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/- Copyright (c) 2019 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin, Kenny Lau -/ import Mathlib.RingTheory.MvPowerSeries.Basic import Mathlib.Data.Finsupp.Interval /-! # Formal (multivariate) power series - Truncation `MvPowerSeries.trunc n φ` truncates a formal multivariate power series to the multivariate polynomial that has the same coefficients as `φ`, for all `m < n`, and `0` otherwise. Note that here, `m` and `n` have types `σ →₀ ℕ`, so that `m < n` means that `m ≠ n` and `m s ≤ n s` for all `s : σ`. -/ noncomputable section open Finset (antidiagonal mem_antidiagonal) namespace MvPowerSeries open Finsupp variable {σ R : Type*} section Trunc variable [CommSemiring R] (n : σ →₀ ℕ) /-- Auxiliary definition for the truncation function. -/ def truncFun (φ : MvPowerSeries σ R) : MvPolynomial σ R := ∑ m ∈ Finset.Iio n, MvPolynomial.monomial m (coeff R m φ) #align mv_power_series.trunc_fun MvPowerSeries.truncFun
Mathlib/RingTheory/MvPowerSeries/Trunc.lean
43
46
theorem coeff_truncFun (m : σ →₀ ℕ) (φ : MvPowerSeries σ R) : (truncFun n φ).coeff m = if m < n then coeff R m φ else 0 := by
classical simp [truncFun, MvPolynomial.coeff_sum]
/- Copyright (c) 2021 Riccardo Brasca. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Riccardo Brasca -/ import Mathlib.LinearAlgebra.FreeModule.Finite.Basic import Mathlib.LinearAlgebra.Matrix.Charpoly.Coeff import Mathlib.FieldTheory.Minpoly.Field #align_import linear_algebra.charpoly.basic from "leanprover-community/mathlib"@"d3e8e0a0237c10c2627bf52c246b15ff8e7df4c0" /-! # Characteristic polynomial We define the characteristic polynomial of `f : M →ₗ[R] M`, where `M` is a finite and free `R`-module. The proof that `f.charpoly` is the characteristic polynomial of the matrix of `f` in any basis is in `LinearAlgebra/Charpoly/ToMatrix`. ## Main definition * `LinearMap.charpoly f` : the characteristic polynomial of `f : M →ₗ[R] M`. -/ universe u v w variable {R : Type u} {M : Type v} [CommRing R] [Nontrivial R] variable [AddCommGroup M] [Module R M] [Module.Free R M] [Module.Finite R M] (f : M →ₗ[R] M) open Matrix Polynomial noncomputable section open Module.Free Polynomial Matrix namespace LinearMap section Basic /-- The characteristic polynomial of `f : M →ₗ[R] M`. -/ def charpoly : R[X] := (toMatrix (chooseBasis R M) (chooseBasis R M) f).charpoly #align linear_map.charpoly LinearMap.charpoly theorem charpoly_def : f.charpoly = (toMatrix (chooseBasis R M) (chooseBasis R M) f).charpoly := rfl #align linear_map.charpoly_def LinearMap.charpoly_def end Basic section Coeff theorem charpoly_monic : f.charpoly.Monic := Matrix.charpoly_monic _ #align linear_map.charpoly_monic LinearMap.charpoly_monic open FiniteDimensional in lemma charpoly_natDegree [StrongRankCondition R] : natDegree (charpoly f) = finrank R M := by rw [charpoly, Matrix.charpoly_natDegree_eq_dim, finrank_eq_card_chooseBasisIndex] end Coeff section CayleyHamilton /-- The **Cayley-Hamilton Theorem**, that the characteristic polynomial of a linear map, applied to the linear map itself, is zero. See `Matrix.aeval_self_charpoly` for the equivalent statement about matrices. -/ theorem aeval_self_charpoly : aeval f f.charpoly = 0 := by apply (LinearEquiv.map_eq_zero_iff (algEquivMatrix (chooseBasis R M)).toLinearEquiv).1 rw [AlgEquiv.toLinearEquiv_apply, ← AlgEquiv.coe_algHom, ← Polynomial.aeval_algHom_apply _ _ _, charpoly_def] exact Matrix.aeval_self_charpoly _ #align linear_map.aeval_self_charpoly LinearMap.aeval_self_charpoly theorem isIntegral : IsIntegral R f := ⟨f.charpoly, ⟨charpoly_monic f, aeval_self_charpoly f⟩⟩ #align linear_map.is_integral LinearMap.isIntegral theorem minpoly_dvd_charpoly {K : Type u} {M : Type v} [Field K] [AddCommGroup M] [Module K M] [FiniteDimensional K M] (f : M →ₗ[K] M) : minpoly K f ∣ f.charpoly := minpoly.dvd _ _ (aeval_self_charpoly f) #align linear_map.minpoly_dvd_charpoly LinearMap.minpoly_dvd_charpoly /-- Any endomorphism polynomial `p` is equivalent under evaluation to `p %ₘ f.charpoly`; that is, `p` is equivalent to a polynomial with degree less than the dimension of the module. -/ theorem aeval_eq_aeval_mod_charpoly (p : R[X]) : aeval f p = aeval f (p %ₘ f.charpoly) := (aeval_modByMonic_eq_self_of_root f.charpoly_monic f.aeval_self_charpoly).symm #align linear_map.aeval_eq_aeval_mod_charpoly LinearMap.aeval_eq_aeval_mod_charpoly /-- Any endomorphism power can be computed as the sum of endomorphism powers less than the dimension of the module. -/
Mathlib/LinearAlgebra/Charpoly/Basic.lean
95
96
theorem pow_eq_aeval_mod_charpoly (k : ℕ) : f ^ k = aeval f (X ^ k %ₘ f.charpoly) := by
rw [← aeval_eq_aeval_mod_charpoly, map_pow, aeval_X]
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Floris van Doorn, Mario Carneiro, Martin Dvorak -/ import Mathlib.Data.List.Basic #align_import data.list.join from "leanprover-community/mathlib"@"18a5306c091183ac90884daa9373fa3b178e8607" /-! # Join of a list of lists This file proves basic properties of `List.join`, which concatenates a list of lists. It is defined in `Init.Data.List.Basic`. -/ -- Make sure we don't import algebra assert_not_exists Monoid variable {α β : Type*} namespace List attribute [simp] join -- Porting note (#10618): simp can prove this -- @[simp] theorem join_singleton (l : List α) : [l].join = l := by rw [join, join, append_nil] #align list.join_singleton List.join_singleton @[simp] theorem join_eq_nil : ∀ {L : List (List α)}, join L = [] ↔ ∀ l ∈ L, l = [] | [] => iff_of_true rfl (forall_mem_nil _) | l :: L => by simp only [join, append_eq_nil, join_eq_nil, forall_mem_cons] #align list.join_eq_nil List.join_eq_nil @[simp] theorem join_append (L₁ L₂ : List (List α)) : join (L₁ ++ L₂) = join L₁ ++ join L₂ := by induction L₁ · rfl · simp [*] #align list.join_append List.join_append theorem join_concat (L : List (List α)) (l : List α) : join (L.concat l) = join L ++ l := by simp #align list.join_concat List.join_concat @[simp] theorem join_filter_not_isEmpty : ∀ {L : List (List α)}, join (L.filter fun l => !l.isEmpty) = L.join | [] => rfl | [] :: L => by simp [join_filter_not_isEmpty (L := L), isEmpty_iff_eq_nil] | (a :: l) :: L => by simp [join_filter_not_isEmpty (L := L)] #align list.join_filter_empty_eq_ff List.join_filter_not_isEmpty @[deprecated (since := "2024-02-25")] alias join_filter_isEmpty_eq_false := join_filter_not_isEmpty @[simp] theorem join_filter_ne_nil [DecidablePred fun l : List α => l ≠ []] {L : List (List α)} : join (L.filter fun l => l ≠ []) = L.join := by simp [join_filter_not_isEmpty, ← isEmpty_iff_eq_nil] #align list.join_filter_ne_nil List.join_filter_ne_nil theorem join_join (l : List (List (List α))) : l.join.join = (l.map join).join := by induction l <;> simp [*] #align list.join_join List.join_join /-- See `List.length_join` for the corresponding statement using `List.sum`. -/ lemma length_join' (L : List (List α)) : length (join L) = Nat.sum (map length L) := by induction L <;> [rfl; simp only [*, join, map, Nat.sum_cons, length_append]] /-- See `List.countP_join` for the corresponding statement using `List.sum`. -/ lemma countP_join' (p : α → Bool) : ∀ L : List (List α), countP p L.join = Nat.sum (L.map (countP p)) | [] => rfl | a :: l => by rw [join, countP_append, map_cons, Nat.sum_cons, countP_join' _ l] /-- See `List.count_join` for the corresponding statement using `List.sum`. -/ lemma count_join' [BEq α] (L : List (List α)) (a : α) : L.join.count a = Nat.sum (L.map (count a)) := countP_join' _ _ /-- See `List.length_bind` for the corresponding statement using `List.sum`. -/ lemma length_bind' (l : List α) (f : α → List β) : length (l.bind f) = Nat.sum (map (length ∘ f) l) := by rw [List.bind, length_join', map_map] /-- See `List.countP_bind` for the corresponding statement using `List.sum`. -/ lemma countP_bind' (p : β → Bool) (l : List α) (f : α → List β) : countP p (l.bind f) = Nat.sum (map (countP p ∘ f) l) := by rw [List.bind, countP_join', map_map] /-- See `List.count_bind` for the corresponding statement using `List.sum`. -/ lemma count_bind' [BEq β] (l : List α) (f : α → List β) (x : β) : count x (l.bind f) = Nat.sum (map (count x ∘ f) l) := countP_bind' _ _ _ @[simp] theorem bind_eq_nil {l : List α} {f : α → List β} : List.bind l f = [] ↔ ∀ x ∈ l, f x = [] := join_eq_nil.trans <| by simp only [mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] #align list.bind_eq_nil List.bind_eq_nil /-- In a join, taking the first elements up to an index which is the sum of the lengths of the first `i` sublists, is the same as taking the join of the first `i` sublists. See `List.take_sum_join` for the corresponding statement using `List.sum`. -/ theorem take_sum_join' (L : List (List α)) (i : ℕ) : L.join.take (Nat.sum ((L.map length).take i)) = (L.take i).join := by induction L generalizing i · simp · cases i <;> simp [take_append, *] /-- In a join, dropping all the elements up to an index which is the sum of the lengths of the first `i` sublists, is the same as taking the join after dropping the first `i` sublists. See `List.drop_sum_join` for the corresponding statement using `List.sum`. -/ theorem drop_sum_join' (L : List (List α)) (i : ℕ) : L.join.drop (Nat.sum ((L.map length).take i)) = (L.drop i).join := by induction L generalizing i · simp · cases i <;> simp [drop_append, *] /-- Taking only the first `i+1` elements in a list, and then dropping the first `i` ones, one is left with a list of length `1` made of the `i`-th element of the original list. -/
Mathlib/Data/List/Join.lean
123
129
theorem drop_take_succ_eq_cons_get (L : List α) (i : Fin L.length) : (L.take (i + 1)).drop i = [get L i] := by
induction' L with head tail ih · exact (Nat.not_succ_le_zero i i.isLt).elim rcases i with ⟨_ | i, hi⟩ · simp · simpa using ih ⟨i, Nat.lt_of_succ_lt_succ hi⟩
/- Copyright (c) 2020 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Lu-Ming Zhang -/ import Mathlib.Combinatorics.SimpleGraph.Basic import Mathlib.Combinatorics.SimpleGraph.Connectivity import Mathlib.LinearAlgebra.Matrix.Trace import Mathlib.LinearAlgebra.Matrix.Symmetric #align_import combinatorics.simple_graph.adj_matrix from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1" /-! # Adjacency Matrices This module defines the adjacency matrix of a graph, and provides theorems connecting graph properties to computational properties of the matrix. ## Main definitions * `Matrix.IsAdjMatrix`: `A : Matrix V V α` is qualified as an "adjacency matrix" if (1) every entry of `A` is `0` or `1`, (2) `A` is symmetric, (3) every diagonal entry of `A` is `0`. * `Matrix.IsAdjMatrix.to_graph`: for `A : Matrix V V α` and `h : A.IsAdjMatrix`, `h.to_graph` is the simple graph induced by `A`. * `Matrix.compl`: for `A : Matrix V V α`, `A.compl` is supposed to be the adjacency matrix of the complement graph of the graph induced by `A`. * `SimpleGraph.adjMatrix`: the adjacency matrix of a `SimpleGraph`. * `SimpleGraph.adjMatrix_pow_apply_eq_card_walk`: each entry of the `n`th power of a graph's adjacency matrix counts the number of length-`n` walks between the corresponding pair of vertices. -/ open Matrix open Finset Matrix SimpleGraph variable {V α β : Type*} namespace Matrix /-- `A : Matrix V V α` is qualified as an "adjacency matrix" if (1) every entry of `A` is `0` or `1`, (2) `A` is symmetric, (3) every diagonal entry of `A` is `0`. -/ structure IsAdjMatrix [Zero α] [One α] (A : Matrix V V α) : Prop where zero_or_one : ∀ i j, A i j = 0 ∨ A i j = 1 := by aesop symm : A.IsSymm := by aesop apply_diag : ∀ i, A i i = 0 := by aesop #align matrix.is_adj_matrix Matrix.IsAdjMatrix namespace IsAdjMatrix variable {A : Matrix V V α} @[simp] theorem apply_diag_ne [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i : V) : ¬A i i = 1 := by simp [h.apply_diag i] #align matrix.is_adj_matrix.apply_diag_ne Matrix.IsAdjMatrix.apply_diag_ne @[simp] theorem apply_ne_one_iff [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i j : V) : ¬A i j = 1 ↔ A i j = 0 := by obtain h | h := h.zero_or_one i j <;> simp [h] #align matrix.is_adj_matrix.apply_ne_one_iff Matrix.IsAdjMatrix.apply_ne_one_iff @[simp]
Mathlib/Combinatorics/SimpleGraph/AdjMatrix.lean
74
75
theorem apply_ne_zero_iff [MulZeroOneClass α] [Nontrivial α] (h : IsAdjMatrix A) (i j : V) : ¬A i j = 0 ↔ A i j = 1 := by
rw [← apply_ne_one_iff h, Classical.not_not]
/- Copyright (c) 2023 Felix Weilacher. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Felix Weilacher -/ import Mathlib.Topology.MetricSpace.PiNat #align_import topology.metric_space.cantor_scheme from "leanprover-community/mathlib"@"49b7f94aab3a3bdca1f9f34c5d818afb253b3993" /-! # (Topological) Schemes and their induced maps In topology, and especially descriptive set theory, one often constructs functions `(ℕ → β) → α`, where α is some topological space and β is a discrete space, as an appropriate limit of some map `List β → Set α`. We call the latter type of map a "`β`-scheme on `α`". This file develops the basic, abstract theory of these schemes and the functions they induce. ## Main Definitions * `CantorScheme.inducedMap A` : The aforementioned "limit" of a scheme `A : List β → Set α`. This is a partial function from `ℕ → β` to `a`, implemented here as an object of type `Σ s : Set (ℕ → β), s → α`. That is, `(inducedMap A).1` is the domain and `(inducedMap A).2` is the function. ## Implementation Notes We consider end-appending to be the fundamental way to build lists (say on `β`) inductively, as this interacts better with the topology on `ℕ → β`. As a result, functions like `List.get?` or `Stream'.take` do not have their intended meaning in this file. See instead `PiNat.res`. ## References * [kechris1995] (Chapters 6-7) ## Tags scheme, cantor scheme, lusin scheme, approximation. -/ namespace CantorScheme open List Function Filter Set PiNat open scoped Classical open Topology variable {β α : Type*} (A : List β → Set α) /-- From a `β`-scheme on `α` `A`, we define a partial function from `(ℕ → β)` to `α` which sends each infinite sequence `x` to an element of the intersection along the branch corresponding to `x`, if it exists. We call this the map induced by the scheme. -/ noncomputable def inducedMap : Σs : Set (ℕ → β), s → α := ⟨fun x => Set.Nonempty (⋂ n : ℕ, A (res x n)), fun x => x.property.some⟩ #align cantor_scheme.induced_map CantorScheme.inducedMap section Topology /-- A scheme is antitone if each set contains its children. -/ protected def Antitone : Prop := ∀ l : List β, ∀ a : β, A (a :: l) ⊆ A l #align cantor_scheme.antitone CantorScheme.Antitone /-- A useful strengthening of being antitone is to require that each set contains the closure of each of its children. -/ def ClosureAntitone [TopologicalSpace α] : Prop := ∀ l : List β, ∀ a : β, closure (A (a :: l)) ⊆ A l #align cantor_scheme.closure_antitone CantorScheme.ClosureAntitone /-- A scheme is disjoint if the children of each set of pairwise disjoint. -/ protected def Disjoint : Prop := ∀ l : List β, Pairwise fun a b => Disjoint (A (a :: l)) (A (b :: l)) #align cantor_scheme.disjoint CantorScheme.Disjoint variable {A} /-- If `x` is in the domain of the induced map of a scheme `A`, its image under this map is in each set along the corresponding branch. -/
Mathlib/Topology/MetricSpace/CantorScheme.lean
83
86
theorem map_mem (x : (inducedMap A).1) (n : ℕ) : (inducedMap A).2 x ∈ A (res x n) := by
have := x.property.some_mem rw [mem_iInter] at this exact this n
/- Copyright (c) 2021 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov -/ import Mathlib.MeasureTheory.Function.L1Space import Mathlib.Analysis.NormedSpace.IndicatorFunction #align_import measure_theory.integral.integrable_on from "leanprover-community/mathlib"@"8b8ba04e2f326f3f7cf24ad129beda58531ada61" /-! # Functions integrable on a set and at a filter We define `IntegrableOn f s μ := Integrable f (μ.restrict s)` and prove theorems like `integrableOn_union : IntegrableOn f (s ∪ t) μ ↔ IntegrableOn f s μ ∧ IntegrableOn f t μ`. Next we define a predicate `IntegrableAtFilter (f : α → E) (l : Filter α) (μ : Measure α)` saying that `f` is integrable at some set `s ∈ l` and prove that a measurable function is integrable at `l` with respect to `μ` provided that `f` is bounded above at `l ⊓ ae μ` and `μ` is finite at `l`. -/ noncomputable section open Set Filter TopologicalSpace MeasureTheory Function open scoped Classical Topology Interval Filter ENNReal MeasureTheory variable {α β E F : Type*} [MeasurableSpace α] section variable [TopologicalSpace β] {l l' : Filter α} {f g : α → β} {μ ν : Measure α} /-- A function `f` is strongly measurable at a filter `l` w.r.t. a measure `μ` if it is ae strongly measurable w.r.t. `μ.restrict s` for some `s ∈ l`. -/ def StronglyMeasurableAtFilter (f : α → β) (l : Filter α) (μ : Measure α := by volume_tac) := ∃ s ∈ l, AEStronglyMeasurable f (μ.restrict s) #align strongly_measurable_at_filter StronglyMeasurableAtFilter @[simp] theorem stronglyMeasurableAt_bot {f : α → β} : StronglyMeasurableAtFilter f ⊥ μ := ⟨∅, mem_bot, by simp⟩ #align strongly_measurable_at_bot stronglyMeasurableAt_bot protected theorem StronglyMeasurableAtFilter.eventually (h : StronglyMeasurableAtFilter f l μ) : ∀ᶠ s in l.smallSets, AEStronglyMeasurable f (μ.restrict s) := (eventually_smallSets' fun _ _ => AEStronglyMeasurable.mono_set).2 h #align strongly_measurable_at_filter.eventually StronglyMeasurableAtFilter.eventually protected theorem StronglyMeasurableAtFilter.filter_mono (h : StronglyMeasurableAtFilter f l μ) (h' : l' ≤ l) : StronglyMeasurableAtFilter f l' μ := let ⟨s, hsl, hs⟩ := h ⟨s, h' hsl, hs⟩ #align strongly_measurable_at_filter.filter_mono StronglyMeasurableAtFilter.filter_mono protected theorem MeasureTheory.AEStronglyMeasurable.stronglyMeasurableAtFilter (h : AEStronglyMeasurable f μ) : StronglyMeasurableAtFilter f l μ := ⟨univ, univ_mem, by rwa [Measure.restrict_univ]⟩ #align measure_theory.ae_strongly_measurable.strongly_measurable_at_filter MeasureTheory.AEStronglyMeasurable.stronglyMeasurableAtFilter theorem AeStronglyMeasurable.stronglyMeasurableAtFilter_of_mem {s} (h : AEStronglyMeasurable f (μ.restrict s)) (hl : s ∈ l) : StronglyMeasurableAtFilter f l μ := ⟨s, hl, h⟩ #align ae_strongly_measurable.strongly_measurable_at_filter_of_mem AeStronglyMeasurable.stronglyMeasurableAtFilter_of_mem protected theorem MeasureTheory.StronglyMeasurable.stronglyMeasurableAtFilter (h : StronglyMeasurable f) : StronglyMeasurableAtFilter f l μ := h.aestronglyMeasurable.stronglyMeasurableAtFilter #align measure_theory.strongly_measurable.strongly_measurable_at_filter MeasureTheory.StronglyMeasurable.stronglyMeasurableAtFilter end namespace MeasureTheory section NormedAddCommGroup theorem hasFiniteIntegral_restrict_of_bounded [NormedAddCommGroup E] {f : α → E} {s : Set α} {μ : Measure α} {C} (hs : μ s < ∞) (hf : ∀ᵐ x ∂μ.restrict s, ‖f x‖ ≤ C) : HasFiniteIntegral f (μ.restrict s) := haveI : IsFiniteMeasure (μ.restrict s) := ⟨by rwa [Measure.restrict_apply_univ]⟩ hasFiniteIntegral_of_bounded hf #align measure_theory.has_finite_integral_restrict_of_bounded MeasureTheory.hasFiniteIntegral_restrict_of_bounded variable [NormedAddCommGroup E] {f g : α → E} {s t : Set α} {μ ν : Measure α} /-- A function is `IntegrableOn` a set `s` if it is almost everywhere strongly measurable on `s` and if the integral of its pointwise norm over `s` is less than infinity. -/ def IntegrableOn (f : α → E) (s : Set α) (μ : Measure α := by volume_tac) : Prop := Integrable f (μ.restrict s) #align measure_theory.integrable_on MeasureTheory.IntegrableOn theorem IntegrableOn.integrable (h : IntegrableOn f s μ) : Integrable f (μ.restrict s) := h #align measure_theory.integrable_on.integrable MeasureTheory.IntegrableOn.integrable @[simp] theorem integrableOn_empty : IntegrableOn f ∅ μ := by simp [IntegrableOn, integrable_zero_measure] #align measure_theory.integrable_on_empty MeasureTheory.integrableOn_empty @[simp]
Mathlib/MeasureTheory/Integral/IntegrableOn.lean
103
104
theorem integrableOn_univ : IntegrableOn f univ μ ↔ Integrable f μ := by
rw [IntegrableOn, Measure.restrict_univ]
/- Copyright (c) 2017 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura -/ import Batteries.Data.DList import Mathlib.Mathport.Rename import Mathlib.Tactic.Cases #align_import data.dlist from "leanprover-community/lean"@"855e5b74e3a52a40552e8f067169d747d48743fd" /-! # Difference list This file provides a few results about `DList`, which is defined in `Batteries`. A difference list is a function that, given a list, returns the original content of the difference list prepended to the given list. It is useful to represent elements of a given type as `a₁ + ... + aₙ` where `+ : α → α → α` is any operation, without actually computing. This structure supports `O(1)` `append` and `push` operations on lists, making it useful for append-heavy uses such as logging and pretty printing. -/ universe u #align dlist Batteries.DList namespace Batteries.DList open Function variable {α : Type u} #align dlist.of_list Batteries.DList.ofList /-- Convert a lazily-evaluated `List` to a `DList` -/ def lazy_ofList (l : Thunk (List α)) : DList α := ⟨fun xs => l.get ++ xs, fun t => by simp⟩ #align dlist.lazy_of_list Batteries.DList.lazy_ofList #align dlist.to_list Batteries.DList.toList #align dlist.empty Batteries.DList.empty #align dlist.singleton Batteries.DList.singleton attribute [local simp] Function.comp #align dlist.cons Batteries.DList.cons #align dlist.concat Batteries.DList.push #align dlist.append Batteries.DList.append attribute [local simp] ofList toList empty singleton cons push append theorem toList_ofList (l : List α) : DList.toList (DList.ofList l) = l := by cases l; rfl; simp only [DList.toList, DList.ofList, List.cons_append, List.append_nil] #align dlist.to_list_of_list Batteries.DList.toList_ofList
Mathlib/Data/DList/Defs.lean
62
66
theorem ofList_toList (l : DList α) : DList.ofList (DList.toList l) = l := by
cases' l with app inv simp only [ofList, toList, mk.injEq] funext x rw [(inv x)]
/- Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Bhavik Mehta -/ import Mathlib.Data.Set.Equitable import Mathlib.Logic.Equiv.Fin import Mathlib.Order.Partition.Finpartition #align_import order.partition.equipartition from "leanprover-community/mathlib"@"b363547b3113d350d053abdf2884e9850a56b205" /-! # Finite equipartitions This file defines finite equipartitions, the partitions whose parts all are the same size up to a difference of `1`. ## Main declarations * `Finpartition.IsEquipartition`: Predicate for a `Finpartition` to be an equipartition. * `Finpartition.IsEquipartition.exists_partPreservingEquiv`: part-preserving enumeration of a finset equipped with an equipartition. Indices of elements in the same part are congruent modulo the number of parts. -/ open Finset Fintype namespace Finpartition variable {α : Type*} [DecidableEq α] {s t : Finset α} (P : Finpartition s) /-- An equipartition is a partition whose parts are all the same size, up to a difference of `1`. -/ def IsEquipartition : Prop := (P.parts : Set (Finset α)).EquitableOn card #align finpartition.is_equipartition Finpartition.IsEquipartition theorem isEquipartition_iff_card_parts_eq_average : P.IsEquipartition ↔ ∀ a : Finset α, a ∈ P.parts → a.card = s.card / P.parts.card ∨ a.card = s.card / P.parts.card + 1 := by simp_rw [IsEquipartition, Finset.equitableOn_iff, P.sum_card_parts] #align finpartition.is_equipartition_iff_card_parts_eq_average Finpartition.isEquipartition_iff_card_parts_eq_average variable {P} lemma not_isEquipartition : ¬P.IsEquipartition ↔ ∃ a ∈ P.parts, ∃ b ∈ P.parts, b.card + 1 < a.card := Set.not_equitableOn theorem _root_.Set.Subsingleton.isEquipartition (h : (P.parts : Set (Finset α)).Subsingleton) : P.IsEquipartition := Set.Subsingleton.equitableOn h _ #align finpartition.set.subsingleton.is_equipartition Set.Subsingleton.isEquipartition theorem IsEquipartition.card_parts_eq_average (hP : P.IsEquipartition) (ht : t ∈ P.parts) : t.card = s.card / P.parts.card ∨ t.card = s.card / P.parts.card + 1 := P.isEquipartition_iff_card_parts_eq_average.1 hP _ ht #align finpartition.is_equipartition.card_parts_eq_average Finpartition.IsEquipartition.card_parts_eq_average theorem IsEquipartition.card_part_eq_average_iff (hP : P.IsEquipartition) (ht : t ∈ P.parts) : t.card = s.card / P.parts.card ↔ t.card ≠ s.card / P.parts.card + 1 := by have a := hP.card_parts_eq_average ht have b : ¬(t.card = s.card / P.parts.card ∧ t.card = s.card / P.parts.card + 1) := by by_contra h; exact absurd (h.1 ▸ h.2) (lt_add_one _).ne tauto theorem IsEquipartition.average_le_card_part (hP : P.IsEquipartition) (ht : t ∈ P.parts) : s.card / P.parts.card ≤ t.card := by rw [← P.sum_card_parts] exact Finset.EquitableOn.le hP ht #align finpartition.is_equipartition.average_le_card_part Finpartition.IsEquipartition.average_le_card_part theorem IsEquipartition.card_part_le_average_add_one (hP : P.IsEquipartition) (ht : t ∈ P.parts) : t.card ≤ s.card / P.parts.card + 1 := by rw [← P.sum_card_parts] exact Finset.EquitableOn.le_add_one hP ht #align finpartition.is_equipartition.card_part_le_average_add_one Finpartition.IsEquipartition.card_part_le_average_add_one theorem IsEquipartition.filter_ne_average_add_one_eq_average (hP : P.IsEquipartition) : P.parts.filter (fun p ↦ ¬p.card = s.card / P.parts.card + 1) = P.parts.filter (fun p ↦ p.card = s.card / P.parts.card) := by ext p simp only [mem_filter, and_congr_right_iff] exact fun hp ↦ (hP.card_part_eq_average_iff hp).symm /-- An equipartition of a finset with `n` elements into `k` parts has `n % k` parts of size `n / k + 1`. -/
Mathlib/Order/Partition/Equipartition.lean
89
100
theorem IsEquipartition.card_large_parts_eq_mod (hP : P.IsEquipartition) : (P.parts.filter fun p ↦ p.card = s.card / P.parts.card + 1).card = s.card % P.parts.card := by
have z := P.sum_card_parts rw [← sum_filter_add_sum_filter_not (s := P.parts) (p := fun x ↦ x.card = s.card / P.parts.card + 1), hP.filter_ne_average_add_one_eq_average, sum_const_nat (m := s.card / P.parts.card + 1) (by simp), sum_const_nat (m := s.card / P.parts.card) (by simp), ← hP.filter_ne_average_add_one_eq_average, mul_add, add_comm, ← add_assoc, ← add_mul, mul_one, add_comm (Finset.card _), filter_card_add_filter_neg_card_eq_card, add_comm] at z rw [← add_left_inj, Nat.mod_add_div, z]
/- 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.Set.Image import Mathlib.Data.Set.Lattice #align_import data.set.sigma from "leanprover-community/mathlib"@"2258b40dacd2942571c8ce136215350c702dc78f" /-! # Sets in sigma types This file defines `Set.sigma`, the indexed sum of sets. -/ namespace Set variable {ι ι' : Type*} {α β : ι → Type*} {s s₁ s₂ : Set ι} {t t₁ t₂ : ∀ i, Set (α i)} {u : Set (Σ i, α i)} {x : Σ i, α i} {i j : ι} {a : α i} @[simp]
Mathlib/Data/Set/Sigma.lean
23
28
theorem range_sigmaMk (i : ι) : range (Sigma.mk i : α i → Sigma α) = Sigma.fst ⁻¹' {i} := by
apply Subset.antisymm · rintro _ ⟨b, rfl⟩ simp · rintro ⟨x, y⟩ (rfl | _) exact mem_range_self y
/- Copyright (c) 2023 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Calculus.LineDeriv.Basic import Mathlib.Analysis.Calculus.FDeriv.Measurable /-! # Measurability of the line derivative We prove in `measurable_lineDeriv` that the line derivative of a function (with respect to a locally compact scalar field) is measurable, provided the function is continuous. In `measurable_lineDeriv_uncurry`, assuming additionally that the source space is second countable, we show that `(x, v) ↦ lineDeriv 𝕜 f x v` is also measurable. An assumption such as continuity is necessary, as otherwise one could alternate in a non-measurable way between differentiable and non-differentiable functions along the various lines directed by `v`. -/ open MeasureTheory variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [LocallyCompactSpace 𝕜] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] [MeasurableSpace E] [OpensMeasurableSpace E] {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F] [CompleteSpace F] {f : E → F} {v : E} /-! Measurability of the line derivative `lineDeriv 𝕜 f x v` with respect to a fixed direction `v`. -/ theorem measurableSet_lineDifferentiableAt (hf : Continuous f) : MeasurableSet {x : E | LineDifferentiableAt 𝕜 f x v} := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by apply hf.comp; continuity exact measurable_prod_mk_right (measurableSet_of_differentiableAt_with_param 𝕜 hg) theorem measurable_lineDeriv [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) : Measurable (fun x ↦ lineDeriv 𝕜 f x v) := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by apply hf.comp; continuity exact (measurable_deriv_with_param hg).comp measurable_prod_mk_right theorem stronglyMeasurable_lineDeriv [SecondCountableTopologyEither E F] (hf : Continuous f) : StronglyMeasurable (fun x ↦ lineDeriv 𝕜 f x v) := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by apply hf.comp; continuity exact (stronglyMeasurable_deriv_with_param hg).comp_measurable measurable_prod_mk_right theorem aemeasurable_lineDeriv [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) (μ : Measure E) : AEMeasurable (fun x ↦ lineDeriv 𝕜 f x v) μ := (measurable_lineDeriv hf).aemeasurable theorem aestronglyMeasurable_lineDeriv [SecondCountableTopologyEither E F] (hf : Continuous f) (μ : Measure E) : AEStronglyMeasurable (fun x ↦ lineDeriv 𝕜 f x v) μ := (stronglyMeasurable_lineDeriv hf).aestronglyMeasurable /-! Measurability of the line derivative `lineDeriv 𝕜 f x v` when varying both `x` and `v`. For this, we need an additional second countability assumption on `E` to make sure that open sets are measurable in `E × E`. -/ variable [SecondCountableTopology E] theorem measurableSet_lineDifferentiableAt_uncurry (hf : Continuous f) : MeasurableSet {p : E × E | LineDifferentiableAt 𝕜 f p.1 p.2} := by borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) have M_meas : MeasurableSet {q : (E × E) × 𝕜 | DifferentiableAt 𝕜 (g q.1) q.2} := measurableSet_of_differentiableAt_with_param 𝕜 this exact measurable_prod_mk_right M_meas theorem measurable_lineDeriv_uncurry [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) : Measurable (fun (p : E × E) ↦ lineDeriv 𝕜 f p.1 p.2) := by borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) exact (measurable_deriv_with_param this).comp measurable_prod_mk_right
Mathlib/Analysis/Calculus/LineDeriv/Measurable.lean
92
99
theorem stronglyMeasurable_lineDeriv_uncurry (hf : Continuous f) : StronglyMeasurable (fun (p : E × E) ↦ lineDeriv 𝕜 f p.1 p.2) := by
borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) exact (stronglyMeasurable_deriv_with_param this).comp_measurable measurable_prod_mk_right
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel, Rémy Degenne, David Loeffler -/ import Mathlib.Analysis.SpecialFunctions.Complex.Log #align_import analysis.special_functions.pow.complex from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8" /-! # Power function on `ℂ` We construct the power functions `x ^ y`, where `x` and `y` are complex numbers. -/ open scoped Classical open Real Topology Filter ComplexConjugate Finset Set namespace Complex /-- The complex power function `x ^ y`, given by `x ^ y = exp(y log x)` (where `log` is the principal determination of the logarithm), unless `x = 0` where one sets `0 ^ 0 = 1` and `0 ^ y = 0` for `y ≠ 0`. -/ noncomputable def cpow (x y : ℂ) : ℂ := if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) #align complex.cpow Complex.cpow noncomputable instance : Pow ℂ ℂ := ⟨cpow⟩ @[simp] theorem cpow_eq_pow (x y : ℂ) : cpow x y = x ^ y := rfl #align complex.cpow_eq_pow Complex.cpow_eq_pow theorem cpow_def (x y : ℂ) : x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := rfl #align complex.cpow_def Complex.cpow_def theorem cpow_def_of_ne_zero {x : ℂ} (hx : x ≠ 0) (y : ℂ) : x ^ y = exp (log x * y) := if_neg hx #align complex.cpow_def_of_ne_zero Complex.cpow_def_of_ne_zero @[simp] theorem cpow_zero (x : ℂ) : x ^ (0 : ℂ) = 1 := by simp [cpow_def] #align complex.cpow_zero Complex.cpow_zero @[simp] theorem cpow_eq_zero_iff (x y : ℂ) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by simp only [cpow_def] split_ifs <;> simp [*, exp_ne_zero] #align complex.cpow_eq_zero_iff Complex.cpow_eq_zero_iff @[simp] theorem zero_cpow {x : ℂ} (h : x ≠ 0) : (0 : ℂ) ^ x = 0 := by simp [cpow_def, *] #align complex.zero_cpow Complex.zero_cpow theorem zero_cpow_eq_iff {x : ℂ} {a : ℂ} : (0 : ℂ) ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by constructor · intro hyp simp only [cpow_def, eq_self_iff_true, if_true] at hyp by_cases h : x = 0 · subst h simp only [if_true, eq_self_iff_true] at hyp right exact ⟨rfl, hyp.symm⟩ · rw [if_neg h] at hyp left exact ⟨h, hyp.symm⟩ · rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩) · exact zero_cpow h · exact cpow_zero _ #align complex.zero_cpow_eq_iff Complex.zero_cpow_eq_iff theorem eq_zero_cpow_iff {x : ℂ} {a : ℂ} : a = (0 : ℂ) ^ x ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by rw [← zero_cpow_eq_iff, eq_comm] #align complex.eq_zero_cpow_iff Complex.eq_zero_cpow_iff @[simp] theorem cpow_one (x : ℂ) : x ^ (1 : ℂ) = x := if hx : x = 0 then by simp [hx, cpow_def] else by rw [cpow_def, if_neg (one_ne_zero : (1 : ℂ) ≠ 0), if_neg hx, mul_one, exp_log hx] #align complex.cpow_one Complex.cpow_one @[simp] theorem one_cpow (x : ℂ) : (1 : ℂ) ^ x = 1 := by rw [cpow_def] split_ifs <;> simp_all [one_ne_zero] #align complex.one_cpow Complex.one_cpow theorem cpow_add {x : ℂ} (y z : ℂ) (hx : x ≠ 0) : x ^ (y + z) = x ^ y * x ^ z := by simp only [cpow_def, ite_mul, boole_mul, mul_ite, mul_boole] simp_all [exp_add, mul_add] #align complex.cpow_add Complex.cpow_add theorem cpow_mul {x y : ℂ} (z : ℂ) (h₁ : -π < (log x * y).im) (h₂ : (log x * y).im ≤ π) : x ^ (y * z) = (x ^ y) ^ z := by simp only [cpow_def] split_ifs <;> simp_all [exp_ne_zero, log_exp h₁ h₂, mul_assoc] #align complex.cpow_mul Complex.cpow_mul theorem cpow_neg (x y : ℂ) : x ^ (-y) = (x ^ y)⁻¹ := by simp only [cpow_def, neg_eq_zero, mul_neg] split_ifs <;> simp [exp_neg] #align complex.cpow_neg Complex.cpow_neg
Mathlib/Analysis/SpecialFunctions/Pow/Complex.lean
107
108
theorem cpow_sub {x : ℂ} (y z : ℂ) (hx : x ≠ 0) : x ^ (y - z) = x ^ y / x ^ z := by
rw [sub_eq_add_neg, cpow_add _ _ hx, cpow_neg, div_eq_mul_inv]
/- Copyright (c) 2022 Kexing Ying. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kexing Ying, Bhavik Mehta -/ import Mathlib.Probability.ConditionalProbability import Mathlib.MeasureTheory.Measure.Count #align_import probability.cond_count from "leanprover-community/mathlib"@"117e93f82b5f959f8193857370109935291f0cc4" /-! # Classical probability The classical formulation of probability states that the probability of an event occurring in a finite probability space is the ratio of that event to all possible events. This notion can be expressed with measure theory using the counting measure. In particular, given the sets `s` and `t`, we define the probability of `t` occurring in `s` to be `|s|⁻¹ * |s ∩ t|`. With this definition, we recover the probability over the entire sample space when `s = Set.univ`. Classical probability is often used in combinatorics and we prove some useful lemmas in this file for that purpose. ## Main definition * `ProbabilityTheory.condCount`: given a set `s`, `condCount s` is the counting measure conditioned on `s`. This is a probability measure when `s` is finite and nonempty. ## Notes The original aim of this file is to provide a measure theoretic method of describing the probability an element of a set `s` satisfies some predicate `P`. Our current formulation still allow us to describe this by abusing the definitional equality of sets and predicates by simply writing `condCount s P`. We should avoid this however as none of the lemmas are written for predicates. -/ noncomputable section open ProbabilityTheory open MeasureTheory MeasurableSpace namespace ProbabilityTheory variable {Ω : Type*} [MeasurableSpace Ω] /-- Given a set `s`, `condCount s` is the counting measure conditioned on `s`. In particular, `condCount s t` is the proportion of `s` that is contained in `t`. This is a probability measure when `s` is finite and nonempty and is given by `ProbabilityTheory.condCount_isProbabilityMeasure`. -/ def condCount (s : Set Ω) : Measure Ω := Measure.count[|s] #align probability_theory.cond_count ProbabilityTheory.condCount @[simp] theorem condCount_empty_meas : (condCount ∅ : Measure Ω) = 0 := by simp [condCount] #align probability_theory.cond_count_empty_meas ProbabilityTheory.condCount_empty_meas theorem condCount_empty {s : Set Ω} : condCount s ∅ = 0 := by simp #align probability_theory.cond_count_empty ProbabilityTheory.condCount_empty
Mathlib/Probability/CondCount.lean
65
67
theorem finite_of_condCount_ne_zero {s t : Set Ω} (h : condCount s t ≠ 0) : s.Finite := by
by_contra hs' simp [condCount, cond, Measure.count_apply_infinite hs'] at h
/- Copyright (c) 2022 Markus Himmel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Markus Himmel -/ import Mathlib.CategoryTheory.Generator import Mathlib.CategoryTheory.Preadditive.Yoneda.Basic #align_import category_theory.preadditive.generator from "leanprover-community/mathlib"@"09f981f72d43749f1fa072deade828d9c1e185bb" /-! # Separators in preadditive categories This file contains characterizations of separating sets and objects that are valid in all preadditive categories. -/ universe v u open CategoryTheory Opposite namespace CategoryTheory variable {C : Type u} [Category.{v} C] [Preadditive C] theorem Preadditive.isSeparating_iff (𝒢 : Set C) : IsSeparating 𝒢 ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : G ⟶ X), h ≫ f = 0) → f = 0 := ⟨fun h𝒢 X Y f hf => h𝒢 _ _ (by simpa only [Limits.comp_zero] using hf), fun h𝒢 X Y f g hfg => sub_eq_zero.1 <| h𝒢 _ (by simpa only [Preadditive.comp_sub, sub_eq_zero] using hfg)⟩ #align category_theory.preadditive.is_separating_iff CategoryTheory.Preadditive.isSeparating_iff theorem Preadditive.isCoseparating_iff (𝒢 : Set C) : IsCoseparating 𝒢 ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ G ∈ 𝒢, ∀ (h : Y ⟶ G), f ≫ h = 0) → f = 0 := ⟨fun h𝒢 X Y f hf => h𝒢 _ _ (by simpa only [Limits.zero_comp] using hf), fun h𝒢 X Y f g hfg => sub_eq_zero.1 <| h𝒢 _ (by simpa only [Preadditive.sub_comp, sub_eq_zero] using hfg)⟩ #align category_theory.preadditive.is_coseparating_iff CategoryTheory.Preadditive.isCoseparating_iff theorem Preadditive.isSeparator_iff (G : C) : IsSeparator G ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : G ⟶ X, h ≫ f = 0) → f = 0 := ⟨fun hG X Y f hf => hG.def _ _ (by simpa only [Limits.comp_zero] using hf), fun hG => (isSeparator_def _).2 fun X Y f g hfg => sub_eq_zero.1 <| hG _ (by simpa only [Preadditive.comp_sub, sub_eq_zero] using hfg)⟩ #align category_theory.preadditive.is_separator_iff CategoryTheory.Preadditive.isSeparator_iff theorem Preadditive.isCoseparator_iff (G : C) : IsCoseparator G ↔ ∀ ⦃X Y : C⦄ (f : X ⟶ Y), (∀ h : Y ⟶ G, f ≫ h = 0) → f = 0 := ⟨fun hG X Y f hf => hG.def _ _ (by simpa only [Limits.zero_comp] using hf), fun hG => (isCoseparator_def _).2 fun X Y f g hfg => sub_eq_zero.1 <| hG _ (by simpa only [Preadditive.sub_comp, sub_eq_zero] using hfg)⟩ #align category_theory.preadditive.is_coseparator_iff CategoryTheory.Preadditive.isCoseparator_iff theorem isSeparator_iff_faithful_preadditiveCoyoneda (G : C) : IsSeparator G ↔ (preadditiveCoyoneda.obj (op G)).Faithful := by rw [isSeparator_iff_faithful_coyoneda_obj, ← whiskering_preadditiveCoyoneda, Functor.comp_obj, whiskeringRight_obj_obj] exact ⟨fun h => Functor.Faithful.of_comp _ (forget AddCommGroupCat), fun h => Functor.Faithful.comp _ _⟩ #align category_theory.is_separator_iff_faithful_preadditive_coyoneda CategoryTheory.isSeparator_iff_faithful_preadditiveCoyoneda
Mathlib/CategoryTheory/Preadditive/Generator.lean
62
66
theorem isSeparator_iff_faithful_preadditiveCoyonedaObj (G : C) : IsSeparator G ↔ (preadditiveCoyonedaObj (op G)).Faithful := by
rw [isSeparator_iff_faithful_preadditiveCoyoneda, preadditiveCoyoneda_obj] exact ⟨fun h => Functor.Faithful.of_comp _ (forget₂ _ AddCommGroupCat.{v}), fun h => Functor.Faithful.comp _ _⟩
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Yury Kudryashov -/ import Mathlib.MeasureTheory.Constructions.BorelSpace.Order #align_import measure_theory.constructions.borel_space.basic from "leanprover-community/mathlib"@"9f55d0d4363ae59948c33864cbc52e0b12e0e8ce" /-! # Borel (measurable) spaces ℝ, ℝ≥0, ℝ≥0∞ ## Main statements * `borel_eq_generateFrom_Ixx_rat` (where Ixx is one of {Ioo, Ioi, Iio, Ici, Iic): the Borel sigma algebra on ℝ is generated by intervals with rational endpoints; * `isPiSystem_Ixx_rat` (where Ixx is one of {Ioo, Ioi, Iio, Ici, Iic): intervals with rational endpoints form a pi system on ℝ; * `measurable_real_toNNReal`, `measurable_coe_nnreal_real`, `measurable_coe_nnreal_ennreal`, `ENNReal.measurable_ofReal`, `ENNReal.measurable_toReal`: measurability of various coercions between ℝ, ℝ≥0, and ℝ≥0∞; * `Measurable.real_toNNReal`, `Measurable.coe_nnreal_real`, `Measurable.coe_nnreal_ennreal`, `Measurable.ennreal_ofReal`, `Measurable.ennreal_toNNReal`, `Measurable.ennreal_toReal`: measurability of functions composed with various coercions between ℝ, ℝ≥0, and ℝ≥0∞ (also similar results for a.e.-measurability); * `Measurable.ennreal*` : measurability of special cases for arithmetic operations on `ℝ≥0∞`. -/ open Set Filter MeasureTheory MeasurableSpace open scoped Classical Topology NNReal ENNReal MeasureTheory universe u v w x y variable {α β γ δ : Type*} {ι : Sort y} {s t u : Set α} namespace Real theorem borel_eq_generateFrom_Ioo_rat : borel ℝ = .generateFrom (⋃ (a : ℚ) (b : ℚ) (_ : a < b), {Ioo (a : ℝ) (b : ℝ)}) := isTopologicalBasis_Ioo_rat.borel_eq_generateFrom #align real.borel_eq_generate_from_Ioo_rat Real.borel_eq_generateFrom_Ioo_rat theorem borel_eq_generateFrom_Iio_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Iio (a : ℝ)}) := by rw [borel_eq_generateFrom_Iio] refine le_antisymm (generateFrom_le ?_) (generateFrom_mono <| iUnion_subset fun q ↦ singleton_subset_iff.mpr <| mem_range_self _) rintro _ ⟨a, rfl⟩ have : IsLUB (range ((↑) : ℚ → ℝ) ∩ Iio a) a := by simp [isLUB_iff_le_iff, mem_upperBounds, ← le_iff_forall_rat_lt_imp_le] rw [← this.biUnion_Iio_eq, ← image_univ, ← image_inter_preimage, univ_inter, biUnion_image] exact MeasurableSet.biUnion (to_countable _) fun b _ => GenerateMeasurable.basic (Iio (b : ℝ)) (by simp) theorem borel_eq_generateFrom_Ioi_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Ioi (a : ℝ)}) := by rw [borel_eq_generateFrom_Ioi] refine le_antisymm (generateFrom_le ?_) (generateFrom_mono <| iUnion_subset fun q ↦ singleton_subset_iff.mpr <| mem_range_self _) rintro _ ⟨a, rfl⟩ have : IsGLB (range ((↑) : ℚ → ℝ) ∩ Ioi a) a := by simp [isGLB_iff_le_iff, mem_lowerBounds, ← le_iff_forall_lt_rat_imp_le] rw [← this.biUnion_Ioi_eq, ← image_univ, ← image_inter_preimage, univ_inter, biUnion_image] exact MeasurableSet.biUnion (to_countable _) fun b _ => GenerateMeasurable.basic (Ioi (b : ℝ)) (by simp) theorem borel_eq_generateFrom_Iic_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Iic (a : ℝ)}) := by rw [borel_eq_generateFrom_Ioi_rat, iUnion_singleton_eq_range, iUnion_singleton_eq_range] refine le_antisymm (generateFrom_le ?_) (generateFrom_le ?_) <;> rintro _ ⟨q, rfl⟩ <;> dsimp only <;> [rw [← compl_Iic]; rw [← compl_Ioi]] <;> exact MeasurableSet.compl (GenerateMeasurable.basic _ (mem_range_self q)) theorem borel_eq_generateFrom_Ici_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Ici (a : ℝ)}) := by rw [borel_eq_generateFrom_Iio_rat, iUnion_singleton_eq_range, iUnion_singleton_eq_range] refine le_antisymm (generateFrom_le ?_) (generateFrom_le ?_) <;> rintro _ ⟨q, rfl⟩ <;> dsimp only <;> [rw [← compl_Ici]; rw [← compl_Iio]] <;> exact MeasurableSet.compl (GenerateMeasurable.basic _ (mem_range_self q))
Mathlib/MeasureTheory/Constructions/BorelSpace/Real.lean
84
88
theorem isPiSystem_Ioo_rat : IsPiSystem (⋃ (a : ℚ) (b : ℚ) (_ : a < b), {Ioo (a : ℝ) (b : ℝ)}) := by
