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/- Copyright (c) 2021 Shing Tak Lam. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Shing Tak Lam -/ import Mathlib.LinearAlgebra.GeneralLinearGroup import Mathlib.LinearAlgebra.Matrix.ToLin import Mathlib.LinearAlgebra.Matrix.NonsingularInverse import Mathlib.Algebra.Star.Unitary #align_import linear_algebra.unitary_group from "leanprover-community/mathlib"@"2705404e701abc6b3127da906f40bae062a169c9" /-! # The Unitary Group This file defines elements of the unitary group `Matrix.unitaryGroup n α`, where `α` is a `StarRing`. This consists of all `n` by `n` matrices with entries in `α` such that the star-transpose is its inverse. In addition, we define the group structure on `Matrix.unitaryGroup n α`, and the embedding into the general linear group `LinearMap.GeneralLinearGroup α (n → α)`. We also define the orthogonal group `Matrix.orthogonalGroup n β`, where `β` is a `CommRing`. ## Main Definitions * `Matrix.unitaryGroup` is the submonoid of matrices where the star-transpose is the inverse; the group structure (under multiplication) is inherited from a more general `unitary` construction. * `Matrix.UnitaryGroup.embeddingGL` is the embedding `Matrix.unitaryGroup n α → GLₙ(α)`, where `GLₙ(α)` is `LinearMap.GeneralLinearGroup α (n → α)`. * `Matrix.orthogonalGroup` is the submonoid of matrices where the transpose is the inverse. ## References * https://en.wikipedia.org/wiki/Unitary_group ## Tags matrix group, group, unitary group, orthogonal group -/ universe u v namespace Matrix open LinearMap Matrix section variable (n : Type u) [DecidableEq n] [Fintype n] variable (α : Type v) [CommRing α] [StarRing α] /-- `Matrix.unitaryGroup n` is the group of `n` by `n` matrices where the star-transpose is the inverse. -/ abbrev unitaryGroup := unitary (Matrix n n α) #align matrix.unitary_group Matrix.unitaryGroup end variable {n : Type u} [DecidableEq n] [Fintype n] variable {α : Type v} [CommRing α] [StarRing α] {A : Matrix n n α} theorem mem_unitaryGroup_iff : A ∈ Matrix.unitaryGroup n α ↔ A * star A = 1 := by refine ⟨And.right, fun hA => ⟨?_, hA⟩⟩ simpa only [mul_eq_one_comm] using hA #align matrix.mem_unitary_group_iff Matrix.mem_unitaryGroup_iff theorem mem_unitaryGroup_iff' : A ∈ Matrix.unitaryGroup n α ↔ star A * A = 1 := by refine ⟨And.left, fun hA => ⟨hA, ?_⟩⟩ rwa [mul_eq_one_comm] at hA #align matrix.mem_unitary_group_iff' Matrix.mem_unitaryGroup_iff'
Mathlib/LinearAlgebra/UnitaryGroup.lean
76
80
theorem det_of_mem_unitary {A : Matrix n n α} (hA : A ∈ Matrix.unitaryGroup n α) : A.det ∈ unitary α := by
constructor · simpa [star, det_transpose] using congr_arg det hA.1 · simpa [star, det_transpose] using congr_arg det hA.2
/- Copyright (c) 2024 Mitchell Lee. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mitchell Lee -/ import Mathlib.GroupTheory.Coxeter.Length import Mathlib.Data.ZMod.Parity /-! # Reflections, inversions, and inversion sequences Throughout this file, `B` is a type and `M : CoxeterMatrix B` is a Coxeter matrix. `cs : CoxeterSystem M W` is a Coxeter system; that is, `W` is a group, and `cs` holds the data of a group isomorphism `W ≃* M.group`, where `M.group` refers to the quotient of the free group on `B` by the Coxeter relations given by the matrix `M`. See `Mathlib/GroupTheory/Coxeter/Basic.lean` for more details. We define a *reflection* (`CoxeterSystem.IsReflection`) to be an element of the form $t = u s_i u^{-1}$, where $u \in W$ and $s_i$ is a simple reflection. We say that a reflection $t$ is a *left inversion* (`CoxeterSystem.IsLeftInversion`) of an element $w \in W$ if $\ell(t w) < \ell(w)$, and we say it is a *right inversion* (`CoxeterSystem.IsRightInversion`) of $w$ if $\ell(w t) > \ell(w)$. Here $\ell$ is the length function (see `Mathlib/GroupTheory/Coxeter/Length.lean`). Given a word, we define its *left inversion sequence* (`CoxeterSystem.leftInvSeq`) and its *right inversion sequence* (`CoxeterSystem.rightInvSeq`). We prove that if a word is reduced, then both of its inversion sequences contain no duplicates. In fact, the right (respectively, left) inversion sequence of a reduced word for $w$ consists of all of the right (respectively, left) inversions of $w$ in some order, but we do not prove that in this file. ## Main definitions * `CoxeterSystem.IsReflection` * `CoxeterSystem.IsLeftInversion` * `CoxeterSystem.IsRightInversion` * `CoxeterSystem.leftInvSeq` * `CoxeterSystem.rightInvSeq` ## References * [A. Björner and F. Brenti, *Combinatorics of Coxeter Groups*](bjorner2005) -/ namespace CoxeterSystem open List Matrix Function variable {B : Type*} variable {W : Type*} [Group W] variable {M : CoxeterMatrix B} (cs : CoxeterSystem M W) local prefix:100 "s" => cs.simple local prefix:100 "π" => cs.wordProd local prefix:100 "ℓ" => cs.length /-- `t : W` is a *reflection* of the Coxeter system `cs` if it is of the form $w s_i w^{-1}$, where $w \in W$ and $s_i$ is a simple reflection. -/ def IsReflection (t : W) : Prop := ∃ w i, t = w * s i * w⁻¹ theorem isReflection_simple (i : B) : cs.IsReflection (s i) := by use 1, i; simp namespace IsReflection variable {cs} variable {t : W} (ht : cs.IsReflection t) theorem pow_two : t ^ 2 = 1 := by rcases ht with ⟨w, i, rfl⟩ simp theorem mul_self : t * t = 1 := by rcases ht with ⟨w, i, rfl⟩ simp theorem inv : t⁻¹ = t := by rcases ht with ⟨w, i, rfl⟩ simp [mul_assoc] theorem isReflection_inv : cs.IsReflection t⁻¹ := by rwa [ht.inv] theorem odd_length : Odd (ℓ t) := by suffices cs.lengthParity t = Multiplicative.ofAdd 1 by simpa [lengthParity_eq_ofAdd_length, ZMod.eq_one_iff_odd] rcases ht with ⟨w, i, rfl⟩ simp [lengthParity_simple] theorem length_mul_left_ne (w : W) : ℓ (w * t) ≠ ℓ w := by suffices cs.lengthParity (w * t) ≠ cs.lengthParity w by contrapose! this simp only [lengthParity_eq_ofAdd_length, this] rcases ht with ⟨w, i, rfl⟩ simp [lengthParity_simple] theorem length_mul_right_ne (w : W) : ℓ (t * w) ≠ ℓ w := by suffices cs.lengthParity (t * w) ≠ cs.lengthParity w by contrapose! this simp only [lengthParity_eq_ofAdd_length, this] rcases ht with ⟨w, i, rfl⟩ simp [lengthParity_simple]
Mathlib/GroupTheory/Coxeter/Inversion.lean
102
105
theorem conj (w : W) : cs.IsReflection (w * t * w⁻¹) := by
obtain ⟨u, i, rfl⟩ := ht use w * u, i group
/- Copyright (c) 2020 Aaron Anderson, Jalex Stark, Kyle Miller. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Alena Gusakov -/ import Mathlib.Algebra.Order.Ring.Defs import Mathlib.Combinatorics.SimpleGraph.Basic import Mathlib.Data.Sym.Card /-! # Definitions for finite and locally finite graphs This file defines finite versions of `edgeSet`, `neighborSet` and `incidenceSet` and proves some of their basic properties. It also defines the notion of a locally finite graph, which is one whose vertices have finite degree. The design for finiteness is that each definition takes the smallest finiteness assumption necessary. For example, `SimpleGraph.neighborFinset v` only requires that `v` have finitely many neighbors. ## Main definitions * `SimpleGraph.edgeFinset` is the `Finset` of edges in a graph, if `edgeSet` is finite * `SimpleGraph.neighborFinset` is the `Finset` of vertices adjacent to a given vertex, if `neighborSet` is finite * `SimpleGraph.incidenceFinset` is the `Finset` of edges containing a given vertex, if `incidenceSet` is finite ## Naming conventions If the vertex type of a graph is finite, we refer to its cardinality as `CardVerts` or `card_verts`. ## Implementation notes * A locally finite graph is one with instances `Π v, Fintype (G.neighborSet v)`. * Given instances `DecidableRel G.Adj` and `Fintype V`, then the graph is locally finite, too. -/ open Finset Function namespace SimpleGraph variable {V : Type*} (G : SimpleGraph V) {e : Sym2 V} section EdgeFinset variable {G₁ G₂ : SimpleGraph V} [Fintype G.edgeSet] [Fintype G₁.edgeSet] [Fintype G₂.edgeSet] /-- The `edgeSet` of the graph as a `Finset`. -/ abbrev edgeFinset : Finset (Sym2 V) := Set.toFinset G.edgeSet #align simple_graph.edge_finset SimpleGraph.edgeFinset @[norm_cast] theorem coe_edgeFinset : (G.edgeFinset : Set (Sym2 V)) = G.edgeSet := Set.coe_toFinset _ #align simple_graph.coe_edge_finset SimpleGraph.coe_edgeFinset variable {G} theorem mem_edgeFinset : e ∈ G.edgeFinset ↔ e ∈ G.edgeSet := Set.mem_toFinset #align simple_graph.mem_edge_finset SimpleGraph.mem_edgeFinset theorem not_isDiag_of_mem_edgeFinset : e ∈ G.edgeFinset → ¬e.IsDiag := not_isDiag_of_mem_edgeSet _ ∘ mem_edgeFinset.1 #align simple_graph.not_is_diag_of_mem_edge_finset SimpleGraph.not_isDiag_of_mem_edgeFinset theorem edgeFinset_inj : G₁.edgeFinset = G₂.edgeFinset ↔ G₁ = G₂ := by simp #align simple_graph.edge_finset_inj SimpleGraph.edgeFinset_inj theorem edgeFinset_subset_edgeFinset : G₁.edgeFinset ⊆ G₂.edgeFinset ↔ G₁ ≤ G₂ := by simp #align simple_graph.edge_finset_subset_edge_finset SimpleGraph.edgeFinset_subset_edgeFinset
Mathlib/Combinatorics/SimpleGraph/Finite.lean
78
78
theorem edgeFinset_ssubset_edgeFinset : G₁.edgeFinset ⊂ G₂.edgeFinset ↔ G₁ < G₂ := by
simp
/- Copyright (c) 2019 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl -/ import Mathlib.Order.Filter.Bases import Mathlib.Order.ConditionallyCompleteLattice.Basic #align_import order.filter.lift from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1" /-! # Lift filters along filter and set functions -/ open Set Classical Filter Function namespace Filter variable {α β γ : Type*} {ι : Sort*} section lift /-- A variant on `bind` using a function `g` taking a set instead of a member of `α`. This is essentially a push-forward along a function mapping each set to a filter. -/ protected def lift (f : Filter α) (g : Set α → Filter β) := ⨅ s ∈ f, g s #align filter.lift Filter.lift variable {f f₁ f₂ : Filter α} {g g₁ g₂ : Set α → Filter β} @[simp]
Mathlib/Order/Filter/Lift.lean
32
32
theorem lift_top (g : Set α → Filter β) : (⊤ : Filter α).lift g = g univ := by
simp [Filter.lift]
/- Copyright (c) 2022 Moritz Firsching. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Firsching, Fabian Kruse, Nikolas Kuhn -/ import Mathlib.Analysis.PSeries import Mathlib.Data.Real.Pi.Wallis import Mathlib.Tactic.AdaptationNote #align_import analysis.special_functions.stirling from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1" /-! # Stirling's formula This file proves Stirling's formula for the factorial. It states that $n!$ grows asymptotically like $\sqrt{2\pi n}(\frac{n}{e})^n$. ## Proof outline The proof follows: <https://proofwiki.org/wiki/Stirling%27s_Formula>. We proceed in two parts. **Part 1**: We consider the sequence $a_n$ of fractions $\frac{n!}{\sqrt{2n}(\frac{n}{e})^n}$ and prove that this sequence converges to a real, positive number $a$. For this the two main ingredients are - taking the logarithm of the sequence and - using the series expansion of $\log(1 + x)$. **Part 2**: We use the fact that the series defined in part 1 converges against a real number $a$ and prove that $a = \sqrt{\pi}$. Here the main ingredient is the convergence of Wallis' product formula for `π`. -/ open scoped Topology Real Nat Asymptotics open Finset Filter Nat Real namespace Stirling /-! ### Part 1 https://proofwiki.org/wiki/Stirling%27s_Formula#Part_1 -/ /-- Define `stirlingSeq n` as $\frac{n!}{\sqrt{2n}(\frac{n}{e})^n}$. Stirling's formula states that this sequence has limit $\sqrt(π)$. -/ noncomputable def stirlingSeq (n : ℕ) : ℝ := n ! / (√(2 * n : ℝ) * (n / exp 1) ^ n) #align stirling.stirling_seq Stirling.stirlingSeq @[simp] theorem stirlingSeq_zero : stirlingSeq 0 = 0 := by rw [stirlingSeq, cast_zero, mul_zero, Real.sqrt_zero, zero_mul, div_zero] #align stirling.stirling_seq_zero Stirling.stirlingSeq_zero @[simp]
Mathlib/Analysis/SpecialFunctions/Stirling.lean
61
62
theorem stirlingSeq_one : stirlingSeq 1 = exp 1 / √2 := by
rw [stirlingSeq, pow_one, factorial_one, cast_one, mul_one, mul_one_div, one_div_div]
/- 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]
Mathlib/Order/Interval/Set/OrderIso.lean
42
44
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]
/- Copyright (c) 2021 Martin Dvorak. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Martin Dvorak, Kyle Miller, Eric Wieser -/ import Mathlib.Data.Matrix.Notation import Mathlib.LinearAlgebra.BilinearMap import Mathlib.LinearAlgebra.Matrix.Determinant.Basic import Mathlib.Algebra.Lie.Basic #align_import linear_algebra.cross_product from "leanprover-community/mathlib"@"91288e351d51b3f0748f0a38faa7613fb0ae2ada" /-! # Cross products This module defines the cross product of vectors in $R^3$ for $R$ a commutative ring, as a bilinear map. ## Main definitions * `crossProduct` is the cross product of pairs of vectors in $R^3$. ## Main results * `triple_product_eq_det` * `cross_dot_cross` * `jacobi_cross` ## Notation The locale `Matrix` gives the following notation: * `×₃` for the cross product ## Tags crossproduct -/ open Matrix open Matrix variable {R : Type*} [CommRing R] /-- The cross product of two vectors in $R^3$ for $R$ a commutative ring. -/ def crossProduct : (Fin 3 → R) →ₗ[R] (Fin 3 → R) →ₗ[R] Fin 3 → R := by apply LinearMap.mk₂ R fun a b : Fin 3 → R => ![a 1 * b 2 - a 2 * b 1, a 2 * b 0 - a 0 * b 2, a 0 * b 1 - a 1 * b 0] · intros simp_rw [vec3_add, Pi.add_apply] apply vec3_eq <;> ring · intros simp_rw [smul_vec3, Pi.smul_apply, smul_sub, smul_mul_assoc] · intros simp_rw [vec3_add, Pi.add_apply] apply vec3_eq <;> ring · intros simp_rw [smul_vec3, Pi.smul_apply, smul_sub, mul_smul_comm] #align cross_product crossProduct scoped[Matrix] infixl:74 " ×₃ " => crossProduct theorem cross_apply (a b : Fin 3 → R) : a ×₃ b = ![a 1 * b 2 - a 2 * b 1, a 2 * b 0 - a 0 * b 2, a 0 * b 1 - a 1 * b 0] := rfl #align cross_apply cross_apply section ProductsProperties #adaptation_note /-- nightly-2024-04-01 The simpNF linter now times out on this lemma, likely due to https://github.com/leanprover/lean4/pull/3807 -/ @[simp, nolint simpNF] theorem cross_anticomm (v w : Fin 3 → R) : -(v ×₃ w) = w ×₃ v := by simp [cross_apply, mul_comm] #align cross_anticomm cross_anticomm alias neg_cross := cross_anticomm #align neg_cross neg_cross #adaptation_note /-- nightly-2024-04-01 The simpNF linter now times out on this lemma, likely due to https://github.com/leanprover/lean4/pull/3807 -/ @[simp, nolint simpNF] theorem cross_anticomm' (v w : Fin 3 → R) : v ×₃ w + w ×₃ v = 0 := by rw [add_eq_zero_iff_eq_neg, cross_anticomm] #align cross_anticomm' cross_anticomm' #adaptation_note /-- nightly-2024-04-01 The simpNF linter now times out on this lemma, likely due to https://github.com/leanprover/lean4/pull/3807 -/ @[simp, nolint simpNF] theorem cross_self (v : Fin 3 → R) : v ×₃ v = 0 := by simp [cross_apply, mul_comm] #align cross_self cross_self #adaptation_note /-- nightly-2024-04-01 The simpNF linter now times out on this lemma, likely due to https://github.com/leanprover/lean4/pull/3807 -/ /-- The cross product of two vectors is perpendicular to the first vector. -/ @[simp 1100, nolint simpNF] -- Porting note: increase priority so that the LHS doesn't simplify theorem dot_self_cross (v w : Fin 3 → R) : v ⬝ᵥ v ×₃ w = 0 := by rw [cross_apply, vec3_dotProduct] set_option tactic.skipAssignedInstances false in norm_num ring #align dot_self_cross dot_self_cross #adaptation_note /-- nightly-2024-04-01 The simpNF linter now times out on this lemma, likely due to https://github.com/leanprover/lean4/pull/3807 -/ /-- The cross product of two vectors is perpendicular to the second vector. -/ @[simp 1100, nolint simpNF] -- Porting note: increase priority so that the LHS doesn't simplify theorem dot_cross_self (v w : Fin 3 → R) : w ⬝ᵥ v ×₃ w = 0 := by rw [← cross_anticomm, Matrix.dotProduct_neg, dot_self_cross, neg_zero] #align dot_cross_self dot_cross_self /-- Cyclic permutations preserve the triple product. See also `triple_product_eq_det`. -/ theorem triple_product_permutation (u v w : Fin 3 → R) : u ⬝ᵥ v ×₃ w = v ⬝ᵥ w ×₃ u := by simp_rw [cross_apply, vec3_dotProduct] norm_num ring #align triple_product_permutation triple_product_permutation /-- The triple product of `u`, `v`, and `w` is equal to the determinant of the matrix with those vectors as its rows. -/ theorem triple_product_eq_det (u v w : Fin 3 → R) : u ⬝ᵥ v ×₃ w = Matrix.det ![u, v, w] := by rw [vec3_dotProduct, cross_apply, det_fin_three] norm_num ring #align triple_product_eq_det triple_product_eq_det /-- The scalar quadruple product identity, related to the Binet-Cauchy identity. -/
Mathlib/LinearAlgebra/CrossProduct.lean
134
138
theorem cross_dot_cross (u v w x : Fin 3 → R) : u ×₃ v ⬝ᵥ w ×₃ x = u ⬝ᵥ w * v ⬝ᵥ x - u ⬝ᵥ x * v ⬝ᵥ w := by
simp_rw [cross_apply, vec3_dotProduct] norm_num ring
/- Copyright (c) 2021 Anatole Dedecker. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anatole Dedecker, Floris van Doorn -/ import Mathlib.Analysis.Convex.Normed import Mathlib.Analysis.NormedSpace.Connected import Mathlib.LinearAlgebra.AffineSpace.ContinuousAffineEquiv /-! # Ample subsets of real vector spaces In this file we study ample sets in real vector spaces. A set is ample if all its connected component have full convex hull. Ample sets are an important ingredient for defining ample differential relations. ## Main results - `ampleSet_empty` and `ampleSet_univ`: the empty set and `univ` are ample - `AmpleSet.union`: the union of two ample sets is ample - `AmpleSet.{pre}image`: being ample is invariant under continuous affine equivalences; `AmpleSet.{pre}image_iff` are "iff" versions of these - `AmpleSet.vadd`: in particular, ample-ness is invariant under affine translations - `AmpleSet.of_one_lt_codim`: a linear subspace of codimension at least two has an ample complement. This is the crucial geometric ingredient which allows to apply convex integration to the theory of immersions in positive codimension. ## Implementation notes A priori, the definition of ample subset asks for a vector space structure and a topology on the ambient type without any link between those structures. In practice, we care most about using these for finite dimensional vector spaces with their natural topology. All vector spaces in the file are real vector spaces. While the definition generalises to other connected fields, that is not useful in practice. ## Tags ample set -/ /-! ## Definition and invariance -/ open Set variable {F : Type*} [AddCommGroup F] [Module ℝ F] [TopologicalSpace F] /-- A subset of a topological real vector space is ample if the convex hull of each of its connected components is the full space. -/ def AmpleSet (s : Set F) : Prop := ∀ x ∈ s, convexHull ℝ (connectedComponentIn s x) = univ /-- A whole vector space is ample. -/ @[simp] theorem ampleSet_univ {F : Type*} [NormedAddCommGroup F] [NormedSpace ℝ F] : AmpleSet (univ : Set F) := by intro x _ rw [connectedComponentIn_univ, PreconnectedSpace.connectedComponent_eq_univ, convexHull_univ] /-- The empty set in a vector space is ample. -/ @[simp] theorem ampleSet_empty : AmpleSet (∅ : Set F) := fun _ ↦ False.elim namespace AmpleSet /-- The union of two ample sets is ample. -/ theorem union {s t : Set F} (hs : AmpleSet s) (ht : AmpleSet t) : AmpleSet (s ∪ t) := by intro x hx rcases hx with (h | h) <;> -- The connected component of `x ∈ s` in `s ∪ t` contains the connected component of `x` in `s`, -- hence is also full; similarly for `t`. [have hx := hs x h; have hx := ht x h] <;> rw [← Set.univ_subset_iff, ← hx] <;> apply convexHull_mono <;> apply connectedComponentIn_mono <;> [apply subset_union_left; apply subset_union_right] variable {E : Type*} [AddCommGroup E] [Module ℝ E] [TopologicalSpace E] /-- Images of ample sets under continuous affine equivalences are ample. -/
Mathlib/Analysis/Convex/AmpleSet.lean
79
86
theorem image {s : Set E} (h : AmpleSet s) (L : E ≃ᵃL[ℝ] F) : AmpleSet (L '' s) := forall_mem_image.mpr fun x hx ↦ calc (convexHull ℝ) (connectedComponentIn (L '' s) (L x)) _ = (convexHull ℝ) (L '' (connectedComponentIn s x)) := .symm <| congrArg _ <| L.toHomeomorph.image_connectedComponentIn hx _ = L '' (convexHull ℝ (connectedComponentIn s x)) := .symm <| L.toAffineMap.image_convexHull _ _ = univ := by
rw [h x hx, image_univ, L.surjective.range_eq]
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro -/ import Mathlib.Algebra.MonoidAlgebra.Degree import Mathlib.Algebra.MvPolynomial.Rename import Mathlib.Algebra.Order.BigOperators.Ring.Finset #align_import data.mv_polynomial.variables from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4" /-! # Degrees of polynomials This file establishes many results about the degree of a multivariate polynomial. The *degree set* of a polynomial $P \in R[X]$ is a `Multiset` containing, for each $x$ in the variable set, $n$ copies of $x$, where $n$ is the maximum number of copies of $x$ appearing in a monomial of $P$. ## Main declarations * `MvPolynomial.degrees p` : the multiset of variables representing the union of the multisets corresponding to each non-zero monomial in `p`. For example if `7 ≠ 0` in `R` and `p = x²y+7y³` then `degrees p = {x, x, y, y, y}` * `MvPolynomial.degreeOf n p : ℕ` : the total degree of `p` with respect to the variable `n`. For example if `p = x⁴y+yz` then `degreeOf y p = 1`. * `MvPolynomial.totalDegree p : ℕ` : the max of the sizes of the multisets `s` whose monomials `X^s` occur in `p`. For example if `p = x⁴y+yz` then `totalDegree p = 5`. ## Notation As in other polynomial files, we typically use the notation: + `σ τ : Type*` (indexing the variables) + `R : Type*` `[CommSemiring R]` (the coefficients) + `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set. This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s` + `r : R` + `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians + `p : MvPolynomial σ R` -/ noncomputable section open Set Function Finsupp AddMonoidAlgebra universe u v w variable {R : Type u} {S : Type v} namespace MvPolynomial variable {σ τ : Type*} {r : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ} section CommSemiring variable [CommSemiring R] {p q : MvPolynomial σ R} section Degrees /-! ### `degrees` -/ /-- The maximal degrees of each variable in a multi-variable polynomial, expressed as a multiset. (For example, `degrees (x^2 * y + y^3)` would be `{x, x, y, y, y}`.) -/ def degrees (p : MvPolynomial σ R) : Multiset σ := letI := Classical.decEq σ p.support.sup fun s : σ →₀ ℕ => toMultiset s #align mv_polynomial.degrees MvPolynomial.degrees
Mathlib/Algebra/MvPolynomial/Degrees.lean
84
85
theorem degrees_def [DecidableEq σ] (p : MvPolynomial σ R) : p.degrees = p.support.sup fun s : σ →₀ ℕ => Finsupp.toMultiset s := by
rw [degrees]; convert rfl
/- Copyright (c) 2022 Yakov Pechersky. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yakov Pechersky -/ import Mathlib.Data.List.Infix #align_import data.list.rdrop from "leanprover-community/mathlib"@"26f081a2fb920140ed5bc5cc5344e84bcc7cb2b2" /-! # Dropping or taking from lists on the right Taking or removing element from the tail end of a list ## Main definitions - `rdrop n`: drop `n : ℕ` elements from the tail - `rtake n`: take `n : ℕ` elements from the tail - `rdropWhile p`: remove all the elements from the tail of a list until it finds the first element for which `p : α → Bool` returns false. This element and everything before is returned. - `rtakeWhile p`: Returns the longest terminal segment of a list for which `p : α → Bool` returns true. ## Implementation detail The two predicate-based methods operate by performing the regular "from-left" operation on `List.reverse`, followed by another `List.reverse`, so they are not the most performant. The other two rely on `List.length l` so they still traverse the list twice. One could construct another function that takes a `L : ℕ` and use `L - n`. Under a proof condition that `L = l.length`, the function would do the right thing. -/ -- Make sure we don't import algebra assert_not_exists Monoid variable {α : Type*} (p : α → Bool) (l : List α) (n : ℕ) namespace List /-- Drop `n` elements from the tail end of a list. -/ def rdrop : List α := l.take (l.length - n) #align list.rdrop List.rdrop @[simp] theorem rdrop_nil : rdrop ([] : List α) n = [] := by simp [rdrop] #align list.rdrop_nil List.rdrop_nil @[simp] theorem rdrop_zero : rdrop l 0 = l := by simp [rdrop] #align list.rdrop_zero List.rdrop_zero theorem rdrop_eq_reverse_drop_reverse : l.rdrop n = reverse (l.reverse.drop n) := by rw [rdrop] induction' l using List.reverseRecOn with xs x IH generalizing n · simp · cases n · simp [take_append] · simp [take_append_eq_append_take, IH] #align list.rdrop_eq_reverse_drop_reverse List.rdrop_eq_reverse_drop_reverse @[simp] theorem rdrop_concat_succ (x : α) : rdrop (l ++ [x]) (n + 1) = rdrop l n := by simp [rdrop_eq_reverse_drop_reverse] #align list.rdrop_concat_succ List.rdrop_concat_succ /-- Take `n` elements from the tail end of a list. -/ def rtake : List α := l.drop (l.length - n) #align list.rtake List.rtake @[simp] theorem rtake_nil : rtake ([] : List α) n = [] := by simp [rtake] #align list.rtake_nil List.rtake_nil @[simp] theorem rtake_zero : rtake l 0 = [] := by simp [rtake] #align list.rtake_zero List.rtake_zero theorem rtake_eq_reverse_take_reverse : l.rtake n = reverse (l.reverse.take n) := by rw [rtake] induction' l using List.reverseRecOn with xs x IH generalizing n · simp · cases n · exact drop_length _ · simp [drop_append_eq_append_drop, IH] #align list.rtake_eq_reverse_take_reverse List.rtake_eq_reverse_take_reverse @[simp] theorem rtake_concat_succ (x : α) : rtake (l ++ [x]) (n + 1) = rtake l n ++ [x] := by simp [rtake_eq_reverse_take_reverse] #align list.rtake_concat_succ List.rtake_concat_succ /-- Drop elements from the tail end of a list that satisfy `p : α → Bool`. Implemented naively via `List.reverse` -/ def rdropWhile : List α := reverse (l.reverse.dropWhile p) #align list.rdrop_while List.rdropWhile @[simp] theorem rdropWhile_nil : rdropWhile p ([] : List α) = [] := by simp [rdropWhile, dropWhile] #align list.rdrop_while_nil List.rdropWhile_nil
Mathlib/Data/List/DropRight.lean
105
108
theorem rdropWhile_concat (x : α) : rdropWhile p (l ++ [x]) = if p x then rdropWhile p l else l ++ [x] := by
simp only [rdropWhile, dropWhile, reverse_append, reverse_singleton, singleton_append] split_ifs with h <;> simp [h]
/- 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.Polynomial.AlgebraMap import Mathlib.Algebra.Polynomial.Degree.Lemmas import Mathlib.Algebra.Polynomial.Monic #align_import data.polynomial.integral_normalization from "leanprover-community/mathlib"@"6f401acf4faec3ab9ab13a42789c4f68064a61cd" /-! # Theory of monic polynomials We define `integralNormalization`, which relate arbitrary polynomials to monic ones. -/ open Polynomial namespace Polynomial universe u v y variable {R : Type u} {S : Type v} {a b : R} {m n : ℕ} {ι : Type y} section IntegralNormalization section Semiring variable [Semiring R] /-- If `f : R[X]` is a nonzero polynomial with root `z`, `integralNormalization f` is a monic polynomial with root `leadingCoeff f * z`. Moreover, `integralNormalization 0 = 0`. -/ noncomputable def integralNormalization (f : R[X]) : R[X] := ∑ i ∈ f.support, monomial i (if f.degree = i then 1 else coeff f i * f.leadingCoeff ^ (f.natDegree - 1 - i)) #align polynomial.integral_normalization Polynomial.integralNormalization @[simp] theorem integralNormalization_zero : integralNormalization (0 : R[X]) = 0 := by simp [integralNormalization] #align polynomial.integral_normalization_zero Polynomial.integralNormalization_zero theorem integralNormalization_coeff {f : R[X]} {i : ℕ} : (integralNormalization f).coeff i = if f.degree = i then 1 else coeff f i * f.leadingCoeff ^ (f.natDegree - 1 - i) := by have : f.coeff i = 0 → f.degree ≠ i := fun hc hd => coeff_ne_zero_of_eq_degree hd hc simp (config := { contextual := true }) [integralNormalization, coeff_monomial, this, mem_support_iff] #align polynomial.integral_normalization_coeff Polynomial.integralNormalization_coeff theorem integralNormalization_support {f : R[X]} : (integralNormalization f).support ⊆ f.support := by intro simp (config := { contextual := true }) [integralNormalization, coeff_monomial, mem_support_iff] #align polynomial.integral_normalization_support Polynomial.integralNormalization_support theorem integralNormalization_coeff_degree {f : R[X]} {i : ℕ} (hi : f.degree = i) : (integralNormalization f).coeff i = 1 := by rw [integralNormalization_coeff, if_pos hi] #align polynomial.integral_normalization_coeff_degree Polynomial.integralNormalization_coeff_degree theorem integralNormalization_coeff_natDegree {f : R[X]} (hf : f ≠ 0) : (integralNormalization f).coeff (natDegree f) = 1 := integralNormalization_coeff_degree (degree_eq_natDegree hf) #align polynomial.integral_normalization_coeff_nat_degree Polynomial.integralNormalization_coeff_natDegree
Mathlib/RingTheory/Polynomial/IntegralNormalization.lean
71
73
theorem integralNormalization_coeff_ne_degree {f : R[X]} {i : ℕ} (hi : f.degree ≠ i) : coeff (integralNormalization f) i = coeff f i * f.leadingCoeff ^ (f.natDegree - 1 - i) := by
rw [integralNormalization_coeff, if_neg hi]
/- Copyright (c) 2020 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison -/ import Mathlib.Algebra.Polynomial.Degree.Definitions import Mathlib.Algebra.Polynomial.Eval import Mathlib.Algebra.Polynomial.Monic import Mathlib.Algebra.Polynomial.RingDivision import Mathlib.Tactic.Abel #align_import ring_theory.polynomial.pochhammer from "leanprover-community/mathlib"@"53b216bcc1146df1c4a0a86877890ea9f1f01589" /-! # The Pochhammer polynomials We define and prove some basic relations about `ascPochhammer S n : S[X] := X * (X + 1) * ... * (X + n - 1)` which is also known as the rising factorial and about `descPochhammer R n : R[X] := X * (X - 1) * ... * (X - n + 1)` which is also known as the falling factorial. Versions of this definition that are focused on `Nat` can be found in `Data.Nat.Factorial` as `Nat.ascFactorial` and `Nat.descFactorial`. ## Implementation As with many other families of polynomials, even though the coefficients are always in `ℕ` or `ℤ` , we define the polynomial with coefficients in any `[Semiring S]` or `[Ring R]`. ## TODO There is lots more in this direction: * q-factorials, q-binomials, q-Pochhammer. -/ universe u v open Polynomial open Polynomial section Semiring variable (S : Type u) [Semiring S] /-- `ascPochhammer S n` is the polynomial `X * (X + 1) * ... * (X + n - 1)`, with coefficients in the semiring `S`. -/ noncomputable def ascPochhammer : ℕ → S[X] | 0 => 1 | n + 1 => X * (ascPochhammer n).comp (X + 1) #align pochhammer ascPochhammer @[simp] theorem ascPochhammer_zero : ascPochhammer S 0 = 1 := rfl #align pochhammer_zero ascPochhammer_zero @[simp] theorem ascPochhammer_one : ascPochhammer S 1 = X := by simp [ascPochhammer] #align pochhammer_one ascPochhammer_one theorem ascPochhammer_succ_left (n : ℕ) : ascPochhammer S (n + 1) = X * (ascPochhammer S n).comp (X + 1) := by rw [ascPochhammer] #align pochhammer_succ_left ascPochhammer_succ_left
Mathlib/RingTheory/Polynomial/Pochhammer.lean
69
76
theorem monic_ascPochhammer (n : ℕ) [Nontrivial S] [NoZeroDivisors S] : Monic <| ascPochhammer S n := by
induction' n with n hn · simp · have : leadingCoeff (X + 1 : S[X]) = 1 := leadingCoeff_X_add_C 1 rw [ascPochhammer_succ_left, Monic.def, leadingCoeff_mul, leadingCoeff_comp (ne_zero_of_eq_one <| natDegree_X_add_C 1 : natDegree (X + 1) ≠ 0), hn, monic_X, one_mul, one_mul, this, one_pow]
/- Copyright (c) 2020 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson -/ import Mathlib.Algebra.Order.BigOperators.Group.Finset import Mathlib.Data.Nat.Factors import Mathlib.Order.Interval.Finset.Nat #align_import number_theory.divisors from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3" /-! # Divisor Finsets This file defines sets of divisors of a natural number. This is particularly useful as background for defining Dirichlet convolution. ## Main Definitions Let `n : ℕ`. All of the following definitions are in the `Nat` namespace: * `divisors n` is the `Finset` of natural numbers that divide `n`. * `properDivisors n` is the `Finset` of natural numbers that divide `n`, other than `n`. * `divisorsAntidiagonal n` is the `Finset` of pairs `(x,y)` such that `x * y = n`. * `Perfect n` is true when `n` is positive and the sum of `properDivisors n` is `n`. ## Implementation details * `divisors 0`, `properDivisors 0`, and `divisorsAntidiagonal 0` are defined to be `∅`. ## Tags divisors, perfect numbers -/ open scoped Classical open Finset namespace Nat variable (n : ℕ) /-- `divisors n` is the `Finset` of divisors of `n`. As a special case, `divisors 0 = ∅`. -/ def divisors : Finset ℕ := Finset.filter (fun x : ℕ => x ∣ n) (Finset.Ico 1 (n + 1)) #align nat.divisors Nat.divisors /-- `properDivisors n` is the `Finset` of divisors of `n`, other than `n`. As a special case, `properDivisors 0 = ∅`. -/ def properDivisors : Finset ℕ := Finset.filter (fun x : ℕ => x ∣ n) (Finset.Ico 1 n) #align nat.proper_divisors Nat.properDivisors /-- `divisorsAntidiagonal n` is the `Finset` of pairs `(x,y)` such that `x * y = n`. As a special case, `divisorsAntidiagonal 0 = ∅`. -/ def divisorsAntidiagonal : Finset (ℕ × ℕ) := Finset.filter (fun x => x.fst * x.snd = n) (Ico 1 (n + 1) ×ˢ Ico 1 (n + 1)) #align nat.divisors_antidiagonal Nat.divisorsAntidiagonal variable {n} @[simp] theorem filter_dvd_eq_divisors (h : n ≠ 0) : (Finset.range n.succ).filter (· ∣ n) = n.divisors := by ext simp only [divisors, mem_filter, mem_range, mem_Ico, and_congr_left_iff, iff_and_self] exact fun ha _ => succ_le_iff.mpr (pos_of_dvd_of_pos ha h.bot_lt) #align nat.filter_dvd_eq_divisors Nat.filter_dvd_eq_divisors @[simp]
Mathlib/NumberTheory/Divisors.lean
68
72
theorem filter_dvd_eq_properDivisors (h : n ≠ 0) : (Finset.range n).filter (· ∣ n) = n.properDivisors := by
ext simp only [properDivisors, mem_filter, mem_range, mem_Ico, and_congr_left_iff, iff_and_self] exact fun ha _ => succ_le_iff.mpr (pos_of_dvd_of_pos ha h.bot_lt)
/- Copyright (c) 2022 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.GroupTheory.QuotientGroup #align_import algebra.char_zero.quotient from "leanprover-community/mathlib"@"d90e4e186f1d18e375dcd4e5b5f6364b01cb3e46" /-! # Lemmas about quotients in characteristic zero -/ variable {R : Type*} [DivisionRing R] [CharZero R] {p : R} namespace AddSubgroup /-- `z • r` is a multiple of `p` iff `r` is `pk/z` above a multiple of `p`, where `0 ≤ k < |z|`. -/ theorem zsmul_mem_zmultiples_iff_exists_sub_div {r : R} {z : ℤ} (hz : z ≠ 0) : z • r ∈ AddSubgroup.zmultiples p ↔ ∃ k : Fin z.natAbs, r - (k : ℕ) • (p / z : R) ∈ AddSubgroup.zmultiples p := by rw [AddSubgroup.mem_zmultiples_iff] simp_rw [AddSubgroup.mem_zmultiples_iff, div_eq_mul_inv, ← smul_mul_assoc, eq_sub_iff_add_eq] have hz' : (z : R) ≠ 0 := Int.cast_ne_zero.mpr hz conv_rhs => simp (config := { singlePass := true }) only [← (mul_right_injective₀ hz').eq_iff] simp_rw [← zsmul_eq_mul, smul_add, ← mul_smul_comm, zsmul_eq_mul (z : R)⁻¹, mul_inv_cancel hz', mul_one, ← natCast_zsmul, smul_smul, ← add_smul] constructor · rintro ⟨k, h⟩ simp_rw [← h] refine ⟨⟨(k % z).toNat, ?_⟩, k / z, ?_⟩ · rw [← Int.ofNat_lt, Int.toNat_of_nonneg (Int.emod_nonneg _ hz)] exact (Int.emod_lt _ hz).trans_eq (Int.abs_eq_natAbs _) rw [Fin.val_mk, Int.toNat_of_nonneg (Int.emod_nonneg _ hz)] nth_rewrite 3 [← Int.ediv_add_emod k z] rfl · rintro ⟨k, n, h⟩ exact ⟨_, h⟩ #align add_subgroup.zsmul_mem_zmultiples_iff_exists_sub_div AddSubgroup.zsmul_mem_zmultiples_iff_exists_sub_div theorem nsmul_mem_zmultiples_iff_exists_sub_div {r : R} {n : ℕ} (hn : n ≠ 0) : n • r ∈ AddSubgroup.zmultiples p ↔ ∃ k : Fin n, r - (k : ℕ) • (p / n : R) ∈ AddSubgroup.zmultiples p := by rw [← natCast_zsmul r, zsmul_mem_zmultiples_iff_exists_sub_div (Int.natCast_ne_zero.mpr hn), Int.cast_natCast] rfl #align add_subgroup.nsmul_mem_zmultiples_iff_exists_sub_div AddSubgroup.nsmul_mem_zmultiples_iff_exists_sub_div end AddSubgroup namespace QuotientAddGroup theorem zmultiples_zsmul_eq_zsmul_iff {ψ θ : R ⧸ AddSubgroup.zmultiples p} {z : ℤ} (hz : z ≠ 0) : z • ψ = z • θ ↔ ∃ k : Fin z.natAbs, ψ = θ + ((k : ℕ) • (p / z) : R) := by induction ψ using Quotient.inductionOn' induction θ using Quotient.inductionOn' -- Porting note: Introduced Zp notation to shorten lines let Zp := AddSubgroup.zmultiples p have : (Quotient.mk'' : R → R ⧸ Zp) = ((↑) : R → R ⧸ Zp) := rfl simp only [this] simp_rw [← QuotientAddGroup.mk_zsmul, ← QuotientAddGroup.mk_add, QuotientAddGroup.eq_iff_sub_mem, ← smul_sub, ← sub_sub] exact AddSubgroup.zsmul_mem_zmultiples_iff_exists_sub_div hz #align quotient_add_group.zmultiples_zsmul_eq_zsmul_iff QuotientAddGroup.zmultiples_zsmul_eq_zsmul_iff
Mathlib/Algebra/CharZero/Quotient.lean
67
71
