.lapply_apply]
| add x y hx hy => simp [map_add, hx, hy]
@[simp]
lemma finsuppLeft_symm_apply_single (i : ι) (m : M) (n : N) :
(finsuppLeft R M N ι).symm (Finsupp.single i (m ⊗ₜ[R] n)) =
Finsupp.single i m ⊗ₜ[R] n := by
simp [finsuppLeft, Finsupp.lsum]
variable (R M N ι)
/-- The tensor product of `M` and `ι →₀ N` is linearly equivalent to `ι →₀ M ⊗[R] N` -/
noncomputable def finsuppRight :
M ⊗[R] (ι →₀ N) ≃ₗ[R] ι →₀ M ⊗[R] N :=
congr (.refl R M) (finsuppLEquivDirectSum R N ι) ≪≫ₗ
directSumRight R M (fun _ : ι ↦ N) ≪≫ₗ (finsuppLEquivDirectSum R _ ι).symm
variable {R M N ι}
lemma finsuppRight_apply_tmul (m : M) (p : ι →₀ N) :
finsuppRight R M N ι (m ⊗ₜ[R] p) = p.sum fun i n ↦ Finsupp.single i (m ⊗ₜ[R] n) := by
apply p.induction_linear
· simp
· intros f g hf hg; simp [tmul_add, map_add, hf, hg, Finsupp.sum_add_index]
· simp [finsuppRight]
@[simp]
lemma finsuppRight_apply_tmul_apply (m : M) (p : ι →₀ N) (i : ι) :
finsuppRight R M N ι (m ⊗ₜ[R] p) i = m ⊗ₜ[R] p i := by
rw [finsuppRight_apply_tmul, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
theorem finsuppRight_apply (t : M ⊗[R] (ι →₀ N)) (i : ι) :
finsuppRight R M N ι t i = lTensor M (Finsupp.lapply i) t := by
induction t using TensorProduct.induction_on with
| zero => simp
| tmul m f => simp [finsuppRight_apply_tmul_apply]
| add x y hx hy => simp [map_add, hx, hy]
@[simp]
lemma finsuppRight_symm_apply_single (i : ι) (m : M) (n : N) :
(finsuppRight R M N ι).symm (Finsupp.single i (m ⊗ₜ[R] n)) =
m ⊗ₜ[R] Finsupp.single i n := by
simp [finsuppRight, Finsupp.lsum]
variable {S : Type*} [CommSemiring S] [Algebra R S]
[Module S M] [IsScalarTower R S M]
lemma finsuppLeft_smul' (s : S) (t : (ι →₀ M) ⊗[R] N) :
finsuppLeft R M N ι (s • t) = s • finsuppLeft R M N ι t := by
induction t using TensorProduct.induction_on with
| zero => simp
| add x y hx hy => simp [hx, hy]
| tmul p n => ext; simp [smul_tmul', finsuppLeft_apply_tmul_apply]
variable (R M N ι S)
/-- When `M` is also an `S`-module, then `TensorProduct.finsuppLeft R M N``
is an `S`-linear equiv -/
noncomputable def finsuppLeft' :
(ι →₀ M) ⊗[R] N ≃ₗ[S] ι →₀ M ⊗[R] N where
__ := finsuppLeft R M N ι
map_smul' := finsuppLeft_smul'
variable {R M N ι S}
lemma finsuppLeft'_apply (x : (ι →₀ M) ⊗[R] N) :
finsuppLeft' R M N ι S x = finsuppLeft R M N ι x := rfl
/- -- TODO : reprove using the existing heterobasic lemmas
noncomputable example :
(ι →₀ M) ⊗[R] N ≃ₗ[S] ι →₀ (M ⊗[R] N) := by
have f : (⨁ (i₁ : ι), M) ⊗[R] N ≃ₗ[S] ⨁ (i : ι), M ⊗[R] N := sorry
exact (AlgebraTensorModule.congr
(finsuppLEquivDirectSum S M ι) (.refl R N)).trans
(f.trans (finsuppLEquivDirectSum S (M ⊗[R] N) ι).symm) -/
variable (R M N ι)
/-- The tensor product of `ι →₀ R` and `N` is linearly equivalent to `ι →₀ N` -/
noncomputable def finsuppScalarLeft :
(ι →₀ R) ⊗[R] N ≃ₗ[R] ι →₀ N :=
finsuppLeft R R N ι ≪≫ₗ (Finsupp.mapRange.linearEquiv (TensorProduct.lid R N))
variable {R M N ι}
@[simp]
lemma finsuppScalarLeft_apply_tmul_apply (p : ι →₀ R) (n : N) (i : ι) :
finsuppScalarLeft R N ι (p ⊗ₜ[R] n) i = p i • n := by
simp [finsuppScalarLeft]
lemma finsuppScalarLeft_apply_tmul (p : ι →₀ R) (n : N) :
finsuppScalarLeft R N ι (p ⊗ₜ[R] n) = p.sum fun i m ↦ Finsupp.single i (m • n) := by
ext i
rw [finsuppScalarLeft_apply_tmul_apply, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
lemma finsuppScalarLeft_apply (pn : (ι →₀ R) ⊗[R] N) (i : ι) :
finsuppScalarLeft R N ι pn i = TensorProduct.lid R N ((Finsupp.lapply i).rTensor N pn) := by
simp [finsuppScalarLeft, finsuppLeft_apply]
@[simp]
lemma finsuppScalarLeft_symm_apply_single (i : ι) (n : N) :
(finsuppScalarLeft R N ι).symm (Finsupp.single i n) =
(Finsupp.single i 1) ⊗ₜ[R] n := by
simp [finsuppScalarLeft, finsuppLeft_symm_apply_single]
variable (R M N ι)
/-- The tensor product of `M` and `ι →₀ R` is linearly equivalent to `ι →₀ N` -/
noncomputable def finsuppScalarRight :
M ⊗[R] (ι →₀ R) ≃ₗ[R] ι →₀ M :=
finsuppRight R M R ι ≪≫ₗ Finsupp.mapRange.linearEquiv (TensorProduct.rid R M)
variable {R M N ι}
@[simp]
lemma finsuppScalarRight_apply_tmul_apply (m : M) (p : ι →₀ R) (i : ι) :
finsuppScalarRight R M ι (m ⊗ₜ[R] p) i = p i • m := by
simp [finsuppScalarRight]
lemma finsuppScalarRight_apply_tmul (m : M) (p : ι →₀ R) :
finsuppScalarRight R M ι (m ⊗ₜ[R] p) = p.sum fun i n ↦ Finsupp.single i (n • m) := by
ext i
rw [finsuppScalarRight_apply_tmul_apply, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
lemma finsuppScalarRight_apply (t : M ⊗[R] (ι →₀ R)) (i : ι) :
finsuppScalarRight R M ι t i = TensorProduct.rid R M ((Finsupp.lapply i).lTensor M t) := by
simp [finsuppScalarRight, finsuppRight_apply]
@[simp]
lemma finsuppScalarRight_symm_apply_single (i : ι) (m : M) :
(finsuppScalarRight R M ι).symm (Finsupp.single i m) =
m ⊗ₜ[R] (Finsupp.single i 1) := by
simp [finsuppScalarRight, finsuppRight_symm_apply_single]
end TensorProduct
end TensorProduct
variable (R S M N ι κ : Type*)
[CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid N] [Module R N]
[Semiring S] [Algebra R S] [Module S M] [IsScalarTower R S M]
open scoped Classical in
/-- The tensor product of `ι →₀ M` and `κ →₀ N` is linearly equivalent to `(ι × κ) →₀ (M ⊗ N)`. -/
def finsuppTensorFinsupp : (ι →₀ M) ⊗[R] (κ →₀ N) ≃ₗ[S] ι × κ →₀ M ⊗[R] N :=
TensorProduct.AlgebraTensorModule.congr
(finsuppLEquivDirectSum S M ι) (finsuppLEquivDirectSum R N κ) ≪≫ₗ
((TensorProduct.directSum R S (fun _ : ι => M) fun _ : κ => N) ≪≫ₗ
(finsuppLEquivDirectSum S (M ⊗[R] N) (ι × κ)).symm)
#align finsupp_tensor_finsupp finsuppTensorFinsupp
@[simp]
theorem finsuppTensorFinsupp_single (i : ι) (m : M) (k : κ) (n : N) :
finsuppTensorFinsupp R S M N ι κ (Finsupp.single i m ⊗ₜ Finsupp.single k n) =
Finsupp.single (i, k) (m ⊗ₜ n) := by
simp [finsuppTensorFinsupp]
#align finsupp_tensor_finsupp_single finsuppTensorFinsupp_single
@[simp]
theorem finsuppTensorFinsupp_apply (f : ι →₀ M) (g : κ →₀ N) (i : ι) (k : κ) :
finsuppTensorFinsupp R S M N ι κ (f ⊗ₜ g) (i, k) = f i ⊗ₜ g k := by
apply Finsupp.induction_linear f
· simp
· intro f₁ f₂ hf₁ hf₂
simp [add_tmul, hf₁, hf₂]
intro i' m
apply Finsupp.induction_linear g
· simp
· intro g₁ g₂ hg₁ hg₂
simp [tmul_add, hg₁, hg₂]
intro k' n
classical
simp_rw [finsuppTensorFinsupp_single, Finsupp.single_apply, Prod.mk.inj_iff, ite_and]
split_ifs <;> simp
#align finsupp_tensor_finsupp_apply finsuppTensorFinsupp_apply
@[simp]
theorem finsuppTensorFinsupp_symm_single (i : ι × κ) (m : M) (n : N) :
(finsuppTensorFinsupp R S M N ι κ).symm (Finsupp.single i (m ⊗ₜ n)) =
Finsupp.single i.1 m ⊗ₜ Finsupp.single i.2 n :=
Prod.casesOn i fun _ _ =>
(LinearEquiv.symm_apply_eq _).2 (finsuppTensorFinsupp_single _ _ _ _ _ _ _ _ _ _).symm
#align finsupp_tensor_finsupp_symm_single finsuppTensorFinsupp_symm_single
/-- A variant of `finsuppTensorFinsupp` where the first module is the ground ring. -/
def finsuppTensorFinsuppLid : (ι →₀ R) ⊗[R] (κ →₀ N) ≃ₗ[R] ι × κ →₀ N :=
finsuppTensorFinsupp R R R N ι κ ≪≫ₗ Finsupp.lcongr (Equiv.refl _) (TensorProduct.lid R N)
@[simp]
theorem finsuppTensorFinsuppLid_apply_apply (f : ι →₀ R) (g : κ →₀ N) (a : ι) (b : κ) :
finsuppTensorFinsuppLid R N ι κ (f ⊗ₜ[R] g) (a, b) = f a • g b := by
simp [finsuppTensorFinsuppLid]
@[simp]
theorem finsuppTensorFinsuppLid_single_tmul_single (a : ι) (b : κ) (r : R) (n : N) :
finsuppTensorFinsuppLid R N ι κ (Finsupp.single a r ⊗ₜ[R] Finsupp.single b n) =
Finsupp.single (a, b) (r • n) := by
simp [finsuppTensorFinsuppLid]
@[simp]
theorem finsuppTensorFinsuppLid_symm_single_smul (i : ι × κ) (r : R) (n : N) :
(finsuppTensorFinsuppLid R N ι κ).symm (Finsupp.single i (r • n)) =
Finsupp.single i.1 r ⊗ₜ Finsupp.single i.2 n :=
Prod.casesOn i fun _ _ =>
(LinearEquiv.symm_apply_eq _).2 (finsuppTensorFinsuppLid_single_tmul_single ..).symm
/-- A variant of `finsuppTensorFinsupp` where the second module is the ground ring. -/
def finsuppTensorFinsuppRid : (ι →₀ M) ⊗[R] (κ →₀ R) ≃ₗ[R] ι × κ →₀ M :=
finsuppTensorFinsupp R R M R ι κ ≪≫ₗ Finsupp.lcongr (Equiv.refl _) (TensorProduct.rid R M)
@[simp]
theorem finsuppTensorFinsuppRid_apply_apply (f : ι →₀ M) (g : κ →₀ R) (a : ι) (b : κ) :
finsuppTensorFinsuppRid R M ι κ (f ⊗ₜ[R] g) (a, b) = g b • f a := by
simp [finsuppTensorFinsuppRid]
@[simp]
theorem finsuppTensorFinsuppRid_single_tmul_single (a : ι) (b : κ) (m : M) (r : R) :
finsuppTensorFinsuppRid R M ι κ (Finsupp.single a m ⊗ₜ[R] Finsupp.single b r) =
Finsupp.single (a, b) (r • m) := by
simp [finsuppTensorFinsuppRid]
@[simp]
theorem finsuppTensorFinsuppRid_symm_single_smul (i : ι × κ) (m : M) (r : R) :
(finsuppTensorFinsuppRid R M ι κ).symm (Finsupp.single i (r • m)) =
Finsupp.single i.1 m ⊗ₜ Finsupp.single i.2 r :=
Prod.casesOn i fun _ _ =>
(LinearEquiv.symm_apply_eq _).2 (finsuppTensorFinsuppRid_single_tmul_single ..).symm
/-- A variant of `finsuppTensorFinsupp` where both modules are the ground ring. -/
def finsuppTensorFinsupp' : (ι →₀ R) ⊗[R] (κ →₀ R) ≃ₗ[R] ι × κ →₀ R :=
finsuppTensorFinsuppLid R R ι κ
#align finsupp_tensor_finsupp' finsuppTensorFinsupp'
@[simp]
theorem finsuppTensorFinsupp'_apply_apply (f : ι →₀ R) (g : κ →₀ R) (a : ι) (b : κ) :
finsuppTensorFinsupp' R ι κ (f ⊗ₜ[R] g) (a, b) = f a * g b :=
finsuppTensorFinsuppLid_apply_apply R R ι κ f g a b
#align finsupp_tensor_finsupp'_apply_apply finsuppTensorFinsupp'_apply_apply
@[simp]
theorem finsuppTensorFinsupp'_single_tmul_single (a : ι) (b : κ) (r₁ r₂ : R) :
finsuppTensorFinsupp' R ι κ (Finsupp.single a r₁ ⊗ₜ[R] Finsupp.single b r₂) =
Finsupp.single (a, b) (r₁ * r₂) :=
finsuppTensorFinsuppLid_single_tmul_single R R ι κ a b r₁ r₂
#align finsupp_tensor_finsupp'_single_tmul_single finsuppTensorFinsupp'_single_tmul_single
theorem finsuppTensorFinsupp'_symm_single_mul (i : ι × κ) (r₁ r₂ : R) :
(finsuppTensorFinsupp' R ι κ).symm (Finsupp.single i (r₁ * r₂)) =
Finsupp.single i.1 r₁ ⊗ₜ Finsupp.single i.2 r₂ :=
finsuppTensorFinsuppLid_symm_single_smul R R ι κ i r₁ r₂
theorem finsuppTensorFinsupp'_symm_single_eq_single_one_tmul (i : ι × κ) (r : R) :
(finsuppTensorFinsupp' R ι κ).symm (Finsupp.single i r) =
Finsupp.single i.1 1 ⊗ₜ Finsupp.single i.2 r := by
nth_rw 1 [← one_mul r]
exact finsuppTensorFinsupp'_symm_single_mul R ι κ i _ _
| Mathlib/LinearAlgebra/DirectSum/Finsupp.lean | 361 | 365 | theorem finsuppTensorFinsupp'_symm_single_eq_tmul_single_one (i : ι × κ) (r : R) :
(finsuppTensorFinsupp' R ι κ).symm (Finsupp.single i r) =
Finsupp.single i.1 r ⊗ₜ Finsupp.single i.2 1 := by |
nth_rw 1 [← mul_one r]
exact finsuppTensorFinsupp'_symm_single_mul R ι κ i _ _
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Mario Carneiro
-/
import Mathlib.Tactic.FinCases
import Mathlib.Data.Nat.Choose.Sum
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.Algebra.Field.IsField
#align_import ring_theory.ideal.basic from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# Ideals over a ring
This file defines `Ideal R`, the type of (left) ideals over a ring `R`.
Note that over commutative rings, left ideals and two-sided ideals are equivalent.
## Implementation notes
`Ideal R` is implemented using `Submodule R R`, where `•` is interpreted as `*`.
## TODO
Support right ideals, and two-sided ideals over non-commutative rings.
-/
universe u v w
variable {α : Type u} {β : Type v}
open Set Function
open Pointwise
/-- A (left) ideal in a semiring `R` is an additive submonoid `s` such that
`a * b ∈ s` whenever `b ∈ s`. If `R` is a ring, then `s` is an additive subgroup. -/
abbrev Ideal (R : Type u) [Semiring R] :=
Submodule R R
#align ideal Ideal
/-- A ring is a principal ideal ring if all (left) ideals are principal. -/
@[mk_iff]
class IsPrincipalIdealRing (R : Type u) [Semiring R] : Prop where
principal : ∀ S : Ideal R, S.IsPrincipal
#align is_principal_ideal_ring IsPrincipalIdealRing
attribute [instance] IsPrincipalIdealRing.principal
section Semiring
namespace Ideal
variable [Semiring α] (I : Ideal α) {a b : α}
protected theorem zero_mem : (0 : α) ∈ I :=
Submodule.zero_mem I
#align ideal.zero_mem Ideal.zero_mem
protected theorem add_mem : a ∈ I → b ∈ I → a + b ∈ I :=
Submodule.add_mem I
#align ideal.add_mem Ideal.add_mem
variable (a)
theorem mul_mem_left : b ∈ I → a * b ∈ I :=
Submodule.smul_mem I a
#align ideal.mul_mem_left Ideal.mul_mem_left
variable {a}
@[ext]
theorem ext {I J : Ideal α} (h : ∀ x, x ∈ I ↔ x ∈ J) : I = J :=
Submodule.ext h
#align ideal.ext Ideal.ext
theorem sum_mem (I : Ideal α) {ι : Type*} {t : Finset ι} {f : ι → α} :
(∀ c ∈ t, f c ∈ I) → (∑ i ∈ t, f i) ∈ I :=
Submodule.sum_mem I
#align ideal.sum_mem Ideal.sum_mem
theorem eq_top_of_unit_mem (x y : α) (hx : x ∈ I) (h : y * x = 1) : I = ⊤ :=
eq_top_iff.2 fun z _ =>
calc
z = z * (y * x) := by simp [h]
_ = z * y * x := Eq.symm <| mul_assoc z y x
_ ∈ I := I.mul_mem_left _ hx
#align ideal.eq_top_of_unit_mem Ideal.eq_top_of_unit_mem
theorem eq_top_of_isUnit_mem {x} (hx : x ∈ I) (h : IsUnit x) : I = ⊤ :=
let ⟨y, hy⟩ := h.exists_left_inv
eq_top_of_unit_mem I x y hx hy
#align ideal.eq_top_of_is_unit_mem Ideal.eq_top_of_isUnit_mem
theorem eq_top_iff_one : I = ⊤ ↔ (1 : α) ∈ I :=
⟨by rintro rfl; trivial, fun h => eq_top_of_unit_mem _ _ 1 h (by simp)⟩
#align ideal.eq_top_iff_one Ideal.eq_top_iff_one
theorem ne_top_iff_one : I ≠ ⊤ ↔ (1 : α) ∉ I :=
not_congr I.eq_top_iff_one
#align ideal.ne_top_iff_one Ideal.ne_top_iff_one
@[simp]
theorem unit_mul_mem_iff_mem {x y : α} (hy : IsUnit y) : y * x ∈ I ↔ x ∈ I := by
refine ⟨fun h => ?_, fun h => I.mul_mem_left y h⟩
obtain ⟨y', hy'⟩ := hy.exists_left_inv
have := I.mul_mem_left y' h
rwa [← mul_assoc, hy', one_mul] at this
#align ideal.unit_mul_mem_iff_mem Ideal.unit_mul_mem_iff_mem
/-- The ideal generated by a subset of a ring -/
def span (s : Set α) : Ideal α :=
Submodule.span α s
#align ideal.span Ideal.span
@[simp]
theorem submodule_span_eq {s : Set α} : Submodule.span α s = Ideal.span s :=
rfl
#align ideal.submodule_span_eq Ideal.submodule_span_eq
@[simp]
theorem span_empty : span (∅ : Set α) = ⊥ :=
Submodule.span_empty
#align ideal.span_empty Ideal.span_empty
@[simp]
theorem span_univ : span (Set.univ : Set α) = ⊤ :=
Submodule.span_univ
#align ideal.span_univ Ideal.span_univ
theorem span_union (s t : Set α) : span (s ∪ t) = span s ⊔ span t :=
Submodule.span_union _ _
#align ideal.span_union Ideal.span_union
theorem span_iUnion {ι} (s : ι → Set α) : span (⋃ i, s i) = ⨆ i, span (s i) :=
Submodule.span_iUnion _
#align ideal.span_Union Ideal.span_iUnion
theorem mem_span {s : Set α} (x) : x ∈ span s ↔ ∀ p : Ideal α, s ⊆ p → x ∈ p :=
mem_iInter₂
#align ideal.mem_span Ideal.mem_span
theorem subset_span {s : Set α} : s ⊆ span s :=
Submodule.subset_span
#align ideal.subset_span Ideal.subset_span
theorem span_le {s : Set α} {I} : span s ≤ I ↔ s ⊆ I :=
Submodule.span_le
#align ideal.span_le Ideal.span_le
theorem span_mono {s t : Set α} : s ⊆ t → span s ≤ span t :=
Submodule.span_mono
#align ideal.span_mono Ideal.span_mono
@[simp]
theorem span_eq : span (I : Set α) = I :=
Submodule.span_eq _
#align ideal.span_eq Ideal.span_eq
@[simp]
theorem span_singleton_one : span ({1} : Set α) = ⊤ :=
(eq_top_iff_one _).2 <| subset_span <| mem_singleton _
#align ideal.span_singleton_one Ideal.span_singleton_one
theorem isCompactElement_top : CompleteLattice.IsCompactElement (⊤ : Ideal α) := by
simpa only [← span_singleton_one] using Submodule.singleton_span_isCompactElement 1
theorem mem_span_insert {s : Set α} {x y} :
x ∈ span (insert y s) ↔ ∃ a, ∃ z ∈ span s, x = a * y + z :=
Submodule.mem_span_insert
#align ideal.mem_span_insert Ideal.mem_span_insert
theorem mem_span_singleton' {x y : α} : x ∈ span ({y} : Set α) ↔ ∃ a, a * y = x :=
Submodule.mem_span_singleton
#align ideal.mem_span_singleton' Ideal.mem_span_singleton'
theorem span_singleton_le_iff_mem {x : α} : span {x} ≤ I ↔ x ∈ I :=
Submodule.span_singleton_le_iff_mem _ _
#align ideal.span_singleton_le_iff_mem Ideal.span_singleton_le_iff_mem
theorem span_singleton_mul_left_unit {a : α} (h2 : IsUnit a) (x : α) :
span ({a * x} : Set α) = span {x} := by
apply le_antisymm <;> rw [span_singleton_le_iff_mem, mem_span_singleton']
exacts [⟨a, rfl⟩, ⟨_, h2.unit.inv_mul_cancel_left x⟩]
#align ideal.span_singleton_mul_left_unit Ideal.span_singleton_mul_left_unit
theorem span_insert (x) (s : Set α) : span (insert x s) = span ({x} : Set α) ⊔ span s :=
Submodule.span_insert x s
#align ideal.span_insert Ideal.span_insert
theorem span_eq_bot {s : Set α} : span s = ⊥ ↔ ∀ x ∈ s, (x : α) = 0 :=
Submodule.span_eq_bot
#align ideal.span_eq_bot Ideal.span_eq_bot
@[simp]
theorem span_singleton_eq_bot {x} : span ({x} : Set α) = ⊥ ↔ x = 0 :=
Submodule.span_singleton_eq_bot
#align ideal.span_singleton_eq_bot Ideal.span_singleton_eq_bot
theorem span_singleton_ne_top {α : Type*} [CommSemiring α] {x : α} (hx : ¬IsUnit x) :
Ideal.span ({x} : Set α) ≠ ⊤ :=
(Ideal.ne_top_iff_one _).mpr fun h1 =>
let ⟨y, hy⟩ := Ideal.mem_span_singleton'.mp h1
hx ⟨⟨x, y, mul_comm y x ▸ hy, hy⟩, rfl⟩
#align ideal.span_singleton_ne_top Ideal.span_singleton_ne_top
@[simp]
theorem span_zero : span (0 : Set α) = ⊥ := by rw [← Set.singleton_zero, span_singleton_eq_bot]
#align ideal.span_zero Ideal.span_zero
@[simp]
theorem span_one : span (1 : Set α) = ⊤ := by rw [← Set.singleton_one, span_singleton_one]
#align ideal.span_one Ideal.span_one
theorem span_eq_top_iff_finite (s : Set α) :
span s = ⊤ ↔ ∃ s' : Finset α, ↑s' ⊆ s ∧ span (s' : Set α) = ⊤ := by
simp_rw [eq_top_iff_one]
exact ⟨Submodule.mem_span_finite_of_mem_span, fun ⟨s', h₁, h₂⟩ => span_mono h₁ h₂⟩
#align ideal.span_eq_top_iff_finite Ideal.span_eq_top_iff_finite
theorem mem_span_singleton_sup {S : Type*} [CommSemiring S] {x y : S} {I : Ideal S} :
x ∈ Ideal.span {y} ⊔ I ↔ ∃ a : S, ∃ b ∈ I, a * y + b = x := by
rw [Submodule.mem_sup]
constructor
· rintro ⟨ya, hya, b, hb, rfl⟩
obtain ⟨a, rfl⟩ := mem_span_singleton'.mp hya
exact ⟨a, b, hb, rfl⟩
· rintro ⟨a, b, hb, rfl⟩
exact ⟨a * y, Ideal.mem_span_singleton'.mpr ⟨a, rfl⟩, b, hb, rfl⟩
#align ideal.mem_span_singleton_sup Ideal.mem_span_singleton_sup
/-- The ideal generated by an arbitrary binary relation.
-/
def ofRel (r : α → α → Prop) : Ideal α :=
Submodule.span α { x | ∃ a b, r a b ∧ x + b = a }
#align ideal.of_rel Ideal.ofRel
/-- An ideal `P` of a ring `R` is prime if `P ≠ R` and `xy ∈ P → x ∈ P ∨ y ∈ P` -/
class IsPrime (I : Ideal α) : Prop where
/-- The prime ideal is not the entire ring. -/
ne_top' : I ≠ ⊤
/-- If a product lies in the prime ideal, then at least one element lies in the prime ideal. -/
mem_or_mem' : ∀ {x y : α}, x * y ∈ I → x ∈ I ∨ y ∈ I
#align ideal.is_prime Ideal.IsPrime
theorem isPrime_iff {I : Ideal α} : IsPrime I ↔ I ≠ ⊤ ∧ ∀ {x y : α}, x * y ∈ I → x ∈ I ∨ y ∈ I :=
⟨fun h => ⟨h.1, h.2⟩, fun h => ⟨h.1, h.2⟩⟩
#align ideal.is_prime_iff Ideal.isPrime_iff
theorem IsPrime.ne_top {I : Ideal α} (hI : I.IsPrime) : I ≠ ⊤ :=
hI.1
#align ideal.is_prime.ne_top Ideal.IsPrime.ne_top
theorem IsPrime.mem_or_mem {I : Ideal α} (hI : I.IsPrime) {x y : α} : x * y ∈ I → x ∈ I ∨ y ∈ I :=
hI.2
#align ideal.is_prime.mem_or_mem Ideal.IsPrime.mem_or_mem
theorem IsPrime.mem_or_mem_of_mul_eq_zero {I : Ideal α} (hI : I.IsPrime) {x y : α} (h : x * y = 0) :
x ∈ I ∨ y ∈ I :=
hI.mem_or_mem (h.symm ▸ I.zero_mem)
#align ideal.is_prime.mem_or_mem_of_mul_eq_zero Ideal.IsPrime.mem_or_mem_of_mul_eq_zero
theorem IsPrime.mem_of_pow_mem {I : Ideal α} (hI : I.IsPrime) {r : α} (n : ℕ) (H : r ^ n ∈ I) :
r ∈ I := by
induction' n with n ih
· rw [pow_zero] at H
exact (mt (eq_top_iff_one _).2 hI.1).elim H
· rw [pow_succ] at H
exact Or.casesOn (hI.mem_or_mem H) ih id
#align ideal.is_prime.mem_of_pow_mem Ideal.IsPrime.mem_of_pow_mem
theorem not_isPrime_iff {I : Ideal α} :
¬I.IsPrime ↔ I = ⊤ ∨ ∃ (x : α) (_hx : x ∉ I) (y : α) (_hy : y ∉ I), x * y ∈ I := by
simp_rw [Ideal.isPrime_iff, not_and_or, Ne, Classical.not_not, not_forall, not_or]
exact
or_congr Iff.rfl
⟨fun ⟨x, y, hxy, hx, hy⟩ => ⟨x, hx, y, hy, hxy⟩, fun ⟨x, hx, y, hy, hxy⟩ =>
⟨x, y, hxy, hx, hy⟩⟩
#align ideal.not_is_prime_iff Ideal.not_isPrime_iff
theorem zero_ne_one_of_proper {I : Ideal α} (h : I ≠ ⊤) : (0 : α) ≠ 1 := fun hz =>
I.ne_top_iff_one.1 h <| hz ▸ I.zero_mem
#align ideal.zero_ne_one_of_proper Ideal.zero_ne_one_of_proper
theorem bot_prime [IsDomain α] : (⊥ : Ideal α).IsPrime :=
⟨fun h => one_ne_zero (by rwa [Ideal.eq_top_iff_one, Submodule.mem_bot] at h), fun h =>
mul_eq_zero.mp (by simpa only [Submodule.mem_bot] using h)⟩
#align ideal.bot_prime Ideal.bot_prime
/-- An ideal is maximal if it is maximal in the collection of proper ideals. -/
class IsMaximal (I : Ideal α) : Prop where
/-- The maximal ideal is a coatom in the ordering on ideals; that is, it is not the entire ring,
and there are no other proper ideals strictly containing it. -/
out : IsCoatom I
#align ideal.is_maximal Ideal.IsMaximal
theorem isMaximal_def {I : Ideal α} : I.IsMaximal ↔ IsCoatom I :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align ideal.is_maximal_def Ideal.isMaximal_def
theorem IsMaximal.ne_top {I : Ideal α} (h : I.IsMaximal) : I ≠ ⊤ :=
(isMaximal_def.1 h).1
#align ideal.is_maximal.ne_top Ideal.IsMaximal.ne_top
theorem isMaximal_iff {I : Ideal α} :
I.IsMaximal ↔ (1 : α) ∉ I ∧ ∀ (J : Ideal α) (x), I ≤ J → x ∉ I → x ∈ J → (1 : α) ∈ J :=
isMaximal_def.trans <|
and_congr I.ne_top_iff_one <|
forall_congr' fun J => by
rw [lt_iff_le_not_le];
exact
⟨fun H x h hx₁ hx₂ => J.eq_top_iff_one.1 <| H ⟨h, not_subset.2 ⟨_, hx₂, hx₁⟩⟩,
fun H ⟨h₁, h₂⟩ =>
let ⟨x, xJ, xI⟩ := not_subset.1 h₂
J.eq_top_iff_one.2 <| H x h₁ xI xJ⟩
#align ideal.is_maximal_iff Ideal.isMaximal_iff
theorem IsMaximal.eq_of_le {I J : Ideal α} (hI : I.IsMaximal) (hJ : J ≠ ⊤) (IJ : I ≤ J) : I = J :=
eq_iff_le_not_lt.2 ⟨IJ, fun h => hJ (hI.1.2 _ h)⟩
#align ideal.is_maximal.eq_of_le Ideal.IsMaximal.eq_of_le
instance : IsCoatomic (Ideal α) := by
apply CompleteLattice.coatomic_of_top_compact
rw [← span_singleton_one]
exact Submodule.singleton_span_isCompactElement 1
theorem IsMaximal.coprime_of_ne {M M' : Ideal α} (hM : M.IsMaximal) (hM' : M'.IsMaximal)
(hne : M ≠ M') : M ⊔ M' = ⊤ := by
contrapose! hne with h
exact hM.eq_of_le hM'.ne_top (le_sup_left.trans_eq (hM'.eq_of_le h le_sup_right).symm)
#align ideal.is_maximal.coprime_of_ne Ideal.IsMaximal.coprime_of_ne
/-- **Krull's theorem**: if `I` is an ideal that is not the whole ring, then it is included in some
maximal ideal. -/
theorem exists_le_maximal (I : Ideal α) (hI : I ≠ ⊤) : ∃ M : Ideal α, M.IsMaximal ∧ I ≤ M :=
let ⟨m, hm⟩ := (eq_top_or_exists_le_coatom I).resolve_left hI
⟨m, ⟨⟨hm.1⟩, hm.2⟩⟩
#align ideal.exists_le_maximal Ideal.exists_le_maximal
variable (α)
/-- Krull's theorem: a nontrivial ring has a maximal ideal. -/
theorem exists_maximal [Nontrivial α] : ∃ M : Ideal α, M.IsMaximal :=
let ⟨I, ⟨hI, _⟩⟩ := exists_le_maximal (⊥ : Ideal α) bot_ne_top
⟨I, hI⟩
#align ideal.exists_maximal Ideal.exists_maximal
variable {α}
instance [Nontrivial α] : Nontrivial (Ideal α) := by
rcases@exists_maximal α _ _ with ⟨M, hM, _⟩
exact nontrivial_of_ne M ⊤ hM
/-- If P is not properly contained in any maximal ideal then it is not properly contained
in any proper ideal -/
theorem maximal_of_no_maximal {P : Ideal α}
(hmax : ∀ m : Ideal α, P < m → ¬IsMaximal m) (J : Ideal α) (hPJ : P < J) : J = ⊤ := by
by_contra hnonmax
rcases exists_le_maximal J hnonmax with ⟨M, hM1, hM2⟩
exact hmax M (lt_of_lt_of_le hPJ hM2) hM1
#align ideal.maximal_of_no_maximal Ideal.maximal_of_no_maximal
theorem span_pair_comm {x y : α} : (span {x, y} : Ideal α) = span {y, x} := by
simp only [span_insert, sup_comm]
#align ideal.span_pair_comm Ideal.span_pair_comm
theorem mem_span_pair {x y z : α} : z ∈ span ({x, y} : Set α) ↔ ∃ a b, a * x + b * y = z :=
Submodule.mem_span_pair
#align ideal.mem_span_pair Ideal.mem_span_pair
@[simp]
theorem span_pair_add_mul_left {R : Type u} [CommRing R] {x y : R} (z : R) :
(span {x + y * z, y} : Ideal R) = span {x, y} := by
ext
rw [mem_span_pair, mem_span_pair]
exact
⟨fun ⟨a, b, h⟩ =>
⟨a, b + a * z, by
rw [← h]
ring1⟩,
fun ⟨a, b, h⟩ =>
⟨a, b - a * z, by
rw [← h]
ring1⟩⟩
#align ideal.span_pair_add_mul_left Ideal.span_pair_add_mul_left
@[simp]
theorem span_pair_add_mul_right {R : Type u} [CommRing R] {x y : R} (z : R) :
(span {x, y + x * z} : Ideal R) = span {x, y} := by
rw [span_pair_comm, span_pair_add_mul_left, span_pair_comm]
#align ideal.span_pair_add_mul_right Ideal.span_pair_add_mul_right
theorem IsMaximal.exists_inv {I : Ideal α} (hI : I.IsMaximal) {x} (hx : x ∉ I) :
∃ y, ∃ i ∈ I, y * x + i = 1 := by
cases' isMaximal_iff.1 hI with H₁ H₂
rcases mem_span_insert.1
(H₂ (span (insert x I)) x (Set.Subset.trans (subset_insert _ _) subset_span) hx
(subset_span (mem_insert _ _))) with
⟨y, z, hz, hy⟩
refine ⟨y, z, ?_, hy.symm⟩
rwa [← span_eq I]
#align ideal.is_maximal.exists_inv Ideal.IsMaximal.exists_inv
section Lattice
variable {R : Type u} [Semiring R]
-- Porting note: is this the right approach? or is there a better way to prove? (next 4 decls)
theorem mem_sup_left {S T : Ideal R} : ∀ {x : R}, x ∈ S → x ∈ S ⊔ T :=
@le_sup_left _ _ S T
#align ideal.mem_sup_left Ideal.mem_sup_left
theorem mem_sup_right {S T : Ideal R} : ∀ {x : R}, x ∈ T → x ∈ S ⊔ T :=
@le_sup_right _ _ S T
#align ideal.mem_sup_right Ideal.mem_sup_right
theorem mem_iSup_of_mem {ι : Sort*} {S : ι → Ideal R} (i : ι) : ∀ {x : R}, x ∈ S i → x ∈ iSup S :=
@le_iSup _ _ _ S _
#align ideal.mem_supr_of_mem Ideal.mem_iSup_of_mem
theorem mem_sSup_of_mem {S : Set (Ideal R)} {s : Ideal R} (hs : s ∈ S) :
∀ {x : R}, x ∈ s → x ∈ sSup S :=
@le_sSup _ _ _ _ hs
#align ideal.mem_Sup_of_mem Ideal.mem_sSup_of_mem
theorem mem_sInf {s : Set (Ideal R)} {x : R} : x ∈ sInf s ↔ ∀ ⦃I⦄, I ∈ s → x ∈ I :=
⟨fun hx I his => hx I ⟨I, iInf_pos his⟩, fun H _I ⟨_J, hij⟩ => hij ▸ fun _S ⟨hj, hS⟩ => hS ▸ H hj⟩
#align ideal.mem_Inf Ideal.mem_sInf
@[simp 1001] -- Porting note: increased priority to appease `simpNF`
theorem mem_inf {I J : Ideal R} {x : R} : x ∈ I ⊓ J ↔ x ∈ I ∧ x ∈ J :=
Iff.rfl
#align ideal.mem_inf Ideal.mem_inf
@[simp 1001] -- Porting note: increased priority to appease `simpNF`
theorem mem_iInf {ι : Sort*} {I : ι → Ideal R} {x : R} : x ∈ iInf I ↔ ∀ i, x ∈ I i :=
Submodule.mem_iInf _
#align ideal.mem_infi Ideal.mem_iInf
@[simp 1001] -- Porting note: increased priority to appease `simpNF`
theorem mem_bot {x : R} : x ∈ (⊥ : Ideal R) ↔ x = 0 :=
Submodule.mem_bot _
#align ideal.mem_bot Ideal.mem_bot
end Lattice
section Pi
variable (ι : Type v)
/-- `I^n` as an ideal of `R^n`. -/
def pi : Ideal (ι → α) where
carrier := { x | ∀ i, x i ∈ I }
zero_mem' _i := I.zero_mem
add_mem' ha hb i := I.add_mem (ha i) (hb i)
smul_mem' a _b hb i := I.mul_mem_left (a i) (hb i)
#align ideal.pi Ideal.pi
theorem mem_pi (x : ι → α) : x ∈ I.pi ι ↔ ∀ i, x i ∈ I :=
Iff.rfl
#align ideal.mem_pi Ideal.mem_pi
end Pi
theorem sInf_isPrime_of_isChain {s : Set (Ideal α)} (hs : s.Nonempty) (hs' : IsChain (· ≤ ·) s)
(H : ∀ p ∈ s, Ideal.IsPrime p) : (sInf s).IsPrime :=
⟨fun e =>
let ⟨x, hx⟩ := hs
(H x hx).ne_top (eq_top_iff.mpr (e.symm.trans_le (sInf_le hx))),
fun e =>
or_iff_not_imp_left.mpr fun hx => by
rw [Ideal.mem_sInf] at hx e ⊢
push_neg at hx
obtain ⟨I, hI, hI'⟩ := hx
intro J hJ
cases' hs'.total hI hJ with h h
· exact h (((H I hI).mem_or_mem (e hI)).resolve_left hI')
· exact ((H J hJ).mem_or_mem (e hJ)).resolve_left fun x => hI' <| h x⟩
#align ideal.Inf_is_prime_of_is_chain Ideal.sInf_isPrime_of_isChain
end Ideal
end Semiring
section CommSemiring
variable {a b : α}
-- A separate namespace definition is needed because the variables were historically in a different
-- order.
namespace Ideal
variable [CommSemiring α] (I : Ideal α)
@[simp]
theorem mul_unit_mem_iff_mem {x y : α} (hy : IsUnit y) : x * y ∈ I ↔ x ∈ I :=
mul_comm y x ▸ unit_mul_mem_iff_mem I hy
#align ideal.mul_unit_mem_iff_mem Ideal.mul_unit_mem_iff_mem
theorem mem_span_singleton {x y : α} : x ∈ span ({y} : Set α) ↔ y ∣ x :=
mem_span_singleton'.trans <| exists_congr fun _ => by rw [eq_comm, mul_comm]
#align ideal.mem_span_singleton Ideal.mem_span_singleton
theorem mem_span_singleton_self (x : α) : x ∈ span ({x} : Set α) :=
mem_span_singleton.mpr dvd_rfl
#align ideal.mem_span_singleton_self Ideal.mem_span_singleton_self
theorem span_singleton_le_span_singleton {x y : α} :
span ({x} : Set α) ≤ span ({y} : Set α) ↔ y ∣ x :=
span_le.trans <| singleton_subset_iff.trans mem_span_singleton
#align ideal.span_singleton_le_span_singleton Ideal.span_singleton_le_span_singleton
theorem span_singleton_eq_span_singleton {α : Type u} [CommRing α] [IsDomain α] {x y : α} :
span ({x} : Set α) = span ({y} : Set α) ↔ Associated x y := by
rw [← dvd_dvd_iff_associated, le_antisymm_iff, and_comm]
apply and_congr <;> rw [span_singleton_le_span_singleton]
#align ideal.span_singleton_eq_span_singleton Ideal.span_singleton_eq_span_singleton
theorem span_singleton_mul_right_unit {a : α} (h2 : IsUnit a) (x : α) :
span ({x * a} : Set α) = span {x} := by rw [mul_comm, span_singleton_mul_left_unit h2]
#align ideal.span_singleton_mul_right_unit Ideal.span_singleton_mul_right_unit
@[simp]
theorem span_singleton_eq_top {x} : span ({x} : Set α) = ⊤ ↔ IsUnit x := by
rw [isUnit_iff_dvd_one, ← span_singleton_le_span_singleton, span_singleton_one, eq_top_iff]
#align ideal.span_singleton_eq_top Ideal.span_singleton_eq_top
theorem span_singleton_prime {p : α} (hp : p ≠ 0) : IsPrime (span ({p} : Set α)) ↔ Prime p := by
simp [isPrime_iff, Prime, span_singleton_eq_top, hp, mem_span_singleton]
#align ideal.span_singleton_prime Ideal.span_singleton_prime
theorem IsMaximal.isPrime {I : Ideal α} (H : I.IsMaximal) : I.IsPrime :=
⟨H.1.1, @fun x y hxy =>
or_iff_not_imp_left.2 fun hx => by
let J : Ideal α := Submodule.span α (insert x ↑I)
have IJ : I ≤ J := Set.Subset.trans (subset_insert _ _) subset_span
have xJ : x ∈ J := Ideal.subset_span (Set.mem_insert x I)
cases' isMaximal_iff.1 H with _ oJ
specialize oJ J x IJ hx xJ
rcases Submodule.mem_span_insert.mp oJ with ⟨a, b, h, oe⟩
obtain F : y * 1 = y * (a • x + b) := congr_arg (fun g : α => y * g) oe
rw [← mul_one y, F, mul_add, mul_comm, smul_eq_mul, mul_assoc]
refine Submodule.add_mem I (I.mul_mem_left a hxy) (Submodule.smul_mem I y ?_)
rwa [Submodule.span_eq] at h⟩
#align ideal.is_maximal.is_prime Ideal.IsMaximal.isPrime
-- see Note [lower instance priority]
instance (priority := 100) IsMaximal.isPrime' (I : Ideal α) : ∀ [_H : I.IsMaximal], I.IsPrime :=
@IsMaximal.isPrime _ _ _
#align ideal.is_maximal.is_prime' Ideal.IsMaximal.isPrime'
theorem span_singleton_lt_span_singleton [IsDomain α] {x y : α} :
span ({x} : Set α) < span ({y} : Set α) ↔ DvdNotUnit y x := by
rw [lt_iff_le_not_le, span_singleton_le_span_singleton, span_singleton_le_span_singleton,
dvd_and_not_dvd_iff]
#align ideal.span_singleton_lt_span_singleton Ideal.span_singleton_lt_span_singleton
theorem factors_decreasing [IsDomain α] (b₁ b₂ : α) (h₁ : b₁ ≠ 0) (h₂ : ¬IsUnit b₂) :
span ({b₁ * b₂} : Set α) < span {b₁} :=
lt_of_le_not_le
(Ideal.span_le.2 <| singleton_subset_iff.2 <| Ideal.mem_span_singleton.2 ⟨b₂, rfl⟩) fun h =>
h₂ <| isUnit_of_dvd_one <|
(mul_dvd_mul_iff_left h₁).1 <| by rwa [mul_one, ← Ideal.span_singleton_le_span_singleton]
#align ideal.factors_decreasing Ideal.factors_decreasing
variable (b)
theorem mul_mem_right (h : a ∈ I) : a * b ∈ I :=
mul_comm b a ▸ I.mul_mem_left b h
#align ideal.mul_mem_right Ideal.mul_mem_right
variable {b}
theorem pow_mem_of_mem (ha : a ∈ I) (n : ℕ) (hn : 0 < n) : a ^ n ∈ I :=
Nat.casesOn n (Not.elim (by decide))
(fun m _hm => (pow_succ a m).symm ▸ I.mul_mem_left (a ^ m) ha) hn
#align ideal.pow_mem_of_mem Ideal.pow_mem_of_mem
theorem pow_mem_of_pow_mem {m n : ℕ} (ha : a ^ m ∈ I) (h : m ≤ n) : a ^ n ∈ I := by
rw [← Nat.add_sub_of_le h, pow_add]
exact I.mul_mem_right _ ha
theorem add_pow_mem_of_pow_mem_of_le {m n k : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hk : m + n ≤ k + 1) :
(a + b) ^ k ∈ I := by
rw [add_pow]
apply I.sum_mem
intro c _
apply mul_mem_right
by_cases h : m ≤ c
· exact I.mul_mem_right _ (I.pow_mem_of_pow_mem ha h)
· refine I.mul_mem_left _ (I.pow_mem_of_pow_mem hb ?_)
simp only [not_le, Nat.lt_iff_add_one_le] at h
have hck : c ≤ k := by
rw [← add_le_add_iff_right 1]
exact le_trans h (le_trans (Nat.le_add_right _ _) hk)
rw [Nat.le_sub_iff_add_le hck, ← add_le_add_iff_right 1]
exact le_trans (by rwa [add_comm _ n, add_assoc, add_le_add_iff_left]) hk
theorem add_pow_add_pred_mem_of_pow_mem {m n : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) :
(a + b) ^ (m + n - 1) ∈ I :=
I.add_pow_mem_of_pow_mem_of_le ha hb <| by rw [← Nat.sub_le_iff_le_add]
theorem IsPrime.mul_mem_iff_mem_or_mem {I : Ideal α} (hI : I.IsPrime) :
∀ {x y : α}, x * y ∈ I ↔ x ∈ I ∨ y ∈ I := @fun x y =>
⟨hI.mem_or_mem, by
rintro (h | h)
exacts [I.mul_mem_right y h, I.mul_mem_left x h]⟩
#align ideal.is_prime.mul_mem_iff_mem_or_mem Ideal.IsPrime.mul_mem_iff_mem_or_mem
theorem IsPrime.pow_mem_iff_mem {I : Ideal α} (hI : I.IsPrime) {r : α} (n : ℕ) (hn : 0 < n) :
r ^ n ∈ I ↔ r ∈ I :=
⟨hI.mem_of_pow_mem n, fun hr => I.pow_mem_of_mem hr n hn⟩
#align ideal.is_prime.pow_mem_iff_mem Ideal.IsPrime.pow_mem_iff_mem
theorem pow_multiset_sum_mem_span_pow [DecidableEq α] (s : Multiset α) (n : ℕ) :
s.sum ^ (Multiset.card s * n + 1) ∈
span ((s.map fun (x:α) ↦ x ^ (n + 1)).toFinset : Set α) := by
induction' s using Multiset.induction_on with a s hs
· simp
simp only [Finset.coe_insert, Multiset.map_cons, Multiset.toFinset_cons, Multiset.sum_cons,
Multiset.card_cons, add_pow]
refine Submodule.sum_mem _ ?_
intro c _hc
rw [mem_span_insert]
by_cases h : n + 1 ≤ c
· refine ⟨a ^ (c - (n + 1)) * s.sum ^ ((Multiset.card s + 1) * n + 1 - c) *
((Multiset.card s + 1) * n + 1).choose c, 0, Submodule.zero_mem _, ?_⟩
rw [mul_comm _ (a ^ (n + 1))]
simp_rw [← mul_assoc]
rw [← pow_add, add_zero, add_tsub_cancel_of_le h]
· use 0
simp_rw [zero_mul, zero_add]
refine ⟨_, ?_, rfl⟩
replace h : c ≤ n := Nat.lt_succ_iff.mp (not_le.mp h)
have : (Multiset.card s + 1) * n + 1 - c = Multiset.card s * n + 1 + (n - c) := by
rw [add_mul, one_mul, add_assoc, add_comm n 1, ← add_assoc, add_tsub_assoc_of_le h]
rw [this, pow_add]
simp_rw [mul_assoc, mul_comm (s.sum ^ (Multiset.card s * n + 1)), ← mul_assoc]
exact mul_mem_left _ _ hs
#align ideal.pow_multiset_sum_mem_span_pow Ideal.pow_multiset_sum_mem_span_pow
theorem sum_pow_mem_span_pow {ι} (s : Finset ι) (f : ι → α) (n : ℕ) :
(∑ i ∈ s, f i) ^ (s.card * n + 1) ∈ span ((fun i => f i ^ (n + 1)) '' s) := by
classical
simpa only [Multiset.card_map, Multiset.map_map, comp_apply, Multiset.toFinset_map,
Finset.coe_image, Finset.val_toFinset] using pow_multiset_sum_mem_span_pow (s.1.map f) n
#align ideal.sum_pow_mem_span_pow Ideal.sum_pow_mem_span_pow
theorem span_pow_eq_top (s : Set α) (hs : span s = ⊤) (n : ℕ) :
span ((fun (x : α) => x ^ n) '' s) = ⊤ := by
rw [eq_top_iff_one]
cases' n with n
· obtain rfl | ⟨x, hx⟩ := eq_empty_or_nonempty s
· rw [Set.image_empty, hs]
trivial
· exact subset_span ⟨_, hx, pow_zero _⟩
rw [eq_top_iff_one, span, Finsupp.mem_span_iff_total] at hs
rcases hs with ⟨f, hf⟩
have hf : (f.support.sum fun a => f a * a) = 1 := hf -- Porting note: was `change ... at hf`
have := sum_pow_mem_span_pow f.support (fun a => f a * a) n
rw [hf, one_pow] at this
refine span_le.mpr ?_ this
rintro _ hx
simp_rw [Set.mem_image] at hx
rcases hx with ⟨x, _, rfl⟩
have : span ({(x:α) ^ (n + 1)} : Set α) ≤ span ((fun x : α => x ^ (n + 1)) '' s) := by
rw [span_le, Set.singleton_subset_iff]
exact subset_span ⟨x, x.prop, rfl⟩
refine this ?_
rw [mul_pow, mem_span_singleton]
exact ⟨f x ^ (n + 1), mul_comm _ _⟩
#align ideal.span_pow_eq_top Ideal.span_pow_eq_top
lemma isPrime_of_maximally_disjoint (I : Ideal α)
(S : Submonoid α)
(disjoint : Disjoint (I : Set α) S)
(maximally_disjoint : ∀ (J : Ideal α), I < J → ¬ Disjoint (J : Set α) S) :
I.IsPrime where
ne_top' := by
rintro rfl
have : 1 ∈ (S : Set α) := S.one_mem
aesop
mem_or_mem' {x y} hxy := by
by_contra! rid
have hx := maximally_disjoint (I ⊔ span {x}) (Submodule.lt_sup_iff_not_mem.mpr rid.1)
have hy := maximally_disjoint (I ⊔ span {y}) (Submodule.lt_sup_iff_not_mem.mpr rid.2)
simp only [Set.not_disjoint_iff, mem_inter_iff, SetLike.mem_coe, Submodule.mem_sup,
mem_span_singleton] at hx hy
obtain ⟨s₁, ⟨i₁, hi₁, ⟨_, ⟨r₁, rfl⟩, hr₁⟩⟩, hs₁⟩ := hx
obtain ⟨s₂, ⟨i₂, hi₂, ⟨_, ⟨r₂, rfl⟩, hr₂⟩⟩, hs₂⟩ := hy
refine disjoint.ne_of_mem
(I.add_mem (I.mul_mem_left (i₁ + x * r₁) hi₂) <| I.add_mem (I.mul_mem_right (y * r₂) hi₁) <|
I.mul_mem_right (r₁ * r₂) hxy)
(S.mul_mem hs₁ hs₂) ?_
rw [← hr₁, ← hr₂]
ring
end Ideal
end CommSemiring
section Ring
namespace Ideal
variable [Ring α] (I : Ideal α) {a b : α}
protected theorem neg_mem_iff : -a ∈ I ↔ a ∈ I :=
Submodule.neg_mem_iff I
#align ideal.neg_mem_iff Ideal.neg_mem_iff
protected theorem add_mem_iff_left : b ∈ I → (a + b ∈ I ↔ a ∈ I) :=
Submodule.add_mem_iff_left I
#align ideal.add_mem_iff_left Ideal.add_mem_iff_left
protected theorem add_mem_iff_right : a ∈ I → (a + b ∈ I ↔ b ∈ I) :=
Submodule.add_mem_iff_right I
#align ideal.add_mem_iff_right Ideal.add_mem_iff_right
protected theorem sub_mem : a ∈ I → b ∈ I → a - b ∈ I :=
Submodule.sub_mem I
#align ideal.sub_mem Ideal.sub_mem
theorem mem_span_insert' {s : Set α} {x y} : x ∈ span (insert y s) ↔ ∃ a, x + a * y ∈ span s :=
Submodule.mem_span_insert'
#align ideal.mem_span_insert' Ideal.mem_span_insert'
@[simp]
theorem span_singleton_neg (x : α) : (span {-x} : Ideal α) = span {x} := by
ext
simp only [mem_span_singleton']
exact ⟨fun ⟨y, h⟩ => ⟨-y, h ▸ neg_mul_comm y x⟩, fun ⟨y, h⟩ => ⟨-y, h ▸ neg_mul_neg y x⟩⟩
#align ideal.span_singleton_neg Ideal.span_singleton_neg
end Ideal
end Ring
section DivisionSemiring
variable {K : Type u} [DivisionSemiring K] (I : Ideal K)
namespace Ideal
/-- All ideals in a division (semi)ring are trivial. -/
| Mathlib/RingTheory/Ideal/Basic.lean | 750 | 758 | theorem eq_bot_or_top : I = ⊥ ∨ I = ⊤ := by |
rw [or_iff_not_imp_right]
change _ ≠ _ → _
rw [Ideal.ne_top_iff_one]
intro h1
rw [eq_bot_iff]
intro r hr
by_cases H : r = 0; · simpa
simpa [H, h1] using I.mul_mem_left r⁻¹ hr
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Scott Morrison
-/
import Mathlib.CategoryTheory.Subobject.Lattice
#align_import category_theory.subobject.limits from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
# Specific subobjects
We define `equalizerSubobject`, `kernelSubobject` and `imageSubobject`, which are the subobjects
represented by the equalizer, kernel and image of (a pair of) morphism(s) and provide conditions
for `P.factors f`, where `P` is one of these special subobjects.
TODO: Add conditions for when `P` is a pullback subobject.
TODO: an iff characterisation of `(imageSubobject f).Factors h`
-/
universe v u
noncomputable section
open CategoryTheory CategoryTheory.Category CategoryTheory.Limits CategoryTheory.Subobject Opposite
variable {C : Type u} [Category.{v} C] {X Y Z : C}
namespace CategoryTheory
namespace Limits
section Equalizer
variable (f g : X ⟶ Y) [HasEqualizer f g]
/-- The equalizer of morphisms `f g : X ⟶ Y` as a `Subobject X`. -/
abbrev equalizerSubobject : Subobject X :=
Subobject.mk (equalizer.ι f g)
#align category_theory.limits.equalizer_subobject CategoryTheory.Limits.equalizerSubobject
/-- The underlying object of `equalizerSubobject f g` is (up to isomorphism!)
the same as the chosen object `equalizer f g`. -/
def equalizerSubobjectIso : (equalizerSubobject f g : C) ≅ equalizer f g :=
Subobject.underlyingIso (equalizer.ι f g)
#align category_theory.limits.equalizer_subobject_iso CategoryTheory.Limits.equalizerSubobjectIso
@[reassoc (attr := simp)]
theorem equalizerSubobject_arrow :
(equalizerSubobjectIso f g).hom ≫ equalizer.ι f g = (equalizerSubobject f g).arrow := by
simp [equalizerSubobjectIso]
#align category_theory.limits.equalizer_subobject_arrow CategoryTheory.Limits.equalizerSubobject_arrow
@[reassoc (attr := simp)]
theorem equalizerSubobject_arrow' :
(equalizerSubobjectIso f g).inv ≫ (equalizerSubobject f g).arrow = equalizer.ι f g := by
simp [equalizerSubobjectIso]
#align category_theory.limits.equalizer_subobject_arrow' CategoryTheory.Limits.equalizerSubobject_arrow'
@[reassoc]
theorem equalizerSubobject_arrow_comp :
(equalizerSubobject f g).arrow ≫ f = (equalizerSubobject f g).arrow ≫ g := by
rw [← equalizerSubobject_arrow, Category.assoc, Category.assoc, equalizer.condition]
#align category_theory.limits.equalizer_subobject_arrow_comp CategoryTheory.Limits.equalizerSubobject_arrow_comp
theorem equalizerSubobject_factors {W : C} (h : W ⟶ X) (w : h ≫ f = h ≫ g) :
(equalizerSubobject f g).Factors h :=
⟨equalizer.lift h w, by simp⟩
#align category_theory.limits.equalizer_subobject_factors CategoryTheory.Limits.equalizerSubobject_factors
theorem equalizerSubobject_factors_iff {W : C} (h : W ⟶ X) :
(equalizerSubobject f g).Factors h ↔ h ≫ f = h ≫ g :=
⟨fun w => by
rw [← Subobject.factorThru_arrow _ _ w, Category.assoc, equalizerSubobject_arrow_comp,
Category.assoc],
equalizerSubobject_factors f g h⟩
#align category_theory.limits.equalizer_subobject_factors_iff CategoryTheory.Limits.equalizerSubobject_factors_iff
end Equalizer
section Kernel
variable [HasZeroMorphisms C] (f : X ⟶ Y) [HasKernel f]
/-- The kernel of a morphism `f : X ⟶ Y` as a `Subobject X`. -/
abbrev kernelSubobject : Subobject X :=
Subobject.mk (kernel.ι f)
#align category_theory.limits.kernel_subobject CategoryTheory.Limits.kernelSubobject
/-- The underlying object of `kernelSubobject f` is (up to isomorphism!)
the same as the chosen object `kernel f`. -/
def kernelSubobjectIso : (kernelSubobject f : C) ≅ kernel f :=
Subobject.underlyingIso (kernel.ι f)
#align category_theory.limits.kernel_subobject_iso CategoryTheory.Limits.kernelSubobjectIso
@[reassoc (attr := simp), elementwise (attr := simp)]
theorem kernelSubobject_arrow :
(kernelSubobjectIso f).hom ≫ kernel.ι f = (kernelSubobject f).arrow := by
simp [kernelSubobjectIso]
#align category_theory.limits.kernel_subobject_arrow CategoryTheory.Limits.kernelSubobject_arrow
@[reassoc (attr := simp), elementwise (attr := simp)]
theorem kernelSubobject_arrow' :
(kernelSubobjectIso f).inv ≫ (kernelSubobject f).arrow = kernel.ι f := by
simp [kernelSubobjectIso]
#align category_theory.limits.kernel_subobject_arrow' CategoryTheory.Limits.kernelSubobject_arrow'
@[reassoc (attr := simp), elementwise (attr := simp)]
| Mathlib/CategoryTheory/Subobject/Limits.lean | 110 | 112 | theorem kernelSubobject_arrow_comp : (kernelSubobject f).arrow ≫ f = 0 := by |
rw [← kernelSubobject_arrow]
simp only [Category.assoc, kernel.condition, comp_zero]
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.GeomSum
import Mathlib.LinearAlgebra.Matrix.Block
import Mathlib.LinearAlgebra.Matrix.Determinant.Basic
import Mathlib.LinearAlgebra.Matrix.Nondegenerate
#align_import linear_algebra.vandermonde from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Vandermonde matrix
This file defines the `vandermonde` matrix and gives its determinant.
## Main definitions
- `vandermonde v`: a square matrix with the `i, j`th entry equal to `v i ^ j`.
## Main results
- `det_vandermonde`: `det (vandermonde v)` is the product of `v i - v j`, where
`(i, j)` ranges over the unordered pairs.
-/
variable {R : Type*} [CommRing R]
open Equiv Finset
open Matrix
namespace Matrix
/-- `vandermonde v` is the square matrix with `i`th row equal to `1, v i, v i ^ 2, v i ^ 3, ...`.
-/
def vandermonde {n : ℕ} (v : Fin n → R) : Matrix (Fin n) (Fin n) R := fun i j => v i ^ (j : ℕ)
#align matrix.vandermonde Matrix.vandermonde
@[simp]
theorem vandermonde_apply {n : ℕ} (v : Fin n → R) (i j) : vandermonde v i j = v i ^ (j : ℕ) :=
rfl
#align matrix.vandermonde_apply Matrix.vandermonde_apply
@[simp]
theorem vandermonde_cons {n : ℕ} (v0 : R) (v : Fin n → R) :
vandermonde (Fin.cons v0 v : Fin n.succ → R) =
Fin.cons (fun (j : Fin n.succ) => v0 ^ (j : ℕ)) fun i => Fin.cons 1
fun j => v i * vandermonde v i j := by
ext i j
refine Fin.cases (by simp) (fun i => ?_) i
refine Fin.cases (by simp) (fun j => ?_) j
simp [pow_succ']
#align matrix.vandermonde_cons Matrix.vandermonde_cons
theorem vandermonde_succ {n : ℕ} (v : Fin n.succ → R) :
vandermonde v =
Fin.cons (fun (j : Fin n.succ) => v 0 ^ (j : ℕ)) fun i =>
Fin.cons 1 fun j => v i.succ * vandermonde (Fin.tail v) i j := by
conv_lhs => rw [← Fin.cons_self_tail v, vandermonde_cons]
rfl
#align matrix.vandermonde_succ Matrix.vandermonde_succ
theorem vandermonde_mul_vandermonde_transpose {n : ℕ} (v w : Fin n → R) (i j) :
(vandermonde v * (vandermonde w)ᵀ) i j = ∑ k : Fin n, (v i * w j) ^ (k : ℕ) := by
simp only [vandermonde_apply, Matrix.mul_apply, Matrix.transpose_apply, mul_pow]
#align matrix.vandermonde_mul_vandermonde_transpose Matrix.vandermonde_mul_vandermonde_transpose
theorem vandermonde_transpose_mul_vandermonde {n : ℕ} (v : Fin n → R) (i j) :
((vandermonde v)ᵀ * vandermonde v) i j = ∑ k : Fin n, v k ^ (i + j : ℕ) := by
simp only [vandermonde_apply, Matrix.mul_apply, Matrix.transpose_apply, pow_add]
#align matrix.vandermonde_transpose_mul_vandermonde Matrix.vandermonde_transpose_mul_vandermonde
theorem det_vandermonde {n : ℕ} (v : Fin n → R) :
det (vandermonde v) = ∏ i : Fin n, ∏ j ∈ Ioi i, (v j - v i) := by
unfold vandermonde
induction' n with n ih
· exact det_eq_one_of_card_eq_zero (Fintype.card_fin 0)
calc
det (of fun i j : Fin n.succ => v i ^ (j : ℕ)) =
det
(of fun i j : Fin n.succ =>
Matrix.vecCons (v 0 ^ (j : ℕ)) (fun i => v (Fin.succ i) ^ (j : ℕ) - v 0 ^ (j : ℕ)) i) :=
det_eq_of_forall_row_eq_smul_add_const (Matrix.vecCons 0 1) 0 (Fin.cons_zero _ _) ?_
_ =
det
(of fun i j : Fin n =>
Matrix.vecCons (v 0 ^ (j.succ : ℕ))
(fun i : Fin n => v (Fin.succ i) ^ (j.succ : ℕ) - v 0 ^ (j.succ : ℕ))
(Fin.succAbove 0 i)) := by
simp_rw [det_succ_column_zero, Fin.sum_univ_succ, of_apply, Matrix.cons_val_zero, submatrix,
of_apply, Matrix.cons_val_succ, Fin.val_zero, pow_zero, one_mul, sub_self,
mul_zero, zero_mul, Finset.sum_const_zero, add_zero]
_ =
det
(of fun i j : Fin n =>
(v (Fin.succ i) - v 0) *
∑ k ∈ Finset.range (j + 1 : ℕ), v i.succ ^ k * v 0 ^ (j - k : ℕ) :
Matrix _ _ R) := by
congr
ext i j
rw [Fin.succAbove_zero, Matrix.cons_val_succ, Fin.val_succ, mul_comm]
exact (geom_sum₂_mul (v i.succ) (v 0) (j + 1 : ℕ)).symm
_ =
(∏ i ∈ Finset.univ, (v (Fin.succ i) - v 0)) *
det fun i j : Fin n =>
∑ k ∈ Finset.range (j + 1 : ℕ), v i.succ ^ k * v 0 ^ (j - k : ℕ) :=
(det_mul_column (fun i => v (Fin.succ i) - v 0) _)
_ = (∏ i ∈ Finset.univ, (v (Fin.succ i) - v 0)) *
det fun i j : Fin n => v (Fin.succ i) ^ (j : ℕ) := congr_arg _ ?_
_ = ∏ i : Fin n.succ, ∏ j ∈ Ioi i, (v j - v i) := by
simp_rw [Fin.prod_univ_succ, Fin.prod_Ioi_zero, Fin.prod_Ioi_succ]
have h := ih (v ∘ Fin.succ)
unfold Function.comp at h
rw [h]
· intro i j
simp_rw [of_apply]
rw [Matrix.cons_val_zero]
refine Fin.cases ?_ (fun i => ?_) i
· simp
rw [Matrix.cons_val_succ, Matrix.cons_val_succ, Pi.one_apply]
ring
· cases n
· rw [det_eq_one_of_card_eq_zero (Fintype.card_fin 0),
det_eq_one_of_card_eq_zero (Fintype.card_fin 0)]
apply det_eq_of_forall_col_eq_smul_add_pred fun _ => v 0
· intro j
simp
· intro i j
simp only [smul_eq_mul, Pi.add_apply, Fin.val_succ, Fin.coe_castSucc, Pi.smul_apply]
rw [Finset.sum_range_succ, add_comm, tsub_self, pow_zero, mul_one, Finset.mul_sum]
congr 1
refine Finset.sum_congr rfl fun i' hi' => ?_
rw [mul_left_comm (v 0), Nat.succ_sub, pow_succ']
exact Nat.lt_succ_iff.mp (Finset.mem_range.mp hi')
#align matrix.det_vandermonde Matrix.det_vandermonde
| Mathlib/LinearAlgebra/Vandermonde.lean | 142 | 150 | theorem det_vandermonde_eq_zero_iff [IsDomain R] {n : ℕ} {v : Fin n → R} :
det (vandermonde v) = 0 ↔ ∃ i j : Fin n, v i = v j ∧ i ≠ j := by |
constructor
· simp only [det_vandermonde v, Finset.prod_eq_zero_iff, sub_eq_zero, forall_exists_index]
rintro i ⟨_, j, h₁, h₂⟩
exact ⟨j, i, h₂, (mem_Ioi.mp h₁).ne'⟩
· simp only [Ne, forall_exists_index, and_imp]
refine fun i j h₁ h₂ => Matrix.det_zero_of_row_eq h₂ (funext fun k => ?_)
rw [vandermonde_apply, vandermonde_apply, h₁]
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.Analysis.SpecialFunctions.Sqrt
import Mathlib.Analysis.NormedSpace.HomeomorphBall
#align_import analysis.inner_product_space.calculus from "leanprover-community/mathlib"@"f9dd3204df14a0749cd456fac1e6849dfe7d2b88"
/-!
# Calculus in inner product spaces
In this file we prove that the inner product and square of the norm in an inner space are
infinitely `ℝ`-smooth. In order to state these results, we need a `NormedSpace ℝ E`
instance. Though we can deduce this structure from `InnerProductSpace 𝕜 E`, this instance may be
not definitionally equal to some other “natural” instance. So, we assume `[NormedSpace ℝ E]`.
We also prove that functions to a `EuclideanSpace` are (higher) differentiable if and only if
their components are. This follows from the corresponding fact for finite product of normed spaces,
and from the equivalence of norms in finite dimensions.
## TODO
The last part of the file should be generalized to `PiLp`.
-/
noncomputable section
open RCLike Real Filter
open scoped Classical Topology
section DerivInner
variable {𝕜 E F : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
variable (𝕜) [NormedSpace ℝ E]
/-- Derivative of the inner product. -/
def fderivInnerCLM (p : E × E) : E × E →L[ℝ] 𝕜 :=
isBoundedBilinearMap_inner.deriv p
#align fderiv_inner_clm fderivInnerCLM
@[simp]
theorem fderivInnerCLM_apply (p x : E × E) : fderivInnerCLM 𝕜 p x = ⟪p.1, x.2⟫ + ⟪x.1, p.2⟫ :=
rfl
#align fderiv_inner_clm_apply fderivInnerCLM_apply
variable {𝕜} -- Porting note: Lean 3 magically switches back to `{𝕜}` here
theorem contDiff_inner {n} : ContDiff ℝ n fun p : E × E => ⟪p.1, p.2⟫ :=
isBoundedBilinearMap_inner.contDiff
#align cont_diff_inner contDiff_inner
theorem contDiffAt_inner {p : E × E} {n} : ContDiffAt ℝ n (fun p : E × E => ⟪p.1, p.2⟫) p :=
ContDiff.contDiffAt contDiff_inner
#align cont_diff_at_inner contDiffAt_inner
theorem differentiable_inner : Differentiable ℝ fun p : E × E => ⟪p.1, p.2⟫ :=
isBoundedBilinearMap_inner.differentiableAt
#align differentiable_inner differentiable_inner
variable (𝕜)
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace ℝ G] {f g : G → E} {f' g' : G →L[ℝ] E}
{s : Set G} {x : G} {n : ℕ∞}
theorem ContDiffWithinAt.inner (hf : ContDiffWithinAt ℝ n f s x) (hg : ContDiffWithinAt ℝ n g s x) :
ContDiffWithinAt ℝ n (fun x => ⟪f x, g x⟫) s x :=
contDiffAt_inner.comp_contDiffWithinAt x (hf.prod hg)
#align cont_diff_within_at.inner ContDiffWithinAt.inner
nonrec theorem ContDiffAt.inner (hf : ContDiffAt ℝ n f x) (hg : ContDiffAt ℝ n g x) :
ContDiffAt ℝ n (fun x => ⟪f x, g x⟫) x :=
hf.inner 𝕜 hg
#align cont_diff_at.inner ContDiffAt.inner
theorem ContDiffOn.inner (hf : ContDiffOn ℝ n f s) (hg : ContDiffOn ℝ n g s) :
ContDiffOn ℝ n (fun x => ⟪f x, g x⟫) s := fun x hx => (hf x hx).inner 𝕜 (hg x hx)
#align cont_diff_on.inner ContDiffOn.inner
theorem ContDiff.inner (hf : ContDiff ℝ n f) (hg : ContDiff ℝ n g) :
ContDiff ℝ n fun x => ⟪f x, g x⟫ :=
contDiff_inner.comp (hf.prod hg)
#align cont_diff.inner ContDiff.inner
theorem HasFDerivWithinAt.inner (hf : HasFDerivWithinAt f f' s x)
(hg : HasFDerivWithinAt g g' s x) :
HasFDerivWithinAt (fun t => ⟪f t, g t⟫) ((fderivInnerCLM 𝕜 (f x, g x)).comp <| f'.prod g') s
x :=
(isBoundedBilinearMap_inner.hasFDerivAt (f x, g x)).comp_hasFDerivWithinAt x (hf.prod hg)
#align has_fderiv_within_at.inner HasFDerivWithinAt.inner
theorem HasStrictFDerivAt.inner (hf : HasStrictFDerivAt f f' x) (hg : HasStrictFDerivAt g g' x) :
HasStrictFDerivAt (fun t => ⟪f t, g t⟫) ((fderivInnerCLM 𝕜 (f x, g x)).comp <| f'.prod g') x :=
(isBoundedBilinearMap_inner.hasStrictFDerivAt (f x, g x)).comp x (hf.prod hg)
#align has_strict_fderiv_at.inner HasStrictFDerivAt.inner
theorem HasFDerivAt.inner (hf : HasFDerivAt f f' x) (hg : HasFDerivAt g g' x) :
HasFDerivAt (fun t => ⟪f t, g t⟫) ((fderivInnerCLM 𝕜 (f x, g x)).comp <| f'.prod g') x :=
(isBoundedBilinearMap_inner.hasFDerivAt (f x, g x)).comp x (hf.prod hg)
#align has_fderiv_at.inner HasFDerivAt.inner
theorem HasDerivWithinAt.inner {f g : ℝ → E} {f' g' : E} {s : Set ℝ} {x : ℝ}
(hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x) :
HasDerivWithinAt (fun t => ⟪f t, g t⟫) (⟪f x, g'⟫ + ⟪f', g x⟫) s x := by
simpa using (hf.hasFDerivWithinAt.inner 𝕜 hg.hasFDerivWithinAt).hasDerivWithinAt
#align has_deriv_within_at.inner HasDerivWithinAt.inner
theorem HasDerivAt.inner {f g : ℝ → E} {f' g' : E} {x : ℝ} :
HasDerivAt f f' x → HasDerivAt g g' x →
HasDerivAt (fun t => ⟪f t, g t⟫) (⟪f x, g'⟫ + ⟪f', g x⟫) x := by
simpa only [← hasDerivWithinAt_univ] using HasDerivWithinAt.inner 𝕜
#align has_deriv_at.inner HasDerivAt.inner
theorem DifferentiableWithinAt.inner (hf : DifferentiableWithinAt ℝ f s x)
(hg : DifferentiableWithinAt ℝ g s x) : DifferentiableWithinAt ℝ (fun x => ⟪f x, g x⟫) s x :=
((differentiable_inner _).hasFDerivAt.comp_hasFDerivWithinAt x
(hf.prod hg).hasFDerivWithinAt).differentiableWithinAt
#align differentiable_within_at.inner DifferentiableWithinAt.inner
theorem DifferentiableAt.inner (hf : DifferentiableAt ℝ f x) (hg : DifferentiableAt ℝ g x) :
DifferentiableAt ℝ (fun x => ⟪f x, g x⟫) x :=
(differentiable_inner _).comp x (hf.prod hg)
#align differentiable_at.inner DifferentiableAt.inner
theorem DifferentiableOn.inner (hf : DifferentiableOn ℝ f s) (hg : DifferentiableOn ℝ g s) :
DifferentiableOn ℝ (fun x => ⟪f x, g x⟫) s := fun x hx => (hf x hx).inner 𝕜 (hg x hx)
#align differentiable_on.inner DifferentiableOn.inner
theorem Differentiable.inner (hf : Differentiable ℝ f) (hg : Differentiable ℝ g) :
Differentiable ℝ fun x => ⟪f x, g x⟫ := fun x => (hf x).inner 𝕜 (hg x)
#align differentiable.inner Differentiable.inner
theorem fderiv_inner_apply (hf : DifferentiableAt ℝ f x) (hg : DifferentiableAt ℝ g x) (y : G) :
fderiv ℝ (fun t => ⟪f t, g t⟫) x y = ⟪f x, fderiv ℝ g x y⟫ + ⟪fderiv ℝ f x y, g x⟫ := by
rw [(hf.hasFDerivAt.inner 𝕜 hg.hasFDerivAt).fderiv]; rfl
#align fderiv_inner_apply fderiv_inner_apply
theorem deriv_inner_apply {f g : ℝ → E} {x : ℝ} (hf : DifferentiableAt ℝ f x)
(hg : DifferentiableAt ℝ g x) :
deriv (fun t => ⟪f t, g t⟫) x = ⟪f x, deriv g x⟫ + ⟪deriv f x, g x⟫ :=
(hf.hasDerivAt.inner 𝕜 hg.hasDerivAt).deriv
#align deriv_inner_apply deriv_inner_apply
theorem contDiff_norm_sq : ContDiff ℝ n fun x : E => ‖x‖ ^ 2 := by
convert (reCLM : 𝕜 →L[ℝ] ℝ).contDiff.comp ((contDiff_id (E := E)).inner 𝕜 (contDiff_id (E := E)))
exact (inner_self_eq_norm_sq _).symm
#align cont_diff_norm_sq contDiff_norm_sq
theorem ContDiff.norm_sq (hf : ContDiff ℝ n f) : ContDiff ℝ n fun x => ‖f x‖ ^ 2 :=
(contDiff_norm_sq 𝕜).comp hf
#align cont_diff.norm_sq ContDiff.norm_sq
theorem ContDiffWithinAt.norm_sq (hf : ContDiffWithinAt ℝ n f s x) :
ContDiffWithinAt ℝ n (fun y => ‖f y‖ ^ 2) s x :=
(contDiff_norm_sq 𝕜).contDiffAt.comp_contDiffWithinAt x hf
#align cont_diff_within_at.norm_sq ContDiffWithinAt.norm_sq
nonrec theorem ContDiffAt.norm_sq (hf : ContDiffAt ℝ n f x) : ContDiffAt ℝ n (‖f ·‖ ^ 2) x :=
hf.norm_sq 𝕜
#align cont_diff_at.norm_sq ContDiffAt.norm_sq
theorem contDiffAt_norm {x : E} (hx : x ≠ 0) : ContDiffAt ℝ n norm x := by
have : ‖id x‖ ^ 2 ≠ 0 := pow_ne_zero 2 (norm_pos_iff.2 hx).ne'
simpa only [id, sqrt_sq, norm_nonneg] using (contDiffAt_id.norm_sq 𝕜).sqrt this
#align cont_diff_at_norm contDiffAt_norm
theorem ContDiffAt.norm (hf : ContDiffAt ℝ n f x) (h0 : f x ≠ 0) :
ContDiffAt ℝ n (fun y => ‖f y‖) x :=
(contDiffAt_norm 𝕜 h0).comp x hf
#align cont_diff_at.norm ContDiffAt.norm
theorem ContDiffAt.dist (hf : ContDiffAt ℝ n f x) (hg : ContDiffAt ℝ n g x) (hne : f x ≠ g x) :
ContDiffAt ℝ n (fun y => dist (f y) (g y)) x := by
simp only [dist_eq_norm]
exact (hf.sub hg).norm 𝕜 (sub_ne_zero.2 hne)
#align cont_diff_at.dist ContDiffAt.dist
theorem ContDiffWithinAt.norm (hf : ContDiffWithinAt ℝ n f s x) (h0 : f x ≠ 0) :
ContDiffWithinAt ℝ n (fun y => ‖f y‖) s x :=
(contDiffAt_norm 𝕜 h0).comp_contDiffWithinAt x hf
#align cont_diff_within_at.norm ContDiffWithinAt.norm
theorem ContDiffWithinAt.dist (hf : ContDiffWithinAt ℝ n f s x) (hg : ContDiffWithinAt ℝ n g s x)
(hne : f x ≠ g x) : ContDiffWithinAt ℝ n (fun y => dist (f y) (g y)) s x := by
simp only [dist_eq_norm]; exact (hf.sub hg).norm 𝕜 (sub_ne_zero.2 hne)
#align cont_diff_within_at.dist ContDiffWithinAt.dist
theorem ContDiffOn.norm_sq (hf : ContDiffOn ℝ n f s) : ContDiffOn ℝ n (fun y => ‖f y‖ ^ 2) s :=
fun x hx => (hf x hx).norm_sq 𝕜
#align cont_diff_on.norm_sq ContDiffOn.norm_sq
theorem ContDiffOn.norm (hf : ContDiffOn ℝ n f s) (h0 : ∀ x ∈ s, f x ≠ 0) :
ContDiffOn ℝ n (fun y => ‖f y‖) s := fun x hx => (hf x hx).norm 𝕜 (h0 x hx)
#align cont_diff_on.norm ContDiffOn.norm
theorem ContDiffOn.dist (hf : ContDiffOn ℝ n f s) (hg : ContDiffOn ℝ n g s)
(hne : ∀ x ∈ s, f x ≠ g x) : ContDiffOn ℝ n (fun y => dist (f y) (g y)) s := fun x hx =>
(hf x hx).dist 𝕜 (hg x hx) (hne x hx)
#align cont_diff_on.dist ContDiffOn.dist
theorem ContDiff.norm (hf : ContDiff ℝ n f) (h0 : ∀ x, f x ≠ 0) : ContDiff ℝ n fun y => ‖f y‖ :=
contDiff_iff_contDiffAt.2 fun x => hf.contDiffAt.norm 𝕜 (h0 x)
#align cont_diff.norm ContDiff.norm
theorem ContDiff.dist (hf : ContDiff ℝ n f) (hg : ContDiff ℝ n g) (hne : ∀ x, f x ≠ g x) :
ContDiff ℝ n fun y => dist (f y) (g y) :=
contDiff_iff_contDiffAt.2 fun x => hf.contDiffAt.dist 𝕜 hg.contDiffAt (hne x)
#align cont_diff.dist ContDiff.dist
-- Porting note: use `2 •` instead of `bit0`
| Mathlib/Analysis/InnerProductSpace/Calculus.lean | 218 | 223 | theorem hasStrictFDerivAt_norm_sq (x : F) :
HasStrictFDerivAt (fun x => ‖x‖ ^ 2) (2 • (innerSL ℝ x)) x := by |
simp only [sq, ← @inner_self_eq_norm_mul_norm ℝ]
convert (hasStrictFDerivAt_id x).inner ℝ (hasStrictFDerivAt_id x)
ext y
simp [two_smul, real_inner_comm]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.MeasureTheory.Function.SimpleFunc
import Mathlib.MeasureTheory.Measure.MutuallySingular
import Mathlib.MeasureTheory.Measure.Count
import Mathlib.Topology.IndicatorConstPointwise
import Mathlib.MeasureTheory.Constructions.BorelSpace.Real
#align_import measure_theory.integral.lebesgue from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Lower Lebesgue integral for `ℝ≥0∞`-valued functions
We define the lower Lebesgue integral of an `ℝ≥0∞`-valued function.
## Notation
We introduce the following notation for the lower Lebesgue integral of a function `f : α → ℝ≥0∞`.
* `∫⁻ x, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` with respect to a measure `μ`;
* `∫⁻ x, f x`: integral of a function `f : α → ℝ≥0∞` with respect to the canonical measure
`volume` on `α`;
* `∫⁻ x in s, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect
to a measure `μ`, defined as `∫⁻ x, f x ∂(μ.restrict s)`;
* `∫⁻ x in s, f x`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect
to the canonical measure `volume`, defined as `∫⁻ x, f x ∂(volume.restrict s)`.
-/
assert_not_exists NormedSpace
set_option autoImplicit true
noncomputable section
open Set hiding restrict restrict_apply
open Filter ENNReal
open Function (support)
open scoped Classical
open Topology NNReal ENNReal MeasureTheory
namespace MeasureTheory
local infixr:25 " →ₛ " => SimpleFunc
variable {α β γ δ : Type*}
section Lintegral
open SimpleFunc
variable {m : MeasurableSpace α} {μ ν : Measure α}
/-- The **lower Lebesgue integral** of a function `f` with respect to a measure `μ`. -/
irreducible_def lintegral {_ : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) : ℝ≥0∞ :=
⨆ (g : α →ₛ ℝ≥0∞) (_ : ⇑g ≤ f), g.lintegral μ
#align measure_theory.lintegral MeasureTheory.lintegral
/-! In the notation for integrals, an expression like `∫⁻ x, g ‖x‖ ∂μ` will not be parsed correctly,
and needs parentheses. We do not set the binding power of `r` to `0`, because then
`∫⁻ x, f x = 0` will be parsed incorrectly. -/
@[inherit_doc MeasureTheory.lintegral]
notation3 "∫⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => lintegral μ r
@[inherit_doc MeasureTheory.lintegral]
notation3 "∫⁻ "(...)", "r:60:(scoped f => lintegral volume f) => r
@[inherit_doc MeasureTheory.lintegral]
notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => lintegral (Measure.restrict μ s) r
@[inherit_doc MeasureTheory.lintegral]
notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => lintegral (Measure.restrict volume s) f) => r
theorem SimpleFunc.lintegral_eq_lintegral {m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (μ : Measure α) :
∫⁻ a, f a ∂μ = f.lintegral μ := by
rw [MeasureTheory.lintegral]
exact le_antisymm (iSup₂_le fun g hg => lintegral_mono hg <| le_rfl)
(le_iSup₂_of_le f le_rfl le_rfl)
#align measure_theory.simple_func.lintegral_eq_lintegral MeasureTheory.SimpleFunc.lintegral_eq_lintegral
@[mono]
theorem lintegral_mono' {m : MeasurableSpace α} ⦃μ ν : Measure α⦄ (hμν : μ ≤ ν) ⦃f g : α → ℝ≥0∞⦄
(hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂ν := by
rw [lintegral, lintegral]
exact iSup_mono fun φ => iSup_mono' fun hφ => ⟨le_trans hφ hfg, lintegral_mono (le_refl φ) hμν⟩
#align measure_theory.lintegral_mono' MeasureTheory.lintegral_mono'
-- workaround for the known eta-reduction issue with `@[gcongr]`
@[gcongr] theorem lintegral_mono_fn' ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) (h2 : μ ≤ ν) :
lintegral μ f ≤ lintegral ν g :=
lintegral_mono' h2 hfg
theorem lintegral_mono ⦃f g : α → ℝ≥0∞⦄ (hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ :=
lintegral_mono' (le_refl μ) hfg
#align measure_theory.lintegral_mono MeasureTheory.lintegral_mono
-- workaround for the known eta-reduction issue with `@[gcongr]`
@[gcongr] theorem lintegral_mono_fn ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) :
lintegral μ f ≤ lintegral μ g :=
lintegral_mono hfg
theorem lintegral_mono_nnreal {f g : α → ℝ≥0} (h : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ :=
lintegral_mono fun a => ENNReal.coe_le_coe.2 (h a)
#align measure_theory.lintegral_mono_nnreal MeasureTheory.lintegral_mono_nnreal
theorem iSup_lintegral_measurable_le_eq_lintegral (f : α → ℝ≥0∞) :
⨆ (g : α → ℝ≥0∞) (_ : Measurable g) (_ : g ≤ f), ∫⁻ a, g a ∂μ = ∫⁻ a, f a ∂μ := by
apply le_antisymm
· exact iSup_le fun i => iSup_le fun _ => iSup_le fun h'i => lintegral_mono h'i
· rw [lintegral]
refine iSup₂_le fun i hi => le_iSup₂_of_le i i.measurable <| le_iSup_of_le hi ?_
exact le_of_eq (i.lintegral_eq_lintegral _).symm
#align measure_theory.supr_lintegral_measurable_le_eq_lintegral MeasureTheory.iSup_lintegral_measurable_le_eq_lintegral
theorem lintegral_mono_set {_ : MeasurableSpace α} ⦃μ : Measure α⦄ {s t : Set α} {f : α → ℝ≥0∞}
(hst : s ⊆ t) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in t, f x ∂μ :=
lintegral_mono' (Measure.restrict_mono hst (le_refl μ)) (le_refl f)
#align measure_theory.lintegral_mono_set MeasureTheory.lintegral_mono_set
theorem lintegral_mono_set' {_ : MeasurableSpace α} ⦃μ : Measure α⦄ {s t : Set α} {f : α → ℝ≥0∞}
(hst : s ≤ᵐ[μ] t) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in t, f x ∂μ :=
lintegral_mono' (Measure.restrict_mono' hst (le_refl μ)) (le_refl f)
#align measure_theory.lintegral_mono_set' MeasureTheory.lintegral_mono_set'
theorem monotone_lintegral {_ : MeasurableSpace α} (μ : Measure α) : Monotone (lintegral μ) :=
lintegral_mono
#align measure_theory.monotone_lintegral MeasureTheory.monotone_lintegral
@[simp]
theorem lintegral_const (c : ℝ≥0∞) : ∫⁻ _, c ∂μ = c * μ univ := by
rw [← SimpleFunc.const_lintegral, ← SimpleFunc.lintegral_eq_lintegral, SimpleFunc.coe_const]
rfl
#align measure_theory.lintegral_const MeasureTheory.lintegral_const
theorem lintegral_zero : ∫⁻ _ : α, 0 ∂μ = 0 := by simp
#align measure_theory.lintegral_zero MeasureTheory.lintegral_zero
theorem lintegral_zero_fun : lintegral μ (0 : α → ℝ≥0∞) = 0 :=
lintegral_zero
#align measure_theory.lintegral_zero_fun MeasureTheory.lintegral_zero_fun
-- @[simp] -- Porting note (#10618): simp can prove this
theorem lintegral_one : ∫⁻ _, (1 : ℝ≥0∞) ∂μ = μ univ := by rw [lintegral_const, one_mul]
#align measure_theory.lintegral_one MeasureTheory.lintegral_one
theorem set_lintegral_const (s : Set α) (c : ℝ≥0∞) : ∫⁻ _ in s, c ∂μ = c * μ s := by
rw [lintegral_const, Measure.restrict_apply_univ]
#align measure_theory.set_lintegral_const MeasureTheory.set_lintegral_const
theorem set_lintegral_one (s) : ∫⁻ _ in s, 1 ∂μ = μ s := by rw [set_lintegral_const, one_mul]
#align measure_theory.set_lintegral_one MeasureTheory.set_lintegral_one
theorem set_lintegral_const_lt_top [IsFiniteMeasure μ] (s : Set α) {c : ℝ≥0∞} (hc : c ≠ ∞) :
∫⁻ _ in s, c ∂μ < ∞ := by
rw [lintegral_const]
exact ENNReal.mul_lt_top hc (measure_ne_top (μ.restrict s) univ)
#align measure_theory.set_lintegral_const_lt_top MeasureTheory.set_lintegral_const_lt_top
theorem lintegral_const_lt_top [IsFiniteMeasure μ] {c : ℝ≥0∞} (hc : c ≠ ∞) : ∫⁻ _, c ∂μ < ∞ := by
simpa only [Measure.restrict_univ] using set_lintegral_const_lt_top (univ : Set α) hc
#align measure_theory.lintegral_const_lt_top MeasureTheory.lintegral_const_lt_top
section
variable (μ)
/-- For any function `f : α → ℝ≥0∞`, there exists a measurable function `g ≤ f` with the same
integral. -/
theorem exists_measurable_le_lintegral_eq (f : α → ℝ≥0∞) :
∃ g : α → ℝ≥0∞, Measurable g ∧ g ≤ f ∧ ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ := by
rcases eq_or_ne (∫⁻ a, f a ∂μ) 0 with h₀ | h₀
· exact ⟨0, measurable_zero, zero_le f, h₀.trans lintegral_zero.symm⟩
rcases exists_seq_strictMono_tendsto' h₀.bot_lt with ⟨L, _, hLf, hL_tendsto⟩
have : ∀ n, ∃ g : α → ℝ≥0∞, Measurable g ∧ g ≤ f ∧ L n < ∫⁻ a, g a ∂μ := by
intro n
simpa only [← iSup_lintegral_measurable_le_eq_lintegral f, lt_iSup_iff, exists_prop] using
(hLf n).2
choose g hgm hgf hLg using this
refine
⟨fun x => ⨆ n, g n x, measurable_iSup hgm, fun x => iSup_le fun n => hgf n x, le_antisymm ?_ ?_⟩
· refine le_of_tendsto' hL_tendsto fun n => (hLg n).le.trans <| lintegral_mono fun x => ?_
exact le_iSup (fun n => g n x) n
· exact lintegral_mono fun x => iSup_le fun n => hgf n x
#align measure_theory.exists_measurable_le_lintegral_eq MeasureTheory.exists_measurable_le_lintegral_eq
end
/-- `∫⁻ a in s, f a ∂μ` is defined as the supremum of integrals of simple functions
`φ : α →ₛ ℝ≥0∞` such that `φ ≤ f`. This lemma says that it suffices to take
functions `φ : α →ₛ ℝ≥0`. -/
theorem lintegral_eq_nnreal {m : MeasurableSpace α} (f : α → ℝ≥0∞) (μ : Measure α) :
∫⁻ a, f a ∂μ =
⨆ (φ : α →ₛ ℝ≥0) (_ : ∀ x, ↑(φ x) ≤ f x), (φ.map ((↑) : ℝ≥0 → ℝ≥0∞)).lintegral μ := by
rw [lintegral]
refine
le_antisymm (iSup₂_le fun φ hφ => ?_) (iSup_mono' fun φ => ⟨φ.map ((↑) : ℝ≥0 → ℝ≥0∞), le_rfl⟩)
by_cases h : ∀ᵐ a ∂μ, φ a ≠ ∞
· let ψ := φ.map ENNReal.toNNReal
replace h : ψ.map ((↑) : ℝ≥0 → ℝ≥0∞) =ᵐ[μ] φ := h.mono fun a => ENNReal.coe_toNNReal
have : ∀ x, ↑(ψ x) ≤ f x := fun x => le_trans ENNReal.coe_toNNReal_le_self (hφ x)
exact
le_iSup_of_le (φ.map ENNReal.toNNReal) (le_iSup_of_le this (ge_of_eq <| lintegral_congr h))
· have h_meas : μ (φ ⁻¹' {∞}) ≠ 0 := mt measure_zero_iff_ae_nmem.1 h
refine le_trans le_top (ge_of_eq <| (iSup_eq_top _).2 fun b hb => ?_)
obtain ⟨n, hn⟩ : ∃ n : ℕ, b < n * μ (φ ⁻¹' {∞}) := exists_nat_mul_gt h_meas (ne_of_lt hb)
use (const α (n : ℝ≥0)).restrict (φ ⁻¹' {∞})
simp only [lt_iSup_iff, exists_prop, coe_restrict, φ.measurableSet_preimage, coe_const,
ENNReal.coe_indicator, map_coe_ennreal_restrict, SimpleFunc.map_const, ENNReal.coe_natCast,
restrict_const_lintegral]
refine ⟨indicator_le fun x hx => le_trans ?_ (hφ _), hn⟩
simp only [mem_preimage, mem_singleton_iff] at hx
simp only [hx, le_top]
#align measure_theory.lintegral_eq_nnreal MeasureTheory.lintegral_eq_nnreal
theorem exists_simpleFunc_forall_lintegral_sub_lt_of_pos {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞)
{ε : ℝ≥0∞} (hε : ε ≠ 0) :
∃ φ : α →ₛ ℝ≥0,
(∀ x, ↑(φ x) ≤ f x) ∧
∀ ψ : α →ₛ ℝ≥0, (∀ x, ↑(ψ x) ≤ f x) → (map (↑) (ψ - φ)).lintegral μ < ε := by
rw [lintegral_eq_nnreal] at h
have := ENNReal.lt_add_right h hε
erw [ENNReal.biSup_add] at this <;> [skip; exact ⟨0, fun x => zero_le _⟩]
simp_rw [lt_iSup_iff, iSup_lt_iff, iSup_le_iff] at this
rcases this with ⟨φ, hle : ∀ x, ↑(φ x) ≤ f x, b, hbφ, hb⟩
refine ⟨φ, hle, fun ψ hψ => ?_⟩
have : (map (↑) φ).lintegral μ ≠ ∞ := ne_top_of_le_ne_top h (by exact le_iSup₂ (α := ℝ≥0∞) φ hle)
rw [← ENNReal.add_lt_add_iff_left this, ← add_lintegral, ← SimpleFunc.map_add @ENNReal.coe_add]
refine (hb _ fun x => le_trans ?_ (max_le (hle x) (hψ x))).trans_lt hbφ
norm_cast
simp only [add_apply, sub_apply, add_tsub_eq_max]
rfl
#align measure_theory.exists_simple_func_forall_lintegral_sub_lt_of_pos MeasureTheory.exists_simpleFunc_forall_lintegral_sub_lt_of_pos
theorem iSup_lintegral_le {ι : Sort*} (f : ι → α → ℝ≥0∞) :
⨆ i, ∫⁻ a, f i a ∂μ ≤ ∫⁻ a, ⨆ i, f i a ∂μ := by
simp only [← iSup_apply]
exact (monotone_lintegral μ).le_map_iSup
#align measure_theory.supr_lintegral_le MeasureTheory.iSup_lintegral_le
theorem iSup₂_lintegral_le {ι : Sort*} {ι' : ι → Sort*} (f : ∀ i, ι' i → α → ℝ≥0∞) :
⨆ (i) (j), ∫⁻ a, f i j a ∂μ ≤ ∫⁻ a, ⨆ (i) (j), f i j a ∂μ := by
convert (monotone_lintegral μ).le_map_iSup₂ f with a
simp only [iSup_apply]
#align measure_theory.supr₂_lintegral_le MeasureTheory.iSup₂_lintegral_le
theorem le_iInf_lintegral {ι : Sort*} (f : ι → α → ℝ≥0∞) :
∫⁻ a, ⨅ i, f i a ∂μ ≤ ⨅ i, ∫⁻ a, f i a ∂μ := by
simp only [← iInf_apply]
exact (monotone_lintegral μ).map_iInf_le
#align measure_theory.le_infi_lintegral MeasureTheory.le_iInf_lintegral
theorem le_iInf₂_lintegral {ι : Sort*} {ι' : ι → Sort*} (f : ∀ i, ι' i → α → ℝ≥0∞) :
∫⁻ a, ⨅ (i) (h : ι' i), f i h a ∂μ ≤ ⨅ (i) (h : ι' i), ∫⁻ a, f i h a ∂μ := by
convert (monotone_lintegral μ).map_iInf₂_le f with a
simp only [iInf_apply]
#align measure_theory.le_infi₂_lintegral MeasureTheory.le_iInf₂_lintegral
theorem lintegral_mono_ae {f g : α → ℝ≥0∞} (h : ∀ᵐ a ∂μ, f a ≤ g a) :
∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ := by
rcases exists_measurable_superset_of_null h with ⟨t, hts, ht, ht0⟩
have : ∀ᵐ x ∂μ, x ∉ t := measure_zero_iff_ae_nmem.1 ht0
rw [lintegral, lintegral]
refine iSup_le fun s => iSup_le fun hfs => le_iSup_of_le (s.restrict tᶜ) <| le_iSup_of_le ?_ ?_
· intro a
by_cases h : a ∈ t <;>
simp only [restrict_apply s ht.compl, mem_compl_iff, h, not_true, not_false_eq_true,
indicator_of_not_mem, zero_le, not_false_eq_true, indicator_of_mem]
exact le_trans (hfs a) (_root_.by_contradiction fun hnfg => h (hts hnfg))
· refine le_of_eq (SimpleFunc.lintegral_congr <| this.mono fun a hnt => ?_)
by_cases hat : a ∈ t <;> simp only [restrict_apply s ht.compl, mem_compl_iff, hat, not_true,
not_false_eq_true, indicator_of_not_mem, not_false_eq_true, indicator_of_mem]
exact (hnt hat).elim
#align measure_theory.lintegral_mono_ae MeasureTheory.lintegral_mono_ae
theorem set_lintegral_mono_ae {s : Set α} {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
lintegral_mono_ae <| (ae_restrict_iff <| measurableSet_le hf hg).2 hfg
#align measure_theory.set_lintegral_mono_ae MeasureTheory.set_lintegral_mono_ae
theorem set_lintegral_mono {s : Set α} {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g)
(hfg : ∀ x ∈ s, f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
set_lintegral_mono_ae hf hg (ae_of_all _ hfg)
#align measure_theory.set_lintegral_mono MeasureTheory.set_lintegral_mono
theorem set_lintegral_mono_ae' {s : Set α} {f g : α → ℝ≥0∞} (hs : MeasurableSet s)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
lintegral_mono_ae <| (ae_restrict_iff' hs).2 hfg
theorem set_lintegral_mono' {s : Set α} {f g : α → ℝ≥0∞} (hs : MeasurableSet s)
(hfg : ∀ x ∈ s, f x ≤ g x) : ∫⁻ x in s, f x ∂μ ≤ ∫⁻ x in s, g x ∂μ :=
set_lintegral_mono_ae' hs (ae_of_all _ hfg)
theorem set_lintegral_le_lintegral (s : Set α) (f : α → ℝ≥0∞) :
∫⁻ x in s, f x ∂μ ≤ ∫⁻ x, f x ∂μ :=
lintegral_mono' Measure.restrict_le_self le_rfl
theorem lintegral_congr_ae {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ :=
le_antisymm (lintegral_mono_ae <| h.le) (lintegral_mono_ae <| h.symm.le)
#align measure_theory.lintegral_congr_ae MeasureTheory.lintegral_congr_ae
theorem lintegral_congr {f g : α → ℝ≥0∞} (h : ∀ a, f a = g a) : ∫⁻ a, f a ∂μ = ∫⁻ a, g a ∂μ := by
simp only [h]
#align measure_theory.lintegral_congr MeasureTheory.lintegral_congr
theorem set_lintegral_congr {f : α → ℝ≥0∞} {s t : Set α} (h : s =ᵐ[μ] t) :
∫⁻ x in s, f x ∂μ = ∫⁻ x in t, f x ∂μ := by rw [Measure.restrict_congr_set h]
#align measure_theory.set_lintegral_congr MeasureTheory.set_lintegral_congr
theorem set_lintegral_congr_fun {f g : α → ℝ≥0∞} {s : Set α} (hs : MeasurableSet s)
(hfg : ∀ᵐ x ∂μ, x ∈ s → f x = g x) : ∫⁻ x in s, f x ∂μ = ∫⁻ x in s, g x ∂μ := by
rw [lintegral_congr_ae]
rw [EventuallyEq]
rwa [ae_restrict_iff' hs]
#align measure_theory.set_lintegral_congr_fun MeasureTheory.set_lintegral_congr_fun
theorem lintegral_ofReal_le_lintegral_nnnorm (f : α → ℝ) :
∫⁻ x, ENNReal.ofReal (f x) ∂μ ≤ ∫⁻ x, ‖f x‖₊ ∂μ := by
simp_rw [← ofReal_norm_eq_coe_nnnorm]
refine lintegral_mono fun x => ENNReal.ofReal_le_ofReal ?_
rw [Real.norm_eq_abs]
exact le_abs_self (f x)
#align measure_theory.lintegral_of_real_le_lintegral_nnnorm MeasureTheory.lintegral_ofReal_le_lintegral_nnnorm
theorem lintegral_nnnorm_eq_of_ae_nonneg {f : α → ℝ} (h_nonneg : 0 ≤ᵐ[μ] f) :
∫⁻ x, ‖f x‖₊ ∂μ = ∫⁻ x, ENNReal.ofReal (f x) ∂μ := by
apply lintegral_congr_ae
filter_upwards [h_nonneg] with x hx
rw [Real.nnnorm_of_nonneg hx, ENNReal.ofReal_eq_coe_nnreal hx]
#align measure_theory.lintegral_nnnorm_eq_of_ae_nonneg MeasureTheory.lintegral_nnnorm_eq_of_ae_nonneg
theorem lintegral_nnnorm_eq_of_nonneg {f : α → ℝ} (h_nonneg : 0 ≤ f) :
∫⁻ x, ‖f x‖₊ ∂μ = ∫⁻ x, ENNReal.ofReal (f x) ∂μ :=
lintegral_nnnorm_eq_of_ae_nonneg (Filter.eventually_of_forall h_nonneg)
#align measure_theory.lintegral_nnnorm_eq_of_nonneg MeasureTheory.lintegral_nnnorm_eq_of_nonneg
/-- **Monotone convergence theorem** -- sometimes called **Beppo-Levi convergence**.