convert isPiSystem_Ioo ((↑) : ℚ → ℝ) ((↑) : ℚ → ℝ) ext x simp [eq_comm]
/- Copyright (c) 2017 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Oliver Nash -/ import Mathlib.Data.Finset.Card #align_import data.finset.prod from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853" /-! # Finsets in product types This file defines finset constructions on the product type `α × β`. Beware not to confuse with the `Finset.prod` operation which computes the multiplicative product. ## Main declarations * `Finset.product`: Turns `s : Finset α`, `t : Finset β` into their product in `Finset (α × β)`. * `Finset.diag`: For `s : Finset α`, `s.diag` is the `Finset (α × α)` of pairs `(a, a)` with `a ∈ s`. * `Finset.offDiag`: For `s : Finset α`, `s.offDiag` is the `Finset (α × α)` of pairs `(a, b)` with `a, b ∈ s` and `a ≠ b`. -/ assert_not_exists MonoidWithZero open Multiset variable {α β γ : Type*} namespace Finset /-! ### prod -/ section Prod variable {s s' : Finset α} {t t' : Finset β} {a : α} {b : β} /-- `product s t` is the set of pairs `(a, b)` such that `a ∈ s` and `b ∈ t`. -/ protected def product (s : Finset α) (t : Finset β) : Finset (α × β) := ⟨_, s.nodup.product t.nodup⟩ #align finset.product Finset.product instance instSProd : SProd (Finset α) (Finset β) (Finset (α × β)) where sprod := Finset.product @[simp] theorem product_val : (s ×ˢ t).1 = s.1 ×ˢ t.1 := rfl #align finset.product_val Finset.product_val @[simp] theorem mem_product {p : α × β} : p ∈ s ×ˢ t ↔ p.1 ∈ s ∧ p.2 ∈ t := Multiset.mem_product #align finset.mem_product Finset.mem_product theorem mk_mem_product (ha : a ∈ s) (hb : b ∈ t) : (a, b) ∈ s ×ˢ t := mem_product.2 ⟨ha, hb⟩ #align finset.mk_mem_product Finset.mk_mem_product @[simp, norm_cast] theorem coe_product (s : Finset α) (t : Finset β) : (↑(s ×ˢ t) : Set (α × β)) = (s : Set α) ×ˢ t := Set.ext fun _ => Finset.mem_product #align finset.coe_product Finset.coe_product theorem subset_product_image_fst [DecidableEq α] : (s ×ˢ t).image Prod.fst ⊆ s := fun i => by simp (config := { contextual := true }) [mem_image] #align finset.subset_product_image_fst Finset.subset_product_image_fst theorem subset_product_image_snd [DecidableEq β] : (s ×ˢ t).image Prod.snd ⊆ t := fun i => by simp (config := { contextual := true }) [mem_image] #align finset.subset_product_image_snd Finset.subset_product_image_snd theorem product_image_fst [DecidableEq α] (ht : t.Nonempty) : (s ×ˢ t).image Prod.fst = s := by ext i simp [mem_image, ht.exists_mem] #align finset.product_image_fst Finset.product_image_fst
Mathlib/Data/Finset/Prod.lean
81
83
theorem product_image_snd [DecidableEq β] (ht : s.Nonempty) : (s ×ˢ t).image Prod.snd = t := by
ext i simp [mem_image, ht.exists_mem]
/- Copyright (c) 2021 Vladimir Goryachev. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Vladimir Goryachev, Kyle Miller, Scott Morrison, Eric Rodriguez -/ import Mathlib.SetTheory.Cardinal.Basic import Mathlib.Tactic.Ring #align_import data.nat.count from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988" /-! # Counting on ℕ This file defines the `count` function, which gives, for any predicate on the natural numbers, "how many numbers under `k` satisfy this predicate?". We then prove several expected lemmas about `count`, relating it to the cardinality of other objects, and helping to evaluate it for specific `k`. -/ open Finset namespace Nat variable (p : ℕ → Prop) section Count variable [DecidablePred p] /-- Count the number of naturals `k < n` satisfying `p k`. -/ def count (n : ℕ) : ℕ := (List.range n).countP p #align nat.count Nat.count @[simp] theorem count_zero : count p 0 = 0 := by rw [count, List.range_zero, List.countP, List.countP.go] #align nat.count_zero Nat.count_zero /-- A fintype instance for the set relevant to `Nat.count`. Locally an instance in locale `count` -/ def CountSet.fintype (n : ℕ) : Fintype { i // i < n ∧ p i } := by apply Fintype.ofFinset ((Finset.range n).filter p) intro x rw [mem_filter, mem_range] rfl #align nat.count_set.fintype Nat.CountSet.fintype scoped[Count] attribute [instance] Nat.CountSet.fintype open Count theorem count_eq_card_filter_range (n : ℕ) : count p n = ((range n).filter p).card := by rw [count, List.countP_eq_length_filter] rfl #align nat.count_eq_card_filter_range Nat.count_eq_card_filter_range /-- `count p n` can be expressed as the cardinality of `{k // k < n ∧ p k}`. -/ theorem count_eq_card_fintype (n : ℕ) : count p n = Fintype.card { k : ℕ // k < n ∧ p k } := by rw [count_eq_card_filter_range, ← Fintype.card_ofFinset, ← CountSet.fintype] rfl #align nat.count_eq_card_fintype Nat.count_eq_card_fintype theorem count_succ (n : ℕ) : count p (n + 1) = count p n + if p n then 1 else 0 := by split_ifs with h <;> simp [count, List.range_succ, h] #align nat.count_succ Nat.count_succ @[mono] theorem count_monotone : Monotone (count p) := monotone_nat_of_le_succ fun n ↦ by by_cases h : p n <;> simp [count_succ, h] #align nat.count_monotone Nat.count_monotone theorem count_add (a b : ℕ) : count p (a + b) = count p a + count (fun k ↦ p (a + k)) b := by have : Disjoint ((range a).filter p) (((range b).map <| addLeftEmbedding a).filter p) := by apply disjoint_filter_filter rw [Finset.disjoint_left] simp_rw [mem_map, mem_range, addLeftEmbedding_apply] rintro x hx ⟨c, _, rfl⟩ exact (self_le_add_right _ _).not_lt hx simp_rw [count_eq_card_filter_range, range_add, filter_union, card_union_of_disjoint this, filter_map, addLeftEmbedding, card_map] rfl #align nat.count_add Nat.count_add
Mathlib/Data/Nat/Count.lean
86
88
theorem count_add' (a b : ℕ) : count p (a + b) = count (fun k ↦ p (k + b)) a + count p b := by
rw [add_comm, count_add, add_comm] simp_rw [add_comm b]
/- 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] theorem volume_Ioo {a b : ℝ} : volume (Ioo a b) = ofReal (b - a) := by simp [volume_val] #align real.volume_Ioo Real.volume_Ioo @[simp] theorem volume_Ioc {a b : ℝ} : volume (Ioc a b) = ofReal (b - a) := by simp [volume_val] #align real.volume_Ioc Real.volume_Ioc -- @[simp] -- Porting note (#10618): simp can prove this theorem volume_singleton {a : ℝ} : volume ({a} : Set ℝ) = 0 := by simp [volume_val] #align real.volume_singleton Real.volume_singleton -- @[simp] -- Porting note (#10618): simp can prove this, after mathlib4#4628 theorem volume_univ : volume (univ : Set ℝ) = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => calc (r : ℝ≥0∞) = volume (Icc (0 : ℝ) r) := by simp _ ≤ volume univ := measure_mono (subset_univ _) #align real.volume_univ Real.volume_univ @[simp]
Mathlib/MeasureTheory/Measure/Lebesgue/Basic.lean
108
109
theorem volume_ball (a r : ℝ) : volume (Metric.ball a r) = ofReal (2 * r) := by
rw [ball_eq_Ioo, volume_Ioo, ← sub_add, add_sub_cancel_left, two_mul]
/- Copyright (c) 2021 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes -/ import Mathlib.Algebra.MvPolynomial.Equiv import Mathlib.Algebra.MvPolynomial.Supported import Mathlib.LinearAlgebra.LinearIndependent import Mathlib.RingTheory.Adjoin.Basic import Mathlib.RingTheory.Algebraic import Mathlib.RingTheory.MvPolynomial.Basic #align_import ring_theory.algebraic_independent from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69" /-! # Algebraic Independence This file defines algebraic independence of a family of element of an `R` algebra. ## Main definitions * `AlgebraicIndependent` - `AlgebraicIndependent R x` states the family of elements `x` is algebraically independent over `R`, meaning that the canonical map out of the multivariable polynomial ring is injective. * `AlgebraicIndependent.repr` - The canonical map from the subalgebra generated by an algebraic independent family into the polynomial ring. ## References * [Stacks: Transcendence](https://stacks.math.columbia.edu/tag/030D) ## TODO Define the transcendence degree and show it is independent of the choice of a transcendence basis. ## Tags transcendence basis, transcendence degree, transcendence -/ noncomputable section open Function Set Subalgebra MvPolynomial Algebra open scoped Classical universe x u v w variable {ι : Type*} {ι' : Type*} (R : Type*) {K : Type*} variable {A : Type*} {A' A'' : Type*} {V : Type u} {V' : Type*} variable (x : ι → A) variable [CommRing R] [CommRing A] [CommRing A'] [CommRing A''] variable [Algebra R A] [Algebra R A'] [Algebra R A''] variable {a b : R} /-- `AlgebraicIndependent R x` states the family of elements `x` is algebraically independent over `R`, meaning that the canonical map out of the multivariable polynomial ring is injective. -/ def AlgebraicIndependent : Prop := Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A) #align algebraic_independent AlgebraicIndependent variable {R} {x} theorem algebraicIndependent_iff_ker_eq_bot : AlgebraicIndependent R x ↔ RingHom.ker (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A).toRingHom = ⊥ := RingHom.injective_iff_ker_eq_bot _ #align algebraic_independent_iff_ker_eq_bot algebraicIndependent_iff_ker_eq_bot theorem algebraicIndependent_iff : AlgebraicIndependent R x ↔ ∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 := injective_iff_map_eq_zero _ #align algebraic_independent_iff algebraicIndependent_iff theorem AlgebraicIndependent.eq_zero_of_aeval_eq_zero (h : AlgebraicIndependent R x) : ∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 := algebraicIndependent_iff.1 h #align algebraic_independent.eq_zero_of_aeval_eq_zero AlgebraicIndependent.eq_zero_of_aeval_eq_zero theorem algebraicIndependent_iff_injective_aeval : AlgebraicIndependent R x ↔ Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A) := Iff.rfl #align algebraic_independent_iff_injective_aeval algebraicIndependent_iff_injective_aeval @[simp] theorem algebraicIndependent_empty_type_iff [IsEmpty ι] : AlgebraicIndependent R x ↔ Injective (algebraMap R A) := by have : aeval x = (Algebra.ofId R A).comp (@isEmptyAlgEquiv R ι _ _).toAlgHom := by ext i exact IsEmpty.elim' ‹IsEmpty ι› i rw [AlgebraicIndependent, this, ← Injective.of_comp_iff' _ (@isEmptyAlgEquiv R ι _ _).bijective] rfl #align algebraic_independent_empty_type_iff algebraicIndependent_empty_type_iff namespace AlgebraicIndependent variable (hx : AlgebraicIndependent R x) theorem algebraMap_injective : Injective (algebraMap R A) := by simpa [Function.comp] using (Injective.of_comp_iff (algebraicIndependent_iff_injective_aeval.1 hx) MvPolynomial.C).2 (MvPolynomial.C_injective _ _) #align algebraic_independent.algebra_map_injective AlgebraicIndependent.algebraMap_injective theorem linearIndependent : LinearIndependent R x := by rw [linearIndependent_iff_injective_total] have : Finsupp.total ι A R x = (MvPolynomial.aeval x).toLinearMap.comp (Finsupp.total ι _ R X) := by ext simp rw [this] refine hx.comp ?_ rw [← linearIndependent_iff_injective_total] exact linearIndependent_X _ _ #align algebraic_independent.linear_independent AlgebraicIndependent.linearIndependent protected theorem injective [Nontrivial R] : Injective x := hx.linearIndependent.injective #align algebraic_independent.injective AlgebraicIndependent.injective theorem ne_zero [Nontrivial R] (i : ι) : x i ≠ 0 := hx.linearIndependent.ne_zero i #align algebraic_independent.ne_zero AlgebraicIndependent.ne_zero theorem comp (f : ι' → ι) (hf : Function.Injective f) : AlgebraicIndependent R (x ∘ f) := by intro p q simpa [aeval_rename, (rename_injective f hf).eq_iff] using @hx (rename f p) (rename f q) #align algebraic_independent.comp AlgebraicIndependent.comp theorem coe_range : AlgebraicIndependent R ((↑) : range x → A) := by simpa using hx.comp _ (rangeSplitting_injective x) #align algebraic_independent.coe_range AlgebraicIndependent.coe_range
Mathlib/RingTheory/AlgebraicIndependent.lean
138
149
theorem map {f : A →ₐ[R] A'} (hf_inj : Set.InjOn f (adjoin R (range x))) : AlgebraicIndependent R (f ∘ x) := by
have : aeval (f ∘ x) = f.comp (aeval x) := by ext; simp have h : ∀ p : MvPolynomial ι R, aeval x p ∈ (@aeval R _ _ _ _ _ ((↑) : range x → A)).range := by intro p rw [AlgHom.mem_range] refine ⟨MvPolynomial.rename (codRestrict x (range x) mem_range_self) p, ?_⟩ simp [Function.comp, aeval_rename] intro x y hxy rw [this] at hxy rw [adjoin_eq_range] at hf_inj exact hx (hf_inj (h x) (h y) hxy)
/- Copyright (c) 2020 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau -/ import Mathlib.Algebra.BigOperators.Pi import Mathlib.Algebra.BigOperators.Ring import Mathlib.Algebra.Order.BigOperators.Ring.Finset import Mathlib.Algebra.BigOperators.Fin import Mathlib.Algebra.Group.Submonoid.Membership import Mathlib.Data.Finsupp.Fin import Mathlib.Data.Finsupp.Indicator #align_import algebra.big_operators.finsupp from "leanprover-community/mathlib"@"842328d9df7e96fd90fc424e115679c15fb23a71" /-! # Big operators for finsupps This file contains theorems relevant to big operators in finitely supported functions. -/ noncomputable section open Finset Function variable {α ι γ A B C : Type*} [AddCommMonoid A] [AddCommMonoid B] [AddCommMonoid C] variable {t : ι → A → C} (h0 : ∀ i, t i 0 = 0) (h1 : ∀ i x y, t i (x + y) = t i x + t i y) variable {s : Finset α} {f : α → ι →₀ A} (i : ι) variable (g : ι →₀ A) (k : ι → A → γ → B) (x : γ) variable {β M M' N P G H R S : Type*} namespace Finsupp /-! ### Declarations about `Finsupp.sum` and `Finsupp.prod` In most of this section, the domain `β` is assumed to be an `AddMonoid`. -/ section SumProd /-- `prod f g` is the product of `g a (f a)` over the support of `f`. -/ @[to_additive "`sum f g` is the sum of `g a (f a)` over the support of `f`. "] def prod [Zero M] [CommMonoid N] (f : α →₀ M) (g : α → M → N) : N := ∏ a ∈ f.support, g a (f a) #align finsupp.prod Finsupp.prod #align finsupp.sum Finsupp.sum variable [Zero M] [Zero M'] [CommMonoid N] @[to_additive] theorem prod_of_support_subset (f : α →₀ M) {s : Finset α} (hs : f.support ⊆ s) (g : α → M → N) (h : ∀ i ∈ s, g i 0 = 1) : f.prod g = ∏ x ∈ s, g x (f x) := by refine Finset.prod_subset hs fun x hxs hx => h x hxs ▸ (congr_arg (g x) ?_) exact not_mem_support_iff.1 hx #align finsupp.prod_of_support_subset Finsupp.prod_of_support_subset #align finsupp.sum_of_support_subset Finsupp.sum_of_support_subset @[to_additive] theorem prod_fintype [Fintype α] (f : α →₀ M) (g : α → M → N) (h : ∀ i, g i 0 = 1) : f.prod g = ∏ i, g i (f i) := f.prod_of_support_subset (subset_univ _) g fun x _ => h x #align finsupp.prod_fintype Finsupp.prod_fintype #align finsupp.sum_fintype Finsupp.sum_fintype @[to_additive (attr := simp)]
Mathlib/Algebra/BigOperators/Finsupp.lean
69
75
theorem prod_single_index {a : α} {b : M} {h : α → M → N} (h_zero : h a 0 = 1) : (single a b).prod h = h a b := calc (single a b).prod h = ∏ x ∈ {a}, h x (single a b x) := prod_of_support_subset _ support_single_subset h fun x hx => (mem_singleton.1 hx).symm ▸ h_zero _ = h a b := by
simp
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro -/ import Mathlib.Algebra.MonoidAlgebra.Degree import Mathlib.Algebra.MvPolynomial.Rename import Mathlib.Algebra.Order.BigOperators.Ring.Finset #align_import data.mv_polynomial.variables from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4" /-! # Degrees of polynomials This file establishes many results about the degree of a multivariate polynomial. The *degree set* of a polynomial $P \in R[X]$ is a `Multiset` containing, for each $x$ in the variable set, $n$ copies of $x$, where $n$ is the maximum number of copies of $x$ appearing in a monomial of $P$. ## Main declarations * `MvPolynomial.degrees p` : the multiset of variables representing the union of the multisets corresponding to each non-zero monomial in `p`. For example if `7 ≠ 0` in `R` and `p = x²y+7y³` then `degrees p = {x, x, y, y, y}` * `MvPolynomial.degreeOf n p : ℕ` : the total degree of `p` with respect to the variable `n`. For example if `p = x⁴y+yz` then `degreeOf y p = 1`. * `MvPolynomial.totalDegree p : ℕ` : the max of the sizes of the multisets `s` whose monomials `X^s` occur in `p`. For example if `p = x⁴y+yz` then `totalDegree p = 5`. ## Notation As in other polynomial files, we typically use the notation: + `σ τ : Type*` (indexing the variables) + `R : Type*` `[CommSemiring R]` (the coefficients) + `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set. This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s` + `r : R` + `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians + `p : MvPolynomial σ R` -/ noncomputable section open Set Function Finsupp AddMonoidAlgebra universe u v w variable {R : Type u} {S : Type v} namespace MvPolynomial variable {σ τ : Type*} {r : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ} section CommSemiring variable [CommSemiring R] {p q : MvPolynomial σ R} section Degrees /-! ### `degrees` -/ /-- The maximal degrees of each variable in a multi-variable polynomial, expressed as a multiset. (For example, `degrees (x^2 * y + y^3)` would be `{x, x, y, y, y}`.) -/ def degrees (p : MvPolynomial σ R) : Multiset σ := letI := Classical.decEq σ p.support.sup fun s : σ →₀ ℕ => toMultiset s #align mv_polynomial.degrees MvPolynomial.degrees theorem degrees_def [DecidableEq σ] (p : MvPolynomial σ R) : p.degrees = p.support.sup fun s : σ →₀ ℕ => Finsupp.toMultiset s := by rw [degrees]; convert rfl #align mv_polynomial.degrees_def MvPolynomial.degrees_def theorem degrees_monomial (s : σ →₀ ℕ) (a : R) : degrees (monomial s a) ≤ toMultiset s := by classical refine (supDegree_single s a).trans_le ?_ split_ifs exacts [bot_le, le_rfl] #align mv_polynomial.degrees_monomial MvPolynomial.degrees_monomial theorem degrees_monomial_eq (s : σ →₀ ℕ) (a : R) (ha : a ≠ 0) : degrees (monomial s a) = toMultiset s := by classical exact (supDegree_single s a).trans (if_neg ha) #align mv_polynomial.degrees_monomial_eq MvPolynomial.degrees_monomial_eq theorem degrees_C (a : R) : degrees (C a : MvPolynomial σ R) = 0 := Multiset.le_zero.1 <| degrees_monomial _ _ set_option linter.uppercaseLean3 false in #align mv_polynomial.degrees_C MvPolynomial.degrees_C theorem degrees_X' (n : σ) : degrees (X n : MvPolynomial σ R) ≤ {n} := le_trans (degrees_monomial _ _) <| le_of_eq <| toMultiset_single _ _ set_option linter.uppercaseLean3 false in #align mv_polynomial.degrees_X' MvPolynomial.degrees_X' @[simp] theorem degrees_X [Nontrivial R] (n : σ) : degrees (X n : MvPolynomial σ R) = {n} := (degrees_monomial_eq _ (1 : R) one_ne_zero).trans (toMultiset_single _ _) set_option linter.uppercaseLean3 false in #align mv_polynomial.degrees_X MvPolynomial.degrees_X @[simp] theorem degrees_zero : degrees (0 : MvPolynomial σ R) = 0 := by rw [← C_0] exact degrees_C 0 #align mv_polynomial.degrees_zero MvPolynomial.degrees_zero @[simp] theorem degrees_one : degrees (1 : MvPolynomial σ R) = 0 := degrees_C 1 #align mv_polynomial.degrees_one MvPolynomial.degrees_one theorem degrees_add [DecidableEq σ] (p q : MvPolynomial σ R) : (p + q).degrees ≤ p.degrees ⊔ q.degrees := by simp_rw [degrees_def]; exact supDegree_add_le #align mv_polynomial.degrees_add MvPolynomial.degrees_add theorem degrees_sum {ι : Type*} [DecidableEq σ] (s : Finset ι) (f : ι → MvPolynomial σ R) : (∑ i ∈ s, f i).degrees ≤ s.sup fun i => (f i).degrees := by simp_rw [degrees_def]; exact supDegree_sum_le #align mv_polynomial.degrees_sum MvPolynomial.degrees_sum
Mathlib/Algebra/MvPolynomial/Degrees.lean
138
141
theorem degrees_mul (p q : MvPolynomial σ R) : (p * q).degrees ≤ p.degrees + q.degrees := by
classical simp_rw [degrees_def] exact supDegree_mul_le (map_add _)
/- 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.Topology.Instances.Real import Mathlib.Order.Filter.Archimedean #align_import analysis.subadditive from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982" /-! # Convergence of subadditive sequences A subadditive sequence `u : ℕ → ℝ` is a sequence satisfying `u (m + n) ≤ u m + u n` for all `m, n`. We define this notion as `Subadditive u`, and prove in `Subadditive.tendsto_lim` that, if `u n / n` is bounded below, then it converges to a limit (that we denote by `Subadditive.lim` for convenience). This result is known as Fekete's lemma in the literature. ## TODO Define a bundled `SubadditiveHom`, use it. -/ noncomputable section open Set Filter Topology /-- A real-valued sequence is subadditive if it satisfies the inequality `u (m + n) ≤ u m + u n` for all `m, n`. -/ def Subadditive (u : ℕ → ℝ) : Prop := ∀ m n, u (m + n) ≤ u m + u n #align subadditive Subadditive namespace Subadditive variable {u : ℕ → ℝ} (h : Subadditive u) /-- The limit of a bounded-below subadditive sequence. The fact that the sequence indeed tends to this limit is given in `Subadditive.tendsto_lim` -/ @[nolint unusedArguments] -- Porting note: was irreducible protected def lim (_h : Subadditive u) := sInf ((fun n : ℕ => u n / n) '' Ici 1) #align subadditive.lim Subadditive.lim theorem lim_le_div (hbdd : BddBelow (range fun n => u n / n)) {n : ℕ} (hn : n ≠ 0) : h.lim ≤ u n / n := by rw [Subadditive.lim] exact csInf_le (hbdd.mono <| image_subset_range _ _) ⟨n, hn.bot_lt, rfl⟩ #align subadditive.lim_le_div Subadditive.lim_le_div
Mathlib/Analysis/Subadditive.lean
51
59
theorem apply_mul_add_le (k n r) : u (k * n + r) ≤ k * u n + u r := by
induction k with | zero => simp only [Nat.zero_eq, Nat.cast_zero, zero_mul, zero_add]; rfl | succ k IH => calc u ((k + 1) * n + r) = u (n + (k * n + r)) := by congr 1; ring _ ≤ u n + u (k * n + r) := h _ _ _ ≤ u n + (k * u n + u r) := add_le_add_left IH _ _ = (k + 1 : ℕ) * u n + u r := by simp; ring