theorem zmultiples_nsmul_eq_nsmul_iff {ψ θ : R ⧸ AddSubgroup.zmultiples p} {n : ℕ} (hz : n ≠ 0) : n • ψ = n • θ ↔ ∃ k : Fin n, ψ = θ + (k : ℕ) • (p / n : R) := by
rw [← natCast_zsmul ψ, ← natCast_zsmul θ, zmultiples_zsmul_eq_zsmul_iff (Int.natCast_ne_zero.mpr hz), Int.cast_natCast] rfl
/- Copyright (c) 2023 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.CategoryTheory.Monoidal.Transport import Mathlib.Algebra.Category.AlgebraCat.Basic import Mathlib.Algebra.Category.ModuleCat.Monoidal.Basic import Mathlib.RingTheory.TensorProduct.Basic /-! # The monoidal category structure on R-algebras -/ open CategoryTheory open scoped MonoidalCategory universe v u variable {R : Type u} [CommRing R] namespace AlgebraCat noncomputable section namespace instMonoidalCategory open scoped TensorProduct /-- Auxiliary definition used to fight a timeout when building `AlgebraCat.instMonoidalCategory`. -/ @[simps!] noncomputable abbrev tensorObj (X Y : AlgebraCat.{u} R) : AlgebraCat.{u} R := of R (X ⊗[R] Y) /-- Auxiliary definition used to fight a timeout when building `AlgebraCat.instMonoidalCategory`. -/ noncomputable abbrev tensorHom {W X Y Z : AlgebraCat.{u} R} (f : W ⟶ X) (g : Y ⟶ Z) : tensorObj W Y ⟶ tensorObj X Z := Algebra.TensorProduct.map f g open MonoidalCategory end instMonoidalCategory open instMonoidalCategory instance : MonoidalCategoryStruct (AlgebraCat.{u} R) where tensorObj := instMonoidalCategory.tensorObj whiskerLeft X _ _ f := tensorHom (𝟙 X) f whiskerRight {X₁ X₂} (f : X₁ ⟶ X₂) Y := tensorHom f (𝟙 Y) tensorHom := tensorHom tensorUnit := of R R associator X Y Z := (Algebra.TensorProduct.assoc R X Y Z).toAlgebraIso leftUnitor X := (Algebra.TensorProduct.lid R X).toAlgebraIso rightUnitor X := (Algebra.TensorProduct.rid R R X).toAlgebraIso
Mathlib/Algebra/Category/AlgebraCat/Monoidal.lean
58
64
theorem forget₂_map_associator_hom (X Y Z : AlgebraCat.{u} R) : (forget₂ (AlgebraCat R) (ModuleCat R)).map (α_ X Y Z).hom = (α_ (forget₂ _ (ModuleCat R) |>.obj X) (forget₂ _ (ModuleCat R) |>.obj Y) (forget₂ _ (ModuleCat R) |>.obj Z)).hom := by
rfl
/- Copyright (c) 2023 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Probability.Kernel.Basic import Mathlib.MeasureTheory.Constructions.Prod.Basic import Mathlib.MeasureTheory.Integral.DominatedConvergence #align_import probability.kernel.measurable_integral from "leanprover-community/mathlib"@"28b2a92f2996d28e580450863c130955de0ed398" /-! # Measurability of the integral against a kernel The Lebesgue integral of a measurable function against a kernel is measurable. The Bochner integral is strongly measurable. ## Main statements * `Measurable.lintegral_kernel_prod_right`: the function `a ↦ ∫⁻ b, f a b ∂(κ a)` is measurable, for an s-finite kernel `κ : kernel α β` and a function `f : α → β → ℝ≥0∞` such that `uncurry f` is measurable. * `MeasureTheory.StronglyMeasurable.integral_kernel_prod_right`: the function `a ↦ ∫ b, f a b ∂(κ a)` is measurable, for an s-finite kernel `κ : kernel α β` and a function `f : α → β → E` such that `uncurry f` is measurable. -/ open MeasureTheory ProbabilityTheory Function Set Filter open scoped MeasureTheory ENNReal Topology variable {α β γ : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} {κ : kernel α β} {η : kernel (α × β) γ} {a : α} namespace ProbabilityTheory namespace kernel /-- This is an auxiliary lemma for `measurable_kernel_prod_mk_left`. -/ theorem measurable_kernel_prod_mk_left_of_finite {t : Set (α × β)} (ht : MeasurableSet t) (hκs : ∀ a, IsFiniteMeasure (κ a)) : Measurable fun a => κ a (Prod.mk a ⁻¹' t) := by -- `t` is a measurable set in the product `α × β`: we use that the product σ-algebra is generated -- by boxes to prove the result by induction. -- Porting note: added motive refine MeasurableSpace.induction_on_inter (C := fun t => Measurable fun a => κ a (Prod.mk a ⁻¹' t)) generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ ht ·-- case `t = ∅` simp only [preimage_empty, measure_empty, measurable_const] · -- case of a box: `t = t₁ ×ˢ t₂` for measurable sets `t₁` and `t₂` intro t' ht' simp only [Set.mem_image2, Set.mem_setOf_eq, exists_and_left] at ht' obtain ⟨t₁, ht₁, t₂, ht₂, rfl⟩ := ht' classical simp_rw [mk_preimage_prod_right_eq_if] have h_eq_ite : (fun a => κ a (ite (a ∈ t₁) t₂ ∅)) = fun a => ite (a ∈ t₁) (κ a t₂) 0 := by ext1 a split_ifs exacts [rfl, measure_empty] rw [h_eq_ite] exact Measurable.ite ht₁ (kernel.measurable_coe κ ht₂) measurable_const · -- we assume that the result is true for `t` and we prove it for `tᶜ` intro t' ht' h_meas have h_eq_sdiff : ∀ a, Prod.mk a ⁻¹' t'ᶜ = Set.univ \ Prod.mk a ⁻¹' t' := by intro a ext1 b simp only [mem_compl_iff, mem_preimage, mem_diff, mem_univ, true_and_iff] simp_rw [h_eq_sdiff] have : (fun a => κ a (Set.univ \ Prod.mk a ⁻¹' t')) = fun a => κ a Set.univ - κ a (Prod.mk a ⁻¹' t') := by ext1 a rw [← Set.diff_inter_self_eq_diff, Set.inter_univ, measure_diff (Set.subset_univ _)] · exact (@measurable_prod_mk_left α β _ _ a) ht' · exact measure_ne_top _ _ rw [this] exact Measurable.sub (kernel.measurable_coe κ MeasurableSet.univ) h_meas · -- we assume that the result is true for a family of disjoint sets and prove it for their union intro f h_disj hf_meas hf have h_Union : (fun a => κ a (Prod.mk a ⁻¹' ⋃ i, f i)) = fun a => κ a (⋃ i, Prod.mk a ⁻¹' f i) := by ext1 a congr with b simp only [mem_iUnion, mem_preimage] rw [h_Union] have h_tsum : (fun a => κ a (⋃ i, Prod.mk a ⁻¹' f i)) = fun a => ∑' i, κ a (Prod.mk a ⁻¹' f i) := by ext1 a rw [measure_iUnion] · intro i j hij s hsi hsj b hbs have habi : {(a, b)} ⊆ f i := by rw [Set.singleton_subset_iff]; exact hsi hbs have habj : {(a, b)} ⊆ f j := by rw [Set.singleton_subset_iff]; exact hsj hbs simpa only [Set.bot_eq_empty, Set.le_eq_subset, Set.singleton_subset_iff, Set.mem_empty_iff_false] using h_disj hij habi habj · exact fun i => (@measurable_prod_mk_left α β _ _ a) (hf_meas i) rw [h_tsum] exact Measurable.ennreal_tsum hf #align probability_theory.kernel.measurable_kernel_prod_mk_left_of_finite ProbabilityTheory.kernel.measurable_kernel_prod_mk_left_of_finite
Mathlib/Probability/Kernel/MeasurableIntegral.lean
102
110
theorem measurable_kernel_prod_mk_left [IsSFiniteKernel κ] {t : Set (α × β)} (ht : MeasurableSet t) : Measurable fun a => κ a (Prod.mk a ⁻¹' t) := by
rw [← kernel.kernel_sum_seq κ] have : ∀ a, kernel.sum (kernel.seq κ) a (Prod.mk a ⁻¹' t) = ∑' n, kernel.seq κ n a (Prod.mk a ⁻¹' t) := fun a => kernel.sum_apply' _ _ (measurable_prod_mk_left ht) simp_rw [this] refine Measurable.ennreal_tsum fun n => ?_ exact measurable_kernel_prod_mk_left_of_finite ht inferInstance
/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Normed.Group.InfiniteSum import Mathlib.Topology.Instances.ENNReal #align_import analysis.calculus.series from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Continuity of series of functions We show that series of functions are continuous when each individual function in the series is and additionally suitable uniform summable bounds are satisfied, in `continuous_tsum`. For smoothness of series of functions, see the file `Analysis.Calculus.SmoothSeries`. -/ open Set Metric TopologicalSpace Function Filter open scoped Topology NNReal variable {α β F : Type*} [NormedAddCommGroup F] [CompleteSpace F] {u : α → ℝ} /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version relative to a set, with general index set. -/ theorem tendstoUniformlyOn_tsum {f : α → β → F} (hu : Summable u) {s : Set β} (hfu : ∀ n x, x ∈ s → ‖f n x‖ ≤ u n) : TendstoUniformlyOn (fun t : Finset α => fun x => ∑ n ∈ t, f n x) (fun x => ∑' n, f n x) atTop s := by refine tendstoUniformlyOn_iff.2 fun ε εpos => ?_ filter_upwards [(tendsto_order.1 (tendsto_tsum_compl_atTop_zero u)).2 _ εpos] with t ht x hx have A : Summable fun n => ‖f n x‖ := .of_nonneg_of_le (fun _ ↦ norm_nonneg _) (fun n => hfu n x hx) hu rw [dist_eq_norm, ← sum_add_tsum_subtype_compl A.of_norm t, add_sub_cancel_left] apply lt_of_le_of_lt _ ht apply (norm_tsum_le_tsum_norm (A.subtype _)).trans exact tsum_le_tsum (fun n => hfu _ _ hx) (A.subtype _) (hu.subtype _) #align tendsto_uniformly_on_tsum tendstoUniformlyOn_tsum /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version relative to a set, with index set `ℕ`. -/ theorem tendstoUniformlyOn_tsum_nat {f : ℕ → β → F} {u : ℕ → ℝ} (hu : Summable u) {s : Set β} (hfu : ∀ n x, x ∈ s → ‖f n x‖ ≤ u n) : TendstoUniformlyOn (fun N => fun x => ∑ n ∈ Finset.range N, f n x) (fun x => ∑' n, f n x) atTop s := fun v hv => tendsto_finset_range.eventually (tendstoUniformlyOn_tsum hu hfu v hv) #align tendsto_uniformly_on_tsum_nat tendstoUniformlyOn_tsum_nat /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version with general index set. -/ theorem tendstoUniformly_tsum {f : α → β → F} (hu : Summable u) (hfu : ∀ n x, ‖f n x‖ ≤ u n) : TendstoUniformly (fun t : Finset α => fun x => ∑ n ∈ t, f n x) (fun x => ∑' n, f n x) atTop := by rw [← tendstoUniformlyOn_univ]; exact tendstoUniformlyOn_tsum hu fun n x _ => hfu n x #align tendsto_uniformly_tsum tendstoUniformly_tsum /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version with index set `ℕ`. -/ theorem tendstoUniformly_tsum_nat {f : ℕ → β → F} {u : ℕ → ℝ} (hu : Summable u) (hfu : ∀ n x, ‖f n x‖ ≤ u n) : TendstoUniformly (fun N => fun x => ∑ n ∈ Finset.range N, f n x) (fun x => ∑' n, f n x) atTop := fun v hv => tendsto_finset_range.eventually (tendstoUniformly_tsum hu hfu v hv) #align tendsto_uniformly_tsum_nat tendstoUniformly_tsum_nat /-- An infinite sum of functions with summable sup norm is continuous on a set if each individual function is. -/
Mathlib/Analysis/NormedSpace/FunctionSeries.lean
70
76
theorem continuousOn_tsum [TopologicalSpace β] {f : α → β → F} {s : Set β} (hf : ∀ i, ContinuousOn (f i) s) (hu : Summable u) (hfu : ∀ n x, x ∈ s → ‖f n x‖ ≤ u n) : ContinuousOn (fun x => ∑' n, f n x) s := by
classical refine (tendstoUniformlyOn_tsum hu hfu).continuousOn (eventually_of_forall ?_) intro t exact continuousOn_finset_sum _ fun i _ => hf i
/- Copyright (c) 2022 Pim Otte. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kyle Miller, Pim Otte -/ import Mathlib.Algebra.BigOperators.Fin import Mathlib.Data.Nat.Choose.Sum import Mathlib.Data.Nat.Factorial.BigOperators import Mathlib.Data.Fin.VecNotation import Mathlib.Data.Finset.Sym import Mathlib.Data.Finsupp.Multiset #align_import data.nat.choose.multinomial from "leanprover-community/mathlib"@"2738d2ca56cbc63be80c3bd48e9ed90ad94e947d" /-! # Multinomial This file defines the multinomial coefficient and several small lemma's for manipulating it. ## Main declarations - `Nat.multinomial`: the multinomial coefficient ## Main results - `Finset.sum_pow`: The expansion of `(s.sum x) ^ n` using multinomial coefficients -/ open Finset open scoped Nat namespace Nat variable {α : Type*} (s : Finset α) (f : α → ℕ) {a b : α} (n : ℕ) /-- The multinomial coefficient. Gives the number of strings consisting of symbols from `s`, where `c ∈ s` appears with multiplicity `f c`. Defined as `(∑ i ∈ s, f i)! / ∏ i ∈ s, (f i)!`. -/ def multinomial : ℕ := (∑ i ∈ s, f i)! / ∏ i ∈ s, (f i)! #align nat.multinomial Nat.multinomial theorem multinomial_pos : 0 < multinomial s f := Nat.div_pos (le_of_dvd (factorial_pos _) (prod_factorial_dvd_factorial_sum s f)) (prod_factorial_pos s f) #align nat.multinomial_pos Nat.multinomial_pos theorem multinomial_spec : (∏ i ∈ s, (f i)!) * multinomial s f = (∑ i ∈ s, f i)! := Nat.mul_div_cancel' (prod_factorial_dvd_factorial_sum s f) #align nat.multinomial_spec Nat.multinomial_spec @[simp] lemma multinomial_empty : multinomial ∅ f = 1 := by simp [multinomial] #align nat.multinomial_nil Nat.multinomial_empty @[deprecated (since := "2024-06-01")] alias multinomial_nil := multinomial_empty variable {s f} lemma multinomial_cons (ha : a ∉ s) (f : α → ℕ) : multinomial (s.cons a ha) f = (f a + ∑ i ∈ s, f i).choose (f a) * multinomial s f := by rw [multinomial, Nat.div_eq_iff_eq_mul_left _ (prod_factorial_dvd_factorial_sum _ _), prod_cons, multinomial, mul_assoc, mul_left_comm _ (f a)!, Nat.div_mul_cancel (prod_factorial_dvd_factorial_sum _ _), ← mul_assoc, Nat.choose_symm_add, Nat.add_choose_mul_factorial_mul_factorial, Finset.sum_cons] positivity lemma multinomial_insert [DecidableEq α] (ha : a ∉ s) (f : α → ℕ) : multinomial (insert a s) f = (f a + ∑ i ∈ s, f i).choose (f a) * multinomial s f := by rw [← cons_eq_insert _ _ ha, multinomial_cons] #align nat.multinomial_insert Nat.multinomial_insert @[simp] lemma multinomial_singleton (a : α) (f : α → ℕ) : multinomial {a} f = 1 := by rw [← cons_empty, multinomial_cons]; simp #align nat.multinomial_singleton Nat.multinomial_singleton @[simp] theorem multinomial_insert_one [DecidableEq α] (h : a ∉ s) (h₁ : f a = 1) : multinomial (insert a s) f = (s.sum f).succ * multinomial s f := by simp only [multinomial, one_mul, factorial] rw [Finset.sum_insert h, Finset.prod_insert h, h₁, add_comm, ← succ_eq_add_one, factorial_succ] simp only [factorial_one, one_mul, Function.comp_apply, factorial, mul_one, ← one_eq_succ_zero] rw [Nat.mul_div_assoc _ (prod_factorial_dvd_factorial_sum _ _)] #align nat.multinomial_insert_one Nat.multinomial_insert_one theorem multinomial_congr {f g : α → ℕ} (h : ∀ a ∈ s, f a = g a) : multinomial s f = multinomial s g := by simp only [multinomial]; congr 1 · rw [Finset.sum_congr rfl h] · exact Finset.prod_congr rfl fun a ha => by rw [h a ha] #align nat.multinomial_congr Nat.multinomial_congr /-! ### Connection to binomial coefficients When `Nat.multinomial` is applied to a `Finset` of two elements `{a, b}`, the result a binomial coefficient. We use `binomial` in the names of lemmas that involves `Nat.multinomial {a, b}`. -/
Mathlib/Data/Nat/Choose/Multinomial.lean
102
104
theorem binomial_eq [DecidableEq α] (h : a ≠ b) : multinomial {a, b} f = (f a + f b)! / ((f a)! * (f b)!) := by
simp [multinomial, Finset.sum_pair h, Finset.prod_pair h]
/- Copyright (c) 2021 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Yaël Dillies -/ import Mathlib.Analysis.Normed.Group.Pointwise import Mathlib.Analysis.NormedSpace.Real #align_import analysis.normed_space.pointwise from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156" /-! # Properties of pointwise scalar multiplication of sets in normed spaces. We explore the relationships between scalar multiplication of sets in vector spaces, and the norm. Notably, we express arbitrary balls as rescaling of other balls, and we show that the multiplication of bounded sets remain bounded. -/ open Metric Set open Pointwise Topology variable {𝕜 E : Type*} section SMulZeroClass variable [SeminormedAddCommGroup 𝕜] [SeminormedAddCommGroup E] variable [SMulZeroClass 𝕜 E] [BoundedSMul 𝕜 E] theorem ediam_smul_le (c : 𝕜) (s : Set E) : EMetric.diam (c • s) ≤ ‖c‖₊ • EMetric.diam s := (lipschitzWith_smul c).ediam_image_le s #align ediam_smul_le ediam_smul_le end SMulZeroClass section DivisionRing variable [NormedDivisionRing 𝕜] [SeminormedAddCommGroup E] variable [Module 𝕜 E] [BoundedSMul 𝕜 E] theorem ediam_smul₀ (c : 𝕜) (s : Set E) : EMetric.diam (c • s) = ‖c‖₊ • EMetric.diam s := by refine le_antisymm (ediam_smul_le c s) ?_ obtain rfl | hc := eq_or_ne c 0 · obtain rfl | hs := s.eq_empty_or_nonempty · simp simp [zero_smul_set hs, ← Set.singleton_zero] · have := (lipschitzWith_smul c⁻¹).ediam_image_le (c • s) rwa [← smul_eq_mul, ← ENNReal.smul_def, Set.image_smul, inv_smul_smul₀ hc s, nnnorm_inv, le_inv_smul_iff_of_pos (nnnorm_pos.2 hc)] at this #align ediam_smul₀ ediam_smul₀ theorem diam_smul₀ (c : 𝕜) (x : Set E) : diam (c • x) = ‖c‖ * diam x := by simp_rw [diam, ediam_smul₀, ENNReal.toReal_smul, NNReal.smul_def, coe_nnnorm, smul_eq_mul] #align diam_smul₀ diam_smul₀ theorem infEdist_smul₀ {c : 𝕜} (hc : c ≠ 0) (s : Set E) (x : E) : EMetric.infEdist (c • x) (c • s) = ‖c‖₊ • EMetric.infEdist x s := by simp_rw [EMetric.infEdist] have : Function.Surjective ((c • ·) : E → E) := Function.RightInverse.surjective (smul_inv_smul₀ hc) trans ⨅ (y) (_ : y ∈ s), ‖c‖₊ • edist x y · refine (this.iInf_congr _ fun y => ?_).symm simp_rw [smul_mem_smul_set_iff₀ hc, edist_smul₀] · have : (‖c‖₊ : ENNReal) ≠ 0 := by simp [hc] simp_rw [ENNReal.smul_def, smul_eq_mul, ENNReal.mul_iInf_of_ne this ENNReal.coe_ne_top] #align inf_edist_smul₀ infEdist_smul₀ theorem infDist_smul₀ {c : 𝕜} (hc : c ≠ 0) (s : Set E) (x : E) : Metric.infDist (c • x) (c • s) = ‖c‖ * Metric.infDist x s := by simp_rw [Metric.infDist, infEdist_smul₀ hc s, ENNReal.toReal_smul, NNReal.smul_def, coe_nnnorm, smul_eq_mul] #align inf_dist_smul₀ infDist_smul₀ end DivisionRing variable [NormedField 𝕜] section SeminormedAddCommGroup variable [SeminormedAddCommGroup E] [NormedSpace 𝕜 E] theorem smul_ball {c : 𝕜} (hc : c ≠ 0) (x : E) (r : ℝ) : c • ball x r = ball (c • x) (‖c‖ * r) := by ext y rw [mem_smul_set_iff_inv_smul_mem₀ hc] conv_lhs => rw [← inv_smul_smul₀ hc x] simp [← div_eq_inv_mul, div_lt_iff (norm_pos_iff.2 hc), mul_comm _ r, dist_smul₀] #align smul_ball smul_ball
Mathlib/Analysis/NormedSpace/Pointwise.lean
91
92
theorem smul_unitBall {c : 𝕜} (hc : c ≠ 0) : c • ball (0 : E) (1 : ℝ) = ball (0 : E) ‖c‖ := by
rw [_root_.smul_ball hc, smul_zero, mul_one]
/- Copyright (c) 2021 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Algebra.Lie.Abelian import Mathlib.Algebra.Lie.IdealOperations import Mathlib.Order.Hom.Basic #align_import algebra.lie.solvable from "leanprover-community/mathlib"@"a50170a88a47570ed186b809ca754110590f9476" /-! # Solvable Lie algebras Like groups, Lie algebras admit a natural concept of solvability. We define this here via the derived series and prove some related results. We also define the radical of a Lie algebra and prove that it is solvable when the Lie algebra is Noetherian. ## Main definitions * `LieAlgebra.derivedSeriesOfIdeal` * `LieAlgebra.derivedSeries` * `LieAlgebra.IsSolvable` * `LieAlgebra.isSolvableAdd` * `LieAlgebra.radical` * `LieAlgebra.radicalIsSolvable` * `LieAlgebra.derivedLengthOfIdeal` * `LieAlgebra.derivedLength` * `LieAlgebra.derivedAbelianOfIdeal` ## Tags lie algebra, derived series, derived length, solvable, radical -/ universe u v w w₁ w₂ variable (R : Type u) (L : Type v) (M : Type w) {L' : Type w₁} variable [CommRing R] [LieRing L] [LieAlgebra R L] [LieRing L'] [LieAlgebra R L'] variable (I J : LieIdeal R L) {f : L' →ₗ⁅R⁆ L} namespace LieAlgebra /-- A generalisation of the derived series of a Lie algebra, whose zeroth term is a specified ideal. It can be more convenient to work with this generalisation when considering the derived series of an ideal since it provides a type-theoretic expression of the fact that the terms of the ideal's derived series are also ideals of the enclosing algebra. See also `LieIdeal.derivedSeries_eq_derivedSeriesOfIdeal_comap` and `LieIdeal.derivedSeries_eq_derivedSeriesOfIdeal_map` below. -/ def derivedSeriesOfIdeal (k : ℕ) : LieIdeal R L → LieIdeal R L := (fun I => ⁅I, I⁆)^[k] #align lie_algebra.derived_series_of_ideal LieAlgebra.derivedSeriesOfIdeal @[simp] theorem derivedSeriesOfIdeal_zero : derivedSeriesOfIdeal R L 0 I = I := rfl #align lie_algebra.derived_series_of_ideal_zero LieAlgebra.derivedSeriesOfIdeal_zero @[simp] theorem derivedSeriesOfIdeal_succ (k : ℕ) : derivedSeriesOfIdeal R L (k + 1) I = ⁅derivedSeriesOfIdeal R L k I, derivedSeriesOfIdeal R L k I⁆ := Function.iterate_succ_apply' (fun I => ⁅I, I⁆) k I #align lie_algebra.derived_series_of_ideal_succ LieAlgebra.derivedSeriesOfIdeal_succ /-- The derived series of Lie ideals of a Lie algebra. -/ abbrev derivedSeries (k : ℕ) : LieIdeal R L := derivedSeriesOfIdeal R L k ⊤ #align lie_algebra.derived_series LieAlgebra.derivedSeries theorem derivedSeries_def (k : ℕ) : derivedSeries R L k = derivedSeriesOfIdeal R L k ⊤ := rfl #align lie_algebra.derived_series_def LieAlgebra.derivedSeries_def variable {R L} local notation "D" => derivedSeriesOfIdeal R L
Mathlib/Algebra/Lie/Solvable.lean
82
85
theorem derivedSeriesOfIdeal_add (k l : ℕ) : D (k + l) I = D k (D l I) := by
induction' k with k ih · rw [Nat.zero_add, derivedSeriesOfIdeal_zero] · rw [Nat.succ_add k l, derivedSeriesOfIdeal_succ, derivedSeriesOfIdeal_succ, ih]
/- Copyright (c) 2023 David Loeffler. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: David Loeffler -/ import Mathlib.NumberTheory.ModularForms.JacobiTheta.TwoVariable import Mathlib.Analysis.Complex.UpperHalfPlane.Basic #align_import number_theory.modular_forms.jacobi_theta.basic from "leanprover-community/mathlib"@"57f9349f2fe19d2de7207e99b0341808d977cdcf" /-! # Jacobi's theta function This file defines the one-variable Jacobi theta function $$\theta(\tau) = \sum_{n \in \mathbb{Z}} \exp (i \pi n ^ 2 \tau),$$ and proves the modular transformation properties `θ (τ + 2) = θ τ` and `θ (-1 / τ) = (-I * τ) ^ (1 / 2) * θ τ`, using Poisson's summation formula for the latter. We also show that `θ` is differentiable on `ℍ`, and `θ(τ) - 1` has exponential decay as `im τ → ∞`. -/ open Complex Real Asymptotics Filter Topology open scoped Real UpperHalfPlane /-- Jacobi's one-variable theta function `∑' (n : ℤ), exp (π * I * n ^ 2 * τ)`. -/ noncomputable def jacobiTheta (τ : ℂ) : ℂ := ∑' n : ℤ, cexp (π * I * (n : ℂ) ^ 2 * τ) #align jacobi_theta jacobiTheta lemma jacobiTheta_eq_jacobiTheta₂ (τ : ℂ) : jacobiTheta τ = jacobiTheta₂ 0 τ := tsum_congr (by simp [jacobiTheta₂_term]) theorem jacobiTheta_two_add (τ : ℂ) : jacobiTheta (2 + τ) = jacobiTheta τ := by simp_rw [jacobiTheta_eq_jacobiTheta₂, add_comm, jacobiTheta₂_add_right] #align jacobi_theta_two_add jacobiTheta_two_add theorem jacobiTheta_T_sq_smul (τ : ℍ) : jacobiTheta (ModularGroup.T ^ 2 • τ :) = jacobiTheta τ := by suffices (ModularGroup.T ^ 2 • τ :) = (2 : ℂ) + ↑τ by simp_rw [this, jacobiTheta_two_add] have : ModularGroup.T ^ (2 : ℕ) = ModularGroup.T ^ (2 : ℤ) := rfl simp_rw [this, UpperHalfPlane.modular_T_zpow_smul, UpperHalfPlane.coe_vadd] norm_cast set_option linter.uppercaseLean3 false in #align jacobi_theta_T_sq_smul jacobiTheta_T_sq_smul theorem jacobiTheta_S_smul (τ : ℍ) : jacobiTheta ↑(ModularGroup.S • τ) = (-I * τ) ^ (1 / 2 : ℂ) * jacobiTheta τ := by have h0 : (τ : ℂ) ≠ 0 := ne_of_apply_ne im (zero_im.symm ▸ ne_of_gt τ.2) have h1 : (-I * τ) ^ (1 / 2 : ℂ) ≠ 0 := by rw [Ne, cpow_eq_zero_iff, not_and_or] exact Or.inl <| mul_ne_zero (neg_ne_zero.mpr I_ne_zero) h0 simp_rw [UpperHalfPlane.modular_S_smul, jacobiTheta_eq_jacobiTheta₂] conv_rhs => erw [← ofReal_zero, jacobiTheta₂_functional_equation 0 τ] rw [zero_pow two_ne_zero, mul_zero, zero_div, Complex.exp_zero, mul_one, ← mul_assoc, mul_one_div, div_self h1, one_mul, UpperHalfPlane.coe_mk, inv_neg, neg_div, one_div] set_option linter.uppercaseLean3 false in #align jacobi_theta_S_smul jacobiTheta_S_smul theorem norm_exp_mul_sq_le {τ : ℂ} (hτ : 0 < τ.im) (n : ℤ) : ‖cexp (π * I * (n : ℂ) ^ 2 * τ)‖ ≤ rexp (-π * τ.im) ^ n.natAbs := by let y := rexp (-π * τ.im) have h : y < 1 := exp_lt_one_iff.mpr (mul_neg_of_neg_of_pos (neg_lt_zero.mpr pi_pos) hτ) refine (le_of_eq ?_).trans (?_ : y ^ n ^ 2 ≤ _) · rw [Complex.norm_eq_abs, Complex.abs_exp] have : (π * I * n ^ 2 * τ : ℂ).re = -π * τ.im * (n : ℝ) ^ 2 := by rw [(by push_cast; ring : (π * I * n ^ 2 * τ : ℂ) = (π * n ^ 2 : ℝ) * (τ * I)), re_ofReal_mul, mul_I_re] ring obtain ⟨m, hm⟩ := Int.eq_ofNat_of_zero_le (sq_nonneg n) rw [this, exp_mul, ← Int.cast_pow, rpow_intCast, hm, zpow_natCast] · have : n ^ 2 = (n.natAbs ^ 2 :) := by rw [Nat.cast_pow, Int.natAbs_sq] rw [this, zpow_natCast] exact pow_le_pow_of_le_one (exp_pos _).le h.le ((sq n.natAbs).symm ▸ n.natAbs.le_mul_self) #align norm_exp_mul_sq_le norm_exp_mul_sq_le
Mathlib/NumberTheory/ModularForms/JacobiTheta/OneVariable.lean
75
86
theorem hasSum_nat_jacobiTheta {τ : ℂ} (hτ : 0 < im τ) : HasSum (fun n : ℕ => cexp (π * I * ((n : ℂ) + 1) ^ 2 * τ)) ((jacobiTheta τ - 1) / 2) := by
have := hasSum_jacobiTheta₂_term 0 hτ simp_rw [jacobiTheta₂_term, mul_zero, zero_add, ← jacobiTheta_eq_jacobiTheta₂] at this have := this.nat_add_neg rw [← hasSum_nat_add_iff' 1] at this simp_rw [Finset.sum_range_one, Int.cast_neg, Int.cast_natCast, Nat.cast_zero, neg_zero, Int.cast_zero, sq (0 : ℂ), mul_zero, zero_mul, neg_sq, ← mul_two, Complex.exp_zero, add_sub_assoc, (by norm_num : (1 : ℂ) - 1 * 2 = -1), ← sub_eq_add_neg, Nat.cast_add, Nat.cast_one] at this convert this.div_const 2 using 1 simp_rw [mul_div_cancel_right₀ _ (two_ne_zero' ℂ)]
/- Copyright (c) 2017 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Stephen Morgan, Scott Morrison -/ import Mathlib.CategoryTheory.Products.Basic #align_import category_theory.products.bifunctor from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988" /-! # Lemmas about functors out of product categories. -/ open CategoryTheory namespace CategoryTheory.Bifunctor universe v₁ v₂ v₃ u₁ u₂ u₃ variable {C : Type u₁} {D : Type u₂} {E : Type u₃} variable [Category.{v₁} C] [Category.{v₂} D] [Category.{v₃} E] @[simp] theorem map_id (F : C × D ⥤ E) (X : C) (Y : D) : F.map ((𝟙 X, 𝟙 Y) : (X, Y) ⟶ (X, Y)) = 𝟙 (F.obj (X, Y)) := F.map_id (X, Y) #align category_theory.bifunctor.map_id CategoryTheory.Bifunctor.map_id @[simp] theorem map_id_comp (F : C × D ⥤ E) (W : C) {X Y Z : D} (f : X ⟶ Y) (g : Y ⟶ Z) : F.map ((𝟙 W, f ≫ g) : (W, X) ⟶ (W, Z)) = F.map ((𝟙 W, f) : (W, X) ⟶ (W, Y)) ≫ F.map ((𝟙 W, g) : (W, Y) ⟶ (W, Z)) := by rw [← Functor.map_comp, prod_comp, Category.comp_id] #align category_theory.bifunctor.map_id_comp CategoryTheory.Bifunctor.map_id_comp @[simp] theorem map_comp_id (F : C × D ⥤ E) (X Y Z : C) (W : D) (f : X ⟶ Y) (g : Y ⟶ Z) : F.map ((f ≫ g, 𝟙 W) : (X, W) ⟶ (Z, W)) = F.map ((f, 𝟙 W) : (X, W) ⟶ (Y, W)) ≫ F.map ((g, 𝟙 W) : (Y, W) ⟶ (Z, W)) := by rw [← Functor.map_comp, prod_comp, Category.comp_id] #align category_theory.bifunctor.map_comp_id CategoryTheory.Bifunctor.map_comp_id @[simp] theorem diagonal (F : C × D ⥤ E) (X X' : C) (f : X ⟶ X') (Y Y' : D) (g : Y ⟶ Y') : F.map ((𝟙 X, g) : (X, Y) ⟶ (X, Y')) ≫ F.map ((f, 𝟙 Y') : (X, Y') ⟶ (X', Y')) = F.map ((f, g) : (X, Y) ⟶ (X', Y')) := by rw [← Functor.map_comp, prod_comp, Category.id_comp, Category.comp_id] #align category_theory.bifunctor.diagonal CategoryTheory.Bifunctor.diagonal @[simp]
Mathlib/CategoryTheory/Products/Bifunctor.lean
52
55
theorem diagonal' (F : C × D ⥤ E) (X X' : C) (f : X ⟶ X') (Y Y' : D) (g : Y ⟶ Y') : F.map ((f, 𝟙 Y) : (X, Y) ⟶ (X', Y)) ≫ F.map ((𝟙 X', g) : (X', Y) ⟶ (X', Y')) = F.map ((f, g) : (X, Y) ⟶ (X', Y')) := by
rw [← Functor.map_comp, prod_comp, Category.id_comp, Category.comp_id]
/- Copyright (c) 2022 Yury G. Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury G. Kudryashov -/ import Mathlib.Data.Set.Image import Mathlib.Order.Interval.Set.Basic #align_import data.set.intervals.with_bot_top from "leanprover-community/mathlib"@"d012cd09a9b256d870751284dd6a29882b0be105" /-! # Intervals in `WithTop α` and `WithBot α` In this file we prove various lemmas about `Set.image`s and `Set.preimage`s of intervals under `some : α → WithTop α` and `some : α → WithBot α`. -/ open Set variable {α : Type*} /-! ### `WithTop` -/ namespace WithTop @[simp] theorem preimage_coe_top : (some : α → WithTop α) ⁻¹' {⊤} = (∅ : Set α) := eq_empty_of_subset_empty fun _ => coe_ne_top #align with_top.preimage_coe_top WithTop.preimage_coe_top variable [Preorder α] {a b : α} theorem range_coe : range (some : α → WithTop α) = Iio ⊤ := by ext x rw [mem_Iio, WithTop.lt_top_iff_ne_top, mem_range, ne_top_iff_exists] #align with_top.range_coe WithTop.range_coe @[simp] theorem preimage_coe_Ioi : (some : α → WithTop α) ⁻¹' Ioi a = Ioi a := ext fun _ => coe_lt_coe #align with_top.preimage_coe_Ioi WithTop.preimage_coe_Ioi @[simp] theorem preimage_coe_Ici : (some : α → WithTop α) ⁻¹' Ici a = Ici a := ext fun _ => coe_le_coe #align with_top.preimage_coe_Ici WithTop.preimage_coe_Ici @[simp] theorem preimage_coe_Iio : (some : α → WithTop α) ⁻¹' Iio a = Iio a := ext fun _ => coe_lt_coe #align with_top.preimage_coe_Iio WithTop.preimage_coe_Iio @[simp] theorem preimage_coe_Iic : (some : α → WithTop α) ⁻¹' Iic a = Iic a := ext fun _ => coe_le_coe #align with_top.preimage_coe_Iic WithTop.preimage_coe_Iic @[simp] theorem preimage_coe_Icc : (some : α → WithTop α) ⁻¹' Icc a b = Icc a b := by simp [← Ici_inter_Iic] #align with_top.preimage_coe_Icc WithTop.preimage_coe_Icc @[simp] theorem preimage_coe_Ico : (some : α → WithTop α) ⁻¹' Ico a b = Ico a b := by simp [← Ici_inter_Iio] #align with_top.preimage_coe_Ico WithTop.preimage_coe_Ico @[simp] theorem preimage_coe_Ioc : (some : α → WithTop α) ⁻¹' Ioc a b = Ioc a b := by simp [← Ioi_inter_Iic] #align with_top.preimage_coe_Ioc WithTop.preimage_coe_Ioc @[simp] theorem preimage_coe_Ioo : (some : α → WithTop α) ⁻¹' Ioo a b = Ioo a b := by simp [← Ioi_inter_Iio] #align with_top.preimage_coe_Ioo WithTop.preimage_coe_Ioo @[simp] theorem preimage_coe_Iio_top : (some : α → WithTop α) ⁻¹' Iio ⊤ = univ := by rw [← range_coe, preimage_range] #align with_top.preimage_coe_Iio_top WithTop.preimage_coe_Iio_top @[simp] theorem preimage_coe_Ico_top : (some : α → WithTop α) ⁻¹' Ico a ⊤ = Ici a := by simp [← Ici_inter_Iio] #align with_top.preimage_coe_Ico_top WithTop.preimage_coe_Ico_top @[simp] theorem preimage_coe_Ioo_top : (some : α → WithTop α) ⁻¹' Ioo a ⊤ = Ioi a := by simp [← Ioi_inter_Iio] #align with_top.preimage_coe_Ioo_top WithTop.preimage_coe_Ioo_top theorem image_coe_Ioi : (some : α → WithTop α) '' Ioi a = Ioo (a : WithTop α) ⊤ := by rw [← preimage_coe_Ioi, image_preimage_eq_inter_range, range_coe, Ioi_inter_Iio] #align with_top.image_coe_Ioi WithTop.image_coe_Ioi theorem image_coe_Ici : (some : α → WithTop α) '' Ici a = Ico (a : WithTop α) ⊤ := by rw [← preimage_coe_Ici, image_preimage_eq_inter_range, range_coe, Ici_inter_Iio] #align with_top.image_coe_Ici WithTop.image_coe_Ici theorem image_coe_Iio : (some : α → WithTop α) '' Iio a = Iio (a : WithTop α) := by rw [← preimage_coe_Iio, image_preimage_eq_inter_range, range_coe, inter_eq_self_of_subset_left (Iio_subset_Iio le_top)] #align with_top.image_coe_Iio WithTop.image_coe_Iio
Mathlib/Order/Interval/Set/WithBotTop.lean
102
104
theorem image_coe_Iic : (some : α → WithTop α) '' Iic a = Iic (a : WithTop α) := by
rw [← preimage_coe_Iic, image_preimage_eq_inter_range, range_coe, inter_eq_self_of_subset_left (Iic_subset_Iio.2 <| coe_lt_top a)]
/- Copyright (c) 2019 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Sébastien Gouëzel, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.FDeriv.Basic #align_import analysis.calculus.fderiv.restrict_scalars from "leanprover-community/mathlib"@"e3fb84046afd187b710170887195d50bada934ee" /-! # The derivative of the scalar restriction of a linear map For detailed documentation of the Fréchet derivative, see the module docstring of `Analysis/Calculus/FDeriv/Basic.lean`. This file contains the usual formulas (and existence assertions) for the derivative of the scalar restriction of a linear map. -/ open Filter Asymptotics ContinuousLinearMap Set Metric open scoped Classical open Topology NNReal Filter Asymptotics ENNReal noncomputable section section RestrictScalars /-! ### Restricting from `ℂ` to `ℝ`, or generally from `𝕜'` to `𝕜` If a function is differentiable over `ℂ`, then it is differentiable over `ℝ`. In this paragraph, we give variants of this statement, in the general situation where `ℂ` and `ℝ` are replaced respectively by `𝕜'` and `𝕜` where `𝕜'` is a normed algebra over `𝕜`. -/ variable (𝕜 : Type*) [NontriviallyNormedField 𝕜] variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedSpace 𝕜' E] variable [IsScalarTower 𝕜 𝕜' E] variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedSpace 𝕜' F] variable [IsScalarTower 𝕜 𝕜' F] variable {f : E → F} {f' : E →L[𝕜'] F} {s : Set E} {x : E} @[fun_prop] theorem HasStrictFDerivAt.restrictScalars (h : HasStrictFDerivAt f f' x) : HasStrictFDerivAt f (f'.restrictScalars 𝕜) x := h #align has_strict_fderiv_at.restrict_scalars HasStrictFDerivAt.restrictScalars theorem HasFDerivAtFilter.restrictScalars {L} (h : HasFDerivAtFilter f f' x L) : HasFDerivAtFilter f (f'.restrictScalars 𝕜) x L := .of_isLittleO h.1 #align has_fderiv_at_filter.restrict_scalars HasFDerivAtFilter.restrictScalars @[fun_prop] theorem HasFDerivAt.restrictScalars (h : HasFDerivAt f f' x) : HasFDerivAt f (f'.restrictScalars 𝕜) x := .of_isLittleO h.1 #align has_fderiv_at.restrict_scalars HasFDerivAt.restrictScalars @[fun_prop] theorem HasFDerivWithinAt.restrictScalars (h : HasFDerivWithinAt f f' s x) : HasFDerivWithinAt f (f'.restrictScalars 𝕜) s x := .of_isLittleO h.1 #align has_fderiv_within_at.restrict_scalars HasFDerivWithinAt.restrictScalars @[fun_prop] theorem DifferentiableAt.restrictScalars (h : DifferentiableAt 𝕜' f x) : DifferentiableAt 𝕜 f x := (h.hasFDerivAt.restrictScalars 𝕜).differentiableAt #align differentiable_at.restrict_scalars DifferentiableAt.restrictScalars @[fun_prop] theorem DifferentiableWithinAt.restrictScalars (h : DifferentiableWithinAt 𝕜' f s x) : DifferentiableWithinAt 𝕜 f s x := (h.hasFDerivWithinAt.restrictScalars 𝕜).differentiableWithinAt #align differentiable_within_at.restrict_scalars DifferentiableWithinAt.restrictScalars @[fun_prop] theorem DifferentiableOn.restrictScalars (h : DifferentiableOn 𝕜' f s) : DifferentiableOn 𝕜 f s := fun x hx => (h x hx).restrictScalars 𝕜 #align differentiable_on.restrict_scalars DifferentiableOn.restrictScalars @[fun_prop] theorem Differentiable.restrictScalars (h : Differentiable 𝕜' f) : Differentiable 𝕜 f := fun x => (h x).restrictScalars 𝕜 #align differentiable.restrict_scalars Differentiable.restrictScalars @[fun_prop] theorem HasFDerivWithinAt.of_restrictScalars {g' : E →L[𝕜] F} (h : HasFDerivWithinAt f g' s x) (H : f'.restrictScalars 𝕜 = g') : HasFDerivWithinAt f f' s x := by rw [← H] at h exact .of_isLittleO h.1 #align has_fderiv_within_at_of_restrict_scalars HasFDerivWithinAt.of_restrictScalars @[fun_prop] theorem hasFDerivAt_of_restrictScalars {g' : E →L[𝕜] F} (h : HasFDerivAt f g' x) (H : f'.restrictScalars 𝕜 = g') : HasFDerivAt f f' x := by rw [← H] at h exact .of_isLittleO h.1 #align has_fderiv_at_of_restrict_scalars hasFDerivAt_of_restrictScalars theorem DifferentiableAt.fderiv_restrictScalars (h : DifferentiableAt 𝕜' f x) : fderiv 𝕜 f x = (fderiv 𝕜' f x).restrictScalars 𝕜 := (h.hasFDerivAt.restrictScalars 𝕜).fderiv #align differentiable_at.fderiv_restrict_scalars DifferentiableAt.fderiv_restrictScalars theorem differentiableWithinAt_iff_restrictScalars (hf : DifferentiableWithinAt 𝕜 f s x) (hs : UniqueDiffWithinAt 𝕜 s x) : DifferentiableWithinAt 𝕜' f s x ↔ ∃ g' : E →L[𝕜'] F, g'.restrictScalars 𝕜 = fderivWithin 𝕜 f s x := by constructor · rintro ⟨g', hg'⟩ exact ⟨g', hs.eq (hg'.restrictScalars 𝕜) hf.hasFDerivWithinAt⟩ · rintro ⟨f', hf'⟩ exact ⟨f', hf.hasFDerivWithinAt.of_restrictScalars 𝕜 hf'⟩ #align differentiable_within_at_iff_restrict_scalars differentiableWithinAt_iff_restrictScalars
Mathlib/Analysis/Calculus/FDeriv/RestrictScalars.lean
120
124
theorem differentiableAt_iff_restrictScalars (hf : DifferentiableAt 𝕜 f x) : DifferentiableAt 𝕜' f x ↔ ∃ g' : E →L[𝕜'] F, g'.restrictScalars 𝕜 = fderiv 𝕜 f x := by
rw [← differentiableWithinAt_univ, ← fderivWithin_univ] exact differentiableWithinAt_iff_restrictScalars 𝕜 hf.differentiableWithinAt uniqueDiffWithinAt_univ
/- Copyright (c) 2020 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Deprecated.Group #align_import deprecated.ring from "leanprover-community/mathlib"@"5a3e819569b0f12cbec59d740a2613018e7b8eec" /-! # Unbundled semiring and ring homomorphisms (deprecated) This file is deprecated, and is no longer imported by anything in mathlib other than other deprecated files, and test files. You should not need to import it. This file defines predicates for unbundled semiring and ring homomorphisms. Instead of using this file, please use `RingHom`, defined in `Algebra.Hom.Ring`, with notation `→+*`, for morphisms between semirings or rings. For example use `φ : A →+* B` to represent a ring homomorphism. ## Main Definitions `IsSemiringHom` (deprecated), `IsRingHom` (deprecated) ## Tags IsSemiringHom, IsRingHom -/ universe u v w variable {α : Type u} /-- Predicate for semiring homomorphisms (deprecated -- use the bundled `RingHom` version). -/ structure IsSemiringHom {α : Type u} {β : Type v} [Semiring α] [Semiring β] (f : α → β) : Prop where /-- The proposition that `f` preserves the additive identity. -/ map_zero : f 0 = 0 /-- The proposition that `f` preserves the multiplicative identity. -/ map_one : f 1 = 1 /-- The proposition that `f` preserves addition. -/ map_add : ∀ x y, f (x + y) = f x + f y /-- The proposition that `f` preserves multiplication. -/ map_mul : ∀ x y, f (x * y) = f x * f y #align is_semiring_hom IsSemiringHom namespace IsSemiringHom variable {β : Type v} [Semiring α] [Semiring β] variable {f : α → β} (hf : IsSemiringHom f) {x y : α} /-- The identity map is a semiring homomorphism. -/
Mathlib/Deprecated/Ring.lean
54
54
theorem id : IsSemiringHom (@id α) := by
constructor <;> intros <;> rfl