See `lintegral_iSup_directed` for a more general form. -/
theorem lintegral_iSup {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, Measurable (f n)) (h_mono : Monotone f) :
∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
set c : ℝ≥0 → ℝ≥0∞ := (↑)
set F := fun a : α => ⨆ n, f n a
refine le_antisymm ?_ (iSup_lintegral_le _)
rw [lintegral_eq_nnreal]
refine iSup_le fun s => iSup_le fun hsf => ?_
refine ENNReal.le_of_forall_lt_one_mul_le fun a ha => ?_
rcases ENNReal.lt_iff_exists_coe.1 ha with ⟨r, rfl, _⟩
have ha : r < 1 := ENNReal.coe_lt_coe.1 ha
let rs := s.map fun a => r * a
have eq_rs : rs.map c = (const α r : α →ₛ ℝ≥0∞) * map c s := rfl
have eq : ∀ p, rs.map c ⁻¹' {p} = ⋃ n, rs.map c ⁻¹' {p} ∩ { a | p ≤ f n a } := by
intro p
rw [← inter_iUnion]; nth_rw 1 [← inter_univ (map c rs ⁻¹' {p})]
refine Set.ext fun x => and_congr_right fun hx => true_iff_iff.2 ?_
by_cases p_eq : p = 0
· simp [p_eq]
simp only [coe_map, mem_preimage, Function.comp_apply, mem_singleton_iff] at hx
subst hx
have : r * s x ≠ 0 := by rwa [Ne, ← ENNReal.coe_eq_zero]
have : s x ≠ 0 := right_ne_zero_of_mul this
have : (rs.map c) x < ⨆ n : ℕ, f n x := by
refine lt_of_lt_of_le (ENNReal.coe_lt_coe.2 ?_) (hsf x)
suffices r * s x < 1 * s x by simpa
exact mul_lt_mul_of_pos_right ha (pos_iff_ne_zero.2 this)
rcases lt_iSup_iff.1 this with ⟨i, hi⟩
exact mem_iUnion.2 ⟨i, le_of_lt hi⟩
have mono : ∀ r : ℝ≥0∞, Monotone fun n => rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a } := by
intro r i j h
refine inter_subset_inter_right _ ?_
simp_rw [subset_def, mem_setOf]
intro x hx
exact le_trans hx (h_mono h x)
have h_meas : ∀ n, MeasurableSet {a : α | map c rs a ≤ f n a} := fun n =>
measurableSet_le (SimpleFunc.measurable _) (hf n)
calc
(r : ℝ≥0∞) * (s.map c).lintegral μ = ∑ r ∈ (rs.map c).range, r * μ (rs.map c ⁻¹' {r}) := by
rw [← const_mul_lintegral, eq_rs, SimpleFunc.lintegral]
_ = ∑ r ∈ (rs.map c).range, r * μ (⋃ n, rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) := by
simp only [(eq _).symm]
_ = ∑ r ∈ (rs.map c).range, ⨆ n, r * μ (rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) :=
(Finset.sum_congr rfl fun x _ => by
rw [measure_iUnion_eq_iSup (mono x).directed_le, ENNReal.mul_iSup])
_ = ⨆ n, ∑ r ∈ (rs.map c).range, r * μ (rs.map c ⁻¹' {r} ∩ { a | r ≤ f n a }) := by
refine ENNReal.finset_sum_iSup_nat fun p i j h ↦ ?_
gcongr _ * μ ?_
exact mono p h
_ ≤ ⨆ n : ℕ, ((rs.map c).restrict { a | (rs.map c) a ≤ f n a }).lintegral μ := by
gcongr with n
rw [restrict_lintegral _ (h_meas n)]
refine le_of_eq (Finset.sum_congr rfl fun r _ => ?_)
congr 2 with a
refine and_congr_right ?_
simp (config := { contextual := true })
_ ≤ ⨆ n, ∫⁻ a, f n a ∂μ := by
simp only [← SimpleFunc.lintegral_eq_lintegral]
gcongr with n a
simp only [map_apply] at h_meas
simp only [coe_map, restrict_apply _ (h_meas _), (· ∘ ·)]
exact indicator_apply_le id
#align measure_theory.lintegral_supr MeasureTheory.lintegral_iSup
/-- Monotone convergence theorem -- sometimes called Beppo-Levi convergence. Version with
ae_measurable functions. -/
theorem lintegral_iSup' {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, AEMeasurable (f n) μ)
(h_mono : ∀ᵐ x ∂μ, Monotone fun n => f n x) : ∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
simp_rw [← iSup_apply]
let p : α → (ℕ → ℝ≥0∞) → Prop := fun _ f' => Monotone f'
have hp : ∀ᵐ x ∂μ, p x fun i => f i x := h_mono
have h_ae_seq_mono : Monotone (aeSeq hf p) := by
intro n m hnm x
by_cases hx : x ∈ aeSeqSet hf p
· exact aeSeq.prop_of_mem_aeSeqSet hf hx hnm
· simp only [aeSeq, hx, if_false, le_rfl]
rw [lintegral_congr_ae (aeSeq.iSup hf hp).symm]
simp_rw [iSup_apply]
rw [lintegral_iSup (aeSeq.measurable hf p) h_ae_seq_mono]
congr with n
exact lintegral_congr_ae (aeSeq.aeSeq_n_eq_fun_n_ae hf hp n)
#align measure_theory.lintegral_supr' MeasureTheory.lintegral_iSup'
/-- Monotone convergence theorem expressed with limits -/
theorem lintegral_tendsto_of_tendsto_of_monotone {f : ℕ → α → ℝ≥0∞} {F : α → ℝ≥0∞}
(hf : ∀ n, AEMeasurable (f n) μ) (h_mono : ∀ᵐ x ∂μ, Monotone fun n => f n x)
(h_tendsto : ∀ᵐ x ∂μ, Tendsto (fun n => f n x) atTop (𝓝 <| F x)) :
Tendsto (fun n => ∫⁻ x, f n x ∂μ) atTop (𝓝 <| ∫⁻ x, F x ∂μ) := by
have : Monotone fun n => ∫⁻ x, f n x ∂μ := fun i j hij =>
lintegral_mono_ae (h_mono.mono fun x hx => hx hij)
suffices key : ∫⁻ x, F x ∂μ = ⨆ n, ∫⁻ x, f n x ∂μ by
rw [key]
exact tendsto_atTop_iSup this
rw [← lintegral_iSup' hf h_mono]
refine lintegral_congr_ae ?_
filter_upwards [h_mono, h_tendsto] with _ hx_mono hx_tendsto using
tendsto_nhds_unique hx_tendsto (tendsto_atTop_iSup hx_mono)
#align measure_theory.lintegral_tendsto_of_tendsto_of_monotone MeasureTheory.lintegral_tendsto_of_tendsto_of_monotone
theorem lintegral_eq_iSup_eapprox_lintegral {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, f a ∂μ = ⨆ n, (eapprox f n).lintegral μ :=
calc
∫⁻ a, f a ∂μ = ∫⁻ a, ⨆ n, (eapprox f n : α → ℝ≥0∞) a ∂μ := by
congr; ext a; rw [iSup_eapprox_apply f hf]
_ = ⨆ n, ∫⁻ a, (eapprox f n : α → ℝ≥0∞) a ∂μ := by
apply lintegral_iSup
· measurability
· intro i j h
exact monotone_eapprox f h
_ = ⨆ n, (eapprox f n).lintegral μ := by
congr; ext n; rw [(eapprox f n).lintegral_eq_lintegral]
#align measure_theory.lintegral_eq_supr_eapprox_lintegral MeasureTheory.lintegral_eq_iSup_eapprox_lintegral
/-- If `f` has finite integral, then `∫⁻ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. This lemma states this fact in terms of `ε` and `δ`. -/
theorem exists_pos_set_lintegral_lt_of_measure_lt {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞) {ε : ℝ≥0∞}
(hε : ε ≠ 0) : ∃ δ > 0, ∀ s, μ s < δ → ∫⁻ x in s, f x ∂μ < ε := by
rcases exists_between (pos_iff_ne_zero.mpr hε) with ⟨ε₂, hε₂0, hε₂ε⟩
rcases exists_between hε₂0 with ⟨ε₁, hε₁0, hε₁₂⟩
rcases exists_simpleFunc_forall_lintegral_sub_lt_of_pos h hε₁0.ne' with ⟨φ, _, hφ⟩
rcases φ.exists_forall_le with ⟨C, hC⟩
use (ε₂ - ε₁) / C, ENNReal.div_pos_iff.2 ⟨(tsub_pos_iff_lt.2 hε₁₂).ne', ENNReal.coe_ne_top⟩
refine fun s hs => lt_of_le_of_lt ?_ hε₂ε
simp only [lintegral_eq_nnreal, iSup_le_iff]
intro ψ hψ
calc
(map (↑) ψ).lintegral (μ.restrict s) ≤
(map (↑) φ).lintegral (μ.restrict s) + (map (↑) (ψ - φ)).lintegral (μ.restrict s) := by
rw [← SimpleFunc.add_lintegral, ← SimpleFunc.map_add @ENNReal.coe_add]
refine SimpleFunc.lintegral_mono (fun x => ?_) le_rfl
simp only [add_tsub_eq_max, le_max_right, coe_map, Function.comp_apply, SimpleFunc.coe_add,
SimpleFunc.coe_sub, Pi.add_apply, Pi.sub_apply, ENNReal.coe_max (φ x) (ψ x)]
_ ≤ (map (↑) φ).lintegral (μ.restrict s) + ε₁ := by
gcongr
refine le_trans ?_ (hφ _ hψ).le
exact SimpleFunc.lintegral_mono le_rfl Measure.restrict_le_self
_ ≤ (SimpleFunc.const α (C : ℝ≥0∞)).lintegral (μ.restrict s) + ε₁ := by
gcongr
exact SimpleFunc.lintegral_mono (fun x ↦ ENNReal.coe_le_coe.2 (hC x)) le_rfl
_ = C * μ s + ε₁ := by
simp only [← SimpleFunc.lintegral_eq_lintegral, coe_const, lintegral_const,
Measure.restrict_apply, MeasurableSet.univ, univ_inter, Function.const]
_ ≤ C * ((ε₂ - ε₁) / C) + ε₁ := by gcongr
_ ≤ ε₂ - ε₁ + ε₁ := by gcongr; apply mul_div_le
_ = ε₂ := tsub_add_cancel_of_le hε₁₂.le
#align measure_theory.exists_pos_set_lintegral_lt_of_measure_lt MeasureTheory.exists_pos_set_lintegral_lt_of_measure_lt
/-- If `f` has finite integral, then `∫⁻ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. -/
theorem tendsto_set_lintegral_zero {ι} {f : α → ℝ≥0∞} (h : ∫⁻ x, f x ∂μ ≠ ∞) {l : Filter ι}
{s : ι → Set α} (hl : Tendsto (μ ∘ s) l (𝓝 0)) :
Tendsto (fun i => ∫⁻ x in s i, f x ∂μ) l (𝓝 0) := by
simp only [ENNReal.nhds_zero, tendsto_iInf, tendsto_principal, mem_Iio,
← pos_iff_ne_zero] at hl ⊢
intro ε ε0
rcases exists_pos_set_lintegral_lt_of_measure_lt h ε0.ne' with ⟨δ, δ0, hδ⟩
exact (hl δ δ0).mono fun i => hδ _
#align measure_theory.tendsto_set_lintegral_zero MeasureTheory.tendsto_set_lintegral_zero
/-- The sum of the lower Lebesgue integrals of two functions is less than or equal to the integral
of their sum. The other inequality needs one of these functions to be (a.e.-)measurable. -/
theorem le_lintegral_add (f g : α → ℝ≥0∞) :
∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ ≤ ∫⁻ a, f a + g a ∂μ := by
simp only [lintegral]
refine ENNReal.biSup_add_biSup_le' (p := fun h : α →ₛ ℝ≥0∞ => h ≤ f)
(q := fun h : α →ₛ ℝ≥0∞ => h ≤ g) ⟨0, zero_le f⟩ ⟨0, zero_le g⟩ fun f' hf' g' hg' => ?_
exact le_iSup₂_of_le (f' + g') (add_le_add hf' hg') (add_lintegral _ _).ge
#align measure_theory.le_lintegral_add MeasureTheory.le_lintegral_add
-- Use stronger lemmas `lintegral_add_left`/`lintegral_add_right` instead
theorem lintegral_add_aux {f g : α → ℝ≥0∞} (hf : Measurable f) (hg : Measurable g) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
calc
∫⁻ a, f a + g a ∂μ =
∫⁻ a, (⨆ n, (eapprox f n : α → ℝ≥0∞) a) + ⨆ n, (eapprox g n : α → ℝ≥0∞) a ∂μ := by
simp only [iSup_eapprox_apply, hf, hg]
_ = ∫⁻ a, ⨆ n, (eapprox f n + eapprox g n : α → ℝ≥0∞) a ∂μ := by
congr; funext a
rw [ENNReal.iSup_add_iSup_of_monotone]
· simp only [Pi.add_apply]
· intro i j h
exact monotone_eapprox _ h a
· intro i j h
exact monotone_eapprox _ h a
_ = ⨆ n, (eapprox f n).lintegral μ + (eapprox g n).lintegral μ := by
rw [lintegral_iSup]
· congr
funext n
rw [← SimpleFunc.add_lintegral, ← SimpleFunc.lintegral_eq_lintegral]
simp only [Pi.add_apply, SimpleFunc.coe_add]
· measurability
· intro i j h a
dsimp
gcongr <;> exact monotone_eapprox _ h _
_ = (⨆ n, (eapprox f n).lintegral μ) + ⨆ n, (eapprox g n).lintegral μ := by
refine (ENNReal.iSup_add_iSup_of_monotone ?_ ?_).symm <;>
· intro i j h
exact SimpleFunc.lintegral_mono (monotone_eapprox _ h) le_rfl
_ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
rw [lintegral_eq_iSup_eapprox_lintegral hf, lintegral_eq_iSup_eapprox_lintegral hg]
#align measure_theory.lintegral_add_aux MeasureTheory.lintegral_add_aux
/-- If `f g : α → ℝ≥0∞` are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of `f + g` equals the sum of integrals. This lemma assumes that `f` is integrable, see also
`MeasureTheory.lintegral_add_right` and primed versions of these lemmas. -/
@[simp]
theorem lintegral_add_left {f : α → ℝ≥0∞} (hf : Measurable f) (g : α → ℝ≥0∞) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
refine le_antisymm ?_ (le_lintegral_add _ _)
rcases exists_measurable_le_lintegral_eq μ fun a => f a + g a with ⟨φ, hφm, hφ_le, hφ_eq⟩
calc
∫⁻ a, f a + g a ∂μ = ∫⁻ a, φ a ∂μ := hφ_eq
_ ≤ ∫⁻ a, f a + (φ a - f a) ∂μ := lintegral_mono fun a => le_add_tsub
_ = ∫⁻ a, f a ∂μ + ∫⁻ a, φ a - f a ∂μ := lintegral_add_aux hf (hφm.sub hf)
_ ≤ ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
add_le_add_left (lintegral_mono fun a => tsub_le_iff_left.2 <| hφ_le a) _
#align measure_theory.lintegral_add_left MeasureTheory.lintegral_add_left
theorem lintegral_add_left' {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (g : α → ℝ≥0∞) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
rw [lintegral_congr_ae hf.ae_eq_mk, ← lintegral_add_left hf.measurable_mk,
lintegral_congr_ae (hf.ae_eq_mk.add (ae_eq_refl g))]
#align measure_theory.lintegral_add_left' MeasureTheory.lintegral_add_left'
theorem lintegral_add_right' (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : AEMeasurable g μ) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ := by
simpa only [add_comm] using lintegral_add_left' hg f
#align measure_theory.lintegral_add_right' MeasureTheory.lintegral_add_right'
/-- If `f g : α → ℝ≥0∞` are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of `f + g` equals the sum of integrals. This lemma assumes that `g` is integrable, see also
`MeasureTheory.lintegral_add_left` and primed versions of these lemmas. -/
@[simp]
theorem lintegral_add_right (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : Measurable g) :
∫⁻ a, f a + g a ∂μ = ∫⁻ a, f a ∂μ + ∫⁻ a, g a ∂μ :=
lintegral_add_right' f hg.aemeasurable
#align measure_theory.lintegral_add_right MeasureTheory.lintegral_add_right
@[simp]
theorem lintegral_smul_measure (c : ℝ≥0∞) (f : α → ℝ≥0∞) : ∫⁻ a, f a ∂c • μ = c * ∫⁻ a, f a ∂μ := by
simp only [lintegral, iSup_subtype', SimpleFunc.lintegral_smul, ENNReal.mul_iSup, smul_eq_mul]
#align measure_theory.lintegral_smul_measure MeasureTheory.lintegral_smul_measure
lemma set_lintegral_smul_measure (c : ℝ≥0∞) (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a in s, f a ∂(c • μ) = c * ∫⁻ a in s, f a ∂μ := by
rw [Measure.restrict_smul, lintegral_smul_measure]
@[simp]
theorem lintegral_sum_measure {m : MeasurableSpace α} {ι} (f : α → ℝ≥0∞) (μ : ι → Measure α) :
∫⁻ a, f a ∂Measure.sum μ = ∑' i, ∫⁻ a, f a ∂μ i := by
simp only [lintegral, iSup_subtype', SimpleFunc.lintegral_sum, ENNReal.tsum_eq_iSup_sum]
rw [iSup_comm]
congr; funext s
induction' s using Finset.induction_on with i s hi hs
· simp
simp only [Finset.sum_insert hi, ← hs]
refine (ENNReal.iSup_add_iSup ?_).symm
intro φ ψ
exact
⟨⟨φ ⊔ ψ, fun x => sup_le (φ.2 x) (ψ.2 x)⟩,
add_le_add (SimpleFunc.lintegral_mono le_sup_left le_rfl)
(Finset.sum_le_sum fun j _ => SimpleFunc.lintegral_mono le_sup_right le_rfl)⟩
#align measure_theory.lintegral_sum_measure MeasureTheory.lintegral_sum_measure
theorem hasSum_lintegral_measure {ι} {_ : MeasurableSpace α} (f : α → ℝ≥0∞) (μ : ι → Measure α) :
HasSum (fun i => ∫⁻ a, f a ∂μ i) (∫⁻ a, f a ∂Measure.sum μ) :=
(lintegral_sum_measure f μ).symm ▸ ENNReal.summable.hasSum
#align measure_theory.has_sum_lintegral_measure MeasureTheory.hasSum_lintegral_measure
@[simp]
theorem lintegral_add_measure {m : MeasurableSpace α} (f : α → ℝ≥0∞) (μ ν : Measure α) :
∫⁻ a, f a ∂(μ + ν) = ∫⁻ a, f a ∂μ + ∫⁻ a, f a ∂ν := by
simpa [tsum_fintype] using lintegral_sum_measure f fun b => cond b μ ν
#align measure_theory.lintegral_add_measure MeasureTheory.lintegral_add_measure
@[simp]
theorem lintegral_finset_sum_measure {ι} {m : MeasurableSpace α} (s : Finset ι) (f : α → ℝ≥0∞)
(μ : ι → Measure α) : ∫⁻ a, f a ∂(∑ i ∈ s, μ i) = ∑ i ∈ s, ∫⁻ a, f a ∂μ i := by
rw [← Measure.sum_coe_finset, lintegral_sum_measure, ← Finset.tsum_subtype']
simp only [Finset.coe_sort_coe]
#align measure_theory.lintegral_finset_sum_measure MeasureTheory.lintegral_finset_sum_measure
@[simp]
theorem lintegral_zero_measure {m : MeasurableSpace α} (f : α → ℝ≥0∞) :
∫⁻ a, f a ∂(0 : Measure α) = 0 := by
simp [lintegral]
#align measure_theory.lintegral_zero_measure MeasureTheory.lintegral_zero_measure
@[simp]
theorem lintegral_of_isEmpty {α} [MeasurableSpace α] [IsEmpty α] (μ : Measure α) (f : α → ℝ≥0∞) :
∫⁻ x, f x ∂μ = 0 := by
have : Subsingleton (Measure α) := inferInstance
convert lintegral_zero_measure f
theorem set_lintegral_empty (f : α → ℝ≥0∞) : ∫⁻ x in ∅, f x ∂μ = 0 := by
rw [Measure.restrict_empty, lintegral_zero_measure]
#align measure_theory.set_lintegral_empty MeasureTheory.set_lintegral_empty
theorem set_lintegral_univ (f : α → ℝ≥0∞) : ∫⁻ x in univ, f x ∂μ = ∫⁻ x, f x ∂μ := by
rw [Measure.restrict_univ]
#align measure_theory.set_lintegral_univ MeasureTheory.set_lintegral_univ
theorem set_lintegral_measure_zero (s : Set α) (f : α → ℝ≥0∞) (hs' : μ s = 0) :
∫⁻ x in s, f x ∂μ = 0 := by
convert lintegral_zero_measure _
exact Measure.restrict_eq_zero.2 hs'
#align measure_theory.set_lintegral_measure_zero MeasureTheory.set_lintegral_measure_zero
theorem lintegral_finset_sum' (s : Finset β) {f : β → α → ℝ≥0∞}
(hf : ∀ b ∈ s, AEMeasurable (f b) μ) :
∫⁻ a, ∑ b ∈ s, f b a ∂μ = ∑ b ∈ s, ∫⁻ a, f b a ∂μ := by
induction' s using Finset.induction_on with a s has ih
· simp
· simp only [Finset.sum_insert has]
rw [Finset.forall_mem_insert] at hf
rw [lintegral_add_left' hf.1, ih hf.2]
#align measure_theory.lintegral_finset_sum' MeasureTheory.lintegral_finset_sum'
theorem lintegral_finset_sum (s : Finset β) {f : β → α → ℝ≥0∞} (hf : ∀ b ∈ s, Measurable (f b)) :
∫⁻ a, ∑ b ∈ s, f b a ∂μ = ∑ b ∈ s, ∫⁻ a, f b a ∂μ :=
lintegral_finset_sum' s fun b hb => (hf b hb).aemeasurable
#align measure_theory.lintegral_finset_sum MeasureTheory.lintegral_finset_sum
@[simp]
theorem lintegral_const_mul (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ :=
calc
∫⁻ a, r * f a ∂μ = ∫⁻ a, ⨆ n, (const α r * eapprox f n) a ∂μ := by
congr
funext a
rw [← iSup_eapprox_apply f hf, ENNReal.mul_iSup]
simp
_ = ⨆ n, r * (eapprox f n).lintegral μ := by
rw [lintegral_iSup]
· congr
funext n
rw [← SimpleFunc.const_mul_lintegral, ← SimpleFunc.lintegral_eq_lintegral]
· intro n
exact SimpleFunc.measurable _
· intro i j h a
exact mul_le_mul_left' (monotone_eapprox _ h _) _
_ = r * ∫⁻ a, f a ∂μ := by rw [← ENNReal.mul_iSup, lintegral_eq_iSup_eapprox_lintegral hf]
#align measure_theory.lintegral_const_mul MeasureTheory.lintegral_const_mul
theorem lintegral_const_mul'' (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ := by
have A : ∫⁻ a, f a ∂μ = ∫⁻ a, hf.mk f a ∂μ := lintegral_congr_ae hf.ae_eq_mk
have B : ∫⁻ a, r * f a ∂μ = ∫⁻ a, r * hf.mk f a ∂μ :=
lintegral_congr_ae (EventuallyEq.fun_comp hf.ae_eq_mk _)
rw [A, B, lintegral_const_mul _ hf.measurable_mk]
#align measure_theory.lintegral_const_mul'' MeasureTheory.lintegral_const_mul''
theorem lintegral_const_mul_le (r : ℝ≥0∞) (f : α → ℝ≥0∞) :
r * ∫⁻ a, f a ∂μ ≤ ∫⁻ a, r * f a ∂μ := by
rw [lintegral, ENNReal.mul_iSup]
refine iSup_le fun s => ?_
rw [ENNReal.mul_iSup, iSup_le_iff]
intro hs
rw [← SimpleFunc.const_mul_lintegral, lintegral]
refine le_iSup_of_le (const α r * s) (le_iSup_of_le (fun x => ?_) le_rfl)
exact mul_le_mul_left' (hs x) _
#align measure_theory.lintegral_const_mul_le MeasureTheory.lintegral_const_mul_le
theorem lintegral_const_mul' (r : ℝ≥0∞) (f : α → ℝ≥0∞) (hr : r ≠ ∞) :
∫⁻ a, r * f a ∂μ = r * ∫⁻ a, f a ∂μ := by
by_cases h : r = 0
· simp [h]
apply le_antisymm _ (lintegral_const_mul_le r f)
have rinv : r * r⁻¹ = 1 := ENNReal.mul_inv_cancel h hr
have rinv' : r⁻¹ * r = 1 := by
rw [mul_comm]
exact rinv
have := lintegral_const_mul_le (μ := μ) r⁻¹ fun x => r * f x
simp? [(mul_assoc _ _ _).symm, rinv'] at this says
simp only [(mul_assoc _ _ _).symm, rinv', one_mul] at this
simpa [(mul_assoc _ _ _).symm, rinv] using mul_le_mul_left' this r
#align measure_theory.lintegral_const_mul' MeasureTheory.lintegral_const_mul'
theorem lintegral_mul_const (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : Measurable f) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul r hf]
#align measure_theory.lintegral_mul_const MeasureTheory.lintegral_mul_const
theorem lintegral_mul_const'' (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul'' r hf]
#align measure_theory.lintegral_mul_const'' MeasureTheory.lintegral_mul_const''
theorem lintegral_mul_const_le (r : ℝ≥0∞) (f : α → ℝ≥0∞) :
(∫⁻ a, f a ∂μ) * r ≤ ∫⁻ a, f a * r ∂μ := by
simp_rw [mul_comm, lintegral_const_mul_le r f]
#align measure_theory.lintegral_mul_const_le MeasureTheory.lintegral_mul_const_le
theorem lintegral_mul_const' (r : ℝ≥0∞) (f : α → ℝ≥0∞) (hr : r ≠ ∞) :
∫⁻ a, f a * r ∂μ = (∫⁻ a, f a ∂μ) * r := by simp_rw [mul_comm, lintegral_const_mul' r f hr]
#align measure_theory.lintegral_mul_const' MeasureTheory.lintegral_mul_const'
/- A double integral of a product where each factor contains only one variable
is a product of integrals -/
theorem lintegral_lintegral_mul {β} [MeasurableSpace β] {ν : Measure β} {f : α → ℝ≥0∞}
{g : β → ℝ≥0∞} (hf : AEMeasurable f μ) (hg : AEMeasurable g ν) :
∫⁻ x, ∫⁻ y, f x * g y ∂ν ∂μ = (∫⁻ x, f x ∂μ) * ∫⁻ y, g y ∂ν := by
simp [lintegral_const_mul'' _ hg, lintegral_mul_const'' _ hf]
#align measure_theory.lintegral_lintegral_mul MeasureTheory.lintegral_lintegral_mul
-- TODO: Need a better way of rewriting inside of an integral
theorem lintegral_rw₁ {f f' : α → β} (h : f =ᵐ[μ] f') (g : β → ℝ≥0∞) :
∫⁻ a, g (f a) ∂μ = ∫⁻ a, g (f' a) ∂μ :=
lintegral_congr_ae <| h.mono fun a h => by dsimp only; rw [h]
#align measure_theory.lintegral_rw₁ MeasureTheory.lintegral_rw₁
-- TODO: Need a better way of rewriting inside of an integral
theorem lintegral_rw₂ {f₁ f₁' : α → β} {f₂ f₂' : α → γ} (h₁ : f₁ =ᵐ[μ] f₁') (h₂ : f₂ =ᵐ[μ] f₂')
(g : β → γ → ℝ≥0∞) : ∫⁻ a, g (f₁ a) (f₂ a) ∂μ = ∫⁻ a, g (f₁' a) (f₂' a) ∂μ :=
lintegral_congr_ae <| h₁.mp <| h₂.mono fun _ h₂ h₁ => by dsimp only; rw [h₁, h₂]
#align measure_theory.lintegral_rw₂ MeasureTheory.lintegral_rw₂
theorem lintegral_indicator_le (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a, s.indicator f a ∂μ ≤ ∫⁻ a in s, f a ∂μ := by
simp only [lintegral]
apply iSup_le (fun g ↦ (iSup_le (fun hg ↦ ?_)))
have : g ≤ f := hg.trans (indicator_le_self s f)
refine le_iSup_of_le g (le_iSup_of_le this (le_of_eq ?_))
rw [lintegral_restrict, SimpleFunc.lintegral]
congr with t
by_cases H : t = 0
· simp [H]
congr with x
simp only [mem_preimage, mem_singleton_iff, mem_inter_iff, iff_self_and]
rintro rfl
contrapose! H
simpa [H] using hg x
@[simp]
theorem lintegral_indicator (f : α → ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
∫⁻ a, s.indicator f a ∂μ = ∫⁻ a in s, f a ∂μ := by
apply le_antisymm (lintegral_indicator_le f s)
simp only [lintegral, ← restrict_lintegral_eq_lintegral_restrict _ hs, iSup_subtype']
refine iSup_mono' (Subtype.forall.2 fun φ hφ => ?_)
refine ⟨⟨φ.restrict s, fun x => ?_⟩, le_rfl⟩
simp [hφ x, hs, indicator_le_indicator]
#align measure_theory.lintegral_indicator MeasureTheory.lintegral_indicator
theorem lintegral_indicator₀ (f : α → ℝ≥0∞) {s : Set α} (hs : NullMeasurableSet s μ) :
∫⁻ a, s.indicator f a ∂μ = ∫⁻ a in s, f a ∂μ := by
rw [← lintegral_congr_ae (indicator_ae_eq_of_ae_eq_set hs.toMeasurable_ae_eq),
lintegral_indicator _ (measurableSet_toMeasurable _ _),
Measure.restrict_congr_set hs.toMeasurable_ae_eq]
#align measure_theory.lintegral_indicator₀ MeasureTheory.lintegral_indicator₀
theorem lintegral_indicator_const_le (s : Set α) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ ≤ c * μ s :=
(lintegral_indicator_le _ _).trans (set_lintegral_const s c).le
theorem lintegral_indicator_const₀ {s : Set α} (hs : NullMeasurableSet s μ) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ = c * μ s := by
rw [lintegral_indicator₀ _ hs, set_lintegral_const]
theorem lintegral_indicator_const {s : Set α} (hs : MeasurableSet s) (c : ℝ≥0∞) :
∫⁻ a, s.indicator (fun _ => c) a ∂μ = c * μ s :=
lintegral_indicator_const₀ hs.nullMeasurableSet c
#align measure_theory.lintegral_indicator_const MeasureTheory.lintegral_indicator_const
theorem set_lintegral_eq_const {f : α → ℝ≥0∞} (hf : Measurable f) (r : ℝ≥0∞) :
∫⁻ x in { x | f x = r }, f x ∂μ = r * μ { x | f x = r } := by
have : ∀ᵐ x ∂μ, x ∈ { x | f x = r } → f x = r := ae_of_all μ fun _ hx => hx
rw [set_lintegral_congr_fun _ this]
· rw [lintegral_const, Measure.restrict_apply MeasurableSet.univ, Set.univ_inter]
· exact hf (measurableSet_singleton r)
#align measure_theory.set_lintegral_eq_const MeasureTheory.set_lintegral_eq_const
theorem lintegral_indicator_one_le (s : Set α) : ∫⁻ a, s.indicator 1 a ∂μ ≤ μ s :=
(lintegral_indicator_const_le _ _).trans <| (one_mul _).le
@[simp]
theorem lintegral_indicator_one₀ (hs : NullMeasurableSet s μ) : ∫⁻ a, s.indicator 1 a ∂μ = μ s :=
(lintegral_indicator_const₀ hs _).trans <| one_mul _
@[simp]
theorem lintegral_indicator_one (hs : MeasurableSet s) : ∫⁻ a, s.indicator 1 a ∂μ = μ s :=
(lintegral_indicator_const hs _).trans <| one_mul _
#align measure_theory.lintegral_indicator_one MeasureTheory.lintegral_indicator_one
/-- A version of **Markov's inequality** for two functions. It doesn't follow from the standard
Markov's inequality because we only assume measurability of `g`, not `f`. -/
theorem lintegral_add_mul_meas_add_le_le_lintegral {f g : α → ℝ≥0∞} (hle : f ≤ᵐ[μ] g)
(hg : AEMeasurable g μ) (ε : ℝ≥0∞) :
∫⁻ a, f a ∂μ + ε * μ { x | f x + ε ≤ g x } ≤ ∫⁻ a, g a ∂μ := by
rcases exists_measurable_le_lintegral_eq μ f with ⟨φ, hφm, hφ_le, hφ_eq⟩
calc
∫⁻ x, f x ∂μ + ε * μ { x | f x + ε ≤ g x } = ∫⁻ x, φ x ∂μ + ε * μ { x | f x + ε ≤ g x } := by
rw [hφ_eq]
_ ≤ ∫⁻ x, φ x ∂μ + ε * μ { x | φ x + ε ≤ g x } := by
gcongr
exact fun x => (add_le_add_right (hφ_le _) _).trans
_ = ∫⁻ x, φ x + indicator { x | φ x + ε ≤ g x } (fun _ => ε) x ∂μ := by
rw [lintegral_add_left hφm, lintegral_indicator₀, set_lintegral_const]
exact measurableSet_le (hφm.nullMeasurable.measurable'.add_const _) hg.nullMeasurable
_ ≤ ∫⁻ x, g x ∂μ := lintegral_mono_ae (hle.mono fun x hx₁ => ?_)
simp only [indicator_apply]; split_ifs with hx₂
exacts [hx₂, (add_zero _).trans_le <| (hφ_le x).trans hx₁]
#align measure_theory.lintegral_add_mul_meas_add_le_le_lintegral MeasureTheory.lintegral_add_mul_meas_add_le_le_lintegral
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. -/
theorem mul_meas_ge_le_lintegral₀ {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (ε : ℝ≥0∞) :
ε * μ { x | ε ≤ f x } ≤ ∫⁻ a, f a ∂μ := by
simpa only [lintegral_zero, zero_add] using
lintegral_add_mul_meas_add_le_le_lintegral (ae_of_all _ fun x => zero_le (f x)) hf ε
#align measure_theory.mul_meas_ge_le_lintegral₀ MeasureTheory.mul_meas_ge_le_lintegral₀
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. For a version assuming
`AEMeasurable`, see `mul_meas_ge_le_lintegral₀`. -/
theorem mul_meas_ge_le_lintegral {f : α → ℝ≥0∞} (hf : Measurable f) (ε : ℝ≥0∞) :
ε * μ { x | ε ≤ f x } ≤ ∫⁻ a, f a ∂μ :=
mul_meas_ge_le_lintegral₀ hf.aemeasurable ε
#align measure_theory.mul_meas_ge_le_lintegral MeasureTheory.mul_meas_ge_le_lintegral
lemma meas_le_lintegral₀ {f : α → ℝ≥0∞} (hf : AEMeasurable f μ)
{s : Set α} (hs : ∀ x ∈ s, 1 ≤ f x) : μ s ≤ ∫⁻ a, f a ∂μ := by
apply le_trans _ (mul_meas_ge_le_lintegral₀ hf 1)
rw [one_mul]
exact measure_mono hs
lemma lintegral_le_meas {s : Set α} {f : α → ℝ≥0∞} (hf : ∀ a, f a ≤ 1) (h'f : ∀ a ∈ sᶜ, f a = 0) :
∫⁻ a, f a ∂μ ≤ μ s := by
apply (lintegral_mono (fun x ↦ ?_)).trans (lintegral_indicator_one_le s)
by_cases hx : x ∈ s
· simpa [hx] using hf x
· simpa [hx] using h'f x hx
theorem lintegral_eq_top_of_measure_eq_top_ne_zero {f : α → ℝ≥0∞} (hf : AEMeasurable f μ)
(hμf : μ {x | f x = ∞} ≠ 0) : ∫⁻ x, f x ∂μ = ∞ :=
eq_top_iff.mpr <|
calc
∞ = ∞ * μ { x | ∞ ≤ f x } := by simp [mul_eq_top, hμf]
_ ≤ ∫⁻ x, f x ∂μ := mul_meas_ge_le_lintegral₀ hf ∞
#align measure_theory.lintegral_eq_top_of_measure_eq_top_ne_zero MeasureTheory.lintegral_eq_top_of_measure_eq_top_ne_zero
theorem setLintegral_eq_top_of_measure_eq_top_ne_zero (hf : AEMeasurable f (μ.restrict s))
(hμf : μ ({x ∈ s | f x = ∞}) ≠ 0) : ∫⁻ x in s, f x ∂μ = ∞ :=
lintegral_eq_top_of_measure_eq_top_ne_zero hf <|
mt (eq_bot_mono <| by rw [← setOf_inter_eq_sep]; exact Measure.le_restrict_apply _ _) hμf
#align measure_theory.set_lintegral_eq_top_of_measure_eq_top_ne_zero MeasureTheory.setLintegral_eq_top_of_measure_eq_top_ne_zero
theorem measure_eq_top_of_lintegral_ne_top (hf : AEMeasurable f μ) (hμf : ∫⁻ x, f x ∂μ ≠ ∞) :
μ {x | f x = ∞} = 0 :=
of_not_not fun h => hμf <| lintegral_eq_top_of_measure_eq_top_ne_zero hf h
#align measure_theory.measure_eq_top_of_lintegral_ne_top MeasureTheory.measure_eq_top_of_lintegral_ne_top
theorem measure_eq_top_of_setLintegral_ne_top (hf : AEMeasurable f (μ.restrict s))
(hμf : ∫⁻ x in s, f x ∂μ ≠ ∞) : μ ({x ∈ s | f x = ∞}) = 0 :=
of_not_not fun h => hμf <| setLintegral_eq_top_of_measure_eq_top_ne_zero hf h
#align measure_theory.measure_eq_top_of_set_lintegral_ne_top MeasureTheory.measure_eq_top_of_setLintegral_ne_top
/-- **Markov's inequality** also known as **Chebyshev's first inequality**. -/
theorem meas_ge_le_lintegral_div {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) {ε : ℝ≥0∞} (hε : ε ≠ 0)
(hε' : ε ≠ ∞) : μ { x | ε ≤ f x } ≤ (∫⁻ a, f a ∂μ) / ε :=
(ENNReal.le_div_iff_mul_le (Or.inl hε) (Or.inl hε')).2 <| by
rw [mul_comm]
exact mul_meas_ge_le_lintegral₀ hf ε
#align measure_theory.meas_ge_le_lintegral_div MeasureTheory.meas_ge_le_lintegral_div
theorem ae_eq_of_ae_le_of_lintegral_le {f g : α → ℝ≥0∞} (hfg : f ≤ᵐ[μ] g) (hf : ∫⁻ x, f x ∂μ ≠ ∞)
(hg : AEMeasurable g μ) (hgf : ∫⁻ x, g x ∂μ ≤ ∫⁻ x, f x ∂μ) : f =ᵐ[μ] g := by
have : ∀ n : ℕ, ∀ᵐ x ∂μ, g x < f x + (n : ℝ≥0∞)⁻¹ := by
intro n
simp only [ae_iff, not_lt]
have : ∫⁻ x, f x ∂μ + (↑n)⁻¹ * μ { x : α | f x + (n : ℝ≥0∞)⁻¹ ≤ g x } ≤ ∫⁻ x, f x ∂μ :=
(lintegral_add_mul_meas_add_le_le_lintegral hfg hg n⁻¹).trans hgf
rw [(ENNReal.cancel_of_ne hf).add_le_iff_nonpos_right, nonpos_iff_eq_zero, mul_eq_zero] at this
exact this.resolve_left (ENNReal.inv_ne_zero.2 (ENNReal.natCast_ne_top _))
refine hfg.mp ((ae_all_iff.2 this).mono fun x hlt hle => hle.antisymm ?_)
suffices Tendsto (fun n : ℕ => f x + (n : ℝ≥0∞)⁻¹) atTop (𝓝 (f x)) from
ge_of_tendsto' this fun i => (hlt i).le
simpa only [inv_top, add_zero] using
tendsto_const_nhds.add (ENNReal.tendsto_inv_iff.2 ENNReal.tendsto_nat_nhds_top)
#align measure_theory.ae_eq_of_ae_le_of_lintegral_le MeasureTheory.ae_eq_of_ae_le_of_lintegral_le
@[simp]
theorem lintegral_eq_zero_iff' {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) :
∫⁻ a, f a ∂μ = 0 ↔ f =ᵐ[μ] 0 :=
have : ∫⁻ _ : α, 0 ∂μ ≠ ∞ := by simp [lintegral_zero, zero_ne_top]
⟨fun h =>
(ae_eq_of_ae_le_of_lintegral_le (ae_of_all _ <| zero_le f) this hf
(h.trans lintegral_zero.symm).le).symm,
fun h => (lintegral_congr_ae h).trans lintegral_zero⟩
#align measure_theory.lintegral_eq_zero_iff' MeasureTheory.lintegral_eq_zero_iff'
@[simp]
theorem lintegral_eq_zero_iff {f : α → ℝ≥0∞} (hf : Measurable f) : ∫⁻ a, f a ∂μ = 0 ↔ f =ᵐ[μ] 0 :=
lintegral_eq_zero_iff' hf.aemeasurable
#align measure_theory.lintegral_eq_zero_iff MeasureTheory.lintegral_eq_zero_iff
theorem lintegral_pos_iff_support {f : α → ℝ≥0∞} (hf : Measurable f) :
(0 < ∫⁻ a, f a ∂μ) ↔ 0 < μ (Function.support f) := by
simp [pos_iff_ne_zero, hf, Filter.EventuallyEq, ae_iff, Function.support]
#align measure_theory.lintegral_pos_iff_support MeasureTheory.lintegral_pos_iff_support
theorem setLintegral_pos_iff {f : α → ℝ≥0∞} (hf : Measurable f) {s : Set α} :
0 < ∫⁻ a in s, f a ∂μ ↔ 0 < μ (Function.support f ∩ s) := by
rw [lintegral_pos_iff_support hf, Measure.restrict_apply (measurableSet_support hf)]
/-- Weaker version of the monotone convergence theorem-/
theorem lintegral_iSup_ae {f : ℕ → α → ℝ≥0∞} (hf : ∀ n, Measurable (f n))
(h_mono : ∀ n, ∀ᵐ a ∂μ, f n a ≤ f n.succ a) : ∫⁻ a, ⨆ n, f n a ∂μ = ⨆ n, ∫⁻ a, f n a ∂μ := by
let ⟨s, hs⟩ := exists_measurable_superset_of_null (ae_iff.1 (ae_all_iff.2 h_mono))
let g n a := if a ∈ s then 0 else f n a
have g_eq_f : ∀ᵐ a ∂μ, ∀ n, g n a = f n a :=
(measure_zero_iff_ae_nmem.1 hs.2.2).mono fun a ha n => if_neg ha
calc
∫⁻ a, ⨆ n, f n a ∂μ = ∫⁻ a, ⨆ n, g n a ∂μ :=
lintegral_congr_ae <| g_eq_f.mono fun a ha => by simp only [ha]
_ = ⨆ n, ∫⁻ a, g n a ∂μ :=
(lintegral_iSup (fun n => measurable_const.piecewise hs.2.1 (hf n))
(monotone_nat_of_le_succ fun n a => ?_))
_ = ⨆ n, ∫⁻ a, f n a ∂μ := by simp only [lintegral_congr_ae (g_eq_f.mono fun _a ha => ha _)]
simp only [g]
split_ifs with h
· rfl
· have := Set.not_mem_subset hs.1 h
simp only [not_forall, not_le, mem_setOf_eq, not_exists, not_lt] at this
exact this n
#align measure_theory.lintegral_supr_ae MeasureTheory.lintegral_iSup_ae
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 967 | 971 | theorem lintegral_sub' {f g : α → ℝ≥0∞} (hg : AEMeasurable g μ) (hg_fin : ∫⁻ a, g a ∂μ ≠ ∞)
(h_le : g ≤ᵐ[μ] f) : ∫⁻ a, f a - g a ∂μ = ∫⁻ a, f a ∂μ - ∫⁻ a, g a ∂μ := by |
refine ENNReal.eq_sub_of_add_eq hg_fin ?_
rw [← lintegral_add_right' _ hg]
exact lintegral_congr_ae (h_le.mono fun x hx => tsub_add_cancel_of_le hx)
|
/-
Copyright (c) 2023 Andrew Yang, Patrick Lutz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.RingTheory.RootsOfUnity.Basic
import Mathlib.RingTheory.AdjoinRoot
import Mathlib.FieldTheory.Galois
import Mathlib.LinearAlgebra.Eigenspace.Minpoly
import Mathlib.RingTheory.Norm
/-!
# Kummer Extensions
## Main result
- `isCyclic_tfae`:
Suppose `L/K` is a finite extension of dimension `n`, and `K` contains all `n`-th roots of unity.
Then `L/K` is cyclic iff
`L` is a splitting field of some irreducible polynomial of the form `Xⁿ - a : K[X]` iff
`L = K[α]` for some `αⁿ ∈ K`.
- `autEquivRootsOfUnity`:
Given an instance `IsSplittingField K L (X ^ n - C a)`
(perhaps via `isSplittingField_X_pow_sub_C_of_root_adjoin_eq_top`),
then the galois group is isomorphic to `rootsOfUnity n K`, by sending
`σ ↦ σ α / α` for `α ^ n = a`, and the inverse is given by `μ ↦ (α ↦ μ • α)`.
- `autEquivZmod`:
Furthermore, given an explicit choice `ζ` of a primitive `n`-th root of unity, the galois group is
then isomorphic to `Multiplicative (ZMod n)` whose inverse is given by
`i ↦ (α ↦ ζⁱ • α)`.
## Other results
Criteria for `X ^ n - C a` to be irreducible is given:
- `X_pow_sub_C_irreducible_iff_of_prime`:
For `n = p` a prime, `X ^ n - C a` is irreducible iff `a` is not a `p`-power.
- `X_pow_sub_C_irreducible_iff_of_prime_pow`:
For `n = p ^ k` an odd prime power, `X ^ n - C a` is irreducible iff `a` is not a `p`-power.
- `X_pow_sub_C_irreducible_iff_forall_prime_of_odd`:
For `n` odd, `X ^ n - C a` is irreducible iff `a` is not a `p`-power for all prime `p ∣ n`.
- `X_pow_sub_C_irreducible_iff_of_odd`:
For `n` odd, `X ^ n - C a` is irreducible iff `a` is not a `d`-power for `d ∣ n` and `d ≠ 1`.
TODO: criteria for even `n`. See [serge_lang_algebra] VI,§9.
-/
universe u
variable {K : Type u} [Field K]
open Polynomial IntermediateField AdjoinRoot
section Splits
lemma root_X_pow_sub_C_pow (n : ℕ) (a : K) :
(AdjoinRoot.root (X ^ n - C a)) ^ n = AdjoinRoot.of _ a := by
rw [← sub_eq_zero, ← AdjoinRoot.eval₂_root, eval₂_sub, eval₂_C, eval₂_pow, eval₂_X]
lemma root_X_pow_sub_C_ne_zero {n : ℕ} (hn : 1 < n) (a : K) :
(AdjoinRoot.root (X ^ n - C a)) ≠ 0 :=
mk_ne_zero_of_natDegree_lt (monic_X_pow_sub_C _ (Nat.not_eq_zero_of_lt hn))
X_ne_zero <| by rwa [natDegree_X_pow_sub_C, natDegree_X]
lemma root_X_pow_sub_C_ne_zero' {n : ℕ} {a : K} (hn : 0 < n) (ha : a ≠ 0) :
(AdjoinRoot.root (X ^ n - C a)) ≠ 0 := by
obtain (rfl|hn) := (Nat.succ_le_iff.mpr hn).eq_or_lt
· rw [← Nat.one_eq_succ_zero, pow_one]
intro e
refine mk_ne_zero_of_natDegree_lt (monic_X_sub_C a) (C_ne_zero.mpr ha) (by simp) ?_
trans AdjoinRoot.mk (X - C a) (X - (X - C a))
· rw [sub_sub_cancel]
· rw [map_sub, mk_self, sub_zero, mk_X, e]
· exact root_X_pow_sub_C_ne_zero hn a
theorem X_pow_sub_C_splits_of_isPrimitiveRoot
{n : ℕ} {ζ : K} (hζ : IsPrimitiveRoot ζ n) {α a : K} (e : α ^ n = a) :
(X ^ n - C a).Splits (RingHom.id _) := by
cases n.eq_zero_or_pos with
| inl hn =>
rw [hn, pow_zero, ← C.map_one, ← map_sub]
exact splits_C _ _
| inr hn =>
rw [splits_iff_card_roots, ← nthRoots, hζ.card_nthRoots, natDegree_X_pow_sub_C, if_pos ⟨α, e⟩]
open BigOperators
-- make this private, as we only use it to prove a strictly more general version
private
theorem X_pow_sub_C_eq_prod'
{n : ℕ} {ζ : K} (hζ : IsPrimitiveRoot ζ n) {α a : K} (hn : 0 < n) (e : α ^ n = a) :
(X ^ n - C a) = ∏ i ∈ Finset.range n, (X - C (ζ ^ i * α)) := by
rw [eq_prod_roots_of_monic_of_splits_id (monic_X_pow_sub_C _ (Nat.pos_iff_ne_zero.mp hn))
(X_pow_sub_C_splits_of_isPrimitiveRoot hζ e), ← nthRoots, hζ.nthRoots_eq e, Multiset.map_map]
rfl
lemma X_pow_sub_C_eq_prod {R : Type*} [CommRing R] [IsDomain R]
{n : ℕ} {ζ : R} (hζ : IsPrimitiveRoot ζ n) {α a : R} (hn : 0 < n) (e : α ^ n = a) :
(X ^ n - C a) = ∏ i ∈ Finset.range n, (X - C (ζ ^ i * α)) := by
let K := FractionRing R
let i := algebraMap R K
have h := NoZeroSMulDivisors.algebraMap_injective R K
apply_fun Polynomial.map i using map_injective i h
simpa only [Polynomial.map_sub, Polynomial.map_pow, map_X, map_C, map_mul, map_pow,
Polynomial.map_prod, Polynomial.map_mul]
using X_pow_sub_C_eq_prod' (hζ.map_of_injective h) hn <| map_pow i α n ▸ congrArg i e
end Splits
section Irreducible
lemma ne_zero_of_irreducible_X_pow_sub_C {n : ℕ} {a : K} (H : Irreducible (X ^ n - C a)) :
n ≠ 0 := by
rintro rfl
rw [pow_zero, ← C.map_one, ← map_sub] at H
exact not_irreducible_C _ H
lemma ne_zero_of_irreducible_X_pow_sub_C' {n : ℕ} (hn : n ≠ 1) {a : K}
(H : Irreducible (X ^ n - C a)) : a ≠ 0 := by
rintro rfl
rw [map_zero, sub_zero] at H
exact not_irreducible_pow hn H
lemma root_X_pow_sub_C_eq_zero_iff {n : ℕ} {a : K} (H : Irreducible (X ^ n - C a)) :
(AdjoinRoot.root (X ^ n - C a)) = 0 ↔ a = 0 := by
have hn := Nat.pos_iff_ne_zero.mpr (ne_zero_of_irreducible_X_pow_sub_C H)
refine ⟨not_imp_not.mp (root_X_pow_sub_C_ne_zero' hn), ?_⟩
rintro rfl
have := not_imp_not.mp (fun hn ↦ ne_zero_of_irreducible_X_pow_sub_C' hn H) rfl
rw [this, pow_one, map_zero, sub_zero, ← mk_X, mk_self]
lemma root_X_pow_sub_C_ne_zero_iff {n : ℕ} {a : K} (H : Irreducible (X ^ n - C a)) :
(AdjoinRoot.root (X ^ n - C a)) ≠ 0 ↔ a ≠ 0 :=
(root_X_pow_sub_C_eq_zero_iff H).not
| Mathlib/FieldTheory/KummerExtension.lean | 134 | 149 | theorem pow_ne_of_irreducible_X_pow_sub_C {n : ℕ} {a : K}
(H : Irreducible (X ^ n - C a)) {m : ℕ} (hm : m ∣ n) (hm' : m ≠ 1) (b : K) : b ^ m ≠ a := by |
have hn : n ≠ 0 := fun e ↦ not_irreducible_C
(1 - a) (by simpa only [e, pow_zero, ← C.map_one, ← map_sub] using H)
obtain ⟨k, rfl⟩ := hm
rintro rfl
obtain ⟨q, hq⟩ := sub_dvd_pow_sub_pow (X ^ k) (C b) m
rw [mul_comm, pow_mul, map_pow, hq] at H
have : degree q = 0 := by
simpa [isUnit_iff_degree_eq_zero, degree_X_pow_sub_C,
Nat.pos_iff_ne_zero, (mul_ne_zero_iff.mp hn).2] using H.2 _ q rfl
apply_fun degree at hq
simp only [this, ← pow_mul, mul_comm k m, degree_X_pow_sub_C, Nat.pos_iff_ne_zero.mpr hn,
Nat.pos_iff_ne_zero.mpr (mul_ne_zero_iff.mp hn).2, degree_mul, ← map_pow, add_zero,
Nat.cast_injective.eq_iff] at hq
exact hm' ((mul_eq_right₀ (mul_ne_zero_iff.mp hn).2).mp hq)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.MFDeriv.Basic
/-!
### Relations between vector space derivative and manifold derivative
The manifold derivative `mfderiv`, when considered on the model vector space with its trivial
manifold structure, coincides with the usual Frechet derivative `fderiv`. In this section, we prove
this and related statements.
-/
noncomputable section
open scoped Manifold
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {f : E → E'}
{s : Set E} {x : E}
section MFDerivFderiv
theorem uniqueMDiffWithinAt_iff_uniqueDiffWithinAt :
UniqueMDiffWithinAt 𝓘(𝕜, E) s x ↔ UniqueDiffWithinAt 𝕜 s x := by
simp only [UniqueMDiffWithinAt, mfld_simps]
#align unique_mdiff_within_at_iff_unique_diff_within_at uniqueMDiffWithinAt_iff_uniqueDiffWithinAt
alias ⟨UniqueMDiffWithinAt.uniqueDiffWithinAt, UniqueDiffWithinAt.uniqueMDiffWithinAt⟩ :=
uniqueMDiffWithinAt_iff_uniqueDiffWithinAt
#align unique_mdiff_within_at.unique_diff_within_at UniqueMDiffWithinAt.uniqueDiffWithinAt
#align unique_diff_within_at.unique_mdiff_within_at UniqueDiffWithinAt.uniqueMDiffWithinAt
theorem uniqueMDiffOn_iff_uniqueDiffOn : UniqueMDiffOn 𝓘(𝕜, E) s ↔ UniqueDiffOn 𝕜 s := by
simp [UniqueMDiffOn, UniqueDiffOn, uniqueMDiffWithinAt_iff_uniqueDiffWithinAt]
#align unique_mdiff_on_iff_unique_diff_on uniqueMDiffOn_iff_uniqueDiffOn
alias ⟨UniqueMDiffOn.uniqueDiffOn, UniqueDiffOn.uniqueMDiffOn⟩ := uniqueMDiffOn_iff_uniqueDiffOn
#align unique_mdiff_on.unique_diff_on UniqueMDiffOn.uniqueDiffOn
#align unique_diff_on.unique_mdiff_on UniqueDiffOn.uniqueMDiffOn
-- Porting note (#10618): was `@[simp, mfld_simps]` but `simp` can prove it
theorem writtenInExtChartAt_model_space : writtenInExtChartAt 𝓘(𝕜, E) 𝓘(𝕜, E') x f = f :=
rfl
#align written_in_ext_chart_model_space writtenInExtChartAt_model_space
theorem hasMFDerivWithinAt_iff_hasFDerivWithinAt {f'} :
HasMFDerivWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x f' ↔ HasFDerivWithinAt f f' s x := by
simpa only [HasMFDerivWithinAt, and_iff_right_iff_imp, mfld_simps] using
HasFDerivWithinAt.continuousWithinAt
#align has_mfderiv_within_at_iff_has_fderiv_within_at hasMFDerivWithinAt_iff_hasFDerivWithinAt
alias ⟨HasMFDerivWithinAt.hasFDerivWithinAt, HasFDerivWithinAt.hasMFDerivWithinAt⟩ :=
hasMFDerivWithinAt_iff_hasFDerivWithinAt
#align has_mfderiv_within_at.has_fderiv_within_at HasMFDerivWithinAt.hasFDerivWithinAt
#align has_fderiv_within_at.has_mfderiv_within_at HasFDerivWithinAt.hasMFDerivWithinAt
theorem hasMFDerivAt_iff_hasFDerivAt {f'} :
HasMFDerivAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x f' ↔ HasFDerivAt f f' x := by
rw [← hasMFDerivWithinAt_univ, hasMFDerivWithinAt_iff_hasFDerivWithinAt, hasFDerivWithinAt_univ]
#align has_mfderiv_at_iff_has_fderiv_at hasMFDerivAt_iff_hasFDerivAt
alias ⟨HasMFDerivAt.hasFDerivAt, HasFDerivAt.hasMFDerivAt⟩ := hasMFDerivAt_iff_hasFDerivAt
#align has_mfderiv_at.has_fderiv_at HasMFDerivAt.hasFDerivAt
#align has_fderiv_at.has_mfderiv_at HasFDerivAt.hasMFDerivAt
/-- For maps between vector spaces, `MDifferentiableWithinAt` and `DifferentiableWithinAt`
coincide -/
theorem mdifferentiableWithinAt_iff_differentiableWithinAt :
MDifferentiableWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x ↔ DifferentiableWithinAt 𝕜 f s x := by
simp only [mdifferentiableWithinAt_iff', mfld_simps]
exact ⟨fun H => H.2, fun H => ⟨H.continuousWithinAt, H⟩⟩
#align mdifferentiable_within_at_iff_differentiable_within_at mdifferentiableWithinAt_iff_differentiableWithinAt
alias ⟨MDifferentiableWithinAt.differentiableWithinAt,
DifferentiableWithinAt.mdifferentiableWithinAt⟩ :=
mdifferentiableWithinAt_iff_differentiableWithinAt
#align mdifferentiable_within_at.differentiable_within_at MDifferentiableWithinAt.differentiableWithinAt
#align differentiable_within_at.mdifferentiable_within_at DifferentiableWithinAt.mdifferentiableWithinAt
/-- For maps between vector spaces, `MDifferentiableAt` and `DifferentiableAt` coincide -/
theorem mdifferentiableAt_iff_differentiableAt :
MDifferentiableAt 𝓘(𝕜, E) 𝓘(𝕜, E') f x ↔ DifferentiableAt 𝕜 f x := by
simp only [mdifferentiableAt_iff, differentiableWithinAt_univ, mfld_simps]
exact ⟨fun H => H.2, fun H => ⟨H.continuousAt, H⟩⟩
#align mdifferentiable_at_iff_differentiable_at mdifferentiableAt_iff_differentiableAt
alias ⟨MDifferentiableAt.differentiableAt, DifferentiableAt.mdifferentiableAt⟩ :=
mdifferentiableAt_iff_differentiableAt
#align mdifferentiable_at.differentiable_at MDifferentiableAt.differentiableAt
#align differentiable_at.mdifferentiable_at DifferentiableAt.mdifferentiableAt
/-- For maps between vector spaces, `MDifferentiableOn` and `DifferentiableOn` coincide -/
theorem mdifferentiableOn_iff_differentiableOn :
MDifferentiableOn 𝓘(𝕜, E) 𝓘(𝕜, E') f s ↔ DifferentiableOn 𝕜 f s := by
simp only [MDifferentiableOn, DifferentiableOn,
mdifferentiableWithinAt_iff_differentiableWithinAt]
#align mdifferentiable_on_iff_differentiable_on mdifferentiableOn_iff_differentiableOn
alias ⟨MDifferentiableOn.differentiableOn, DifferentiableOn.mdifferentiableOn⟩ :=
mdifferentiableOn_iff_differentiableOn
#align mdifferentiable_on.differentiable_on MDifferentiableOn.differentiableOn
#align differentiable_on.mdifferentiable_on DifferentiableOn.mdifferentiableOn
/-- For maps between vector spaces, `MDifferentiable` and `Differentiable` coincide -/
theorem mdifferentiable_iff_differentiable :
MDifferentiable 𝓘(𝕜, E) 𝓘(𝕜, E') f ↔ Differentiable 𝕜 f := by
simp only [MDifferentiable, Differentiable, mdifferentiableAt_iff_differentiableAt]
#align mdifferentiable_iff_differentiable mdifferentiable_iff_differentiable
alias ⟨MDifferentiable.differentiable, Differentiable.mdifferentiable⟩ :=
mdifferentiable_iff_differentiable
#align mdifferentiable.differentiable MDifferentiable.differentiable
#align differentiable.mdifferentiable Differentiable.mdifferentiable
/-- For maps between vector spaces, `mfderivWithin` and `fderivWithin` coincide -/
@[simp]
| Mathlib/Geometry/Manifold/MFDeriv/FDeriv.lean | 120 | 126 | theorem mfderivWithin_eq_fderivWithin :
mfderivWithin 𝓘(𝕜, E) 𝓘(𝕜, E') f s x = fderivWithin 𝕜 f s x := by |
by_cases h : MDifferentiableWithinAt 𝓘(𝕜, E) 𝓘(𝕜, E') f s x
· simp only [mfderivWithin, h, if_pos, mfld_simps]
· simp only [mfderivWithin, h, if_neg, not_false_iff]
rw [mdifferentiableWithinAt_iff_differentiableWithinAt] at h
exact (fderivWithin_zero_of_not_differentiableWithinAt h).symm
|
/-
Copyright (c) 2020 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, Yury Kudryashov, Frédéric Dupuis
-/
import Mathlib.Topology.Algebra.InfiniteSum.Constructions
import Mathlib.Topology.Algebra.Module.Basic
#align_import topology.algebra.infinite_sum.module from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-! # Infinite sums in topological vector spaces -/
variable {α β γ δ : Type*}
open Filter Finset Function
section ConstSMul
variable [Monoid γ] [TopologicalSpace α] [AddCommMonoid α] [DistribMulAction γ α]
[ContinuousConstSMul γ α] {f : β → α}
theorem HasSum.const_smul {a : α} (b : γ) (hf : HasSum f a) : HasSum (fun i ↦ b • f i) (b • a) :=
hf.map (DistribMulAction.toAddMonoidHom α _) <| continuous_const_smul _
#align has_sum.const_smul HasSum.const_smul
theorem Summable.const_smul (b : γ) (hf : Summable f) : Summable fun i ↦ b • f i :=
(hf.hasSum.const_smul _).summable
#align summable.const_smul Summable.const_smul
/-- Infinite sums commute with scalar multiplication. Version for scalars living in a `Monoid`, but
requiring a summability hypothesis. -/
theorem tsum_const_smul [T2Space α] (b : γ) (hf : Summable f) : ∑' i, b • f i = b • ∑' i, f i :=
(hf.hasSum.const_smul _).tsum_eq
#align tsum_const_smul tsum_const_smul
/-- Infinite sums commute with scalar multiplication. Version for scalars living in a `Group`, but
not requiring any summability hypothesis. -/
lemma tsum_const_smul' {γ : Type*} [Group γ] [DistribMulAction γ α] [ContinuousConstSMul γ α]
[T2Space α] (g : γ) : ∑' (i : β), g • f i = g • ∑' (i : β), f i := by
by_cases hf : Summable f
· exact tsum_const_smul g hf
rw [tsum_eq_zero_of_not_summable hf]
simp only [smul_zero]
let mul_g : α ≃+ α := DistribMulAction.toAddEquiv α g
apply tsum_eq_zero_of_not_summable
change ¬ Summable (mul_g ∘ f)
rwa [Summable.map_iff_of_equiv mul_g]
· apply continuous_const_smul
· apply continuous_const_smul
/-- Infinite sums commute with scalar multiplication. Version for scalars living in a
`DivisionRing`; no summability hypothesis. This could be made to work for a
`[GroupWithZero γ]` if there was such a thing as `DistribMulActionWithZero`. -/
lemma tsum_const_smul'' {γ : Type*} [DivisionRing γ] [Module γ α] [ContinuousConstSMul γ α]
[T2Space α] (g : γ) : ∑' (i : β), g • f i = g • ∑' (i : β), f i := by
rcases eq_or_ne g 0 with rfl | hg
· simp
· exact tsum_const_smul' (Units.mk0 g hg)
end ConstSMul
variable {ι κ R R₂ M M₂ : Type*}
section SMulConst
variable [Semiring R] [TopologicalSpace R] [TopologicalSpace M] [AddCommMonoid M] [Module R M]
[ContinuousSMul R M] {f : ι → R}
theorem HasSum.smul_const {r : R} (hf : HasSum f r) (a : M) : HasSum (fun z ↦ f z • a) (r • a) :=
hf.map ((smulAddHom R M).flip a) (continuous_id.smul continuous_const)
#align has_sum.smul_const HasSum.smul_const
theorem Summable.smul_const (hf : Summable f) (a : M) : Summable fun z ↦ f z • a :=
(hf.hasSum.smul_const _).summable
#align summable.smul_const Summable.smul_const
theorem tsum_smul_const [T2Space M] (hf : Summable f) (a : M) : ∑' z, f z • a = (∑' z, f z) • a :=
(hf.hasSum.smul_const _).tsum_eq
#align tsum_smul_const tsum_smul_const
end SMulConst
/-!
Note we cannot derive the `mul` lemmas from these `smul` lemmas, as the `mul` versions do not
require associativity, but `Module` does.
-/
section tsum_smul_tsum
variable [Semiring R] [AddCommMonoid M] [Module R M]
variable [TopologicalSpace R] [TopologicalSpace M] [T3Space M]
variable [ContinuousAdd M] [ContinuousSMul R M]
variable {f : ι → R} {g : κ → M} {s : R} {t u : M}
theorem HasSum.smul_eq (hf : HasSum f s) (hg : HasSum g t)
(hfg : HasSum (fun x : ι × κ ↦ f x.1 • g x.2) u) : s • t = u :=
have key₁ : HasSum (fun i ↦ f i • t) (s • t) := hf.smul_const t
have this : ∀ i : ι, HasSum (fun c : κ ↦ f i • g c) (f i • t) := fun i ↦ hg.const_smul (f i)
have key₂ : HasSum (fun i ↦ f i • t) u := HasSum.prod_fiberwise hfg this
key₁.unique key₂
theorem HasSum.smul (hf : HasSum f s) (hg : HasSum g t)
(hfg : Summable fun x : ι × κ ↦ f x.1 • g x.2) :
HasSum (fun x : ι × κ ↦ f x.1 • g x.2) (s • t) :=
let ⟨_u, hu⟩ := hfg
(hf.smul_eq hg hu).symm ▸ hu
/-- Scalar product of two infinites sums indexed by arbitrary types. -/
theorem tsum_smul_tsum (hf : Summable f) (hg : Summable g)
(hfg : Summable fun x : ι × κ ↦ f x.1 • g x.2) :
((∑' x, f x) • ∑' y, g y) = ∑' z : ι × κ, f z.1 • g z.2 :=
hf.hasSum.smul_eq hg.hasSum hfg.hasSum
end tsum_smul_tsum
section HasSum
-- Results in this section hold for continuous additive monoid homomorphisms or equivalences but we
-- don't have bundled continuous additive homomorphisms.
variable [Semiring R] [Semiring R₂] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂] [Module R₂ M₂]
[TopologicalSpace M] [TopologicalSpace M₂] {σ : R →+* R₂} {σ' : R₂ →+* R} [RingHomInvPair σ σ']
[RingHomInvPair σ' σ]
/-- Applying a continuous linear map commutes with taking an (infinite) sum. -/
protected theorem ContinuousLinearMap.hasSum {f : ι → M} (φ : M →SL[σ] M₂) {x : M}
(hf : HasSum f x) : HasSum (fun b : ι ↦ φ (f b)) (φ x) := by
simpa only using hf.map φ.toLinearMap.toAddMonoidHom φ.continuous
#align continuous_linear_map.has_sum ContinuousLinearMap.hasSum
alias HasSum.mapL := ContinuousLinearMap.hasSum
set_option linter.uppercaseLean3 false in
#align has_sum.mapL HasSum.mapL
protected theorem ContinuousLinearMap.summable {f : ι → M} (φ : M →SL[σ] M₂) (hf : Summable f) :
Summable fun b : ι ↦ φ (f b) :=
(hf.hasSum.mapL φ).summable
#align continuous_linear_map.summable ContinuousLinearMap.summable
alias Summable.mapL := ContinuousLinearMap.summable
set_option linter.uppercaseLean3 false in
#align summable.mapL Summable.mapL
protected theorem ContinuousLinearMap.map_tsum [T2Space M₂] {f : ι → M} (φ : M →SL[σ] M₂)
(hf : Summable f) : φ (∑' z, f z) = ∑' z, φ (f z) :=
(hf.hasSum.mapL φ).tsum_eq.symm
#align continuous_linear_map.map_tsum ContinuousLinearMap.map_tsum
/-- Applying a continuous linear map commutes with taking an (infinite) sum. -/
protected theorem ContinuousLinearEquiv.hasSum {f : ι → M} (e : M ≃SL[σ] M₂) {y : M₂} :
HasSum (fun b : ι ↦ e (f b)) y ↔ HasSum f (e.symm y) :=
⟨fun h ↦ by simpa only [e.symm.coe_coe, e.symm_apply_apply] using h.mapL (e.symm : M₂ →SL[σ'] M),
fun h ↦ by simpa only [e.coe_coe, e.apply_symm_apply] using (e : M →SL[σ] M₂).hasSum h⟩
#align continuous_linear_equiv.has_sum ContinuousLinearEquiv.hasSum
/-- Applying a continuous linear map commutes with taking an (infinite) sum. -/
protected theorem ContinuousLinearEquiv.hasSum' {f : ι → M} (e : M ≃SL[σ] M₂) {x : M} :
HasSum (fun b : ι ↦ e (f b)) (e x) ↔ HasSum f x := by
rw [e.hasSum, ContinuousLinearEquiv.symm_apply_apply]
#align continuous_linear_equiv.has_sum' ContinuousLinearEquiv.hasSum'
protected theorem ContinuousLinearEquiv.summable {f : ι → M} (e : M ≃SL[σ] M₂) :
(Summable fun b : ι ↦ e (f b)) ↔ Summable f :=
⟨fun hf ↦ (e.hasSum.1 hf.hasSum).summable, (e : M →SL[σ] M₂).summable⟩
#align continuous_linear_equiv.summable ContinuousLinearEquiv.summable
| Mathlib/Topology/Algebra/InfiniteSum/Module.lean | 167 | 178 | theorem ContinuousLinearEquiv.tsum_eq_iff [T2Space M] [T2Space M₂] {f : ι → M} (e : M ≃SL[σ] M₂)
{y : M₂} : (∑' z, e (f z)) = y ↔ ∑' z, f z = e.symm y := by |
by_cases hf : Summable f
· exact
⟨fun h ↦ (e.hasSum.mp ((e.summable.mpr hf).hasSum_iff.mpr h)).tsum_eq, fun h ↦
(e.hasSum.mpr (hf.hasSum_iff.mpr h)).tsum_eq⟩
· have hf' : ¬Summable fun z ↦ e (f z) := fun h ↦ hf (e.summable.mp h)
rw [tsum_eq_zero_of_not_summable hf, tsum_eq_zero_of_not_summable hf']
refine ⟨?_, fun H ↦ ?_⟩
· rintro rfl
simp
· simpa using congr_arg (fun z ↦ e z) H
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Analysis.InnerProductSpace.Basic
import Mathlib.LinearAlgebra.SesquilinearForm
#align_import analysis.inner_product_space.orthogonal from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Orthogonal complements of submodules
In this file, the `orthogonal` complement of a submodule `K` is defined, and basic API established.
Some of the more subtle results about the orthogonal complement are delayed to
`Analysis.InnerProductSpace.Projection`.
See also `BilinForm.orthogonal` for orthogonality with respect to a general bilinear form.
## Notation
The orthogonal complement of a submodule `K` is denoted by `Kᗮ`.
The proposition that two submodules are orthogonal, `Submodule.IsOrtho`, is denoted by `U ⟂ V`.
Note this is not the same unicode symbol as `⊥` (`Bot`).
-/
variable {𝕜 E F : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
namespace Submodule
variable (K : Submodule 𝕜 E)
/-- The subspace of vectors orthogonal to a given subspace. -/
def orthogonal : Submodule 𝕜 E where
carrier := { v | ∀ u ∈ K, ⟪u, v⟫ = 0 }
zero_mem' _ _ := inner_zero_right _
add_mem' hx hy u hu := by rw [inner_add_right, hx u hu, hy u hu, add_zero]
smul_mem' c x hx u hu := by rw [inner_smul_right, hx u hu, mul_zero]
#align submodule.orthogonal Submodule.orthogonal
@[inherit_doc]
notation:1200 K "ᗮ" => orthogonal K
/-- When a vector is in `Kᗮ`. -/
theorem mem_orthogonal (v : E) : v ∈ Kᗮ ↔ ∀ u ∈ K, ⟪u, v⟫ = 0 :=
Iff.rfl
#align submodule.mem_orthogonal Submodule.mem_orthogonal
/-- When a vector is in `Kᗮ`, with the inner product the
other way round. -/
theorem mem_orthogonal' (v : E) : v ∈ Kᗮ ↔ ∀ u ∈ K, ⟪v, u⟫ = 0 := by
simp_rw [mem_orthogonal, inner_eq_zero_symm]
#align submodule.mem_orthogonal' Submodule.mem_orthogonal'
variable {K}
/-- A vector in `K` is orthogonal to one in `Kᗮ`. -/
theorem inner_right_of_mem_orthogonal {u v : E} (hu : u ∈ K) (hv : v ∈ Kᗮ) : ⟪u, v⟫ = 0 :=
(K.mem_orthogonal v).1 hv u hu
#align submodule.inner_right_of_mem_orthogonal Submodule.inner_right_of_mem_orthogonal
/-- A vector in `Kᗮ` is orthogonal to one in `K`. -/
theorem inner_left_of_mem_orthogonal {u v : E} (hu : u ∈ K) (hv : v ∈ Kᗮ) : ⟪v, u⟫ = 0 := by
rw [inner_eq_zero_symm]; exact inner_right_of_mem_orthogonal hu hv
#align submodule.inner_left_of_mem_orthogonal Submodule.inner_left_of_mem_orthogonal
/-- A vector is in `(𝕜 ∙ u)ᗮ` iff it is orthogonal to `u`. -/
theorem mem_orthogonal_singleton_iff_inner_right {u v : E} : v ∈ (𝕜 ∙ u)ᗮ ↔ ⟪u, v⟫ = 0 := by
refine ⟨inner_right_of_mem_orthogonal (mem_span_singleton_self u), ?_⟩
intro hv w hw
rw [mem_span_singleton] at hw
obtain ⟨c, rfl⟩ := hw
simp [inner_smul_left, hv]
#align submodule.mem_orthogonal_singleton_iff_inner_right Submodule.mem_orthogonal_singleton_iff_inner_right
/-- A vector in `(𝕜 ∙ u)ᗮ` is orthogonal to `u`. -/
theorem mem_orthogonal_singleton_iff_inner_left {u v : E} : v ∈ (𝕜 ∙ u)ᗮ ↔ ⟪v, u⟫ = 0 := by
rw [mem_orthogonal_singleton_iff_inner_right, inner_eq_zero_symm]
#align submodule.mem_orthogonal_singleton_iff_inner_left Submodule.mem_orthogonal_singleton_iff_inner_left
theorem sub_mem_orthogonal_of_inner_left {x y : E} (h : ∀ v : K, ⟪x, v⟫ = ⟪y, v⟫) : x - y ∈ Kᗮ := by
rw [mem_orthogonal']
intro u hu
rw [inner_sub_left, sub_eq_zero]
exact h ⟨u, hu⟩
#align submodule.sub_mem_orthogonal_of_inner_left Submodule.sub_mem_orthogonal_of_inner_left
theorem sub_mem_orthogonal_of_inner_right {x y : E} (h : ∀ v : K, ⟪(v : E), x⟫ = ⟪(v : E), y⟫) :
x - y ∈ Kᗮ := by
intro u hu
rw [inner_sub_right, sub_eq_zero]
exact h ⟨u, hu⟩
#align submodule.sub_mem_orthogonal_of_inner_right Submodule.sub_mem_orthogonal_of_inner_right
variable (K)
/-- `K` and `Kᗮ` have trivial intersection. -/
theorem inf_orthogonal_eq_bot : K ⊓ Kᗮ = ⊥ := by
rw [eq_bot_iff]
intro x
rw [mem_inf]
exact fun ⟨hx, ho⟩ => inner_self_eq_zero.1 (ho x hx)
#align submodule.inf_orthogonal_eq_bot Submodule.inf_orthogonal_eq_bot
/-- `K` and `Kᗮ` have trivial intersection. -/
theorem orthogonal_disjoint : Disjoint K Kᗮ := by simp [disjoint_iff, K.inf_orthogonal_eq_bot]
#align submodule.orthogonal_disjoint Submodule.orthogonal_disjoint
/-- `Kᗮ` can be characterized as the intersection of the kernels of the operations of
inner product with each of the elements of `K`. -/
theorem orthogonal_eq_inter : Kᗮ = ⨅ v : K, LinearMap.ker (innerSL 𝕜 (v : E)) := by
apply le_antisymm
· rw [le_iInf_iff]
rintro ⟨v, hv⟩ w hw
simpa using hw _ hv
· intro v hv w hw
simp only [mem_iInf] at hv
exact hv ⟨w, hw⟩
#align submodule.orthogonal_eq_inter Submodule.orthogonal_eq_inter
/-- The orthogonal complement of any submodule `K` is closed. -/
theorem isClosed_orthogonal : IsClosed (Kᗮ : Set E) := by
rw [orthogonal_eq_inter K]
have := fun v : K => ContinuousLinearMap.isClosed_ker (innerSL 𝕜 (v : E))
convert isClosed_iInter this
simp only [iInf_coe]
#align submodule.is_closed_orthogonal Submodule.isClosed_orthogonal
/-- In a complete space, the orthogonal complement of any submodule `K` is complete. -/
instance instOrthogonalCompleteSpace [CompleteSpace E] : CompleteSpace Kᗮ :=
K.isClosed_orthogonal.completeSpace_coe
variable (𝕜 E)
/-- `orthogonal` gives a `GaloisConnection` between
`Submodule 𝕜 E` and its `OrderDual`. -/
theorem orthogonal_gc :
@GaloisConnection (Submodule 𝕜 E) (Submodule 𝕜 E)ᵒᵈ _ _ orthogonal orthogonal := fun _K₁ _K₂ =>
⟨fun h _v hv _u hu => inner_left_of_mem_orthogonal hv (h hu), fun h _v hv _u hu =>
inner_left_of_mem_orthogonal hv (h hu)⟩
#align submodule.orthogonal_gc Submodule.orthogonal_gc
variable {𝕜 E}
/-- `orthogonal` reverses the `≤` ordering of two
subspaces. -/
theorem orthogonal_le {K₁ K₂ : Submodule 𝕜 E} (h : K₁ ≤ K₂) : K₂ᗮ ≤ K₁ᗮ :=
(orthogonal_gc 𝕜 E).monotone_l h
#align submodule.orthogonal_le Submodule.orthogonal_le
/-- `orthogonal.orthogonal` preserves the `≤` ordering of two
subspaces. -/
theorem orthogonal_orthogonal_monotone {K₁ K₂ : Submodule 𝕜 E} (h : K₁ ≤ K₂) : K₁ᗮᗮ ≤ K₂ᗮᗮ :=
orthogonal_le (orthogonal_le h)
#align submodule.orthogonal_orthogonal_monotone Submodule.orthogonal_orthogonal_monotone
/-- `K` is contained in `Kᗮᗮ`. -/
theorem le_orthogonal_orthogonal : K ≤ Kᗮᗮ :=
(orthogonal_gc 𝕜 E).le_u_l _
#align submodule.le_orthogonal_orthogonal Submodule.le_orthogonal_orthogonal
/-- The inf of two orthogonal subspaces equals the subspace orthogonal
to the sup. -/
theorem inf_orthogonal (K₁ K₂ : Submodule 𝕜 E) : K₁ᗮ ⊓ K₂ᗮ = (K₁ ⊔ K₂)ᗮ :=
(orthogonal_gc 𝕜 E).l_sup.symm
#align submodule.inf_orthogonal Submodule.inf_orthogonal
/-- The inf of an indexed family of orthogonal subspaces equals the
subspace orthogonal to the sup. -/
theorem iInf_orthogonal {ι : Type*} (K : ι → Submodule 𝕜 E) : ⨅ i, (K i)ᗮ = (iSup K)ᗮ :=
(orthogonal_gc 𝕜 E).l_iSup.symm
#align submodule.infi_orthogonal Submodule.iInf_orthogonal
/-- The inf of a set of orthogonal subspaces equals the subspace orthogonal to the sup. -/
theorem sInf_orthogonal (s : Set <| Submodule 𝕜 E) : ⨅ K ∈ s, Kᗮ = (sSup s)ᗮ :=
(orthogonal_gc 𝕜 E).l_sSup.symm
#align submodule.Inf_orthogonal Submodule.sInf_orthogonal
@[simp]
theorem top_orthogonal_eq_bot : (⊤ : Submodule 𝕜 E)ᗮ = ⊥ := by
ext x
rw [mem_bot, mem_orthogonal]
exact
⟨fun h => inner_self_eq_zero.mp (h x mem_top), by
rintro rfl
simp⟩
#align submodule.top_orthogonal_eq_bot Submodule.top_orthogonal_eq_bot
@[simp]
theorem bot_orthogonal_eq_top : (⊥ : Submodule 𝕜 E)ᗮ = ⊤ := by
rw [← top_orthogonal_eq_bot, eq_top_iff]
exact le_orthogonal_orthogonal ⊤
#align submodule.bot_orthogonal_eq_top Submodule.bot_orthogonal_eq_top
@[simp]
theorem orthogonal_eq_top_iff : Kᗮ = ⊤ ↔ K = ⊥ := by
refine
⟨?_, by
rintro rfl
exact bot_orthogonal_eq_top⟩
intro h
have : K ⊓ Kᗮ = ⊥ := K.orthogonal_disjoint.eq_bot
rwa [h, inf_comm, top_inf_eq] at this
#align submodule.orthogonal_eq_top_iff Submodule.orthogonal_eq_top_iff
theorem orthogonalFamily_self :
OrthogonalFamily 𝕜 (fun b => ↥(cond b K Kᗮ)) fun b => (cond b K Kᗮ).subtypeₗᵢ
| true, true => absurd rfl
| true, false => fun _ x y => inner_right_of_mem_orthogonal x.prop y.prop
| false, true => fun _ x y => inner_left_of_mem_orthogonal y.prop x.prop
| false, false => absurd rfl
#align submodule.orthogonal_family_self Submodule.orthogonalFamily_self
end Submodule
@[simp]
theorem bilinFormOfRealInner_orthogonal {E} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
(K : Submodule ℝ E) : K.orthogonalBilin bilinFormOfRealInner = Kᗮ :=
rfl
#align bilin_form_of_real_inner_orthogonal bilinFormOfRealInner_orthogonal
/-!
### Orthogonality of submodules
In this section we define `Submodule.IsOrtho U V`, with notation `U ⟂ V`.
The API roughly matches that of `Disjoint`.
-/
namespace Submodule
/-- The proposition that two submodules are orthogonal. Has notation `U ⟂ V`. -/
def IsOrtho (U V : Submodule 𝕜 E) : Prop :=
U ≤ Vᗮ
#align submodule.is_ortho Submodule.IsOrtho
@[inherit_doc]
infixl:50 " ⟂ " => Submodule.IsOrtho
theorem isOrtho_iff_le {U V : Submodule 𝕜 E} : U ⟂ V ↔ U ≤ Vᗮ :=
Iff.rfl
#align submodule.is_ortho_iff_le Submodule.isOrtho_iff_le
@[symm]
theorem IsOrtho.symm {U V : Submodule 𝕜 E} (h : U ⟂ V) : V ⟂ U :=
(le_orthogonal_orthogonal _).trans (orthogonal_le h)
#align submodule.is_ortho.symm Submodule.IsOrtho.symm
theorem isOrtho_comm {U V : Submodule 𝕜 E} : U ⟂ V ↔ V ⟂ U :=
⟨IsOrtho.symm, IsOrtho.symm⟩
#align submodule.is_ortho_comm Submodule.isOrtho_comm
theorem symmetric_isOrtho : Symmetric (IsOrtho : Submodule 𝕜 E → Submodule 𝕜 E → Prop) := fun _ _ =>
IsOrtho.symm
#align submodule.symmetric_is_ortho Submodule.symmetric_isOrtho
theorem IsOrtho.inner_eq {U V : Submodule 𝕜 E} (h : U ⟂ V) {u v : E} (hu : u ∈ U) (hv : v ∈ V) :
⟪u, v⟫ = 0 :=
h.symm hv _ hu
#align submodule.is_ortho.inner_eq Submodule.IsOrtho.inner_eq
theorem isOrtho_iff_inner_eq {U V : Submodule 𝕜 E} : U ⟂ V ↔ ∀ u ∈ U, ∀ v ∈ V, ⟪u, v⟫ = 0 :=
forall₄_congr fun _u _hu _v _hv => inner_eq_zero_symm
#align submodule.is_ortho_iff_inner_eq Submodule.isOrtho_iff_inner_eq
/- TODO: generalize `Submodule.map₂` to semilinear maps, so that we can state
`U ⟂ V ↔ Submodule.map₂ (innerₛₗ 𝕜) U V ≤ ⊥`. -/
@[simp]
theorem isOrtho_bot_left {V : Submodule 𝕜 E} : ⊥ ⟂ V :=
bot_le
#align submodule.is_ortho_bot_left Submodule.isOrtho_bot_left
@[simp]
theorem isOrtho_bot_right {U : Submodule 𝕜 E} : U ⟂ ⊥ :=
isOrtho_bot_left.symm
#align submodule.is_ortho_bot_right Submodule.isOrtho_bot_right
theorem IsOrtho.mono_left {U₁ U₂ V : Submodule 𝕜 E} (hU : U₂ ≤ U₁) (h : U₁ ⟂ V) : U₂ ⟂ V :=
hU.trans h
#align submodule.is_ortho.mono_left Submodule.IsOrtho.mono_left
theorem IsOrtho.mono_right {U V₁ V₂ : Submodule 𝕜 E} (hV : V₂ ≤ V₁) (h : U ⟂ V₁) : U ⟂ V₂ :=
(h.symm.mono_left hV).symm
#align submodule.is_ortho.mono_right Submodule.IsOrtho.mono_right
theorem IsOrtho.mono {U₁ V₁ U₂ V₂ : Submodule 𝕜 E} (hU : U₂ ≤ U₁) (hV : V₂ ≤ V₁) (h : U₁ ⟂ V₁) :
U₂ ⟂ V₂ :=
(h.mono_right hV).mono_left hU
#align submodule.is_ortho.mono Submodule.IsOrtho.mono
@[simp]
theorem isOrtho_self {U : Submodule 𝕜 E} : U ⟂ U ↔ U = ⊥ :=
⟨fun h => eq_bot_iff.mpr fun x hx => inner_self_eq_zero.mp (h hx x hx), fun h =>
h.symm ▸ isOrtho_bot_left⟩
#align submodule.is_ortho_self Submodule.isOrtho_self
@[simp]
theorem isOrtho_orthogonal_right (U : Submodule 𝕜 E) : U ⟂ Uᗮ :=
le_orthogonal_orthogonal _
#align submodule.is_ortho_orthogonal_right Submodule.isOrtho_orthogonal_right
@[simp]
theorem isOrtho_orthogonal_left (U : Submodule 𝕜 E) : Uᗮ ⟂ U :=
(isOrtho_orthogonal_right U).symm
#align submodule.is_ortho_orthogonal_left Submodule.isOrtho_orthogonal_left
theorem IsOrtho.le {U V : Submodule 𝕜 E} (h : U ⟂ V) : U ≤ Vᗮ :=
h
#align submodule.is_ortho.le Submodule.IsOrtho.le
theorem IsOrtho.ge {U V : Submodule 𝕜 E} (h : U ⟂ V) : V ≤ Uᗮ :=
h.symm
#align submodule.is_ortho.ge Submodule.IsOrtho.ge
@[simp]
theorem isOrtho_top_right {U : Submodule 𝕜 E} : U ⟂ ⊤ ↔ U = ⊥ :=
⟨fun h => eq_bot_iff.mpr fun _x hx => inner_self_eq_zero.mp (h hx _ mem_top), fun h =>
h.symm ▸ isOrtho_bot_left⟩
#align submodule.is_ortho_top_right Submodule.isOrtho_top_right
@[simp]
theorem isOrtho_top_left {V : Submodule 𝕜 E} : ⊤ ⟂ V ↔ V = ⊥ :=
isOrtho_comm.trans isOrtho_top_right
#align submodule.is_ortho_top_left Submodule.isOrtho_top_left
/-- Orthogonal submodules are disjoint. -/
theorem IsOrtho.disjoint {U V : Submodule 𝕜 E} (h : U ⟂ V) : Disjoint U V :=
(Submodule.orthogonal_disjoint _).mono_right h.symm
#align submodule.is_ortho.disjoint Submodule.IsOrtho.disjoint
@[simp]
theorem isOrtho_sup_left {U₁ U₂ V : Submodule 𝕜 E} : U₁ ⊔ U₂ ⟂ V ↔ U₁ ⟂ V ∧ U₂ ⟂ V :=
sup_le_iff
#align submodule.is_ortho_sup_left Submodule.isOrtho_sup_left
@[simp]
theorem isOrtho_sup_right {U V₁ V₂ : Submodule 𝕜 E} : U ⟂ V₁ ⊔ V₂ ↔ U ⟂ V₁ ∧ U ⟂ V₂ :=
isOrtho_comm.trans <| isOrtho_sup_left.trans <| isOrtho_comm.and isOrtho_comm
#align submodule.is_ortho_sup_right Submodule.isOrtho_sup_right
@[simp]
theorem isOrtho_sSup_left {U : Set (Submodule 𝕜 E)} {V : Submodule 𝕜 E} :
sSup U ⟂ V ↔ ∀ Uᵢ ∈ U, Uᵢ ⟂ V :=
sSup_le_iff
#align submodule.is_ortho_Sup_left Submodule.isOrtho_sSup_left
@[simp]
theorem isOrtho_sSup_right {U : Submodule 𝕜 E} {V : Set (Submodule 𝕜 E)} :
U ⟂ sSup V ↔ ∀ Vᵢ ∈ V, U ⟂ Vᵢ :=
isOrtho_comm.trans <| isOrtho_sSup_left.trans <| by simp_rw [isOrtho_comm]
#align submodule.is_ortho_Sup_right Submodule.isOrtho_sSup_right
@[simp]
theorem isOrtho_iSup_left {ι : Sort*} {U : ι → Submodule 𝕜 E} {V : Submodule 𝕜 E} :
iSup U ⟂ V ↔ ∀ i, U i ⟂ V :=
iSup_le_iff
#align submodule.is_ortho_supr_left Submodule.isOrtho_iSup_left
@[simp]
theorem isOrtho_iSup_right {ι : Sort*} {U : Submodule 𝕜 E} {V : ι → Submodule 𝕜 E} :
U ⟂ iSup V ↔ ∀ i, U ⟂ V i :=
isOrtho_comm.trans <| isOrtho_iSup_left.trans <| by simp_rw [isOrtho_comm]
#align submodule.is_ortho_supr_right Submodule.isOrtho_iSup_right
@[simp]
theorem isOrtho_span {s t : Set E} :
span 𝕜 s ⟂ span 𝕜 t ↔ ∀ ⦃u⦄, u ∈ s → ∀ ⦃v⦄, v ∈ t → ⟪u, v⟫ = 0 := by
simp_rw [span_eq_iSup_of_singleton_spans s, span_eq_iSup_of_singleton_spans t, isOrtho_iSup_left,
isOrtho_iSup_right, isOrtho_iff_le, span_le, Set.subset_def, SetLike.mem_coe,
mem_orthogonal_singleton_iff_inner_left, Set.mem_singleton_iff, forall_eq]
#align submodule.is_ortho_span Submodule.isOrtho_span
| Mathlib/Analysis/InnerProductSpace/Orthogonal.lean | 379 | 383 | theorem IsOrtho.map (f : E →ₗᵢ[𝕜] F) {U V : Submodule 𝕜 E} (h : U ⟂ V) : U.map f ⟂ V.map f := by |
rw [isOrtho_iff_inner_eq] at *
simp_rw [mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂,
LinearIsometry.inner_map_map]
exact h
|
/-
Copyright (c) 2019 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Yury Kudryashov, Sébastien Gouëzel, Chris Hughes
-/
import Mathlib.Algebra.Group.Basic
import Mathlib.Algebra.Group.Pi.Basic
import Mathlib.Order.Fin
import Mathlib.Order.PiLex
import Mathlib.Order.Interval.Set.Basic
#align_import data.fin.tuple.basic from "leanprover-community/mathlib"@"ef997baa41b5c428be3fb50089a7139bf4ee886b"
/-!
# Operation on tuples
We interpret maps `∀ i : Fin n, α i` as `n`-tuples of elements of possibly varying type `α i`,
`(α 0, …, α (n-1))`. A particular case is `Fin n → α` of elements with all the same type.
In this case when `α i` is a constant map, then tuples are isomorphic (but not definitionally equal)
to `Vector`s.
We define the following operations:
* `Fin.tail` : the tail of an `n+1` tuple, i.e., its last `n` entries;
* `Fin.cons` : adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple;
* `Fin.init` : the beginning of an `n+1` tuple, i.e., its first `n` entries;
* `Fin.snoc` : adding an element at the end of an `n`-tuple, to get an `n+1`-tuple. The name `snoc`
comes from `cons` (i.e., adding an element to the left of a tuple) read in reverse order.
* `Fin.insertNth` : insert an element to a tuple at a given position.
* `Fin.find p` : returns the first index `n` where `p n` is satisfied, and `none` if it is never
satisfied.
* `Fin.append a b` : append two tuples.
* `Fin.repeat n a` : repeat a tuple `n` times.
-/
assert_not_exists MonoidWithZero
universe u v
namespace Fin
variable {m n : ℕ}
open Function
section Tuple
/-- There is exactly one tuple of size zero. -/
example (α : Fin 0 → Sort u) : Unique (∀ i : Fin 0, α i) := by infer_instance
theorem tuple0_le {α : Fin 0 → Type*} [∀ i, Preorder (α i)] (f g : ∀ i, α i) : f ≤ g :=
finZeroElim
#align fin.tuple0_le Fin.tuple0_le
variable {α : Fin (n + 1) → Type u} (x : α 0) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.succ) (i : Fin n)
(y : α i.succ) (z : α 0)
/-- The tail of an `n+1` tuple, i.e., its last `n` entries. -/
def tail (q : ∀ i, α i) : ∀ i : Fin n, α i.succ := fun i ↦ q i.succ
#align fin.tail Fin.tail
theorem tail_def {n : ℕ} {α : Fin (n + 1) → Type*} {q : ∀ i, α i} :
(tail fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.succ :=
rfl
#align fin.tail_def Fin.tail_def
/-- Adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple. -/
def cons (x : α 0) (p : ∀ i : Fin n, α i.succ) : ∀ i, α i := fun j ↦ Fin.cases x p j
#align fin.cons Fin.cons
@[simp]
theorem tail_cons : tail (cons x p) = p := by
simp (config := { unfoldPartialApp := true }) [tail, cons]
#align fin.tail_cons Fin.tail_cons
@[simp]
theorem cons_succ : cons x p i.succ = p i := by simp [cons]
#align fin.cons_succ Fin.cons_succ
@[simp]
theorem cons_zero : cons x p 0 = x := by simp [cons]
#align fin.cons_zero Fin.cons_zero
@[simp]
theorem cons_one {α : Fin (n + 2) → Type*} (x : α 0) (p : ∀ i : Fin n.succ, α i.succ) :
cons x p 1 = p 0 := by
rw [← cons_succ x p]; rfl
/-- Updating a tuple and adding an element at the beginning commute. -/
@[simp]
theorem cons_update : cons x (update p i y) = update (cons x p) i.succ y := by
ext j
by_cases h : j = 0
· rw [h]
simp [Ne.symm (succ_ne_zero i)]
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ]
by_cases h' : j' = i
· rw [h']
simp
· have : j'.succ ≠ i.succ := by rwa [Ne, succ_inj]
rw [update_noteq h', update_noteq this, cons_succ]
#align fin.cons_update Fin.cons_update
/-- As a binary function, `Fin.cons` is injective. -/
theorem cons_injective2 : Function.Injective2 (@cons n α) := fun x₀ y₀ x y h ↦
⟨congr_fun h 0, funext fun i ↦ by simpa using congr_fun h (Fin.succ i)⟩
#align fin.cons_injective2 Fin.cons_injective2
@[simp]
theorem cons_eq_cons {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} :
cons x₀ x = cons y₀ y ↔ x₀ = y₀ ∧ x = y :=
cons_injective2.eq_iff
#align fin.cons_eq_cons Fin.cons_eq_cons
theorem cons_left_injective (x : ∀ i : Fin n, α i.succ) : Function.Injective fun x₀ ↦ cons x₀ x :=
cons_injective2.left _
#align fin.cons_left_injective Fin.cons_left_injective
theorem cons_right_injective (x₀ : α 0) : Function.Injective (cons x₀) :=
cons_injective2.right _
#align fin.cons_right_injective Fin.cons_right_injective
/-- Adding an element at the beginning of a tuple and then updating it amounts to adding it
directly. -/
theorem update_cons_zero : update (cons x p) 0 z = cons z p := by
ext j
by_cases h : j = 0
· rw [h]
simp
· simp only [h, update_noteq, Ne, not_false_iff]
let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ, cons_succ]
#align fin.update_cons_zero Fin.update_cons_zero
/-- Concatenating the first element of a tuple with its tail gives back the original tuple -/
@[simp, nolint simpNF] -- Porting note: linter claims LHS doesn't simplify
theorem cons_self_tail : cons (q 0) (tail q) = q := by
ext j
by_cases h : j = 0
· rw [h]
simp
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this]
unfold tail
rw [cons_succ]
#align fin.cons_self_tail Fin.cons_self_tail
-- Porting note: Mathport removes `_root_`?
/-- Recurse on an `n+1`-tuple by splitting it into a single element and an `n`-tuple. -/
@[elab_as_elim]
def consCases {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x))
(x : ∀ i : Fin n.succ, α i) : P x :=
_root_.cast (by rw [cons_self_tail]) <| h (x 0) (tail x)
#align fin.cons_cases Fin.consCases
@[simp]
theorem consCases_cons {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x))
(x₀ : α 0) (x : ∀ i : Fin n, α i.succ) : @consCases _ _ _ h (cons x₀ x) = h x₀ x := by
rw [consCases, cast_eq]
congr
#align fin.cons_cases_cons Fin.consCases_cons
/-- Recurse on a tuple by splitting into `Fin.elim0` and `Fin.cons`. -/
@[elab_as_elim]
def consInduction {α : Type*} {P : ∀ {n : ℕ}, (Fin n → α) → Sort v} (h0 : P Fin.elim0)
(h : ∀ {n} (x₀) (x : Fin n → α), P x → P (Fin.cons x₀ x)) : ∀ {n : ℕ} (x : Fin n → α), P x
| 0, x => by convert h0
| n + 1, x => consCases (fun x₀ x ↦ h _ _ <| consInduction h0 h _) x
#align fin.cons_induction Fin.consInductionₓ -- Porting note: universes
theorem cons_injective_of_injective {α} {x₀ : α} {x : Fin n → α} (hx₀ : x₀ ∉ Set.range x)
(hx : Function.Injective x) : Function.Injective (cons x₀ x : Fin n.succ → α) := by
refine Fin.cases ?_ ?_
· refine Fin.cases ?_ ?_
· intro
rfl
· intro j h
rw [cons_zero, cons_succ] at h
exact hx₀.elim ⟨_, h.symm⟩
· intro i
refine Fin.cases ?_ ?_
· intro h
rw [cons_zero, cons_succ] at h
exact hx₀.elim ⟨_, h⟩
· intro j h
rw [cons_succ, cons_succ] at h
exact congr_arg _ (hx h)
#align fin.cons_injective_of_injective Fin.cons_injective_of_injective
theorem cons_injective_iff {α} {x₀ : α} {x : Fin n → α} :
Function.Injective (cons x₀ x : Fin n.succ → α) ↔ x₀ ∉ Set.range x ∧ Function.Injective x := by
refine ⟨fun h ↦ ⟨?_, ?_⟩, fun h ↦ cons_injective_of_injective h.1 h.2⟩
· rintro ⟨i, hi⟩
replace h := @h i.succ 0
simp [hi, succ_ne_zero] at h
· simpa [Function.comp] using h.comp (Fin.succ_injective _)
#align fin.cons_injective_iff Fin.cons_injective_iff
@[simp]
theorem forall_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} :
(∀ x, P x) ↔ P finZeroElim :=
⟨fun h ↦ h _, fun h x ↦ Subsingleton.elim finZeroElim x ▸ h⟩
#align fin.forall_fin_zero_pi Fin.forall_fin_zero_pi
@[simp]
theorem exists_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} :
(∃ x, P x) ↔ P finZeroElim :=
⟨fun ⟨x, h⟩ ↦ Subsingleton.elim x finZeroElim ▸ h, fun h ↦ ⟨_, h⟩⟩
#align fin.exists_fin_zero_pi Fin.exists_fin_zero_pi
theorem forall_fin_succ_pi {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ ∀ a v, P (Fin.cons a v) :=
⟨fun h a v ↦ h (Fin.cons a v), consCases⟩
#align fin.forall_fin_succ_pi Fin.forall_fin_succ_pi
theorem exists_fin_succ_pi {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ ∃ a v, P (Fin.cons a v) :=
⟨fun ⟨x, h⟩ ↦ ⟨x 0, tail x, (cons_self_tail x).symm ▸ h⟩, fun ⟨_, _, h⟩ ↦ ⟨_, h⟩⟩
#align fin.exists_fin_succ_pi Fin.exists_fin_succ_pi
/-- Updating the first element of a tuple does not change the tail. -/
@[simp]
theorem tail_update_zero : tail (update q 0 z) = tail q := by
ext j
simp [tail, Fin.succ_ne_zero]
#align fin.tail_update_zero Fin.tail_update_zero
/-- Updating a nonzero element and taking the tail commute. -/
@[simp]
theorem tail_update_succ : tail (update q i.succ y) = update (tail q) i y := by
ext j
by_cases h : j = i
· rw [h]
simp [tail]
· simp [tail, (Fin.succ_injective n).ne h, h]
#align fin.tail_update_succ Fin.tail_update_succ
theorem comp_cons {α : Type*} {β : Type*} (g : α → β) (y : α) (q : Fin n → α) :
g ∘ cons y q = cons (g y) (g ∘ q) := by
ext j
by_cases h : j = 0
· rw [h]
rfl
· let j' := pred j h
have : j'.succ = j := succ_pred j h
rw [← this, cons_succ, comp_apply, comp_apply, cons_succ]
#align fin.comp_cons Fin.comp_cons
| Mathlib/Data/Fin/Tuple/Basic.lean | 252 | 255 | theorem comp_tail {α : Type*} {β : Type*} (g : α → β) (q : Fin n.succ → α) :
g ∘ tail q = tail (g ∘ q) := by |
ext j
simp [tail]
|
/-
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
-/
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.Ring.Divisibility.Basic
import Mathlib.Data.List.Cycle
import Mathlib.Data.Nat.Prime
import Mathlib.Data.PNat.Basic
import Mathlib.Dynamics.FixedPoints.Basic
import Mathlib.GroupTheory.GroupAction.Group
#align_import dynamics.periodic_pts from "leanprover-community/mathlib"@"d07245fd37786daa997af4f1a73a49fa3b748408"
/-!
# Periodic points
A point `x : α` is a periodic point of `f : α → α` of period `n` if `f^[n] x = x`.
## Main definitions
* `IsPeriodicPt f n x` : `x` is a periodic point of `f` of period `n`, i.e. `f^[n] x = x`.
We do not require `n > 0` in the definition.
* `ptsOfPeriod f n` : the set `{x | IsPeriodicPt f n x}`. Note that `n` is not required to
be the minimal period of `x`.
* `periodicPts f` : the set of all periodic points of `f`.
* `minimalPeriod f x` : the minimal period of a point `x` under an endomorphism `f` or zero
if `x` is not a periodic point of `f`.
* `orbit f x`: the cycle `[x, f x, f (f x), ...]` for a periodic point.
* `MulAction.period g x` : the minimal period of a point `x` under the multiplicative action of `g`;
an equivalent `AddAction.period g x` is defined for additive actions.
## Main statements
We provide “dot syntax”-style operations on terms of the form `h : IsPeriodicPt f n x` including
arithmetic operations on `n` and `h.map (hg : SemiconjBy g f f')`. We also prove that `f`
is bijective on each set `ptsOfPeriod f n` and on `periodicPts f`. Finally, we prove that `x`
is a periodic point of `f` of period `n` if and only if `minimalPeriod f x | n`.
## References
* https://en.wikipedia.org/wiki/Periodic_point
-/
open Set
namespace Function
open Function (Commute)
variable {α : Type*} {β : Type*} {f fa : α → α} {fb : β → β} {x y : α} {m n : ℕ}
/-- A point `x` is a periodic point of `f : α → α` of period `n` if `f^[n] x = x`.
Note that we do not require `0 < n` in this definition. Many theorems about periodic points
need this assumption. -/
def IsPeriodicPt (f : α → α) (n : ℕ) (x : α) :=
IsFixedPt f^[n] x
#align function.is_periodic_pt Function.IsPeriodicPt
/-- A fixed point of `f` is a periodic point of `f` of any prescribed period. -/
theorem IsFixedPt.isPeriodicPt (hf : IsFixedPt f x) (n : ℕ) : IsPeriodicPt f n x :=
hf.iterate n
#align function.is_fixed_pt.is_periodic_pt Function.IsFixedPt.isPeriodicPt
/-- For the identity map, all points are periodic. -/
theorem is_periodic_id (n : ℕ) (x : α) : IsPeriodicPt id n x :=
(isFixedPt_id x).isPeriodicPt n
#align function.is_periodic_id Function.is_periodic_id
/-- Any point is a periodic point of period `0`. -/
theorem isPeriodicPt_zero (f : α → α) (x : α) : IsPeriodicPt f 0 x :=
isFixedPt_id x
#align function.is_periodic_pt_zero Function.isPeriodicPt_zero
namespace IsPeriodicPt
instance [DecidableEq α] {f : α → α} {n : ℕ} {x : α} : Decidable (IsPeriodicPt f n x) :=
IsFixedPt.decidable
protected theorem isFixedPt (hf : IsPeriodicPt f n x) : IsFixedPt f^[n] x :=
hf
#align function.is_periodic_pt.is_fixed_pt Function.IsPeriodicPt.isFixedPt
protected theorem map (hx : IsPeriodicPt fa n x) {g : α → β} (hg : Semiconj g fa fb) :
IsPeriodicPt fb n (g x) :=
IsFixedPt.map hx (hg.iterate_right n)
#align function.is_periodic_pt.map Function.IsPeriodicPt.map
theorem apply_iterate (hx : IsPeriodicPt f n x) (m : ℕ) : IsPeriodicPt f n (f^[m] x) :=
hx.map <| Commute.iterate_self f m
#align function.is_periodic_pt.apply_iterate Function.IsPeriodicPt.apply_iterate
protected theorem apply (hx : IsPeriodicPt f n x) : IsPeriodicPt f n (f x) :=
hx.apply_iterate 1
#align function.is_periodic_pt.apply Function.IsPeriodicPt.apply
protected theorem add (hn : IsPeriodicPt f n x) (hm : IsPeriodicPt f m x) :
IsPeriodicPt f (n + m) x := by
rw [IsPeriodicPt, iterate_add]
exact hn.comp hm
#align function.is_periodic_pt.add Function.IsPeriodicPt.add
theorem left_of_add (hn : IsPeriodicPt f (n + m) x) (hm : IsPeriodicPt f m x) :
IsPeriodicPt f n x := by
rw [IsPeriodicPt, iterate_add] at hn
exact hn.left_of_comp hm
#align function.is_periodic_pt.left_of_add Function.IsPeriodicPt.left_of_add
theorem right_of_add (hn : IsPeriodicPt f (n + m) x) (hm : IsPeriodicPt f n x) :
IsPeriodicPt f m x := by
rw [add_comm] at hn
exact hn.left_of_add hm
#align function.is_periodic_pt.right_of_add Function.IsPeriodicPt.right_of_add
protected theorem sub (hm : IsPeriodicPt f m x) (hn : IsPeriodicPt f n x) :
IsPeriodicPt f (m - n) x := by
rcases le_total n m with h | h
· refine left_of_add ?_ hn
rwa [tsub_add_cancel_of_le h]
· rw [tsub_eq_zero_iff_le.mpr h]
apply isPeriodicPt_zero
#align function.is_periodic_pt.sub Function.IsPeriodicPt.sub
protected theorem mul_const (hm : IsPeriodicPt f m x) (n : ℕ) : IsPeriodicPt f (m * n) x := by
simp only [IsPeriodicPt, iterate_mul, hm.isFixedPt.iterate n]
#align function.is_periodic_pt.mul_const Function.IsPeriodicPt.mul_const
protected theorem const_mul (hm : IsPeriodicPt f m x) (n : ℕ) : IsPeriodicPt f (n * m) x := by
simp only [mul_comm n, hm.mul_const n]
#align function.is_periodic_pt.const_mul Function.IsPeriodicPt.const_mul
theorem trans_dvd (hm : IsPeriodicPt f m x) {n : ℕ} (hn : m ∣ n) : IsPeriodicPt f n x :=
let ⟨k, hk⟩ := hn
hk.symm ▸ hm.mul_const k
#align function.is_periodic_pt.trans_dvd Function.IsPeriodicPt.trans_dvd
protected theorem iterate (hf : IsPeriodicPt f n x) (m : ℕ) : IsPeriodicPt f^[m] n x := by
rw [IsPeriodicPt, ← iterate_mul, mul_comm, iterate_mul]
exact hf.isFixedPt.iterate m
#align function.is_periodic_pt.iterate Function.IsPeriodicPt.iterate
theorem comp {g : α → α} (hco : Commute f g) (hf : IsPeriodicPt f n x) (hg : IsPeriodicPt g n x) :
IsPeriodicPt (f ∘ g) n x := by
rw [IsPeriodicPt, hco.comp_iterate]
exact IsFixedPt.comp hf hg
#align function.is_periodic_pt.comp Function.IsPeriodicPt.comp
theorem comp_lcm {g : α → α} (hco : Commute f g) (hf : IsPeriodicPt f m x)
(hg : IsPeriodicPt g n x) : IsPeriodicPt (f ∘ g) (Nat.lcm m n) x :=
(hf.trans_dvd <| Nat.dvd_lcm_left _ _).comp hco (hg.trans_dvd <| Nat.dvd_lcm_right _ _)
#align function.is_periodic_pt.comp_lcm Function.IsPeriodicPt.comp_lcm
theorem left_of_comp {g : α → α} (hco : Commute f g) (hfg : IsPeriodicPt (f ∘ g) n x)
(hg : IsPeriodicPt g n x) : IsPeriodicPt f n x := by
rw [IsPeriodicPt, hco.comp_iterate] at hfg
exact hfg.left_of_comp hg
#align function.is_periodic_pt.left_of_comp Function.IsPeriodicPt.left_of_comp
theorem iterate_mod_apply (h : IsPeriodicPt f n x) (m : ℕ) : f^[m % n] x = f^[m] x := by
conv_rhs => rw [← Nat.mod_add_div m n, iterate_add_apply, (h.mul_const _).eq]
#align function.is_periodic_pt.iterate_mod_apply Function.IsPeriodicPt.iterate_mod_apply
protected theorem mod (hm : IsPeriodicPt f m x) (hn : IsPeriodicPt f n x) :
IsPeriodicPt f (m % n) x :=
(hn.iterate_mod_apply m).trans hm
#align function.is_periodic_pt.mod Function.IsPeriodicPt.mod
protected theorem gcd (hm : IsPeriodicPt f m x) (hn : IsPeriodicPt f n x) :
IsPeriodicPt f (m.gcd n) x := by
revert hm hn
refine Nat.gcd.induction m n (fun n _ hn => ?_) fun m n _ ih hm hn => ?_
· rwa [Nat.gcd_zero_left]
· rw [Nat.gcd_rec]
exact ih (hn.mod hm) hm
#align function.is_periodic_pt.gcd Function.IsPeriodicPt.gcd
/-- If `f` sends two periodic points `x` and `y` of the same positive period to the same point,
then `x = y`. For a similar statement about points of different periods see `eq_of_apply_eq`. -/
theorem eq_of_apply_eq_same (hx : IsPeriodicPt f n x) (hy : IsPeriodicPt f n y) (hn : 0 < n)
(h : f x = f y) : x = y := by
rw [← hx.eq, ← hy.eq, ← iterate_pred_comp_of_pos f hn, comp_apply, comp_apply, h]
#align function.is_periodic_pt.eq_of_apply_eq_same Function.IsPeriodicPt.eq_of_apply_eq_same
/-- If `f` sends two periodic points `x` and `y` of positive periods to the same point,
then `x = y`. -/
theorem eq_of_apply_eq (hx : IsPeriodicPt f m x) (hy : IsPeriodicPt f n y) (hm : 0 < m) (hn : 0 < n)
(h : f x = f y) : x = y :=
(hx.mul_const n).eq_of_apply_eq_same (hy.const_mul m) (mul_pos hm hn) h
#align function.is_periodic_pt.eq_of_apply_eq Function.IsPeriodicPt.eq_of_apply_eq
end IsPeriodicPt
/-- The set of periodic points of a given (possibly non-minimal) period. -/
def ptsOfPeriod (f : α → α) (n : ℕ) : Set α :=
{ x : α | IsPeriodicPt f n x }
#align function.pts_of_period Function.ptsOfPeriod
@[simp]
theorem mem_ptsOfPeriod : x ∈ ptsOfPeriod f n ↔ IsPeriodicPt f n x :=
Iff.rfl
#align function.mem_pts_of_period Function.mem_ptsOfPeriod
theorem Semiconj.mapsTo_ptsOfPeriod {g : α → β} (h : Semiconj g fa fb) (n : ℕ) :
MapsTo g (ptsOfPeriod fa n) (ptsOfPeriod fb n) :=
(h.iterate_right n).mapsTo_fixedPoints
#align function.semiconj.maps_to_pts_of_period Function.Semiconj.mapsTo_ptsOfPeriod
theorem bijOn_ptsOfPeriod (f : α → α) {n : ℕ} (hn : 0 < n) :
BijOn f (ptsOfPeriod f n) (ptsOfPeriod f n) :=
⟨(Commute.refl f).mapsTo_ptsOfPeriod n, fun x hx y hy hxy => hx.eq_of_apply_eq_same hy hn hxy,
fun x hx =>
⟨f^[n.pred] x, hx.apply_iterate _, by
rw [← comp_apply (f := f), comp_iterate_pred_of_pos f hn, hx.eq]⟩⟩
#align function.bij_on_pts_of_period Function.bijOn_ptsOfPeriod
theorem directed_ptsOfPeriod_pNat (f : α → α) : Directed (· ⊆ ·) fun n : ℕ+ => ptsOfPeriod f n :=
fun m n => ⟨m * n, fun _ hx => hx.mul_const n, fun _ hx => hx.const_mul m⟩
#align function.directed_pts_of_period_pnat Function.directed_ptsOfPeriod_pNat
/-- The set of periodic points of a map `f : α → α`. -/
def periodicPts (f : α → α) : Set α :=
{ x : α | ∃ n > 0, IsPeriodicPt f n x }
#align function.periodic_pts Function.periodicPts
theorem mk_mem_periodicPts (hn : 0 < n) (hx : IsPeriodicPt f n x) : x ∈ periodicPts f :=
⟨n, hn, hx⟩
#align function.mk_mem_periodic_pts Function.mk_mem_periodicPts
theorem mem_periodicPts : x ∈ periodicPts f ↔ ∃ n > 0, IsPeriodicPt f n x :=
Iff.rfl
#align function.mem_periodic_pts Function.mem_periodicPts
theorem isPeriodicPt_of_mem_periodicPts_of_isPeriodicPt_iterate (hx : x ∈ periodicPts f)
(hm : IsPeriodicPt f m (f^[n] x)) : IsPeriodicPt f m x := by
rcases hx with ⟨r, hr, hr'⟩
suffices n ≤ (n / r + 1) * r by
-- Porting note: convert used to unfold IsPeriodicPt
change _ = _
convert (hm.apply_iterate ((n / r + 1) * r - n)).eq <;>
rw [← iterate_add_apply, Nat.sub_add_cancel this, iterate_mul, (hr'.iterate _).eq]
rw [add_mul, one_mul]
exact (Nat.lt_div_mul_add hr).le
#align function.is_periodic_pt_of_mem_periodic_pts_of_is_periodic_pt_iterate Function.isPeriodicPt_of_mem_periodicPts_of_isPeriodicPt_iterate
variable (f)
theorem bUnion_ptsOfPeriod : ⋃ n > 0, ptsOfPeriod f n = periodicPts f :=
Set.ext fun x => by simp [mem_periodicPts]
#align function.bUnion_pts_of_period Function.bUnion_ptsOfPeriod
theorem iUnion_pNat_ptsOfPeriod : ⋃ n : ℕ+, ptsOfPeriod f n = periodicPts f :=
iSup_subtype.trans <| bUnion_ptsOfPeriod f
#align function.Union_pnat_pts_of_period Function.iUnion_pNat_ptsOfPeriod
theorem bijOn_periodicPts : BijOn f (periodicPts f) (periodicPts f) :=
iUnion_pNat_ptsOfPeriod f ▸
bijOn_iUnion_of_directed (directed_ptsOfPeriod_pNat f) fun i => bijOn_ptsOfPeriod f i.pos
#align function.bij_on_periodic_pts Function.bijOn_periodicPts
variable {f}
theorem Semiconj.mapsTo_periodicPts {g : α → β} (h : Semiconj g fa fb) :
MapsTo g (periodicPts fa) (periodicPts fb) := fun _ ⟨n, hn, hx⟩ => ⟨n, hn, hx.map h⟩
#align function.semiconj.maps_to_periodic_pts Function.Semiconj.mapsTo_periodicPts
open scoped Classical
noncomputable section
/-- Minimal period of a point `x` under an endomorphism `f`. If `x` is not a periodic point of `f`,
then `minimalPeriod f x = 0`. -/
def minimalPeriod (f : α → α) (x : α) :=
if h : x ∈ periodicPts f then Nat.find h else 0
#align function.minimal_period Function.minimalPeriod
theorem isPeriodicPt_minimalPeriod (f : α → α) (x : α) : IsPeriodicPt f (minimalPeriod f x) x := by
delta minimalPeriod
split_ifs with hx
· exact (Nat.find_spec hx).2
· exact isPeriodicPt_zero f x
#align function.is_periodic_pt_minimal_period Function.isPeriodicPt_minimalPeriod
@[simp]
theorem iterate_minimalPeriod : f^[minimalPeriod f x] x = x :=
isPeriodicPt_minimalPeriod f x
#align function.iterate_minimal_period Function.iterate_minimalPeriod
@[simp]
theorem iterate_add_minimalPeriod_eq : f^[n + minimalPeriod f x] x = f^[n] x := by
rw [iterate_add_apply]
congr
exact isPeriodicPt_minimalPeriod f x
#align function.iterate_add_minimal_period_eq Function.iterate_add_minimalPeriod_eq
@[simp]
theorem iterate_mod_minimalPeriod_eq : f^[n % minimalPeriod f x] x = f^[n] x :=
(isPeriodicPt_minimalPeriod f x).iterate_mod_apply n
#align function.iterate_mod_minimal_period_eq Function.iterate_mod_minimalPeriod_eq
| Mathlib/Dynamics/PeriodicPts.lean | 303 | 304 | theorem minimalPeriod_pos_of_mem_periodicPts (hx : x ∈ periodicPts f) : 0 < minimalPeriod f x := by |
simp only [minimalPeriod, dif_pos hx, (Nat.find_spec hx).1.lt]
|
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Analytic.Basic
import Mathlib.Analysis.Analytic.CPolynomial
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.ContDiff.Defs
import Mathlib.Analysis.Calculus.FDeriv.Add
#align_import analysis.calculus.fderiv_analytic from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Frechet derivatives of analytic functions.
A function expressible as a power series at a point has a Frechet derivative there.
Also the special case in terms of `deriv` when the domain is 1-dimensional.
As an application, we show that continuous multilinear maps are smooth. We also compute their
iterated derivatives, in `ContinuousMultilinearMap.iteratedFDeriv_eq`.
-/
open Filter Asymptotics
open scoped ENNReal
universe u v
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {E : Type u} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
section fderiv
variable {p : FormalMultilinearSeries 𝕜 E F} {r : ℝ≥0∞}
variable {f : E → F} {x : E} {s : Set E}
theorem HasFPowerSeriesAt.hasStrictFDerivAt (h : HasFPowerSeriesAt f p x) :
HasStrictFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p 1)) x := by
refine h.isBigO_image_sub_norm_mul_norm_sub.trans_isLittleO (IsLittleO.of_norm_right ?_)
refine isLittleO_iff_exists_eq_mul.2 ⟨fun y => ‖y - (x, x)‖, ?_, EventuallyEq.rfl⟩
refine (continuous_id.sub continuous_const).norm.tendsto' _ _ ?_
rw [_root_.id, sub_self, norm_zero]
#align has_fpower_series_at.has_strict_fderiv_at HasFPowerSeriesAt.hasStrictFDerivAt
theorem HasFPowerSeriesAt.hasFDerivAt (h : HasFPowerSeriesAt f p x) :
HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p 1)) x :=
h.hasStrictFDerivAt.hasFDerivAt
#align has_fpower_series_at.has_fderiv_at HasFPowerSeriesAt.hasFDerivAt
theorem HasFPowerSeriesAt.differentiableAt (h : HasFPowerSeriesAt f p x) : DifferentiableAt 𝕜 f x :=
h.hasFDerivAt.differentiableAt
#align has_fpower_series_at.differentiable_at HasFPowerSeriesAt.differentiableAt
theorem AnalyticAt.differentiableAt : AnalyticAt 𝕜 f x → DifferentiableAt 𝕜 f x
| ⟨_, hp⟩ => hp.differentiableAt
#align analytic_at.differentiable_at AnalyticAt.differentiableAt
theorem AnalyticAt.differentiableWithinAt (h : AnalyticAt 𝕜 f x) : DifferentiableWithinAt 𝕜 f s x :=
h.differentiableAt.differentiableWithinAt
#align analytic_at.differentiable_within_at AnalyticAt.differentiableWithinAt
theorem HasFPowerSeriesAt.fderiv_eq (h : HasFPowerSeriesAt f p x) :
fderiv 𝕜 f x = continuousMultilinearCurryFin1 𝕜 E F (p 1) :=
h.hasFDerivAt.fderiv
#align has_fpower_series_at.fderiv_eq HasFPowerSeriesAt.fderiv_eq
theorem HasFPowerSeriesOnBall.differentiableOn [CompleteSpace F]
(h : HasFPowerSeriesOnBall f p x r) : DifferentiableOn 𝕜 f (EMetric.ball x r) := fun _ hy =>
(h.analyticAt_of_mem hy).differentiableWithinAt
#align has_fpower_series_on_ball.differentiable_on HasFPowerSeriesOnBall.differentiableOn
theorem AnalyticOn.differentiableOn (h : AnalyticOn 𝕜 f s) : DifferentiableOn 𝕜 f s := fun y hy =>
(h y hy).differentiableWithinAt
#align analytic_on.differentiable_on AnalyticOn.differentiableOn
theorem HasFPowerSeriesOnBall.hasFDerivAt [CompleteSpace F] (h : HasFPowerSeriesOnBall f p x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1)) (x + y) :=
(h.changeOrigin hy).hasFPowerSeriesAt.hasFDerivAt
#align has_fpower_series_on_ball.has_fderiv_at HasFPowerSeriesOnBall.hasFDerivAt
theorem HasFPowerSeriesOnBall.fderiv_eq [CompleteSpace F] (h : HasFPowerSeriesOnBall f p x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
fderiv 𝕜 f (x + y) = continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1) :=
(h.hasFDerivAt hy).fderiv
#align has_fpower_series_on_ball.fderiv_eq HasFPowerSeriesOnBall.fderiv_eq
/-- If a function has a power series on a ball, then so does its derivative. -/
theorem HasFPowerSeriesOnBall.fderiv [CompleteSpace F] (h : HasFPowerSeriesOnBall f p x r) :
HasFPowerSeriesOnBall (fderiv 𝕜 f) p.derivSeries x r := by
refine .congr (f := fun z ↦ continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin (z - x) 1)) ?_
fun z hz ↦ ?_
· refine continuousMultilinearCurryFin1 𝕜 E F
|>.toContinuousLinearEquiv.toContinuousLinearMap.comp_hasFPowerSeriesOnBall ?_
simpa using ((p.hasFPowerSeriesOnBall_changeOrigin 1
(h.r_pos.trans_le h.r_le)).mono h.r_pos h.r_le).comp_sub x
dsimp only
rw [← h.fderiv_eq, add_sub_cancel]
simpa only [edist_eq_coe_nnnorm_sub, EMetric.mem_ball] using hz
#align has_fpower_series_on_ball.fderiv HasFPowerSeriesOnBall.fderiv
/-- If a function is analytic on a set `s`, so is its Fréchet derivative. -/
theorem AnalyticOn.fderiv [CompleteSpace F] (h : AnalyticOn 𝕜 f s) :
AnalyticOn 𝕜 (fderiv 𝕜 f) s := by
intro y hy
rcases h y hy with ⟨p, r, hp⟩
exact hp.fderiv.analyticAt
#align analytic_on.fderiv AnalyticOn.fderiv
/-- If a function is analytic on a set `s`, so are its successive Fréchet derivative. -/
theorem AnalyticOn.iteratedFDeriv [CompleteSpace F] (h : AnalyticOn 𝕜 f s) (n : ℕ) :
AnalyticOn 𝕜 (iteratedFDeriv 𝕜 n f) s := by
induction' n with n IH
· rw [iteratedFDeriv_zero_eq_comp]
exact ((continuousMultilinearCurryFin0 𝕜 E F).symm : F →L[𝕜] E[×0]→L[𝕜] F).comp_analyticOn h
· rw [iteratedFDeriv_succ_eq_comp_left]
-- Porting note: for reasons that I do not understand at all, `?g` cannot be inlined.
convert ContinuousLinearMap.comp_analyticOn ?g IH.fderiv
case g => exact ↑(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (n + 1) ↦ E) F)
simp
#align analytic_on.iterated_fderiv AnalyticOn.iteratedFDeriv
/-- An analytic function is infinitely differentiable. -/
theorem AnalyticOn.contDiffOn [CompleteSpace F] (h : AnalyticOn 𝕜 f s) {n : ℕ∞} :
ContDiffOn 𝕜 n f s :=
let t := { x | AnalyticAt 𝕜 f x }
suffices ContDiffOn 𝕜 n f t from this.mono h
have H : AnalyticOn 𝕜 f t := fun _x hx ↦ hx
have t_open : IsOpen t := isOpen_analyticAt 𝕜 f
contDiffOn_of_continuousOn_differentiableOn
(fun m _ ↦ (H.iteratedFDeriv m).continuousOn.congr
fun _ hx ↦ iteratedFDerivWithin_of_isOpen _ t_open hx)
(fun m _ ↦ (H.iteratedFDeriv m).differentiableOn.congr
fun _ hx ↦ iteratedFDerivWithin_of_isOpen _ t_open hx)
#align analytic_on.cont_diff_on AnalyticOn.contDiffOn
theorem AnalyticAt.contDiffAt [CompleteSpace F] (h : AnalyticAt 𝕜 f x) {n : ℕ∞} :
ContDiffAt 𝕜 n f x := by
obtain ⟨s, hs, hf⟩ := h.exists_mem_nhds_analyticOn
exact hf.contDiffOn.contDiffAt hs
end fderiv
section deriv
variable {p : FormalMultilinearSeries 𝕜 𝕜 F} {r : ℝ≥0∞}
variable {f : 𝕜 → F} {x : 𝕜} {s : Set 𝕜}
protected theorem HasFPowerSeriesAt.hasStrictDerivAt (h : HasFPowerSeriesAt f p x) :
HasStrictDerivAt f (p 1 fun _ => 1) x :=
h.hasStrictFDerivAt.hasStrictDerivAt
#align has_fpower_series_at.has_strict_deriv_at HasFPowerSeriesAt.hasStrictDerivAt
protected theorem HasFPowerSeriesAt.hasDerivAt (h : HasFPowerSeriesAt f p x) :
HasDerivAt f (p 1 fun _ => 1) x :=
h.hasStrictDerivAt.hasDerivAt
#align has_fpower_series_at.has_deriv_at HasFPowerSeriesAt.hasDerivAt
protected theorem HasFPowerSeriesAt.deriv (h : HasFPowerSeriesAt f p x) :
deriv f x = p 1 fun _ => 1 :=
h.hasDerivAt.deriv
#align has_fpower_series_at.deriv HasFPowerSeriesAt.deriv
/-- If a function is analytic on a set `s`, so is its derivative. -/
theorem AnalyticOn.deriv [CompleteSpace F] (h : AnalyticOn 𝕜 f s) : AnalyticOn 𝕜 (deriv f) s :=
(ContinuousLinearMap.apply 𝕜 F (1 : 𝕜)).comp_analyticOn h.fderiv
#align analytic_on.deriv AnalyticOn.deriv
/-- If a function is analytic on a set `s`, so are its successive derivatives. -/
theorem AnalyticOn.iterated_deriv [CompleteSpace F] (h : AnalyticOn 𝕜 f s) (n : ℕ) :
AnalyticOn 𝕜 (_root_.deriv^[n] f) s := by
induction' n with n IH
· exact h
· simpa only [Function.iterate_succ', Function.comp_apply] using IH.deriv
#align analytic_on.iterated_deriv AnalyticOn.iterated_deriv
end deriv
section fderiv
variable {p : FormalMultilinearSeries 𝕜 E F} {r : ℝ≥0∞} {n : ℕ}
variable {f : E → F} {x : E} {s : Set E}
/-! The case of continuously polynomial functions. We get the same differentiability
results as for analytic functions, but without the assumptions that `F` is complete. -/
theorem HasFiniteFPowerSeriesOnBall.differentiableOn
(h : HasFiniteFPowerSeriesOnBall f p x n r) : DifferentiableOn 𝕜 f (EMetric.ball x r) :=
fun _ hy ↦ (h.cPolynomialAt_of_mem hy).analyticAt.differentiableWithinAt
theorem HasFiniteFPowerSeriesOnBall.hasFDerivAt (h : HasFiniteFPowerSeriesOnBall f p x n r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1)) (x + y) :=
(h.changeOrigin hy).toHasFPowerSeriesOnBall.hasFPowerSeriesAt.hasFDerivAt
theorem HasFiniteFPowerSeriesOnBall.fderiv_eq (h : HasFiniteFPowerSeriesOnBall f p x n r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
fderiv 𝕜 f (x + y) = continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1) :=
(h.hasFDerivAt hy).fderiv
/-- If a function has a finite power series on a ball, then so does its derivative. -/
protected theorem HasFiniteFPowerSeriesOnBall.fderiv
(h : HasFiniteFPowerSeriesOnBall f p x (n + 1) r) :
HasFiniteFPowerSeriesOnBall (fderiv 𝕜 f) p.derivSeries x n r := by
refine .congr (f := fun z ↦ continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin (z - x) 1)) ?_
fun z hz ↦ ?_
· refine continuousMultilinearCurryFin1 𝕜 E F
|>.toContinuousLinearEquiv.toContinuousLinearMap.comp_hasFiniteFPowerSeriesOnBall ?_
simpa using
((p.hasFiniteFPowerSeriesOnBall_changeOrigin 1 h.finite).mono h.r_pos le_top).comp_sub x
dsimp only
rw [← h.fderiv_eq, add_sub_cancel]
simpa only [edist_eq_coe_nnnorm_sub, EMetric.mem_ball] using hz
/-- If a function has a finite power series on a ball, then so does its derivative.