/- Copyright (c) 2023 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.MeasureTheory.Decomposition.RadonNikodym import Mathlib.Probability.Kernel.Disintegration.CdfToKernel #align_import probability.kernel.cond_cdf from "leanprover-community/mathlib"@"3b88f4005dc2e28d42f974cc1ce838f0dafb39b8" /-! # Conditional cumulative distribution function Given `ρ : Measure (α × ℝ)`, we define the conditional cumulative distribution function (conditional cdf) of `ρ`. It is a function `condCDF ρ : α → ℝ → ℝ` such that if `ρ` is a finite measure, then for all `a : α` `condCDF ρ a` is monotone and right-continuous with limit 0 at -∞ and limit 1 at +∞, and such that for all `x : ℝ`, `a ↦ condCDF ρ a x` is measurable. For all `x : ℝ` and measurable set `s`, that function satisfies `∫⁻ a in s, ennreal.of_real (condCDF ρ a x) ∂ρ.fst = ρ (s ×ˢ Iic x)`. `condCDF` is build from the more general tools about kernel CDFs developed in the file `Probability.Kernel.Disintegration.CdfToKernel`. In that file, we build a function `α × β → StieltjesFunction` (which is `α × β → ℝ → ℝ` with additional properties) from a function `α × β → ℚ → ℝ`. The restriction to `ℚ` allows to prove some properties like measurability more easily. Here we apply that construction to the case `β = Unit` and then drop `β` to build `condCDF : α → StieltjesFunction`. ## Main definitions * `ProbabilityTheory.condCDF ρ : α → StieltjesFunction`: the conditional cdf of `ρ : Measure (α × ℝ)`. A `StieltjesFunction` is a function `ℝ → ℝ` which is monotone and right-continuous. ## Main statements * `ProbabilityTheory.set_lintegral_condCDF`: for all `a : α` and `x : ℝ`, all measurable set `s`, `∫⁻ a in s, ENNReal.ofReal (condCDF ρ a x) ∂ρ.fst = ρ (s ×ˢ Iic x)`. -/ open MeasureTheory Set Filter TopologicalSpace open scoped NNReal ENNReal MeasureTheory Topology namespace MeasureTheory.Measure variable {α β : Type*} {mα : MeasurableSpace α} (ρ : Measure (α × ℝ)) /-- Measure on `α` such that for a measurable set `s`, `ρ.IicSnd r s = ρ (s ×ˢ Iic r)`. -/ noncomputable def IicSnd (r : ℝ) : Measure α := (ρ.restrict (univ ×ˢ Iic r)).fst #align measure_theory.measure.Iic_snd MeasureTheory.Measure.IicSnd theorem IicSnd_apply (r : ℝ) {s : Set α} (hs : MeasurableSet s) : ρ.IicSnd r s = ρ (s ×ˢ Iic r) := by rw [IicSnd, fst_apply hs, restrict_apply' (MeasurableSet.univ.prod (measurableSet_Iic : MeasurableSet (Iic r))), ← prod_univ, prod_inter_prod, inter_univ, univ_inter] #align measure_theory.measure.Iic_snd_apply MeasureTheory.Measure.IicSnd_apply theorem IicSnd_univ (r : ℝ) : ρ.IicSnd r univ = ρ (univ ×ˢ Iic r) := IicSnd_apply ρ r MeasurableSet.univ #align measure_theory.measure.Iic_snd_univ MeasureTheory.Measure.IicSnd_univ theorem IicSnd_mono {r r' : ℝ} (h_le : r ≤ r') : ρ.IicSnd r ≤ ρ.IicSnd r' := by refine Measure.le_iff.2 fun s hs ↦ ?_ simp_rw [IicSnd_apply ρ _ hs] refine measure_mono (prod_subset_prod_iff.mpr (Or.inl ⟨subset_rfl, Iic_subset_Iic.mpr ?_⟩)) exact mod_cast h_le #align measure_theory.measure.Iic_snd_mono MeasureTheory.Measure.IicSnd_mono theorem IicSnd_le_fst (r : ℝ) : ρ.IicSnd r ≤ ρ.fst := by refine Measure.le_iff.2 fun s hs ↦ ?_ simp_rw [fst_apply hs, IicSnd_apply ρ r hs] exact measure_mono (prod_subset_preimage_fst _ _) #align measure_theory.measure.Iic_snd_le_fst MeasureTheory.Measure.IicSnd_le_fst theorem IicSnd_ac_fst (r : ℝ) : ρ.IicSnd r ≪ ρ.fst := Measure.absolutelyContinuous_of_le (IicSnd_le_fst ρ r) #align measure_theory.measure.Iic_snd_ac_fst MeasureTheory.Measure.IicSnd_ac_fst theorem IsFiniteMeasure.IicSnd {ρ : Measure (α × ℝ)} [IsFiniteMeasure ρ] (r : ℝ) : IsFiniteMeasure (ρ.IicSnd r) := isFiniteMeasure_of_le _ (IicSnd_le_fst ρ _) #align measure_theory.measure.is_finite_measure.Iic_snd MeasureTheory.Measure.IsFiniteMeasure.IicSnd theorem iInf_IicSnd_gt (t : ℚ) {s : Set α} (hs : MeasurableSet s) [IsFiniteMeasure ρ] : ⨅ r : { r' : ℚ // t < r' }, ρ.IicSnd r s = ρ.IicSnd t s := by simp_rw [ρ.IicSnd_apply _ hs, Measure.iInf_rat_gt_prod_Iic hs] #align measure_theory.measure.infi_Iic_snd_gt MeasureTheory.Measure.iInf_IicSnd_gt
Mathlib/Probability/Kernel/Disintegration/CondCdf.lean
92
99
theorem tendsto_IicSnd_atTop {s : Set α} (hs : MeasurableSet s) : Tendsto (fun r : ℚ ↦ ρ.IicSnd r s) atTop (𝓝 (ρ.fst s)) := by
simp_rw [ρ.IicSnd_apply _ hs, fst_apply hs, ← prod_univ] rw [← Real.iUnion_Iic_rat, prod_iUnion] refine tendsto_measure_iUnion fun r q hr_le_q x ↦ ?_ simp only [mem_prod, mem_Iic, and_imp] refine fun hxs hxr ↦ ⟨hxs, hxr.trans ?_⟩ exact mod_cast hr_le_q
/- 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, Floris van Doorn, Yury Kudryashov, Neil Strickland -/ import Mathlib.Algebra.Ring.InjSurj import Mathlib.Algebra.Group.Units.Hom import Mathlib.Algebra.Ring.Hom.Defs #align_import algebra.ring.units from "leanprover-community/mathlib"@"2ed7e4aec72395b6a7c3ac4ac7873a7a43ead17c" /-! # Units in semirings and rings -/ universe u v w x variable {α : Type u} {β : Type v} {γ : Type w} {R : Type x} open Function namespace Units section HasDistribNeg variable [Monoid α] [HasDistribNeg α] {a b : α} /-- Each element of the group of units of a ring has an additive inverse. -/ instance : Neg αˣ := ⟨fun u => ⟨-↑u, -↑u⁻¹, by simp, by simp⟩⟩ /-- Representing an element of a ring's unit group as an element of the ring commutes with mapping this element to its additive inverse. -/ @[simp, norm_cast] protected theorem val_neg (u : αˣ) : (↑(-u) : α) = -u := rfl #align units.coe_neg Units.val_neg @[simp, norm_cast] protected theorem coe_neg_one : ((-1 : αˣ) : α) = -1 := rfl #align units.coe_neg_one Units.coe_neg_one instance : HasDistribNeg αˣ := Units.ext.hasDistribNeg _ Units.val_neg Units.val_mul @[field_simps] theorem neg_divp (a : α) (u : αˣ) : -(a /ₚ u) = -a /ₚ u := by simp only [divp, neg_mul] #align units.neg_divp Units.neg_divp end HasDistribNeg section Ring variable [Ring α] {a b : α} -- Needs to have higher simp priority than divp_add_divp. 1000 is the default priority. @[field_simps 1010]
Mathlib/Algebra/Ring/Units.lean
61
62
theorem divp_add_divp_same (a b : α) (u : αˣ) : a /ₚ u + b /ₚ u = (a + b) /ₚ u := by
simp only [divp, add_mul]
/- 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.Data.DFinsupp.Interval import Mathlib.Data.DFinsupp.Multiset import Mathlib.Order.Interval.Finset.Nat #align_import data.multiset.interval from "leanprover-community/mathlib"@"1d29de43a5ba4662dd33b5cfeecfc2a27a5a8a29" /-! # Finite intervals of multisets This file provides the `LocallyFiniteOrder` instance for `Multiset α` and calculates the cardinality of its finite intervals. ## Implementation notes We implement the intervals via the intervals on `DFinsupp`, rather than via filtering `Multiset.Powerset`; this is because `(Multiset.replicate n x).Powerset` has `2^n` entries not `n+1` entries as it contains duplicates. We do not go via `Finsupp` as this would be noncomputable, and multisets are typically used computationally. -/ open Finset DFinsupp Function open Pointwise variable {α : Type*} namespace Multiset variable [DecidableEq α] (s t : Multiset α) instance instLocallyFiniteOrder : LocallyFiniteOrder (Multiset α) := LocallyFiniteOrder.ofIcc (Multiset α) (fun s t => (Finset.Icc (toDFinsupp s) (toDFinsupp t)).map Multiset.equivDFinsupp.toEquiv.symm.toEmbedding) fun s t x => by simp theorem Icc_eq : Finset.Icc s t = (Finset.Icc (toDFinsupp s) (toDFinsupp t)).map Multiset.equivDFinsupp.toEquiv.symm.toEmbedding := rfl #align multiset.Icc_eq Multiset.Icc_eq theorem uIcc_eq : uIcc s t = (uIcc (toDFinsupp s) (toDFinsupp t)).map Multiset.equivDFinsupp.toEquiv.symm.toEmbedding := (Icc_eq _ _).trans <| by simp [uIcc] #align multiset.uIcc_eq Multiset.uIcc_eq theorem card_Icc : (Finset.Icc s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) := by simp_rw [Icc_eq, Finset.card_map, DFinsupp.card_Icc, Nat.card_Icc, Multiset.toDFinsupp_apply, toDFinsupp_support] #align multiset.card_Icc Multiset.card_Icc theorem card_Ico : (Finset.Ico s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) - 1 := by rw [Finset.card_Ico_eq_card_Icc_sub_one, card_Icc] #align multiset.card_Ico Multiset.card_Ico
Mathlib/Data/Multiset/Interval.lean
67
69
theorem card_Ioc : (Finset.Ioc s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) - 1 := by
rw [Finset.card_Ioc_eq_card_Icc_sub_one, card_Icc]
/- Copyright (c) 2021 Kexing Ying. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kexing Ying -/ import Mathlib.MeasureTheory.Decomposition.SignedHahn import Mathlib.MeasureTheory.Measure.MutuallySingular #align_import measure_theory.decomposition.jordan from "leanprover-community/mathlib"@"70a4f2197832bceab57d7f41379b2592d1110570" /-! # Jordan decomposition This file proves the existence and uniqueness of the Jordan decomposition for signed measures. The Jordan decomposition theorem states that, given a signed measure `s`, there exists a unique pair of mutually singular measures `μ` and `ν`, such that `s = μ - ν`. The Jordan decomposition theorem for measures is a corollary of the Hahn decomposition theorem and is useful for the Lebesgue decomposition theorem. ## Main definitions * `MeasureTheory.JordanDecomposition`: a Jordan decomposition of a measurable space is a pair of mutually singular finite measures. We say `j` is a Jordan decomposition of a signed measure `s` if `s = j.posPart - j.negPart`. * `MeasureTheory.SignedMeasure.toJordanDecomposition`: the Jordan decomposition of a signed measure. * `MeasureTheory.SignedMeasure.toJordanDecompositionEquiv`: is the `Equiv` between `MeasureTheory.SignedMeasure` and `MeasureTheory.JordanDecomposition` formed by `MeasureTheory.SignedMeasure.toJordanDecomposition`. ## Main results * `MeasureTheory.SignedMeasure.toSignedMeasure_toJordanDecomposition` : the Jordan decomposition theorem. * `MeasureTheory.JordanDecomposition.toSignedMeasure_injective` : the Jordan decomposition of a signed measure is unique. ## Tags Jordan decomposition theorem -/ noncomputable section open scoped Classical MeasureTheory ENNReal NNReal variable {α β : Type*} [MeasurableSpace α] namespace MeasureTheory /-- A Jordan decomposition of a measurable space is a pair of mutually singular, finite measures. -/ @[ext] structure JordanDecomposition (α : Type*) [MeasurableSpace α] where (posPart negPart : Measure α) [posPart_finite : IsFiniteMeasure posPart] [negPart_finite : IsFiniteMeasure negPart] mutuallySingular : posPart ⟂ₘ negPart #align measure_theory.jordan_decomposition MeasureTheory.JordanDecomposition #align measure_theory.jordan_decomposition.pos_part MeasureTheory.JordanDecomposition.posPart #align measure_theory.jordan_decomposition.neg_part MeasureTheory.JordanDecomposition.negPart #align measure_theory.jordan_decomposition.pos_part_finite MeasureTheory.JordanDecomposition.posPart_finite #align measure_theory.jordan_decomposition.neg_part_finite MeasureTheory.JordanDecomposition.negPart_finite #align measure_theory.jordan_decomposition.mutually_singular MeasureTheory.JordanDecomposition.mutuallySingular attribute [instance] JordanDecomposition.posPart_finite attribute [instance] JordanDecomposition.negPart_finite namespace JordanDecomposition open Measure VectorMeasure variable (j : JordanDecomposition α) instance instZero : Zero (JordanDecomposition α) where zero := ⟨0, 0, MutuallySingular.zero_right⟩ #align measure_theory.jordan_decomposition.has_zero MeasureTheory.JordanDecomposition.instZero instance instInhabited : Inhabited (JordanDecomposition α) where default := 0 #align measure_theory.jordan_decomposition.inhabited MeasureTheory.JordanDecomposition.instInhabited instance instInvolutiveNeg : InvolutiveNeg (JordanDecomposition α) where neg j := ⟨j.negPart, j.posPart, j.mutuallySingular.symm⟩ neg_neg _ := JordanDecomposition.ext _ _ rfl rfl #align measure_theory.jordan_decomposition.has_involutive_neg MeasureTheory.JordanDecomposition.instInvolutiveNeg instance instSMul : SMul ℝ≥0 (JordanDecomposition α) where smul r j := ⟨r • j.posPart, r • j.negPart, MutuallySingular.smul _ (MutuallySingular.smul _ j.mutuallySingular.symm).symm⟩ #align measure_theory.jordan_decomposition.has_smul MeasureTheory.JordanDecomposition.instSMul instance instSMulReal : SMul ℝ (JordanDecomposition α) where smul r j := if 0 ≤ r then r.toNNReal • j else -((-r).toNNReal • j) #align measure_theory.jordan_decomposition.has_smul_real MeasureTheory.JordanDecomposition.instSMulReal @[simp] theorem zero_posPart : (0 : JordanDecomposition α).posPart = 0 := rfl #align measure_theory.jordan_decomposition.zero_pos_part MeasureTheory.JordanDecomposition.zero_posPart @[simp] theorem zero_negPart : (0 : JordanDecomposition α).negPart = 0 := rfl #align measure_theory.jordan_decomposition.zero_neg_part MeasureTheory.JordanDecomposition.zero_negPart @[simp] theorem neg_posPart : (-j).posPart = j.negPart := rfl #align measure_theory.jordan_decomposition.neg_pos_part MeasureTheory.JordanDecomposition.neg_posPart @[simp] theorem neg_negPart : (-j).negPart = j.posPart := rfl #align measure_theory.jordan_decomposition.neg_neg_part MeasureTheory.JordanDecomposition.neg_negPart @[simp] theorem smul_posPart (r : ℝ≥0) : (r • j).posPart = r • j.posPart := rfl #align measure_theory.jordan_decomposition.smul_pos_part MeasureTheory.JordanDecomposition.smul_posPart @[simp] theorem smul_negPart (r : ℝ≥0) : (r • j).negPart = r • j.negPart := rfl #align measure_theory.jordan_decomposition.smul_neg_part MeasureTheory.JordanDecomposition.smul_negPart theorem real_smul_def (r : ℝ) (j : JordanDecomposition α) : r • j = if 0 ≤ r then r.toNNReal • j else -((-r).toNNReal • j) := rfl #align measure_theory.jordan_decomposition.real_smul_def MeasureTheory.JordanDecomposition.real_smul_def @[simp] theorem coe_smul (r : ℝ≥0) : (r : ℝ) • j = r • j := by -- Porting note: replaced `show` rw [real_smul_def, if_pos (NNReal.coe_nonneg r), Real.toNNReal_coe] #align measure_theory.jordan_decomposition.coe_smul MeasureTheory.JordanDecomposition.coe_smul theorem real_smul_nonneg (r : ℝ) (hr : 0 ≤ r) : r • j = r.toNNReal • j := dif_pos hr #align measure_theory.jordan_decomposition.real_smul_nonneg MeasureTheory.JordanDecomposition.real_smul_nonneg theorem real_smul_neg (r : ℝ) (hr : r < 0) : r • j = -((-r).toNNReal • j) := dif_neg (not_le.2 hr) #align measure_theory.jordan_decomposition.real_smul_neg MeasureTheory.JordanDecomposition.real_smul_neg
Mathlib/MeasureTheory/Decomposition/Jordan.lean
148
150
theorem real_smul_posPart_nonneg (r : ℝ) (hr : 0 ≤ r) : (r • j).posPart = r.toNNReal • j.posPart := by
rw [real_smul_def, ← smul_posPart, if_pos hr]
/- Copyright (c) 2022 Jiale Miao. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jiale Miao, Kevin Buzzard, Alexander Bentkamp -/ import Mathlib.Analysis.InnerProductSpace.PiL2 import Mathlib.LinearAlgebra.Matrix.Block #align_import analysis.inner_product_space.gram_schmidt_ortho from "leanprover-community/mathlib"@"1a4df69ca1a9a0e5e26bfe12e2b92814216016d0" /-! # Gram-Schmidt Orthogonalization and Orthonormalization In this file we introduce Gram-Schmidt Orthogonalization and Orthonormalization. The Gram-Schmidt process takes a set of vectors as input and outputs a set of orthogonal vectors which have the same span. ## Main results - `gramSchmidt` : the Gram-Schmidt process - `gramSchmidt_orthogonal` : `gramSchmidt` produces an orthogonal system of vectors. - `span_gramSchmidt` : `gramSchmidt` preserves span of vectors. - `gramSchmidt_ne_zero` : If the input vectors of `gramSchmidt` are linearly independent, then the output vectors are non-zero. - `gramSchmidt_basis` : The basis produced by the Gram-Schmidt process when given a basis as input. - `gramSchmidtNormed` : the normalized `gramSchmidt` (i.e each vector in `gramSchmidtNormed` has unit length.) - `gramSchmidt_orthonormal` : `gramSchmidtNormed` produces an orthornormal system of vectors. - `gramSchmidtOrthonormalBasis`: orthonormal basis constructed by the Gram-Schmidt process from an indexed set of vectors of the right size -/ open Finset Submodule FiniteDimensional variable (𝕜 : Type*) {E : Type*} [RCLike 𝕜] [NormedAddCommGroup E] [InnerProductSpace 𝕜 E] variable {ι : Type*} [LinearOrder ι] [LocallyFiniteOrderBot ι] [IsWellOrder ι (· < ·)] attribute [local instance] IsWellOrder.toHasWellFounded local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y /-- The Gram-Schmidt process takes a set of vectors as input and outputs a set of orthogonal vectors which have the same span. -/ noncomputable def gramSchmidt [IsWellOrder ι (· < ·)] (f : ι → E) (n : ι) : E := f n - ∑ i : Iio n, orthogonalProjection (𝕜 ∙ gramSchmidt f i) (f n) termination_by n decreasing_by exact mem_Iio.1 i.2 #align gram_schmidt gramSchmidt /-- This lemma uses `∑ i in` instead of `∑ i :`. -/ theorem gramSchmidt_def (f : ι → E) (n : ι) : gramSchmidt 𝕜 f n = f n - ∑ i ∈ Iio n, orthogonalProjection (𝕜 ∙ gramSchmidt 𝕜 f i) (f n) := by rw [← sum_attach, attach_eq_univ, gramSchmidt] #align gram_schmidt_def gramSchmidt_def
Mathlib/Analysis/InnerProductSpace/GramSchmidtOrtho.lean
63
65
theorem gramSchmidt_def' (f : ι → E) (n : ι) : f n = gramSchmidt 𝕜 f n + ∑ i ∈ Iio n, orthogonalProjection (𝕜 ∙ gramSchmidt 𝕜 f i) (f n) := by
rw [gramSchmidt_def, sub_add_cancel]
/- Copyright (c) 2022 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson -/ import Mathlib.ModelTheory.ElementarySubstructures #align_import model_theory.skolem from "leanprover-community/mathlib"@"3d7987cda72abc473c7cdbbb075170e9ac620042" /-! # Skolem Functions and Downward Löwenheim–Skolem ## Main Definitions * `FirstOrder.Language.skolem₁` is a language consisting of Skolem functions for another language. ## Main Results * `FirstOrder.Language.exists_elementarySubstructure_card_eq` is the Downward Löwenheim–Skolem theorem: If `s` is a set in an `L`-structure `M` and `κ` an infinite cardinal such that `max (#s, L.card) ≤ κ` and `κ ≤ # M`, then `M` has an elementary substructure containing `s` of cardinality `κ`. ## TODO * Use `skolem₁` recursively to construct an actual Skolemization of a language. -/ universe u v w w' namespace FirstOrder namespace Language open Structure Cardinal open Cardinal variable (L : Language.{u, v}) {M : Type w} [Nonempty M] [L.Structure M] /-- A language consisting of Skolem functions for another language. Called `skolem₁` because it is the first step in building a Skolemization of a language. -/ @[simps] def skolem₁ : Language := ⟨fun n => L.BoundedFormula Empty (n + 1), fun _ => Empty⟩ #align first_order.language.skolem₁ FirstOrder.Language.skolem₁ #align first_order.language.skolem₁_functions FirstOrder.Language.skolem₁_Functions variable {L} theorem card_functions_sum_skolem₁ : #(Σ n, (L.sum L.skolem₁).Functions n) = #(Σ n, L.BoundedFormula Empty (n + 1)) := by simp only [card_functions_sum, skolem₁_Functions, mk_sigma, sum_add_distrib'] conv_lhs => enter [2, 1, i]; rw [lift_id'.{u, v}] rw [add_comm, add_eq_max, max_eq_left] · refine sum_le_sum _ _ fun n => ?_ rw [← lift_le.{_, max u v}, lift_lift, lift_mk_le.{v}] refine ⟨⟨fun f => (func f default).bdEqual (func f default), fun f g h => ?_⟩⟩ rcases h with ⟨rfl, ⟨rfl⟩⟩ rfl · rw [← mk_sigma] exact infinite_iff.1 (Infinite.of_injective (fun n => ⟨n, ⊥⟩) fun x y xy => (Sigma.mk.inj_iff.1 xy).1) #align first_order.language.card_functions_sum_skolem₁ FirstOrder.Language.card_functions_sum_skolem₁
Mathlib/ModelTheory/Skolem.lean
65
73
theorem card_functions_sum_skolem₁_le : #(Σ n, (L.sum L.skolem₁).Functions n) ≤ max ℵ₀ L.card := by
rw [card_functions_sum_skolem₁] trans #(Σ n, L.BoundedFormula Empty n) · exact ⟨⟨Sigma.map Nat.succ fun _ => id, Nat.succ_injective.sigma_map fun _ => Function.injective_id⟩⟩ · refine _root_.trans BoundedFormula.card_le (lift_le.{max u v}.1 ?_) simp only [mk_empty, lift_zero, lift_uzero, zero_add] rfl
/- 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.RepresentationTheory.Basic import Mathlib.RepresentationTheory.FdRep #align_import representation_theory.invariants from "leanprover-community/mathlib"@"55b3f8206b8596db8bb1804d8a92814a0b6670c9" /-! # Subspace of invariants a group representation This file introduces the subspace of invariants of a group representation and proves basic results about it. The main tool used is the average of all elements of the group, seen as an element of `MonoidAlgebra k G`. The action of this special element gives a projection onto the subspace of invariants. In order for the definition of the average element to make sense, we need to assume for most of the results that the order of `G` is invertible in `k` (e. g. `k` has characteristic `0`). -/ suppress_compilation open MonoidAlgebra open Representation namespace GroupAlgebra variable (k G : Type*) [CommSemiring k] [Group G] variable [Fintype G] [Invertible (Fintype.card G : k)] /-- The average of all elements of the group `G`, considered as an element of `MonoidAlgebra k G`. -/ noncomputable def average : MonoidAlgebra k G := ⅟ (Fintype.card G : k) • ∑ g : G, of k G g #align group_algebra.average GroupAlgebra.average /-- `average k G` is invariant under left multiplication by elements of `G`. -/ @[simp] theorem mul_average_left (g : G) : ↑(Finsupp.single g 1) * average k G = average k G := by simp only [mul_one, Finset.mul_sum, Algebra.mul_smul_comm, average, MonoidAlgebra.of_apply, Finset.sum_congr, MonoidAlgebra.single_mul_single] set f : G → MonoidAlgebra k G := fun x => Finsupp.single x 1 show ⅟ (Fintype.card G : k) • ∑ x : G, f (g * x) = ⅟ (Fintype.card G : k) • ∑ x : G, f x rw [Function.Bijective.sum_comp (Group.mulLeft_bijective g) _] #align group_algebra.mul_average_left GroupAlgebra.mul_average_left /-- `average k G` is invariant under right multiplication by elements of `G`. -/ @[simp] theorem mul_average_right (g : G) : average k G * ↑(Finsupp.single g 1) = average k G := by simp only [mul_one, Finset.sum_mul, Algebra.smul_mul_assoc, average, MonoidAlgebra.of_apply, Finset.sum_congr, MonoidAlgebra.single_mul_single] set f : G → MonoidAlgebra k G := fun x => Finsupp.single x 1 show ⅟ (Fintype.card G : k) • ∑ x : G, f (x * g) = ⅟ (Fintype.card G : k) • ∑ x : G, f x rw [Function.Bijective.sum_comp (Group.mulRight_bijective g) _] #align group_algebra.mul_average_right GroupAlgebra.mul_average_right end GroupAlgebra namespace Representation section Invariants open GroupAlgebra variable {k G V : Type*} [CommSemiring k] [Group G] [AddCommMonoid V] [Module k V] variable (ρ : Representation k G V) /-- The subspace of invariants, consisting of the vectors fixed by all elements of `G`. -/ def invariants : Submodule k V where carrier := setOf fun v => ∀ g : G, ρ g v = v zero_mem' g := by simp only [map_zero] add_mem' hv hw g := by simp only [hv g, hw g, map_add] smul_mem' r v hv g := by simp only [hv g, LinearMap.map_smulₛₗ, RingHom.id_apply] #align representation.invariants Representation.invariants @[simp] theorem mem_invariants (v : V) : v ∈ invariants ρ ↔ ∀ g : G, ρ g v = v := by rfl #align representation.mem_invariants Representation.mem_invariants theorem invariants_eq_inter : (invariants ρ).carrier = ⋂ g : G, Function.fixedPoints (ρ g) := by ext; simp [Function.IsFixedPt] #align representation.invariants_eq_inter Representation.invariants_eq_inter theorem invariants_eq_top [ρ.IsTrivial] : invariants ρ = ⊤ := eq_top_iff.2 (fun x _ g => ρ.apply_eq_self g x) variable [Fintype G] [Invertible (Fintype.card G : k)] /-- The action of `average k G` gives a projection map onto the subspace of invariants. -/ @[simp] noncomputable def averageMap : V →ₗ[k] V := asAlgebraHom ρ (average k G) #align representation.average_map Representation.averageMap /-- The `averageMap` sends elements of `V` to the subspace of invariants. -/ theorem averageMap_invariant (v : V) : averageMap ρ v ∈ invariants ρ := fun g => by rw [averageMap, ← asAlgebraHom_single_one, ← LinearMap.mul_apply, ← map_mul (asAlgebraHom ρ), mul_average_left] #align representation.average_map_invariant Representation.averageMap_invariant /-- The `averageMap` acts as the identity on the subspace of invariants. -/ theorem averageMap_id (v : V) (hv : v ∈ invariants ρ) : averageMap ρ v = v := by rw [mem_invariants] at hv simp [average, map_sum, hv, Finset.card_univ, nsmul_eq_smul_cast k _ v, smul_smul] #align representation.average_map_id Representation.averageMap_id theorem isProj_averageMap : LinearMap.IsProj ρ.invariants ρ.averageMap := ⟨ρ.averageMap_invariant, ρ.averageMap_id⟩ #align representation.is_proj_average_map Representation.isProj_averageMap end Invariants namespace linHom universe u open CategoryTheory Action section Rep variable {k : Type u} [CommRing k] {G : GroupCat.{u}}