/- Copyright (c) 2023 Patrick Massot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot -/ import Mathlib.Order.Filter.Germ import Mathlib.Topology.NhdsSet import Mathlib.Topology.LocallyConstant.Basic import Mathlib.Analysis.NormedSpace.Basic /-! # Germs of functions between topological spaces In this file, we prove basic properties of germs of functions between topological spaces, with respect to the neighbourhood filter `𝓝 x`. ## Main definitions and results * `Filter.Germ.value φ f`: value associated to the germ `φ` at a point `x`, w.r.t. the neighbourhood filter at `x`. This is the common value of all representatives of `φ` at `x`. * `Filter.Germ.valueOrderRingHom` and friends: the map `Germ (𝓝 x) E → E` is a monoid homomorphism, 𝕜-module homomorphism, ring homomorphism, monotone ring homomorphism * `RestrictGermPredicate`: given a predicate on germs `P : Π x : X, germ (𝓝 x) Y → Prop` and `A : set X`, build a new predicate on germs `restrictGermPredicate P A` such that `(∀ x, RestrictGermPredicate P A x f) ↔ ∀ᶠ x near A, P x f`; `forall_restrictRermPredicate_iff` is this equivalence. * `Filter.Germ.sliceLeft, sliceRight`: map the germ of functions `X × Y → Z` at `p = (x,y) ∈ X × Y` to the corresponding germ of functions `X → Z` at `x ∈ X` resp. `Y → Z` at `y ∈ Y`. * `eq_of_germ_isConstant`: if each germ of `f : X → Y` is constant and `X` is pre-connected, `f` is constant. -/ variable {F G : Type*} [NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup G] [NormedSpace ℝ G] open scoped Topology open Filter Set variable {X Y Z : Type*} [TopologicalSpace X] {f g : X → Y} {A : Set X} {x : X} namespace Filter.Germ /-- The value associated to a germ at a point. This is the common value shared by all representatives at the given point. -/ def value {X α : Type*} [TopologicalSpace X] {x : X} (φ : Germ (𝓝 x) α) : α := Quotient.liftOn' φ (fun f ↦ f x) fun f g h ↦ by dsimp only; rw [Eventually.self_of_nhds h] theorem value_smul {α β : Type*} [SMul α β] (φ : Germ (𝓝 x) α) (ψ : Germ (𝓝 x) β) : (φ • ψ).value = φ.value • ψ.value := Germ.inductionOn φ fun _ ↦ Germ.inductionOn ψ fun _ ↦ rfl /-- The map `Germ (𝓝 x) E → E` into a monoid `E` as a monoid homomorphism -/ @[to_additive "The map `Germ (𝓝 x) E → E` as an additive monoid homomorphism"] def valueMulHom {X E : Type*} [Monoid E] [TopologicalSpace X] {x : X} : Germ (𝓝 x) E →* E where toFun := Filter.Germ.value map_one' := rfl map_mul' φ ψ := Germ.inductionOn φ fun _ ↦ Germ.inductionOn ψ fun _ ↦ rfl /-- The map `Germ (𝓝 x) E → E` into a `𝕜`-module `E` as a `𝕜`-linear map -/ def valueₗ {X 𝕜 E : Type*} [Semiring 𝕜] [AddCommMonoid E] [Module 𝕜 E] [TopologicalSpace X] {x : X} : Germ (𝓝 x) E →ₗ[𝕜] E where __ := Filter.Germ.valueAddHom map_smul' := fun _ φ ↦ Germ.inductionOn φ fun _ ↦ rfl /-- The map `Germ (𝓝 x) E → E` as a ring homomorphism -/ def valueRingHom {X E : Type*} [Semiring E] [TopologicalSpace X] {x : X} : Germ (𝓝 x) E →+* E := { Filter.Germ.valueMulHom, Filter.Germ.valueAddHom with } /-- The map `Germ (𝓝 x) E → E` as a monotone ring homomorphism -/ def valueOrderRingHom {X E : Type*} [OrderedSemiring E] [TopologicalSpace X] {x : X} : Germ (𝓝 x) E →+*o E where __ := Filter.Germ.valueRingHom monotone' := fun φ ψ ↦ Germ.inductionOn φ fun _ ↦ Germ.inductionOn ψ fun _ h ↦ h.self_of_nhds end Filter.Germ section RestrictGermPredicate /-- Given a predicate on germs `P : Π x : X, germ (𝓝 x) Y → Prop` and `A : set X`, build a new predicate on germs `RestrictGermPredicate P A` such that `(∀ x, RestrictGermPredicate P A x f) ↔ ∀ᶠ x near A, P x f`, see `forall_restrictGermPredicate_iff` for this equivalence. -/ def RestrictGermPredicate (P : ∀ x : X, Germ (𝓝 x) Y → Prop) (A : Set X) : ∀ x : X, Germ (𝓝 x) Y → Prop := fun x φ ↦ Germ.liftOn φ (fun f ↦ x ∈ A → ∀ᶠ y in 𝓝 x, P y f) haveI : ∀ f f' : X → Y, f =ᶠ[𝓝 x] f' → (∀ᶠ y in 𝓝 x, P y f) → ∀ᶠ y in 𝓝 x, P y f' := by intro f f' hff' hf apply (hf.and <| Eventually.eventually_nhds hff').mono rintro y ⟨hy, hy'⟩ rwa [Germ.coe_eq.mpr (EventuallyEq.symm hy')] fun f f' hff' ↦ propext <| forall_congr' fun _ ↦ ⟨this f f' hff', this f' f hff'.symm⟩
Mathlib/Topology/Germ.lean
94
102
theorem Filter.Eventually.germ_congr_set {P : ∀ x : X, Germ (𝓝 x) Y → Prop} (hf : ∀ᶠ x in 𝓝ˢ A, P x f) (h : ∀ᶠ z in 𝓝ˢ A, g z = f z) : ∀ᶠ x in 𝓝ˢ A, P x g := by
rw [eventually_nhdsSet_iff_forall] at * intro x hx apply ((hf x hx).and (h x hx).eventually_nhds).mono intro y hy convert hy.1 using 1 exact Germ.coe_eq.mpr hy.2
/- Copyright (c) 2019 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Scott Morrison -/ import Mathlib.Algebra.Order.Hom.Monoid import Mathlib.SetTheory.Game.Ordinal #align_import set_theory.surreal.basic from "leanprover-community/mathlib"@"8900d545017cd21961daa2a1734bb658ef52c618" /-! # Surreal numbers The basic theory of surreal numbers, built on top of the theory of combinatorial (pre-)games. A pregame is `Numeric` if all the Left options are strictly smaller than all the Right options, and all those options are themselves numeric. In terms of combinatorial games, the numeric games have "frozen"; you can only make your position worse by playing, and Left is some definite "number" of moves ahead (or behind) Right. A surreal number is an equivalence class of numeric pregames. In fact, the surreals form a complete ordered field, containing a copy of the reals (and much else besides!) but we do not yet have a complete development. ## Order properties Surreal numbers inherit the relations `≤` and `<` from games (`Surreal.instLE` and `Surreal.instLT`), and these relations satisfy the axioms of a partial order. ## Algebraic operations We show that the surreals form a linear ordered commutative group. One can also map all the ordinals into the surreals! ### Multiplication of surreal numbers The proof that multiplication lifts to surreal numbers is surprisingly difficult and is currently missing in the library. A sample proof can be found in Theorem 3.8 in the second reference below. The difficulty lies in the length of the proof and the number of theorems that need to proven simultaneously. This will make for a fun and challenging project. The branch `surreal_mul` contains some progress on this proof. ### Todo - Define the field structure on the surreals. ## References * [Conway, *On numbers and games*][conway2001] * [Schleicher, Stoll, *An introduction to Conway's games and numbers*][schleicher_stoll] -/ universe u namespace SetTheory open scoped PGame namespace PGame /-- A pre-game is numeric if everything in the L set is less than everything in the R set, and all the elements of L and R are also numeric. -/ def Numeric : PGame → Prop | ⟨_, _, L, R⟩ => (∀ i j, L i < R j) ∧ (∀ i, Numeric (L i)) ∧ ∀ j, Numeric (R j) #align pgame.numeric SetTheory.PGame.Numeric theorem numeric_def {x : PGame} : Numeric x ↔ (∀ i j, x.moveLeft i < x.moveRight j) ∧ (∀ i, Numeric (x.moveLeft i)) ∧ ∀ j, Numeric (x.moveRight j) := by cases x; rfl #align pgame.numeric_def SetTheory.PGame.numeric_def namespace Numeric theorem mk {x : PGame} (h₁ : ∀ i j, x.moveLeft i < x.moveRight j) (h₂ : ∀ i, Numeric (x.moveLeft i)) (h₃ : ∀ j, Numeric (x.moveRight j)) : Numeric x := numeric_def.2 ⟨h₁, h₂, h₃⟩ #align pgame.numeric.mk SetTheory.PGame.Numeric.mk theorem left_lt_right {x : PGame} (o : Numeric x) (i : x.LeftMoves) (j : x.RightMoves) : x.moveLeft i < x.moveRight j := by cases x; exact o.1 i j #align pgame.numeric.left_lt_right SetTheory.PGame.Numeric.left_lt_right theorem moveLeft {x : PGame} (o : Numeric x) (i : x.LeftMoves) : Numeric (x.moveLeft i) := by cases x; exact o.2.1 i #align pgame.numeric.move_left SetTheory.PGame.Numeric.moveLeft theorem moveRight {x : PGame} (o : Numeric x) (j : x.RightMoves) : Numeric (x.moveRight j) := by cases x; exact o.2.2 j #align pgame.numeric.move_right SetTheory.PGame.Numeric.moveRight end Numeric @[elab_as_elim] theorem numeric_rec {C : PGame → Prop} (H : ∀ (l r) (L : l → PGame) (R : r → PGame), (∀ i j, L i < R j) → (∀ i, Numeric (L i)) → (∀ i, Numeric (R i)) → (∀ i, C (L i)) → (∀ i, C (R i)) → C ⟨l, r, L, R⟩) : ∀ x, Numeric x → C x | ⟨_, _, _, _⟩, ⟨h, hl, hr⟩ => H _ _ _ _ h hl hr (fun i => numeric_rec H _ (hl i)) fun i => numeric_rec H _ (hr i) #align pgame.numeric_rec SetTheory.PGame.numeric_rec
Mathlib/SetTheory/Surreal/Basic.lean
109
115
theorem Relabelling.numeric_imp {x y : PGame} (r : x ≡r y) (ox : Numeric x) : Numeric y := by
induction' x using PGame.moveRecOn with x IHl IHr generalizing y apply Numeric.mk (fun i j => ?_) (fun i => ?_) fun j => ?_ · rw [← lt_congr (r.moveLeftSymm i).equiv (r.moveRightSymm j).equiv] apply ox.left_lt_right · exact IHl _ (r.moveLeftSymm i) (ox.moveLeft _) · exact IHr _ (r.moveRightSymm j) (ox.moveRight _)
/- Copyright (c) 2021 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Analytic.Composition #align_import analysis.analytic.inverse from "leanprover-community/mathlib"@"284fdd2962e67d2932fa3a79ce19fcf92d38e228" /-! # Inverse of analytic functions We construct the left and right inverse of a formal multilinear series with invertible linear term, we prove that they coincide and study their properties (notably convergence). ## Main statements * `p.leftInv i`: the formal left inverse of the formal multilinear series `p`, for `i : E ≃L[𝕜] F` which coincides with `p₁`. * `p.rightInv i`: the formal right inverse of the formal multilinear series `p`, for `i : E ≃L[𝕜] F` which coincides with `p₁`. * `p.leftInv_comp` says that `p.leftInv i` is indeed a left inverse to `p` when `p₁ = i`. * `p.rightInv_comp` says that `p.rightInv i` is indeed a right inverse to `p` when `p₁ = i`. * `p.leftInv_eq_rightInv`: the two inverses coincide. * `p.radius_rightInv_pos_of_radius_pos`: if a power series has a positive radius of convergence, then so does its inverse. -/ open scoped Classical Topology open Finset Filter namespace FormalMultilinearSeries variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F] /-! ### The left inverse of a formal multilinear series -/ /-- The left inverse of a formal multilinear series, where the `n`-th term is defined inductively in terms of the previous ones to make sure that `(leftInv p i) ∘ p = id`. For this, the linear term `p₁` in `p` should be invertible. In the definition, `i` is a linear isomorphism that should coincide with `p₁`, so that one can use its inverse in the construction. The definition does not use that `i = p₁`, but proofs that the definition is well-behaved do. The `n`-th term in `q ∘ p` is `∑ qₖ (p_{j₁}, ..., p_{jₖ})` over `j₁ + ... + jₖ = n`. In this expression, `qₙ` appears only once, in `qₙ (p₁, ..., p₁)`. We adjust the definition so that this term compensates the rest of the sum, using `i⁻¹` as an inverse to `p₁`. These formulas only make sense when the constant term `p₀` vanishes. The definition we give is general, but it ignores the value of `p₀`. -/ noncomputable def leftInv (p : FormalMultilinearSeries 𝕜 E F) (i : E ≃L[𝕜] F) : FormalMultilinearSeries 𝕜 F E | 0 => 0 | 1 => (continuousMultilinearCurryFin1 𝕜 F E).symm i.symm | n + 2 => -∑ c : { c : Composition (n + 2) // c.length < n + 2 }, (leftInv p i (c : Composition (n + 2)).length).compAlongComposition (p.compContinuousLinearMap i.symm) c #align formal_multilinear_series.left_inv FormalMultilinearSeries.leftInv @[simp] theorem leftInv_coeff_zero (p : FormalMultilinearSeries 𝕜 E F) (i : E ≃L[𝕜] F) : p.leftInv i 0 = 0 := by rw [leftInv] #align formal_multilinear_series.left_inv_coeff_zero FormalMultilinearSeries.leftInv_coeff_zero @[simp] theorem leftInv_coeff_one (p : FormalMultilinearSeries 𝕜 E F) (i : E ≃L[𝕜] F) : p.leftInv i 1 = (continuousMultilinearCurryFin1 𝕜 F E).symm i.symm := by rw [leftInv] #align formal_multilinear_series.left_inv_coeff_one FormalMultilinearSeries.leftInv_coeff_one /-- The left inverse does not depend on the zeroth coefficient of a formal multilinear series. -/
Mathlib/Analysis/Analytic/Inverse.lean
79
92
theorem leftInv_removeZero (p : FormalMultilinearSeries 𝕜 E F) (i : E ≃L[𝕜] F) : p.removeZero.leftInv i = p.leftInv i := by
ext1 n induction' n using Nat.strongRec' with n IH match n with | 0 => simp -- if one replaces `simp` with `refl`, the proof times out in the kernel. | 1 => simp -- TODO: why? | n + 2 => simp only [leftInv, neg_inj] refine Finset.sum_congr rfl fun c cuniv => ?_ rcases c with ⟨c, hc⟩ ext v dsimp simp [IH _ hc]
/- Copyright (c) 2023 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison -/ import Mathlib.Algebra.Category.ModuleCat.ChangeOfRings import Mathlib.Algebra.Category.Ring.Basic /-! # Presheaves of modules over a presheaf of rings. We give a hands-on description of a presheaf of modules over a fixed presheaf of rings `R`, as a presheaf of abelian groups with additional data. We also provide two alternative constructors : * When `M : CorePresheafOfModules R` consists of a family of unbundled modules over `R.obj X` for all `X`, the corresponding presheaf of modules is `M.toPresheafOfModules`. * When `M : BundledCorePresheafOfModules R` consists of a family of objects in `ModuleCat (R.obj X)` for all `X`, the corresponding presheaf of modules is `M.toPresheafOfModules`. ## Future work * Compare this to the definition as a presheaf of pairs `(R, M)` with specified first part. * Compare this to the definition as a module object of the presheaf of rings thought of as a monoid object. * (Pre)sheaves of modules over a given sheaf of rings are an abelian category. * Presheaves of modules over a presheaf of commutative rings form a monoidal category. * Pushforward and pullback. -/ universe v v₁ u₁ u open CategoryTheory LinearMap Opposite variable {C : Type u₁} [Category.{v₁} C] /-- A presheaf of modules over a given presheaf of rings, described as a presheaf of abelian groups, and the extra data of the action at each object, and a condition relating functoriality and scalar multiplication. -/ structure PresheafOfModules (R : Cᵒᵖ ⥤ RingCat.{u}) where presheaf : Cᵒᵖ ⥤ AddCommGroupCat.{v} module : ∀ X : Cᵒᵖ, Module (R.obj X) (presheaf.obj X) := by infer_instance map_smul : ∀ {X Y : Cᵒᵖ} (f : X ⟶ Y) (r : R.obj X) (x : presheaf.obj X), presheaf.map f (r • x) = R.map f r • presheaf.map f x := by aesop_cat variable {R : Cᵒᵖ ⥤ RingCat.{u}} namespace PresheafOfModules attribute [instance] PresheafOfModules.module /-- The bundled module over an object `X`. -/ def obj (P : PresheafOfModules R) (X : Cᵒᵖ) : ModuleCat (R.obj X) := ModuleCat.of _ (P.presheaf.obj X) /-- If `P` is a presheaf of modules over a presheaf of rings `R`, both over some category `C`, and `f : X ⟶ Y` is a morphism in `Cᵒᵖ`, we construct the `R.map f`-semilinear map from the `R.obj X`-module `P.presheaf.obj X` to the `R.obj Y`-module `P.presheaf.obj Y`. -/ def map (P : PresheafOfModules R) {X Y : Cᵒᵖ} (f : X ⟶ Y) : P.obj X →ₛₗ[R.map f] P.obj Y := { toAddHom := (P.presheaf.map f).toAddHom, map_smul' := P.map_smul f, } theorem map_apply (P : PresheafOfModules R) {X Y : Cᵒᵖ} (f : X ⟶ Y) (x) : P.map f x = (P.presheaf.map f) x := rfl instance (X : Cᵒᵖ) : RingHomId (R.map (𝟙 X)) where eq_id := R.map_id X instance {X Y Z : Cᵒᵖ} (f : X ⟶ Y) (g : Y ⟶ Z) : RingHomCompTriple (R.map f) (R.map g) (R.map (f ≫ g)) where comp_eq := (R.map_comp f g).symm @[simp] theorem map_id (P : PresheafOfModules R) (X : Cᵒᵖ) : P.map (𝟙 X) = LinearMap.id' := by ext simp [map_apply] @[simp]
Mathlib/Algebra/Category/ModuleCat/Presheaf.lean
85
88
theorem map_comp (P : PresheafOfModules R) {X Y Z : Cᵒᵖ} (f : X ⟶ Y) (g : Y ⟶ Z) : P.map (f ≫ g) = (P.map g).comp (P.map f) := by
ext simp [map_apply]
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov -/ import Mathlib.Topology.Order.Basic import Mathlib.Data.Set.Pointwise.Basic /-! # Neighborhoods to the left and to the right on an `OrderTopology` We've seen some properties of left and right neighborhood of a point in an `OrderClosedTopology`. In an `OrderTopology`, such neighborhoods can be characterized as the sets containing suitable intervals to the right or to the left of `a`. We give now these characterizations. -/ open Set Filter TopologicalSpace Topology Function open OrderDual (toDual ofDual) variable {α β γ : Type*} section LinearOrder variable [TopologicalSpace α] [LinearOrder α] section OrderTopology variable [OrderTopology α] open List in /-- The following statements are equivalent: 0. `s` is a neighborhood of `a` within `(a, +∞)`; 1. `s` is a neighborhood of `a` within `(a, b]`; 2. `s` is a neighborhood of `a` within `(a, b)`; 3. `s` includes `(a, u)` for some `u ∈ (a, b]`; 4. `s` includes `(a, u)` for some `u > a`. -/
Mathlib/Topology/Order/LeftRightNhds.lean
40
60
theorem TFAE_mem_nhdsWithin_Ioi {a b : α} (hab : a < b) (s : Set α) : TFAE [s ∈ 𝓝[>] a, s ∈ 𝓝[Ioc a b] a, s ∈ 𝓝[Ioo a b] a, ∃ u ∈ Ioc a b, Ioo a u ⊆ s, ∃ u ∈ Ioi a, Ioo a u ⊆ s] := by
tfae_have 1 ↔ 2 · rw [nhdsWithin_Ioc_eq_nhdsWithin_Ioi hab] tfae_have 1 ↔ 3 · rw [nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab] tfae_have 4 → 5 · exact fun ⟨u, umem, hu⟩ => ⟨u, umem.1, hu⟩ tfae_have 5 → 1 · rintro ⟨u, hau, hu⟩ exact mem_of_superset (Ioo_mem_nhdsWithin_Ioi ⟨le_refl a, hau⟩) hu tfae_have 1 → 4 · intro h rcases mem_nhdsWithin_iff_exists_mem_nhds_inter.1 h with ⟨v, va, hv⟩ rcases exists_Ico_subset_of_mem_nhds' va hab with ⟨u, au, hu⟩ exact ⟨u, au, fun x hx => hv ⟨hu ⟨le_of_lt hx.1, hx.2⟩, hx.1⟩⟩ tfae_finish
/- Copyright (c) 2021 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.Algebra.Quaternion import Mathlib.Tactic.Ring #align_import algebra.quaternion_basis from "leanprover-community/mathlib"@"3aa5b8a9ed7a7cabd36e6e1d022c9858ab8a8c2d" /-! # Basis on a quaternion-like algebra ## Main definitions * `QuaternionAlgebra.Basis A c₁ c₂`: a basis for a subspace of an `R`-algebra `A` that has the same algebra structure as `ℍ[R,c₁,c₂]`. * `QuaternionAlgebra.Basis.self R`: the canonical basis for `ℍ[R,c₁,c₂]`. * `QuaternionAlgebra.Basis.compHom b f`: transform a basis `b` by an AlgHom `f`. * `QuaternionAlgebra.lift`: Define an `AlgHom` out of `ℍ[R,c₁,c₂]` by its action on the basis elements `i`, `j`, and `k`. In essence, this is a universal property. Analogous to `Complex.lift`, but takes a bundled `QuaternionAlgebra.Basis` instead of just a `Subtype` as the amount of data / proves is non-negligible. -/ open Quaternion namespace QuaternionAlgebra /-- A quaternion basis contains the information both sufficient and necessary to construct an `R`-algebra homomorphism from `ℍ[R,c₁,c₂]` to `A`; or equivalently, a surjective `R`-algebra homomorphism from `ℍ[R,c₁,c₂]` to an `R`-subalgebra of `A`. Note that for definitional convenience, `k` is provided as a field even though `i_mul_j` fully determines it. -/ structure Basis {R : Type*} (A : Type*) [CommRing R] [Ring A] [Algebra R A] (c₁ c₂ : R) where (i j k : A) i_mul_i : i * i = c₁ • (1 : A) j_mul_j : j * j = c₂ • (1 : A) i_mul_j : i * j = k j_mul_i : j * i = -k #align quaternion_algebra.basis QuaternionAlgebra.Basis variable {R : Type*} {A B : Type*} [CommRing R] [Ring A] [Ring B] [Algebra R A] [Algebra R B] variable {c₁ c₂ : R} namespace Basis /-- Since `k` is redundant, it is not necessary to show `q₁.k = q₂.k` when showing `q₁ = q₂`. -/ @[ext] protected theorem ext ⦃q₁ q₂ : Basis A c₁ c₂⦄ (hi : q₁.i = q₂.i) (hj : q₁.j = q₂.j) : q₁ = q₂ := by cases q₁; rename_i q₁_i_mul_j _ cases q₂; rename_i q₂_i_mul_j _ congr rw [← q₁_i_mul_j, ← q₂_i_mul_j] congr #align quaternion_algebra.basis.ext QuaternionAlgebra.Basis.ext variable (R) /-- There is a natural quaternionic basis for the `QuaternionAlgebra`. -/ @[simps i j k] protected def self : Basis ℍ[R,c₁,c₂] c₁ c₂ where i := ⟨0, 1, 0, 0⟩ i_mul_i := by ext <;> simp j := ⟨0, 0, 1, 0⟩ j_mul_j := by ext <;> simp k := ⟨0, 0, 0, 1⟩ i_mul_j := by ext <;> simp j_mul_i := by ext <;> simp #align quaternion_algebra.basis.self QuaternionAlgebra.Basis.self variable {R} instance : Inhabited (Basis ℍ[R,c₁,c₂] c₁ c₂) := ⟨Basis.self R⟩ variable (q : Basis A c₁ c₂) attribute [simp] i_mul_i j_mul_j i_mul_j j_mul_i @[simp] theorem i_mul_k : q.i * q.k = c₁ • q.j := by rw [← i_mul_j, ← mul_assoc, i_mul_i, smul_mul_assoc, one_mul] #align quaternion_algebra.basis.i_mul_k QuaternionAlgebra.Basis.i_mul_k @[simp] theorem k_mul_i : q.k * q.i = -c₁ • q.j := by rw [← i_mul_j, mul_assoc, j_mul_i, mul_neg, i_mul_k, neg_smul] #align quaternion_algebra.basis.k_mul_i QuaternionAlgebra.Basis.k_mul_i @[simp] theorem k_mul_j : q.k * q.j = c₂ • q.i := by rw [← i_mul_j, mul_assoc, j_mul_j, mul_smul_comm, mul_one] #align quaternion_algebra.basis.k_mul_j QuaternionAlgebra.Basis.k_mul_j @[simp] theorem j_mul_k : q.j * q.k = -c₂ • q.i := by rw [← i_mul_j, ← mul_assoc, j_mul_i, neg_mul, k_mul_j, neg_smul] #align quaternion_algebra.basis.j_mul_k QuaternionAlgebra.Basis.j_mul_k @[simp] theorem k_mul_k : q.k * q.k = -((c₁ * c₂) • (1 : A)) := by rw [← i_mul_j, mul_assoc, ← mul_assoc q.j _ _, j_mul_i, ← i_mul_j, ← mul_assoc, mul_neg, ← mul_assoc, i_mul_i, smul_mul_assoc, one_mul, neg_mul, smul_mul_assoc, j_mul_j, smul_smul] #align quaternion_algebra.basis.k_mul_k QuaternionAlgebra.Basis.k_mul_k /-- Intermediate result used to define `QuaternionAlgebra.Basis.liftHom`. -/ def lift (x : ℍ[R,c₁,c₂]) : A := algebraMap R _ x.re + x.imI • q.i + x.imJ • q.j + x.imK • q.k #align quaternion_algebra.basis.lift QuaternionAlgebra.Basis.lift theorem lift_zero : q.lift (0 : ℍ[R,c₁,c₂]) = 0 := by simp [lift] #align quaternion_algebra.basis.lift_zero QuaternionAlgebra.Basis.lift_zero
Mathlib/Algebra/QuaternionBasis.lean
117
117
theorem lift_one : q.lift (1 : ℍ[R,c₁,c₂]) = 1 := by
simp [lift]
/- Copyright (c) 2021 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn -/ import Mathlib.Algebra.Group.Even import Mathlib.Algebra.Order.Monoid.Canonical.Defs import Mathlib.Algebra.Order.Sub.Defs #align_import algebra.order.sub.canonical from "leanprover-community/mathlib"@"62a5626868683c104774de8d85b9855234ac807c" /-! # Lemmas about subtraction in canonically ordered monoids -/ variable {α : Type*} section ExistsAddOfLE variable [AddCommSemigroup α] [PartialOrder α] [ExistsAddOfLE α] [CovariantClass α α (· + ·) (· ≤ ·)] [Sub α] [OrderedSub α] {a b c d : α} @[simp] theorem add_tsub_cancel_of_le (h : a ≤ b) : a + (b - a) = b := by refine le_antisymm ?_ le_add_tsub obtain ⟨c, rfl⟩ := exists_add_of_le h exact add_le_add_left add_tsub_le_left a #align add_tsub_cancel_of_le add_tsub_cancel_of_le
Mathlib/Algebra/Order/Sub/Canonical.lean
31
33
theorem tsub_add_cancel_of_le (h : a ≤ b) : b - a + a = b := by
rw [add_comm] exact add_tsub_cancel_of_le h
/- Copyright (c) 2021 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser, Jireh Loreaux -/ import Mathlib.Algebra.Group.Center import Mathlib.Data.Int.Cast.Lemmas #align_import group_theory.subsemigroup.center from "leanprover-community/mathlib"@"1ac8d4304efba9d03fa720d06516fac845aa5353" /-! # Centers of rings -/ variable {M : Type*} namespace Set variable (M) @[simp]
Mathlib/Algebra/Ring/Center.lean
24
37
theorem natCast_mem_center [NonAssocSemiring M] (n : ℕ) : (n : M) ∈ Set.center M where comm _:= by
rw [Nat.commute_cast] left_assoc _ _ := by induction n with | zero => rw [Nat.cast_zero, zero_mul, zero_mul, zero_mul] | succ n ihn => rw [Nat.cast_succ, add_mul, one_mul, ihn, add_mul, add_mul, one_mul] mid_assoc _ _ := by induction n with | zero => rw [Nat.cast_zero, zero_mul, mul_zero, zero_mul] | succ n ihn => rw [Nat.cast_succ, add_mul, mul_add, add_mul, ihn, mul_add, one_mul, mul_one] right_assoc _ _ := by induction n with | zero => rw [Nat.cast_zero, mul_zero, mul_zero, mul_zero] | succ n ihn => rw [Nat.cast_succ, mul_add, ihn, mul_add, mul_add, mul_one, mul_one]
/- Copyright (c) 2023 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.Data.Int.Order.Units import Mathlib.Data.ZMod.IntUnitsPower import Mathlib.RingTheory.TensorProduct.Basic import Mathlib.LinearAlgebra.DirectSum.TensorProduct import Mathlib.Algebra.DirectSum.Algebra /-! # Graded tensor products over graded algebras The graded tensor product $A \hat\otimes_R B$ is imbued with a multiplication defined on homogeneous tensors by: $$(a \otimes b) \cdot (a' \otimes b') = (-1)^{\deg a' \deg b} (a \cdot a') \otimes (b \cdot b')$$ where $A$ and $B$ are algebras graded by `ℕ`, `ℤ`, or `ZMod 2` (or more generally, any index that satisfies `Module ι (Additive ℤˣ)`). The results for internally-graded algebras (via `GradedAlgebra`) are elsewhere, as is the type `GradedTensorProduct`. ## Main results * `TensorProduct.gradedComm`: the symmetric braiding operator on the tensor product of externally-graded rings. * `TensorProduct.gradedMul`: the previously-described multiplication on externally-graded rings, as a bilinear map. ## Implementation notes Rather than implementing the multiplication directly as above, we first implement the canonical non-trivial braiding sending $a \otimes b$ to $(-1)^{\deg a' \deg b} (b \otimes a)$, as the multiplication follows trivially from this after some point-free nonsense. ## References * https://math.stackexchange.com/q/202718/1896 * [*Algebra I*, Bourbaki : Chapter III, §4.7, example (2)][bourbaki1989] -/ suppress_compilation open scoped TensorProduct DirectSum variable {R ι A B : Type*} namespace TensorProduct variable [CommSemiring ι] [Module ι (Additive ℤˣ)] [DecidableEq ι] variable (𝒜 : ι → Type*) (ℬ : ι → Type*) variable [CommRing R] variable [∀ i, AddCommGroup (𝒜 i)] [∀ i, AddCommGroup (ℬ i)] variable [∀ i, Module R (𝒜 i)] [∀ i, Module R (ℬ i)] variable [DirectSum.GRing 𝒜] [DirectSum.GRing ℬ] variable [DirectSum.GAlgebra R 𝒜] [DirectSum.GAlgebra R ℬ] -- this helps with performance instance (i : ι × ι) : Module R (𝒜 (Prod.fst i) ⊗[R] ℬ (Prod.snd i)) := TensorProduct.leftModule open DirectSum (lof) variable (R) section gradedComm local notation "𝒜ℬ" => (fun i : ι × ι => 𝒜 (Prod.fst i) ⊗[R] ℬ (Prod.snd i)) local notation "ℬ𝒜" => (fun i : ι × ι => ℬ (Prod.fst i) ⊗[R] 𝒜 (Prod.snd i)) /-- Auxliary construction used to build `TensorProduct.gradedComm`. This operates on direct sums of tensors instead of tensors of direct sums. -/ def gradedCommAux : DirectSum _ 𝒜ℬ →ₗ[R] DirectSum _ ℬ𝒜 := by refine DirectSum.toModule R _ _ fun i => ?_ have o := DirectSum.lof R _ ℬ𝒜 i.swap have s : ℤˣ := ((-1 : ℤˣ)^(i.1* i.2 : ι) : ℤˣ) exact (s • o) ∘ₗ (TensorProduct.comm R _ _).toLinearMap @[simp]
Mathlib/LinearAlgebra/TensorProduct/Graded/External.lean
85
90
theorem gradedCommAux_lof_tmul (i j : ι) (a : 𝒜 i) (b : ℬ j) : gradedCommAux R 𝒜 ℬ (lof R _ 𝒜ℬ (i, j) (a ⊗ₜ b)) = (-1 : ℤˣ)^(j * i) • lof R _ ℬ𝒜 (j, i) (b ⊗ₜ a) := by
rw [gradedCommAux] dsimp simp [mul_comm i j]
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel, Rémy Degenne, David Loeffler -/ import Mathlib.Analysis.SpecialFunctions.Pow.Complex import Qq #align_import analysis.special_functions.pow.real from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8" /-! # Power function on `ℝ` We construct the power functions `x ^ y`, where `x` and `y` are real numbers. -/ noncomputable section open scoped Classical open Real ComplexConjugate open Finset Set /- ## Definitions -/ namespace Real variable {x y z : ℝ} /-- The real power function `x ^ y`, defined as the real part of the complex power function. For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`, one sets `0 ^ 0=1` and `0 ^ y=0` for `y ≠ 0`. For `x < 0`, the definition is somewhat arbitrary as it depends on the choice of a complex determination of the logarithm. With our conventions, it is equal to `exp (y log x) cos (π y)`. -/ noncomputable def rpow (x y : ℝ) := ((x : ℂ) ^ (y : ℂ)).re #align real.rpow Real.rpow noncomputable instance : Pow ℝ ℝ := ⟨rpow⟩ @[simp] theorem rpow_eq_pow (x y : ℝ) : rpow x y = x ^ y := rfl #align real.rpow_eq_pow Real.rpow_eq_pow theorem rpow_def (x y : ℝ) : x ^ y = ((x : ℂ) ^ (y : ℂ)).re := rfl #align real.rpow_def Real.rpow_def theorem rpow_def_of_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := by simp only [rpow_def, Complex.cpow_def]; split_ifs <;> simp_all [(Complex.ofReal_log hx).symm, -Complex.ofReal_mul, -RCLike.ofReal_mul, (Complex.ofReal_mul _ _).symm, Complex.exp_ofReal_re, Complex.ofReal_eq_zero] #align real.rpow_def_of_nonneg Real.rpow_def_of_nonneg theorem rpow_def_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : x ^ y = exp (log x * y) := by rw [rpow_def_of_nonneg (le_of_lt hx), if_neg (ne_of_gt hx)] #align real.rpow_def_of_pos Real.rpow_def_of_pos theorem exp_mul (x y : ℝ) : exp (x * y) = exp x ^ y := by rw [rpow_def_of_pos (exp_pos _), log_exp] #align real.exp_mul Real.exp_mul @[simp, norm_cast] theorem rpow_intCast (x : ℝ) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by simp only [rpow_def, ← Complex.ofReal_zpow, Complex.cpow_intCast, Complex.ofReal_intCast, Complex.ofReal_re] #align real.rpow_int_cast Real.rpow_intCast @[deprecated (since := "2024-04-17")] alias rpow_int_cast := rpow_intCast @[simp, norm_cast] theorem rpow_natCast (x : ℝ) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by simpa using rpow_intCast x n #align real.rpow_nat_cast Real.rpow_natCast @[deprecated (since := "2024-04-17")] alias rpow_nat_cast := rpow_natCast @[simp] theorem exp_one_rpow (x : ℝ) : exp 1 ^ x = exp x := by rw [← exp_mul, one_mul] #align real.exp_one_rpow Real.exp_one_rpow @[simp] lemma exp_one_pow (n : ℕ) : exp 1 ^ n = exp n := by rw [← rpow_natCast, exp_one_rpow]
Mathlib/Analysis/SpecialFunctions/Pow/Real.lean
85
87
theorem rpow_eq_zero_iff_of_nonneg (hx : 0 ≤ x) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [rpow_def_of_nonneg hx] split_ifs <;> simp [*, exp_ne_zero]
/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Calculus.ContDiff.Basic import Mathlib.Analysis.Calculus.UniformLimitsDeriv import Mathlib.Topology.Algebra.InfiniteSum.Module import Mathlib.Analysis.NormedSpace.FunctionSeries #align_import analysis.calculus.series from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Smoothness of series We show that series of functions are differentiable, or smooth, when each individual function in the series is and additionally suitable uniform summable bounds are satisfied. More specifically, * `differentiable_tsum` ensures that a series of differentiable functions is differentiable. * `contDiff_tsum` ensures that a series of smooth functions is smooth. We also give versions of these statements which are localized to a set. -/ open Set Metric TopologicalSpace Function Asymptotics Filter open scoped Topology NNReal variable {α β 𝕜 E F : Type*} [RCLike 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [CompleteSpace F] {u : α → ℝ} /-! ### Differentiability -/ variable [NormedSpace 𝕜 F] variable {f : α → E → F} {f' : α → E → E →L[𝕜] F} {g : α → 𝕜 → F} {g' : α → 𝕜 → F} {v : ℕ → α → ℝ} {s : Set E} {t : Set 𝕜} {x₀ x : E} {y₀ y : 𝕜} {N : ℕ∞} /-- Consider a series of functions `∑' n, f n x` on a preconnected open set. If the series converges at a point, and all functions in the series are differentiable with a summable bound on the derivatives, then the series converges everywhere on the set. -/ theorem summable_of_summable_hasFDerivAt_of_isPreconnected (hu : Summable u) (hs : IsOpen s) (h's : IsPreconnected s) (hf : ∀ n x, x ∈ s → HasFDerivAt (f n) (f' n x) x) (hf' : ∀ n x, x ∈ s → ‖f' n x‖ ≤ u n) (hx₀ : x₀ ∈ s) (hf0 : Summable (f · x₀)) (hx : x ∈ s) : Summable fun n => f n x := by haveI := Classical.decEq α rw [summable_iff_cauchySeq_finset] at hf0 ⊢ have A : UniformCauchySeqOn (fun t : Finset α => fun x => ∑ i ∈ t, f' i x) atTop s := (tendstoUniformlyOn_tsum hu hf').uniformCauchySeqOn -- Porting note: Lean 4 failed to find `f` by unification refine cauchy_map_of_uniformCauchySeqOn_fderiv (f := fun t x ↦ ∑ i ∈ t, f i x) hs h's A (fun t y hy => ?_) hx₀ hx hf0 exact HasFDerivAt.sum fun i _ => hf i y hy #align summable_of_summable_has_fderiv_at_of_is_preconnected summable_of_summable_hasFDerivAt_of_isPreconnected /-- Consider a series of functions `∑' n, f n x` on a preconnected open set. If the series converges at a point, and all functions in the series are differentiable with a summable bound on the derivatives, then the series converges everywhere on the set. -/ theorem summable_of_summable_hasDerivAt_of_isPreconnected (hu : Summable u) (ht : IsOpen t) (h't : IsPreconnected t) (hg : ∀ n y, y ∈ t → HasDerivAt (g n) (g' n y) y) (hg' : ∀ n y, y ∈ t → ‖g' n y‖ ≤ u n) (hy₀ : y₀ ∈ t) (hg0 : Summable (g · y₀)) (hy : y ∈ t) : Summable fun n => g n y := by simp_rw [hasDerivAt_iff_hasFDerivAt] at hg refine summable_of_summable_hasFDerivAt_of_isPreconnected hu ht h't hg ?_ hy₀ hg0 hy simpa? says simpa only [ContinuousLinearMap.norm_smulRight_apply, norm_one, one_mul] /-- Consider a series of functions `∑' n, f n x` on a preconnected open set. If the series converges at a point, and all functions in the series are differentiable with a summable bound on the derivatives, then the series is differentiable on the set and its derivative is the sum of the derivatives. -/
Mathlib/Analysis/Calculus/SmoothSeries.lean
72
84
theorem hasFDerivAt_tsum_of_isPreconnected (hu : Summable u) (hs : IsOpen s) (h's : IsPreconnected s) (hf : ∀ n x, x ∈ s → HasFDerivAt (f n) (f' n x) x) (hf' : ∀ n x, x ∈ s → ‖f' n x‖ ≤ u n) (hx₀ : x₀ ∈ s) (hf0 : Summable fun n => f n x₀) (hx : x ∈ s) : HasFDerivAt (fun y => ∑' n, f n y) (∑' n, f' n x) x := by
classical have A : ∀ x : E, x ∈ s → Tendsto (fun t : Finset α => ∑ n ∈ t, f n x) atTop (𝓝 (∑' n, f n x)) := by intro y hy apply Summable.hasSum exact summable_of_summable_hasFDerivAt_of_isPreconnected hu hs h's hf hf' hx₀ hf0 hy refine hasFDerivAt_of_tendstoUniformlyOn hs (tendstoUniformlyOn_tsum hu hf') (fun t y hy => ?_) A _ hx exact HasFDerivAt.sum fun n _ => hf n y hy
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Fintype.Prod import Mathlib.Data.Fintype.Sum import Mathlib.SetTheory.Cardinal.Finite #align_import data.fintype.units from "leanprover-community/mathlib"@"509de852e1de55e1efa8eacfa11df0823f26f226" /-! # fintype instances relating to units -/ variable {α : Type*} instance UnitsInt.fintype : Fintype ℤˣ := ⟨{1, -1}, fun x ↦ by cases Int.units_eq_one_or x <;> simp [*]⟩ #align units_int.fintype UnitsInt.fintype @[simp] theorem UnitsInt.univ : (Finset.univ : Finset ℤˣ) = {1, -1} := rfl #align units_int.univ UnitsInt.univ @[simp] theorem Fintype.card_units_int : Fintype.card ℤˣ = 2 := rfl #align fintype.card_units_int Fintype.card_units_int instance [Monoid α] [Fintype α] [DecidableEq α] : Fintype αˣ := Fintype.ofEquiv _ (unitsEquivProdSubtype α).symm instance [Monoid α] [Finite α] : Finite αˣ := Finite.of_injective _ Units.ext theorem Fintype.card_eq_card_units_add_one [GroupWithZero α] [Fintype α] [DecidableEq α] : Fintype.card α = Fintype.card αˣ + 1 := by rw [eq_comm, Fintype.card_congr unitsEquivNeZero] have := Fintype.card_congr (Equiv.sumCompl (· = (0 : α))) rwa [Fintype.card_sum, add_comm, Fintype.card_subtype_eq] at this theorem Nat.card_eq_card_units_add_one [GroupWithZero α] [Finite α] : Nat.card α = Nat.card αˣ + 1 := by have : Fintype α := Fintype.ofFinite α classical rw [Nat.card_eq_fintype_card, Nat.card_eq_fintype_card, Fintype.card_eq_card_units_add_one]
Mathlib/Data/Fintype/Units.lean
48
50
theorem Fintype.card_units [GroupWithZero α] [Fintype α] [DecidableEq α] : Fintype.card αˣ = Fintype.card α - 1 := by
rw [@Fintype.card_eq_card_units_add_one α, Nat.add_sub_cancel]