This is a variant of `HasFiniteFPowerSeriesOnBall.fderiv` where the degree of `f` is `< n`
and not `< n + 1`. -/
theorem HasFiniteFPowerSeriesOnBall.fderiv' (h : HasFiniteFPowerSeriesOnBall f p x n r) :
HasFiniteFPowerSeriesOnBall (fderiv 𝕜 f) p.derivSeries x (n - 1) r := by
obtain rfl | hn := eq_or_ne n 0
· rw [zero_tsub]
refine HasFiniteFPowerSeriesOnBall.bound_zero_of_eq_zero (fun y hy ↦ ?_) h.r_pos fun n ↦ ?_
· rw [Filter.EventuallyEq.fderiv_eq (f := fun _ ↦ 0)]
· rw [fderiv_const, Pi.zero_apply]
· exact Filter.eventuallyEq_iff_exists_mem.mpr ⟨EMetric.ball x r,
EMetric.isOpen_ball.mem_nhds hy, fun z hz ↦ by rw [h.eq_zero_of_bound_zero z hz]⟩
· apply ContinuousMultilinearMap.ext; intro a
change (continuousMultilinearCurryFin1 𝕜 E F) (p.changeOriginSeries 1 n a) = 0
rw [p.changeOriginSeries_finite_of_finite h.finite 1 (Nat.zero_le _)]
exact map_zero _
· rw [← Nat.succ_pred hn] at h
exact h.fderiv
/-- If a function is polynomial on a set `s`, so is its Fréchet derivative. -/
theorem CPolynomialOn.fderiv (h : CPolynomialOn 𝕜 f s) :
CPolynomialOn 𝕜 (fderiv 𝕜 f) s := by
intro y hy
rcases h y hy with ⟨p, r, n, hp⟩
exact hp.fderiv'.cPolynomialAt
/-- If a function is polynomial on a set `s`, so are its successive Fréchet derivative. -/
theorem CPolynomialOn.iteratedFDeriv (h : CPolynomialOn 𝕜 f s) (n : ℕ) :
CPolynomialOn 𝕜 (iteratedFDeriv 𝕜 n f) s := by
induction' n with n IH
· rw [iteratedFDeriv_zero_eq_comp]
exact ((continuousMultilinearCurryFin0 𝕜 E F).symm : F →L[𝕜] E[×0]→L[𝕜] F).comp_cPolynomialOn h
· rw [iteratedFDeriv_succ_eq_comp_left]
convert ContinuousLinearMap.comp_cPolynomialOn ?g IH.fderiv
case g => exact ↑(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (n + 1) ↦ E) F)
simp
/-- A polynomial function is infinitely differentiable. -/
theorem CPolynomialOn.contDiffOn (h : CPolynomialOn 𝕜 f s) {n : ℕ∞} :
ContDiffOn 𝕜 n f s :=
let t := { x | CPolynomialAt 𝕜 f x }
suffices ContDiffOn 𝕜 n f t from this.mono h
have H : CPolynomialOn 𝕜 f t := fun _x hx ↦ hx
have t_open : IsOpen t := isOpen_cPolynomialAt 𝕜 f
contDiffOn_of_continuousOn_differentiableOn
(fun m _ ↦ (H.iteratedFDeriv m).continuousOn.congr
fun _ hx ↦ iteratedFDerivWithin_of_isOpen _ t_open hx)
(fun m _ ↦ (H.iteratedFDeriv m).analyticOn.differentiableOn.congr
fun _ hx ↦ iteratedFDerivWithin_of_isOpen _ t_open hx)
theorem CPolynomialAt.contDiffAt (h : CPolynomialAt 𝕜 f x) {n : ℕ∞} :
ContDiffAt 𝕜 n f x :=
let ⟨_, hs, hf⟩ := h.exists_mem_nhds_cPolynomialOn
hf.contDiffOn.contDiffAt hs
end fderiv
section deriv
variable {p : FormalMultilinearSeries 𝕜 𝕜 F} {r : ℝ≥0∞}
variable {f : 𝕜 → F} {x : 𝕜} {s : Set 𝕜}
/-- If a function is polynomial on a set `s`, so is its derivative. -/
protected theorem CPolynomialOn.deriv (h : CPolynomialOn 𝕜 f s) : CPolynomialOn 𝕜 (deriv f) s :=
(ContinuousLinearMap.apply 𝕜 F (1 : 𝕜)).comp_cPolynomialOn h.fderiv
/-- If a function is polynomial on a set `s`, so are its successive derivatives. -/
theorem CPolynomialOn.iterated_deriv (h : CPolynomialOn 𝕜 f s) (n : ℕ) :
CPolynomialOn 𝕜 (deriv^[n] f) s := by
induction' n with n IH
· exact h
· simpa only [Function.iterate_succ', Function.comp_apply] using IH.deriv
end deriv
namespace ContinuousMultilinearMap
variable {ι : Type*} {E : ι → Type*} [∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)]
[Fintype ι] (f : ContinuousMultilinearMap 𝕜 E F)
open FormalMultilinearSeries
protected theorem hasFiniteFPowerSeriesOnBall :
HasFiniteFPowerSeriesOnBall f f.toFormalMultilinearSeries 0 (Fintype.card ι + 1) ⊤ :=
.mk' (fun m hm ↦ dif_neg (Nat.succ_le_iff.mp hm).ne) ENNReal.zero_lt_top fun y _ ↦ by
rw [Finset.sum_eq_single_of_mem _ (Finset.self_mem_range_succ _), zero_add]
· rw [toFormalMultilinearSeries, dif_pos rfl]; rfl
· intro m _ ne; rw [toFormalMultilinearSeries, dif_neg ne.symm]; rfl
theorem changeOriginSeries_support {k l : ℕ} (h : k + l ≠ Fintype.card ι) :
f.toFormalMultilinearSeries.changeOriginSeries k l = 0 :=
Finset.sum_eq_zero fun _ _ ↦ by
simp_rw [FormalMultilinearSeries.changeOriginSeriesTerm,
toFormalMultilinearSeries, dif_neg h.symm, LinearIsometryEquiv.map_zero]
variable {n : ℕ∞} (x : ∀ i, E i)
open Finset in
theorem changeOrigin_toFormalMultilinearSeries [DecidableEq ι] :
continuousMultilinearCurryFin1 𝕜 (∀ i, E i) F (f.toFormalMultilinearSeries.changeOrigin x 1) =
f.linearDeriv x := by
ext y
rw [continuousMultilinearCurryFin1_apply, linearDeriv_apply,
changeOrigin, FormalMultilinearSeries.sum]
cases isEmpty_or_nonempty ι
· have (l) : 1 + l ≠ Fintype.card ι := by
rw [add_comm, Fintype.card_eq_zero]; exact Nat.succ_ne_zero _
simp_rw [Fintype.sum_empty, changeOriginSeries_support _ (this _), zero_apply _, tsum_zero]; rfl
rw [tsum_eq_single (Fintype.card ι - 1), changeOriginSeries]; swap
· intro m hm
rw [Ne, eq_tsub_iff_add_eq_of_le (by exact Fintype.card_pos), add_comm] at hm
rw [f.changeOriginSeries_support hm, zero_apply]
rw [sum_apply, ContinuousMultilinearMap.sum_apply, Fin.snoc_zero]
simp_rw [changeOriginSeriesTerm_apply]
refine (Fintype.sum_bijective (?_ ∘ Fintype.equivFinOfCardEq (Nat.add_sub_of_le
Fintype.card_pos).symm) (.comp ?_ <| Equiv.bijective _) _ _ fun i ↦ ?_).symm
· exact (⟨{·}ᶜ, by
rw [card_compl, Fintype.card_fin, card_singleton, Nat.add_sub_cancel_left]⟩)
· use fun _ _ ↦ (singleton_injective <| compl_injective <| Subtype.ext_iff.mp ·)
intro ⟨s, hs⟩
have h : sᶜ.card = 1 := by rw [card_compl, hs, Fintype.card_fin, Nat.add_sub_cancel]
obtain ⟨a, ha⟩ := card_eq_one.mp h
exact ⟨a, Subtype.ext (compl_eq_comm.mp ha)⟩
rw [Function.comp_apply, Subtype.coe_mk, compl_singleton, piecewise_erase_univ,
toFormalMultilinearSeries, dif_pos (Nat.add_sub_of_le Fintype.card_pos).symm]
simp_rw [domDomCongr_apply, compContinuousLinearMap_apply, ContinuousLinearMap.proj_apply,
Function.update_apply, (Equiv.injective _).eq_iff, ite_apply]
congr; ext j
obtain rfl | hj := eq_or_ne j i
· rw [Function.update_same, if_pos rfl]
· rw [Function.update_noteq hj, if_neg hj]
protected theorem hasFDerivAt [DecidableEq ι] : HasFDerivAt f (f.linearDeriv x) x := by
rw [← changeOrigin_toFormalMultilinearSeries]
convert f.hasFiniteFPowerSeriesOnBall.hasFDerivAt (y := x) ENNReal.coe_lt_top
rw [zero_add]
/-- Technical lemma used in the proof of `hasFTaylorSeriesUpTo_iteratedFDeriv`, to compare sums
over embedding of `Fin k` and `Fin (k + 1)`. -/
private lemma _root_.Equiv.succ_embeddingFinSucc_fst_symm_apply {ι : Type*} [DecidableEq ι]
{n : ℕ} (e : Fin (n+1) ↪ ι) {k : ι}
(h'k : k ∈ Set.range (Equiv.embeddingFinSucc n ι e).1) (hk : k ∈ Set.range e) :
Fin.succ ((Equiv.embeddingFinSucc n ι e).1.toEquivRange.symm ⟨k, h'k⟩)
= e.toEquivRange.symm ⟨k, hk⟩ := by
rcases hk with ⟨j, rfl⟩
have hj : j ≠ 0 := by
rintro rfl
simp at h'k
simp only [Function.Embedding.toEquivRange_symm_apply_self]
have : e j = (Equiv.embeddingFinSucc n ι e).1 (Fin.pred j hj) := by simp
simp_rw [this]
simp [-Equiv.embeddingFinSucc_fst]
/-- A continuous multilinear function `f` admits a Taylor series, whose successive terms are given
by `f.iteratedFDeriv n`. This is the point of the definition of `f.iteratedFDeriv`. -/
theorem hasFTaylorSeriesUpTo_iteratedFDeriv :
HasFTaylorSeriesUpTo ⊤ f (fun v n ↦ f.iteratedFDeriv n v) := by
classical
constructor
· simp [ContinuousMultilinearMap.iteratedFDeriv]
· rintro n - x
suffices H : curryLeft (f.iteratedFDeriv (Nat.succ n) x) = (∑ e : Fin n ↪ ι,
((iteratedFDerivComponent f e.toEquivRange).linearDeriv
(Pi.compRightL 𝕜 _ Subtype.val x)) ∘L (Pi.compRightL 𝕜 _ Subtype.val)) by
have A : HasFDerivAt (f.iteratedFDeriv n) (∑ e : Fin n ↪ ι,
((iteratedFDerivComponent f e.toEquivRange).linearDeriv (Pi.compRightL 𝕜 _ Subtype.val x))
∘L (Pi.compRightL 𝕜 _ Subtype.val)) x := by
apply HasFDerivAt.sum (fun s _hs ↦ ?_)
exact (ContinuousMultilinearMap.hasFDerivAt _ _).comp x (ContinuousLinearMap.hasFDerivAt _)
rwa [← H] at A
ext v m
simp only [ContinuousMultilinearMap.iteratedFDeriv, curryLeft_apply, sum_apply,
iteratedFDerivComponent_apply, Finset.univ_sigma_univ,
Pi.compRightL_apply, ContinuousLinearMap.coe_sum', ContinuousLinearMap.coe_comp',
Finset.sum_apply, Function.comp_apply, linearDeriv_apply, Finset.sum_sigma']
rw [← (Equiv.embeddingFinSucc n ι).sum_comp]
congr with e
congr with k
by_cases hke : k ∈ Set.range e
· simp only [hke, ↓reduceDite]
split_ifs with hkf
· simp only [← Equiv.succ_embeddingFinSucc_fst_symm_apply e hkf hke, Fin.cons_succ]
· obtain rfl : k = e 0 := by
rcases hke with ⟨j, rfl⟩
simpa using hkf
simp only [Function.Embedding.toEquivRange_symm_apply_self, Fin.cons_zero, Function.update,
Pi.compRightL_apply]
split_ifs with h
· congr!
· exfalso
apply h
simp_rw [← Equiv.embeddingFinSucc_snd e]
· have hkf : k ∉ Set.range (Equiv.embeddingFinSucc n ι e).1 := by
contrapose! hke
rw [Equiv.embeddingFinSucc_fst] at hke
exact Set.range_comp_subset_range _ _ hke
simp only [hke, hkf, ↓reduceDite, Pi.compRightL,
ContinuousLinearMap.coe_mk', LinearMap.coe_mk, AddHom.coe_mk]
rw [Function.update_noteq]
contrapose! hke
rw [show k = _ from Subtype.ext_iff_val.1 hke, Equiv.embeddingFinSucc_snd e]
exact Set.mem_range_self _
· rintro n -
apply continuous_finset_sum _ (fun e _ ↦ ?_)
exact (ContinuousMultilinearMap.coe_continuous _).comp (ContinuousLinearMap.continuous _)
theorem iteratedFDeriv_eq (n : ℕ) :
iteratedFDeriv 𝕜 n f = f.iteratedFDeriv n :=
funext fun x ↦ (f.hasFTaylorSeriesUpTo_iteratedFDeriv.eq_iteratedFDeriv (m := n) le_top x).symm
theorem norm_iteratedFDeriv_le (n : ℕ) (x : (i : ι) → E i) :
‖iteratedFDeriv 𝕜 n f x‖
≤ Nat.descFactorial (Fintype.card ι) n * ‖f‖ * ‖x‖ ^ (Fintype.card ι - n) := by
rw [f.iteratedFDeriv_eq]
exact f.norm_iteratedFDeriv_le' n x
lemma cPolynomialAt : CPolynomialAt 𝕜 f x :=
f.hasFiniteFPowerSeriesOnBall.cPolynomialAt_of_mem
(by simp only [Metric.emetric_ball_top, Set.mem_univ])
lemma cPolyomialOn : CPolynomialOn 𝕜 f ⊤ := fun x _ ↦ f.cPolynomialAt x
lemma contDiffAt : ContDiffAt 𝕜 n f x := (f.cPolynomialAt x).contDiffAt
lemma contDiff : ContDiff 𝕜 n f := contDiff_iff_contDiffAt.mpr f.contDiffAt
end ContinuousMultilinearMap
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F)
open Fintype ContinuousLinearMap in
theorem derivSeries_apply_diag (n : ℕ) (x : E) :
derivSeries p n (fun _ ↦ x) x = (n + 1) • p (n + 1) fun _ ↦ x := by
simp only [derivSeries, compFormalMultilinearSeries_apply, changeOriginSeries,
compContinuousMultilinearMap_coe, ContinuousLinearEquiv.coe_coe, LinearIsometryEquiv.coe_coe,
Function.comp_apply, ContinuousMultilinearMap.sum_apply, map_sum, coe_sum', Finset.sum_apply,
continuousMultilinearCurryFin1_apply, Matrix.zero_empty]
convert Finset.sum_const _
· rw [Fin.snoc_zero, changeOriginSeriesTerm_apply, Finset.piecewise_same, add_comm]
· rw [← card, card_subtype, ← Finset.powerset_univ, ← Finset.powersetCard_eq_filter,
Finset.card_powersetCard, ← card, card_fin, eq_comm, add_comm, Nat.choose_succ_self_right]
end FormalMultilinearSeries
namespace HasFPowerSeriesOnBall
open FormalMultilinearSeries ENNReal Nat
variable {p : FormalMultilinearSeries 𝕜 E F} {f : E → F} {x : E} {r : ℝ≥0∞}
(h : HasFPowerSeriesOnBall f p x r) (y : E)
theorem iteratedFDeriv_zero_apply_diag : iteratedFDeriv 𝕜 0 f x = p 0 := by
ext
convert (h.hasSum <| EMetric.mem_ball_self h.r_pos).tsum_eq.symm
· rw [iteratedFDeriv_zero_apply, add_zero]
· rw [tsum_eq_single 0 fun n hn ↦ by haveI := NeZero.mk hn; exact (p n).map_zero]
exact congr(p 0 $(Subsingleton.elim _ _))
open ContinuousLinearMap
private theorem factorial_smul' {n : ℕ} : ∀ {F : Type max u v} [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [CompleteSpace F] {p : FormalMultilinearSeries 𝕜 E F}
{f : E → F}, HasFPowerSeriesOnBall f p x r →
n ! • p n (fun _ ↦ y) = iteratedFDeriv 𝕜 n f x (fun _ ↦ y) := by
induction' n with n ih <;> intro F _ _ _ p f h
· rw [factorial_zero, one_smul, h.iteratedFDeriv_zero_apply_diag]
· rw [factorial_succ, mul_comm, mul_smul, ← derivSeries_apply_diag, ← smul_apply,
ih h.fderiv, iteratedFDeriv_succ_apply_right]
rfl
variable [CompleteSpace F]
| Mathlib/Analysis/Calculus/FDeriv/Analytic.lean | 490 | 496 | theorem factorial_smul (n : ℕ) :
n ! • p n (fun _ ↦ y) = iteratedFDeriv 𝕜 n f x (fun _ ↦ y) := by |
cases n
· rw [factorial_zero, one_smul, h.iteratedFDeriv_zero_apply_diag]
· rw [factorial_succ, mul_comm, mul_smul, ← derivSeries_apply_diag, ← smul_apply,
factorial_smul'.{_,u,v} _ h.fderiv, iteratedFDeriv_succ_apply_right]
rfl
|
/-
Copyright (c) 2021 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov
-/
import Mathlib.Geometry.Manifold.Algebra.Structures
import Mathlib.Geometry.Manifold.BumpFunction
import Mathlib.Topology.MetricSpace.PartitionOfUnity
import Mathlib.Topology.ShrinkingLemma
#align_import geometry.manifold.partition_of_unity from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Smooth partition of unity
In this file we define two structures, `SmoothBumpCovering` and `SmoothPartitionOfUnity`. Both
structures describe coverings of a set by a locally finite family of supports of smooth functions
with some additional properties. The former structure is mostly useful as an intermediate step in
the construction of a smooth partition of unity but some proofs that traditionally deal with a
partition of unity can use a `SmoothBumpCovering` as well.
Given a real manifold `M` and its subset `s`, a `SmoothBumpCovering ι I M s` is a collection of
`SmoothBumpFunction`s `f i` indexed by `i : ι` such that
* the center of each `f i` belongs to `s`;
* the family of sets `support (f i)` is locally finite;
* for each `x ∈ s`, there exists `i : ι` such that `f i =ᶠ[𝓝 x] 1`.
In the same settings, a `SmoothPartitionOfUnity ι I M s` is a collection of smooth nonnegative
functions `f i : C^∞⟮I, M; 𝓘(ℝ), ℝ⟯`, `i : ι`, such that
* the family of sets `support (f i)` is locally finite;
* for each `x ∈ s`, the sum `∑ᶠ i, f i x` equals one;
* for each `x`, the sum `∑ᶠ i, f i x` is less than or equal to one.
We say that `f : SmoothBumpCovering ι I M s` is *subordinate* to a map `U : M → Set M` if for each
index `i`, we have `tsupport (f i) ⊆ U (f i).c`. This notion is a bit more general than
being subordinate to an open covering of `M`, because we make no assumption about the way `U x`
depends on `x`.
We prove that on a smooth finitely dimensional real manifold with `σ`-compact Hausdorff topology,
for any `U : M → Set M` such that `∀ x ∈ s, U x ∈ 𝓝 x` there exists a `SmoothBumpCovering ι I M s`
subordinate to `U`. Then we use this fact to prove a similar statement about smooth partitions of
unity, see `SmoothPartitionOfUnity.exists_isSubordinate`.
Finally, we use existence of a partition of unity to prove lemma
`exists_smooth_forall_mem_convex_of_local` that allows us to construct a globally defined smooth
function from local functions.
## TODO
* Build a framework for to transfer local definitions to global using partition of unity and use it
to define, e.g., the integral of a differential form over a manifold. Lemma
`exists_smooth_forall_mem_convex_of_local` is a first step in this direction.
## Tags
smooth bump function, partition of unity
-/
universe uι uE uH uM uF
open Function Filter FiniteDimensional Set
open scoped Topology Manifold Classical Filter
noncomputable section
variable {ι : Type uι} {E : Type uE} [NormedAddCommGroup E] [NormedSpace ℝ E]
[FiniteDimensional ℝ E] {F : Type uF} [NormedAddCommGroup F] [NormedSpace ℝ F] {H : Type uH}
[TopologicalSpace H] (I : ModelWithCorners ℝ E H) {M : Type uM} [TopologicalSpace M]
[ChartedSpace H M] [SmoothManifoldWithCorners I M]
/-!
### Covering by supports of smooth bump functions
In this section we define `SmoothBumpCovering ι I M s` to be a collection of
`SmoothBumpFunction`s such that their supports is a locally finite family of sets and for each
`x ∈ s` some function `f i` from the collection is equal to `1` in a neighborhood of `x`. A covering
of this type is useful to construct a smooth partition of unity and can be used instead of a
partition of unity in some proofs.
We prove that on a smooth finite dimensional real manifold with `σ`-compact Hausdorff topology, for
any `U : M → Set M` such that `∀ x ∈ s, U x ∈ 𝓝 x` there exists a `SmoothBumpCovering ι I M s`
subordinate to `U`. -/
variable (ι M)
/-- We say that a collection of `SmoothBumpFunction`s is a `SmoothBumpCovering` of a set `s` if
* `(f i).c ∈ s` for all `i`;
* the family `fun i ↦ support (f i)` is locally finite;
* for each point `x ∈ s` there exists `i` such that `f i =ᶠ[𝓝 x] 1`;
in other words, `x` belongs to the interior of `{y | f i y = 1}`;
If `M` is a finite dimensional real manifold which is a `σ`-compact Hausdorff topological space,
then for every covering `U : M → Set M`, `∀ x, U x ∈ 𝓝 x`, there exists a `SmoothBumpCovering`
subordinate to `U`, see `SmoothBumpCovering.exists_isSubordinate`.
This covering can be used, e.g., to construct a partition of unity and to prove the weak
Whitney embedding theorem. -/
-- Porting note(#5171): was @[nolint has_nonempty_instance]
structure SmoothBumpCovering (s : Set M := univ) where
/-- The center point of each bump in the smooth covering. -/
c : ι → M
/-- A smooth bump function around `c i`. -/
toFun : ∀ i, SmoothBumpFunction I (c i)
/-- All the bump functions in the covering are centered at points in `s`. -/
c_mem' : ∀ i, c i ∈ s
/-- Around each point, there are only finitely many nonzero bump functions in the family. -/
locallyFinite' : LocallyFinite fun i => support (toFun i)
/-- Around each point in `s`, one of the bump functions is equal to `1`. -/
eventuallyEq_one' : ∀ x ∈ s, ∃ i, toFun i =ᶠ[𝓝 x] 1
#align smooth_bump_covering SmoothBumpCovering
/-- We say that a collection of functions form a smooth partition of unity on a set `s` if
* all functions are infinitely smooth and nonnegative;
* the family `fun i ↦ support (f i)` is locally finite;
* for all `x ∈ s` the sum `∑ᶠ i, f i x` equals one;
* for all `x`, the sum `∑ᶠ i, f i x` is less than or equal to one. -/
structure SmoothPartitionOfUnity (s : Set M := univ) where
/-- The family of functions forming the partition of unity. -/
toFun : ι → C^∞⟮I, M; 𝓘(ℝ), ℝ⟯
/-- Around each point, there are only finitely many nonzero functions in the family. -/
locallyFinite' : LocallyFinite fun i => support (toFun i)
/-- All the functions in the partition of unity are nonnegative. -/
nonneg' : ∀ i x, 0 ≤ toFun i x
/-- The functions in the partition of unity add up to `1` at any point of `s`. -/
sum_eq_one' : ∀ x ∈ s, ∑ᶠ i, toFun i x = 1
/-- The functions in the partition of unity add up to at most `1` everywhere. -/
sum_le_one' : ∀ x, ∑ᶠ i, toFun i x ≤ 1
#align smooth_partition_of_unity SmoothPartitionOfUnity
variable {ι I M}
namespace SmoothPartitionOfUnity
variable {s : Set M} (f : SmoothPartitionOfUnity ι I M s) {n : ℕ∞}
instance {s : Set M} : FunLike (SmoothPartitionOfUnity ι I M s) ι C^∞⟮I, M; 𝓘(ℝ), ℝ⟯ where
coe := toFun
coe_injective' f g h := by cases f; cases g; congr
protected theorem locallyFinite : LocallyFinite fun i => support (f i) :=
f.locallyFinite'
#align smooth_partition_of_unity.locally_finite SmoothPartitionOfUnity.locallyFinite
theorem nonneg (i : ι) (x : M) : 0 ≤ f i x :=
f.nonneg' i x
#align smooth_partition_of_unity.nonneg SmoothPartitionOfUnity.nonneg
theorem sum_eq_one {x} (hx : x ∈ s) : ∑ᶠ i, f i x = 1 :=
f.sum_eq_one' x hx
#align smooth_partition_of_unity.sum_eq_one SmoothPartitionOfUnity.sum_eq_one
theorem exists_pos_of_mem {x} (hx : x ∈ s) : ∃ i, 0 < f i x := by
by_contra! h
have H : ∀ i, f i x = 0 := fun i ↦ le_antisymm (h i) (f.nonneg i x)
have := f.sum_eq_one hx
simp_rw [H] at this
simpa
theorem sum_le_one (x : M) : ∑ᶠ i, f i x ≤ 1 :=
f.sum_le_one' x
#align smooth_partition_of_unity.sum_le_one SmoothPartitionOfUnity.sum_le_one
/-- Reinterpret a smooth partition of unity as a continuous partition of unity. -/
@[simps]
def toPartitionOfUnity : PartitionOfUnity ι M s :=
{ f with toFun := fun i => f i }
#align smooth_partition_of_unity.to_partition_of_unity SmoothPartitionOfUnity.toPartitionOfUnity
theorem smooth_sum : Smooth I 𝓘(ℝ) fun x => ∑ᶠ i, f i x :=
smooth_finsum (fun i => (f i).smooth) f.locallyFinite
#align smooth_partition_of_unity.smooth_sum SmoothPartitionOfUnity.smooth_sum
theorem le_one (i : ι) (x : M) : f i x ≤ 1 :=
f.toPartitionOfUnity.le_one i x
#align smooth_partition_of_unity.le_one SmoothPartitionOfUnity.le_one
theorem sum_nonneg (x : M) : 0 ≤ ∑ᶠ i, f i x :=
f.toPartitionOfUnity.sum_nonneg x
#align smooth_partition_of_unity.sum_nonneg SmoothPartitionOfUnity.sum_nonneg
theorem contMDiff_smul {g : M → F} {i} (hg : ∀ x ∈ tsupport (f i), ContMDiffAt I 𝓘(ℝ, F) n g x) :
ContMDiff I 𝓘(ℝ, F) n fun x => f i x • g x :=
contMDiff_of_tsupport fun x hx =>
((f i).contMDiff.contMDiffAt.of_le le_top).smul <| hg x <| tsupport_smul_subset_left _ _ hx
#align smooth_partition_of_unity.cont_mdiff_smul SmoothPartitionOfUnity.contMDiff_smul
theorem smooth_smul {g : M → F} {i} (hg : ∀ x ∈ tsupport (f i), SmoothAt I 𝓘(ℝ, F) g x) :
Smooth I 𝓘(ℝ, F) fun x => f i x • g x :=
f.contMDiff_smul hg
#align smooth_partition_of_unity.smooth_smul SmoothPartitionOfUnity.smooth_smul
/-- If `f` is a smooth partition of unity on a set `s : Set M` and `g : ι → M → F` is a family of
functions such that `g i` is $C^n$ smooth at every point of the topological support of `f i`, then
the sum `fun x ↦ ∑ᶠ i, f i x • g i x` is smooth on the whole manifold. -/
theorem contMDiff_finsum_smul {g : ι → M → F}
(hg : ∀ (i), ∀ x ∈ tsupport (f i), ContMDiffAt I 𝓘(ℝ, F) n (g i) x) :
ContMDiff I 𝓘(ℝ, F) n fun x => ∑ᶠ i, f i x • g i x :=
(contMDiff_finsum fun i => f.contMDiff_smul (hg i)) <|
f.locallyFinite.subset fun _ => support_smul_subset_left _ _
#align smooth_partition_of_unity.cont_mdiff_finsum_smul SmoothPartitionOfUnity.contMDiff_finsum_smul
/-- If `f` is a smooth partition of unity on a set `s : Set M` and `g : ι → M → F` is a family of
functions such that `g i` is smooth at every point of the topological support of `f i`, then the sum
`fun x ↦ ∑ᶠ i, f i x • g i x` is smooth on the whole manifold. -/
theorem smooth_finsum_smul {g : ι → M → F}
(hg : ∀ (i), ∀ x ∈ tsupport (f i), SmoothAt I 𝓘(ℝ, F) (g i) x) :
Smooth I 𝓘(ℝ, F) fun x => ∑ᶠ i, f i x • g i x :=
f.contMDiff_finsum_smul hg
#align smooth_partition_of_unity.smooth_finsum_smul SmoothPartitionOfUnity.smooth_finsum_smul
theorem contMDiffAt_finsum {x₀ : M} {g : ι → M → F}
(hφ : ∀ i, x₀ ∈ tsupport (f i) → ContMDiffAt I 𝓘(ℝ, F) n (g i) x₀) :
ContMDiffAt I 𝓘(ℝ, F) n (fun x ↦ ∑ᶠ i, f i x • g i x) x₀ := by
refine _root_.contMDiffAt_finsum (f.locallyFinite.smul_left _) fun i ↦ ?_
by_cases hx : x₀ ∈ tsupport (f i)
· exact ContMDiffAt.smul ((f i).smooth.of_le le_top).contMDiffAt (hφ i hx)
· exact contMDiffAt_of_not_mem (compl_subset_compl.mpr
(tsupport_smul_subset_left (f i) (g i)) hx) n
theorem contDiffAt_finsum {s : Set E} (f : SmoothPartitionOfUnity ι 𝓘(ℝ, E) E s) {x₀ : E}
{g : ι → E → F} (hφ : ∀ i, x₀ ∈ tsupport (f i) → ContDiffAt ℝ n (g i) x₀) :
ContDiffAt ℝ n (fun x ↦ ∑ᶠ i, f i x • g i x) x₀ := by
simp only [← contMDiffAt_iff_contDiffAt] at *
exact f.contMDiffAt_finsum hφ
theorem finsum_smul_mem_convex {g : ι → M → F} {t : Set F} {x : M} (hx : x ∈ s)
(hg : ∀ i, f i x ≠ 0 → g i x ∈ t) (ht : Convex ℝ t) : ∑ᶠ i, f i x • g i x ∈ t :=
ht.finsum_mem (fun _ => f.nonneg _ _) (f.sum_eq_one hx) hg
#align smooth_partition_of_unity.finsum_smul_mem_convex SmoothPartitionOfUnity.finsum_smul_mem_convex
section finsupport
variable {s : Set M} (ρ : SmoothPartitionOfUnity ι I M s) (x₀ : M)
/-- The support of a smooth partition of unity at a point `x₀` as a `Finset`.
This is the set of `i : ι` such that `x₀ ∈ support f i`, i.e. `f i ≠ x₀`. -/
def finsupport : Finset ι := ρ.toPartitionOfUnity.finsupport x₀
@[simp]
theorem mem_finsupport {i : ι} : i ∈ ρ.finsupport x₀ ↔ i ∈ support fun i ↦ ρ i x₀ :=
ρ.toPartitionOfUnity.mem_finsupport x₀
@[simp]
theorem coe_finsupport : (ρ.finsupport x₀ : Set ι) = support fun i ↦ ρ i x₀ :=
ρ.toPartitionOfUnity.coe_finsupport x₀
theorem sum_finsupport (hx₀ : x₀ ∈ s) : ∑ i ∈ ρ.finsupport x₀, ρ i x₀ = 1 :=
ρ.toPartitionOfUnity.sum_finsupport hx₀
theorem sum_finsupport' (hx₀ : x₀ ∈ s) {I : Finset ι} (hI : ρ.finsupport x₀ ⊆ I) :
∑ i ∈ I, ρ i x₀ = 1 :=
ρ.toPartitionOfUnity.sum_finsupport' hx₀ hI
theorem sum_finsupport_smul_eq_finsum {A : Type*} [AddCommGroup A] [Module ℝ A] (φ : ι → M → A) :
∑ i ∈ ρ.finsupport x₀, ρ i x₀ • φ i x₀ = ∑ᶠ i, ρ i x₀ • φ i x₀ :=
ρ.toPartitionOfUnity.sum_finsupport_smul_eq_finsum φ
end finsupport
section fintsupport -- smooth partitions of unity have locally finite `tsupport`
variable {s : Set M} (ρ : SmoothPartitionOfUnity ι I M s) (x₀ : M)
/-- The `tsupport`s of a smooth partition of unity are locally finite. -/
theorem finite_tsupport : {i | x₀ ∈ tsupport (ρ i)}.Finite :=
ρ.toPartitionOfUnity.finite_tsupport _
/-- The tsupport of a partition of unity at a point `x₀` as a `Finset`.
This is the set of `i : ι` such that `x₀ ∈ tsupport f i`. -/
def fintsupport (x : M) : Finset ι :=
(ρ.finite_tsupport x).toFinset
theorem mem_fintsupport_iff (i : ι) : i ∈ ρ.fintsupport x₀ ↔ x₀ ∈ tsupport (ρ i) :=
Finite.mem_toFinset _
theorem eventually_fintsupport_subset : ∀ᶠ y in 𝓝 x₀, ρ.fintsupport y ⊆ ρ.fintsupport x₀ :=
ρ.toPartitionOfUnity.eventually_fintsupport_subset _
theorem finsupport_subset_fintsupport : ρ.finsupport x₀ ⊆ ρ.fintsupport x₀ :=
ρ.toPartitionOfUnity.finsupport_subset_fintsupport x₀
theorem eventually_finsupport_subset : ∀ᶠ y in 𝓝 x₀, ρ.finsupport y ⊆ ρ.fintsupport x₀ :=
ρ.toPartitionOfUnity.eventually_finsupport_subset x₀
end fintsupport
section IsSubordinate
/-- A smooth partition of unity `f i` is subordinate to a family of sets `U i` indexed by the same
type if for each `i` the closure of the support of `f i` is a subset of `U i`. -/
def IsSubordinate (f : SmoothPartitionOfUnity ι I M s) (U : ι → Set M) :=
∀ i, tsupport (f i) ⊆ U i
#align smooth_partition_of_unity.is_subordinate SmoothPartitionOfUnity.IsSubordinate
variable {f} {U : ι → Set M}
@[simp]
theorem isSubordinate_toPartitionOfUnity :
f.toPartitionOfUnity.IsSubordinate U ↔ f.IsSubordinate U :=
Iff.rfl
#align smooth_partition_of_unity.is_subordinate_to_partition_of_unity SmoothPartitionOfUnity.isSubordinate_toPartitionOfUnity
alias ⟨_, IsSubordinate.toPartitionOfUnity⟩ := isSubordinate_toPartitionOfUnity
#align smooth_partition_of_unity.is_subordinate.to_partition_of_unity SmoothPartitionOfUnity.IsSubordinate.toPartitionOfUnity
/-- If `f` is a smooth partition of unity on a set `s : Set M` subordinate to a family of open sets
`U : ι → Set M` and `g : ι → M → F` is a family of functions such that `g i` is $C^n$ smooth on
`U i`, then the sum `fun x ↦ ∑ᶠ i, f i x • g i x` is $C^n$ smooth on the whole manifold. -/
theorem IsSubordinate.contMDiff_finsum_smul {g : ι → M → F} (hf : f.IsSubordinate U)
(ho : ∀ i, IsOpen (U i)) (hg : ∀ i, ContMDiffOn I 𝓘(ℝ, F) n (g i) (U i)) :
ContMDiff I 𝓘(ℝ, F) n fun x => ∑ᶠ i, f i x • g i x :=
f.contMDiff_finsum_smul fun i _ hx => (hg i).contMDiffAt <| (ho i).mem_nhds (hf i hx)
#align smooth_partition_of_unity.is_subordinate.cont_mdiff_finsum_smul SmoothPartitionOfUnity.IsSubordinate.contMDiff_finsum_smul
/-- If `f` is a smooth partition of unity on a set `s : Set M` subordinate to a family of open sets
`U : ι → Set M` and `g : ι → M → F` is a family of functions such that `g i` is smooth on `U i`,
then the sum `fun x ↦ ∑ᶠ i, f i x • g i x` is smooth on the whole manifold. -/
theorem IsSubordinate.smooth_finsum_smul {g : ι → M → F} (hf : f.IsSubordinate U)
(ho : ∀ i, IsOpen (U i)) (hg : ∀ i, SmoothOn I 𝓘(ℝ, F) (g i) (U i)) :
Smooth I 𝓘(ℝ, F) fun x => ∑ᶠ i, f i x • g i x :=
hf.contMDiff_finsum_smul ho hg
#align smooth_partition_of_unity.is_subordinate.smooth_finsum_smul SmoothPartitionOfUnity.IsSubordinate.smooth_finsum_smul
end IsSubordinate
end SmoothPartitionOfUnity
namespace BumpCovering
-- Repeat variables to drop `[FiniteDimensional ℝ E]` and `[SmoothManifoldWithCorners I M]`
theorem smooth_toPartitionOfUnity {E : Type uE} [NormedAddCommGroup E] [NormedSpace ℝ E]
{H : Type uH} [TopologicalSpace H] {I : ModelWithCorners ℝ E H} {M : Type uM}
[TopologicalSpace M] [ChartedSpace H M] {s : Set M} (f : BumpCovering ι M s)
(hf : ∀ i, Smooth I 𝓘(ℝ) (f i)) (i : ι) : Smooth I 𝓘(ℝ) (f.toPartitionOfUnity i) :=
(hf i).mul <| (smooth_finprod_cond fun j _ => smooth_const.sub (hf j)) <| by
simp only [Pi.sub_def, mulSupport_one_sub]
exact f.locallyFinite
#align bump_covering.smooth_to_partition_of_unity BumpCovering.smooth_toPartitionOfUnity
variable {s : Set M}
/-- A `BumpCovering` such that all functions in this covering are smooth generates a smooth
partition of unity.
In our formalization, not every `f : BumpCovering ι M s` with smooth functions `f i` is a
`SmoothBumpCovering`; instead, a `SmoothBumpCovering` is a covering by supports of
`SmoothBumpFunction`s. So, we define `BumpCovering.toSmoothPartitionOfUnity`, then reuse it
in `SmoothBumpCovering.toSmoothPartitionOfUnity`. -/
def toSmoothPartitionOfUnity (f : BumpCovering ι M s) (hf : ∀ i, Smooth I 𝓘(ℝ) (f i)) :
SmoothPartitionOfUnity ι I M s :=
{ f.toPartitionOfUnity with
toFun := fun i => ⟨f.toPartitionOfUnity i, f.smooth_toPartitionOfUnity hf i⟩ }
#align bump_covering.to_smooth_partition_of_unity BumpCovering.toSmoothPartitionOfUnity
@[simp]
theorem toSmoothPartitionOfUnity_toPartitionOfUnity (f : BumpCovering ι M s)
(hf : ∀ i, Smooth I 𝓘(ℝ) (f i)) :
(f.toSmoothPartitionOfUnity hf).toPartitionOfUnity = f.toPartitionOfUnity :=
rfl
#align bump_covering.to_smooth_partition_of_unity_to_partition_of_unity BumpCovering.toSmoothPartitionOfUnity_toPartitionOfUnity
@[simp]
theorem coe_toSmoothPartitionOfUnity (f : BumpCovering ι M s) (hf : ∀ i, Smooth I 𝓘(ℝ) (f i))
(i : ι) : ⇑(f.toSmoothPartitionOfUnity hf i) = f.toPartitionOfUnity i :=
rfl
#align bump_covering.coe_to_smooth_partition_of_unity BumpCovering.coe_toSmoothPartitionOfUnity
theorem IsSubordinate.toSmoothPartitionOfUnity {f : BumpCovering ι M s} {U : ι → Set M}
(h : f.IsSubordinate U) (hf : ∀ i, Smooth I 𝓘(ℝ) (f i)) :
(f.toSmoothPartitionOfUnity hf).IsSubordinate U :=
h.toPartitionOfUnity
#align bump_covering.is_subordinate.to_smooth_partition_of_unity BumpCovering.IsSubordinate.toSmoothPartitionOfUnity
end BumpCovering
namespace SmoothBumpCovering
variable {s : Set M} {U : M → Set M} (fs : SmoothBumpCovering ι I M s)
instance : CoeFun (SmoothBumpCovering ι I M s) fun x => ∀ i : ι, SmoothBumpFunction I (x.c i) :=
⟨toFun⟩
#noalign smooth_bump_covering.coe_mk
/--
We say that `f : SmoothBumpCovering ι I M s` is *subordinate* to a map `U : M → Set M` if for each
index `i`, we have `tsupport (f i) ⊆ U (f i).c`. This notion is a bit more general than
being subordinate to an open covering of `M`, because we make no assumption about the way `U x`
depends on `x`.
-/
def IsSubordinate {s : Set M} (f : SmoothBumpCovering ι I M s) (U : M → Set M) :=
∀ i, tsupport (f i) ⊆ U (f.c i)
#align smooth_bump_covering.is_subordinate SmoothBumpCovering.IsSubordinate
theorem IsSubordinate.support_subset {fs : SmoothBumpCovering ι I M s} {U : M → Set M}
(h : fs.IsSubordinate U) (i : ι) : support (fs i) ⊆ U (fs.c i) :=
Subset.trans subset_closure (h i)
#align smooth_bump_covering.is_subordinate.support_subset SmoothBumpCovering.IsSubordinate.support_subset
variable (I)
/-- Let `M` be a smooth manifold with corners modelled on a finite dimensional real vector space.
Suppose also that `M` is a Hausdorff `σ`-compact topological space. Let `s` be a closed set
in `M` and `U : M → Set M` be a collection of sets such that `U x ∈ 𝓝 x` for every `x ∈ s`.
Then there exists a smooth bump covering of `s` that is subordinate to `U`. -/
theorem exists_isSubordinate [T2Space M] [SigmaCompactSpace M] (hs : IsClosed s)
(hU : ∀ x ∈ s, U x ∈ 𝓝 x) :
∃ (ι : Type uM) (f : SmoothBumpCovering ι I M s), f.IsSubordinate U := by
-- First we deduce some missing instances
haveI : LocallyCompactSpace H := I.locallyCompactSpace
haveI : LocallyCompactSpace M := ChartedSpace.locallyCompactSpace H M
-- Next we choose a covering by supports of smooth bump functions
have hB := fun x hx => SmoothBumpFunction.nhds_basis_support I (hU x hx)
rcases refinement_of_locallyCompact_sigmaCompact_of_nhds_basis_set hs hB with
⟨ι, c, f, hf, hsub', hfin⟩
choose hcs hfU using hf
-- Then we use the shrinking lemma to get a covering by smaller open
rcases exists_subset_iUnion_closed_subset hs (fun i => (f i).isOpen_support)
(fun x _ => hfin.point_finite x) hsub' with ⟨V, hsV, hVc, hVf⟩
choose r hrR hr using fun i => (f i).exists_r_pos_lt_subset_ball (hVc i) (hVf i)
refine ⟨ι, ⟨c, fun i => (f i).updateRIn (r i) (hrR i), hcs, ?_, fun x hx => ?_⟩, fun i => ?_⟩
· simpa only [SmoothBumpFunction.support_updateRIn]
· refine (mem_iUnion.1 <| hsV hx).imp fun i hi => ?_
exact ((f i).updateRIn _ _).eventuallyEq_one_of_dist_lt
((f i).support_subset_source <| hVf _ hi) (hr i hi).2
· simpa only [SmoothBumpFunction.support_updateRIn, tsupport] using hfU i
#align smooth_bump_covering.exists_is_subordinate SmoothBumpCovering.exists_isSubordinate
variable {I}
protected theorem locallyFinite : LocallyFinite fun i => support (fs i) :=
fs.locallyFinite'
#align smooth_bump_covering.locally_finite SmoothBumpCovering.locallyFinite
protected theorem point_finite (x : M) : {i | fs i x ≠ 0}.Finite :=
fs.locallyFinite.point_finite x
#align smooth_bump_covering.point_finite SmoothBumpCovering.point_finite
theorem mem_chartAt_source_of_eq_one {i : ι} {x : M} (h : fs i x = 1) :
x ∈ (chartAt H (fs.c i)).source :=
(fs i).support_subset_source <| by simp [h]
#align smooth_bump_covering.mem_chart_at_source_of_eq_one SmoothBumpCovering.mem_chartAt_source_of_eq_one
theorem mem_extChartAt_source_of_eq_one {i : ι} {x : M} (h : fs i x = 1) :
x ∈ (extChartAt I (fs.c i)).source := by
rw [extChartAt_source]; exact fs.mem_chartAt_source_of_eq_one h
#align smooth_bump_covering.mem_ext_chart_at_source_of_eq_one SmoothBumpCovering.mem_extChartAt_source_of_eq_one
/-- Index of a bump function such that `fs i =ᶠ[𝓝 x] 1`. -/
def ind (x : M) (hx : x ∈ s) : ι :=
(fs.eventuallyEq_one' x hx).choose
#align smooth_bump_covering.ind SmoothBumpCovering.ind
theorem eventuallyEq_one (x : M) (hx : x ∈ s) : fs (fs.ind x hx) =ᶠ[𝓝 x] 1 :=
(fs.eventuallyEq_one' x hx).choose_spec
#align smooth_bump_covering.eventually_eq_one SmoothBumpCovering.eventuallyEq_one
theorem apply_ind (x : M) (hx : x ∈ s) : fs (fs.ind x hx) x = 1 :=
(fs.eventuallyEq_one x hx).eq_of_nhds
#align smooth_bump_covering.apply_ind SmoothBumpCovering.apply_ind
theorem mem_support_ind (x : M) (hx : x ∈ s) : x ∈ support (fs <| fs.ind x hx) := by
simp [fs.apply_ind x hx]
#align smooth_bump_covering.mem_support_ind SmoothBumpCovering.mem_support_ind
theorem mem_chartAt_ind_source (x : M) (hx : x ∈ s) : x ∈ (chartAt H (fs.c (fs.ind x hx))).source :=
fs.mem_chartAt_source_of_eq_one (fs.apply_ind x hx)
#align smooth_bump_covering.mem_chart_at_ind_source SmoothBumpCovering.mem_chartAt_ind_source
theorem mem_extChartAt_ind_source (x : M) (hx : x ∈ s) :
x ∈ (extChartAt I (fs.c (fs.ind x hx))).source :=
fs.mem_extChartAt_source_of_eq_one (fs.apply_ind x hx)
#align smooth_bump_covering.mem_ext_chart_at_ind_source SmoothBumpCovering.mem_extChartAt_ind_source
/-- The index type of a `SmoothBumpCovering` of a compact manifold is finite. -/
protected def fintype [CompactSpace M] : Fintype ι :=
fs.locallyFinite.fintypeOfCompact fun i => (fs i).nonempty_support
#align smooth_bump_covering.fintype SmoothBumpCovering.fintype
variable [T2Space M]
/-- Reinterpret a `SmoothBumpCovering` as a continuous `BumpCovering`. Note that not every
`f : BumpCovering ι M s` with smooth functions `f i` is a `SmoothBumpCovering`. -/
def toBumpCovering : BumpCovering ι M s where
toFun i := ⟨fs i, (fs i).continuous⟩
locallyFinite' := fs.locallyFinite
nonneg' i _ := (fs i).nonneg
le_one' i _ := (fs i).le_one
eventuallyEq_one' := fs.eventuallyEq_one'
#align smooth_bump_covering.to_bump_covering SmoothBumpCovering.toBumpCovering
-- Porting note: `simpNF` says that `simp` can't simplify LHS but it can.
@[simp, nolint simpNF]
theorem isSubordinate_toBumpCovering {f : SmoothBumpCovering ι I M s} {U : M → Set M} :
(f.toBumpCovering.IsSubordinate fun i => U (f.c i)) ↔ f.IsSubordinate U :=
Iff.rfl
#align smooth_bump_covering.is_subordinate_to_bump_covering SmoothBumpCovering.isSubordinate_toBumpCovering
alias ⟨_, IsSubordinate.toBumpCovering⟩ := isSubordinate_toBumpCovering
#align smooth_bump_covering.is_subordinate.to_bump_covering SmoothBumpCovering.IsSubordinate.toBumpCovering
/-- Every `SmoothBumpCovering` defines a smooth partition of unity. -/
def toSmoothPartitionOfUnity : SmoothPartitionOfUnity ι I M s :=
fs.toBumpCovering.toSmoothPartitionOfUnity fun i => (fs i).smooth
#align smooth_bump_covering.to_smooth_partition_of_unity SmoothBumpCovering.toSmoothPartitionOfUnity
theorem toSmoothPartitionOfUnity_apply (i : ι) (x : M) :
fs.toSmoothPartitionOfUnity i x = fs i x * ∏ᶠ (j) (_ : WellOrderingRel j i), (1 - fs j x) :=
rfl
#align smooth_bump_covering.to_smooth_partition_of_unity_apply SmoothBumpCovering.toSmoothPartitionOfUnity_apply
theorem toSmoothPartitionOfUnity_eq_mul_prod (i : ι) (x : M) (t : Finset ι)
(ht : ∀ j, WellOrderingRel j i → fs j x ≠ 0 → j ∈ t) :
fs.toSmoothPartitionOfUnity i x =
fs i x * ∏ j ∈ t.filter fun j => WellOrderingRel j i, (1 - fs j x) :=
fs.toBumpCovering.toPartitionOfUnity_eq_mul_prod i x t ht
#align smooth_bump_covering.to_smooth_partition_of_unity_eq_mul_prod SmoothBumpCovering.toSmoothPartitionOfUnity_eq_mul_prod
theorem exists_finset_toSmoothPartitionOfUnity_eventuallyEq (i : ι) (x : M) :
∃ t : Finset ι,
fs.toSmoothPartitionOfUnity i =ᶠ[𝓝 x]
fs i * ∏ j ∈ t.filter fun j => WellOrderingRel j i, ((1 : M → ℝ) - fs j) := by
-- Porting note: was defeq, now the continuous lemma uses bundled homs
simpa using fs.toBumpCovering.exists_finset_toPartitionOfUnity_eventuallyEq i x
#align smooth_bump_covering.exists_finset_to_smooth_partition_of_unity_eventually_eq SmoothBumpCovering.exists_finset_toSmoothPartitionOfUnity_eventuallyEq
theorem toSmoothPartitionOfUnity_zero_of_zero {i : ι} {x : M} (h : fs i x = 0) :
fs.toSmoothPartitionOfUnity i x = 0 :=
fs.toBumpCovering.toPartitionOfUnity_zero_of_zero h
#align smooth_bump_covering.to_smooth_partition_of_unity_zero_of_zero SmoothBumpCovering.toSmoothPartitionOfUnity_zero_of_zero
theorem support_toSmoothPartitionOfUnity_subset (i : ι) :
support (fs.toSmoothPartitionOfUnity i) ⊆ support (fs i) :=
fs.toBumpCovering.support_toPartitionOfUnity_subset i
#align smooth_bump_covering.support_to_smooth_partition_of_unity_subset SmoothBumpCovering.support_toSmoothPartitionOfUnity_subset
theorem IsSubordinate.toSmoothPartitionOfUnity {f : SmoothBumpCovering ι I M s} {U : M → Set M}
(h : f.IsSubordinate U) : f.toSmoothPartitionOfUnity.IsSubordinate fun i => U (f.c i) :=
h.toBumpCovering.toPartitionOfUnity
#align smooth_bump_covering.is_subordinate.to_smooth_partition_of_unity SmoothBumpCovering.IsSubordinate.toSmoothPartitionOfUnity
theorem sum_toSmoothPartitionOfUnity_eq (x : M) :
∑ᶠ i, fs.toSmoothPartitionOfUnity i x = 1 - ∏ᶠ i, (1 - fs i x) :=
fs.toBumpCovering.sum_toPartitionOfUnity_eq x
#align smooth_bump_covering.sum_to_smooth_partition_of_unity_eq SmoothBumpCovering.sum_toSmoothPartitionOfUnity_eq
end SmoothBumpCovering
variable (I)
/-- Given two disjoint closed sets `s, t` in a Hausdorff σ-compact finite dimensional manifold,
there exists an infinitely smooth function that is equal to `0` on `s` and to `1` on `t`.
See also `exists_msmooth_zero_iff_one_iff_of_isClosed`, which ensures additionally that
`f` is equal to `0` exactly on `s` and to `1` exactly on `t`. -/
| Mathlib/Geometry/Manifold/PartitionOfUnity.lean | 559 | 570 | theorem exists_smooth_zero_one_of_isClosed [T2Space M] [SigmaCompactSpace M] {s t : Set M}
(hs : IsClosed s) (ht : IsClosed t) (hd : Disjoint s t) :
∃ f : C^∞⟮I, M; 𝓘(ℝ), ℝ⟯, EqOn f 0 s ∧ EqOn f 1 t ∧ ∀ x, f x ∈ Icc 0 1 := by |
have : ∀ x ∈ t, sᶜ ∈ 𝓝 x := fun x hx => hs.isOpen_compl.mem_nhds (disjoint_right.1 hd hx)
rcases SmoothBumpCovering.exists_isSubordinate I ht this with ⟨ι, f, hf⟩
set g := f.toSmoothPartitionOfUnity
refine
⟨⟨_, g.smooth_sum⟩, fun x hx => ?_, fun x => g.sum_eq_one, fun x =>
⟨g.sum_nonneg x, g.sum_le_one x⟩⟩
suffices ∀ i, g i x = 0 by simp only [this, ContMDiffMap.coeFn_mk, finsum_zero, Pi.zero_apply]
refine fun i => f.toSmoothPartitionOfUnity_zero_of_zero ?_
exact nmem_support.1 (subset_compl_comm.1 (hf.support_subset i) hx)
|
/-
Copyright (c) 2022 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.Bochner
import Mathlib.MeasureTheory.Measure.GiryMonad
#align_import probability.kernel.basic from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Markov Kernels
A kernel from a measurable space `α` to another measurable space `β` is a measurable map
`α → MeasureTheory.Measure β`, where the measurable space instance on `measure β` is the one defined
in `MeasureTheory.Measure.instMeasurableSpace`. That is, a kernel `κ` verifies that for all
measurable sets `s` of `β`, `a ↦ κ a s` is measurable.
## Main definitions
Classes of kernels:
* `ProbabilityTheory.kernel α β`: kernels from `α` to `β`, defined as the `AddSubmonoid` of the
measurable functions in `α → Measure β`.
* `ProbabilityTheory.IsMarkovKernel κ`: a kernel from `α` to `β` is said to be a Markov kernel
if for all `a : α`, `k a` is a probability measure.
* `ProbabilityTheory.IsFiniteKernel κ`: a kernel from `α` to `β` is said to be finite if there
exists `C : ℝ≥0∞` such that `C < ∞` and for all `a : α`, `κ a univ ≤ C`. This implies in
particular that all measures in the image of `κ` are finite, but is stronger since it requires a
uniform bound. This stronger condition is necessary to ensure that the composition of two finite
kernels is finite.
* `ProbabilityTheory.IsSFiniteKernel κ`: a kernel is called s-finite if it is a countable
sum of finite kernels.
Particular kernels:
* `ProbabilityTheory.kernel.deterministic (f : α → β) (hf : Measurable f)`:
kernel `a ↦ Measure.dirac (f a)`.
* `ProbabilityTheory.kernel.const α (μβ : measure β)`: constant kernel `a ↦ μβ`.
* `ProbabilityTheory.kernel.restrict κ (hs : MeasurableSet s)`: kernel for which the image of
`a : α` is `(κ a).restrict s`.
Integral: `∫⁻ b, f b ∂(kernel.restrict κ hs a) = ∫⁻ b in s, f b ∂(κ a)`
## Main statements
* `ProbabilityTheory.kernel.ext_fun`: if `∫⁻ b, f b ∂(κ a) = ∫⁻ b, f b ∂(η a)` for all measurable
functions `f` and all `a`, then the two kernels `κ` and `η` are equal.
-/
open MeasureTheory
open scoped MeasureTheory ENNReal NNReal
namespace ProbabilityTheory
/-- A kernel from a measurable space `α` to another measurable space `β` is a measurable function
`κ : α → Measure β`. The measurable space structure on `MeasureTheory.Measure β` is given by
`MeasureTheory.Measure.instMeasurableSpace`. A map `κ : α → MeasureTheory.Measure β` is measurable
iff `∀ s : Set β, MeasurableSet s → Measurable (fun a ↦ κ a s)`. -/
noncomputable def kernel (α β : Type*) [MeasurableSpace α] [MeasurableSpace β] :
AddSubmonoid (α → Measure β) where
carrier := Measurable
zero_mem' := measurable_zero
add_mem' hf hg := Measurable.add hf hg
#align probability_theory.kernel ProbabilityTheory.kernel
-- Porting note: using `FunLike` instead of `CoeFun` to use `DFunLike.coe`
instance {α β : Type*} [MeasurableSpace α] [MeasurableSpace β] :
FunLike (kernel α β) α (Measure β) where
coe := Subtype.val
coe_injective' := Subtype.val_injective
instance kernel.instCovariantAddLE {α β : Type*} [MeasurableSpace α] [MeasurableSpace β] :
CovariantClass (kernel α β) (kernel α β) (· + ·) (· ≤ ·) :=
⟨fun _ _ _ hμ a ↦ add_le_add_left (hμ a) _⟩
noncomputable
instance kernel.instOrderBot {α β : Type*} [MeasurableSpace α] [MeasurableSpace β] :
OrderBot (kernel α β) where
bot := 0
bot_le κ a := by simp only [ZeroMemClass.coe_zero, Pi.zero_apply, Measure.zero_le]
variable {α β ι : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β}
namespace kernel
@[simp]
theorem coeFn_zero : ⇑(0 : kernel α β) = 0 :=
rfl
#align probability_theory.kernel.coe_fn_zero ProbabilityTheory.kernel.coeFn_zero
@[simp]
theorem coeFn_add (κ η : kernel α β) : ⇑(κ + η) = κ + η :=
rfl
#align probability_theory.kernel.coe_fn_add ProbabilityTheory.kernel.coeFn_add
/-- Coercion to a function as an additive monoid homomorphism. -/
def coeAddHom (α β : Type*) [MeasurableSpace α] [MeasurableSpace β] :
kernel α β →+ α → Measure β :=
AddSubmonoid.subtype _
#align probability_theory.kernel.coe_add_hom ProbabilityTheory.kernel.coeAddHom
@[simp]
theorem zero_apply (a : α) : (0 : kernel α β) a = 0 :=
rfl
#align probability_theory.kernel.zero_apply ProbabilityTheory.kernel.zero_apply
@[simp]
theorem coe_finset_sum (I : Finset ι) (κ : ι → kernel α β) : ⇑(∑ i ∈ I, κ i) = ∑ i ∈ I, ⇑(κ i) :=
map_sum (coeAddHom α β) _ _
#align probability_theory.kernel.coe_finset_sum ProbabilityTheory.kernel.coe_finset_sum
theorem finset_sum_apply (I : Finset ι) (κ : ι → kernel α β) (a : α) :
(∑ i ∈ I, κ i) a = ∑ i ∈ I, κ i a := by rw [coe_finset_sum, Finset.sum_apply]
#align probability_theory.kernel.finset_sum_apply ProbabilityTheory.kernel.finset_sum_apply
theorem finset_sum_apply' (I : Finset ι) (κ : ι → kernel α β) (a : α) (s : Set β) :
(∑ i ∈ I, κ i) a s = ∑ i ∈ I, κ i a s := by rw [finset_sum_apply, Measure.finset_sum_apply]
#align probability_theory.kernel.finset_sum_apply' ProbabilityTheory.kernel.finset_sum_apply'
end kernel
/-- A kernel is a Markov kernel if every measure in its image is a probability measure. -/
class IsMarkovKernel (κ : kernel α β) : Prop where
isProbabilityMeasure : ∀ a, IsProbabilityMeasure (κ a)
#align probability_theory.is_markov_kernel ProbabilityTheory.IsMarkovKernel
/-- A kernel is finite if every measure in its image is finite, with a uniform bound. -/
class IsFiniteKernel (κ : kernel α β) : Prop where
exists_univ_le : ∃ C : ℝ≥0∞, C < ∞ ∧ ∀ a, κ a Set.univ ≤ C
#align probability_theory.is_finite_kernel ProbabilityTheory.IsFiniteKernel
/-- A constant `C : ℝ≥0∞` such that `C < ∞` (`ProbabilityTheory.IsFiniteKernel.bound_lt_top κ`) and
for all `a : α` and `s : Set β`, `κ a s ≤ C` (`ProbabilityTheory.kernel.measure_le_bound κ a s`).
Porting note (#11215): TODO: does it make sense to
-- make `ProbabilityTheory.IsFiniteKernel.bound` the least possible bound?
-- Should it be an `NNReal` number? -/
noncomputable def IsFiniteKernel.bound (κ : kernel α β) [h : IsFiniteKernel κ] : ℝ≥0∞ :=
h.exists_univ_le.choose
#align probability_theory.is_finite_kernel.bound ProbabilityTheory.IsFiniteKernel.bound
theorem IsFiniteKernel.bound_lt_top (κ : kernel α β) [h : IsFiniteKernel κ] :
IsFiniteKernel.bound κ < ∞ :=
h.exists_univ_le.choose_spec.1
#align probability_theory.is_finite_kernel.bound_lt_top ProbabilityTheory.IsFiniteKernel.bound_lt_top
theorem IsFiniteKernel.bound_ne_top (κ : kernel α β) [IsFiniteKernel κ] :
IsFiniteKernel.bound κ ≠ ∞ :=
(IsFiniteKernel.bound_lt_top κ).ne
#align probability_theory.is_finite_kernel.bound_ne_top ProbabilityTheory.IsFiniteKernel.bound_ne_top
theorem kernel.measure_le_bound (κ : kernel α β) [h : IsFiniteKernel κ] (a : α) (s : Set β) :
κ a s ≤ IsFiniteKernel.bound κ :=
(measure_mono (Set.subset_univ s)).trans (h.exists_univ_le.choose_spec.2 a)
#align probability_theory.kernel.measure_le_bound ProbabilityTheory.kernel.measure_le_bound
instance isFiniteKernel_zero (α β : Type*) {mα : MeasurableSpace α} {mβ : MeasurableSpace β} :
IsFiniteKernel (0 : kernel α β) :=
⟨⟨0, ENNReal.coe_lt_top, fun _ => by
simp only [kernel.zero_apply, Measure.coe_zero, Pi.zero_apply, le_zero_iff]⟩⟩
#align probability_theory.is_finite_kernel_zero ProbabilityTheory.isFiniteKernel_zero
instance IsFiniteKernel.add (κ η : kernel α β) [IsFiniteKernel κ] [IsFiniteKernel η] :
IsFiniteKernel (κ + η) := by
refine ⟨⟨IsFiniteKernel.bound κ + IsFiniteKernel.bound η,
ENNReal.add_lt_top.mpr ⟨IsFiniteKernel.bound_lt_top κ, IsFiniteKernel.bound_lt_top η⟩,
fun a => ?_⟩⟩
exact add_le_add (kernel.measure_le_bound _ _ _) (kernel.measure_le_bound _ _ _)
#align probability_theory.is_finite_kernel.add ProbabilityTheory.IsFiniteKernel.add
lemma isFiniteKernel_of_le {κ ν : kernel α β} [hν : IsFiniteKernel ν] (hκν : κ ≤ ν) :
IsFiniteKernel κ := by
refine ⟨hν.bound, hν.bound_lt_top, fun a ↦ (hκν _ _).trans (kernel.measure_le_bound ν a Set.univ)⟩
variable {κ : kernel α β}
instance IsMarkovKernel.is_probability_measure' [IsMarkovKernel κ] (a : α) :
IsProbabilityMeasure (κ a) :=
IsMarkovKernel.isProbabilityMeasure a
#align probability_theory.is_markov_kernel.is_probability_measure' ProbabilityTheory.IsMarkovKernel.is_probability_measure'
instance IsFiniteKernel.isFiniteMeasure [IsFiniteKernel κ] (a : α) : IsFiniteMeasure (κ a) :=
⟨(kernel.measure_le_bound κ a Set.univ).trans_lt (IsFiniteKernel.bound_lt_top κ)⟩
#align probability_theory.is_finite_kernel.is_finite_measure ProbabilityTheory.IsFiniteKernel.isFiniteMeasure
instance (priority := 100) IsMarkovKernel.isFiniteKernel [IsMarkovKernel κ] :
IsFiniteKernel κ :=
⟨⟨1, ENNReal.one_lt_top, fun _ => prob_le_one⟩⟩
#align probability_theory.is_markov_kernel.is_finite_kernel ProbabilityTheory.IsMarkovKernel.isFiniteKernel
namespace kernel
@[ext]
theorem ext {η : kernel α β} (h : ∀ a, κ a = η a) : κ = η := DFunLike.ext _ _ h
#align probability_theory.kernel.ext ProbabilityTheory.kernel.ext
theorem ext_iff {η : kernel α β} : κ = η ↔ ∀ a, κ a = η a := DFunLike.ext_iff
#align probability_theory.kernel.ext_iff ProbabilityTheory.kernel.ext_iff
theorem ext_iff' {η : kernel α β} :
κ = η ↔ ∀ a s, MeasurableSet s → κ a s = η a s := by
simp_rw [ext_iff, Measure.ext_iff]
#align probability_theory.kernel.ext_iff' ProbabilityTheory.kernel.ext_iff'
theorem ext_fun {η : kernel α β} (h : ∀ a f, Measurable f → ∫⁻ b, f b ∂κ a = ∫⁻ b, f b ∂η a) :
κ = η := by
ext a s hs
specialize h a (s.indicator fun _ => 1) (Measurable.indicator measurable_const hs)
simp_rw [lintegral_indicator_const hs, one_mul] at h
rw [h]
#align probability_theory.kernel.ext_fun ProbabilityTheory.kernel.ext_fun
theorem ext_fun_iff {η : kernel α β} :
κ = η ↔ ∀ a f, Measurable f → ∫⁻ b, f b ∂κ a = ∫⁻ b, f b ∂η a :=
⟨fun h a f _ => by rw [h], ext_fun⟩
#align probability_theory.kernel.ext_fun_iff ProbabilityTheory.kernel.ext_fun_iff
protected theorem measurable (κ : kernel α β) : Measurable κ :=
κ.prop
#align probability_theory.kernel.measurable ProbabilityTheory.kernel.measurable
protected theorem measurable_coe (κ : kernel α β) {s : Set β} (hs : MeasurableSet s) :
Measurable fun a => κ a s :=
(Measure.measurable_coe hs).comp (kernel.measurable κ)
#align probability_theory.kernel.measurable_coe ProbabilityTheory.kernel.measurable_coe
lemma IsFiniteKernel.integrable (μ : Measure α) [IsFiniteMeasure μ]
(κ : kernel α β) [IsFiniteKernel κ] {s : Set β} (hs : MeasurableSet s) :
Integrable (fun x => (κ x s).toReal) μ := by
refine Integrable.mono' (integrable_const (IsFiniteKernel.bound κ).toReal)
((kernel.measurable_coe κ hs).ennreal_toReal.aestronglyMeasurable)
(ae_of_all μ fun x => ?_)
rw [Real.norm_eq_abs, abs_of_nonneg ENNReal.toReal_nonneg,
ENNReal.toReal_le_toReal (measure_ne_top _ _) (IsFiniteKernel.bound_ne_top _)]
exact kernel.measure_le_bound _ _ _
lemma IsMarkovKernel.integrable (μ : Measure α) [IsFiniteMeasure μ]
(κ : kernel α β) [IsMarkovKernel κ] {s : Set β} (hs : MeasurableSet s) :
Integrable (fun x => (κ x s).toReal) μ :=
IsFiniteKernel.integrable μ κ hs
section Sum
/-- Sum of an indexed family of kernels. -/
protected noncomputable def sum [Countable ι] (κ : ι → kernel α β) : kernel α β where
val a := Measure.sum fun n => κ n a
property := by
refine Measure.measurable_of_measurable_coe _ fun s hs => ?_
simp_rw [Measure.sum_apply _ hs]
exact Measurable.ennreal_tsum fun n => kernel.measurable_coe (κ n) hs
#align probability_theory.kernel.sum ProbabilityTheory.kernel.sum
theorem sum_apply [Countable ι] (κ : ι → kernel α β) (a : α) :
kernel.sum κ a = Measure.sum fun n => κ n a :=
rfl
#align probability_theory.kernel.sum_apply ProbabilityTheory.kernel.sum_apply
theorem sum_apply' [Countable ι] (κ : ι → kernel α β) (a : α) {s : Set β} (hs : MeasurableSet s) :
kernel.sum κ a s = ∑' n, κ n a s := by rw [sum_apply κ a, Measure.sum_apply _ hs]
#align probability_theory.kernel.sum_apply' ProbabilityTheory.kernel.sum_apply'
@[simp]
theorem sum_zero [Countable ι] : (kernel.sum fun _ : ι => (0 : kernel α β)) = 0 := by
ext a s hs
rw [sum_apply' _ a hs]
simp only [zero_apply, Measure.coe_zero, Pi.zero_apply, tsum_zero]
#align probability_theory.kernel.sum_zero ProbabilityTheory.kernel.sum_zero
theorem sum_comm [Countable ι] (κ : ι → ι → kernel α β) :
(kernel.sum fun n => kernel.sum (κ n)) = kernel.sum fun m => kernel.sum fun n => κ n m := by
ext a s; simp_rw [sum_apply]; rw [Measure.sum_comm]
#align probability_theory.kernel.sum_comm ProbabilityTheory.kernel.sum_comm
@[simp]
theorem sum_fintype [Fintype ι] (κ : ι → kernel α β) : kernel.sum κ = ∑ i, κ i := by
ext a s hs
simp only [sum_apply' κ a hs, finset_sum_apply' _ κ a s, tsum_fintype]
#align probability_theory.kernel.sum_fintype ProbabilityTheory.kernel.sum_fintype
theorem sum_add [Countable ι] (κ η : ι → kernel α β) :
(kernel.sum fun n => κ n + η n) = kernel.sum κ + kernel.sum η := by
ext a s hs
simp only [coeFn_add, Pi.add_apply, sum_apply, Measure.sum_apply _ hs, Pi.add_apply,
Measure.coe_add, tsum_add ENNReal.summable ENNReal.summable]
#align probability_theory.kernel.sum_add ProbabilityTheory.kernel.sum_add
end Sum
section SFinite
/-- A kernel is s-finite if it can be written as the sum of countably many finite kernels. -/
class _root_.ProbabilityTheory.IsSFiniteKernel (κ : kernel α β) : Prop where
tsum_finite : ∃ κs : ℕ → kernel α β, (∀ n, IsFiniteKernel (κs n)) ∧ κ = kernel.sum κs
#align probability_theory.is_s_finite_kernel ProbabilityTheory.IsSFiniteKernel
instance (priority := 100) IsFiniteKernel.isSFiniteKernel [h : IsFiniteKernel κ] :
IsSFiniteKernel κ :=
⟨⟨fun n => if n = 0 then κ else 0, fun n => by
simp only; split_ifs
· exact h
· infer_instance, by
ext a s hs
rw [kernel.sum_apply' _ _ hs]
have : (fun i => ((ite (i = 0) κ 0) a) s) = fun i => ite (i = 0) (κ a s) 0 := by
ext1 i; split_ifs <;> rfl
rw [this, tsum_ite_eq]⟩⟩
#align probability_theory.kernel.is_finite_kernel.is_s_finite_kernel ProbabilityTheory.kernel.IsFiniteKernel.isSFiniteKernel
/-- A sequence of finite kernels such that `κ = ProbabilityTheory.kernel.sum (seq κ)`. See
`ProbabilityTheory.kernel.isFiniteKernel_seq` and `ProbabilityTheory.kernel.kernel_sum_seq`. -/
noncomputable def seq (κ : kernel α β) [h : IsSFiniteKernel κ] : ℕ → kernel α β :=
h.tsum_finite.choose
#align probability_theory.kernel.seq ProbabilityTheory.kernel.seq
theorem kernel_sum_seq (κ : kernel α β) [h : IsSFiniteKernel κ] : kernel.sum (seq κ) = κ :=
h.tsum_finite.choose_spec.2.symm
#align probability_theory.kernel.kernel_sum_seq ProbabilityTheory.kernel.kernel_sum_seq
theorem measure_sum_seq (κ : kernel α β) [h : IsSFiniteKernel κ] (a : α) :
(Measure.sum fun n => seq κ n a) = κ a := by rw [← kernel.sum_apply, kernel_sum_seq κ]
#align probability_theory.kernel.measure_sum_seq ProbabilityTheory.kernel.measure_sum_seq
instance isFiniteKernel_seq (κ : kernel α β) [h : IsSFiniteKernel κ] (n : ℕ) :
IsFiniteKernel (kernel.seq κ n) :=
h.tsum_finite.choose_spec.1 n
#align probability_theory.kernel.is_finite_kernel_seq ProbabilityTheory.kernel.isFiniteKernel_seq
instance IsSFiniteKernel.sFinite [IsSFiniteKernel κ] (a : α) : SFinite (κ a) :=
⟨⟨fun n ↦ seq κ n a, inferInstance, (measure_sum_seq κ a).symm⟩⟩
instance IsSFiniteKernel.add (κ η : kernel α β) [IsSFiniteKernel κ] [IsSFiniteKernel η] :
IsSFiniteKernel (κ + η) := by
refine ⟨⟨fun n => seq κ n + seq η n, fun n => inferInstance, ?_⟩⟩
rw [sum_add, kernel_sum_seq κ, kernel_sum_seq η]
#align probability_theory.kernel.is_s_finite_kernel.add ProbabilityTheory.kernel.IsSFiniteKernel.add
theorem IsSFiniteKernel.finset_sum {κs : ι → kernel α β} (I : Finset ι)
(h : ∀ i ∈ I, IsSFiniteKernel (κs i)) : IsSFiniteKernel (∑ i ∈ I, κs i) := by
classical
induction' I using Finset.induction with i I hi_nmem_I h_ind h
· rw [Finset.sum_empty]; infer_instance
· rw [Finset.sum_insert hi_nmem_I]
haveI : IsSFiniteKernel (κs i) := h i (Finset.mem_insert_self _ _)
have : IsSFiniteKernel (∑ x ∈ I, κs x) :=
h_ind fun i hiI => h i (Finset.mem_insert_of_mem hiI)
exact IsSFiniteKernel.add _ _
#align probability_theory.kernel.is_s_finite_kernel.finset_sum ProbabilityTheory.kernel.IsSFiniteKernel.finset_sum
theorem isSFiniteKernel_sum_of_denumerable [Denumerable ι] {κs : ι → kernel α β}
(hκs : ∀ n, IsSFiniteKernel (κs n)) : IsSFiniteKernel (kernel.sum κs) := by
let e : ℕ ≃ ι × ℕ := (Denumerable.eqv (ι × ℕ)).symm
refine ⟨⟨fun n => seq (κs (e n).1) (e n).2, inferInstance, ?_⟩⟩
have hκ_eq : kernel.sum κs = kernel.sum fun n => kernel.sum (seq (κs n)) := by
simp_rw [kernel_sum_seq]
ext a s hs
rw [hκ_eq]
simp_rw [kernel.sum_apply' _ _ hs]
change (∑' i, ∑' m, seq (κs i) m a s) = ∑' n, (fun im : ι × ℕ => seq (κs im.fst) im.snd a s) (e n)
rw [e.tsum_eq (fun im : ι × ℕ => seq (κs im.fst) im.snd a s),
tsum_prod' ENNReal.summable fun _ => ENNReal.summable]
#align probability_theory.kernel.is_s_finite_kernel_sum_of_denumerable ProbabilityTheory.kernel.isSFiniteKernel_sum_of_denumerable
theorem isSFiniteKernel_sum [Countable ι] {κs : ι → kernel α β}
(hκs : ∀ n, IsSFiniteKernel (κs n)) : IsSFiniteKernel (kernel.sum κs) := by
cases fintypeOrInfinite ι
· rw [sum_fintype]
exact IsSFiniteKernel.finset_sum Finset.univ fun i _ => hκs i
cases nonempty_denumerable ι
exact isSFiniteKernel_sum_of_denumerable hκs
#align probability_theory.kernel.is_s_finite_kernel_sum ProbabilityTheory.kernel.isSFiniteKernel_sum
end SFinite
section Deterministic
/-- Kernel which to `a` associates the dirac measure at `f a`. This is a Markov kernel. -/
noncomputable def deterministic (f : α → β) (hf : Measurable f) : kernel α β where
val a := Measure.dirac (f a)
property := by
refine Measure.measurable_of_measurable_coe _ fun s hs => ?_
simp_rw [Measure.dirac_apply' _ hs]
exact measurable_one.indicator (hf hs)
#align probability_theory.kernel.deterministic ProbabilityTheory.kernel.deterministic
theorem deterministic_apply {f : α → β} (hf : Measurable f) (a : α) :
deterministic f hf a = Measure.dirac (f a) :=
rfl
#align probability_theory.kernel.deterministic_apply ProbabilityTheory.kernel.deterministic_apply
theorem deterministic_apply' {f : α → β} (hf : Measurable f) (a : α) {s : Set β}
(hs : MeasurableSet s) : deterministic f hf a s = s.indicator (fun _ => 1) (f a) := by
rw [deterministic]
change Measure.dirac (f a) s = s.indicator 1 (f a)
simp_rw [Measure.dirac_apply' _ hs]
#align probability_theory.kernel.deterministic_apply' ProbabilityTheory.kernel.deterministic_apply'
instance isMarkovKernel_deterministic {f : α → β} (hf : Measurable f) :
IsMarkovKernel (deterministic f hf) :=
⟨fun a => by rw [deterministic_apply hf]; infer_instance⟩
#align probability_theory.kernel.is_markov_kernel_deterministic ProbabilityTheory.kernel.isMarkovKernel_deterministic
theorem lintegral_deterministic' {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
(hf : Measurable f) : ∫⁻ x, f x ∂kernel.deterministic g hg a = f (g a) := by
rw [kernel.deterministic_apply, lintegral_dirac' _ hf]
#align probability_theory.kernel.lintegral_deterministic' ProbabilityTheory.kernel.lintegral_deterministic'
@[simp]
theorem lintegral_deterministic {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] : ∫⁻ x, f x ∂kernel.deterministic g hg a = f (g a) := by
rw [kernel.deterministic_apply, lintegral_dirac (g a) f]
#align probability_theory.kernel.lintegral_deterministic ProbabilityTheory.kernel.lintegral_deterministic
theorem set_lintegral_deterministic' {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
(hf : Measurable f) {s : Set β} (hs : MeasurableSet s) [Decidable (g a ∈ s)] :
∫⁻ x in s, f x ∂kernel.deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [kernel.deterministic_apply, set_lintegral_dirac' hf hs]
#align probability_theory.kernel.set_lintegral_deterministic' ProbabilityTheory.kernel.set_lintegral_deterministic'
@[simp]
theorem set_lintegral_deterministic {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] (s : Set β) [Decidable (g a ∈ s)] :
∫⁻ x in s, f x ∂kernel.deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [kernel.deterministic_apply, set_lintegral_dirac f s]
#align probability_theory.kernel.set_lintegral_deterministic ProbabilityTheory.kernel.set_lintegral_deterministic
theorem integral_deterministic' {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[CompleteSpace E] {f : β → E} {g : α → β} {a : α} (hg : Measurable g)
(hf : StronglyMeasurable f) : ∫ x, f x ∂kernel.deterministic g hg a = f (g a) := by
rw [kernel.deterministic_apply, integral_dirac' _ _ hf]
#align probability_theory.kernel.integral_deterministic' ProbabilityTheory.kernel.integral_deterministic'
@[simp]
theorem integral_deterministic {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[CompleteSpace E] {f : β → E} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] : ∫ x, f x ∂kernel.deterministic g hg a = f (g a) := by
rw [kernel.deterministic_apply, integral_dirac _ (g a)]
#align probability_theory.kernel.integral_deterministic ProbabilityTheory.kernel.integral_deterministic
theorem setIntegral_deterministic' {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[CompleteSpace E] {f : β → E} {g : α → β} {a : α} (hg : Measurable g)
(hf : StronglyMeasurable f) {s : Set β} (hs : MeasurableSet s) [Decidable (g a ∈ s)] :
∫ x in s, f x ∂kernel.deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [kernel.deterministic_apply, setIntegral_dirac' hf _ hs]
#align probability_theory.kernel.set_integral_deterministic' ProbabilityTheory.kernel.setIntegral_deterministic'
@[deprecated (since := "2024-04-17")]
alias set_integral_deterministic' := setIntegral_deterministic'
@[simp]
theorem setIntegral_deterministic {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[CompleteSpace E] {f : β → E} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] (s : Set β) [Decidable (g a ∈ s)] :
∫ x in s, f x ∂kernel.deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [kernel.deterministic_apply, setIntegral_dirac f _ s]
#align probability_theory.kernel.set_integral_deterministic ProbabilityTheory.kernel.setIntegral_deterministic
@[deprecated (since := "2024-04-17")]
alias set_integral_deterministic := setIntegral_deterministic
end Deterministic
section Const
/-- Constant kernel, which always returns the same measure. -/
def const (α : Type*) {β : Type*} [MeasurableSpace α] {_ : MeasurableSpace β} (μβ : Measure β) :
kernel α β where
val _ := μβ
property := measurable_const
#align probability_theory.kernel.const ProbabilityTheory.kernel.const
@[simp]
theorem const_apply (μβ : Measure β) (a : α) : const α μβ a = μβ :=
rfl
#align probability_theory.kernel.const_apply ProbabilityTheory.kernel.const_apply
@[simp]
lemma const_zero : kernel.const α (0 : Measure β) = 0 := by
ext x s _; simp [kernel.const_apply]
lemma const_add (β : Type*) [MeasurableSpace β] (μ ν : Measure α) :
const β (μ + ν) = const β μ + const β ν := by ext; simp
lemma sum_const [Countable ι] (μ : ι → Measure β) :
kernel.sum (fun n ↦ const α (μ n)) = const α (Measure.sum μ) := by
ext x s hs
rw [const_apply, Measure.sum_apply _ hs, kernel.sum_apply' _ _ hs]
simp only [const_apply]
instance isFiniteKernel_const {μβ : Measure β} [IsFiniteMeasure μβ] :
IsFiniteKernel (const α μβ) :=
⟨⟨μβ Set.univ, measure_lt_top _ _, fun _ => le_rfl⟩⟩
#align probability_theory.kernel.is_finite_kernel_const ProbabilityTheory.kernel.isFiniteKernel_const
instance isSFiniteKernel_const {μβ : Measure β} [SFinite μβ] :
IsSFiniteKernel (const α μβ) :=
⟨fun n ↦ const α (sFiniteSeq μβ n), fun n ↦ inferInstance, by rw [sum_const, sum_sFiniteSeq]⟩
instance isMarkovKernel_const {μβ : Measure β} [hμβ : IsProbabilityMeasure μβ] :
IsMarkovKernel (const α μβ) :=
⟨fun _ => hμβ⟩
#align probability_theory.kernel.is_markov_kernel_const ProbabilityTheory.kernel.isMarkovKernel_const
@[simp]
theorem lintegral_const {f : β → ℝ≥0∞} {μ : Measure β} {a : α} :
∫⁻ x, f x ∂kernel.const α μ a = ∫⁻ x, f x ∂μ := by rw [kernel.const_apply]
#align probability_theory.kernel.lintegral_const ProbabilityTheory.kernel.lintegral_const
@[simp]
theorem set_lintegral_const {f : β → ℝ≥0∞} {μ : Measure β} {a : α} {s : Set β} :
∫⁻ x in s, f x ∂kernel.const α μ a = ∫⁻ x in s, f x ∂μ := by rw [kernel.const_apply]
#align probability_theory.kernel.set_lintegral_const ProbabilityTheory.kernel.set_lintegral_const
@[simp]
theorem integral_const {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
{f : β → E} {μ : Measure β} {a : α} : ∫ x, f x ∂kernel.const α μ a = ∫ x, f x ∂μ := by
rw [kernel.const_apply]
#align probability_theory.kernel.integral_const ProbabilityTheory.kernel.integral_const
@[simp]
theorem setIntegral_const {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
{f : β → E} {μ : Measure β} {a : α} {s : Set β} :
∫ x in s, f x ∂kernel.const α μ a = ∫ x in s, f x ∂μ := by rw [kernel.const_apply]
#align probability_theory.kernel.set_integral_const ProbabilityTheory.kernel.setIntegral_const
@[deprecated (since := "2024-04-17")]
alias set_integral_const := setIntegral_const
end Const
/-- In a countable space with measurable singletons, every function `α → MeasureTheory.Measure β`
defines a kernel. -/
def ofFunOfCountable [MeasurableSpace α] {_ : MeasurableSpace β} [Countable α]
[MeasurableSingletonClass α] (f : α → Measure β) : kernel α β where
val := f
property := measurable_of_countable f
#align probability_theory.kernel.of_fun_of_countable ProbabilityTheory.kernel.ofFunOfCountable
section Restrict
variable {s t : Set β}
/-- Kernel given by the restriction of the measures in the image of a kernel to a set. -/
protected noncomputable def restrict (κ : kernel α β) (hs : MeasurableSet s) : kernel α β where
val a := (κ a).restrict s
property := by
refine Measure.measurable_of_measurable_coe _ fun t ht => ?_
simp_rw [Measure.restrict_apply ht]
exact kernel.measurable_coe κ (ht.inter hs)
#align probability_theory.kernel.restrict ProbabilityTheory.kernel.restrict
theorem restrict_apply (κ : kernel α β) (hs : MeasurableSet s) (a : α) :
kernel.restrict κ hs a = (κ a).restrict s :=
rfl
#align probability_theory.kernel.restrict_apply ProbabilityTheory.kernel.restrict_apply
| Mathlib/Probability/Kernel/Basic.lean | 557 | 559 | theorem restrict_apply' (κ : kernel α β) (hs : MeasurableSet s) (a : α) (ht : MeasurableSet t) :
kernel.restrict κ hs a t = (κ a) (t ∩ s) := by |
rw [restrict_apply κ hs a, Measure.restrict_apply ht]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot, Yury Kudryashov, Rémy Degenne
-/
import Mathlib.Order.Interval.Set.Basic
import Mathlib.Order.Hom.Set
#align_import data.set.intervals.order_iso from "leanprover-community/mathlib"@"d012cd09a9b256d870751284dd6a29882b0be105"
/-!
# Lemmas about images of intervals under order isomorphisms.
-/
open Set
namespace OrderIso
section Preorder
variable {α β : Type*} [Preorder α] [Preorder β]
@[simp]
theorem preimage_Iic (e : α ≃o β) (b : β) : e ⁻¹' Iic b = Iic (e.symm b) := by
ext x
simp [← e.le_iff_le]
#align order_iso.preimage_Iic OrderIso.preimage_Iic
@[simp]
theorem preimage_Ici (e : α ≃o β) (b : β) : e ⁻¹' Ici b = Ici (e.symm b) := by
ext x
simp [← e.le_iff_le]
#align order_iso.preimage_Ici OrderIso.preimage_Ici
@[simp]
theorem preimage_Iio (e : α ≃o β) (b : β) : e ⁻¹' Iio b = Iio (e.symm b) := by
ext x
simp [← e.lt_iff_lt]
#align order_iso.preimage_Iio OrderIso.preimage_Iio
@[simp]
theorem preimage_Ioi (e : α ≃o β) (b : β) : e ⁻¹' Ioi b = Ioi (e.symm b) := by
ext x
simp [← e.lt_iff_lt]
#align order_iso.preimage_Ioi OrderIso.preimage_Ioi
@[simp]
theorem preimage_Icc (e : α ≃o β) (a b : β) : e ⁻¹' Icc a b = Icc (e.symm a) (e.symm b) := by
simp [← Ici_inter_Iic]
#align order_iso.preimage_Icc OrderIso.preimage_Icc
@[simp]
theorem preimage_Ico (e : α ≃o β) (a b : β) : e ⁻¹' Ico a b = Ico (e.symm a) (e.symm b) := by
simp [← Ici_inter_Iio]
#align order_iso.preimage_Ico OrderIso.preimage_Ico
@[simp]
theorem preimage_Ioc (e : α ≃o β) (a b : β) : e ⁻¹' Ioc a b = Ioc (e.symm a) (e.symm b) := by
simp [← Ioi_inter_Iic]
#align order_iso.preimage_Ioc OrderIso.preimage_Ioc
@[simp]
theorem preimage_Ioo (e : α ≃o β) (a b : β) : e ⁻¹' Ioo a b = Ioo (e.symm a) (e.symm b) := by
simp [← Ioi_inter_Iio]
#align order_iso.preimage_Ioo OrderIso.preimage_Ioo
@[simp]
theorem image_Iic (e : α ≃o β) (a : α) : e '' Iic a = Iic (e a) := by
rw [e.image_eq_preimage, e.symm.preimage_Iic, e.symm_symm]
#align order_iso.image_Iic OrderIso.image_Iic
@[simp]
theorem image_Ici (e : α ≃o β) (a : α) : e '' Ici a = Ici (e a) :=
e.dual.image_Iic a
#align order_iso.image_Ici OrderIso.image_Ici
@[simp]
| Mathlib/Order/Interval/Set/OrderIso.lean | 78 | 79 | theorem image_Iio (e : α ≃o β) (a : α) : e '' Iio a = Iio (e a) := by |
rw [e.image_eq_preimage, e.symm.preimage_Iio, e.symm_symm]
|
/-
Copyright (c) 2022 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.Tactic.Linarith
#align_import combinatorics.simple_graph.acyclic from "leanprover-community/mathlib"@"b07688016d62f81d14508ff339ea3415558d6353"
/-!
# Acyclic graphs and trees
This module introduces *acyclic graphs* (a.k.a. *forests*) and *trees*.
## Main definitions
* `SimpleGraph.IsAcyclic` is a predicate for a graph having no cyclic walks
* `SimpleGraph.IsTree` is a predicate for a graph being a tree (a connected acyclic graph)
## Main statements
* `SimpleGraph.isAcyclic_iff_path_unique` characterizes acyclicity in terms of uniqueness of
paths between pairs of vertices.
* `SimpleGraph.isAcyclic_iff_forall_edge_isBridge` characterizes acyclicity in terms of every
edge being a bridge edge.
* `SimpleGraph.isTree_iff_existsUnique_path` characterizes trees in terms of existence and
uniqueness of paths between pairs of vertices from a nonempty vertex type.
## References
The structure of the proofs for `SimpleGraph.IsAcyclic` and `SimpleGraph.IsTree`, including
supporting lemmas about `SimpleGraph.IsBridge`, generally follows the high-level description
for these theorems for multigraphs from [Chou1994].
## Tags
acyclic graphs, trees
-/
universe u v
namespace SimpleGraph
open Walk
variable {V : Type u} (G : SimpleGraph V)
/-- A graph is *acyclic* (or a *forest*) if it has no cycles. -/
def IsAcyclic : Prop := ∀ ⦃v : V⦄ (c : G.Walk v v), ¬c.IsCycle
#align simple_graph.is_acyclic SimpleGraph.IsAcyclic
/-- A *tree* is a connected acyclic graph. -/
@[mk_iff]
structure IsTree : Prop where
/-- Graph is connected. -/
protected isConnected : G.Connected
/-- Graph is acyclic. -/
protected IsAcyclic : G.IsAcyclic
#align simple_graph.is_tree SimpleGraph.IsTree
variable {G}
@[simp] lemma isAcyclic_bot : IsAcyclic (⊥ : SimpleGraph V) := fun _a _w hw ↦ hw.ne_bot rfl
theorem isAcyclic_iff_forall_adj_isBridge :
G.IsAcyclic ↔ ∀ ⦃v w : V⦄, G.Adj v w → G.IsBridge s(v, w) := by
simp_rw [isBridge_iff_adj_and_forall_cycle_not_mem]
constructor
· intro ha v w hvw
apply And.intro hvw
intro u p hp
cases ha p hp
· rintro hb v (_ | ⟨ha, p⟩) hp
· exact hp.not_of_nil
· apply (hb ha).2 _ hp
rw [Walk.edges_cons]
apply List.mem_cons_self
#align simple_graph.is_acyclic_iff_forall_adj_is_bridge SimpleGraph.isAcyclic_iff_forall_adj_isBridge
theorem isAcyclic_iff_forall_edge_isBridge :
G.IsAcyclic ↔ ∀ ⦃e⦄, e ∈ (G.edgeSet) → G.IsBridge e := by
simp [isAcyclic_iff_forall_adj_isBridge, Sym2.forall]
#align simple_graph.is_acyclic_iff_forall_edge_is_bridge SimpleGraph.isAcyclic_iff_forall_edge_isBridge
theorem IsAcyclic.path_unique {G : SimpleGraph V} (h : G.IsAcyclic) {v w : V} (p q : G.Path v w) :
p = q := by
obtain ⟨p, hp⟩ := p
obtain ⟨q, hq⟩ := q
rw [Subtype.mk.injEq]
induction p with
| nil =>
cases (Walk.isPath_iff_eq_nil _).mp hq
rfl
| cons ph p ih =>
rw [isAcyclic_iff_forall_adj_isBridge] at h
specialize h ph
rw [isBridge_iff_adj_and_forall_walk_mem_edges] at h
replace h := h.2 (q.append p.reverse)
simp only [Walk.edges_append, Walk.edges_reverse, List.mem_append, List.mem_reverse] at h
cases' h with h h
· cases q with
| nil => simp [Walk.isPath_def] at hp
| cons _ q =>
rw [Walk.cons_isPath_iff] at hp hq
simp only [Walk.edges_cons, List.mem_cons, Sym2.eq_iff, true_and] at h
rcases h with (⟨h, rfl⟩ | ⟨rfl, rfl⟩) | h
· cases ih hp.1 q hq.1
rfl
· simp at hq
· exact absurd (Walk.fst_mem_support_of_mem_edges _ h) hq.2
· rw [Walk.cons_isPath_iff] at hp
exact absurd (Walk.fst_mem_support_of_mem_edges _ h) hp.2
#align simple_graph.is_acyclic.path_unique SimpleGraph.IsAcyclic.path_unique
| Mathlib/Combinatorics/SimpleGraph/Acyclic.lean | 118 | 127 | theorem isAcyclic_of_path_unique (h : ∀ (v w : V) (p q : G.Path v w), p = q) : G.IsAcyclic := by |
intro v c hc
simp only [Walk.isCycle_def, Ne] at hc
cases c with
| nil => cases hc.2.1 rfl
| cons ha c' =>
simp only [Walk.cons_isTrail_iff, Walk.support_cons, List.tail_cons, true_and_iff] at hc
specialize h _ _ ⟨c', by simp only [Walk.isPath_def, hc.2]⟩ (Path.singleton ha.symm)
rw [Path.singleton, Subtype.mk.injEq] at h
simp [h] at hc
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Algebra.Order.Nonneg.Ring
import Mathlib.Algebra.Order.Ring.Rat
import Mathlib.Data.Int.Lemmas
#align_import data.rat.nnrat from "leanprover-community/mathlib"@"b3f4f007a962e3787aa0f3b5c7942a1317f7d88e"
/-!
# Nonnegative rationals
This file defines the nonnegative rationals as a subtype of `Rat` and provides its basic algebraic
order structure.
Note that `NNRat` is not declared as a `Field` here. See `Data.NNRat.Lemmas` for that instance.
We also define an instance `CanLift ℚ ℚ≥0`. This instance can be used by the `lift` tactic to
replace `x : ℚ` and `hx : 0 ≤ x` in the proof context with `x : ℚ≥0` while replacing all occurrences
of `x` with `↑x`. This tactic also works for a function `f : α → ℚ` with a hypothesis
`hf : ∀ x, 0 ≤ f x`.
## Notation
`ℚ≥0` is notation for `NNRat` in locale `NNRat`.
## Huge warning
Whenever you state a lemma about the coercion `ℚ≥0 → ℚ`, check that Lean inserts `NNRat.cast`, not
`Subtype.val`. Else your lemma will never apply.
-/
open Function
deriving instance CanonicallyOrderedCommSemiring for NNRat
deriving instance CanonicallyLinearOrderedAddCommMonoid for NNRat
deriving instance Sub for NNRat
deriving instance Inhabited for NNRat
-- TODO: `deriving instance OrderedSub for NNRat` doesn't work yet, so we add the instance manually
instance NNRat.instOrderedSub : OrderedSub ℚ≥0 := Nonneg.orderedSub
namespace NNRat
variable {α : Type*} {p q : ℚ≥0}
@[simp] lemma val_eq_cast (q : ℚ≥0) : q.1 = q := rfl
#align nnrat.val_eq_coe NNRat.val_eq_cast
instance canLift : CanLift ℚ ℚ≥0 (↑) fun q ↦ 0 ≤ q where
prf q hq := ⟨⟨q, hq⟩, rfl⟩
#align nnrat.can_lift NNRat.canLift
@[ext]
theorem ext : (p : ℚ) = (q : ℚ) → p = q :=
Subtype.ext
#align nnrat.ext NNRat.ext
protected theorem coe_injective : Injective ((↑) : ℚ≥0 → ℚ) :=
Subtype.coe_injective
#align nnrat.coe_injective NNRat.coe_injective
@[simp, norm_cast]
theorem coe_inj : (p : ℚ) = q ↔ p = q :=
Subtype.coe_inj
#align nnrat.coe_inj NNRat.coe_inj
theorem ext_iff : p = q ↔ (p : ℚ) = q :=
Subtype.ext_iff
#align nnrat.ext_iff NNRat.ext_iff
theorem ne_iff {x y : ℚ≥0} : (x : ℚ) ≠ (y : ℚ) ↔ x ≠ y :=
NNRat.coe_inj.not
#align nnrat.ne_iff NNRat.ne_iff
-- TODO: We have to write `NNRat.cast` explicitly, else the statement picks up `Subtype.val` instead
@[simp, norm_cast] lemma coe_mk (q : ℚ) (hq) : NNRat.cast ⟨q, hq⟩ = q := rfl
#align nnrat.coe_mk NNRat.coe_mk
lemma «forall» {p : ℚ≥0 → Prop} : (∀ q, p q) ↔ ∀ q hq, p ⟨q, hq⟩ := Subtype.forall
lemma «exists» {p : ℚ≥0 → Prop} : (∃ q, p q) ↔ ∃ q hq, p ⟨q, hq⟩ := Subtype.exists
/-- Reinterpret a rational number `q` as a non-negative rational number. Returns `0` if `q ≤ 0`. -/
def _root_.Rat.toNNRat (q : ℚ) : ℚ≥0 :=
⟨max q 0, le_max_right _ _⟩
#align rat.to_nnrat Rat.toNNRat
theorem _root_.Rat.coe_toNNRat (q : ℚ) (hq : 0 ≤ q) : (q.toNNRat : ℚ) = q :=
max_eq_left hq
#align rat.coe_to_nnrat Rat.coe_toNNRat
theorem _root_.Rat.le_coe_toNNRat (q : ℚ) : q ≤ q.toNNRat :=
le_max_left _ _
#align rat.le_coe_to_nnrat Rat.le_coe_toNNRat
open Rat (toNNRat)
@[simp]
theorem coe_nonneg (q : ℚ≥0) : (0 : ℚ) ≤ q :=
q.2
#align nnrat.coe_nonneg NNRat.coe_nonneg
-- eligible for dsimp
@[simp, nolint simpNF, norm_cast] lemma coe_zero : ((0 : ℚ≥0) : ℚ) = 0 := rfl
#align nnrat.coe_zero NNRat.coe_zero
-- eligible for dsimp
@[simp, nolint simpNF, norm_cast] lemma coe_one : ((1 : ℚ≥0) : ℚ) = 1 := rfl
#align nnrat.coe_one NNRat.coe_one
@[simp, norm_cast]
theorem coe_add (p q : ℚ≥0) : ((p + q : ℚ≥0) : ℚ) = p + q :=
rfl
#align nnrat.coe_add NNRat.coe_add
@[simp, norm_cast]
theorem coe_mul (p q : ℚ≥0) : ((p * q : ℚ≥0) : ℚ) = p * q :=
rfl
#align nnrat.coe_mul NNRat.coe_mul
-- eligible for dsimp
@[simp, nolint simpNF, norm_cast] lemma coe_pow (q : ℚ≥0) (n : ℕ) : (↑(q ^ n) : ℚ) = (q : ℚ) ^ n :=
rfl
#align nnrat.coe_pow NNRat.coe_pow
@[simp] lemma num_pow (q : ℚ≥0) (n : ℕ) : (q ^ n).num = q.num ^ n := by simp [num, Int.natAbs_pow]
@[simp] lemma den_pow (q : ℚ≥0) (n : ℕ) : (q ^ n).den = q.den ^ n := rfl
-- Porting note: `bit0` `bit1` are deprecated, so remove these theorems.
#noalign nnrat.coe_bit0
#noalign nnrat.coe_bit1
@[simp, norm_cast]
theorem coe_sub (h : q ≤ p) : ((p - q : ℚ≥0) : ℚ) = p - q :=
max_eq_left <| le_sub_comm.2 <| by rwa [sub_zero]
#align nnrat.coe_sub NNRat.coe_sub
@[simp]
theorem coe_eq_zero : (q : ℚ) = 0 ↔ q = 0 := by norm_cast
#align nnrat.coe_eq_zero NNRat.coe_eq_zero
theorem coe_ne_zero : (q : ℚ) ≠ 0 ↔ q ≠ 0 :=
coe_eq_zero.not
#align nnrat.coe_ne_zero NNRat.coe_ne_zero
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_le_coe : (p : ℚ) ≤ q ↔ p ≤ q :=
Iff.rfl
#align nnrat.coe_le_coe NNRat.coe_le_coe
@[norm_cast] -- Porting note (#10618): simp can prove this
theorem coe_lt_coe : (p : ℚ) < q ↔ p < q :=
Iff.rfl
#align nnrat.coe_lt_coe NNRat.coe_lt_coe
-- `cast_pos`, defined in a later file, makes this lemma redundant
@[simp, norm_cast, nolint simpNF]
theorem coe_pos : (0 : ℚ) < q ↔ 0 < q :=
Iff.rfl
#align nnrat.coe_pos NNRat.coe_pos
theorem coe_mono : Monotone ((↑) : ℚ≥0 → ℚ) :=
fun _ _ ↦ coe_le_coe.2
#align nnrat.coe_mono NNRat.coe_mono
theorem toNNRat_mono : Monotone toNNRat :=
fun _ _ h ↦ max_le_max h le_rfl
#align nnrat.to_nnrat_mono NNRat.toNNRat_mono
@[simp]
theorem toNNRat_coe (q : ℚ≥0) : toNNRat q = q :=
ext <| max_eq_left q.2
#align nnrat.to_nnrat_coe NNRat.toNNRat_coe
@[simp]
theorem toNNRat_coe_nat (n : ℕ) : toNNRat n = n :=
ext <| by simp only [Nat.cast_nonneg, Rat.coe_toNNRat]; rfl
#align nnrat.to_nnrat_coe_nat NNRat.toNNRat_coe_nat
/-- `toNNRat` and `(↑) : ℚ≥0 → ℚ` form a Galois insertion. -/
protected def gi : GaloisInsertion toNNRat (↑) :=
GaloisInsertion.monotoneIntro coe_mono toNNRat_mono Rat.le_coe_toNNRat toNNRat_coe
#align nnrat.gi NNRat.gi
/-- Coercion `ℚ≥0 → ℚ` as a `RingHom`. -/
def coeHom : ℚ≥0 →+* ℚ where
toFun := (↑)
map_one' := coe_one
map_mul' := coe_mul
map_zero' := coe_zero
map_add' := coe_add
#align nnrat.coe_hom NNRat.coeHom
-- eligible for dsimp
@[simp, nolint simpNF, norm_cast] lemma coe_natCast (n : ℕ) : (↑(↑n : ℚ≥0) : ℚ) = n := rfl
#align nnrat.coe_nat_cast NNRat.coe_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem mk_natCast (n : ℕ) : @Eq ℚ≥0 (⟨(n : ℚ), n.cast_nonneg⟩ : ℚ≥0) n :=
rfl
#align nnrat.mk_coe_nat NNRat.mk_natCast
@[deprecated (since := "2024-04-05")] alias mk_coe_nat := mk_natCast
@[simp]
theorem coe_coeHom : ⇑coeHom = ((↑) : ℚ≥0 → ℚ) :=
rfl
#align nnrat.coe_coe_hom NNRat.coe_coeHom
@[norm_cast]
theorem nsmul_coe (q : ℚ≥0) (n : ℕ) : ↑(n • q) = n • (q : ℚ) :=
coeHom.toAddMonoidHom.map_nsmul _ _
#align nnrat.nsmul_coe NNRat.nsmul_coe
theorem bddAbove_coe {s : Set ℚ≥0} : BddAbove ((↑) '' s : Set ℚ) ↔ BddAbove s :=
⟨fun ⟨b, hb⟩ ↦
⟨toNNRat b, fun ⟨y, _⟩ hys ↦
show y ≤ max b 0 from (hb <| Set.mem_image_of_mem _ hys).trans <| le_max_left _ _⟩,
fun ⟨b, hb⟩ ↦ ⟨b, fun _ ⟨_, hx, Eq⟩ ↦ Eq ▸ hb hx⟩⟩
#align nnrat.bdd_above_coe NNRat.bddAbove_coe
theorem bddBelow_coe (s : Set ℚ≥0) : BddBelow (((↑) : ℚ≥0 → ℚ) '' s) :=
⟨0, fun _ ⟨q, _, h⟩ ↦ h ▸ q.2⟩
#align nnrat.bdd_below_coe NNRat.bddBelow_coe
-- `cast_max`, defined in a later file, makes this lemma redundant
@[simp, norm_cast, nolint simpNF]
theorem coe_max (x y : ℚ≥0) : ((max x y : ℚ≥0) : ℚ) = max (x : ℚ) (y : ℚ) :=
coe_mono.map_max
#align nnrat.coe_max NNRat.coe_max
-- `cast_max`, defined in a later file, makes this lemma redundant
@[simp, norm_cast, nolint simpNF]
theorem coe_min (x y : ℚ≥0) : ((min x y : ℚ≥0) : ℚ) = min (x : ℚ) (y : ℚ) :=
coe_mono.map_min
#align nnrat.coe_min NNRat.coe_min
theorem sub_def (p q : ℚ≥0) : p - q = toNNRat (p - q) :=
rfl
#align nnrat.sub_def NNRat.sub_def
@[simp]
theorem abs_coe (q : ℚ≥0) : |(q : ℚ)| = q :=
abs_of_nonneg q.2
#align nnrat.abs_coe NNRat.abs_coe
end NNRat
open NNRat
namespace Rat
variable {p q : ℚ}
@[simp]
theorem toNNRat_zero : toNNRat 0 = 0 := rfl
#align rat.to_nnrat_zero Rat.toNNRat_zero
@[simp]
theorem toNNRat_one : toNNRat 1 = 1 := rfl
#align rat.to_nnrat_one Rat.toNNRat_one
@[simp]
theorem toNNRat_pos : 0 < toNNRat q ↔ 0 < q := by simp [toNNRat, ← coe_lt_coe]
#align rat.to_nnrat_pos Rat.toNNRat_pos
@[simp]
theorem toNNRat_eq_zero : toNNRat q = 0 ↔ q ≤ 0 := by
simpa [-toNNRat_pos] using (@toNNRat_pos q).not
#align rat.to_nnrat_eq_zero Rat.toNNRat_eq_zero
alias ⟨_, toNNRat_of_nonpos⟩ := toNNRat_eq_zero
#align rat.to_nnrat_of_nonpos Rat.toNNRat_of_nonpos
@[simp]
theorem toNNRat_le_toNNRat_iff (hp : 0 ≤ p) : toNNRat q ≤ toNNRat p ↔ q ≤ p := by
simp [← coe_le_coe, toNNRat, hp]
#align rat.to_nnrat_le_to_nnrat_iff Rat.toNNRat_le_toNNRat_iff
@[simp]
theorem toNNRat_lt_toNNRat_iff' : toNNRat q < toNNRat p ↔ q < p ∧ 0 < p := by
simp [← coe_lt_coe, toNNRat, lt_irrefl]
#align rat.to_nnrat_lt_to_nnrat_iff' Rat.toNNRat_lt_toNNRat_iff'
theorem toNNRat_lt_toNNRat_iff (h : 0 < p) : toNNRat q < toNNRat p ↔ q < p :=
toNNRat_lt_toNNRat_iff'.trans (and_iff_left h)
#align rat.to_nnrat_lt_to_nnrat_iff Rat.toNNRat_lt_toNNRat_iff
theorem toNNRat_lt_toNNRat_iff_of_nonneg (hq : 0 ≤ q) : toNNRat q < toNNRat p ↔ q < p :=
toNNRat_lt_toNNRat_iff'.trans ⟨And.left, fun h ↦ ⟨h, hq.trans_lt h⟩⟩
#align rat.to_nnrat_lt_to_nnrat_iff_of_nonneg Rat.toNNRat_lt_toNNRat_iff_of_nonneg
@[simp]
theorem toNNRat_add (hq : 0 ≤ q) (hp : 0 ≤ p) : toNNRat (q + p) = toNNRat q + toNNRat p :=
NNRat.ext <| by simp [toNNRat, hq, hp, add_nonneg]
#align rat.to_nnrat_add Rat.toNNRat_add
theorem toNNRat_add_le : toNNRat (q + p) ≤ toNNRat q + toNNRat p :=
coe_le_coe.1 <| max_le (add_le_add (le_max_left _ _) (le_max_left _ _)) <| coe_nonneg _
#align rat.to_nnrat_add_le Rat.toNNRat_add_le
theorem toNNRat_le_iff_le_coe {p : ℚ≥0} : toNNRat q ≤ p ↔ q ≤ ↑p :=
NNRat.gi.gc q p
#align rat.to_nnrat_le_iff_le_coe Rat.toNNRat_le_iff_le_coe
theorem le_toNNRat_iff_coe_le {q : ℚ≥0} (hp : 0 ≤ p) : q ≤ toNNRat p ↔ ↑q ≤ p := by
rw [← coe_le_coe, Rat.coe_toNNRat p hp]
#align rat.le_to_nnrat_iff_coe_le Rat.le_toNNRat_iff_coe_le
theorem le_toNNRat_iff_coe_le' {q : ℚ≥0} (hq : 0 < q) : q ≤ toNNRat p ↔ ↑q ≤ p :=
(le_or_lt 0 p).elim le_toNNRat_iff_coe_le fun hp ↦ by
simp only [(hp.trans_le q.coe_nonneg).not_le, toNNRat_eq_zero.2 hp.le, hq.not_le]
#align rat.le_to_nnrat_iff_coe_le' Rat.le_toNNRat_iff_coe_le'
theorem toNNRat_lt_iff_lt_coe {p : ℚ≥0} (hq : 0 ≤ q) : toNNRat q < p ↔ q < ↑p := by
rw [← coe_lt_coe, Rat.coe_toNNRat q hq]
#align rat.to_nnrat_lt_iff_lt_coe Rat.toNNRat_lt_iff_lt_coe
theorem lt_toNNRat_iff_coe_lt {q : ℚ≥0} : q < toNNRat p ↔ ↑q < p :=
NNRat.gi.gc.lt_iff_lt
#align rat.lt_to_nnrat_iff_coe_lt Rat.lt_toNNRat_iff_coe_lt
-- Porting note: `bit0` `bit1` are deprecated, so remove these theorems.
#noalign rat.to_nnrat_bit0
#noalign rat.to_nnrat_bit1
theorem toNNRat_mul (hp : 0 ≤ p) : toNNRat (p * q) = toNNRat p * toNNRat q := by
rcases le_total 0 q with hq | hq
· ext; simp [toNNRat, hp, hq, max_eq_left, mul_nonneg]
· have hpq := mul_nonpos_of_nonneg_of_nonpos hp hq
rw [toNNRat_eq_zero.2 hq, toNNRat_eq_zero.2 hpq, mul_zero]
#align rat.to_nnrat_mul Rat.toNNRat_mul
end Rat
/-- The absolute value on `ℚ` as a map to `ℚ≥0`. -/
--@[pp_nodot] -- Porting note: Commented out.
def Rat.nnabs (x : ℚ) : ℚ≥0 :=
⟨abs x, abs_nonneg x⟩
#align rat.nnabs Rat.nnabs
@[norm_cast, simp]
theorem Rat.coe_nnabs (x : ℚ) : (Rat.nnabs x : ℚ) = abs x := rfl
#align rat.coe_nnabs Rat.coe_nnabs
/-! ### Numerator and denominator -/
namespace NNRat
variable {p q : ℚ≥0}
@[norm_cast] lemma num_coe (q : ℚ≥0) : (q : ℚ).num = q.num := by
simp [num, abs_of_nonneg, Rat.num_nonneg, q.2]
theorem natAbs_num_coe : (q : ℚ).num.natAbs = q.num := rfl
#align nnrat.nat_abs_num_coe NNRat.natAbs_num_coe
@[norm_cast] lemma den_coe : (q : ℚ).den = q.den := rfl
#align nnrat.denom_coe NNRat.den_coe
@[simp] lemma num_ne_zero : q.num ≠ 0 ↔ q ≠ 0 := by simp [num]
@[simp] lemma num_pos : 0 < q.num ↔ 0 < q := by simp [pos_iff_ne_zero]
@[simp] lemma den_pos (q : ℚ≥0) : 0 < q.den := Rat.den_pos _
@[simp] lemma den_ne_zero (q : ℚ≥0) : q.den ≠ 0 := Rat.den_ne_zero _
lemma coprime_num_den (q : ℚ≥0) : q.num.Coprime q.den := by simpa [num, den] using Rat.reduced _
-- TODO: Rename `Rat.coe_nat_num`, `Rat.intCast_den`, `Rat.ofNat_num`, `Rat.ofNat_den`
@[simp, norm_cast] lemma num_natCast (n : ℕ) : num n = n := rfl
@[simp, norm_cast] lemma den_natCast (n : ℕ) : den n = 1 := rfl
-- See note [no_index around OfNat.ofNat]
@[simp] lemma num_ofNat (n : ℕ) [n.AtLeastTwo] : num (no_index (OfNat.ofNat n)) = OfNat.ofNat n :=
rfl
@[simp] lemma den_ofNat (n : ℕ) [n.AtLeastTwo] : den (no_index (OfNat.ofNat n)) = 1 := rfl
| Mathlib/Data/NNRat/Defs.lean | 382 | 387 | theorem ext_num_den (hn : p.num = q.num) (hd : p.den = q.den) : p = q := by |
refine ext <| Rat.ext ?_ ?_
· apply (Int.natAbs_inj_of_nonneg_of_nonneg _ _).1 hn
· exact Rat.num_nonneg.2 p.2
· exact Rat.num_nonneg.2 q.2
· exact hd
|
/-
Copyright (c) 2021 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.RingTheory.IntegrallyClosed
import Mathlib.RingTheory.Trace
import Mathlib.RingTheory.Norm
#align_import ring_theory.discriminant from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1"
/-!