Mathlib/RepresentationTheory/Invariants.lean
133
139
theorem mem_invariants_iff_comm {X Y : Rep k G} (f : X.V →ₗ[k] Y.V) (g : G) : (linHom X.ρ Y.ρ) g f = f ↔ f.comp (X.ρ g) = (Y.ρ g).comp f := by
dsimp erw [← ρAut_apply_inv] rw [← LinearMap.comp_assoc, ← ModuleCat.comp_def, ← ModuleCat.comp_def, Iso.inv_comp_eq, ρAut_apply_hom] exact comm
/- Copyright (c) 2019 Gabriel Ebner. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Gabriel Ebner, Anatole Dedecker, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.Deriv.Basic import Mathlib.Analysis.Calculus.FDeriv.Mul import Mathlib.Analysis.Calculus.FDeriv.Add #align_import analysis.calculus.deriv.mul from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe" /-! # Derivative of `f x * g x` In this file we prove formulas for `(f x * g x)'` and `(f x • g x)'`. For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of `Analysis/Calculus/Deriv/Basic`. ## Keywords derivative, multiplication -/ universe u v w noncomputable section open scoped Classical Topology Filter ENNReal open Filter Asymptotics Set open ContinuousLinearMap (smulRight smulRight_one_eq_iff) variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F] variable {E : Type w} [NormedAddCommGroup E] [NormedSpace 𝕜 E] variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] variable {f f₀ f₁ g : 𝕜 → F} variable {f' f₀' f₁' g' : F} variable {x : 𝕜} variable {s t : Set 𝕜} variable {L L₁ L₂ : Filter 𝕜} /-! ### Derivative of bilinear maps -/ namespace ContinuousLinearMap variable {B : E →L[𝕜] F →L[𝕜] G} {u : 𝕜 → E} {v : 𝕜 → F} {u' : E} {v' : F} theorem hasDerivWithinAt_of_bilinear (hu : HasDerivWithinAt u u' s x) (hv : HasDerivWithinAt v v' s x) : HasDerivWithinAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) s x := by simpa using (B.hasFDerivWithinAt_of_bilinear hu.hasFDerivWithinAt hv.hasFDerivWithinAt).hasDerivWithinAt theorem hasDerivAt_of_bilinear (hu : HasDerivAt u u' x) (hv : HasDerivAt v v' x) : HasDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by simpa using (B.hasFDerivAt_of_bilinear hu.hasFDerivAt hv.hasFDerivAt).hasDerivAt theorem hasStrictDerivAt_of_bilinear (hu : HasStrictDerivAt u u' x) (hv : HasStrictDerivAt v v' x) : HasStrictDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by simpa using (B.hasStrictFDerivAt_of_bilinear hu.hasStrictFDerivAt hv.hasStrictFDerivAt).hasStrictDerivAt theorem derivWithin_of_bilinear (hxs : UniqueDiffWithinAt 𝕜 s x) (hu : DifferentiableWithinAt 𝕜 u s x) (hv : DifferentiableWithinAt 𝕜 v s x) : derivWithin (fun y => B (u y) (v y)) s x = B (u x) (derivWithin v s x) + B (derivWithin u s x) (v x) := (B.hasDerivWithinAt_of_bilinear hu.hasDerivWithinAt hv.hasDerivWithinAt).derivWithin hxs theorem deriv_of_bilinear (hu : DifferentiableAt 𝕜 u x) (hv : DifferentiableAt 𝕜 v x) : deriv (fun y => B (u y) (v y)) x = B (u x) (deriv v x) + B (deriv u x) (v x) := (B.hasDerivAt_of_bilinear hu.hasDerivAt hv.hasDerivAt).deriv end ContinuousLinearMap section SMul /-! ### Derivative of the multiplication of a scalar function and a vector function -/ variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F] [IsScalarTower 𝕜 𝕜' F] {c : 𝕜 → 𝕜'} {c' : 𝕜'} theorem HasDerivWithinAt.smul (hc : HasDerivWithinAt c c' s x) (hf : HasDerivWithinAt f f' s x) : HasDerivWithinAt (fun y => c y • f y) (c x • f' + c' • f x) s x := by simpa using (HasFDerivWithinAt.smul hc hf).hasDerivWithinAt #align has_deriv_within_at.smul HasDerivWithinAt.smul theorem HasDerivAt.smul (hc : HasDerivAt c c' x) (hf : HasDerivAt f f' x) : HasDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by rw [← hasDerivWithinAt_univ] at * exact hc.smul hf #align has_deriv_at.smul HasDerivAt.smul nonrec theorem HasStrictDerivAt.smul (hc : HasStrictDerivAt c c' x) (hf : HasStrictDerivAt f f' x) : HasStrictDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by simpa using (hc.smul hf).hasStrictDerivAt #align has_strict_deriv_at.smul HasStrictDerivAt.smul theorem derivWithin_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x) (hf : DifferentiableWithinAt 𝕜 f s x) : derivWithin (fun y => c y • f y) s x = c x • derivWithin f s x + derivWithin c s x • f x := (hc.hasDerivWithinAt.smul hf.hasDerivWithinAt).derivWithin hxs #align deriv_within_smul derivWithin_smul theorem deriv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) : deriv (fun y => c y • f y) x = c x • deriv f x + deriv c x • f x := (hc.hasDerivAt.smul hf.hasDerivAt).deriv #align deriv_smul deriv_smul
Mathlib/Analysis/Calculus/Deriv/Mul.lean
114
117
theorem HasStrictDerivAt.smul_const (hc : HasStrictDerivAt c c' x) (f : F) : HasStrictDerivAt (fun y => c y • f) (c' • f) x := by
have := hc.smul (hasStrictDerivAt_const x f) rwa [smul_zero, zero_add] at this
/- Copyright (c) 2020 Damiano Testa. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Damiano Testa, Alex Meiburg -/ import Mathlib.Algebra.BigOperators.Fin import Mathlib.Algebra.Polynomial.Degree.Lemmas #align_import data.polynomial.erase_lead from "leanprover-community/mathlib"@"fa256f00ce018e7b40e1dc756e403c86680bf448" /-! # Erase the leading term of a univariate polynomial ## Definition * `eraseLead f`: the polynomial `f - leading term of f` `eraseLead` serves as reduction step in an induction, shaving off one monomial from a polynomial. The definition is set up so that it does not mention subtraction in the definition, and thus works for polynomials over semirings as well as rings. -/ noncomputable section open Polynomial open Polynomial Finset namespace Polynomial variable {R : Type*} [Semiring R] {f : R[X]} /-- `eraseLead f` for a polynomial `f` is the polynomial obtained by subtracting from `f` the leading term of `f`. -/ def eraseLead (f : R[X]) : R[X] := Polynomial.erase f.natDegree f #align polynomial.erase_lead Polynomial.eraseLead section EraseLead theorem eraseLead_support (f : R[X]) : f.eraseLead.support = f.support.erase f.natDegree := by simp only [eraseLead, support_erase] #align polynomial.erase_lead_support Polynomial.eraseLead_support theorem eraseLead_coeff (i : ℕ) : f.eraseLead.coeff i = if i = f.natDegree then 0 else f.coeff i := by simp only [eraseLead, coeff_erase] #align polynomial.erase_lead_coeff Polynomial.eraseLead_coeff @[simp] theorem eraseLead_coeff_natDegree : f.eraseLead.coeff f.natDegree = 0 := by simp [eraseLead_coeff] #align polynomial.erase_lead_coeff_nat_degree Polynomial.eraseLead_coeff_natDegree theorem eraseLead_coeff_of_ne (i : ℕ) (hi : i ≠ f.natDegree) : f.eraseLead.coeff i = f.coeff i := by simp [eraseLead_coeff, hi] #align polynomial.erase_lead_coeff_of_ne Polynomial.eraseLead_coeff_of_ne @[simp] theorem eraseLead_zero : eraseLead (0 : R[X]) = 0 := by simp only [eraseLead, erase_zero] #align polynomial.erase_lead_zero Polynomial.eraseLead_zero @[simp] theorem eraseLead_add_monomial_natDegree_leadingCoeff (f : R[X]) : f.eraseLead + monomial f.natDegree f.leadingCoeff = f := (add_comm _ _).trans (f.monomial_add_erase _) #align polynomial.erase_lead_add_monomial_nat_degree_leading_coeff Polynomial.eraseLead_add_monomial_natDegree_leadingCoeff @[simp] theorem eraseLead_add_C_mul_X_pow (f : R[X]) : f.eraseLead + C f.leadingCoeff * X ^ f.natDegree = f := by rw [C_mul_X_pow_eq_monomial, eraseLead_add_monomial_natDegree_leadingCoeff] set_option linter.uppercaseLean3 false in #align polynomial.erase_lead_add_C_mul_X_pow Polynomial.eraseLead_add_C_mul_X_pow @[simp] theorem self_sub_monomial_natDegree_leadingCoeff {R : Type*} [Ring R] (f : R[X]) : f - monomial f.natDegree f.leadingCoeff = f.eraseLead := (eq_sub_iff_add_eq.mpr (eraseLead_add_monomial_natDegree_leadingCoeff f)).symm #align polynomial.self_sub_monomial_nat_degree_leading_coeff Polynomial.self_sub_monomial_natDegree_leadingCoeff @[simp] theorem self_sub_C_mul_X_pow {R : Type*} [Ring R] (f : R[X]) : f - C f.leadingCoeff * X ^ f.natDegree = f.eraseLead := by rw [C_mul_X_pow_eq_monomial, self_sub_monomial_natDegree_leadingCoeff] set_option linter.uppercaseLean3 false in #align polynomial.self_sub_C_mul_X_pow Polynomial.self_sub_C_mul_X_pow theorem eraseLead_ne_zero (f0 : 2 ≤ f.support.card) : eraseLead f ≠ 0 := by rw [Ne, ← card_support_eq_zero, eraseLead_support] exact (zero_lt_one.trans_le <| (tsub_le_tsub_right f0 1).trans Finset.pred_card_le_card_erase).ne.symm #align polynomial.erase_lead_ne_zero Polynomial.eraseLead_ne_zero theorem lt_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) : a < f.natDegree := by rw [eraseLead_support, mem_erase] at h exact (le_natDegree_of_mem_supp a h.2).lt_of_ne h.1 #align polynomial.lt_nat_degree_of_mem_erase_lead_support Polynomial.lt_natDegree_of_mem_eraseLead_support theorem ne_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) : a ≠ f.natDegree := (lt_natDegree_of_mem_eraseLead_support h).ne #align polynomial.ne_nat_degree_of_mem_erase_lead_support Polynomial.ne_natDegree_of_mem_eraseLead_support theorem natDegree_not_mem_eraseLead_support : f.natDegree ∉ (eraseLead f).support := fun h => ne_natDegree_of_mem_eraseLead_support h rfl #align polynomial.nat_degree_not_mem_erase_lead_support Polynomial.natDegree_not_mem_eraseLead_support theorem eraseLead_support_card_lt (h : f ≠ 0) : (eraseLead f).support.card < f.support.card := by rw [eraseLead_support] exact card_lt_card (erase_ssubset <| natDegree_mem_support_of_nonzero h) #align polynomial.erase_lead_support_card_lt Polynomial.eraseLead_support_card_lt theorem card_support_eraseLead_add_one (h : f ≠ 0) : f.eraseLead.support.card + 1 = f.support.card := by set c := f.support.card with hc cases h₁ : c case zero => by_contra exact h (card_support_eq_zero.mp h₁) case succ => rw [eraseLead_support, card_erase_of_mem (natDegree_mem_support_of_nonzero h), ← hc, h₁] rfl @[simp]
Mathlib/Algebra/Polynomial/EraseLead.lean
127
130
theorem card_support_eraseLead : f.eraseLead.support.card = f.support.card - 1 := by
by_cases hf : f = 0 · rw [hf, eraseLead_zero, support_zero, card_empty] · rw [← card_support_eraseLead_add_one hf, add_tsub_cancel_right]
/- 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.MonoidAlgebra.Degree import Mathlib.Algebra.Polynomial.Coeff import Mathlib.Algebra.Polynomial.Monomial import Mathlib.Data.Fintype.BigOperators import Mathlib.Data.Nat.WithBot import Mathlib.Data.Nat.Cast.WithTop import Mathlib.Data.Nat.SuccPred #align_import data.polynomial.degree.definitions from "leanprover-community/mathlib"@"808ea4ebfabeb599f21ec4ae87d6dc969597887f" /-! # Theory of univariate polynomials The definitions include `degree`, `Monic`, `leadingCoeff` Results include - `degree_mul` : The degree of the product is the sum of degrees - `leadingCoeff_add_of_degree_eq` and `leadingCoeff_add_of_degree_lt` : The leading_coefficient of a sum is determined by the leading coefficients and degrees -/ -- Porting note: `Mathlib.Data.Nat.Cast.WithTop` should be imported for `Nat.cast_withBot`. set_option linter.uppercaseLean3 false noncomputable section open Finsupp Finset open Polynomial namespace Polynomial universe u v variable {R : Type u} {S : Type v} {a b c d : R} {n m : ℕ} section Semiring variable [Semiring R] {p q r : R[X]} /-- `degree p` is the degree of the polynomial `p`, i.e. the largest `X`-exponent in `p`. `degree p = some n` when `p ≠ 0` and `n` is the highest power of `X` that appears in `p`, otherwise `degree 0 = ⊥`. -/ def degree (p : R[X]) : WithBot ℕ := p.support.max #align polynomial.degree Polynomial.degree theorem supDegree_eq_degree (p : R[X]) : p.toFinsupp.supDegree WithBot.some = p.degree := max_eq_sup_coe theorem degree_lt_wf : WellFounded fun p q : R[X] => degree p < degree q := InvImage.wf degree wellFounded_lt #align polynomial.degree_lt_wf Polynomial.degree_lt_wf instance : WellFoundedRelation R[X] := ⟨_, degree_lt_wf⟩ /-- `natDegree p` forces `degree p` to ℕ, by defining `natDegree 0 = 0`. -/ def natDegree (p : R[X]) : ℕ := (degree p).unbot' 0 #align polynomial.nat_degree Polynomial.natDegree /-- `leadingCoeff p` gives the coefficient of the highest power of `X` in `p`-/ def leadingCoeff (p : R[X]) : R := coeff p (natDegree p) #align polynomial.leading_coeff Polynomial.leadingCoeff /-- a polynomial is `Monic` if its leading coefficient is 1 -/ def Monic (p : R[X]) := leadingCoeff p = (1 : R) #align polynomial.monic Polynomial.Monic @[nontriviality] theorem monic_of_subsingleton [Subsingleton R] (p : R[X]) : Monic p := Subsingleton.elim _ _ #align polynomial.monic_of_subsingleton Polynomial.monic_of_subsingleton theorem Monic.def : Monic p ↔ leadingCoeff p = 1 := Iff.rfl #align polynomial.monic.def Polynomial.Monic.def instance Monic.decidable [DecidableEq R] : Decidable (Monic p) := by unfold Monic; infer_instance #align polynomial.monic.decidable Polynomial.Monic.decidable @[simp] theorem Monic.leadingCoeff {p : R[X]} (hp : p.Monic) : leadingCoeff p = 1 := hp #align polynomial.monic.leading_coeff Polynomial.Monic.leadingCoeff theorem Monic.coeff_natDegree {p : R[X]} (hp : p.Monic) : p.coeff p.natDegree = 1 := hp #align polynomial.monic.coeff_nat_degree Polynomial.Monic.coeff_natDegree @[simp] theorem degree_zero : degree (0 : R[X]) = ⊥ := rfl #align polynomial.degree_zero Polynomial.degree_zero @[simp] theorem natDegree_zero : natDegree (0 : R[X]) = 0 := rfl #align polynomial.nat_degree_zero Polynomial.natDegree_zero @[simp] theorem coeff_natDegree : coeff p (natDegree p) = leadingCoeff p := rfl #align polynomial.coeff_nat_degree Polynomial.coeff_natDegree @[simp] theorem degree_eq_bot : degree p = ⊥ ↔ p = 0 := ⟨fun h => support_eq_empty.1 (Finset.max_eq_bot.1 h), fun h => h.symm ▸ rfl⟩ #align polynomial.degree_eq_bot Polynomial.degree_eq_bot @[nontriviality] theorem degree_of_subsingleton [Subsingleton R] : degree p = ⊥ := by rw [Subsingleton.elim p 0, degree_zero] #align polynomial.degree_of_subsingleton Polynomial.degree_of_subsingleton @[nontriviality] theorem natDegree_of_subsingleton [Subsingleton R] : natDegree p = 0 := by rw [Subsingleton.elim p 0, natDegree_zero] #align polynomial.nat_degree_of_subsingleton Polynomial.natDegree_of_subsingleton theorem degree_eq_natDegree (hp : p ≠ 0) : degree p = (natDegree p : WithBot ℕ) := by let ⟨n, hn⟩ := not_forall.1 (mt Option.eq_none_iff_forall_not_mem.2 (mt degree_eq_bot.1 hp)) have hn : degree p = some n := Classical.not_not.1 hn rw [natDegree, hn]; rfl #align polynomial.degree_eq_nat_degree Polynomial.degree_eq_natDegree theorem supDegree_eq_natDegree (p : R[X]) : p.toFinsupp.supDegree id = p.natDegree := by obtain rfl|h := eq_or_ne p 0 · simp apply WithBot.coe_injective rw [← AddMonoidAlgebra.supDegree_withBot_some_comp, Function.comp_id, supDegree_eq_degree, degree_eq_natDegree h, Nat.cast_withBot] rwa [support_toFinsupp, nonempty_iff_ne_empty, Ne, support_eq_empty] theorem degree_eq_iff_natDegree_eq {p : R[X]} {n : ℕ} (hp : p ≠ 0) : p.degree = n ↔ p.natDegree = n := by rw [degree_eq_natDegree hp]; exact WithBot.coe_eq_coe #align polynomial.degree_eq_iff_nat_degree_eq Polynomial.degree_eq_iff_natDegree_eq
Mathlib/Algebra/Polynomial/Degree/Definitions.lean
150
154
theorem degree_eq_iff_natDegree_eq_of_pos {p : R[X]} {n : ℕ} (hn : 0 < n) : p.degree = n ↔ p.natDegree = n := by
obtain rfl|h := eq_or_ne p 0 · simp [hn.ne] · exact degree_eq_iff_natDegree_eq h
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Kenny Lau, Scott Morrison -/ import Mathlib.Data.List.Chain import Mathlib.Data.List.Enum import Mathlib.Data.List.Nodup import Mathlib.Data.List.Pairwise import Mathlib.Data.List.Zip #align_import data.list.range from "leanprover-community/mathlib"@"7b78d1776212a91ecc94cf601f83bdcc46b04213" /-! # Ranges of naturals as lists This file shows basic results about `List.iota`, `List.range`, `List.range'` and defines `List.finRange`. `finRange n` is the list of elements of `Fin n`. `iota n = [n, n - 1, ..., 1]` and `range n = [0, ..., n - 1]` are basic list constructions used for tactics. `range' a b = [a, ..., a + b - 1]` is there to help prove properties about them. Actual maths should use `List.Ico` instead. -/ set_option autoImplicit true universe u open Nat namespace List variable {α : Type u} @[simp] theorem range'_one {step} : range' s 1 step = [s] := rfl #align list.length_range' List.length_range' #align list.range'_eq_nil List.range'_eq_nil #align list.mem_range' List.mem_range'_1 #align list.map_add_range' List.map_add_range' #align list.map_sub_range' List.map_sub_range' #align list.chain_succ_range' List.chain_succ_range' #align list.chain_lt_range' List.chain_lt_range' theorem pairwise_lt_range' : ∀ s n (step := 1) (_ : 0 < step := by simp), Pairwise (· < ·) (range' s n step) | _, 0, _, _ => Pairwise.nil | s, n + 1, _, h => chain_iff_pairwise.1 (chain_lt_range' s n h) #align list.pairwise_lt_range' List.pairwise_lt_range' theorem nodup_range' (s n : ℕ) (step := 1) (h : 0 < step := by simp) : Nodup (range' s n step) := (pairwise_lt_range' s n step h).imp _root_.ne_of_lt #align list.nodup_range' List.nodup_range' #align list.range'_append List.range'_append #align list.range'_sublist_right List.range'_sublist_right #align list.range'_subset_right List.range'_subset_right #align list.nth_range' List.get?_range' set_option linter.deprecated false in @[simp] theorem nthLe_range' {n m step} (i) (H : i < (range' n m step).length) : nthLe (range' n m step) i H = n + step * i := get_range' i H set_option linter.deprecated false in theorem nthLe_range'_1 {n m} (i) (H : i < (range' n m).length) : nthLe (range' n m) i H = n + i := by simp #align list.nth_le_range' List.nthLe_range'_1 #align list.range'_concat List.range'_concat #align list.range_core List.range.loop #align list.range_core_range' List.range_loop_range' #align list.range_eq_range' List.range_eq_range' #align list.range_succ_eq_map List.range_succ_eq_map #align list.range'_eq_map_range List.range'_eq_map_range #align list.length_range List.length_range #align list.range_eq_nil List.range_eq_nil theorem pairwise_lt_range (n : ℕ) : Pairwise (· < ·) (range n) := by simp (config := {decide := true}) only [range_eq_range', pairwise_lt_range'] #align list.pairwise_lt_range List.pairwise_lt_range theorem pairwise_le_range (n : ℕ) : Pairwise (· ≤ ·) (range n) := Pairwise.imp (@le_of_lt ℕ _) (pairwise_lt_range _) #align list.pairwise_le_range List.pairwise_le_range theorem take_range (m n : ℕ) : take m (range n) = range (min m n) := by apply List.ext_get · simp · simp (config := { contextual := true }) [← get_take, Nat.lt_min] theorem nodup_range (n : ℕ) : Nodup (range n) := by simp (config := {decide := true}) only [range_eq_range', nodup_range'] #align list.nodup_range List.nodup_range #align list.range_sublist List.range_sublist #align list.range_subset List.range_subset #align list.mem_range List.mem_range #align list.not_mem_range_self List.not_mem_range_self #align list.self_mem_range_succ List.self_mem_range_succ #align list.nth_range List.get?_range #align list.range_succ List.range_succ #align list.range_zero List.range_zero theorem chain'_range_succ (r : ℕ → ℕ → Prop) (n : ℕ) : Chain' r (range n.succ) ↔ ∀ m < n, r m m.succ := by rw [range_succ] induction' n with n hn · simp · rw [range_succ] simp only [append_assoc, singleton_append, chain'_append_cons_cons, chain'_singleton, and_true_iff] rw [hn, forall_lt_succ] #align list.chain'_range_succ List.chain'_range_succ theorem chain_range_succ (r : ℕ → ℕ → Prop) (n a : ℕ) : Chain r a (range n.succ) ↔ r a 0 ∧ ∀ m < n, r m m.succ := by rw [range_succ_eq_map, chain_cons, and_congr_right_iff, ← chain'_range_succ, range_succ_eq_map] exact fun _ => Iff.rfl #align list.chain_range_succ List.chain_range_succ #align list.range_add List.range_add #align list.iota_eq_reverse_range' List.iota_eq_reverse_range' #align list.length_iota List.length_iota
Mathlib/Data/List/Range.lean
125
126
theorem pairwise_gt_iota (n : ℕ) : Pairwise (· > ·) (iota n) := by
simpa only [iota_eq_reverse_range', pairwise_reverse] using pairwise_lt_range' 1 n