/- Copyright (c) 2022 Floris van Doorn, Heather Macbeth. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn, Heather Macbeth -/ import Mathlib.Geometry.Manifold.ContMDiff.Atlas import Mathlib.Geometry.Manifold.VectorBundle.FiberwiseLinear import Mathlib.Topology.VectorBundle.Constructions #align_import geometry.manifold.vector_bundle.basic from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833" /-! # Smooth vector bundles This file defines smooth vector bundles over a smooth manifold. Let `E` be a topological vector bundle, with model fiber `F` and base space `B`. We consider `E` as carrying a charted space structure given by its trivializations -- these are charts to `B × F`. Then, by "composition", if `B` is itself a charted space over `H` (e.g. a smooth manifold), then `E` is also a charted space over `H × F`. Now, we define `SmoothVectorBundle` as the `Prop` of having smooth transition functions. Recall the structure groupoid `smoothFiberwiseLinear` on `B × F` consisting of smooth, fiberwise linear partial homeomorphisms. We show that our definition of "smooth vector bundle" implies `HasGroupoid` for this groupoid, and show (by a "composition" of `HasGroupoid` instances) that this means that a smooth vector bundle is a smooth manifold. Since `SmoothVectorBundle` is a mixin, it should be easy to make variants and for many such variants to coexist -- vector bundles can be smooth vector bundles over several different base fields, they can also be C^k vector bundles, etc. ## Main definitions and constructions * `FiberBundle.chartedSpace`: A fiber bundle `E` over a base `B` with model fiber `F` is naturally a charted space modelled on `B × F`. * `FiberBundle.chartedSpace'`: Let `B` be a charted space modelled on `HB`. Then a fiber bundle `E` over a base `B` with model fiber `F` is naturally a charted space modelled on `HB.prod F`. * `SmoothVectorBundle`: Mixin class stating that a (topological) `VectorBundle` is smooth, in the sense of having smooth transition functions. * `SmoothFiberwiseLinear.hasGroupoid`: For a smooth vector bundle `E` over `B` with fiber modelled on `F`, the change-of-co-ordinates between two trivializations `e`, `e'` for `E`, considered as charts to `B × F`, is smooth and fiberwise linear, in the sense of belonging to the structure groupoid `smoothFiberwiseLinear`. * `Bundle.TotalSpace.smoothManifoldWithCorners`: A smooth vector bundle is naturally a smooth manifold. * `VectorBundleCore.smoothVectorBundle`: If a (topological) `VectorBundleCore` is smooth, in the sense of having smooth transition functions (cf. `VectorBundleCore.IsSmooth`), then the vector bundle constructed from it is a smooth vector bundle. * `VectorPrebundle.smoothVectorBundle`: If a `VectorPrebundle` is smooth, in the sense of having smooth transition functions (cf. `VectorPrebundle.IsSmooth`), then the vector bundle constructed from it is a smooth vector bundle. * `Bundle.Prod.smoothVectorBundle`: The direct sum of two smooth vector bundles is a smooth vector bundle. -/ assert_not_exists mfderiv open Bundle Set PartialHomeomorph open Function (id_def) open Filter open scoped Manifold Bundle Topology variable {𝕜 B B' F M : Type*} {E : B → Type*} /-! ### Charted space structure on a fiber bundle -/ section variable [TopologicalSpace F] [TopologicalSpace (TotalSpace F E)] [∀ x, TopologicalSpace (E x)] {HB : Type*} [TopologicalSpace HB] [TopologicalSpace B] [ChartedSpace HB B] [FiberBundle F E] /-- A fiber bundle `E` over a base `B` with model fiber `F` is naturally a charted space modelled on `B × F`. -/ instance FiberBundle.chartedSpace' : ChartedSpace (B × F) (TotalSpace F E) where atlas := (fun e : Trivialization F (π F E) => e.toPartialHomeomorph) '' trivializationAtlas F E chartAt x := (trivializationAt F E x.proj).toPartialHomeomorph mem_chart_source x := (trivializationAt F E x.proj).mem_source.mpr (mem_baseSet_trivializationAt F E x.proj) chart_mem_atlas _ := mem_image_of_mem _ (trivialization_mem_atlas F E _) #align fiber_bundle.charted_space FiberBundle.chartedSpace' theorem FiberBundle.chartedSpace'_chartAt (x : TotalSpace F E) : chartAt (B × F) x = (trivializationAt F E x.proj).toPartialHomeomorph := rfl /- Porting note: In Lean 3, the next instance was inside a section with locally reducible `ModelProd` and it used `ModelProd B F` as the intermediate space. Using `B × F` in the middle gives the same instance. -/ --attribute [local reducible] ModelProd /-- Let `B` be a charted space modelled on `HB`. Then a fiber bundle `E` over a base `B` with model fiber `F` is naturally a charted space modelled on `HB.prod F`. -/ instance FiberBundle.chartedSpace : ChartedSpace (ModelProd HB F) (TotalSpace F E) := ChartedSpace.comp _ (B × F) _ #align fiber_bundle.charted_space' FiberBundle.chartedSpace
Mathlib/Geometry/Manifold/VectorBundle/Basic.lean
108
114
theorem FiberBundle.chartedSpace_chartAt (x : TotalSpace F E) : chartAt (ModelProd HB F) x = (trivializationAt F E x.proj).toPartialHomeomorph ≫ₕ (chartAt HB x.proj).prod (PartialHomeomorph.refl F) := by
dsimp only [chartAt_comp, prodChartedSpace_chartAt, FiberBundle.chartedSpace'_chartAt, chartAt_self_eq] rw [Trivialization.coe_coe, Trivialization.coe_fst' _ (mem_baseSet_trivializationAt F E x.proj)]
/- Copyright (c) 2020 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers, Manuel Candales -/ import Mathlib.Analysis.InnerProductSpace.Projection import Mathlib.Geometry.Euclidean.PerpBisector import Mathlib.Algebra.QuadraticDiscriminant #align_import geometry.euclidean.basic from "leanprover-community/mathlib"@"2de9c37fa71dde2f1c6feff19876dd6a7b1519f0" /-! # Euclidean spaces This file makes some definitions and proves very basic geometrical results about real inner product spaces and Euclidean affine spaces. Results about real inner product spaces that involve the norm and inner product but not angles generally go in `Analysis.NormedSpace.InnerProduct`. Results with longer proofs or more geometrical content generally go in separate files. ## Main definitions * `EuclideanGeometry.orthogonalProjection` is the orthogonal projection of a point onto an affine subspace. * `EuclideanGeometry.reflection` is the reflection of a point in an affine subspace. ## Implementation notes To declare `P` as the type of points in a Euclidean affine space with `V` as the type of vectors, use `[NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] [NormedAddTorsor V P]`. This works better with `outParam` to make `V` implicit in most cases than having a separate type alias for Euclidean affine spaces. Rather than requiring Euclidean affine spaces to be finite-dimensional (as in the definition on Wikipedia), this is specified only for those theorems that need it. ## References * https://en.wikipedia.org/wiki/Euclidean_space -/ noncomputable section open scoped Classical open RealInnerProductSpace namespace EuclideanGeometry /-! ### Geometrical results on Euclidean affine spaces This section develops some geometrical definitions and results on Euclidean affine spaces. -/ variable {V : Type*} {P : Type*} variable [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] variable [NormedAddTorsor V P] /-- The midpoint of the segment AB is the same distance from A as it is from B. -/ theorem dist_left_midpoint_eq_dist_right_midpoint (p1 p2 : P) : dist p1 (midpoint ℝ p1 p2) = dist p2 (midpoint ℝ p1 p2) := by rw [dist_left_midpoint (𝕜 := ℝ) p1 p2, dist_right_midpoint (𝕜 := ℝ) p1 p2] #align euclidean_geometry.dist_left_midpoint_eq_dist_right_midpoint EuclideanGeometry.dist_left_midpoint_eq_dist_right_midpoint /-- The inner product of two vectors given with `weightedVSub`, in terms of the pairwise distances. -/ theorem inner_weightedVSub {ι₁ : Type*} {s₁ : Finset ι₁} {w₁ : ι₁ → ℝ} (p₁ : ι₁ → P) (h₁ : ∑ i ∈ s₁, w₁ i = 0) {ι₂ : Type*} {s₂ : Finset ι₂} {w₂ : ι₂ → ℝ} (p₂ : ι₂ → P) (h₂ : ∑ i ∈ s₂, w₂ i = 0) : ⟪s₁.weightedVSub p₁ w₁, s₂.weightedVSub p₂ w₂⟫ = (-∑ i₁ ∈ s₁, ∑ i₂ ∈ s₂, w₁ i₁ * w₂ i₂ * (dist (p₁ i₁) (p₂ i₂) * dist (p₁ i₁) (p₂ i₂))) / 2 := by rw [Finset.weightedVSub_apply, Finset.weightedVSub_apply, inner_sum_smul_sum_smul_of_sum_eq_zero _ h₁ _ h₂] simp_rw [vsub_sub_vsub_cancel_right] rcongr (i₁ i₂) <;> rw [dist_eq_norm_vsub V (p₁ i₁) (p₂ i₂)] #align euclidean_geometry.inner_weighted_vsub EuclideanGeometry.inner_weightedVSub /-- The distance between two points given with `affineCombination`, in terms of the pairwise distances between the points in that combination. -/ theorem dist_affineCombination {ι : Type*} {s : Finset ι} {w₁ w₂ : ι → ℝ} (p : ι → P) (h₁ : ∑ i ∈ s, w₁ i = 1) (h₂ : ∑ i ∈ s, w₂ i = 1) : by have a₁ := s.affineCombination ℝ p w₁ have a₂ := s.affineCombination ℝ p w₂ exact dist a₁ a₂ * dist a₁ a₂ = (-∑ i₁ ∈ s, ∑ i₂ ∈ s, (w₁ - w₂) i₁ * (w₁ - w₂) i₂ * (dist (p i₁) (p i₂) * dist (p i₁) (p i₂))) / 2 := by dsimp only rw [dist_eq_norm_vsub V (s.affineCombination ℝ p w₁) (s.affineCombination ℝ p w₂), ← @inner_self_eq_norm_mul_norm ℝ, Finset.affineCombination_vsub] have h : (∑ i ∈ s, (w₁ - w₂) i) = 0 := by simp_rw [Pi.sub_apply, Finset.sum_sub_distrib, h₁, h₂, sub_self] exact inner_weightedVSub p h p h #align euclidean_geometry.dist_affine_combination EuclideanGeometry.dist_affineCombination -- Porting note: `inner_vsub_vsub_of_dist_eq_of_dist_eq` moved to `PerpendicularBisector` /-- The squared distance between points on a line (expressed as a multiple of a fixed vector added to a point) and another point, expressed as a quadratic. -/
Mathlib/Geometry/Euclidean/Basic.lean
112
117
theorem dist_smul_vadd_sq (r : ℝ) (v : V) (p₁ p₂ : P) : dist (r • v +ᵥ p₁) p₂ * dist (r • v +ᵥ p₁) p₂ = ⟪v, v⟫ * r * r + 2 * ⟪v, p₁ -ᵥ p₂⟫ * r + ⟪p₁ -ᵥ p₂, p₁ -ᵥ p₂⟫ := by
rw [dist_eq_norm_vsub V _ p₂, ← real_inner_self_eq_norm_mul_norm, vadd_vsub_assoc, real_inner_add_add_self, real_inner_smul_left, real_inner_smul_left, real_inner_smul_right] ring
/- Copyright (c) 2020 Simon Hudon. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Simon Hudon -/ import Mathlib.Data.Stream.Init import Mathlib.Tactic.ApplyFun import Mathlib.Control.Fix import Mathlib.Order.OmegaCompletePartialOrder #align_import control.lawful_fix from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7" /-! # Lawful fixed point operators This module defines the laws required of a `Fix` instance, using the theory of omega complete partial orders (ωCPO). Proofs of the lawfulness of all `Fix` instances in `Control.Fix` are provided. ## Main definition * class `LawfulFix` -/ universe u v open scoped Classical variable {α : Type*} {β : α → Type*} open OmegaCompletePartialOrder /- Porting note: in `#align`s, mathport is putting some `fix`es where `Fix`es should be. -/ /-- Intuitively, a fixed point operator `fix` is lawful if it satisfies `fix f = f (fix f)` for all `f`, but this is inconsistent / uninteresting in most cases due to the existence of "exotic" functions `f`, such as the function that is defined iff its argument is not, familiar from the halting problem. Instead, this requirement is limited to only functions that are `Continuous` in the sense of `ω`-complete partial orders, which excludes the example because it is not monotone (making the input argument less defined can make `f` more defined). -/ class LawfulFix (α : Type*) [OmegaCompletePartialOrder α] extends Fix α where fix_eq : ∀ {f : α →o α}, Continuous f → Fix.fix f = f (Fix.fix f) #align lawful_fix LawfulFix theorem LawfulFix.fix_eq' {α} [OmegaCompletePartialOrder α] [LawfulFix α] {f : α → α} (hf : Continuous' f) : Fix.fix f = f (Fix.fix f) := LawfulFix.fix_eq (hf.to_bundled _) #align lawful_fix.fix_eq' LawfulFix.fix_eq' namespace Part open Part Nat Nat.Upto namespace Fix variable (f : ((a : _) → Part <| β a) →o (a : _) → Part <| β a) theorem approx_mono' {i : ℕ} : Fix.approx f i ≤ Fix.approx f (succ i) := by induction i with | zero => dsimp [approx]; apply @bot_le _ _ _ (f ⊥) | succ _ i_ih => intro; apply f.monotone; apply i_ih #align part.fix.approx_mono' Part.Fix.approx_mono' theorem approx_mono ⦃i j : ℕ⦄ (hij : i ≤ j) : approx f i ≤ approx f j := by induction' j with j ih · cases hij exact le_rfl cases hij; · exact le_rfl exact le_trans (ih ‹_›) (approx_mono' f) #align part.fix.approx_mono Part.Fix.approx_mono theorem mem_iff (a : α) (b : β a) : b ∈ Part.fix f a ↔ ∃ i, b ∈ approx f i a := by by_cases h₀ : ∃ i : ℕ, (approx f i a).Dom · simp only [Part.fix_def f h₀] constructor <;> intro hh · exact ⟨_, hh⟩ have h₁ := Nat.find_spec h₀ rw [dom_iff_mem] at h₁ cases' h₁ with y h₁ replace h₁ := approx_mono' f _ _ h₁ suffices y = b by subst this exact h₁ cases' hh with i hh revert h₁; generalize succ (Nat.find h₀) = j; intro h₁ wlog case : i ≤ j · rcases le_total i j with H | H <;> [skip; symm] <;> apply_assumption <;> assumption replace hh := approx_mono f case _ _ hh apply Part.mem_unique h₁ hh · simp only [fix_def' (⇑f) h₀, not_exists, false_iff_iff, not_mem_none] simp only [dom_iff_mem, not_exists] at h₀ intro; apply h₀ #align part.fix.mem_iff Part.Fix.mem_iff theorem approx_le_fix (i : ℕ) : approx f i ≤ Part.fix f := fun a b hh ↦ by rw [mem_iff f] exact ⟨_, hh⟩ #align part.fix.approx_le_fix Part.Fix.approx_le_fix theorem exists_fix_le_approx (x : α) : ∃ i, Part.fix f x ≤ approx f i x := by by_cases hh : ∃ i b, b ∈ approx f i x · rcases hh with ⟨i, b, hb⟩ exists i intro b' h' have hb' := approx_le_fix f i _ _ hb obtain rfl := Part.mem_unique h' hb' exact hb · simp only [not_exists] at hh exists 0 intro b' h' simp only [mem_iff f] at h' cases' h' with i h' cases hh _ _ h' #align part.fix.exists_fix_le_approx Part.Fix.exists_fix_le_approx /-- The series of approximations of `fix f` (see `approx`) as a `Chain` -/ def approxChain : Chain ((a : _) → Part <| β a) := ⟨approx f, approx_mono f⟩ #align part.fix.approx_chain Part.Fix.approxChain
Mathlib/Control/LawfulFix.lean
120
123
theorem le_f_of_mem_approx {x} : x ∈ approxChain f → x ≤ f x := by
simp only [(· ∈ ·), forall_exists_index] rintro i rfl apply approx_mono'
/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Probability.IdentDistrib import Mathlib.MeasureTheory.Integral.DominatedConvergence import Mathlib.Analysis.SpecificLimits.FloorPow import Mathlib.Analysis.PSeries import Mathlib.Analysis.Asymptotics.SpecificAsymptotics #align_import probability.strong_law from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # The strong law of large numbers We prove the strong law of large numbers, in `ProbabilityTheory.strong_law_ae`: If `X n` is a sequence of independent identically distributed integrable random variables, then `∑ i ∈ range n, X i / n` converges almost surely to `𝔼[X 0]`. We give here the strong version, due to Etemadi, that only requires pairwise independence. This file also contains the Lᵖ version of the strong law of large numbers provided by `ProbabilityTheory.strong_law_Lp` which shows `∑ i ∈ range n, X i / n` converges in Lᵖ to `𝔼[X 0]` provided `X n` is independent identically distributed and is Lᵖ. ## Implementation The main point is to prove the result for real-valued random variables, as the general case of Banach-space valued random variables follows from this case and approximation by simple functions. The real version is given in `ProbabilityTheory.strong_law_ae_real`. We follow the proof by Etemadi [Etemadi, *An elementary proof of the strong law of large numbers*][etemadi_strong_law], which goes as follows. It suffices to prove the result for nonnegative `X`, as one can prove the general result by splitting a general `X` into its positive part and negative part. Consider `Xₙ` a sequence of nonnegative integrable identically distributed pairwise independent random variables. Let `Yₙ` be the truncation of `Xₙ` up to `n`. We claim that * Almost surely, `Xₙ = Yₙ` for all but finitely many indices. Indeed, `∑ ℙ (Xₙ ≠ Yₙ)` is bounded by `1 + 𝔼[X]` (see `sum_prob_mem_Ioc_le` and `tsum_prob_mem_Ioi_lt_top`). * Let `c > 1`. Along the sequence `n = c ^ k`, then `(∑_{i=0}^{n-1} Yᵢ - 𝔼[Yᵢ])/n` converges almost surely to `0`. This follows from a variance control, as ``` ∑_k ℙ (|∑_{i=0}^{c^k - 1} Yᵢ - 𝔼[Yᵢ]| > c^k ε) ≤ ∑_k (c^k ε)^{-2} ∑_{i=0}^{c^k - 1} Var[Yᵢ] (by Markov inequality) ≤ ∑_i (C/i^2) Var[Yᵢ] (as ∑_{c^k > i} 1/(c^k)^2 ≤ C/i^2) ≤ ∑_i (C/i^2) 𝔼[Yᵢ^2] ≤ 2C 𝔼[X^2] (see `sum_variance_truncation_le`) ``` * As `𝔼[Yᵢ]` converges to `𝔼[X]`, it follows from the two previous items and Cesàro that, along the sequence `n = c^k`, one has `(∑_{i=0}^{n-1} Xᵢ) / n → 𝔼[X]` almost surely. * To generalize it to all indices, we use the fact that `∑_{i=0}^{n-1} Xᵢ` is nondecreasing and that, if `c` is close enough to `1`, the gap between `c^k` and `c^(k+1)` is small. -/ noncomputable section open MeasureTheory Filter Finset Asymptotics open Set (indicator) open scoped Topology MeasureTheory ProbabilityTheory ENNReal NNReal namespace ProbabilityTheory /-! ### Prerequisites on truncations -/ section Truncation variable {α : Type*} /-- Truncating a real-valued function to the interval `(-A, A]`. -/ def truncation (f : α → ℝ) (A : ℝ) := indicator (Set.Ioc (-A) A) id ∘ f #align probability_theory.truncation ProbabilityTheory.truncation variable {m : MeasurableSpace α} {μ : Measure α} {f : α → ℝ} theorem _root_.MeasureTheory.AEStronglyMeasurable.truncation (hf : AEStronglyMeasurable f μ) {A : ℝ} : AEStronglyMeasurable (truncation f A) μ := by apply AEStronglyMeasurable.comp_aemeasurable _ hf.aemeasurable exact (stronglyMeasurable_id.indicator measurableSet_Ioc).aestronglyMeasurable #align measure_theory.ae_strongly_measurable.truncation MeasureTheory.AEStronglyMeasurable.truncation
Mathlib/Probability/StrongLaw.lean
88
92
theorem abs_truncation_le_bound (f : α → ℝ) (A : ℝ) (x : α) : |truncation f A x| ≤ |A| := by
simp only [truncation, Set.indicator, Set.mem_Icc, id, Function.comp_apply] split_ifs with h · exact abs_le_abs h.2 (neg_le.2 h.1.le) · simp [abs_nonneg]
/- Copyright (c) 2022 Antoine Labelle. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Labelle -/ import Mathlib.Algebra.Group.Equiv.TypeTags import Mathlib.Algebra.Module.Defs import Mathlib.Algebra.Module.LinearMap.Basic import Mathlib.Algebra.MonoidAlgebra.Basic import Mathlib.LinearAlgebra.Dual import Mathlib.LinearAlgebra.Contraction import Mathlib.RingTheory.TensorProduct.Basic #align_import representation_theory.basic from "leanprover-community/mathlib"@"c04bc6e93e23aa0182aba53661a2211e80b6feac" /-! # Monoid representations This file introduces monoid representations and their characters and defines a few ways to construct representations. ## Main definitions * Representation.Representation * Representation.character * Representation.tprod * Representation.linHom * Representation.dual ## Implementation notes Representations of a monoid `G` on a `k`-module `V` are implemented as homomorphisms `G →* (V →ₗ[k] V)`. We use the abbreviation `Representation` for this hom space. The theorem `asAlgebraHom_def` constructs a module over the group `k`-algebra of `G` (implemented as `MonoidAlgebra k G`) corresponding to a representation. If `ρ : Representation k G V`, this module can be accessed via `ρ.asModule`. Conversely, given a `MonoidAlgebra k G-module `M` `M.ofModule` is the associociated representation seen as a homomorphism. -/ open MonoidAlgebra (lift of) open LinearMap section variable (k G V : Type*) [CommSemiring k] [Monoid G] [AddCommMonoid V] [Module k V] /-- A representation of `G` on the `k`-module `V` is a homomorphism `G →* (V →ₗ[k] V)`. -/ abbrev Representation := G →* V →ₗ[k] V #align representation Representation end namespace Representation section trivial variable (k : Type*) {G V : Type*} [CommSemiring k] [Monoid G] [AddCommMonoid V] [Module k V] /-- The trivial representation of `G` on a `k`-module V. -/ def trivial : Representation k G V := 1 #align representation.trivial Representation.trivial -- Porting note: why is `V` implicit theorem trivial_def (g : G) (v : V) : trivial k (V := V) g v = v := rfl #align representation.trivial_def Representation.trivial_def variable {k} /-- A predicate for representations that fix every element. -/ class IsTrivial (ρ : Representation k G V) : Prop where out : ∀ g x, ρ g x = x := by aesop instance : IsTrivial (trivial k (G := G) (V := V)) where @[simp] theorem apply_eq_self (ρ : Representation k G V) (g : G) (x : V) [h : IsTrivial ρ] : ρ g x = x := h.out g x end trivial section MonoidAlgebra variable {k G V : Type*} [CommSemiring k] [Monoid G] [AddCommMonoid V] [Module k V] variable (ρ : Representation k G V) /-- A `k`-linear representation of `G` on `V` can be thought of as an algebra map from `MonoidAlgebra k G` into the `k`-linear endomorphisms of `V`. -/ noncomputable def asAlgebraHom : MonoidAlgebra k G →ₐ[k] Module.End k V := (lift k G _) ρ #align representation.as_algebra_hom Representation.asAlgebraHom theorem asAlgebraHom_def : asAlgebraHom ρ = (lift k G _) ρ := rfl #align representation.as_algebra_hom_def Representation.asAlgebraHom_def @[simp] theorem asAlgebraHom_single (g : G) (r : k) : asAlgebraHom ρ (Finsupp.single g r) = r • ρ g := by simp only [asAlgebraHom_def, MonoidAlgebra.lift_single] #align representation.as_algebra_hom_single Representation.asAlgebraHom_single theorem asAlgebraHom_single_one (g : G) : asAlgebraHom ρ (Finsupp.single g 1) = ρ g := by simp #align representation.as_algebra_hom_single_one Representation.asAlgebraHom_single_one theorem asAlgebraHom_of (g : G) : asAlgebraHom ρ (of k G g) = ρ g := by simp only [MonoidAlgebra.of_apply, asAlgebraHom_single, one_smul] #align representation.as_algebra_hom_of Representation.asAlgebraHom_of /-- If `ρ : Representation k G V`, then `ρ.asModule` is a type synonym for `V`, which we equip with an instance `Module (MonoidAlgebra k G) ρ.asModule`. You should use `asModuleEquiv : ρ.asModule ≃+ V` to translate terms. -/ @[nolint unusedArguments] def asModule (_ : Representation k G V) := V #align representation.as_module Representation.asModule -- Porting note: no derive handler instance : AddCommMonoid (ρ.asModule) := inferInstanceAs <| AddCommMonoid V instance : Inhabited ρ.asModule where default := 0 /-- A `k`-linear representation of `G` on `V` can be thought of as a module over `MonoidAlgebra k G`. -/ noncomputable instance asModuleModule : Module (MonoidAlgebra k G) ρ.asModule := Module.compHom V (asAlgebraHom ρ).toRingHom #align representation.as_module_module Representation.asModuleModule -- Porting note: ρ.asModule doesn't unfold now instance : Module k ρ.asModule := inferInstanceAs <| Module k V /-- The additive equivalence from the `Module (MonoidAlgebra k G)` to the original vector space of the representative. This is just the identity, but it is helpful for typechecking and keeping track of instances. -/ def asModuleEquiv : ρ.asModule ≃+ V := AddEquiv.refl _ #align representation.as_module_equiv Representation.asModuleEquiv @[simp] theorem asModuleEquiv_map_smul (r : MonoidAlgebra k G) (x : ρ.asModule) : ρ.asModuleEquiv (r • x) = ρ.asAlgebraHom r (ρ.asModuleEquiv x) := rfl #align representation.as_module_equiv_map_smul Representation.asModuleEquiv_map_smul @[simp] theorem asModuleEquiv_symm_map_smul (r : k) (x : V) : ρ.asModuleEquiv.symm (r • x) = algebraMap k (MonoidAlgebra k G) r • ρ.asModuleEquiv.symm x := by apply_fun ρ.asModuleEquiv simp #align representation.as_module_equiv_symm_map_smul Representation.asModuleEquiv_symm_map_smul @[simp]
Mathlib/RepresentationTheory/Basic.lean
166
169
theorem asModuleEquiv_symm_map_rho (g : G) (x : V) : ρ.asModuleEquiv.symm (ρ g x) = MonoidAlgebra.of k G g • ρ.asModuleEquiv.symm x := by
apply_fun ρ.asModuleEquiv simp
/- 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
Mathlib/Order/Heyting/Regular.lean
63
63
theorem isRegular_top : IsRegular (⊤ : α) := by
rw [IsRegular, compl_top, compl_bot]
/- Copyright (c) 2022 Michael Stoll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Michael Stoll, Thomas Zhu, Mario Carneiro -/ import Mathlib.NumberTheory.LegendreSymbol.QuadraticReciprocity #align_import number_theory.legendre_symbol.jacobi_symbol from "leanprover-community/mathlib"@"74a27133cf29446a0983779e37c8f829a85368f3" /-! # The Jacobi Symbol We define the Jacobi symbol and prove its main properties. ## Main definitions We define the Jacobi symbol, `jacobiSym a b`, for integers `a` and natural numbers `b` as the product over the prime factors `p` of `b` of the Legendre symbols `legendreSym p a`. This agrees with the mathematical definition when `b` is odd. The prime factors are obtained via `Nat.factors`. Since `Nat.factors 0 = []`, this implies in particular that `jacobiSym a 0 = 1` for all `a`. ## Main statements We prove the main properties of the Jacobi symbol, including the following. * Multiplicativity in both arguments (`jacobiSym.mul_left`, `jacobiSym.mul_right`) * The value of the symbol is `1` or `-1` when the arguments are coprime (`jacobiSym.eq_one_or_neg_one`) * The symbol vanishes if and only if `b ≠ 0` and the arguments are not coprime (`jacobiSym.eq_zero_iff_not_coprime`) * If the symbol has the value `-1`, then `a : ZMod b` is not a square (`ZMod.nonsquare_of_jacobiSym_eq_neg_one`); the converse holds when `b = p` is a prime (`ZMod.nonsquare_iff_jacobiSym_eq_neg_one`); in particular, in this case `a` is a square mod `p` when the symbol has the value `1` (`ZMod.isSquare_of_jacobiSym_eq_one`). * Quadratic reciprocity (`jacobiSym.quadratic_reciprocity`, `jacobiSym.quadratic_reciprocity_one_mod_four`, `jacobiSym.quadratic_reciprocity_three_mod_four`) * The supplementary laws for `a = -1`, `a = 2`, `a = -2` (`jacobiSym.at_neg_one`, `jacobiSym.at_two`, `jacobiSym.at_neg_two`) * The symbol depends on `a` only via its residue class mod `b` (`jacobiSym.mod_left`) and on `b` only via its residue class mod `4*a` (`jacobiSym.mod_right`) * A `csimp` rule for `jacobiSym` and `legendreSym` that evaluates `J(a | b)` efficiently by reducing to the case `0 ≤ a < b` and `a`, `b` odd, and then swaps `a`, `b` and recurses using quadratic reciprocity. ## Notations We define the notation `J(a | b)` for `jacobiSym a b`, localized to `NumberTheorySymbols`. ## Tags Jacobi symbol, quadratic reciprocity -/ section Jacobi /-! ### Definition of the Jacobi symbol We define the Jacobi symbol $\Bigl(\frac{a}{b}\Bigr)$ for integers `a` and natural numbers `b` as the product of the Legendre symbols $\Bigl(\frac{a}{p}\Bigr)$, where `p` runs through the prime divisors (with multiplicity) of `b`, as provided by `b.factors`. This agrees with the Jacobi symbol when `b` is odd and gives less meaningful values when it is not (e.g., the symbol is `1` when `b = 0`). This is called `jacobiSym a b`. We define localized notation (locale `NumberTheorySymbols`) `J(a | b)` for the Jacobi symbol `jacobiSym a b`. -/ open Nat ZMod -- Since we need the fact that the factors are prime, we use `List.pmap`. /-- The Jacobi symbol of `a` and `b` -/ def jacobiSym (a : ℤ) (b : ℕ) : ℤ := (b.factors.pmap (fun p pp => @legendreSym p ⟨pp⟩ a) fun _ pf => prime_of_mem_factors pf).prod #align jacobi_sym jacobiSym -- Notation for the Jacobi symbol. @[inherit_doc] scoped[NumberTheorySymbols] notation "J(" a " | " b ")" => jacobiSym a b -- Porting note: Without the following line, Lean expected `|` on several lines, e.g. line 102. open NumberTheorySymbols /-! ### Properties of the Jacobi symbol -/ namespace jacobiSym /-- The symbol `J(a | 0)` has the value `1`. -/ @[simp]
Mathlib/NumberTheory/LegendreSymbol/JacobiSymbol.lean
104
105
theorem zero_right (a : ℤ) : J(a | 0) = 1 := by
simp only [jacobiSym, factors_zero, List.prod_nil, List.pmap]
/- Copyright (c) 2021 Heather Macbeth. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Heather Macbeth -/ import Mathlib.Analysis.InnerProductSpace.Rayleigh import Mathlib.Analysis.InnerProductSpace.PiL2 import Mathlib.Algebra.DirectSum.Decomposition import Mathlib.LinearAlgebra.Eigenspace.Minpoly #align_import analysis.inner_product_space.spectrum from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1" /-! # Spectral theory of self-adjoint operators This file covers the spectral theory of self-adjoint operators on an inner product space. The first part of the file covers general properties, true without any condition on boundedness or compactness of the operator or finite-dimensionality of the underlying space, notably: * `LinearMap.IsSymmetric.conj_eigenvalue_eq_self`: the eigenvalues are real * `LinearMap.IsSymmetric.orthogonalFamily_eigenspaces`: the eigenspaces are orthogonal * `LinearMap.IsSymmetric.orthogonalComplement_iSup_eigenspaces`: the restriction of the operator to the mutual orthogonal complement of the eigenspaces has, itself, no eigenvectors The second part of the file covers properties of self-adjoint operators in finite dimension. Letting `T` be a self-adjoint operator on a finite-dimensional inner product space `T`, * The definition `LinearMap.IsSymmetric.diagonalization` provides a linear isometry equivalence `E` to the direct sum of the eigenspaces of `T`. The theorem `LinearMap.IsSymmetric.diagonalization_apply_self_apply` states that, when `T` is transferred via this equivalence to an operator on the direct sum, it acts diagonally. * The definition `LinearMap.IsSymmetric.eigenvectorBasis` provides an orthonormal basis for `E` consisting of eigenvectors of `T`, with `LinearMap.IsSymmetric.eigenvalues` giving the corresponding list of eigenvalues, as real numbers. The definition `LinearMap.IsSymmetric.eigenvectorBasis` gives the associated linear isometry equivalence from `E` to Euclidean space, and the theorem `LinearMap.IsSymmetric.eigenvectorBasis_apply_self_apply` states that, when `T` is transferred via this equivalence to an operator on Euclidean space, it acts diagonally. These are forms of the *diagonalization theorem* for self-adjoint operators on finite-dimensional inner product spaces. ## TODO Spectral theory for compact self-adjoint operators, bounded self-adjoint operators. ## Tags self-adjoint operator, spectral theorem, diagonalization theorem -/ variable {𝕜 : Type*} [RCLike 𝕜] variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace 𝕜 E] local notation "⟪" x ", " y "⟫" => @inner 𝕜 E _ x y open scoped ComplexConjugate open Module.End namespace LinearMap namespace IsSymmetric variable {T : E →ₗ[𝕜] E} (hT : T.IsSymmetric) /-- A self-adjoint operator preserves orthogonal complements of its eigenspaces. -/ theorem invariant_orthogonalComplement_eigenspace (μ : 𝕜) (v : E) (hv : v ∈ (eigenspace T μ)ᗮ) : T v ∈ (eigenspace T μ)ᗮ := by intro w hw have : T w = (μ : 𝕜) • w := by rwa [mem_eigenspace_iff] at hw simp [← hT w, this, inner_smul_left, hv w hw] #align linear_map.is_symmetric.invariant_orthogonal_eigenspace LinearMap.IsSymmetric.invariant_orthogonalComplement_eigenspace /-- The eigenvalues of a self-adjoint operator are real. -/ theorem conj_eigenvalue_eq_self {μ : 𝕜} (hμ : HasEigenvalue T μ) : conj μ = μ := by obtain ⟨v, hv₁, hv₂⟩ := hμ.exists_hasEigenvector rw [mem_eigenspace_iff] at hv₁ simpa [hv₂, inner_smul_left, inner_smul_right, hv₁] using hT v v #align linear_map.is_symmetric.conj_eigenvalue_eq_self LinearMap.IsSymmetric.conj_eigenvalue_eq_self /-- The eigenspaces of a self-adjoint operator are mutually orthogonal. -/ theorem orthogonalFamily_eigenspaces : OrthogonalFamily 𝕜 (fun μ => eigenspace T μ) fun μ => (eigenspace T μ).subtypeₗᵢ := by rintro μ ν hμν ⟨v, hv⟩ ⟨w, hw⟩ by_cases hv' : v = 0 · simp [hv'] have H := hT.conj_eigenvalue_eq_self (hasEigenvalue_of_hasEigenvector ⟨hv, hv'⟩) rw [mem_eigenspace_iff] at hv hw refine Or.resolve_left ?_ hμν.symm simpa [inner_smul_left, inner_smul_right, hv, hw, H] using (hT v w).symm #align linear_map.is_symmetric.orthogonal_family_eigenspaces LinearMap.IsSymmetric.orthogonalFamily_eigenspaces theorem orthogonalFamily_eigenspaces' : OrthogonalFamily 𝕜 (fun μ : Eigenvalues T => eigenspace T μ) fun μ => (eigenspace T μ).subtypeₗᵢ := hT.orthogonalFamily_eigenspaces.comp Subtype.coe_injective #align linear_map.is_symmetric.orthogonal_family_eigenspaces' LinearMap.IsSymmetric.orthogonalFamily_eigenspaces' /-- The mutual orthogonal complement of the eigenspaces of a self-adjoint operator on an inner product space is an invariant subspace of the operator. -/ theorem orthogonalComplement_iSup_eigenspaces_invariant ⦃v : E⦄ (hv : v ∈ (⨆ μ, eigenspace T μ)ᗮ) : T v ∈ (⨆ μ, eigenspace T μ)ᗮ := by rw [← Submodule.iInf_orthogonal] at hv ⊢ exact T.iInf_invariant hT.invariant_orthogonalComplement_eigenspace v hv #align linear_map.is_symmetric.orthogonal_supr_eigenspaces_invariant LinearMap.IsSymmetric.orthogonalComplement_iSup_eigenspaces_invariant /-- The mutual orthogonal complement of the eigenspaces of a self-adjoint operator on an inner product space has no eigenvalues. -/
Mathlib/Analysis/InnerProductSpace/Spectrum.lean
110
115
theorem orthogonalComplement_iSup_eigenspaces (μ : 𝕜) : eigenspace (T.restrict hT.orthogonalComplement_iSup_eigenspaces_invariant) μ = ⊥ := by
set p : Submodule 𝕜 E := (⨆ μ, eigenspace T μ)ᗮ refine eigenspace_restrict_eq_bot hT.orthogonalComplement_iSup_eigenspaces_invariant ?_ have H₂ : eigenspace T μ ⟂ p := (Submodule.isOrtho_orthogonal_right _).mono_left (le_iSup _ _) exact H₂.disjoint
/- Copyright (c) 2024 Josha Dekker. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Josha Dekker -/ import Mathlib.Order.Filter.Basic import Mathlib.Order.Filter.CountableInter import Mathlib.SetTheory.Cardinal.Ordinal import Mathlib.SetTheory.Cardinal.Cofinality /-! # Filters with a cardinal intersection property In this file we define `CardinalInterFilter l c` to be the class of filters with the following property: for any collection of sets `s ∈ l` with cardinality strictly less than `c`, their intersection belongs to `l` as well. # Main results * `Filter.cardinalInterFilter_aleph0` establishes that every filter `l` is a `CardinalInterFilter l aleph0` * `CardinalInterFilter.toCountableInterFilter` establishes that every `CardinalInterFilter l c` with `c > aleph0` is a `CountableInterFilter`. * `CountableInterFilter.toCardinalInterFilter` establishes that every `CountableInterFilter l` is a `CardinalInterFilter l aleph1`. * `CardinalInterFilter.of_CardinalInterFilter_of_lt` establishes that we have `CardinalInterFilter l c` → `CardinalInterFilter l a` for all `a < c`. ## Tags filter, cardinal -/ open Set Filter Cardinal universe u variable {ι : Type u} {α β : Type u} {c : Cardinal.{u}} /-- A filter `l` has the cardinal `c` intersection property if for any collection of less than `c` sets `s ∈ l`, their intersection belongs to `l` as well. -/ class CardinalInterFilter (l : Filter α) (c : Cardinal.{u}) : Prop where /-- For a collection of sets `s ∈ l` with cardinality below c, their intersection belongs to `l` as well. -/ cardinal_sInter_mem : ∀ S : Set (Set α), (#S < c) → (∀ s ∈ S, s ∈ l) → ⋂₀ S ∈ l variable {l : Filter α} theorem cardinal_sInter_mem {S : Set (Set α)} [CardinalInterFilter l c] (hSc : #S < c) : ⋂₀ S ∈ l ↔ ∀ s ∈ S, s ∈ l := ⟨fun hS _s hs => mem_of_superset hS (sInter_subset_of_mem hs), CardinalInterFilter.cardinal_sInter_mem _ hSc⟩ /-- Every filter is a CardinalInterFilter with c = aleph0 -/
Mathlib/Order/Filter/CardinalInter.lean
52
55
theorem _root_.Filter.cardinalInterFilter_aleph0 (l : Filter α) : CardinalInterFilter l aleph0 where cardinal_sInter_mem := by
simp_all only [aleph_zero, lt_aleph0_iff_subtype_finite, setOf_mem_eq, sInter_mem, implies_true, forall_const]
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Kenny Lau, Johan Commelin, Mario Carneiro, Kevin Buzzard, Amelia Livingston, Yury Kudryashov -/ import Mathlib.Algebra.FreeMonoid.Basic import Mathlib.Algebra.Group.Submonoid.MulOpposite import Mathlib.Algebra.Group.Submonoid.Operations import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Data.Finset.NoncommProd import Mathlib.Data.Int.Order.Lemmas #align_import group_theory.submonoid.membership from "leanprover-community/mathlib"@"e655e4ea5c6d02854696f97494997ba4c31be802" /-! # Submonoids: membership criteria In this file we prove various facts about membership in a submonoid: * `list_prod_mem`, `multiset_prod_mem`, `prod_mem`: if each element of a collection belongs to a multiplicative submonoid, then so does their product; * `list_sum_mem`, `multiset_sum_mem`, `sum_mem`: if each element of a collection belongs to an additive submonoid, then so does their sum; * `pow_mem`, `nsmul_mem`: if `x ∈ S` where `S` is a multiplicative (resp., additive) submonoid and `n` is a natural number, then `x^n` (resp., `n • x`) belongs to `S`; * `mem_iSup_of_directed`, `coe_iSup_of_directed`, `mem_sSup_of_directedOn`, `coe_sSup_of_directedOn`: the supremum of a directed collection of submonoid is their union. * `sup_eq_range`, `mem_sup`: supremum of two submonoids `S`, `T` of a commutative monoid is the set of products; * `closure_singleton_eq`, `mem_closure_singleton`, `mem_closure_pair`: the multiplicative (resp., additive) closure of `{x}` consists of powers (resp., natural multiples) of `x`, and a similar result holds for the closure of `{x, y}`. ## Tags submonoid, submonoids -/ variable {M A B : Type*} section Assoc variable [Monoid M] [SetLike B M] [SubmonoidClass B M] {S : B} namespace SubmonoidClass @[to_additive (attr := norm_cast, simp)] theorem coe_list_prod (l : List S) : (l.prod : M) = (l.map (↑)).prod := map_list_prod (SubmonoidClass.subtype S : _ →* M) l #align submonoid_class.coe_list_prod SubmonoidClass.coe_list_prod #align add_submonoid_class.coe_list_sum AddSubmonoidClass.coe_list_sum @[to_additive (attr := norm_cast, simp)] theorem coe_multiset_prod {M} [CommMonoid M] [SetLike B M] [SubmonoidClass B M] (m : Multiset S) : (m.prod : M) = (m.map (↑)).prod := (SubmonoidClass.subtype S : _ →* M).map_multiset_prod m #align submonoid_class.coe_multiset_prod SubmonoidClass.coe_multiset_prod #align add_submonoid_class.coe_multiset_sum AddSubmonoidClass.coe_multiset_sum @[to_additive (attr := norm_cast)] -- Porting note (#10618): removed `simp`, `simp` can prove it theorem coe_finset_prod {ι M} [CommMonoid M] [SetLike B M] [SubmonoidClass B M] (f : ι → S) (s : Finset ι) : ↑(∏ i ∈ s, f i) = (∏ i ∈ s, f i : M) := map_prod (SubmonoidClass.subtype S) f s #align submonoid_class.coe_finset_prod SubmonoidClass.coe_finset_prod #align add_submonoid_class.coe_finset_sum AddSubmonoidClass.coe_finset_sum end SubmonoidClass open SubmonoidClass /-- Product of a list of elements in a submonoid is in the submonoid. -/ @[to_additive "Sum of a list of elements in an `AddSubmonoid` is in the `AddSubmonoid`."]