# Discriminant of a family of vectors
Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define the
*discriminant* of `b` as the determinant of the matrix whose `(i j)`-th element is the trace of
`b i * b j`.
## Main definition
* `Algebra.discr A b` : the discriminant of `b : ι → B`.
## Main results
* `Algebra.discr_zero_of_not_linearIndependent` : if `b` is not linear independent, then
`Algebra.discr A b = 0`.
* `Algebra.discr_of_matrix_vecMul` and `Algebra.discr_of_matrix_mulVec` : formulas relating
`Algebra.discr A ι b` with `Algebra.discr A (b ᵥ* P.map (algebraMap A B))` and
`Algebra.discr A (P.map (algebraMap A B) *ᵥ b)`.
* `Algebra.discr_not_zero_of_basis` : over a field, if `b` is a basis, then
`Algebra.discr K b ≠ 0`.
* `Algebra.discr_eq_det_embeddingsMatrixReindex_pow_two` : if `L/K` is a field extension and
`b : ι → L`, then `discr K b` is the square of the determinant of the matrix whose `(i, j)`
coefficient is `σⱼ (b i)`, where `σⱼ : L →ₐ[K] E` is the embedding in an algebraically closed
field `E` corresponding to `j : ι` via a bijection `e : ι ≃ (L →ₐ[K] E)`.
* `Algebra.discr_powerBasis_eq_prod` : the discriminant of a power basis.
* `Algebra.discr_isIntegral` : if `K` and `L` are fields and `IsScalarTower R K L`, if
`b : ι → L` satisfies `∀ i, IsIntegral R (b i)`, then `IsIntegral R (discr K b)`.
* `Algebra.discr_mul_isIntegral_mem_adjoin` : let `K` be the fraction field of an integrally
closed domain `R` and let `L` be a finite separable extension of `K`. Let `B : PowerBasis K L`
be such that `IsIntegral R B.gen`. Then for all, `z : L` we have
`(discr K B.basis) • z ∈ adjoin R ({B.gen} : Set L)`.
## Implementation details
Our definition works for any `A`-algebra `B`, but note that if `B` is not free as an `A`-module,
then `trace A B = 0` by definition, so `discr A b = 0` for any `b`.
-/
universe u v w z
open scoped Matrix
open Matrix FiniteDimensional Fintype Polynomial Finset IntermediateField
namespace Algebra
variable (A : Type u) {B : Type v} (C : Type z) {ι : Type w} [DecidableEq ι]
variable [CommRing A] [CommRing B] [Algebra A B] [CommRing C] [Algebra A C]
section Discr
/-- Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define
`discr A ι b` as the determinant of `traceMatrix A ι b`. -/
-- Porting note: using `[DecidableEq ι]` instead of `by classical...` did not work in
-- mathlib3.
noncomputable def discr (A : Type u) {B : Type v} [CommRing A] [CommRing B] [Algebra A B]
[Fintype ι] (b : ι → B) := (traceMatrix A b).det
#align algebra.discr Algebra.discr
theorem discr_def [Fintype ι] (b : ι → B) : discr A b = (traceMatrix A b).det := rfl
variable {A C} in
/-- Mapping a family of vectors along an `AlgEquiv` preserves the discriminant. -/
theorem discr_eq_discr_of_algEquiv [Fintype ι] (b : ι → B) (f : B ≃ₐ[A] C) :
Algebra.discr A b = Algebra.discr A (f ∘ b) := by
rw [discr_def]; congr; ext
simp_rw [traceMatrix_apply, traceForm_apply, Function.comp, ← map_mul f, trace_eq_of_algEquiv]
#align algebra.discr_def Algebra.discr_def
variable {ι' : Type*} [Fintype ι'] [Fintype ι] [DecidableEq ι']
section Basic
@[simp]
theorem discr_reindex (b : Basis ι A B) (f : ι ≃ ι') : discr A (b ∘ ⇑f.symm) = discr A b := by
classical rw [← Basis.coe_reindex, discr_def, traceMatrix_reindex, det_reindex_self, ← discr_def]
#align algebra.discr_reindex Algebra.discr_reindex
/-- If `b` is not linear independent, then `Algebra.discr A b = 0`. -/
| Mathlib/RingTheory/Discriminant.lean | 93 | 106 | theorem discr_zero_of_not_linearIndependent [IsDomain A] {b : ι → B}
(hli : ¬LinearIndependent A b) : discr A b = 0 := by |
classical
obtain ⟨g, hg, i, hi⟩ := Fintype.not_linearIndependent_iff.1 hli
have : (traceMatrix A b) *ᵥ g = 0 := by
ext i
have : ∀ j, (trace A B) (b i * b j) * g j = (trace A B) (g j • b j * b i) := by
intro j;
simp [mul_comm]
simp only [mulVec, dotProduct, traceMatrix_apply, Pi.zero_apply, traceForm_apply, fun j =>
this j, ← map_sum, ← sum_mul, hg, zero_mul, LinearMap.map_zero]
by_contra h
rw [discr_def] at h
simp [Matrix.eq_zero_of_mulVec_eq_zero h this] at hi
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Group.Nat
import Mathlib.Algebra.Order.Sub.Canonical
import Mathlib.Data.List.Perm
import Mathlib.Data.Set.List
import Mathlib.Init.Quot
import Mathlib.Order.Hom.Basic
#align_import data.multiset.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Multisets
These are implemented as the quotient of a list by permutations.
## Notation
We define the global infix notation `::ₘ` for `Multiset.cons`.
-/
universe v
open List Subtype Nat Function
variable {α : Type*} {β : Type v} {γ : Type*}
/-- `Multiset α` is the quotient of `List α` by list permutation. The result
is a type of finite sets with duplicates allowed. -/
def Multiset.{u} (α : Type u) : Type u :=
Quotient (List.isSetoid α)
#align multiset Multiset
namespace Multiset
-- Porting note: new
/-- The quotient map from `List α` to `Multiset α`. -/
@[coe]
def ofList : List α → Multiset α :=
Quot.mk _
instance : Coe (List α) (Multiset α) :=
⟨ofList⟩
@[simp]
theorem quot_mk_to_coe (l : List α) : @Eq (Multiset α) ⟦l⟧ l :=
rfl
#align multiset.quot_mk_to_coe Multiset.quot_mk_to_coe
@[simp]
theorem quot_mk_to_coe' (l : List α) : @Eq (Multiset α) (Quot.mk (· ≈ ·) l) l :=
rfl
#align multiset.quot_mk_to_coe' Multiset.quot_mk_to_coe'
@[simp]
theorem quot_mk_to_coe'' (l : List α) : @Eq (Multiset α) (Quot.mk Setoid.r l) l :=
rfl
#align multiset.quot_mk_to_coe'' Multiset.quot_mk_to_coe''
@[simp]
theorem coe_eq_coe {l₁ l₂ : List α} : (l₁ : Multiset α) = l₂ ↔ l₁ ~ l₂ :=
Quotient.eq
#align multiset.coe_eq_coe Multiset.coe_eq_coe
-- Porting note: new instance;
-- Porting note (#11215): TODO: move to better place
instance [DecidableEq α] (l₁ l₂ : List α) : Decidable (l₁ ≈ l₂) :=
inferInstanceAs (Decidable (l₁ ~ l₂))
-- Porting note: `Quotient.recOnSubsingleton₂ s₁ s₂` was in parens which broke elaboration
instance decidableEq [DecidableEq α] : DecidableEq (Multiset α)
| s₁, s₂ => Quotient.recOnSubsingleton₂ s₁ s₂ fun _ _ => decidable_of_iff' _ Quotient.eq
#align multiset.has_decidable_eq Multiset.decidableEq
/-- defines a size for a multiset by referring to the size of the underlying list -/
protected
def sizeOf [SizeOf α] (s : Multiset α) : ℕ :=
(Quot.liftOn s SizeOf.sizeOf) fun _ _ => Perm.sizeOf_eq_sizeOf
#align multiset.sizeof Multiset.sizeOf
instance [SizeOf α] : SizeOf (Multiset α) :=
⟨Multiset.sizeOf⟩
/-! ### Empty multiset -/
/-- `0 : Multiset α` is the empty set -/
protected def zero : Multiset α :=
@nil α
#align multiset.zero Multiset.zero
instance : Zero (Multiset α) :=
⟨Multiset.zero⟩
instance : EmptyCollection (Multiset α) :=
⟨0⟩
instance inhabitedMultiset : Inhabited (Multiset α) :=
⟨0⟩
#align multiset.inhabited_multiset Multiset.inhabitedMultiset
instance [IsEmpty α] : Unique (Multiset α) where
default := 0
uniq := by rintro ⟨_ | ⟨a, l⟩⟩; exacts [rfl, isEmptyElim a]
@[simp]
theorem coe_nil : (@nil α : Multiset α) = 0 :=
rfl
#align multiset.coe_nil Multiset.coe_nil
@[simp]
theorem empty_eq_zero : (∅ : Multiset α) = 0 :=
rfl
#align multiset.empty_eq_zero Multiset.empty_eq_zero
@[simp]
theorem coe_eq_zero (l : List α) : (l : Multiset α) = 0 ↔ l = [] :=
Iff.trans coe_eq_coe perm_nil
#align multiset.coe_eq_zero Multiset.coe_eq_zero
theorem coe_eq_zero_iff_isEmpty (l : List α) : (l : Multiset α) = 0 ↔ l.isEmpty :=
Iff.trans (coe_eq_zero l) isEmpty_iff_eq_nil.symm
#align multiset.coe_eq_zero_iff_empty Multiset.coe_eq_zero_iff_isEmpty
/-! ### `Multiset.cons` -/
/-- `cons a s` is the multiset which contains `s` plus one more instance of `a`. -/
def cons (a : α) (s : Multiset α) : Multiset α :=
Quot.liftOn s (fun l => (a :: l : Multiset α)) fun _ _ p => Quot.sound (p.cons a)
#align multiset.cons Multiset.cons
@[inherit_doc Multiset.cons]
infixr:67 " ::ₘ " => Multiset.cons
instance : Insert α (Multiset α) :=
⟨cons⟩
@[simp]
theorem insert_eq_cons (a : α) (s : Multiset α) : insert a s = a ::ₘ s :=
rfl
#align multiset.insert_eq_cons Multiset.insert_eq_cons
@[simp]
theorem cons_coe (a : α) (l : List α) : (a ::ₘ l : Multiset α) = (a :: l : List α) :=
rfl
#align multiset.cons_coe Multiset.cons_coe
@[simp]
theorem cons_inj_left {a b : α} (s : Multiset α) : a ::ₘ s = b ::ₘ s ↔ a = b :=
⟨Quot.inductionOn s fun l e =>
have : [a] ++ l ~ [b] ++ l := Quotient.exact e
singleton_perm_singleton.1 <| (perm_append_right_iff _).1 this,
congr_arg (· ::ₘ _)⟩
#align multiset.cons_inj_left Multiset.cons_inj_left
@[simp]
theorem cons_inj_right (a : α) : ∀ {s t : Multiset α}, a ::ₘ s = a ::ₘ t ↔ s = t := by
rintro ⟨l₁⟩ ⟨l₂⟩; simp
#align multiset.cons_inj_right Multiset.cons_inj_right
@[elab_as_elim]
protected theorem induction {p : Multiset α → Prop} (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : ∀ s, p s := by
rintro ⟨l⟩; induction' l with _ _ ih <;> [exact empty; exact cons _ _ ih]
#align multiset.induction Multiset.induction
@[elab_as_elim]
protected theorem induction_on {p : Multiset α → Prop} (s : Multiset α) (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : p s :=
Multiset.induction empty cons s
#align multiset.induction_on Multiset.induction_on
theorem cons_swap (a b : α) (s : Multiset α) : a ::ₘ b ::ₘ s = b ::ₘ a ::ₘ s :=
Quot.inductionOn s fun _ => Quotient.sound <| Perm.swap _ _ _
#align multiset.cons_swap Multiset.cons_swap
section Rec
variable {C : Multiset α → Sort*}
/-- Dependent recursor on multisets.
TODO: should be @[recursor 6], but then the definition of `Multiset.pi` fails with a stack
overflow in `whnf`.
-/
protected
def rec (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b)))
(m : Multiset α) : C m :=
Quotient.hrecOn m (@List.rec α (fun l => C ⟦l⟧) C_0 fun a l b => C_cons a ⟦l⟧ b) fun l l' h =>
h.rec_heq
(fun hl _ ↦ by congr 1; exact Quot.sound hl)
(C_cons_heq _ _ ⟦_⟧ _)
#align multiset.rec Multiset.rec
/-- Companion to `Multiset.rec` with more convenient argument order. -/
@[elab_as_elim]
protected
def recOn (m : Multiset α) (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))) :
C m :=
Multiset.rec C_0 C_cons C_cons_heq m
#align multiset.rec_on Multiset.recOn
variable {C_0 : C 0} {C_cons : ∀ a m, C m → C (a ::ₘ m)}
{C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))}
@[simp]
theorem recOn_0 : @Multiset.recOn α C (0 : Multiset α) C_0 C_cons C_cons_heq = C_0 :=
rfl
#align multiset.rec_on_0 Multiset.recOn_0
@[simp]
theorem recOn_cons (a : α) (m : Multiset α) :
(a ::ₘ m).recOn C_0 C_cons C_cons_heq = C_cons a m (m.recOn C_0 C_cons C_cons_heq) :=
Quotient.inductionOn m fun _ => rfl
#align multiset.rec_on_cons Multiset.recOn_cons
end Rec
section Mem
/-- `a ∈ s` means that `a` has nonzero multiplicity in `s`. -/
def Mem (a : α) (s : Multiset α) : Prop :=
Quot.liftOn s (fun l => a ∈ l) fun l₁ l₂ (e : l₁ ~ l₂) => propext <| e.mem_iff
#align multiset.mem Multiset.Mem
instance : Membership α (Multiset α) :=
⟨Mem⟩
@[simp]
theorem mem_coe {a : α} {l : List α} : a ∈ (l : Multiset α) ↔ a ∈ l :=
Iff.rfl
#align multiset.mem_coe Multiset.mem_coe
instance decidableMem [DecidableEq α] (a : α) (s : Multiset α) : Decidable (a ∈ s) :=
Quot.recOnSubsingleton' s fun l ↦ inferInstanceAs (Decidable (a ∈ l))
#align multiset.decidable_mem Multiset.decidableMem
@[simp]
theorem mem_cons {a b : α} {s : Multiset α} : a ∈ b ::ₘ s ↔ a = b ∨ a ∈ s :=
Quot.inductionOn s fun _ => List.mem_cons
#align multiset.mem_cons Multiset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Multiset α} (h : a ∈ s) : a ∈ b ::ₘ s :=
mem_cons.2 <| Or.inr h
#align multiset.mem_cons_of_mem Multiset.mem_cons_of_mem
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mem_cons_self (a : α) (s : Multiset α) : a ∈ a ::ₘ s :=
mem_cons.2 (Or.inl rfl)
#align multiset.mem_cons_self Multiset.mem_cons_self
theorem forall_mem_cons {p : α → Prop} {a : α} {s : Multiset α} :
(∀ x ∈ a ::ₘ s, p x) ↔ p a ∧ ∀ x ∈ s, p x :=
Quotient.inductionOn' s fun _ => List.forall_mem_cons
#align multiset.forall_mem_cons Multiset.forall_mem_cons
theorem exists_cons_of_mem {s : Multiset α} {a : α} : a ∈ s → ∃ t, s = a ::ₘ t :=
Quot.inductionOn s fun l (h : a ∈ l) =>
let ⟨l₁, l₂, e⟩ := append_of_mem h
e.symm ▸ ⟨(l₁ ++ l₂ : List α), Quot.sound perm_middle⟩
#align multiset.exists_cons_of_mem Multiset.exists_cons_of_mem
@[simp]
theorem not_mem_zero (a : α) : a ∉ (0 : Multiset α) :=
List.not_mem_nil _
#align multiset.not_mem_zero Multiset.not_mem_zero
theorem eq_zero_of_forall_not_mem {s : Multiset α} : (∀ x, x ∉ s) → s = 0 :=
Quot.inductionOn s fun l H => by rw [eq_nil_iff_forall_not_mem.mpr H]; rfl
#align multiset.eq_zero_of_forall_not_mem Multiset.eq_zero_of_forall_not_mem
theorem eq_zero_iff_forall_not_mem {s : Multiset α} : s = 0 ↔ ∀ a, a ∉ s :=
⟨fun h => h.symm ▸ fun _ => not_mem_zero _, eq_zero_of_forall_not_mem⟩
#align multiset.eq_zero_iff_forall_not_mem Multiset.eq_zero_iff_forall_not_mem
theorem exists_mem_of_ne_zero {s : Multiset α} : s ≠ 0 → ∃ a : α, a ∈ s :=
Quot.inductionOn s fun l hl =>
match l, hl with
| [], h => False.elim <| h rfl
| a :: l, _ => ⟨a, by simp⟩
#align multiset.exists_mem_of_ne_zero Multiset.exists_mem_of_ne_zero
theorem empty_or_exists_mem (s : Multiset α) : s = 0 ∨ ∃ a, a ∈ s :=
or_iff_not_imp_left.mpr Multiset.exists_mem_of_ne_zero
#align multiset.empty_or_exists_mem Multiset.empty_or_exists_mem
@[simp]
theorem zero_ne_cons {a : α} {m : Multiset α} : 0 ≠ a ::ₘ m := fun h =>
have : a ∈ (0 : Multiset α) := h.symm ▸ mem_cons_self _ _
not_mem_zero _ this
#align multiset.zero_ne_cons Multiset.zero_ne_cons
@[simp]
theorem cons_ne_zero {a : α} {m : Multiset α} : a ::ₘ m ≠ 0 :=
zero_ne_cons.symm
#align multiset.cons_ne_zero Multiset.cons_ne_zero
theorem cons_eq_cons {a b : α} {as bs : Multiset α} :
a ::ₘ as = b ::ₘ bs ↔ a = b ∧ as = bs ∨ a ≠ b ∧ ∃ cs, as = b ::ₘ cs ∧ bs = a ::ₘ cs := by
haveI : DecidableEq α := Classical.decEq α
constructor
· intro eq
by_cases h : a = b
· subst h
simp_all
· have : a ∈ b ::ₘ bs := eq ▸ mem_cons_self _ _
have : a ∈ bs := by simpa [h]
rcases exists_cons_of_mem this with ⟨cs, hcs⟩
simp only [h, hcs, false_and, ne_eq, not_false_eq_true, cons_inj_right, exists_eq_right',
true_and, false_or]
have : a ::ₘ as = b ::ₘ a ::ₘ cs := by simp [eq, hcs]
have : a ::ₘ as = a ::ₘ b ::ₘ cs := by rwa [cons_swap]
simpa using this
· intro h
rcases h with (⟨eq₁, eq₂⟩ | ⟨_, cs, eq₁, eq₂⟩)
· simp [*]
· simp [*, cons_swap a b]
#align multiset.cons_eq_cons Multiset.cons_eq_cons
end Mem
/-! ### Singleton -/
instance : Singleton α (Multiset α) :=
⟨fun a => a ::ₘ 0⟩
instance : LawfulSingleton α (Multiset α) :=
⟨fun _ => rfl⟩
@[simp]
theorem cons_zero (a : α) : a ::ₘ 0 = {a} :=
rfl
#align multiset.cons_zero Multiset.cons_zero
@[simp, norm_cast]
theorem coe_singleton (a : α) : ([a] : Multiset α) = {a} :=
rfl
#align multiset.coe_singleton Multiset.coe_singleton
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Multiset α) ↔ b = a := by
simp only [← cons_zero, mem_cons, iff_self_iff, or_false_iff, not_mem_zero]
#align multiset.mem_singleton Multiset.mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Multiset α) := by
rw [← cons_zero]
exact mem_cons_self _ _
#align multiset.mem_singleton_self Multiset.mem_singleton_self
@[simp]
theorem singleton_inj {a b : α} : ({a} : Multiset α) = {b} ↔ a = b := by
simp_rw [← cons_zero]
exact cons_inj_left _
#align multiset.singleton_inj Multiset.singleton_inj
@[simp, norm_cast]
theorem coe_eq_singleton {l : List α} {a : α} : (l : Multiset α) = {a} ↔ l = [a] := by
rw [← coe_singleton, coe_eq_coe, List.perm_singleton]
#align multiset.coe_eq_singleton Multiset.coe_eq_singleton
@[simp]
theorem singleton_eq_cons_iff {a b : α} (m : Multiset α) : {a} = b ::ₘ m ↔ a = b ∧ m = 0 := by
rw [← cons_zero, cons_eq_cons]
simp [eq_comm]
#align multiset.singleton_eq_cons_iff Multiset.singleton_eq_cons_iff
theorem pair_comm (x y : α) : ({x, y} : Multiset α) = {y, x} :=
cons_swap x y 0
#align multiset.pair_comm Multiset.pair_comm
/-! ### `Multiset.Subset` -/
section Subset
variable {s : Multiset α} {a : α}
/-- `s ⊆ t` is the lift of the list subset relation. It means that any
element with nonzero multiplicity in `s` has nonzero multiplicity in `t`,
but it does not imply that the multiplicity of `a` in `s` is less or equal than in `t`;
see `s ≤ t` for this relation. -/
protected def Subset (s t : Multiset α) : Prop :=
∀ ⦃a : α⦄, a ∈ s → a ∈ t
#align multiset.subset Multiset.Subset
instance : HasSubset (Multiset α) :=
⟨Multiset.Subset⟩
instance : HasSSubset (Multiset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance instIsNonstrictStrictOrder : IsNonstrictStrictOrder (Multiset α) (· ⊆ ·) (· ⊂ ·) where
right_iff_left_not_left _ _ := Iff.rfl
@[simp]
theorem coe_subset {l₁ l₂ : List α} : (l₁ : Multiset α) ⊆ l₂ ↔ l₁ ⊆ l₂ :=
Iff.rfl
#align multiset.coe_subset Multiset.coe_subset
@[simp]
theorem Subset.refl (s : Multiset α) : s ⊆ s := fun _ h => h
#align multiset.subset.refl Multiset.Subset.refl
theorem Subset.trans {s t u : Multiset α} : s ⊆ t → t ⊆ u → s ⊆ u := fun h₁ h₂ _ m => h₂ (h₁ m)
#align multiset.subset.trans Multiset.Subset.trans
theorem subset_iff {s t : Multiset α} : s ⊆ t ↔ ∀ ⦃x⦄, x ∈ s → x ∈ t :=
Iff.rfl
#align multiset.subset_iff Multiset.subset_iff
theorem mem_of_subset {s t : Multiset α} {a : α} (h : s ⊆ t) : a ∈ s → a ∈ t :=
@h _
#align multiset.mem_of_subset Multiset.mem_of_subset
@[simp]
theorem zero_subset (s : Multiset α) : 0 ⊆ s := fun a => (not_mem_nil a).elim
#align multiset.zero_subset Multiset.zero_subset
theorem subset_cons (s : Multiset α) (a : α) : s ⊆ a ::ₘ s := fun _ => mem_cons_of_mem
#align multiset.subset_cons Multiset.subset_cons
theorem ssubset_cons {s : Multiset α} {a : α} (ha : a ∉ s) : s ⊂ a ::ₘ s :=
⟨subset_cons _ _, fun h => ha <| h <| mem_cons_self _ _⟩
#align multiset.ssubset_cons Multiset.ssubset_cons
@[simp]
theorem cons_subset {a : α} {s t : Multiset α} : a ::ₘ s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp [subset_iff, or_imp, forall_and]
#align multiset.cons_subset Multiset.cons_subset
theorem cons_subset_cons {a : α} {s t : Multiset α} : s ⊆ t → a ::ₘ s ⊆ a ::ₘ t :=
Quotient.inductionOn₂ s t fun _ _ => List.cons_subset_cons _
#align multiset.cons_subset_cons Multiset.cons_subset_cons
theorem eq_zero_of_subset_zero {s : Multiset α} (h : s ⊆ 0) : s = 0 :=
eq_zero_of_forall_not_mem fun _ hx ↦ not_mem_zero _ (h hx)
#align multiset.eq_zero_of_subset_zero Multiset.eq_zero_of_subset_zero
@[simp] lemma subset_zero : s ⊆ 0 ↔ s = 0 :=
⟨eq_zero_of_subset_zero, fun xeq => xeq.symm ▸ Subset.refl 0⟩
#align multiset.subset_zero Multiset.subset_zero
@[simp] lemma zero_ssubset : 0 ⊂ s ↔ s ≠ 0 := by simp [ssubset_iff_subset_not_subset]
@[simp] lemma singleton_subset : {a} ⊆ s ↔ a ∈ s := by simp [subset_iff]
theorem induction_on' {p : Multiset α → Prop} (S : Multiset α) (h₁ : p 0)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → p s → p (insert a s)) : p S :=
@Multiset.induction_on α (fun T => T ⊆ S → p T) S (fun _ => h₁)
(fun _ _ hps hs =>
let ⟨hS, sS⟩ := cons_subset.1 hs
h₂ hS sS (hps sS))
(Subset.refl S)
#align multiset.induction_on' Multiset.induction_on'
end Subset
/-! ### `Multiset.toList` -/
section ToList
/-- Produces a list of the elements in the multiset using choice. -/
noncomputable def toList (s : Multiset α) :=
s.out'
#align multiset.to_list Multiset.toList
@[simp, norm_cast]
theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s :=
s.out_eq'
#align multiset.coe_to_list Multiset.coe_toList
@[simp]
theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by
rw [← coe_eq_zero, coe_toList]
#align multiset.to_list_eq_nil Multiset.toList_eq_nil
@[simp]
theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 :=
isEmpty_iff_eq_nil.trans toList_eq_nil
#align multiset.empty_to_list Multiset.empty_toList
@[simp]
theorem toList_zero : (Multiset.toList 0 : List α) = [] :=
toList_eq_nil.mpr rfl
#align multiset.to_list_zero Multiset.toList_zero
@[simp]
theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by
rw [← mem_coe, coe_toList]
#align multiset.mem_to_list Multiset.mem_toList
@[simp]
theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by
rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton]
#align multiset.to_list_eq_singleton_iff Multiset.toList_eq_singleton_iff
@[simp]
theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] :=
Multiset.toList_eq_singleton_iff.2 rfl
#align multiset.to_list_singleton Multiset.toList_singleton
end ToList
/-! ### Partial order on `Multiset`s -/
/-- `s ≤ t` means that `s` is a sublist of `t` (up to permutation).
Equivalently, `s ≤ t` means that `count a s ≤ count a t` for all `a`. -/
protected def Le (s t : Multiset α) : Prop :=
(Quotient.liftOn₂ s t (· <+~ ·)) fun _ _ _ _ p₁ p₂ =>
propext (p₂.subperm_left.trans p₁.subperm_right)
#align multiset.le Multiset.Le
instance : PartialOrder (Multiset α) where
le := Multiset.Le
le_refl := by rintro ⟨l⟩; exact Subperm.refl _
le_trans := by rintro ⟨l₁⟩ ⟨l₂⟩ ⟨l₃⟩; exact @Subperm.trans _ _ _ _
le_antisymm := by rintro ⟨l₁⟩ ⟨l₂⟩ h₁ h₂; exact Quot.sound (Subperm.antisymm h₁ h₂)
instance decidableLE [DecidableEq α] : DecidableRel ((· ≤ ·) : Multiset α → Multiset α → Prop) :=
fun s t => Quotient.recOnSubsingleton₂ s t List.decidableSubperm
#align multiset.decidable_le Multiset.decidableLE
section
variable {s t : Multiset α} {a : α}
theorem subset_of_le : s ≤ t → s ⊆ t :=
Quotient.inductionOn₂ s t fun _ _ => Subperm.subset
#align multiset.subset_of_le Multiset.subset_of_le
alias Le.subset := subset_of_le
#align multiset.le.subset Multiset.Le.subset
theorem mem_of_le (h : s ≤ t) : a ∈ s → a ∈ t :=
mem_of_subset (subset_of_le h)
#align multiset.mem_of_le Multiset.mem_of_le
theorem not_mem_mono (h : s ⊆ t) : a ∉ t → a ∉ s :=
mt <| @h _
#align multiset.not_mem_mono Multiset.not_mem_mono
@[simp]
theorem coe_le {l₁ l₂ : List α} : (l₁ : Multiset α) ≤ l₂ ↔ l₁ <+~ l₂ :=
Iff.rfl
#align multiset.coe_le Multiset.coe_le
@[elab_as_elim]
theorem leInductionOn {C : Multiset α → Multiset α → Prop} {s t : Multiset α} (h : s ≤ t)
(H : ∀ {l₁ l₂ : List α}, l₁ <+ l₂ → C l₁ l₂) : C s t :=
Quotient.inductionOn₂ s t (fun l₁ _ ⟨l, p, s⟩ => (show ⟦l⟧ = ⟦l₁⟧ from Quot.sound p) ▸ H s) h
#align multiset.le_induction_on Multiset.leInductionOn
theorem zero_le (s : Multiset α) : 0 ≤ s :=
Quot.inductionOn s fun l => (nil_sublist l).subperm
#align multiset.zero_le Multiset.zero_le
instance : OrderBot (Multiset α) where
bot := 0
bot_le := zero_le
/-- This is a `rfl` and `simp` version of `bot_eq_zero`. -/
@[simp]
theorem bot_eq_zero : (⊥ : Multiset α) = 0 :=
rfl
#align multiset.bot_eq_zero Multiset.bot_eq_zero
theorem le_zero : s ≤ 0 ↔ s = 0 :=
le_bot_iff
#align multiset.le_zero Multiset.le_zero
theorem lt_cons_self (s : Multiset α) (a : α) : s < a ::ₘ s :=
Quot.inductionOn s fun l =>
suffices l <+~ a :: l ∧ ¬l ~ a :: l by simpa [lt_iff_le_and_ne]
⟨(sublist_cons _ _).subperm, fun p => _root_.ne_of_lt (lt_succ_self (length l)) p.length_eq⟩
#align multiset.lt_cons_self Multiset.lt_cons_self
theorem le_cons_self (s : Multiset α) (a : α) : s ≤ a ::ₘ s :=
le_of_lt <| lt_cons_self _ _
#align multiset.le_cons_self Multiset.le_cons_self
theorem cons_le_cons_iff (a : α) : a ::ₘ s ≤ a ::ₘ t ↔ s ≤ t :=
Quotient.inductionOn₂ s t fun _ _ => subperm_cons a
#align multiset.cons_le_cons_iff Multiset.cons_le_cons_iff
theorem cons_le_cons (a : α) : s ≤ t → a ::ₘ s ≤ a ::ₘ t :=
(cons_le_cons_iff a).2
#align multiset.cons_le_cons Multiset.cons_le_cons
@[simp] lemma cons_lt_cons_iff : a ::ₘ s < a ::ₘ t ↔ s < t :=
lt_iff_lt_of_le_iff_le' (cons_le_cons_iff _) (cons_le_cons_iff _)
lemma cons_lt_cons (a : α) (h : s < t) : a ::ₘ s < a ::ₘ t := cons_lt_cons_iff.2 h
theorem le_cons_of_not_mem (m : a ∉ s) : s ≤ a ::ₘ t ↔ s ≤ t := by
refine ⟨?_, fun h => le_trans h <| le_cons_self _ _⟩
suffices ∀ {t'}, s ≤ t' → a ∈ t' → a ::ₘ s ≤ t' by
exact fun h => (cons_le_cons_iff a).1 (this h (mem_cons_self _ _))
introv h
revert m
refine leInductionOn h ?_
introv s m₁ m₂
rcases append_of_mem m₂ with ⟨r₁, r₂, rfl⟩
exact
perm_middle.subperm_left.2
((subperm_cons _).2 <| ((sublist_or_mem_of_sublist s).resolve_right m₁).subperm)
#align multiset.le_cons_of_not_mem Multiset.le_cons_of_not_mem
@[simp]
theorem singleton_ne_zero (a : α) : ({a} : Multiset α) ≠ 0 :=
ne_of_gt (lt_cons_self _ _)
#align multiset.singleton_ne_zero Multiset.singleton_ne_zero
@[simp]
theorem singleton_le {a : α} {s : Multiset α} : {a} ≤ s ↔ a ∈ s :=
⟨fun h => mem_of_le h (mem_singleton_self _), fun h =>
let ⟨_t, e⟩ := exists_cons_of_mem h
e.symm ▸ cons_le_cons _ (zero_le _)⟩
#align multiset.singleton_le Multiset.singleton_le
@[simp] lemma le_singleton : s ≤ {a} ↔ s = 0 ∨ s = {a} :=
Quot.induction_on s fun l ↦ by simp only [cons_zero, ← coe_singleton, quot_mk_to_coe'', coe_le,
coe_eq_zero, coe_eq_coe, perm_singleton, subperm_singleton_iff]
@[simp] lemma lt_singleton : s < {a} ↔ s = 0 := by
simp only [lt_iff_le_and_ne, le_singleton, or_and_right, Ne, and_not_self, or_false,
and_iff_left_iff_imp]
rintro rfl
exact (singleton_ne_zero _).symm
@[simp] lemma ssubset_singleton_iff : s ⊂ {a} ↔ s = 0 := by
refine ⟨fun hs ↦ eq_zero_of_subset_zero fun b hb ↦ (hs.2 ?_).elim, ?_⟩
· obtain rfl := mem_singleton.1 (hs.1 hb)
rwa [singleton_subset]
· rintro rfl
simp
end
/-! ### Additive monoid -/
/-- The sum of two multisets is the lift of the list append operation.
This adds the multiplicities of each element,
i.e. `count a (s + t) = count a s + count a t`. -/
protected def add (s₁ s₂ : Multiset α) : Multiset α :=
(Quotient.liftOn₂ s₁ s₂ fun l₁ l₂ => ((l₁ ++ l₂ : List α) : Multiset α)) fun _ _ _ _ p₁ p₂ =>
Quot.sound <| p₁.append p₂
#align multiset.add Multiset.add
instance : Add (Multiset α) :=
⟨Multiset.add⟩
@[simp]
theorem coe_add (s t : List α) : (s + t : Multiset α) = (s ++ t : List α) :=
rfl
#align multiset.coe_add Multiset.coe_add
@[simp]
theorem singleton_add (a : α) (s : Multiset α) : {a} + s = a ::ₘ s :=
rfl
#align multiset.singleton_add Multiset.singleton_add
private theorem add_le_add_iff_left' {s t u : Multiset α} : s + t ≤ s + u ↔ t ≤ u :=
Quotient.inductionOn₃ s t u fun _ _ _ => subperm_append_left _
instance : CovariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.2⟩
instance : ContravariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.1⟩
instance : OrderedCancelAddCommMonoid (Multiset α) where
zero := 0
add := (· + ·)
add_comm := fun s t => Quotient.inductionOn₂ s t fun l₁ l₂ => Quot.sound perm_append_comm
add_assoc := fun s₁ s₂ s₃ =>
Quotient.inductionOn₃ s₁ s₂ s₃ fun l₁ l₂ l₃ => congr_arg _ <| append_assoc l₁ l₂ l₃
zero_add := fun s => Quot.inductionOn s fun l => rfl
add_zero := fun s => Quotient.inductionOn s fun l => congr_arg _ <| append_nil l
add_le_add_left := fun s₁ s₂ => add_le_add_left
le_of_add_le_add_left := fun s₁ s₂ s₃ => le_of_add_le_add_left
nsmul := nsmulRec
theorem le_add_right (s t : Multiset α) : s ≤ s + t := by simpa using add_le_add_left (zero_le t) s
#align multiset.le_add_right Multiset.le_add_right
theorem le_add_left (s t : Multiset α) : s ≤ t + s := by simpa using add_le_add_right (zero_le t) s
#align multiset.le_add_left Multiset.le_add_left
theorem le_iff_exists_add {s t : Multiset α} : s ≤ t ↔ ∃ u, t = s + u :=
⟨fun h =>
leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩,
fun ⟨_u, e⟩ => e.symm ▸ le_add_right _ _⟩
#align multiset.le_iff_exists_add Multiset.le_iff_exists_add
instance : CanonicallyOrderedAddCommMonoid (Multiset α) where
__ := inferInstanceAs (OrderBot (Multiset α))
le_self_add := le_add_right
exists_add_of_le h := leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩
@[simp]
theorem cons_add (a : α) (s t : Multiset α) : a ::ₘ s + t = a ::ₘ (s + t) := by
rw [← singleton_add, ← singleton_add, add_assoc]
#align multiset.cons_add Multiset.cons_add
@[simp]
theorem add_cons (a : α) (s t : Multiset α) : s + a ::ₘ t = a ::ₘ (s + t) := by
rw [add_comm, cons_add, add_comm]
#align multiset.add_cons Multiset.add_cons
@[simp]
theorem mem_add {a : α} {s t : Multiset α} : a ∈ s + t ↔ a ∈ s ∨ a ∈ t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => mem_append
#align multiset.mem_add Multiset.mem_add
theorem mem_of_mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h : a ∈ n • s) : a ∈ s := by
induction' n with n ih
· rw [zero_nsmul] at h
exact absurd h (not_mem_zero _)
· rw [succ_nsmul, mem_add] at h
exact h.elim ih id
#align multiset.mem_of_mem_nsmul Multiset.mem_of_mem_nsmul
@[simp]
theorem mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h0 : n ≠ 0) : a ∈ n • s ↔ a ∈ s := by
refine ⟨mem_of_mem_nsmul, fun h => ?_⟩
obtain ⟨n, rfl⟩ := exists_eq_succ_of_ne_zero h0
rw [succ_nsmul, mem_add]
exact Or.inr h
#align multiset.mem_nsmul Multiset.mem_nsmul
theorem nsmul_cons {s : Multiset α} (n : ℕ) (a : α) :
n • (a ::ₘ s) = n • ({a} : Multiset α) + n • s := by
rw [← singleton_add, nsmul_add]
#align multiset.nsmul_cons Multiset.nsmul_cons
/-! ### Cardinality -/
/-- The cardinality of a multiset is the sum of the multiplicities
of all its elements, or simply the length of the underlying list. -/
def card : Multiset α →+ ℕ where
toFun s := (Quot.liftOn s length) fun _l₁ _l₂ => Perm.length_eq
map_zero' := rfl
map_add' s t := Quotient.inductionOn₂ s t length_append
#align multiset.card Multiset.card
@[simp]
theorem coe_card (l : List α) : card (l : Multiset α) = length l :=
rfl
#align multiset.coe_card Multiset.coe_card
@[simp]
| Mathlib/Data/Multiset/Basic.lean | 764 | 765 | theorem length_toList (s : Multiset α) : s.toList.length = card s := by |
rw [← coe_card, coe_toList]
|
/-
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)
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
theorem Finite.injOn_of_encard_image_eq (hs : s.Finite) (h : (f '' s).encard = s.encard) :
InjOn f s := by
obtain (h' | hne) := isEmpty_or_nonempty α
· rw [s.eq_empty_of_isEmpty]; simp
rw [← (f.invFunOn_injOn_image s).encard_image] at h
rw [injOn_iff_invFunOn_image_image_eq_self]
exact hs.eq_of_subset_of_encard_le (f.invFunOn_image_image_subset s) h.symm.le
theorem encard_preimage_of_injective_subset_range (hf : f.Injective) (ht : t ⊆ range f) :
(f ⁻¹' t).encard = t.encard := by
rw [← hf.encard_image, image_preimage_eq_inter_range, inter_eq_self_of_subset_left ht]
theorem encard_le_encard_of_injOn (hf : MapsTo f s t) (f_inj : InjOn f s) :
s.encard ≤ t.encard := by
rw [← f_inj.encard_image]; apply encard_le_card; rintro _ ⟨x, hx, rfl⟩; exact hf hx
theorem Finite.exists_injOn_of_encard_le [Nonempty β] {s : Set α} {t : Set β} (hs : s.Finite)
(hle : s.encard ≤ t.encard) : ∃ (f : α → β), s ⊆ f ⁻¹' t ∧ InjOn f s := by
classical
obtain (rfl | h | ⟨a, has, -⟩) := s.eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt
· simp
· exact (encard_ne_top_iff.mpr hs h).elim
obtain ⟨b, hbt⟩ := encard_pos.1 ((encard_pos.2 ⟨_, has⟩).trans_le hle)
have hle' : (s \ {a}).encard ≤ (t \ {b}).encard := by
rwa [← WithTop.add_le_add_iff_right WithTop.one_ne_top,
encard_diff_singleton_add_one has, encard_diff_singleton_add_one hbt]
obtain ⟨f₀, hf₀s, hinj⟩ := exists_injOn_of_encard_le (hs.diff {a}) hle'
simp only [preimage_diff, subset_def, mem_diff, mem_singleton_iff, mem_preimage, and_imp] at hf₀s
use Function.update f₀ a b
rw [← insert_eq_of_mem has, ← insert_diff_singleton, injOn_insert (fun h ↦ h.2 rfl)]
simp only [mem_diff, mem_singleton_iff, not_true, and_false, insert_diff_singleton, subset_def,
mem_insert_iff, mem_preimage, ne_eq, Function.update_apply, forall_eq_or_imp, ite_true, and_imp,
mem_image, ite_eq_left_iff, not_exists, not_and, not_forall, exists_prop, and_iff_right hbt]
refine ⟨?_, ?_, fun x hxs hxa ↦ ⟨hxa, (hf₀s x hxs hxa).2⟩⟩
· rintro x hx; split_ifs with h
· assumption
· exact (hf₀s x hx h).1
exact InjOn.congr hinj (fun x ⟨_, hxa⟩ ↦ by rwa [Function.update_noteq])
termination_by encard s
theorem Finite.exists_bijOn_of_encard_eq [Nonempty β] (hs : s.Finite) (h : s.encard = t.encard) :
∃ (f : α → β), BijOn f s t := by
obtain ⟨f, hf, hinj⟩ := hs.exists_injOn_of_encard_le h.le; use f
convert hinj.bijOn_image
rw [(hs.image f).eq_of_subset_of_encard_le' (image_subset_iff.mpr hf)
(h.symm.trans hinj.encard_image.symm).le]
end Function
section ncard
open Nat
/-- A tactic (for use in default params) that applies `Set.toFinite` to synthesize a `Set.Finite`
term. -/
syntax "toFinite_tac" : tactic
macro_rules
| `(tactic| toFinite_tac) => `(tactic| apply Set.toFinite)
/-- A tactic useful for transferring proofs for `encard` to their corresponding `card` statements -/
syntax "to_encard_tac" : tactic
macro_rules
| `(tactic| to_encard_tac) => `(tactic|
simp only [← Nat.cast_le (α := ℕ∞), ← Nat.cast_inj (R := ℕ∞), Nat.cast_add, Nat.cast_one])
/-- The cardinality of `s : Set α` . Has the junk value `0` if `s` is infinite -/
noncomputable def ncard (s : Set α) : ℕ := ENat.toNat s.encard
#align set.ncard Set.ncard
theorem ncard_def (s : Set α) : s.ncard = ENat.toNat s.encard := rfl
theorem Finite.cast_ncard_eq (hs : s.Finite) : s.ncard = s.encard := by
rwa [ncard, ENat.coe_toNat_eq_self, ne_eq, encard_eq_top_iff, Set.Infinite, not_not]
theorem Nat.card_coe_set_eq (s : Set α) : Nat.card s = s.ncard := by
obtain (h | h) := s.finite_or_infinite
· have := h.fintype
rw [ncard, h.encard_eq_coe_toFinset_card, Nat.card_eq_fintype_card,
toFinite_toFinset, toFinset_card, ENat.toNat_coe]
have := infinite_coe_iff.2 h
rw [ncard, h.encard_eq, Nat.card_eq_zero_of_infinite, ENat.toNat_top]
#align set.nat.card_coe_set_eq Set.Nat.card_coe_set_eq
theorem ncard_eq_toFinset_card (s : Set α) (hs : s.Finite := by toFinite_tac) :
s.ncard = hs.toFinset.card := by
rw [← Nat.card_coe_set_eq, @Nat.card_eq_fintype_card _ hs.fintype,
@Finite.card_toFinset _ _ hs.fintype hs]
#align set.ncard_eq_to_finset_card Set.ncard_eq_toFinset_card
theorem ncard_eq_toFinset_card' (s : Set α) [Fintype s] :
s.ncard = s.toFinset.card := by
simp [← Nat.card_coe_set_eq, Nat.card_eq_fintype_card]
theorem encard_le_coe_iff_finite_ncard_le {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ s.ncard ≤ k := by
rw [encard_le_coe_iff, and_congr_right_iff]
exact fun hfin ↦ ⟨fun ⟨n₀, hn₀, hle⟩ ↦ by rwa [ncard_def, hn₀, ENat.toNat_coe],
fun h ↦ ⟨s.ncard, by rw [hfin.cast_ncard_eq], h⟩⟩
theorem Infinite.ncard (hs : s.Infinite) : s.ncard = 0 := by
rw [← Nat.card_coe_set_eq, @Nat.card_eq_zero_of_infinite _ hs.to_subtype]
#align set.infinite.ncard Set.Infinite.ncard
theorem ncard_le_ncard (hst : s ⊆ t) (ht : t.Finite := by toFinite_tac) :
s.ncard ≤ t.ncard := by
rw [← Nat.cast_le (α := ℕ∞), ht.cast_ncard_eq, (ht.subset hst).cast_ncard_eq]
exact encard_mono hst
#align set.ncard_le_of_subset Set.ncard_le_ncard
theorem ncard_mono [Finite α] : @Monotone (Set α) _ _ _ ncard := fun _ _ ↦ ncard_le_ncard
#align set.ncard_mono Set.ncard_mono
@[simp] theorem ncard_eq_zero (hs : s.Finite := by toFinite_tac) :
s.ncard = 0 ↔ s = ∅ := by
rw [← Nat.cast_inj (R := ℕ∞), hs.cast_ncard_eq, Nat.cast_zero, encard_eq_zero]
#align set.ncard_eq_zero Set.ncard_eq_zero
@[simp] theorem ncard_coe_Finset (s : Finset α) : (s : Set α).ncard = s.card := by
rw [ncard_eq_toFinset_card _, Finset.finite_toSet_toFinset]
#align set.ncard_coe_finset Set.ncard_coe_Finset
theorem ncard_univ (α : Type*) : (univ : Set α).ncard = Nat.card α := by
cases' finite_or_infinite α with h h
· have hft := Fintype.ofFinite α
rw [ncard_eq_toFinset_card, Finite.toFinset_univ, Finset.card_univ, Nat.card_eq_fintype_card]
rw [Nat.card_eq_zero_of_infinite, Infinite.ncard]
exact infinite_univ
#align set.ncard_univ Set.ncard_univ
@[simp] theorem ncard_empty (α : Type*) : (∅ : Set α).ncard = 0 := by
rw [ncard_eq_zero]
#align set.ncard_empty Set.ncard_empty
theorem ncard_pos (hs : s.Finite := by toFinite_tac) : 0 < s.ncard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, Ne, ncard_eq_zero hs, nonempty_iff_ne_empty]
#align set.ncard_pos Set.ncard_pos
theorem ncard_ne_zero_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) : s.ncard ≠ 0 :=
((ncard_pos hs).mpr ⟨a, h⟩).ne.symm
#align set.ncard_ne_zero_of_mem Set.ncard_ne_zero_of_mem
theorem finite_of_ncard_ne_zero (hs : s.ncard ≠ 0) : s.Finite :=
s.finite_or_infinite.elim id fun h ↦ (hs h.ncard).elim
#align set.finite_of_ncard_ne_zero Set.finite_of_ncard_ne_zero
theorem finite_of_ncard_pos (hs : 0 < s.ncard) : s.Finite :=
finite_of_ncard_ne_zero hs.ne.symm
#align set.finite_of_ncard_pos Set.finite_of_ncard_pos
theorem nonempty_of_ncard_ne_zero (hs : s.ncard ≠ 0) : s.Nonempty := by
rw [nonempty_iff_ne_empty]; rintro rfl; simp at hs
#align set.nonempty_of_ncard_ne_zero Set.nonempty_of_ncard_ne_zero
@[simp] theorem ncard_singleton (a : α) : ({a} : Set α).ncard = 1 := by
simp [ncard, ncard_eq_toFinset_card]
#align set.ncard_singleton Set.ncard_singleton
theorem ncard_singleton_inter (a : α) (s : Set α) : ({a} ∩ s).ncard ≤ 1 := by
rw [← Nat.cast_le (α := ℕ∞), (toFinite _).cast_ncard_eq, Nat.cast_one]
apply encard_singleton_inter
#align set.ncard_singleton_inter Set.ncard_singleton_inter
section InsertErase
@[simp] theorem ncard_insert_of_not_mem {a : α} (h : a ∉ s) (hs : s.Finite := by toFinite_tac) :
(insert a s).ncard = s.ncard + 1 := by
rw [← Nat.cast_inj (R := ℕ∞), (hs.insert a).cast_ncard_eq, Nat.cast_add, Nat.cast_one,
hs.cast_ncard_eq, encard_insert_of_not_mem h]
#align set.ncard_insert_of_not_mem Set.ncard_insert_of_not_mem
theorem ncard_insert_of_mem {a : α} (h : a ∈ s) : ncard (insert a s) = s.ncard := by
rw [insert_eq_of_mem h]
#align set.ncard_insert_of_mem Set.ncard_insert_of_mem
theorem ncard_insert_le (a : α) (s : Set α) : (insert a s).ncard ≤ s.ncard + 1 := by
obtain hs | hs := s.finite_or_infinite
· to_encard_tac; rw [hs.cast_ncard_eq, (hs.insert _).cast_ncard_eq]; apply encard_insert_le
rw [(hs.mono (subset_insert a s)).ncard]
exact Nat.zero_le _
#align set.ncard_insert_le Set.ncard_insert_le
theorem ncard_insert_eq_ite {a : α} [Decidable (a ∈ s)] (hs : s.Finite := by toFinite_tac) :
ncard (insert a s) = if a ∈ s then s.ncard else s.ncard + 1 := by
by_cases h : a ∈ s
· rw [ncard_insert_of_mem h, if_pos h]
· rw [ncard_insert_of_not_mem h hs, if_neg h]
#align set.ncard_insert_eq_ite Set.ncard_insert_eq_ite
theorem ncard_le_ncard_insert (a : α) (s : Set α) : s.ncard ≤ (insert a s).ncard := by
classical
refine
s.finite_or_infinite.elim (fun h ↦ ?_) (fun h ↦ by (rw [h.ncard]; exact Nat.zero_le _))
rw [ncard_insert_eq_ite h]; split_ifs <;> simp
#align set.ncard_le_ncard_insert Set.ncard_le_ncard_insert
@[simp] theorem ncard_pair {a b : α} (h : a ≠ b) : ({a, b} : Set α).ncard = 2 := by
rw [ncard_insert_of_not_mem, ncard_singleton]; simpa
#align set.card_doubleton Set.ncard_pair
@[simp] theorem ncard_diff_singleton_add_one {a : α} (h : a ∈ s)
(hs : s.Finite := by toFinite_tac) : (s \ {a}).ncard + 1 = s.ncard := by
to_encard_tac; rw [hs.cast_ncard_eq, (hs.diff _).cast_ncard_eq,
encard_diff_singleton_add_one h]
#align set.ncard_diff_singleton_add_one Set.ncard_diff_singleton_add_one
@[simp] theorem ncard_diff_singleton_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) :
(s \ {a}).ncard = s.ncard - 1 :=
eq_tsub_of_add_eq (ncard_diff_singleton_add_one h hs)
#align set.ncard_diff_singleton_of_mem Set.ncard_diff_singleton_of_mem
theorem ncard_diff_singleton_lt_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) :
(s \ {a}).ncard < s.ncard := by
rw [← ncard_diff_singleton_add_one h hs]; apply lt_add_one
#align set.ncard_diff_singleton_lt_of_mem Set.ncard_diff_singleton_lt_of_mem
theorem ncard_diff_singleton_le (s : Set α) (a : α) : (s \ {a}).ncard ≤ s.ncard := by
obtain hs | hs := s.finite_or_infinite
· apply ncard_le_ncard diff_subset hs
convert @zero_le ℕ _ _
exact (hs.diff (by simp : Set.Finite {a})).ncard
#align set.ncard_diff_singleton_le Set.ncard_diff_singleton_le
theorem pred_ncard_le_ncard_diff_singleton (s : Set α) (a : α) : s.ncard - 1 ≤ (s \ {a}).ncard := by
cases' s.finite_or_infinite with hs hs
· by_cases h : a ∈ s
· rw [ncard_diff_singleton_of_mem h hs]
rw [diff_singleton_eq_self h]
apply Nat.pred_le
convert Nat.zero_le _
rw [hs.ncard]
#align set.pred_ncard_le_ncard_diff_singleton Set.pred_ncard_le_ncard_diff_singleton
theorem ncard_exchange {a b : α} (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).ncard = s.ncard :=
congr_arg ENat.toNat <| encard_exchange ha hb
#align set.ncard_exchange Set.ncard_exchange
theorem ncard_exchange' {a b : α} (ha : a ∉ s) (hb : b ∈ s) :
(insert a s \ {b}).ncard = s.ncard := by
rw [← ncard_exchange ha hb, ← singleton_union, ← singleton_union, union_diff_distrib,
@diff_singleton_eq_self _ b {a} fun h ↦ ha (by rwa [← mem_singleton_iff.mp h])]
#align set.ncard_exchange' Set.ncard_exchange'
end InsertErase
variable {f : α → β}
theorem ncard_image_le (hs : s.Finite := by toFinite_tac) : (f '' s).ncard ≤ s.ncard := by
to_encard_tac; rw [hs.cast_ncard_eq, (hs.image _).cast_ncard_eq]; apply encard_image_le
#align set.ncard_image_le Set.ncard_image_le
theorem ncard_image_of_injOn (H : Set.InjOn f s) : (f '' s).ncard = s.ncard :=
congr_arg ENat.toNat <| H.encard_image
#align set.ncard_image_of_inj_on Set.ncard_image_of_injOn
theorem injOn_of_ncard_image_eq (h : (f '' s).ncard = s.ncard) (hs : s.Finite := by toFinite_tac) :
Set.InjOn f s := by
rw [← Nat.cast_inj (R := ℕ∞), hs.cast_ncard_eq, (hs.image _).cast_ncard_eq] at h
exact hs.injOn_of_encard_image_eq h
#align set.inj_on_of_ncard_image_eq Set.injOn_of_ncard_image_eq
theorem ncard_image_iff (hs : s.Finite := by toFinite_tac) :
(f '' s).ncard = s.ncard ↔ Set.InjOn f s :=
⟨fun h ↦ injOn_of_ncard_image_eq h hs, ncard_image_of_injOn⟩
#align set.ncard_image_iff Set.ncard_image_iff
theorem ncard_image_of_injective (s : Set α) (H : f.Injective) : (f '' s).ncard = s.ncard :=
ncard_image_of_injOn fun _ _ _ _ h ↦ H h
#align set.ncard_image_of_injective Set.ncard_image_of_injective
theorem ncard_preimage_of_injective_subset_range {s : Set β} (H : f.Injective)
(hs : s ⊆ Set.range f) :
(f ⁻¹' s).ncard = s.ncard := by
rw [← ncard_image_of_injective _ H, image_preimage_eq_iff.mpr hs]
#align set.ncard_preimage_of_injective_subset_range Set.ncard_preimage_of_injective_subset_range
theorem fiber_ncard_ne_zero_iff_mem_image {y : β} (hs : s.Finite := by toFinite_tac) :
{ x ∈ s | f x = y }.ncard ≠ 0 ↔ y ∈ f '' s := by
refine ⟨nonempty_of_ncard_ne_zero, ?_⟩
rintro ⟨z, hz, rfl⟩
exact @ncard_ne_zero_of_mem _ ({ x ∈ s | f x = f z }) z (mem_sep hz rfl)
(hs.subset (sep_subset _ _))
#align set.fiber_ncard_ne_zero_iff_mem_image Set.fiber_ncard_ne_zero_iff_mem_image
@[simp] theorem ncard_map (f : α ↪ β) : (f '' s).ncard = s.ncard :=
ncard_image_of_injective _ f.inj'
#align set.ncard_map Set.ncard_map
@[simp] theorem ncard_subtype (P : α → Prop) (s : Set α) :
{ x : Subtype P | (x : α) ∈ s }.ncard = (s ∩ setOf P).ncard := by
convert (ncard_image_of_injective _ (@Subtype.coe_injective _ P)).symm
ext x
simp [← and_assoc, exists_eq_right]
#align set.ncard_subtype Set.ncard_subtype
theorem ncard_inter_le_ncard_left (s t : Set α) (hs : s.Finite := by toFinite_tac) :
(s ∩ t).ncard ≤ s.ncard :=
ncard_le_ncard inter_subset_left hs
#align set.ncard_inter_le_ncard_left Set.ncard_inter_le_ncard_left
theorem ncard_inter_le_ncard_right (s t : Set α) (ht : t.Finite := by toFinite_tac) :
(s ∩ t).ncard ≤ t.ncard :=
ncard_le_ncard inter_subset_right ht
#align set.ncard_inter_le_ncard_right Set.ncard_inter_le_ncard_right
theorem eq_of_subset_of_ncard_le (h : s ⊆ t) (h' : t.ncard ≤ s.ncard)
(ht : t.Finite := by toFinite_tac) : s = t :=
ht.eq_of_subset_of_encard_le h
(by rwa [← Nat.cast_le (α := ℕ∞), ht.cast_ncard_eq, (ht.subset h).cast_ncard_eq] at h')
#align set.eq_of_subset_of_ncard_le Set.eq_of_subset_of_ncard_le
theorem subset_iff_eq_of_ncard_le (h : t.ncard ≤ s.ncard) (ht : t.Finite := by toFinite_tac) :
s ⊆ t ↔ s = t :=
⟨fun hst ↦ eq_of_subset_of_ncard_le hst h ht, Eq.subset'⟩
#align set.subset_iff_eq_of_ncard_le Set.subset_iff_eq_of_ncard_le
theorem map_eq_of_subset {f : α ↪ α} (h : f '' s ⊆ s) (hs : s.Finite := by toFinite_tac) :
f '' s = s :=
eq_of_subset_of_ncard_le h (ncard_map _).ge hs
#align set.map_eq_of_subset Set.map_eq_of_subset
theorem sep_of_ncard_eq {a : α} {P : α → Prop} (h : { x ∈ s | P x }.ncard = s.ncard) (ha : a ∈ s)
(hs : s.Finite := by toFinite_tac) : P a :=
sep_eq_self_iff_mem_true.mp (eq_of_subset_of_ncard_le (by simp) h.symm.le hs) _ ha
#align set.sep_of_ncard_eq Set.sep_of_ncard_eq
theorem ncard_lt_ncard (h : s ⊂ t) (ht : t.Finite := by toFinite_tac) :
s.ncard < t.ncard := by
rw [← Nat.cast_lt (α := ℕ∞), ht.cast_ncard_eq, (ht.subset h.subset).cast_ncard_eq]
exact ht.encard_lt_encard h
#align set.ncard_lt_ncard Set.ncard_lt_ncard
theorem ncard_strictMono [Finite α] : @StrictMono (Set α) _ _ _ ncard :=
fun _ _ h ↦ ncard_lt_ncard h
#align set.ncard_strict_mono Set.ncard_strictMono
theorem ncard_eq_of_bijective {n : ℕ} (f : ∀ i, i < n → α)
(hf : ∀ a ∈ s, ∃ i, ∃ h : i < n, f i h = a) (hf' : ∀ (i) (h : i < n), f i h ∈ s)
(f_inj : ∀ (i j) (hi : i < n) (hj : j < n), f i hi = f j hj → i = j) : s.ncard = n := by
let f' : Fin n → α := fun i ↦ f i.val i.is_lt
suffices himage : s = f' '' Set.univ by
rw [← Fintype.card_fin n, ← Nat.card_eq_fintype_card, ← Set.ncard_univ, himage]
exact ncard_image_of_injOn <| fun i _hi j _hj h ↦ Fin.ext <| f_inj i.val j.val i.is_lt j.is_lt h
ext x
simp only [image_univ, mem_range]
refine ⟨fun hx ↦ ?_, fun ⟨⟨i, hi⟩, hx⟩ ↦ hx ▸ hf' i hi⟩
obtain ⟨i, hi, rfl⟩ := hf x hx
use ⟨i, hi⟩
#align set.ncard_eq_of_bijective Set.ncard_eq_of_bijective
| Mathlib/Data/Set/Card.lean | 755 | 769 | theorem ncard_congr {t : Set β} (f : ∀ a ∈ s, β) (h₁ : ∀ a ha, f a ha ∈ t)
(h₂ : ∀ a b ha hb, f a ha = f b hb → a = b) (h₃ : ∀ b ∈ t, ∃ a ha, f a ha = b) :
s.ncard = t.ncard := by |
set f' : s → t := fun x ↦ ⟨f x.1 x.2, h₁ _ _⟩
have hbij : f'.Bijective := by
constructor
· rintro ⟨x, hx⟩ ⟨y, hy⟩ hxy
simp only [f', Subtype.mk.injEq] at hxy ⊢
exact h₂ _ _ hx hy hxy
rintro ⟨y, hy⟩
obtain ⟨a, ha, rfl⟩ := h₃ y hy
simp only [Subtype.mk.injEq, Subtype.exists]
exact ⟨_, ha, rfl⟩
simp_rw [← Nat.card_coe_set_eq]
exact Nat.card_congr (Equiv.ofBijective f' hbij)
|
/-
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.GroupWithZero.Divisibility
import Mathlib.Algebra.MonoidAlgebra.Basic
import Mathlib.Data.Finset.Sort
#align_import data.polynomial.basic from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Theory of univariate polynomials
This file defines `Polynomial R`, the type of univariate polynomials over the semiring `R`, builds
a semiring structure on it, and gives basic definitions that are expanded in other files in this
directory.
## Main definitions
* `monomial n a` is the polynomial `a X^n`. Note that `monomial n` is defined as an `R`-linear map.
* `C a` is the constant polynomial `a`. Note that `C` is defined as a ring homomorphism.
* `X` is the polynomial `X`, i.e., `monomial 1 1`.
* `p.sum f` is `∑ n ∈ p.support, f n (p.coeff n)`, i.e., one sums the values of functions applied
to coefficients of the polynomial `p`.
* `p.erase n` is the polynomial `p` in which one removes the `c X^n` term.
There are often two natural variants of lemmas involving sums, depending on whether one acts on the
polynomials, or on the function. The naming convention is that one adds `index` when acting on
the polynomials. For instance,
* `sum_add_index` states that `(p + q).sum f = p.sum f + q.sum f`;
* `sum_add` states that `p.sum (fun n x ↦ f n x + g n x) = p.sum f + p.sum g`.
* Notation to refer to `Polynomial R`, as `R[X]` or `R[t]`.
## Implementation
Polynomials are defined using `R[ℕ]`, where `R` is a semiring.
The variable `X` commutes with every polynomial `p`: lemma `X_mul` proves the identity
`X * p = p * X`. The relationship to `R[ℕ]` is through a structure
to make polynomials irreducible from the point of view of the kernel. Most operations
are irreducible since Lean can not compute anyway with `AddMonoidAlgebra`. There are two
exceptions that we make semireducible:
* The zero polynomial, so that its coefficients are definitionally equal to `0`.
* The scalar action, to permit typeclass search to unfold it to resolve potential instance
diamonds.
The raw implementation of the equivalence between `R[X]` and `R[ℕ]` is
done through `ofFinsupp` and `toFinsupp` (or, equivalently, `rcases p` when `p` is a polynomial
gives an element `q` of `R[ℕ]`, and conversely `⟨q⟩` gives back `p`). The
equivalence is also registered as a ring equiv in `Polynomial.toFinsuppIso`. These should
in general not be used once the basic API for polynomials is constructed.
-/
set_option linter.uppercaseLean3 false
noncomputable section
/-- `Polynomial R` is the type of univariate polynomials over `R`.
Polynomials should be seen as (semi-)rings with the additional constructor `X`.
The embedding from `R` is called `C`. -/
structure Polynomial (R : Type*) [Semiring R] where ofFinsupp ::
toFinsupp : AddMonoidAlgebra R ℕ
#align polynomial Polynomial
#align polynomial.of_finsupp Polynomial.ofFinsupp
#align polynomial.to_finsupp Polynomial.toFinsupp
@[inherit_doc] scoped[Polynomial] notation:9000 R "[X]" => Polynomial R
open AddMonoidAlgebra
open Finsupp hiding single
open Function hiding Commute
open Polynomial
namespace Polynomial
universe u
variable {R : Type u} {a b : R} {m n : ℕ}
section Semiring
variable [Semiring R] {p q : R[X]}
theorem forall_iff_forall_finsupp (P : R[X] → Prop) :
(∀ p, P p) ↔ ∀ q : R[ℕ], P ⟨q⟩ :=
⟨fun h q => h ⟨q⟩, fun h ⟨p⟩ => h p⟩
#align polynomial.forall_iff_forall_finsupp Polynomial.forall_iff_forall_finsupp
theorem exists_iff_exists_finsupp (P : R[X] → Prop) :
(∃ p, P p) ↔ ∃ q : R[ℕ], P ⟨q⟩ :=
⟨fun ⟨⟨p⟩, hp⟩ => ⟨p, hp⟩, fun ⟨q, hq⟩ => ⟨⟨q⟩, hq⟩⟩
#align polynomial.exists_iff_exists_finsupp Polynomial.exists_iff_exists_finsupp
@[simp]
theorem eta (f : R[X]) : Polynomial.ofFinsupp f.toFinsupp = f := by cases f; rfl
#align polynomial.eta Polynomial.eta
/-! ### Conversions to and from `AddMonoidAlgebra`
Since `R[X]` is not defeq to `R[ℕ]`, but instead is a structure wrapping
it, we have to copy across all the arithmetic operators manually, along with the lemmas about how
they unfold around `Polynomial.ofFinsupp` and `Polynomial.toFinsupp`.
-/
section AddMonoidAlgebra
private irreducible_def add : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a + b⟩
private irreducible_def neg {R : Type u} [Ring R] : R[X] → R[X]
| ⟨a⟩ => ⟨-a⟩
private irreducible_def mul : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a * b⟩
instance zero : Zero R[X] :=
⟨⟨0⟩⟩
#align polynomial.has_zero Polynomial.zero
instance one : One R[X] :=
⟨⟨1⟩⟩
#align polynomial.one Polynomial.one
instance add' : Add R[X] :=
⟨add⟩
#align polynomial.has_add Polynomial.add'
instance neg' {R : Type u} [Ring R] : Neg R[X] :=
⟨neg⟩
#align polynomial.has_neg Polynomial.neg'
instance sub {R : Type u} [Ring R] : Sub R[X] :=
⟨fun a b => a + -b⟩
#align polynomial.has_sub Polynomial.sub
instance mul' : Mul R[X] :=
⟨mul⟩
#align polynomial.has_mul Polynomial.mul'
-- If the private definitions are accidentally exposed, simplify them away.
@[simp] theorem add_eq_add : add p q = p + q := rfl
@[simp] theorem mul_eq_mul : mul p q = p * q := rfl
instance smulZeroClass {S : Type*} [SMulZeroClass S R] : SMulZeroClass S R[X] where
smul r p := ⟨r • p.toFinsupp⟩
smul_zero a := congr_arg ofFinsupp (smul_zero a)
#align polynomial.smul_zero_class Polynomial.smulZeroClass
-- to avoid a bug in the `ring` tactic
instance (priority := 1) pow : Pow R[X] ℕ where pow p n := npowRec n p
#align polynomial.has_pow Polynomial.pow
@[simp]
theorem ofFinsupp_zero : (⟨0⟩ : R[X]) = 0 :=
rfl
#align polynomial.of_finsupp_zero Polynomial.ofFinsupp_zero
@[simp]
theorem ofFinsupp_one : (⟨1⟩ : R[X]) = 1 :=
rfl
#align polynomial.of_finsupp_one Polynomial.ofFinsupp_one
@[simp]
theorem ofFinsupp_add {a b} : (⟨a + b⟩ : R[X]) = ⟨a⟩ + ⟨b⟩ :=
show _ = add _ _ by rw [add_def]
#align polynomial.of_finsupp_add Polynomial.ofFinsupp_add
@[simp]
theorem ofFinsupp_neg {R : Type u} [Ring R] {a} : (⟨-a⟩ : R[X]) = -⟨a⟩ :=
show _ = neg _ by rw [neg_def]
#align polynomial.of_finsupp_neg Polynomial.ofFinsupp_neg
@[simp]
theorem ofFinsupp_sub {R : Type u} [Ring R] {a b} : (⟨a - b⟩ : R[X]) = ⟨a⟩ - ⟨b⟩ := by
rw [sub_eq_add_neg, ofFinsupp_add, ofFinsupp_neg]
rfl
#align polynomial.of_finsupp_sub Polynomial.ofFinsupp_sub
@[simp]
theorem ofFinsupp_mul (a b) : (⟨a * b⟩ : R[X]) = ⟨a⟩ * ⟨b⟩ :=
show _ = mul _ _ by rw [mul_def]
#align polynomial.of_finsupp_mul Polynomial.ofFinsupp_mul
@[simp]
theorem ofFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b) :
(⟨a • b⟩ : R[X]) = (a • ⟨b⟩ : R[X]) :=
rfl
#align polynomial.of_finsupp_smul Polynomial.ofFinsupp_smul
@[simp]
theorem ofFinsupp_pow (a) (n : ℕ) : (⟨a ^ n⟩ : R[X]) = ⟨a⟩ ^ n := by
change _ = npowRec n _
induction n with
| zero => simp [npowRec]
| succ n n_ih => simp [npowRec, n_ih, pow_succ]
#align polynomial.of_finsupp_pow Polynomial.ofFinsupp_pow
@[simp]
theorem toFinsupp_zero : (0 : R[X]).toFinsupp = 0 :=
rfl
#align polynomial.to_finsupp_zero Polynomial.toFinsupp_zero
@[simp]
theorem toFinsupp_one : (1 : R[X]).toFinsupp = 1 :=
rfl
#align polynomial.to_finsupp_one Polynomial.toFinsupp_one
@[simp]
theorem toFinsupp_add (a b : R[X]) : (a + b).toFinsupp = a.toFinsupp + b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_add]
#align polynomial.to_finsupp_add Polynomial.toFinsupp_add
@[simp]
theorem toFinsupp_neg {R : Type u} [Ring R] (a : R[X]) : (-a).toFinsupp = -a.toFinsupp := by
cases a
rw [← ofFinsupp_neg]
#align polynomial.to_finsupp_neg Polynomial.toFinsupp_neg
@[simp]
theorem toFinsupp_sub {R : Type u} [Ring R] (a b : R[X]) :
(a - b).toFinsupp = a.toFinsupp - b.toFinsupp := by
rw [sub_eq_add_neg, ← toFinsupp_neg, ← toFinsupp_add]
rfl
#align polynomial.to_finsupp_sub Polynomial.toFinsupp_sub
@[simp]
theorem toFinsupp_mul (a b : R[X]) : (a * b).toFinsupp = a.toFinsupp * b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_mul]
#align polynomial.to_finsupp_mul Polynomial.toFinsupp_mul
@[simp]
theorem toFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b : R[X]) :
(a • b).toFinsupp = a • b.toFinsupp :=
rfl
#align polynomial.to_finsupp_smul Polynomial.toFinsupp_smul
@[simp]
theorem toFinsupp_pow (a : R[X]) (n : ℕ) : (a ^ n).toFinsupp = a.toFinsupp ^ n := by
cases a
rw [← ofFinsupp_pow]
#align polynomial.to_finsupp_pow Polynomial.toFinsupp_pow
theorem _root_.IsSMulRegular.polynomial {S : Type*} [Monoid S] [DistribMulAction S R] {a : S}
(ha : IsSMulRegular R a) : IsSMulRegular R[X] a
| ⟨_x⟩, ⟨_y⟩, h => congr_arg _ <| ha.finsupp (Polynomial.ofFinsupp.inj h)
#align is_smul_regular.polynomial IsSMulRegular.polynomial
theorem toFinsupp_injective : Function.Injective (toFinsupp : R[X] → AddMonoidAlgebra _ _) :=
fun ⟨_x⟩ ⟨_y⟩ => congr_arg _
#align polynomial.to_finsupp_injective Polynomial.toFinsupp_injective
@[simp]
theorem toFinsupp_inj {a b : R[X]} : a.toFinsupp = b.toFinsupp ↔ a = b :=
toFinsupp_injective.eq_iff
#align polynomial.to_finsupp_inj Polynomial.toFinsupp_inj
@[simp]
theorem toFinsupp_eq_zero {a : R[X]} : a.toFinsupp = 0 ↔ a = 0 := by
rw [← toFinsupp_zero, toFinsupp_inj]
#align polynomial.to_finsupp_eq_zero Polynomial.toFinsupp_eq_zero
@[simp]
theorem toFinsupp_eq_one {a : R[X]} : a.toFinsupp = 1 ↔ a = 1 := by
rw [← toFinsupp_one, toFinsupp_inj]
#align polynomial.to_finsupp_eq_one Polynomial.toFinsupp_eq_one
/-- A more convenient spelling of `Polynomial.ofFinsupp.injEq` in terms of `Iff`. -/
theorem ofFinsupp_inj {a b} : (⟨a⟩ : R[X]) = ⟨b⟩ ↔ a = b :=
iff_of_eq (ofFinsupp.injEq _ _)
#align polynomial.of_finsupp_inj Polynomial.ofFinsupp_inj
@[simp]
theorem ofFinsupp_eq_zero {a} : (⟨a⟩ : R[X]) = 0 ↔ a = 0 := by
rw [← ofFinsupp_zero, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_zero Polynomial.ofFinsupp_eq_zero
@[simp]
theorem ofFinsupp_eq_one {a} : (⟨a⟩ : R[X]) = 1 ↔ a = 1 := by rw [← ofFinsupp_one, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_one Polynomial.ofFinsupp_eq_one
instance inhabited : Inhabited R[X] :=
⟨0⟩
#align polynomial.inhabited Polynomial.inhabited
instance instNatCast : NatCast R[X] where natCast n := ofFinsupp n
#align polynomial.has_nat_cast Polynomial.instNatCast
instance semiring : Semiring R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.semiring toFinsupp toFinsupp_injective toFinsupp_zero toFinsupp_one
toFinsupp_add toFinsupp_mul (fun _ _ => toFinsupp_smul _ _) toFinsupp_pow fun _ => rfl with
toAdd := Polynomial.add'
toMul := Polynomial.mul'
toZero := Polynomial.zero
toOne := Polynomial.one
nsmul := (· • ·)
npow := fun n x => (x ^ n) }
#align polynomial.semiring Polynomial.semiring
instance distribSMul {S} [DistribSMul S R] : DistribSMul S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribSMul ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toSMulZeroClass := Polynomial.smulZeroClass }
#align polynomial.distrib_smul Polynomial.distribSMul
instance distribMulAction {S} [Monoid S] [DistribMulAction S R] : DistribMulAction S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribMulAction ⟨⟨toFinsupp, toFinsupp_zero (R := R)⟩, toFinsupp_add⟩
toFinsupp_injective toFinsupp_smul with
toSMul := Polynomial.smulZeroClass.toSMul }
#align polynomial.distrib_mul_action Polynomial.distribMulAction
instance faithfulSMul {S} [SMulZeroClass S R] [FaithfulSMul S R] : FaithfulSMul S R[X] where
eq_of_smul_eq_smul {_s₁ _s₂} h :=
eq_of_smul_eq_smul fun a : ℕ →₀ R => congr_arg toFinsupp (h ⟨a⟩)
#align polynomial.has_faithful_smul Polynomial.faithfulSMul
instance module {S} [Semiring S] [Module S R] : Module S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.module _ ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toDistribMulAction := Polynomial.distribMulAction }
#align polynomial.module Polynomial.module
instance smulCommClass {S₁ S₂} [SMulZeroClass S₁ R] [SMulZeroClass S₂ R] [SMulCommClass S₁ S₂ R] :
SMulCommClass S₁ S₂ R[X] :=
⟨by
rintro m n ⟨f⟩
simp_rw [← ofFinsupp_smul, smul_comm m n f]⟩
#align polynomial.smul_comm_class Polynomial.smulCommClass
instance isScalarTower {S₁ S₂} [SMul S₁ S₂] [SMulZeroClass S₁ R] [SMulZeroClass S₂ R]
[IsScalarTower S₁ S₂ R] : IsScalarTower S₁ S₂ R[X] :=
⟨by
rintro _ _ ⟨⟩
simp_rw [← ofFinsupp_smul, smul_assoc]⟩
#align polynomial.is_scalar_tower Polynomial.isScalarTower
instance isScalarTower_right {α K : Type*} [Semiring K] [DistribSMul α K] [IsScalarTower α K K] :
IsScalarTower α K[X] K[X] :=
⟨by
rintro _ ⟨⟩ ⟨⟩;
simp_rw [smul_eq_mul, ← ofFinsupp_smul, ← ofFinsupp_mul, ← ofFinsupp_smul, smul_mul_assoc]⟩
#align polynomial.is_scalar_tower_right Polynomial.isScalarTower_right
instance isCentralScalar {S} [SMulZeroClass S R] [SMulZeroClass Sᵐᵒᵖ R] [IsCentralScalar S R] :
IsCentralScalar S R[X] :=
⟨by
rintro _ ⟨⟩
simp_rw [← ofFinsupp_smul, op_smul_eq_smul]⟩
#align polynomial.is_central_scalar Polynomial.isCentralScalar
instance unique [Subsingleton R] : Unique R[X] :=
{ Polynomial.inhabited with
uniq := by
rintro ⟨x⟩
apply congr_arg ofFinsupp
simp [eq_iff_true_of_subsingleton] }
#align polynomial.unique Polynomial.unique
variable (R)
/-- Ring isomorphism between `R[X]` and `R[ℕ]`. This is just an
implementation detail, but it can be useful to transfer results from `Finsupp` to polynomials. -/
@[simps apply symm_apply]
def toFinsuppIso : R[X] ≃+* R[ℕ] where
toFun := toFinsupp
invFun := ofFinsupp
left_inv := fun ⟨_p⟩ => rfl
right_inv _p := rfl
map_mul' := toFinsupp_mul
map_add' := toFinsupp_add
#align polynomial.to_finsupp_iso Polynomial.toFinsuppIso
#align polynomial.to_finsupp_iso_apply Polynomial.toFinsuppIso_apply
#align polynomial.to_finsupp_iso_symm_apply Polynomial.toFinsuppIso_symm_apply
instance [DecidableEq R] : DecidableEq R[X] :=
@Equiv.decidableEq R[X] _ (toFinsuppIso R).toEquiv (Finsupp.instDecidableEq)
end AddMonoidAlgebra
theorem ofFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[ℕ]) :
(⟨∑ i ∈ s, f i⟩ : R[X]) = ∑ i ∈ s, ⟨f i⟩ :=
map_sum (toFinsuppIso R).symm f s
#align polynomial.of_finsupp_sum Polynomial.ofFinsupp_sum
theorem toFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[X]) :
(∑ i ∈ s, f i : R[X]).toFinsupp = ∑ i ∈ s, (f i).toFinsupp :=
map_sum (toFinsuppIso R) f s
#align polynomial.to_finsupp_sum Polynomial.toFinsupp_sum
/-- The set of all `n` such that `X^n` has a non-zero coefficient.
-/
-- @[simp] -- Porting note: The original generated theorem is same to `support_ofFinsupp` and
-- the new generated theorem is different, so this attribute should be
-- removed.
def support : R[X] → Finset ℕ
| ⟨p⟩ => p.support
#align polynomial.support Polynomial.support
@[simp]
theorem support_ofFinsupp (p) : support (⟨p⟩ : R[X]) = p.support := by rw [support]
#align polynomial.support_of_finsupp Polynomial.support_ofFinsupp
theorem support_toFinsupp (p : R[X]) : p.toFinsupp.support = p.support := by rw [support]
@[simp]
theorem support_zero : (0 : R[X]).support = ∅ :=
rfl
#align polynomial.support_zero Polynomial.support_zero
@[simp]
theorem support_eq_empty : p.support = ∅ ↔ p = 0 := by
rcases p with ⟨⟩
simp [support]
#align polynomial.support_eq_empty Polynomial.support_eq_empty
@[simp] lemma support_nonempty : p.support.Nonempty ↔ p ≠ 0 :=
Finset.nonempty_iff_ne_empty.trans support_eq_empty.not
theorem card_support_eq_zero : p.support.card = 0 ↔ p = 0 := by simp
#align polynomial.card_support_eq_zero Polynomial.card_support_eq_zero
/-- `monomial s a` is the monomial `a * X^s` -/
def monomial (n : ℕ) : R →ₗ[R] R[X] where
toFun t := ⟨Finsupp.single n t⟩
-- porting note (#10745): was `simp`.
map_add' x y := by simp; rw [ofFinsupp_add]
-- porting note (#10745): was `simp [← ofFinsupp_smul]`.
map_smul' r x := by simp; rw [← ofFinsupp_smul, smul_single']
#align polynomial.monomial Polynomial.monomial
@[simp]
theorem toFinsupp_monomial (n : ℕ) (r : R) : (monomial n r).toFinsupp = Finsupp.single n r := by
simp [monomial]
#align polynomial.to_finsupp_monomial Polynomial.toFinsupp_monomial
@[simp]
theorem ofFinsupp_single (n : ℕ) (r : R) : (⟨Finsupp.single n r⟩ : R[X]) = monomial n r := by
simp [monomial]
#align polynomial.of_finsupp_single Polynomial.ofFinsupp_single
-- @[simp] -- Porting note (#10618): simp can prove this
theorem monomial_zero_right (n : ℕ) : monomial n (0 : R) = 0 :=
(monomial n).map_zero
#align polynomial.monomial_zero_right Polynomial.monomial_zero_right
-- This is not a `simp` lemma as `monomial_zero_left` is more general.
theorem monomial_zero_one : monomial 0 (1 : R) = 1 :=
rfl
#align polynomial.monomial_zero_one Polynomial.monomial_zero_one
-- TODO: can't we just delete this one?
theorem monomial_add (n : ℕ) (r s : R) : monomial n (r + s) = monomial n r + monomial n s :=
(monomial n).map_add _ _
#align polynomial.monomial_add Polynomial.monomial_add
theorem monomial_mul_monomial (n m : ℕ) (r s : R) :
monomial n r * monomial m s = monomial (n + m) (r * s) :=
toFinsupp_injective <| by
simp only [toFinsupp_monomial, toFinsupp_mul, AddMonoidAlgebra.single_mul_single]
#align polynomial.monomial_mul_monomial Polynomial.monomial_mul_monomial
@[simp]
theorem monomial_pow (n : ℕ) (r : R) (k : ℕ) : monomial n r ^ k = monomial (n * k) (r ^ k) := by
induction' k with k ih
· simp [pow_zero, monomial_zero_one]
· simp [pow_succ, ih, monomial_mul_monomial, Nat.succ_eq_add_one, mul_add, add_comm]
#align polynomial.monomial_pow Polynomial.monomial_pow
theorem smul_monomial {S} [SMulZeroClass S R] (a : S) (n : ℕ) (b : R) :
a • monomial n b = monomial n (a • b) :=
toFinsupp_injective <| by simp; rw [smul_single]
#align polynomial.smul_monomial Polynomial.smul_monomial
theorem monomial_injective (n : ℕ) : Function.Injective (monomial n : R → R[X]) :=
(toFinsuppIso R).symm.injective.comp (single_injective n)
#align polynomial.monomial_injective Polynomial.monomial_injective
@[simp]
theorem monomial_eq_zero_iff (t : R) (n : ℕ) : monomial n t = 0 ↔ t = 0 :=
LinearMap.map_eq_zero_iff _ (Polynomial.monomial_injective n)
#align polynomial.monomial_eq_zero_iff Polynomial.monomial_eq_zero_iff
theorem support_add : (p + q).support ⊆ p.support ∪ q.support := by
simpa [support] using Finsupp.support_add
#align polynomial.support_add Polynomial.support_add
/-- `C a` is the constant polynomial `a`.
`C` is provided as a ring homomorphism.
-/
def C : R →+* R[X] :=
{ monomial 0 with
map_one' := by simp [monomial_zero_one]
map_mul' := by simp [monomial_mul_monomial]
map_zero' := by simp }
#align polynomial.C Polynomial.C
@[simp]
theorem monomial_zero_left (a : R) : monomial 0 a = C a :=
rfl
#align polynomial.monomial_zero_left Polynomial.monomial_zero_left
@[simp]
theorem toFinsupp_C (a : R) : (C a).toFinsupp = single 0 a :=
rfl
#align polynomial.to_finsupp_C Polynomial.toFinsupp_C
theorem C_0 : C (0 : R) = 0 := by simp
#align polynomial.C_0 Polynomial.C_0
theorem C_1 : C (1 : R) = 1 :=
rfl
#align polynomial.C_1 Polynomial.C_1
theorem C_mul : C (a * b) = C a * C b :=
C.map_mul a b
#align polynomial.C_mul Polynomial.C_mul
theorem C_add : C (a + b) = C a + C b :=
C.map_add a b
#align polynomial.C_add Polynomial.C_add
@[simp]
theorem smul_C {S} [SMulZeroClass S R] (s : S) (r : R) : s • C r = C (s • r) :=
smul_monomial _ _ r
#align polynomial.smul_C Polynomial.smul_C
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit0 : C (bit0 a) = bit0 (C a) :=
C_add
#align polynomial.C_bit0 Polynomial.C_bit0
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit1 : C (bit1 a) = bit1 (C a) := by simp [bit1, C_bit0]
#align polynomial.C_bit1 Polynomial.C_bit1
theorem C_pow : C (a ^ n) = C a ^ n :=
C.map_pow a n
#align polynomial.C_pow Polynomial.C_pow
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_eq_natCast (n : ℕ) : C (n : R) = (n : R[X]) :=
map_natCast C n
#align polynomial.C_eq_nat_cast Polynomial.C_eq_natCast
@[deprecated (since := "2024-04-17")]
alias C_eq_nat_cast := C_eq_natCast
@[simp]
theorem C_mul_monomial : C a * monomial n b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, zero_add]
#align polynomial.C_mul_monomial Polynomial.C_mul_monomial
@[simp]
theorem monomial_mul_C : monomial n a * C b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, add_zero]
#align polynomial.monomial_mul_C Polynomial.monomial_mul_C
/-- `X` is the polynomial variable (aka indeterminate). -/
def X : R[X] :=
monomial 1 1
#align polynomial.X Polynomial.X
theorem monomial_one_one_eq_X : monomial 1 (1 : R) = X :=
rfl
#align polynomial.monomial_one_one_eq_X Polynomial.monomial_one_one_eq_X
theorem monomial_one_right_eq_X_pow (n : ℕ) : monomial n (1 : R) = X ^ n := by
induction' n with n ih
· simp [monomial_zero_one]
· rw [pow_succ, ← ih, ← monomial_one_one_eq_X, monomial_mul_monomial, mul_one]
#align polynomial.monomial_one_right_eq_X_pow Polynomial.monomial_one_right_eq_X_pow
@[simp]
theorem toFinsupp_X : X.toFinsupp = Finsupp.single 1 (1 : R) :=
rfl
#align polynomial.to_finsupp_X Polynomial.toFinsupp_X
/-- `X` commutes with everything, even when the coefficients are noncommutative. -/
theorem X_mul : X * p = p * X := by
rcases p with ⟨⟩
-- Porting note: `ofFinsupp.injEq` is required.
simp only [X, ← ofFinsupp_single, ← ofFinsupp_mul, LinearMap.coe_mk, ofFinsupp.injEq]
-- Porting note: Was `ext`.
refine Finsupp.ext fun _ => ?_
simp [AddMonoidAlgebra.mul_apply, AddMonoidAlgebra.sum_single_index, add_comm]
#align polynomial.X_mul Polynomial.X_mul
theorem X_pow_mul {n : ℕ} : X ^ n * p = p * X ^ n := by
induction' n with n ih
· simp
· conv_lhs => rw [pow_succ]
rw [mul_assoc, X_mul, ← mul_assoc, ih, mul_assoc, ← pow_succ]
#align polynomial.X_pow_mul Polynomial.X_pow_mul
/-- Prefer putting constants to the left of `X`.
This lemma is the loop-avoiding `simp` version of `Polynomial.X_mul`. -/
@[simp]
theorem X_mul_C (r : R) : X * C r = C r * X :=
X_mul
#align polynomial.X_mul_C Polynomial.X_mul_C
/-- Prefer putting constants to the left of `X ^ n`.
This lemma is the loop-avoiding `simp` version of `X_pow_mul`. -/
@[simp]
theorem X_pow_mul_C (r : R) (n : ℕ) : X ^ n * C r = C r * X ^ n :=
X_pow_mul
#align polynomial.X_pow_mul_C Polynomial.X_pow_mul_C
theorem X_pow_mul_assoc {n : ℕ} : p * X ^ n * q = p * q * X ^ n := by
rw [mul_assoc, X_pow_mul, ← mul_assoc]
#align polynomial.X_pow_mul_assoc Polynomial.X_pow_mul_assoc
/-- Prefer putting constants to the left of `X ^ n`.
This lemma is the loop-avoiding `simp` version of `X_pow_mul_assoc`. -/
@[simp]
theorem X_pow_mul_assoc_C {n : ℕ} (r : R) : p * X ^ n * C r = p * C r * X ^ n :=
X_pow_mul_assoc
#align polynomial.X_pow_mul_assoc_C Polynomial.X_pow_mul_assoc_C
theorem commute_X (p : R[X]) : Commute X p :=
X_mul
#align polynomial.commute_X Polynomial.commute_X
theorem commute_X_pow (p : R[X]) (n : ℕ) : Commute (X ^ n) p :=
X_pow_mul
#align polynomial.commute_X_pow Polynomial.commute_X_pow
@[simp]
theorem monomial_mul_X (n : ℕ) (r : R) : monomial n r * X = monomial (n + 1) r := by
erw [monomial_mul_monomial, mul_one]
#align polynomial.monomial_mul_X Polynomial.monomial_mul_X
@[simp]
theorem monomial_mul_X_pow (n : ℕ) (r : R) (k : ℕ) :
monomial n r * X ^ k = monomial (n + k) r := by
induction' k with k ih
· simp
· simp [ih, pow_succ, ← mul_assoc, add_assoc, Nat.succ_eq_add_one]
#align polynomial.monomial_mul_X_pow Polynomial.monomial_mul_X_pow
@[simp]
theorem X_mul_monomial (n : ℕ) (r : R) : X * monomial n r = monomial (n + 1) r := by
rw [X_mul, monomial_mul_X]
#align polynomial.X_mul_monomial Polynomial.X_mul_monomial
@[simp]
theorem X_pow_mul_monomial (k n : ℕ) (r : R) : X ^ k * monomial n r = monomial (n + k) r := by
rw [X_pow_mul, monomial_mul_X_pow]
#align polynomial.X_pow_mul_monomial Polynomial.X_pow_mul_monomial
/-- `coeff p n` (often denoted `p.coeff n`) is the coefficient of `X^n` in `p`. -/
-- @[simp] -- Porting note: The original generated theorem is same to `coeff_ofFinsupp` and
-- the new generated theorem is different, so this attribute should be
-- removed.
def coeff : R[X] → ℕ → R
| ⟨p⟩ => p
#align polynomial.coeff Polynomial.coeff
-- Porting note (#10756): new theorem
@[simp]
theorem coeff_ofFinsupp (p) : coeff (⟨p⟩ : R[X]) = p := by rw [coeff]
theorem coeff_injective : Injective (coeff : R[X] → ℕ → R) := by
rintro ⟨p⟩ ⟨q⟩
-- Porting note: `ofFinsupp.injEq` is required.
simp only [coeff, DFunLike.coe_fn_eq, imp_self, ofFinsupp.injEq]
#align polynomial.coeff_injective Polynomial.coeff_injective
@[simp]
theorem coeff_inj : p.coeff = q.coeff ↔ p = q :=
coeff_injective.eq_iff
#align polynomial.coeff_inj Polynomial.coeff_inj
theorem toFinsupp_apply (f : R[X]) (i) : f.toFinsupp i = f.coeff i := by cases f; rfl
#align polynomial.to_finsupp_apply Polynomial.toFinsupp_apply
theorem coeff_monomial : coeff (monomial n a) m = if n = m then a else 0 := by
simp [coeff, Finsupp.single_apply]
#align polynomial.coeff_monomial Polynomial.coeff_monomial
@[simp]
theorem coeff_zero (n : ℕ) : coeff (0 : R[X]) n = 0 :=
rfl
#align polynomial.coeff_zero Polynomial.coeff_zero
theorem coeff_one {n : ℕ} : coeff (1 : R[X]) n = if n = 0 then 1 else 0 := by
simp_rw [eq_comm (a := n) (b := 0)]
exact coeff_monomial
#align polynomial.coeff_one Polynomial.coeff_one
@[simp]
theorem coeff_one_zero : coeff (1 : R[X]) 0 = 1 := by
simp [coeff_one]
#align polynomial.coeff_one_zero Polynomial.coeff_one_zero
@[simp]
theorem coeff_X_one : coeff (X : R[X]) 1 = 1 :=
coeff_monomial
#align polynomial.coeff_X_one Polynomial.coeff_X_one
@[simp]
theorem coeff_X_zero : coeff (X : R[X]) 0 = 0 :=
coeff_monomial
#align polynomial.coeff_X_zero Polynomial.coeff_X_zero
@[simp]
theorem coeff_monomial_succ : coeff (monomial (n + 1) a) 0 = 0 := by simp [coeff_monomial]
#align polynomial.coeff_monomial_succ Polynomial.coeff_monomial_succ
theorem coeff_X : coeff (X : R[X]) n = if 1 = n then 1 else 0 :=
coeff_monomial
#align polynomial.coeff_X Polynomial.coeff_X
theorem coeff_X_of_ne_one {n : ℕ} (hn : n ≠ 1) : coeff (X : R[X]) n = 0 := by
rw [coeff_X, if_neg hn.symm]
#align polynomial.coeff_X_of_ne_one Polynomial.coeff_X_of_ne_one
@[simp]
| Mathlib/Algebra/Polynomial/Basic.lean | 735 | 737 | theorem mem_support_iff : n ∈ p.support ↔ p.coeff n ≠ 0 := by |
rcases p with ⟨⟩
simp
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Finsupp.Encodable
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Span
import Mathlib.Data.Set.Countable
#align_import linear_algebra.finsupp from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Properties of the module `α →₀ M`
Given an `R`-module `M`, the `R`-module structure on `α →₀ M` is defined in
`Data.Finsupp.Basic`.
In this file we define `Finsupp.supported s` to be the set `{f : α →₀ M | f.support ⊆ s}`
interpreted as a submodule of `α →₀ M`. We also define `LinearMap` versions of various maps:
* `Finsupp.lsingle a : M →ₗ[R] ι →₀ M`: `Finsupp.single a` as a linear map;
* `Finsupp.lapply a : (ι →₀ M) →ₗ[R] M`: the map `fun f ↦ f a` as a linear map;
* `Finsupp.lsubtypeDomain (s : Set α) : (α →₀ M) →ₗ[R] (s →₀ M)`: restriction to a subtype as a
linear map;
* `Finsupp.restrictDom`: `Finsupp.filter` as a linear map to `Finsupp.supported s`;
* `Finsupp.lsum`: `Finsupp.sum` or `Finsupp.liftAddHom` as a `LinearMap`;
* `Finsupp.total α M R (v : ι → M)`: sends `l : ι → R` to the linear combination of `v i` with
coefficients `l i`;
* `Finsupp.totalOn`: a restricted version of `Finsupp.total` with domain `Finsupp.supported R R s`
and codomain `Submodule.span R (v '' s)`;
* `Finsupp.supportedEquivFinsupp`: a linear equivalence between the functions `α →₀ M` supported
on `s` and the functions `s →₀ M`;
* `Finsupp.lmapDomain`: a linear map version of `Finsupp.mapDomain`;
* `Finsupp.domLCongr`: a `LinearEquiv` version of `Finsupp.domCongr`;
* `Finsupp.congr`: if the sets `s` and `t` are equivalent, then `supported M R s` is equivalent to
`supported M R t`;
* `Finsupp.lcongr`: a `LinearEquiv`alence between `α →₀ M` and `β →₀ N` constructed using
`e : α ≃ β` and `e' : M ≃ₗ[R] N`.
## Tags
function with finite support, module, linear algebra
-/
noncomputable section
open Set LinearMap Submodule
namespace Finsupp
section SMul
variable {α : Type*} {β : Type*} {R : Type*} {M : Type*} {M₂ : Type*}
theorem smul_sum [Zero β] [AddCommMonoid M] [DistribSMul R M] {v : α →₀ β} {c : R} {h : α → β → M} :
c • v.sum h = v.sum fun a b => c • h a b :=
Finset.smul_sum
#align finsupp.smul_sum Finsupp.smul_sum
@[simp]
theorem sum_smul_index_linearMap' [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂]
[Module R M₂] {v : α →₀ M} {c : R} {h : α → M →ₗ[R] M₂} :
((c • v).sum fun a => h a) = c • v.sum fun a => h a := by
rw [Finsupp.sum_smul_index', Finsupp.smul_sum]
· simp only [map_smul]
· intro i
exact (h i).map_zero
#align finsupp.sum_smul_index_linear_map' Finsupp.sum_smul_index_linearMap'
end SMul
section LinearEquivFunOnFinite
variable (R : Type*) {S : Type*} (M : Type*) (α : Type*)
variable [Finite α] [AddCommMonoid M] [Semiring R] [Module R M]
/-- Given `Finite α`, `linearEquivFunOnFinite R` is the natural `R`-linear equivalence between
`α →₀ β` and `α → β`. -/
@[simps apply]
noncomputable def linearEquivFunOnFinite : (α →₀ M) ≃ₗ[R] α → M :=
{ equivFunOnFinite with
toFun := (⇑)
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv_fun_on_finite Finsupp.linearEquivFunOnFinite
@[simp]
theorem linearEquivFunOnFinite_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α) (single x m) = Pi.single x m :=
equivFunOnFinite_single x m
#align finsupp.linear_equiv_fun_on_finite_single Finsupp.linearEquivFunOnFinite_single
@[simp]
theorem linearEquivFunOnFinite_symm_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α).symm (Pi.single x m) = single x m :=
equivFunOnFinite_symm_single x m
#align finsupp.linear_equiv_fun_on_finite_symm_single Finsupp.linearEquivFunOnFinite_symm_single
@[simp]
theorem linearEquivFunOnFinite_symm_coe (f : α →₀ M) : (linearEquivFunOnFinite R M α).symm f = f :=
(linearEquivFunOnFinite R M α).symm_apply_apply f
#align finsupp.linear_equiv_fun_on_finite_symm_coe Finsupp.linearEquivFunOnFinite_symm_coe
end LinearEquivFunOnFinite
section LinearEquiv.finsuppUnique
variable (R : Type*) {S : Type*} (M : Type*)
variable [AddCommMonoid M] [Semiring R] [Module R M]
variable (α : Type*) [Unique α]
/-- If `α` has a unique term, then the type of finitely supported functions `α →₀ M` is
`R`-linearly equivalent to `M`. -/
noncomputable def LinearEquiv.finsuppUnique : (α →₀ M) ≃ₗ[R] M :=
{ Finsupp.equivFunOnFinite.trans (Equiv.funUnique α M) with
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv.finsupp_unique Finsupp.LinearEquiv.finsuppUnique
variable {R M}
@[simp]
theorem LinearEquiv.finsuppUnique_apply (f : α →₀ M) :
LinearEquiv.finsuppUnique R M α f = f default :=
rfl
#align finsupp.linear_equiv.finsupp_unique_apply Finsupp.LinearEquiv.finsuppUnique_apply
variable {α}
@[simp]
theorem LinearEquiv.finsuppUnique_symm_apply [Unique α] (m : M) :
(LinearEquiv.finsuppUnique R M α).symm m = Finsupp.single default m := by
ext; simp [LinearEquiv.finsuppUnique, Equiv.funUnique, single, Pi.single,
equivFunOnFinite, Function.update]
#align finsupp.linear_equiv.finsupp_unique_symm_apply Finsupp.LinearEquiv.finsuppUnique_symm_apply
end LinearEquiv.finsuppUnique
variable {α : Type*} {M : Type*} {N : Type*} {P : Type*} {R : Type*} {S : Type*}
variable [Semiring R] [Semiring S] [AddCommMonoid M] [Module R M]
variable [AddCommMonoid N] [Module R N]
variable [AddCommMonoid P] [Module R P]
/-- Interpret `Finsupp.single a` as a linear map. -/
def lsingle (a : α) : M →ₗ[R] α →₀ M :=
{ Finsupp.singleAddHom a with map_smul' := fun _ _ => (smul_single _ _ _).symm }
#align finsupp.lsingle Finsupp.lsingle
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a b, φ (single a b) = ψ (single a b)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align finsupp.lhom_ext Finsupp.lhom_ext
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere.
We formulate this fact using equality of linear maps `φ.comp (lsingle a)` and `ψ.comp (lsingle a)`
so that the `ext` tactic can apply a type-specific extensionality lemma to prove equality of these
maps. E.g., if `M = R`, then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
-- Porting note: The priority should be higher than `LinearMap.ext`.
@[ext high]
theorem lhom_ext' ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a, φ.comp (lsingle a) = ψ.comp (lsingle a)) :
φ = ψ :=
lhom_ext fun a => LinearMap.congr_fun (h a)
#align finsupp.lhom_ext' Finsupp.lhom_ext'
/-- Interpret `fun f : α →₀ M ↦ f a` as a linear map. -/
def lapply (a : α) : (α →₀ M) →ₗ[R] M :=
{ Finsupp.applyAddHom a with map_smul' := fun _ _ => rfl }
#align finsupp.lapply Finsupp.lapply
section CompatibleSMul
variable (R S M N ι : Type*)
variable [Semiring S] [AddCommMonoid M] [AddCommMonoid N] [Module S M] [Module S N]
instance _root_.LinearMap.CompatibleSMul.finsupp_dom [SMulZeroClass R M] [DistribSMul R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul (ι →₀ M) N R S where
map_smul f r m := by
conv_rhs => rw [← sum_single m, map_finsupp_sum, smul_sum]
erw [← sum_single (r • m), sum_mapRange_index single_zero, map_finsupp_sum]
congr; ext i m; exact (f.comp <| lsingle i).map_smul_of_tower r m
instance _root_.LinearMap.CompatibleSMul.finsupp_cod [SMul R M] [SMulZeroClass R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul M (ι →₀ N) R S where
map_smul f r m := by ext i; apply ((lapply i).comp f).map_smul_of_tower
end CompatibleSMul
/-- Forget that a function is finitely supported.
This is the linear version of `Finsupp.toFun`. -/
@[simps]
def lcoeFun : (α →₀ M) →ₗ[R] α → M where
toFun := (⇑)
map_add' x y := by
ext
simp
map_smul' x y := by
ext
simp
#align finsupp.lcoe_fun Finsupp.lcoeFun
section LSubtypeDomain
variable (s : Set α)
/-- Interpret `Finsupp.subtypeDomain s` as a linear map. -/
def lsubtypeDomain : (α →₀ M) →ₗ[R] s →₀ M where
toFun := subtypeDomain fun x => x ∈ s
map_add' _ _ := subtypeDomain_add
map_smul' _ _ := ext fun _ => rfl
#align finsupp.lsubtype_domain Finsupp.lsubtypeDomain
theorem lsubtypeDomain_apply (f : α →₀ M) :
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M) f = subtypeDomain (fun x => x ∈ s) f :=
rfl
#align finsupp.lsubtype_domain_apply Finsupp.lsubtypeDomain_apply
end LSubtypeDomain
@[simp]
theorem lsingle_apply (a : α) (b : M) : (lsingle a : M →ₗ[R] α →₀ M) b = single a b :=
rfl
#align finsupp.lsingle_apply Finsupp.lsingle_apply
@[simp]
theorem lapply_apply (a : α) (f : α →₀ M) : (lapply a : (α →₀ M) →ₗ[R] M) f = f a :=
rfl
#align finsupp.lapply_apply Finsupp.lapply_apply
@[simp]
theorem lapply_comp_lsingle_same (a : α) : lapply a ∘ₗ lsingle a = (.id : M →ₗ[R] M) := by ext; simp
@[simp]
theorem lapply_comp_lsingle_of_ne (a a' : α) (h : a ≠ a') :
lapply a ∘ₗ lsingle a' = (0 : M →ₗ[R] M) := by ext; simp [h.symm]
@[simp]
theorem ker_lsingle (a : α) : ker (lsingle a : M →ₗ[R] α →₀ M) = ⊥ :=
ker_eq_bot_of_injective (single_injective a)
#align finsupp.ker_lsingle Finsupp.ker_lsingle
theorem lsingle_range_le_ker_lapply (s t : Set α) (h : Disjoint s t) :
⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) ≤
⨅ a ∈ t, ker (lapply a : (α →₀ M) →ₗ[R] M) := by
refine iSup_le fun a₁ => iSup_le fun h₁ => range_le_iff_comap.2 ?_
simp only [(ker_comp _ _).symm, eq_top_iff, SetLike.le_def, mem_ker, comap_iInf, mem_iInf]
intro b _ a₂ h₂
have : a₁ ≠ a₂ := fun eq => h.le_bot ⟨h₁, eq.symm ▸ h₂⟩
exact single_eq_of_ne this
#align finsupp.lsingle_range_le_ker_lapply Finsupp.lsingle_range_le_ker_lapply
theorem iInf_ker_lapply_le_bot : ⨅ a, ker (lapply a : (α →₀ M) →ₗ[R] M) ≤ ⊥ := by
simp only [SetLike.le_def, mem_iInf, mem_ker, mem_bot, lapply_apply]
exact fun a h => Finsupp.ext h
#align finsupp.infi_ker_lapply_le_bot Finsupp.iInf_ker_lapply_le_bot
theorem iSup_lsingle_range : ⨆ a, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) = ⊤ := by
refine eq_top_iff.2 <| SetLike.le_def.2 fun f _ => ?_
rw [← sum_single f]
exact sum_mem fun a _ => Submodule.mem_iSup_of_mem a ⟨_, rfl⟩
#align finsupp.supr_lsingle_range Finsupp.iSup_lsingle_range
theorem disjoint_lsingle_lsingle (s t : Set α) (hs : Disjoint s t) :
Disjoint (⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M))
(⨆ a ∈ t, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M)) := by
-- Porting note: 2 placeholders are added to prevent timeout.
refine
(Disjoint.mono
(lsingle_range_le_ker_lapply s sᶜ ?_)
(lsingle_range_le_ker_lapply t tᶜ ?_))
?_
· apply disjoint_compl_right
· apply disjoint_compl_right
rw [disjoint_iff_inf_le]
refine le_trans (le_iInf fun i => ?_) iInf_ker_lapply_le_bot
classical
by_cases his : i ∈ s
· by_cases hit : i ∈ t
· exact (hs.le_bot ⟨his, hit⟩).elim
exact inf_le_of_right_le (iInf_le_of_le i <| iInf_le _ hit)
exact inf_le_of_left_le (iInf_le_of_le i <| iInf_le _ his)
#align finsupp.disjoint_lsingle_lsingle Finsupp.disjoint_lsingle_lsingle
theorem span_single_image (s : Set M) (a : α) :
Submodule.span R (single a '' s) = (Submodule.span R s).map (lsingle a : M →ₗ[R] α →₀ M) := by
rw [← span_image]; rfl
#align finsupp.span_single_image Finsupp.span_single_image
variable (M R)
/-- `Finsupp.supported M R s` is the `R`-submodule of all `p : α →₀ M` such that `p.support ⊆ s`. -/
def supported (s : Set α) : Submodule R (α →₀ M) where
carrier := { p | ↑p.support ⊆ s }
add_mem' {p q} hp hq := by
classical
refine Subset.trans (Subset.trans (Finset.coe_subset.2 support_add) ?_) (union_subset hp hq)
rw [Finset.coe_union]
zero_mem' := by
simp only [subset_def, Finset.mem_coe, Set.mem_setOf_eq, mem_support_iff, zero_apply]
intro h ha
exact (ha rfl).elim
smul_mem' a p hp := Subset.trans (Finset.coe_subset.2 support_smul) hp
#align finsupp.supported Finsupp.supported
variable {M}
theorem mem_supported {s : Set α} (p : α →₀ M) : p ∈ supported M R s ↔ ↑p.support ⊆ s :=
Iff.rfl
#align finsupp.mem_supported Finsupp.mem_supported
theorem mem_supported' {s : Set α} (p : α →₀ M) :
p ∈ supported M R s ↔ ∀ x ∉ s, p x = 0 := by
haveI := Classical.decPred fun x : α => x ∈ s; simp [mem_supported, Set.subset_def, not_imp_comm]
#align finsupp.mem_supported' Finsupp.mem_supported'
theorem mem_supported_support (p : α →₀ M) : p ∈ Finsupp.supported M R (p.support : Set α) := by
rw [Finsupp.mem_supported]
#align finsupp.mem_supported_support Finsupp.mem_supported_support
theorem single_mem_supported {s : Set α} {a : α} (b : M) (h : a ∈ s) :
single a b ∈ supported M R s :=
Set.Subset.trans support_single_subset (Finset.singleton_subset_set_iff.2 h)
#align finsupp.single_mem_supported Finsupp.single_mem_supported
theorem supported_eq_span_single (s : Set α) :
supported R R s = span R ((fun i => single i 1) '' s) := by
refine (span_eq_of_le _ ?_ (SetLike.le_def.2 fun l hl => ?_)).symm
· rintro _ ⟨_, hp, rfl⟩
exact single_mem_supported R 1 hp
· rw [← l.sum_single]
refine sum_mem fun i il => ?_
-- Porting note: Needed to help this convert quite a bit replacing underscores
convert smul_mem (M := α →₀ R) (x := single i 1) (span R ((fun i => single i 1) '' s)) (l i) ?_
· simp [span]
· apply subset_span
apply Set.mem_image_of_mem _ (hl il)
#align finsupp.supported_eq_span_single Finsupp.supported_eq_span_single
variable (M)
/-- Interpret `Finsupp.filter s` as a linear map from `α →₀ M` to `supported M R s`. -/
def restrictDom (s : Set α) [DecidablePred (· ∈ s)] : (α →₀ M) →ₗ[R] supported M R s :=
LinearMap.codRestrict _
{ toFun := filter (· ∈ s)
map_add' := fun _ _ => filter_add
map_smul' := fun _ _ => filter_smul } fun l =>
(mem_supported' _ _).2 fun _ => filter_apply_neg (· ∈ s) l
#align finsupp.restrict_dom Finsupp.restrictDom
variable {M R}
section
@[simp]
theorem restrictDom_apply (s : Set α) (l : α →₀ M) [DecidablePred (· ∈ s)]:
(restrictDom M R s l : α →₀ M) = Finsupp.filter (· ∈ s) l := rfl
#align finsupp.restrict_dom_apply Finsupp.restrictDom_apply
end
theorem restrictDom_comp_subtype (s : Set α) [DecidablePred (· ∈ s)] :
(restrictDom M R s).comp (Submodule.subtype _) = LinearMap.id := by
ext l a
by_cases h : a ∈ s <;> simp [h]
exact ((mem_supported' R l.1).1 l.2 a h).symm
#align finsupp.restrict_dom_comp_subtype Finsupp.restrictDom_comp_subtype
theorem range_restrictDom (s : Set α) [DecidablePred (· ∈ s)] :
LinearMap.range (restrictDom M R s) = ⊤ :=
range_eq_top.2 <|
Function.RightInverse.surjective <| LinearMap.congr_fun (restrictDom_comp_subtype s)
#align finsupp.range_restrict_dom Finsupp.range_restrictDom
theorem supported_mono {s t : Set α} (st : s ⊆ t) : supported M R s ≤ supported M R t := fun _ h =>
Set.Subset.trans h st
#align finsupp.supported_mono Finsupp.supported_mono
@[simp]
theorem supported_empty : supported M R (∅ : Set α) = ⊥ :=
eq_bot_iff.2 fun l h => (Submodule.mem_bot R).2 <| by ext; simp_all [mem_supported']
#align finsupp.supported_empty Finsupp.supported_empty
@[simp]
theorem supported_univ : supported M R (Set.univ : Set α) = ⊤ :=
eq_top_iff.2 fun _ _ => Set.subset_univ _
#align finsupp.supported_univ Finsupp.supported_univ
theorem supported_iUnion {δ : Type*} (s : δ → Set α) :
supported M R (⋃ i, s i) = ⨆ i, supported M R (s i) := by
refine le_antisymm ?_ (iSup_le fun i => supported_mono <| Set.subset_iUnion _ _)
haveI := Classical.decPred fun x => x ∈ ⋃ i, s i
suffices
LinearMap.range ((Submodule.subtype _).comp (restrictDom M R (⋃ i, s i))) ≤
⨆ i, supported M R (s i) by
rwa [LinearMap.range_comp, range_restrictDom, Submodule.map_top, range_subtype] at this
rw [range_le_iff_comap, eq_top_iff]
rintro l ⟨⟩
-- Porting note: Was ported as `induction l using Finsupp.induction`
refine Finsupp.induction l ?_ ?_
· exact zero_mem _
· refine fun x a l _ _ => add_mem ?_
by_cases h : ∃ i, x ∈ s i <;> simp [h]
cases' h with i hi
exact le_iSup (fun i => supported M R (s i)) i (single_mem_supported R _ hi)
#align finsupp.supported_Union Finsupp.supported_iUnion
theorem supported_union (s t : Set α) :
supported M R (s ∪ t) = supported M R s ⊔ supported M R t := by
erw [Set.union_eq_iUnion, supported_iUnion, iSup_bool_eq]; rfl
#align finsupp.supported_union Finsupp.supported_union
theorem supported_iInter {ι : Type*} (s : ι → Set α) :
supported M R (⋂ i, s i) = ⨅ i, supported M R (s i) :=
Submodule.ext fun x => by simp [mem_supported, subset_iInter_iff]
#align finsupp.supported_Inter Finsupp.supported_iInter
theorem supported_inter (s t : Set α) :
supported M R (s ∩ t) = supported M R s ⊓ supported M R t := by
rw [Set.inter_eq_iInter, supported_iInter, iInf_bool_eq]; rfl
#align finsupp.supported_inter Finsupp.supported_inter
theorem disjoint_supported_supported {s t : Set α} (h : Disjoint s t) :
Disjoint (supported M R s) (supported M R t) :=
disjoint_iff.2 <| by rw [← supported_inter, disjoint_iff_inter_eq_empty.1 h, supported_empty]
#align finsupp.disjoint_supported_supported Finsupp.disjoint_supported_supported
theorem disjoint_supported_supported_iff [Nontrivial M] {s t : Set α} :
Disjoint (supported M R s) (supported M R t) ↔ Disjoint s t := by
refine ⟨fun h => Set.disjoint_left.mpr fun x hx1 hx2 => ?_, disjoint_supported_supported⟩
rcases exists_ne (0 : M) with ⟨y, hy⟩
have := h.le_bot ⟨single_mem_supported R y hx1, single_mem_supported R y hx2⟩
rw [mem_bot, single_eq_zero] at this
exact hy this
#align finsupp.disjoint_supported_supported_iff Finsupp.disjoint_supported_supported_iff
/-- Interpret `Finsupp.restrictSupportEquiv` as a linear equivalence between
`supported M R s` and `s →₀ M`. -/
def supportedEquivFinsupp (s : Set α) : supported M R s ≃ₗ[R] s →₀ M := by
let F : supported M R s ≃ (s →₀ M) := restrictSupportEquiv s M
refine F.toLinearEquiv ?_
have :
(F : supported M R s → ↥s →₀ M) =
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M).comp (Submodule.subtype (supported M R s)) :=
rfl
rw [this]
exact LinearMap.isLinear _
#align finsupp.supported_equiv_finsupp Finsupp.supportedEquivFinsupp
section LSum
variable (S)
variable [Module S N] [SMulCommClass R S N]
/-- Lift a family of linear maps `M →ₗ[R] N` indexed by `x : α` to a linear map from `α →₀ M` to
`N` using `Finsupp.sum`. This is an upgraded version of `Finsupp.liftAddHom`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used.
-/
def lsum : (α → M →ₗ[R] N) ≃ₗ[S] (α →₀ M) →ₗ[R] N where
toFun F :=
{ toFun := fun d => d.sum fun i => F i
map_add' := (liftAddHom (α := α) (M := M) (N := N) fun x => (F x).toAddMonoidHom).map_add
map_smul' := fun c f => by simp [sum_smul_index', smul_sum] }
invFun F x := F.comp (lsingle x)
left_inv F := by
ext x y
simp
right_inv F := by
ext x y
simp
map_add' F G := by
ext x y
simp
map_smul' F G := by
ext x y
simp
#align finsupp.lsum Finsupp.lsum
@[simp]
theorem coe_lsum (f : α → M →ₗ[R] N) : (lsum S f : (α →₀ M) → N) = fun d => d.sum fun i => f i :=
rfl
#align finsupp.coe_lsum Finsupp.coe_lsum
theorem lsum_apply (f : α → M →ₗ[R] N) (l : α →₀ M) : Finsupp.lsum S f l = l.sum fun b => f b :=
rfl
#align finsupp.lsum_apply Finsupp.lsum_apply
theorem lsum_single (f : α → M →ₗ[R] N) (i : α) (m : M) :
Finsupp.lsum S f (Finsupp.single i m) = f i m :=
Finsupp.sum_single_index (f i).map_zero
#align finsupp.lsum_single Finsupp.lsum_single
@[simp] theorem lsum_comp_lsingle (f : α → M →ₗ[R] N) (i : α) :
Finsupp.lsum S f ∘ₗ lsingle i = f i := by ext; simp
theorem lsum_symm_apply (f : (α →₀ M) →ₗ[R] N) (x : α) : (lsum S).symm f x = f.comp (lsingle x) :=
rfl
#align finsupp.lsum_symm_apply Finsupp.lsum_symm_apply
end LSum
section
variable (M) (R) (X : Type*) (S)
variable [Module S M] [SMulCommClass R S M]
/-- A slight rearrangement from `lsum` gives us
the bijection underlying the free-forgetful adjunction for R-modules.