/- 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.Init.Function #align_import data.option.n_ary from "leanprover-community/mathlib"@"995b47e555f1b6297c7cf16855f1023e355219fb" /-! # Binary map of options This file defines the binary map of `Option`. This is mostly useful to define pointwise operations on intervals. ## Main declarations * `Option.map₂`: Binary map of options. ## Notes This file is very similar to the n-ary section of `Mathlib.Data.Set.Basic`, to `Mathlib.Data.Finset.NAry` and to `Mathlib.Order.Filter.NAry`. Please keep them in sync. (porting note - only some of these may exist right now!) We do not define `Option.map₃` as its only purpose so far would be to prove properties of `Option.map₂` and casing already fulfills this task. -/ universe u open Function namespace Option variable {α β γ δ : Type*} {f : α → β → γ} {a : Option α} {b : Option β} {c : Option γ} /-- The image of a binary function `f : α → β → γ` as a function `Option α → Option β → Option γ`. Mathematically this should be thought of as the image of the corresponding function `α × β → γ`. -/ def map₂ (f : α → β → γ) (a : Option α) (b : Option β) : Option γ := a.bind fun a => b.map <| f a #align option.map₂ Option.map₂ /-- `Option.map₂` in terms of monadic operations. Note that this can't be taken as the definition because of the lack of universe polymorphism. -/ theorem map₂_def {α β γ : Type u} (f : α → β → γ) (a : Option α) (b : Option β) : map₂ f a b = f <$> a <*> b := by cases a <;> rfl #align option.map₂_def Option.map₂_def -- Porting note (#10618): In Lean3, was `@[simp]` but now `simp` can prove it theorem map₂_some_some (f : α → β → γ) (a : α) (b : β) : map₂ f (some a) (some b) = f a b := rfl #align option.map₂_some_some Option.map₂_some_some theorem map₂_coe_coe (f : α → β → γ) (a : α) (b : β) : map₂ f a b = f a b := rfl #align option.map₂_coe_coe Option.map₂_coe_coe @[simp] theorem map₂_none_left (f : α → β → γ) (b : Option β) : map₂ f none b = none := rfl #align option.map₂_none_left Option.map₂_none_left @[simp] theorem map₂_none_right (f : α → β → γ) (a : Option α) : map₂ f a none = none := by cases a <;> rfl #align option.map₂_none_right Option.map₂_none_right @[simp] theorem map₂_coe_left (f : α → β → γ) (a : α) (b : Option β) : map₂ f a b = b.map fun b => f a b := rfl #align option.map₂_coe_left Option.map₂_coe_left -- Porting note: This proof was `rfl` in Lean3, but now is not. @[simp] theorem map₂_coe_right (f : α → β → γ) (a : Option α) (b : β) : map₂ f a b = a.map fun a => f a b := by cases a <;> rfl #align option.map₂_coe_right Option.map₂_coe_right -- Porting note: Removed the `@[simp]` tag as membership of an `Option` is no-longer simp-normal. theorem mem_map₂_iff {c : γ} : c ∈ map₂ f a b ↔ ∃ a' b', a' ∈ a ∧ b' ∈ b ∧ f a' b' = c := by simp [map₂, bind_eq_some] #align option.mem_map₂_iff Option.mem_map₂_iff @[simp] theorem map₂_eq_none_iff : map₂ f a b = none ↔ a = none ∨ b = none := by cases a <;> cases b <;> simp #align option.map₂_eq_none_iff Option.map₂_eq_none_iff theorem map₂_swap (f : α → β → γ) (a : Option α) (b : Option β) : map₂ f a b = map₂ (fun a b => f b a) b a := by cases a <;> cases b <;> rfl #align option.map₂_swap Option.map₂_swap
Mathlib/Data/Option/NAry.lean
91
92
theorem map_map₂ (f : α → β → γ) (g : γ → δ) : (map₂ f a b).map g = map₂ (fun a b => g (f a b)) a b := by
cases a <;> cases b <;> rfl
/- Copyright (c) 2024 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Order.Sublattice import Mathlib.Order.Hom.CompleteLattice /-! # Complete Sublattices This file defines complete sublattices. These are subsets of complete lattices which are closed under arbitrary suprema and infima. As a standard example one could take the complete sublattice of invariant submodules of some module with respect to a linear map. ## Main definitions: * `CompleteSublattice`: the definition of a complete sublattice * `CompleteSublattice.mk'`: an alternate constructor for a complete sublattice, demanding fewer hypotheses * `CompleteSublattice.instCompleteLattice`: a complete sublattice is a complete lattice * `CompleteSublattice.map`: complete sublattices push forward under complete lattice morphisms. * `CompleteSublattice.comap`: complete sublattices pull back under complete lattice morphisms. -/ open Function Set variable (α β : Type*) [CompleteLattice α] [CompleteLattice β] (f : CompleteLatticeHom α β) /-- A complete sublattice is a subset of a complete lattice that is closed under arbitrary suprema and infima. -/ structure CompleteSublattice extends Sublattice α where sSupClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sSup s ∈ carrier sInfClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sInf s ∈ carrier variable {α β} namespace CompleteSublattice /-- To check that a subset is a complete sublattice, one does not need to check that it is closed under binary `Sup` since this follows from the stronger `sSup` condition. Likewise for infima. -/ @[simps] def mk' (carrier : Set α) (sSupClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sSup s ∈ carrier) (sInfClosed' : ∀ ⦃s : Set α⦄, s ⊆ carrier → sInf s ∈ carrier) : CompleteSublattice α where carrier := carrier sSupClosed' := sSupClosed' sInfClosed' := sInfClosed' supClosed' := fun x hx y hy ↦ by suffices x ⊔ y = sSup {x, y} by exact this ▸ sSupClosed' (fun z hz ↦ by aesop) simp [sSup_singleton] infClosed' := fun x hx y hy ↦ by suffices x ⊓ y = sInf {x, y} by exact this ▸ sInfClosed' (fun z hz ↦ by aesop) simp [sInf_singleton] variable {L : CompleteSublattice α} instance instSetLike : SetLike (CompleteSublattice α) α where coe L := L.carrier coe_injective' L M h := by cases L; cases M; congr; exact SetLike.coe_injective' h instance instBot : Bot L where bot := ⟨⊥, by simpa using L.sSupClosed' <| empty_subset _⟩ instance instTop : Top L where top := ⟨⊤, by simpa using L.sInfClosed' <| empty_subset _⟩ instance instSupSet : SupSet L where sSup s := ⟨sSup s, L.sSupClosed' image_val_subset⟩ instance instInfSet : InfSet L where sInf s := ⟨sInf s, L.sInfClosed' image_val_subset⟩ theorem sSupClosed {s : Set α} (h : s ⊆ L) : sSup s ∈ L := L.sSupClosed' h theorem sInfClosed {s : Set α} (h : s ⊆ L) : sInf s ∈ L := L.sInfClosed' h @[simp] theorem coe_bot : (↑(⊥ : L) : α) = ⊥ := rfl @[simp] theorem coe_top : (↑(⊤ : L) : α) = ⊤ := rfl @[simp] theorem coe_sSup (S : Set L) : (↑(sSup S) : α) = sSup {(s : α) | s ∈ S} := rfl
Mathlib/Order/CompleteSublattice.lean
84
85
theorem coe_sSup' (S : Set L) : (↑(sSup S) : α) = ⨆ N ∈ S, (N : α) := by
rw [coe_sSup, ← Set.image, sSup_image]
/- Copyright (c) 2022 Yuma Mizuno. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yuma Mizuno -/ import Mathlib.CategoryTheory.Bicategory.Functor.Oplax #align_import category_theory.bicategory.natural_transformation from "leanprover-community/mathlib"@"4ff75f5b8502275a4c2eb2d2f02bdf84d7fb8993" /-! # Oplax natural transformations Just as there are natural transformations between functors, there are oplax natural transformations between oplax functors. The equality in the naturality of natural transformations is replaced by a specified 2-morphism `F.map f ≫ app b ⟶ app a ≫ G.map f` in the case of oplax natural transformations. ## Main definitions * `OplaxNatTrans F G` : oplax natural transformations between oplax functors `F` and `G` * `OplaxNatTrans.vcomp η θ` : the vertical composition of oplax natural transformations `η` and `θ` * `OplaxNatTrans.category F G` : the category structure on the oplax natural transformations between `F` and `G` -/ namespace CategoryTheory open Category Bicategory open scoped Bicategory universe w₁ w₂ v₁ v₂ u₁ u₂ variable {B : Type u₁} [Bicategory.{w₁, v₁} B] {C : Type u₂} [Bicategory.{w₂, v₂} C] /-- If `η` is an oplax natural transformation between `F` and `G`, we have a 1-morphism `η.app a : F.obj a ⟶ G.obj a` for each object `a : B`. We also have a 2-morphism `η.naturality f : F.map f ≫ app b ⟶ app a ≫ G.map f` for each 1-morphism `f : a ⟶ b`. These 2-morphisms satisfies the naturality condition, and preserve the identities and the compositions modulo some adjustments of domains and codomains of 2-morphisms. -/ structure OplaxNatTrans (F G : OplaxFunctor B C) where app (a : B) : F.obj a ⟶ G.obj a naturality {a b : B} (f : a ⟶ b) : F.map f ≫ app b ⟶ app a ≫ G.map f naturality_naturality : ∀ {a b : B} {f g : a ⟶ b} (η : f ⟶ g), F.map₂ η ▷ app b ≫ naturality g = naturality f ≫ app a ◁ G.map₂ η := by aesop_cat naturality_id : ∀ a : B, naturality (𝟙 a) ≫ app a ◁ G.mapId a = F.mapId a ▷ app a ≫ (λ_ (app a)).hom ≫ (ρ_ (app a)).inv := by aesop_cat naturality_comp : ∀ {a b c : B} (f : a ⟶ b) (g : b ⟶ c), naturality (f ≫ g) ≫ app a ◁ G.mapComp f g = F.mapComp f g ▷ app c ≫ (α_ _ _ _).hom ≫ F.map f ◁ naturality g ≫ (α_ _ _ _).inv ≫ naturality f ▷ G.map g ≫ (α_ _ _ _).hom := by aesop_cat #align category_theory.oplax_nat_trans CategoryTheory.OplaxNatTrans #align category_theory.oplax_nat_trans.app CategoryTheory.OplaxNatTrans.app #align category_theory.oplax_nat_trans.naturality CategoryTheory.OplaxNatTrans.naturality #align category_theory.oplax_nat_trans.naturality_naturality' CategoryTheory.OplaxNatTrans.naturality_naturality #align category_theory.oplax_nat_trans.naturality_naturality CategoryTheory.OplaxNatTrans.naturality_naturality #align category_theory.oplax_nat_trans.naturality_id' CategoryTheory.OplaxNatTrans.naturality_id #align category_theory.oplax_nat_trans.naturality_id CategoryTheory.OplaxNatTrans.naturality_id #align category_theory.oplax_nat_trans.naturality_comp' CategoryTheory.OplaxNatTrans.naturality_comp #align category_theory.oplax_nat_trans.naturality_comp CategoryTheory.OplaxNatTrans.naturality_comp attribute [nolint docBlame] CategoryTheory.OplaxNatTrans.app CategoryTheory.OplaxNatTrans.naturality CategoryTheory.OplaxNatTrans.naturality_naturality CategoryTheory.OplaxNatTrans.naturality_id CategoryTheory.OplaxNatTrans.naturality_comp attribute [reassoc (attr := simp)] OplaxNatTrans.naturality_naturality OplaxNatTrans.naturality_id OplaxNatTrans.naturality_comp namespace OplaxNatTrans section variable (F : OplaxFunctor B C) /-- The identity oplax natural transformation. -/ @[simps] def id : OplaxNatTrans F F where app a := 𝟙 (F.obj a) naturality {a b} f := (ρ_ (F.map f)).hom ≫ (λ_ (F.map f)).inv #align category_theory.oplax_nat_trans.id CategoryTheory.OplaxNatTrans.id instance : Inhabited (OplaxNatTrans F F) := ⟨id F⟩ variable {F} {G H : OplaxFunctor B C} (η : OplaxNatTrans F G) (θ : OplaxNatTrans G H) section variable {a b c : B} {a' : C} @[reassoc (attr := simp)] theorem whiskerLeft_naturality_naturality (f : a' ⟶ G.obj a) {g h : a ⟶ b} (β : g ⟶ h) : f ◁ G.map₂ β ▷ θ.app b ≫ f ◁ θ.naturality h = f ◁ θ.naturality g ≫ f ◁ θ.app a ◁ H.map₂ β := by simp_rw [← whiskerLeft_comp, naturality_naturality] #align category_theory.oplax_nat_trans.whisker_left_naturality_naturality CategoryTheory.OplaxNatTrans.whiskerLeft_naturality_naturality @[reassoc (attr := simp)]
Mathlib/CategoryTheory/Bicategory/NaturalTransformation.lean
111
114
theorem whiskerRight_naturality_naturality {f g : a ⟶ b} (β : f ⟶ g) (h : G.obj b ⟶ a') : F.map₂ β ▷ η.app b ▷ h ≫ η.naturality g ▷ h = η.naturality f ▷ h ≫ (α_ _ _ _).hom ≫ η.app a ◁ G.map₂ β ▷ h ≫ (α_ _ _ _).inv := by
rw [← comp_whiskerRight, naturality_naturality, comp_whiskerRight, whisker_assoc]
/- 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.Module.LinearMap.Basic import Mathlib.RingTheory.HahnSeries.Basic #align_import ring_theory.hahn_series from "leanprover-community/mathlib"@"a484a7d0eade4e1268f4fb402859b6686037f965" /-! # Additive properties of Hahn series If `Γ` is ordered and `R` has zero, then `HahnSeries Γ R` consists of formal series over `Γ` with coefficients in `R`, whose supports are partially well-ordered. With further structure on `R` and `Γ`, we can add further structure on `HahnSeries Γ R`. When `R` has an addition operation, `HahnSeries Γ R` also has addition by adding coefficients. ## Main Definitions * If `R` is a (commutative) additive monoid or group, then so is `HahnSeries Γ R`. ## References - [J. van der Hoeven, *Operators on Generalized Power Series*][van_der_hoeven] -/ set_option linter.uppercaseLean3 false open Finset Function open scoped Classical noncomputable section variable {Γ R : Type*} namespace HahnSeries section Addition variable [PartialOrder Γ] section AddMonoid variable [AddMonoid R] instance : Add (HahnSeries Γ R) where add x y := { coeff := x.coeff + y.coeff isPWO_support' := (x.isPWO_support.union y.isPWO_support).mono (Function.support_add _ _) } instance : AddMonoid (HahnSeries Γ R) where zero := 0 add := (· + ·) nsmul := nsmulRec add_assoc x y z := by ext apply add_assoc zero_add x := by ext apply zero_add add_zero x := by ext apply add_zero @[simp] theorem add_coeff' {x y : HahnSeries Γ R} : (x + y).coeff = x.coeff + y.coeff := rfl #align hahn_series.add_coeff' HahnSeries.add_coeff' theorem add_coeff {x y : HahnSeries Γ R} {a : Γ} : (x + y).coeff a = x.coeff a + y.coeff a := rfl #align hahn_series.add_coeff HahnSeries.add_coeff theorem support_add_subset {x y : HahnSeries Γ R} : support (x + y) ⊆ support x ∪ support y := fun a ha => by rw [mem_support, add_coeff] at ha rw [Set.mem_union, mem_support, mem_support] contrapose! ha rw [ha.1, ha.2, add_zero] #align hahn_series.support_add_subset HahnSeries.support_add_subset theorem min_order_le_order_add {Γ} [Zero Γ] [LinearOrder Γ] {x y : HahnSeries Γ R} (hxy : x + y ≠ 0) : min x.order y.order ≤ (x + y).order := by by_cases hx : x = 0; · simp [hx] by_cases hy : y = 0; · simp [hy] rw [order_of_ne hx, order_of_ne hy, order_of_ne hxy] apply le_of_eq_of_le _ (Set.IsWF.min_le_min_of_subset (support_add_subset (x := x) (y := y))) · simp · simp [hy] · exact (Set.IsWF.min_union _ _ _ _).symm #align hahn_series.min_order_le_order_add HahnSeries.min_order_le_order_add /-- `single` as an additive monoid/group homomorphism -/ @[simps!] def single.addMonoidHom (a : Γ) : R →+ HahnSeries Γ R := { single a with map_add' := fun x y => by ext b by_cases h : b = a <;> simp [h] } #align hahn_series.single.add_monoid_hom HahnSeries.single.addMonoidHom /-- `coeff g` as an additive monoid/group homomorphism -/ @[simps] def coeff.addMonoidHom (g : Γ) : HahnSeries Γ R →+ R where toFun f := f.coeff g map_zero' := zero_coeff map_add' _ _ := add_coeff #align hahn_series.coeff.add_monoid_hom HahnSeries.coeff.addMonoidHom section Domain variable {Γ' : Type*} [PartialOrder Γ'] theorem embDomain_add (f : Γ ↪o Γ') (x y : HahnSeries Γ R) : embDomain f (x + y) = embDomain f x + embDomain f y := by ext g by_cases hg : g ∈ Set.range f · obtain ⟨a, rfl⟩ := hg simp · simp [embDomain_notin_range hg] #align hahn_series.emb_domain_add HahnSeries.embDomain_add end Domain end AddMonoid instance [AddCommMonoid R] : AddCommMonoid (HahnSeries Γ R) := { inferInstanceAs (AddMonoid (HahnSeries Γ R)) with add_comm := fun x y => by ext apply add_comm } section AddGroup variable [AddGroup R] instance : Neg (HahnSeries Γ R) where neg x := { coeff := fun a => -x.coeff a isPWO_support' := by rw [Function.support_neg] exact x.isPWO_support } instance : AddGroup (HahnSeries Γ R) := { inferInstanceAs (AddMonoid (HahnSeries Γ R)) with zsmul := zsmulRec add_left_neg := fun x => by ext apply add_left_neg } @[simp] theorem neg_coeff' {x : HahnSeries Γ R} : (-x).coeff = -x.coeff := rfl #align hahn_series.neg_coeff' HahnSeries.neg_coeff' theorem neg_coeff {x : HahnSeries Γ R} {a : Γ} : (-x).coeff a = -x.coeff a := rfl #align hahn_series.neg_coeff HahnSeries.neg_coeff @[simp] theorem support_neg {x : HahnSeries Γ R} : (-x).support = x.support := by ext simp #align hahn_series.support_neg HahnSeries.support_neg @[simp] theorem sub_coeff' {x y : HahnSeries Γ R} : (x - y).coeff = x.coeff - y.coeff := by ext simp [sub_eq_add_neg] #align hahn_series.sub_coeff' HahnSeries.sub_coeff' theorem sub_coeff {x y : HahnSeries Γ R} {a : Γ} : (x - y).coeff a = x.coeff a - y.coeff a := by simp #align hahn_series.sub_coeff HahnSeries.sub_coeff @[simp]
Mathlib/RingTheory/HahnSeries/Addition.lean
176
179
theorem order_neg [Zero Γ] {f : HahnSeries Γ R} : (-f).order = f.order := by
by_cases hf : f = 0 · simp only [hf, neg_zero] simp only [order, support_neg, neg_eq_zero]
/- 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]
Mathlib/Data/List/ReduceOption.lean
55
57
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]
/- Copyright (c) 2018 Andreas Swerdlow. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andreas Swerdlow -/ import Mathlib.Algebra.Field.Basic import Mathlib.Deprecated.Subring #align_import deprecated.subfield from "leanprover-community/mathlib"@"bd9851ca476957ea4549eb19b40e7b5ade9428cc" /-! # Unbundled subfields (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 subfields. Instead of using this file, please use `Subfield`, defined in `FieldTheory.Subfield`, for subfields of fields. ## Main definitions `IsSubfield (S : Set F) : Prop` : the predicate that `S` is the underlying set of a subfield of the field `F`. The bundled variant `Subfield F` should be used in preference to this. ## Tags IsSubfield, subfield -/ variable {F : Type*} [Field F] (S : Set F) /-- `IsSubfield (S : Set F)` is the predicate saying that a given subset of a field is the set underlying a subfield. This structure is deprecated; use the bundled variant `Subfield F` to model subfields of a field. -/ structure IsSubfield extends IsSubring S : Prop where inv_mem : ∀ {x : F}, x ∈ S → x⁻¹ ∈ S #align is_subfield IsSubfield theorem IsSubfield.div_mem {S : Set F} (hS : IsSubfield S) {x y : F} (hx : x ∈ S) (hy : y ∈ S) : x / y ∈ S := by rw [div_eq_mul_inv] exact hS.toIsSubring.toIsSubmonoid.mul_mem hx (hS.inv_mem hy) #align is_subfield.div_mem IsSubfield.div_mem theorem IsSubfield.pow_mem {a : F} {n : ℤ} {s : Set F} (hs : IsSubfield s) (h : a ∈ s) : a ^ n ∈ s := by cases' n with n n · suffices a ^ (n : ℤ) ∈ s by exact this rw [zpow_natCast] exact hs.toIsSubring.toIsSubmonoid.pow_mem h · rw [zpow_negSucc] exact hs.inv_mem (hs.toIsSubring.toIsSubmonoid.pow_mem h) #align is_subfield.pow_mem IsSubfield.pow_mem theorem Univ.isSubfield : IsSubfield (@Set.univ F) := { Univ.isSubmonoid, IsAddSubgroup.univ_addSubgroup with inv_mem := fun _ ↦ trivial } #align univ.is_subfield Univ.isSubfield theorem Preimage.isSubfield {K : Type*} [Field K] (f : F →+* K) {s : Set K} (hs : IsSubfield s) : IsSubfield (f ⁻¹' s) := { f.isSubring_preimage hs.toIsSubring with inv_mem := fun {a} (ha : f a ∈ s) ↦ show f a⁻¹ ∈ s by rw [map_inv₀] exact hs.inv_mem ha } #align preimage.is_subfield Preimage.isSubfield theorem Image.isSubfield {K : Type*} [Field K] (f : F →+* K) {s : Set F} (hs : IsSubfield s) : IsSubfield (f '' s) := { f.isSubring_image hs.toIsSubring with inv_mem := fun ⟨x, xmem, ha⟩ ↦ ⟨x⁻¹, hs.inv_mem xmem, ha ▸ map_inv₀ f x⟩ } #align image.is_subfield Image.isSubfield theorem Range.isSubfield {K : Type*} [Field K] (f : F →+* K) : IsSubfield (Set.range f) := by rw [← Set.image_univ] apply Image.isSubfield _ Univ.isSubfield #align range.is_subfield Range.isSubfield namespace Field /-- `Field.closure s` is the minimal subfield that includes `s`. -/ def closure : Set F := { x | ∃ y ∈ Ring.closure S, ∃ z ∈ Ring.closure S, y / z = x } #align field.closure Field.closure variable {S} theorem ring_closure_subset : Ring.closure S ⊆ closure S := fun x hx ↦ ⟨x, hx, 1, Ring.closure.isSubring.toIsSubmonoid.one_mem, div_one x⟩ #align field.ring_closure_subset Field.ring_closure_subset
Mathlib/Deprecated/Subfield.lean
93
99
theorem closure.isSubmonoid : IsSubmonoid (closure S) := { mul_mem := by
rintro _ _ ⟨p, hp, q, hq, hq0, rfl⟩ ⟨r, hr, s, hs, hs0, rfl⟩ exact ⟨p * r, IsSubmonoid.mul_mem Ring.closure.isSubring.toIsSubmonoid hp hr, q * s, IsSubmonoid.mul_mem Ring.closure.isSubring.toIsSubmonoid hq hs, (div_mul_div_comm _ _ _ _).symm⟩ one_mem := ring_closure_subset <| IsSubmonoid.one_mem Ring.closure.isSubring.toIsSubmonoid }
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl -/ import Mathlib.MeasureTheory.Measure.Typeclasses import Mathlib.MeasureTheory.Measure.MutuallySingular import Mathlib.MeasureTheory.MeasurableSpace.CountablyGenerated /-! # Dirac measure In this file we define the Dirac measure `MeasureTheory.Measure.dirac a` and prove some basic facts about it. -/ open Function Set open scoped ENNReal Classical noncomputable section variable {α β δ : Type*} [MeasurableSpace α] [MeasurableSpace β] {s : Set α} {a : α} namespace MeasureTheory namespace Measure /-- The dirac measure. -/ def dirac (a : α) : Measure α := (OuterMeasure.dirac a).toMeasure (by simp) #align measure_theory.measure.dirac MeasureTheory.Measure.dirac instance : MeasureSpace PUnit := ⟨dirac PUnit.unit⟩ theorem le_dirac_apply {a} : s.indicator 1 a ≤ dirac a s := OuterMeasure.dirac_apply a s ▸ le_toMeasure_apply _ _ _ #align measure_theory.measure.le_dirac_apply MeasureTheory.Measure.le_dirac_apply @[simp] theorem dirac_apply' (a : α) (hs : MeasurableSet s) : dirac a s = s.indicator 1 a := toMeasure_apply _ _ hs #align measure_theory.measure.dirac_apply' MeasureTheory.Measure.dirac_apply' @[simp] theorem dirac_apply_of_mem {a : α} (h : a ∈ s) : dirac a s = 1 := by have : ∀ t : Set α, a ∈ t → t.indicator (1 : α → ℝ≥0∞) a = 1 := fun t ht => indicator_of_mem ht 1 refine le_antisymm (this univ trivial ▸ ?_) (this s h ▸ le_dirac_apply) rw [← dirac_apply' a MeasurableSet.univ] exact measure_mono (subset_univ s) #align measure_theory.measure.dirac_apply_of_mem MeasureTheory.Measure.dirac_apply_of_mem @[simp] theorem dirac_apply [MeasurableSingletonClass α] (a : α) (s : Set α) : dirac a s = s.indicator 1 a := by by_cases h : a ∈ s; · rw [dirac_apply_of_mem h, indicator_of_mem h, Pi.one_apply] rw [indicator_of_not_mem h, ← nonpos_iff_eq_zero] calc dirac a s ≤ dirac a {a}ᶜ := measure_mono (subset_compl_comm.1 <| singleton_subset_iff.2 h) _ = 0 := by simp [dirac_apply' _ (measurableSet_singleton _).compl] #align measure_theory.measure.dirac_apply MeasureTheory.Measure.dirac_apply theorem map_dirac {f : α → β} (hf : Measurable f) (a : α) : (dirac a).map f = dirac (f a) := ext fun s hs => by simp [hs, map_apply hf hs, hf hs, indicator_apply] #align measure_theory.measure.map_dirac MeasureTheory.Measure.map_dirac lemma map_const (μ : Measure α) (c : β) : μ.map (fun _ ↦ c) = (μ Set.univ) • dirac c := by ext s hs simp only [aemeasurable_const, measurable_const, Measure.coe_smul, Pi.smul_apply, dirac_apply' _ hs, smul_eq_mul] classical rw [Measure.map_apply measurable_const hs, Set.preimage_const] by_cases hsc : c ∈ s · rw [(Set.indicator_eq_one_iff_mem _).mpr hsc, mul_one, if_pos hsc] · rw [if_neg hsc, (Set.indicator_eq_zero_iff_not_mem _).mpr hsc, measure_empty, mul_zero] @[simp] theorem restrict_singleton (μ : Measure α) (a : α) : μ.restrict {a} = μ {a} • dirac a := by ext1 s hs by_cases ha : a ∈ s · have : s ∩ {a} = {a} := by simpa simp [*] · have : s ∩ {a} = ∅ := inter_singleton_eq_empty.2 ha simp [*] #align measure_theory.measure.restrict_singleton MeasureTheory.Measure.restrict_singleton /-- If `f` is a map with countable codomain, then `μ.map f` is a sum of Dirac measures. -/ theorem map_eq_sum [Countable β] [MeasurableSingletonClass β] (μ : Measure α) (f : α → β) (hf : Measurable f) : μ.map f = sum fun b : β => μ (f ⁻¹' {b}) • dirac b := by ext s have : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y}) := fun y _ => hf (measurableSet_singleton _) simp [← tsum_measure_preimage_singleton (to_countable s) this, *, tsum_subtype s fun b => μ (f ⁻¹' {b}), ← indicator_mul_right s fun b => μ (f ⁻¹' {b})] #align measure_theory.measure.map_eq_sum MeasureTheory.Measure.map_eq_sum /-- A measure on a countable type is a sum of Dirac measures. -/ @[simp] theorem sum_smul_dirac [Countable α] [MeasurableSingletonClass α] (μ : Measure α) : (sum fun a => μ {a} • dirac a) = μ := by simpa using (map_eq_sum μ id measurable_id).symm #align measure_theory.measure.sum_smul_dirac MeasureTheory.Measure.sum_smul_dirac /-- Given that `α` is a countable, measurable space with all singleton sets measurable, write the measure of a set `s` as the sum of the measure of `{x}` for all `x ∈ s`. -/ theorem tsum_indicator_apply_singleton [Countable α] [MeasurableSingletonClass α] (μ : Measure α) (s : Set α) (hs : MeasurableSet s) : (∑' x : α, s.indicator (fun x => μ {x}) x) = μ s := calc (∑' x : α, s.indicator (fun x => μ {x}) x) = Measure.sum (fun a => μ {a} • Measure.dirac a) s := by simp only [Measure.sum_apply _ hs, Measure.smul_apply, smul_eq_mul, Measure.dirac_apply, Set.indicator_apply, mul_ite, Pi.one_apply, mul_one, mul_zero] _ = μ s := by rw [μ.sum_smul_dirac] #align measure_theory.measure.tsum_indicator_apply_singleton MeasureTheory.Measure.tsum_indicator_apply_singleton end Measure open Measure