Mathlib/Algebra/Group/Submonoid/Membership.lean
73
76
theorem list_prod_mem {l : List M} (hl : ∀ x ∈ l, x ∈ S) : l.prod ∈ S := by
lift l to List S using hl rw [← coe_list_prod] exact l.prod.coe_prop
/- 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.LinearAlgebra.Dimension.DivisionRing import Mathlib.LinearAlgebra.Dimension.FreeAndStrongRankCondition /-! # The rank of a linear map ## Main Definition - `LinearMap.rank`: The rank of a linear map. -/ noncomputable section universe u v v' v'' variable {K : Type u} {V V₁ : Type v} {V' V'₁ : Type v'} {V'' : Type v''} open Cardinal Basis Submodule Function Set namespace LinearMap section Ring variable [Ring K] [AddCommGroup V] [Module K V] [AddCommGroup V₁] [Module K V₁] variable [AddCommGroup V'] [Module K V'] /-- `rank f` is the rank of a `LinearMap` `f`, defined as the dimension of `f.range`. -/ abbrev rank (f : V →ₗ[K] V') : Cardinal := Module.rank K (LinearMap.range f) #align linear_map.rank LinearMap.rank theorem rank_le_range (f : V →ₗ[K] V') : rank f ≤ Module.rank K V' := rank_submodule_le _ #align linear_map.rank_le_range LinearMap.rank_le_range theorem rank_le_domain (f : V →ₗ[K] V₁) : rank f ≤ Module.rank K V := rank_range_le _ #align linear_map.rank_le_domain LinearMap.rank_le_domain @[simp] theorem rank_zero [Nontrivial K] : rank (0 : V →ₗ[K] V') = 0 := by rw [rank, LinearMap.range_zero, rank_bot] #align linear_map.rank_zero LinearMap.rank_zero variable [AddCommGroup V''] [Module K V'']
Mathlib/LinearAlgebra/Dimension/LinearMap.lean
52
55
theorem rank_comp_le_left (g : V →ₗ[K] V') (f : V' →ₗ[K] V'') : rank (f.comp g) ≤ rank f := by
refine rank_le_of_submodule _ _ ?_ rw [LinearMap.range_comp] exact LinearMap.map_le_range
/- 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}
Mathlib/MeasureTheory/Measure/WithDensityVectorMeasure.lean
59
60
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
/- 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.CategoryTheory.Idempotents.Basic import Mathlib.CategoryTheory.Preadditive.AdditiveFunctor import Mathlib.CategoryTheory.Equivalence #align_import category_theory.idempotents.karoubi from "leanprover-community/mathlib"@"200eda15d8ff5669854ff6bcc10aaf37cb70498f" /-! # The Karoubi envelope of a category In this file, we define the Karoubi envelope `Karoubi C` of a category `C`. ## Main constructions and definitions - `Karoubi C` is the Karoubi envelope of a category `C`: it is an idempotent complete category. It is also preadditive when `C` is preadditive. - `toKaroubi C : C ⥤ Karoubi C` is a fully faithful functor, which is an equivalence (`toKaroubiIsEquivalence`) when `C` is idempotent complete. -/ noncomputable section open CategoryTheory.Category CategoryTheory.Preadditive CategoryTheory.Limits BigOperators namespace CategoryTheory variable (C : Type*) [Category C] namespace Idempotents -- porting note (#5171): removed @[nolint has_nonempty_instance] /-- In a preadditive category `C`, when an object `X` decomposes as `X ≅ P ⨿ Q`, one may consider `P` as a direct factor of `X` and up to unique isomorphism, it is determined by the obvious idempotent `X ⟶ P ⟶ X` which is the projection onto `P` with kernel `Q`. More generally, one may define a formal direct factor of an object `X : C` : it consists of an idempotent `p : X ⟶ X` which is thought as the "formal image" of `p`. The type `Karoubi C` shall be the type of the objects of the karoubi envelope of `C`. It makes sense for any category `C`. -/ structure Karoubi where /-- an object of the underlying category -/ X : C /-- an endomorphism of the object -/ p : X ⟶ X /-- the condition that the given endomorphism is an idempotent -/ idem : p ≫ p = p := by aesop_cat #align category_theory.idempotents.karoubi CategoryTheory.Idempotents.Karoubi namespace Karoubi variable {C} attribute [reassoc (attr := simp)] idem @[ext] theorem ext {P Q : Karoubi C} (h_X : P.X = Q.X) (h_p : P.p ≫ eqToHom h_X = eqToHom h_X ≫ Q.p) : P = Q := by cases P cases Q dsimp at h_X h_p subst h_X simpa only [mk.injEq, heq_eq_eq, true_and, eqToHom_refl, comp_id, id_comp] using h_p #align category_theory.idempotents.karoubi.ext CategoryTheory.Idempotents.Karoubi.ext /-- A morphism `P ⟶ Q` in the category `Karoubi C` is a morphism in the underlying category `C` which satisfies a relation, which in the preadditive case, expresses that it induces a map between the corresponding "formal direct factors" and that it vanishes on the complement formal direct factor. -/ @[ext] structure Hom (P Q : Karoubi C) where /-- a morphism between the underlying objects -/ f : P.X ⟶ Q.X /-- compatibility of the given morphism with the given idempotents -/ comm : f = P.p ≫ f ≫ Q.p := by aesop_cat #align category_theory.idempotents.karoubi.hom CategoryTheory.Idempotents.Karoubi.Hom instance [Preadditive C] (P Q : Karoubi C) : Inhabited (Hom P Q) := ⟨⟨0, by rw [zero_comp, comp_zero]⟩⟩ @[reassoc (attr := simp)] theorem p_comp {P Q : Karoubi C} (f : Hom P Q) : P.p ≫ f.f = f.f := by rw [f.comm, ← assoc, P.idem] #align category_theory.idempotents.karoubi.p_comp CategoryTheory.Idempotents.Karoubi.p_comp @[reassoc (attr := simp)]
Mathlib/CategoryTheory/Idempotents/Karoubi.lean
89
90
theorem comp_p {P Q : Karoubi C} (f : Hom P Q) : f.f ≫ Q.p = f.f := by
rw [f.comm, assoc, assoc, Q.idem]
/- 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.Analysis.Convex.Hull #align_import analysis.convex.join from "leanprover-community/mathlib"@"951bf1d9e98a2042979ced62c0620bcfb3587cf8" /-! # Convex join This file defines the convex join of two sets. The convex join of `s` and `t` is the union of the segments with one end in `s` and the other in `t`. This is notably a useful gadget to deal with convex hulls of finite sets. -/ open Set variable {ι : Sort*} {𝕜 E : Type*} section OrderedSemiring variable (𝕜) [OrderedSemiring 𝕜] [AddCommMonoid E] [Module 𝕜 E] {s t s₁ s₂ t₁ t₂ u : Set E} {x y : E} /-- The join of two sets is the union of the segments joining them. This can be interpreted as the topological join, but within the original space. -/ def convexJoin (s t : Set E) : Set E := ⋃ (x ∈ s) (y ∈ t), segment 𝕜 x y #align convex_join convexJoin variable {𝕜} theorem mem_convexJoin : x ∈ convexJoin 𝕜 s t ↔ ∃ a ∈ s, ∃ b ∈ t, x ∈ segment 𝕜 a b := by simp [convexJoin] #align mem_convex_join mem_convexJoin theorem convexJoin_comm (s t : Set E) : convexJoin 𝕜 s t = convexJoin 𝕜 t s := (iUnion₂_comm _).trans <| by simp_rw [convexJoin, segment_symm] #align convex_join_comm convexJoin_comm theorem convexJoin_mono (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) : convexJoin 𝕜 s₁ t₁ ⊆ convexJoin 𝕜 s₂ t₂ := biUnion_mono hs fun _ _ => biUnion_subset_biUnion_left ht #align convex_join_mono convexJoin_mono theorem convexJoin_mono_left (hs : s₁ ⊆ s₂) : convexJoin 𝕜 s₁ t ⊆ convexJoin 𝕜 s₂ t := convexJoin_mono hs Subset.rfl #align convex_join_mono_left convexJoin_mono_left theorem convexJoin_mono_right (ht : t₁ ⊆ t₂) : convexJoin 𝕜 s t₁ ⊆ convexJoin 𝕜 s t₂ := convexJoin_mono Subset.rfl ht #align convex_join_mono_right convexJoin_mono_right @[simp] theorem convexJoin_empty_left (t : Set E) : convexJoin 𝕜 ∅ t = ∅ := by simp [convexJoin] #align convex_join_empty_left convexJoin_empty_left @[simp] theorem convexJoin_empty_right (s : Set E) : convexJoin 𝕜 s ∅ = ∅ := by simp [convexJoin] #align convex_join_empty_right convexJoin_empty_right @[simp]
Mathlib/Analysis/Convex/Join.lean
65
66
theorem convexJoin_singleton_left (t : Set E) (x : E) : convexJoin 𝕜 {x} t = ⋃ y ∈ t, segment 𝕜 x y := by
simp [convexJoin]
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro -/ import Mathlib.Algebra.MvPolynomial.Degrees #align_import data.mv_polynomial.variables from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4" /-! # Variables of polynomials This file establishes many results about the variable sets of a multivariate polynomial. The *variable set* of a polynomial $P \in R[X]$ is a `Finset` containing each $x \in X$ that appears in a monomial in $P$. ## Main declarations * `MvPolynomial.vars p` : the finset of variables occurring in `p`. For example if `p = x⁴y+yz` then `vars p = {x, y, z}` ## Notation As in other polynomial files, we typically use the notation: + `σ τ : Type*` (indexing the variables) + `R : Type*` `[CommSemiring R]` (the coefficients) + `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set. This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s` + `r : R` + `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians + `p : MvPolynomial σ R` -/ noncomputable section open Set Function Finsupp AddMonoidAlgebra universe u v w variable {R : Type u} {S : Type v} namespace MvPolynomial variable {σ τ : Type*} {r : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ} section CommSemiring variable [CommSemiring R] {p q : MvPolynomial σ R} section Vars /-! ### `vars` -/ /-- `vars p` is the set of variables appearing in the polynomial `p` -/ def vars (p : MvPolynomial σ R) : Finset σ := letI := Classical.decEq σ p.degrees.toFinset #align mv_polynomial.vars MvPolynomial.vars theorem vars_def [DecidableEq σ] (p : MvPolynomial σ R) : p.vars = p.degrees.toFinset := by rw [vars] convert rfl #align mv_polynomial.vars_def MvPolynomial.vars_def @[simp]
Mathlib/Algebra/MvPolynomial/Variables.lean
77
78
theorem vars_0 : (0 : MvPolynomial σ R).vars = ∅ := by
classical rw [vars_def, degrees_zero, Multiset.toFinset_zero]
/- Copyright (c) 2022 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.LinearAlgebra.CliffordAlgebra.Contraction /-! # Results about inverses in Clifford algebras This contains some basic results about the inversion of vectors, related to the fact that $ι(m)^{-1} = \frac{ι(m)}{Q(m)}$. -/ variable {R M : Type*} variable [CommRing R] [AddCommGroup M] [Module R M] {Q : QuadraticForm R M} namespace CliffordAlgebra variable (Q) /-- If the quadratic form of a vector is invertible, then so is that vector. -/ def invertibleιOfInvertible (m : M) [Invertible (Q m)] : Invertible (ι Q m) where invOf := ι Q (⅟ (Q m) • m) invOf_mul_self := by rw [map_smul, smul_mul_assoc, ι_sq_scalar, Algebra.smul_def, ← map_mul, invOf_mul_self, map_one] mul_invOf_self := by rw [map_smul, mul_smul_comm, ι_sq_scalar, Algebra.smul_def, ← map_mul, invOf_mul_self, map_one] #align clifford_algebra.invertible_ι_of_invertible CliffordAlgebra.invertibleιOfInvertible /-- For a vector with invertible quadratic form, $v^{-1} = \frac{v}{Q(v)}$ -/ theorem invOf_ι (m : M) [Invertible (Q m)] [Invertible (ι Q m)] : ⅟ (ι Q m) = ι Q (⅟ (Q m) • m) := by letI := invertibleιOfInvertible Q m convert (rfl : ⅟ (ι Q m) = _) #align clifford_algebra.inv_of_ι CliffordAlgebra.invOf_ι
Mathlib/LinearAlgebra/CliffordAlgebra/Inversion.lean
37
40
theorem isUnit_ι_of_isUnit {m : M} (h : IsUnit (Q m)) : IsUnit (ι Q m) := by
cases h.nonempty_invertible letI := invertibleιOfInvertible Q m exact isUnit_of_invertible (ι Q m)
/- Copyright (c) 2021 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison -/ import Mathlib.Algebra.Homology.Single #align_import algebra.homology.augment from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a" /-! # Augmentation and truncation of `ℕ`-indexed (co)chain complexes. -/ noncomputable section open CategoryTheory Limits HomologicalComplex universe v u variable {V : Type u} [Category.{v} V] namespace ChainComplex /-- The truncation of an `ℕ`-indexed chain complex, deleting the object at `0` and shifting everything else down. -/ @[simps] def truncate [HasZeroMorphisms V] : ChainComplex V ℕ ⥤ ChainComplex V ℕ where obj C := { X := fun i => C.X (i + 1) d := fun i j => C.d (i + 1) (j + 1) shape := fun i j w => C.shape _ _ <| by simpa } map f := { f := fun i => f.f (i + 1) } #align chain_complex.truncate ChainComplex.truncate /-- There is a canonical chain map from the truncation of a chain map `C` to the "single object" chain complex consisting of the truncated object `C.X 0` in degree 0. The components of this chain map are `C.d 1 0` in degree 0, and zero otherwise. -/ def truncateTo [HasZeroObject V] [HasZeroMorphisms V] (C : ChainComplex V ℕ) : truncate.obj C ⟶ (single₀ V).obj (C.X 0) := (toSingle₀Equiv (truncate.obj C) (C.X 0)).symm ⟨C.d 1 0, by aesop⟩ #align chain_complex.truncate_to ChainComplex.truncateTo -- PROJECT when `V` is abelian (but not generally?) -- `[∀ n, Exact (C.d (n+2) (n+1)) (C.d (n+1) n)] [Epi (C.d 1 0)]` iff `QuasiIso (C.truncate_to)` variable [HasZeroMorphisms V] /-- We can "augment" a chain complex by inserting an arbitrary object in degree zero (shifting everything else up), along with a suitable differential. -/ def augment (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) : ChainComplex V ℕ where X | 0 => X | i + 1 => C.X i d | 1, 0 => f | i + 1, j + 1 => C.d i j | _, _ => 0 shape | 1, 0, h => absurd rfl h | i + 2, 0, _ => rfl | 0, _, _ => rfl | i + 1, j + 1, h => by simp only; exact C.shape i j (Nat.succ_ne_succ.1 h) d_comp_d' | _, _, 0, rfl, rfl => w | _, _, k + 1, rfl, rfl => C.d_comp_d _ _ _ #align chain_complex.augment ChainComplex.augment @[simp] theorem augment_X_zero (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) : (augment C f w).X 0 = X := rfl set_option linter.uppercaseLean3 false in #align chain_complex.augment_X_zero ChainComplex.augment_X_zero @[simp] theorem augment_X_succ (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) (i : ℕ) : (augment C f w).X (i + 1) = C.X i := rfl set_option linter.uppercaseLean3 false in #align chain_complex.augment_X_succ ChainComplex.augment_X_succ @[simp] theorem augment_d_one_zero (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) : (augment C f w).d 1 0 = f := rfl #align chain_complex.augment_d_one_zero ChainComplex.augment_d_one_zero @[simp] theorem augment_d_succ_succ (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) (i j : ℕ) : (augment C f w).d (i + 1) (j + 1) = C.d i j := by cases i <;> rfl #align chain_complex.augment_d_succ_succ ChainComplex.augment_d_succ_succ /-- Truncating an augmented chain complex is isomorphic (with components the identity) to the original complex. -/ def truncateAugment (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) : truncate.obj (augment C f w) ≅ C where hom := { f := fun i => 𝟙 _ } inv := { f := fun i => 𝟙 _ comm' := fun i j => by cases j <;> · dsimp simp } hom_inv_id := by ext (_ | i) <;> · dsimp simp inv_hom_id := by ext (_ | i) <;> · dsimp simp #align chain_complex.truncate_augment ChainComplex.truncateAugment @[simp] theorem truncateAugment_hom_f (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) (i : ℕ) : (truncateAugment C f w).hom.f i = 𝟙 (C.X i) := rfl #align chain_complex.truncate_augment_hom_f ChainComplex.truncateAugment_hom_f @[simp] theorem truncateAugment_inv_f (C : ChainComplex V ℕ) {X : V} (f : C.X 0 ⟶ X) (w : C.d 1 0 ≫ f = 0) (i : ℕ) : (truncateAugment C f w).inv.f i = 𝟙 ((truncate.obj (augment C f w)).X i) := rfl #align chain_complex.truncate_augment_inv_f ChainComplex.truncateAugment_inv_f @[simp]
Mathlib/Algebra/Homology/Augment.lean
132
134
theorem chainComplex_d_succ_succ_zero (C : ChainComplex V ℕ) (i : ℕ) : C.d (i + 2) 0 = 0 := by
rw [C.shape] exact i.succ_succ_ne_one.symm
/- Copyright (c) 2022 George Peter Banyard, Yaël Dillies, Kyle Miller. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: George Peter Banyard, Yaël Dillies, Kyle Miller -/ import Mathlib.Combinatorics.SimpleGraph.Connectivity #align_import combinatorics.simple_graph.prod from "leanprover-community/mathlib"@"2985fa3c31a27274aed06c433510bc14b73d6488" /-! # Graph products This file defines the box product of graphs and other product constructions. The box product of `G` and `H` is the graph on the product of the vertices such that `x` and `y` are related iff they agree on one component and the other one is related via either `G` or `H`. For example, the box product of two edges is a square. ## Main declarations * `SimpleGraph.boxProd`: The box product. ## Notation * `G □ H`: The box product of `G` and `H`. ## TODO Define all other graph products! -/ variable {α β γ : Type*} namespace SimpleGraph -- Porting note: pruned variables to keep things out of local contexts, which -- can impact how generalization works, or what aesop does. variable {G : SimpleGraph α} {H : SimpleGraph β} /-- Box product of simple graphs. It relates `(a₁, b)` and `(a₂, b)` if `G` relates `a₁` and `a₂`, and `(a, b₁)` and `(a, b₂)` if `H` relates `b₁` and `b₂`. -/ def boxProd (G : SimpleGraph α) (H : SimpleGraph β) : SimpleGraph (α × β) where Adj x y := G.Adj x.1 y.1 ∧ x.2 = y.2 ∨ H.Adj x.2 y.2 ∧ x.1 = y.1 symm x y := by simp [and_comm, or_comm, eq_comm, adj_comm] loopless x := by simp #align simple_graph.box_prod SimpleGraph.boxProd /-- Box product of simple graphs. It relates `(a₁, b)` and `(a₂, b)` if `G` relates `a₁` and `a₂`, and `(a, b₁)` and `(a, b₂)` if `H` relates `b₁` and `b₂`. -/ infixl:70 " □ " => boxProd set_option autoImplicit true in @[simp] theorem boxProd_adj : (G □ H).Adj x y ↔ G.Adj x.1 y.1 ∧ x.2 = y.2 ∨ H.Adj x.2 y.2 ∧ x.1 = y.1 := Iff.rfl #align simple_graph.box_prod_adj SimpleGraph.boxProd_adj set_option autoImplicit true in --@[simp] Porting note (#10618): `simp` can prove theorem boxProd_adj_left : (G □ H).Adj (a₁, b) (a₂, b) ↔ G.Adj a₁ a₂ := by simp only [boxProd_adj, and_true, SimpleGraph.irrefl, false_and, or_false] #align simple_graph.box_prod_adj_left SimpleGraph.boxProd_adj_left set_option autoImplicit true in --@[simp] Porting note (#10618): `simp` can prove theorem boxProd_adj_right : (G □ H).Adj (a, b₁) (a, b₂) ↔ H.Adj b₁ b₂ := by simp only [boxProd_adj, SimpleGraph.irrefl, false_and, and_true, false_or] #align simple_graph.box_prod_adj_right SimpleGraph.boxProd_adj_right
Mathlib/Combinatorics/SimpleGraph/Prod.lean
69
73
theorem boxProd_neighborSet (x : α × β) : (G □ H).neighborSet x = G.neighborSet x.1 ×ˢ {x.2} ∪ {x.1} ×ˢ H.neighborSet x.2 := by
ext ⟨a', b'⟩ simp only [mem_neighborSet, Set.mem_union, boxProd_adj, Set.mem_prod, Set.mem_singleton_iff] simp only [eq_comm, and_comm]
/- Copyright (c) 2024 Judith Ludwig, Christian Merten. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Judith Ludwig, Christian Merten -/ import Mathlib.RingTheory.AdicCompletion.Basic import Mathlib.Algebra.Module.Torsion /-! # Algebra instance on adic completion In this file we provide an algebra instance on the adic completion of a ring. Then the adic completion of any module is a module over the adic completion of the ring. ## Implementation details We do not make a separate adic completion type in algebra case, to not duplicate all module theoretic results on adic completions. This choice does cause some trouble though, since `I ^ n • ⊤` is not defeq to `I ^ n`. We try to work around most of the trouble by providing as much API as possible. -/ open Submodule variable {R : Type*} [CommRing R] (I : Ideal R) variable {M : Type*} [AddCommGroup M] [Module R M] namespace AdicCompletion attribute [-simp] smul_eq_mul Algebra.id.smul_eq_mul @[local simp] theorem transitionMap_ideal_mk {m n : ℕ} (hmn : m ≤ n) (x : R) : transitionMap I R hmn (Ideal.Quotient.mk (I ^ n • ⊤ : Ideal R) x) = Ideal.Quotient.mk (I ^ m • ⊤ : Ideal R) x := rfl @[local simp] theorem transitionMap_map_one {m n : ℕ} (hmn : m ≤ n) : transitionMap I R hmn 1 = 1 := rfl @[local simp] theorem transitionMap_map_mul {m n : ℕ} (hmn : m ≤ n) (x y : R ⧸ (I ^ n • ⊤ : Ideal R)) : transitionMap I R hmn (x * y) = transitionMap I R hmn x * transitionMap I R hmn y := Quotient.inductionOn₂' x y (fun _ _ ↦ rfl) /-- `AdicCompletion.transitionMap` as an algebra homomorphism. -/ def transitionMapₐ {m n : ℕ} (hmn : m ≤ n) : R ⧸ (I ^ n • ⊤ : Ideal R) →ₐ[R] R ⧸ (I ^ m • ⊤ : Ideal R) := AlgHom.ofLinearMap (transitionMap I R hmn) rfl (transitionMap_map_mul I hmn) /-- `AdicCompletion I R` is an `R`-subalgebra of `∀ n, R ⧸ (I ^ n • ⊤ : Ideal R)`. -/ def subalgebra : Subalgebra R (∀ n, R ⧸ (I ^ n • ⊤ : Ideal R)) := Submodule.toSubalgebra (submodule I R) (fun _ ↦ by simp) (fun x y hx hy m n hmn ↦ by simp [hx hmn, hy hmn]) /-- `AdicCompletion I R` is a subring of `∀ n, R ⧸ (I ^ n • ⊤ : Ideal R)`. -/ def subring : Subring (∀ n, R ⧸ (I ^ n • ⊤ : Ideal R)) := Subalgebra.toSubring (subalgebra I) instance : CommRing (AdicCompletion I R) := inferInstanceAs <| CommRing (subring I) instance : Algebra R (AdicCompletion I R) := inferInstanceAs <| Algebra R (subalgebra I) @[simp] theorem val_one (n : ℕ) : (1 : AdicCompletion I R).val n = 1 := rfl @[simp] theorem val_mul (n : ℕ) (x y : AdicCompletion I R) : (x * y).val n = x.val n * y.val n := rfl /-- The canonical algebra map from the adic completion to `R ⧸ I ^ n`. This is `AdicCompletion.eval` postcomposed with the algebra isomorphism `R ⧸ (I ^ n • ⊤) ≃ₐ[R] R ⧸ I ^ n`. -/ def evalₐ (n : ℕ) : AdicCompletion I R →ₐ[R] R ⧸ I ^ n := have h : (I ^ n • ⊤ : Ideal R) = I ^ n := by ext x; simp AlgHom.comp (Ideal.quotientEquivAlgOfEq R h) (AlgHom.ofLinearMap (eval I R n) rfl (fun _ _ ↦ rfl)) @[simp] theorem evalₐ_mk (n : ℕ) (x : AdicCauchySequence I R) : evalₐ I n (mk I R x) = Ideal.Quotient.mk (I ^ n) (x.val n) := by simp [evalₐ] /-- `AdicCauchySequence I R` is an `R`-subalgebra of `ℕ → R`. -/ def AdicCauchySequence.subalgebra : Subalgebra R (ℕ → R) := Submodule.toSubalgebra (AdicCauchySequence.submodule I R) (fun {m n} _ ↦ by simp; rfl) (fun x y hx hy {m n} hmn ↦ by simp only [Pi.mul_apply] exact SModEq.mul (hx hmn) (hy hmn)) /-- `AdicCauchySequence I R` is a subring of `ℕ → R`. -/ def AdicCauchySequence.subring : Subring (ℕ → R) := Subalgebra.toSubring (AdicCauchySequence.subalgebra I) instance : CommRing (AdicCauchySequence I R) := inferInstanceAs <| CommRing (AdicCauchySequence.subring I) instance : Algebra R (AdicCauchySequence I R) := inferInstanceAs <| Algebra R (AdicCauchySequence.subalgebra I) @[simp] theorem one_apply (n : ℕ) : (1 : AdicCauchySequence I R) n = 1 := rfl @[simp] theorem mul_apply (n : ℕ) (f g : AdicCauchySequence I R) : (f * g) n = f n * g n := rfl /-- The canonical algebra map from adic cauchy sequences to the adic completion. -/ @[simps!] def mkₐ : AdicCauchySequence I R →ₐ[R] AdicCompletion I R := AlgHom.ofLinearMap (mk I R) rfl (fun _ _ ↦ rfl) @[simp] theorem evalₐ_mkₐ (n : ℕ) (x : AdicCauchySequence I R) : evalₐ I n (mkₐ I x) = Ideal.Quotient.mk (I ^ n) (x.val n) := by simp [mkₐ]
Mathlib/RingTheory/AdicCompletion/Algebra.lean
127
131
theorem Ideal.mk_eq_mk {m n : ℕ} (hmn : m ≤ n) (r : AdicCauchySequence I R) : Ideal.Quotient.mk (I ^ m) (r.val n) = Ideal.Quotient.mk (I ^ m) (r.val m) := by
have h : I ^ m = I ^ m • ⊤ := by simp rw [h, ← Ideal.Quotient.mk_eq_mk, ← Ideal.Quotient.mk_eq_mk] exact (r.property hmn).symm
/- Copyright (c) 2022 Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Bhavik Mehta -/ import Mathlib.Algebra.IsPrimePow import Mathlib.Data.Nat.Factorization.Basic #align_import data.nat.factorization.prime_pow from "leanprover-community/mathlib"@"6ca1a09bc9aa75824bf97388c9e3b441fc4ccf3f" /-! # Prime powers and factorizations This file deals with factorizations of prime powers. -/ variable {R : Type*} [CommMonoidWithZero R] (n p : R) (k : ℕ) theorem IsPrimePow.minFac_pow_factorization_eq {n : ℕ} (hn : IsPrimePow n) : n.minFac ^ n.factorization n.minFac = n := by obtain ⟨p, k, hp, hk, rfl⟩ := hn rw [← Nat.prime_iff] at hp rw [hp.pow_minFac hk.ne', hp.factorization_pow, Finsupp.single_eq_same] #align is_prime_pow.min_fac_pow_factorization_eq IsPrimePow.minFac_pow_factorization_eq theorem isPrimePow_of_minFac_pow_factorization_eq {n : ℕ} (h : n.minFac ^ n.factorization n.minFac = n) (hn : n ≠ 1) : IsPrimePow n := by rcases eq_or_ne n 0 with (rfl | hn') · simp_all refine ⟨_, _, (Nat.minFac_prime hn).prime, ?_, h⟩ simp [pos_iff_ne_zero, ← Finsupp.mem_support_iff, Nat.support_factorization, hn', Nat.minFac_prime hn, Nat.minFac_dvd] #align is_prime_pow_of_min_fac_pow_factorization_eq isPrimePow_of_minFac_pow_factorization_eq theorem isPrimePow_iff_minFac_pow_factorization_eq {n : ℕ} (hn : n ≠ 1) : IsPrimePow n ↔ n.minFac ^ n.factorization n.minFac = n := ⟨fun h => h.minFac_pow_factorization_eq, fun h => isPrimePow_of_minFac_pow_factorization_eq h hn⟩ #align is_prime_pow_iff_min_fac_pow_factorization_eq isPrimePow_iff_minFac_pow_factorization_eq
Mathlib/Data/Nat/Factorization/PrimePow.lean
41
54
theorem isPrimePow_iff_factorization_eq_single {n : ℕ} : IsPrimePow n ↔ ∃ p k : ℕ, 0 < k ∧ n.factorization = Finsupp.single p k := by
rw [isPrimePow_nat_iff] refine exists₂_congr fun p k => ?_ constructor · rintro ⟨hp, hk, hn⟩ exact ⟨hk, by rw [← hn, Nat.Prime.factorization_pow hp]⟩ · rintro ⟨hk, hn⟩ have hn0 : n ≠ 0 := by rintro rfl simp_all only [Finsupp.single_eq_zero, eq_comm, Nat.factorization_zero, hk.ne'] rw [Nat.eq_pow_of_factorization_eq_single hn0 hn] exact ⟨Nat.prime_of_mem_primeFactors <| Finsupp.mem_support_iff.2 (by simp [hn, hk.ne'] : n.factorization p ≠ 0), hk, rfl⟩
/- Copyright (c) 2017 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison -/ import Mathlib.CategoryTheory.Functor.Hom import Mathlib.CategoryTheory.Products.Basic import Mathlib.Data.ULift #align_import category_theory.yoneda from "leanprover-community/mathlib"@"369525b73f229ccd76a6ec0e0e0bf2be57599768" /-! # The Yoneda embedding The Yoneda embedding as a functor `yoneda : C ⥤ (Cᵒᵖ ⥤ Type v₁)`, along with an instance that it is `FullyFaithful`. Also the Yoneda lemma, `yonedaLemma : (yoneda_pairing C) ≅ (yoneda_evaluation C)`. ## References * [Stacks: Opposite Categories and the Yoneda Lemma](https://stacks.math.columbia.edu/tag/001L) -/ namespace CategoryTheory open Opposite universe v₁ u₁ u₂ -- morphism levels before object levels. See note [CategoryTheory universes]. variable {C : Type u₁} [Category.{v₁} C] /-- The Yoneda embedding, as a functor from `C` into presheaves on `C`. See <https://stacks.math.columbia.edu/tag/001O>. -/ @[simps] def yoneda : C ⥤ Cᵒᵖ ⥤ Type v₁ where obj X := { obj := fun Y => unop Y ⟶ X map := fun f g => f.unop ≫ g } map f := { app := fun Y g => g ≫ f } #align category_theory.yoneda CategoryTheory.yoneda /-- The co-Yoneda embedding, as a functor from `Cᵒᵖ` into co-presheaves on `C`. -/ @[simps] def coyoneda : Cᵒᵖ ⥤ C ⥤ Type v₁ where obj X := { obj := fun Y => unop X ⟶ Y map := fun f g => g ≫ f } map f := { app := fun Y g => f.unop ≫ g } #align category_theory.coyoneda CategoryTheory.coyoneda namespace Yoneda
Mathlib/CategoryTheory/Yoneda.lean
59
62
theorem obj_map_id {X Y : C} (f : op X ⟶ op Y) : (yoneda.obj X).map f (𝟙 X) = (yoneda.map f.unop).app (op Y) (𝟙 Y) := by
dsimp simp
/- Copyright (c) 2022 Moritz Doll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Doll -/ import Mathlib.Analysis.LocallyConvex.Basic #align_import analysis.locally_convex.balanced_core_hull from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Balanced Core and Balanced Hull ## Main definitions * `balancedCore`: The largest balanced subset of a set `s`. * `balancedHull`: The smallest balanced superset of a set `s`. ## Main statements * `balancedCore_eq_iInter`: Characterization of the balanced core as an intersection over subsets. * `nhds_basis_closed_balanced`: The closed balanced sets form a basis of the neighborhood filter. ## Implementation details The balanced core and hull are implemented differently: for the core we take the obvious definition of the union over all balanced sets that are contained in `s`, whereas for the hull, we take the union over `r • s`, for `r` the scalars with `‖r‖ ≤ 1`. We show that `balancedHull` has the defining properties of a hull in `Balanced.balancedHull_subset_of_subset` and `subset_balancedHull`. For the core we need slightly stronger assumptions to obtain a characterization as an intersection, this is `balancedCore_eq_iInter`. ## References * [Bourbaki, *Topological Vector Spaces*][bourbaki1987] ## Tags balanced -/ open Set Pointwise Topology Filter variable {𝕜 E ι : Type*} section balancedHull section SeminormedRing variable [SeminormedRing 𝕜] section SMul variable (𝕜) [SMul 𝕜 E] {s t : Set E} {x : E} /-- The largest balanced subset of `s`. -/ def balancedCore (s : Set E) := ⋃₀ { t : Set E | Balanced 𝕜 t ∧ t ⊆ s } #align balanced_core balancedCore /-- Helper definition to prove `balanced_core_eq_iInter`-/ def balancedCoreAux (s : Set E) := ⋂ (r : 𝕜) (_ : 1 ≤ ‖r‖), r • s #align balanced_core_aux balancedCoreAux /-- The smallest balanced superset of `s`. -/ def balancedHull (s : Set E) := ⋃ (r : 𝕜) (_ : ‖r‖ ≤ 1), r • s #align balanced_hull balancedHull variable {𝕜} theorem balancedCore_subset (s : Set E) : balancedCore 𝕜 s ⊆ s := sUnion_subset fun _ ht => ht.2 #align balanced_core_subset balancedCore_subset theorem balancedCore_empty : balancedCore 𝕜 (∅ : Set E) = ∅ := eq_empty_of_subset_empty (balancedCore_subset _) #align balanced_core_empty balancedCore_empty theorem mem_balancedCore_iff : x ∈ balancedCore 𝕜 s ↔ ∃ t, Balanced 𝕜 t ∧ t ⊆ s ∧ x ∈ t := by simp_rw [balancedCore, mem_sUnion, mem_setOf_eq, and_assoc] #align mem_balanced_core_iff mem_balancedCore_iff theorem smul_balancedCore_subset (s : Set E) {a : 𝕜} (ha : ‖a‖ ≤ 1) : a • balancedCore 𝕜 s ⊆ balancedCore 𝕜 s := by rintro x ⟨y, hy, rfl⟩ rw [mem_balancedCore_iff] at hy rcases hy with ⟨t, ht1, ht2, hy⟩ exact ⟨t, ⟨ht1, ht2⟩, ht1 a ha (smul_mem_smul_set hy)⟩ #align smul_balanced_core_subset smul_balancedCore_subset theorem balancedCore_balanced (s : Set E) : Balanced 𝕜 (balancedCore 𝕜 s) := fun _ => smul_balancedCore_subset s #align balanced_core_balanced balancedCore_balanced /-- The balanced core of `t` is maximal in the sense that it contains any balanced subset `s` of `t`. -/ theorem Balanced.subset_balancedCore_of_subset (hs : Balanced 𝕜 s) (h : s ⊆ t) : s ⊆ balancedCore 𝕜 t := subset_sUnion_of_mem ⟨hs, h⟩ #align balanced.subset_core_of_subset Balanced.subset_balancedCore_of_subset theorem mem_balancedCoreAux_iff : x ∈ balancedCoreAux 𝕜 s ↔ ∀ r : 𝕜, 1 ≤ ‖r‖ → x ∈ r • s := mem_iInter₂ #align mem_balanced_core_aux_iff mem_balancedCoreAux_iff theorem mem_balancedHull_iff : x ∈ balancedHull 𝕜 s ↔ ∃ r : 𝕜, ‖r‖ ≤ 1 ∧ x ∈ r • s := by simp [balancedHull] #align mem_balanced_hull_iff mem_balancedHull_iff /-- The balanced hull of `s` is minimal in the sense that it is contained in any balanced superset `t` of `s`. -/
Mathlib/Analysis/LocallyConvex/BalancedCoreHull.lean
114
118
theorem Balanced.balancedHull_subset_of_subset (ht : Balanced 𝕜 t) (h : s ⊆ t) : balancedHull 𝕜 s ⊆ t := by
intros x hx obtain ⟨r, hr, y, hy, rfl⟩ := mem_balancedHull_iff.1 hx exact ht.smul_mem hr (h hy)
/- Copyright (c) 2019 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro -/ import Mathlib.Algebra.GroupWithZero.Units.Lemmas import Mathlib.Data.Rat.Cast.Defs #align_import data.rat.cast from "leanprover-community/mathlib"@"acebd8d49928f6ed8920e502a6c90674e75bd441" /-! # Casts of rational numbers into characteristic zero fields (or division rings). -/ variable {F ι α β : Type*} namespace Rat open Rat section WithDivRing variable [DivisionRing α] @[simp, norm_cast] theorem cast_inj [CharZero α] : ∀ {m n : ℚ}, (m : α) = n ↔ m = n | ⟨n₁, d₁, d₁0, c₁⟩, ⟨n₂, d₂, d₂0, c₂⟩ => by refine ⟨fun h => ?_, congr_arg _⟩ have d₁a : (d₁ : α) ≠ 0 := Nat.cast_ne_zero.2 d₁0 have d₂a : (d₂ : α) ≠ 0 := Nat.cast_ne_zero.2 d₂0 rw [mk'_eq_divInt, mk'_eq_divInt] at h ⊢ rw [cast_divInt_of_ne_zero, cast_divInt_of_ne_zero] at h <;> simp [d₁0, d₂0] at h ⊢ rwa [eq_div_iff_mul_eq d₂a, division_def, mul_assoc, (d₁.cast_commute (d₂ : α)).inv_left₀.eq, ← mul_assoc, ← division_def, eq_comm, eq_div_iff_mul_eq d₁a, eq_comm, ← Int.cast_natCast d₁, ← Int.cast_mul, ← Int.cast_natCast d₂, ← Int.cast_mul, Int.cast_inj, ← mkRat_eq_iff d₁0 d₂0] at h #align rat.cast_inj Rat.cast_inj theorem cast_injective [CharZero α] : Function.Injective ((↑) : ℚ → α) | _, _ => cast_inj.1 #align rat.cast_injective Rat.cast_injective @[simp] theorem cast_eq_zero [CharZero α] {n : ℚ} : (n : α) = 0 ↔ n = 0 := by rw [← cast_zero, cast_inj] #align rat.cast_eq_zero Rat.cast_eq_zero theorem cast_ne_zero [CharZero α] {n : ℚ} : (n : α) ≠ 0 ↔ n ≠ 0 := not_congr cast_eq_zero #align rat.cast_ne_zero Rat.cast_ne_zero @[simp, norm_cast] theorem cast_add [CharZero α] (m n) : ((m + n : ℚ) : α) = m + n := cast_add_of_ne_zero (Nat.cast_ne_zero.2 <| ne_of_gt m.pos) (Nat.cast_ne_zero.2 <| ne_of_gt n.pos) #align rat.cast_add Rat.cast_add @[simp, norm_cast] theorem cast_sub [CharZero α] (m n) : ((m - n : ℚ) : α) = m - n := cast_sub_of_ne_zero (Nat.cast_ne_zero.2 <| ne_of_gt m.pos) (Nat.cast_ne_zero.2 <| ne_of_gt n.pos) #align rat.cast_sub Rat.cast_sub @[simp, norm_cast] theorem cast_mul [CharZero α] (m n) : ((m * n : ℚ) : α) = m * n := cast_mul_of_ne_zero (Nat.cast_ne_zero.2 <| ne_of_gt m.pos) (Nat.cast_ne_zero.2 <| ne_of_gt n.pos) #align rat.cast_mul Rat.cast_mul section set_option linter.deprecated false @[simp, norm_cast] theorem cast_bit0 [CharZero α] (n : ℚ) : ((bit0 n : ℚ) : α) = (bit0 n : α) := cast_add _ _ #align rat.cast_bit0 Rat.cast_bit0 @[simp, norm_cast]
Mathlib/Data/Rat/Cast/CharZero.lean
78
79
theorem cast_bit1 [CharZero α] (n : ℚ) : ((bit1 n : ℚ) : α) = (bit1 n : α) := by
rw [bit1, cast_add, cast_one, cast_bit0]; rfl