-/
noncomputable def lift : (X → M) ≃+ ((X →₀ R) →ₗ[R] M) :=
(AddEquiv.arrowCongr (Equiv.refl X) (ringLmapEquivSelf R ℕ M).toAddEquiv.symm).trans
(lsum _ : _ ≃ₗ[ℕ] _).toAddEquiv
#align finsupp.lift Finsupp.lift
@[simp]
theorem lift_symm_apply (f) (x) : ((lift M R X).symm f) x = f (single x 1) :=
rfl
#align finsupp.lift_symm_apply Finsupp.lift_symm_apply
@[simp]
theorem lift_apply (f) (g) : ((lift M R X) f) g = g.sum fun x r => r • f x :=
rfl
#align finsupp.lift_apply Finsupp.lift_apply
/-- Given compatible `S` and `R`-module structures on `M` and a type `X`, the set of functions
`X → M` is `S`-linearly equivalent to the `R`-linear maps from the free `R`-module
on `X` to `M`. -/
noncomputable def llift : (X → M) ≃ₗ[S] (X →₀ R) →ₗ[R] M :=
{ lift M R X with
map_smul' := by
intros
dsimp
ext
simp only [coe_comp, Function.comp_apply, lsingle_apply, lift_apply, Pi.smul_apply,
sum_single_index, zero_smul, one_smul, LinearMap.smul_apply] }
#align finsupp.llift Finsupp.llift
@[simp]
theorem llift_apply (f : X → M) (x : X →₀ R) : llift M R S X f x = lift M R X f x :=
rfl
#align finsupp.llift_apply Finsupp.llift_apply
@[simp]
theorem llift_symm_apply (f : (X →₀ R) →ₗ[R] M) (x : X) :
(llift M R S X).symm f x = f (single x 1) :=
rfl
#align finsupp.llift_symm_apply Finsupp.llift_symm_apply
end
section LMapDomain
variable {α' : Type*} {α'' : Type*} (M R)
/-- Interpret `Finsupp.mapDomain` as a linear map. -/
def lmapDomain (f : α → α') : (α →₀ M) →ₗ[R] α' →₀ M where
toFun := mapDomain f
map_add' _ _ := mapDomain_add
map_smul' := mapDomain_smul
#align finsupp.lmap_domain Finsupp.lmapDomain
@[simp]
theorem lmapDomain_apply (f : α → α') (l : α →₀ M) :
(lmapDomain M R f : (α →₀ M) →ₗ[R] α' →₀ M) l = mapDomain f l :=
rfl
#align finsupp.lmap_domain_apply Finsupp.lmapDomain_apply
@[simp]
theorem lmapDomain_id : (lmapDomain M R _root_.id : (α →₀ M) →ₗ[R] α →₀ M) = LinearMap.id :=
LinearMap.ext fun _ => mapDomain_id
#align finsupp.lmap_domain_id Finsupp.lmapDomain_id
theorem lmapDomain_comp (f : α → α') (g : α' → α'') :
lmapDomain M R (g ∘ f) = (lmapDomain M R g).comp (lmapDomain M R f) :=
LinearMap.ext fun _ => mapDomain_comp
#align finsupp.lmap_domain_comp Finsupp.lmapDomain_comp
theorem supported_comap_lmapDomain (f : α → α') (s : Set α') :
supported M R (f ⁻¹' s) ≤ (supported M R s).comap (lmapDomain M R f) := by
classical
intro l (hl : (l.support : Set α) ⊆ f ⁻¹' s)
show ↑(mapDomain f l).support ⊆ s
rw [← Set.image_subset_iff, ← Finset.coe_image] at hl
exact Set.Subset.trans mapDomain_support hl
#align finsupp.supported_comap_lmap_domain Finsupp.supported_comap_lmapDomain
theorem lmapDomain_supported (f : α → α') (s : Set α) :
(supported M R s).map (lmapDomain M R f) = supported M R (f '' s) := by
classical
cases isEmpty_or_nonempty α
· simp [s.eq_empty_of_isEmpty]
refine
le_antisymm
(map_le_iff_le_comap.2 <|
le_trans (supported_mono <| Set.subset_preimage_image _ _)
(supported_comap_lmapDomain M R _ _))
?_
intro l hl
refine ⟨(lmapDomain M R (Function.invFunOn f s) : (α' →₀ M) →ₗ[R] α →₀ M) l, fun x hx => ?_, ?_⟩
· rcases Finset.mem_image.1 (mapDomain_support hx) with ⟨c, hc, rfl⟩
exact Function.invFunOn_mem (by simpa using hl hc)
· rw [← LinearMap.comp_apply, ← lmapDomain_comp]
refine (mapDomain_congr fun c hc => ?_).trans mapDomain_id
exact Function.invFunOn_eq (by simpa using hl hc)
#align finsupp.lmap_domain_supported Finsupp.lmapDomain_supported
theorem lmapDomain_disjoint_ker (f : α → α') {s : Set α}
(H : ∀ a ∈ s, ∀ b ∈ s, f a = f b → a = b) :
Disjoint (supported M R s) (ker (lmapDomain M R f)) := by
rw [disjoint_iff_inf_le]
rintro l ⟨h₁, h₂⟩
rw [SetLike.mem_coe, mem_ker, lmapDomain_apply, mapDomain] at h₂
simp; ext x
haveI := Classical.decPred fun x => x ∈ s
by_cases xs : x ∈ s
· have : Finsupp.sum l (fun a => Finsupp.single (f a)) (f x) = 0 := by
rw [h₂]
rfl
rw [Finsupp.sum_apply, Finsupp.sum_eq_single x, single_eq_same] at this
· simpa
· intro y hy xy
simp only [SetLike.mem_coe, mem_supported, subset_def, Finset.mem_coe, mem_support_iff] at h₁
simp [mt (H _ (h₁ _ hy) _ xs) xy]
· simp (config := { contextual := true })
· by_contra h
exact xs (h₁ <| Finsupp.mem_support_iff.2 h)
#align finsupp.lmap_domain_disjoint_ker Finsupp.lmapDomain_disjoint_ker
end LMapDomain
section LComapDomain
variable {β : Type*}
/-- Given `f : α → β` and a proof `hf` that `f` is injective, `lcomapDomain f hf` is the linear map
sending `l : β →₀ M` to the finitely supported function from `α` to `M` given by composing
`l` with `f`.
This is the linear version of `Finsupp.comapDomain`. -/
def lcomapDomain (f : α → β) (hf : Function.Injective f) : (β →₀ M) →ₗ[R] α →₀ M where
toFun l := Finsupp.comapDomain f l hf.injOn
map_add' x y := by ext; simp
map_smul' c x := by ext; simp
#align finsupp.lcomap_domain Finsupp.lcomapDomain
end LComapDomain
section Total
variable (α) (M) (R)
variable {α' : Type*} {M' : Type*} [AddCommMonoid M'] [Module R M'] (v : α → M) {v' : α' → M'}
/-- Interprets (l : α →₀ R) as linear combination of the elements in the family (v : α → M) and
evaluates this linear combination. -/
protected def total : (α →₀ R) →ₗ[R] M :=
Finsupp.lsum ℕ fun i => LinearMap.id.smulRight (v i)
#align finsupp.total Finsupp.total
variable {α M v}
theorem total_apply (l : α →₀ R) : Finsupp.total α M R v l = l.sum fun i a => a • v i :=
rfl
#align finsupp.total_apply Finsupp.total_apply
theorem total_apply_of_mem_supported {l : α →₀ R} {s : Finset α}
(hs : l ∈ supported R R (↑s : Set α)) : Finsupp.total α M R v l = s.sum fun i => l i • v i :=
Finset.sum_subset hs fun x _ hxg =>
show l x • v x = 0 by rw [not_mem_support_iff.1 hxg, zero_smul]
#align finsupp.total_apply_of_mem_supported Finsupp.total_apply_of_mem_supported
@[simp]
theorem total_single (c : R) (a : α) : Finsupp.total α M R v (single a c) = c • v a := by
simp [total_apply, sum_single_index]
#align finsupp.total_single Finsupp.total_single
theorem total_zero_apply (x : α →₀ R) : (Finsupp.total α M R 0) x = 0 := by
simp [Finsupp.total_apply]
#align finsupp.total_zero_apply Finsupp.total_zero_apply
variable (α M)
@[simp]
theorem total_zero : Finsupp.total α M R 0 = 0 :=
LinearMap.ext (total_zero_apply R)
#align finsupp.total_zero Finsupp.total_zero
variable {α M}
theorem apply_total (f : M →ₗ[R] M') (v) (l : α →₀ R) :
f (Finsupp.total α M R v l) = Finsupp.total α M' R (f ∘ v) l := by
apply Finsupp.induction_linear l <;> simp (config := { contextual := true })
#align finsupp.apply_total Finsupp.apply_total
theorem apply_total_id (f : M →ₗ[R] M') (l : M →₀ R) :
f (Finsupp.total M M R _root_.id l) = Finsupp.total M M' R f l :=
apply_total ..
theorem total_unique [Unique α] (l : α →₀ R) (v) :
Finsupp.total α M R v l = l default • v default := by rw [← total_single, ← unique_single l]
#align finsupp.total_unique Finsupp.total_unique
theorem total_surjective (h : Function.Surjective v) :
Function.Surjective (Finsupp.total α M R v) := by
intro x
obtain ⟨y, hy⟩ := h x
exact ⟨Finsupp.single y 1, by simp [hy]⟩
#align finsupp.total_surjective Finsupp.total_surjective
theorem total_range (h : Function.Surjective v) : LinearMap.range (Finsupp.total α M R v) = ⊤ :=
range_eq_top.2 <| total_surjective R h
#align finsupp.total_range Finsupp.total_range
/-- Any module is a quotient of a free module. This is stated as surjectivity of
`Finsupp.total M M R id : (M →₀ R) →ₗ[R] M`. -/
theorem total_id_surjective (M) [AddCommMonoid M] [Module R M] :
Function.Surjective (Finsupp.total M M R _root_.id) :=
total_surjective R Function.surjective_id
#align finsupp.total_id_surjective Finsupp.total_id_surjective
theorem range_total : LinearMap.range (Finsupp.total α M R v) = span R (range v) := by
ext x
constructor
· intro hx
rw [LinearMap.mem_range] at hx
rcases hx with ⟨l, hl⟩
rw [← hl]
rw [Finsupp.total_apply]
exact sum_mem fun i _ => Submodule.smul_mem _ _ (subset_span (mem_range_self i))
· apply span_le.2
intro x hx
rcases hx with ⟨i, hi⟩
rw [SetLike.mem_coe, LinearMap.mem_range]
use Finsupp.single i 1
simp [hi]
#align finsupp.range_total Finsupp.range_total
theorem lmapDomain_total (f : α → α') (g : M →ₗ[R] M') (h : ∀ i, g (v i) = v' (f i)) :
(Finsupp.total α' M' R v').comp (lmapDomain R R f) = g.comp (Finsupp.total α M R v) := by
ext l
simp [total_apply, Finsupp.sum_mapDomain_index, add_smul, h]
#align finsupp.lmap_domain_total Finsupp.lmapDomain_total
theorem total_comp_lmapDomain (f : α → α') :
(Finsupp.total α' M' R v').comp (Finsupp.lmapDomain R R f) = Finsupp.total α M' R (v' ∘ f) := by
ext
simp
#align finsupp.total_comp_lmap_domain Finsupp.total_comp_lmapDomain
@[simp]
theorem total_embDomain (f : α ↪ α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (embDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l := by
simp [total_apply, Finsupp.sum, support_embDomain, embDomain_apply]
#align finsupp.total_emb_domain Finsupp.total_embDomain
@[simp]
theorem total_mapDomain (f : α → α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (mapDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l :=
LinearMap.congr_fun (total_comp_lmapDomain _ _) l
#align finsupp.total_map_domain Finsupp.total_mapDomain
@[simp]
theorem total_equivMapDomain (f : α ≃ α') (l : α →₀ R) :
(Finsupp.total α' M' R v') (equivMapDomain f l) = (Finsupp.total α M' R (v' ∘ f)) l := by
rw [equivMapDomain_eq_mapDomain, total_mapDomain]
#align finsupp.total_equiv_map_domain Finsupp.total_equivMapDomain
/-- A version of `Finsupp.range_total` which is useful for going in the other direction -/
theorem span_eq_range_total (s : Set M) : span R s = LinearMap.range (Finsupp.total s M R (↑)) := by
rw [range_total, Subtype.range_coe_subtype, Set.setOf_mem_eq]
#align finsupp.span_eq_range_total Finsupp.span_eq_range_total
theorem mem_span_iff_total (s : Set M) (x : M) :
x ∈ span R s ↔ ∃ l : s →₀ R, Finsupp.total s M R (↑) l = x :=
(SetLike.ext_iff.1 <| span_eq_range_total _ _) x
#align finsupp.mem_span_iff_total Finsupp.mem_span_iff_total
variable {R}
theorem mem_span_range_iff_exists_finsupp {v : α → M} {x : M} :
x ∈ span R (range v) ↔ ∃ c : α →₀ R, (c.sum fun i a => a • v i) = x := by
simp only [← Finsupp.range_total, LinearMap.mem_range, Finsupp.total_apply]
#align finsupp.mem_span_range_iff_exists_finsupp Finsupp.mem_span_range_iff_exists_finsupp
variable (R)
theorem span_image_eq_map_total (s : Set α) :
span R (v '' s) = Submodule.map (Finsupp.total α M R v) (supported R R s) := by
apply span_eq_of_le
· intro x hx
rw [Set.mem_image] at hx
apply Exists.elim hx
intro i hi
exact ⟨_, Finsupp.single_mem_supported R 1 hi.1, by simp [hi.2]⟩
· refine map_le_iff_le_comap.2 fun z hz => ?_
have : ∀ i, z i • v i ∈ span R (v '' s) := by
intro c
haveI := Classical.decPred fun x => x ∈ s
by_cases h : c ∈ s
· exact smul_mem _ _ (subset_span (Set.mem_image_of_mem _ h))
· simp [(Finsupp.mem_supported' R _).1 hz _ h]
-- Porting note: `rw` is required to infer metavariables in `sum_mem`.
rw [mem_comap, total_apply]
refine sum_mem ?_
simp [this]
#align finsupp.span_image_eq_map_total Finsupp.span_image_eq_map_total
theorem mem_span_image_iff_total {s : Set α} {x : M} :
x ∈ span R (v '' s) ↔ ∃ l ∈ supported R R s, Finsupp.total α M R v l = x := by
rw [span_image_eq_map_total]
simp
#align finsupp.mem_span_image_iff_total Finsupp.mem_span_image_iff_total
theorem total_option (v : Option α → M) (f : Option α →₀ R) :
Finsupp.total (Option α) M R v f =
f none • v none + Finsupp.total α M R (v ∘ Option.some) f.some := by
rw [total_apply, sum_option_index_smul, total_apply]; simp
#align finsupp.total_option Finsupp.total_option
theorem total_total {α β : Type*} (A : α → M) (B : β → α →₀ R) (f : β →₀ R) :
Finsupp.total α M R A (Finsupp.total β (α →₀ R) R B f) =
Finsupp.total β M R (fun b => Finsupp.total α M R A (B b)) f := by
classical
simp only [total_apply]
apply induction_linear f
· simp only [sum_zero_index]
· intro f₁ f₂ h₁ h₂
simp [sum_add_index, h₁, h₂, add_smul]
· simp [sum_single_index, sum_smul_index, smul_sum, mul_smul]
#align finsupp.total_total Finsupp.total_total
@[simp]
theorem total_fin_zero (f : Fin 0 → M) : Finsupp.total (Fin 0) M R f = 0 := by
ext i
apply finZeroElim i
#align finsupp.total_fin_zero Finsupp.total_fin_zero
variable (α) (M) (v)
/-- `Finsupp.totalOn M v s` interprets `p : α →₀ R` as a linear combination of a
subset of the vectors in `v`, mapping it to the span of those vectors.
The subset is indicated by a set `s : Set α` of indices.
-/
protected def totalOn (s : Set α) : supported R R s →ₗ[R] span R (v '' s) :=
LinearMap.codRestrict _ ((Finsupp.total _ _ _ v).comp (Submodule.subtype (supported R R s)))
fun ⟨l, hl⟩ => (mem_span_image_iff_total _).2 ⟨l, hl, rfl⟩
#align finsupp.total_on Finsupp.totalOn
variable {α} {M} {v}
theorem totalOn_range (s : Set α) : LinearMap.range (Finsupp.totalOn α M R v s) = ⊤ := by
rw [Finsupp.totalOn, LinearMap.range_eq_map, LinearMap.map_codRestrict,
← LinearMap.range_le_iff_comap, range_subtype, Submodule.map_top, LinearMap.range_comp,
range_subtype]
exact (span_image_eq_map_total _ _).le
#align finsupp.total_on_range Finsupp.totalOn_range
theorem total_comp (f : α' → α) :
Finsupp.total α' M R (v ∘ f) = (Finsupp.total α M R v).comp (lmapDomain R R f) := by
ext
simp [total_apply]
#align finsupp.total_comp Finsupp.total_comp
theorem total_comapDomain (f : α → α') (l : α' →₀ R) (hf : Set.InjOn f (f ⁻¹' ↑l.support)) :
Finsupp.total α M R v (Finsupp.comapDomain f l hf) =
(l.support.preimage f hf).sum fun i => l (f i) • v i := by
rw [Finsupp.total_apply]; rfl
#align finsupp.total_comap_domain Finsupp.total_comapDomain
theorem total_onFinset {s : Finset α} {f : α → R} (g : α → M) (hf : ∀ a, f a ≠ 0 → a ∈ s) :
Finsupp.total α M R g (Finsupp.onFinset s f hf) = Finset.sum s fun x : α => f x • g x := by
classical
simp only [Finsupp.total_apply, Finsupp.sum, Finsupp.onFinset_apply, Finsupp.support_onFinset]
rw [Finset.sum_filter_of_ne]
intro x _ h
contrapose! h
simp [h]
#align finsupp.total_on_finset Finsupp.total_onFinset
end Total
/-- An equivalence of domains induces a linear equivalence of finitely supported functions.
This is `Finsupp.domCongr` as a `LinearEquiv`.
See also `LinearMap.funCongrLeft` for the case of arbitrary functions. -/
protected def domLCongr {α₁ α₂ : Type*} (e : α₁ ≃ α₂) : (α₁ →₀ M) ≃ₗ[R] α₂ →₀ M :=
(Finsupp.domCongr e : (α₁ →₀ M) ≃+ (α₂ →₀ M)).toLinearEquiv <| by
simpa only [equivMapDomain_eq_mapDomain, domCongr_apply] using (lmapDomain M R e).map_smul
#align finsupp.dom_lcongr Finsupp.domLCongr
@[simp]
theorem domLCongr_apply {α₁ : Type*} {α₂ : Type*} (e : α₁ ≃ α₂) (v : α₁ →₀ M) :
(Finsupp.domLCongr e : _ ≃ₗ[R] _) v = Finsupp.domCongr e v :=
rfl
#align finsupp.dom_lcongr_apply Finsupp.domLCongr_apply
@[simp]
theorem domLCongr_refl : Finsupp.domLCongr (Equiv.refl α) = LinearEquiv.refl R (α →₀ M) :=
LinearEquiv.ext fun _ => equivMapDomain_refl _
#align finsupp.dom_lcongr_refl Finsupp.domLCongr_refl
theorem domLCongr_trans {α₁ α₂ α₃ : Type*} (f : α₁ ≃ α₂) (f₂ : α₂ ≃ α₃) :
(Finsupp.domLCongr f).trans (Finsupp.domLCongr f₂) =
(Finsupp.domLCongr (f.trans f₂) : (_ →₀ M) ≃ₗ[R] _) :=
LinearEquiv.ext fun _ => (equivMapDomain_trans _ _ _).symm
#align finsupp.dom_lcongr_trans Finsupp.domLCongr_trans
@[simp]
theorem domLCongr_symm {α₁ α₂ : Type*} (f : α₁ ≃ α₂) :
((Finsupp.domLCongr f).symm : (_ →₀ M) ≃ₗ[R] _) = Finsupp.domLCongr f.symm :=
LinearEquiv.ext fun _ => rfl
#align finsupp.dom_lcongr_symm Finsupp.domLCongr_symm
-- @[simp] -- Porting note (#10618): simp can prove this
theorem domLCongr_single {α₁ : Type*} {α₂ : Type*} (e : α₁ ≃ α₂) (i : α₁) (m : M) :
(Finsupp.domLCongr e : _ ≃ₗ[R] _) (Finsupp.single i m) = Finsupp.single (e i) m := by
simp
#align finsupp.dom_lcongr_single Finsupp.domLCongr_single
/-- An equivalence of sets induces a linear equivalence of `Finsupp`s supported on those sets. -/
noncomputable def congr {α' : Type*} (s : Set α) (t : Set α') (e : s ≃ t) :
supported M R s ≃ₗ[R] supported M R t := by
haveI := Classical.decPred fun x => x ∈ s
haveI := Classical.decPred fun x => x ∈ t
exact Finsupp.supportedEquivFinsupp s ≪≫ₗ
(Finsupp.domLCongr e ≪≫ₗ (Finsupp.supportedEquivFinsupp t).symm)
#align finsupp.congr Finsupp.congr
/-- `Finsupp.mapRange` as a `LinearMap`. -/
def mapRange.linearMap (f : M →ₗ[R] N) : (α →₀ M) →ₗ[R] α →₀ N :=
{ mapRange.addMonoidHom f.toAddMonoidHom with
toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N)
-- Porting note: `hf` should be specified.
map_smul' := fun c v => mapRange_smul (hf := f.map_zero) c v (f.map_smul c) }
#align finsupp.map_range.linear_map Finsupp.mapRange.linearMap
-- Porting note: This was generated by `simps!`.
@[simp]
theorem mapRange.linearMap_apply (f : M →ₗ[R] N) (g : α →₀ M) :
mapRange.linearMap f g = mapRange f f.map_zero g := rfl
#align finsupp.map_range.linear_map_apply Finsupp.mapRange.linearMap_apply
@[simp]
theorem mapRange.linearMap_id :
mapRange.linearMap LinearMap.id = (LinearMap.id : (α →₀ M) →ₗ[R] _) :=
LinearMap.ext mapRange_id
#align finsupp.map_range.linear_map_id Finsupp.mapRange.linearMap_id
theorem mapRange.linearMap_comp (f : N →ₗ[R] P) (f₂ : M →ₗ[R] N) :
(mapRange.linearMap (f.comp f₂) : (α →₀ _) →ₗ[R] _) =
(mapRange.linearMap f).comp (mapRange.linearMap f₂) :=
-- Porting note: Placeholders should be filled.
LinearMap.ext <| mapRange_comp f f.map_zero f₂ f₂.map_zero (comp f f₂).map_zero
#align finsupp.map_range.linear_map_comp Finsupp.mapRange.linearMap_comp
@[simp]
theorem mapRange.linearMap_toAddMonoidHom (f : M →ₗ[R] N) :
(mapRange.linearMap f).toAddMonoidHom =
(mapRange.addMonoidHom f.toAddMonoidHom : (α →₀ M) →+ _) :=
AddMonoidHom.ext fun _ => rfl
#align finsupp.map_range.linear_map_to_add_monoid_hom Finsupp.mapRange.linearMap_toAddMonoidHom
/-- `Finsupp.mapRange` as a `LinearEquiv`. -/
def mapRange.linearEquiv (e : M ≃ₗ[R] N) : (α →₀ M) ≃ₗ[R] α →₀ N :=
{ mapRange.linearMap e.toLinearMap,
mapRange.addEquiv e.toAddEquiv with
toFun := mapRange e e.map_zero
invFun := mapRange e.symm e.symm.map_zero }
#align finsupp.map_range.linear_equiv Finsupp.mapRange.linearEquiv
-- Porting note: This was generated by `simps`.
@[simp]
theorem mapRange.linearEquiv_apply (e : M ≃ₗ[R] N) (g : α →₀ M) :
mapRange.linearEquiv e g = mapRange.linearMap e.toLinearMap g := rfl
#align finsupp.map_range.linear_equiv_apply Finsupp.mapRange.linearEquiv_apply
@[simp]
theorem mapRange.linearEquiv_refl :
mapRange.linearEquiv (LinearEquiv.refl R M) = LinearEquiv.refl R (α →₀ M) :=
LinearEquiv.ext mapRange_id
#align finsupp.map_range.linear_equiv_refl Finsupp.mapRange.linearEquiv_refl
theorem mapRange.linearEquiv_trans (f : M ≃ₗ[R] N) (f₂ : N ≃ₗ[R] P) :
(mapRange.linearEquiv (f.trans f₂) : (α →₀ _) ≃ₗ[R] _) =
(mapRange.linearEquiv f).trans (mapRange.linearEquiv f₂) :=
-- Porting note: Placeholders should be filled.
LinearEquiv.ext <| mapRange_comp f₂ f₂.map_zero f f.map_zero (f.trans f₂).map_zero
#align finsupp.map_range.linear_equiv_trans Finsupp.mapRange.linearEquiv_trans
@[simp]
theorem mapRange.linearEquiv_symm (f : M ≃ₗ[R] N) :
((mapRange.linearEquiv f).symm : (α →₀ _) ≃ₗ[R] _) = mapRange.linearEquiv f.symm :=
LinearEquiv.ext fun _x => rfl
#align finsupp.map_range.linear_equiv_symm Finsupp.mapRange.linearEquiv_symm
-- Porting note: This priority should be higher than `LinearEquiv.coe_toAddEquiv`.
@[simp 1500]
theorem mapRange.linearEquiv_toAddEquiv (f : M ≃ₗ[R] N) :
(mapRange.linearEquiv f).toAddEquiv = (mapRange.addEquiv f.toAddEquiv : (α →₀ M) ≃+ _) :=
AddEquiv.ext fun _ => rfl
#align finsupp.map_range.linear_equiv_to_add_equiv Finsupp.mapRange.linearEquiv_toAddEquiv
@[simp]
theorem mapRange.linearEquiv_toLinearMap (f : M ≃ₗ[R] N) :
(mapRange.linearEquiv f).toLinearMap = (mapRange.linearMap f.toLinearMap : (α →₀ M) →ₗ[R] _) :=
LinearMap.ext fun _ => rfl
#align finsupp.map_range.linear_equiv_to_linear_map Finsupp.mapRange.linearEquiv_toLinearMap
/-- An equivalence of domain and a linear equivalence of codomain induce a linear equivalence of the
corresponding finitely supported functions. -/
def lcongr {ι κ : Sort _} (e₁ : ι ≃ κ) (e₂ : M ≃ₗ[R] N) : (ι →₀ M) ≃ₗ[R] κ →₀ N :=
(Finsupp.domLCongr e₁).trans (mapRange.linearEquiv e₂)
#align finsupp.lcongr Finsupp.lcongr
@[simp]
theorem lcongr_single {ι κ : Sort _} (e₁ : ι ≃ κ) (e₂ : M ≃ₗ[R] N) (i : ι) (m : M) :
lcongr e₁ e₂ (Finsupp.single i m) = Finsupp.single (e₁ i) (e₂ m) := by simp [lcongr]
#align finsupp.lcongr_single Finsupp.lcongr_single
@[simp]
theorem lcongr_apply_apply {ι κ : Sort _} (e₁ : ι ≃ κ) (e₂ : M ≃ₗ[R] N) (f : ι →₀ M) (k : κ) :
lcongr e₁ e₂ f k = e₂ (f (e₁.symm k)) :=
rfl
#align finsupp.lcongr_apply_apply Finsupp.lcongr_apply_apply
theorem lcongr_symm_single {ι κ : Sort _} (e₁ : ι ≃ κ) (e₂ : M ≃ₗ[R] N) (k : κ) (n : N) :
(lcongr e₁ e₂).symm (Finsupp.single k n) = Finsupp.single (e₁.symm k) (e₂.symm n) := by
apply_fun (lcongr e₁ e₂ : (ι →₀ M) → (κ →₀ N)) using (lcongr e₁ e₂).injective
simp
#align finsupp.lcongr_symm_single Finsupp.lcongr_symm_single
@[simp]
theorem lcongr_symm {ι κ : Sort _} (e₁ : ι ≃ κ) (e₂ : M ≃ₗ[R] N) :
(lcongr e₁ e₂).symm = lcongr e₁.symm e₂.symm := by
ext
rfl
#align finsupp.lcongr_symm Finsupp.lcongr_symm
section Sum
variable (R)
/-- The linear equivalence between `(α ⊕ β) →₀ M` and `(α →₀ M) × (β →₀ M)`.
This is the `LinearEquiv` version of `Finsupp.sumFinsuppEquivProdFinsupp`. -/
@[simps apply symm_apply]
def sumFinsuppLEquivProdFinsupp {α β : Type*} : (Sum α β →₀ M) ≃ₗ[R] (α →₀ M) × (β →₀ M) :=
{ sumFinsuppAddEquivProdFinsupp with
map_smul' := by
intros
ext <;>
-- Porting note: `add_equiv.to_fun_eq_coe` →
-- `Equiv.toFun_as_coe` & `AddEquiv.toEquiv_eq_coe` & `AddEquiv.coe_toEquiv`
simp only [Equiv.toFun_as_coe, AddEquiv.toEquiv_eq_coe, AddEquiv.coe_toEquiv, Prod.smul_fst,
Prod.smul_snd, smul_apply,
snd_sumFinsuppAddEquivProdFinsupp, fst_sumFinsuppAddEquivProdFinsupp,
RingHom.id_apply] }
#align finsupp.sum_finsupp_lequiv_prod_finsupp Finsupp.sumFinsuppLEquivProdFinsupp
theorem fst_sumFinsuppLEquivProdFinsupp {α β : Type*} (f : Sum α β →₀ M) (x : α) :
(sumFinsuppLEquivProdFinsupp R f).1 x = f (Sum.inl x) :=
rfl
#align finsupp.fst_sum_finsupp_lequiv_prod_finsupp Finsupp.fst_sumFinsuppLEquivProdFinsupp
theorem snd_sumFinsuppLEquivProdFinsupp {α β : Type*} (f : Sum α β →₀ M) (y : β) :
(sumFinsuppLEquivProdFinsupp R f).2 y = f (Sum.inr y) :=
rfl
#align finsupp.snd_sum_finsupp_lequiv_prod_finsupp Finsupp.snd_sumFinsuppLEquivProdFinsupp
theorem sumFinsuppLEquivProdFinsupp_symm_inl {α β : Type*} (fg : (α →₀ M) × (β →₀ M)) (x : α) :
((sumFinsuppLEquivProdFinsupp R).symm fg) (Sum.inl x) = fg.1 x :=
rfl
#align finsupp.sum_finsupp_lequiv_prod_finsupp_symm_inl Finsupp.sumFinsuppLEquivProdFinsupp_symm_inl
theorem sumFinsuppLEquivProdFinsupp_symm_inr {α β : Type*} (fg : (α →₀ M) × (β →₀ M)) (y : β) :
((sumFinsuppLEquivProdFinsupp R).symm fg) (Sum.inr y) = fg.2 y :=
rfl
#align finsupp.sum_finsupp_lequiv_prod_finsupp_symm_inr Finsupp.sumFinsuppLEquivProdFinsupp_symm_inr
end Sum
section Sigma
variable {η : Type*} [Fintype η] {ιs : η → Type*} [Zero α]
variable (R)
/-- On a `Fintype η`, `Finsupp.split` is a linear equivalence between
`(Σ (j : η), ιs j) →₀ M` and `(j : η) → (ιs j →₀ M)`.
This is the `LinearEquiv` version of `Finsupp.sigmaFinsuppAddEquivPiFinsupp`. -/
noncomputable def sigmaFinsuppLEquivPiFinsupp {M : Type*} {ιs : η → Type*} [AddCommMonoid M]
[Module R M] : ((Σ j, ιs j) →₀ M) ≃ₗ[R] (j : _) → (ιs j →₀ M) :=
-- Porting note: `ιs` should be specified.
{ sigmaFinsuppAddEquivPiFinsupp (ιs := ιs) with
map_smul' := fun c f => by
ext
simp }
#align finsupp.sigma_finsupp_lequiv_pi_finsupp Finsupp.sigmaFinsuppLEquivPiFinsupp
@[simp]
theorem sigmaFinsuppLEquivPiFinsupp_apply {M : Type*} {ιs : η → Type*} [AddCommMonoid M]
[Module R M] (f : (Σj, ιs j) →₀ M) (j i) : sigmaFinsuppLEquivPiFinsupp R f j i = f ⟨j, i⟩ :=
rfl
#align finsupp.sigma_finsupp_lequiv_pi_finsupp_apply Finsupp.sigmaFinsuppLEquivPiFinsupp_apply
@[simp]
theorem sigmaFinsuppLEquivPiFinsupp_symm_apply {M : Type*} {ιs : η → Type*} [AddCommMonoid M]
[Module R M] (f : (j : _) → (ιs j →₀ M)) (ji) :
(Finsupp.sigmaFinsuppLEquivPiFinsupp R).symm f ji = f ji.1 ji.2 :=
rfl
#align finsupp.sigma_finsupp_lequiv_pi_finsupp_symm_apply Finsupp.sigmaFinsuppLEquivPiFinsupp_symm_apply
end Sigma
section Prod
/-- The linear equivalence between `α × β →₀ M` and `α →₀ β →₀ M`.
This is the `LinearEquiv` version of `Finsupp.finsuppProdEquiv`. -/
noncomputable def finsuppProdLEquiv {α β : Type*} (R : Type*) {M : Type*} [Semiring R]
[AddCommMonoid M] [Module R M] : (α × β →₀ M) ≃ₗ[R] α →₀ β →₀ M :=
{ finsuppProdEquiv with
map_add' := fun f g => by
ext
simp [finsuppProdEquiv, curry_apply]
map_smul' := fun c f => by
ext
simp [finsuppProdEquiv, curry_apply] }
#align finsupp.finsupp_prod_lequiv Finsupp.finsuppProdLEquiv
@[simp]
theorem finsuppProdLEquiv_apply {α β R M : Type*} [Semiring R] [AddCommMonoid M] [Module R M]
(f : α × β →₀ M) (x y) : finsuppProdLEquiv R f x y = f (x, y) := by
rw [finsuppProdLEquiv, LinearEquiv.coe_mk, finsuppProdEquiv, Finsupp.curry_apply]
#align finsupp.finsupp_prod_lequiv_apply Finsupp.finsuppProdLEquiv_apply
@[simp]
theorem finsuppProdLEquiv_symm_apply {α β R M : Type*} [Semiring R] [AddCommMonoid M] [Module R M]
(f : α →₀ β →₀ M) (xy) : (finsuppProdLEquiv R).symm f xy = f xy.1 xy.2 := by
conv_rhs =>
rw [← (finsuppProdLEquiv R).apply_symm_apply f, finsuppProdLEquiv_apply]
#align finsupp.finsupp_prod_lequiv_symm_apply Finsupp.finsuppProdLEquiv_symm_apply
end Prod
/-- If `R` is countable, then any `R`-submodule spanned by a countable family of vectors is
countable. -/
instance {ι : Type*} [Countable R] [Countable ι] (v : ι → M) :
Countable (Submodule.span R (Set.range v)) := by
refine Set.countable_coe_iff.mpr (Set.Countable.mono ?_ (Set.countable_range
(fun c : (ι →₀ R) => c.sum fun i _ => (c i) • v i)))
exact fun _ h => Finsupp.mem_span_range_iff_exists_finsupp.mp (SetLike.mem_coe.mp h)
end Finsupp
section Fintype
variable {α M : Type*} (R : Type*) [Fintype α] [Semiring R] [AddCommMonoid M] [Module R M]
variable (S : Type*) [Semiring S] [Module S M] [SMulCommClass R S M]
variable (v : α → M)
/-- `Fintype.total R S v f` is the linear combination of vectors in `v` with weights in `f`.
This variant of `Finsupp.total` is defined on fintype indexed vectors.
This map is linear in `v` if `R` is commutative, and always linear in `f`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used.
-/
protected def Fintype.total : (α → M) →ₗ[S] (α → R) →ₗ[R] M where
toFun v :=
{ toFun := fun f => ∑ i, f i • v i
map_add' := fun f g => by simp_rw [← Finset.sum_add_distrib, ← add_smul]; rfl
map_smul' := fun r f => by simp_rw [Finset.smul_sum, smul_smul]; rfl }
map_add' u v := by ext; simp [Finset.sum_add_distrib, Pi.add_apply, smul_add]
map_smul' r v := by ext; simp [Finset.smul_sum, smul_comm]
#align fintype.total Fintype.total
variable {S}
theorem Fintype.total_apply (f) : Fintype.total R S v f = ∑ i, f i • v i :=
rfl
#align fintype.total_apply Fintype.total_apply
@[simp]
theorem Fintype.total_apply_single [DecidableEq α] (i : α) (r : R) :
Fintype.total R S v (Pi.single i r) = r • v i := by
simp_rw [Fintype.total_apply, Pi.single_apply, ite_smul, zero_smul]
rw [Finset.sum_ite_eq', if_pos (Finset.mem_univ _)]
#align fintype.total_apply_single Fintype.total_apply_single
variable (S)
theorem Finsupp.total_eq_fintype_total_apply (x : α → R) : Finsupp.total α M R v
((Finsupp.linearEquivFunOnFinite R R α).symm x) = Fintype.total R S v x := by
apply Finset.sum_subset
· exact Finset.subset_univ _
· intro x _ hx
rw [Finsupp.not_mem_support_iff.mp hx]
exact zero_smul _ _
#align finsupp.total_eq_fintype_total_apply Finsupp.total_eq_fintype_total_apply
theorem Finsupp.total_eq_fintype_total :
(Finsupp.total α M R v).comp (Finsupp.linearEquivFunOnFinite R R α).symm.toLinearMap =
Fintype.total R S v :=
LinearMap.ext <| Finsupp.total_eq_fintype_total_apply R S v
#align finsupp.total_eq_fintype_total Finsupp.total_eq_fintype_total
variable {S}
@[simp]
theorem Fintype.range_total :
LinearMap.range (Fintype.total R S v) = Submodule.span R (Set.range v) := by
rw [← Finsupp.total_eq_fintype_total, LinearMap.range_comp, LinearEquiv.range,
Submodule.map_top, Finsupp.range_total]
#align fintype.range_total Fintype.range_total
section SpanRange
variable {v} {x : M}
/-- An element `x` lies in the span of `v` iff it can be written as sum `∑ cᵢ • vᵢ = x`.
-/
theorem mem_span_range_iff_exists_fun :
x ∈ span R (range v) ↔ ∃ c : α → R, ∑ i, c i • v i = x := by
-- Porting note: `Finsupp.equivFunOnFinite.surjective.exists` should be come before `simp`.
rw [Finsupp.equivFunOnFinite.surjective.exists]
simp only [Finsupp.mem_span_range_iff_exists_finsupp, Finsupp.equivFunOnFinite_apply]
exact exists_congr fun c => Eq.congr_left <| Finsupp.sum_fintype _ _ fun i => zero_smul _ _
#align mem_span_range_iff_exists_fun mem_span_range_iff_exists_fun
/-- A family `v : α → V` is generating `V` iff every element `(x : V)`
can be written as sum `∑ cᵢ • vᵢ = x`.
-/
theorem top_le_span_range_iff_forall_exists_fun :
⊤ ≤ span R (range v) ↔ ∀ x, ∃ c : α → R, ∑ i, c i • v i = x := by
simp_rw [← mem_span_range_iff_exists_fun]
exact ⟨fun h x => h trivial, fun h x _ => h x⟩
#align top_le_span_range_iff_forall_exists_fun top_le_span_range_iff_forall_exists_fun
end SpanRange
end Fintype
variable {R : Type*} {M : Type*} {N : Type*}
variable [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid N] [Module R N]
section
variable (R)
/-- Pick some representation of `x : span R w` as a linear combination in `w`,
using the axiom of choice.
-/
irreducible_def Span.repr (w : Set M) (x : span R w) : w →₀ R :=
((Finsupp.mem_span_iff_total _ _ _).mp x.2).choose
#align span.repr Span.repr
@[simp]
theorem Span.finsupp_total_repr {w : Set M} (x : span R w) :
Finsupp.total w M R (↑) (Span.repr R w x) = x := by
rw [Span.repr_def]
exact ((Finsupp.mem_span_iff_total _ _ _).mp x.2).choose_spec
#align span.finsupp_total_repr Span.finsupp_total_repr
end
protected theorem Submodule.finsupp_sum_mem {ι β : Type*} [Zero β] (S : Submodule R M) (f : ι →₀ β)
(g : ι → β → M) (h : ∀ c, f c ≠ 0 → g c (f c) ∈ S) : f.sum g ∈ S :=
AddSubmonoidClass.finsupp_sum_mem S f g h
#align submodule.finsupp_sum_mem Submodule.finsupp_sum_mem
theorem LinearMap.map_finsupp_total (f : M →ₗ[R] N) {ι : Type*} {g : ι → M} (l : ι →₀ R) :
f (Finsupp.total ι M R g l) = Finsupp.total ι N R (f ∘ g) l := by
-- Porting note: `(· ∘ ·)` is required.
simp only [Finsupp.total_apply, Finsupp.total_apply, Finsupp.sum, map_sum, map_smul, (· ∘ ·)]
#align linear_map.map_finsupp_total LinearMap.map_finsupp_total
| Mathlib/LinearAlgebra/Finsupp.lean | 1,280 | 1,286 | theorem Submodule.exists_finset_of_mem_iSup {ι : Sort _} (p : ι → Submodule R M) {m : M}
(hm : m ∈ ⨆ i, p i) : ∃ s : Finset ι, m ∈ ⨆ i ∈ s, p i := by |
have :=
CompleteLattice.IsCompactElement.exists_finset_of_le_iSup (Submodule R M)
(Submodule.singleton_span_isCompactElement m) p
simp only [Submodule.span_singleton_le_iff_mem] at this
exact this hm
|
/-
Copyright (c) 2023 Sophie Morel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sophie Morel
-/
import Mathlib.Analysis.Analytic.Basic
/-! We specialize the theory fo analytic functions to the case of functions that admit a
development given by a *finite* formal multilinear series. We call them "continuously polynomial",
which is abbreviated to `CPolynomial`. One reason to do that is that we no longer need a
completeness assumption on the target space `F` to make the series converge, so some of the results
are more general. The class of continuously polynomial functions includes functions defined by
polynomials on a normed `𝕜`-algebra and continuous multilinear maps.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`, and let `f` be a function from `E` to `F`.
* `HasFiniteFPowerSeriesOnBall f p x n r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₘ yᵐ`, and moreover `pₘ = 0` if `n ≤ m`.
* `HasFiniteFPowerSeriesAt f p x n`: on some ball of center `x` with positive radius, holds
`HasFiniteFPowerSeriesOnBall f p x n r`.
* `CPolynomialAt 𝕜 f x`: there exists a power series `p` and a natural number `n` such that
holds `HasFPowerSeriesAt f p x n`.
* `CPolynomialOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function is continuously polynomial, then it is analytic, see
`HasFiniteFPowerSeriesOnBall.hasFPowerSeriesOnBall`, `HasFiniteFPowerSeriesAt.hasFPowerSeriesAt`,
`CPolynomialAt.analyticAt` and `CPolynomialOn.analyticOn`.
* The sum of a finite formal power series with positive radius is well defined on the whole space,
see `FormalMultilinearSeries.hasFiniteFPowerSeriesOnBall_of_finite`.
* If a function admits a finite power series in a ball, then it is continuously polynomial at
any point `y` of this ball, and the power series there can be expressed in terms of the initial
power series `p` as `p.changeOrigin y`, which is finite (with the same bound as `p`) by
`changeOrigin_finite_of_finite`. See `HasFiniteFPowerSeriesOnBall.changeOrigin `. It follows in
particular that the set of points at which a given function is continuously polynomial is open,
see `isOpen_cPolynomialAt`.
-/
variable {𝕜 E F G : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E]
[NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
open scoped Classical
open Topology NNReal Filter ENNReal
open Set Filter Asymptotics
variable {f g : E → F} {p pf pg : FormalMultilinearSeries 𝕜 E F} {x : E} {r r' : ℝ≥0∞} {n m : ℕ}
section FiniteFPowerSeries
/-- Given a function `f : E → F`, a formal multilinear series `p` and `n : ℕ`, we say that
`f` has `p` as a finite power series on the ball of radius `r > 0` around `x` if
`f (x + y) = ∑' pₘ yᵐ` for all `‖y‖ < r` and `pₙ = 0` for `n ≤ m`. -/
structure HasFiniteFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E)
(n : ℕ) (r : ℝ≥0∞) extends HasFPowerSeriesOnBall f p x r : Prop where
finite : ∀ (m : ℕ), n ≤ m → p m = 0
theorem HasFiniteFPowerSeriesOnBall.mk' {f : E → F} {p : FormalMultilinearSeries 𝕜 E F} {x : E}
{n : ℕ} {r : ℝ≥0∞} (finite : ∀ (m : ℕ), n ≤ m → p m = 0) (pos : 0 < r)
(sum_eq : ∀ y ∈ EMetric.ball 0 r, (∑ i ∈ Finset.range n, p i fun _ ↦ y) = f (x + y)) :
HasFiniteFPowerSeriesOnBall f p x n r where
r_le := p.radius_eq_top_of_eventually_eq_zero (Filter.eventually_atTop.mpr ⟨n, finite⟩) ▸ le_top
r_pos := pos
hasSum hy := sum_eq _ hy ▸ hasSum_sum_of_ne_finset_zero fun m hm ↦ by
rw [Finset.mem_range, not_lt] at hm; rw [finite m hm]; rfl
finite := finite
/-- Given a function `f : E → F`, a formal multilinear series `p` and `n : ℕ`, we say that
`f` has `p` as a finite power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a
neighborhood of `0`and `pₙ = 0` for `n ≤ m`. -/
def HasFiniteFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (n : ℕ) :=
∃ r, HasFiniteFPowerSeriesOnBall f p x n r
theorem HasFiniteFPowerSeriesAt.toHasFPowerSeriesAt
(hf : HasFiniteFPowerSeriesAt f p x n) : HasFPowerSeriesAt f p x :=
let ⟨r, hf⟩ := hf
⟨r, hf.toHasFPowerSeriesOnBall⟩
theorem HasFiniteFPowerSeriesAt.finite (hf : HasFiniteFPowerSeriesAt f p x n) :
∀ m : ℕ, n ≤ m → p m = 0 := let ⟨_, hf⟩ := hf; hf.finite
variable (𝕜)
/-- Given a function `f : E → F`, we say that `f` is continuously polynomial (cpolynomial)
at `x` if it admits a finite power series expansion around `x`. -/
def CPolynomialAt (f : E → F) (x : E) :=
∃ (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ), HasFiniteFPowerSeriesAt f p x n
/-- Given a function `f : E → F`, we say that `f` is continuously polynomial on a set `s`
if it is continuously polynomial around every point of `s`. -/
def CPolynomialOn (f : E → F) (s : Set E) :=
∀ x, x ∈ s → CPolynomialAt 𝕜 f x
variable {𝕜}
theorem HasFiniteFPowerSeriesOnBall.hasFiniteFPowerSeriesAt
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
HasFiniteFPowerSeriesAt f p x n :=
⟨r, hf⟩
theorem HasFiniteFPowerSeriesAt.cPolynomialAt (hf : HasFiniteFPowerSeriesAt f p x n) :
CPolynomialAt 𝕜 f x :=
⟨p, n, hf⟩
theorem HasFiniteFPowerSeriesOnBall.cPolynomialAt (hf : HasFiniteFPowerSeriesOnBall f p x n r) :
CPolynomialAt 𝕜 f x :=
hf.hasFiniteFPowerSeriesAt.cPolynomialAt
theorem CPolynomialAt.analyticAt (hf : CPolynomialAt 𝕜 f x) : AnalyticAt 𝕜 f x :=
let ⟨p, _, hp⟩ := hf
⟨p, hp.toHasFPowerSeriesAt⟩
theorem CPolynomialOn.analyticOn {s : Set E} (hf : CPolynomialOn 𝕜 f s) : AnalyticOn 𝕜 f s :=
fun x hx ↦ (hf x hx).analyticAt
theorem HasFiniteFPowerSeriesOnBall.congr (hf : HasFiniteFPowerSeriesOnBall f p x n r)
(hg : EqOn f g (EMetric.ball x r)) : HasFiniteFPowerSeriesOnBall g p x n r :=
⟨hf.1.congr hg, hf.finite⟩
/-- If a function `f` has a finite power series `p` around `x`, then the function
`z ↦ f (z - y)` has the same finite power series around `x + y`. -/
theorem HasFiniteFPowerSeriesOnBall.comp_sub (hf : HasFiniteFPowerSeriesOnBall f p x n r) (y : E) :
HasFiniteFPowerSeriesOnBall (fun z => f (z - y)) p (x + y) n r :=
⟨hf.1.comp_sub y, hf.finite⟩
theorem HasFiniteFPowerSeriesOnBall.mono (hf : HasFiniteFPowerSeriesOnBall f p x n r)
(r'_pos : 0 < r') (hr : r' ≤ r) : HasFiniteFPowerSeriesOnBall f p x n r' :=
⟨hf.1.mono r'_pos hr, hf.finite⟩
theorem HasFiniteFPowerSeriesAt.congr (hf : HasFiniteFPowerSeriesAt f p x n) (hg : f =ᶠ[𝓝 x] g) :
HasFiniteFPowerSeriesAt g p x n :=
Exists.imp (fun _ hg ↦ ⟨hg, hf.finite⟩) (hf.toHasFPowerSeriesAt.congr hg)
protected theorem HasFiniteFPowerSeriesAt.eventually (hf : HasFiniteFPowerSeriesAt f p x n) :
∀ᶠ r : ℝ≥0∞ in 𝓝[>] 0, HasFiniteFPowerSeriesOnBall f p x n r :=
hf.toHasFPowerSeriesAt.eventually.mono fun _ h ↦ ⟨h, hf.finite⟩
theorem hasFiniteFPowerSeriesOnBall_const {c : F} {e : E} :
HasFiniteFPowerSeriesOnBall (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 ⊤ :=
⟨hasFPowerSeriesOnBall_const, fun n hn ↦ constFormalMultilinearSeries_apply (id hn : 0 < n).ne'⟩
theorem hasFiniteFPowerSeriesAt_const {c : F} {e : E} :
HasFiniteFPowerSeriesAt (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 :=
⟨⊤, hasFiniteFPowerSeriesOnBall_const⟩
theorem CPolynomialAt_const {v : F} : CPolynomialAt 𝕜 (fun _ => v) x :=
⟨constFormalMultilinearSeries 𝕜 E v, 1, hasFiniteFPowerSeriesAt_const⟩
theorem CPolynomialOn_const {v : F} {s : Set E} : CPolynomialOn 𝕜 (fun _ => v) s :=
fun _ _ => CPolynomialAt_const
theorem HasFiniteFPowerSeriesOnBall.add (hf : HasFiniteFPowerSeriesOnBall f pf x n r)
(hg : HasFiniteFPowerSeriesOnBall g pg x m r) :
HasFiniteFPowerSeriesOnBall (f + g) (pf + pg) x (max n m) r :=
⟨hf.1.add hg.1, fun N hN ↦ by
rw [Pi.add_apply, hf.finite _ ((le_max_left n m).trans hN),
hg.finite _ ((le_max_right n m).trans hN), zero_add]⟩
theorem HasFiniteFPowerSeriesAt.add (hf : HasFiniteFPowerSeriesAt f pf x n)
(hg : HasFiniteFPowerSeriesAt g pg x m) :
HasFiniteFPowerSeriesAt (f + g) (pf + pg) x (max n m) := by
rcases (hf.eventually.and hg.eventually).exists with ⟨r, hr⟩
exact ⟨r, hr.1.add hr.2⟩
theorem CPolynomialAt.congr (hf : CPolynomialAt 𝕜 f x) (hg : f =ᶠ[𝓝 x] g) : CPolynomialAt 𝕜 g x :=
let ⟨_, _, hpf⟩ := hf
(hpf.congr hg).cPolynomialAt
theorem CPolynomialAt_congr (h : f =ᶠ[𝓝 x] g) : CPolynomialAt 𝕜 f x ↔ CPolynomialAt 𝕜 g x :=
⟨fun hf ↦ hf.congr h, fun hg ↦ hg.congr h.symm⟩
theorem CPolynomialAt.add (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) :
CPolynomialAt 𝕜 (f + g) x :=
let ⟨_, _, hpf⟩ := hf
let ⟨_, _, hqf⟩ := hg
(hpf.add hqf).cPolynomialAt
theorem HasFiniteFPowerSeriesOnBall.neg (hf : HasFiniteFPowerSeriesOnBall f pf x n r) :
HasFiniteFPowerSeriesOnBall (-f) (-pf) x n r :=
⟨hf.1.neg, fun m hm ↦ by rw [Pi.neg_apply, hf.finite m hm, neg_zero]⟩
theorem HasFiniteFPowerSeriesAt.neg (hf : HasFiniteFPowerSeriesAt f pf x n) :
HasFiniteFPowerSeriesAt (-f) (-pf) x n :=
let ⟨_, hrf⟩ := hf
hrf.neg.hasFiniteFPowerSeriesAt
theorem CPolynomialAt.neg (hf : CPolynomialAt 𝕜 f x) : CPolynomialAt 𝕜 (-f) x :=
let ⟨_, _, hpf⟩ := hf
hpf.neg.cPolynomialAt
theorem HasFiniteFPowerSeriesOnBall.sub (hf : HasFiniteFPowerSeriesOnBall f pf x n r)
(hg : HasFiniteFPowerSeriesOnBall g pg x m r) :
HasFiniteFPowerSeriesOnBall (f - g) (pf - pg) x (max n m) r := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem HasFiniteFPowerSeriesAt.sub (hf : HasFiniteFPowerSeriesAt f pf x n)
(hg : HasFiniteFPowerSeriesAt g pg x m) :
HasFiniteFPowerSeriesAt (f - g) (pf - pg) x (max n m) := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem CPolynomialAt.sub (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) :
CPolynomialAt 𝕜 (f - g) x := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem CPolynomialOn.mono {s t : Set E} (hf : CPolynomialOn 𝕜 f t) (hst : s ⊆ t) :
CPolynomialOn 𝕜 f s :=
fun z hz => hf z (hst hz)
theorem CPolynomialOn.congr' {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : f =ᶠ[𝓝ˢ s] g) :
CPolynomialOn 𝕜 g s :=
fun z hz => (hf z hz).congr (mem_nhdsSet_iff_forall.mp hg z hz)
theorem CPolynomialOn_congr' {s : Set E} (h : f =ᶠ[𝓝ˢ s] g) :
CPolynomialOn 𝕜 f s ↔ CPolynomialOn 𝕜 g s :=
⟨fun hf => hf.congr' h, fun hg => hg.congr' h.symm⟩
theorem CPolynomialOn.congr {s : Set E} (hs : IsOpen s) (hf : CPolynomialOn 𝕜 f s)
(hg : s.EqOn f g) : CPolynomialOn 𝕜 g s :=
hf.congr' <| mem_nhdsSet_iff_forall.mpr
(fun _ hz => eventuallyEq_iff_exists_mem.mpr ⟨s, hs.mem_nhds hz, hg⟩)
theorem CPolynomialOn_congr {s : Set E} (hs : IsOpen s) (h : s.EqOn f g) :
CPolynomialOn 𝕜 f s ↔ CPolynomialOn 𝕜 g s :=
⟨fun hf => hf.congr hs h, fun hg => hg.congr hs h.symm⟩
theorem CPolynomialOn.add {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) :
CPolynomialOn 𝕜 (f + g) s :=
fun z hz => (hf z hz).add (hg z hz)
theorem CPolynomialOn.sub {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) :
CPolynomialOn 𝕜 (f - g) s :=
fun z hz => (hf z hz).sub (hg z hz)
/-- If a function `f` has a finite power series `p` on a ball and `g` is a continuous linear map,
then `g ∘ f` has the finite power series `g ∘ p` on the same ball. -/
theorem ContinuousLinearMap.comp_hasFiniteFPowerSeriesOnBall (g : F →L[𝕜] G)
(h : HasFiniteFPowerSeriesOnBall f p x n r) :
HasFiniteFPowerSeriesOnBall (g ∘ f) (g.compFormalMultilinearSeries p) x n r :=
⟨g.comp_hasFPowerSeriesOnBall h.1, fun m hm ↦ by
rw [compFormalMultilinearSeries_apply, h.finite m hm]
ext; exact map_zero g⟩
/-- If a function `f` is continuously polynomial on a set `s` and `g` is a continuous linear map,
then `g ∘ f` is continuously polynomial on `s`. -/
theorem ContinuousLinearMap.comp_cPolynomialOn {s : Set E} (g : F →L[𝕜] G)
(h : CPolynomialOn 𝕜 f s) : CPolynomialOn 𝕜 (g ∘ f) s := by
rintro x hx
rcases h x hx with ⟨p, n, r, hp⟩
exact ⟨g.compFormalMultilinearSeries p, n, r, g.comp_hasFiniteFPowerSeriesOnBall hp⟩
/-- If a function admits a finite power series expansion bounded by `n`, then it is equal to
the `m`th partial sums of this power series at every point of the disk for `n ≤ m`. -/
theorem HasFiniteFPowerSeriesOnBall.eq_partialSum
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
∀ y ∈ EMetric.ball (0 : E) r, ∀ m, n ≤ m →
f (x + y) = p.partialSum m y :=
fun y hy m hm ↦ (hf.hasSum hy).unique (hasSum_sum_of_ne_finset_zero
(f := fun m => p m (fun _ => y)) (s := Finset.range m)
(fun N hN => by simp only; simp only [Finset.mem_range, not_lt] at hN
rw [hf.finite _ (le_trans hm hN), ContinuousMultilinearMap.zero_apply]))
/-- Variant of the previous result with the variable expressed as `y` instead of `x + y`. -/
theorem HasFiniteFPowerSeriesOnBall.eq_partialSum'
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
∀ y ∈ EMetric.ball x r, ∀ m, n ≤ m →
f y = p.partialSum m (y - x) := by
intro y hy m hm
rw [EMetric.mem_ball, edist_eq_coe_nnnorm_sub, ← mem_emetric_ball_zero_iff] at hy
rw [← (HasFiniteFPowerSeriesOnBall.eq_partialSum hf _ hy m hm), add_sub_cancel]
/-! The particular cases where `f` has a finite power series bounded by `0` or `1`. -/
/-- If `f` has a formal power series on a ball bounded by `0`, then `f` is equal to `0` on
the ball. -/
theorem HasFiniteFPowerSeriesOnBall.eq_zero_of_bound_zero
(hf : HasFiniteFPowerSeriesOnBall f pf x 0 r) : ∀ y ∈ EMetric.ball x r, f y = 0 := by
intro y hy
rw [hf.eq_partialSum' y hy 0 le_rfl, FormalMultilinearSeries.partialSum]
simp only [Finset.range_zero, Finset.sum_empty]
| Mathlib/Analysis/Analytic/CPolynomial.lean | 284 | 294 | theorem HasFiniteFPowerSeriesOnBall.bound_zero_of_eq_zero (hf : ∀ y ∈ EMetric.ball x r, f y = 0)
(r_pos : 0 < r) (hp : ∀ n, p n = 0) : HasFiniteFPowerSeriesOnBall f p x 0 r := by |
refine ⟨⟨?_, r_pos, ?_⟩, fun n _ ↦ hp n⟩
· rw [p.radius_eq_top_of_forall_image_add_eq_zero 0 (fun n ↦ by rw [add_zero]; exact hp n)]
exact le_top
· intro y hy
rw [hf (x + y)]
· convert hasSum_zero
rw [hp, ContinuousMultilinearMap.zero_apply]
· rwa [EMetric.mem_ball, edist_eq_coe_nnnorm_sub, add_comm, add_sub_cancel_right,
← edist_eq_coe_nnnorm, ← EMetric.mem_ball]
|
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Order.GaloisConnection
#align_import order.heyting.regular from "leanprover-community/mathlib"@"09597669f02422ed388036273d8848119699c22f"
/-!
# Heyting regular elements
This file defines Heyting regular elements, elements of a Heyting algebra that are their own double
complement, and proves that they form a boolean algebra.
From a logic standpoint, this means that we can perform classical logic within intuitionistic logic
by simply double-negating all propositions. This is practical for synthetic computability theory.
## Main declarations
* `IsRegular`: `a` is Heyting-regular if `aᶜᶜ = a`.
* `Regular`: The subtype of Heyting-regular elements.
* `Regular.BooleanAlgebra`: Heyting-regular elements form a boolean algebra.
## References
* [Francis Borceux, *Handbook of Categorical Algebra III*][borceux-vol3]
-/
open Function
variable {α : Type*}
namespace Heyting
section HasCompl
variable [HasCompl α] {a : α}
/-- An element of a Heyting algebra is regular if its double complement is itself. -/
def IsRegular (a : α) : Prop :=
aᶜᶜ = a
#align heyting.is_regular Heyting.IsRegular
protected theorem IsRegular.eq : IsRegular a → aᶜᶜ = a :=
id
#align heyting.is_regular.eq Heyting.IsRegular.eq
instance IsRegular.decidablePred [DecidableEq α] : @DecidablePred α IsRegular := fun _ =>
‹DecidableEq α› _ _
#align heyting.is_regular.decidable_pred Heyting.IsRegular.decidablePred
end HasCompl
section HeytingAlgebra
variable [HeytingAlgebra α] {a b : α}
theorem isRegular_bot : IsRegular (⊥ : α) := by rw [IsRegular, compl_bot, compl_top]
#align heyting.is_regular_bot Heyting.isRegular_bot
theorem isRegular_top : IsRegular (⊤ : α) := by rw [IsRegular, compl_top, compl_bot]
#align heyting.is_regular_top Heyting.isRegular_top
theorem IsRegular.inf (ha : IsRegular a) (hb : IsRegular b) : IsRegular (a ⊓ b) := by
rw [IsRegular, compl_compl_inf_distrib, ha.eq, hb.eq]
#align heyting.is_regular.inf Heyting.IsRegular.inf
| Mathlib/Order/Heyting/Regular.lean | 70 | 71 | theorem IsRegular.himp (ha : IsRegular a) (hb : IsRegular b) : IsRegular (a ⇨ b) := by |
rw [IsRegular, compl_compl_himp_distrib, ha.eq, hb.eq]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.BigOperators.Group.List
import Mathlib.Algebra.Group.Prod
import Mathlib.Data.Multiset.Basic
#align_import algebra.big_operators.multiset.basic from "leanprover-community/mathlib"@"6c5f73fd6f6cc83122788a80a27cdd54663609f4"
/-!
# Sums and products over multisets
In this file we define products and sums indexed by multisets. This is later used to define products
and sums indexed by finite sets.
## Main declarations
* `Multiset.prod`: `s.prod f` is the product of `f i` over all `i ∈ s`. Not to be mistaken with
the cartesian product `Multiset.product`.
* `Multiset.sum`: `s.sum f` is the sum of `f i` over all `i ∈ s`.
-/
assert_not_exists MonoidWithZero
variable {F ι α β γ : Type*}
namespace Multiset
section CommMonoid
variable [CommMonoid α] [CommMonoid β] {s t : Multiset α} {a : α} {m : Multiset ι} {f g : ι → α}
/-- Product of a multiset given a commutative monoid structure on `α`.
`prod {a, b, c} = a * b * c` -/
@[to_additive
"Sum of a multiset given a commutative additive monoid structure on `α`.
`sum {a, b, c} = a + b + c`"]
def prod : Multiset α → α :=
foldr (· * ·) (fun x y z => by simp [mul_left_comm]) 1
#align multiset.prod Multiset.prod
#align multiset.sum Multiset.sum
@[to_additive]
theorem prod_eq_foldr (s : Multiset α) :
prod s = foldr (· * ·) (fun x y z => by simp [mul_left_comm]) 1 s :=
rfl
#align multiset.prod_eq_foldr Multiset.prod_eq_foldr
#align multiset.sum_eq_foldr Multiset.sum_eq_foldr
@[to_additive]
theorem prod_eq_foldl (s : Multiset α) :
prod s = foldl (· * ·) (fun x y z => by simp [mul_right_comm]) 1 s :=
(foldr_swap _ _ _ _).trans (by simp [mul_comm])
#align multiset.prod_eq_foldl Multiset.prod_eq_foldl
#align multiset.sum_eq_foldl Multiset.sum_eq_foldl
@[to_additive (attr := simp, norm_cast)]
theorem prod_coe (l : List α) : prod ↑l = l.prod :=
prod_eq_foldl _
#align multiset.coe_prod Multiset.prod_coe
#align multiset.coe_sum Multiset.sum_coe
@[to_additive (attr := simp)]
theorem prod_toList (s : Multiset α) : s.toList.prod = s.prod := by
conv_rhs => rw [← coe_toList s]
rw [prod_coe]
#align multiset.prod_to_list Multiset.prod_toList
#align multiset.sum_to_list Multiset.sum_toList
@[to_additive (attr := simp)]
theorem prod_zero : @prod α _ 0 = 1 :=
rfl
#align multiset.prod_zero Multiset.prod_zero
#align multiset.sum_zero Multiset.sum_zero
@[to_additive (attr := simp)]
theorem prod_cons (a : α) (s) : prod (a ::ₘ s) = a * prod s :=
foldr_cons _ _ _ _ _
#align multiset.prod_cons Multiset.prod_cons
#align multiset.sum_cons Multiset.sum_cons
@[to_additive (attr := simp)]
theorem prod_erase [DecidableEq α] (h : a ∈ s) : a * (s.erase a).prod = s.prod := by
rw [← s.coe_toList, coe_erase, prod_coe, prod_coe, List.prod_erase (mem_toList.2 h)]
#align multiset.prod_erase Multiset.prod_erase
#align multiset.sum_erase Multiset.sum_erase
@[to_additive (attr := simp)]
theorem prod_map_erase [DecidableEq ι] {a : ι} (h : a ∈ m) :
f a * ((m.erase a).map f).prod = (m.map f).prod := by
rw [← m.coe_toList, coe_erase, map_coe, map_coe, prod_coe, prod_coe,
List.prod_map_erase f (mem_toList.2 h)]
#align multiset.prod_map_erase Multiset.prod_map_erase
#align multiset.sum_map_erase Multiset.sum_map_erase
@[to_additive (attr := simp)]
theorem prod_singleton (a : α) : prod {a} = a := by
simp only [mul_one, prod_cons, ← cons_zero, eq_self_iff_true, prod_zero]
#align multiset.prod_singleton Multiset.prod_singleton
#align multiset.sum_singleton Multiset.sum_singleton
@[to_additive]
theorem prod_pair (a b : α) : ({a, b} : Multiset α).prod = a * b := by
rw [insert_eq_cons, prod_cons, prod_singleton]
#align multiset.prod_pair Multiset.prod_pair
#align multiset.sum_pair Multiset.sum_pair
@[to_additive (attr := simp)]
theorem prod_add (s t : Multiset α) : prod (s + t) = prod s * prod t :=
Quotient.inductionOn₂ s t fun l₁ l₂ => by simp
#align multiset.prod_add Multiset.prod_add
#align multiset.sum_add Multiset.sum_add
@[to_additive]
theorem prod_nsmul (m : Multiset α) : ∀ n : ℕ, (n • m).prod = m.prod ^ n
| 0 => by
rw [zero_nsmul, pow_zero]
rfl
| n + 1 => by rw [add_nsmul, one_nsmul, pow_add, pow_one, prod_add, prod_nsmul m n]
#align multiset.prod_nsmul Multiset.prod_nsmul
@[to_additive]
theorem prod_filter_mul_prod_filter_not (p) [DecidablePred p] :
(s.filter p).prod * (s.filter (fun a ↦ ¬ p a)).prod = s.prod := by
rw [← prod_add, filter_add_not]
@[to_additive (attr := simp)]
theorem prod_replicate (n : ℕ) (a : α) : (replicate n a).prod = a ^ n := by
simp [replicate, List.prod_replicate]
#align multiset.prod_replicate Multiset.prod_replicate
#align multiset.sum_replicate Multiset.sum_replicate
@[to_additive]
theorem prod_map_eq_pow_single [DecidableEq ι] (i : ι)
(hf : ∀ i' ≠ i, i' ∈ m → f i' = 1) : (m.map f).prod = f i ^ m.count i := by
induction' m using Quotient.inductionOn with l
simp [List.prod_map_eq_pow_single i f hf]
#align multiset.prod_map_eq_pow_single Multiset.prod_map_eq_pow_single
#align multiset.sum_map_eq_nsmul_single Multiset.sum_map_eq_nsmul_single
@[to_additive]
theorem prod_eq_pow_single [DecidableEq α] (a : α) (h : ∀ a' ≠ a, a' ∈ s → a' = 1) :
s.prod = a ^ s.count a := by
induction' s using Quotient.inductionOn with l
simp [List.prod_eq_pow_single a h]
#align multiset.prod_eq_pow_single Multiset.prod_eq_pow_single
#align multiset.sum_eq_nsmul_single Multiset.sum_eq_nsmul_single
@[to_additive]
lemma prod_eq_one (h : ∀ x ∈ s, x = (1 : α)) : s.prod = 1 := by
induction' s using Quotient.inductionOn with l; simp [List.prod_eq_one h]
#align multiset.prod_eq_one Multiset.prod_eq_one
#align multiset.sum_eq_zero Multiset.sum_eq_zero
@[to_additive]
theorem pow_count [DecidableEq α] (a : α) : a ^ s.count a = (s.filter (Eq a)).prod := by
rw [filter_eq, prod_replicate]
#align multiset.pow_count Multiset.pow_count
#align multiset.nsmul_count Multiset.nsmul_count
@[to_additive]
theorem prod_hom [CommMonoid β] (s : Multiset α) {F : Type*} [FunLike F α β]
[MonoidHomClass F α β] (f : F) :
(s.map f).prod = f s.prod :=
Quotient.inductionOn s fun l => by simp only [l.prod_hom f, quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom Multiset.prod_hom
#align multiset.sum_hom Multiset.sum_hom
@[to_additive]
theorem prod_hom' [CommMonoid β] (s : Multiset ι) {F : Type*} [FunLike F α β]
[MonoidHomClass F α β] (f : F)
(g : ι → α) : (s.map fun i => f <| g i).prod = f (s.map g).prod := by
convert (s.map g).prod_hom f
exact (map_map _ _ _).symm
#align multiset.prod_hom' Multiset.prod_hom'
#align multiset.sum_hom' Multiset.sum_hom'
@[to_additive]
theorem prod_hom₂ [CommMonoid β] [CommMonoid γ] (s : Multiset ι) (f : α → β → γ)
(hf : ∀ a b c d, f (a * b) (c * d) = f a c * f b d) (hf' : f 1 1 = 1) (f₁ : ι → α)
(f₂ : ι → β) : (s.map fun i => f (f₁ i) (f₂ i)).prod = f (s.map f₁).prod (s.map f₂).prod :=
Quotient.inductionOn s fun l => by
simp only [l.prod_hom₂ f hf hf', quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom₂ Multiset.prod_hom₂
#align multiset.sum_hom₂ Multiset.sum_hom₂
@[to_additive]
theorem prod_hom_rel [CommMonoid β] (s : Multiset ι) {r : α → β → Prop} {f : ι → α} {g : ι → β}
(h₁ : r 1 1) (h₂ : ∀ ⦃a b c⦄, r b c → r (f a * b) (g a * c)) :
r (s.map f).prod (s.map g).prod :=
Quotient.inductionOn s fun l => by
simp only [l.prod_hom_rel h₁ h₂, quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom_rel Multiset.prod_hom_rel
#align multiset.sum_hom_rel Multiset.sum_hom_rel
@[to_additive]
theorem prod_map_one : prod (m.map fun _ => (1 : α)) = 1 := by
rw [map_const', prod_replicate, one_pow]
#align multiset.prod_map_one Multiset.prod_map_one
#align multiset.sum_map_zero Multiset.sum_map_zero
@[to_additive (attr := simp)]
theorem prod_map_mul : (m.map fun i => f i * g i).prod = (m.map f).prod * (m.map g).prod :=
m.prod_hom₂ (· * ·) mul_mul_mul_comm (mul_one _) _ _
#align multiset.prod_map_mul Multiset.prod_map_mul
#align multiset.sum_map_add Multiset.sum_map_add
@[to_additive]
theorem prod_map_pow {n : ℕ} : (m.map fun i => f i ^ n).prod = (m.map f).prod ^ n :=
m.prod_hom' (powMonoidHom n : α →* α) f
#align multiset.prod_map_pow Multiset.prod_map_pow
#align multiset.sum_map_nsmul Multiset.sum_map_nsmul
@[to_additive]
theorem prod_map_prod_map (m : Multiset β) (n : Multiset γ) {f : β → γ → α} :
prod (m.map fun a => prod <| n.map fun b => f a b) =
prod (n.map fun b => prod <| m.map fun a => f a b) :=
Multiset.induction_on m (by simp) fun a m ih => by simp [ih]
#align multiset.prod_map_prod_map Multiset.prod_map_prod_map
#align multiset.sum_map_sum_map Multiset.sum_map_sum_map
@[to_additive]
theorem prod_induction (p : α → Prop) (s : Multiset α) (p_mul : ∀ a b, p a → p b → p (a * b))
(p_one : p 1) (p_s : ∀ a ∈ s, p a) : p s.prod := by
rw [prod_eq_foldr]
exact foldr_induction (· * ·) (fun x y z => by simp [mul_left_comm]) 1 p s p_mul p_one p_s
#align multiset.prod_induction Multiset.prod_induction
#align multiset.sum_induction Multiset.sum_induction
@[to_additive]
| Mathlib/Algebra/BigOperators/Group/Multiset.lean | 233 | 242 | theorem prod_induction_nonempty (p : α → Prop) (p_mul : ∀ a b, p a → p b → p (a * b)) (hs : s ≠ ∅)
(p_s : ∀ a ∈ s, p a) : p s.prod := by |
-- Porting note: used to be `refine' Multiset.induction _ _`
induction' s using Multiset.induction_on with a s hsa
· simp at hs
rw [prod_cons]
by_cases hs_empty : s = ∅
· simp [hs_empty, p_s a]
have hps : ∀ x, x ∈ s → p x := fun x hxs => p_s x (mem_cons_of_mem hxs)
exact p_mul a s.prod (p_s a (mem_cons_self a s)) (hsa hs_empty hps)
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Sébastien Gouëzel, Patrick Massot
-/
import Mathlib.Topology.UniformSpace.Cauchy
import Mathlib.Topology.UniformSpace.Separation
import Mathlib.Topology.DenseEmbedding
#align_import topology.uniform_space.uniform_embedding from "leanprover-community/mathlib"@"195fcd60ff2bfe392543bceb0ec2adcdb472db4c"
/-!
# Uniform embeddings of uniform spaces.
Extension of uniform continuous functions.
-/
open Filter Function Set Uniformity Topology
section
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w} [UniformSpace α] [UniformSpace β] [UniformSpace γ]
/-!
### Uniform inducing maps
-/
/-- A map `f : α → β` between uniform spaces is called *uniform inducing* if the uniformity filter
on `α` is the pullback of the uniformity filter on `β` under `Prod.map f f`. If `α` is a separated
space, then this implies that `f` is injective, hence it is a `UniformEmbedding`. -/
@[mk_iff]
structure UniformInducing (f : α → β) : Prop where
/-- The uniformity filter on the domain is the pullback of the uniformity filter on the codomain
under `Prod.map f f`. -/
comap_uniformity : comap (fun x : α × α => (f x.1, f x.2)) (𝓤 β) = 𝓤 α
#align uniform_inducing UniformInducing
#align uniform_inducing_iff uniformInducing_iff
lemma uniformInducing_iff_uniformSpace {f : α → β} :
UniformInducing f ↔ ‹UniformSpace β›.comap f = ‹UniformSpace α› := by
rw [uniformInducing_iff, UniformSpace.ext_iff, Filter.ext_iff]
rfl
protected alias ⟨UniformInducing.comap_uniformSpace, _⟩ := uniformInducing_iff_uniformSpace
#align uniform_inducing.comap_uniform_space UniformInducing.comap_uniformSpace
lemma uniformInducing_iff' {f : α → β} :
UniformInducing f ↔ UniformContinuous f ∧ comap (Prod.map f f) (𝓤 β) ≤ 𝓤 α := by
rw [uniformInducing_iff, UniformContinuous, tendsto_iff_comap, le_antisymm_iff, and_comm]; rfl
#align uniform_inducing_iff' uniformInducing_iff'
protected lemma Filter.HasBasis.uniformInducing_iff {ι ι'} {p : ι → Prop} {p' : ι' → Prop} {s s'}
(h : (𝓤 α).HasBasis p s) (h' : (𝓤 β).HasBasis p' s') {f : α → β} :
UniformInducing f ↔
(∀ i, p' i → ∃ j, p j ∧ ∀ x y, (x, y) ∈ s j → (f x, f y) ∈ s' i) ∧
(∀ j, p j → ∃ i, p' i ∧ ∀ x y, (f x, f y) ∈ s' i → (x, y) ∈ s j) := by
simp [uniformInducing_iff', h.uniformContinuous_iff h', (h'.comap _).le_basis_iff h, subset_def]
#align filter.has_basis.uniform_inducing_iff Filter.HasBasis.uniformInducing_iff
theorem UniformInducing.mk' {f : α → β}
(h : ∀ s, s ∈ 𝓤 α ↔ ∃ t ∈ 𝓤 β, ∀ x y : α, (f x, f y) ∈ t → (x, y) ∈ s) : UniformInducing f :=
⟨by simp [eq_comm, Filter.ext_iff, subset_def, h]⟩
#align uniform_inducing.mk' UniformInducing.mk'
theorem uniformInducing_id : UniformInducing (@id α) :=
⟨by rw [← Prod.map_def, Prod.map_id, comap_id]⟩
#align uniform_inducing_id uniformInducing_id
theorem UniformInducing.comp {g : β → γ} (hg : UniformInducing g) {f : α → β}
(hf : UniformInducing f) : UniformInducing (g ∘ f) :=
⟨by rw [← hf.1, ← hg.1, comap_comap]; rfl⟩
#align uniform_inducing.comp UniformInducing.comp
theorem UniformInducing.of_comp_iff {g : β → γ} (hg : UniformInducing g) {f : α → β} :
UniformInducing (g ∘ f) ↔ UniformInducing f := by
refine ⟨fun h ↦ ?_, hg.comp⟩
rw [uniformInducing_iff, ← hg.comap_uniformity, comap_comap, ← h.comap_uniformity,
Function.comp, Function.comp]
theorem UniformInducing.basis_uniformity {f : α → β} (hf : UniformInducing f) {ι : Sort*}
{p : ι → Prop} {s : ι → Set (β × β)} (H : (𝓤 β).HasBasis p s) :
(𝓤 α).HasBasis p fun i => Prod.map f f ⁻¹' s i :=
hf.1 ▸ H.comap _
#align uniform_inducing.basis_uniformity UniformInducing.basis_uniformity
theorem UniformInducing.cauchy_map_iff {f : α → β} (hf : UniformInducing f) {F : Filter α} :
Cauchy (map f F) ↔ Cauchy F := by
simp only [Cauchy, map_neBot_iff, prod_map_map_eq, map_le_iff_le_comap, ← hf.comap_uniformity]
#align uniform_inducing.cauchy_map_iff UniformInducing.cauchy_map_iff
theorem uniformInducing_of_compose {f : α → β} {g : β → γ} (hf : UniformContinuous f)
(hg : UniformContinuous g) (hgf : UniformInducing (g ∘ f)) : UniformInducing f := by
refine ⟨le_antisymm ?_ hf.le_comap⟩
rw [← hgf.1, ← Prod.map_def, ← Prod.map_def, ← Prod.map_comp_map f f g g, ← comap_comap]
exact comap_mono hg.le_comap
#align uniform_inducing_of_compose uniformInducing_of_compose
theorem UniformInducing.uniformContinuous {f : α → β} (hf : UniformInducing f) :
UniformContinuous f := (uniformInducing_iff'.1 hf).1
#align uniform_inducing.uniform_continuous UniformInducing.uniformContinuous
theorem UniformInducing.uniformContinuous_iff {f : α → β} {g : β → γ} (hg : UniformInducing g) :
UniformContinuous f ↔ UniformContinuous (g ∘ f) := by
dsimp only [UniformContinuous, Tendsto]
rw [← hg.comap_uniformity, ← map_le_iff_le_comap, Filter.map_map]; rfl
#align uniform_inducing.uniform_continuous_iff UniformInducing.uniformContinuous_iff
theorem UniformInducing.uniformContinuousOn_iff {f : α → β} {g : β → γ} {S : Set α}
(hg : UniformInducing g) :
UniformContinuousOn f S ↔ UniformContinuousOn (g ∘ f) S := by
dsimp only [UniformContinuousOn, Tendsto]
rw [← hg.comap_uniformity, ← map_le_iff_le_comap, Filter.map_map, comp_def, comp_def]
theorem UniformInducing.inducing {f : α → β} (h : UniformInducing f) : Inducing f := by
obtain rfl := h.comap_uniformSpace
exact inducing_induced f
#align uniform_inducing.inducing UniformInducing.inducing
theorem UniformInducing.prod {α' : Type*} {β' : Type*} [UniformSpace α'] [UniformSpace β']
{e₁ : α → α'} {e₂ : β → β'} (h₁ : UniformInducing e₁) (h₂ : UniformInducing e₂) :
UniformInducing fun p : α × β => (e₁ p.1, e₂ p.2) :=
⟨by simp [(· ∘ ·), uniformity_prod, ← h₁.1, ← h₂.1, comap_inf, comap_comap]⟩
#align uniform_inducing.prod UniformInducing.prod
theorem UniformInducing.denseInducing {f : α → β} (h : UniformInducing f) (hd : DenseRange f) :
DenseInducing f :=
{ dense := hd
induced := h.inducing.induced }
#align uniform_inducing.dense_inducing UniformInducing.denseInducing
theorem SeparationQuotient.uniformInducing_mk : UniformInducing (mk : α → SeparationQuotient α) :=
⟨comap_mk_uniformity⟩
protected theorem UniformInducing.injective [T0Space α] {f : α → β} (h : UniformInducing f) :
Injective f :=
h.inducing.injective
/-!
### Uniform embeddings
-/
/-- A map `f : α → β` between uniform spaces is a *uniform embedding* if it is uniform inducing and
injective. If `α` is a separated space, then the latter assumption follows from the former. -/
@[mk_iff]
structure UniformEmbedding (f : α → β) extends UniformInducing f : Prop where
/-- A uniform embedding is injective. -/
inj : Function.Injective f
#align uniform_embedding UniformEmbedding
#align uniform_embedding_iff uniformEmbedding_iff
theorem uniformEmbedding_iff' {f : α → β} :
UniformEmbedding f ↔ Injective f ∧ UniformContinuous f ∧ comap (Prod.map f f) (𝓤 β) ≤ 𝓤 α := by
rw [uniformEmbedding_iff, and_comm, uniformInducing_iff']
#align uniform_embedding_iff' uniformEmbedding_iff'
theorem Filter.HasBasis.uniformEmbedding_iff' {ι ι'} {p : ι → Prop} {p' : ι' → Prop} {s s'}
(h : (𝓤 α).HasBasis p s) (h' : (𝓤 β).HasBasis p' s') {f : α → β} :
UniformEmbedding f ↔ Injective f ∧
(∀ i, p' i → ∃ j, p j ∧ ∀ x y, (x, y) ∈ s j → (f x, f y) ∈ s' i) ∧
(∀ j, p j → ∃ i, p' i ∧ ∀ x y, (f x, f y) ∈ s' i → (x, y) ∈ s j) := by
rw [uniformEmbedding_iff, and_comm, h.uniformInducing_iff h']
#align filter.has_basis.uniform_embedding_iff' Filter.HasBasis.uniformEmbedding_iff'
| Mathlib/Topology/UniformSpace/UniformEmbedding.lean | 166 | 170 | theorem Filter.HasBasis.uniformEmbedding_iff {ι ι'} {p : ι → Prop} {p' : ι' → Prop} {s s'}
(h : (𝓤 α).HasBasis p s) (h' : (𝓤 β).HasBasis p' s') {f : α → β} :
UniformEmbedding f ↔ Injective f ∧ UniformContinuous f ∧
(∀ j, p j → ∃ i, p' i ∧ ∀ x y, (f x, f y) ∈ s' i → (x, y) ∈ s j) := by |
simp only [h.uniformEmbedding_iff' h', h.uniformContinuous_iff h']
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Asymptotics
#align_import analysis.special_functions.pow.continuity from "leanprover-community/mathlib"@"0b9eaaa7686280fad8cce467f5c3c57ee6ce77f8"
/-!
# Continuity of power functions
This file contains lemmas about continuity of the power functions on `ℂ`, `ℝ`, `ℝ≥0`, and `ℝ≥0∞`.
-/
noncomputable section
open scoped Classical
open Real Topology NNReal ENNReal Filter ComplexConjugate
open Filter Finset Set
section CpowLimits
/-!
## Continuity for complex powers
-/
open Complex
variable {α : Type*}
theorem zero_cpow_eq_nhds {b : ℂ} (hb : b ≠ 0) : (fun x : ℂ => (0 : ℂ) ^ x) =ᶠ[𝓝 b] 0 := by
suffices ∀ᶠ x : ℂ in 𝓝 b, x ≠ 0 from
this.mono fun x hx ↦ by
dsimp only
rw [zero_cpow hx, Pi.zero_apply]
exact IsOpen.eventually_mem isOpen_ne hb
#align zero_cpow_eq_nhds zero_cpow_eq_nhds
theorem cpow_eq_nhds {a b : ℂ} (ha : a ≠ 0) :
(fun x => x ^ b) =ᶠ[𝓝 a] fun x => exp (log x * b) := by
suffices ∀ᶠ x : ℂ in 𝓝 a, x ≠ 0 from
this.mono fun x hx ↦ by
dsimp only
rw [cpow_def_of_ne_zero hx]
exact IsOpen.eventually_mem isOpen_ne ha
#align cpow_eq_nhds cpow_eq_nhds
theorem cpow_eq_nhds' {p : ℂ × ℂ} (hp_fst : p.fst ≠ 0) :
(fun x => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) := by
suffices ∀ᶠ x : ℂ × ℂ in 𝓝 p, x.1 ≠ 0 from
this.mono fun x hx ↦ by
dsimp only
rw [cpow_def_of_ne_zero hx]
refine IsOpen.eventually_mem ?_ hp_fst
change IsOpen { x : ℂ × ℂ | x.1 = 0 }ᶜ
rw [isOpen_compl_iff]
exact isClosed_eq continuous_fst continuous_const
#align cpow_eq_nhds' cpow_eq_nhds'
-- Continuity of `fun x => a ^ x`: union of these two lemmas is optimal.
theorem continuousAt_const_cpow {a b : ℂ} (ha : a ≠ 0) : ContinuousAt (fun x : ℂ => a ^ x) b := by
have cpow_eq : (fun x : ℂ => a ^ x) = fun x => exp (log a * x) := by
ext1 b
rw [cpow_def_of_ne_zero ha]
rw [cpow_eq]
exact continuous_exp.continuousAt.comp (ContinuousAt.mul continuousAt_const continuousAt_id)
#align continuous_at_const_cpow continuousAt_const_cpow
theorem continuousAt_const_cpow' {a b : ℂ} (h : b ≠ 0) : ContinuousAt (fun x : ℂ => a ^ x) b := by
by_cases ha : a = 0
· rw [ha, continuousAt_congr (zero_cpow_eq_nhds h)]
exact continuousAt_const
· exact continuousAt_const_cpow ha
#align continuous_at_const_cpow' continuousAt_const_cpow'
/-- The function `z ^ w` is continuous in `(z, w)` provided that `z` does not belong to the interval
`(-∞, 0]` on the real line. See also `Complex.continuousAt_cpow_zero_of_re_pos` for a version that
works for `z = 0` but assumes `0 < re w`. -/
| Mathlib/Analysis/SpecialFunctions/Pow/Continuity.lean | 84 | 91 | theorem continuousAt_cpow {p : ℂ × ℂ} (hp_fst : p.fst ∈ slitPlane) :
ContinuousAt (fun x : ℂ × ℂ => x.1 ^ x.2) p := by |
rw [continuousAt_congr (cpow_eq_nhds' <| slitPlane_ne_zero hp_fst)]
refine continuous_exp.continuousAt.comp ?_
exact
ContinuousAt.mul
(ContinuousAt.comp (continuousAt_clog hp_fst) continuous_fst.continuousAt)
continuous_snd.continuousAt
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.Topology.Maps
import Mathlib.Topology.NhdsSet
#align_import topology.constructions from "leanprover-community/mathlib"@"f7ebde7ee0d1505dfccac8644ae12371aa3c1c9f"
/-!
# Constructions of new topological spaces from old ones
This file constructs products, sums, subtypes and quotients of topological spaces
and sets up their basic theory, such as criteria for maps into or out of these
constructions to be continuous; descriptions of the open sets, neighborhood filters,
and generators of these constructions; and their behavior with respect to embeddings
and other specific classes of maps.
## Implementation note
The constructed topologies are defined using induced and coinduced topologies
along with the complete lattice structure on topologies. Their universal properties
(for example, a map `X → Y × Z` is continuous if and only if both projections
`X → Y`, `X → Z` are) follow easily using order-theoretic descriptions of
continuity. With more work we can also extract descriptions of the open sets,
neighborhood filters and so on.
## Tags
product, sum, disjoint union, subspace, quotient space
-/
noncomputable section
open scoped Classical
open Topology TopologicalSpace Set Filter Function
universe u v
variable {X : Type u} {Y : Type v} {Z W ε ζ : Type*}
section Constructions
instance instTopologicalSpaceSubtype {p : X → Prop} [t : TopologicalSpace X] :
TopologicalSpace (Subtype p) :=
induced (↑) t
instance {r : X → X → Prop} [t : TopologicalSpace X] : TopologicalSpace (Quot r) :=
coinduced (Quot.mk r) t
instance instTopologicalSpaceQuotient {s : Setoid X} [t : TopologicalSpace X] :
TopologicalSpace (Quotient s) :=
coinduced Quotient.mk' t
instance instTopologicalSpaceProd [t₁ : TopologicalSpace X] [t₂ : TopologicalSpace Y] :
TopologicalSpace (X × Y) :=
induced Prod.fst t₁ ⊓ induced Prod.snd t₂
instance instTopologicalSpaceSum [t₁ : TopologicalSpace X] [t₂ : TopologicalSpace Y] :
TopologicalSpace (X ⊕ Y) :=
coinduced Sum.inl t₁ ⊔ coinduced Sum.inr t₂
instance instTopologicalSpaceSigma {ι : Type*} {X : ι → Type v} [t₂ : ∀ i, TopologicalSpace (X i)] :
TopologicalSpace (Sigma X) :=
⨆ i, coinduced (Sigma.mk i) (t₂ i)
instance Pi.topologicalSpace {ι : Type*} {Y : ι → Type v} [t₂ : (i : ι) → TopologicalSpace (Y i)] :
TopologicalSpace ((i : ι) → Y i) :=
⨅ i, induced (fun f => f i) (t₂ i)
#align Pi.topological_space Pi.topologicalSpace
instance ULift.topologicalSpace [t : TopologicalSpace X] : TopologicalSpace (ULift.{v, u} X) :=
t.induced ULift.down
#align ulift.topological_space ULift.topologicalSpace
/-!
### `Additive`, `Multiplicative`
The topology on those type synonyms is inherited without change.
-/
section
variable [TopologicalSpace X]
open Additive Multiplicative
instance : TopologicalSpace (Additive X) := ‹TopologicalSpace X›
instance : TopologicalSpace (Multiplicative X) := ‹TopologicalSpace X›
instance [DiscreteTopology X] : DiscreteTopology (Additive X) := ‹DiscreteTopology X›
instance [DiscreteTopology X] : DiscreteTopology (Multiplicative X) := ‹DiscreteTopology X›
theorem continuous_ofMul : Continuous (ofMul : X → Additive X) := continuous_id
#align continuous_of_mul continuous_ofMul
theorem continuous_toMul : Continuous (toMul : Additive X → X) := continuous_id
#align continuous_to_mul continuous_toMul
theorem continuous_ofAdd : Continuous (ofAdd : X → Multiplicative X) := continuous_id
#align continuous_of_add continuous_ofAdd
theorem continuous_toAdd : Continuous (toAdd : Multiplicative X → X) := continuous_id
#align continuous_to_add continuous_toAdd
theorem isOpenMap_ofMul : IsOpenMap (ofMul : X → Additive X) := IsOpenMap.id
#align is_open_map_of_mul isOpenMap_ofMul
theorem isOpenMap_toMul : IsOpenMap (toMul : Additive X → X) := IsOpenMap.id
#align is_open_map_to_mul isOpenMap_toMul
theorem isOpenMap_ofAdd : IsOpenMap (ofAdd : X → Multiplicative X) := IsOpenMap.id
#align is_open_map_of_add isOpenMap_ofAdd
theorem isOpenMap_toAdd : IsOpenMap (toAdd : Multiplicative X → X) := IsOpenMap.id
#align is_open_map_to_add isOpenMap_toAdd
theorem isClosedMap_ofMul : IsClosedMap (ofMul : X → Additive X) := IsClosedMap.id
#align is_closed_map_of_mul isClosedMap_ofMul
theorem isClosedMap_toMul : IsClosedMap (toMul : Additive X → X) := IsClosedMap.id
#align is_closed_map_to_mul isClosedMap_toMul
theorem isClosedMap_ofAdd : IsClosedMap (ofAdd : X → Multiplicative X) := IsClosedMap.id
#align is_closed_map_of_add isClosedMap_ofAdd
theorem isClosedMap_toAdd : IsClosedMap (toAdd : Multiplicative X → X) := IsClosedMap.id
#align is_closed_map_to_add isClosedMap_toAdd
theorem nhds_ofMul (x : X) : 𝓝 (ofMul x) = map ofMul (𝓝 x) := rfl
#align nhds_of_mul nhds_ofMul
theorem nhds_ofAdd (x : X) : 𝓝 (ofAdd x) = map ofAdd (𝓝 x) := rfl
#align nhds_of_add nhds_ofAdd
theorem nhds_toMul (x : Additive X) : 𝓝 (toMul x) = map toMul (𝓝 x) := rfl
#align nhds_to_mul nhds_toMul
theorem nhds_toAdd (x : Multiplicative X) : 𝓝 (toAdd x) = map toAdd (𝓝 x) := rfl
#align nhds_to_add nhds_toAdd
end
/-!
### Order dual
The topology on this type synonym is inherited without change.
-/
section
variable [TopologicalSpace X]
open OrderDual
instance : TopologicalSpace Xᵒᵈ := ‹TopologicalSpace X›
instance [DiscreteTopology X] : DiscreteTopology Xᵒᵈ := ‹DiscreteTopology X›
theorem continuous_toDual : Continuous (toDual : X → Xᵒᵈ) := continuous_id
#align continuous_to_dual continuous_toDual
theorem continuous_ofDual : Continuous (ofDual : Xᵒᵈ → X) := continuous_id
#align continuous_of_dual continuous_ofDual
theorem isOpenMap_toDual : IsOpenMap (toDual : X → Xᵒᵈ) := IsOpenMap.id
#align is_open_map_to_dual isOpenMap_toDual
theorem isOpenMap_ofDual : IsOpenMap (ofDual : Xᵒᵈ → X) := IsOpenMap.id
#align is_open_map_of_dual isOpenMap_ofDual
theorem isClosedMap_toDual : IsClosedMap (toDual : X → Xᵒᵈ) := IsClosedMap.id
#align is_closed_map_to_dual isClosedMap_toDual
theorem isClosedMap_ofDual : IsClosedMap (ofDual : Xᵒᵈ → X) := IsClosedMap.id
#align is_closed_map_of_dual isClosedMap_ofDual
theorem nhds_toDual (x : X) : 𝓝 (toDual x) = map toDual (𝓝 x) := rfl
#align nhds_to_dual nhds_toDual
theorem nhds_ofDual (x : X) : 𝓝 (ofDual x) = map ofDual (𝓝 x) := rfl
#align nhds_of_dual nhds_ofDual
end
theorem Quotient.preimage_mem_nhds [TopologicalSpace X] [s : Setoid X] {V : Set <| Quotient s}
{x : X} (hs : V ∈ 𝓝 (Quotient.mk' x)) : Quotient.mk' ⁻¹' V ∈ 𝓝 x :=
preimage_nhds_coinduced hs
#align quotient.preimage_mem_nhds Quotient.preimage_mem_nhds
/-- The image of a dense set under `Quotient.mk'` is a dense set. -/
theorem Dense.quotient [Setoid X] [TopologicalSpace X] {s : Set X} (H : Dense s) :
Dense (Quotient.mk' '' s) :=
Quotient.surjective_Quotient_mk''.denseRange.dense_image continuous_coinduced_rng H
#align dense.quotient Dense.quotient
/-- The composition of `Quotient.mk'` and a function with dense range has dense range. -/
theorem DenseRange.quotient [Setoid X] [TopologicalSpace X] {f : Y → X} (hf : DenseRange f) :
DenseRange (Quotient.mk' ∘ f) :=
Quotient.surjective_Quotient_mk''.denseRange.comp hf continuous_coinduced_rng
#align dense_range.quotient DenseRange.quotient
theorem continuous_map_of_le {α : Type*} [TopologicalSpace α]
{s t : Setoid α} (h : s ≤ t) : Continuous (Setoid.map_of_le h) :=
continuous_coinduced_rng
theorem continuous_map_sInf {α : Type*} [TopologicalSpace α]
{S : Set (Setoid α)} {s : Setoid α} (h : s ∈ S) : Continuous (Setoid.map_sInf h) :=
continuous_coinduced_rng
instance {p : X → Prop} [TopologicalSpace X] [DiscreteTopology X] : DiscreteTopology (Subtype p) :=
⟨bot_unique fun s _ => ⟨(↑) '' s, isOpen_discrete _, preimage_image_eq _ Subtype.val_injective⟩⟩
instance Sum.discreteTopology [TopologicalSpace X] [TopologicalSpace Y] [h : DiscreteTopology X]
[hY : DiscreteTopology Y] : DiscreteTopology (X ⊕ Y) :=
⟨sup_eq_bot_iff.2 <| by simp [h.eq_bot, hY.eq_bot]⟩
#align sum.discrete_topology Sum.discreteTopology
instance Sigma.discreteTopology {ι : Type*} {Y : ι → Type v} [∀ i, TopologicalSpace (Y i)]
[h : ∀ i, DiscreteTopology (Y i)] : DiscreteTopology (Sigma Y) :=
⟨iSup_eq_bot.2 fun _ => by simp only [(h _).eq_bot, coinduced_bot]⟩
#align sigma.discrete_topology Sigma.discreteTopology
section Top
variable [TopologicalSpace X]
/-
The 𝓝 filter and the subspace topology.