Mathlib/MeasureTheory/Measure/Dirac.lean
117
118
theorem mem_ae_dirac_iff {a : α} (hs : MeasurableSet s) : s ∈ ae (dirac a) ↔ a ∈ s := by
by_cases a ∈ s <;> simp [mem_ae_iff, dirac_apply', hs.compl, indicator_apply, *]
/- Copyright (c) 2021 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.CategoryTheory.Limits.ConeCategory import Mathlib.CategoryTheory.Limits.FilteredColimitCommutesFiniteLimit import Mathlib.CategoryTheory.Limits.Preserves.Filtered import Mathlib.CategoryTheory.Limits.Preserves.FunctorCategory import Mathlib.CategoryTheory.Limits.Bicones import Mathlib.CategoryTheory.Limits.Comma import Mathlib.CategoryTheory.Limits.Preserves.Finite import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits #align_import category_theory.functor.flat from "leanprover-community/mathlib"@"39478763114722f0ec7613cb2f3f7701f9b86c8d" /-! # Representably flat functors We define representably flat functors as functors such that the category of structured arrows over `X` is cofiltered for each `X`. This concept is also known as flat functors as in [Elephant] Remark C2.3.7, and this name is suggested by Mike Shulman in https://golem.ph.utexas.edu/category/2011/06/flat_functors_and_morphisms_of.html to avoid confusion with other notions of flatness. This definition is equivalent to left exact functors (functors that preserves finite limits) when `C` has all finite limits. ## Main results * `flat_of_preservesFiniteLimits`: If `F : C ⥤ D` preserves finite limits and `C` has all finite limits, then `F` is flat. * `preservesFiniteLimitsOfFlat`: If `F : C ⥤ D` is flat, then it preserves all finite limits. * `preservesFiniteLimitsIffFlat`: If `C` has all finite limits, then `F` is flat iff `F` is left_exact. * `lanPreservesFiniteLimitsOfFlat`: If `F : C ⥤ D` is a flat functor between small categories, then the functor `Lan F.op` between presheaves of sets preserves all finite limits. * `flat_iff_lan_flat`: If `C`, `D` are small and `C` has all finite limits, then `F` is flat iff `Lan F.op : (Cᵒᵖ ⥤ Type*) ⥤ (Dᵒᵖ ⥤ Type*)` is flat. * `preservesFiniteLimitsIffLanPreservesFiniteLimits`: If `C`, `D` are small and `C` has all finite limits, then `F` preserves finite limits iff `Lan F.op : (Cᵒᵖ ⥤ Type*) ⥤ (Dᵒᵖ ⥤ Type*)` does. -/ universe w v₁ v₂ v₃ u₁ u₂ u₃ open CategoryTheory open CategoryTheory.Limits open Opposite namespace CategoryTheory section RepresentablyFlat variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] variable {E : Type u₃} [Category.{v₃} E] /-- A functor `F : C ⥤ D` is representably-flat functor if the comma category `(X/F)` is cofiltered for each `X : C`. -/ class RepresentablyFlat (F : C ⥤ D) : Prop where cofiltered : ∀ X : D, IsCofiltered (StructuredArrow X F) #align category_theory.representably_flat CategoryTheory.RepresentablyFlat attribute [instance] RepresentablyFlat.cofiltered instance RepresentablyFlat.of_isRightAdjoint (F : C ⥤ D) [F.IsRightAdjoint] : RepresentablyFlat F where cofiltered _ := IsCofiltered.of_isInitial _ (mkInitialOfLeftAdjoint _ (.ofIsRightAdjoint F) _) theorem RepresentablyFlat.id : RepresentablyFlat (𝟭 C) := inferInstance #align category_theory.representably_flat.id CategoryTheory.RepresentablyFlat.id instance RepresentablyFlat.comp (F : C ⥤ D) (G : D ⥤ E) [RepresentablyFlat F] [RepresentablyFlat G] : RepresentablyFlat (F ⋙ G) := by refine ⟨fun X => IsCofiltered.of_cone_nonempty.{0} _ (fun {J} _ _ H => ?_)⟩ obtain ⟨c₁⟩ := IsCofiltered.cone_nonempty (H ⋙ StructuredArrow.pre X F G) let H₂ : J ⥤ StructuredArrow c₁.pt.right F := { obj := fun j => StructuredArrow.mk (c₁.π.app j).right map := fun {j j'} f => StructuredArrow.homMk (H.map f).right (congrArg CommaMorphism.right (c₁.w f)) } obtain ⟨c₂⟩ := IsCofiltered.cone_nonempty H₂ exact ⟨⟨StructuredArrow.mk (c₁.pt.hom ≫ G.map c₂.pt.hom), ⟨fun j => StructuredArrow.homMk (c₂.π.app j).right (by simp [← G.map_comp, (c₂.π.app j).w]), fun j j' f => by simpa using (c₂.w f).symm⟩⟩⟩ #align category_theory.representably_flat.comp CategoryTheory.RepresentablyFlat.comp end RepresentablyFlat section HasLimit variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D]
Mathlib/CategoryTheory/Functor/Flat.lean
97
106
theorem flat_of_preservesFiniteLimits [HasFiniteLimits C] (F : C ⥤ D) [PreservesFiniteLimits F] : RepresentablyFlat F := ⟨fun X => haveI : HasFiniteLimits (StructuredArrow X F) := by
apply hasFiniteLimits_of_hasFiniteLimits_of_size.{v₁} (StructuredArrow X F) intro J sJ fJ constructor -- Porting note: instance was inferred automatically in Lean 3 infer_instance IsCofiltered.of_hasFiniteLimits _⟩
/- 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.Algebra.Star.Basic import Mathlib.Data.Set.Finite import Mathlib.Data.Set.Pointwise.Basic #align_import algebra.star.pointwise from "leanprover-community/mathlib"@"30413fc89f202a090a54d78e540963ed3de0056e" /-! # Pointwise star operation on sets This file defines the star operation pointwise on sets and provides the basic API. Besides basic facts about how the star operation acts on sets (e.g., `(s ∩ t)⋆ = s⋆ ∩ t⋆`), if `s t : Set α`, then under suitable assumption on `α`, it is shown * `(s + t)⋆ = s⋆ + t⋆` * `(s * t)⋆ = t⋆ + s⋆` * `(s⁻¹)⋆ = (s⋆)⁻¹` -/ namespace Set open Pointwise local postfix:max "⋆" => star variable {α : Type*} {s t : Set α} {a : α} /-- The set `(star s : Set α)` is defined as `{x | star x ∈ s}` in the locale `Pointwise`. In the usual case where `star` is involutive, it is equal to `{star s | x ∈ s}`, see `Set.image_star`. -/ protected def star [Star α] : Star (Set α) := ⟨preimage Star.star⟩ #align set.has_star Set.star scoped[Pointwise] attribute [instance] Set.star @[simp] theorem star_empty [Star α] : (∅ : Set α)⋆ = ∅ := rfl #align set.star_empty Set.star_empty @[simp] theorem star_univ [Star α] : (univ : Set α)⋆ = univ := rfl #align set.star_univ Set.star_univ @[simp] theorem nonempty_star [InvolutiveStar α] {s : Set α} : s⋆.Nonempty ↔ s.Nonempty := star_involutive.surjective.nonempty_preimage #align set.nonempty_star Set.nonempty_star theorem Nonempty.star [InvolutiveStar α] {s : Set α} (h : s.Nonempty) : s⋆.Nonempty := nonempty_star.2 h #align set.nonempty.star Set.Nonempty.star @[simp] theorem mem_star [Star α] : a ∈ s⋆ ↔ a⋆ ∈ s := Iff.rfl #align set.mem_star Set.mem_star
Mathlib/Algebra/Star/Pointwise.lean
62
62
theorem star_mem_star [InvolutiveStar α] : a⋆ ∈ s⋆ ↔ a ∈ s := by
simp only [mem_star, star_star]
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl -/ import Mathlib.Order.Disjoint #align_import order.prop_instances from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1" /-! # The order on `Prop` Instances on `Prop` such as `DistribLattice`, `BoundedOrder`, `LinearOrder`. -/ /-- Propositions form a distributive lattice. -/ instance Prop.instDistribLattice : DistribLattice Prop where sup := Or le_sup_left := @Or.inl le_sup_right := @Or.inr sup_le := fun _ _ _ => Or.rec inf := And inf_le_left := @And.left inf_le_right := @And.right le_inf := fun _ _ _ Hab Hac Ha => And.intro (Hab Ha) (Hac Ha) le_sup_inf := fun _ _ _ => or_and_left.2 #align Prop.distrib_lattice Prop.instDistribLattice /-- Propositions form a bounded order. -/ instance Prop.instBoundedOrder : BoundedOrder Prop where top := True le_top _ _ := True.intro bot := False bot_le := @False.elim #align Prop.bounded_order Prop.instBoundedOrder @[simp] theorem Prop.bot_eq_false : (⊥ : Prop) = False := rfl #align Prop.bot_eq_false Prop.bot_eq_false @[simp] theorem Prop.top_eq_true : (⊤ : Prop) = True := rfl #align Prop.top_eq_true Prop.top_eq_true instance Prop.le_isTotal : IsTotal Prop (· ≤ ·) := ⟨fun p q => by by_cases h : q <;> simp [h]⟩ #align Prop.le_is_total Prop.le_isTotal noncomputable instance Prop.linearOrder : LinearOrder Prop := by classical exact Lattice.toLinearOrder Prop #align Prop.linear_order Prop.linearOrder @[simp] theorem sup_Prop_eq : (· ⊔ ·) = (· ∨ ·) := rfl #align sup_Prop_eq sup_Prop_eq @[simp] theorem inf_Prop_eq : (· ⊓ ·) = (· ∧ ·) := rfl #align inf_Prop_eq inf_Prop_eq namespace Pi variable {ι : Type*} {α' : ι → Type*} [∀ i, PartialOrder (α' i)] theorem disjoint_iff [∀ i, OrderBot (α' i)] {f g : ∀ i, α' i} : Disjoint f g ↔ ∀ i, Disjoint (f i) (g i) := by classical constructor · intro h i x hf hg exact (update_le_iff.mp <| h (update_le_iff.mpr ⟨hf, fun _ _ => bot_le⟩) (update_le_iff.mpr ⟨hg, fun _ _ => bot_le⟩)).1 · intro h x hf hg i apply h i (hf i) (hg i) #align pi.disjoint_iff Pi.disjoint_iff theorem codisjoint_iff [∀ i, OrderTop (α' i)] {f g : ∀ i, α' i} : Codisjoint f g ↔ ∀ i, Codisjoint (f i) (g i) := @disjoint_iff _ (fun i => (α' i)ᵒᵈ) _ _ _ _ #align pi.codisjoint_iff Pi.codisjoint_iff theorem isCompl_iff [∀ i, BoundedOrder (α' i)] {f g : ∀ i, α' i} : IsCompl f g ↔ ∀ i, IsCompl (f i) (g i) := by simp_rw [_root_.isCompl_iff, disjoint_iff, codisjoint_iff, forall_and] #align pi.is_compl_iff Pi.isCompl_iff end Pi @[simp] theorem Prop.disjoint_iff {P Q : Prop} : Disjoint P Q ↔ ¬(P ∧ Q) := disjoint_iff_inf_le #align Prop.disjoint_iff Prop.disjoint_iff @[simp] theorem Prop.codisjoint_iff {P Q : Prop} : Codisjoint P Q ↔ P ∨ Q := codisjoint_iff_le_sup.trans <| forall_const True #align Prop.codisjoint_iff Prop.codisjoint_iff @[simp]
Mathlib/Order/PropInstances.lean
106
108
theorem Prop.isCompl_iff {P Q : Prop} : IsCompl P Q ↔ ¬(P ↔ Q) := by
rw [_root_.isCompl_iff, Prop.disjoint_iff, Prop.codisjoint_iff, not_iff] by_cases P <;> by_cases Q <;> 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.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] theorem convexJoin_singleton_left (t : Set E) (x : E) : convexJoin 𝕜 {x} t = ⋃ y ∈ t, segment 𝕜 x y := by simp [convexJoin] #align convex_join_singleton_left convexJoin_singleton_left @[simp] theorem convexJoin_singleton_right (s : Set E) (y : E) : convexJoin 𝕜 s {y} = ⋃ x ∈ s, segment 𝕜 x y := by simp [convexJoin] #align convex_join_singleton_right convexJoin_singleton_right -- Porting note (#10618): simp can prove it theorem convexJoin_singletons (x : E) : convexJoin 𝕜 {x} {y} = segment 𝕜 x y := by simp #align convex_join_singletons convexJoin_singletons @[simp] theorem convexJoin_union_left (s₁ s₂ t : Set E) : convexJoin 𝕜 (s₁ ∪ s₂) t = convexJoin 𝕜 s₁ t ∪ convexJoin 𝕜 s₂ t := by simp_rw [convexJoin, mem_union, iUnion_or, iUnion_union_distrib] #align convex_join_union_left convexJoin_union_left @[simp]
Mathlib/Analysis/Convex/Join.lean
85
87
theorem convexJoin_union_right (s t₁ t₂ : Set E) : convexJoin 𝕜 s (t₁ ∪ t₂) = convexJoin 𝕜 s t₁ ∪ convexJoin 𝕜 s t₂ := by
simp_rw [convexJoin_comm s, convexJoin_union_left]
/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Algebra.GroupWithZero.Invertible import Mathlib.Algebra.Ring.Defs #align_import algebra.invertible from "leanprover-community/mathlib"@"722b3b152ddd5e0cf21c0a29787c76596cb6b422" /-! # Theorems about invertible elements in rings -/ universe u variable {α : Type u} /-- `-⅟a` is the inverse of `-a` -/ def invertibleNeg [Mul α] [One α] [HasDistribNeg α] (a : α) [Invertible a] : Invertible (-a) := ⟨-⅟ a, by simp, by simp⟩ #align invertible_neg invertibleNeg @[simp] theorem invOf_neg [Monoid α] [HasDistribNeg α] (a : α) [Invertible a] [Invertible (-a)] : ⅟ (-a) = -⅟ a := invOf_eq_right_inv (by simp) #align inv_of_neg invOf_neg @[simp] theorem one_sub_invOf_two [Ring α] [Invertible (2 : α)] : 1 - (⅟ 2 : α) = ⅟ 2 := (isUnit_of_invertible (2 : α)).mul_right_inj.1 <| by rw [mul_sub, mul_invOf_self, mul_one, ← one_add_one_eq_two, add_sub_cancel_right] #align one_sub_inv_of_two one_sub_invOf_two @[simp] theorem invOf_two_add_invOf_two [NonAssocSemiring α] [Invertible (2 : α)] : (⅟ 2 : α) + (⅟ 2 : α) = 1 := by rw [← two_mul, mul_invOf_self] #align inv_of_two_add_inv_of_two invOf_two_add_invOf_two theorem pos_of_invertible_cast [Semiring α] [Nontrivial α] (n : ℕ) [Invertible (n : α)] : 0 < n := Nat.zero_lt_of_ne_zero fun h => nonzero_of_invertible (n : α) (h ▸ Nat.cast_zero) theorem invOf_add_invOf [Semiring α] (a b : α) [Invertible a] [Invertible b] : ⅟a + ⅟b = ⅟a * (a + b) * ⅟b:= by rw [mul_add, invOf_mul_self, add_mul, one_mul, mul_assoc, mul_invOf_self, mul_one, add_comm] /-- A version of `inv_sub_inv'` for `invOf`. -/ theorem invOf_sub_invOf [Ring α] (a b : α) [Invertible a] [Invertible b] : ⅟a - ⅟b = ⅟a * (b - a) * ⅟b := by rw [mul_sub, invOf_mul_self, sub_mul, one_mul, mul_assoc, mul_invOf_self, mul_one] /-- A version of `inv_add_inv'` for `Ring.inverse`. -/ theorem Ring.inverse_add_inverse [Semiring α] {a b : α} (h : IsUnit a ↔ IsUnit b) : Ring.inverse a + Ring.inverse b = Ring.inverse a * (a + b) * Ring.inverse b := by by_cases ha : IsUnit a · have hb := h.mp ha obtain ⟨ia⟩ := ha.nonempty_invertible obtain ⟨ib⟩ := hb.nonempty_invertible simp_rw [inverse_invertible, invOf_add_invOf] · have hb := h.not.mp ha simp [inverse_non_unit, ha, hb] /-- A version of `inv_sub_inv'` for `Ring.inverse`. -/
Mathlib/Algebra/Ring/Invertible.lean
65
73
theorem Ring.inverse_sub_inverse [Ring α] {a b : α} (h : IsUnit a ↔ IsUnit b) : Ring.inverse a - Ring.inverse b = Ring.inverse a * (b - a) * Ring.inverse b := by
by_cases ha : IsUnit a · have hb := h.mp ha obtain ⟨ia⟩ := ha.nonempty_invertible obtain ⟨ib⟩ := hb.nonempty_invertible simp_rw [inverse_invertible, invOf_sub_invOf] · have hb := h.not.mp ha simp [inverse_non_unit, ha, hb]
/- Copyright (c) 2020 Anatole Dedecker. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anatole Dedecker, Alexey Soloyev, Junyan Xu, Kamila Szewczyk -/ import Mathlib.Data.Real.Irrational import Mathlib.Data.Nat.Fib.Basic import Mathlib.Data.Fin.VecNotation import Mathlib.Algebra.LinearRecurrence import Mathlib.Tactic.NormNum.NatFib import Mathlib.Tactic.NormNum.Prime #align_import data.real.golden_ratio from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2" /-! # The golden ratio and its conjugate This file defines the golden ratio `φ := (1 + √5)/2` and its conjugate `ψ := (1 - √5)/2`, which are the two real roots of `X² - X - 1`. Along with various computational facts about them, we prove their irrationality, and we link them to the Fibonacci sequence by proving Binet's formula. -/ noncomputable section open Polynomial /-- The golden ratio `φ := (1 + √5)/2`. -/ abbrev goldenRatio : ℝ := (1 + √5) / 2 #align golden_ratio goldenRatio /-- The conjugate of the golden ratio `ψ := (1 - √5)/2`. -/ abbrev goldenConj : ℝ := (1 - √5) / 2 #align golden_conj goldenConj @[inherit_doc goldenRatio] scoped[goldenRatio] notation "φ" => goldenRatio @[inherit_doc goldenConj] scoped[goldenRatio] notation "ψ" => goldenConj open Real goldenRatio /-- The inverse of the golden ratio is the opposite of its conjugate. -/ theorem inv_gold : φ⁻¹ = -ψ := by have : 1 + √5 ≠ 0 := ne_of_gt (add_pos (by norm_num) <| Real.sqrt_pos.mpr (by norm_num)) field_simp [sub_mul, mul_add] norm_num #align inv_gold inv_gold /-- The opposite of the golden ratio is the inverse of its conjugate. -/ theorem inv_goldConj : ψ⁻¹ = -φ := by rw [inv_eq_iff_eq_inv, ← neg_inv, ← neg_eq_iff_eq_neg] exact inv_gold.symm #align inv_gold_conj inv_goldConj @[simp] theorem gold_mul_goldConj : φ * ψ = -1 := by field_simp rw [← sq_sub_sq] norm_num #align gold_mul_gold_conj gold_mul_goldConj @[simp] theorem goldConj_mul_gold : ψ * φ = -1 := by rw [mul_comm] exact gold_mul_goldConj #align gold_conj_mul_gold goldConj_mul_gold @[simp] theorem gold_add_goldConj : φ + ψ = 1 := by rw [goldenRatio, goldenConj] ring #align gold_add_gold_conj gold_add_goldConj theorem one_sub_goldConj : 1 - φ = ψ := by linarith [gold_add_goldConj] #align one_sub_gold_conj one_sub_goldConj theorem one_sub_gold : 1 - ψ = φ := by linarith [gold_add_goldConj] #align one_sub_gold one_sub_gold @[simp] theorem gold_sub_goldConj : φ - ψ = √5 := by ring #align gold_sub_gold_conj gold_sub_goldConj theorem gold_pow_sub_gold_pow (n : ℕ) : φ ^ (n + 2) - φ ^ (n + 1) = φ ^ n := by rw [goldenRatio]; ring_nf; norm_num; ring @[simp 1200] theorem gold_sq : φ ^ 2 = φ + 1 := by rw [goldenRatio, ← sub_eq_zero] ring_nf rw [Real.sq_sqrt] <;> norm_num #align gold_sq gold_sq @[simp 1200] theorem goldConj_sq : ψ ^ 2 = ψ + 1 := by rw [goldenConj, ← sub_eq_zero] ring_nf rw [Real.sq_sqrt] <;> norm_num #align gold_conj_sq goldConj_sq theorem gold_pos : 0 < φ := mul_pos (by apply add_pos <;> norm_num) <| inv_pos.2 zero_lt_two #align gold_pos gold_pos theorem gold_ne_zero : φ ≠ 0 := ne_of_gt gold_pos #align gold_ne_zero gold_ne_zero
Mathlib/Data/Real/GoldenRatio.lean
112
114
theorem one_lt_gold : 1 < φ := by
refine lt_of_mul_lt_mul_left ?_ (le_of_lt gold_pos) simp [← sq, gold_pos, zero_lt_one, - div_pow] -- Porting note: Added `- div_pow`
/- Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Violeta Hernández Palacios -/ import Mathlib.Order.SuccPred.Basic import Mathlib.Order.BoundedOrder #align_import order.succ_pred.limit from "leanprover-community/mathlib"@"1e05171a5e8cf18d98d9cf7b207540acb044acae" /-! # Successor and predecessor limits We define the predicate `Order.IsSuccLimit` for "successor limits", values that don't cover any others. They are so named since they can't be the successors of anything smaller. We define `Order.IsPredLimit` analogously, and prove basic results. ## Todo The plan is to eventually replace `Ordinal.IsLimit` and `Cardinal.IsLimit` with the common predicate `Order.IsSuccLimit`. -/ variable {α : Type*} namespace Order open Function Set OrderDual /-! ### Successor limits -/ section LT variable [LT α] /-- A successor limit is a value that doesn't cover any other. It's so named because in a successor order, a successor limit can't be the successor of anything smaller. -/ def IsSuccLimit (a : α) : Prop := ∀ b, ¬b ⋖ a #align order.is_succ_limit Order.IsSuccLimit theorem not_isSuccLimit_iff_exists_covBy (a : α) : ¬IsSuccLimit a ↔ ∃ b, b ⋖ a := by simp [IsSuccLimit] #align order.not_is_succ_limit_iff_exists_covby Order.not_isSuccLimit_iff_exists_covBy @[simp] theorem isSuccLimit_of_dense [DenselyOrdered α] (a : α) : IsSuccLimit a := fun _ => not_covBy #align order.is_succ_limit_of_dense Order.isSuccLimit_of_dense end LT section Preorder variable [Preorder α] {a : α} protected theorem _root_.IsMin.isSuccLimit : IsMin a → IsSuccLimit a := fun h _ hab => not_isMin_of_lt hab.lt h #align is_min.is_succ_limit IsMin.isSuccLimit theorem isSuccLimit_bot [OrderBot α] : IsSuccLimit (⊥ : α) := IsMin.isSuccLimit isMin_bot #align order.is_succ_limit_bot Order.isSuccLimit_bot variable [SuccOrder α] protected theorem IsSuccLimit.isMax (h : IsSuccLimit (succ a)) : IsMax a := by by_contra H exact h a (covBy_succ_of_not_isMax H) #align order.is_succ_limit.is_max Order.IsSuccLimit.isMax theorem not_isSuccLimit_succ_of_not_isMax (ha : ¬IsMax a) : ¬IsSuccLimit (succ a) := by contrapose! ha exact ha.isMax #align order.not_is_succ_limit_succ_of_not_is_max Order.not_isSuccLimit_succ_of_not_isMax section NoMaxOrder variable [NoMaxOrder α] theorem IsSuccLimit.succ_ne (h : IsSuccLimit a) (b : α) : succ b ≠ a := by rintro rfl exact not_isMax _ h.isMax #align order.is_succ_limit.succ_ne Order.IsSuccLimit.succ_ne @[simp] theorem not_isSuccLimit_succ (a : α) : ¬IsSuccLimit (succ a) := fun h => h.succ_ne _ rfl #align order.not_is_succ_limit_succ Order.not_isSuccLimit_succ end NoMaxOrder section IsSuccArchimedean variable [IsSuccArchimedean α] theorem IsSuccLimit.isMin_of_noMax [NoMaxOrder α] (h : IsSuccLimit a) : IsMin a := fun b hb => by rcases hb.exists_succ_iterate with ⟨_ | n, rfl⟩ · exact le_rfl · rw [iterate_succ_apply'] at h exact (not_isSuccLimit_succ _ h).elim #align order.is_succ_limit.is_min_of_no_max Order.IsSuccLimit.isMin_of_noMax @[simp] theorem isSuccLimit_iff_of_noMax [NoMaxOrder α] : IsSuccLimit a ↔ IsMin a := ⟨IsSuccLimit.isMin_of_noMax, IsMin.isSuccLimit⟩ #align order.is_succ_limit_iff_of_no_max Order.isSuccLimit_iff_of_noMax theorem not_isSuccLimit_of_noMax [NoMinOrder α] [NoMaxOrder α] : ¬IsSuccLimit a := by simp #align order.not_is_succ_limit_of_no_max Order.not_isSuccLimit_of_noMax end IsSuccArchimedean end Preorder section PartialOrder variable [PartialOrder α] [SuccOrder α] {a b : α} {C : α → Sort*} theorem isSuccLimit_of_succ_ne (h : ∀ b, succ b ≠ a) : IsSuccLimit a := fun b hba => h b (CovBy.succ_eq hba) #align order.is_succ_limit_of_succ_ne Order.isSuccLimit_of_succ_ne theorem not_isSuccLimit_iff : ¬IsSuccLimit a ↔ ∃ b, ¬IsMax b ∧ succ b = a := by rw [not_isSuccLimit_iff_exists_covBy] refine exists_congr fun b => ⟨fun hba => ⟨hba.lt.not_isMax, (CovBy.succ_eq hba)⟩, ?_⟩ rintro ⟨h, rfl⟩ exact covBy_succ_of_not_isMax h #align order.not_is_succ_limit_iff Order.not_isSuccLimit_iff /-- See `not_isSuccLimit_iff` for a version that states that `a` is a successor of a value other than itself. -/