/- Copyright (c) 2020 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Anne Baanen -/ import Mathlib.Algebra.Algebra.Equiv import Mathlib.LinearAlgebra.Span #align_import algebra.algebra.tower from "leanprover-community/mathlib"@"71150516f28d9826c7341f8815b31f7d8770c212" /-! # Towers of algebras In this file we prove basic facts about towers of algebra. An algebra tower A/S/R is expressed by having instances of `Algebra A S`, `Algebra R S`, `Algebra R A` and `IsScalarTower R S A`, the later asserting the compatibility condition `(r • s) • a = r • (s • a)`. An important definition is `toAlgHom R S A`, the canonical `R`-algebra homomorphism `S →ₐ[R] A`. -/ open Pointwise universe u v w u₁ v₁ variable (R : Type u) (S : Type v) (A : Type w) (B : Type u₁) (M : Type v₁) namespace Algebra variable [CommSemiring R] [Semiring A] [Semiring B] [Algebra R A] [Algebra R B] variable [AddCommMonoid M] [Module R M] [Module A M] [Module B M] variable [IsScalarTower R A M] [IsScalarTower R B M] [SMulCommClass A B M] variable {A} /-- The `R`-algebra morphism `A → End (M)` corresponding to the representation of the algebra `A` on the `B`-module `M`. This is a stronger version of `DistribMulAction.toLinearMap`, and could also have been called `Algebra.toModuleEnd`. The typeclasses correspond to the situation where the types act on each other as ``` R ----→ B | ⟍ | | ⟍ | ↓ ↘ ↓ A ----→ M ``` where the diagram commutes, the action by `R` commutes with everything, and the action by `A` and `B` on `M` commute. Typically this is most useful with `B = R` as `Algebra.lsmul R R A : A →ₐ[R] Module.End R M`. However this can be used to get the fact that left-multiplication by `A` is right `A`-linear, and vice versa, as ```lean example : A →ₐ[R] Module.End Aᵐᵒᵖ A := Algebra.lsmul R Aᵐᵒᵖ A example : Aᵐᵒᵖ →ₐ[R] Module.End A A := Algebra.lsmul R A A ``` respectively; though `LinearMap.mulLeft` and `LinearMap.mulRight` can also be used here. -/ def lsmul : A →ₐ[R] Module.End B M where toFun := DistribMulAction.toLinearMap B M map_one' := LinearMap.ext fun _ => one_smul A _ map_mul' a b := LinearMap.ext <| smul_assoc a b map_zero' := LinearMap.ext fun _ => zero_smul A _ map_add' _a _b := LinearMap.ext fun _ => add_smul _ _ _ commutes' r := LinearMap.ext <| algebraMap_smul A r #align algebra.lsmul Algebra.lsmulₓ @[simp] theorem lsmul_coe (a : A) : (lsmul R B M a : M → M) = (a • ·) := rfl #align algebra.lsmul_coe Algebra.lsmul_coe end Algebra namespace IsScalarTower section Module variable [CommSemiring R] [Semiring A] [Algebra R A] variable [MulAction A M] variable {R} {M}
Mathlib/Algebra/Algebra/Tower.lean
88
90
theorem algebraMap_smul [SMul R M] [IsScalarTower R A M] (r : R) (x : M) : algebraMap R A r • x = r • x := by
rw [Algebra.algebraMap_eq_smul_one, smul_assoc, one_smul]
/- 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.Data.Multiset.Basic #align_import data.multiset.range from "leanprover-community/mathlib"@"0a0ec35061ed9960bf0e7ffb0335f44447b58977" /-! # `Multiset.range n` gives `{0, 1, ..., n-1}` as a multiset. -/ open List Nat namespace Multiset -- range /-- `range n` is the multiset lifted from the list `range n`, that is, the set `{0, 1, ..., n-1}`. -/ def range (n : ℕ) : Multiset ℕ := List.range n #align multiset.range Multiset.range theorem coe_range (n : ℕ) : ↑(List.range n) = range n := rfl #align multiset.coe_range Multiset.coe_range @[simp] theorem range_zero : range 0 = 0 := rfl #align multiset.range_zero Multiset.range_zero @[simp] theorem range_succ (n : ℕ) : range (succ n) = n ::ₘ range n := by rw [range, List.range_succ, ← coe_add, add_comm]; rfl #align multiset.range_succ Multiset.range_succ @[simp] theorem card_range (n : ℕ) : card (range n) = n := length_range _ #align multiset.card_range Multiset.card_range theorem range_subset {m n : ℕ} : range m ⊆ range n ↔ m ≤ n := List.range_subset #align multiset.range_subset Multiset.range_subset @[simp] theorem mem_range {m n : ℕ} : m ∈ range n ↔ m < n := List.mem_range #align multiset.mem_range Multiset.mem_range -- Porting note (#10618): removing @[simp], `simp` can prove it theorem not_mem_range_self {n : ℕ} : n ∉ range n := List.not_mem_range_self #align multiset.not_mem_range_self Multiset.not_mem_range_self theorem self_mem_range_succ (n : ℕ) : n ∈ range (n + 1) := List.self_mem_range_succ n #align multiset.self_mem_range_succ Multiset.self_mem_range_succ theorem range_add (a b : ℕ) : range (a + b) = range a + (range b).map (a + ·) := congr_arg ((↑) : List ℕ → Multiset ℕ) (List.range_add _ _) #align multiset.range_add Multiset.range_add
Mathlib/Data/Multiset/Range.lean
65
70
theorem range_disjoint_map_add (a : ℕ) (m : Multiset ℕ) : (range a).Disjoint (m.map (a + ·)) := by
intro x hxa hxb rw [range, mem_coe, List.mem_range] at hxa obtain ⟨c, _, rfl⟩ := mem_map.1 hxb exact (Nat.le_add_right _ _).not_lt hxa
/- Copyright (c) 2020 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison -/ import Mathlib.RepresentationTheory.Action.Limits import Mathlib.RepresentationTheory.Action.Concrete import Mathlib.CategoryTheory.Monoidal.FunctorCategory import Mathlib.CategoryTheory.Monoidal.Transport import Mathlib.CategoryTheory.Monoidal.Rigid.OfEquivalence import Mathlib.CategoryTheory.Monoidal.Rigid.FunctorCategory import Mathlib.CategoryTheory.Monoidal.Linear import Mathlib.CategoryTheory.Monoidal.Braided.Basic import Mathlib.CategoryTheory.Monoidal.Types.Basic /-! # Induced monoidal structure on `Action V G` We show: * When `V` is monoidal, braided, or symmetric, so is `Action V G`. -/ universe u v open CategoryTheory Limits variable {V : Type (u + 1)} [LargeCategory V] {G : MonCat.{u}} namespace Action section Monoidal open MonoidalCategory variable [MonoidalCategory V] instance instMonoidalCategory : MonoidalCategory (Action V G) := Monoidal.transport (Action.functorCategoryEquivalence _ _).symm @[simp] theorem tensorUnit_v : (𝟙_ (Action V G)).V = 𝟙_ V := rfl set_option linter.uppercaseLean3 false in #align Action.tensor_unit_V Action.tensorUnit_v -- Porting note: removed @[simp] as the simpNF linter complains theorem tensorUnit_rho {g : G} : (𝟙_ (Action V G)).ρ g = 𝟙 (𝟙_ V) := rfl set_option linter.uppercaseLean3 false in #align Action.tensor_unit_rho Action.tensorUnit_rho @[simp] theorem tensor_v {X Y : Action V G} : (X ⊗ Y).V = X.V ⊗ Y.V := rfl set_option linter.uppercaseLean3 false in #align Action.tensor_V Action.tensor_v -- Porting note: removed @[simp] as the simpNF linter complains theorem tensor_rho {X Y : Action V G} {g : G} : (X ⊗ Y).ρ g = X.ρ g ⊗ Y.ρ g := rfl set_option linter.uppercaseLean3 false in #align Action.tensor_rho Action.tensor_rho @[simp] theorem tensor_hom {W X Y Z : Action V G} (f : W ⟶ X) (g : Y ⟶ Z) : (f ⊗ g).hom = f.hom ⊗ g.hom := rfl set_option linter.uppercaseLean3 false in #align Action.tensor_hom Action.tensor_hom @[simp] theorem whiskerLeft_hom (X : Action V G) {Y Z : Action V G} (f : Y ⟶ Z) : (X ◁ f).hom = X.V ◁ f.hom := rfl @[simp] theorem whiskerRight_hom {X Y : Action V G} (f : X ⟶ Y) (Z : Action V G) : (f ▷ Z).hom = f.hom ▷ Z.V := rfl -- Porting note: removed @[simp] as the simpNF linter complains theorem associator_hom_hom {X Y Z : Action V G} : Hom.hom (α_ X Y Z).hom = (α_ X.V Y.V Z.V).hom := by dsimp simp set_option linter.uppercaseLean3 false in #align Action.associator_hom_hom Action.associator_hom_hom -- Porting note: removed @[simp] as the simpNF linter complains theorem associator_inv_hom {X Y Z : Action V G} : Hom.hom (α_ X Y Z).inv = (α_ X.V Y.V Z.V).inv := by dsimp simp set_option linter.uppercaseLean3 false in #align Action.associator_inv_hom Action.associator_inv_hom -- Porting note: removed @[simp] as the simpNF linter complains theorem leftUnitor_hom_hom {X : Action V G} : Hom.hom (λ_ X).hom = (λ_ X.V).hom := by dsimp simp set_option linter.uppercaseLean3 false in #align Action.left_unitor_hom_hom Action.leftUnitor_hom_hom -- Porting note: removed @[simp] as the simpNF linter complains
Mathlib/RepresentationTheory/Action/Monoidal.lean
105
107
theorem leftUnitor_inv_hom {X : Action V G} : Hom.hom (λ_ X).inv = (λ_ X.V).inv := by
dsimp simp
/- Copyright (c) 2023 Alex Keizer. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Alex Keizer -/ import Mathlib.Data.Vector.Basic import Mathlib.Data.Vector.Snoc /-! This file establishes a set of normalization lemmas for `map`/`mapAccumr` operations on vectors -/ set_option autoImplicit true namespace Vector /-! ## Fold nested `mapAccumr`s into one -/ section Fold section Unary variable (xs : Vector α n) (f₁ : β → σ₁ → σ₁ × γ) (f₂ : α → σ₂ → σ₂ × β) @[simp]
Mathlib/Data/Vector/MapLemmas.lean
27
35
theorem mapAccumr_mapAccumr : mapAccumr f₁ (mapAccumr f₂ xs s₂).snd s₁ = let m := (mapAccumr (fun x s => let r₂ := f₂ x s.snd let r₁ := f₁ r₂.snd s.fst ((r₁.fst, r₂.fst), r₁.snd) ) xs (s₁, s₂)) (m.fst.fst, m.snd) := by
induction xs using Vector.revInductionOn generalizing s₁ s₂ <;> simp_all
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Floris van Doorn, Gabriel Ebner, Yury Kudryashov -/ import Mathlib.Order.ConditionallyCompleteLattice.Finset import Mathlib.Order.Interval.Finset.Nat #align_import data.nat.lattice from "leanprover-community/mathlib"@"52fa514ec337dd970d71d8de8d0fd68b455a1e54" /-! # Conditionally complete linear order structure on `ℕ` In this file we * define a `ConditionallyCompleteLinearOrderBot` structure on `ℕ`; * prove a few lemmas about `iSup`/`iInf`/`Set.iUnion`/`Set.iInter` and natural numbers. -/ assert_not_exists MonoidWithZero open Set namespace Nat open scoped Classical noncomputable instance : InfSet ℕ := ⟨fun s ↦ if h : ∃ n, n ∈ s then @Nat.find (fun n ↦ n ∈ s) _ h else 0⟩ noncomputable instance : SupSet ℕ := ⟨fun s ↦ if h : ∃ n, ∀ a ∈ s, a ≤ n then @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h else 0⟩ theorem sInf_def {s : Set ℕ} (h : s.Nonempty) : sInf s = @Nat.find (fun n ↦ n ∈ s) _ h := dif_pos _ #align nat.Inf_def Nat.sInf_def theorem sSup_def {s : Set ℕ} (h : ∃ n, ∀ a ∈ s, a ≤ n) : sSup s = @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h := dif_pos _ #align nat.Sup_def Nat.sSup_def theorem _root_.Set.Infinite.Nat.sSup_eq_zero {s : Set ℕ} (h : s.Infinite) : sSup s = 0 := dif_neg fun ⟨n, hn⟩ ↦ let ⟨k, hks, hk⟩ := h.exists_gt n (hn k hks).not_lt hk #align set.infinite.nat.Sup_eq_zero Set.Infinite.Nat.sSup_eq_zero @[simp] theorem sInf_eq_zero {s : Set ℕ} : sInf s = 0 ↔ 0 ∈ s ∨ s = ∅ := by cases eq_empty_or_nonempty s with | inl h => subst h simp only [or_true_iff, eq_self_iff_true, iff_true_iff, iInf, InfSet.sInf, mem_empty_iff_false, exists_false, dif_neg, not_false_iff] | inr h => simp only [h.ne_empty, or_false_iff, Nat.sInf_def, h, Nat.find_eq_zero] #align nat.Inf_eq_zero Nat.sInf_eq_zero @[simp] theorem sInf_empty : sInf ∅ = 0 := by rw [sInf_eq_zero] right rfl #align nat.Inf_empty Nat.sInf_empty @[simp]
Mathlib/Data/Nat/Lattice.lean
66
67
theorem iInf_of_empty {ι : Sort*} [IsEmpty ι] (f : ι → ℕ) : iInf f = 0 := by
rw [iInf_of_isEmpty, sInf_empty]
/- Copyright (c) 2021 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.FieldTheory.PrimitiveElement import Mathlib.LinearAlgebra.Determinant import Mathlib.LinearAlgebra.FiniteDimensional import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly import Mathlib.LinearAlgebra.Matrix.ToLinearEquiv import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure import Mathlib.FieldTheory.Galois #align_import ring_theory.norm from "leanprover-community/mathlib"@"fecd3520d2a236856f254f27714b80dcfe28ea57" /-! # Norm for (finite) ring extensions Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`, the determinant of the linear map given by multiplying by `s` gives information about the roots of the minimal polynomial of `s` over `R`. ## Implementation notes Typically, the norm is defined specifically for finite field extensions. The current definition is as general as possible and the assumption that we have fields or that the extension is finite is added to the lemmas as needed. We only define the norm for left multiplication (`Algebra.leftMulMatrix`, i.e. `LinearMap.mulLeft`). For now, the definitions assume `S` is commutative, so the choice doesn't matter anyway. See also `Algebra.trace`, which is defined similarly as the trace of `Algebra.leftMulMatrix`. ## References * https://en.wikipedia.org/wiki/Field_norm -/ universe u v w variable {R S T : Type*} [CommRing R] [Ring S] variable [Algebra R S] variable {K L F : Type*} [Field K] [Field L] [Field F] variable [Algebra K L] [Algebra K F] variable {ι : Type w} open FiniteDimensional open LinearMap open Matrix Polynomial open scoped Matrix namespace Algebra variable (R) /-- The norm of an element `s` of an `R`-algebra is the determinant of `(*) s`. -/ noncomputable def norm : S →* R := LinearMap.det.comp (lmul R S).toRingHom.toMonoidHom #align algebra.norm Algebra.norm theorem norm_apply (x : S) : norm R x = LinearMap.det (lmul R S x) := rfl #align algebra.norm_apply Algebra.norm_apply theorem norm_eq_one_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) (x : S) : norm R x = 1 := by rw [norm_apply, LinearMap.det]; split_ifs <;> trivial #align algebra.norm_eq_one_of_not_exists_basis Algebra.norm_eq_one_of_not_exists_basis variable {R} theorem norm_eq_one_of_not_module_finite (h : ¬Module.Finite R S) (x : S) : norm R x = 1 := by refine norm_eq_one_of_not_exists_basis _ (mt ?_ h) _ rintro ⟨s, ⟨b⟩⟩ exact Module.Finite.of_basis b #align algebra.norm_eq_one_of_not_module_finite Algebra.norm_eq_one_of_not_module_finite -- Can't be a `simp` lemma because it depends on a choice of basis theorem norm_eq_matrix_det [Fintype ι] [DecidableEq ι] (b : Basis ι R S) (s : S) : norm R s = Matrix.det (Algebra.leftMulMatrix b s) := by rw [norm_apply, ← LinearMap.det_toMatrix b, ← toMatrix_lmul_eq]; rfl #align algebra.norm_eq_matrix_det Algebra.norm_eq_matrix_det /-- If `x` is in the base ring `K`, then the norm is `x ^ [L : K]`. -/ theorem norm_algebraMap_of_basis [Fintype ι] (b : Basis ι R S) (x : R) : norm R (algebraMap R S x) = x ^ Fintype.card ι := by haveI := Classical.decEq ι rw [norm_apply, ← det_toMatrix b, lmul_algebraMap] convert @det_diagonal _ _ _ _ _ fun _ : ι => x · ext (i j); rw [toMatrix_lsmul] · rw [Finset.prod_const, Finset.card_univ] #align algebra.norm_algebra_map_of_basis Algebra.norm_algebraMap_of_basis /-- If `x` is in the base field `K`, then the norm is `x ^ [L : K]`. (If `L` is not finite-dimensional over `K`, then `norm = 1 = x ^ 0 = x ^ (finrank L K)`.) -/ @[simp] protected theorem norm_algebraMap {L : Type*} [Ring L] [Algebra K L] (x : K) : norm K (algebraMap K L x) = x ^ finrank K L := by by_cases H : ∃ s : Finset L, Nonempty (Basis s K L) · rw [norm_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some] · rw [norm_eq_one_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis, pow_zero] rintro ⟨s, ⟨b⟩⟩ exact H ⟨s, ⟨b⟩⟩ #align algebra.norm_algebra_map Algebra.norm_algebraMap section EqProdRoots /-- Given `pb : PowerBasis K S`, then the norm of `pb.gen` is `(-1) ^ pb.dim * coeff (minpoly K pb.gen) 0`. -/ theorem PowerBasis.norm_gen_eq_coeff_zero_minpoly (pb : PowerBasis R S) : norm R pb.gen = (-1) ^ pb.dim * coeff (minpoly R pb.gen) 0 := by rw [norm_eq_matrix_det pb.basis, det_eq_sign_charpoly_coeff, charpoly_leftMulMatrix, Fintype.card_fin] #align algebra.power_basis.norm_gen_eq_coeff_zero_minpoly Algebra.PowerBasis.norm_gen_eq_coeff_zero_minpoly /-- Given `pb : PowerBasis R S`, then the norm of `pb.gen` is `((minpoly R pb.gen).aroots F).prod`. -/
Mathlib/RingTheory/Norm.lean
126
135
theorem PowerBasis.norm_gen_eq_prod_roots [Algebra R F] (pb : PowerBasis R S) (hf : (minpoly R pb.gen).Splits (algebraMap R F)) : algebraMap R F (norm R pb.gen) = ((minpoly R pb.gen).aroots F).prod := by
haveI := Module.nontrivial R F have := minpoly.monic pb.isIntegral_gen rw [PowerBasis.norm_gen_eq_coeff_zero_minpoly, ← pb.natDegree_minpoly, RingHom.map_mul, ← coeff_map, prod_roots_eq_coeff_zero_of_monic_of_split (this.map _) ((splits_id_iff_splits _).2 hf), this.natDegree_map, map_pow, ← mul_assoc, ← mul_pow] simp only [map_neg, _root_.map_one, neg_mul, neg_neg, one_pow, one_mul]
/- Copyright (c) 2021 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.MeasureTheory.Measure.Typeclasses /-! # Restriction of a measure to a sub-σ-algebra ## Main definitions * `MeasureTheory.Measure.trim`: restriction of a measure to a sub-sigma algebra. -/ open scoped ENNReal namespace MeasureTheory variable {α : Type*} /-- Restriction of a measure to a sub-σ-algebra. It is common to see a measure `μ` on a measurable space structure `m0` as being also a measure on any `m ≤ m0`. Since measures in mathlib have to be trimmed to the measurable space, `μ` itself cannot be a measure on `m`, hence the definition of `μ.trim hm`. This notion is related to `OuterMeasure.trim`, see the lemma `toOuterMeasure_trim_eq_trim_toOuterMeasure`. -/ noncomputable def Measure.trim {m m0 : MeasurableSpace α} (μ : @Measure α m0) (hm : m ≤ m0) : @Measure α m := @OuterMeasure.toMeasure α m μ.toOuterMeasure (hm.trans (le_toOuterMeasure_caratheodory μ)) #align measure_theory.measure.trim MeasureTheory.Measure.trim @[simp] theorem trim_eq_self [MeasurableSpace α] {μ : Measure α} : μ.trim le_rfl = μ := by simp [Measure.trim] #align measure_theory.trim_eq_self MeasureTheory.trim_eq_self variable {m m0 : MeasurableSpace α} {μ : Measure α} {s : Set α} theorem toOuterMeasure_trim_eq_trim_toOuterMeasure (μ : Measure α) (hm : m ≤ m0) : @Measure.toOuterMeasure _ m (μ.trim hm) = @OuterMeasure.trim _ m μ.toOuterMeasure := by rw [Measure.trim, toMeasure_toOuterMeasure (ms := m)] #align measure_theory.to_outer_measure_trim_eq_trim_to_outer_measure MeasureTheory.toOuterMeasure_trim_eq_trim_toOuterMeasure @[simp] theorem zero_trim (hm : m ≤ m0) : (0 : Measure α).trim hm = (0 : @Measure α m) := by simp [Measure.trim, @OuterMeasure.toMeasure_zero _ m] #align measure_theory.zero_trim MeasureTheory.zero_trim theorem trim_measurableSet_eq (hm : m ≤ m0) (hs : @MeasurableSet α m s) : μ.trim hm s = μ s := by rw [Measure.trim, toMeasure_apply (ms := m) _ _ hs, Measure.coe_toOuterMeasure] #align measure_theory.trim_measurable_set_eq MeasureTheory.trim_measurableSet_eq
Mathlib/MeasureTheory/Measure/Trim.lean
57
59
theorem le_trim (hm : m ≤ m0) : μ s ≤ μ.trim hm s := by
simp_rw [Measure.trim] exact @le_toMeasure_apply _ m _ _ _
/- 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. -/
Mathlib/Analysis/InnerProductSpace/Orthogonal.lean
111
111
theorem orthogonal_disjoint : Disjoint K Kᗮ := by
simp [disjoint_iff, K.inf_orthogonal_eq_bot]
/- Copyright (c) 2022 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Data.Finset.Lattice #align_import combinatorics.set_family.compression.down from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853" /-! # Down-compressions This file defines down-compression. Down-compressing `𝒜 : Finset (Finset α)` along `a : α` means removing `a` from the elements of `𝒜`, when the resulting set is not already in `𝒜`. ## Main declarations * `Finset.nonMemberSubfamily`: `𝒜.nonMemberSubfamily a` is the subfamily of sets not containing `a`. * `Finset.memberSubfamily`: `𝒜.memberSubfamily a` is the image of the subfamily of sets containing `a` under removing `a`. * `Down.compression`: Down-compression. ## Notation `𝓓 a 𝒜` is notation for `Down.compress a 𝒜` in locale `SetFamily`. ## References * https://github.com/b-mehta/maths-notes/blob/master/iii/mich/combinatorics.pdf ## Tags compression, down-compression -/ variable {α : Type*} [DecidableEq α] {𝒜 ℬ : Finset (Finset α)} {s : Finset α} {a : α} namespace Finset /-- Elements of `𝒜` that do not contain `a`. -/ def nonMemberSubfamily (a : α) (𝒜 : Finset (Finset α)) : Finset (Finset α) := 𝒜.filter fun s => a ∉ s #align finset.non_member_subfamily Finset.nonMemberSubfamily /-- Image of the elements of `𝒜` which contain `a` under removing `a`. Finsets that do not contain `a` such that `insert a s ∈ 𝒜`. -/ def memberSubfamily (a : α) (𝒜 : Finset (Finset α)) : Finset (Finset α) := (𝒜.filter fun s => a ∈ s).image fun s => erase s a #align finset.member_subfamily Finset.memberSubfamily @[simp] theorem mem_nonMemberSubfamily : s ∈ 𝒜.nonMemberSubfamily a ↔ s ∈ 𝒜 ∧ a ∉ s := by simp [nonMemberSubfamily] #align finset.mem_non_member_subfamily Finset.mem_nonMemberSubfamily @[simp] theorem mem_memberSubfamily : s ∈ 𝒜.memberSubfamily a ↔ insert a s ∈ 𝒜 ∧ a ∉ s := by simp_rw [memberSubfamily, mem_image, mem_filter] refine ⟨?_, fun h => ⟨insert a s, ⟨h.1, by simp⟩, erase_insert h.2⟩⟩ rintro ⟨s, ⟨hs1, hs2⟩, rfl⟩ rw [insert_erase hs2] exact ⟨hs1, not_mem_erase _ _⟩ #align finset.mem_member_subfamily Finset.mem_memberSubfamily theorem nonMemberSubfamily_inter (a : α) (𝒜 ℬ : Finset (Finset α)) : (𝒜 ∩ ℬ).nonMemberSubfamily a = 𝒜.nonMemberSubfamily a ∩ ℬ.nonMemberSubfamily a := filter_inter_distrib _ _ _ #align finset.non_member_subfamily_inter Finset.nonMemberSubfamily_inter theorem memberSubfamily_inter (a : α) (𝒜 ℬ : Finset (Finset α)) : (𝒜 ∩ ℬ).memberSubfamily a = 𝒜.memberSubfamily a ∩ ℬ.memberSubfamily a := by unfold memberSubfamily rw [filter_inter_distrib, image_inter_of_injOn _ _ ((erase_injOn' _).mono _)] simp #align finset.member_subfamily_inter Finset.memberSubfamily_inter theorem nonMemberSubfamily_union (a : α) (𝒜 ℬ : Finset (Finset α)) : (𝒜 ∪ ℬ).nonMemberSubfamily a = 𝒜.nonMemberSubfamily a ∪ ℬ.nonMemberSubfamily a := filter_union _ _ _ #align finset.non_member_subfamily_union Finset.nonMemberSubfamily_union theorem memberSubfamily_union (a : α) (𝒜 ℬ : Finset (Finset α)) : (𝒜 ∪ ℬ).memberSubfamily a = 𝒜.memberSubfamily a ∪ ℬ.memberSubfamily a := by simp_rw [memberSubfamily, filter_union, image_union] #align finset.member_subfamily_union Finset.memberSubfamily_union theorem card_memberSubfamily_add_card_nonMemberSubfamily (a : α) (𝒜 : Finset (Finset α)) : (𝒜.memberSubfamily a).card + (𝒜.nonMemberSubfamily a).card = 𝒜.card := by rw [memberSubfamily, nonMemberSubfamily, card_image_of_injOn] · conv_rhs => rw [← filter_card_add_filter_neg_card_eq_card (fun s => (a ∈ s))] · apply (erase_injOn' _).mono simp #align finset.card_member_subfamily_add_card_non_member_subfamily Finset.card_memberSubfamily_add_card_nonMemberSubfamily theorem memberSubfamily_union_nonMemberSubfamily (a : α) (𝒜 : Finset (Finset α)) : 𝒜.memberSubfamily a ∪ 𝒜.nonMemberSubfamily a = 𝒜.image fun s => s.erase a := by ext s simp only [mem_union, mem_memberSubfamily, mem_nonMemberSubfamily, mem_image, exists_prop] constructor · rintro (h | h) · exact ⟨_, h.1, erase_insert h.2⟩ · exact ⟨_, h.1, erase_eq_of_not_mem h.2⟩ · rintro ⟨s, hs, rfl⟩ by_cases ha : a ∈ s · exact Or.inl ⟨by rwa [insert_erase ha], not_mem_erase _ _⟩ · exact Or.inr ⟨by rwa [erase_eq_of_not_mem ha], not_mem_erase _ _⟩ #align finset.member_subfamily_union_non_member_subfamily Finset.memberSubfamily_union_nonMemberSubfamily @[simp] theorem memberSubfamily_memberSubfamily : (𝒜.memberSubfamily a).memberSubfamily a = ∅ := by ext simp #align finset.member_subfamily_member_subfamily Finset.memberSubfamily_memberSubfamily @[simp]
Mathlib/Combinatorics/SetFamily/Compression/Down.lean
120
122
theorem memberSubfamily_nonMemberSubfamily : (𝒜.nonMemberSubfamily a).memberSubfamily a = ∅ := by
ext simp
/- Copyright (c) 2023 Jireh Loreaux. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jireh Loreaux -/ import Mathlib.Algebra.Star.Basic import Mathlib.Algebra.Star.Pointwise import Mathlib.Algebra.Group.Centralizer /-! # `Set.center`, `Set.centralizer` and the `star` operation -/ variable {R : Type*} [Mul R] [StarMul R] {a : R} {s : Set R}
Mathlib/Algebra/Star/Center.lean
14
34
theorem Set.star_mem_center (ha : a ∈ Set.center R) : star a ∈ Set.center R where comm := by
simpa only [star_mul, star_star] using fun g => congr_arg star (((Set.mem_center_iff R).mp ha).comm <| star g).symm left_assoc b c := calc star a * (b * c) = star a * (star (star b) * star (star c)) := by rw [star_star, star_star] _ = star a * star (star c * star b) := by rw [star_mul] _ = star ((star c * star b) * a) := by rw [← star_mul] _ = star (star c * (star b * a)) := by rw [ha.right_assoc] _ = star (star b * a) * c := by rw [star_mul, star_star] _ = (star a * b) * c := by rw [star_mul, star_star] mid_assoc b c := calc b * star a * c = star (star c * star (b * star a)) := by rw [← star_mul, star_star] _ = star (star c * (a * star b)) := by rw [star_mul b, star_star] _ = star ((star c * a) * star b) := by rw [ha.mid_assoc] _ = b * (star a * c) := by rw [star_mul, star_star, star_mul (star c), star_star] right_assoc b c := calc b * c * star a = star (a * star (b * c)) := by rw [star_mul, star_star] _ = star (a * (star c * star b)) := by rw [star_mul b] _ = star ((a * star c) * star b) := by rw [ha.left_assoc] _ = b * star (a * star c) := by rw [star_mul, star_star] _ = b * (c * star a) := by rw [star_mul, star_star]
/- Copyright (c) 2023 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Order.Filter.Bases import Mathlib.Order.Filter.Ultrafilter /-! # Subsingleton filters We say that a filter `l` is a *subsingleton* if there exists a subsingleton set `s ∈ l`. Equivalently, `l` is either `⊥` or `pure a` for some `a`. -/ open Set variable {α β : Type*} {l : Filter α} namespace Filter /-- We say that a filter is a *subsingleton* if there exists a subsingleton set that belongs to the filter. -/ protected def Subsingleton (l : Filter α) : Prop := ∃ s ∈ l, Set.Subsingleton s theorem HasBasis.subsingleton_iff {ι : Sort*} {p : ι → Prop} {s : ι → Set α} (h : l.HasBasis p s) : l.Subsingleton ↔ ∃ i, p i ∧ (s i).Subsingleton := h.exists_iff fun _ _ hsub h ↦ h.anti hsub theorem Subsingleton.anti {l'} (hl : l.Subsingleton) (hl' : l' ≤ l) : l'.Subsingleton := let ⟨s, hsl, hs⟩ := hl; ⟨s, hl' hsl, hs⟩ @[nontriviality] theorem Subsingleton.of_subsingleton [Subsingleton α] : l.Subsingleton := ⟨univ, univ_mem, subsingleton_univ⟩ theorem Subsingleton.map (hl : l.Subsingleton) (f : α → β) : (map f l).Subsingleton := let ⟨s, hsl, hs⟩ := hl; ⟨f '' s, image_mem_map hsl, hs.image f⟩ theorem Subsingleton.prod (hl : l.Subsingleton) {l' : Filter β} (hl' : l'.Subsingleton) : (l ×ˢ l').Subsingleton := let ⟨s, hsl, hs⟩ := hl; let ⟨t, htl', ht⟩ := hl'; ⟨s ×ˢ t, prod_mem_prod hsl htl', hs.prod ht⟩ @[simp] theorem subsingleton_pure {a : α} : Filter.Subsingleton (pure a) := ⟨{a}, rfl, subsingleton_singleton⟩ @[simp] theorem subsingleton_bot : Filter.Subsingleton (⊥ : Filter α) := ⟨∅, trivial, subsingleton_empty⟩ /-- A nontrivial subsingleton filter is equal to `pure a` for some `a`. -/
Mathlib/Order/Filter/Subsingleton.lean
51
55
theorem Subsingleton.exists_eq_pure [l.NeBot] (hl : l.Subsingleton) : ∃ a, l = pure a := by
rcases hl with ⟨s, hsl, hs⟩ rcases exists_eq_singleton_iff_nonempty_subsingleton.2 ⟨nonempty_of_mem hsl, hs⟩ with ⟨a, rfl⟩ refine ⟨a, (NeBot.le_pure_iff ‹_›).1 ?_⟩ rwa [le_pure_iff]
/- Copyright (c) 2020 Yakov Pechersky. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yakov Pechersky -/ import Mathlib.Data.List.Basic /-! # Properties of `List.reduceOption` In this file we prove basic lemmas about `List.reduceOption`. -/ namespace List variable {α β : Type*} @[simp] theorem reduceOption_cons_of_some (x : α) (l : List (Option α)) : reduceOption (some x :: l) = x :: l.reduceOption := by simp only [reduceOption, filterMap, id, eq_self_iff_true, and_self_iff] #align list.reduce_option_cons_of_some List.reduceOption_cons_of_some @[simp] theorem reduceOption_cons_of_none (l : List (Option α)) : reduceOption (none :: l) = l.reduceOption := by simp only [reduceOption, filterMap, id] #align list.reduce_option_cons_of_none List.reduceOption_cons_of_none @[simp] theorem reduceOption_nil : @reduceOption α [] = [] := rfl #align list.reduce_option_nil List.reduceOption_nil @[simp] theorem reduceOption_map {l : List (Option α)} {f : α → β} : reduceOption (map (Option.map f) l) = map f (reduceOption l) := by induction' l with hd tl hl · simp only [reduceOption_nil, map_nil] · cases hd <;> simpa [true_and_iff, Option.map_some', map, eq_self_iff_true, reduceOption_cons_of_some] using hl #align list.reduce_option_map List.reduceOption_map theorem reduceOption_append (l l' : List (Option α)) : (l ++ l').reduceOption = l.reduceOption ++ l'.reduceOption := filterMap_append l l' id #align list.reduce_option_append List.reduceOption_append theorem reduceOption_length_eq {l : List (Option α)} : l.reduceOption.length = (l.filter Option.isSome).length := by induction' l with hd tl hl · simp_rw [reduceOption_nil, filter_nil, length] · cases hd <;> simp [hl] theorem length_eq_reduceOption_length_add_filter_none {l : List (Option α)} : l.length = l.reduceOption.length + (l.filter Option.isNone).length := by simp_rw [reduceOption_length_eq, l.length_eq_length_filter_add Option.isSome, Option.bnot_isSome] theorem reduceOption_length_le (l : List (Option α)) : l.reduceOption.length ≤ l.length := by rw [length_eq_reduceOption_length_add_filter_none] apply Nat.le_add_right #align list.reduce_option_length_le List.reduceOption_length_le theorem reduceOption_length_eq_iff {l : List (Option α)} : l.reduceOption.length = l.length ↔ ∀ x ∈ l, Option.isSome x := by rw [reduceOption_length_eq, List.filter_length_eq_length] #align list.reduce_option_length_eq_iff List.reduceOption_length_eq_iff theorem reduceOption_length_lt_iff {l : List (Option α)} : l.reduceOption.length < l.length ↔ none ∈ l := by rw [Nat.lt_iff_le_and_ne, and_iff_right (reduceOption_length_le l), Ne, reduceOption_length_eq_iff] induction l <;> simp [*] rw [@eq_comm _ none, ← Option.not_isSome_iff_eq_none, Decidable.imp_iff_not_or] #align list.reduce_option_length_lt_iff List.reduceOption_length_lt_iff
Mathlib/Data/List/ReduceOption.lean
77
77
theorem reduceOption_singleton (x : Option α) : [x].reduceOption = x.toList := by
cases x <;> rfl
/- Copyright (c) 2020 Alexander Bentkamp. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Alexander Bentkamp -/ import Mathlib.LinearAlgebra.Eigenspace.Basic import Mathlib.FieldTheory.Minpoly.Field #align_import linear_algebra.eigenspace.minpoly from "leanprover-community/mathlib"@"c3216069e5f9369e6be586ccbfcde2592b3cec92" /-! # Eigenvalues are the roots of the minimal polynomial. ## Tags eigenvalue, minimal polynomial -/ universe u v w namespace Module namespace End open Polynomial FiniteDimensional open scoped Polynomial variable {K : Type v} {V : Type w} [Field K] [AddCommGroup V] [Module K V] theorem eigenspace_aeval_polynomial_degree_1 (f : End K V) (q : K[X]) (hq : degree q = 1) : eigenspace f (-q.coeff 0 / q.leadingCoeff) = LinearMap.ker (aeval f q) := calc eigenspace f (-q.coeff 0 / q.leadingCoeff) _ = LinearMap.ker (q.leadingCoeff • f - algebraMap K (End K V) (-q.coeff 0)) := by rw [eigenspace_div] intro h rw [leadingCoeff_eq_zero_iff_deg_eq_bot.1 h] at hq cases hq _ = LinearMap.ker (aeval f (C q.leadingCoeff * X + C (q.coeff 0))) := by rw [C_mul', aeval_def]; simp [algebraMap, Algebra.toRingHom] _ = LinearMap.ker (aeval f q) := by rwa [← eq_X_add_C_of_degree_eq_one] #align module.End.eigenspace_aeval_polynomial_degree_1 Module.End.eigenspace_aeval_polynomial_degree_1 theorem ker_aeval_ring_hom'_unit_polynomial (f : End K V) (c : K[X]ˣ) : LinearMap.ker (aeval f (c : K[X])) = ⊥ := by rw [Polynomial.eq_C_of_degree_eq_zero (degree_coe_units c)] simp only [aeval_def, eval₂_C] apply ker_algebraMap_end apply coeff_coe_units_zero_ne_zero c #align module.End.ker_aeval_ring_hom'_unit_polynomial Module.End.ker_aeval_ring_hom'_unit_polynomial theorem aeval_apply_of_hasEigenvector {f : End K V} {p : K[X]} {μ : K} {x : V} (h : f.HasEigenvector μ x) : aeval f p x = p.eval μ • x := by refine p.induction_on ?_ ?_ ?_ · intro a; simp [Module.algebraMap_end_apply] · intro p q hp hq; simp [hp, hq, add_smul] · intro n a hna rw [mul_comm, pow_succ', mul_assoc, AlgHom.map_mul, LinearMap.mul_apply, mul_comm, hna] simp only [mem_eigenspace_iff.1 h.1, smul_smul, aeval_X, eval_mul, eval_C, eval_pow, eval_X, LinearMap.map_smulₛₗ, RingHom.id_apply, mul_comm] #align module.End.aeval_apply_of_has_eigenvector Module.End.aeval_apply_of_hasEigenvector theorem isRoot_of_hasEigenvalue {f : End K V} {μ : K} (h : f.HasEigenvalue μ) : (minpoly K f).IsRoot μ := by rcases (Submodule.ne_bot_iff _).1 h with ⟨w, ⟨H, ne0⟩⟩ refine Or.resolve_right (smul_eq_zero.1 ?_) ne0 simp [← aeval_apply_of_hasEigenvector ⟨H, ne0⟩, minpoly.aeval K f] #align module.End.is_root_of_has_eigenvalue Module.End.isRoot_of_hasEigenvalue variable [FiniteDimensional K V] (f : End K V) variable {f} {μ : K}
Mathlib/LinearAlgebra/Eigenspace/Minpoly.lean
75
91
theorem hasEigenvalue_of_isRoot (h : (minpoly K f).IsRoot μ) : f.HasEigenvalue μ := by
cases' dvd_iff_isRoot.2 h with p hp rw [HasEigenvalue, eigenspace] intro con cases' (LinearMap.isUnit_iff_ker_eq_bot _).2 con with u hu have p_ne_0 : p ≠ 0 := by intro con apply minpoly.ne_zero (Algebra.IsIntegral.isIntegral (R := K) f) rw [hp, con, mul_zero] have : (aeval f) p = 0 := by have h_aeval := minpoly.aeval K f revert h_aeval simp [hp, ← hu] have h_deg := minpoly.degree_le_of_ne_zero K f p_ne_0 this rw [hp, degree_mul, degree_X_sub_C, Polynomial.degree_eq_natDegree p_ne_0] at h_deg norm_cast at h_deg omega
/- Copyright (c) 2021 Stuart Presnell. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Stuart Presnell -/ import Mathlib.Data.Finsupp.Multiset import Mathlib.Data.Nat.GCD.BigOperators import Mathlib.Data.Nat.PrimeFin import Mathlib.NumberTheory.Padics.PadicVal import Mathlib.Order.Interval.Finset.Nat #align_import data.nat.factorization.basic from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e" /-! # Prime factorizations `n.factorization` is the finitely supported function `ℕ →₀ ℕ` mapping each prime factor of `n` to its multiplicity in `n`. For example, since 2000 = 2^4 * 5^3, * `factorization 2000 2` is 4 * `factorization 2000 5` is 3 * `factorization 2000 k` is 0 for all other `k : ℕ`. ## TODO * As discussed in this Zulip thread: https://leanprover.zulipchat.com/#narrow/stream/217875/topic/Multiplicity.20in.20the.20naturals We have lots of disparate ways of talking about the multiplicity of a prime in a natural number, including `factors.count`, `padicValNat`, `multiplicity`, and the material in `Data/PNat/Factors`. Move some of this material to this file, prove results about the relationships between these definitions, and (where appropriate) choose a uniform canonical way of expressing these ideas. * Moreover, the results here should be generalised to an arbitrary unique factorization monoid with a normalization function, and then deduplicated. The basics of this have been started in `RingTheory/UniqueFactorizationDomain`. * Extend the inductions to any `NormalizationMonoid` with unique factorization. -/ -- Workaround for lean4#2038 attribute [-instance] instBEqNat open Nat Finset List Finsupp namespace Nat variable {a b m n p : ℕ} /-- `n.factorization` is the finitely supported function `ℕ →₀ ℕ` mapping each prime factor of `n` to its multiplicity in `n`. -/ def factorization (n : ℕ) : ℕ →₀ ℕ where support := n.primeFactors toFun p := if p.Prime then padicValNat p n else 0 mem_support_toFun := by simp [not_or]; aesop #align nat.factorization Nat.factorization /-- The support of `n.factorization` is exactly `n.primeFactors`. -/ @[simp] lemma support_factorization (n : ℕ) : (factorization n).support = n.primeFactors := rfl theorem factorization_def (n : ℕ) {p : ℕ} (pp : p.Prime) : n.factorization p = padicValNat p n := by simpa [factorization] using absurd pp #align nat.factorization_def Nat.factorization_def /-- We can write both `n.factorization p` and `n.factors.count p` to represent the power of `p` in the factorization of `n`: we declare the former to be the simp-normal form. -/ @[simp]