-/
theorem mem_nhds_subtype (s : Set X) (x : { x // x ∈ s }) (t : Set { x // x ∈ s }) :
t ∈ 𝓝 x ↔ ∃ u ∈ 𝓝 (x : X), Subtype.val ⁻¹' u ⊆ t :=
mem_nhds_induced _ x t
#align mem_nhds_subtype mem_nhds_subtype
theorem nhds_subtype (s : Set X) (x : { x // x ∈ s }) : 𝓝 x = comap (↑) (𝓝 (x : X)) :=
nhds_induced _ x
#align nhds_subtype nhds_subtype
theorem nhdsWithin_subtype_eq_bot_iff {s t : Set X} {x : s} :
𝓝[((↑) : s → X) ⁻¹' t] x = ⊥ ↔ 𝓝[t] (x : X) ⊓ 𝓟 s = ⊥ := by
rw [inf_principal_eq_bot_iff_comap, nhdsWithin, nhdsWithin, comap_inf, comap_principal,
nhds_induced]
#align nhds_within_subtype_eq_bot_iff nhdsWithin_subtype_eq_bot_iff
theorem nhds_ne_subtype_eq_bot_iff {S : Set X} {x : S} :
𝓝[≠] x = ⊥ ↔ 𝓝[≠] (x : X) ⊓ 𝓟 S = ⊥ := by
rw [← nhdsWithin_subtype_eq_bot_iff, preimage_compl, ← image_singleton,
Subtype.coe_injective.preimage_image]
#align nhds_ne_subtype_eq_bot_iff nhds_ne_subtype_eq_bot_iff
theorem nhds_ne_subtype_neBot_iff {S : Set X} {x : S} :
(𝓝[≠] x).NeBot ↔ (𝓝[≠] (x : X) ⊓ 𝓟 S).NeBot := by
rw [neBot_iff, neBot_iff, not_iff_not, nhds_ne_subtype_eq_bot_iff]
#align nhds_ne_subtype_ne_bot_iff nhds_ne_subtype_neBot_iff
theorem discreteTopology_subtype_iff {S : Set X} :
DiscreteTopology S ↔ ∀ x ∈ S, 𝓝[≠] x ⊓ 𝓟 S = ⊥ := by
simp_rw [discreteTopology_iff_nhds_ne, SetCoe.forall', nhds_ne_subtype_eq_bot_iff]
#align discrete_topology_subtype_iff discreteTopology_subtype_iff
end Top
/-- A type synonym equipped with the topology whose open sets are the empty set and the sets with
finite complements. -/
def CofiniteTopology (X : Type*) := X
#align cofinite_topology CofiniteTopology
namespace CofiniteTopology
/-- The identity equivalence between `` and `CofiniteTopology `. -/
def of : X ≃ CofiniteTopology X :=
Equiv.refl X
#align cofinite_topology.of CofiniteTopology.of
instance [Inhabited X] : Inhabited (CofiniteTopology X) where default := of default
instance : TopologicalSpace (CofiniteTopology X) where
IsOpen s := s.Nonempty → Set.Finite sᶜ
isOpen_univ := by simp
isOpen_inter s t := by
rintro hs ht ⟨x, hxs, hxt⟩
rw [compl_inter]
exact (hs ⟨x, hxs⟩).union (ht ⟨x, hxt⟩)
isOpen_sUnion := by
rintro s h ⟨x, t, hts, hzt⟩
rw [compl_sUnion]
exact Finite.sInter (mem_image_of_mem _ hts) (h t hts ⟨x, hzt⟩)
theorem isOpen_iff {s : Set (CofiniteTopology X)} : IsOpen s ↔ s.Nonempty → sᶜ.Finite :=
Iff.rfl
#align cofinite_topology.is_open_iff CofiniteTopology.isOpen_iff
theorem isOpen_iff' {s : Set (CofiniteTopology X)} : IsOpen s ↔ s = ∅ ∨ sᶜ.Finite := by
simp only [isOpen_iff, nonempty_iff_ne_empty, or_iff_not_imp_left]
#align cofinite_topology.is_open_iff' CofiniteTopology.isOpen_iff'
theorem isClosed_iff {s : Set (CofiniteTopology X)} : IsClosed s ↔ s = univ ∨ s.Finite := by
simp only [← isOpen_compl_iff, isOpen_iff', compl_compl, compl_empty_iff]
#align cofinite_topology.is_closed_iff CofiniteTopology.isClosed_iff
theorem nhds_eq (x : CofiniteTopology X) : 𝓝 x = pure x ⊔ cofinite := by
ext U
rw [mem_nhds_iff]
constructor
· rintro ⟨V, hVU, V_op, haV⟩
exact mem_sup.mpr ⟨hVU haV, mem_of_superset (V_op ⟨_, haV⟩) hVU⟩
· rintro ⟨hU : x ∈ U, hU' : Uᶜ.Finite⟩
exact ⟨U, Subset.rfl, fun _ => hU', hU⟩
#align cofinite_topology.nhds_eq CofiniteTopology.nhds_eq
theorem mem_nhds_iff {x : CofiniteTopology X} {s : Set (CofiniteTopology X)} :
s ∈ 𝓝 x ↔ x ∈ s ∧ sᶜ.Finite := by simp [nhds_eq]
#align cofinite_topology.mem_nhds_iff CofiniteTopology.mem_nhds_iff
end CofiniteTopology
end Constructions
section Prod
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace W]
[TopologicalSpace ε] [TopologicalSpace ζ]
-- Porting note (#11215): TODO: Lean 4 fails to deduce implicit args
@[simp] theorem continuous_prod_mk {f : X → Y} {g : X → Z} :
(Continuous fun x => (f x, g x)) ↔ Continuous f ∧ Continuous g :=
(@continuous_inf_rng X (Y × Z) _ _ (TopologicalSpace.induced Prod.fst _)
(TopologicalSpace.induced Prod.snd _)).trans <|
continuous_induced_rng.and continuous_induced_rng
#align continuous_prod_mk continuous_prod_mk
@[continuity]
theorem continuous_fst : Continuous (@Prod.fst X Y) :=
(continuous_prod_mk.1 continuous_id).1
#align continuous_fst continuous_fst
/-- Postcomposing `f` with `Prod.fst` is continuous -/
@[fun_prop]
theorem Continuous.fst {f : X → Y × Z} (hf : Continuous f) : Continuous fun x : X => (f x).1 :=
continuous_fst.comp hf
#align continuous.fst Continuous.fst
/-- Precomposing `f` with `Prod.fst` is continuous -/
theorem Continuous.fst' {f : X → Z} (hf : Continuous f) : Continuous fun x : X × Y => f x.fst :=
hf.comp continuous_fst
#align continuous.fst' Continuous.fst'
theorem continuousAt_fst {p : X × Y} : ContinuousAt Prod.fst p :=
continuous_fst.continuousAt
#align continuous_at_fst continuousAt_fst
/-- Postcomposing `f` with `Prod.fst` is continuous at `x` -/
@[fun_prop]
theorem ContinuousAt.fst {f : X → Y × Z} {x : X} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X => (f x).1) x :=
continuousAt_fst.comp hf
#align continuous_at.fst ContinuousAt.fst
/-- Precomposing `f` with `Prod.fst` is continuous at `(x, y)` -/
theorem ContinuousAt.fst' {f : X → Z} {x : X} {y : Y} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X × Y => f x.fst) (x, y) :=
ContinuousAt.comp hf continuousAt_fst
#align continuous_at.fst' ContinuousAt.fst'
/-- Precomposing `f` with `Prod.fst` is continuous at `x : X × Y` -/
theorem ContinuousAt.fst'' {f : X → Z} {x : X × Y} (hf : ContinuousAt f x.fst) :
ContinuousAt (fun x : X × Y => f x.fst) x :=
hf.comp continuousAt_fst
#align continuous_at.fst'' ContinuousAt.fst''
theorem Filter.Tendsto.fst_nhds {l : Filter X} {f : X → Y × Z} {p : Y × Z}
(h : Tendsto f l (𝓝 p)) : Tendsto (fun a ↦ (f a).1) l (𝓝 <| p.1) :=
continuousAt_fst.tendsto.comp h
@[continuity]
theorem continuous_snd : Continuous (@Prod.snd X Y) :=
(continuous_prod_mk.1 continuous_id).2
#align continuous_snd continuous_snd
/-- Postcomposing `f` with `Prod.snd` is continuous -/
@[fun_prop]
theorem Continuous.snd {f : X → Y × Z} (hf : Continuous f) : Continuous fun x : X => (f x).2 :=
continuous_snd.comp hf
#align continuous.snd Continuous.snd
/-- Precomposing `f` with `Prod.snd` is continuous -/
theorem Continuous.snd' {f : Y → Z} (hf : Continuous f) : Continuous fun x : X × Y => f x.snd :=
hf.comp continuous_snd
#align continuous.snd' Continuous.snd'
theorem continuousAt_snd {p : X × Y} : ContinuousAt Prod.snd p :=
continuous_snd.continuousAt
#align continuous_at_snd continuousAt_snd
/-- Postcomposing `f` with `Prod.snd` is continuous at `x` -/
@[fun_prop]
theorem ContinuousAt.snd {f : X → Y × Z} {x : X} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X => (f x).2) x :=
continuousAt_snd.comp hf
#align continuous_at.snd ContinuousAt.snd
/-- Precomposing `f` with `Prod.snd` is continuous at `(x, y)` -/
theorem ContinuousAt.snd' {f : Y → Z} {x : X} {y : Y} (hf : ContinuousAt f y) :
ContinuousAt (fun x : X × Y => f x.snd) (x, y) :=
ContinuousAt.comp hf continuousAt_snd
#align continuous_at.snd' ContinuousAt.snd'
/-- Precomposing `f` with `Prod.snd` is continuous at `x : X × Y` -/
theorem ContinuousAt.snd'' {f : Y → Z} {x : X × Y} (hf : ContinuousAt f x.snd) :
ContinuousAt (fun x : X × Y => f x.snd) x :=
hf.comp continuousAt_snd
#align continuous_at.snd'' ContinuousAt.snd''
theorem Filter.Tendsto.snd_nhds {l : Filter X} {f : X → Y × Z} {p : Y × Z}
(h : Tendsto f l (𝓝 p)) : Tendsto (fun a ↦ (f a).2) l (𝓝 <| p.2) :=
continuousAt_snd.tendsto.comp h
@[continuity, fun_prop]
theorem Continuous.prod_mk {f : Z → X} {g : Z → Y} (hf : Continuous f) (hg : Continuous g) :
Continuous fun x => (f x, g x) :=
continuous_prod_mk.2 ⟨hf, hg⟩
#align continuous.prod_mk Continuous.prod_mk
@[continuity]
theorem Continuous.Prod.mk (x : X) : Continuous fun y : Y => (x, y) :=
continuous_const.prod_mk continuous_id
#align continuous.prod.mk Continuous.Prod.mk
@[continuity]
theorem Continuous.Prod.mk_left (y : Y) : Continuous fun x : X => (x, y) :=
continuous_id.prod_mk continuous_const
#align continuous.prod.mk_left Continuous.Prod.mk_left
/-- If `f x y` is continuous in `x` for all `y ∈ s`,
then the set of `x` such that `f x` maps `s` to `t` is closed. -/
lemma IsClosed.setOf_mapsTo {α : Type*} {f : X → α → Z} {s : Set α} {t : Set Z} (ht : IsClosed t)
(hf : ∀ a ∈ s, Continuous (f · a)) : IsClosed {x | MapsTo (f x) s t} := by
simpa only [MapsTo, setOf_forall] using isClosed_biInter fun y hy ↦ ht.preimage (hf y hy)
theorem Continuous.comp₂ {g : X × Y → Z} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) : Continuous fun w => g (e w, f w) :=
hg.comp <| he.prod_mk hf
#align continuous.comp₂ Continuous.comp₂
theorem Continuous.comp₃ {g : X × Y × Z → ε} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) {k : W → Z} (hk : Continuous k) :
Continuous fun w => g (e w, f w, k w) :=
hg.comp₂ he <| hf.prod_mk hk
#align continuous.comp₃ Continuous.comp₃
theorem Continuous.comp₄ {g : X × Y × Z × ζ → ε} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) {k : W → Z} (hk : Continuous k) {l : W → ζ}
(hl : Continuous l) : Continuous fun w => g (e w, f w, k w, l w) :=
hg.comp₃ he hf <| hk.prod_mk hl
#align continuous.comp₄ Continuous.comp₄
@[continuity]
theorem Continuous.prod_map {f : Z → X} {g : W → Y} (hf : Continuous f) (hg : Continuous g) :
Continuous fun p : Z × W => (f p.1, g p.2) :=
hf.fst'.prod_mk hg.snd'
#align continuous.prod_map Continuous.prod_map
/-- A version of `continuous_inf_dom_left` for binary functions -/
theorem continuous_inf_dom_left₂ {X Y Z} {f : X → Y → Z} {ta1 ta2 : TopologicalSpace X}
{tb1 tb2 : TopologicalSpace Y} {tc1 : TopologicalSpace Z}
(h : by haveI := ta1; haveI := tb1; exact Continuous fun p : X × Y => f p.1 p.2) : by
haveI := ta1 ⊓ ta2; haveI := tb1 ⊓ tb2; exact Continuous fun p : X × Y => f p.1 p.2 := by
have ha := @continuous_inf_dom_left _ _ id ta1 ta2 ta1 (@continuous_id _ (id _))
have hb := @continuous_inf_dom_left _ _ id tb1 tb2 tb1 (@continuous_id _ (id _))
have h_continuous_id := @Continuous.prod_map _ _ _ _ ta1 tb1 (ta1 ⊓ ta2) (tb1 ⊓ tb2) _ _ ha hb
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ h h_continuous_id
#align continuous_inf_dom_left₂ continuous_inf_dom_left₂
/-- A version of `continuous_inf_dom_right` for binary functions -/
theorem continuous_inf_dom_right₂ {X Y Z} {f : X → Y → Z} {ta1 ta2 : TopologicalSpace X}
{tb1 tb2 : TopologicalSpace Y} {tc1 : TopologicalSpace Z}
(h : by haveI := ta2; haveI := tb2; exact Continuous fun p : X × Y => f p.1 p.2) : by
haveI := ta1 ⊓ ta2; haveI := tb1 ⊓ tb2; exact Continuous fun p : X × Y => f p.1 p.2 := by
have ha := @continuous_inf_dom_right _ _ id ta1 ta2 ta2 (@continuous_id _ (id _))
have hb := @continuous_inf_dom_right _ _ id tb1 tb2 tb2 (@continuous_id _ (id _))
have h_continuous_id := @Continuous.prod_map _ _ _ _ ta2 tb2 (ta1 ⊓ ta2) (tb1 ⊓ tb2) _ _ ha hb
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ h h_continuous_id
#align continuous_inf_dom_right₂ continuous_inf_dom_right₂
/-- A version of `continuous_sInf_dom` for binary functions -/
theorem continuous_sInf_dom₂ {X Y Z} {f : X → Y → Z} {tas : Set (TopologicalSpace X)}
{tbs : Set (TopologicalSpace Y)} {tX : TopologicalSpace X} {tY : TopologicalSpace Y}
{tc : TopologicalSpace Z} (hX : tX ∈ tas) (hY : tY ∈ tbs)
(hf : Continuous fun p : X × Y => f p.1 p.2) : by
haveI := sInf tas; haveI := sInf tbs;
exact @Continuous _ _ _ tc fun p : X × Y => f p.1 p.2 := by
have hX := continuous_sInf_dom hX continuous_id
have hY := continuous_sInf_dom hY continuous_id
have h_continuous_id := @Continuous.prod_map _ _ _ _ tX tY (sInf tas) (sInf tbs) _ _ hX hY
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ hf h_continuous_id
#align continuous_Inf_dom₂ continuous_sInf_dom₂
theorem Filter.Eventually.prod_inl_nhds {p : X → Prop} {x : X} (h : ∀ᶠ x in 𝓝 x, p x) (y : Y) :
∀ᶠ x in 𝓝 (x, y), p (x : X × Y).1 :=
continuousAt_fst h
#align filter.eventually.prod_inl_nhds Filter.Eventually.prod_inl_nhds
theorem Filter.Eventually.prod_inr_nhds {p : Y → Prop} {y : Y} (h : ∀ᶠ x in 𝓝 y, p x) (x : X) :
∀ᶠ x in 𝓝 (x, y), p (x : X × Y).2 :=
continuousAt_snd h
#align filter.eventually.prod_inr_nhds Filter.Eventually.prod_inr_nhds
theorem Filter.Eventually.prod_mk_nhds {px : X → Prop} {x} (hx : ∀ᶠ x in 𝓝 x, px x) {py : Y → Prop}
{y} (hy : ∀ᶠ y in 𝓝 y, py y) : ∀ᶠ p in 𝓝 (x, y), px (p : X × Y).1 ∧ py p.2 :=
(hx.prod_inl_nhds y).and (hy.prod_inr_nhds x)
#align filter.eventually.prod_mk_nhds Filter.Eventually.prod_mk_nhds
theorem continuous_swap : Continuous (Prod.swap : X × Y → Y × X) :=
continuous_snd.prod_mk continuous_fst
#align continuous_swap continuous_swap
lemma isClosedMap_swap : IsClosedMap (Prod.swap : X × Y → Y × X) := fun s hs ↦ by
rw [image_swap_eq_preimage_swap]
exact hs.preimage continuous_swap
theorem Continuous.uncurry_left {f : X → Y → Z} (x : X) (h : Continuous (uncurry f)) :
Continuous (f x) :=
h.comp (Continuous.Prod.mk _)
#align continuous_uncurry_left Continuous.uncurry_left
theorem Continuous.uncurry_right {f : X → Y → Z} (y : Y) (h : Continuous (uncurry f)) :
Continuous fun a => f a y :=
h.comp (Continuous.Prod.mk_left _)
#align continuous_uncurry_right Continuous.uncurry_right
-- 2024-03-09
@[deprecated] alias continuous_uncurry_left := Continuous.uncurry_left
@[deprecated] alias continuous_uncurry_right := Continuous.uncurry_right
theorem continuous_curry {g : X × Y → Z} (x : X) (h : Continuous g) : Continuous (curry g x) :=
Continuous.uncurry_left x h
#align continuous_curry continuous_curry
theorem IsOpen.prod {s : Set X} {t : Set Y} (hs : IsOpen s) (ht : IsOpen t) : IsOpen (s ×ˢ t) :=
(hs.preimage continuous_fst).inter (ht.preimage continuous_snd)
#align is_open.prod IsOpen.prod
-- Porting note (#11215): TODO: Lean fails to find `t₁` and `t₂` by unification
theorem nhds_prod_eq {x : X} {y : Y} : 𝓝 (x, y) = 𝓝 x ×ˢ 𝓝 y := by
dsimp only [SProd.sprod]
rw [Filter.prod, instTopologicalSpaceProd, nhds_inf (t₁ := TopologicalSpace.induced Prod.fst _)
(t₂ := TopologicalSpace.induced Prod.snd _), nhds_induced, nhds_induced]
#align nhds_prod_eq nhds_prod_eq
-- Porting note: moved from `Topology.ContinuousOn`
theorem nhdsWithin_prod_eq (x : X) (y : Y) (s : Set X) (t : Set Y) :
𝓝[s ×ˢ t] (x, y) = 𝓝[s] x ×ˢ 𝓝[t] y := by
simp only [nhdsWithin, nhds_prod_eq, ← prod_inf_prod, prod_principal_principal]
#align nhds_within_prod_eq nhdsWithin_prod_eq
#noalign continuous_uncurry_of_discrete_topology
theorem mem_nhds_prod_iff {x : X} {y : Y} {s : Set (X × Y)} :
s ∈ 𝓝 (x, y) ↔ ∃ u ∈ 𝓝 x, ∃ v ∈ 𝓝 y, u ×ˢ v ⊆ s := by rw [nhds_prod_eq, mem_prod_iff]
#align mem_nhds_prod_iff mem_nhds_prod_iff
theorem mem_nhdsWithin_prod_iff {x : X} {y : Y} {s : Set (X × Y)} {tx : Set X} {ty : Set Y} :
s ∈ 𝓝[tx ×ˢ ty] (x, y) ↔ ∃ u ∈ 𝓝[tx] x, ∃ v ∈ 𝓝[ty] y, u ×ˢ v ⊆ s := by
rw [nhdsWithin_prod_eq, mem_prod_iff]
-- Porting note: moved up
theorem Filter.HasBasis.prod_nhds {ιX ιY : Type*} {px : ιX → Prop} {py : ιY → Prop}
{sx : ιX → Set X} {sy : ιY → Set Y} {x : X} {y : Y} (hx : (𝓝 x).HasBasis px sx)
(hy : (𝓝 y).HasBasis py sy) :
(𝓝 (x, y)).HasBasis (fun i : ιX × ιY => px i.1 ∧ py i.2) fun i => sx i.1 ×ˢ sy i.2 := by
rw [nhds_prod_eq]
exact hx.prod hy
#align filter.has_basis.prod_nhds Filter.HasBasis.prod_nhds
-- Porting note: moved up
theorem Filter.HasBasis.prod_nhds' {ιX ιY : Type*} {pX : ιX → Prop} {pY : ιY → Prop}
{sx : ιX → Set X} {sy : ιY → Set Y} {p : X × Y} (hx : (𝓝 p.1).HasBasis pX sx)
(hy : (𝓝 p.2).HasBasis pY sy) :
(𝓝 p).HasBasis (fun i : ιX × ιY => pX i.1 ∧ pY i.2) fun i => sx i.1 ×ˢ sy i.2 :=
hx.prod_nhds hy
#align filter.has_basis.prod_nhds' Filter.HasBasis.prod_nhds'
theorem mem_nhds_prod_iff' {x : X} {y : Y} {s : Set (X × Y)} :
s ∈ 𝓝 (x, y) ↔ ∃ u v, IsOpen u ∧ x ∈ u ∧ IsOpen v ∧ y ∈ v ∧ u ×ˢ v ⊆ s :=
((nhds_basis_opens x).prod_nhds (nhds_basis_opens y)).mem_iff.trans <| by
simp only [Prod.exists, and_comm, and_assoc, and_left_comm]
#align mem_nhds_prod_iff' mem_nhds_prod_iff'
theorem Prod.tendsto_iff {X} (seq : X → Y × Z) {f : Filter X} (p : Y × Z) :
Tendsto seq f (𝓝 p) ↔
Tendsto (fun n => (seq n).fst) f (𝓝 p.fst) ∧ Tendsto (fun n => (seq n).snd) f (𝓝 p.snd) := by
rw [nhds_prod_eq, Filter.tendsto_prod_iff']
#align prod.tendsto_iff Prod.tendsto_iff
instance [DiscreteTopology X] [DiscreteTopology Y] : DiscreteTopology (X × Y) :=
discreteTopology_iff_nhds.2 fun (a, b) => by
rw [nhds_prod_eq, nhds_discrete X, nhds_discrete Y, prod_pure_pure]
theorem prod_mem_nhds_iff {s : Set X} {t : Set Y} {x : X} {y : Y} :
s ×ˢ t ∈ 𝓝 (x, y) ↔ s ∈ 𝓝 x ∧ t ∈ 𝓝 y := by rw [nhds_prod_eq, prod_mem_prod_iff]
#align prod_mem_nhds_iff prod_mem_nhds_iff
theorem prod_mem_nhds {s : Set X} {t : Set Y} {x : X} {y : Y} (hx : s ∈ 𝓝 x) (hy : t ∈ 𝓝 y) :
s ×ˢ t ∈ 𝓝 (x, y) :=
prod_mem_nhds_iff.2 ⟨hx, hy⟩
#align prod_mem_nhds prod_mem_nhds
theorem isOpen_setOf_disjoint_nhds_nhds : IsOpen { p : X × X | Disjoint (𝓝 p.1) (𝓝 p.2) } := by
simp only [isOpen_iff_mem_nhds, Prod.forall, mem_setOf_eq]
intro x y h
obtain ⟨U, hU, V, hV, hd⟩ := ((nhds_basis_opens x).disjoint_iff (nhds_basis_opens y)).mp h
exact mem_nhds_prod_iff'.mpr ⟨U, V, hU.2, hU.1, hV.2, hV.1, fun ⟨x', y'⟩ ⟨hx', hy'⟩ =>
disjoint_of_disjoint_of_mem hd (hU.2.mem_nhds hx') (hV.2.mem_nhds hy')⟩
#align is_open_set_of_disjoint_nhds_nhds isOpen_setOf_disjoint_nhds_nhds
theorem Filter.Eventually.prod_nhds {p : X → Prop} {q : Y → Prop} {x : X} {y : Y}
(hx : ∀ᶠ x in 𝓝 x, p x) (hy : ∀ᶠ y in 𝓝 y, q y) : ∀ᶠ z : X × Y in 𝓝 (x, y), p z.1 ∧ q z.2 :=
prod_mem_nhds hx hy
#align filter.eventually.prod_nhds Filter.Eventually.prod_nhds
theorem nhds_swap (x : X) (y : Y) : 𝓝 (x, y) = (𝓝 (y, x)).map Prod.swap := by
rw [nhds_prod_eq, Filter.prod_comm, nhds_prod_eq]; rfl
#align nhds_swap nhds_swap
theorem Filter.Tendsto.prod_mk_nhds {γ} {x : X} {y : Y} {f : Filter γ} {mx : γ → X} {my : γ → Y}
(hx : Tendsto mx f (𝓝 x)) (hy : Tendsto my f (𝓝 y)) :
Tendsto (fun c => (mx c, my c)) f (𝓝 (x, y)) := by
rw [nhds_prod_eq]; exact Filter.Tendsto.prod_mk hx hy
#align filter.tendsto.prod_mk_nhds Filter.Tendsto.prod_mk_nhds
theorem Filter.Eventually.curry_nhds {p : X × Y → Prop} {x : X} {y : Y}
(h : ∀ᶠ x in 𝓝 (x, y), p x) : ∀ᶠ x' in 𝓝 x, ∀ᶠ y' in 𝓝 y, p (x', y') := by
rw [nhds_prod_eq] at h
exact h.curry
#align filter.eventually.curry_nhds Filter.Eventually.curry_nhds
@[fun_prop]
theorem ContinuousAt.prod {f : X → Y} {g : X → Z} {x : X} (hf : ContinuousAt f x)
(hg : ContinuousAt g x) : ContinuousAt (fun x => (f x, g x)) x :=
hf.prod_mk_nhds hg
#align continuous_at.prod ContinuousAt.prod
theorem ContinuousAt.prod_map {f : X → Z} {g : Y → W} {p : X × Y} (hf : ContinuousAt f p.fst)
(hg : ContinuousAt g p.snd) : ContinuousAt (fun p : X × Y => (f p.1, g p.2)) p :=
hf.fst''.prod hg.snd''
#align continuous_at.prod_map ContinuousAt.prod_map
theorem ContinuousAt.prod_map' {f : X → Z} {g : Y → W} {x : X} {y : Y} (hf : ContinuousAt f x)
(hg : ContinuousAt g y) : ContinuousAt (fun p : X × Y => (f p.1, g p.2)) (x, y) :=
hf.fst'.prod hg.snd'
#align continuous_at.prod_map' ContinuousAt.prod_map'
theorem ContinuousAt.comp₂ {f : Y × Z → W} {g : X → Y} {h : X → Z} {x : X}
(hf : ContinuousAt f (g x, h x)) (hg : ContinuousAt g x) (hh : ContinuousAt h x) :
ContinuousAt (fun x ↦ f (g x, h x)) x :=
ContinuousAt.comp hf (hg.prod hh)
theorem ContinuousAt.comp₂_of_eq {f : Y × Z → W} {g : X → Y} {h : X → Z} {x : X} {y : Y × Z}
(hf : ContinuousAt f y) (hg : ContinuousAt g x) (hh : ContinuousAt h x) (e : (g x, h x) = y) :
ContinuousAt (fun x ↦ f (g x, h x)) x := by
rw [← e] at hf
exact hf.comp₂ hg hh
/-- Continuous functions on products are continuous in their first argument -/
theorem Continuous.curry_left {f : X × Y → Z} (hf : Continuous f) {y : Y} :
Continuous fun x ↦ f (x, y) :=
hf.comp (continuous_id.prod_mk continuous_const)
alias Continuous.along_fst := Continuous.curry_left
/-- Continuous functions on products are continuous in their second argument -/
theorem Continuous.curry_right {f : X × Y → Z} (hf : Continuous f) {x : X} :
Continuous fun y ↦ f (x, y) :=
hf.comp (continuous_const.prod_mk continuous_id)
alias Continuous.along_snd := Continuous.curry_right
-- todo: prove a version of `generateFrom_union` with `image2 (∩) s t` in the LHS and use it here
theorem prod_generateFrom_generateFrom_eq {X Y : Type*} {s : Set (Set X)} {t : Set (Set Y)}
(hs : ⋃₀ s = univ) (ht : ⋃₀ t = univ) :
@instTopologicalSpaceProd X Y (generateFrom s) (generateFrom t) =
generateFrom (image2 (· ×ˢ ·) s t) :=
let G := generateFrom (image2 (· ×ˢ ·) s t)
le_antisymm
(le_generateFrom fun g ⟨u, hu, v, hv, g_eq⟩ =>
g_eq.symm ▸
@IsOpen.prod _ _ (generateFrom s) (generateFrom t) _ _ (GenerateOpen.basic _ hu)
(GenerateOpen.basic _ hv))
(le_inf
(coinduced_le_iff_le_induced.mp <|
le_generateFrom fun u hu =>
have : ⋃ v ∈ t, u ×ˢ v = Prod.fst ⁻¹' u := by
simp_rw [← prod_iUnion, ← sUnion_eq_biUnion, ht, prod_univ]
show G.IsOpen (Prod.fst ⁻¹' u) by
rw [← this]
exact
isOpen_iUnion fun v =>
isOpen_iUnion fun hv => GenerateOpen.basic _ ⟨_, hu, _, hv, rfl⟩)
(coinduced_le_iff_le_induced.mp <|
le_generateFrom fun v hv =>
have : ⋃ u ∈ s, u ×ˢ v = Prod.snd ⁻¹' v := by
simp_rw [← iUnion_prod_const, ← sUnion_eq_biUnion, hs, univ_prod]
show G.IsOpen (Prod.snd ⁻¹' v) by
rw [← this]
exact
isOpen_iUnion fun u =>
isOpen_iUnion fun hu => GenerateOpen.basic _ ⟨_, hu, _, hv, rfl⟩))
#align prod_generate_from_generate_from_eq prod_generateFrom_generateFrom_eq
-- todo: use the previous lemma?
theorem prod_eq_generateFrom :
instTopologicalSpaceProd =
generateFrom { g | ∃ (s : Set X) (t : Set Y), IsOpen s ∧ IsOpen t ∧ g = s ×ˢ t } :=
le_antisymm (le_generateFrom fun g ⟨s, t, hs, ht, g_eq⟩ => g_eq.symm ▸ hs.prod ht)
(le_inf
(forall_mem_image.2 fun t ht =>
GenerateOpen.basic _ ⟨t, univ, by simpa [Set.prod_eq] using ht⟩)
(forall_mem_image.2 fun t ht =>
GenerateOpen.basic _ ⟨univ, t, by simpa [Set.prod_eq] using ht⟩))
#align prod_eq_generate_from prod_eq_generateFrom
-- Porting note (#11215): TODO: align with `mem_nhds_prod_iff'`
theorem isOpen_prod_iff {s : Set (X × Y)} :
IsOpen s ↔ ∀ a b, (a, b) ∈ s →
∃ u v, IsOpen u ∧ IsOpen v ∧ a ∈ u ∧ b ∈ v ∧ u ×ˢ v ⊆ s :=
isOpen_iff_mem_nhds.trans <| by simp_rw [Prod.forall, mem_nhds_prod_iff', and_left_comm]
#align is_open_prod_iff isOpen_prod_iff
/-- A product of induced topologies is induced by the product map -/
theorem prod_induced_induced (f : X → Y) (g : Z → W) :
@instTopologicalSpaceProd X Z (induced f ‹_›) (induced g ‹_›) =
induced (fun p => (f p.1, g p.2)) instTopologicalSpaceProd := by
delta instTopologicalSpaceProd
simp_rw [induced_inf, induced_compose]
rfl
#align prod_induced_induced prod_induced_induced
#noalign continuous_uncurry_of_discrete_topology_left
/-- Given a neighborhood `s` of `(x, x)`, then `(x, x)` has a square open neighborhood
that is a subset of `s`. -/
theorem exists_nhds_square {s : Set (X × X)} {x : X} (hx : s ∈ 𝓝 (x, x)) :
∃ U : Set X, IsOpen U ∧ x ∈ U ∧ U ×ˢ U ⊆ s := by
simpa [nhds_prod_eq, (nhds_basis_opens x).prod_self.mem_iff, and_assoc, and_left_comm] using hx
#align exists_nhds_square exists_nhds_square
/-- `Prod.fst` maps neighborhood of `x : X × Y` within the section `Prod.snd ⁻¹' {x.2}`
to `𝓝 x.1`. -/
theorem map_fst_nhdsWithin (x : X × Y) : map Prod.fst (𝓝[Prod.snd ⁻¹' {x.2}] x) = 𝓝 x.1 := by
refine le_antisymm (continuousAt_fst.mono_left inf_le_left) fun s hs => ?_
rcases x with ⟨x, y⟩
rw [mem_map, nhdsWithin, mem_inf_principal, mem_nhds_prod_iff] at hs
rcases hs with ⟨u, hu, v, hv, H⟩
simp only [prod_subset_iff, mem_singleton_iff, mem_setOf_eq, mem_preimage] at H
exact mem_of_superset hu fun z hz => H _ hz _ (mem_of_mem_nhds hv) rfl
#align map_fst_nhds_within map_fst_nhdsWithin
@[simp]
theorem map_fst_nhds (x : X × Y) : map Prod.fst (𝓝 x) = 𝓝 x.1 :=
le_antisymm continuousAt_fst <| (map_fst_nhdsWithin x).symm.trans_le (map_mono inf_le_left)
#align map_fst_nhds map_fst_nhds
/-- The first projection in a product of topological spaces sends open sets to open sets. -/
theorem isOpenMap_fst : IsOpenMap (@Prod.fst X Y) :=
isOpenMap_iff_nhds_le.2 fun x => (map_fst_nhds x).ge
#align is_open_map_fst isOpenMap_fst
/-- `Prod.snd` maps neighborhood of `x : X × Y` within the section `Prod.fst ⁻¹' {x.1}`
to `𝓝 x.2`. -/
theorem map_snd_nhdsWithin (x : X × Y) : map Prod.snd (𝓝[Prod.fst ⁻¹' {x.1}] x) = 𝓝 x.2 := by
refine le_antisymm (continuousAt_snd.mono_left inf_le_left) fun s hs => ?_
rcases x with ⟨x, y⟩
rw [mem_map, nhdsWithin, mem_inf_principal, mem_nhds_prod_iff] at hs
rcases hs with ⟨u, hu, v, hv, H⟩
simp only [prod_subset_iff, mem_singleton_iff, mem_setOf_eq, mem_preimage] at H
exact mem_of_superset hv fun z hz => H _ (mem_of_mem_nhds hu) _ hz rfl
#align map_snd_nhds_within map_snd_nhdsWithin
@[simp]
theorem map_snd_nhds (x : X × Y) : map Prod.snd (𝓝 x) = 𝓝 x.2 :=
le_antisymm continuousAt_snd <| (map_snd_nhdsWithin x).symm.trans_le (map_mono inf_le_left)
#align map_snd_nhds map_snd_nhds
/-- The second projection in a product of topological spaces sends open sets to open sets. -/
theorem isOpenMap_snd : IsOpenMap (@Prod.snd X Y) :=
isOpenMap_iff_nhds_le.2 fun x => (map_snd_nhds x).ge
#align is_open_map_snd isOpenMap_snd
/-- A product set is open in a product space if and only if each factor is open, or one of them is
empty -/
theorem isOpen_prod_iff' {s : Set X} {t : Set Y} :
IsOpen (s ×ˢ t) ↔ IsOpen s ∧ IsOpen t ∨ s = ∅ ∨ t = ∅ := by
rcases (s ×ˢ t).eq_empty_or_nonempty with h | h
· simp [h, prod_eq_empty_iff.1 h]
· have st : s.Nonempty ∧ t.Nonempty := prod_nonempty_iff.1 h
constructor
· intro (H : IsOpen (s ×ˢ t))
refine Or.inl ⟨?_, ?_⟩
· show IsOpen s
rw [← fst_image_prod s st.2]
exact isOpenMap_fst _ H
· show IsOpen t
rw [← snd_image_prod st.1 t]
exact isOpenMap_snd _ H
· intro H
simp only [st.1.ne_empty, st.2.ne_empty, not_false_iff, or_false_iff] at H
exact H.1.prod H.2
#align is_open_prod_iff' isOpen_prod_iff'
theorem closure_prod_eq {s : Set X} {t : Set Y} : closure (s ×ˢ t) = closure s ×ˢ closure t :=
ext fun ⟨a, b⟩ => by
simp_rw [mem_prod, mem_closure_iff_nhdsWithin_neBot, nhdsWithin_prod_eq, prod_neBot]
#align closure_prod_eq closure_prod_eq
theorem interior_prod_eq (s : Set X) (t : Set Y) : interior (s ×ˢ t) = interior s ×ˢ interior t :=
ext fun ⟨a, b⟩ => by simp only [mem_interior_iff_mem_nhds, mem_prod, prod_mem_nhds_iff]
#align interior_prod_eq interior_prod_eq
theorem frontier_prod_eq (s : Set X) (t : Set Y) :
frontier (s ×ˢ t) = closure s ×ˢ frontier t ∪ frontier s ×ˢ closure t := by
simp only [frontier, closure_prod_eq, interior_prod_eq, prod_diff_prod]
#align frontier_prod_eq frontier_prod_eq
@[simp]
theorem frontier_prod_univ_eq (s : Set X) :
frontier (s ×ˢ (univ : Set Y)) = frontier s ×ˢ univ := by
simp [frontier_prod_eq]
#align frontier_prod_univ_eq frontier_prod_univ_eq
@[simp]
theorem frontier_univ_prod_eq (s : Set Y) :
frontier ((univ : Set X) ×ˢ s) = univ ×ˢ frontier s := by
simp [frontier_prod_eq]
#align frontier_univ_prod_eq frontier_univ_prod_eq
theorem map_mem_closure₂ {f : X → Y → Z} {x : X} {y : Y} {s : Set X} {t : Set Y} {u : Set Z}
(hf : Continuous (uncurry f)) (hx : x ∈ closure s) (hy : y ∈ closure t)
(h : ∀ a ∈ s, ∀ b ∈ t, f a b ∈ u) : f x y ∈ closure u :=
have H₁ : (x, y) ∈ closure (s ×ˢ t) := by simpa only [closure_prod_eq] using mk_mem_prod hx hy
have H₂ : MapsTo (uncurry f) (s ×ˢ t) u := forall_prod_set.2 h
H₂.closure hf H₁
#align map_mem_closure₂ map_mem_closure₂
theorem IsClosed.prod {s₁ : Set X} {s₂ : Set Y} (h₁ : IsClosed s₁) (h₂ : IsClosed s₂) :
IsClosed (s₁ ×ˢ s₂) :=
closure_eq_iff_isClosed.mp <| by simp only [h₁.closure_eq, h₂.closure_eq, closure_prod_eq]
#align is_closed.prod IsClosed.prod
/-- The product of two dense sets is a dense set. -/
theorem Dense.prod {s : Set X} {t : Set Y} (hs : Dense s) (ht : Dense t) : Dense (s ×ˢ t) :=
fun x => by
rw [closure_prod_eq]
exact ⟨hs x.1, ht x.2⟩
#align dense.prod Dense.prod
/-- If `f` and `g` are maps with dense range, then `Prod.map f g` has dense range. -/
theorem DenseRange.prod_map {ι : Type*} {κ : Type*} {f : ι → Y} {g : κ → Z} (hf : DenseRange f)
(hg : DenseRange g) : DenseRange (Prod.map f g) := by
simpa only [DenseRange, prod_range_range_eq] using hf.prod hg
#align dense_range.prod_map DenseRange.prod_map
theorem Inducing.prod_map {f : X → Y} {g : Z → W} (hf : Inducing f) (hg : Inducing g) :
Inducing (Prod.map f g) :=
inducing_iff_nhds.2 fun (x, z) => by simp_rw [Prod.map_def, nhds_prod_eq, hf.nhds_eq_comap,
hg.nhds_eq_comap, prod_comap_comap_eq]
#align inducing.prod_mk Inducing.prod_map
@[simp]
theorem inducing_const_prod {x : X} {f : Y → Z} : (Inducing fun x' => (x, f x')) ↔ Inducing f := by
simp_rw [inducing_iff, instTopologicalSpaceProd, induced_inf, induced_compose, Function.comp,
induced_const, top_inf_eq]
#align inducing_const_prod inducing_const_prod
@[simp]
theorem inducing_prod_const {y : Y} {f : X → Z} : (Inducing fun x => (f x, y)) ↔ Inducing f := by
simp_rw [inducing_iff, instTopologicalSpaceProd, induced_inf, induced_compose, Function.comp,
induced_const, inf_top_eq]
#align inducing_prod_const inducing_prod_const
theorem Embedding.prod_map {f : X → Y} {g : Z → W} (hf : Embedding f) (hg : Embedding g) :
Embedding (Prod.map f g) :=
{ hf.toInducing.prod_map hg.toInducing with
inj := fun ⟨x₁, z₁⟩ ⟨x₂, z₂⟩ => by simp [hf.inj.eq_iff, hg.inj.eq_iff] }
#align embedding.prod_mk Embedding.prod_map
protected theorem IsOpenMap.prod {f : X → Y} {g : Z → W} (hf : IsOpenMap f) (hg : IsOpenMap g) :
IsOpenMap fun p : X × Z => (f p.1, g p.2) := by
rw [isOpenMap_iff_nhds_le]
rintro ⟨a, b⟩
rw [nhds_prod_eq, nhds_prod_eq, ← Filter.prod_map_map_eq]
exact Filter.prod_mono (hf.nhds_le a) (hg.nhds_le b)
#align is_open_map.prod IsOpenMap.prod
protected theorem OpenEmbedding.prod {f : X → Y} {g : Z → W} (hf : OpenEmbedding f)
(hg : OpenEmbedding g) : OpenEmbedding fun x : X × Z => (f x.1, g x.2) :=
openEmbedding_of_embedding_open (hf.1.prod_map hg.1) (hf.isOpenMap.prod hg.isOpenMap)
#align open_embedding.prod OpenEmbedding.prod
theorem embedding_graph {f : X → Y} (hf : Continuous f) : Embedding fun x => (x, f x) :=
embedding_of_embedding_compose (continuous_id.prod_mk hf) continuous_fst embedding_id
#align embedding_graph embedding_graph
theorem embedding_prod_mk (x : X) : Embedding (Prod.mk x : Y → X × Y) :=
embedding_of_embedding_compose (Continuous.Prod.mk x) continuous_snd embedding_id
end Prod
section Bool
lemma continuous_bool_rng [TopologicalSpace X] {f : X → Bool} (b : Bool) :
Continuous f ↔ IsClopen (f ⁻¹' {b}) := by
rw [continuous_discrete_rng, Bool.forall_bool' b, IsClopen, ← isOpen_compl_iff, ← preimage_compl,
Bool.compl_singleton, and_comm]
end Bool
section Sum
open Sum
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace W]
theorem continuous_sum_dom {f : X ⊕ Y → Z} :
Continuous f ↔ Continuous (f ∘ Sum.inl) ∧ Continuous (f ∘ Sum.inr) :=
(continuous_sup_dom (t₁ := TopologicalSpace.coinduced Sum.inl _)
(t₂ := TopologicalSpace.coinduced Sum.inr _)).trans <|
continuous_coinduced_dom.and continuous_coinduced_dom
#align continuous_sum_dom continuous_sum_dom
theorem continuous_sum_elim {f : X → Z} {g : Y → Z} :
Continuous (Sum.elim f g) ↔ Continuous f ∧ Continuous g :=
continuous_sum_dom
#align continuous_sum_elim continuous_sum_elim
@[continuity]
theorem Continuous.sum_elim {f : X → Z} {g : Y → Z} (hf : Continuous f) (hg : Continuous g) :
Continuous (Sum.elim f g) :=
continuous_sum_elim.2 ⟨hf, hg⟩
#align continuous.sum_elim Continuous.sum_elim
@[continuity]
theorem continuous_isLeft : Continuous (isLeft : X ⊕ Y → Bool) :=
continuous_sum_dom.2 ⟨continuous_const, continuous_const⟩
@[continuity]
theorem continuous_isRight : Continuous (isRight : X ⊕ Y → Bool) :=
continuous_sum_dom.2 ⟨continuous_const, continuous_const⟩
@[continuity]
-- Porting note: the proof was `continuous_sup_rng_left continuous_coinduced_rng`
theorem continuous_inl : Continuous (@inl X Y) := ⟨fun _ => And.left⟩
#align continuous_inl continuous_inl
@[continuity]
-- Porting note: the proof was `continuous_sup_rng_right continuous_coinduced_rng`
theorem continuous_inr : Continuous (@inr X Y) := ⟨fun _ => And.right⟩
#align continuous_inr continuous_inr
theorem isOpen_sum_iff {s : Set (X ⊕ Y)} : IsOpen s ↔ IsOpen (inl ⁻¹' s) ∧ IsOpen (inr ⁻¹' s) :=
Iff.rfl
#align is_open_sum_iff isOpen_sum_iff
-- Porting note (#10756): new theorem
theorem isClosed_sum_iff {s : Set (X ⊕ Y)} :
IsClosed s ↔ IsClosed (inl ⁻¹' s) ∧ IsClosed (inr ⁻¹' s) := by
simp only [← isOpen_compl_iff, isOpen_sum_iff, preimage_compl]
theorem isOpenMap_inl : IsOpenMap (@inl X Y) := fun u hu => by
simpa [isOpen_sum_iff, preimage_image_eq u Sum.inl_injective]
#align is_open_map_inl isOpenMap_inl
theorem isOpenMap_inr : IsOpenMap (@inr X Y) := fun u hu => by
simpa [isOpen_sum_iff, preimage_image_eq u Sum.inr_injective]
#align is_open_map_inr isOpenMap_inr
theorem openEmbedding_inl : OpenEmbedding (@inl X Y) :=
openEmbedding_of_continuous_injective_open continuous_inl inl_injective isOpenMap_inl
#align open_embedding_inl openEmbedding_inl
theorem openEmbedding_inr : OpenEmbedding (@inr X Y) :=
openEmbedding_of_continuous_injective_open continuous_inr inr_injective isOpenMap_inr
#align open_embedding_inr openEmbedding_inr
theorem embedding_inl : Embedding (@inl X Y) :=
openEmbedding_inl.1
#align embedding_inl embedding_inl
theorem embedding_inr : Embedding (@inr X Y) :=
openEmbedding_inr.1
#align embedding_inr embedding_inr
theorem isOpen_range_inl : IsOpen (range (inl : X → X ⊕ Y)) :=
openEmbedding_inl.2
#align is_open_range_inl isOpen_range_inl
theorem isOpen_range_inr : IsOpen (range (inr : Y → X ⊕ Y)) :=
openEmbedding_inr.2
#align is_open_range_inr isOpen_range_inr
theorem isClosed_range_inl : IsClosed (range (inl : X → X ⊕ Y)) := by
rw [← isOpen_compl_iff, compl_range_inl]
exact isOpen_range_inr
#align is_closed_range_inl isClosed_range_inl
| Mathlib/Topology/Constructions.lean | 1,008 | 1,010 | theorem isClosed_range_inr : IsClosed (range (inr : Y → X ⊕ Y)) := by |
rw [← isOpen_compl_iff, compl_range_inr]
exact isOpen_range_inl
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Geometry.Euclidean.Angle.Oriented.Affine
import Mathlib.Geometry.Euclidean.Angle.Unoriented.RightAngle
#align_import geometry.euclidean.angle.oriented.right_angle from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Oriented angles in right-angled triangles.
This file proves basic geometrical results about distances and oriented angles in (possibly
degenerate) right-angled triangles in real inner product spaces and Euclidean affine spaces.
-/
noncomputable section
open scoped EuclideanGeometry
open scoped Real
open scoped RealInnerProductSpace
namespace Orientation
open FiniteDimensional
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable [hd2 : Fact (finrank ℝ V = 2)] (o : Orientation ℝ V (Fin 2))
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arccos (‖x‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arccos_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arccos (‖y‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arcsin (‖y‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arcsin_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arcsin (‖x‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arctan (‖y‖ / ‖x‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arctan_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h) (o.left_ne_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arctan (‖x‖ / ‖y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle x (x + y)) = ‖x‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle (x + y) y) = ‖y‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle x (x + y)) = ‖y‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle (x + y) y) = ‖x‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle x (x + y)) = ‖y‖ / ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle (x + y) y) = ‖x‖ / ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle x (x + y)) * ‖x + y‖ = ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle (x + y) y) * ‖x + y‖ = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle x (x + y)) * ‖x + y‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle (x + y) y) * ‖x + y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle x (x + y)) * ‖x‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle (x + y) y) * ‖y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.cos (o.oangle x (x + y)) = ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.norm_div_cos_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.cos (o.oangle (x + y) y) = ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_cos_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_add_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.sin (o.oangle x (x + y)) = ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.norm_div_sin_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.sin (o.oangle (x + y) y) = ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_sin_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_add_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.tan (o.oangle x (x + y)) = ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.norm_div_tan_angle_add_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.tan (o.oangle (x + y) y) = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).norm_div_tan_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_add_left_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arccos (‖y‖ / ‖y - x‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arccos_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arccos (‖x‖ / ‖x - y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arccos_of_oangle_eq_pi_div_two h
#align orientation.oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_sub_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arcsin (‖x‖ / ‖y - x‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arcsin_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
theorem oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arcsin (‖y‖ / ‖x - y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arcsin_of_oangle_eq_pi_div_two h
#align orientation.oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_sub_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, version subtracting vectors. -/
theorem oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle y (y - x) = Real.arctan (‖x‖ / ‖y‖) := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_sub_eq_arctan_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h) (o.right_ne_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, version subtracting vectors. -/
theorem oangle_sub_left_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x - y) x = Real.arctan (‖y‖ / ‖x‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).oangle_sub_right_eq_arctan_of_oangle_eq_pi_div_two h
#align orientation.oangle_sub_left_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_sub_left_eq_arctan_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem cos_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle y (y - x)) = ‖y‖ / ‖y - x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.cos_oangle_sub_right_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem cos_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle (x - y) x) = ‖x‖ / ‖x - y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).cos_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.cos_oangle_sub_left_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem sin_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle y (y - x)) = ‖x‖ / ‖y - x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.sin_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.sin_oangle_sub_right_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem sin_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle (x - y) x) = ‖y‖ / ‖x - y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).sin_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.sin_oangle_sub_left_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem tan_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle y (y - x)) = ‖x‖ / ‖y‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.tan_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.tan_oangle_sub_right_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
theorem tan_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle (x - y) x) = ‖y‖ / ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).tan_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.tan_oangle_sub_left_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side, version subtracting vectors. -/
theorem cos_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle y (y - x)) * ‖y - x‖ = ‖y‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_sub_mul_norm_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side, version subtracting vectors. -/
theorem cos_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle (x - y) x) * ‖x - y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).cos_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side, version subtracting vectors. -/
theorem sin_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle y (y - x)) * ‖y - x‖ = ‖x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_sub_mul_norm_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.sin_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side, version subtracting vectors. -/
theorem sin_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle (x - y) x) * ‖x - y‖ = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).sin_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side, version subtracting vectors. -/
theorem tan_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle y (y - x)) * ‖y‖ = ‖x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_sub_mul_norm_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.tan_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side, version subtracting vectors. -/
theorem tan_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle (x - y) x) * ‖x‖ = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).tan_oangle_sub_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_sub_left_mul_norm_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse, version subtracting vectors. -/
theorem norm_div_cos_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.cos (o.oangle y (y - x)) = ‖y - x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.norm_div_cos_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.right_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_cos_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_sub_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse, version subtracting vectors. -/
theorem norm_div_cos_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.cos (o.oangle (x - y) x) = ‖x - y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).norm_div_cos_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_cos_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.norm_div_cos_oangle_sub_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse, version subtracting vectors. -/
theorem norm_div_sin_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.sin (o.oangle y (y - x)) = ‖y - x‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.norm_div_sin_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_sin_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_sub_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse, version subtracting vectors. -/
theorem norm_div_sin_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.sin (o.oangle (x - y) x) = ‖x - y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).norm_div_sin_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_sin_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.norm_div_sin_oangle_sub_left_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side, version subtracting vectors. -/
theorem norm_div_tan_oangle_sub_right_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖x‖ / Real.Angle.tan (o.oangle y (y - x)) = ‖y‖ := by
have hs : (o.oangle y (y - x)).sign = 1 := by
rw [oangle_sign_sub_right_swap, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.norm_div_tan_angle_sub_of_inner_eq_zero
(o.inner_rev_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inr (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.norm_div_tan_oangle_sub_right_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_sub_right_of_oangle_eq_pi_div_two
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side, version subtracting vectors. -/
theorem norm_div_tan_oangle_sub_left_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : ‖y‖ / Real.Angle.tan (o.oangle (x - y) x) = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
exact (-o).norm_div_tan_oangle_sub_right_of_oangle_eq_pi_div_two h
#align orientation.norm_div_tan_oangle_sub_left_of_oangle_eq_pi_div_two Orientation.norm_div_tan_oangle_sub_left_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, where one side is a multiple
of a rotation of another by `π / 2`. -/
theorem oangle_add_right_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
o.oangle x (x + r • o.rotation (π / 2 : ℝ) x) = Real.arctan r := by
rcases lt_trichotomy r 0 with (hr | rfl | hr)
· have ha : o.oangle x (r • o.rotation (π / 2 : ℝ) x) = -(π / 2 : ℝ) := by
rw [o.oangle_smul_right_of_neg _ _ hr, o.oangle_neg_right h, o.oangle_rotation_self_right h, ←
sub_eq_zero, add_comm, sub_neg_eq_add, ← Real.Angle.coe_add, ← Real.Angle.coe_add,
add_assoc, add_halves, ← two_mul, Real.Angle.coe_two_pi]
simpa using h
-- Porting note: if the type is not given in `neg_neg` then Lean "forgets" about the instance
-- `Neg (Orientation ℝ V (Fin 2))`
rw [← neg_inj, ← oangle_neg_orientation_eq_neg, @neg_neg Real.Angle] at ha
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj, oangle_rev,
(-o).oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two ha, norm_smul,
LinearIsometryEquiv.norm_map, mul_div_assoc, div_self (norm_ne_zero_iff.2 h), mul_one,
Real.norm_eq_abs, abs_of_neg hr, Real.arctan_neg, Real.Angle.coe_neg, neg_neg]
· rw [zero_smul, add_zero, oangle_self, Real.arctan_zero, Real.Angle.coe_zero]
· have ha : o.oangle x (r • o.rotation (π / 2 : ℝ) x) = (π / 2 : ℝ) := by
rw [o.oangle_smul_right_of_pos _ _ hr, o.oangle_rotation_self_right h]
rw [o.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two ha, norm_smul,
LinearIsometryEquiv.norm_map, mul_div_assoc, div_self (norm_ne_zero_iff.2 h), mul_one,
Real.norm_eq_abs, abs_of_pos hr]
#align orientation.oangle_add_right_smul_rotation_pi_div_two Orientation.oangle_add_right_smul_rotation_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, where one side is a multiple
of a rotation of another by `π / 2`. -/
theorem oangle_add_left_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
o.oangle (x + r • o.rotation (π / 2 : ℝ) x) (r • o.rotation (π / 2 : ℝ) x)
= Real.arctan r⁻¹ := by
by_cases hr : r = 0; · simp [hr]
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj, ←
neg_neg ((π / 2 : ℝ) : Real.Angle), ← rotation_neg_orientation_eq_neg, add_comm]
have hx : x = r⁻¹ • (-o).rotation (π / 2 : ℝ) (r • (-o).rotation (-(π / 2 : ℝ)) x) := by simp [hr]
nth_rw 3 [hx]
refine (-o).oangle_add_right_smul_rotation_pi_div_two ?_ _
simp [hr, h]
#align orientation.oangle_add_left_smul_rotation_pi_div_two Orientation.oangle_add_left_smul_rotation_pi_div_two
/-- The tangent of an angle in a right-angled triangle, where one side is a multiple of a
rotation of another by `π / 2`. -/
theorem tan_oangle_add_right_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
Real.Angle.tan (o.oangle x (x + r • o.rotation (π / 2 : ℝ) x)) = r := by
rw [o.oangle_add_right_smul_rotation_pi_div_two h, Real.Angle.tan_coe, Real.tan_arctan]
#align orientation.tan_oangle_add_right_smul_rotation_pi_div_two Orientation.tan_oangle_add_right_smul_rotation_pi_div_two
/-- The tangent of an angle in a right-angled triangle, where one side is a multiple of a
rotation of another by `π / 2`. -/
theorem tan_oangle_add_left_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
Real.Angle.tan (o.oangle (x + r • o.rotation (π / 2 : ℝ) x) (r • o.rotation (π / 2 : ℝ) x)) =
r⁻¹ := by
rw [o.oangle_add_left_smul_rotation_pi_div_two h, Real.Angle.tan_coe, Real.tan_arctan]
#align orientation.tan_oangle_add_left_smul_rotation_pi_div_two Orientation.tan_oangle_add_left_smul_rotation_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, where one side is a multiple
of a rotation of another by `π / 2`, version subtracting vectors. -/
theorem oangle_sub_right_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
o.oangle (r • o.rotation (π / 2 : ℝ) x) (r • o.rotation (π / 2 : ℝ) x - x)
= Real.arctan r⁻¹ := by
by_cases hr : r = 0; · simp [hr]
have hx : -x = r⁻¹ • o.rotation (π / 2 : ℝ) (r • o.rotation (π / 2 : ℝ) x) := by
simp [hr, ← Real.Angle.coe_add]
rw [sub_eq_add_neg, hx, o.oangle_add_right_smul_rotation_pi_div_two]
simpa [hr] using h
#align orientation.oangle_sub_right_smul_rotation_pi_div_two Orientation.oangle_sub_right_smul_rotation_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`, where one side is a multiple
of a rotation of another by `π / 2`, version subtracting vectors. -/
theorem oangle_sub_left_smul_rotation_pi_div_two {x : V} (h : x ≠ 0) (r : ℝ) :
o.oangle (x - r • o.rotation (π / 2 : ℝ) x) x = Real.arctan r := by
by_cases hr : r = 0; · simp [hr]
have hx : x = r⁻¹ • o.rotation (π / 2 : ℝ) (-(r • o.rotation (π / 2 : ℝ) x)) := by
simp [hr, ← Real.Angle.coe_add]
rw [sub_eq_add_neg, add_comm]
nth_rw 3 [hx]
nth_rw 2 [hx]
rw [o.oangle_add_left_smul_rotation_pi_div_two, inv_inv]
simpa [hr] using h
#align orientation.oangle_sub_left_smul_rotation_pi_div_two Orientation.oangle_sub_left_smul_rotation_pi_div_two
end Orientation
namespace EuclideanGeometry
open FiniteDimensional
variable {V : Type*} {P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
[NormedAddTorsor V P] [hd2 : Fact (finrank ℝ V = 2)] [Module.Oriented ℝ V (Fin 2)]
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_right_eq_arccos_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₂ p₃ p₁ = Real.arccos (dist p₃ p₂ / dist p₁ p₃) := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs,
angle_eq_arccos_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)]
#align euclidean_geometry.oangle_right_eq_arccos_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_left_eq_arccos_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₃ p₁ p₂ = Real.arccos (dist p₁ p₂ / dist p₁ p₃) := by
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm,
angle_eq_arccos_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h),
dist_comm p₁ p₃]
#align euclidean_geometry.oangle_left_eq_arccos_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_right_eq_arcsin_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₂ p₃ p₁ = Real.arcsin (dist p₁ p₂ / dist p₁ p₃) := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs,
angle_eq_arcsin_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(Or.inl (left_ne_of_oangle_eq_pi_div_two h))]
#align euclidean_geometry.oangle_right_eq_arcsin_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_left_eq_arcsin_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₃ p₁ p₂ = Real.arcsin (dist p₃ p₂ / dist p₁ p₃) := by
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm,
angle_eq_arcsin_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(Or.inr (left_ne_of_oangle_eq_pi_div_two h)),
dist_comm p₁ p₃]
#align euclidean_geometry.oangle_left_eq_arcsin_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_right_eq_arctan_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₂ p₃ p₁ = Real.arctan (dist p₁ p₂ / dist p₃ p₂) := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs,
angle_eq_arctan_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(right_ne_of_oangle_eq_pi_div_two h)]
#align euclidean_geometry.oangle_right_eq_arctan_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_left_eq_arctan_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∡ p₃ p₁ p₂ = Real.arctan (dist p₃ p₂ / dist p₁ p₂) := by
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm,
angle_eq_arctan_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(left_ne_of_oangle_eq_pi_div_two h)]
#align euclidean_geometry.oangle_left_eq_arctan_of_oangle_eq_pi_div_two EuclideanGeometry.oangle_left_eq_arctan_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_right_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.cos (∡ p₂ p₃ p₁) = dist p₃ p₂ / dist p₁ p₃ := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
cos_angle_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)]
#align euclidean_geometry.cos_oangle_right_of_oangle_eq_pi_div_two EuclideanGeometry.cos_oangle_right_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_left_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.cos (∡ p₃ p₁ p₂) = dist p₁ p₂ / dist p₁ p₃ := by
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm, Real.Angle.cos_coe,
cos_angle_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h),
dist_comm p₁ p₃]
#align euclidean_geometry.cos_oangle_left_of_oangle_eq_pi_div_two EuclideanGeometry.cos_oangle_left_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_right_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.sin (∡ p₂ p₃ p₁) = dist p₁ p₂ / dist p₁ p₃ := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
sin_angle_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(Or.inl (left_ne_of_oangle_eq_pi_div_two h))]
#align euclidean_geometry.sin_oangle_right_of_oangle_eq_pi_div_two EuclideanGeometry.sin_oangle_right_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_left_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.sin (∡ p₃ p₁ p₂) = dist p₃ p₂ / dist p₁ p₃ := by
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm, Real.Angle.sin_coe,
sin_angle_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h)
(Or.inr (left_ne_of_oangle_eq_pi_div_two h)),
dist_comm p₁ p₃]
#align euclidean_geometry.sin_oangle_left_of_oangle_eq_pi_div_two EuclideanGeometry.sin_oangle_left_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_right_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.tan (∡ p₂ p₃ p₁) = dist p₁ p₂ / dist p₃ p₂ := by
have hs : (∡ p₂ p₃ p₁).sign = 1 := by rw [oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
tan_angle_of_angle_eq_pi_div_two (angle_eq_pi_div_two_of_oangle_eq_pi_div_two h)]
#align euclidean_geometry.tan_oangle_right_of_oangle_eq_pi_div_two EuclideanGeometry.tan_oangle_right_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
| Mathlib/Geometry/Euclidean/Angle/Oriented/RightAngle.lean | 682 | 686 | theorem tan_oangle_left_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
Real.Angle.tan (∡ p₃ p₁ p₂) = dist p₃ p₂ / dist p₁ p₂ := by |
have hs : (∡ p₃ p₁ p₂).sign = 1 := by rw [← oangle_rotate_sign, h, Real.Angle.sign_coe_pi_div_two]
rw [oangle_eq_angle_of_sign_eq_one hs, angle_comm, Real.Angle.tan_coe,
tan_angle_of_angle_eq_pi_div_two (angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two h)]
|
/-
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.Algebra.UniformGroup
import Mathlib.Topology.Algebra.UniformMulAction
import Mathlib.Topology.UniformSpace.Completion
#align_import topology.algebra.group_completion from "leanprover-community/mathlib"@"a148d797a1094ab554ad4183a4ad6f130358ef64"
/-!
# Completion of topological groups:
This files endows the completion of a topological abelian group with a group structure.
More precisely the instance `UniformSpace.Completion.addGroup` builds an abelian group structure
on the completion of an abelian group endowed with a compatible uniform structure.
Then the instance `UniformSpace.Completion.uniformAddGroup` proves this group structure is
compatible with the completed uniform structure. The compatibility condition is `UniformAddGroup`.
## Main declarations:
Beyond the instances explained above (that don't have to be explicitly invoked),
the main constructions deal with continuous group morphisms.
* `AddMonoidHom.extension`: extends a continuous group morphism from `G`
to a complete separated group `H` to `Completion G`.
* `AddMonoidHom.completion`: promotes a continuous group morphism
from `G` to `H` into a continuous group morphism
from `Completion G` to `Completion H`.
-/
noncomputable section
variable {M R α β : Type*}
section Group
open UniformSpace CauchyFilter Filter Set
variable [UniformSpace α]
instance [Zero α] : Zero (Completion α) :=
⟨(0 : α)⟩
instance [Neg α] : Neg (Completion α) :=
⟨Completion.map (fun a ↦ -a : α → α)⟩
instance [Add α] : Add (Completion α) :=
⟨Completion.map₂ (· + ·)⟩
instance [Sub α] : Sub (Completion α) :=
⟨Completion.map₂ Sub.sub⟩
@[norm_cast]
theorem UniformSpace.Completion.coe_zero [Zero α] : ((0 : α) : Completion α) = 0 :=
rfl
#align uniform_space.completion.coe_zero UniformSpace.Completion.coe_zero
end Group
namespace UniformSpace.Completion
open UniformSpace
section Zero
instance [UniformSpace α] [MonoidWithZero M] [Zero α] [MulActionWithZero M α]
[UniformContinuousConstSMul M α] : MulActionWithZero M (Completion α) :=
{ (inferInstance : MulAction M <| Completion α) with
smul_zero := fun r ↦ by rw [← coe_zero, ← coe_smul, MulActionWithZero.smul_zero r]
zero_smul :=
ext' (continuous_const_smul _) continuous_const fun a ↦ by
rw [← coe_smul, zero_smul, coe_zero] }
end Zero
section UniformAddGroup
variable [UniformSpace α] [AddGroup α] [UniformAddGroup α]
@[norm_cast]
theorem coe_neg (a : α) : ((-a : α) : Completion α) = -a :=
(map_coe uniformContinuous_neg a).symm
#align uniform_space.completion.coe_neg UniformSpace.Completion.coe_neg
@[norm_cast]
theorem coe_sub (a b : α) : ((a - b : α) : Completion α) = a - b :=
(map₂_coe_coe a b Sub.sub uniformContinuous_sub).symm
#align uniform_space.completion.coe_sub UniformSpace.Completion.coe_sub
@[norm_cast]
theorem coe_add (a b : α) : ((a + b : α) : Completion α) = a + b :=
(map₂_coe_coe a b (· + ·) uniformContinuous_add).symm
#align uniform_space.completion.coe_add UniformSpace.Completion.coe_add
instance : AddMonoid (Completion α) :=
{ (inferInstance : Zero <| Completion α),
(inferInstance : Add <| Completion α) with
zero_add := fun a ↦
Completion.induction_on a
(isClosed_eq (continuous_map₂ continuous_const continuous_id) continuous_id) fun a ↦
show 0 + (a : Completion α) = a by rw [← coe_zero, ← coe_add, zero_add]
add_zero := fun a ↦
Completion.induction_on a
(isClosed_eq (continuous_map₂ continuous_id continuous_const) continuous_id) fun a ↦
show (a : Completion α) + 0 = a by rw [← coe_zero, ← coe_add, add_zero]
add_assoc := fun a b c ↦
Completion.induction_on₃ a b c
(isClosed_eq
(continuous_map₂ (continuous_map₂ continuous_fst (continuous_fst.comp continuous_snd))
(continuous_snd.comp continuous_snd))
(continuous_map₂ continuous_fst
(continuous_map₂ (continuous_fst.comp continuous_snd)
(continuous_snd.comp continuous_snd))))
fun a b c ↦
show (a : Completion α) + b + c = a + (b + c) by repeat' rw_mod_cast [add_assoc]
nsmul := (· • ·)
nsmul_zero := fun a ↦
Completion.induction_on a (isClosed_eq continuous_map continuous_const) fun a ↦
show 0 • (a : Completion α) = 0 by rw [← coe_smul, ← coe_zero, zero_smul]
nsmul_succ := fun n a ↦
Completion.induction_on a
(isClosed_eq continuous_map <| continuous_map₂ continuous_map continuous_id) fun a ↦
show (n + 1) • (a : Completion α) = n • (a : Completion α) + (a : Completion α) by
rw [← coe_smul, succ_nsmul, coe_add, coe_smul] }
instance : SubNegMonoid (Completion α) :=
{ (inferInstance : AddMonoid <| Completion α),
(inferInstance : Neg <| Completion α),
(inferInstance : Sub <| Completion α) with
sub_eq_add_neg := fun a b ↦
Completion.induction_on₂ a b
(isClosed_eq (continuous_map₂ continuous_fst continuous_snd)
(continuous_map₂ continuous_fst (Completion.continuous_map.comp continuous_snd)))
fun a b ↦ mod_cast congr_arg ((↑) : α → Completion α) (sub_eq_add_neg a b)
zsmul := (· • ·)
zsmul_zero' := fun a ↦
Completion.induction_on a (isClosed_eq continuous_map continuous_const) fun a ↦
show (0 : ℤ) • (a : Completion α) = 0 by rw [← coe_smul, ← coe_zero, zero_smul]
zsmul_succ' := fun n a ↦
Completion.induction_on a
(isClosed_eq continuous_map <| continuous_map₂ continuous_map continuous_id) fun a ↦
show Int.ofNat n.succ • (a : Completion α) = _ by
rw [← coe_smul, show Int.ofNat n.succ • a = Int.ofNat n • a + a from
SubNegMonoid.zsmul_succ' n a, coe_add, coe_smul]
zsmul_neg' := fun n a ↦
Completion.induction_on a
(isClosed_eq continuous_map <| Completion.continuous_map.comp continuous_map) fun a ↦
show (Int.negSucc n) • (a : Completion α) = _ by
rw [← coe_smul, show (Int.negSucc n) • a = -((n.succ : ℤ) • a) from
SubNegMonoid.zsmul_neg' n a, coe_neg, coe_smul] }
instance addGroup : AddGroup (Completion α) :=
{ (inferInstance : SubNegMonoid <| Completion α) with
add_left_neg := fun a ↦
Completion.induction_on a
(isClosed_eq (continuous_map₂ Completion.continuous_map continuous_id) continuous_const)
fun a ↦
show -(a : Completion α) + a = 0 by
rw_mod_cast [add_left_neg]
rfl }
instance uniformAddGroup : UniformAddGroup (Completion α) :=
⟨uniformContinuous_map₂ Sub.sub⟩
instance {M} [Monoid M] [DistribMulAction M α] [UniformContinuousConstSMul M α] :
DistribMulAction M (Completion α) :=
{ (inferInstance : MulAction M <| Completion α) with
smul_add := fun r x y ↦
induction_on₂ x y
(isClosed_eq ((continuous_fst.add continuous_snd).const_smul _)
((continuous_fst.const_smul _).add (continuous_snd.const_smul _)))
fun a b ↦ by simp only [← coe_add, ← coe_smul, smul_add]
smul_zero := fun r ↦ by rw [← coe_zero, ← coe_smul, smul_zero r] }
/-- The map from a group to its completion as a group hom. -/
@[simps]
def toCompl : α →+ Completion α where
toFun := (↑)
map_add' := coe_add
map_zero' := coe_zero
#align uniform_space.completion.to_compl UniformSpace.Completion.toCompl
theorem continuous_toCompl : Continuous (toCompl : α → Completion α) :=
continuous_coe α
#align uniform_space.completion.continuous_to_compl UniformSpace.Completion.continuous_toCompl
variable (α)
theorem denseInducing_toCompl : DenseInducing (toCompl : α → Completion α) :=
denseInducing_coe
#align uniform_space.completion.dense_inducing_to_compl UniformSpace.Completion.denseInducing_toCompl
variable {α}
end UniformAddGroup
section UniformAddCommGroup
variable [UniformSpace α] [AddCommGroup α] [UniformAddGroup α]
instance instAddCommGroup : AddCommGroup (Completion α) :=
{ (inferInstance : AddGroup <| Completion α) with
add_comm := fun a b ↦
Completion.induction_on₂ a b
(isClosed_eq (continuous_map₂ continuous_fst continuous_snd)
(continuous_map₂ continuous_snd continuous_fst))
fun x y ↦ by
change (x : Completion α) + ↑y = ↑y + ↑x
rw [← coe_add, ← coe_add, add_comm] }
instance instModule [Semiring R] [Module R α] [UniformContinuousConstSMul R α] :
Module R (Completion α) :=
{ (inferInstance : DistribMulAction R <| Completion α),
(inferInstance : MulActionWithZero R <| Completion α) with
add_smul := fun a b ↦
ext' (continuous_const_smul _) ((continuous_const_smul _).add (continuous_const_smul _))
fun x ↦ by
rw [← coe_smul, add_smul, coe_add, coe_smul, coe_smul] }
#align uniform_space.completion.module UniformSpace.Completion.instModule
end UniformAddCommGroup
end UniformSpace.Completion
section AddMonoidHom
variable [UniformSpace α] [AddGroup α] [UniformAddGroup α] [UniformSpace β] [AddGroup β]
[UniformAddGroup β]
open UniformSpace UniformSpace.Completion
/-- Extension to the completion of a continuous group hom. -/
def AddMonoidHom.extension [CompleteSpace β] [T0Space β] (f : α →+ β) (hf : Continuous f) :
Completion α →+ β :=
have hf : UniformContinuous f := uniformContinuous_addMonoidHom_of_continuous hf
{ toFun := Completion.extension f
map_zero' := by rw [← coe_zero, extension_coe hf, f.map_zero]
map_add' := fun a b ↦
Completion.induction_on₂ a b
(isClosed_eq (continuous_extension.comp continuous_add)
((continuous_extension.comp continuous_fst).add
(continuous_extension.comp continuous_snd)))
fun a b ↦
show Completion.extension f _ = Completion.extension f _ + Completion.extension f _ by
rw_mod_cast [extension_coe hf, extension_coe hf, extension_coe hf, f.map_add] }
#align add_monoid_hom.extension AddMonoidHom.extension
theorem AddMonoidHom.extension_coe [CompleteSpace β] [T0Space β] (f : α →+ β)
(hf : Continuous f) (a : α) : f.extension hf a = f a :=
UniformSpace.Completion.extension_coe (uniformContinuous_addMonoidHom_of_continuous hf) a
#align add_monoid_hom.extension_coe AddMonoidHom.extension_coe
@[continuity]
theorem AddMonoidHom.continuous_extension [CompleteSpace β] [T0Space β] (f : α →+ β)
(hf : Continuous f) : Continuous (f.extension hf) :=
UniformSpace.Completion.continuous_extension
#align add_monoid_hom.continuous_extension AddMonoidHom.continuous_extension
/-- Completion of a continuous group hom, as a group hom. -/
def AddMonoidHom.completion (f : α →+ β) (hf : Continuous f) : Completion α →+ Completion β :=
(toCompl.comp f).extension (continuous_toCompl.comp hf)
#align add_monoid_hom.completion AddMonoidHom.completion
@[continuity]
theorem AddMonoidHom.continuous_completion (f : α →+ β) (hf : Continuous f) :
Continuous (AddMonoidHom.completion f hf : Completion α → Completion β) :=
continuous_map
#align add_monoid_hom.continuous_completion AddMonoidHom.continuous_completion
theorem AddMonoidHom.completion_coe (f : α →+ β) (hf : Continuous f) (a : α) :
AddMonoidHom.completion f hf a = f a :=
map_coe (uniformContinuous_addMonoidHom_of_continuous hf) a
#align add_monoid_hom.completion_coe AddMonoidHom.completion_coe
| Mathlib/Topology/Algebra/GroupCompletion.lean | 278 | 285 | theorem AddMonoidHom.completion_zero :
AddMonoidHom.completion (0 : α →+ β) continuous_const = 0 := by |
ext x
refine Completion.induction_on x ?_ ?_
· apply isClosed_eq (AddMonoidHom.continuous_completion (0 : α →+ β) continuous_const)
simp [continuous_const]
· intro a
simp [(0 : α →+ β).completion_coe continuous_const, coe_zero]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen
-/
import Mathlib.LinearAlgebra.Matrix.Reindex
import Mathlib.LinearAlgebra.Matrix.ToLin
#align_import linear_algebra.matrix.basis from "leanprover-community/mathlib"@"6c263e4bfc2e6714de30f22178b4d0ca4d149a76"
/-!
# Bases and matrices
This file defines the map `Basis.toMatrix` that sends a family of vectors to
the matrix of their coordinates with respect to some basis.
## Main definitions
* `Basis.toMatrix e v` is the matrix whose `i, j`th entry is `e.repr (v j) i`
* `basis.toMatrixEquiv` is `Basis.toMatrix` bundled as a linear equiv
## Main results
* `LinearMap.toMatrix_id_eq_basis_toMatrix`: `LinearMap.toMatrix b c id`
is equal to `Basis.toMatrix b c`
* `Basis.toMatrix_mul_toMatrix`: multiplying `Basis.toMatrix` with another
`Basis.toMatrix` gives a `Basis.toMatrix`
## Tags
matrix, basis
-/
noncomputable section
open LinearMap Matrix Set Submodule
open Matrix
section BasisToMatrix
variable {ι ι' κ κ' : Type*}
variable {R M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M]
variable {R₂ M₂ : Type*} [CommRing R₂] [AddCommGroup M₂] [Module R₂ M₂]
open Function Matrix
/-- From a basis `e : ι → M` and a family of vectors `v : ι' → M`, make the matrix whose columns
are the vectors `v i` written in the basis `e`. -/
def Basis.toMatrix (e : Basis ι R M) (v : ι' → M) : Matrix ι ι' R := fun i j => e.repr (v j) i
#align basis.to_matrix Basis.toMatrix
variable (e : Basis ι R M) (v : ι' → M) (i : ι) (j : ι')
namespace Basis
theorem toMatrix_apply : e.toMatrix v i j = e.repr (v j) i :=
rfl
#align basis.to_matrix_apply Basis.toMatrix_apply
theorem toMatrix_transpose_apply : (e.toMatrix v)ᵀ j = e.repr (v j) :=
funext fun _ => rfl
#align basis.to_matrix_transpose_apply Basis.toMatrix_transpose_apply
theorem toMatrix_eq_toMatrix_constr [Fintype ι] [DecidableEq ι] (v : ι → M) :
e.toMatrix v = LinearMap.toMatrix e e (e.constr ℕ v) := by
ext
rw [Basis.toMatrix_apply, LinearMap.toMatrix_apply, Basis.constr_basis]
#align basis.to_matrix_eq_to_matrix_constr Basis.toMatrix_eq_toMatrix_constr
-- TODO (maybe) Adjust the definition of `Basis.toMatrix` to eliminate the transpose.
theorem coePiBasisFun.toMatrix_eq_transpose [Finite ι] :
((Pi.basisFun R ι).toMatrix : Matrix ι ι R → Matrix ι ι R) = Matrix.transpose := by
ext M i j
rfl
#align basis.coe_pi_basis_fun.to_matrix_eq_transpose Basis.coePiBasisFun.toMatrix_eq_transpose
@[simp]
theorem toMatrix_self [DecidableEq ι] : e.toMatrix e = 1 := by
unfold Basis.toMatrix
ext i j
simp [Basis.equivFun, Matrix.one_apply, Finsupp.single_apply, eq_comm]
#align basis.to_matrix_self Basis.toMatrix_self
| Mathlib/LinearAlgebra/Matrix/Basis.lean | 86 | 92 | theorem toMatrix_update [DecidableEq ι'] (x : M) :
e.toMatrix (Function.update v j x) = Matrix.updateColumn (e.toMatrix v) j (e.repr x) := by |
ext i' k
rw [Basis.toMatrix, Matrix.updateColumn_apply, e.toMatrix_apply]
split_ifs with h
· rw [h, update_same j x v]
· rw [update_noteq h]
|
/-
Copyright (c) 2019 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Eric Wieser
-/
import Mathlib.LinearAlgebra.Span
import Mathlib.LinearAlgebra.BilinearMap
#align_import algebra.module.submodule.bilinear from "leanprover-community/mathlib"@"6010cf523816335f7bae7f8584cb2edaace73940"
/-!
# Images of pairs of submodules under bilinear maps
This file provides `Submodule.map₂`, which is later used to implement `Submodule.mul`.
## Main results
* `Submodule.map₂_eq_span_image2`: the image of two submodules under a bilinear map is the span of
their `Set.image2`.
## Notes
This file is quite similar to the n-ary section of `Data.Set.Basic` and to `Order.Filter.NAry`.
Please keep them in sync.
-/
universe uι u v
open Set
open Pointwise
namespace Submodule
variable {ι : Sort uι} {R M N P : Type*}
variable [CommSemiring R] [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P]
variable [Module R M] [Module R N] [Module R P]
/-- Map a pair of submodules under a bilinear map.
This is the submodule version of `Set.image2`. -/
def map₂ (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) (q : Submodule R N) : Submodule R P :=
⨆ s : p, q.map (f s)
#align submodule.map₂ Submodule.map₂
theorem apply_mem_map₂ (f : M →ₗ[R] N →ₗ[R] P) {m : M} {n : N} {p : Submodule R M}
{q : Submodule R N} (hm : m ∈ p) (hn : n ∈ q) : f m n ∈ map₂ f p q :=
(le_iSup _ ⟨m, hm⟩ : _ ≤ map₂ f p q) ⟨n, hn, by rfl⟩
#align submodule.apply_mem_map₂ Submodule.apply_mem_map₂
theorem map₂_le {f : M →ₗ[R] N →ₗ[R] P} {p : Submodule R M} {q : Submodule R N}
{r : Submodule R P} : map₂ f p q ≤ r ↔ ∀ m ∈ p, ∀ n ∈ q, f m n ∈ r :=
⟨fun H _m hm _n hn => H <| apply_mem_map₂ _ hm hn, fun H =>
iSup_le fun ⟨m, hm⟩ => map_le_iff_le_comap.2 fun n hn => H m hm n hn⟩
#align submodule.map₂_le Submodule.map₂_le
variable (R)
theorem map₂_span_span (f : M →ₗ[R] N →ₗ[R] P) (s : Set M) (t : Set N) :
map₂ f (span R s) (span R t) = span R (Set.image2 (fun m n => f m n) s t) := by
apply le_antisymm
· rw [map₂_le]
apply @span_induction' R M _ _ _ s
intro a ha
apply @span_induction' R N _ _ _ t
intro b hb
exact subset_span ⟨_, ‹_›, _, ‹_›, rfl⟩
all_goals intros; simp only [*, add_mem, smul_mem, zero_mem, _root_.map_zero, map_add,
LinearMap.zero_apply, LinearMap.add_apply, LinearMap.smul_apply,
map_smul]
· rw [span_le, image2_subset_iff]
intro a ha b hb
exact apply_mem_map₂ _ (subset_span ha) (subset_span hb)
#align submodule.map₂_span_span Submodule.map₂_span_span
variable {R}
@[simp]
theorem map₂_bot_right (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) : map₂ f p ⊥ = ⊥ :=
eq_bot_iff.2 <|
map₂_le.2 fun m _hm n hn => by
rw [Submodule.mem_bot] at hn
rw [hn, LinearMap.map_zero]; simp only [mem_bot]
#align submodule.map₂_bot_right Submodule.map₂_bot_right
@[simp]
theorem map₂_bot_left (f : M →ₗ[R] N →ₗ[R] P) (q : Submodule R N) : map₂ f ⊥ q = ⊥ :=
eq_bot_iff.2 <|
map₂_le.2 fun m hm n hn => by
rw [Submodule.mem_bot] at hm ⊢
rw [hm, LinearMap.map_zero₂]
#align submodule.map₂_bot_left Submodule.map₂_bot_left
@[mono]
theorem map₂_le_map₂ {f : M →ₗ[R] N →ₗ[R] P} {p₁ p₂ : Submodule R M} {q₁ q₂ : Submodule R N}
(hp : p₁ ≤ p₂) (hq : q₁ ≤ q₂) : map₂ f p₁ q₁ ≤ map₂ f p₂ q₂ :=
map₂_le.2 fun _m hm _n hn => apply_mem_map₂ _ (hp hm) (hq hn)
#align submodule.map₂_le_map₂ Submodule.map₂_le_map₂
theorem map₂_le_map₂_left {f : M →ₗ[R] N →ₗ[R] P} {p₁ p₂ : Submodule R M} {q : Submodule R N}
(h : p₁ ≤ p₂) : map₂ f p₁ q ≤ map₂ f p₂ q :=
map₂_le_map₂ h (le_refl q)
#align submodule.map₂_le_map₂_left Submodule.map₂_le_map₂_left
theorem map₂_le_map₂_right {f : M →ₗ[R] N →ₗ[R] P} {p : Submodule R M} {q₁ q₂ : Submodule R N}
(h : q₁ ≤ q₂) : map₂ f p q₁ ≤ map₂ f p q₂ :=
map₂_le_map₂ (le_refl p) h
#align submodule.map₂_le_map₂_right Submodule.map₂_le_map₂_right
theorem map₂_sup_right (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) (q₁ q₂ : Submodule R N) :
map₂ f p (q₁ ⊔ q₂) = map₂ f p q₁ ⊔ map₂ f p q₂ :=
le_antisymm
(map₂_le.2 fun _m hm _np hnp =>
let ⟨_n, hn, _p, hp, hnp⟩ := mem_sup.1 hnp
mem_sup.2 ⟨_, apply_mem_map₂ _ hm hn, _, apply_mem_map₂ _ hm hp, hnp ▸ (map_add _ _ _).symm⟩)
(sup_le (map₂_le_map₂_right le_sup_left) (map₂_le_map₂_right le_sup_right))
#align submodule.map₂_sup_right Submodule.map₂_sup_right
theorem map₂_sup_left (f : M →ₗ[R] N →ₗ[R] P) (p₁ p₂ : Submodule R M) (q : Submodule R N) :
map₂ f (p₁ ⊔ p₂) q = map₂ f p₁ q ⊔ map₂ f p₂ q :=
le_antisymm
(map₂_le.2 fun _mn hmn _p hp =>
let ⟨_m, hm, _n, hn, hmn⟩ := mem_sup.1 hmn
mem_sup.2
⟨_, apply_mem_map₂ _ hm hp, _, apply_mem_map₂ _ hn hp,
hmn ▸ (LinearMap.map_add₂ _ _ _ _).symm⟩)
(sup_le (map₂_le_map₂_left le_sup_left) (map₂_le_map₂_left le_sup_right))
#align submodule.map₂_sup_left Submodule.map₂_sup_left
theorem image2_subset_map₂ (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) (q : Submodule R N) :
Set.image2 (fun m n => f m n) (↑p : Set M) (↑q : Set N) ⊆ (↑(map₂ f p q) : Set P) := by
rintro _ ⟨i, hi, j, hj, rfl⟩
exact apply_mem_map₂ _ hi hj
#align submodule.image2_subset_map₂ Submodule.image2_subset_map₂
theorem map₂_eq_span_image2 (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) (q : Submodule R N) :
map₂ f p q = span R (Set.image2 (fun m n => f m n) (p : Set M) (q : Set N)) := by
rw [← map₂_span_span, span_eq, span_eq]
#align submodule.map₂_eq_span_image2 Submodule.map₂_eq_span_image2
theorem map₂_flip (f : M →ₗ[R] N →ₗ[R] P) (p : Submodule R M) (q : Submodule R N) :
map₂ f.flip q p = map₂ f p q := by
rw [map₂_eq_span_image2, map₂_eq_span_image2, Set.image2_swap]
rfl
#align submodule.map₂_flip Submodule.map₂_flip
theorem map₂_iSup_left (f : M →ₗ[R] N →ₗ[R] P) (s : ι → Submodule R M) (t : Submodule R N) :
map₂ f (⨆ i, s i) t = ⨆ i, map₂ f (s i) t := by
suffices map₂ f (⨆ i, span R (s i : Set M)) (span R t) = ⨆ i, map₂ f (span R (s i)) (span R t) by
simpa only [span_eq] using this
simp_rw [map₂_span_span, ← span_iUnion, map₂_span_span, Set.image2_iUnion_left]
#align submodule.map₂_supr_left Submodule.map₂_iSup_left
| Mathlib/Algebra/Module/Submodule/Bilinear.lean | 153 | 157 | theorem map₂_iSup_right (f : M →ₗ[R] N →ₗ[R] P) (s : Submodule R M) (t : ι → Submodule R N) :
map₂ f s (⨆ i, t i) = ⨆ i, map₂ f s (t i) := by |
suffices map₂ f (span R s) (⨆ i, span R (t i : Set N)) = ⨆ i, map₂ f (span R s) (span R (t i)) by
simpa only [span_eq] using this
simp_rw [map₂_span_span, ← span_iUnion, map₂_span_span, Set.image2_iUnion_right]
|
/-
Copyright (c) 2022 Wrenna Robson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Wrenna Robson
-/
import Mathlib.Topology.MetricSpace.Basic
#align_import topology.metric_space.infsep from "leanprover-community/mathlib"@"5316314b553dcf8c6716541851517c1a9715e22b"
/-!
# Infimum separation
This file defines the extended infimum separation of a set. This is approximately dual to the
diameter of a set, but where the extended diameter of a set is the supremum of the extended distance
between elements of the set, the extended infimum separation is the infimum of the (extended)
distance between *distinct* elements in the set.
We also define the infimum separation as the cast of the extended infimum separation to the reals.
This is the infimum of the distance between distinct elements of the set when in a pseudometric
space.
All lemmas and definitions are in the `Set` namespace to give access to dot notation.
## Main definitions
* `Set.einfsep`: Extended infimum separation of a set.
* `Set.infsep`: Infimum separation of a set (when in a pseudometric space).
!-/
variable {α β : Type*}
namespace Set
section Einfsep
open ENNReal
open Function
/-- The "extended infimum separation" of a set with an edist function. -/
noncomputable def einfsep [EDist α] (s : Set α) : ℝ≥0∞ :=
⨅ (x ∈ s) (y ∈ s) (_ : x ≠ y), edist x y
#align set.einfsep Set.einfsep
section EDist
variable [EDist α] {x y : α} {s t : Set α}
theorem le_einfsep_iff {d} :
d ≤ s.einfsep ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y := by
simp_rw [einfsep, le_iInf_iff]
#align set.le_einfsep_iff Set.le_einfsep_iff
theorem einfsep_zero : s.einfsep = 0 ↔ ∀ C > 0, ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < C := by
simp_rw [einfsep, ← _root_.bot_eq_zero, iInf_eq_bot, iInf_lt_iff, exists_prop]
#align set.einfsep_zero Set.einfsep_zero
theorem einfsep_pos : 0 < s.einfsep ↔ ∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y := by
rw [pos_iff_ne_zero, Ne, einfsep_zero]
simp only [not_forall, not_exists, not_lt, exists_prop, not_and]
#align set.einfsep_pos Set.einfsep_pos
theorem einfsep_top :
s.einfsep = ∞ ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → edist x y = ∞ := by
simp_rw [einfsep, iInf_eq_top]
#align set.einfsep_top Set.einfsep_top
theorem einfsep_lt_top :
s.einfsep < ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < ∞ := by
simp_rw [einfsep, iInf_lt_iff, exists_prop]
#align set.einfsep_lt_top Set.einfsep_lt_top
theorem einfsep_ne_top :
s.einfsep ≠ ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y ≠ ∞ := by
simp_rw [← lt_top_iff_ne_top, einfsep_lt_top]
#align set.einfsep_ne_top Set.einfsep_ne_top
theorem einfsep_lt_iff {d} :
s.einfsep < d ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < d := by
simp_rw [einfsep, iInf_lt_iff, exists_prop]
#align set.einfsep_lt_iff Set.einfsep_lt_iff
theorem nontrivial_of_einfsep_lt_top (hs : s.einfsep < ∞) : s.Nontrivial := by
rcases einfsep_lt_top.1 hs with ⟨_, hx, _, hy, hxy, _⟩
exact ⟨_, hx, _, hy, hxy⟩
#align set.nontrivial_of_einfsep_lt_top Set.nontrivial_of_einfsep_lt_top
theorem nontrivial_of_einfsep_ne_top (hs : s.einfsep ≠ ∞) : s.Nontrivial :=
nontrivial_of_einfsep_lt_top (lt_top_iff_ne_top.mpr hs)
#align set.nontrivial_of_einfsep_ne_top Set.nontrivial_of_einfsep_ne_top
theorem Subsingleton.einfsep (hs : s.Subsingleton) : s.einfsep = ∞ := by
rw [einfsep_top]
exact fun _ hx _ hy hxy => (hxy <| hs hx hy).elim
#align set.subsingleton.einfsep Set.Subsingleton.einfsep
theorem le_einfsep_image_iff {d} {f : β → α} {s : Set β} : d ≤ einfsep (f '' s)
↔ ∀ x ∈ s, ∀ y ∈ s, f x ≠ f y → d ≤ edist (f x) (f y) := by
simp_rw [le_einfsep_iff, forall_mem_image]
#align set.le_einfsep_image_iff Set.le_einfsep_image_iff
theorem le_edist_of_le_einfsep {d x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y)
(hd : d ≤ s.einfsep) : d ≤ edist x y :=
le_einfsep_iff.1 hd x hx y hy hxy
#align set.le_edist_of_le_einfsep Set.le_edist_of_le_einfsep
theorem einfsep_le_edist_of_mem {x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y) :
s.einfsep ≤ edist x y :=
le_edist_of_le_einfsep hx hy hxy le_rfl
#align set.einfsep_le_edist_of_mem Set.einfsep_le_edist_of_mem
theorem einfsep_le_of_mem_of_edist_le {d x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y)
(hxy' : edist x y ≤ d) : s.einfsep ≤ d :=
le_trans (einfsep_le_edist_of_mem hx hy hxy) hxy'
#align set.einfsep_le_of_mem_of_edist_le Set.einfsep_le_of_mem_of_edist_le
theorem le_einfsep {d} (h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y) : d ≤ s.einfsep :=
le_einfsep_iff.2 h
#align set.le_einfsep Set.le_einfsep
@[simp]
theorem einfsep_empty : (∅ : Set α).einfsep = ∞ :=
subsingleton_empty.einfsep
#align set.einfsep_empty Set.einfsep_empty
@[simp]
theorem einfsep_singleton : ({x} : Set α).einfsep = ∞ :=
subsingleton_singleton.einfsep
#align set.einfsep_singleton Set.einfsep_singleton
theorem einfsep_iUnion_mem_option {ι : Type*} (o : Option ι) (s : ι → Set α) :
(⋃ i ∈ o, s i).einfsep = ⨅ i ∈ o, (s i).einfsep := by cases o <;> simp
#align set.einfsep_Union_mem_option Set.einfsep_iUnion_mem_option
theorem einfsep_anti (hst : s ⊆ t) : t.einfsep ≤ s.einfsep :=
le_einfsep fun _x hx _y hy => einfsep_le_edist_of_mem (hst hx) (hst hy)
#align set.einfsep_anti Set.einfsep_anti
theorem einfsep_insert_le : (insert x s).einfsep ≤ ⨅ (y ∈ s) (_ : x ≠ y), edist x y := by
simp_rw [le_iInf_iff]
exact fun _ hy hxy => einfsep_le_edist_of_mem (mem_insert _ _) (mem_insert_of_mem _ hy) hxy
#align set.einfsep_insert_le Set.einfsep_insert_le
theorem le_einfsep_pair : edist x y ⊓ edist y x ≤ ({x, y} : Set α).einfsep := by
simp_rw [le_einfsep_iff, inf_le_iff, mem_insert_iff, mem_singleton_iff]
rintro a (rfl | rfl) b (rfl | rfl) hab <;> (try simp only [le_refl, true_or, or_true]) <;>
contradiction
#align set.le_einfsep_pair Set.le_einfsep_pair
theorem einfsep_pair_le_left (hxy : x ≠ y) : ({x, y} : Set α).einfsep ≤ edist x y :=
einfsep_le_edist_of_mem (mem_insert _ _) (mem_insert_of_mem _ (mem_singleton _)) hxy
#align set.einfsep_pair_le_left Set.einfsep_pair_le_left
theorem einfsep_pair_le_right (hxy : x ≠ y) : ({x, y} : Set α).einfsep ≤ edist y x := by
rw [pair_comm]; exact einfsep_pair_le_left hxy.symm
#align set.einfsep_pair_le_right Set.einfsep_pair_le_right
theorem einfsep_pair_eq_inf (hxy : x ≠ y) : ({x, y} : Set α).einfsep = edist x y ⊓ edist y x :=
le_antisymm (le_inf (einfsep_pair_le_left hxy) (einfsep_pair_le_right hxy)) le_einfsep_pair
#align set.einfsep_pair_eq_inf Set.einfsep_pair_eq_inf
theorem einfsep_eq_iInf : s.einfsep = ⨅ d : s.offDiag, (uncurry edist) (d : α × α) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, le_iInf_iff, imp_forall_iff, SetCoe.forall, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.einfsep_eq_infi Set.einfsep_eq_iInf
theorem einfsep_of_fintype [DecidableEq α] [Fintype s] :
s.einfsep = s.offDiag.toFinset.inf (uncurry edist) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, imp_forall_iff, Finset.le_inf_iff, mem_toFinset, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.einfsep_of_fintype Set.einfsep_of_fintype
theorem Finite.einfsep (hs : s.Finite) : s.einfsep = hs.offDiag.toFinset.inf (uncurry edist) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, imp_forall_iff, Finset.le_inf_iff, Finite.mem_toFinset, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.finite.einfsep Set.Finite.einfsep
theorem Finset.coe_einfsep [DecidableEq α] {s : Finset α} :
(s : Set α).einfsep = s.offDiag.inf (uncurry edist) := by
simp_rw [einfsep_of_fintype, ← Finset.coe_offDiag, Finset.toFinset_coe]
#align set.finset.coe_einfsep Set.Finset.coe_einfsep
theorem Nontrivial.einfsep_exists_of_finite [Finite s] (hs : s.Nontrivial) :
∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ s.einfsep = edist x y := by
classical
cases nonempty_fintype s
simp_rw [einfsep_of_fintype]
rcases Finset.exists_mem_eq_inf s.offDiag.toFinset (by simpa) (uncurry edist) with ⟨w, hxy, hed⟩
simp_rw [mem_toFinset] at hxy
exact ⟨w.fst, hxy.1, w.snd, hxy.2.1, hxy.2.2, hed⟩
#align set.nontrivial.einfsep_exists_of_finite Set.Nontrivial.einfsep_exists_of_finite
theorem Finite.einfsep_exists_of_nontrivial (hsf : s.Finite) (hs : s.Nontrivial) :
∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ s.einfsep = edist x y :=
letI := hsf.fintype
hs.einfsep_exists_of_finite
#align set.finite.einfsep_exists_of_nontrivial Set.Finite.einfsep_exists_of_nontrivial
end EDist
section PseudoEMetricSpace
variable [PseudoEMetricSpace α] {x y z : α} {s t : Set α}
theorem einfsep_pair (hxy : x ≠ y) : ({x, y} : Set α).einfsep = edist x y := by
nth_rw 1 [← min_self (edist x y)]
convert einfsep_pair_eq_inf hxy using 2
rw [edist_comm]
#align set.einfsep_pair Set.einfsep_pair
theorem einfsep_insert : einfsep (insert x s) =
(⨅ (y ∈ s) (_ : x ≠ y), edist x y) ⊓ s.einfsep := by
refine le_antisymm (le_min einfsep_insert_le (einfsep_anti (subset_insert _ _))) ?_
simp_rw [le_einfsep_iff, inf_le_iff, mem_insert_iff]
rintro y (rfl | hy) z (rfl | hz) hyz
· exact False.elim (hyz rfl)
· exact Or.inl (iInf_le_of_le _ (iInf₂_le hz hyz))
· rw [edist_comm]
exact Or.inl (iInf_le_of_le _ (iInf₂_le hy hyz.symm))
· exact Or.inr (einfsep_le_edist_of_mem hy hz hyz)
#align set.einfsep_insert Set.einfsep_insert
theorem einfsep_triple (hxy : x ≠ y) (hyz : y ≠ z) (hxz : x ≠ z) :
einfsep ({x, y, z} : Set α) = edist x y ⊓ edist x z ⊓ edist y z := by
simp_rw [einfsep_insert, iInf_insert, iInf_singleton, einfsep_singleton, inf_top_eq,
ciInf_pos hxy, ciInf_pos hyz, ciInf_pos hxz]
#align set.einfsep_triple Set.einfsep_triple
theorem le_einfsep_pi_of_le {π : β → Type*} [Fintype β] [∀ b, PseudoEMetricSpace (π b)]
{s : ∀ b : β, Set (π b)} {c : ℝ≥0∞} (h : ∀ b, c ≤ einfsep (s b)) :
c ≤ einfsep (Set.pi univ s) := by
refine le_einfsep fun x hx y hy hxy => ?_
rw [mem_univ_pi] at hx hy
rcases Function.ne_iff.mp hxy with ⟨i, hi⟩
exact le_trans (le_einfsep_iff.1 (h i) _ (hx _) _ (hy _) hi) (edist_le_pi_edist _ _ i)
#align set.le_einfsep_pi_of_le Set.le_einfsep_pi_of_le
end PseudoEMetricSpace
section PseudoMetricSpace
variable [PseudoMetricSpace α] {s : Set α}
theorem subsingleton_of_einfsep_eq_top (hs : s.einfsep = ∞) : s.Subsingleton := by
rw [einfsep_top] at hs
exact fun _ hx _ hy => of_not_not fun hxy => edist_ne_top _ _ (hs _ hx _ hy hxy)
#align set.subsingleton_of_einfsep_eq_top Set.subsingleton_of_einfsep_eq_top
theorem einfsep_eq_top_iff : s.einfsep = ∞ ↔ s.Subsingleton :=
⟨subsingleton_of_einfsep_eq_top, Subsingleton.einfsep⟩
#align set.einfsep_eq_top_iff Set.einfsep_eq_top_iff
theorem Nontrivial.einfsep_ne_top (hs : s.Nontrivial) : s.einfsep ≠ ∞ := by
contrapose! hs
rw [not_nontrivial_iff]
exact subsingleton_of_einfsep_eq_top hs
#align set.nontrivial.einfsep_ne_top Set.Nontrivial.einfsep_ne_top
theorem Nontrivial.einfsep_lt_top (hs : s.Nontrivial) : s.einfsep < ∞ := by
rw [lt_top_iff_ne_top]
exact hs.einfsep_ne_top
#align set.nontrivial.einfsep_lt_top Set.Nontrivial.einfsep_lt_top
theorem einfsep_lt_top_iff : s.einfsep < ∞ ↔ s.Nontrivial :=
⟨nontrivial_of_einfsep_lt_top, Nontrivial.einfsep_lt_top⟩
#align set.einfsep_lt_top_iff Set.einfsep_lt_top_iff
theorem einfsep_ne_top_iff : s.einfsep ≠ ∞ ↔ s.Nontrivial :=
⟨nontrivial_of_einfsep_ne_top, Nontrivial.einfsep_ne_top⟩
#align set.einfsep_ne_top_iff Set.einfsep_ne_top_iff
theorem le_einfsep_of_forall_dist_le {d} (h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ dist x y) :
ENNReal.ofReal d ≤ s.einfsep :=
le_einfsep fun x hx y hy hxy => (edist_dist x y).symm ▸ ENNReal.ofReal_le_ofReal (h x hx y hy hxy)
#align set.le_einfsep_of_forall_dist_le Set.le_einfsep_of_forall_dist_le
end PseudoMetricSpace
section EMetricSpace
variable [EMetricSpace α] {x y z : α} {s t : Set α} {C : ℝ≥0∞} {sC : Set ℝ≥0∞}
theorem einfsep_pos_of_finite [Finite s] : 0 < s.einfsep := by
cases nonempty_fintype s
by_cases hs : s.Nontrivial
· rcases hs.einfsep_exists_of_finite with ⟨x, _hx, y, _hy, hxy, hxy'⟩
exact hxy'.symm ▸ edist_pos.2 hxy
· rw [not_nontrivial_iff] at hs
exact hs.einfsep.symm ▸ WithTop.zero_lt_top
#align set.einfsep_pos_of_finite Set.einfsep_pos_of_finite
theorem relatively_discrete_of_finite [Finite s] :
∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y := by
rw [← einfsep_pos]
exact einfsep_pos_of_finite
#align set.relatively_discrete_of_finite Set.relatively_discrete_of_finite
theorem Finite.einfsep_pos (hs : s.Finite) : 0 < s.einfsep :=
letI := hs.fintype
einfsep_pos_of_finite
#align set.finite.einfsep_pos Set.Finite.einfsep_pos
theorem Finite.relatively_discrete (hs : s.Finite) :
∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y :=
letI := hs.fintype
relatively_discrete_of_finite
#align set.finite.relatively_discrete Set.Finite.relatively_discrete
end EMetricSpace
end Einfsep
section Infsep
open ENNReal
open Set Function
/-- The "infimum separation" of a set with an edist function. -/
noncomputable def infsep [EDist α] (s : Set α) : ℝ :=
ENNReal.toReal s.einfsep
#align set.infsep Set.infsep
section EDist
variable [EDist α] {x y : α} {s : Set α}
| Mathlib/Topology/MetricSpace/Infsep.lean | 332 | 333 | theorem infsep_zero : s.infsep = 0 ↔ s.einfsep = 0 ∨ s.einfsep = ∞ := by |
rw [infsep, ENNReal.toReal_eq_zero_iff]
|
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Data.List.Cycle
import Mathlib.GroupTheory.Perm.Cycle.Type
import Mathlib.GroupTheory.Perm.List
#align_import group_theory.perm.cycle.concrete from "leanprover-community/mathlib"@"00638177efd1b2534fc5269363ebf42a7871df9a"
/-!
# Properties of cyclic permutations constructed from lists/cycles
In the following, `{α : Type*} [Fintype α] [DecidableEq α]`.
## Main definitions
* `Cycle.formPerm`: the cyclic permutation created by looping over a `Cycle α`
* `Equiv.Perm.toList`: the list formed by iterating application of a permutation
* `Equiv.Perm.toCycle`: the cycle formed by iterating application of a permutation
* `Equiv.Perm.isoCycle`: the equivalence between cyclic permutations `f : Perm α`
and the terms of `Cycle α` that correspond to them
* `Equiv.Perm.isoCycle'`: the same equivalence as `Equiv.Perm.isoCycle`
but with evaluation via choosing over fintypes
* The notation `c[1, 2, 3]` to emulate notation of cyclic permutations `(1 2 3)`
* A `Repr` instance for any `Perm α`, by representing the `Finset` of
`Cycle α` that correspond to the cycle factors.
## Main results
* `List.isCycle_formPerm`: a nontrivial list without duplicates, when interpreted as
a permutation, is cyclic
* `Equiv.Perm.IsCycle.existsUnique_cycle`: there is only one nontrivial `Cycle α`
corresponding to each cyclic `f : Perm α`
## Implementation details
The forward direction of `Equiv.Perm.isoCycle'` uses `Fintype.choose` of the uniqueness
result, relying on the `Fintype` instance of a `Cycle.nodup` subtype.
It is unclear if this works faster than the `Equiv.Perm.toCycle`, which relies
on recursion over `Finset.univ`.
Running `#eval` on even a simple noncyclic permutation `c[(1 : Fin 7), 2, 3] * c[0, 5]`
to show it takes a long time. TODO: is this because computing the cycle factors is slow?
-/
open Equiv Equiv.Perm List
variable {α : Type*}
namespace List
variable [DecidableEq α] {l l' : List α}
theorem formPerm_disjoint_iff (hl : Nodup l) (hl' : Nodup l') (hn : 2 ≤ l.length)
(hn' : 2 ≤ l'.length) : Perm.Disjoint (formPerm l) (formPerm l') ↔ l.Disjoint l' := by
rw [disjoint_iff_eq_or_eq, List.Disjoint]
constructor
· rintro h x hx hx'
specialize h x
rw [formPerm_apply_mem_eq_self_iff _ hl _ hx, formPerm_apply_mem_eq_self_iff _ hl' _ hx'] at h
omega
· intro h x
by_cases hx : x ∈ l
on_goal 1 => by_cases hx' : x ∈ l'
· exact (h hx hx').elim
all_goals have := formPerm_eq_self_of_not_mem _ _ ‹_›; tauto
#align list.form_perm_disjoint_iff List.formPerm_disjoint_iff
theorem isCycle_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) : IsCycle (formPerm l) := by
cases' l with x l
· set_option tactic.skipAssignedInstances false in norm_num at hn
induction' l with y l generalizing x
· set_option tactic.skipAssignedInstances false in norm_num at hn
· use x
constructor
· rwa [formPerm_apply_mem_ne_self_iff _ hl _ (mem_cons_self _ _)]
· intro w hw
have : w ∈ x::y::l := mem_of_formPerm_ne_self _ _ hw
obtain ⟨k, hk⟩ := get_of_mem this
use k
rw [← hk]
simp only [zpow_natCast, formPerm_pow_apply_head _ _ hl k, Nat.mod_eq_of_lt k.isLt]
#align list.is_cycle_form_perm List.isCycle_formPerm
theorem pairwise_sameCycle_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) :
Pairwise l.formPerm.SameCycle l :=
Pairwise.imp_mem.mpr
(pairwise_of_forall fun _ _ hx hy =>
(isCycle_formPerm hl hn).sameCycle ((formPerm_apply_mem_ne_self_iff _ hl _ hx).mpr hn)
((formPerm_apply_mem_ne_self_iff _ hl _ hy).mpr hn))
#align list.pairwise_same_cycle_form_perm List.pairwise_sameCycle_formPerm
theorem cycleOf_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) (x) :
cycleOf l.attach.formPerm x = l.attach.formPerm :=
have hn : 2 ≤ l.attach.length := by rwa [← length_attach] at hn
have hl : l.attach.Nodup := by rwa [← nodup_attach] at hl
(isCycle_formPerm hl hn).cycleOf_eq
((formPerm_apply_mem_ne_self_iff _ hl _ (mem_attach _ _)).mpr hn)
#align list.cycle_of_form_perm List.cycleOf_formPerm
theorem cycleType_formPerm (hl : Nodup l) (hn : 2 ≤ l.length) :
cycleType l.attach.formPerm = {l.length} := by
rw [← length_attach] at hn
rw [← nodup_attach] at hl
rw [cycleType_eq [l.attach.formPerm]]
· simp only [map, Function.comp_apply]
rw [support_formPerm_of_nodup _ hl, card_toFinset, dedup_eq_self.mpr hl]
· simp
· intro x h
simp [h, Nat.succ_le_succ_iff] at hn
· simp
· simpa using isCycle_formPerm hl hn
· simp
#align list.cycle_type_form_perm List.cycleType_formPerm
theorem formPerm_apply_mem_eq_next (hl : Nodup l) (x : α) (hx : x ∈ l) :
formPerm l x = next l x hx := by
obtain ⟨k, rfl⟩ := get_of_mem hx
rw [next_get _ hl, formPerm_apply_get _ hl]
#align list.form_perm_apply_mem_eq_next List.formPerm_apply_mem_eq_next
end List
namespace Cycle
variable [DecidableEq α] (s s' : Cycle α)
/-- A cycle `s : Cycle α`, given `Nodup s` can be interpreted as an `Equiv.Perm α`
where each element in the list is permuted to the next one, defined as `formPerm`.
-/
def formPerm : ∀ s : Cycle α, Nodup s → Equiv.Perm α :=
fun s => Quotient.hrecOn s (fun l _ => List.formPerm l) fun l₁ l₂ (h : l₁ ~r l₂) => by
apply Function.hfunext
· ext
exact h.nodup_iff
· intro h₁ h₂ _
exact heq_of_eq (formPerm_eq_of_isRotated h₁ h)
#align cycle.form_perm Cycle.formPerm
@[simp]
theorem formPerm_coe (l : List α) (hl : l.Nodup) : formPerm (l : Cycle α) hl = l.formPerm :=
rfl
#align cycle.form_perm_coe Cycle.formPerm_coe
theorem formPerm_subsingleton (s : Cycle α) (h : Subsingleton s) : formPerm s h.nodup = 1 := by
induction' s using Quot.inductionOn with s
simp only [formPerm_coe, mk_eq_coe]
simp only [length_subsingleton_iff, length_coe, mk_eq_coe] at h
cases' s with hd tl
· simp
· simp only [length_eq_zero, add_le_iff_nonpos_left, List.length, nonpos_iff_eq_zero] at h
simp [h]
#align cycle.form_perm_subsingleton Cycle.formPerm_subsingleton
theorem isCycle_formPerm (s : Cycle α) (h : Nodup s) (hn : Nontrivial s) :
IsCycle (formPerm s h) := by
induction s using Quot.inductionOn
exact List.isCycle_formPerm h (length_nontrivial hn)
#align cycle.is_cycle_form_perm Cycle.isCycle_formPerm
theorem support_formPerm [Fintype α] (s : Cycle α) (h : Nodup s) (hn : Nontrivial s) :
support (formPerm s h) = s.toFinset := by
induction' s using Quot.inductionOn with s
refine support_formPerm_of_nodup s h ?_
rintro _ rfl
simpa [Nat.succ_le_succ_iff] using length_nontrivial hn
#align cycle.support_form_perm Cycle.support_formPerm
theorem formPerm_eq_self_of_not_mem (s : Cycle α) (h : Nodup s) (x : α) (hx : x ∉ s) :
formPerm s h x = x := by
induction s using Quot.inductionOn
simpa using List.formPerm_eq_self_of_not_mem _ _ hx
#align cycle.form_perm_eq_self_of_not_mem Cycle.formPerm_eq_self_of_not_mem
theorem formPerm_apply_mem_eq_next (s : Cycle α) (h : Nodup s) (x : α) (hx : x ∈ s) :
formPerm s h x = next s h x hx := by
induction s using Quot.inductionOn
simpa using List.formPerm_apply_mem_eq_next h _ (by simp_all)
#align cycle.form_perm_apply_mem_eq_next Cycle.formPerm_apply_mem_eq_next
nonrec theorem formPerm_reverse (s : Cycle α) (h : Nodup s) :
formPerm s.reverse (nodup_reverse_iff.mpr h) = (formPerm s h)⁻¹ := by
induction s using Quot.inductionOn
simpa using formPerm_reverse _
#align cycle.form_perm_reverse Cycle.formPerm_reverse
nonrec theorem formPerm_eq_formPerm_iff {α : Type*} [DecidableEq α] {s s' : Cycle α} {hs : s.Nodup}
{hs' : s'.Nodup} :
s.formPerm hs = s'.formPerm hs' ↔ s = s' ∨ s.Subsingleton ∧ s'.Subsingleton := by
rw [Cycle.length_subsingleton_iff, Cycle.length_subsingleton_iff]
revert s s'
intro s s'
apply @Quotient.inductionOn₂' _ _ _ _ _ s s'
intro l l'
-- Porting note: was `simpa using formPerm_eq_formPerm_iff`
simp_all
intro hs hs'
constructor <;> intro h <;> simp_all only [formPerm_eq_formPerm_iff]
#align cycle.form_perm_eq_form_perm_iff Cycle.formPerm_eq_formPerm_iff
end Cycle
namespace Equiv.Perm
section Fintype
variable [Fintype α] [DecidableEq α] (p : Equiv.Perm α) (x : α)
/-- `Equiv.Perm.toList (f : Perm α) (x : α)` generates the list `[x, f x, f (f x), ...]`
until looping. That means when `f x = x`, `toList f x = []`.
-/
def toList : List α :=
(List.range (cycleOf p x).support.card).map fun k => (p ^ k) x
#align equiv.perm.to_list Equiv.Perm.toList
@[simp]
theorem toList_one : toList (1 : Perm α) x = [] := by simp [toList, cycleOf_one]
#align equiv.perm.to_list_one Equiv.Perm.toList_one
@[simp]
theorem toList_eq_nil_iff {p : Perm α} {x} : toList p x = [] ↔ x ∉ p.support := by simp [toList]
#align equiv.perm.to_list_eq_nil_iff Equiv.Perm.toList_eq_nil_iff
@[simp]
theorem length_toList : length (toList p x) = (cycleOf p x).support.card := by simp [toList]
#align equiv.perm.length_to_list Equiv.Perm.length_toList
theorem toList_ne_singleton (y : α) : toList p x ≠ [y] := by
intro H
simpa [card_support_ne_one] using congr_arg length H
#align equiv.perm.to_list_ne_singleton Equiv.Perm.toList_ne_singleton
theorem two_le_length_toList_iff_mem_support {p : Perm α} {x : α} :
2 ≤ length (toList p x) ↔ x ∈ p.support := by simp
#align equiv.perm.two_le_length_to_list_iff_mem_support Equiv.Perm.two_le_length_toList_iff_mem_support
theorem length_toList_pos_of_mem_support (h : x ∈ p.support) : 0 < length (toList p x) :=
zero_lt_two.trans_le (two_le_length_toList_iff_mem_support.mpr h)
#align equiv.perm.length_to_list_pos_of_mem_support Equiv.Perm.length_toList_pos_of_mem_support
theorem get_toList (n : ℕ) (hn : n < length (toList p x)) :
(toList p x).get ⟨n, hn⟩ = (p ^ n) x := by simp [toList]
| Mathlib/GroupTheory/Perm/Cycle/Concrete.lean | 248 | 249 | theorem toList_get_zero (h : x ∈ p.support) :
(toList p x).get ⟨0, (length_toList_pos_of_mem_support _ _ h)⟩ = x := by | simp [toList]
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Analysis.Convex.Side
import Mathlib.Geometry.Euclidean.Angle.Oriented.Rotation
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Affine
#align_import geometry.euclidean.angle.oriented.affine from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Oriented angles.
This file defines oriented angles in Euclidean affine spaces.
## Main definitions
* `EuclideanGeometry.oangle`, with notation `∡`, is the oriented angle determined by three
points.
-/
noncomputable section
open FiniteDimensional Complex
open scoped Affine EuclideanGeometry Real RealInnerProductSpace ComplexConjugate
namespace EuclideanGeometry
variable {V : Type*} {P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
[NormedAddTorsor V P] [hd2 : Fact (finrank ℝ V = 2)] [Module.Oriented ℝ V (Fin 2)]
/-- A fixed choice of positive orientation of Euclidean space `ℝ²` -/
abbrev o := @Module.Oriented.positiveOrientation
/-- The oriented angle at `p₂` between the line segments to `p₁` and `p₃`, modulo `2 * π`. If
either of those points equals `p₂`, this is 0. See `EuclideanGeometry.angle` for the
corresponding unoriented angle definition. -/
def oangle (p₁ p₂ p₃ : P) : Real.Angle :=
o.oangle (p₁ -ᵥ p₂) (p₃ -ᵥ p₂)
#align euclidean_geometry.oangle EuclideanGeometry.oangle
@[inherit_doc] scoped notation "∡" => EuclideanGeometry.oangle
/-- Oriented angles are continuous when neither end point equals the middle point. -/
theorem continuousAt_oangle {x : P × P × P} (hx12 : x.1 ≠ x.2.1) (hx32 : x.2.2 ≠ x.2.1) :
ContinuousAt (fun y : P × P × P => ∡ y.1 y.2.1 y.2.2) x := by
let f : P × P × P → V × V := fun y => (y.1 -ᵥ y.2.1, y.2.2 -ᵥ y.2.1)
have hf1 : (f x).1 ≠ 0 := by simp [hx12]
have hf2 : (f x).2 ≠ 0 := by simp [hx32]
exact (o.continuousAt_oangle hf1 hf2).comp ((continuous_fst.vsub continuous_snd.fst).prod_mk
(continuous_snd.snd.vsub continuous_snd.fst)).continuousAt
#align euclidean_geometry.continuous_at_oangle EuclideanGeometry.continuousAt_oangle
/-- The angle ∡AAB at a point. -/
@[simp]
theorem oangle_self_left (p₁ p₂ : P) : ∡ p₁ p₁ p₂ = 0 := by simp [oangle]
#align euclidean_geometry.oangle_self_left EuclideanGeometry.oangle_self_left
/-- The angle ∡ABB at a point. -/
@[simp]
theorem oangle_self_right (p₁ p₂ : P) : ∡ p₁ p₂ p₂ = 0 := by simp [oangle]
#align euclidean_geometry.oangle_self_right EuclideanGeometry.oangle_self_right
/-- The angle ∡ABA at a point. -/
@[simp]
theorem oangle_self_left_right (p₁ p₂ : P) : ∡ p₁ p₂ p₁ = 0 :=
o.oangle_self _
#align euclidean_geometry.oangle_self_left_right EuclideanGeometry.oangle_self_left_right
/-- If the angle between three points is nonzero, the first two points are not equal. -/
theorem left_ne_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₁ ≠ p₂ := by
rw [← @vsub_ne_zero V]; exact o.left_ne_zero_of_oangle_ne_zero h
#align euclidean_geometry.left_ne_of_oangle_ne_zero EuclideanGeometry.left_ne_of_oangle_ne_zero
/-- If the angle between three points is nonzero, the last two points are not equal. -/
theorem right_ne_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₃ ≠ p₂ := by
rw [← @vsub_ne_zero V]; exact o.right_ne_zero_of_oangle_ne_zero h
#align euclidean_geometry.right_ne_of_oangle_ne_zero EuclideanGeometry.right_ne_of_oangle_ne_zero
/-- If the angle between three points is nonzero, the first and third points are not equal. -/
theorem left_ne_right_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₁ ≠ p₃ := by
rw [← (vsub_left_injective p₂).ne_iff]; exact o.ne_of_oangle_ne_zero h
#align euclidean_geometry.left_ne_right_of_oangle_ne_zero EuclideanGeometry.left_ne_right_of_oangle_ne_zero
/-- If the angle between three points is `π`, the first two points are not equal. -/
theorem left_ne_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₁ ≠ p₂ :=
left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_of_oangle_eq_pi EuclideanGeometry.left_ne_of_oangle_eq_pi
/-- If the angle between three points is `π`, the last two points are not equal. -/
theorem right_ne_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₃ ≠ p₂ :=
right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.right_ne_of_oangle_eq_pi EuclideanGeometry.right_ne_of_oangle_eq_pi
/-- If the angle between three points is `π`, the first and third points are not equal. -/
theorem left_ne_right_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₁ ≠ p₃ :=
left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_right_of_oangle_eq_pi EuclideanGeometry.left_ne_right_of_oangle_eq_pi
/-- If the angle between three points is `π / 2`, the first two points are not equal. -/
theorem left_ne_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) : p₁ ≠ p₂ :=
left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_of_oangle_eq_pi_div_two EuclideanGeometry.left_ne_of_oangle_eq_pi_div_two
/-- If the angle between three points is `π / 2`, the last two points are not equal. -/
theorem right_ne_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) : p₃ ≠ p₂ :=
right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.right_ne_of_oangle_eq_pi_div_two EuclideanGeometry.right_ne_of_oangle_eq_pi_div_two
/-- If the angle between three points is `π / 2`, the first and third points are not equal. -/
theorem left_ne_right_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) :
p₁ ≠ p₃ :=
left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_right_of_oangle_eq_pi_div_two EuclideanGeometry.left_ne_right_of_oangle_eq_pi_div_two
/-- If the angle between three points is `-π / 2`, the first two points are not equal. -/
theorem left_ne_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) :
p₁ ≠ p₂ :=
left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_of_oangle_eq_neg_pi_div_two EuclideanGeometry.left_ne_of_oangle_eq_neg_pi_div_two
/-- If the angle between three points is `-π / 2`, the last two points are not equal. -/
theorem right_ne_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) :
p₃ ≠ p₂ :=
right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.right_ne_of_oangle_eq_neg_pi_div_two EuclideanGeometry.right_ne_of_oangle_eq_neg_pi_div_two
/-- If the angle between three points is `-π / 2`, the first and third points are not equal. -/
theorem left_ne_right_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) :
p₁ ≠ p₃ :=
left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0)
#align euclidean_geometry.left_ne_right_of_oangle_eq_neg_pi_div_two EuclideanGeometry.left_ne_right_of_oangle_eq_neg_pi_div_two
/-- If the sign of the angle between three points is nonzero, the first two points are not
equal. -/
theorem left_ne_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₁ ≠ p₂ :=
left_ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
#align euclidean_geometry.left_ne_of_oangle_sign_ne_zero EuclideanGeometry.left_ne_of_oangle_sign_ne_zero
/-- If the sign of the angle between three points is nonzero, the last two points are not
equal. -/
theorem right_ne_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₃ ≠ p₂ :=
right_ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
#align euclidean_geometry.right_ne_of_oangle_sign_ne_zero EuclideanGeometry.right_ne_of_oangle_sign_ne_zero
/-- If the sign of the angle between three points is nonzero, the first and third points are not
equal. -/
theorem left_ne_right_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₁ ≠ p₃ :=
left_ne_right_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
#align euclidean_geometry.left_ne_right_of_oangle_sign_ne_zero EuclideanGeometry.left_ne_right_of_oangle_sign_ne_zero
/-- If the sign of the angle between three points is positive, the first two points are not
equal. -/
theorem left_ne_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₁ ≠ p₂ :=
left_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.left_ne_of_oangle_sign_eq_one EuclideanGeometry.left_ne_of_oangle_sign_eq_one
/-- If the sign of the angle between three points is positive, the last two points are not
equal. -/
theorem right_ne_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₃ ≠ p₂ :=
right_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.right_ne_of_oangle_sign_eq_one EuclideanGeometry.right_ne_of_oangle_sign_eq_one
/-- If the sign of the angle between three points is positive, the first and third points are not
equal. -/
theorem left_ne_right_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₁ ≠ p₃ :=
left_ne_right_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.left_ne_right_of_oangle_sign_eq_one EuclideanGeometry.left_ne_right_of_oangle_sign_eq_one
/-- If the sign of the angle between three points is negative, the first two points are not
equal. -/
theorem left_ne_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : p₁ ≠ p₂ :=
left_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.left_ne_of_oangle_sign_eq_neg_one EuclideanGeometry.left_ne_of_oangle_sign_eq_neg_one
/-- If the sign of the angle between three points is negative, the last two points are not equal.