Mathlib/Data/Nat/Factorization/Basic.lean
67
81
theorem factors_count_eq {n p : ℕ} : n.factors.count p = n.factorization p := by
rcases n.eq_zero_or_pos with (rfl | hn0) · simp [factorization, count] if pp : p.Prime then ?_ else rw [count_eq_zero_of_not_mem (mt prime_of_mem_factors pp)] simp [factorization, pp] simp only [factorization_def _ pp] apply _root_.le_antisymm · rw [le_padicValNat_iff_replicate_subperm_factors pp hn0.ne'] exact List.le_count_iff_replicate_sublist.mp le_rfl |>.subperm · rw [← lt_add_one_iff, lt_iff_not_ge, ge_iff_le, le_padicValNat_iff_replicate_subperm_factors pp hn0.ne'] intro h have := h.count_le p simp at this
/- Copyright (c) 2021 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Order.Interval.Finset.Fin #align_import data.fintype.fin from "leanprover-community/mathlib"@"759575657f189ccb424b990164c8b1fa9f55cdfe" /-! # The structure of `Fintype (Fin n)` This file contains some basic results about the `Fintype` instance for `Fin`, especially properties of `Finset.univ : Finset (Fin n)`. -/ open Finset open Fintype namespace Fin variable {α β : Type*} {n : ℕ}
Mathlib/Data/Fintype/Fin.lean
25
27
theorem map_valEmbedding_univ : (Finset.univ : Finset (Fin n)).map Fin.valEmbedding = Iio n := by
ext simp [orderIsoSubtype.symm.surjective.exists, OrderIso.symm]
/- 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, Yury Kudryashov -/ import Mathlib.Dynamics.Ergodic.MeasurePreserving import Mathlib.LinearAlgebra.Determinant import Mathlib.LinearAlgebra.Matrix.Diagonal import Mathlib.LinearAlgebra.Matrix.Transvection import Mathlib.MeasureTheory.Group.LIntegral import Mathlib.MeasureTheory.Integral.Marginal import Mathlib.MeasureTheory.Measure.Stieltjes import Mathlib.MeasureTheory.Measure.Haar.OfBasis #align_import measure_theory.measure.lebesgue.basic from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844" /-! # Lebesgue measure on the real line and on `ℝⁿ` We show that the Lebesgue measure on the real line (constructed as a particular case of additive Haar measure on inner product spaces) coincides with the Stieltjes measure associated to the function `x ↦ x`. We deduce properties of this measure on `ℝ`, and then of the product Lebesgue measure on `ℝⁿ`. In particular, we prove that they are translation invariant. We show that, on `ℝⁿ`, a linear map acts on Lebesgue measure by rescaling it through the absolute value of its determinant, in `Real.map_linearMap_volume_pi_eq_smul_volume_pi`. More properties of the Lebesgue measure are deduced from this in `Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean`, where they are proved more generally for any additive Haar measure on a finite-dimensional real vector space. -/ assert_not_exists MeasureTheory.integral noncomputable section open scoped Classical open Set Filter MeasureTheory MeasureTheory.Measure TopologicalSpace open ENNReal (ofReal) open scoped ENNReal NNReal Topology /-! ### Definition of the Lebesgue measure and lengths of intervals -/ namespace Real variable {ι : Type*} [Fintype ι] /-- The volume on the real line (as a particular case of the volume on a finite-dimensional inner product space) coincides with the Stieltjes measure coming from the identity function. -/ theorem volume_eq_stieltjes_id : (volume : Measure ℝ) = StieltjesFunction.id.measure := by haveI : IsAddLeftInvariant StieltjesFunction.id.measure := ⟨fun a => Eq.symm <| Real.measure_ext_Ioo_rat fun p q => by simp only [Measure.map_apply (measurable_const_add a) measurableSet_Ioo, sub_sub_sub_cancel_right, StieltjesFunction.measure_Ioo, StieltjesFunction.id_leftLim, StieltjesFunction.id_apply, id, preimage_const_add_Ioo]⟩ have A : StieltjesFunction.id.measure (stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped = 1 := by change StieltjesFunction.id.measure (parallelepiped (stdOrthonormalBasis ℝ ℝ)) = 1 rcases parallelepiped_orthonormalBasis_one_dim (stdOrthonormalBasis ℝ ℝ) with (H | H) <;> simp only [H, StieltjesFunction.measure_Icc, StieltjesFunction.id_apply, id, tsub_zero, StieltjesFunction.id_leftLim, sub_neg_eq_add, zero_add, ENNReal.ofReal_one] conv_rhs => rw [addHaarMeasure_unique StieltjesFunction.id.measure (stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped, A] simp only [volume, Basis.addHaar, one_smul] #align real.volume_eq_stieltjes_id Real.volume_eq_stieltjes_id theorem volume_val (s) : volume s = StieltjesFunction.id.measure s := by simp [volume_eq_stieltjes_id] #align real.volume_val Real.volume_val @[simp] theorem volume_Ico {a b : ℝ} : volume (Ico a b) = ofReal (b - a) := by simp [volume_val] #align real.volume_Ico Real.volume_Ico @[simp] theorem volume_Icc {a b : ℝ} : volume (Icc a b) = ofReal (b - a) := by simp [volume_val] #align real.volume_Icc Real.volume_Icc @[simp]
Mathlib/MeasureTheory/Measure/Lebesgue/Basic.lean
88
88
theorem volume_Ioo {a b : ℝ} : volume (Ioo a b) = ofReal (b - a) := by
simp [volume_val]
/- Copyright (c) 2019 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Yakov Pechersky -/ import Mathlib.Data.List.Nodup import Mathlib.Data.List.Zip import Mathlib.Data.Nat.Defs import Mathlib.Data.List.Infix #align_import data.list.rotate from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e" /-! # List rotation This file proves basic results about `List.rotate`, the list rotation. ## Main declarations * `List.IsRotated l₁ l₂`: States that `l₁` is a rotated version of `l₂`. * `List.cyclicPermutations l`: The list of all cyclic permutants of `l`, up to the length of `l`. ## Tags rotated, rotation, permutation, cycle -/ universe u variable {α : Type u} open Nat Function namespace List theorem rotate_mod (l : List α) (n : ℕ) : l.rotate (n % l.length) = l.rotate n := by simp [rotate] #align list.rotate_mod List.rotate_mod @[simp] theorem rotate_nil (n : ℕ) : ([] : List α).rotate n = [] := by simp [rotate] #align list.rotate_nil List.rotate_nil @[simp] theorem rotate_zero (l : List α) : l.rotate 0 = l := by simp [rotate] #align list.rotate_zero List.rotate_zero -- Porting note: removing simp, simp can prove it theorem rotate'_nil (n : ℕ) : ([] : List α).rotate' n = [] := by cases n <;> rfl #align list.rotate'_nil List.rotate'_nil @[simp] theorem rotate'_zero (l : List α) : l.rotate' 0 = l := by cases l <;> rfl #align list.rotate'_zero List.rotate'_zero
Mathlib/Data/List/Rotate.lean
56
57
theorem rotate'_cons_succ (l : List α) (a : α) (n : ℕ) : (a :: l : List α).rotate' n.succ = (l ++ [a]).rotate' n := by
simp [rotate']
/- Copyright (c) 2014 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Leonardo de Moura -/ import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Algebra.Order.Ring.Nat import Mathlib.Tactic.NthRewrite #align_import data.nat.gcd.basic from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3" /-! # Definitions and properties of `Nat.gcd`, `Nat.lcm`, and `Nat.coprime` Generalizations of these are provided in a later file as `GCDMonoid.gcd` and `GCDMonoid.lcm`. Note that the global `IsCoprime` is not a straightforward generalization of `Nat.coprime`, see `Nat.isCoprime_iff_coprime` for the connection between the two. -/ namespace Nat /-! ### `gcd` -/ theorem gcd_greatest {a b d : ℕ} (hda : d ∣ a) (hdb : d ∣ b) (hd : ∀ e : ℕ, e ∣ a → e ∣ b → e ∣ d) : d = a.gcd b := (dvd_antisymm (hd _ (gcd_dvd_left a b) (gcd_dvd_right a b)) (dvd_gcd hda hdb)).symm #align nat.gcd_greatest Nat.gcd_greatest /-! Lemmas where one argument consists of addition of a multiple of the other -/ @[simp] theorem gcd_add_mul_right_right (m n k : ℕ) : gcd m (n + k * m) = gcd m n := by simp [gcd_rec m (n + k * m), gcd_rec m n] #align nat.gcd_add_mul_right_right Nat.gcd_add_mul_right_right @[simp] theorem gcd_add_mul_left_right (m n k : ℕ) : gcd m (n + m * k) = gcd m n := by simp [gcd_rec m (n + m * k), gcd_rec m n] #align nat.gcd_add_mul_left_right Nat.gcd_add_mul_left_right @[simp] theorem gcd_mul_right_add_right (m n k : ℕ) : gcd m (k * m + n) = gcd m n := by simp [add_comm _ n] #align nat.gcd_mul_right_add_right Nat.gcd_mul_right_add_right @[simp] theorem gcd_mul_left_add_right (m n k : ℕ) : gcd m (m * k + n) = gcd m n := by simp [add_comm _ n] #align nat.gcd_mul_left_add_right Nat.gcd_mul_left_add_right @[simp] theorem gcd_add_mul_right_left (m n k : ℕ) : gcd (m + k * n) n = gcd m n := by rw [gcd_comm, gcd_add_mul_right_right, gcd_comm] #align nat.gcd_add_mul_right_left Nat.gcd_add_mul_right_left @[simp]
Mathlib/Data/Nat/GCD/Basic.lean
58
59
theorem gcd_add_mul_left_left (m n k : ℕ) : gcd (m + n * k) n = gcd m n := by
rw [gcd_comm, gcd_add_mul_left_right, gcd_comm]
/- Copyright (c) 2022 Jujian Zhang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jujian Zhang -/ import Mathlib.Algebra.Category.GroupCat.EquivalenceGroupAddGroup import Mathlib.GroupTheory.QuotientGroup #align_import algebra.category.Group.epi_mono from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a" /-! # Monomorphisms and epimorphisms in `Group` In this file, we prove monomorphisms in the category of groups are injective homomorphisms and epimorphisms are surjective homomorphisms. -/ noncomputable section open scoped Pointwise universe u v namespace MonoidHom open QuotientGroup variable {A : Type u} {B : Type v} section variable [Group A] [Group B] @[to_additive] theorem ker_eq_bot_of_cancel {f : A →* B} (h : ∀ u v : f.ker →* A, f.comp u = f.comp v → u = v) : f.ker = ⊥ := by simpa using _root_.congr_arg range (h f.ker.subtype 1 (by aesop_cat)) #align monoid_hom.ker_eq_bot_of_cancel MonoidHom.ker_eq_bot_of_cancel #align add_monoid_hom.ker_eq_bot_of_cancel AddMonoidHom.ker_eq_bot_of_cancel end section variable [CommGroup A] [CommGroup B] @[to_additive]
Mathlib/Algebra/Category/GroupCat/EpiMono.lean
47
56
theorem range_eq_top_of_cancel {f : A →* B} (h : ∀ u v : B →* B ⧸ f.range, u.comp f = v.comp f → u = v) : f.range = ⊤ := by
specialize h 1 (QuotientGroup.mk' _) _ · ext1 x simp only [one_apply, coe_comp, coe_mk', Function.comp_apply] rw [show (1 : B ⧸ f.range) = (1 : B) from QuotientGroup.mk_one _, QuotientGroup.eq, inv_one, one_mul] exact ⟨x, rfl⟩ replace h : (QuotientGroup.mk' f.range).ker = (1 : B →* B ⧸ f.range).ker := by rw [h] rwa [ker_one, QuotientGroup.ker_mk'] at h
/- Copyright (c) 2021 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson -/ import Mathlib.Algebra.Group.ConjFinite import Mathlib.GroupTheory.Perm.Fin import Mathlib.GroupTheory.Subgroup.Simple import Mathlib.Tactic.IntervalCases #align_import group_theory.specific_groups.alternating from "leanprover-community/mathlib"@"0f6670b8af2dff699de1c0b4b49039b31bc13c46" /-! # Alternating Groups The alternating group on a finite type `α` is the subgroup of the permutation group `Perm α` consisting of the even permutations. ## Main definitions * `alternatingGroup α` is the alternating group on `α`, defined as a `Subgroup (Perm α)`. ## Main results * `two_mul_card_alternatingGroup` shows that the alternating group is half as large as the permutation group it is a subgroup of. * `closure_three_cycles_eq_alternating` shows that the alternating group is generated by 3-cycles. * `alternatingGroup.isSimpleGroup_five` shows that the alternating group on `Fin 5` is simple. The proof shows that the normal closure of any non-identity element of this group contains a 3-cycle. ## Tags alternating group permutation ## TODO * Show that `alternatingGroup α` is simple if and only if `Fintype.card α ≠ 4`. -/ -- An example on how to determine the order of an element of a finite group. example : orderOf (-1 : ℤˣ) = 2 := orderOf_eq_prime (Int.units_sq _) (by decide) open Equiv Equiv.Perm Subgroup Fintype variable (α : Type*) [Fintype α] [DecidableEq α] /-- The alternating group on a finite type, realized as a subgroup of `Equiv.Perm`. For $A_n$, use `alternatingGroup (Fin n)`. -/ def alternatingGroup : Subgroup (Perm α) := sign.ker #align alternating_group alternatingGroup -- Porting note (#10754): manually added instance instance fta : Fintype (alternatingGroup α) := @Subtype.fintype _ _ sign.decidableMemKer _ instance [Subsingleton α] : Unique (alternatingGroup α) := ⟨⟨1⟩, fun ⟨p, _⟩ => Subtype.eq (Subsingleton.elim p _)⟩ variable {α} theorem alternatingGroup_eq_sign_ker : alternatingGroup α = sign.ker := rfl #align alternating_group_eq_sign_ker alternatingGroup_eq_sign_ker namespace Equiv.Perm @[simp] theorem mem_alternatingGroup {f : Perm α} : f ∈ alternatingGroup α ↔ sign f = 1 := sign.mem_ker #align equiv.perm.mem_alternating_group Equiv.Perm.mem_alternatingGroup
Mathlib/GroupTheory/SpecificGroups/Alternating.lean
77
80
theorem prod_list_swap_mem_alternatingGroup_iff_even_length {l : List (Perm α)} (hl : ∀ g ∈ l, IsSwap g) : l.prod ∈ alternatingGroup α ↔ Even l.length := by
rw [mem_alternatingGroup, sign_prod_list_swap hl, neg_one_pow_eq_one_iff_even] decide
/- 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.Fin.Basic namespace Fin attribute [norm_cast] val_last protected theorem le_antisymm_iff {x y : Fin n} : x = y ↔ x ≤ y ∧ y ≤ x := Fin.ext_iff.trans Nat.le_antisymm_iff protected theorem le_antisymm {x y : Fin n} (h1 : x ≤ y) (h2 : y ≤ x) : x = y := Fin.le_antisymm_iff.2 ⟨h1, h2⟩ /-! ### clamp -/ @[simp] theorem coe_clamp (n m : Nat) : (clamp n m : Nat) = min n m := rfl /-! ### enum/list -/ @[simp] theorem size_enum (n) : (enum n).size = n := Array.size_ofFn .. @[simp] theorem enum_zero : (enum 0) = #[] := by simp [enum, Array.ofFn, Array.ofFn.go] @[simp] theorem getElem_enum (i) (h : i < (enum n).size) : (enum n)[i] = ⟨i, size_enum n ▸ h⟩ := Array.getElem_ofFn .. @[simp] theorem length_list (n) : (list n).length = n := by simp [list] @[simp] theorem get_list (i : Fin (list n).length) : (list n).get i = i.cast (length_list n) := by cases i; simp only [list]; rw [← Array.getElem_eq_data_get, getElem_enum, cast_mk] @[simp] theorem list_zero : list 0 = [] := by simp [list] theorem list_succ (n) : list (n+1) = 0 :: (list n).map Fin.succ := by apply List.ext_get; simp; intro i; cases i <;> simp
.lake/packages/batteries/Batteries/Data/Fin/Lemmas.lean
41
47
theorem list_succ_last (n) : list (n+1) = (list n).map castSucc ++ [last n] := by
rw [list_succ] induction n with | zero => rfl | succ n ih => rw [list_succ, List.map_cons castSucc, ih] simp [Function.comp_def, succ_castSucc]
/- Copyright (c) 2023 Antoine Chambert-Loir and María Inés de Frutos-Fernández. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Chambert-Loir, María Inés de Frutos-Fernández, Bhavik Mehta, Eric Wieser -/ import Mathlib.Algebra.Order.Sub.Defs import Mathlib.Data.Finset.Basic import Mathlib.Order.Interval.Finset.Defs /-! # Antidiagonal with values in general types We define a type class `Finset.HasAntidiagonal A` which contains a function `antidiagonal : A → Finset (A × A)` such that `antidiagonal n` is the finset of all pairs adding to `n`, as witnessed by `mem_antidiagonal`. When `A` is a canonically ordered add monoid with locally finite order this typeclass can be instantiated with `Finset.antidiagonalOfLocallyFinite`. This applies in particular when `A` is `ℕ`, more generally or `σ →₀ ℕ`, or even `ι →₀ A` under the additional assumption `OrderedSub A` that make it a canonically ordered add monoid. (In fact, we would just need an `AddMonoid` with a compatible order, finite `Iic`, such that if `a + b = n`, then `a, b ≤ n`, and any finiteness condition would be OK.) For computational reasons it is better to manually provide instances for `ℕ` and `σ →₀ ℕ`, to avoid quadratic runtime performance. These instances are provided as `Finset.Nat.instHasAntidiagonal` and `Finsupp.instHasAntidiagonal`. This is why `Finset.antidiagonalOfLocallyFinite` is an `abbrev` and not an `instance`. This definition does not exactly match with that of `Multiset.antidiagonal` defined in `Mathlib.Data.Multiset.Antidiagonal`, because of the multiplicities. Indeed, by counting multiplicities, `Multiset α` is equivalent to `α →₀ ℕ`, but `Finset.antidiagonal` and `Multiset.antidiagonal` will return different objects. For example, for `s : Multiset ℕ := {0,0,0}`, `Multiset.antidiagonal s` has 8 elements but `Finset.antidiagonal s` has only 4. ```lean def s : Multiset ℕ := {0, 0, 0} #eval (Finset.antidiagonal s).card -- 4 #eval Multiset.card (Multiset.antidiagonal s) -- 8 ``` ## TODO * Define `HasMulAntidiagonal` (for monoids). For `PNat`, we will recover the set of divisors of a strictly positive integer. -/ open Function namespace Finset /-- The class of additive monoids with an antidiagonal -/ class HasAntidiagonal (A : Type*) [AddMonoid A] where /-- The antidiagonal of an element `n` is the finset of pairs `(i, j)` such that `i + j = n`. -/ antidiagonal : A → Finset (A × A) /-- A pair belongs to `antidiagonal n` iff the sum of its components is equal to `n`. -/ mem_antidiagonal {n} {a} : a ∈ antidiagonal n ↔ a.fst + a.snd = n export HasAntidiagonal (antidiagonal mem_antidiagonal) attribute [simp] mem_antidiagonal variable {A : Type*} /-- All `HasAntidiagonal` instances are equal -/ instance [AddMonoid A] : Subsingleton (HasAntidiagonal A) := ⟨by rintro ⟨a, ha⟩ ⟨b, hb⟩ congr with n xy rw [ha, hb]⟩ -- The goal of this lemma is to allow to rewrite antidiagonal -- when the decidability instances obsucate Lean lemma hasAntidiagonal_congr (A : Type*) [AddMonoid A] [H1 : HasAntidiagonal A] [H2 : HasAntidiagonal A] : H1.antidiagonal = H2.antidiagonal := by congr!; apply Subsingleton.elim theorem swap_mem_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} {xy : A × A}: xy.swap ∈ antidiagonal n ↔ xy ∈ antidiagonal n := by simp [add_comm] @[simp] theorem map_prodComm_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} : (antidiagonal n).map (Equiv.prodComm A A) = antidiagonal n := Finset.ext fun ⟨a, b⟩ => by simp [add_comm] /-- See also `Finset.map_prodComm_antidiagonal`. -/ @[simp] theorem map_swap_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} : (antidiagonal n).map ⟨Prod.swap, Prod.swap_injective⟩ = antidiagonal n := map_prodComm_antidiagonal #align finset.nat.map_swap_antidiagonal Finset.map_swap_antidiagonal section AddCancelMonoid variable [AddCancelMonoid A] [HasAntidiagonal A] {p q : A × A} {n : A} /-- A point in the antidiagonal is determined by its first coordinate. See also `Finset.antidiagonal_congr'`. -/
Mathlib/Data/Finset/Antidiagonal.lean
100
104
theorem antidiagonal_congr (hp : p ∈ antidiagonal n) (hq : q ∈ antidiagonal n) : p = q ↔ p.1 = q.1 := by
refine ⟨congr_arg Prod.fst, fun h ↦ Prod.ext h ((add_right_inj q.fst).mp ?_)⟩ rw [mem_antidiagonal] at hp hq rw [hq, ← h, hp]
/- Copyright (c) 2022 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.Analysis.NormedSpace.Exponential import Mathlib.Analysis.Matrix import Mathlib.LinearAlgebra.Matrix.ZPow import Mathlib.LinearAlgebra.Matrix.Hermitian import Mathlib.LinearAlgebra.Matrix.Symmetric import Mathlib.Topology.UniformSpace.Matrix #align_import analysis.normed_space.matrix_exponential from "leanprover-community/mathlib"@"1e3201306d4d9eb1fd54c60d7c4510ad5126f6f9" /-! # Lemmas about the matrix exponential In this file, we provide results about `exp` on `Matrix`s over a topological or normed algebra. Note that generic results over all topological spaces such as `NormedSpace.exp_zero` can be used on matrices without issue, so are not repeated here. The topological results specific to matrices are: * `Matrix.exp_transpose` * `Matrix.exp_conjTranspose` * `Matrix.exp_diagonal` * `Matrix.exp_blockDiagonal` * `Matrix.exp_blockDiagonal'` Lemmas like `NormedSpace.exp_add_of_commute` require a canonical norm on the type; while there are multiple sensible choices for the norm of a `Matrix` (`Matrix.normedAddCommGroup`, `Matrix.frobeniusNormedAddCommGroup`, `Matrix.linftyOpNormedAddCommGroup`), none of them are canonical. In an application where a particular norm is chosen using `attribute [local instance]`, then the usual lemmas about `NormedSpace.exp` are fine. When choosing a norm is undesirable, the results in this file can be used. In this file, we copy across the lemmas about `NormedSpace.exp`, but hide the requirement for a norm inside the proof. * `Matrix.exp_add_of_commute` * `Matrix.exp_sum_of_commute` * `Matrix.exp_nsmul` * `Matrix.isUnit_exp` * `Matrix.exp_units_conj` * `Matrix.exp_units_conj'` Additionally, we prove some results about `matrix.has_inv` and `matrix.div_inv_monoid`, as the results for general rings are instead stated about `Ring.inverse`: * `Matrix.exp_neg` * `Matrix.exp_zsmul` * `Matrix.exp_conj` * `Matrix.exp_conj'` ## TODO * Show that `Matrix.det (exp 𝕂 A) = exp 𝕂 (Matrix.trace A)` ## References * https://en.wikipedia.org/wiki/Matrix_exponential -/ open scoped Matrix open NormedSpace -- For `exp`. variable (𝕂 : Type*) {m n p : Type*} {n' : m → Type*} {𝔸 : Type*} namespace Matrix section Topological section Ring variable [Fintype m] [DecidableEq m] [Fintype n] [DecidableEq n] [∀ i, Fintype (n' i)] [∀ i, DecidableEq (n' i)] [Field 𝕂] [Ring 𝔸] [TopologicalSpace 𝔸] [TopologicalRing 𝔸] [Algebra 𝕂 𝔸] [T2Space 𝔸] theorem exp_diagonal (v : m → 𝔸) : exp 𝕂 (diagonal v) = diagonal (exp 𝕂 v) := by simp_rw [exp_eq_tsum, diagonal_pow, ← diagonal_smul, ← diagonal_tsum] #align matrix.exp_diagonal Matrix.exp_diagonal
Mathlib/Analysis/NormedSpace/MatrixExponential.lean
84
86
theorem exp_blockDiagonal (v : m → Matrix n n 𝔸) : exp 𝕂 (blockDiagonal v) = blockDiagonal (exp 𝕂 v) := by
simp_rw [exp_eq_tsum, ← blockDiagonal_pow, ← blockDiagonal_smul, ← blockDiagonal_tsum]
/- Copyright (c) 2022 Felix Weilacher. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Felix Weilacher -/ import Mathlib.Topology.Separation /-! # Perfect Sets In this file we define perfect subsets of a topological space, and prove some basic properties, including a version of the Cantor-Bendixson Theorem. ## Main Definitions * `Perfect C`: A set `C` is perfect, meaning it is closed and every point of it is an accumulation point of itself. * `PerfectSpace X`: A topological space `X` is perfect if its universe is a perfect set. ## Main Statements * `Perfect.splitting`: A perfect nonempty set contains two disjoint perfect nonempty subsets. The main inductive step in the construction of an embedding from the Cantor space to a perfect nonempty complete metric space. * `exists_countable_union_perfect_of_isClosed`: One version of the **Cantor-Bendixson Theorem**: A closed set in a second countable space can be written as the union of a countable set and a perfect set. ## Implementation Notes We do not require perfect sets to be nonempty. We define a nonstandard predicate, `Preperfect`, which drops the closed-ness requirement from the definition of perfect. In T1 spaces, this is equivalent to having a perfect closure, see `preperfect_iff_perfect_closure`. ## See also `Mathlib.Topology.MetricSpace.Perfect`, for properties of perfect sets in metric spaces, namely Polish spaces. ## References * [kechris1995] (Chapters 6-7) ## Tags accumulation point, perfect set, cantor-bendixson. -/ open Topology Filter Set TopologicalSpace section Basic variable {α : Type*} [TopologicalSpace α] {C : Set α} /-- If `x` is an accumulation point of a set `C` and `U` is a neighborhood of `x`, then `x` is an accumulation point of `U ∩ C`. -/ theorem AccPt.nhds_inter {x : α} {U : Set α} (h_acc : AccPt x (𝓟 C)) (hU : U ∈ 𝓝 x) : AccPt x (𝓟 (U ∩ C)) := by have : 𝓝[≠] x ≤ 𝓟 U := by rw [le_principal_iff] exact mem_nhdsWithin_of_mem_nhds hU rw [AccPt, ← inf_principal, ← inf_assoc, inf_of_le_left this] exact h_acc #align acc_pt.nhds_inter AccPt.nhds_inter /-- A set `C` is preperfect if all of its points are accumulation points of itself. If `C` is nonempty and `α` is a T1 space, this is equivalent to the closure of `C` being perfect. See `preperfect_iff_perfect_closure`. -/ def Preperfect (C : Set α) : Prop := ∀ x ∈ C, AccPt x (𝓟 C) #align preperfect Preperfect /-- A set `C` is called perfect if it is closed and all of its points are accumulation points of itself. Note that we do not require `C` to be nonempty. -/ @[mk_iff perfect_def] structure Perfect (C : Set α) : Prop where closed : IsClosed C acc : Preperfect C #align perfect Perfect theorem preperfect_iff_nhds : Preperfect C ↔ ∀ x ∈ C, ∀ U ∈ 𝓝 x, ∃ y ∈ U ∩ C, y ≠ x := by simp only [Preperfect, accPt_iff_nhds] #align preperfect_iff_nhds preperfect_iff_nhds section PerfectSpace variable (α) /-- A topological space `X` is said to be perfect if its universe is a perfect set. Equivalently, this means that `𝓝[≠] x ≠ ⊥` for every point `x : X`. -/ @[mk_iff perfectSpace_def] class PerfectSpace : Prop := univ_preperfect : Preperfect (Set.univ : Set α) theorem PerfectSpace.univ_perfect [PerfectSpace α] : Perfect (Set.univ : Set α) := ⟨isClosed_univ, PerfectSpace.univ_preperfect⟩ end PerfectSpace section Preperfect /-- The intersection of a preperfect set and an open set is preperfect. -/
Mathlib/Topology/Perfect.lean
111
115
theorem Preperfect.open_inter {U : Set α} (hC : Preperfect C) (hU : IsOpen U) : Preperfect (U ∩ C) := by
rintro x ⟨xU, xC⟩ apply (hC _ xC).nhds_inter exact hU.mem_nhds xU
/- 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, Anne Baanen -/ import Mathlib.Data.Matrix.Block import Mathlib.Data.Matrix.Notation import Mathlib.Data.Matrix.RowCol import Mathlib.GroupTheory.GroupAction.Ring import Mathlib.GroupTheory.Perm.Fin import Mathlib.LinearAlgebra.Alternating.Basic #align_import linear_algebra.matrix.determinant from "leanprover-community/mathlib"@"c3019c79074b0619edb4b27553a91b2e82242395" /-! # Determinant of a matrix This file defines the determinant of a matrix, `Matrix.det`, and its essential properties. ## Main definitions - `Matrix.det`: the determinant of a square matrix, as a sum over permutations - `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix ## Main results - `det_mul`: the determinant of `A * B` is the product of determinants - `det_zero_of_row_eq`: the determinant is zero if there is a repeated row - `det_block_diagonal`: the determinant of a block diagonal matrix is a product of the blocks' determinants ## Implementation notes It is possible to configure `simp` to compute determinants. See the file `test/matrix.lean` for some examples. -/ universe u v w z open Equiv Equiv.Perm Finset Function namespace Matrix open Matrix variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m] variable {R : Type v} [CommRing R] local notation "ε " σ:arg => ((sign σ : ℤ) : R) /-- `det` is an `AlternatingMap` in the rows of the matrix. -/ def detRowAlternating : (n → R) [⋀^n]→ₗ[R] R := MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj) #align matrix.det_row_alternating Matrix.detRowAlternating /-- The determinant of a matrix given by the Leibniz formula. -/ abbrev det (M : Matrix n n R) : R := detRowAlternating M #align matrix.det Matrix.det theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i := MultilinearMap.alternatization_apply _ M #align matrix.det_apply Matrix.det_apply -- This is what the old definition was. We use it to avoid having to change the old proofs below theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by simp [det_apply, Units.smul_def] #align matrix.det_apply' Matrix.det_apply' @[simp] theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by rw [det_apply'] refine (Finset.sum_eq_single 1 ?_ ?_).trans ?_ · rintro σ - h2 cases' not_forall.1 (mt Equiv.ext h2) with x h3 convert mul_zero (ε σ) apply Finset.prod_eq_zero (mem_univ x) exact if_neg h3 · simp · simp #align matrix.det_diagonal Matrix.det_diagonal -- @[simp] -- Porting note (#10618): simp can prove this theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 := (detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_zero #align matrix.det_zero Matrix.det_zero @[simp] theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one] #align matrix.det_one Matrix.det_one theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply] #align matrix.det_is_empty Matrix.det_isEmpty @[simp]
Mathlib/LinearAlgebra/Matrix/Determinant/Basic.lean
98
100
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext exact det_isEmpty
/- Copyright (c) 2021 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Data.Finset.Lattice #align_import data.finset.pairwise from "leanprover-community/mathlib"@"c4c2ed622f43768eff32608d4a0f8a6cec1c047d" /-! # Relations holding pairwise on finite sets In this file we prove a few results about the interaction of `Set.PairwiseDisjoint` and `Finset`, as well as the interaction of `List.Pairwise Disjoint` and the condition of `Disjoint` on `List.toFinset`, in `Set` form. -/ open Finset variable {α ι ι' : Type*} instance [DecidableEq α] {r : α → α → Prop} [DecidableRel r] {s : Finset α} : Decidable ((s : Set α).Pairwise r) := decidable_of_iff' (∀ a ∈ s, ∀ b ∈ s, a ≠ b → r a b) Iff.rfl theorem Finset.pairwiseDisjoint_range_singleton : (Set.range (singleton : α → Finset α)).PairwiseDisjoint id := by rintro _ ⟨a, rfl⟩ _ ⟨b, rfl⟩ h exact disjoint_singleton.2 (ne_of_apply_ne _ h) #align finset.pairwise_disjoint_range_singleton Finset.pairwiseDisjoint_range_singleton namespace Set theorem PairwiseDisjoint.elim_finset {s : Set ι} {f : ι → Finset α} (hs : s.PairwiseDisjoint f) {i j : ι} (hi : i ∈ s) (hj : j ∈ s) (a : α) (hai : a ∈ f i) (haj : a ∈ f j) : i = j := hs.elim hi hj (Finset.not_disjoint_iff.2 ⟨a, hai, haj⟩) #align set.pairwise_disjoint.elim_finset Set.PairwiseDisjoint.elim_finset section SemilatticeInf variable [SemilatticeInf α] [OrderBot α] {s : Finset ι} {f : ι → α} theorem PairwiseDisjoint.image_finset_of_le [DecidableEq ι] {s : Finset ι} {f : ι → α} (hs : (s : Set ι).PairwiseDisjoint f) {g : ι → ι} (hf : ∀ a, f (g a) ≤ f a) : (s.image g : Set ι).PairwiseDisjoint f := by rw [coe_image] exact hs.image_of_le hf #align set.pairwise_disjoint.image_finset_of_le Set.PairwiseDisjoint.image_finset_of_le theorem PairwiseDisjoint.attach (hs : (s : Set ι).PairwiseDisjoint f) : (s.attach : Set { x // x ∈ s }).PairwiseDisjoint (f ∘ Subtype.val) := fun i _ j _ hij => hs i.2 j.2 <| mt Subtype.ext_val hij #align set.pairwise_disjoint.attach Set.PairwiseDisjoint.attach end SemilatticeInf variable [Lattice α] [OrderBot α] /-- Bind operation for `Set.PairwiseDisjoint`. In a complete lattice, you can use `Set.PairwiseDisjoint.biUnion`. -/ theorem PairwiseDisjoint.biUnion_finset {s : Set ι'} {g : ι' → Finset ι} {f : ι → α} (hs : s.PairwiseDisjoint fun i' : ι' => (g i').sup f) (hg : ∀ i ∈ s, (g i : Set ι).PairwiseDisjoint f) : (⋃ i ∈ s, ↑(g i)).PairwiseDisjoint f := by rintro a ha b hb hab simp_rw [Set.mem_iUnion] at ha hb obtain ⟨c, hc, ha⟩ := ha obtain ⟨d, hd, hb⟩ := hb obtain hcd | hcd := eq_or_ne (g c) (g d) · exact hg d hd (by rwa [hcd] at ha) hb hab · exact (hs hc hd (ne_of_apply_ne _ hcd)).mono (Finset.le_sup ha) (Finset.le_sup hb) #align set.pairwise_disjoint.bUnion_finset Set.PairwiseDisjoint.biUnion_finset end Set namespace List variable {β : Type*} [DecidableEq α] {r : α → α → Prop} {l : List α}
Mathlib/Data/Finset/Pairwise.lean
80
83
theorem pairwise_of_coe_toFinset_pairwise (hl : (l.toFinset : Set α).Pairwise r) (hn : l.Nodup) : l.Pairwise r := by
rw [coe_toFinset] at hl exact hn.pairwise_of_set_pairwise hl