-/
theorem right_ne_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : p₃ ≠ p₂ :=
right_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.right_ne_of_oangle_sign_eq_neg_one EuclideanGeometry.right_ne_of_oangle_sign_eq_neg_one
/-- If the sign of the angle between three points is negative, the first and third points are not
equal. -/
theorem left_ne_right_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) :
p₁ ≠ p₃ :=
left_ne_right_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0)
#align euclidean_geometry.left_ne_right_of_oangle_sign_eq_neg_one EuclideanGeometry.left_ne_right_of_oangle_sign_eq_neg_one
/-- Reversing the order of the points passed to `oangle` negates the angle. -/
theorem oangle_rev (p₁ p₂ p₃ : P) : ∡ p₃ p₂ p₁ = -∡ p₁ p₂ p₃ :=
o.oangle_rev _ _
#align euclidean_geometry.oangle_rev EuclideanGeometry.oangle_rev
/-- Adding an angle to that with the order of the points reversed results in 0. -/
@[simp]
theorem oangle_add_oangle_rev (p₁ p₂ p₃ : P) : ∡ p₁ p₂ p₃ + ∡ p₃ p₂ p₁ = 0 :=
o.oangle_add_oangle_rev _ _
#align euclidean_geometry.oangle_add_oangle_rev EuclideanGeometry.oangle_add_oangle_rev
/-- An oriented angle is zero if and only if the angle with the order of the points reversed is
zero. -/
theorem oangle_eq_zero_iff_oangle_rev_eq_zero {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = 0 ↔ ∡ p₃ p₂ p₁ = 0 :=
o.oangle_eq_zero_iff_oangle_rev_eq_zero
#align euclidean_geometry.oangle_eq_zero_iff_oangle_rev_eq_zero EuclideanGeometry.oangle_eq_zero_iff_oangle_rev_eq_zero
/-- An oriented angle is `π` if and only if the angle with the order of the points reversed is
`π`. -/
theorem oangle_eq_pi_iff_oangle_rev_eq_pi {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = π ↔ ∡ p₃ p₂ p₁ = π :=
o.oangle_eq_pi_iff_oangle_rev_eq_pi
#align euclidean_geometry.oangle_eq_pi_iff_oangle_rev_eq_pi EuclideanGeometry.oangle_eq_pi_iff_oangle_rev_eq_pi
/-- An oriented angle is not zero or `π` if and only if the three points are affinely
independent. -/
theorem oangle_ne_zero_and_ne_pi_iff_affineIndependent {p₁ p₂ p₃ : P} :
∡ p₁ p₂ p₃ ≠ 0 ∧ ∡ p₁ p₂ p₃ ≠ π ↔ AffineIndependent ℝ ![p₁, p₂, p₃] := by
rw [oangle, o.oangle_ne_zero_and_ne_pi_iff_linearIndependent,
affineIndependent_iff_linearIndependent_vsub ℝ _ (1 : Fin 3), ←
linearIndependent_equiv (finSuccAboveEquiv (1 : Fin 3)).toEquiv]
convert Iff.rfl
ext i
fin_cases i <;> rfl
#align euclidean_geometry.oangle_ne_zero_and_ne_pi_iff_affine_independent EuclideanGeometry.oangle_ne_zero_and_ne_pi_iff_affineIndependent
/-- An oriented angle is zero or `π` if and only if the three points are collinear. -/
theorem oangle_eq_zero_or_eq_pi_iff_collinear {p₁ p₂ p₃ : P} :
∡ p₁ p₂ p₃ = 0 ∨ ∡ p₁ p₂ p₃ = π ↔ Collinear ℝ ({p₁, p₂, p₃} : Set P) := by
rw [← not_iff_not, not_or, oangle_ne_zero_and_ne_pi_iff_affineIndependent,
affineIndependent_iff_not_collinear_set]
#align euclidean_geometry.oangle_eq_zero_or_eq_pi_iff_collinear EuclideanGeometry.oangle_eq_zero_or_eq_pi_iff_collinear
/-- An oriented angle has a sign zero if and only if the three points are collinear. -/
theorem oangle_sign_eq_zero_iff_collinear {p₁ p₂ p₃ : P} :
(∡ p₁ p₂ p₃).sign = 0 ↔ Collinear ℝ ({p₁, p₂, p₃} : Set P) := by
rw [Real.Angle.sign_eq_zero_iff, oangle_eq_zero_or_eq_pi_iff_collinear]
/-- If twice the oriented angles between two triples of points are equal, one triple is affinely
independent if and only if the other is. -/
theorem affineIndependent_iff_of_two_zsmul_oangle_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P}
(h : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆) :
AffineIndependent ℝ ![p₁, p₂, p₃] ↔ AffineIndependent ℝ ![p₄, p₅, p₆] := by
simp_rw [← oangle_ne_zero_and_ne_pi_iff_affineIndependent, ← Real.Angle.two_zsmul_ne_zero_iff, h]
#align euclidean_geometry.affine_independent_iff_of_two_zsmul_oangle_eq EuclideanGeometry.affineIndependent_iff_of_two_zsmul_oangle_eq
/-- If twice the oriented angles between two triples of points are equal, one triple is collinear
if and only if the other is. -/
theorem collinear_iff_of_two_zsmul_oangle_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P}
(h : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆) :
Collinear ℝ ({p₁, p₂, p₃} : Set P) ↔ Collinear ℝ ({p₄, p₅, p₆} : Set P) := by
simp_rw [← oangle_eq_zero_or_eq_pi_iff_collinear, ← Real.Angle.two_zsmul_eq_zero_iff, h]
#align euclidean_geometry.collinear_iff_of_two_zsmul_oangle_eq EuclideanGeometry.collinear_iff_of_two_zsmul_oangle_eq
/-- If corresponding pairs of points in two angles have the same vector span, twice those angles
are equal. -/
theorem two_zsmul_oangle_of_vectorSpan_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P}
(h₁₂₄₅ : vectorSpan ℝ ({p₁, p₂} : Set P) = vectorSpan ℝ ({p₄, p₅} : Set P))
(h₃₂₆₅ : vectorSpan ℝ ({p₃, p₂} : Set P) = vectorSpan ℝ ({p₆, p₅} : Set P)) :
(2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆ := by
simp_rw [vectorSpan_pair] at h₁₂₄₅ h₃₂₆₅
exact o.two_zsmul_oangle_of_span_eq_of_span_eq h₁₂₄₅ h₃₂₆₅
#align euclidean_geometry.two_zsmul_oangle_of_vector_span_eq EuclideanGeometry.two_zsmul_oangle_of_vectorSpan_eq
/-- If the lines determined by corresponding pairs of points in two angles are parallel, twice
those angles are equal. -/
theorem two_zsmul_oangle_of_parallel {p₁ p₂ p₃ p₄ p₅ p₆ : P}
(h₁₂₄₅ : line[ℝ, p₁, p₂] ∥ line[ℝ, p₄, p₅]) (h₃₂₆₅ : line[ℝ, p₃, p₂] ∥ line[ℝ, p₆, p₅]) :
(2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆ := by
rw [AffineSubspace.affineSpan_pair_parallel_iff_vectorSpan_eq] at h₁₂₄₅ h₃₂₆₅
exact two_zsmul_oangle_of_vectorSpan_eq h₁₂₄₅ h₃₂₆₅
#align euclidean_geometry.two_zsmul_oangle_of_parallel EuclideanGeometry.two_zsmul_oangle_of_parallel
/-- Given three points not equal to `p`, the angle between the first and the second at `p` plus
the angle between the second and the third equals the angle between the first and the third. -/
@[simp]
theorem oangle_add {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) :
∡ p₁ p p₂ + ∡ p₂ p p₃ = ∡ p₁ p p₃ :=
o.oangle_add (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃)
#align euclidean_geometry.oangle_add EuclideanGeometry.oangle_add
/-- Given three points not equal to `p`, the angle between the second and the third at `p` plus
the angle between the first and the second equals the angle between the first and the third. -/
@[simp]
theorem oangle_add_swap {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) :
∡ p₂ p p₃ + ∡ p₁ p p₂ = ∡ p₁ p p₃ :=
o.oangle_add_swap (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃)
#align euclidean_geometry.oangle_add_swap EuclideanGeometry.oangle_add_swap
/-- Given three points not equal to `p`, the angle between the first and the third at `p` minus
the angle between the first and the second equals the angle between the second and the third. -/
@[simp]
theorem oangle_sub_left {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) :
∡ p₁ p p₃ - ∡ p₁ p p₂ = ∡ p₂ p p₃ :=
o.oangle_sub_left (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃)
#align euclidean_geometry.oangle_sub_left EuclideanGeometry.oangle_sub_left
/-- Given three points not equal to `p`, the angle between the first and the third at `p` minus
the angle between the second and the third equals the angle between the first and the second. -/
@[simp]
theorem oangle_sub_right {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) :
∡ p₁ p p₃ - ∡ p₂ p p₃ = ∡ p₁ p p₂ :=
o.oangle_sub_right (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃)
#align euclidean_geometry.oangle_sub_right EuclideanGeometry.oangle_sub_right
/-- Given three points not equal to `p`, adding the angles between them at `p` in cyclic order
results in 0. -/
@[simp]
theorem oangle_add_cyc3 {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) :
∡ p₁ p p₂ + ∡ p₂ p p₃ + ∡ p₃ p p₁ = 0 :=
o.oangle_add_cyc3 (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃)
#align euclidean_geometry.oangle_add_cyc3 EuclideanGeometry.oangle_add_cyc3
/-- Pons asinorum, oriented angle-at-point form. -/
theorem oangle_eq_oangle_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₁ p₂ = dist p₁ p₃) :
∡ p₁ p₂ p₃ = ∡ p₂ p₃ p₁ := by
simp_rw [dist_eq_norm_vsub V] at h
rw [oangle, oangle, ← vsub_sub_vsub_cancel_left p₃ p₂ p₁, ← vsub_sub_vsub_cancel_left p₂ p₃ p₁,
o.oangle_sub_eq_oangle_sub_rev_of_norm_eq h]
#align euclidean_geometry.oangle_eq_oangle_of_dist_eq EuclideanGeometry.oangle_eq_oangle_of_dist_eq
/-- The angle at the apex of an isosceles triangle is `π` minus twice a base angle, oriented
angle-at-point form. -/
theorem oangle_eq_pi_sub_two_zsmul_oangle_of_dist_eq {p₁ p₂ p₃ : P} (hn : p₂ ≠ p₃)
(h : dist p₁ p₂ = dist p₁ p₃) : ∡ p₃ p₁ p₂ = π - (2 : ℤ) • ∡ p₁ p₂ p₃ := by
simp_rw [dist_eq_norm_vsub V] at h
rw [oangle, oangle]
convert o.oangle_eq_pi_sub_two_zsmul_oangle_sub_of_norm_eq _ h using 1
· rw [← neg_vsub_eq_vsub_rev p₁ p₃, ← neg_vsub_eq_vsub_rev p₁ p₂, o.oangle_neg_neg]
· rw [← o.oangle_sub_eq_oangle_sub_rev_of_norm_eq h]; simp
· simpa using hn
#align euclidean_geometry.oangle_eq_pi_sub_two_zsmul_oangle_of_dist_eq EuclideanGeometry.oangle_eq_pi_sub_two_zsmul_oangle_of_dist_eq
/-- A base angle of an isosceles triangle is acute, oriented angle-at-point form. -/
theorem abs_oangle_right_toReal_lt_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P}
(h : dist p₁ p₂ = dist p₁ p₃) : |(∡ p₁ p₂ p₃).toReal| < π / 2 := by
simp_rw [dist_eq_norm_vsub V] at h
rw [oangle, ← vsub_sub_vsub_cancel_left p₃ p₂ p₁]
exact o.abs_oangle_sub_right_toReal_lt_pi_div_two h
#align euclidean_geometry.abs_oangle_right_to_real_lt_pi_div_two_of_dist_eq EuclideanGeometry.abs_oangle_right_toReal_lt_pi_div_two_of_dist_eq
/-- A base angle of an isosceles triangle is acute, oriented angle-at-point form. -/
theorem abs_oangle_left_toReal_lt_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P}
(h : dist p₁ p₂ = dist p₁ p₃) : |(∡ p₂ p₃ p₁).toReal| < π / 2 :=
oangle_eq_oangle_of_dist_eq h ▸ abs_oangle_right_toReal_lt_pi_div_two_of_dist_eq h
#align euclidean_geometry.abs_oangle_left_to_real_lt_pi_div_two_of_dist_eq EuclideanGeometry.abs_oangle_left_toReal_lt_pi_div_two_of_dist_eq
/-- The cosine of the oriented angle at `p` between two points not equal to `p` equals that of the
unoriented angle. -/
theorem cos_oangle_eq_cos_angle {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) :
Real.Angle.cos (∡ p₁ p p₂) = Real.cos (∠ p₁ p p₂) :=
o.cos_oangle_eq_cos_angle (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂)
#align euclidean_geometry.cos_oangle_eq_cos_angle EuclideanGeometry.cos_oangle_eq_cos_angle
/-- The oriented angle at `p` between two points not equal to `p` is plus or minus the unoriented
angle. -/
theorem oangle_eq_angle_or_eq_neg_angle {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) :
∡ p₁ p p₂ = ∠ p₁ p p₂ ∨ ∡ p₁ p p₂ = -∠ p₁ p p₂ :=
o.oangle_eq_angle_or_eq_neg_angle (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂)
#align euclidean_geometry.oangle_eq_angle_or_eq_neg_angle EuclideanGeometry.oangle_eq_angle_or_eq_neg_angle
/-- The unoriented angle at `p` between two points not equal to `p` is the absolute value of the
oriented angle. -/
theorem angle_eq_abs_oangle_toReal {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) :
∠ p₁ p p₂ = |(∡ p₁ p p₂).toReal| :=
o.angle_eq_abs_oangle_toReal (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂)
#align euclidean_geometry.angle_eq_abs_oangle_to_real EuclideanGeometry.angle_eq_abs_oangle_toReal
/-- If the sign of the oriented angle at `p` between two points is zero, either one of the points
equals `p` or the unoriented angle is 0 or π. -/
theorem eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero {p p₁ p₂ : P}
(h : (∡ p₁ p p₂).sign = 0) : p₁ = p ∨ p₂ = p ∨ ∠ p₁ p p₂ = 0 ∨ ∠ p₁ p p₂ = π := by
convert o.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero h <;> simp
#align euclidean_geometry.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero EuclideanGeometry.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero
/-- If two unoriented angles are equal, and the signs of the corresponding oriented angles are
equal, then the oriented angles are equal (even in degenerate cases). -/
theorem oangle_eq_of_angle_eq_of_sign_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h : ∠ p₁ p₂ p₃ = ∠ p₄ p₅ p₆)
(hs : (∡ p₁ p₂ p₃).sign = (∡ p₄ p₅ p₆).sign) : ∡ p₁ p₂ p₃ = ∡ p₄ p₅ p₆ :=
o.oangle_eq_of_angle_eq_of_sign_eq h hs
#align euclidean_geometry.oangle_eq_of_angle_eq_of_sign_eq EuclideanGeometry.oangle_eq_of_angle_eq_of_sign_eq
/-- If the signs of two nondegenerate oriented angles between points are equal, the oriented
angles are equal if and only if the unoriented angles are equal. -/
theorem angle_eq_iff_oangle_eq_of_sign_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (hp₁ : p₁ ≠ p₂) (hp₃ : p₃ ≠ p₂)
(hp₄ : p₄ ≠ p₅) (hp₆ : p₆ ≠ p₅) (hs : (∡ p₁ p₂ p₃).sign = (∡ p₄ p₅ p₆).sign) :
∠ p₁ p₂ p₃ = ∠ p₄ p₅ p₆ ↔ ∡ p₁ p₂ p₃ = ∡ p₄ p₅ p₆ :=
o.angle_eq_iff_oangle_eq_of_sign_eq (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₃) (vsub_ne_zero.2 hp₄)
(vsub_ne_zero.2 hp₆) hs
#align euclidean_geometry.angle_eq_iff_oangle_eq_of_sign_eq EuclideanGeometry.angle_eq_iff_oangle_eq_of_sign_eq
/-- The oriented angle between three points equals the unoriented angle if the sign is
positive. -/
theorem oangle_eq_angle_of_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) :
∡ p₁ p₂ p₃ = ∠ p₁ p₂ p₃ :=
o.oangle_eq_angle_of_sign_eq_one h
#align euclidean_geometry.oangle_eq_angle_of_sign_eq_one EuclideanGeometry.oangle_eq_angle_of_sign_eq_one
/-- The oriented angle between three points equals minus the unoriented angle if the sign is
negative. -/
theorem oangle_eq_neg_angle_of_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) :
∡ p₁ p₂ p₃ = -∠ p₁ p₂ p₃ :=
o.oangle_eq_neg_angle_of_sign_eq_neg_one h
#align euclidean_geometry.oangle_eq_neg_angle_of_sign_eq_neg_one EuclideanGeometry.oangle_eq_neg_angle_of_sign_eq_neg_one
/-- The unoriented angle at `p` between two points not equal to `p` is zero if and only if the
unoriented angle is zero. -/
theorem oangle_eq_zero_iff_angle_eq_zero {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) :
∡ p₁ p p₂ = 0 ↔ ∠ p₁ p p₂ = 0 :=
o.oangle_eq_zero_iff_angle_eq_zero (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂)
#align euclidean_geometry.oangle_eq_zero_iff_angle_eq_zero EuclideanGeometry.oangle_eq_zero_iff_angle_eq_zero
/-- The oriented angle between three points is `π` if and only if the unoriented angle is `π`. -/
theorem oangle_eq_pi_iff_angle_eq_pi {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = π ↔ ∠ p₁ p₂ p₃ = π :=
o.oangle_eq_pi_iff_angle_eq_pi
#align euclidean_geometry.oangle_eq_pi_iff_angle_eq_pi EuclideanGeometry.oangle_eq_pi_iff_angle_eq_pi
/-- If the oriented angle between three points is `π / 2`, so is the unoriented angle. -/
theorem angle_eq_pi_div_two_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∠ p₁ p₂ p₃ = π / 2 := by
rw [angle, ← InnerProductGeometry.inner_eq_zero_iff_angle_eq_pi_div_two]
exact o.inner_eq_zero_of_oangle_eq_pi_div_two h
#align euclidean_geometry.angle_eq_pi_div_two_of_oangle_eq_pi_div_two EuclideanGeometry.angle_eq_pi_div_two_of_oangle_eq_pi_div_two
/-- If the oriented angle between three points is `π / 2`, so is the unoriented angle
(reversed). -/
theorem angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) :
∠ p₃ p₂ p₁ = π / 2 := by
rw [angle_comm]
exact angle_eq_pi_div_two_of_oangle_eq_pi_div_two h
#align euclidean_geometry.angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two EuclideanGeometry.angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two
/-- If the oriented angle between three points is `-π / 2`, the unoriented angle is `π / 2`. -/
theorem angle_eq_pi_div_two_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P}
(h : ∡ p₁ p₂ p₃ = ↑(-π / 2)) : ∠ p₁ p₂ p₃ = π / 2 := by
rw [angle, ← InnerProductGeometry.inner_eq_zero_iff_angle_eq_pi_div_two]
exact o.inner_eq_zero_of_oangle_eq_neg_pi_div_two h
#align euclidean_geometry.angle_eq_pi_div_two_of_oangle_eq_neg_pi_div_two EuclideanGeometry.angle_eq_pi_div_two_of_oangle_eq_neg_pi_div_two
/-- If the oriented angle between three points is `-π / 2`, the unoriented angle (reversed) is
`π / 2`. -/
| Mathlib/Geometry/Euclidean/Angle/Oriented/Affine.lean | 443 | 446 | theorem angle_rev_eq_pi_div_two_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P}
(h : ∡ p₁ p₂ p₃ = ↑(-π / 2)) : ∠ p₃ p₂ p₁ = π / 2 := by |
rw [angle_comm]
exact angle_eq_pi_div_two_of_oangle_eq_neg_pi_div_two h
|
/-
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, Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Associated
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Data.Nat.Factors
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Multiplicity
#align_import ring_theory.unique_factorization_domain from "leanprover-community/mathlib"@"570e9f4877079b3a923135b3027ac3be8695ab8c"
/-!
# Unique factorization
## Main Definitions
* `WfDvdMonoid` holds for `Monoid`s for which a strict divisibility relation is
well-founded.
* `UniqueFactorizationMonoid` holds for `WfDvdMonoid`s where
`Irreducible` is equivalent to `Prime`
## To do
* set up the complete lattice structure on `FactorSet`.
-/
variable {α : Type*}
local infixl:50 " ~ᵤ " => Associated
/-- Well-foundedness of the strict version of |, which is equivalent to the descending chain
condition on divisibility and to the ascending chain condition on
principal ideals in an integral domain.
-/
class WfDvdMonoid (α : Type*) [CommMonoidWithZero α] : Prop where
wellFounded_dvdNotUnit : WellFounded (@DvdNotUnit α _)
#align wf_dvd_monoid WfDvdMonoid
export WfDvdMonoid (wellFounded_dvdNotUnit)
-- see Note [lower instance priority]
instance (priority := 100) IsNoetherianRing.wfDvdMonoid [CommRing α] [IsDomain α]
[IsNoetherianRing α] : WfDvdMonoid α :=
⟨by
convert InvImage.wf (fun a => Ideal.span ({a} : Set α)) (wellFounded_submodule_gt _ _)
ext
exact Ideal.span_singleton_lt_span_singleton.symm⟩
#align is_noetherian_ring.wf_dvd_monoid IsNoetherianRing.wfDvdMonoid
namespace WfDvdMonoid
variable [CommMonoidWithZero α]
open Associates Nat
theorem of_wfDvdMonoid_associates (_ : WfDvdMonoid (Associates α)) : WfDvdMonoid α :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).2 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.of_wf_dvd_monoid_associates WfDvdMonoid.of_wfDvdMonoid_associates
variable [WfDvdMonoid α]
instance wfDvdMonoid_associates : WfDvdMonoid (Associates α) :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).1 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.wf_dvd_monoid_associates WfDvdMonoid.wfDvdMonoid_associates
theorem wellFounded_associates : WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
Subrelation.wf dvdNotUnit_of_lt wellFounded_dvdNotUnit
#align wf_dvd_monoid.well_founded_associates WfDvdMonoid.wellFounded_associates
-- Porting note: elab_as_elim can only be global and cannot be changed on an imported decl
-- attribute [local elab_as_elim] WellFounded.fix
theorem exists_irreducible_factor {a : α} (ha : ¬IsUnit a) (ha0 : a ≠ 0) :
∃ i, Irreducible i ∧ i ∣ a :=
let ⟨b, hs, hr⟩ := wellFounded_dvdNotUnit.has_min { b | b ∣ a ∧ ¬IsUnit b } ⟨a, dvd_rfl, ha⟩
⟨b,
⟨hs.2, fun c d he =>
let h := dvd_trans ⟨d, he⟩ hs.1
or_iff_not_imp_left.2 fun hc =>
of_not_not fun hd => hr c ⟨h, hc⟩ ⟨ne_zero_of_dvd_ne_zero ha0 h, d, hd, he⟩⟩,
hs.1⟩
#align wf_dvd_monoid.exists_irreducible_factor WfDvdMonoid.exists_irreducible_factor
@[elab_as_elim]
theorem induction_on_irreducible {P : α → Prop} (a : α) (h0 : P 0) (hu : ∀ u : α, IsUnit u → P u)
(hi : ∀ a i : α, a ≠ 0 → Irreducible i → P a → P (i * a)) : P a :=
haveI := Classical.dec
wellFounded_dvdNotUnit.fix
(fun a ih =>
if ha0 : a = 0 then ha0.substr h0
else
if hau : IsUnit a then hu a hau
else
let ⟨i, hii, b, hb⟩ := exists_irreducible_factor hau ha0
let hb0 : b ≠ 0 := ne_zero_of_dvd_ne_zero ha0 ⟨i, mul_comm i b ▸ hb⟩
hb.symm ▸ hi b i hb0 hii <| ih b ⟨hb0, i, hii.1, mul_comm i b ▸ hb⟩)
a
#align wf_dvd_monoid.induction_on_irreducible WfDvdMonoid.induction_on_irreducible
theorem exists_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ Associated f.prod a :=
induction_on_irreducible a (fun h => (h rfl).elim)
(fun u hu _ => ⟨0, fun _ h => False.elim (Multiset.not_mem_zero _ h), hu.unit, one_mul _⟩)
fun a i ha0 hi ih _ =>
let ⟨s, hs⟩ := ih ha0
⟨i ::ₘ s, fun b H => (Multiset.mem_cons.1 H).elim (fun h => h.symm ▸ hi) (hs.1 b), by
rw [s.prod_cons i]
exact hs.2.mul_left i⟩
#align wf_dvd_monoid.exists_factors WfDvdMonoid.exists_factors
theorem not_unit_iff_exists_factors_eq (a : α) (hn0 : a ≠ 0) :
¬IsUnit a ↔ ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod = a ∧ f ≠ ∅ :=
⟨fun hnu => by
obtain ⟨f, hi, u, rfl⟩ := exists_factors a hn0
obtain ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero fun h : f = 0 => hnu <| by simp [h]
classical
refine ⟨(f.erase b).cons (b * u), fun a ha => ?_, ?_, Multiset.cons_ne_zero⟩
· obtain rfl | ha := Multiset.mem_cons.1 ha
exacts [Associated.irreducible ⟨u, rfl⟩ (hi b h), hi a (Multiset.mem_of_mem_erase ha)]
· rw [Multiset.prod_cons, mul_comm b, mul_assoc, Multiset.prod_erase h, mul_comm],
fun ⟨f, hi, he, hne⟩ =>
let ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero hne
not_isUnit_of_not_isUnit_dvd (hi b h).not_unit <| he ▸ Multiset.dvd_prod h⟩
#align wf_dvd_monoid.not_unit_iff_exists_factors_eq WfDvdMonoid.not_unit_iff_exists_factors_eq
theorem isRelPrime_of_no_irreducible_factors {x y : α} (nonzero : ¬(x = 0 ∧ y = 0))
(H : ∀ z : α, Irreducible z → z ∣ x → ¬z ∣ y) : IsRelPrime x y :=
isRelPrime_of_no_nonunits_factors nonzero fun _z znu znz zx zy ↦
have ⟨i, h1, h2⟩ := exists_irreducible_factor znu znz
H i h1 (h2.trans zx) (h2.trans zy)
end WfDvdMonoid
theorem WfDvdMonoid.of_wellFounded_associates [CancelCommMonoidWithZero α]
(h : WellFounded ((· < ·) : Associates α → Associates α → Prop)) : WfDvdMonoid α :=
WfDvdMonoid.of_wfDvdMonoid_associates
⟨by
convert h
ext
exact Associates.dvdNotUnit_iff_lt⟩
#align wf_dvd_monoid.of_well_founded_associates WfDvdMonoid.of_wellFounded_associates
theorem WfDvdMonoid.iff_wellFounded_associates [CancelCommMonoidWithZero α] :
WfDvdMonoid α ↔ WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
⟨by apply WfDvdMonoid.wellFounded_associates, WfDvdMonoid.of_wellFounded_associates⟩
#align wf_dvd_monoid.iff_well_founded_associates WfDvdMonoid.iff_wellFounded_associates
theorem WfDvdMonoid.max_power_factor' [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : ¬IsUnit x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a := by
obtain ⟨a, ⟨n, rfl⟩, hm⟩ := wellFounded_dvdNotUnit.has_min
{a | ∃ n, x ^ n * a = a₀} ⟨a₀, 0, by rw [pow_zero, one_mul]⟩
refine ⟨n, a, ?_, rfl⟩; rintro ⟨d, rfl⟩
exact hm d ⟨n + 1, by rw [pow_succ, mul_assoc]⟩
⟨(right_ne_zero_of_mul <| right_ne_zero_of_mul h), x, hx, mul_comm _ _⟩
theorem WfDvdMonoid.max_power_factor [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : Irreducible x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a :=
max_power_factor' h hx.not_unit
theorem multiplicity.finite_of_not_isUnit [CancelCommMonoidWithZero α] [WfDvdMonoid α]
{a b : α} (ha : ¬IsUnit a) (hb : b ≠ 0) : multiplicity.Finite a b := by
obtain ⟨n, c, ndvd, rfl⟩ := WfDvdMonoid.max_power_factor' hb ha
exact ⟨n, by rwa [pow_succ, mul_dvd_mul_iff_left (left_ne_zero_of_mul hb)]⟩
section Prio
-- set_option default_priority 100
-- see Note [default priority]
/-- unique factorization monoids.
These are defined as `CancelCommMonoidWithZero`s with well-founded strict divisibility
relations, but this is equivalent to more familiar definitions:
Each element (except zero) is uniquely represented as a multiset of irreducible factors.
Uniqueness is only up to associated elements.
Each element (except zero) is non-uniquely represented as a multiset
of prime factors.
To define a UFD using the definition in terms of multisets
of irreducible factors, use the definition `of_exists_unique_irreducible_factors`
To define a UFD using the definition in terms of multisets
of prime factors, use the definition `of_exists_prime_factors`
-/
class UniqueFactorizationMonoid (α : Type*) [CancelCommMonoidWithZero α] extends WfDvdMonoid α :
Prop where
protected irreducible_iff_prime : ∀ {a : α}, Irreducible a ↔ Prime a
#align unique_factorization_monoid UniqueFactorizationMonoid
/-- Can't be an instance because it would cause a loop `ufm → WfDvdMonoid → ufm → ...`. -/
theorem ufm_of_decomposition_of_wfDvdMonoid [CancelCommMonoidWithZero α] [WfDvdMonoid α]
[DecompositionMonoid α] : UniqueFactorizationMonoid α :=
{ ‹WfDvdMonoid α› with irreducible_iff_prime := irreducible_iff_prime }
#align ufm_of_gcd_of_wf_dvd_monoid ufm_of_decomposition_of_wfDvdMonoid
@[deprecated] alias ufm_of_gcd_of_wfDvdMonoid := ufm_of_decomposition_of_wfDvdMonoid
instance Associates.ufm [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α] :
UniqueFactorizationMonoid (Associates α) :=
{ (WfDvdMonoid.wfDvdMonoid_associates : WfDvdMonoid (Associates α)) with
irreducible_iff_prime := by
rw [← Associates.irreducible_iff_prime_iff]
apply UniqueFactorizationMonoid.irreducible_iff_prime }
#align associates.ufm Associates.ufm
end Prio
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem exists_prime_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime]
apply WfDvdMonoid.exists_factors a
#align unique_factorization_monoid.exists_prime_factors UniqueFactorizationMonoid.exists_prime_factors
instance : DecompositionMonoid α where
primal a := by
obtain rfl | ha := eq_or_ne a 0; · exact isPrimal_zero
obtain ⟨f, hf, u, rfl⟩ := exists_prime_factors a ha
exact ((Submonoid.isPrimal α).multiset_prod_mem f (hf · ·|>.isPrimal)).mul u.isUnit.isPrimal
lemma exists_prime_iff :
(∃ (p : α), Prime p) ↔ ∃ (x : α), x ≠ 0 ∧ ¬ IsUnit x := by
refine ⟨fun ⟨p, hp⟩ ↦ ⟨p, hp.ne_zero, hp.not_unit⟩, fun ⟨x, hx₀, hxu⟩ ↦ ?_⟩
obtain ⟨f, hf, -⟩ := WfDvdMonoid.exists_irreducible_factor hxu hx₀
exact ⟨f, UniqueFactorizationMonoid.irreducible_iff_prime.mp hf⟩
@[elab_as_elim]
theorem induction_on_prime {P : α → Prop} (a : α) (h₁ : P 0) (h₂ : ∀ x : α, IsUnit x → P x)
(h₃ : ∀ a p : α, a ≠ 0 → Prime p → P a → P (p * a)) : P a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime] at h₃
exact WfDvdMonoid.induction_on_irreducible a h₁ h₂ h₃
#align unique_factorization_monoid.induction_on_prime UniqueFactorizationMonoid.induction_on_prime
end UniqueFactorizationMonoid
theorem prime_factors_unique [CancelCommMonoidWithZero α] :
∀ {f g : Multiset α},
(∀ x ∈ f, Prime x) → (∀ x ∈ g, Prime x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g := by
classical
intro f
induction' f using Multiset.induction_on with p f ih
· intros g _ hg h
exact Multiset.rel_zero_left.2 <|
Multiset.eq_zero_of_forall_not_mem fun x hx =>
have : IsUnit g.prod := by simpa [associated_one_iff_isUnit] using h.symm
(hg x hx).not_unit <|
isUnit_iff_dvd_one.2 <| (Multiset.dvd_prod hx).trans (isUnit_iff_dvd_one.1 this)
· intros g hf hg hfg
let ⟨b, hbg, hb⟩ :=
(exists_associated_mem_of_dvd_prod (hf p (by simp)) fun q hq => hg _ hq) <|
hfg.dvd_iff_dvd_right.1 (show p ∣ (p ::ₘ f).prod by simp)
haveI := Classical.decEq α
rw [← Multiset.cons_erase hbg]
exact
Multiset.Rel.cons hb
(ih (fun q hq => hf _ (by simp [hq]))
(fun {q} (hq : q ∈ g.erase b) => hg q (Multiset.mem_of_mem_erase hq))
(Associated.of_mul_left
(by rwa [← Multiset.prod_cons, ← Multiset.prod_cons, Multiset.cons_erase hbg]) hb
(hf p (by simp)).ne_zero))
#align prime_factors_unique prime_factors_unique
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem factors_unique {f g : Multiset α} (hf : ∀ x ∈ f, Irreducible x)
(hg : ∀ x ∈ g, Irreducible x) (h : f.prod ~ᵤ g.prod) : Multiset.Rel Associated f g :=
prime_factors_unique (fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hf x hx))
(fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hg x hx)) h
#align unique_factorization_monoid.factors_unique UniqueFactorizationMonoid.factors_unique
end UniqueFactorizationMonoid
/-- If an irreducible has a prime factorization,
then it is an associate of one of its prime factors. -/
theorem prime_factors_irreducible [CancelCommMonoidWithZero α] {a : α} {f : Multiset α}
(ha : Irreducible a) (pfa : (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a) : ∃ p, a ~ᵤ p ∧ f = {p} := by
haveI := Classical.decEq α
refine @Multiset.induction_on _
(fun g => (g.prod ~ᵤ a) → (∀ b ∈ g, Prime b) → ∃ p, a ~ᵤ p ∧ g = {p}) f ?_ ?_ pfa.2 pfa.1
· intro h; exact (ha.not_unit (associated_one_iff_isUnit.1 (Associated.symm h))).elim
· rintro p s _ ⟨u, hu⟩ hs
use p
have hs0 : s = 0 := by
by_contra hs0
obtain ⟨q, hq⟩ := Multiset.exists_mem_of_ne_zero hs0
apply (hs q (by simp [hq])).2.1
refine (ha.isUnit_or_isUnit (?_ : _ = p * ↑u * (s.erase q).prod * _)).resolve_left ?_
· rw [mul_right_comm _ _ q, mul_assoc, ← Multiset.prod_cons, Multiset.cons_erase hq, ← hu,
mul_comm, mul_comm p _, mul_assoc]
simp
apply mt isUnit_of_mul_isUnit_left (mt isUnit_of_mul_isUnit_left _)
apply (hs p (Multiset.mem_cons_self _ _)).2.1
simp only [mul_one, Multiset.prod_cons, Multiset.prod_zero, hs0] at *
exact ⟨Associated.symm ⟨u, hu⟩, rfl⟩
#align prime_factors_irreducible prime_factors_irreducible
section ExistsPrimeFactors
variable [CancelCommMonoidWithZero α]
variable (pf : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a)
theorem WfDvdMonoid.of_exists_prime_factors : WfDvdMonoid α :=
⟨by
classical
refine RelHomClass.wellFounded
(RelHom.mk ?_ ?_ : (DvdNotUnit : α → α → Prop) →r ((· < ·) : ℕ∞ → ℕ∞ → Prop)) wellFounded_lt
· intro a
by_cases h : a = 0
· exact ⊤
exact ↑(Multiset.card (Classical.choose (pf a h)))
rintro a b ⟨ane0, ⟨c, hc, b_eq⟩⟩
rw [dif_neg ane0]
by_cases h : b = 0
· simp [h, lt_top_iff_ne_top]
· rw [dif_neg h]
erw [WithTop.coe_lt_coe]
have cne0 : c ≠ 0 := by
refine mt (fun con => ?_) h
rw [b_eq, con, mul_zero]
calc
Multiset.card (Classical.choose (pf a ane0)) <
_ + Multiset.card (Classical.choose (pf c cne0)) :=
lt_add_of_pos_right _
(Multiset.card_pos.mpr fun con => hc (associated_one_iff_isUnit.mp ?_))
_ = Multiset.card (Classical.choose (pf a ane0) + Classical.choose (pf c cne0)) :=
(Multiset.card_add _ _).symm
_ = Multiset.card (Classical.choose (pf b h)) :=
Multiset.card_eq_card_of_rel
(prime_factors_unique ?_ (Classical.choose_spec (pf _ h)).1 ?_)
· convert (Classical.choose_spec (pf c cne0)).2.symm
rw [con, Multiset.prod_zero]
· intro x hadd
rw [Multiset.mem_add] at hadd
cases' hadd with h h <;> apply (Classical.choose_spec (pf _ _)).1 _ h <;> assumption
· rw [Multiset.prod_add]
trans a * c
· apply Associated.mul_mul <;> apply (Classical.choose_spec (pf _ _)).2 <;> assumption
· rw [← b_eq]
apply (Classical.choose_spec (pf _ _)).2.symm; assumption⟩
#align wf_dvd_monoid.of_exists_prime_factors WfDvdMonoid.of_exists_prime_factors
theorem irreducible_iff_prime_of_exists_prime_factors {p : α} : Irreducible p ↔ Prime p := by
by_cases hp0 : p = 0
· simp [hp0]
refine ⟨fun h => ?_, Prime.irreducible⟩
obtain ⟨f, hf⟩ := pf p hp0
obtain ⟨q, hq, rfl⟩ := prime_factors_irreducible h hf
rw [hq.prime_iff]
exact hf.1 q (Multiset.mem_singleton_self _)
#align irreducible_iff_prime_of_exists_prime_factors irreducible_iff_prime_of_exists_prime_factors
theorem UniqueFactorizationMonoid.of_exists_prime_factors : UniqueFactorizationMonoid α :=
{ WfDvdMonoid.of_exists_prime_factors pf with
irreducible_iff_prime := irreducible_iff_prime_of_exists_prime_factors pf }
#align unique_factorization_monoid.of_exists_prime_factors UniqueFactorizationMonoid.of_exists_prime_factors
end ExistsPrimeFactors
theorem UniqueFactorizationMonoid.iff_exists_prime_factors [CancelCommMonoidWithZero α] :
UniqueFactorizationMonoid α ↔
∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a :=
⟨fun h => @UniqueFactorizationMonoid.exists_prime_factors _ _ h,
UniqueFactorizationMonoid.of_exists_prime_factors⟩
#align unique_factorization_monoid.iff_exists_prime_factors UniqueFactorizationMonoid.iff_exists_prime_factors
section
variable {β : Type*} [CancelCommMonoidWithZero α] [CancelCommMonoidWithZero β]
theorem MulEquiv.uniqueFactorizationMonoid (e : α ≃* β) (hα : UniqueFactorizationMonoid α) :
UniqueFactorizationMonoid β := by
rw [UniqueFactorizationMonoid.iff_exists_prime_factors] at hα ⊢
intro a ha
obtain ⟨w, hp, u, h⟩ :=
hα (e.symm a) fun h =>
ha <| by
convert← map_zero e
simp [← h]
exact
⟨w.map e, fun b hb =>
let ⟨c, hc, he⟩ := Multiset.mem_map.1 hb
he ▸ e.prime_iff.1 (hp c hc),
Units.map e.toMonoidHom u,
by
erw [Multiset.prod_hom, ← e.map_mul, h]
simp⟩
#align mul_equiv.unique_factorization_monoid MulEquiv.uniqueFactorizationMonoid
theorem MulEquiv.uniqueFactorizationMonoid_iff (e : α ≃* β) :
UniqueFactorizationMonoid α ↔ UniqueFactorizationMonoid β :=
⟨e.uniqueFactorizationMonoid, e.symm.uniqueFactorizationMonoid⟩
#align mul_equiv.unique_factorization_monoid_iff MulEquiv.uniqueFactorizationMonoid_iff
end
theorem irreducible_iff_prime_of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g)
(p : α) : Irreducible p ↔ Prime p :=
letI := Classical.decEq α
⟨ fun hpi =>
⟨hpi.ne_zero, hpi.1, fun a b ⟨x, hx⟩ =>
if hab0 : a * b = 0 then
(eq_zero_or_eq_zero_of_mul_eq_zero hab0).elim (fun ha0 => by simp [ha0]) fun hb0 => by
simp [hb0]
else by
have hx0 : x ≠ 0 := fun hx0 => by simp_all
have ha0 : a ≠ 0 := left_ne_zero_of_mul hab0
have hb0 : b ≠ 0 := right_ne_zero_of_mul hab0
cases' eif x hx0 with fx hfx
cases' eif a ha0 with fa hfa
cases' eif b hb0 with fb hfb
have h : Multiset.Rel Associated (p ::ₘ fx) (fa + fb) := by
apply uif
· exact fun i hi => (Multiset.mem_cons.1 hi).elim (fun hip => hip.symm ▸ hpi) (hfx.1 _)
· exact fun i hi => (Multiset.mem_add.1 hi).elim (hfa.1 _) (hfb.1 _)
calc
Multiset.prod (p ::ₘ fx) ~ᵤ a * b := by
rw [hx, Multiset.prod_cons]; exact hfx.2.mul_left _
_ ~ᵤ fa.prod * fb.prod := hfa.2.symm.mul_mul hfb.2.symm
_ = _ := by rw [Multiset.prod_add]
exact
let ⟨q, hqf, hq⟩ := Multiset.exists_mem_of_rel_of_mem h (Multiset.mem_cons_self p _)
(Multiset.mem_add.1 hqf).elim
(fun hqa =>
Or.inl <| hq.dvd_iff_dvd_left.2 <| hfa.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqa))
fun hqb =>
Or.inr <| hq.dvd_iff_dvd_left.2 <| hfb.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqb)⟩,
Prime.irreducible⟩
#align irreducible_iff_prime_of_exists_unique_irreducible_factors irreducible_iff_prime_of_exists_unique_irreducible_factors
theorem UniqueFactorizationMonoid.of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g) :
UniqueFactorizationMonoid α :=
UniqueFactorizationMonoid.of_exists_prime_factors
(by
convert eif using 7
simp_rw [irreducible_iff_prime_of_exists_unique_irreducible_factors eif uif])
#align unique_factorization_monoid.of_exists_unique_irreducible_factors UniqueFactorizationMonoid.of_exists_unique_irreducible_factors
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α]
variable [UniqueFactorizationMonoid α]
open Classical in
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def factors (a : α) : Multiset α :=
if h : a = 0 then 0 else Classical.choose (UniqueFactorizationMonoid.exists_prime_factors a h)
#align unique_factorization_monoid.factors UniqueFactorizationMonoid.factors
theorem factors_prod {a : α} (ane0 : a ≠ 0) : Associated (factors a).prod a := by
rw [factors, dif_neg ane0]
exact (Classical.choose_spec (exists_prime_factors a ane0)).2
#align unique_factorization_monoid.factors_prod UniqueFactorizationMonoid.factors_prod
@[simp]
theorem factors_zero : factors (0 : α) = 0 := by simp [factors]
#align unique_factorization_monoid.factors_zero UniqueFactorizationMonoid.factors_zero
theorem ne_zero_of_mem_factors {p a : α} (h : p ∈ factors a) : a ≠ 0 := by
rintro rfl
simp at h
#align unique_factorization_monoid.ne_zero_of_mem_factors UniqueFactorizationMonoid.ne_zero_of_mem_factors
theorem dvd_of_mem_factors {p a : α} (h : p ∈ factors a) : p ∣ a :=
dvd_trans (Multiset.dvd_prod h) (Associated.dvd (factors_prod (ne_zero_of_mem_factors h)))
#align unique_factorization_monoid.dvd_of_mem_factors UniqueFactorizationMonoid.dvd_of_mem_factors
theorem prime_of_factor {a : α} (x : α) (hx : x ∈ factors a) : Prime x := by
have ane0 := ne_zero_of_mem_factors hx
rw [factors, dif_neg ane0] at hx
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 x hx
#align unique_factorization_monoid.prime_of_factor UniqueFactorizationMonoid.prime_of_factor
theorem irreducible_of_factor {a : α} : ∀ x : α, x ∈ factors a → Irreducible x := fun x h =>
(prime_of_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_factor UniqueFactorizationMonoid.irreducible_of_factor
@[simp]
theorem factors_one : factors (1 : α) = 0 := by
nontriviality α using factors
rw [← Multiset.rel_zero_right]
refine factors_unique irreducible_of_factor (fun x hx => (Multiset.not_mem_zero x hx).elim) ?_
rw [Multiset.prod_zero]
exact factors_prod one_ne_zero
#align unique_factorization_monoid.factors_one UniqueFactorizationMonoid.factors_one
theorem exists_mem_factors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ factors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ factors b) (factors a) :=
factors_unique
(fun x hx => (Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_factor _))
irreducible_of_factor
(Associated.symm <|
calc
Multiset.prod (factors a) ~ᵤ a := factors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ factors b) := by
rw [Multiset.prod_cons]; exact (factors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_factors_of_dvd UniqueFactorizationMonoid.exists_mem_factors_of_dvd
theorem exists_mem_factors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) : ∃ p, p ∈ factors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_factors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_factors UniqueFactorizationMonoid.exists_mem_factors
open Classical in
theorem factors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
Multiset.Rel Associated (factors (x * y)) (factors x + factors y) := by
refine
factors_unique irreducible_of_factor
(fun a ha =>
(Multiset.mem_add.mp ha).by_cases (irreducible_of_factor _) (irreducible_of_factor _))
((factors_prod (mul_ne_zero hx hy)).trans ?_)
rw [Multiset.prod_add]
exact (Associated.mul_mul (factors_prod hx) (factors_prod hy)).symm
#align unique_factorization_monoid.factors_mul UniqueFactorizationMonoid.factors_mul
theorem factors_pow {x : α} (n : ℕ) :
Multiset.Rel Associated (factors (x ^ n)) (n • factors x) := by
match n with
| 0 => rw [zero_smul, pow_zero, factors_one, Multiset.rel_zero_right]
| n+1 =>
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
· rw [pow_succ', succ_nsmul']
refine Multiset.Rel.trans _ (factors_mul h0 (pow_ne_zero n h0)) ?_
refine Multiset.Rel.add ?_ <| factors_pow n
exact Multiset.rel_refl_of_refl_on fun y _ => Associated.refl _
#align unique_factorization_monoid.factors_pow UniqueFactorizationMonoid.factors_pow
@[simp]
theorem factors_pos (x : α) (hx : x ≠ 0) : 0 < factors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact (prime_of_factor _ hp).not_unit (isUnit_of_dvd_unit (dvd_of_mem_factors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_factors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.factors_pos UniqueFactorizationMonoid.factors_pos
open Multiset in
theorem factors_pow_count_prod [DecidableEq α] {x : α} (hx : x ≠ 0) :
(∏ p ∈ (factors x).toFinset, p ^ (factors x).count p) ~ᵤ x :=
calc
_ = prod (∑ a ∈ toFinset (factors x), count a (factors x) • {a}) := by
simp only [prod_sum, prod_nsmul, prod_singleton]
_ = prod (factors x) := by rw [toFinset_sum_count_nsmul_eq (factors x)]
_ ~ᵤ x := factors_prod hx
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [NormalizationMonoid α]
variable [UniqueFactorizationMonoid α]
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def normalizedFactors (a : α) : Multiset α :=
Multiset.map normalize <| factors a
#align unique_factorization_monoid.normalized_factors UniqueFactorizationMonoid.normalizedFactors
/-- An arbitrary choice of factors of `x : M` is exactly the (unique) normalized set of factors,
if `M` has a trivial group of units. -/
@[simp]
theorem factors_eq_normalizedFactors {M : Type*} [CancelCommMonoidWithZero M]
[UniqueFactorizationMonoid M] [Unique Mˣ] (x : M) : factors x = normalizedFactors x := by
unfold normalizedFactors
convert (Multiset.map_id (factors x)).symm
ext p
exact normalize_eq p
#align unique_factorization_monoid.factors_eq_normalized_factors UniqueFactorizationMonoid.factors_eq_normalizedFactors
theorem normalizedFactors_prod {a : α} (ane0 : a ≠ 0) :
Associated (normalizedFactors a).prod a := by
rw [normalizedFactors, factors, dif_neg ane0]
refine Associated.trans ?_ (Classical.choose_spec (exists_prime_factors a ane0)).2
rw [← Associates.mk_eq_mk_iff_associated, ← Associates.prod_mk, ← Associates.prod_mk,
Multiset.map_map]
congr 2
ext
rw [Function.comp_apply, Associates.mk_normalize]
#align unique_factorization_monoid.normalized_factors_prod UniqueFactorizationMonoid.normalizedFactors_prod
theorem prime_of_normalized_factor {a : α} : ∀ x : α, x ∈ normalizedFactors a → Prime x := by
rw [normalizedFactors, factors]
split_ifs with ane0; · simp
intro x hx; rcases Multiset.mem_map.1 hx with ⟨y, ⟨hy, rfl⟩⟩
rw [(normalize_associated _).prime_iff]
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 y hy
#align unique_factorization_monoid.prime_of_normalized_factor UniqueFactorizationMonoid.prime_of_normalized_factor
theorem irreducible_of_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → Irreducible x := fun x h =>
(prime_of_normalized_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_normalized_factor UniqueFactorizationMonoid.irreducible_of_normalized_factor
theorem normalize_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → normalize x = x := by
rw [normalizedFactors, factors]
split_ifs with h; · simp
intro x hx
obtain ⟨y, _, rfl⟩ := Multiset.mem_map.1 hx
apply normalize_idem
#align unique_factorization_monoid.normalize_normalized_factor UniqueFactorizationMonoid.normalize_normalized_factor
theorem normalizedFactors_irreducible {a : α} (ha : Irreducible a) :
normalizedFactors a = {normalize a} := by
obtain ⟨p, a_assoc, hp⟩ :=
prime_factors_irreducible ha ⟨prime_of_normalized_factor, normalizedFactors_prod ha.ne_zero⟩
have p_mem : p ∈ normalizedFactors a := by
rw [hp]
exact Multiset.mem_singleton_self _
convert hp
rwa [← normalize_normalized_factor p p_mem, normalize_eq_normalize_iff, dvd_dvd_iff_associated]
#align unique_factorization_monoid.normalized_factors_irreducible UniqueFactorizationMonoid.normalizedFactors_irreducible
theorem normalizedFactors_eq_of_dvd (a : α) :
∀ᵉ (p ∈ normalizedFactors a) (q ∈ normalizedFactors a), p ∣ q → p = q := by
intro p hp q hq hdvd
convert normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd) <;>
apply (normalize_normalized_factor _ ‹_›).symm
#align unique_factorization_monoid.normalized_factors_eq_of_dvd UniqueFactorizationMonoid.normalizedFactors_eq_of_dvd
theorem exists_mem_normalizedFactors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ normalizedFactors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ normalizedFactors b) (normalizedFactors a) :=
factors_unique
(fun x hx =>
(Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_normalized_factor _))
irreducible_of_normalized_factor
(Associated.symm <|
calc
Multiset.prod (normalizedFactors a) ~ᵤ a := normalizedFactors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ normalizedFactors b) := by
rw [Multiset.prod_cons]
exact (normalizedFactors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_normalized_factors_of_dvd UniqueFactorizationMonoid.exists_mem_normalizedFactors_of_dvd
theorem exists_mem_normalizedFactors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) :
∃ p, p ∈ normalizedFactors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_normalizedFactors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_normalized_factors UniqueFactorizationMonoid.exists_mem_normalizedFactors
@[simp]
theorem normalizedFactors_zero : normalizedFactors (0 : α) = 0 := by
simp [normalizedFactors, factors]
#align unique_factorization_monoid.normalized_factors_zero UniqueFactorizationMonoid.normalizedFactors_zero
@[simp]
theorem normalizedFactors_one : normalizedFactors (1 : α) = 0 := by
cases' subsingleton_or_nontrivial α with h h
· dsimp [normalizedFactors, factors]
simp [Subsingleton.elim (1:α) 0]
· rw [← Multiset.rel_zero_right]
apply factors_unique irreducible_of_normalized_factor
· intro x hx
exfalso
apply Multiset.not_mem_zero x hx
· apply normalizedFactors_prod one_ne_zero
#align unique_factorization_monoid.normalized_factors_one UniqueFactorizationMonoid.normalizedFactors_one
@[simp]
theorem normalizedFactors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
normalizedFactors (x * y) = normalizedFactors x + normalizedFactors y := by
have h : (normalize : α → α) = Associates.out ∘ Associates.mk := by
ext
rw [Function.comp_apply, Associates.out_mk]
rw [← Multiset.map_id' (normalizedFactors (x * y)), ← Multiset.map_id' (normalizedFactors x), ←
Multiset.map_id' (normalizedFactors y), ← Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ← Multiset.map_add, h, ←
Multiset.map_map Associates.out, eq_comm, ← Multiset.map_map Associates.out]
refine congr rfl ?_
apply Multiset.map_mk_eq_map_mk_of_rel
apply factors_unique
· intro x hx
rcases Multiset.mem_add.1 hx with (hx | hx) <;> exact irreducible_of_normalized_factor x hx
· exact irreducible_of_normalized_factor
· rw [Multiset.prod_add]
exact
((normalizedFactors_prod hx).mul_mul (normalizedFactors_prod hy)).trans
(normalizedFactors_prod (mul_ne_zero hx hy)).symm
#align unique_factorization_monoid.normalized_factors_mul UniqueFactorizationMonoid.normalizedFactors_mul
@[simp]
theorem normalizedFactors_pow {x : α} (n : ℕ) :
normalizedFactors (x ^ n) = n • normalizedFactors x := by
induction' n with n ih
· simp
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
rw [pow_succ', succ_nsmul', normalizedFactors_mul h0 (pow_ne_zero _ h0), ih]
#align unique_factorization_monoid.normalized_factors_pow UniqueFactorizationMonoid.normalizedFactors_pow
theorem _root_.Irreducible.normalizedFactors_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [UniqueFactorizationMonoid.normalizedFactors_pow, normalizedFactors_irreducible hp,
Multiset.nsmul_singleton]
#align irreducible.normalized_factors_pow Irreducible.normalizedFactors_pow
theorem normalizedFactors_prod_eq (s : Multiset α) (hs : ∀ a ∈ s, Irreducible a) :
normalizedFactors s.prod = s.map normalize := by
induction' s using Multiset.induction with a s ih
· rw [Multiset.prod_zero, normalizedFactors_one, Multiset.map_zero]
· have ia := hs a (Multiset.mem_cons_self a _)
have ib := fun b h => hs b (Multiset.mem_cons_of_mem h)
obtain rfl | ⟨b, hb⟩ := s.empty_or_exists_mem
· rw [Multiset.cons_zero, Multiset.prod_singleton, Multiset.map_singleton,
normalizedFactors_irreducible ia]
haveI := nontrivial_of_ne b 0 (ib b hb).ne_zero
rw [Multiset.prod_cons, Multiset.map_cons,
normalizedFactors_mul ia.ne_zero (Multiset.prod_ne_zero fun h => (ib 0 h).ne_zero rfl),
normalizedFactors_irreducible ia, ih ib, Multiset.singleton_add]
#align unique_factorization_monoid.normalized_factors_prod_eq UniqueFactorizationMonoid.normalizedFactors_prod_eq
theorem dvd_iff_normalizedFactors_le_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ∣ y ↔ normalizedFactors x ≤ normalizedFactors y := by
constructor
· rintro ⟨c, rfl⟩
simp [hx, right_ne_zero_of_mul hy]
· rw [← (normalizedFactors_prod hx).dvd_iff_dvd_left, ←
(normalizedFactors_prod hy).dvd_iff_dvd_right]
apply Multiset.prod_dvd_prod_of_le
#align unique_factorization_monoid.dvd_iff_normalized_factors_le_normalized_factors UniqueFactorizationMonoid.dvd_iff_normalizedFactors_le_normalizedFactors
theorem associated_iff_normalizedFactors_eq_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ~ᵤ y ↔ normalizedFactors x = normalizedFactors y := by
refine
⟨fun h => ?_, fun h =>
(normalizedFactors_prod hx).symm.trans (_root_.trans (by rw [h]) (normalizedFactors_prod hy))⟩
apply le_antisymm <;> rw [← dvd_iff_normalizedFactors_le_normalizedFactors]
all_goals simp [*, h.dvd, h.symm.dvd]
#align unique_factorization_monoid.associated_iff_normalized_factors_eq_normalized_factors UniqueFactorizationMonoid.associated_iff_normalizedFactors_eq_normalizedFactors
theorem normalizedFactors_of_irreducible_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [normalizedFactors_pow, normalizedFactors_irreducible hp, Multiset.nsmul_singleton]
#align unique_factorization_monoid.normalized_factors_of_irreducible_pow UniqueFactorizationMonoid.normalizedFactors_of_irreducible_pow
theorem zero_not_mem_normalizedFactors (x : α) : (0 : α) ∉ normalizedFactors x := fun h =>
Prime.ne_zero (prime_of_normalized_factor _ h) rfl
#align unique_factorization_monoid.zero_not_mem_normalized_factors UniqueFactorizationMonoid.zero_not_mem_normalizedFactors
theorem dvd_of_mem_normalizedFactors {a p : α} (H : p ∈ normalizedFactors a) : p ∣ a := by
by_cases hcases : a = 0
· rw [hcases]
exact dvd_zero p
· exact dvd_trans (Multiset.dvd_prod H) (Associated.dvd (normalizedFactors_prod hcases))
#align unique_factorization_monoid.dvd_of_mem_normalized_factors UniqueFactorizationMonoid.dvd_of_mem_normalizedFactors
theorem mem_normalizedFactors_iff [Unique αˣ] {p x : α} (hx : x ≠ 0) :
p ∈ normalizedFactors x ↔ Prime p ∧ p ∣ x := by
constructor
· intro h
exact ⟨prime_of_normalized_factor p h, dvd_of_mem_normalizedFactors h⟩
· rintro ⟨hprime, hdvd⟩
obtain ⟨q, hqmem, hqeq⟩ := exists_mem_normalizedFactors_of_dvd hx hprime.irreducible hdvd
rw [associated_iff_eq] at hqeq
exact hqeq ▸ hqmem
| Mathlib/RingTheory/UniqueFactorizationDomain.lean | 798 | 802 | theorem exists_associated_prime_pow_of_unique_normalized_factor {p r : α}
(h : ∀ {m}, m ∈ normalizedFactors r → m = p) (hr : r ≠ 0) : ∃ i : ℕ, Associated (p ^ i) r := by |
use Multiset.card.toFun (normalizedFactors r)
have := UniqueFactorizationMonoid.normalizedFactors_prod hr
rwa [Multiset.eq_replicate_of_mem fun b => h, Multiset.prod_replicate] at this
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.MeasureTheory.OuterMeasure.Operations
import Mathlib.Analysis.SpecificLimits.Basic
/-!
# Outer measures from functions
Given an arbitrary function `m : Set α → ℝ≥0∞` that sends `∅` to `0` we can define an outer
measure on `α` that on `s` is defined to be the infimum of `∑ᵢ, m (sᵢ)` for all collections of sets
`sᵢ` that cover `s`. This is the unique maximal outer measure that is at most the given function.
Given an outer measure `m`, the Carathéodory-measurable sets are the sets `s` such that
for all sets `t` we have `m t = m (t ∩ s) + m (t \ s)`. This forms a measurable space.
## Main definitions and statements
* `OuterMeasure.boundedBy` is the greatest outer measure that is at most the given function.
If you know that the given function sends `∅` to `0`, then `OuterMeasure.ofFunction` is a
special case.
* `sInf_eq_boundedBy_sInfGen` is a characterization of the infimum of outer measures.
## References
* <https://en.wikipedia.org/wiki/Outer_measure>
* <https://en.wikipedia.org/wiki/Carath%C3%A9odory%27s_criterion>
## Tags
outer measure, Carathéodory-measurable, Carathéodory's criterion
-/
#align_import measure_theory.measure.outer_measure from "leanprover-community/mathlib"@"343e80208d29d2d15f8050b929aa50fe4ce71b55"
noncomputable section
open Set Function Filter
open scoped Classical NNReal Topology ENNReal
namespace MeasureTheory
namespace OuterMeasure
section OfFunction
-- Porting note: "set_option eqn_compiler.zeta true" removed
variable {α : Type*} (m : Set α → ℝ≥0∞) (m_empty : m ∅ = 0)
/-- Given any function `m` assigning measures to sets satisying `m ∅ = 0`, there is
a unique maximal outer measure `μ` satisfying `μ s ≤ m s` for all `s : Set α`. -/
protected def ofFunction : OuterMeasure α :=
let μ s := ⨅ (f : ℕ → Set α) (_ : s ⊆ ⋃ i, f i), ∑' i, m (f i)
{ measureOf := μ
empty :=
le_antisymm
((iInf_le_of_le fun _ => ∅) <| iInf_le_of_le (empty_subset _) <| by simp [m_empty])
(zero_le _)
mono := fun {s₁ s₂} hs => iInf_mono fun f => iInf_mono' fun hb => ⟨hs.trans hb, le_rfl⟩
iUnion_nat := fun s _ =>
ENNReal.le_of_forall_pos_le_add <| by
intro ε hε (hb : (∑' i, μ (s i)) < ∞)
rcases ENNReal.exists_pos_sum_of_countable (ENNReal.coe_pos.2 hε).ne' ℕ with ⟨ε', hε', hl⟩
refine le_trans ?_ (add_le_add_left (le_of_lt hl) _)
rw [← ENNReal.tsum_add]
choose f hf using
show ∀ i, ∃ f : ℕ → Set α, (s i ⊆ ⋃ i, f i) ∧ (∑' i, m (f i)) < μ (s i) + ε' i by
intro i
have : μ (s i) < μ (s i) + ε' i :=
ENNReal.lt_add_right (ne_top_of_le_ne_top hb.ne <| ENNReal.le_tsum _)
(by simpa using (hε' i).ne')
rcases iInf_lt_iff.mp this with ⟨t, ht⟩
exists t
contrapose! ht
exact le_iInf ht
refine le_trans ?_ (ENNReal.tsum_le_tsum fun i => le_of_lt (hf i).2)
rw [← ENNReal.tsum_prod, ← Nat.pairEquiv.symm.tsum_eq]
refine iInf_le_of_le _ (iInf_le _ ?_)
apply iUnion_subset
intro i
apply Subset.trans (hf i).1
apply iUnion_subset
simp only [Nat.pairEquiv_symm_apply]
rw [iUnion_unpair]
intro j
apply subset_iUnion₂ i }
#align measure_theory.outer_measure.of_function MeasureTheory.OuterMeasure.ofFunction
theorem ofFunction_apply (s : Set α) :
OuterMeasure.ofFunction m m_empty s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, m (t n) :=
rfl
#align measure_theory.outer_measure.of_function_apply MeasureTheory.OuterMeasure.ofFunction_apply
variable {m m_empty}
theorem ofFunction_le (s : Set α) : OuterMeasure.ofFunction m m_empty s ≤ m s :=
let f : ℕ → Set α := fun i => Nat.casesOn i s fun _ => ∅
iInf_le_of_le f <|
iInf_le_of_le (subset_iUnion f 0) <|
le_of_eq <| tsum_eq_single 0 <| by
rintro (_ | i)
· simp
· simp [m_empty]
#align measure_theory.outer_measure.of_function_le MeasureTheory.OuterMeasure.ofFunction_le
theorem ofFunction_eq (s : Set α) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) :
OuterMeasure.ofFunction m m_empty s = m s :=
le_antisymm (ofFunction_le s) <|
le_iInf fun f => le_iInf fun hf => le_trans (m_mono hf) (m_subadd f)
#align measure_theory.outer_measure.of_function_eq MeasureTheory.OuterMeasure.ofFunction_eq
theorem le_ofFunction {μ : OuterMeasure α} :
μ ≤ OuterMeasure.ofFunction m m_empty ↔ ∀ s, μ s ≤ m s :=
⟨fun H s => le_trans (H s) (ofFunction_le s), fun H _ =>
le_iInf fun f =>
le_iInf fun hs =>
le_trans (μ.mono hs) <| le_trans (measure_iUnion_le f) <| ENNReal.tsum_le_tsum fun _ => H _⟩
#align measure_theory.outer_measure.le_of_function MeasureTheory.OuterMeasure.le_ofFunction
theorem isGreatest_ofFunction :
IsGreatest { μ : OuterMeasure α | ∀ s, μ s ≤ m s } (OuterMeasure.ofFunction m m_empty) :=
⟨fun _ => ofFunction_le _, fun _ => le_ofFunction.2⟩
#align measure_theory.outer_measure.is_greatest_of_function MeasureTheory.OuterMeasure.isGreatest_ofFunction
theorem ofFunction_eq_sSup : OuterMeasure.ofFunction m m_empty = sSup { μ | ∀ s, μ s ≤ m s } :=
(@isGreatest_ofFunction α m m_empty).isLUB.sSup_eq.symm
#align measure_theory.outer_measure.of_function_eq_Sup MeasureTheory.OuterMeasure.ofFunction_eq_sSup
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.ofFunction m m_empty`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem ofFunction_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
OuterMeasure.ofFunction m m_empty (s ∪ t) =
OuterMeasure.ofFunction m m_empty s + OuterMeasure.ofFunction m m_empty t := by
refine le_antisymm (measure_union_le _ _) (le_iInf₂ fun f hf ↦ ?_)
set μ := OuterMeasure.ofFunction m m_empty
rcases Classical.em (∃ i, (s ∩ f i).Nonempty ∧ (t ∩ f i).Nonempty) with (⟨i, hs, ht⟩ | he)
· calc
μ s + μ t ≤ ∞ := le_top
_ = m (f i) := (h (f i) hs ht).symm
_ ≤ ∑' i, m (f i) := ENNReal.le_tsum i
set I := fun s => { i : ℕ | (s ∩ f i).Nonempty }
have hd : Disjoint (I s) (I t) := disjoint_iff_inf_le.mpr fun i hi => he ⟨i, hi⟩
have hI : ∀ u ⊆ s ∪ t, μ u ≤ ∑' i : I u, μ (f i) := fun u hu =>
calc
μ u ≤ μ (⋃ i : I u, f i) :=
μ.mono fun x hx =>
let ⟨i, hi⟩ := mem_iUnion.1 (hf (hu hx))
mem_iUnion.2 ⟨⟨i, ⟨x, hx, hi⟩⟩, hi⟩
_ ≤ ∑' i : I u, μ (f i) := measure_iUnion_le _
calc
μ s + μ t ≤ (∑' i : I s, μ (f i)) + ∑' i : I t, μ (f i) :=
add_le_add (hI _ subset_union_left) (hI _ subset_union_right)
_ = ∑' i : ↑(I s ∪ I t), μ (f i) :=
(tsum_union_disjoint (f := fun i => μ (f i)) hd ENNReal.summable ENNReal.summable).symm
_ ≤ ∑' i, μ (f i) :=
(tsum_le_tsum_of_inj (↑) Subtype.coe_injective (fun _ _ => zero_le _) (fun _ => le_rfl)
ENNReal.summable ENNReal.summable)
_ ≤ ∑' i, m (f i) := ENNReal.tsum_le_tsum fun i => ofFunction_le _
#align measure_theory.outer_measure.of_function_union_of_top_of_nonempty_inter MeasureTheory.OuterMeasure.ofFunction_union_of_top_of_nonempty_inter
theorem comap_ofFunction {β} (f : β → α) (h : Monotone m ∨ Surjective f) :
comap f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f '' s)) (by simp; simp [m_empty]) := by
refine le_antisymm (le_ofFunction.2 fun s => ?_) fun s => ?_
· rw [comap_apply]
apply ofFunction_le
· rw [comap_apply, ofFunction_apply, ofFunction_apply]
refine iInf_mono' fun t => ⟨fun k => f ⁻¹' t k, ?_⟩
refine iInf_mono' fun ht => ?_
rw [Set.image_subset_iff, preimage_iUnion] at ht
refine ⟨ht, ENNReal.tsum_le_tsum fun n => ?_⟩
cases' h with hl hr
exacts [hl (image_preimage_subset _ _), (congr_arg m (hr.image_preimage (t n))).le]
#align measure_theory.outer_measure.comap_of_function MeasureTheory.OuterMeasure.comap_ofFunction
theorem map_ofFunction_le {β} (f : α → β) :
map f (OuterMeasure.ofFunction m m_empty) ≤
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty :=
le_ofFunction.2 fun s => by
rw [map_apply]
apply ofFunction_le
#align measure_theory.outer_measure.map_of_function_le MeasureTheory.OuterMeasure.map_ofFunction_le
theorem map_ofFunction {β} {f : α → β} (hf : Injective f) :
map f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty := by
refine (map_ofFunction_le _).antisymm fun s => ?_
simp only [ofFunction_apply, map_apply, le_iInf_iff]
intro t ht
refine iInf_le_of_le (fun n => (range f)ᶜ ∪ f '' t n) (iInf_le_of_le ?_ ?_)
· rw [← union_iUnion, ← inter_subset, ← image_preimage_eq_inter_range, ← image_iUnion]
exact image_subset _ ht
· refine ENNReal.tsum_le_tsum fun n => le_of_eq ?_
simp [hf.preimage_image]
#align measure_theory.outer_measure.map_of_function MeasureTheory.OuterMeasure.map_ofFunction
-- TODO (kmill): change `m (t ∩ s)` to `m (s ∩ t)`
theorem restrict_ofFunction (s : Set α) (hm : Monotone m) :
restrict s (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun t => m (t ∩ s)) (by simp; simp [m_empty]) := by
rw [restrict]
simp only [inter_comm _ s, LinearMap.comp_apply]
rw [comap_ofFunction _ (Or.inl hm)]
simp only [map_ofFunction Subtype.coe_injective, Subtype.image_preimage_coe]
#align measure_theory.outer_measure.restrict_of_function MeasureTheory.OuterMeasure.restrict_ofFunction
theorem smul_ofFunction {c : ℝ≥0∞} (hc : c ≠ ∞) : c • OuterMeasure.ofFunction m m_empty =
OuterMeasure.ofFunction (c • m) (by simp [m_empty]) := by
ext1 s
haveI : Nonempty { t : ℕ → Set α // s ⊆ ⋃ i, t i } := ⟨⟨fun _ => s, subset_iUnion (fun _ => s) 0⟩⟩
simp only [smul_apply, ofFunction_apply, ENNReal.tsum_mul_left, Pi.smul_apply, smul_eq_mul,
iInf_subtype']
rw [ENNReal.iInf_mul_left fun h => (hc h).elim]
#align measure_theory.outer_measure.smul_of_function MeasureTheory.OuterMeasure.smul_ofFunction
end OfFunction
section BoundedBy
variable {α : Type*} (m : Set α → ℝ≥0∞)
/-- Given any function `m` assigning measures to sets, there is a unique maximal outer measure `μ`
satisfying `μ s ≤ m s` for all `s : Set α`. This is the same as `OuterMeasure.ofFunction`,
except that it doesn't require `m ∅ = 0`. -/
def boundedBy : OuterMeasure α :=
OuterMeasure.ofFunction (fun s => ⨆ _ : s.Nonempty, m s) (by simp [Set.not_nonempty_empty])
#align measure_theory.outer_measure.bounded_by MeasureTheory.OuterMeasure.boundedBy
variable {m}
theorem boundedBy_le (s : Set α) : boundedBy m s ≤ m s :=
(ofFunction_le _).trans iSup_const_le
#align measure_theory.outer_measure.bounded_by_le MeasureTheory.OuterMeasure.boundedBy_le
theorem boundedBy_eq_ofFunction (m_empty : m ∅ = 0) (s : Set α) :
boundedBy m s = OuterMeasure.ofFunction m m_empty s := by
have : (fun s : Set α => ⨆ _ : s.Nonempty, m s) = m := by
ext1 t
rcases t.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty, m_empty]
simp [boundedBy, this]
#align measure_theory.outer_measure.bounded_by_eq_of_function MeasureTheory.OuterMeasure.boundedBy_eq_ofFunction
theorem boundedBy_apply (s : Set α) :
boundedBy m s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t),
∑' n, ⨆ _ : (t n).Nonempty, m (t n) := by
simp [boundedBy, ofFunction_apply]
#align measure_theory.outer_measure.bounded_by_apply MeasureTheory.OuterMeasure.boundedBy_apply
theorem boundedBy_eq (s : Set α) (m_empty : m ∅ = 0) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) : boundedBy m s = m s := by
rw [boundedBy_eq_ofFunction m_empty, ofFunction_eq s m_mono m_subadd]
#align measure_theory.outer_measure.bounded_by_eq MeasureTheory.OuterMeasure.boundedBy_eq
@[simp]
theorem boundedBy_eq_self (m : OuterMeasure α) : boundedBy m = m :=
ext fun _ => boundedBy_eq _ measure_empty (fun _ ht => measure_mono ht) measure_iUnion_le
#align measure_theory.outer_measure.bounded_by_eq_self MeasureTheory.OuterMeasure.boundedBy_eq_self
theorem le_boundedBy {μ : OuterMeasure α} : μ ≤ boundedBy m ↔ ∀ s, μ s ≤ m s := by
rw [boundedBy , le_ofFunction, forall_congr']; intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty]
#align measure_theory.outer_measure.le_bounded_by MeasureTheory.OuterMeasure.le_boundedBy
theorem le_boundedBy' {μ : OuterMeasure α} :
μ ≤ boundedBy m ↔ ∀ s : Set α, s.Nonempty → μ s ≤ m s := by
rw [le_boundedBy, forall_congr']
intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h]
#align measure_theory.outer_measure.le_bounded_by' MeasureTheory.OuterMeasure.le_boundedBy'
@[simp]
theorem boundedBy_top : boundedBy (⊤ : Set α → ℝ≥0∞) = ⊤ := by
rw [eq_top_iff, le_boundedBy']
intro s hs
rw [top_apply hs]
exact le_rfl
#align measure_theory.outer_measure.bounded_by_top MeasureTheory.OuterMeasure.boundedBy_top
@[simp]
theorem boundedBy_zero : boundedBy (0 : Set α → ℝ≥0∞) = 0 := by
rw [← coe_bot, eq_bot_iff]
apply boundedBy_le
#align measure_theory.outer_measure.bounded_by_zero MeasureTheory.OuterMeasure.boundedBy_zero
theorem smul_boundedBy {c : ℝ≥0∞} (hc : c ≠ ∞) : c • boundedBy m = boundedBy (c • m) := by
simp only [boundedBy , smul_ofFunction hc]
congr 1 with s : 1
rcases s.eq_empty_or_nonempty with (rfl | hs) <;> simp [*]
#align measure_theory.outer_measure.smul_bounded_by MeasureTheory.OuterMeasure.smul_boundedBy
theorem comap_boundedBy {β} (f : β → α)
(h : (Monotone fun s : { s : Set α // s.Nonempty } => m s) ∨ Surjective f) :
comap f (boundedBy m) = boundedBy fun s => m (f '' s) := by
refine (comap_ofFunction _ ?_).trans ?_
· refine h.imp (fun H s t hst => iSup_le fun hs => ?_) id
have ht : t.Nonempty := hs.mono hst
exact (@H ⟨s, hs⟩ ⟨t, ht⟩ hst).trans (le_iSup (fun _ : t.Nonempty => m t) ht)
· dsimp only [boundedBy]
congr with s : 1
rw [image_nonempty]
#align measure_theory.outer_measure.comap_bounded_by MeasureTheory.OuterMeasure.comap_boundedBy
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.boundedBy m`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem boundedBy_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
boundedBy m (s ∪ t) = boundedBy m s + boundedBy m t :=
ofFunction_union_of_top_of_nonempty_inter fun u hs ht =>
top_unique <| (h u hs ht).ge.trans <| le_iSup (fun _ => m u) (hs.mono inter_subset_right)
#align measure_theory.outer_measure.bounded_by_union_of_top_of_nonempty_inter MeasureTheory.OuterMeasure.boundedBy_union_of_top_of_nonempty_inter
end BoundedBy
section sInfGen
variable {α : Type*}
/-- Given a set of outer measures, we define a new function that on a set `s` is defined to be the
infimum of `μ(s)` for the outer measures `μ` in the collection. We ensure that this
function is defined to be `0` on `∅`, even if the collection of outer measures is empty.
The outer measure generated by this function is the infimum of the given outer measures. -/
def sInfGen (m : Set (OuterMeasure α)) (s : Set α) : ℝ≥0∞ :=
⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ s
#align measure_theory.outer_measure.Inf_gen MeasureTheory.OuterMeasure.sInfGen
theorem sInfGen_def (m : Set (OuterMeasure α)) (t : Set α) :
sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t :=
rfl
#align measure_theory.outer_measure.Inf_gen_def MeasureTheory.OuterMeasure.sInfGen_def
theorem sInf_eq_boundedBy_sInfGen (m : Set (OuterMeasure α)) :
sInf m = OuterMeasure.boundedBy (sInfGen m) := by
refine le_antisymm ?_ ?_
· refine le_boundedBy.2 fun s => le_iInf₂ fun μ hμ => ?_
apply sInf_le hμ
· refine le_sInf ?_
intro μ hμ t
exact le_trans (boundedBy_le t) (iInf₂_le μ hμ)
#align measure_theory.outer_measure.Inf_eq_bounded_by_Inf_gen MeasureTheory.OuterMeasure.sInf_eq_boundedBy_sInfGen
theorem iSup_sInfGen_nonempty {m : Set (OuterMeasure α)} (h : m.Nonempty) (t : Set α) :
⨆ _ : t.Nonempty, sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t := by
rcases t.eq_empty_or_nonempty with (rfl | ht)
· simp [biInf_const h]
· simp [ht, sInfGen_def]
#align measure_theory.outer_measure.supr_Inf_gen_nonempty MeasureTheory.OuterMeasure.iSup_sInfGen_nonempty
/-- The value of the Infimum of a nonempty set of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply {m : Set (OuterMeasure α)} {s : Set α} (h : m.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) := by
simp_rw [sInf_eq_boundedBy_sInfGen, boundedBy_apply, iSup_sInfGen_nonempty h]
#align measure_theory.outer_measure.Inf_apply MeasureTheory.OuterMeasure.sInf_apply
/-- The value of the Infimum of a set of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply' {m : Set (OuterMeasure α)} {s : Set α} (h : s.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) :=
m.eq_empty_or_nonempty.elim (fun hm => by simp [hm, h]) sInf_apply
#align measure_theory.outer_measure.Inf_apply' MeasureTheory.OuterMeasure.sInf_apply'
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply {ι} [Nonempty ι] (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply (range_nonempty m)]
simp only [iInf_range]
#align measure_theory.outer_measure.infi_apply MeasureTheory.OuterMeasure.iInf_apply
/-- The value of the Infimum of a family of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply' {ι} (m : ι → OuterMeasure α) {s : Set α} (hs : s.Nonempty) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply' hs]
simp only [iInf_range]
#align measure_theory.outer_measure.infi_apply' MeasureTheory.OuterMeasure.iInf_apply'
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem biInf_apply {ι} {I : Set ι} (hI : I.Nonempty) (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i ∈ I, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i ∈ I, m i (t n) := by
haveI := hI.to_subtype
simp only [← iInf_subtype'', iInf_apply]
#align measure_theory.outer_measure.binfi_apply MeasureTheory.OuterMeasure.biInf_apply
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem biInf_apply' {ι} (I : Set ι) (m : ι → OuterMeasure α) {s : Set α} (hs : s.Nonempty) :
(⨅ i ∈ I, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i ∈ I, m i (t n) := by
simp only [← iInf_subtype'', iInf_apply' _ hs]
#align measure_theory.outer_measure.binfi_apply' MeasureTheory.OuterMeasure.biInf_apply'
theorem map_iInf_le {ι β} (f : α → β) (m : ι → OuterMeasure α) :
map f (⨅ i, m i) ≤ ⨅ i, map f (m i) :=
(map_mono f).map_iInf_le
#align measure_theory.outer_measure.map_infi_le MeasureTheory.OuterMeasure.map_iInf_le
theorem comap_iInf {ι β} (f : α → β) (m : ι → OuterMeasure β) :
comap f (⨅ i, m i) = ⨅ i, comap f (m i) := by
refine ext_nonempty fun s hs => ?_
refine ((comap_mono f).map_iInf_le s).antisymm ?_
simp only [comap_apply, iInf_apply' _ hs, iInf_apply' _ (hs.image _), le_iInf_iff,
Set.image_subset_iff, preimage_iUnion]
refine fun t ht => iInf_le_of_le _ (iInf_le_of_le ht <| ENNReal.tsum_le_tsum fun k => ?_)
exact iInf_mono fun i => (m i).mono (image_preimage_subset _ _)
#align measure_theory.outer_measure.comap_infi MeasureTheory.OuterMeasure.comap_iInf
theorem map_iInf {ι β} {f : α → β} (hf : Injective f) (m : ι → OuterMeasure α) :
map f (⨅ i, m i) = restrict (range f) (⨅ i, map f (m i)) := by
refine Eq.trans ?_ (map_comap _ _)
simp only [comap_iInf, comap_map hf]
#align measure_theory.outer_measure.map_infi MeasureTheory.OuterMeasure.map_iInf
theorem map_iInf_comap {ι β} [Nonempty ι] {f : α → β} (m : ι → OuterMeasure β) :
map f (⨅ i, comap f (m i)) = ⨅ i, map f (comap f (m i)) := by
refine (map_iInf_le _ _).antisymm fun s => ?_
simp only [map_apply, comap_apply, iInf_apply, le_iInf_iff]
refine fun t ht => iInf_le_of_le (fun n => f '' t n ∪ (range f)ᶜ) (iInf_le_of_le ?_ ?_)
· rw [← iUnion_union, Set.union_comm, ← inter_subset, ← image_iUnion, ←
image_preimage_eq_inter_range]
exact image_subset _ ht
· refine ENNReal.tsum_le_tsum fun n => iInf_mono fun i => (m i).mono ?_
simp only [preimage_union, preimage_compl, preimage_range, compl_univ, union_empty,
image_subset_iff]
exact subset_refl _
#align measure_theory.outer_measure.map_infi_comap MeasureTheory.OuterMeasure.map_iInf_comap
theorem map_biInf_comap {ι β} {I : Set ι} (hI : I.Nonempty) {f : α → β} (m : ι → OuterMeasure β) :
map f (⨅ i ∈ I, comap f (m i)) = ⨅ i ∈ I, map f (comap f (m i)) := by
haveI := hI.to_subtype
rw [← iInf_subtype'', ← iInf_subtype'']
exact map_iInf_comap _
#align measure_theory.outer_measure.map_binfi_comap MeasureTheory.OuterMeasure.map_biInf_comap
theorem restrict_iInf_restrict {ι} (s : Set α) (m : ι → OuterMeasure α) :
restrict s (⨅ i, restrict s (m i)) = restrict s (⨅ i, m i) :=
calc restrict s (⨅ i, restrict s (m i))
_ = restrict (range ((↑) : s → α)) (⨅ i, restrict s (m i)) := by rw [Subtype.range_coe]
_ = map ((↑) : s → α) (⨅ i, comap (↑) (m i)) := (map_iInf Subtype.coe_injective _).symm
_ = restrict s (⨅ i, m i) := congr_arg (map ((↑) : s → α)) (comap_iInf _ _).symm
#align measure_theory.outer_measure.restrict_infi_restrict MeasureTheory.OuterMeasure.restrict_iInf_restrict
theorem restrict_iInf {ι} [Nonempty ι] (s : Set α) (m : ι → OuterMeasure α) :
restrict s (⨅ i, m i) = ⨅ i, restrict s (m i) :=
(congr_arg (map ((↑) : s → α)) (comap_iInf _ _)).trans (map_iInf_comap _)
#align measure_theory.outer_measure.restrict_infi MeasureTheory.OuterMeasure.restrict_iInf
theorem restrict_biInf {ι} {I : Set ι} (hI : I.Nonempty) (s : Set α) (m : ι → OuterMeasure α) :
restrict s (⨅ i ∈ I, m i) = ⨅ i ∈ I, restrict s (m i) := by
haveI := hI.to_subtype
rw [← iInf_subtype'', ← iInf_subtype'']
exact restrict_iInf _ _
#align measure_theory.outer_measure.restrict_binfi MeasureTheory.OuterMeasure.restrict_biInf
/-- This proves that Inf and restrict commute for outer measures, so long as the set of
outer measures is nonempty. -/
| Mathlib/MeasureTheory/OuterMeasure/OfFunction.lean | 481 | 483 | theorem restrict_sInf_eq_sInf_restrict (m : Set (OuterMeasure α)) {s : Set α} (hm : m.Nonempty) :
restrict s (sInf m) = sInf (restrict s '' m) := by |
simp only [sInf_eq_iInf, restrict_biInf, hm, iInf_image]
|
/-
Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn
-/
import Mathlib.Data.Fin.VecNotation
import Mathlib.SetTheory.Cardinal.Basic
#align_import model_theory.basic from "leanprover-community/mathlib"@"369525b73f229ccd76a6ec0e0e0bf2be57599768"
/-!
# Basics on First-Order Structures
This file defines first-order languages and structures in the style of the
[Flypitch project](https://flypitch.github.io/), as well as several important maps between
structures.
## Main Definitions
* A `FirstOrder.Language` defines a language as a pair of functions from the natural numbers to
`Type l`. One sends `n` to the type of `n`-ary functions, and the other sends `n` to the type of
`n`-ary relations.
* A `FirstOrder.Language.Structure` interprets the symbols of a given `FirstOrder.Language` in the
context of a given type.
* A `FirstOrder.Language.Hom`, denoted `M →[L] N`, is a map from the `L`-structure `M` to the
`L`-structure `N` that commutes with the interpretations of functions, and which preserves the
interpretations of relations (although only in the forward direction).
* A `FirstOrder.Language.Embedding`, denoted `M ↪[L] N`, is an embedding from the `L`-structure `M`
to the `L`-structure `N` that commutes with the interpretations of functions, and which preserves
the interpretations of relations in both directions.
* A `FirstOrder.Language.Equiv`, denoted `M ≃[L] N`, is an equivalence from the `L`-structure `M`
to the `L`-structure `N` that commutes with the interpretations of functions, and which preserves
the interpretations of relations in both directions.
## References
For the Flypitch project:
- [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*]
[flypitch_cpp]
- [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of
the continuum hypothesis*][flypitch_itp]
-/
set_option autoImplicit true
universe u v u' v' w w'
open Cardinal
open Cardinal
namespace FirstOrder
/-! ### Languages and Structures -/
-- intended to be used with explicit universe parameters
/-- A first-order language consists of a type of functions of every natural-number arity and a
type of relations of every natural-number arity. -/
@[nolint checkUnivs]
structure Language where
/-- For every arity, a `Type*` of functions of that arity -/
Functions : ℕ → Type u
/-- For every arity, a `Type*` of relations of that arity -/
Relations : ℕ → Type v
#align first_order.language FirstOrder.Language
/-- Used to define `FirstOrder.Language₂`. -/
--@[simp]
def Sequence₂ (a₀ a₁ a₂ : Type u) : ℕ → Type u
| 0 => a₀
| 1 => a₁
| 2 => a₂
| _ => PEmpty
#align first_order.sequence₂ FirstOrder.Sequence₂
namespace Sequence₂
variable (a₀ a₁ a₂ : Type u)
instance inhabited₀ [h : Inhabited a₀] : Inhabited (Sequence₂ a₀ a₁ a₂ 0) :=
h
#align first_order.sequence₂.inhabited₀ FirstOrder.Sequence₂.inhabited₀
instance inhabited₁ [h : Inhabited a₁] : Inhabited (Sequence₂ a₀ a₁ a₂ 1) :=
h
#align first_order.sequence₂.inhabited₁ FirstOrder.Sequence₂.inhabited₁
instance inhabited₂ [h : Inhabited a₂] : Inhabited (Sequence₂ a₀ a₁ a₂ 2) :=
h
#align first_order.sequence₂.inhabited₂ FirstOrder.Sequence₂.inhabited₂
instance {n : ℕ} : IsEmpty (Sequence₂ a₀ a₁ a₂ (n + 3)) := inferInstanceAs (IsEmpty PEmpty)
@[simp]
theorem lift_mk {i : ℕ} :
Cardinal.lift.{v,u} #(Sequence₂ a₀ a₁ a₂ i)
= #(Sequence₂ (ULift.{v,u} a₀) (ULift.{v,u} a₁) (ULift.{v,u} a₂) i) := by
rcases i with (_ | _ | _ | i) <;>
simp only [Sequence₂, mk_uLift, Nat.succ_ne_zero, IsEmpty.forall_iff, Nat.succ.injEq,
add_eq_zero, OfNat.ofNat_ne_zero, and_false, one_ne_zero, mk_eq_zero, lift_zero]
#align first_order.sequence₂.lift_mk FirstOrder.Sequence₂.lift_mk
@[simp]
theorem sum_card : Cardinal.sum (fun i => #(Sequence₂ a₀ a₁ a₂ i)) = #a₀ + #a₁ + #a₂ := by
rw [sum_nat_eq_add_sum_succ, sum_nat_eq_add_sum_succ, sum_nat_eq_add_sum_succ]
simp [add_assoc, Sequence₂]
#align first_order.sequence₂.sum_card FirstOrder.Sequence₂.sum_card
end Sequence₂
namespace Language
/-- A constructor for languages with only constants, unary and binary functions, and
unary and binary relations. -/
@[simps]
protected def mk₂ (c f₁ f₂ : Type u) (r₁ r₂ : Type v) : Language :=
⟨Sequence₂ c f₁ f₂, Sequence₂ PEmpty r₁ r₂⟩
#align first_order.language.mk₂ FirstOrder.Language.mk₂
/-- The empty language has no symbols. -/
protected def empty : Language :=
⟨fun _ => Empty, fun _ => Empty⟩
#align first_order.language.empty FirstOrder.Language.empty
instance : Inhabited Language :=
⟨Language.empty⟩
/-- The sum of two languages consists of the disjoint union of their symbols. -/
protected def sum (L : Language.{u, v}) (L' : Language.{u', v'}) : Language :=
⟨fun n => Sum (L.Functions n) (L'.Functions n), fun n => Sum (L.Relations n) (L'.Relations n)⟩
#align first_order.language.sum FirstOrder.Language.sum
variable (L : Language.{u, v})
/-- The type of constants in a given language. -/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
protected def Constants :=
L.Functions 0
#align first_order.language.constants FirstOrder.Language.Constants
@[simp]
theorem constants_mk₂ (c f₁ f₂ : Type u) (r₁ r₂ : Type v) :
(Language.mk₂ c f₁ f₂ r₁ r₂).Constants = c :=
rfl
#align first_order.language.constants_mk₂ FirstOrder.Language.constants_mk₂
/-- The type of symbols in a given language. -/
-- Porting note(#5171): this linter isn't ported yet.
-- @[nolint has_nonempty_instance]
def Symbols :=
Sum (Σl, L.Functions l) (Σl, L.Relations l)
#align first_order.language.symbols FirstOrder.Language.Symbols
/-- The cardinality of a language is the cardinality of its type of symbols. -/
def card : Cardinal :=
#L.Symbols
#align first_order.language.card FirstOrder.Language.card
/-- A language is relational when it has no function symbols. -/
class IsRelational : Prop where
/-- There are no function symbols in the language. -/
empty_functions : ∀ n, IsEmpty (L.Functions n)
#align first_order.language.is_relational FirstOrder.Language.IsRelational
/-- A language is algebraic when it has no relation symbols. -/
class IsAlgebraic : Prop where
/-- There are no relation symbols in the language. -/
empty_relations : ∀ n, IsEmpty (L.Relations n)
#align first_order.language.is_algebraic FirstOrder.Language.IsAlgebraic
variable {L} {L' : Language.{u', v'}}
theorem card_eq_card_functions_add_card_relations :
L.card =
(Cardinal.sum fun l => Cardinal.lift.{v} #(L.Functions l)) +
Cardinal.sum fun l => Cardinal.lift.{u} #(L.Relations l) := by
simp [card, Symbols]
#align first_order.language.card_eq_card_functions_add_card_relations FirstOrder.Language.card_eq_card_functions_add_card_relations
instance [L.IsRelational] {n : ℕ} : IsEmpty (L.Functions n) :=
IsRelational.empty_functions n
instance [L.IsAlgebraic] {n : ℕ} : IsEmpty (L.Relations n) :=
IsAlgebraic.empty_relations n
instance isRelational_of_empty_functions {symb : ℕ → Type*} :
IsRelational ⟨fun _ => Empty, symb⟩ :=
⟨fun _ => instIsEmptyEmpty⟩
#align first_order.language.is_relational_of_empty_functions FirstOrder.Language.isRelational_of_empty_functions
instance isAlgebraic_of_empty_relations {symb : ℕ → Type*} : IsAlgebraic ⟨symb, fun _ => Empty⟩ :=
⟨fun _ => instIsEmptyEmpty⟩
#align first_order.language.is_algebraic_of_empty_relations FirstOrder.Language.isAlgebraic_of_empty_relations
instance isRelational_empty : IsRelational Language.empty :=
Language.isRelational_of_empty_functions
#align first_order.language.is_relational_empty FirstOrder.Language.isRelational_empty
instance isAlgebraic_empty : IsAlgebraic Language.empty :=
Language.isAlgebraic_of_empty_relations
#align first_order.language.is_algebraic_empty FirstOrder.Language.isAlgebraic_empty
instance isRelational_sum [L.IsRelational] [L'.IsRelational] : IsRelational (L.sum L') :=
⟨fun _ => instIsEmptySum⟩
#align first_order.language.is_relational_sum FirstOrder.Language.isRelational_sum
instance isAlgebraic_sum [L.IsAlgebraic] [L'.IsAlgebraic] : IsAlgebraic (L.sum L') :=
⟨fun _ => instIsEmptySum⟩
#align first_order.language.is_algebraic_sum FirstOrder.Language.isAlgebraic_sum
instance isRelational_mk₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} [h0 : IsEmpty c] [h1 : IsEmpty f₁]
[h2 : IsEmpty f₂] : IsRelational (Language.mk₂ c f₁ f₂ r₁ r₂) :=
⟨fun n =>
Nat.casesOn n h0 fun n => Nat.casesOn n h1 fun n => Nat.casesOn n h2 fun _ =>
inferInstanceAs (IsEmpty PEmpty)⟩
#align first_order.language.is_relational_mk₂ FirstOrder.Language.isRelational_mk₂
instance isAlgebraic_mk₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} [h1 : IsEmpty r₁] [h2 : IsEmpty r₂] :
IsAlgebraic (Language.mk₂ c f₁ f₂ r₁ r₂) :=
⟨fun n =>
Nat.casesOn n (inferInstanceAs (IsEmpty PEmpty)) fun n =>
Nat.casesOn n h1 fun n => Nat.casesOn n h2 fun _ => inferInstanceAs (IsEmpty PEmpty)⟩
#align first_order.language.is_algebraic_mk₂ FirstOrder.Language.isAlgebraic_mk₂
instance subsingleton_mk₂_functions {c f₁ f₂ : Type u} {r₁ r₂ : Type v} [h0 : Subsingleton c]
[h1 : Subsingleton f₁] [h2 : Subsingleton f₂] {n : ℕ} :
Subsingleton ((Language.mk₂ c f₁ f₂ r₁ r₂).Functions n) :=
Nat.casesOn n h0 fun n =>
Nat.casesOn n h1 fun n => Nat.casesOn n h2 fun _ => ⟨fun x => PEmpty.elim x⟩
#align first_order.language.subsingleton_mk₂_functions FirstOrder.Language.subsingleton_mk₂_functions
instance subsingleton_mk₂_relations {c f₁ f₂ : Type u} {r₁ r₂ : Type v} [h1 : Subsingleton r₁]
[h2 : Subsingleton r₂] {n : ℕ} : Subsingleton ((Language.mk₂ c f₁ f₂ r₁ r₂).Relations n) :=
Nat.casesOn n ⟨fun x => PEmpty.elim x⟩ fun n =>
Nat.casesOn n h1 fun n => Nat.casesOn n h2 fun _ => ⟨fun x => PEmpty.elim x⟩
#align first_order.language.subsingleton_mk₂_relations FirstOrder.Language.subsingleton_mk₂_relations
@[simp]
theorem empty_card : Language.empty.card = 0 := by simp [card_eq_card_functions_add_card_relations]
#align first_order.language.empty_card FirstOrder.Language.empty_card
instance isEmpty_empty : IsEmpty Language.empty.Symbols := by
simp only [Language.Symbols, isEmpty_sum, isEmpty_sigma]
exact ⟨fun _ => inferInstance, fun _ => inferInstance⟩
#align first_order.language.is_empty_empty FirstOrder.Language.isEmpty_empty
instance Countable.countable_functions [h : Countable L.Symbols] : Countable (Σl, L.Functions l) :=
@Function.Injective.countable _ _ h _ Sum.inl_injective
#align first_order.language.countable.countable_functions FirstOrder.Language.Countable.countable_functions
@[simp]
theorem card_functions_sum (i : ℕ) :
#((L.sum L').Functions i)
= (Cardinal.lift.{u'} #(L.Functions i) + Cardinal.lift.{u} #(L'.Functions i) : Cardinal) := by
simp [Language.sum]
#align first_order.language.card_functions_sum FirstOrder.Language.card_functions_sum
@[simp]
theorem card_relations_sum (i : ℕ) :
#((L.sum L').Relations i) =
Cardinal.lift.{v'} #(L.Relations i) + Cardinal.lift.{v} #(L'.Relations i) := by
simp [Language.sum]
#align first_order.language.card_relations_sum FirstOrder.Language.card_relations_sum
@[simp]
theorem card_sum :
(L.sum L').card = Cardinal.lift.{max u' v'} L.card + Cardinal.lift.{max u v} L'.card := by
simp only [card_eq_card_functions_add_card_relations, card_functions_sum, card_relations_sum,
sum_add_distrib', lift_add, lift_sum, lift_lift]
simp only [add_assoc, add_comm (Cardinal.sum fun i => (#(L'.Functions i)).lift)]
#align first_order.language.card_sum FirstOrder.Language.card_sum
@[simp]
theorem card_mk₂ (c f₁ f₂ : Type u) (r₁ r₂ : Type v) :
(Language.mk₂ c f₁ f₂ r₁ r₂).card =
Cardinal.lift.{v} #c + Cardinal.lift.{v} #f₁ + Cardinal.lift.{v} #f₂ +
Cardinal.lift.{u} #r₁ + Cardinal.lift.{u} #r₂ := by
simp [card_eq_card_functions_add_card_relations, add_assoc]
#align first_order.language.card_mk₂ FirstOrder.Language.card_mk₂
variable (L) (M : Type w)
/-- A first-order structure on a type `M` consists of interpretations of all the symbols in a given
language. Each function of arity `n` is interpreted as a function sending tuples of length `n`
(modeled as `(Fin n → M)`) to `M`, and a relation of arity `n` is a function from tuples of length
`n` to `Prop`. -/
@[ext]
class Structure where
/-- Interpretation of the function symbols -/
funMap : ∀ {n}, L.Functions n → (Fin n → M) → M
/-- Interpretation of the relation symbols -/
RelMap : ∀ {n}, L.Relations n → (Fin n → M) → Prop
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure FirstOrder.Language.Structure
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.fun_map FirstOrder.Language.Structure.funMap
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.rel_map FirstOrder.Language.Structure.RelMap
variable (N : Type w') [L.Structure M] [L.Structure N]
open Structure
/-- Used for defining `FirstOrder.Language.Theory.ModelType.instInhabited`. -/
def Inhabited.trivialStructure {α : Type*} [Inhabited α] : L.Structure α :=
⟨default, default⟩
#align first_order.language.inhabited.trivial_structure FirstOrder.Language.Inhabited.trivialStructure
/-! ### Maps -/
/-- A homomorphism between first-order structures is a function that commutes with the
interpretations of functions and maps tuples in one structure where a given relation is true to
tuples in the second structure where that relation is still true. -/
structure Hom where
/-- The underlying function of a homomorphism of structures -/
toFun : M → N
/-- The homomorphism commutes with the interpretations of the function symbols -/
-- Porting note:
-- The autoparam here used to be `obviously`. We would like to replace it with `aesop`
-- but that isn't currently sufficient.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Aesop.20and.20cases
-- If that can be improved, we should change this to `by aesop` and remove the proofs below.
map_fun' : ∀ {n} (f : L.Functions n) (x), toFun (funMap f x) = funMap f (toFun ∘ x) := by
intros; trivial
/-- The homomorphism sends related elements to related elements -/
map_rel' : ∀ {n} (r : L.Relations n) (x), RelMap r x → RelMap r (toFun ∘ x) := by
-- Porting note: see porting note on `Hom.map_fun'`
intros; trivial
#align first_order.language.hom FirstOrder.Language.Hom
@[inherit_doc]
scoped[FirstOrder] notation:25 A " →[" L "] " B => FirstOrder.Language.Hom L A B
/-- An embedding of first-order structures is an embedding that commutes with the
interpretations of functions and relations. -/
structure Embedding extends M ↪ N where
map_fun' : ∀ {n} (f : L.Functions n) (x), toFun (funMap f x) = funMap f (toFun ∘ x) := by
-- Porting note: see porting note on `Hom.map_fun'`
intros; trivial
map_rel' : ∀ {n} (r : L.Relations n) (x), RelMap r (toFun ∘ x) ↔ RelMap r x := by
-- Porting note: see porting note on `Hom.map_fun'`
intros; trivial
#align first_order.language.embedding FirstOrder.Language.Embedding
@[inherit_doc]
scoped[FirstOrder] notation:25 A " ↪[" L "] " B => FirstOrder.Language.Embedding L A B
/-- An equivalence of first-order structures is an equivalence that commutes with the
interpretations of functions and relations. -/
structure Equiv extends M ≃ N where
map_fun' : ∀ {n} (f : L.Functions n) (x), toFun (funMap f x) = funMap f (toFun ∘ x) := by
-- Porting note: see porting note on `Hom.map_fun'`
intros; trivial
map_rel' : ∀ {n} (r : L.Relations n) (x), RelMap r (toFun ∘ x) ↔ RelMap r x := by
-- Porting note: see porting note on `Hom.map_fun'`
intros; trivial
#align first_order.language.equiv FirstOrder.Language.Equiv
@[inherit_doc]
scoped[FirstOrder] notation:25 A " ≃[" L "] " B => FirstOrder.Language.Equiv L A B
-- Porting note: was [L.Structure P] and [L.Structure Q]
-- The former reported an error.
variable {L M N} {P : Type*} [Structure L P] {Q : Type*} [Structure L Q]
-- Porting note (#11445): new definition
/-- Interpretation of a constant symbol -/
@[coe]
def constantMap (c : L.Constants) : M := funMap c default
instance : CoeTC L.Constants M :=
⟨constantMap⟩
theorem funMap_eq_coe_constants {c : L.Constants} {x : Fin 0 → M} : funMap c x = c :=
congr rfl (funext finZeroElim)
#align first_order.language.fun_map_eq_coe_constants FirstOrder.Language.funMap_eq_coe_constants
/-- Given a language with a nonempty type of constants, any structure will be nonempty. This cannot
be a global instance, because `L` becomes a metavariable. -/
theorem nonempty_of_nonempty_constants [h : Nonempty L.Constants] : Nonempty M :=
h.map (↑)
#align first_order.language.nonempty_of_nonempty_constants FirstOrder.Language.nonempty_of_nonempty_constants
/-- The function map for `FirstOrder.Language.Structure₂`. -/
def funMap₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} (c' : c → M) (f₁' : f₁ → M → M)
(f₂' : f₂ → M → M → M) : ∀ {n}, (Language.mk₂ c f₁ f₂ r₁ r₂).Functions n → (Fin n → M) → M
| 0, f, _ => c' f
| 1, f, x => f₁' f (x 0)
| 2, f, x => f₂' f (x 0) (x 1)
| _ + 3, f, _ => PEmpty.elim f
#align first_order.language.fun_map₂ FirstOrder.Language.funMap₂
/-- The relation map for `FirstOrder.Language.Structure₂`. -/
def RelMap₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} (r₁' : r₁ → Set M) (r₂' : r₂ → M → M → Prop) :
∀ {n}, (Language.mk₂ c f₁ f₂ r₁ r₂).Relations n → (Fin n → M) → Prop
| 0, r, _ => PEmpty.elim r
| 1, r, x => x 0 ∈ r₁' r
| 2, r, x => r₂' r (x 0) (x 1)
| _ + 3, r, _ => PEmpty.elim r
#align first_order.language.rel_map₂ FirstOrder.Language.RelMap₂
/-- A structure constructor to match `FirstOrder.Language₂`. -/
protected def Structure.mk₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} (c' : c → M) (f₁' : f₁ → M → M)
(f₂' : f₂ → M → M → M) (r₁' : r₁ → Set M) (r₂' : r₂ → M → M → Prop) :
(Language.mk₂ c f₁ f₂ r₁ r₂).Structure M :=
⟨funMap₂ c' f₁' f₂', RelMap₂ r₁' r₂'⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.mk₂ FirstOrder.Language.Structure.mk₂
namespace Structure
variable {c f₁ f₂ : Type u} {r₁ r₂ : Type v}
variable {c' : c → M} {f₁' : f₁ → M → M} {f₂' : f₂ → M → M → M}
variable {r₁' : r₁ → Set M} {r₂' : r₂ → M → M → Prop}
@[simp]
theorem funMap_apply₀ (c₀ : c) {x : Fin 0 → M} :
@Structure.funMap _ M (Structure.mk₂ c' f₁' f₂' r₁' r₂') 0 c₀ x = c' c₀ :=
rfl
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.fun_map_apply₀ FirstOrder.Language.Structure.funMap_apply₀
@[simp]
theorem funMap_apply₁ (f : f₁) (x : M) :
@Structure.funMap _ M (Structure.mk₂ c' f₁' f₂' r₁' r₂') 1 f ![x] = f₁' f x :=
rfl
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.fun_map_apply₁ FirstOrder.Language.Structure.funMap_apply₁
@[simp]
theorem funMap_apply₂ (f : f₂) (x y : M) :
@Structure.funMap _ M (Structure.mk₂ c' f₁' f₂' r₁' r₂') 2 f ![x, y] = f₂' f x y :=
rfl
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.fun_map_apply₂ FirstOrder.Language.Structure.funMap_apply₂
@[simp]
theorem relMap_apply₁ (r : r₁) (x : M) :
@Structure.RelMap _ M (Structure.mk₂ c' f₁' f₂' r₁' r₂') 1 r ![x] = (x ∈ r₁' r) :=
rfl
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.rel_map_apply₁ FirstOrder.Language.Structure.relMap_apply₁
@[simp]
theorem relMap_apply₂ (r : r₂) (x y : M) :
@Structure.RelMap _ M (Structure.mk₂ c' f₁' f₂' r₁' r₂') 2 r ![x, y] = r₂' r x y :=
rfl
set_option linter.uppercaseLean3 false in
#align first_order.language.Structure.rel_map_apply₂ FirstOrder.Language.Structure.relMap_apply₂
end Structure
/-- `HomClass L F M N` states that `F` is a type of `L`-homomorphisms. You should extend this
typeclass when you extend `FirstOrder.Language.Hom`. -/
class HomClass (L : outParam Language) (F M N : Type*)
[FunLike F M N] [L.Structure M] [L.Structure N] : Prop where
map_fun : ∀ (φ : F) {n} (f : L.Functions n) (x), φ (funMap f x) = funMap f (φ ∘ x)
map_rel : ∀ (φ : F) {n} (r : L.Relations n) (x), RelMap r x → RelMap r (φ ∘ x)
#align first_order.language.hom_class FirstOrder.Language.HomClass
/-- `StrongHomClass L F M N` states that `F` is a type of `L`-homomorphisms which preserve
relations in both directions. -/
class StrongHomClass (L : outParam Language) (F M N : Type*)
[FunLike F M N] [L.Structure M] [L.Structure N] : Prop where
map_fun : ∀ (φ : F) {n} (f : L.Functions n) (x), φ (funMap f x) = funMap f (φ ∘ x)
map_rel : ∀ (φ : F) {n} (r : L.Relations n) (x), RelMap r (φ ∘ x) ↔ RelMap r x
#align first_order.language.strong_hom_class FirstOrder.Language.StrongHomClass
-- Porting note: using implicit brackets for `Structure` arguments
instance (priority := 100) StrongHomClass.homClass [L.Structure M]
[L.Structure N] [FunLike F M N] [StrongHomClass L F M N] : HomClass L F M N where
map_fun := StrongHomClass.map_fun
map_rel φ _ R x := (StrongHomClass.map_rel φ R x).2
#align first_order.language.strong_hom_class.hom_class FirstOrder.Language.StrongHomClass.homClass
/-- Not an instance to avoid a loop. -/
theorem HomClass.strongHomClassOfIsAlgebraic [L.IsAlgebraic] {F M N} [L.Structure M] [L.Structure N]
[FunLike F M N] [HomClass L F M N] : StrongHomClass L F M N where
map_fun := HomClass.map_fun
map_rel _ n R _ := (IsAlgebraic.empty_relations n).elim R
#align first_order.language.hom_class.strong_hom_class_of_is_algebraic FirstOrder.Language.HomClass.strongHomClassOfIsAlgebraic
theorem HomClass.map_constants {F M N} [L.Structure M] [L.Structure N] [FunLike F M N]
[HomClass L F M N] (φ : F) (c : L.Constants) : φ c = c :=
(HomClass.map_fun φ c default).trans (congr rfl (funext default))
#align first_order.language.hom_class.map_constants FirstOrder.Language.HomClass.map_constants
attribute [inherit_doc FirstOrder.Language.Hom.map_fun'] FirstOrder.Language.Embedding.map_fun'
FirstOrder.Language.HomClass.map_fun FirstOrder.Language.StrongHomClass.map_fun
FirstOrder.Language.Equiv.map_fun'
attribute [inherit_doc FirstOrder.Language.Hom.map_rel'] FirstOrder.Language.Embedding.map_rel'
FirstOrder.Language.HomClass.map_rel FirstOrder.Language.StrongHomClass.map_rel
FirstOrder.Language.Equiv.map_rel'
namespace Hom
instance instFunLike : FunLike (M →[L] N) M N where
coe := Hom.toFun
coe_injective' f g h := by cases f; cases g; cases h; rfl
#align first_order.language.hom.fun_like FirstOrder.Language.Hom.instFunLike
instance homClass : HomClass L (M →[L] N) M N where
map_fun := map_fun'
map_rel := map_rel'
#align first_order.language.hom.hom_class FirstOrder.Language.Hom.homClass
instance [L.IsAlgebraic] : StrongHomClass L (M →[L] N) M N :=
HomClass.strongHomClassOfIsAlgebraic
instance hasCoeToFun : CoeFun (M →[L] N) fun _ => M → N :=
DFunLike.hasCoeToFun
#align first_order.language.hom.has_coe_to_fun FirstOrder.Language.Hom.hasCoeToFun
@[simp]
theorem toFun_eq_coe {f : M →[L] N} : f.toFun = (f : M → N) :=
rfl
#align first_order.language.hom.to_fun_eq_coe FirstOrder.Language.Hom.toFun_eq_coe
@[ext]
theorem ext ⦃f g : M →[L] N⦄ (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align first_order.language.hom.ext FirstOrder.Language.Hom.ext
theorem ext_iff {f g : M →[L] N} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align first_order.language.hom.ext_iff FirstOrder.Language.Hom.ext_iff
@[simp]
theorem map_fun (φ : M →[L] N) {n : ℕ} (f : L.Functions n) (x : Fin n → M) :
φ (funMap f x) = funMap f (φ ∘ x) :=
HomClass.map_fun φ f x
#align first_order.language.hom.map_fun FirstOrder.Language.Hom.map_fun
@[simp]
theorem map_constants (φ : M →[L] N) (c : L.Constants) : φ c = c :=
HomClass.map_constants φ c
#align first_order.language.hom.map_constants FirstOrder.Language.Hom.map_constants
@[simp]
theorem map_rel (φ : M →[L] N) {n : ℕ} (r : L.Relations n) (x : Fin n → M) :
RelMap r x → RelMap r (φ ∘ x) :=
HomClass.map_rel φ r x
#align first_order.language.hom.map_rel FirstOrder.Language.Hom.map_rel
variable (L) (M)
/-- The identity map from a structure to itself. -/
@[refl]
def id : M →[L] M where
toFun m := m
#align first_order.language.hom.id FirstOrder.Language.Hom.id
variable {L} {M}
instance : Inhabited (M →[L] M) :=
⟨id L M⟩
@[simp]
theorem id_apply (x : M) : id L M x = x :=
rfl
#align first_order.language.hom.id_apply FirstOrder.Language.Hom.id_apply
/-- Composition of first-order homomorphisms. -/
@[trans]
def comp (hnp : N →[L] P) (hmn : M →[L] N) : M →[L] P where
toFun := hnp ∘ hmn
-- Porting note: should be done by autoparam?
map_fun' _ _ := by simp; rfl
-- Porting note: should be done by autoparam?
map_rel' _ _ h := map_rel _ _ _ (map_rel _ _ _ h)
#align first_order.language.hom.comp FirstOrder.Language.Hom.comp
@[simp]
theorem comp_apply (g : N →[L] P) (f : M →[L] N) (x : M) : g.comp f x = g (f x) :=
rfl
#align first_order.language.hom.comp_apply FirstOrder.Language.Hom.comp_apply
/-- Composition of first-order homomorphisms is associative. -/
theorem comp_assoc (f : M →[L] N) (g : N →[L] P) (h : P →[L] Q) :
(h.comp g).comp f = h.comp (g.comp f) :=
rfl
#align first_order.language.hom.comp_assoc FirstOrder.Language.Hom.comp_assoc
@[simp]
theorem comp_id (f : M →[L] N) : f.comp (id L M) = f :=
rfl
@[simp]
theorem id_comp (f : M →[L] N) : (id L N).comp f = f :=
rfl
end Hom
/-- Any element of a `HomClass` can be realized as a first_order homomorphism. -/
def HomClass.toHom {F M N} [L.Structure M] [L.Structure N] [FunLike F M N]
[HomClass L F M N] : F → M →[L] N := fun φ =>
⟨φ, HomClass.map_fun φ, HomClass.map_rel φ⟩
#align first_order.language.hom_class.to_hom FirstOrder.Language.HomClass.toHom
namespace Embedding
instance funLike : FunLike (M ↪[L] N) M N where
coe f := f.toFun
coe_injective' f g h := by
cases f
cases g
congr
ext x
exact Function.funext_iff.1 h x
instance embeddingLike : EmbeddingLike (M ↪[L] N) M N where
injective' f := f.toEmbedding.injective
#align first_order.language.embedding.embedding_like FirstOrder.Language.Embedding.embeddingLike
instance strongHomClass : StrongHomClass L (M ↪[L] N) M N where
map_fun := map_fun'
map_rel := map_rel'
#align first_order.language.embedding.strong_hom_class FirstOrder.Language.Embedding.strongHomClass
#noalign first_order.language.embedding.has_coe_to_fun -- Porting note: replaced by funLike instance
@[simp]
theorem map_fun (φ : M ↪[L] N) {n : ℕ} (f : L.Functions n) (x : Fin n → M) :
φ (funMap f x) = funMap f (φ ∘ x) :=
HomClass.map_fun φ f x
#align first_order.language.embedding.map_fun FirstOrder.Language.Embedding.map_fun
@[simp]
theorem map_constants (φ : M ↪[L] N) (c : L.Constants) : φ c = c :=
HomClass.map_constants φ c
#align first_order.language.embedding.map_constants FirstOrder.Language.Embedding.map_constants
@[simp]
theorem map_rel (φ : M ↪[L] N) {n : ℕ} (r : L.Relations n) (x : Fin n → M) :
RelMap r (φ ∘ x) ↔ RelMap r x :=
StrongHomClass.map_rel φ r x
#align first_order.language.embedding.map_rel FirstOrder.Language.Embedding.map_rel
/-- A first-order embedding is also a first-order homomorphism. -/
def toHom : (M ↪[L] N) → M →[L] N :=
HomClass.toHom
#align first_order.language.embedding.to_hom FirstOrder.Language.Embedding.toHom
@[simp]
theorem coe_toHom {f : M ↪[L] N} : (f.toHom : M → N) = f :=
rfl
#align first_order.language.embedding.coe_to_hom FirstOrder.Language.Embedding.coe_toHom
theorem coe_injective : @Function.Injective (M ↪[L] N) (M → N) (↑)
| f, g, h => by
cases f
cases g
congr
ext x
exact Function.funext_iff.1 h x
#align first_order.language.embedding.coe_injective FirstOrder.Language.Embedding.coe_injective
@[ext]
theorem ext ⦃f g : M ↪[L] N⦄ (h : ∀ x, f x = g x) : f = g :=
coe_injective (funext h)
#align first_order.language.embedding.ext FirstOrder.Language.Embedding.ext
theorem ext_iff {f g : M ↪[L] N} : f = g ↔ ∀ x, f x = g x :=
⟨fun h _ => h ▸ rfl, fun h => ext h⟩
#align first_order.language.embedding.ext_iff FirstOrder.Language.Embedding.ext_iff
theorem toHom_injective : @Function.Injective (M ↪[L] N) (M →[L] N) (·.toHom) := by
intro f f' h
ext
exact congr_fun (congr_arg (↑) h) _
@[simp]
theorem toHom_inj {f g : M ↪[L] N} : f.toHom = g.toHom ↔ f = g :=
⟨fun h ↦ toHom_injective h, fun h ↦ congr_arg (·.toHom) h⟩
theorem injective (f : M ↪[L] N) : Function.Injective f :=
f.toEmbedding.injective
#align first_order.language.embedding.injective FirstOrder.Language.Embedding.injective
/-- In an algebraic language, any injective homomorphism is an embedding. -/
@[simps!]
def ofInjective [L.IsAlgebraic] {f : M →[L] N} (hf : Function.Injective f) : M ↪[L] N :=
{ f with
inj' := hf
map_rel' := fun {_} r x => StrongHomClass.map_rel f r x }
#align first_order.language.embedding.of_injective FirstOrder.Language.Embedding.ofInjective
@[simp]
theorem coeFn_ofInjective [L.IsAlgebraic] {f : M →[L] N} (hf : Function.Injective f) :
(ofInjective hf : M → N) = f :=
rfl
#align first_order.language.embedding.coe_fn_of_injective FirstOrder.Language.Embedding.coeFn_ofInjective
@[simp]
theorem ofInjective_toHom [L.IsAlgebraic] {f : M →[L] N} (hf : Function.Injective f) :
(ofInjective hf).toHom = f := by
ext; simp
#align first_order.language.embedding.of_injective_to_hom FirstOrder.Language.Embedding.ofInjective_toHom
variable (L) (M)
/-- The identity embedding from a structure to itself. -/
@[refl]
def refl : M ↪[L] M where toEmbedding := Function.Embedding.refl M
#align first_order.language.embedding.refl FirstOrder.Language.Embedding.refl
variable {L} {M}
instance : Inhabited (M ↪[L] M) :=
⟨refl L M⟩
@[simp]
theorem refl_apply (x : M) : refl L M x = x :=
rfl
#align first_order.language.embedding.refl_apply FirstOrder.Language.Embedding.refl_apply
/-- Composition of first-order embeddings. -/
@[trans]
def comp (hnp : N ↪[L] P) (hmn : M ↪[L] N) : M ↪[L] P where
toFun := hnp ∘ hmn
inj' := hnp.injective.comp hmn.injective
-- Porting note: should be done by autoparam?
map_fun' := by intros; simp only [Function.comp_apply, map_fun]; trivial
-- Porting note: should be done by autoparam?
map_rel' := by intros; rw [Function.comp.assoc, map_rel, map_rel]
#align first_order.language.embedding.comp FirstOrder.Language.Embedding.comp
@[simp]
theorem comp_apply (g : N ↪[L] P) (f : M ↪[L] N) (x : M) : g.comp f x = g (f x) :=
rfl
#align first_order.language.embedding.comp_apply FirstOrder.Language.Embedding.comp_apply
/-- Composition of first-order embeddings is associative. -/
theorem comp_assoc (f : M ↪[L] N) (g : N ↪[L] P) (h : P ↪[L] Q) :
(h.comp g).comp f = h.comp (g.comp f) :=
rfl
#align first_order.language.embedding.comp_assoc FirstOrder.Language.Embedding.comp_assoc
theorem comp_injective (h : N ↪[L] P) :
Function.Injective (h.comp : (M ↪[L] N) → (M ↪[L] P)) := by
intro f g hfg
ext x; exact h.injective (DFunLike.congr_fun hfg x)
@[simp]
theorem comp_inj (h : N ↪[L] P) (f g : M ↪[L] N) : h.comp f = h.comp g ↔ f = g :=
⟨fun eq ↦ h.comp_injective eq, congr_arg h.comp⟩
theorem toHom_comp_injective (h : N ↪[L] P) :
Function.Injective (h.toHom.comp : (M →[L] N) → (M →[L] P)) := by
intro f g hfg
ext x; exact h.injective (DFunLike.congr_fun hfg x)
@[simp]
theorem toHom_comp_inj (h : N ↪[L] P) (f g : M →[L] N) : h.toHom.comp f = h.toHom.comp g ↔ f = g :=
⟨fun eq ↦ h.toHom_comp_injective eq, congr_arg h.toHom.comp⟩
@[simp]
theorem comp_toHom (hnp : N ↪[L] P) (hmn : M ↪[L] N) :
(hnp.comp hmn).toHom = hnp.toHom.comp hmn.toHom :=
rfl
#align first_order.language.embedding.comp_to_hom FirstOrder.Language.Embedding.comp_toHom
@[simp]
theorem comp_refl (f : M ↪[L] N) : f.comp (refl L M) = f := DFunLike.coe_injective rfl
@[simp]
theorem refl_comp (f : M ↪[L] N) : (refl L N).comp f = f := DFunLike.coe_injective rfl
@[simp]
theorem refl_toHom : (refl L M).toHom = Hom.id L M :=
rfl
end Embedding
/-- Any element of an injective `StrongHomClass` can be realized as a first_order embedding. -/
def StrongHomClass.toEmbedding {F M N} [L.Structure M] [L.Structure N] [FunLike F M N]
[EmbeddingLike F M N] [StrongHomClass L F M N] : F → M ↪[L] N := fun φ =>
⟨⟨φ, EmbeddingLike.injective φ⟩, StrongHomClass.map_fun φ, StrongHomClass.map_rel φ⟩
#align first_order.language.strong_hom_class.to_embedding FirstOrder.Language.StrongHomClass.toEmbedding
namespace Equiv
instance : EquivLike (M ≃[L] N) M N where
coe f := f.toFun
inv f := f.invFun
left_inv f := f.left_inv
right_inv f := f.right_inv
coe_injective' f g h₁ h₂ := by
cases f
cases g
simp only [mk.injEq]
ext x
exact Function.funext_iff.1 h₁ x
instance : StrongHomClass L (M ≃[L] N) M N where
map_fun := map_fun'
map_rel := map_rel'
/-- The inverse of a first-order equivalence is a first-order equivalence. -/
@[symm]
def symm (f : M ≃[L] N) : N ≃[L] M :=
{ f.toEquiv.symm with
map_fun' := fun n f' {x} => by
simp only [Equiv.toFun_as_coe]
rw [Equiv.symm_apply_eq]
refine Eq.trans ?_ (f.map_fun' f' (f.toEquiv.symm ∘ x)).symm
rw [← Function.comp.assoc, Equiv.toFun_as_coe, Equiv.self_comp_symm, Function.id_comp]
map_rel' := fun n r {x} => by
simp only [Equiv.toFun_as_coe]
refine (f.map_rel' r (f.toEquiv.symm ∘ x)).symm.trans ?_
rw [← Function.comp.assoc, Equiv.toFun_as_coe, Equiv.self_comp_symm, Function.id_comp] }
#align first_order.language.equiv.symm FirstOrder.Language.Equiv.symm
instance hasCoeToFun : CoeFun (M ≃[L] N) fun _ => M → N :=
DFunLike.hasCoeToFun
#align first_order.language.equiv.has_coe_to_fun FirstOrder.Language.Equiv.hasCoeToFun
@[simp]
theorem symm_symm (f : M ≃[L] N) :
f.symm.symm = f :=
rfl
@[simp]
theorem apply_symm_apply (f : M ≃[L] N) (a : N) : f (f.symm a) = a :=
f.toEquiv.apply_symm_apply a
#align first_order.language.equiv.apply_symm_apply FirstOrder.Language.Equiv.apply_symm_apply
@[simp]
theorem symm_apply_apply (f : M ≃[L] N) (a : M) : f.symm (f a) = a :=
f.toEquiv.symm_apply_apply a
#align first_order.language.equiv.symm_apply_apply FirstOrder.Language.Equiv.symm_apply_apply
@[simp]
theorem map_fun (φ : M ≃[L] N) {n : ℕ} (f : L.Functions n) (x : Fin n → M) :
φ (funMap f x) = funMap f (φ ∘ x) :=
HomClass.map_fun φ f x
#align first_order.language.equiv.map_fun FirstOrder.Language.Equiv.map_fun
@[simp]
theorem map_constants (φ : M ≃[L] N) (c : L.Constants) : φ c = c :=
HomClass.map_constants φ c
#align first_order.language.equiv.map_constants FirstOrder.Language.Equiv.map_constants
@[simp]
theorem map_rel (φ : M ≃[L] N) {n : ℕ} (r : L.Relations n) (x : Fin n → M) :
RelMap r (φ ∘ x) ↔ RelMap r x :=
StrongHomClass.map_rel φ r x
#align first_order.language.equiv.map_rel FirstOrder.Language.Equiv.map_rel
/-- A first-order equivalence is also a first-order embedding. -/
def toEmbedding : (M ≃[L] N) → M ↪[L] N :=
StrongHomClass.toEmbedding
#align first_order.language.equiv.to_embedding FirstOrder.Language.Equiv.toEmbedding
/-- A first-order equivalence is also a first-order homomorphism. -/
def toHom : (M ≃[L] N) → M →[L] N :=
HomClass.toHom
#align first_order.language.equiv.to_hom FirstOrder.Language.Equiv.toHom
@[simp]
theorem toEmbedding_toHom (f : M ≃[L] N) : f.toEmbedding.toHom = f.toHom :=
rfl
#align first_order.language.equiv.to_embedding_to_hom FirstOrder.Language.Equiv.toEmbedding_toHom
@[simp]
theorem coe_toHom {f : M ≃[L] N} : (f.toHom : M → N) = (f : M → N) :=
rfl
#align first_order.language.equiv.coe_to_hom FirstOrder.Language.Equiv.coe_toHom
@[simp]
theorem coe_toEmbedding (f : M ≃[L] N) : (f.toEmbedding : M → N) = (f : M → N) :=
rfl
#align first_order.language.equiv.coe_to_embedding FirstOrder.Language.Equiv.coe_toEmbedding
theorem injective_toEmbedding : Function.Injective (toEmbedding : (M ≃[L] N) → M ↪[L] N) := by
intro _ _ h; apply DFunLike.coe_injective; exact congr_arg (DFunLike.coe ∘ Embedding.toHom) h
theorem coe_injective : @Function.Injective (M ≃[L] N) (M → N) (↑) :=
DFunLike.coe_injective
#align first_order.language.equiv.coe_injective FirstOrder.Language.Equiv.coe_injective
@[ext]
theorem ext ⦃f g : M ≃[L] N⦄ (h : ∀ x, f x = g x) : f = g :=
coe_injective (funext h)
#align first_order.language.equiv.ext FirstOrder.Language.Equiv.ext
theorem ext_iff {f g : M ≃[L] N} : f = g ↔ ∀ x, f x = g x :=
⟨fun h _ => h ▸ rfl, fun h => ext h⟩
#align first_order.language.equiv.ext_iff FirstOrder.Language.Equiv.ext_iff
theorem bijective (f : M ≃[L] N) : Function.Bijective f :=
EquivLike.bijective f
#align first_order.language.equiv.bijective FirstOrder.Language.Equiv.bijective
theorem injective (f : M ≃[L] N) : Function.Injective f :=
EquivLike.injective f
#align first_order.language.equiv.injective FirstOrder.Language.Equiv.injective
theorem surjective (f : M ≃[L] N) : Function.Surjective f :=
EquivLike.surjective f
#align first_order.language.equiv.surjective FirstOrder.Language.Equiv.surjective
variable (L) (M)
/-- The identity equivalence from a structure to itself. -/
@[refl]
def refl : M ≃[L] M where toEquiv := _root_.Equiv.refl M
#align first_order.language.equiv.refl FirstOrder.Language.Equiv.refl
variable {L} {M}
instance : Inhabited (M ≃[L] M) :=
⟨refl L M⟩
@[simp]
theorem refl_apply (x : M) : refl L M x = x := by simp [refl]; rfl
#align first_order.language.equiv.refl_apply FirstOrder.Language.Equiv.refl_apply
/-- Composition of first-order equivalences. -/
@[trans]
def comp (hnp : N ≃[L] P) (hmn : M ≃[L] N) : M ≃[L] P :=
{ hmn.toEquiv.trans hnp.toEquiv with
toFun := hnp ∘ hmn
-- Porting note: should be done by autoparam?
map_fun' := by intros; simp only [Function.comp_apply, map_fun]; trivial
-- Porting note: should be done by autoparam?
map_rel' := by intros; rw [Function.comp.assoc, map_rel, map_rel] }
#align first_order.language.equiv.comp FirstOrder.Language.Equiv.comp
@[simp]
theorem comp_apply (g : N ≃[L] P) (f : M ≃[L] N) (x : M) : g.comp f x = g (f x) :=
rfl
#align first_order.language.equiv.comp_apply FirstOrder.Language.Equiv.comp_apply
@[simp]
theorem comp_refl (g : M ≃[L] N) : g.comp (refl L M) = g :=
rfl
@[simp]
theorem refl_comp (g : M ≃[L] N) : (refl L N).comp g = g :=
rfl
@[simp]
theorem refl_toEmbedding : (refl L M).toEmbedding = Embedding.refl L M :=
rfl
@[simp]
theorem refl_toHom : (refl L M).toHom = Hom.id L M :=
rfl
/-- Composition of first-order homomorphisms is associative. -/
theorem comp_assoc (f : M ≃[L] N) (g : N ≃[L] P) (h : P ≃[L] Q) :
(h.comp g).comp f = h.comp (g.comp f) :=
rfl
#align first_order.language.equiv.comp_assoc FirstOrder.Language.Equiv.comp_assoc
theorem injective_comp (h : N ≃[L] P) :
Function.Injective (h.comp : (M ≃[L] N) → (M ≃[L] P)) := by
intro f g hfg
ext x; exact h.injective (congr_fun (congr_arg DFunLike.coe hfg) x)
@[simp]
theorem comp_toHom (hnp : N ≃[L] P) (hmn : M ≃[L] N) :
(hnp.comp hmn).toHom = hnp.toHom.comp hmn.toHom :=
rfl
@[simp]
theorem comp_toEmbedding (hnp : N ≃[L] P) (hmn : M ≃[L] N) :
(hnp.comp hmn).toEmbedding = hnp.toEmbedding.comp hmn.toEmbedding :=
rfl
@[simp]
theorem self_comp_symm (f : M ≃[L] N) : f.comp f.symm = refl L N := by
ext; rw [comp_apply, apply_symm_apply, refl_apply]
@[simp]
theorem symm_comp_self (f : M ≃[L] N) : f.symm.comp f = refl L M := by
ext; rw [comp_apply, symm_apply_apply, refl_apply]
@[simp]
theorem symm_comp_self_toEmbedding (f : M ≃[L] N) :
f.symm.toEmbedding.comp f.toEmbedding = Embedding.refl L M := by
rw [← comp_toEmbedding, symm_comp_self, refl_toEmbedding]
@[simp]
theorem self_comp_symm_toEmbedding (f : M ≃[L] N) :
f.toEmbedding.comp f.symm.toEmbedding = Embedding.refl L N := by
rw [← comp_toEmbedding, self_comp_symm, refl_toEmbedding]
@[simp]
theorem symm_comp_self_toHom (f : M ≃[L] N) :
f.symm.toHom.comp f.toHom = Hom.id L M := by
rw [← comp_toHom, symm_comp_self, refl_toHom]
@[simp]
theorem self_comp_symm_toHom (f : M ≃[L] N) :
f.toHom.comp f.symm.toHom = Hom.id L N := by
rw [← comp_toHom, self_comp_symm, refl_toHom]
@[simp]
theorem comp_symm (f : M ≃[L] N) (g : N ≃[L] P) : (g.comp f).symm = f.symm.comp g.symm :=
rfl
| Mathlib/ModelTheory/Basic.lean | 1,007 | 1,011 | theorem comp_right_injective (h : M ≃[L] N) :
Function.Injective (fun f ↦ f.comp h : (N ≃[L] P) → (M ≃[L] P)) := by |
intro f g hfg
convert (congr_arg (fun r : (M ≃[L] P) ↦ r.comp h.symm) hfg) <;>
rw [comp_assoc, self_comp_symm, comp_refl]
|
/-
Copyright (c) 2019 Gabriel Ebner. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Gabriel Ebner, Sébastien Gouëzel, Yury Kudryashov, Anatole Dedecker
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.FDeriv.Add
#align_import analysis.calculus.deriv.add from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# One-dimensional derivatives of sums etc
In this file we prove formulas about derivatives of `f + g`, `-f`, `f - g`, and `∑ i, f i x` for
functions from the base field to a normed space over this field.