/- Copyright (c) 2022 Moritz Doll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Doll -/ import Mathlib.LinearAlgebra.LinearPMap import Mathlib.Topology.Algebra.Module.Basic #align_import topology.algebra.module.linear_pmap from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Partially defined linear operators over topological vector spaces We define basic notions of partially defined linear operators, which we call unbounded operators for short. In this file we prove all elementary properties of unbounded operators that do not assume that the underlying spaces are normed. ## Main definitions * `LinearPMap.IsClosed`: An unbounded operator is closed iff its graph is closed. * `LinearPMap.IsClosable`: An unbounded operator is closable iff the closure of its graph is a graph. * `LinearPMap.closure`: For a closable unbounded operator `f : LinearPMap R E F` the closure is the smallest closed extension of `f`. If `f` is not closable, then `f.closure` is defined as `f`. * `LinearPMap.HasCore`: a submodule contained in the domain is a core if restricting to the core does not lose information about the unbounded operator. ## Main statements * `LinearPMap.closable_iff_exists_closed_extension`: an unbounded operator is closable iff it has a closed extension. * `LinearPMap.closable.exists_unique`: there exists a unique closure * `LinearPMap.closureHasCore`: the domain of `f` is a core of its closure ## References * [J. Weidmann, *Linear Operators in Hilbert Spaces*][weidmann_linear] ## Tags Unbounded operators, closed operators -/ open Topology variable {R E F : Type*} variable [CommRing R] [AddCommGroup E] [AddCommGroup F] variable [Module R E] [Module R F] variable [TopologicalSpace E] [TopologicalSpace F] namespace LinearPMap /-! ### Closed and closable operators -/ /-- An unbounded operator is closed iff its graph is closed. -/ def IsClosed (f : E →ₗ.[R] F) : Prop := _root_.IsClosed (f.graph : Set (E × F)) #align linear_pmap.is_closed LinearPMap.IsClosed variable [ContinuousAdd E] [ContinuousAdd F] variable [TopologicalSpace R] [ContinuousSMul R E] [ContinuousSMul R F] /-- An unbounded operator is closable iff the closure of its graph is a graph. -/ def IsClosable (f : E →ₗ.[R] F) : Prop := ∃ f' : LinearPMap R E F, f.graph.topologicalClosure = f'.graph #align linear_pmap.is_closable LinearPMap.IsClosable /-- A closed operator is trivially closable. -/ theorem IsClosed.isClosable {f : E →ₗ.[R] F} (hf : f.IsClosed) : f.IsClosable := ⟨f, hf.submodule_topologicalClosure_eq⟩ #align linear_pmap.is_closed.is_closable LinearPMap.IsClosed.isClosable /-- If `g` has a closable extension `f`, then `g` itself is closable. -/ theorem IsClosable.leIsClosable {f g : E →ₗ.[R] F} (hf : f.IsClosable) (hfg : g ≤ f) : g.IsClosable := by cases' hf with f' hf have : g.graph.topologicalClosure ≤ f'.graph := by rw [← hf] exact Submodule.topologicalClosure_mono (le_graph_of_le hfg) use g.graph.topologicalClosure.toLinearPMap rw [Submodule.toLinearPMap_graph_eq] exact fun _ hx hx' => f'.graph_fst_eq_zero_snd (this hx) hx' #align linear_pmap.is_closable.le_is_closable LinearPMap.IsClosable.leIsClosable /-- The closure is unique. -/ theorem IsClosable.existsUnique {f : E →ₗ.[R] F} (hf : f.IsClosable) : ∃! f' : E →ₗ.[R] F, f.graph.topologicalClosure = f'.graph := by refine exists_unique_of_exists_of_unique hf fun _ _ hy₁ hy₂ => eq_of_eq_graph ?_ rw [← hy₁, ← hy₂] #align linear_pmap.is_closable.exists_unique LinearPMap.IsClosable.existsUnique open scoped Classical /-- If `f` is closable, then `f.closure` is the closure. Otherwise it is defined as `f.closure = f`. -/ noncomputable def closure (f : E →ₗ.[R] F) : E →ₗ.[R] F := if hf : f.IsClosable then hf.choose else f #align linear_pmap.closure LinearPMap.closure
Mathlib/Topology/Algebra/Module/LinearPMap.lean
103
104
theorem closure_def {f : E →ₗ.[R] F} (hf : f.IsClosable) : f.closure = hf.choose := by
simp [closure, hf]
/- 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.NumberTheory.Liouville.Basic import Mathlib.Topology.Baire.Lemmas import Mathlib.Topology.Baire.LocallyCompactRegular import Mathlib.Topology.Instances.Irrational #align_import number_theory.liouville.residual from "leanprover-community/mathlib"@"32b08ef840dd25ca2e47e035c5da03ce16d2dc3c" /-! # Density of Liouville numbers In this file we prove that the set of Liouville numbers form a dense `Gδ` set. We also prove a similar statement about irrational numbers. -/ open scoped Filter open Filter Set Metric theorem setOf_liouville_eq_iInter_iUnion : { x | Liouville x } = ⋂ n : ℕ, ⋃ (a : ℤ) (b : ℤ) (_ : 1 < b), ball ((a : ℝ) / b) (1 / (b : ℝ) ^ n) \ {(a : ℝ) / b} := by ext x simp only [mem_iInter, mem_iUnion, Liouville, mem_setOf_eq, exists_prop, mem_diff, mem_singleton_iff, mem_ball, Real.dist_eq, and_comm] #align set_of_liouville_eq_Inter_Union setOf_liouville_eq_iInter_iUnion theorem IsGδ.setOf_liouville : IsGδ { x | Liouville x } := by rw [setOf_liouville_eq_iInter_iUnion] refine .iInter fun n => IsOpen.isGδ ?_ refine isOpen_iUnion fun a => isOpen_iUnion fun b => isOpen_iUnion fun _hb => ?_ exact isOpen_ball.inter isClosed_singleton.isOpen_compl set_option linter.uppercaseLean3 false in #align is_Gδ_set_of_liouville IsGδ.setOf_liouville @[deprecated (since := "2024-02-15")] alias isGδ_setOf_liouville := IsGδ.setOf_liouville
Mathlib/NumberTheory/Liouville/Residual.lean
44
55
theorem setOf_liouville_eq_irrational_inter_iInter_iUnion : { x | Liouville x } = { x | Irrational x } ∩ ⋂ n : ℕ, ⋃ (a : ℤ) (b : ℤ) (hb : 1 < b), ball (a / b) (1 / (b : ℝ) ^ n) := by
refine Subset.antisymm ?_ ?_ · refine subset_inter (fun x hx => hx.irrational) ?_ rw [setOf_liouville_eq_iInter_iUnion] exact iInter_mono fun n => iUnion₂_mono fun a b => iUnion_mono fun _hb => diff_subset · simp only [inter_iInter, inter_iUnion, setOf_liouville_eq_iInter_iUnion] refine iInter_mono fun n => iUnion₂_mono fun a b => iUnion_mono fun hb => ?_ rw [inter_comm] exact diff_subset_diff Subset.rfl (singleton_subset_iff.2 ⟨a / b, by norm_cast⟩)
/- 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.SpecificLimits.Basic import Mathlib.Topology.MetricSpace.HausdorffDistance import Mathlib.Topology.Sets.Compacts #align_import topology.metric_space.closeds from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Closed subsets This file defines the metric and emetric space structure on the types of closed subsets and nonempty compact subsets of a metric or emetric space. The Hausdorff distance induces an emetric space structure on the type of closed subsets of an emetric space, called `Closeds`. Its completeness, resp. compactness, resp. second-countability, follow from the corresponding properties of the original space. In a metric space, the type of nonempty compact subsets (called `NonemptyCompacts`) also inherits a metric space structure from the Hausdorff distance, as the Hausdorff edistance is always finite in this context. -/ noncomputable section open scoped Classical open Topology ENNReal universe u open scoped Classical open Set Function TopologicalSpace Filter namespace EMetric section variable {α : Type u} [EMetricSpace α] {s : Set α} /-- In emetric spaces, the Hausdorff edistance defines an emetric space structure on the type of closed subsets -/ instance Closeds.emetricSpace : EMetricSpace (Closeds α) where edist s t := hausdorffEdist (s : Set α) t edist_self s := hausdorffEdist_self edist_comm s t := hausdorffEdist_comm edist_triangle s t u := hausdorffEdist_triangle eq_of_edist_eq_zero {s t} h := Closeds.ext <| (hausdorffEdist_zero_iff_eq_of_closed s.closed t.closed).1 h #align emetric.closeds.emetric_space EMetric.Closeds.emetricSpace /-- The edistance to a closed set depends continuously on the point and the set -/
Mathlib/Topology/MetricSpace/Closeds.lean
56
69
theorem continuous_infEdist_hausdorffEdist : Continuous fun p : α × Closeds α => infEdist p.1 p.2 := by
refine continuous_of_le_add_edist 2 (by simp) ?_ rintro ⟨x, s⟩ ⟨y, t⟩ calc infEdist x s ≤ infEdist x t + hausdorffEdist (t : Set α) s := infEdist_le_infEdist_add_hausdorffEdist _ ≤ infEdist y t + edist x y + hausdorffEdist (t : Set α) s := (add_le_add_right infEdist_le_infEdist_add_edist _) _ = infEdist y t + (edist x y + hausdorffEdist (s : Set α) t) := by rw [add_assoc, hausdorffEdist_comm] _ ≤ infEdist y t + (edist (x, s) (y, t) + edist (x, s) (y, t)) := (add_le_add_left (add_le_add (le_max_left _ _) (le_max_right _ _)) _) _ = infEdist y t + 2 * edist (x, s) (y, t) := by rw [← mul_two, mul_comm]
/- Copyright (c) 2020 Markus Himmel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Markus Himmel, Scott Morrison -/ import Mathlib.CategoryTheory.Preadditive.Yoneda.Basic import Mathlib.CategoryTheory.Preadditive.Projective import Mathlib.Algebra.Category.GroupCat.EpiMono #align_import category_theory.preadditive.yoneda.projective from "leanprover-community/mathlib"@"f8d8465c3c392a93b9ed226956e26dee00975946" /-! An object is projective iff the preadditive coyoneda functor on it preserves epimorphisms. -/ universe v u open Opposite namespace CategoryTheory variable {C : Type u} [Category.{v} C] section Preadditive variable [Preadditive C] namespace Projective
Mathlib/CategoryTheory/Preadditive/Yoneda/Projective.lean
31
39
theorem projective_iff_preservesEpimorphisms_preadditiveCoyoneda_obj (P : C) : Projective P ↔ (preadditiveCoyoneda.obj (op P)).PreservesEpimorphisms := by
rw [projective_iff_preservesEpimorphisms_coyoneda_obj] refine ⟨fun h : (preadditiveCoyoneda.obj (op P) ⋙ forget AddCommGroupCat).PreservesEpimorphisms => ?_, ?_⟩ · exact Functor.preservesEpimorphisms_of_preserves_of_reflects (preadditiveCoyoneda.obj (op P)) (forget _) · intro exact (inferInstance : (preadditiveCoyoneda.obj (op P) ⋙ forget _).PreservesEpimorphisms)
/- Copyright (c) 2021 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn, Sébastien Gouëzel -/ import Mathlib.LinearAlgebra.FiniteDimensional import Mathlib.MeasureTheory.Group.Pointwise import Mathlib.MeasureTheory.Measure.Lebesgue.Basic import Mathlib.MeasureTheory.Measure.Haar.Basic import Mathlib.MeasureTheory.Measure.Doubling import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric #align_import measure_theory.measure.lebesgue.eq_haar from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844" /-! # Relationship between the Haar and Lebesgue measures We prove that the Haar measure and Lebesgue measure are equal on `ℝ` and on `ℝ^ι`, in `MeasureTheory.addHaarMeasure_eq_volume` and `MeasureTheory.addHaarMeasure_eq_volume_pi`. We deduce basic properties of any Haar measure on a finite dimensional real vector space: * `map_linearMap_addHaar_eq_smul_addHaar`: a linear map rescales the Haar measure by the absolute value of its determinant. * `addHaar_preimage_linearMap` : when `f` is a linear map with nonzero determinant, the measure of `f ⁻¹' s` is the measure of `s` multiplied by the absolute value of the inverse of the determinant of `f`. * `addHaar_image_linearMap` : when `f` is a linear map, the measure of `f '' s` is the measure of `s` multiplied by the absolute value of the determinant of `f`. * `addHaar_submodule` : a strict submodule has measure `0`. * `addHaar_smul` : the measure of `r • s` is `|r| ^ dim * μ s`. * `addHaar_ball`: the measure of `ball x r` is `r ^ dim * μ (ball 0 1)`. * `addHaar_closedBall`: the measure of `closedBall x r` is `r ^ dim * μ (ball 0 1)`. * `addHaar_sphere`: spheres have zero measure. This makes it possible to associate a Lebesgue measure to an `n`-alternating map in dimension `n`. This measure is called `AlternatingMap.measure`. Its main property is `ω.measure_parallelepiped v`, stating that the associated measure of the parallelepiped spanned by vectors `v₁, ..., vₙ` is given by `|ω v|`. We also show that a Lebesgue density point `x` of a set `s` (with respect to closed balls) has density one for the rescaled copies `{x} + r • t` of a given set `t` with positive measure, in `tendsto_addHaar_inter_smul_one_of_density_one`. In particular, `s` intersects `{x} + r • t` for small `r`, see `eventually_nonempty_inter_smul_of_density_one`. Statements on integrals of functions with respect to an additive Haar measure can be found in `MeasureTheory.Measure.Haar.NormedSpace`. -/ assert_not_exists MeasureTheory.integral open TopologicalSpace Set Filter Metric Bornology open scoped ENNReal Pointwise Topology NNReal /-- The interval `[0,1]` as a compact set with non-empty interior. -/ def TopologicalSpace.PositiveCompacts.Icc01 : PositiveCompacts ℝ where carrier := Icc 0 1 isCompact' := isCompact_Icc interior_nonempty' := by simp_rw [interior_Icc, nonempty_Ioo, zero_lt_one] #align topological_space.positive_compacts.Icc01 TopologicalSpace.PositiveCompacts.Icc01 universe u /-- The set `[0,1]^ι` as a compact set with non-empty interior. -/ def TopologicalSpace.PositiveCompacts.piIcc01 (ι : Type*) [Finite ι] : PositiveCompacts (ι → ℝ) where carrier := pi univ fun _ => Icc 0 1 isCompact' := isCompact_univ_pi fun _ => isCompact_Icc interior_nonempty' := by simp only [interior_pi_set, Set.toFinite, interior_Icc, univ_pi_nonempty_iff, nonempty_Ioo, imp_true_iff, zero_lt_one] #align topological_space.positive_compacts.pi_Icc01 TopologicalSpace.PositiveCompacts.piIcc01 /-- The parallelepiped formed from the standard basis for `ι → ℝ` is `[0,1]^ι` -/ theorem Basis.parallelepiped_basisFun (ι : Type*) [Fintype ι] : (Pi.basisFun ℝ ι).parallelepiped = TopologicalSpace.PositiveCompacts.piIcc01 ι := SetLike.coe_injective <| by refine Eq.trans ?_ ((uIcc_of_le ?_).trans (Set.pi_univ_Icc _ _).symm) · classical convert parallelepiped_single (ι := ι) 1 · exact zero_le_one #align basis.parallelepiped_basis_fun Basis.parallelepiped_basisFun /-- A parallelepiped can be expressed on the standard basis. -/ theorem Basis.parallelepiped_eq_map {ι E : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedSpace ℝ E] (b : Basis ι ℝ E) : b.parallelepiped = (PositiveCompacts.piIcc01 ι).map b.equivFun.symm b.equivFunL.symm.continuous b.equivFunL.symm.isOpenMap := by classical rw [← Basis.parallelepiped_basisFun, ← Basis.parallelepiped_map] congr with x simp open MeasureTheory MeasureTheory.Measure
Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean
95
104
theorem Basis.map_addHaar {ι E F : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedAddCommGroup F] [NormedSpace ℝ E] [NormedSpace ℝ F] [MeasurableSpace E] [MeasurableSpace F] [BorelSpace E] [BorelSpace F] [SecondCountableTopology F] [SigmaCompactSpace F] (b : Basis ι ℝ E) (f : E ≃L[ℝ] F) : map f b.addHaar = (b.map f.toLinearEquiv).addHaar := by
have : IsAddHaarMeasure (map f b.addHaar) := AddEquiv.isAddHaarMeasure_map b.addHaar f.toAddEquiv f.continuous f.symm.continuous rw [eq_comm, Basis.addHaar_eq_iff, Measure.map_apply f.continuous.measurable (PositiveCompacts.isCompact _).measurableSet, Basis.coe_parallelepiped, Basis.coe_map] erw [← image_parallelepiped, f.toEquiv.preimage_image, addHaar_self]
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.List.Sublists import Mathlib.Data.Multiset.Bind #align_import data.multiset.powerset from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853" /-! # The powerset of a multiset -/ namespace Multiset open List variable {α : Type*} /-! ### powerset -/ -- Porting note (#11215): TODO: Write a more efficient version /-- A helper function for the powerset of a multiset. Given a list `l`, returns a list of sublists of `l` as multisets. -/ def powersetAux (l : List α) : List (Multiset α) := (sublists l).map (↑) #align multiset.powerset_aux Multiset.powersetAux theorem powersetAux_eq_map_coe {l : List α} : powersetAux l = (sublists l).map (↑) := rfl #align multiset.powerset_aux_eq_map_coe Multiset.powersetAux_eq_map_coe @[simp] theorem mem_powersetAux {l : List α} {s} : s ∈ powersetAux l ↔ s ≤ ↑l := Quotient.inductionOn s <| by simp [powersetAux_eq_map_coe, Subperm, and_comm] #align multiset.mem_powerset_aux Multiset.mem_powersetAux /-- Helper function for the powerset of a multiset. Given a list `l`, returns a list of sublists of `l` (using `sublists'`), as multisets. -/ def powersetAux' (l : List α) : List (Multiset α) := (sublists' l).map (↑) #align multiset.powerset_aux' Multiset.powersetAux'
Mathlib/Data/Multiset/Powerset.lean
45
46
theorem powersetAux_perm_powersetAux' {l : List α} : powersetAux l ~ powersetAux' l := by
rw [powersetAux_eq_map_coe]; exact (sublists_perm_sublists' _).map _
/- Copyright (c) 2021 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Algebra.BigOperators.Group.Finset import Mathlib.Data.Finset.Option #align_import algebra.big_operators.option from "leanprover-community/mathlib"@"008205aa645b3f194c1da47025c5f110c8406eab" /-! # Lemmas about products and sums over finite sets in `Option α` In this file we prove formulas for products and sums over `Finset.insertNone s` and `Finset.eraseNone s`. -/ open Function namespace Finset variable {α M : Type*} [CommMonoid M] @[to_additive (attr := simp)]
Mathlib/Algebra/BigOperators/Option.lean
25
26
theorem prod_insertNone (f : Option α → M) (s : Finset α) : ∏ x ∈ insertNone s, f x = f none * ∏ x ∈ s, f (some x) := by
simp [insertNone]
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Benjamin Davidson -/ import Mathlib.Analysis.SpecialFunctions.Trigonometric.Angle import Mathlib.Analysis.SpecialFunctions.Trigonometric.Inverse #align_import analysis.special_functions.complex.arg from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1" /-! # The argument of a complex number. We define `arg : ℂ → ℝ`, returning a real number in the range (-π, π], such that for `x ≠ 0`, `sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`, while `arg 0` defaults to `0` -/ open Filter Metric Set open scoped ComplexConjugate Real Topology namespace Complex variable {a x z : ℂ} /-- `arg` returns values in the range (-π, π], such that for `x ≠ 0`, `sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`, `arg 0` defaults to `0` -/ noncomputable def arg (x : ℂ) : ℝ := if 0 ≤ x.re then Real.arcsin (x.im / abs x) else if 0 ≤ x.im then Real.arcsin ((-x).im / abs x) + π else Real.arcsin ((-x).im / abs x) - π #align complex.arg Complex.arg theorem sin_arg (x : ℂ) : Real.sin (arg x) = x.im / abs x := by unfold arg; split_ifs <;> simp [sub_eq_add_neg, arg, Real.sin_arcsin (abs_le.1 (abs_im_div_abs_le_one x)).1 (abs_le.1 (abs_im_div_abs_le_one x)).2, Real.sin_add, neg_div, Real.arcsin_neg, Real.sin_neg] #align complex.sin_arg Complex.sin_arg theorem cos_arg {x : ℂ} (hx : x ≠ 0) : Real.cos (arg x) = x.re / abs x := by rw [arg] split_ifs with h₁ h₂ · rw [Real.cos_arcsin] field_simp [Real.sqrt_sq, (abs.pos hx).le, *] · rw [Real.cos_add_pi, Real.cos_arcsin] field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs, _root_.abs_of_neg (not_le.1 h₁), *] · rw [Real.cos_sub_pi, Real.cos_arcsin] field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs, _root_.abs_of_neg (not_le.1 h₁), *] #align complex.cos_arg Complex.cos_arg @[simp] theorem abs_mul_exp_arg_mul_I (x : ℂ) : ↑(abs x) * exp (arg x * I) = x := by rcases eq_or_ne x 0 with (rfl | hx) · simp · have : abs x ≠ 0 := abs.ne_zero hx apply Complex.ext <;> field_simp [sin_arg, cos_arg hx, this, mul_comm (abs x)] set_option linter.uppercaseLean3 false in #align complex.abs_mul_exp_arg_mul_I Complex.abs_mul_exp_arg_mul_I @[simp] theorem abs_mul_cos_add_sin_mul_I (x : ℂ) : (abs x * (cos (arg x) + sin (arg x) * I) : ℂ) = x := by rw [← exp_mul_I, abs_mul_exp_arg_mul_I] set_option linter.uppercaseLean3 false in #align complex.abs_mul_cos_add_sin_mul_I Complex.abs_mul_cos_add_sin_mul_I @[simp] lemma abs_mul_cos_arg (x : ℂ) : abs x * Real.cos (arg x) = x.re := by simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg re (abs_mul_cos_add_sin_mul_I x) @[simp] lemma abs_mul_sin_arg (x : ℂ) : abs x * Real.sin (arg x) = x.im := by simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg im (abs_mul_cos_add_sin_mul_I x)
Mathlib/Analysis/SpecialFunctions/Complex/Arg.lean
76
83
theorem abs_eq_one_iff (z : ℂ) : abs z = 1 ↔ ∃ θ : ℝ, exp (θ * I) = z := by
refine ⟨fun hz => ⟨arg z, ?_⟩, ?_⟩ · calc exp (arg z * I) = abs z * exp (arg z * I) := by rw [hz, ofReal_one, one_mul] _ = z := abs_mul_exp_arg_mul_I z · rintro ⟨θ, rfl⟩ exact Complex.abs_exp_ofReal_mul_I θ
/- Copyright (c) 2022 Jireh Loreaux. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jireh Loreaux -/ import Mathlib.Analysis.NormedSpace.Star.Basic import Mathlib.Analysis.NormedSpace.Spectrum import Mathlib.Analysis.SpecialFunctions.Exponential import Mathlib.Algebra.Star.StarAlgHom #align_import analysis.normed_space.star.spectrum from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9" /-! # Spectral properties in C⋆-algebras In this file, we establish various properties related to the spectrum of elements in C⋆-algebras. -/ local postfix:max "⋆" => star section open scoped Topology ENNReal open Filter ENNReal spectrum CstarRing NormedSpace section UnitarySpectrum variable {𝕜 : Type*} [NormedField 𝕜] {E : Type*} [NormedRing E] [StarRing E] [CstarRing E] [NormedAlgebra 𝕜 E] [CompleteSpace E]
Mathlib/Analysis/NormedSpace/Star/Spectrum.lean
31
41
theorem unitary.spectrum_subset_circle (u : unitary E) : spectrum 𝕜 (u : E) ⊆ Metric.sphere 0 1 := by
nontriviality E refine fun k hk => mem_sphere_zero_iff_norm.mpr (le_antisymm ?_ ?_) · simpa only [CstarRing.norm_coe_unitary u] using norm_le_norm_of_mem hk · rw [← unitary.val_toUnits_apply u] at hk have hnk := ne_zero_of_mem_of_unit hk rw [← inv_inv (unitary.toUnits u), ← spectrum.map_inv, Set.mem_inv] at hk have : ‖k‖⁻¹ ≤ ‖(↑(unitary.toUnits u)⁻¹ : E)‖ := by simpa only [norm_inv] using norm_le_norm_of_mem hk simpa using inv_le_of_inv_le (norm_pos_iff.mpr hnk) this
/- 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.NormedSpace.Banach import Mathlib.Topology.Algebra.Module.FiniteDimension #align_import analysis.normed_space.complemented from "leanprover-community/mathlib"@"3397560e65278e5f31acefcdea63138bd53d1cd4" /-! # Complemented subspaces of normed vector spaces A submodule `p` of a topological module `E` over `R` is called *complemented* if there exists a continuous linear projection `f : E →ₗ[R] p`, `∀ x : p, f x = x`. We prove that for a closed subspace of a normed space this condition is equivalent to existence of a closed subspace `q` such that `p ⊓ q = ⊥`, `p ⊔ q = ⊤`. We also prove that a subspace of finite codimension is always a complemented subspace. ## Tags complemented subspace, normed vector space -/ variable {𝕜 E F G : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] noncomputable section open LinearMap (ker range) namespace ContinuousLinearMap section variable [CompleteSpace 𝕜]
Mathlib/Analysis/NormedSpace/Complemented.lean
39
43
theorem ker_closedComplemented_of_finiteDimensional_range (f : E →L[𝕜] F) [FiniteDimensional 𝕜 (range f)] : (ker f).ClosedComplemented := by
set f' : E →L[𝕜] range f := f.codRestrict _ (LinearMap.mem_range_self (f : E →ₗ[𝕜] F)) rcases f'.exists_right_inverse_of_surjective (f : E →ₗ[𝕜] F).range_rangeRestrict with ⟨g, hg⟩ simpa only [f', ker_codRestrict] using f'.closedComplemented_ker_of_rightInverse g (ext_iff.1 hg)
/- Copyright (c) 2022 Antoine Labelle, Rémi Bottinelli. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Labelle, Rémi Bottinelli -/ import Mathlib.Combinatorics.Quiver.Basic import Mathlib.Combinatorics.Quiver.Path #align_import combinatorics.quiver.cast from "leanprover-community/mathlib"@"fc2ed6f838ce7c9b7c7171e58d78eaf7b438fb0e" /-! # Rewriting arrows and paths along vertex equalities This files defines `Hom.cast` and `Path.cast` (and associated lemmas) in order to allow rewriting arrows and paths along equalities of their endpoints. -/ universe v v₁ v₂ u u₁ u₂ variable {U : Type*} [Quiver.{u + 1} U] namespace Quiver /-! ### Rewriting arrows along equalities of vertices -/ /-- Change the endpoints of an arrow using equalities. -/ def Hom.cast {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) : u' ⟶ v' := Eq.ndrec (motive := (· ⟶ v')) (Eq.ndrec e hv) hu #align quiver.hom.cast Quiver.Hom.cast theorem Hom.cast_eq_cast {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) : e.cast hu hv = _root_.cast (by {rw [hu, hv]}) e := by subst_vars rfl #align quiver.hom.cast_eq_cast Quiver.Hom.cast_eq_cast @[simp] theorem Hom.cast_rfl_rfl {u v : U} (e : u ⟶ v) : e.cast rfl rfl = e := rfl #align quiver.hom.cast_rfl_rfl Quiver.Hom.cast_rfl_rfl @[simp] theorem Hom.cast_cast {u v u' v' u'' v'' : U} (e : u ⟶ v) (hu : u = u') (hv : v = v') (hu' : u' = u'') (hv' : v' = v'') : (e.cast hu hv).cast hu' hv' = e.cast (hu.trans hu') (hv.trans hv') := by subst_vars rfl #align quiver.hom.cast_cast Quiver.Hom.cast_cast theorem Hom.cast_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) : HEq (e.cast hu hv) e := by subst_vars rfl #align quiver.hom.cast_heq Quiver.Hom.cast_heq theorem Hom.cast_eq_iff_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) (e' : u' ⟶ v') : e.cast hu hv = e' ↔ HEq e e' := by rw [Hom.cast_eq_cast] exact _root_.cast_eq_iff_heq #align quiver.hom.cast_eq_iff_heq Quiver.Hom.cast_eq_iff_heq theorem Hom.eq_cast_iff_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) (e' : u' ⟶ v') : e' = e.cast hu hv ↔ HEq e' e := by rw [eq_comm, Hom.cast_eq_iff_heq] exact ⟨HEq.symm, HEq.symm⟩ #align quiver.hom.eq_cast_iff_heq Quiver.Hom.eq_cast_iff_heq /-! ### Rewriting paths along equalities of vertices -/ open Path /-- Change the endpoints of a path using equalities. -/ def Path.cast {u v u' v' : U} (hu : u = u') (hv : v = v') (p : Path u v) : Path u' v' := Eq.ndrec (motive := (Path · v')) (Eq.ndrec p hv) hu #align quiver.path.cast Quiver.Path.cast theorem Path.cast_eq_cast {u v u' v' : U} (hu : u = u') (hv : v = v') (p : Path u v) : p.cast hu hv = _root_.cast (by rw [hu, hv]) p := by subst_vars rfl #align quiver.path.cast_eq_cast Quiver.Path.cast_eq_cast @[simp] theorem Path.cast_rfl_rfl {u v : U} (p : Path u v) : p.cast rfl rfl = p := rfl #align quiver.path.cast_rfl_rfl Quiver.Path.cast_rfl_rfl @[simp] theorem Path.cast_cast {u v u' v' u'' v'' : U} (p : Path u v) (hu : u = u') (hv : v = v') (hu' : u' = u'') (hv' : v' = v'') : (p.cast hu hv).cast hu' hv' = p.cast (hu.trans hu') (hv.trans hv') := by subst_vars rfl #align quiver.path.cast_cast Quiver.Path.cast_cast @[simp] theorem Path.cast_nil {u u' : U} (hu : u = u') : (Path.nil : Path u u).cast hu hu = Path.nil := by subst_vars rfl #align quiver.path.cast_nil Quiver.Path.cast_nil theorem Path.cast_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (p : Path u v) : HEq (p.cast hu hv) p := by rw [Path.cast_eq_cast] exact _root_.cast_heq _ _ #align quiver.path.cast_heq Quiver.Path.cast_heq theorem Path.cast_eq_iff_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (p : Path u v) (p' : Path u' v') : p.cast hu hv = p' ↔ HEq p p' := by rw [Path.cast_eq_cast] exact _root_.cast_eq_iff_heq #align quiver.path.cast_eq_iff_heq Quiver.Path.cast_eq_iff_heq theorem Path.eq_cast_iff_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (p : Path u v) (p' : Path u' v') : p' = p.cast hu hv ↔ HEq p' p := ⟨fun h => ((p.cast_eq_iff_heq hu hv p').1 h.symm).symm, fun h => ((p.cast_eq_iff_heq hu hv p').2 h.symm).symm⟩ #align quiver.path.eq_cast_iff_heq Quiver.Path.eq_cast_iff_heq
Mathlib/Combinatorics/Quiver/Cast.lean
130
133
theorem Path.cast_cons {u v w u' w' : U} (p : Path u v) (e : v ⟶ w) (hu : u = u') (hw : w = w') : (p.cons e).cast hu hw = (p.cast hu rfl).cons (e.cast rfl hw) := by
subst_vars rfl
/- Copyright (c) 2020 Jalex Stark. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jalex Stark, Scott Morrison, Eric Wieser, Oliver Nash, Wen Yang -/ import Mathlib.Data.Matrix.Basic import Mathlib.LinearAlgebra.Matrix.Trace #align_import data.matrix.basis from "leanprover-community/mathlib"@"320df450e9abeb5fc6417971e75acb6ae8bc3794" /-! # Matrices with a single non-zero element. This file provides `Matrix.stdBasisMatrix`. The matrix `Matrix.stdBasisMatrix i j c` has `c` at position `(i, j)`, and zeroes elsewhere. -/ variable {l m n : Type*} variable {R α : Type*} namespace Matrix open Matrix variable [DecidableEq l] [DecidableEq m] [DecidableEq n] variable [Semiring α] /-- `stdBasisMatrix i j a` is the matrix with `a` in the `i`-th row, `j`-th column, and zeroes elsewhere. -/ def stdBasisMatrix (i : m) (j : n) (a : α) : Matrix m n α := fun i' j' => if i = i' ∧ j = j' then a else 0 #align matrix.std_basis_matrix Matrix.stdBasisMatrix @[simp] theorem smul_stdBasisMatrix [SMulZeroClass R α] (r : R) (i : m) (j : n) (a : α) : r • stdBasisMatrix i j a = stdBasisMatrix i j (r • a) := by unfold stdBasisMatrix ext simp [smul_ite] #align matrix.smul_std_basis_matrix Matrix.smul_stdBasisMatrix @[simp] theorem stdBasisMatrix_zero (i : m) (j : n) : stdBasisMatrix i j (0 : α) = 0 := by unfold stdBasisMatrix ext simp #align matrix.std_basis_matrix_zero Matrix.stdBasisMatrix_zero theorem stdBasisMatrix_add (i : m) (j : n) (a b : α) : stdBasisMatrix i j (a + b) = stdBasisMatrix i j a + stdBasisMatrix i j b := by unfold stdBasisMatrix; ext split_ifs with h <;> simp [h] #align matrix.std_basis_matrix_add Matrix.stdBasisMatrix_add
Mathlib/Data/Matrix/Basis.lean
57
63
theorem mulVec_stdBasisMatrix [Fintype m] (i : n) (j : m) (c : α) (x : m → α) : mulVec (stdBasisMatrix i j c) x = Function.update (0 : n → α) i (c * x j) := by
ext i' simp [stdBasisMatrix, mulVec, dotProduct] rcases eq_or_ne i i' with rfl|h · simp simp [h, h.symm]
/- Copyright (c) 2023 Scott Carnahan. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Carnahan -/ import Mathlib.Algebra.Group.Defs import Mathlib.Algebra.Group.Prod import Mathlib.Data.PNat.Basic import Mathlib.GroupTheory.GroupAction.Prod /-! # Typeclasses for power-associative structures In this file we define power-associativity for algebraic structures with a multiplication operation. The class is a Prop-valued mixin named `PNatPowAssoc`, where `PNat` means only strictly positive powers are considered. ## Results - `ppow_add` a defining property: `x ^ (k + n) = x ^ k * x ^ n` - `ppow_one` a defining property: `x ^ 1 = x` - `ppow_assoc` strictly positive powers of an element have associative multiplication. - `ppow_comm` `x ^ m * x ^ n = x ^ n * x ^ m` for strictly positive `m` and `n`. - `ppow_mul` `x ^ (m * n) = (x ^ m) ^ n` for strictly positive `m` and `n`. - `ppow_eq_pow` monoid exponentiation coincides with semigroup exponentiation. ## Instances - PNatPowAssoc for products and Pi types ## Todo * `NatPowAssoc` for `MulOneClass` - more or less the same flow * It seems unlikely that anyone will want `NatSMulAssoc` and `PNatSMulAssoc` as additive versions of power-associativity, but we have found that it is not hard to write. -/ variable {M : Type*} /-- A `Prop`-valued mixin for power-associative multiplication in the non-unital setting. -/ class PNatPowAssoc (M : Type*) [Mul M] [Pow M ℕ+] : Prop where /-- Multiplication is power-associative. -/ protected ppow_add : ∀ (k n : ℕ+) (x : M), x ^ (k + n) = x ^ k * x ^ n /-- Exponent one is identity. -/ protected ppow_one : ∀ (x : M), x ^ (1 : ℕ+) = x section Mul variable [Mul M] [Pow M ℕ+] [PNatPowAssoc M] theorem ppow_add (k n : ℕ+) (x : M) : x ^ (k + n) = x ^ k * x ^ n := PNatPowAssoc.ppow_add k n x @[simp] theorem ppow_one (x : M) : x ^ (1 : ℕ+) = x := PNatPowAssoc.ppow_one x
Mathlib/Algebra/Group/PNatPowAssoc.lean
60
62
theorem ppow_mul_assoc (k m n : ℕ+) (x : M) : (x ^ k * x ^ m) * x ^ n = x ^ k * (x ^ m * x ^ n) := by
simp only [← ppow_add, add_assoc]
/- Copyright (c) 2023 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Probability.Kernel.Basic import Mathlib.MeasureTheory.Constructions.Prod.Basic import Mathlib.MeasureTheory.Integral.DominatedConvergence #align_import probability.kernel.measurable_integral from "leanprover-community/mathlib"@"28b2a92f2996d28e580450863c130955de0ed398" /-! # Measurability of the integral against a kernel The Lebesgue integral of a measurable function against a kernel is measurable. The Bochner integral is strongly measurable. ## Main statements * `Measurable.lintegral_kernel_prod_right`: the function `a ↦ ∫⁻ b, f a b ∂(κ a)` is measurable, for an s-finite kernel `κ : kernel α β` and a function `f : α → β → ℝ≥0∞` such that `uncurry f` is measurable. * `MeasureTheory.StronglyMeasurable.integral_kernel_prod_right`: the function `a ↦ ∫ b, f a b ∂(κ a)` is measurable, for an s-finite kernel `κ : kernel α β` and a function `f : α → β → E` such that `uncurry f` is measurable. -/ open MeasureTheory ProbabilityTheory Function Set Filter open scoped MeasureTheory ENNReal Topology variable {α β γ : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} {κ : kernel α β} {η : kernel (α × β) γ} {a : α} namespace ProbabilityTheory namespace kernel /-- This is an auxiliary lemma for `measurable_kernel_prod_mk_left`. -/
Mathlib/Probability/Kernel/MeasurableIntegral.lean
42
99
theorem measurable_kernel_prod_mk_left_of_finite {t : Set (α × β)} (ht : MeasurableSet t) (hκs : ∀ a, IsFiniteMeasure (κ a)) : Measurable fun a => κ a (Prod.mk a ⁻¹' t) := by
-- `t` is a measurable set in the product `α × β`: we use that the product σ-algebra is generated -- by boxes to prove the result by induction. -- Porting note: added motive refine MeasurableSpace.induction_on_inter (C := fun t => Measurable fun a => κ a (Prod.mk a ⁻¹' t)) generateFrom_prod.symm isPiSystem_prod ?_ ?_ ?_ ?_ ht ·-- case `t = ∅` simp only [preimage_empty, measure_empty, measurable_const] · -- case of a box: `t = t₁ ×ˢ t₂` for measurable sets `t₁` and `t₂` intro t' ht' simp only [Set.mem_image2, Set.mem_setOf_eq, exists_and_left] at ht' obtain ⟨t₁, ht₁, t₂, ht₂, rfl⟩ := ht' classical simp_rw [mk_preimage_prod_right_eq_if] have h_eq_ite : (fun a => κ a (ite (a ∈ t₁) t₂ ∅)) = fun a => ite (a ∈ t₁) (κ a t₂) 0 := by ext1 a split_ifs exacts [rfl, measure_empty] rw [h_eq_ite] exact Measurable.ite ht₁ (kernel.measurable_coe κ ht₂) measurable_const · -- we assume that the result is true for `t` and we prove it for `tᶜ` intro t' ht' h_meas have h_eq_sdiff : ∀ a, Prod.mk a ⁻¹' t'ᶜ = Set.univ \ Prod.mk a ⁻¹' t' := by intro a ext1 b simp only [mem_compl_iff, mem_preimage, mem_diff, mem_univ, true_and_iff] simp_rw [h_eq_sdiff] have : (fun a => κ a (Set.univ \ Prod.mk a ⁻¹' t')) = fun a => κ a Set.univ - κ a (Prod.mk a ⁻¹' t') := by ext1 a rw [← Set.diff_inter_self_eq_diff, Set.inter_univ, measure_diff (Set.subset_univ _)] · exact (@measurable_prod_mk_left α β _ _ a) ht' · exact measure_ne_top _ _ rw [this] exact Measurable.sub (kernel.measurable_coe κ MeasurableSet.univ) h_meas · -- we assume that the result is true for a family of disjoint sets and prove it for their union intro f h_disj hf_meas hf have h_Union : (fun a => κ a (Prod.mk a ⁻¹' ⋃ i, f i)) = fun a => κ a (⋃ i, Prod.mk a ⁻¹' f i) := by ext1 a congr with b simp only [mem_iUnion, mem_preimage] rw [h_Union] have h_tsum : (fun a => κ a (⋃ i, Prod.mk a ⁻¹' f i)) = fun a => ∑' i, κ a (Prod.mk a ⁻¹' f i) := by ext1 a rw [measure_iUnion] · intro i j hij s hsi hsj b hbs have habi : {(a, b)} ⊆ f i := by rw [Set.singleton_subset_iff]; exact hsi hbs have habj : {(a, b)} ⊆ f j := by rw [Set.singleton_subset_iff]; exact hsj hbs simpa only [Set.bot_eq_empty, Set.le_eq_subset, Set.singleton_subset_iff, Set.mem_empty_iff_false] using h_disj hij habi habj · exact fun i => (@measurable_prod_mk_left α β _ _ a) (hf_meas i) rw [h_tsum] exact Measurable.ennreal_tsum hf