For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of
`Analysis/Calculus/Deriv/Basic`.
## Keywords
derivative
-/
universe u v w
open scoped Classical
open Topology Filter ENNReal
open Filter Asymptotics Set
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 {f f₀ f₁ g : 𝕜 → F}
variable {f' f₀' f₁' g' : F}
variable {x : 𝕜}
variable {s t : Set 𝕜}
variable {L : Filter 𝕜}
section Add
/-! ### Derivative of the sum of two functions -/
nonrec theorem HasDerivAtFilter.add (hf : HasDerivAtFilter f f' x L)
(hg : HasDerivAtFilter g g' x L) : HasDerivAtFilter (fun y => f y + g y) (f' + g') x L := by
simpa using (hf.add hg).hasDerivAtFilter
#align has_deriv_at_filter.add HasDerivAtFilter.add
nonrec theorem HasStrictDerivAt.add (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) :
HasStrictDerivAt (fun y => f y + g y) (f' + g') x := by simpa using (hf.add hg).hasStrictDerivAt
#align has_strict_deriv_at.add HasStrictDerivAt.add
nonrec theorem HasDerivWithinAt.add (hf : HasDerivWithinAt f f' s x)
(hg : HasDerivWithinAt g g' s x) : HasDerivWithinAt (fun y => f y + g y) (f' + g') s x :=
hf.add hg
#align has_deriv_within_at.add HasDerivWithinAt.add
nonrec theorem HasDerivAt.add (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) :
HasDerivAt (fun x => f x + g x) (f' + g') x :=
hf.add hg
#align has_deriv_at.add HasDerivAt.add
theorem derivWithin_add (hxs : UniqueDiffWithinAt 𝕜 s x) (hf : DifferentiableWithinAt 𝕜 f s x)
(hg : DifferentiableWithinAt 𝕜 g s x) :
derivWithin (fun y => f y + g y) s x = derivWithin f s x + derivWithin g s x :=
(hf.hasDerivWithinAt.add hg.hasDerivWithinAt).derivWithin hxs
#align deriv_within_add derivWithin_add
@[simp]
theorem deriv_add (hf : DifferentiableAt 𝕜 f x) (hg : DifferentiableAt 𝕜 g x) :
deriv (fun y => f y + g y) x = deriv f x + deriv g x :=
(hf.hasDerivAt.add hg.hasDerivAt).deriv
#align deriv_add deriv_add
-- Porting note (#10756): new theorem
theorem HasStrictDerivAt.add_const (c : F) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y ↦ f y + c) f' x :=
add_zero f' ▸ hf.add (hasStrictDerivAt_const x c)
theorem HasDerivAtFilter.add_const (hf : HasDerivAtFilter f f' x L) (c : F) :
HasDerivAtFilter (fun y => f y + c) f' x L :=
add_zero f' ▸ hf.add (hasDerivAtFilter_const x L c)
#align has_deriv_at_filter.add_const HasDerivAtFilter.add_const
nonrec theorem HasDerivWithinAt.add_const (hf : HasDerivWithinAt f f' s x) (c : F) :
HasDerivWithinAt (fun y => f y + c) f' s x :=
hf.add_const c
#align has_deriv_within_at.add_const HasDerivWithinAt.add_const
nonrec theorem HasDerivAt.add_const (hf : HasDerivAt f f' x) (c : F) :
HasDerivAt (fun x => f x + c) f' x :=
hf.add_const c
#align has_deriv_at.add_const HasDerivAt.add_const
theorem derivWithin_add_const (hxs : UniqueDiffWithinAt 𝕜 s x) (c : F) :
derivWithin (fun y => f y + c) s x = derivWithin f s x := by
simp only [derivWithin, fderivWithin_add_const hxs]
#align deriv_within_add_const derivWithin_add_const
theorem deriv_add_const (c : F) : deriv (fun y => f y + c) x = deriv f x := by
simp only [deriv, fderiv_add_const]
#align deriv_add_const deriv_add_const
@[simp]
theorem deriv_add_const' (c : F) : (deriv fun y => f y + c) = deriv f :=
funext fun _ => deriv_add_const c
#align deriv_add_const' deriv_add_const'
-- Porting note (#10756): new theorem
theorem HasStrictDerivAt.const_add (c : F) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y ↦ c + f y) f' x :=
zero_add f' ▸ (hasStrictDerivAt_const x c).add hf
theorem HasDerivAtFilter.const_add (c : F) (hf : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun y => c + f y) f' x L :=
zero_add f' ▸ (hasDerivAtFilter_const x L c).add hf
#align has_deriv_at_filter.const_add HasDerivAtFilter.const_add
nonrec theorem HasDerivWithinAt.const_add (c : F) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c + f y) f' s x :=
hf.const_add c
#align has_deriv_within_at.const_add HasDerivWithinAt.const_add
nonrec theorem HasDerivAt.const_add (c : F) (hf : HasDerivAt f f' x) :
HasDerivAt (fun x => c + f x) f' x :=
hf.const_add c
#align has_deriv_at.const_add HasDerivAt.const_add
theorem derivWithin_const_add (hxs : UniqueDiffWithinAt 𝕜 s x) (c : F) :
derivWithin (fun y => c + f y) s x = derivWithin f s x := by
simp only [derivWithin, fderivWithin_const_add hxs]
#align deriv_within_const_add derivWithin_const_add
theorem deriv_const_add (c : F) : deriv (fun y => c + f y) x = deriv f x := by
simp only [deriv, fderiv_const_add]
#align deriv_const_add deriv_const_add
@[simp]
theorem deriv_const_add' (c : F) : (deriv fun y => c + f y) = deriv f :=
funext fun _ => deriv_const_add c
#align deriv_const_add' deriv_const_add'
end Add
section Sum
/-! ### Derivative of a finite sum of functions -/
variable {ι : Type*} {u : Finset ι} {A : ι → 𝕜 → F} {A' : ι → F}
theorem HasDerivAtFilter.sum (h : ∀ i ∈ u, HasDerivAtFilter (A i) (A' i) x L) :
HasDerivAtFilter (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x L := by
simpa [ContinuousLinearMap.sum_apply] using (HasFDerivAtFilter.sum h).hasDerivAtFilter
#align has_deriv_at_filter.sum HasDerivAtFilter.sum
theorem HasStrictDerivAt.sum (h : ∀ i ∈ u, HasStrictDerivAt (A i) (A' i) x) :
HasStrictDerivAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x := by
simpa [ContinuousLinearMap.sum_apply] using (HasStrictFDerivAt.sum h).hasStrictDerivAt
#align has_strict_deriv_at.sum HasStrictDerivAt.sum
theorem HasDerivWithinAt.sum (h : ∀ i ∈ u, HasDerivWithinAt (A i) (A' i) s x) :
HasDerivWithinAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) s x :=
HasDerivAtFilter.sum h
#align has_deriv_within_at.sum HasDerivWithinAt.sum
theorem HasDerivAt.sum (h : ∀ i ∈ u, HasDerivAt (A i) (A' i) x) :
HasDerivAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x :=
HasDerivAtFilter.sum h
#align has_deriv_at.sum HasDerivAt.sum
theorem derivWithin_sum (hxs : UniqueDiffWithinAt 𝕜 s x)
(h : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (A i) s x) :
derivWithin (fun y => ∑ i ∈ u, A i y) s x = ∑ i ∈ u, derivWithin (A i) s x :=
(HasDerivWithinAt.sum fun i hi => (h i hi).hasDerivWithinAt).derivWithin hxs
#align deriv_within_sum derivWithin_sum
@[simp]
theorem deriv_sum (h : ∀ i ∈ u, DifferentiableAt 𝕜 (A i) x) :
deriv (fun y => ∑ i ∈ u, A i y) x = ∑ i ∈ u, deriv (A i) x :=
(HasDerivAt.sum fun i hi => (h i hi).hasDerivAt).deriv
#align deriv_sum deriv_sum
end Sum
section Neg
/-! ### Derivative of the negative of a function -/
nonrec theorem HasDerivAtFilter.neg (h : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun x => -f x) (-f') x L := by simpa using h.neg.hasDerivAtFilter
#align has_deriv_at_filter.neg HasDerivAtFilter.neg
nonrec theorem HasDerivWithinAt.neg (h : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun x => -f x) (-f') s x :=
h.neg
#align has_deriv_within_at.neg HasDerivWithinAt.neg
nonrec theorem HasDerivAt.neg (h : HasDerivAt f f' x) : HasDerivAt (fun x => -f x) (-f') x :=
h.neg
#align has_deriv_at.neg HasDerivAt.neg
nonrec theorem HasStrictDerivAt.neg (h : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun x => -f x) (-f') x := by simpa using h.neg.hasStrictDerivAt
#align has_strict_deriv_at.neg HasStrictDerivAt.neg
theorem derivWithin.neg (hxs : UniqueDiffWithinAt 𝕜 s x) :
derivWithin (fun y => -f y) s x = -derivWithin f s x := by
simp only [derivWithin, fderivWithin_neg hxs, ContinuousLinearMap.neg_apply]
#align deriv_within.neg derivWithin.neg
theorem deriv.neg : deriv (fun y => -f y) x = -deriv f x := by
simp only [deriv, fderiv_neg, ContinuousLinearMap.neg_apply]
#align deriv.neg deriv.neg
@[simp]
theorem deriv.neg' : (deriv fun y => -f y) = fun x => -deriv f x :=
funext fun _ => deriv.neg
#align deriv.neg' deriv.neg'
end Neg
section Neg2
/-! ### Derivative of the negation function (i.e `Neg.neg`) -/
variable (s x L)
theorem hasDerivAtFilter_neg : HasDerivAtFilter Neg.neg (-1) x L :=
HasDerivAtFilter.neg <| hasDerivAtFilter_id _ _
#align has_deriv_at_filter_neg hasDerivAtFilter_neg
theorem hasDerivWithinAt_neg : HasDerivWithinAt Neg.neg (-1) s x :=
hasDerivAtFilter_neg _ _
#align has_deriv_within_at_neg hasDerivWithinAt_neg
theorem hasDerivAt_neg : HasDerivAt Neg.neg (-1) x :=
hasDerivAtFilter_neg _ _
#align has_deriv_at_neg hasDerivAt_neg
theorem hasDerivAt_neg' : HasDerivAt (fun x => -x) (-1) x :=
hasDerivAtFilter_neg _ _
#align has_deriv_at_neg' hasDerivAt_neg'
theorem hasStrictDerivAt_neg : HasStrictDerivAt Neg.neg (-1) x :=
HasStrictDerivAt.neg <| hasStrictDerivAt_id _
#align has_strict_deriv_at_neg hasStrictDerivAt_neg
theorem deriv_neg : deriv Neg.neg x = -1 :=
HasDerivAt.deriv (hasDerivAt_neg x)
#align deriv_neg deriv_neg
@[simp]
theorem deriv_neg' : deriv (Neg.neg : 𝕜 → 𝕜) = fun _ => -1 :=
funext deriv_neg
#align deriv_neg' deriv_neg'
@[simp]
theorem deriv_neg'' : deriv (fun x : 𝕜 => -x) x = -1 :=
deriv_neg x
#align deriv_neg'' deriv_neg''
theorem derivWithin_neg (hxs : UniqueDiffWithinAt 𝕜 s x) : derivWithin Neg.neg s x = -1 :=
(hasDerivWithinAt_neg x s).derivWithin hxs
#align deriv_within_neg derivWithin_neg
theorem differentiable_neg : Differentiable 𝕜 (Neg.neg : 𝕜 → 𝕜) :=
Differentiable.neg differentiable_id
#align differentiable_neg differentiable_neg
theorem differentiableOn_neg : DifferentiableOn 𝕜 (Neg.neg : 𝕜 → 𝕜) s :=
DifferentiableOn.neg differentiableOn_id
#align differentiable_on_neg differentiableOn_neg
| Mathlib/Analysis/Calculus/Deriv/Add.lean | 276 | 284 | theorem not_differentiableAt_abs_zero : ¬ DifferentiableAt ℝ (abs : ℝ → ℝ) 0 := by |
intro h
have h₁ : deriv abs (0 : ℝ) = 1 :=
(uniqueDiffOn_Ici _ _ Set.left_mem_Ici).eq_deriv _ h.hasDerivAt.hasDerivWithinAt <|
(hasDerivWithinAt_id _ _).congr_of_mem (fun _ h ↦ abs_of_nonneg h) Set.left_mem_Ici
have h₂ : deriv abs (0 : ℝ) = -1 :=
(uniqueDiffOn_Iic _ _ Set.right_mem_Iic).eq_deriv _ h.hasDerivAt.hasDerivWithinAt <|
(hasDerivWithinAt_neg _ _).congr_of_mem (fun _ h ↦ abs_of_nonpos h) Set.right_mem_Iic
linarith
|
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.Regular.Basic
import Mathlib.LinearAlgebra.Matrix.MvPolynomial
import Mathlib.LinearAlgebra.Matrix.Polynomial
import Mathlib.RingTheory.Polynomial.Basic
#align_import linear_algebra.matrix.adjugate from "leanprover-community/mathlib"@"a99f85220eaf38f14f94e04699943e185a5e1d1a"
/-!
# Cramer's rule and adjugate matrices
The adjugate matrix is the transpose of the cofactor matrix.
It is calculated with Cramer's rule, which we introduce first.
The vectors returned by Cramer's rule are given by the linear map `cramer`,
which sends a matrix `A` and vector `b` to the vector consisting of the
determinant of replacing the `i`th column of `A` with `b` at index `i`
(written as `(A.update_column i b).det`).
Using Cramer's rule, we can compute for each matrix `A` the matrix `adjugate A`.
The entries of the adjugate are the minors of `A`.
Instead of defining a minor by deleting row `i` and column `j` of `A`, we
replace the `i`th row of `A` with the `j`th basis vector; the resulting matrix
has the same determinant but more importantly equals Cramer's rule applied
to `A` and the `j`th basis vector, simplifying the subsequent proofs.
We prove the adjugate behaves like `det A • A⁻¹`.
## Main definitions
* `Matrix.cramer A b`: the vector output by Cramer's rule on `A` and `b`.
* `Matrix.adjugate A`: the adjugate (or classical adjoint) of the matrix `A`.
## References
* https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix
## Tags
cramer, cramer's rule, adjugate
-/
namespace Matrix
universe u v w
variable {m : Type u} {n : Type v} {α : Type w}
variable [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m] [CommRing α]
open Matrix Polynomial Equiv Equiv.Perm Finset
section Cramer
/-!
### `cramer` section
Introduce the linear map `cramer` with values defined by `cramerMap`.
After defining `cramerMap` and showing it is linear,
we will restrict our proofs to using `cramer`.
-/
variable (A : Matrix n n α) (b : n → α)
/-- `cramerMap A b i` is the determinant of the matrix `A` with column `i` replaced with `b`,
and thus `cramerMap A b` is the vector output by Cramer's rule on `A` and `b`.
If `A * x = b` has a unique solution in `x`, `cramerMap A` sends the vector `b` to `A.det • x`.
Otherwise, the outcome of `cramerMap` is well-defined but not necessarily useful.
-/
def cramerMap (i : n) : α :=
(A.updateColumn i b).det
#align matrix.cramer_map Matrix.cramerMap
theorem cramerMap_is_linear (i : n) : IsLinearMap α fun b => cramerMap A b i :=
{ map_add := det_updateColumn_add _ _
map_smul := det_updateColumn_smul _ _ }
#align matrix.cramer_map_is_linear Matrix.cramerMap_is_linear
theorem cramer_is_linear : IsLinearMap α (cramerMap A) := by
constructor <;> intros <;> ext i
· apply (cramerMap_is_linear A i).1
· apply (cramerMap_is_linear A i).2
#align matrix.cramer_is_linear Matrix.cramer_is_linear
/-- `cramer A b i` is the determinant of the matrix `A` with column `i` replaced with `b`,
and thus `cramer A b` is the vector output by Cramer's rule on `A` and `b`.
If `A * x = b` has a unique solution in `x`, `cramer A` sends the vector `b` to `A.det • x`.
Otherwise, the outcome of `cramer` is well-defined but not necessarily useful.
-/
def cramer (A : Matrix n n α) : (n → α) →ₗ[α] (n → α) :=
IsLinearMap.mk' (cramerMap A) (cramer_is_linear A)
#align matrix.cramer Matrix.cramer
theorem cramer_apply (i : n) : cramer A b i = (A.updateColumn i b).det :=
rfl
#align matrix.cramer_apply Matrix.cramer_apply
theorem cramer_transpose_apply (i : n) : cramer Aᵀ b i = (A.updateRow i b).det := by
rw [cramer_apply, updateColumn_transpose, det_transpose]
#align matrix.cramer_transpose_apply Matrix.cramer_transpose_apply
theorem cramer_transpose_row_self (i : n) : Aᵀ.cramer (A i) = Pi.single i A.det := by
ext j
rw [cramer_apply, Pi.single_apply]
split_ifs with h
· -- i = j: this entry should be `A.det`
subst h
simp only [updateColumn_transpose, det_transpose, updateRow_eq_self]
· -- i ≠ j: this entry should be 0
rw [updateColumn_transpose, det_transpose]
apply det_zero_of_row_eq h
rw [updateRow_self, updateRow_ne (Ne.symm h)]
#align matrix.cramer_transpose_row_self Matrix.cramer_transpose_row_self
theorem cramer_row_self (i : n) (h : ∀ j, b j = A j i) : A.cramer b = Pi.single i A.det := by
rw [← transpose_transpose A, det_transpose]
convert cramer_transpose_row_self Aᵀ i
exact funext h
#align matrix.cramer_row_self Matrix.cramer_row_self
@[simp]
theorem cramer_one : cramer (1 : Matrix n n α) = 1 := by
-- Porting note: was `ext i j`
refine LinearMap.pi_ext' (fun (i : n) => LinearMap.ext_ring (funext (fun (j : n) => ?_)))
convert congr_fun (cramer_row_self (1 : Matrix n n α) (Pi.single i 1) i _) j
· simp
· intro j
rw [Matrix.one_eq_pi_single, Pi.single_comm]
#align matrix.cramer_one Matrix.cramer_one
theorem cramer_smul (r : α) (A : Matrix n n α) :
cramer (r • A) = r ^ (Fintype.card n - 1) • cramer A :=
LinearMap.ext fun _ => funext fun _ => det_updateColumn_smul' _ _ _ _
#align matrix.cramer_smul Matrix.cramer_smul
@[simp]
theorem cramer_subsingleton_apply [Subsingleton n] (A : Matrix n n α) (b : n → α) (i : n) :
cramer A b i = b i := by rw [cramer_apply, det_eq_elem_of_subsingleton _ i, updateColumn_self]
#align matrix.cramer_subsingleton_apply Matrix.cramer_subsingleton_apply
theorem cramer_zero [Nontrivial n] : cramer (0 : Matrix n n α) = 0 := by
ext i j
obtain ⟨j', hj'⟩ : ∃ j', j' ≠ j := exists_ne j
apply det_eq_zero_of_column_eq_zero j'
intro j''
simp [updateColumn_ne hj']
#align matrix.cramer_zero Matrix.cramer_zero
/-- Use linearity of `cramer` to take it out of a summation. -/
theorem sum_cramer {β} (s : Finset β) (f : β → n → α) :
(∑ x ∈ s, cramer A (f x)) = cramer A (∑ x ∈ s, f x) :=
(map_sum (cramer A) ..).symm
#align matrix.sum_cramer Matrix.sum_cramer
/-- Use linearity of `cramer` and vector evaluation to take `cramer A _ i` out of a summation. -/
theorem sum_cramer_apply {β} (s : Finset β) (f : n → β → α) (i : n) :
(∑ x ∈ s, cramer A (fun j => f j x) i) = cramer A (fun j : n => ∑ x ∈ s, f j x) i :=
calc
(∑ x ∈ s, cramer A (fun j => f j x) i) = (∑ x ∈ s, cramer A fun j => f j x) i :=
(Finset.sum_apply i s _).symm
_ = cramer A (fun j : n => ∑ x ∈ s, f j x) i := by
rw [sum_cramer, cramer_apply, cramer_apply]
simp only [updateColumn]
congr with j
congr
apply Finset.sum_apply
#align matrix.sum_cramer_apply Matrix.sum_cramer_apply
theorem cramer_submatrix_equiv (A : Matrix m m α) (e : n ≃ m) (b : n → α) :
cramer (A.submatrix e e) b = cramer A (b ∘ e.symm) ∘ e := by
ext i
simp_rw [Function.comp_apply, cramer_apply, updateColumn_submatrix_equiv,
det_submatrix_equiv_self e, Function.comp]
#align matrix.cramer_submatrix_equiv Matrix.cramer_submatrix_equiv
theorem cramer_reindex (e : m ≃ n) (A : Matrix m m α) (b : n → α) :
cramer (reindex e e A) b = cramer A (b ∘ e) ∘ e.symm :=
cramer_submatrix_equiv _ _ _
#align matrix.cramer_reindex Matrix.cramer_reindex
end Cramer
section Adjugate
/-!
### `adjugate` section
Define the `adjugate` matrix and a few equations.
These will hold for any matrix over a commutative ring.
-/
/-- The adjugate matrix is the transpose of the cofactor matrix.
Typically, the cofactor matrix is defined by taking minors,
i.e. the determinant of the matrix with a row and column removed.
However, the proof of `mul_adjugate` becomes a lot easier if we use the
matrix replacing a column with a basis vector, since it allows us to use
facts about the `cramer` map.
-/
def adjugate (A : Matrix n n α) : Matrix n n α :=
of fun i => cramer Aᵀ (Pi.single i 1)
#align matrix.adjugate Matrix.adjugate
theorem adjugate_def (A : Matrix n n α) : adjugate A = of fun i => cramer Aᵀ (Pi.single i 1) :=
rfl
#align matrix.adjugate_def Matrix.adjugate_def
theorem adjugate_apply (A : Matrix n n α) (i j : n) :
adjugate A i j = (A.updateRow j (Pi.single i 1)).det := by
rw [adjugate_def, of_apply, cramer_apply, updateColumn_transpose, det_transpose]
#align matrix.adjugate_apply Matrix.adjugate_apply
theorem adjugate_transpose (A : Matrix n n α) : (adjugate A)ᵀ = adjugate Aᵀ := by
ext i j
rw [transpose_apply, adjugate_apply, adjugate_apply, updateRow_transpose, det_transpose]
rw [det_apply', det_apply']
apply Finset.sum_congr rfl
intro σ _
congr 1
by_cases h : i = σ j
· -- Everything except `(i , j)` (= `(σ j , j)`) is given by A, and the rest is a single `1`.
congr
ext j'
subst h
have : σ j' = σ j ↔ j' = j := σ.injective.eq_iff
rw [updateRow_apply, updateColumn_apply]
simp_rw [this]
rw [← dite_eq_ite, ← dite_eq_ite]
congr 1 with rfl
rw [Pi.single_eq_same, Pi.single_eq_same]
· -- Otherwise, we need to show that there is a `0` somewhere in the product.
have : (∏ j' : n, updateColumn A j (Pi.single i 1) (σ j') j') = 0 := by
apply prod_eq_zero (mem_univ j)
rw [updateColumn_self, Pi.single_eq_of_ne' h]
rw [this]
apply prod_eq_zero (mem_univ (σ⁻¹ i))
erw [apply_symm_apply σ i, updateRow_self]
apply Pi.single_eq_of_ne
intro h'
exact h ((symm_apply_eq σ).mp h')
#align matrix.adjugate_transpose Matrix.adjugate_transpose
@[simp]
theorem adjugate_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m α) :
adjugate (A.submatrix e e) = (adjugate A).submatrix e e := by
ext i j
rw [adjugate_apply, submatrix_apply, adjugate_apply, ← det_submatrix_equiv_self e,
updateRow_submatrix_equiv]
-- Porting note: added
suffices (fun j => Pi.single i 1 (e.symm j)) = Pi.single (e i) 1 by
erw [this]
exact Function.update_comp_equiv _ e.symm _ _
#align matrix.adjugate_submatrix_equiv_self Matrix.adjugate_submatrix_equiv_self
theorem adjugate_reindex (e : m ≃ n) (A : Matrix m m α) :
adjugate (reindex e e A) = reindex e e (adjugate A) :=
adjugate_submatrix_equiv_self _ _
#align matrix.adjugate_reindex Matrix.adjugate_reindex
/-- Since the map `b ↦ cramer A b` is linear in `b`, it must be multiplication by some matrix. This
matrix is `A.adjugate`. -/
theorem cramer_eq_adjugate_mulVec (A : Matrix n n α) (b : n → α) :
cramer A b = A.adjugate *ᵥ b := by
nth_rw 2 [← A.transpose_transpose]
rw [← adjugate_transpose, adjugate_def]
have : b = ∑ i, b i • (Pi.single i 1 : n → α) := by
refine (pi_eq_sum_univ b).trans ?_
congr with j
-- Porting note: needed to help `Pi.smul_apply`
simp [Pi.single_apply, eq_comm, Pi.smul_apply (b j)]
conv_lhs =>
rw [this]
ext k
simp [mulVec, dotProduct, mul_comm]
#align matrix.cramer_eq_adjugate_mul_vec Matrix.cramer_eq_adjugate_mulVec
| Mathlib/LinearAlgebra/Matrix/Adjugate.lean | 282 | 285 | theorem mul_adjugate_apply (A : Matrix n n α) (i j k) :
A i k * adjugate A k j = cramer Aᵀ (Pi.single k (A i k)) j := by |
erw [← smul_eq_mul, adjugate, of_apply, ← Pi.smul_apply, ← LinearMap.map_smul, ← Pi.single_smul',
smul_eq_mul, mul_one]
|
/-
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.Map
#align_import linear_algebra.basic from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Kernel of a linear map
This file defines the kernel of a linear map.
## Main definitions
* `LinearMap.ker`: the kernel of a linear map as a submodule of the domain
## Notations
* We continue to use the notations `M →ₛₗ[σ] M₂` and `M →ₗ[R] M₂` for the type of semilinear
(resp. linear) maps from `M` to `M₂` over the ring homomorphism `σ` (resp. over the ring `R`).
## Tags
linear algebra, vector space, module
-/
open Function
open Pointwise
variable {R : Type*} {R₁ : Type*} {R₂ : Type*} {R₃ : Type*}
variable {K : Type*}
variable {M : Type*} {M₁ : Type*} {M₂ : Type*} {M₃ : Type*}
variable {V : Type*} {V₂ : Type*}
/-! ### Properties of linear maps -/
namespace LinearMap
section AddCommMonoid
variable [Semiring R] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃}
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable [Module R M] [Module R₂ M₂] [Module R₃ M₃]
open Submodule
variable {σ₂₁ : R₂ →+* R} {τ₁₂ : R →+* R₂} {τ₂₃ : R₂ →+* R₃} {τ₁₃ : R →+* R₃}
variable [RingHomCompTriple τ₁₂ τ₂₃ τ₁₃]
variable {F : Type*} [FunLike F M M₂] [SemilinearMapClass F τ₁₂ M M₂]
/-- The kernel of a linear map `f : M → M₂` is defined to be `comap f ⊥`. This is equivalent to the
set of `x : M` such that `f x = 0`. The kernel is a submodule of `M`. -/
def ker (f : F) : Submodule R M :=
comap f ⊥
#align linear_map.ker LinearMap.ker
@[simp]
theorem mem_ker {f : F} {y} : y ∈ ker f ↔ f y = 0 :=
mem_bot R₂
#align linear_map.mem_ker LinearMap.mem_ker
@[simp]
theorem ker_id : ker (LinearMap.id : M →ₗ[R] M) = ⊥ :=
rfl
#align linear_map.ker_id LinearMap.ker_id
@[simp]
theorem map_coe_ker (f : F) (x : ker f) : f x = 0 :=
mem_ker.1 x.2
#align linear_map.map_coe_ker LinearMap.map_coe_ker
theorem ker_toAddSubmonoid (f : M →ₛₗ[τ₁₂] M₂) : f.ker.toAddSubmonoid = (AddMonoidHom.mker f) :=
rfl
#align linear_map.ker_to_add_submonoid LinearMap.ker_toAddSubmonoid
theorem comp_ker_subtype (f : M →ₛₗ[τ₁₂] M₂) : f.comp f.ker.subtype = 0 :=
LinearMap.ext fun x => mem_ker.1 x.2
#align linear_map.comp_ker_subtype LinearMap.comp_ker_subtype
theorem ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker (g.comp f : M →ₛₗ[τ₁₃] M₃) = comap f (ker g) :=
rfl
#align linear_map.ker_comp LinearMap.ker_comp
theorem ker_le_ker_comp (f : M →ₛₗ[τ₁₂] M₂) (g : M₂ →ₛₗ[τ₂₃] M₃) :
ker f ≤ ker (g.comp f : M →ₛₗ[τ₁₃] M₃) := by rw [ker_comp]; exact comap_mono bot_le
#align linear_map.ker_le_ker_comp LinearMap.ker_le_ker_comp
theorem ker_sup_ker_le_ker_comp_of_commute {f g : M →ₗ[R] M} (h : Commute f g) :
ker f ⊔ ker g ≤ ker (f ∘ₗ g) := by
refine sup_le_iff.mpr ⟨?_, ker_le_ker_comp g f⟩
rw [← mul_eq_comp, h.eq, mul_eq_comp]
exact ker_le_ker_comp f g
@[simp]
theorem ker_le_comap {p : Submodule R₂ M₂} (f : M →ₛₗ[τ₁₂] M₂) :
ker f ≤ p.comap f :=
fun x hx ↦ by simp [mem_ker.mp hx]
theorem disjoint_ker {f : F} {p : Submodule R M} :
Disjoint p (ker f) ↔ ∀ x ∈ p, f x = 0 → x = 0 := by
simp [disjoint_def]
#align linear_map.disjoint_ker LinearMap.disjoint_ker
| Mathlib/Algebra/Module/Submodule/Ker.lean | 112 | 113 | theorem ker_eq_bot' {f : F} : ker f = ⊥ ↔ ∀ m, f m = 0 → m = 0 := by |
simpa [disjoint_iff_inf_le] using disjoint_ker (f := f) (p := ⊤)
|
/-
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.GroupWithZero.Divisibility
import Mathlib.Algebra.MonoidAlgebra.Basic
import Mathlib.Data.Finset.Sort
#align_import data.polynomial.basic from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Theory of univariate polynomials
This file defines `Polynomial R`, the type of univariate polynomials over the semiring `R`, builds
a semiring structure on it, and gives basic definitions that are expanded in other files in this
directory.
## Main definitions
* `monomial n a` is the polynomial `a X^n`. Note that `monomial n` is defined as an `R`-linear map.
* `C a` is the constant polynomial `a`. Note that `C` is defined as a ring homomorphism.
* `X` is the polynomial `X`, i.e., `monomial 1 1`.
* `p.sum f` is `∑ n ∈ p.support, f n (p.coeff n)`, i.e., one sums the values of functions applied
to coefficients of the polynomial `p`.
* `p.erase n` is the polynomial `p` in which one removes the `c X^n` term.
There are often two natural variants of lemmas involving sums, depending on whether one acts on the
polynomials, or on the function. The naming convention is that one adds `index` when acting on
the polynomials. For instance,
* `sum_add_index` states that `(p + q).sum f = p.sum f + q.sum f`;
* `sum_add` states that `p.sum (fun n x ↦ f n x + g n x) = p.sum f + p.sum g`.
* Notation to refer to `Polynomial R`, as `R[X]` or `R[t]`.
## Implementation
Polynomials are defined using `R[ℕ]`, where `R` is a semiring.
The variable `X` commutes with every polynomial `p`: lemma `X_mul` proves the identity
`X * p = p * X`. The relationship to `R[ℕ]` is through a structure
to make polynomials irreducible from the point of view of the kernel. Most operations
are irreducible since Lean can not compute anyway with `AddMonoidAlgebra`. There are two
exceptions that we make semireducible:
* The zero polynomial, so that its coefficients are definitionally equal to `0`.
* The scalar action, to permit typeclass search to unfold it to resolve potential instance
diamonds.
The raw implementation of the equivalence between `R[X]` and `R[ℕ]` is
done through `ofFinsupp` and `toFinsupp` (or, equivalently, `rcases p` when `p` is a polynomial
gives an element `q` of `R[ℕ]`, and conversely `⟨q⟩` gives back `p`). The
equivalence is also registered as a ring equiv in `Polynomial.toFinsuppIso`. These should
in general not be used once the basic API for polynomials is constructed.
-/
set_option linter.uppercaseLean3 false
noncomputable section
/-- `Polynomial R` is the type of univariate polynomials over `R`.
Polynomials should be seen as (semi-)rings with the additional constructor `X`.
The embedding from `R` is called `C`. -/
structure Polynomial (R : Type*) [Semiring R] where ofFinsupp ::
toFinsupp : AddMonoidAlgebra R ℕ
#align polynomial Polynomial
#align polynomial.of_finsupp Polynomial.ofFinsupp
#align polynomial.to_finsupp Polynomial.toFinsupp
@[inherit_doc] scoped[Polynomial] notation:9000 R "[X]" => Polynomial R
open AddMonoidAlgebra
open Finsupp hiding single
open Function hiding Commute
open Polynomial
namespace Polynomial
universe u
variable {R : Type u} {a b : R} {m n : ℕ}
section Semiring
variable [Semiring R] {p q : R[X]}
theorem forall_iff_forall_finsupp (P : R[X] → Prop) :
(∀ p, P p) ↔ ∀ q : R[ℕ], P ⟨q⟩ :=
⟨fun h q => h ⟨q⟩, fun h ⟨p⟩ => h p⟩
#align polynomial.forall_iff_forall_finsupp Polynomial.forall_iff_forall_finsupp
theorem exists_iff_exists_finsupp (P : R[X] → Prop) :
(∃ p, P p) ↔ ∃ q : R[ℕ], P ⟨q⟩ :=
⟨fun ⟨⟨p⟩, hp⟩ => ⟨p, hp⟩, fun ⟨q, hq⟩ => ⟨⟨q⟩, hq⟩⟩
#align polynomial.exists_iff_exists_finsupp Polynomial.exists_iff_exists_finsupp
@[simp]
theorem eta (f : R[X]) : Polynomial.ofFinsupp f.toFinsupp = f := by cases f; rfl
#align polynomial.eta Polynomial.eta
/-! ### Conversions to and from `AddMonoidAlgebra`
Since `R[X]` is not defeq to `R[ℕ]`, but instead is a structure wrapping
it, we have to copy across all the arithmetic operators manually, along with the lemmas about how
they unfold around `Polynomial.ofFinsupp` and `Polynomial.toFinsupp`.
-/
section AddMonoidAlgebra
private irreducible_def add : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a + b⟩
private irreducible_def neg {R : Type u} [Ring R] : R[X] → R[X]
| ⟨a⟩ => ⟨-a⟩
private irreducible_def mul : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a * b⟩
instance zero : Zero R[X] :=
⟨⟨0⟩⟩
#align polynomial.has_zero Polynomial.zero
instance one : One R[X] :=
⟨⟨1⟩⟩
#align polynomial.one Polynomial.one
instance add' : Add R[X] :=
⟨add⟩
#align polynomial.has_add Polynomial.add'
instance neg' {R : Type u} [Ring R] : Neg R[X] :=
⟨neg⟩
#align polynomial.has_neg Polynomial.neg'
instance sub {R : Type u} [Ring R] : Sub R[X] :=
⟨fun a b => a + -b⟩
#align polynomial.has_sub Polynomial.sub
instance mul' : Mul R[X] :=
⟨mul⟩
#align polynomial.has_mul Polynomial.mul'
-- If the private definitions are accidentally exposed, simplify them away.
@[simp] theorem add_eq_add : add p q = p + q := rfl
@[simp] theorem mul_eq_mul : mul p q = p * q := rfl
instance smulZeroClass {S : Type*} [SMulZeroClass S R] : SMulZeroClass S R[X] where
smul r p := ⟨r • p.toFinsupp⟩
smul_zero a := congr_arg ofFinsupp (smul_zero a)
#align polynomial.smul_zero_class Polynomial.smulZeroClass
-- to avoid a bug in the `ring` tactic
instance (priority := 1) pow : Pow R[X] ℕ where pow p n := npowRec n p
#align polynomial.has_pow Polynomial.pow
@[simp]
theorem ofFinsupp_zero : (⟨0⟩ : R[X]) = 0 :=
rfl
#align polynomial.of_finsupp_zero Polynomial.ofFinsupp_zero
@[simp]
theorem ofFinsupp_one : (⟨1⟩ : R[X]) = 1 :=
rfl
#align polynomial.of_finsupp_one Polynomial.ofFinsupp_one
@[simp]
theorem ofFinsupp_add {a b} : (⟨a + b⟩ : R[X]) = ⟨a⟩ + ⟨b⟩ :=
show _ = add _ _ by rw [add_def]
#align polynomial.of_finsupp_add Polynomial.ofFinsupp_add
@[simp]
theorem ofFinsupp_neg {R : Type u} [Ring R] {a} : (⟨-a⟩ : R[X]) = -⟨a⟩ :=
show _ = neg _ by rw [neg_def]
#align polynomial.of_finsupp_neg Polynomial.ofFinsupp_neg
@[simp]
theorem ofFinsupp_sub {R : Type u} [Ring R] {a b} : (⟨a - b⟩ : R[X]) = ⟨a⟩ - ⟨b⟩ := by
rw [sub_eq_add_neg, ofFinsupp_add, ofFinsupp_neg]
rfl
#align polynomial.of_finsupp_sub Polynomial.ofFinsupp_sub
@[simp]
theorem ofFinsupp_mul (a b) : (⟨a * b⟩ : R[X]) = ⟨a⟩ * ⟨b⟩ :=
show _ = mul _ _ by rw [mul_def]
#align polynomial.of_finsupp_mul Polynomial.ofFinsupp_mul
@[simp]
theorem ofFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b) :
(⟨a • b⟩ : R[X]) = (a • ⟨b⟩ : R[X]) :=
rfl
#align polynomial.of_finsupp_smul Polynomial.ofFinsupp_smul
@[simp]
theorem ofFinsupp_pow (a) (n : ℕ) : (⟨a ^ n⟩ : R[X]) = ⟨a⟩ ^ n := by
change _ = npowRec n _
induction n with
| zero => simp [npowRec]
| succ n n_ih => simp [npowRec, n_ih, pow_succ]
#align polynomial.of_finsupp_pow Polynomial.ofFinsupp_pow
@[simp]
theorem toFinsupp_zero : (0 : R[X]).toFinsupp = 0 :=
rfl
#align polynomial.to_finsupp_zero Polynomial.toFinsupp_zero
@[simp]
theorem toFinsupp_one : (1 : R[X]).toFinsupp = 1 :=
rfl
#align polynomial.to_finsupp_one Polynomial.toFinsupp_one
@[simp]
theorem toFinsupp_add (a b : R[X]) : (a + b).toFinsupp = a.toFinsupp + b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_add]
#align polynomial.to_finsupp_add Polynomial.toFinsupp_add
@[simp]
theorem toFinsupp_neg {R : Type u} [Ring R] (a : R[X]) : (-a).toFinsupp = -a.toFinsupp := by
cases a
rw [← ofFinsupp_neg]
#align polynomial.to_finsupp_neg Polynomial.toFinsupp_neg
@[simp]
theorem toFinsupp_sub {R : Type u} [Ring R] (a b : R[X]) :
(a - b).toFinsupp = a.toFinsupp - b.toFinsupp := by
rw [sub_eq_add_neg, ← toFinsupp_neg, ← toFinsupp_add]
rfl
#align polynomial.to_finsupp_sub Polynomial.toFinsupp_sub
@[simp]
theorem toFinsupp_mul (a b : R[X]) : (a * b).toFinsupp = a.toFinsupp * b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_mul]
#align polynomial.to_finsupp_mul Polynomial.toFinsupp_mul
@[simp]
theorem toFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b : R[X]) :
(a • b).toFinsupp = a • b.toFinsupp :=
rfl
#align polynomial.to_finsupp_smul Polynomial.toFinsupp_smul
@[simp]
theorem toFinsupp_pow (a : R[X]) (n : ℕ) : (a ^ n).toFinsupp = a.toFinsupp ^ n := by
cases a
rw [← ofFinsupp_pow]
#align polynomial.to_finsupp_pow Polynomial.toFinsupp_pow
theorem _root_.IsSMulRegular.polynomial {S : Type*} [Monoid S] [DistribMulAction S R] {a : S}
(ha : IsSMulRegular R a) : IsSMulRegular R[X] a
| ⟨_x⟩, ⟨_y⟩, h => congr_arg _ <| ha.finsupp (Polynomial.ofFinsupp.inj h)
#align is_smul_regular.polynomial IsSMulRegular.polynomial
theorem toFinsupp_injective : Function.Injective (toFinsupp : R[X] → AddMonoidAlgebra _ _) :=
fun ⟨_x⟩ ⟨_y⟩ => congr_arg _
#align polynomial.to_finsupp_injective Polynomial.toFinsupp_injective
@[simp]
theorem toFinsupp_inj {a b : R[X]} : a.toFinsupp = b.toFinsupp ↔ a = b :=
toFinsupp_injective.eq_iff
#align polynomial.to_finsupp_inj Polynomial.toFinsupp_inj
@[simp]
theorem toFinsupp_eq_zero {a : R[X]} : a.toFinsupp = 0 ↔ a = 0 := by
rw [← toFinsupp_zero, toFinsupp_inj]
#align polynomial.to_finsupp_eq_zero Polynomial.toFinsupp_eq_zero
@[simp]
theorem toFinsupp_eq_one {a : R[X]} : a.toFinsupp = 1 ↔ a = 1 := by
rw [← toFinsupp_one, toFinsupp_inj]
#align polynomial.to_finsupp_eq_one Polynomial.toFinsupp_eq_one
/-- A more convenient spelling of `Polynomial.ofFinsupp.injEq` in terms of `Iff`. -/
theorem ofFinsupp_inj {a b} : (⟨a⟩ : R[X]) = ⟨b⟩ ↔ a = b :=
iff_of_eq (ofFinsupp.injEq _ _)
#align polynomial.of_finsupp_inj Polynomial.ofFinsupp_inj
@[simp]
theorem ofFinsupp_eq_zero {a} : (⟨a⟩ : R[X]) = 0 ↔ a = 0 := by
rw [← ofFinsupp_zero, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_zero Polynomial.ofFinsupp_eq_zero
@[simp]
theorem ofFinsupp_eq_one {a} : (⟨a⟩ : R[X]) = 1 ↔ a = 1 := by rw [← ofFinsupp_one, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_one Polynomial.ofFinsupp_eq_one
instance inhabited : Inhabited R[X] :=
⟨0⟩
#align polynomial.inhabited Polynomial.inhabited
instance instNatCast : NatCast R[X] where natCast n := ofFinsupp n
#align polynomial.has_nat_cast Polynomial.instNatCast
instance semiring : Semiring R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.semiring toFinsupp toFinsupp_injective toFinsupp_zero toFinsupp_one
toFinsupp_add toFinsupp_mul (fun _ _ => toFinsupp_smul _ _) toFinsupp_pow fun _ => rfl with
toAdd := Polynomial.add'
toMul := Polynomial.mul'
toZero := Polynomial.zero
toOne := Polynomial.one
nsmul := (· • ·)
npow := fun n x => (x ^ n) }
#align polynomial.semiring Polynomial.semiring
instance distribSMul {S} [DistribSMul S R] : DistribSMul S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribSMul ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toSMulZeroClass := Polynomial.smulZeroClass }
#align polynomial.distrib_smul Polynomial.distribSMul
instance distribMulAction {S} [Monoid S] [DistribMulAction S R] : DistribMulAction S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribMulAction ⟨⟨toFinsupp, toFinsupp_zero (R := R)⟩, toFinsupp_add⟩
toFinsupp_injective toFinsupp_smul with
toSMul := Polynomial.smulZeroClass.toSMul }
#align polynomial.distrib_mul_action Polynomial.distribMulAction
instance faithfulSMul {S} [SMulZeroClass S R] [FaithfulSMul S R] : FaithfulSMul S R[X] where
eq_of_smul_eq_smul {_s₁ _s₂} h :=
eq_of_smul_eq_smul fun a : ℕ →₀ R => congr_arg toFinsupp (h ⟨a⟩)
#align polynomial.has_faithful_smul Polynomial.faithfulSMul
instance module {S} [Semiring S] [Module S R] : Module S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.module _ ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toDistribMulAction := Polynomial.distribMulAction }
#align polynomial.module Polynomial.module
instance smulCommClass {S₁ S₂} [SMulZeroClass S₁ R] [SMulZeroClass S₂ R] [SMulCommClass S₁ S₂ R] :
SMulCommClass S₁ S₂ R[X] :=
⟨by
rintro m n ⟨f⟩
simp_rw [← ofFinsupp_smul, smul_comm m n f]⟩
#align polynomial.smul_comm_class Polynomial.smulCommClass
instance isScalarTower {S₁ S₂} [SMul S₁ S₂] [SMulZeroClass S₁ R] [SMulZeroClass S₂ R]
[IsScalarTower S₁ S₂ R] : IsScalarTower S₁ S₂ R[X] :=
⟨by
rintro _ _ ⟨⟩
simp_rw [← ofFinsupp_smul, smul_assoc]⟩
#align polynomial.is_scalar_tower Polynomial.isScalarTower
instance isScalarTower_right {α K : Type*} [Semiring K] [DistribSMul α K] [IsScalarTower α K K] :
IsScalarTower α K[X] K[X] :=
⟨by
rintro _ ⟨⟩ ⟨⟩;
simp_rw [smul_eq_mul, ← ofFinsupp_smul, ← ofFinsupp_mul, ← ofFinsupp_smul, smul_mul_assoc]⟩
#align polynomial.is_scalar_tower_right Polynomial.isScalarTower_right
instance isCentralScalar {S} [SMulZeroClass S R] [SMulZeroClass Sᵐᵒᵖ R] [IsCentralScalar S R] :
IsCentralScalar S R[X] :=
⟨by
rintro _ ⟨⟩
simp_rw [← ofFinsupp_smul, op_smul_eq_smul]⟩
#align polynomial.is_central_scalar Polynomial.isCentralScalar
instance unique [Subsingleton R] : Unique R[X] :=
{ Polynomial.inhabited with
uniq := by
rintro ⟨x⟩
apply congr_arg ofFinsupp
simp [eq_iff_true_of_subsingleton] }
#align polynomial.unique Polynomial.unique
variable (R)
/-- Ring isomorphism between `R[X]` and `R[ℕ]`. This is just an
implementation detail, but it can be useful to transfer results from `Finsupp` to polynomials. -/
@[simps apply symm_apply]
def toFinsuppIso : R[X] ≃+* R[ℕ] where
toFun := toFinsupp
invFun := ofFinsupp
left_inv := fun ⟨_p⟩ => rfl
right_inv _p := rfl
map_mul' := toFinsupp_mul
map_add' := toFinsupp_add
#align polynomial.to_finsupp_iso Polynomial.toFinsuppIso
#align polynomial.to_finsupp_iso_apply Polynomial.toFinsuppIso_apply
#align polynomial.to_finsupp_iso_symm_apply Polynomial.toFinsuppIso_symm_apply
instance [DecidableEq R] : DecidableEq R[X] :=
@Equiv.decidableEq R[X] _ (toFinsuppIso R).toEquiv (Finsupp.instDecidableEq)
end AddMonoidAlgebra
theorem ofFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[ℕ]) :
(⟨∑ i ∈ s, f i⟩ : R[X]) = ∑ i ∈ s, ⟨f i⟩ :=
map_sum (toFinsuppIso R).symm f s
#align polynomial.of_finsupp_sum Polynomial.ofFinsupp_sum
theorem toFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[X]) :
(∑ i ∈ s, f i : R[X]).toFinsupp = ∑ i ∈ s, (f i).toFinsupp :=
map_sum (toFinsuppIso R) f s
#align polynomial.to_finsupp_sum Polynomial.toFinsupp_sum
/-- The set of all `n` such that `X^n` has a non-zero coefficient.
-/
-- @[simp] -- Porting note: The original generated theorem is same to `support_ofFinsupp` and
-- the new generated theorem is different, so this attribute should be
-- removed.
def support : R[X] → Finset ℕ
| ⟨p⟩ => p.support
#align polynomial.support Polynomial.support
@[simp]
theorem support_ofFinsupp (p) : support (⟨p⟩ : R[X]) = p.support := by rw [support]
#align polynomial.support_of_finsupp Polynomial.support_ofFinsupp
theorem support_toFinsupp (p : R[X]) : p.toFinsupp.support = p.support := by rw [support]
@[simp]
theorem support_zero : (0 : R[X]).support = ∅ :=
rfl
#align polynomial.support_zero Polynomial.support_zero
@[simp]
theorem support_eq_empty : p.support = ∅ ↔ p = 0 := by
rcases p with ⟨⟩
simp [support]
#align polynomial.support_eq_empty Polynomial.support_eq_empty
@[simp] lemma support_nonempty : p.support.Nonempty ↔ p ≠ 0 :=
Finset.nonempty_iff_ne_empty.trans support_eq_empty.not
theorem card_support_eq_zero : p.support.card = 0 ↔ p = 0 := by simp
#align polynomial.card_support_eq_zero Polynomial.card_support_eq_zero
/-- `monomial s a` is the monomial `a * X^s` -/
def monomial (n : ℕ) : R →ₗ[R] R[X] where
toFun t := ⟨Finsupp.single n t⟩
-- porting note (#10745): was `simp`.
map_add' x y := by simp; rw [ofFinsupp_add]
-- porting note (#10745): was `simp [← ofFinsupp_smul]`.
map_smul' r x := by simp; rw [← ofFinsupp_smul, smul_single']
#align polynomial.monomial Polynomial.monomial
@[simp]
theorem toFinsupp_monomial (n : ℕ) (r : R) : (monomial n r).toFinsupp = Finsupp.single n r := by
simp [monomial]
#align polynomial.to_finsupp_monomial Polynomial.toFinsupp_monomial
@[simp]
theorem ofFinsupp_single (n : ℕ) (r : R) : (⟨Finsupp.single n r⟩ : R[X]) = monomial n r := by
simp [monomial]
#align polynomial.of_finsupp_single Polynomial.ofFinsupp_single
-- @[simp] -- Porting note (#10618): simp can prove this
theorem monomial_zero_right (n : ℕ) : monomial n (0 : R) = 0 :=
(monomial n).map_zero
#align polynomial.monomial_zero_right Polynomial.monomial_zero_right
-- This is not a `simp` lemma as `monomial_zero_left` is more general.
theorem monomial_zero_one : monomial 0 (1 : R) = 1 :=
rfl
#align polynomial.monomial_zero_one Polynomial.monomial_zero_one
-- TODO: can't we just delete this one?
theorem monomial_add (n : ℕ) (r s : R) : monomial n (r + s) = monomial n r + monomial n s :=
(monomial n).map_add _ _
#align polynomial.monomial_add Polynomial.monomial_add
theorem monomial_mul_monomial (n m : ℕ) (r s : R) :
monomial n r * monomial m s = monomial (n + m) (r * s) :=
toFinsupp_injective <| by
simp only [toFinsupp_monomial, toFinsupp_mul, AddMonoidAlgebra.single_mul_single]
#align polynomial.monomial_mul_monomial Polynomial.monomial_mul_monomial
@[simp]
theorem monomial_pow (n : ℕ) (r : R) (k : ℕ) : monomial n r ^ k = monomial (n * k) (r ^ k) := by
induction' k with k ih
· simp [pow_zero, monomial_zero_one]
· simp [pow_succ, ih, monomial_mul_monomial, Nat.succ_eq_add_one, mul_add, add_comm]
#align polynomial.monomial_pow Polynomial.monomial_pow
theorem smul_monomial {S} [SMulZeroClass S R] (a : S) (n : ℕ) (b : R) :
a • monomial n b = monomial n (a • b) :=
toFinsupp_injective <| by simp; rw [smul_single]
#align polynomial.smul_monomial Polynomial.smul_monomial
theorem monomial_injective (n : ℕ) : Function.Injective (monomial n : R → R[X]) :=
(toFinsuppIso R).symm.injective.comp (single_injective n)
#align polynomial.monomial_injective Polynomial.monomial_injective
@[simp]
theorem monomial_eq_zero_iff (t : R) (n : ℕ) : monomial n t = 0 ↔ t = 0 :=
LinearMap.map_eq_zero_iff _ (Polynomial.monomial_injective n)
#align polynomial.monomial_eq_zero_iff Polynomial.monomial_eq_zero_iff
theorem support_add : (p + q).support ⊆ p.support ∪ q.support := by
simpa [support] using Finsupp.support_add
#align polynomial.support_add Polynomial.support_add
/-- `C a` is the constant polynomial `a`.
`C` is provided as a ring homomorphism.
-/
def C : R →+* R[X] :=
{ monomial 0 with
map_one' := by simp [monomial_zero_one]
map_mul' := by simp [monomial_mul_monomial]
map_zero' := by simp }
#align polynomial.C Polynomial.C
@[simp]
theorem monomial_zero_left (a : R) : monomial 0 a = C a :=
rfl
#align polynomial.monomial_zero_left Polynomial.monomial_zero_left
@[simp]
theorem toFinsupp_C (a : R) : (C a).toFinsupp = single 0 a :=
rfl
#align polynomial.to_finsupp_C Polynomial.toFinsupp_C
theorem C_0 : C (0 : R) = 0 := by simp
#align polynomial.C_0 Polynomial.C_0
theorem C_1 : C (1 : R) = 1 :=
rfl
#align polynomial.C_1 Polynomial.C_1
theorem C_mul : C (a * b) = C a * C b :=
C.map_mul a b
#align polynomial.C_mul Polynomial.C_mul
theorem C_add : C (a + b) = C a + C b :=
C.map_add a b
#align polynomial.C_add Polynomial.C_add
@[simp]
theorem smul_C {S} [SMulZeroClass S R] (s : S) (r : R) : s • C r = C (s • r) :=
smul_monomial _ _ r
#align polynomial.smul_C Polynomial.smul_C
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit0 : C (bit0 a) = bit0 (C a) :=
C_add
#align polynomial.C_bit0 Polynomial.C_bit0
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit1 : C (bit1 a) = bit1 (C a) := by simp [bit1, C_bit0]
#align polynomial.C_bit1 Polynomial.C_bit1
theorem C_pow : C (a ^ n) = C a ^ n :=
C.map_pow a n
#align polynomial.C_pow Polynomial.C_pow
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_eq_natCast (n : ℕ) : C (n : R) = (n : R[X]) :=
map_natCast C n
#align polynomial.C_eq_nat_cast Polynomial.C_eq_natCast
@[deprecated (since := "2024-04-17")]
alias C_eq_nat_cast := C_eq_natCast
@[simp]
theorem C_mul_monomial : C a * monomial n b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, zero_add]
#align polynomial.C_mul_monomial Polynomial.C_mul_monomial
@[simp]
theorem monomial_mul_C : monomial n a * C b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, add_zero]
#align polynomial.monomial_mul_C Polynomial.monomial_mul_C
/-- `X` is the polynomial variable (aka indeterminate). -/
def X : R[X] :=
monomial 1 1
#align polynomial.X Polynomial.X
theorem monomial_one_one_eq_X : monomial 1 (1 : R) = X :=
rfl
#align polynomial.monomial_one_one_eq_X Polynomial.monomial_one_one_eq_X
theorem monomial_one_right_eq_X_pow (n : ℕ) : monomial n (1 : R) = X ^ n := by
induction' n with n ih
· simp [monomial_zero_one]
· rw [pow_succ, ← ih, ← monomial_one_one_eq_X, monomial_mul_monomial, mul_one]
#align polynomial.monomial_one_right_eq_X_pow Polynomial.monomial_one_right_eq_X_pow
@[simp]
theorem toFinsupp_X : X.toFinsupp = Finsupp.single 1 (1 : R) :=
rfl
#align polynomial.to_finsupp_X Polynomial.toFinsupp_X
/-- `X` commutes with everything, even when the coefficients are noncommutative. -/
| Mathlib/Algebra/Polynomial/Basic.lean | 592 | 598 | theorem X_mul : X * p = p * X := by |
rcases p with ⟨⟩
-- Porting note: `ofFinsupp.injEq` is required.
simp only [X, ← ofFinsupp_single, ← ofFinsupp_mul, LinearMap.coe_mk, ofFinsupp.injEq]
-- Porting note: Was `ext`.
refine Finsupp.ext fun _ => ?_
simp [AddMonoidAlgebra.mul_apply, AddMonoidAlgebra.sum_single_index, add_comm]
|
/-
Copyright (c) 2020 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel, Alex Keizer
-/
import Mathlib.Data.List.GetD
import Mathlib.Data.Nat.Bits
import Mathlib.Algebra.Ring.Nat
import Mathlib.Order.Basic
import Mathlib.Tactic.AdaptationNote
import Mathlib.Tactic.Common
#align_import data.nat.bitwise from "leanprover-community/mathlib"@"6afc9b06856ad973f6a2619e3e8a0a8d537a58f2"
/-!
# Bitwise operations on natural numbers
In the first half of this file, we provide theorems for reasoning about natural numbers from their
bitwise properties. In the second half of this file, we show properties of the bitwise operations
`lor`, `land` and `xor`, which are defined in core.
## Main results
* `eq_of_testBit_eq`: two natural numbers are equal if they have equal bits at every position.
* `exists_most_significant_bit`: if `n ≠ 0`, then there is some position `i` that contains the most
significant `1`-bit of `n`.
* `lt_of_testBit`: if `n` and `m` are numbers and `i` is a position such that the `i`-th bit of
of `n` is zero, the `i`-th bit of `m` is one, and all more significant bits are equal, then
`n < m`.
## Future work
There is another way to express bitwise properties of natural number: `digits 2`. The two ways
should be connected.
## Keywords
bitwise, and, or, xor
-/
open Function
namespace Nat
set_option linter.deprecated false
section
variable {f : Bool → Bool → Bool}
@[simp]
lemma bitwise_zero_left (m : Nat) : bitwise f 0 m = if f false true then m else 0 := by
simp [bitwise]
#align nat.bitwise_zero_left Nat.bitwise_zero_left
@[simp]
lemma bitwise_zero_right (n : Nat) : bitwise f n 0 = if f true false then n else 0 := by
unfold bitwise
simp only [ite_self, decide_False, Nat.zero_div, ite_true, ite_eq_right_iff]
rintro ⟨⟩
split_ifs <;> rfl
#align nat.bitwise_zero_right Nat.bitwise_zero_right
lemma bitwise_zero : bitwise f 0 0 = 0 := by
simp only [bitwise_zero_right, ite_self]
#align nat.bitwise_zero Nat.bitwise_zero
lemma bitwise_of_ne_zero {n m : Nat} (hn : n ≠ 0) (hm : m ≠ 0) :
bitwise f n m = bit (f (bodd n) (bodd m)) (bitwise f (n / 2) (m / 2)) := by
conv_lhs => unfold bitwise
have mod_two_iff_bod x : (x % 2 = 1 : Bool) = bodd x := by
simp only [mod_two_of_bodd, cond]; cases bodd x <;> rfl
simp only [hn, hm, mod_two_iff_bod, ite_false, bit, bit1, bit0, Bool.cond_eq_ite]
split_ifs <;> rfl
theorem binaryRec_of_ne_zero {C : Nat → Sort*} (z : C 0) (f : ∀ b n, C n → C (bit b n)) {n}
(h : n ≠ 0) :
binaryRec z f n = bit_decomp n ▸ f (bodd n) (div2 n) (binaryRec z f (div2 n)) := by
rw [Eq.rec_eq_cast]
rw [binaryRec]
dsimp only
rw [dif_neg h, eq_mpr_eq_cast]
@[simp]
lemma bitwise_bit {f : Bool → Bool → Bool} (h : f false false = false := by rfl) (a m b n) :
bitwise f (bit a m) (bit b n) = bit (f a b) (bitwise f m n) := by
conv_lhs => unfold bitwise
#adaptation_note /-- nightly-2024-03-16: simp was
-- simp (config := { unfoldPartialApp := true }) only [bit, bit1, bit0, Bool.cond_eq_ite] -/
simp only [bit, ite_apply, bit1, bit0, Bool.cond_eq_ite]
have h1 x : (x + x) % 2 = 0 := by rw [← two_mul, mul_comm]; apply mul_mod_left
have h2 x : (x + x + 1) % 2 = 1 := by rw [← two_mul, add_comm]; apply add_mul_mod_self_left
have h3 x : (x + x) / 2 = x := by omega
have h4 x : (x + x + 1) / 2 = x := by rw [← two_mul, add_comm]; simp [add_mul_div_left]
cases a <;> cases b <;> simp [h1, h2, h3, h4] <;> split_ifs
<;> simp_all (config := {decide := true})
#align nat.bitwise_bit Nat.bitwise_bit
lemma bit_mod_two (a : Bool) (x : ℕ) :
bit a x % 2 = if a then 1 else 0 := by
#adaptation_note /-- nightly-2024-03-16: simp was
-- simp (config := { unfoldPartialApp := true }) only [bit, bit1, bit0, ← mul_two,
-- Bool.cond_eq_ite] -/
simp only [bit, ite_apply, bit1, bit0, ← mul_two, Bool.cond_eq_ite]
split_ifs <;> simp [Nat.add_mod]
@[simp]
lemma bit_mod_two_eq_zero_iff (a x) :
bit a x % 2 = 0 ↔ !a := by
rw [bit_mod_two]; split_ifs <;> simp_all
@[simp]
lemma bit_mod_two_eq_one_iff (a x) :
bit a x % 2 = 1 ↔ a := by
rw [bit_mod_two]; split_ifs <;> simp_all
@[simp]
theorem lor_bit : ∀ a m b n, bit a m ||| bit b n = bit (a || b) (m ||| n) :=
bitwise_bit
#align nat.lor_bit Nat.lor_bit
@[simp]
theorem land_bit : ∀ a m b n, bit a m &&& bit b n = bit (a && b) (m &&& n) :=
bitwise_bit
#align nat.land_bit Nat.land_bit
@[simp]
theorem ldiff_bit : ∀ a m b n, ldiff (bit a m) (bit b n) = bit (a && not b) (ldiff m n) :=
bitwise_bit
#align nat.ldiff_bit Nat.ldiff_bit
@[simp]
theorem xor_bit : ∀ a m b n, bit a m ^^^ bit b n = bit (bne a b) (m ^^^ n) :=
bitwise_bit
#align nat.lxor_bit Nat.xor_bit
attribute [simp] Nat.testBit_bitwise
#align nat.test_bit_bitwise Nat.testBit_bitwise
theorem testBit_lor : ∀ m n k, testBit (m ||| n) k = (testBit m k || testBit n k) :=
testBit_bitwise rfl
#align nat.test_bit_lor Nat.testBit_lor
theorem testBit_land : ∀ m n k, testBit (m &&& n) k = (testBit m k && testBit n k) :=
testBit_bitwise rfl
#align nat.test_bit_land Nat.testBit_land
@[simp]
theorem testBit_ldiff : ∀ m n k, testBit (ldiff m n) k = (testBit m k && not (testBit n k)) :=
testBit_bitwise rfl
#align nat.test_bit_ldiff Nat.testBit_ldiff
attribute [simp] testBit_xor
#align nat.test_bit_lxor Nat.testBit_xor
end
@[simp]
theorem bit_false : bit false = bit0 :=
rfl
#align nat.bit_ff Nat.bit_false
@[simp]
theorem bit_true : bit true = bit1 :=
rfl
#align nat.bit_tt Nat.bit_true
@[simp]
theorem bit_eq_zero {n : ℕ} {b : Bool} : n.bit b = 0 ↔ n = 0 ∧ b = false := by
cases b <;> simp [Nat.bit0_eq_zero, Nat.bit1_ne_zero]
#align nat.bit_eq_zero Nat.bit_eq_zero
theorem bit_ne_zero_iff {n : ℕ} {b : Bool} : n.bit b ≠ 0 ↔ n = 0 → b = true := by
simpa only [not_and, Bool.not_eq_false] using (@bit_eq_zero n b).not
/-- An alternative for `bitwise_bit` which replaces the `f false false = false` assumption
with assumptions that neither `bit a m` nor `bit b n` are `0`
(albeit, phrased as the implications `m = 0 → a = true` and `n = 0 → b = true`) -/
lemma bitwise_bit' {f : Bool → Bool → Bool} (a : Bool) (m : Nat) (b : Bool) (n : Nat)
(ham : m = 0 → a = true) (hbn : n = 0 → b = true) :
bitwise f (bit a m) (bit b n) = bit (f a b) (bitwise f m n) := by
conv_lhs => unfold bitwise
rw [← bit_ne_zero_iff] at ham hbn
simp only [ham, hbn, bit_mod_two_eq_one_iff, Bool.decide_coe, ← div2_val, div2_bit, ne_eq,
ite_false]
conv_rhs => simp only [bit, bit1, bit0, Bool.cond_eq_ite]
split_ifs with hf <;> rfl
lemma bitwise_eq_binaryRec (f : Bool → Bool → Bool) :
bitwise f =
binaryRec (fun n => cond (f false true) n 0) fun a m Ia =>
binaryRec (cond (f true false) (bit a m) 0) fun b n _ => bit (f a b) (Ia n) := by
funext x y
induction x using binaryRec' generalizing y with
| z => simp only [bitwise_zero_left, binaryRec_zero, Bool.cond_eq_ite]
| f xb x hxb ih =>
rw [← bit_ne_zero_iff] at hxb
simp_rw [binaryRec_of_ne_zero _ _ hxb, bodd_bit, div2_bit, eq_rec_constant]
induction y using binaryRec' with
| z => simp only [bitwise_zero_right, binaryRec_zero, Bool.cond_eq_ite]
| f yb y hyb =>
rw [← bit_ne_zero_iff] at hyb
simp_rw [binaryRec_of_ne_zero _ _ hyb, bitwise_of_ne_zero hxb hyb, bodd_bit, ← div2_val,
div2_bit, eq_rec_constant, ih]
theorem zero_of_testBit_eq_false {n : ℕ} (h : ∀ i, testBit n i = false) : n = 0 := by
induction' n using Nat.binaryRec with b n hn
· rfl
· have : b = false := by simpa using h 0
rw [this, bit_false, bit0_val, hn fun i => by rw [← h (i + 1), testBit_bit_succ], mul_zero]
#align nat.zero_of_test_bit_eq_ff Nat.zero_of_testBit_eq_false
theorem testBit_eq_false_of_lt {n i} (h : n < 2 ^ i) : n.testBit i = false := by
simp [testBit, shiftRight_eq_div_pow, Nat.div_eq_of_lt h]
#align nat.zero_test_bit Nat.zero_testBit
/-- The ith bit is the ith element of `n.bits`. -/
theorem testBit_eq_inth (n i : ℕ) : n.testBit i = n.bits.getI i := by
induction' i with i ih generalizing n
· simp only [testBit, zero_eq, shiftRight_zero, one_and_eq_mod_two, mod_two_of_bodd,
bodd_eq_bits_head, List.getI_zero_eq_headI]
cases List.headI (bits n) <;> rfl
conv_lhs => rw [← bit_decomp n]
rw [testBit_bit_succ, ih n.div2, div2_bits_eq_tail]
cases n.bits <;> simp
#align nat.test_bit_eq_inth Nat.testBit_eq_inth
#align nat.eq_of_test_bit_eq Nat.eq_of_testBit_eq
theorem exists_most_significant_bit {n : ℕ} (h : n ≠ 0) :
∃ i, testBit n i = true ∧ ∀ j, i < j → testBit n j = false := by
induction' n using Nat.binaryRec with b n hn
· exact False.elim (h rfl)
by_cases h' : n = 0
· subst h'
rw [show b = true by
revert h
cases b <;> simp]
refine ⟨0, ⟨by rw [testBit_bit_zero], fun j hj => ?_⟩⟩
obtain ⟨j', rfl⟩ := exists_eq_succ_of_ne_zero (ne_of_gt hj)
rw [testBit_bit_succ, zero_testBit]
· obtain ⟨k, ⟨hk, hk'⟩⟩ := hn h'
refine ⟨k + 1, ⟨by rw [testBit_bit_succ, hk], fun j hj => ?_⟩⟩
obtain ⟨j', rfl⟩ := exists_eq_succ_of_ne_zero (show j ≠ 0 by intro x; subst x; simp at hj)
exact (testBit_bit_succ _ _ _).trans (hk' _ (lt_of_succ_lt_succ hj))
#align nat.exists_most_significant_bit Nat.exists_most_significant_bit
theorem lt_of_testBit {n m : ℕ} (i : ℕ) (hn : testBit n i = false) (hm : testBit m i = true)
(hnm : ∀ j, i < j → testBit n j = testBit m j) : n < m := by
induction' n using Nat.binaryRec with b n hn' generalizing i m
· rw [Nat.pos_iff_ne_zero]
rintro rfl
simp at hm
induction' m using Nat.binaryRec with b' m hm' generalizing i
· exact False.elim (Bool.false_ne_true ((zero_testBit i).symm.trans hm))
by_cases hi : i = 0
· subst hi
simp only [testBit_bit_zero] at hn hm
have : n = m :=
eq_of_testBit_eq fun i => by convert hnm (i + 1) (Nat.zero_lt_succ _) using 1
<;> rw [testBit_bit_succ]
rw [hn, hm, this, bit_false, bit_true, bit0_val, bit1_val]
exact Nat.lt_succ_self _
· obtain ⟨i', rfl⟩ := exists_eq_succ_of_ne_zero hi
simp only [testBit_bit_succ] at hn hm
have := hn' _ hn hm fun j hj => by
convert hnm j.succ (succ_lt_succ hj) using 1 <;> rw [testBit_bit_succ]
have this' : 2 * n < 2 * m := Nat.mul_lt_mul' (le_refl _) this Nat.two_pos
cases b <;> cases b'
<;> simp only [bit_false, bit_true, bit0_val n, bit1_val n, bit0_val m, bit1_val m]
· exact this'
· exact Nat.lt_add_right 1 this'
· calc
2 * n + 1 < 2 * n + 2 := lt.base _
_ ≤ 2 * m := mul_le_mul_left 2 this
· exact Nat.succ_lt_succ this'
#align nat.lt_of_test_bit Nat.lt_of_testBit
@[simp]
theorem testBit_two_pow_self (n : ℕ) : testBit (2 ^ n) n = true := by
rw [testBit, shiftRight_eq_div_pow, Nat.div_self (Nat.pow_pos Nat.zero_lt_two)]
simp
#align nat.test_bit_two_pow_self Nat.testBit_two_pow_self
theorem testBit_two_pow_of_ne {n m : ℕ} (hm : n ≠ m) : testBit (2 ^ n) m = false := by
rw [testBit, shiftRight_eq_div_pow]
cases' hm.lt_or_lt with hm hm
· rw [Nat.div_eq_of_lt]
· simp
· exact Nat.pow_lt_pow_right Nat.one_lt_two hm
· rw [Nat.pow_div hm.le Nat.two_pos, ← Nat.sub_add_cancel (succ_le_of_lt <| Nat.sub_pos_of_lt hm)]
-- Porting note: XXX why does this make it work?
rw [(rfl : succ 0 = 1)]
simp [pow_succ, and_one_is_mod, mul_mod_left]
#align nat.test_bit_two_pow_of_ne Nat.testBit_two_pow_of_ne
theorem testBit_two_pow (n m : ℕ) : testBit (2 ^ n) m = (n = m) := by
by_cases h : n = m
· cases h
simp
· rw [testBit_two_pow_of_ne h]
simp [h]
#align nat.test_bit_two_pow Nat.testBit_two_pow
theorem bitwise_swap {f : Bool → Bool → Bool} :
bitwise (Function.swap f) = Function.swap (bitwise f) := by
funext m n
simp only [Function.swap]
induction' m using Nat.strongInductionOn with m ih generalizing n
cases' m with m
<;> cases' n with n
<;> try rw [bitwise_zero_left, bitwise_zero_right]
· specialize ih ((m+1) / 2) (div_lt_self' ..)
simp [bitwise_of_ne_zero, ih]
#align nat.bitwise_swap Nat.bitwise_swap
/-- If `f` is a commutative operation on bools such that `f false false = false`, then `bitwise f`
is also commutative. -/
theorem bitwise_comm {f : Bool → Bool → Bool} (hf : ∀ b b', f b b' = f b' b) (n m : ℕ) :
bitwise f n m = bitwise f m n :=
suffices bitwise f = swap (bitwise f) by conv_lhs => rw [this]
calc
bitwise f = bitwise (swap f) := congr_arg _ <| funext fun _ => funext <| hf _
_ = swap (bitwise f) := bitwise_swap
#align nat.bitwise_comm Nat.bitwise_comm
theorem lor_comm (n m : ℕ) : n ||| m = m ||| n :=
bitwise_comm Bool.or_comm n m
#align nat.lor_comm Nat.lor_comm
theorem land_comm (n m : ℕ) : n &&& m = m &&& n :=
bitwise_comm Bool.and_comm n m
#align nat.land_comm Nat.land_comm
protected lemma xor_comm (n m : ℕ) : n ^^^ m = m ^^^ n :=
bitwise_comm (Bool.bne_eq_xor ▸ Bool.xor_comm) n m
#align nat.lxor_comm Nat.xor_comm
lemma and_two_pow (n i : ℕ) : n &&& 2 ^ i = (n.testBit i).toNat * 2 ^ i := by
refine eq_of_testBit_eq fun j => ?_
obtain rfl | hij := Decidable.eq_or_ne i j <;> cases' h : n.testBit i
· simp [h]
· simp [h]
· simp [h, testBit_two_pow_of_ne hij]
· simp [h, testBit_two_pow_of_ne hij]
lemma two_pow_and (n i : ℕ) : 2 ^ i &&& n = 2 ^ i * (n.testBit i).toNat := by
rw [mul_comm, land_comm, and_two_pow]
@[simp]
theorem zero_xor (n : ℕ) : 0 ^^^ n = n := by simp [HXor.hXor, Xor.xor, xor]
#align nat.zero_lxor Nat.zero_xor
@[simp]
theorem xor_zero (n : ℕ) : n ^^^ 0 = n := by simp [HXor.hXor, Xor.xor, xor]
#align nat.lxor_zero Nat.xor_zero
#align nat.zero_land Nat.zero_and
#align nat.land_zero Nat.and_zero
#align nat.zero_lor Nat.zero_or
#align nat.lor_zero Nat.or_zero
/-- Proving associativity of bitwise operations in general essentially boils down to a huge case
distinction, so it is shorter to use this tactic instead of proving it in the general case. -/
macro "bitwise_assoc_tac" : tactic => set_option hygiene false in `(tactic| (
induction' n using Nat.binaryRec with b n hn generalizing m k
· simp
induction' m using Nat.binaryRec with b' m hm
· simp
induction' k using Nat.binaryRec with b'' k hk
-- porting note (#10745): was `simp [hn]`
-- This is necessary because these are simp lemmas in mathlib
<;> simp [hn, Bool.or_assoc, Bool.and_assoc, Bool.bne_eq_xor]))
protected lemma xor_assoc (n m k : ℕ) : (n ^^^ m) ^^^ k = n ^^^ (m ^^^ k) := by bitwise_assoc_tac
#align nat.lxor_assoc Nat.xor_assoc
theorem land_assoc (n m k : ℕ) : (n &&& m) &&& k = n &&& (m &&& k) := by bitwise_assoc_tac
#align nat.land_assoc Nat.land_assoc
theorem lor_assoc (n m k : ℕ) : (n ||| m) ||| k = n ||| (m ||| k) := by bitwise_assoc_tac
#align nat.lor_assoc Nat.lor_assoc
@[simp]
theorem xor_self (n : ℕ) : n ^^^ n = 0 :=
zero_of_testBit_eq_false fun i => by simp
#align nat.lxor_self Nat.xor_self
-- These lemmas match `mul_inv_cancel_right` and `mul_inv_cancel_left`.
theorem xor_cancel_right (n m : ℕ) : (m ^^^ n) ^^^ n = m := by
rw [Nat.xor_assoc, xor_self, xor_zero]
#align nat.lxor_cancel_right Nat.xor_cancel_right
| Mathlib/Data/Nat/Bitwise.lean | 395 | 396 | theorem xor_cancel_left (n m : ℕ) : n ^^^ (n ^^^ m) = m := by |
rw [← Nat.xor_assoc, xor_self, zero_xor]
|
/-
Copyright (c) 2022 Rémi Bottinelli. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémi Bottinelli, Junyan Xu
-/
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.CategoryTheory.Groupoid.VertexGroup
import Mathlib.CategoryTheory.Groupoid.Basic
import Mathlib.CategoryTheory.Groupoid
import Mathlib.Data.Set.Lattice
import Mathlib.Order.GaloisConnection
#align_import category_theory.groupoid.subgroupoid from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Subgroupoid
This file defines subgroupoids as `structure`s containing the subsets of arrows and their
stability under composition and inversion.
Also defined are:
* containment of subgroupoids is a complete lattice;
* images and preimages of subgroupoids under a functor;
* the notion of normality of subgroupoids and its stability under intersection and preimage;
* compatibility of the above with `CategoryTheory.Groupoid.vertexGroup`.
## Main definitions
Given a type `C` with associated `groupoid C` instance.
* `CategoryTheory.Subgroupoid C` is the type of subgroupoids of `C`
* `CategoryTheory.Subgroupoid.IsNormal` is the property that the subgroupoid is stable under
conjugation by arbitrary arrows, _and_ that all identity arrows are contained in the subgroupoid.
* `CategoryTheory.Subgroupoid.comap` is the "preimage" map of subgroupoids along a functor.
* `CategoryTheory.Subgroupoid.map` is the "image" map of subgroupoids along a functor _injective on
objects_.
* `CategoryTheory.Subgroupoid.vertexSubgroup` is the subgroup of the `vertex group` at a given
vertex `v`, assuming `v` is contained in the `CategoryTheory.Subgroupoid` (meaning, by definition,
that the arrow `𝟙 v` is contained in the subgroupoid).
## Implementation details
The structure of this file is copied from/inspired by `Mathlib/GroupTheory/Subgroup/Basic.lean`
and `Mathlib/Combinatorics/SimpleGraph/Subgraph.lean`.
## TODO
* Equivalent inductive characterization of generated (normal) subgroupoids.
* Characterization of normal subgroupoids as kernels.
* Prove that `CategoryTheory.Subgroupoid.full` and `CategoryTheory.Subgroupoid.disconnect` preserve
intersections (and `CategoryTheory.Subgroupoid.disconnect` also unions)
## Tags
category theory, groupoid, subgroupoid
-/
namespace CategoryTheory
open Set Groupoid
universe u v
variable {C : Type u} [Groupoid C]
/-- A sugroupoid of `C` consists of a choice of arrows for each pair of vertices, closed
under composition and inverses.
-/
@[ext]
structure Subgroupoid (C : Type u) [Groupoid C] where
arrows : ∀ c d : C, Set (c ⟶ d)
protected inv : ∀ {c d} {p : c ⟶ d}, p ∈ arrows c d → Groupoid.inv p ∈ arrows d c
protected mul : ∀ {c d e} {p}, p ∈ arrows c d → ∀ {q}, q ∈ arrows d e → p ≫ q ∈ arrows c e
#align category_theory.subgroupoid CategoryTheory.Subgroupoid
namespace Subgroupoid
variable (S : Subgroupoid C)
theorem inv_mem_iff {c d : C} (f : c ⟶ d) :
Groupoid.inv f ∈ S.arrows d c ↔ f ∈ S.arrows c d := by
constructor
· intro h
simpa only [inv_eq_inv, IsIso.inv_inv] using S.inv h
· apply S.inv
#align category_theory.subgroupoid.inv_mem_iff CategoryTheory.Subgroupoid.inv_mem_iff
theorem mul_mem_cancel_left {c d e : C} {f : c ⟶ d} {g : d ⟶ e} (hf : f ∈ S.arrows c d) :
f ≫ g ∈ S.arrows c e ↔ g ∈ S.arrows d e := by
constructor
· rintro h
suffices Groupoid.inv f ≫ f ≫ g ∈ S.arrows d e by
simpa only [inv_eq_inv, IsIso.inv_hom_id_assoc] using this
apply S.mul (S.inv hf) h
· apply S.mul hf
#align category_theory.subgroupoid.mul_mem_cancel_left CategoryTheory.Subgroupoid.mul_mem_cancel_left
theorem mul_mem_cancel_right {c d e : C} {f : c ⟶ d} {g : d ⟶ e} (hg : g ∈ S.arrows d e) :
f ≫ g ∈ S.arrows c e ↔ f ∈ S.arrows c d := by
constructor
· rintro h
suffices (f ≫ g) ≫ Groupoid.inv g ∈ S.arrows c d by
simpa only [inv_eq_inv, IsIso.hom_inv_id, Category.comp_id, Category.assoc] using this
apply S.mul h (S.inv hg)
· exact fun hf => S.mul hf hg
#align category_theory.subgroupoid.mul_mem_cancel_right CategoryTheory.Subgroupoid.mul_mem_cancel_right
/-- The vertices of `C` on which `S` has non-trivial isotropy -/
def objs : Set C :=
{c : C | (S.arrows c c).Nonempty}
#align category_theory.subgroupoid.objs CategoryTheory.Subgroupoid.objs
theorem mem_objs_of_src {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : c ∈ S.objs :=
⟨f ≫ Groupoid.inv f, S.mul h (S.inv h)⟩
#align category_theory.subgroupoid.mem_objs_of_src CategoryTheory.Subgroupoid.mem_objs_of_src
theorem mem_objs_of_tgt {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : d ∈ S.objs :=
⟨Groupoid.inv f ≫ f, S.mul (S.inv h) h⟩
#align category_theory.subgroupoid.mem_objs_of_tgt CategoryTheory.Subgroupoid.mem_objs_of_tgt
theorem id_mem_of_nonempty_isotropy (c : C) : c ∈ objs S → 𝟙 c ∈ S.arrows c c := by
rintro ⟨γ, hγ⟩
convert S.mul hγ (S.inv hγ)
simp only [inv_eq_inv, IsIso.hom_inv_id]
#align category_theory.subgroupoid.id_mem_of_nonempty_isotropy CategoryTheory.Subgroupoid.id_mem_of_nonempty_isotropy
theorem id_mem_of_src {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : 𝟙 c ∈ S.arrows c c :=
id_mem_of_nonempty_isotropy S c (mem_objs_of_src S h)
#align category_theory.subgroupoid.id_mem_of_src CategoryTheory.Subgroupoid.id_mem_of_src
theorem id_mem_of_tgt {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : 𝟙 d ∈ S.arrows d d :=
id_mem_of_nonempty_isotropy S d (mem_objs_of_tgt S h)
#align category_theory.subgroupoid.id_mem_of_tgt CategoryTheory.Subgroupoid.id_mem_of_tgt
/-- A subgroupoid seen as a quiver on vertex set `C` -/
def asWideQuiver : Quiver C :=
⟨fun c d => Subtype <| S.arrows c d⟩
#align category_theory.subgroupoid.as_wide_quiver CategoryTheory.Subgroupoid.asWideQuiver
/-- The coercion of a subgroupoid as a groupoid -/
@[simps comp_coe, simps (config := .lemmasOnly) inv_coe]
instance coe : Groupoid S.objs where
Hom a b := S.arrows a.val b.val
id a := ⟨𝟙 a.val, id_mem_of_nonempty_isotropy S a.val a.prop⟩
comp p q := ⟨p.val ≫ q.val, S.mul p.prop q.prop⟩
inv p := ⟨Groupoid.inv p.val, S.inv p.prop⟩
#align category_theory.subgroupoid.coe CategoryTheory.Subgroupoid.coe
@[simp]
theorem coe_inv_coe' {c d : S.objs} (p : c ⟶ d) :
(CategoryTheory.inv p).val = CategoryTheory.inv p.val := by
simp only [← inv_eq_inv, coe_inv_coe]
#align category_theory.subgroupoid.coe_inv_coe' CategoryTheory.Subgroupoid.coe_inv_coe'
/-- The embedding of the coerced subgroupoid to its parent-/
def hom : S.objs ⥤ C where
obj c := c.val
map f := f.val
map_id _ := rfl
map_comp _ _ := rfl
#align category_theory.subgroupoid.hom CategoryTheory.Subgroupoid.hom
theorem hom.inj_on_objects : Function.Injective (hom S).obj := by
rintro ⟨c, hc⟩ ⟨d, hd⟩ hcd
simp only [Subtype.mk_eq_mk]; exact hcd
#align category_theory.subgroupoid.hom.inj_on_objects CategoryTheory.Subgroupoid.hom.inj_on_objects
theorem hom.faithful : ∀ c d, Function.Injective fun f : c ⟶ d => (hom S).map f := by
rintro ⟨c, hc⟩ ⟨d, hd⟩ ⟨f, hf⟩ ⟨g, hg⟩ hfg; exact Subtype.eq hfg
#align category_theory.subgroupoid.hom.faithful CategoryTheory.Subgroupoid.hom.faithful
/-- The subgroup of the vertex group at `c` given by the subgroupoid -/
def vertexSubgroup {c : C} (hc : c ∈ S.objs) : Subgroup (c ⟶ c) where
carrier := S.arrows c c
mul_mem' hf hg := S.mul hf hg
one_mem' := id_mem_of_nonempty_isotropy _ _ hc
inv_mem' hf := S.inv hf
#align category_theory.subgroupoid.vertex_subgroup CategoryTheory.Subgroupoid.vertexSubgroup
/-- The set of all arrows of a subgroupoid, as a set in `Σ c d : C, c ⟶ d`. -/
@[coe] def toSet (S : Subgroupoid C) : Set (Σ c d : C, c ⟶ d) :=
{F | F.2.2 ∈ S.arrows F.1 F.2.1}
instance : SetLike (Subgroupoid C) (Σ c d : C, c ⟶ d) where
coe := toSet
coe_injective' := fun ⟨S, _, _⟩ ⟨T, _, _⟩ h => by ext c d f; apply Set.ext_iff.1 h ⟨c, d, f⟩
theorem mem_iff (S : Subgroupoid C) (F : Σ c d, c ⟶ d) : F ∈ S ↔ F.2.2 ∈ S.arrows F.1 F.2.1 :=
Iff.rfl
#align category_theory.subgroupoid.mem_iff CategoryTheory.Subgroupoid.mem_iff
theorem le_iff (S T : Subgroupoid C) : S ≤ T ↔ ∀ {c d}, S.arrows c d ⊆ T.arrows c d := by
rw [SetLike.le_def, Sigma.forall]; exact forall_congr' fun c => Sigma.forall
#align category_theory.subgroupoid.le_iff CategoryTheory.Subgroupoid.le_iff
instance : Top (Subgroupoid C) :=
⟨{ arrows := fun _ _ => Set.univ
mul := by intros; trivial
inv := by intros; trivial }⟩
theorem mem_top {c d : C} (f : c ⟶ d) : f ∈ (⊤ : Subgroupoid C).arrows c d :=
trivial
#align category_theory.subgroupoid.mem_top CategoryTheory.Subgroupoid.mem_top
theorem mem_top_objs (c : C) : c ∈ (⊤ : Subgroupoid C).objs := by
dsimp [Top.top, objs]
simp only [univ_nonempty]
#align category_theory.subgroupoid.mem_top_objs CategoryTheory.Subgroupoid.mem_top_objs
instance : Bot (Subgroupoid C) :=
⟨{ arrows := fun _ _ => ∅
mul := False.elim
inv := False.elim }⟩
instance : Inhabited (Subgroupoid C) :=
⟨⊤⟩
instance : Inf (Subgroupoid C) :=
⟨fun S T =>
{ arrows := fun c d => S.arrows c d ∩ T.arrows c d
inv := fun hp ↦ ⟨S.inv hp.1, T.inv hp.2⟩
mul := fun hp _ hq ↦ ⟨S.mul hp.1 hq.1, T.mul hp.2 hq.2⟩ }⟩
instance : InfSet (Subgroupoid C) :=
⟨fun s =>
{ arrows := fun c d => ⋂ S ∈ s, Subgroupoid.arrows S c d
inv := fun hp ↦ by rw [mem_iInter₂] at hp ⊢; exact fun S hS => S.inv (hp S hS)
mul := fun hp _ hq ↦ by
rw [mem_iInter₂] at hp hq ⊢;
exact fun S hS => S.mul (hp S hS) (hq S hS) }⟩
-- Porting note (#10756): new lemma
theorem mem_sInf_arrows {s : Set (Subgroupoid C)} {c d : C} {p : c ⟶ d} :
p ∈ (sInf s).arrows c d ↔ ∀ S ∈ s, p ∈ S.arrows c d :=
mem_iInter₂
theorem mem_sInf {s : Set (Subgroupoid C)} {p : Σ c d : C, c ⟶ d} :
p ∈ sInf s ↔ ∀ S ∈ s, p ∈ S :=
mem_sInf_arrows
instance : CompleteLattice (Subgroupoid C) :=
{ completeLatticeOfInf (Subgroupoid C) (by
refine fun s => ⟨fun S Ss F => ?_, fun T Tl F fT => ?_⟩ <;> simp only [mem_sInf]
exacts [fun hp => hp S Ss, fun S Ss => Tl Ss fT]) with
bot := ⊥
bot_le := fun S => empty_subset _
top := ⊤
le_top := fun S => subset_univ _
inf := (· ⊓ ·)
le_inf := fun R S T RS RT _ pR => ⟨RS pR, RT pR⟩
inf_le_left := fun R S _ => And.left
inf_le_right := fun R S _ => And.right }
theorem le_objs {S T : Subgroupoid C} (h : S ≤ T) : S.objs ⊆ T.objs := fun s ⟨γ, hγ⟩ =>
⟨γ, @h ⟨s, s, γ⟩ hγ⟩
#align category_theory.subgroupoid.le_objs CategoryTheory.Subgroupoid.le_objs
/-- The functor associated to the embedding of subgroupoids -/
def inclusion {S T : Subgroupoid C} (h : S ≤ T) : S.objs ⥤ T.objs where
obj s := ⟨s.val, le_objs h s.prop⟩
map f := ⟨f.val, @h ⟨_, _, f.val⟩ f.prop⟩
map_id _ := rfl
map_comp _ _ := rfl
#align category_theory.subgroupoid.inclusion CategoryTheory.Subgroupoid.inclusion
theorem inclusion_inj_on_objects {S T : Subgroupoid C} (h : S ≤ T) :
Function.Injective (inclusion h).obj := fun ⟨s, hs⟩ ⟨t, ht⟩ => by
simpa only [inclusion, Subtype.mk_eq_mk] using id
#align category_theory.subgroupoid.inclusion_inj_on_objects CategoryTheory.Subgroupoid.inclusion_inj_on_objects
theorem inclusion_faithful {S T : Subgroupoid C} (h : S ≤ T) (s t : S.objs) :
Function.Injective fun f : s ⟶ t => (inclusion h).map f := fun ⟨f, hf⟩ ⟨g, hg⟩ => by
-- Porting note: was `...; simpa only [Subtype.mk_eq_mk] using id`
dsimp only [inclusion]; rw [Subtype.mk_eq_mk, Subtype.mk_eq_mk]; exact id
#align category_theory.subgroupoid.inclusion_faithful CategoryTheory.Subgroupoid.inclusion_faithful
theorem inclusion_refl {S : Subgroupoid C} : inclusion (le_refl S) = 𝟭 S.objs :=
Functor.hext (fun _ => rfl) fun _ _ _ => HEq.refl _
#align category_theory.subgroupoid.inclusion_refl CategoryTheory.Subgroupoid.inclusion_refl
theorem inclusion_trans {R S T : Subgroupoid C} (k : R ≤ S) (h : S ≤ T) :
inclusion (k.trans h) = inclusion k ⋙ inclusion h :=
rfl
#align category_theory.subgroupoid.inclusion_trans CategoryTheory.Subgroupoid.inclusion_trans
theorem inclusion_comp_embedding {S T : Subgroupoid C} (h : S ≤ T) : inclusion h ⋙ T.hom = S.hom :=
rfl
#align category_theory.subgroupoid.inclusion_comp_embedding CategoryTheory.Subgroupoid.inclusion_comp_embedding
/-- The family of arrows of the discrete groupoid -/
inductive Discrete.Arrows : ∀ c d : C, (c ⟶ d) → Prop
| id (c : C) : Discrete.Arrows c c (𝟙 c)
#align category_theory.subgroupoid.discrete.arrows CategoryTheory.Subgroupoid.Discrete.Arrows
/-- The only arrows of the discrete groupoid are the identity arrows. -/
def discrete : Subgroupoid C where
arrows c d := {p | Discrete.Arrows c d p}
inv := by rintro _ _ _ ⟨⟩; simp only [inv_eq_inv, IsIso.inv_id]; constructor
mul := by rintro _ _ _ _ ⟨⟩ _ ⟨⟩; rw [Category.comp_id]; constructor
#align category_theory.subgroupoid.discrete CategoryTheory.Subgroupoid.discrete
theorem mem_discrete_iff {c d : C} (f : c ⟶ d) :
f ∈ discrete.arrows c d ↔ ∃ h : c = d, f = eqToHom h :=
⟨by rintro ⟨⟩; exact ⟨rfl, rfl⟩, by rintro ⟨rfl, rfl⟩; constructor⟩
#align category_theory.subgroupoid.mem_discrete_iff CategoryTheory.Subgroupoid.mem_discrete_iff
/-- A subgroupoid is wide if its carrier set is all of `C`-/
structure IsWide : Prop where
wide : ∀ c, 𝟙 c ∈ S.arrows c c
#align category_theory.subgroupoid.is_wide CategoryTheory.Subgroupoid.IsWide
theorem isWide_iff_objs_eq_univ : S.IsWide ↔ S.objs = Set.univ := by
constructor
· rintro h
ext x; constructor <;> simp only [top_eq_univ, mem_univ, imp_true_iff, forall_true_left]
apply mem_objs_of_src S (h.wide x)
· rintro h
refine ⟨fun c => ?_⟩
obtain ⟨γ, γS⟩ := (le_of_eq h.symm : ⊤ ⊆ S.objs) (Set.mem_univ c)
exact id_mem_of_src S γS
#align category_theory.subgroupoid.is_wide_iff_objs_eq_univ CategoryTheory.Subgroupoid.isWide_iff_objs_eq_univ
theorem IsWide.id_mem {S : Subgroupoid C} (Sw : S.IsWide) (c : C) : 𝟙 c ∈ S.arrows c c :=
Sw.wide c
#align category_theory.subgroupoid.is_wide.id_mem CategoryTheory.Subgroupoid.IsWide.id_mem
theorem IsWide.eqToHom_mem {S : Subgroupoid C} (Sw : S.IsWide) {c d : C} (h : c = d) :
eqToHom h ∈ S.arrows c d := by cases h; simp only [eqToHom_refl]; apply Sw.id_mem c
#align category_theory.subgroupoid.is_wide.eq_to_hom_mem CategoryTheory.Subgroupoid.IsWide.eqToHom_mem
/-- A subgroupoid is normal if it is wide and satisfies the expected stability under conjugacy. -/
structure IsNormal extends IsWide S : Prop where
conj : ∀ {c d} (p : c ⟶ d) {γ : c ⟶ c}, γ ∈ S.arrows c c → Groupoid.inv p ≫ γ ≫ p ∈ S.arrows d d
#align category_theory.subgroupoid.is_normal CategoryTheory.Subgroupoid.IsNormal
theorem IsNormal.conj' {S : Subgroupoid C} (Sn : IsNormal S) :
∀ {c d} (p : d ⟶ c) {γ : c ⟶ c}, γ ∈ S.arrows c c → p ≫ γ ≫ Groupoid.inv p ∈ S.arrows d d :=
fun p γ hs => by convert Sn.conj (Groupoid.inv p) hs; simp
#align category_theory.subgroupoid.is_normal.conj' CategoryTheory.Subgroupoid.IsNormal.conj'
theorem IsNormal.conjugation_bij (Sn : IsNormal S) {c d} (p : c ⟶ d) :
Set.BijOn (fun γ : c ⟶ c => Groupoid.inv p ≫ γ ≫ p) (S.arrows c c) (S.arrows d d) := by
refine ⟨fun γ γS => Sn.conj p γS, fun γ₁ _ γ₂ _ h => ?_, fun δ δS =>
⟨p ≫ δ ≫ Groupoid.inv p, Sn.conj' p δS, ?_⟩⟩
· simpa only [inv_eq_inv, Category.assoc, IsIso.hom_inv_id, Category.comp_id,
IsIso.hom_inv_id_assoc] using p ≫= h =≫ inv p
· simp only [inv_eq_inv, Category.assoc, IsIso.inv_hom_id, Category.comp_id,
IsIso.inv_hom_id_assoc]
#align category_theory.subgroupoid.is_normal.conjugation_bij CategoryTheory.Subgroupoid.IsNormal.conjugation_bij
theorem top_isNormal : IsNormal (⊤ : Subgroupoid C) :=
{ wide := fun _ => trivial
conj := fun _ _ _ => trivial }
#align category_theory.subgroupoid.top_is_normal CategoryTheory.Subgroupoid.top_isNormal
theorem sInf_isNormal (s : Set <| Subgroupoid C) (sn : ∀ S ∈ s, IsNormal S) : IsNormal (sInf s) :=
{ wide := by simp_rw [sInf, mem_iInter₂]; exact fun c S Ss => (sn S Ss).wide c
conj := by simp_rw [sInf, mem_iInter₂]; exact fun p γ hγ S Ss => (sn S Ss).conj p (hγ S Ss) }
#align category_theory.subgroupoid.Inf_is_normal CategoryTheory.Subgroupoid.sInf_isNormal
theorem discrete_isNormal : (@discrete C _).IsNormal :=
{ wide := fun c => by constructor
conj := fun f γ hγ => by
cases hγ
simp only [inv_eq_inv, Category.id_comp, IsIso.inv_hom_id]; constructor }
#align category_theory.subgroupoid.discrete_is_normal CategoryTheory.Subgroupoid.discrete_isNormal
theorem IsNormal.vertexSubgroup (Sn : IsNormal S) (c : C) (cS : c ∈ S.objs) :
(S.vertexSubgroup cS).Normal where
conj_mem x hx y := by rw [mul_assoc]; exact Sn.conj' y hx
#align category_theory.subgroupoid.is_normal.vertex_subgroup CategoryTheory.Subgroupoid.IsNormal.vertexSubgroup
section GeneratedSubgroupoid
-- TODO: proof that generated is just "words in X" and generatedNormal is similarly
variable (X : ∀ c d : C, Set (c ⟶ d))
/-- The subgropoid generated by the set of arrows `X` -/
def generated : Subgroupoid C :=
sInf {S : Subgroupoid C | ∀ c d, X c d ⊆ S.arrows c d}
#align category_theory.subgroupoid.generated CategoryTheory.Subgroupoid.generated
theorem subset_generated (c d : C) : X c d ⊆ (generated X).arrows c d := by
dsimp only [generated, sInf]
simp only [subset_iInter₂_iff]
exact fun S hS f fS => hS _ _ fS
#align category_theory.subgroupoid.subset_generated CategoryTheory.Subgroupoid.subset_generated
/-- The normal sugroupoid generated by the set of arrows `X` -/
def generatedNormal : Subgroupoid C :=
sInf {S : Subgroupoid C | (∀ c d, X c d ⊆ S.arrows c d) ∧ S.IsNormal}
#align category_theory.subgroupoid.generated_normal CategoryTheory.Subgroupoid.generatedNormal
theorem generated_le_generatedNormal : generated X ≤ generatedNormal X := by
apply @sInf_le_sInf (Subgroupoid C) _
exact fun S ⟨h, _⟩ => h
#align category_theory.subgroupoid.generated_le_generated_normal CategoryTheory.Subgroupoid.generated_le_generatedNormal
theorem generatedNormal_isNormal : (generatedNormal X).IsNormal :=
sInf_isNormal _ fun _ h => h.right
#align category_theory.subgroupoid.generated_normal_is_normal CategoryTheory.Subgroupoid.generatedNormal_isNormal
theorem IsNormal.generatedNormal_le {S : Subgroupoid C} (Sn : S.IsNormal) :
generatedNormal X ≤ S ↔ ∀ c d, X c d ⊆ S.arrows c d := by
constructor
· rintro h c d
have h' := generated_le_generatedNormal X
rw [le_iff] at h h'
exact ((subset_generated X c d).trans (@h' c d)).trans (@h c d)
· rintro h
apply @sInf_le (Subgroupoid C) _
exact ⟨h, Sn⟩
#align category_theory.subgroupoid.is_normal.generated_normal_le CategoryTheory.Subgroupoid.IsNormal.generatedNormal_le
end GeneratedSubgroupoid
section Hom
variable {D : Type*} [Groupoid D] (φ : C ⥤ D)
/-- A functor between groupoid defines a map of subgroupoids in the reverse direction
by taking preimages.
-/
def comap (S : Subgroupoid D) : Subgroupoid C where
arrows c d := {f : c ⟶ d | φ.map f ∈ S.arrows (φ.obj c) (φ.obj d)}
inv hp := by rw [mem_setOf, inv_eq_inv, φ.map_inv, ← inv_eq_inv]; exact S.inv hp
mul := by
intros
simp only [mem_setOf, Functor.map_comp]
apply S.mul <;> assumption
#align category_theory.subgroupoid.comap CategoryTheory.Subgroupoid.comap
theorem comap_mono (S T : Subgroupoid D) : S ≤ T → comap φ S ≤ comap φ T := fun ST _ =>
@ST ⟨_, _, _⟩
#align category_theory.subgroupoid.comap_mono CategoryTheory.Subgroupoid.comap_mono
theorem isNormal_comap {S : Subgroupoid D} (Sn : IsNormal S) : IsNormal (comap φ S) where
wide c := by rw [comap, mem_setOf, Functor.map_id]; apply Sn.wide
conj f γ hγ := by
simp_rw [inv_eq_inv f, comap, mem_setOf, Functor.map_comp, Functor.map_inv, ← inv_eq_inv]
exact Sn.conj _ hγ
#align category_theory.subgroupoid.is_normal_comap CategoryTheory.Subgroupoid.isNormal_comap
@[simp]
theorem comap_comp {E : Type*} [Groupoid E] (ψ : D ⥤ E) : comap (φ ⋙ ψ) = comap φ ∘ comap ψ :=
rfl
#align category_theory.subgroupoid.comap_comp CategoryTheory.Subgroupoid.comap_comp
/-- The kernel of a functor between subgroupoid is the preimage. -/
def ker : Subgroupoid C :=
comap φ discrete
#align category_theory.subgroupoid.ker CategoryTheory.Subgroupoid.ker
theorem mem_ker_iff {c d : C} (f : c ⟶ d) :
f ∈ (ker φ).arrows c d ↔ ∃ h : φ.obj c = φ.obj d, φ.map f = eqToHom h :=
mem_discrete_iff (φ.map f)
#align category_theory.subgroupoid.mem_ker_iff CategoryTheory.Subgroupoid.mem_ker_iff
theorem ker_isNormal : (ker φ).IsNormal :=
isNormal_comap φ discrete_isNormal
#align category_theory.subgroupoid.ker_is_normal CategoryTheory.Subgroupoid.ker_isNormal
@[simp]
theorem ker_comp {E : Type*} [Groupoid E] (ψ : D ⥤ E) : ker (φ ⋙ ψ) = comap φ (ker ψ) :=
rfl
#align category_theory.subgroupoid.ker_comp CategoryTheory.Subgroupoid.ker_comp
/-- The family of arrows of the image of a subgroupoid under a functor injective on objects -/
inductive Map.Arrows (hφ : Function.Injective φ.obj) (S : Subgroupoid C) : ∀ c d : D, (c ⟶ d) → Prop
| im {c d : C} (f : c ⟶ d) (hf : f ∈ S.arrows c d) : Map.Arrows hφ S (φ.obj c) (φ.obj d) (φ.map f)
#align category_theory.subgroupoid.map.arrows CategoryTheory.Subgroupoid.Map.Arrows
theorem Map.arrows_iff (hφ : Function.Injective φ.obj) (S : Subgroupoid C) {c d : D} (f : c ⟶ d) :
Map.Arrows φ hφ S c d f ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d) (_hg : g ∈ S.arrows a b),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb := by
constructor
· rintro ⟨g, hg⟩; exact ⟨_, _, g, rfl, rfl, hg, eq_conj_eqToHom _⟩
· rintro ⟨a, b, g, rfl, rfl, hg, rfl⟩; rw [← eq_conj_eqToHom]; constructor; exact hg
#align category_theory.subgroupoid.map.arrows_iff CategoryTheory.Subgroupoid.Map.arrows_iff
/-- The "forward" image of a subgroupoid under a functor injective on objects -/
def map (hφ : Function.Injective φ.obj) (S : Subgroupoid C) : Subgroupoid D where
arrows c d := {x | Map.Arrows φ hφ S c d x}
inv := by
rintro _ _ _ ⟨⟩
rw [inv_eq_inv, ← Functor.map_inv, ← inv_eq_inv]
constructor; apply S.inv; assumption
mul := by
rintro _ _ _ _ ⟨f, hf⟩ q hq
obtain ⟨c₃, c₄, g, he, rfl, hg, gq⟩ := (Map.arrows_iff φ hφ S q).mp hq
cases hφ he; rw [gq, ← eq_conj_eqToHom, ← φ.map_comp]
constructor; exact S.mul hf hg
#align category_theory.subgroupoid.map CategoryTheory.Subgroupoid.map
theorem mem_map_iff (hφ : Function.Injective φ.obj) (S : Subgroupoid C) {c d : D} (f : c ⟶ d) :
f ∈ (map φ hφ S).arrows c d ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d) (_hg : g ∈ S.arrows a b),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb :=
Map.arrows_iff φ hφ S f
#align category_theory.subgroupoid.mem_map_iff CategoryTheory.Subgroupoid.mem_map_iff
theorem galoisConnection_map_comap (hφ : Function.Injective φ.obj) :
GaloisConnection (map φ hφ) (comap φ) := by
rintro S T; simp_rw [le_iff]; constructor
· exact fun h c d f fS => h (Map.Arrows.im f fS)
· rintro h _ _ g ⟨a, gφS⟩
exact h gφS
#align category_theory.subgroupoid.galois_connection_map_comap CategoryTheory.Subgroupoid.galoisConnection_map_comap
theorem map_mono (hφ : Function.Injective φ.obj) (S T : Subgroupoid C) :
S ≤ T → map φ hφ S ≤ map φ hφ T := fun h => (galoisConnection_map_comap φ hφ).monotone_l h
#align category_theory.subgroupoid.map_mono CategoryTheory.Subgroupoid.map_mono
theorem le_comap_map (hφ : Function.Injective φ.obj) (S : Subgroupoid C) :
S ≤ comap φ (map φ hφ S) :=
(galoisConnection_map_comap φ hφ).le_u_l S
#align category_theory.subgroupoid.le_comap_map CategoryTheory.Subgroupoid.le_comap_map
theorem map_comap_le (hφ : Function.Injective φ.obj) (T : Subgroupoid D) :
map φ hφ (comap φ T) ≤ T :=
(galoisConnection_map_comap φ hφ).l_u_le T
#align category_theory.subgroupoid.map_comap_le CategoryTheory.Subgroupoid.map_comap_le
theorem map_le_iff_le_comap (hφ : Function.Injective φ.obj) (S : Subgroupoid C)
(T : Subgroupoid D) : map φ hφ S ≤ T ↔ S ≤ comap φ T :=
(galoisConnection_map_comap φ hφ).le_iff_le
#align category_theory.subgroupoid.map_le_iff_le_comap CategoryTheory.Subgroupoid.map_le_iff_le_comap
theorem mem_map_objs_iff (hφ : Function.Injective φ.obj) (d : D) :
d ∈ (map φ hφ S).objs ↔ ∃ c ∈ S.objs, φ.obj c = d := by
dsimp [objs, map]
constructor
· rintro ⟨f, hf⟩
change Map.Arrows φ hφ S d d f at hf; rw [Map.arrows_iff] at hf
obtain ⟨c, d, g, ec, ed, eg, gS, eg⟩ := hf
exact ⟨c, ⟨mem_objs_of_src S eg, ec⟩⟩
· rintro ⟨c, ⟨γ, γS⟩, rfl⟩
exact ⟨φ.map γ, ⟨γ, γS⟩⟩
#align category_theory.subgroupoid.mem_map_objs_iff CategoryTheory.Subgroupoid.mem_map_objs_iff
@[simp]
theorem map_objs_eq (hφ : Function.Injective φ.obj) : (map φ hφ S).objs = φ.obj '' S.objs := by
ext x; convert mem_map_objs_iff S φ hφ x
#align category_theory.subgroupoid.map_objs_eq CategoryTheory.Subgroupoid.map_objs_eq
/-- The image of a functor injective on objects -/
def im (hφ : Function.Injective φ.obj) :=
map φ hφ ⊤
#align category_theory.subgroupoid.im CategoryTheory.Subgroupoid.im
theorem mem_im_iff (hφ : Function.Injective φ.obj) {c d : D} (f : c ⟶ d) :
f ∈ (im φ hφ).arrows c d ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb := by
convert Map.arrows_iff φ hφ ⊤ f; simp only [Top.top, mem_univ, exists_true_left]
#align category_theory.subgroupoid.mem_im_iff CategoryTheory.Subgroupoid.mem_im_iff
| Mathlib/CategoryTheory/Groupoid/Subgroupoid.lean | 561 | 563 | theorem mem_im_objs_iff (hφ : Function.Injective φ.obj) (d : D) :
d ∈ (im φ hφ).objs ↔ ∃ c : C, φ.obj c = d := by |
simp only [im, mem_map_objs_iff, mem_top_objs, true_and]
|
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