Mathlib/Order/SuccPred/Limit.lean
135
137
theorem mem_range_succ_of_not_isSuccLimit (h : ¬IsSuccLimit a) : a ∈ range (@succ α _ _) := by
cases' not_isSuccLimit_iff.1 h with b hb exact ⟨b, hb.2⟩
/- Copyright (c) 2020 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers -/ import Mathlib.Analysis.SpecialFunctions.Trigonometric.Arctan import Mathlib.Geometry.Euclidean.Angle.Unoriented.Affine #align_import geometry.euclidean.angle.unoriented.right_angle from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5" /-! # Right-angled triangles This file proves basic geometrical results about distances and angles in (possibly degenerate) right-angled triangles in real inner product spaces and Euclidean affine spaces. ## Implementation notes Results in this file are generally given in a form with only those non-degeneracy conditions needed for the particular result, rather than requiring affine independence of the points of a triangle unnecessarily. ## References * https://en.wikipedia.org/wiki/Pythagorean_theorem -/ noncomputable section open scoped EuclideanGeometry open scoped Real open scoped RealInnerProductSpace namespace InnerProductGeometry variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] /-- Pythagorean theorem, if-and-only-if vector angle form. -/
Mathlib/Geometry/Euclidean/Angle/Unoriented/RightAngle.lean
43
46
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two (x y : V) : ‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ angle x y = π / 2 := by
rw [norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero] exact inner_eq_zero_iff_angle_eq_pi_div_two x y
/- Copyright (c) 2022 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Probability.Variance #align_import probability.moments from "leanprover-community/mathlib"@"85453a2a14be8da64caf15ca50930cf4c6e5d8de" /-! # Moments and moment generating function ## Main definitions * `ProbabilityTheory.moment X p μ`: `p`th moment of a real random variable `X` with respect to measure `μ`, `μ[X^p]` * `ProbabilityTheory.centralMoment X p μ`:`p`th central moment of `X` with respect to measure `μ`, `μ[(X - μ[X])^p]` * `ProbabilityTheory.mgf X μ t`: moment generating function of `X` with respect to measure `μ`, `μ[exp(t*X)]` * `ProbabilityTheory.cgf X μ t`: cumulant generating function, logarithm of the moment generating function ## Main results * `ProbabilityTheory.IndepFun.mgf_add`: if two real random variables `X` and `Y` are independent and their mgfs are defined at `t`, then `mgf (X + Y) μ t = mgf X μ t * mgf Y μ t` * `ProbabilityTheory.IndepFun.cgf_add`: if two real random variables `X` and `Y` are independent and their cgfs are defined at `t`, then `cgf (X + Y) μ t = cgf X μ t + cgf Y μ t` * `ProbabilityTheory.measure_ge_le_exp_cgf` and `ProbabilityTheory.measure_le_le_exp_cgf`: Chernoff bound on the upper (resp. lower) tail of a random variable. For `t` nonnegative such that the cgf exists, `ℙ(ε ≤ X) ≤ exp(- t*ε + cgf X ℙ t)`. See also `ProbabilityTheory.measure_ge_le_exp_mul_mgf` and `ProbabilityTheory.measure_le_le_exp_mul_mgf` for versions of these results using `mgf` instead of `cgf`. -/ open MeasureTheory Filter Finset Real noncomputable section open scoped MeasureTheory ProbabilityTheory ENNReal NNReal namespace ProbabilityTheory variable {Ω ι : Type*} {m : MeasurableSpace Ω} {X : Ω → ℝ} {p : ℕ} {μ : Measure Ω} /-- Moment of a real random variable, `μ[X ^ p]`. -/ def moment (X : Ω → ℝ) (p : ℕ) (μ : Measure Ω) : ℝ := μ[X ^ p] #align probability_theory.moment ProbabilityTheory.moment /-- Central moment of a real random variable, `μ[(X - μ[X]) ^ p]`. -/ def centralMoment (X : Ω → ℝ) (p : ℕ) (μ : Measure Ω) : ℝ := by have m := fun (x : Ω) => μ[X] -- Porting note: Lean deems `μ[(X - fun x => μ[X]) ^ p]` ambiguous exact μ[(X - m) ^ p] #align probability_theory.central_moment ProbabilityTheory.centralMoment @[simp] theorem moment_zero (hp : p ≠ 0) : moment 0 p μ = 0 := by simp only [moment, hp, zero_pow, Ne, not_false_iff, Pi.zero_apply, integral_const, smul_eq_mul, mul_zero, integral_zero] #align probability_theory.moment_zero ProbabilityTheory.moment_zero @[simp] theorem centralMoment_zero (hp : p ≠ 0) : centralMoment 0 p μ = 0 := by simp only [centralMoment, hp, Pi.zero_apply, integral_const, smul_eq_mul, mul_zero, zero_sub, Pi.pow_apply, Pi.neg_apply, neg_zero, zero_pow, Ne, not_false_iff] #align probability_theory.central_moment_zero ProbabilityTheory.centralMoment_zero theorem centralMoment_one' [IsFiniteMeasure μ] (h_int : Integrable X μ) : centralMoment X 1 μ = (1 - (μ Set.univ).toReal) * μ[X] := by simp only [centralMoment, Pi.sub_apply, pow_one] rw [integral_sub h_int (integrable_const _)] simp only [sub_mul, integral_const, smul_eq_mul, one_mul] #align probability_theory.central_moment_one' ProbabilityTheory.centralMoment_one' @[simp] theorem centralMoment_one [IsProbabilityMeasure μ] : centralMoment X 1 μ = 0 := by by_cases h_int : Integrable X μ · rw [centralMoment_one' h_int] simp only [measure_univ, ENNReal.one_toReal, sub_self, zero_mul] · simp only [centralMoment, Pi.sub_apply, pow_one] have : ¬Integrable (fun x => X x - integral μ X) μ := by refine fun h_sub => h_int ?_ have h_add : X = (fun x => X x - integral μ X) + fun _ => integral μ X := by ext1 x; simp rw [h_add] exact h_sub.add (integrable_const _) rw [integral_undef this] #align probability_theory.central_moment_one ProbabilityTheory.centralMoment_one theorem centralMoment_two_eq_variance [IsFiniteMeasure μ] (hX : Memℒp X 2 μ) : centralMoment X 2 μ = variance X μ := by rw [hX.variance_eq]; rfl #align probability_theory.central_moment_two_eq_variance ProbabilityTheory.centralMoment_two_eq_variance section MomentGeneratingFunction variable {t : ℝ} /-- Moment generating function of a real random variable `X`: `fun t => μ[exp(t*X)]`. -/ def mgf (X : Ω → ℝ) (μ : Measure Ω) (t : ℝ) : ℝ := μ[fun ω => exp (t * X ω)] #align probability_theory.mgf ProbabilityTheory.mgf /-- Cumulant generating function of a real random variable `X`: `fun t => log μ[exp(t*X)]`. -/ def cgf (X : Ω → ℝ) (μ : Measure Ω) (t : ℝ) : ℝ := log (mgf X μ t) #align probability_theory.cgf ProbabilityTheory.cgf @[simp] theorem mgf_zero_fun : mgf 0 μ t = (μ Set.univ).toReal := by simp only [mgf, Pi.zero_apply, mul_zero, exp_zero, integral_const, smul_eq_mul, mul_one] #align probability_theory.mgf_zero_fun ProbabilityTheory.mgf_zero_fun @[simp] theorem cgf_zero_fun : cgf 0 μ t = log (μ Set.univ).toReal := by simp only [cgf, mgf_zero_fun] #align probability_theory.cgf_zero_fun ProbabilityTheory.cgf_zero_fun @[simp]
Mathlib/Probability/Moments.lean
122
122
theorem mgf_zero_measure : mgf X (0 : Measure Ω) t = 0 := by
simp only [mgf, integral_zero_measure]
/- Copyright (c) 2022 Michael Stoll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Michael Stoll -/ import Mathlib.Data.Fintype.Parity import Mathlib.NumberTheory.LegendreSymbol.ZModChar import Mathlib.FieldTheory.Finite.Basic #align_import number_theory.legendre_symbol.quadratic_char.basic from "leanprover-community/mathlib"@"5b2fe80501ff327b9109fb09b7cc8c325cd0d7d9" /-! # Quadratic characters of finite fields This file defines the quadratic character on a finite field `F` and proves some basic statements about it. ## Tags quadratic character -/ /-! ### Definition of the quadratic character We define the quadratic character of a finite field `F` with values in ℤ. -/ section Define /-- Define the quadratic character with values in ℤ on a monoid with zero `α`. It takes the value zero at zero; for non-zero argument `a : α`, it is `1` if `a` is a square, otherwise it is `-1`. This only deserves the name "character" when it is multiplicative, e.g., when `α` is a finite field. See `quadraticCharFun_mul`. We will later define `quadraticChar` to be a multiplicative character of type `MulChar F ℤ`, when the domain is a finite field `F`. -/ def quadraticCharFun (α : Type*) [MonoidWithZero α] [DecidableEq α] [DecidablePred (IsSquare : α → Prop)] (a : α) : ℤ := if a = 0 then 0 else if IsSquare a then 1 else -1 #align quadratic_char_fun quadraticCharFun end Define /-! ### Basic properties of the quadratic character We prove some properties of the quadratic character. We work with a finite field `F` here. The interesting case is when the characteristic of `F` is odd. -/ section quadraticChar open MulChar variable {F : Type*} [Field F] [Fintype F] [DecidableEq F] /-- Some basic API lemmas -/ theorem quadraticCharFun_eq_zero_iff {a : F} : quadraticCharFun F a = 0 ↔ a = 0 := by simp only [quadraticCharFun] by_cases ha : a = 0 · simp only [ha, eq_self_iff_true, if_true] · simp only [ha, if_false, iff_false_iff] split_ifs <;> simp only [neg_eq_zero, one_ne_zero, not_false_iff] #align quadratic_char_fun_eq_zero_iff quadraticCharFun_eq_zero_iff @[simp]
Mathlib/NumberTheory/LegendreSymbol/QuadraticChar/Basic.lean
75
76
theorem quadraticCharFun_zero : quadraticCharFun F 0 = 0 := by
simp only [quadraticCharFun, eq_self_iff_true, if_true, id]
/- Copyright (c) 2023 Kevin Buzzard. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kevin Buzzard, Richard Hill -/ import Mathlib.Algebra.Polynomial.AlgebraMap import Mathlib.Algebra.Polynomial.Derivative import Mathlib.Algebra.Polynomial.Module.AEval import Mathlib.RingTheory.Derivation.Basic /-! # Derivations of univariate polynomials In this file we prove that an `R`-derivation of `Polynomial R` is determined by its value on `X`. We also provide a constructor `Polynomial.mkDerivation` that builds a derivation from its value on `X`, and a linear equivalence `Polynomial.mkDerivationEquiv` between `A` and `Derivation (Polynomial R) A`. -/ noncomputable section namespace Polynomial section CommSemiring variable {R A : Type*} [CommSemiring R] /-- `Polynomial.derivative` as a derivation. -/ @[simps] def derivative' : Derivation R R[X] R[X] where toFun := derivative map_add' _ _ := derivative_add map_smul' := derivative_smul map_one_eq_zero' := derivative_one leibniz' f g := by simp [mul_comm, add_comm, derivative_mul] variable [AddCommMonoid A] [Module R A] [Module (Polynomial R) A] @[simp] theorem derivation_C (D : Derivation R R[X] A) (a : R) : D (C a) = 0 := D.map_algebraMap a @[simp] theorem C_smul_derivation_apply (D : Derivation R R[X] A) (a : R) (f : R[X]) : C a • D f = a • D f := by have : C a • D f = D (C a * f) := by simp rw [this, C_mul', D.map_smul] @[ext] theorem derivation_ext {D₁ D₂ : Derivation R R[X] A} (h : D₁ X = D₂ X) : D₁ = D₂ := Derivation.ext fun f => Derivation.eqOn_adjoin (Set.eqOn_singleton.2 h) <| by simp only [adjoin_X, Algebra.coe_top, Set.mem_univ] variable [IsScalarTower R (Polynomial R) A] variable (R) /-- The derivation on `R[X]` that takes the value `a` on `X`. -/ def mkDerivation : A →ₗ[R] Derivation R R[X] A where toFun := fun a ↦ (LinearMap.toSpanSingleton R[X] A a).compDer derivative' map_add' := fun a b ↦ by ext; simp map_smul' := fun t a ↦ by ext; simp lemma mkDerivation_apply (a : A) (f : R[X]) : mkDerivation R a f = derivative f • a := by rfl @[simp] theorem mkDerivation_X (a : A) : mkDerivation R a X = a := by simp [mkDerivation_apply] lemma mkDerivation_one_eq_derivative' : mkDerivation R (1 : R[X]) = derivative' := by ext : 1 simp [derivative'] lemma mkDerivation_one_eq_derivative (f : R[X]) : mkDerivation R (1 : R[X]) f = derivative f := by rw [mkDerivation_one_eq_derivative'] rfl /-- `Polynomial.mkDerivation` as a linear equivalence. -/ def mkDerivationEquiv : A ≃ₗ[R] Derivation R R[X] A := LinearEquiv.symm <| { invFun := mkDerivation R toFun := fun D => D X map_add' := fun _ _ => rfl map_smul' := fun _ _ => rfl left_inv := fun _ => derivation_ext <| mkDerivation_X _ _ right_inv := fun _ => mkDerivation_X _ _ } @[simp] lemma mkDerivationEquiv_apply (a : A) : mkDerivationEquiv R a = mkDerivation R a := by rfl @[simp] lemma mkDerivationEquiv_symm_apply (D : Derivation R R[X] A) : (mkDerivationEquiv R).symm D = D X := rfl end CommSemiring end Polynomial namespace Derivation variable {R A M : Type*} [CommSemiring R] [CommSemiring A] [Algebra R A] [AddCommMonoid M] [Module A M] [Module R M] [IsScalarTower R A M] (d : Derivation R A M) (a : A) open Polynomial Module /-- For a derivation `d : A → M` and an element `a : A`, `d.compAEval a` is the derivation of `R[X]` which takes a polynomial `f` to `d(aeval a f)`. This derivation takes values in `Module.AEval R M a`, which is `M`, regarded as an `R[X]`-module, with the action of a polynomial `f` defined by `f • m = (aeval a f) • m`. -/ /- Note: `compAEval` is not defined using `Derivation.compAlgebraMap`. This because `A` is not an `R[X]` algebra and it would be messy to create an algebra instance within the definition. -/ @[simps] def compAEval : Derivation R R[X] <| AEval R M a where toFun f := AEval.of R M a (d (aeval a f)) map_add' := by simp map_smul' := by simp leibniz' := by simp [AEval.of_aeval_smul, -Derivation.map_aeval] map_one_eq_zero' := by simp /-- A form of the chain rule: if `f` is a polynomial over `R` and `d : A → M` is an `R`-derivation then for all `a : A` we have $$ d(f(a)) = f' (a) d a. $$ The equation is in the `R[X]`-module `Module.AEval R M a`. For the same equation in `M`, see `Derivation.compAEval_eq`. -/
Mathlib/Algebra/Polynomial/Derivation.lean
131
136
theorem compAEval_eq (d : Derivation R A M) (f : R[X]) : d.compAEval a f = derivative f • (AEval.of R M a (d a)) := by
rw [← mkDerivation_apply] congr apply derivation_ext simp
/- Copyright (c) 2017 Simon Hudon. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Simon Hudon -/ import Mathlib.Data.PFunctor.Univariate.Basic #align_import data.pfunctor.univariate.M from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1" /-! # M-types M types are potentially infinite tree-like structures. They are defined as the greatest fixpoint of a polynomial functor. -/ universe u v w open Nat Function open List variable (F : PFunctor.{u}) -- Porting note: the ♯ tactic is never used -- local prefix:0 "♯" => cast (by first |simp [*]|cc|solve_by_elim) namespace PFunctor namespace Approx /-- `CofixA F n` is an `n` level approximation of an M-type -/ inductive CofixA : ℕ → Type u | continue : CofixA 0 | intro {n} : ∀ a, (F.B a → CofixA n) → CofixA (succ n) #align pfunctor.approx.cofix_a PFunctor.Approx.CofixA /-- default inhabitant of `CofixA` -/ protected def CofixA.default [Inhabited F.A] : ∀ n, CofixA F n | 0 => CofixA.continue | succ n => CofixA.intro default fun _ => CofixA.default n #align pfunctor.approx.cofix_a.default PFunctor.Approx.CofixA.default instance [Inhabited F.A] {n} : Inhabited (CofixA F n) := ⟨CofixA.default F n⟩ theorem cofixA_eq_zero : ∀ x y : CofixA F 0, x = y | CofixA.continue, CofixA.continue => rfl #align pfunctor.approx.cofix_a_eq_zero PFunctor.Approx.cofixA_eq_zero variable {F} /-- The label of the root of the tree for a non-trivial approximation of the cofix of a pfunctor. -/ def head' : ∀ {n}, CofixA F (succ n) → F.A | _, CofixA.intro i _ => i #align pfunctor.approx.head' PFunctor.Approx.head' /-- for a non-trivial approximation, return all the subtrees of the root -/ def children' : ∀ {n} (x : CofixA F (succ n)), F.B (head' x) → CofixA F n | _, CofixA.intro _ f => f #align pfunctor.approx.children' PFunctor.Approx.children' theorem approx_eta {n : ℕ} (x : CofixA F (n + 1)) : x = CofixA.intro (head' x) (children' x) := by cases x; rfl #align pfunctor.approx.approx_eta PFunctor.Approx.approx_eta /-- Relation between two approximations of the cofix of a pfunctor that state they both contain the same data until one of them is truncated -/ inductive Agree : ∀ {n : ℕ}, CofixA F n → CofixA F (n + 1) → Prop | continu (x : CofixA F 0) (y : CofixA F 1) : Agree x y | intro {n} {a} (x : F.B a → CofixA F n) (x' : F.B a → CofixA F (n + 1)) : (∀ i : F.B a, Agree (x i) (x' i)) → Agree (CofixA.intro a x) (CofixA.intro a x') #align pfunctor.approx.agree PFunctor.Approx.Agree /-- Given an infinite series of approximations `approx`, `AllAgree approx` states that they are all consistent with each other. -/ def AllAgree (x : ∀ n, CofixA F n) := ∀ n, Agree (x n) (x (succ n)) #align pfunctor.approx.all_agree PFunctor.Approx.AllAgree @[simp]
Mathlib/Data/PFunctor/Univariate/M.lean
86
86
theorem agree_trival {x : CofixA F 0} {y : CofixA F 1} : Agree x y := by
constructor
/- Copyright (c) 2022 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen, Alex J. Best -/ import Mathlib.LinearAlgebra.Determinant import Mathlib.LinearAlgebra.FreeModule.Finite.Basic #align_import linear_algebra.free_module.determinant from "leanprover-community/mathlib"@"31c458dc7baf3de906b95d9c5c968b6a4d75fee1" /-! # Determinants in free (finite) modules Quite a lot of our results on determinants (that you might know in vector spaces) will work for all free (finite) modules over any commutative ring. ## Main results * `LinearMap.det_zero''`: The determinant of the constant zero map is zero, in a finite free nontrivial module. -/ @[simp]
Mathlib/LinearAlgebra/FreeModule/Determinant.lean
25
29
theorem LinearMap.det_zero'' {R M : Type*} [CommRing R] [AddCommGroup M] [Module R M] [Module.Free R M] [Module.Finite R M] [Nontrivial M] : LinearMap.det (0 : M →ₗ[R] M) = 0 := by
letI : Nonempty (Module.Free.ChooseBasisIndex R M) := (Module.Free.chooseBasis R M).index_nonempty nontriviality R exact LinearMap.det_zero' (Module.Free.chooseBasis R M)
/- Copyright (c) 2024 Arend Mellendijk. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Arend Mellendijk -/ import Mathlib.Analysis.SpecialFunctions.Integrals import Mathlib.Analysis.SumIntegralComparisons import Mathlib.NumberTheory.Harmonic.Defs /-! This file proves $\log(n+1) \le H_n \le 1 + \log(n)$ for all natural numbers $n$. -/ theorem log_add_one_le_harmonic (n : ℕ) : Real.log ↑(n+1) ≤ harmonic n := by calc _ = ∫ x in (1:ℕ)..↑(n+1), x⁻¹ := ?_ _ ≤ ∑ d ∈ Finset.Icc 1 n, (d:ℝ)⁻¹ := ?_ _ = harmonic n := ?_ · rw [Nat.cast_one, integral_inv (by simp [(show ¬ (1 : ℝ) ≤ 0 by norm_num)]), div_one] · exact (inv_antitoneOn_Icc_right <| by norm_num).integral_le_sum_Ico (Nat.le_add_left 1 n) · simp only [harmonic_eq_sum_Icc, Rat.cast_sum, Rat.cast_inv, Rat.cast_natCast]
Mathlib/NumberTheory/Harmonic/Bounds.lean
26
50
theorem harmonic_le_one_add_log (n : ℕ) : harmonic n ≤ 1 + Real.log n := by
by_cases hn0 : n = 0 · simp [hn0] have hn : 1 ≤ n := Nat.one_le_iff_ne_zero.mpr hn0 simp_rw [harmonic_eq_sum_Icc, Rat.cast_sum, Rat.cast_inv, Rat.cast_natCast] rw [← Finset.sum_erase_add (Finset.Icc 1 n) _ (Finset.left_mem_Icc.mpr hn), add_comm, Nat.cast_one, inv_one] refine add_le_add_left ?_ 1 simp only [Nat.lt_one_iff, Finset.mem_Icc, Finset.Icc_erase_left] calc ∑ d ∈ .Ico 2 (n + 1), (d : ℝ)⁻¹ _ = ∑ d ∈ .Ico 2 (n + 1), (↑(d + 1) - 1)⁻¹ := ?_ _ ≤ ∫ x in (2).. ↑(n + 1), (x - 1)⁻¹ := ?_ _ = ∫ x in (1)..n, x⁻¹ := ?_ _ = Real.log ↑n := ?_ · simp_rw [Nat.cast_add, Nat.cast_one, add_sub_cancel_right] · exact @AntitoneOn.sum_le_integral_Ico 2 (n + 1) (fun x : ℝ ↦ (x - 1)⁻¹) (by linarith [hn]) <| sub_inv_antitoneOn_Icc_right (by norm_num) · convert intervalIntegral.integral_comp_sub_right _ 1 · norm_num · simp only [Nat.cast_add, Nat.cast_one, add_sub_cancel_right] · convert integral_inv _ · rw [div_one] · simp only [Nat.one_le_cast, hn, Set.uIcc_of_le, Set.mem_Icc, Nat.cast_nonneg, and_true, not_le, zero_lt_one]
/- Copyright (c) 2019 Neil Strickland. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Neil Strickland -/ import Mathlib.Algebra.BigOperators.Intervals import Mathlib.Algebra.BigOperators.Ring import Mathlib.Algebra.Order.BigOperators.Ring.Finset import Mathlib.Algebra.Order.Field.Basic import Mathlib.Algebra.Order.Ring.Abs import Mathlib.Algebra.Ring.Opposite import Mathlib.Tactic.Abel #align_import algebra.geom_sum from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c" /-! # Partial sums of geometric series This file determines the values of the geometric series $\sum_{i=0}^{n-1} x^i$ and $\sum_{i=0}^{n-1} x^i y^{n-1-i}$ and variants thereof. We also provide some bounds on the "geometric" sum of `a/b^i` where `a b : ℕ`. ## Main statements * `geom_sum_Ico` proves that $\sum_{i=m}^{n-1} x^i=\frac{x^n-x^m}{x-1}$ in a division ring. * `geom_sum₂_Ico` proves that $\sum_{i=m}^{n-1} x^iy^{n - 1 - i}=\frac{x^n-y^{n-m}x^m}{x-y}$ in a field. Several variants are recorded, generalising in particular to the case of a noncommutative ring in which `x` and `y` commute. Even versions not using division or subtraction, valid in each semiring, are recorded. -/ -- Porting note: corrected type in the description of `geom_sum₂_Ico` (in the doc string only). universe u variable {α : Type u} open Finset MulOpposite section Semiring variable [Semiring α] theorem geom_sum_succ {x : α} {n : ℕ} : ∑ i ∈ range (n + 1), x ^ i = (x * ∑ i ∈ range n, x ^ i) + 1 := by simp only [mul_sum, ← pow_succ', sum_range_succ', pow_zero] #align geom_sum_succ geom_sum_succ theorem geom_sum_succ' {x : α} {n : ℕ} : ∑ i ∈ range (n + 1), x ^ i = x ^ n + ∑ i ∈ range n, x ^ i := (sum_range_succ _ _).trans (add_comm _ _) #align geom_sum_succ' geom_sum_succ' theorem geom_sum_zero (x : α) : ∑ i ∈ range 0, x ^ i = 0 := rfl #align geom_sum_zero geom_sum_zero theorem geom_sum_one (x : α) : ∑ i ∈ range 1, x ^ i = 1 := by simp [geom_sum_succ'] #align geom_sum_one geom_sum_one @[simp] theorem geom_sum_two {x : α} : ∑ i ∈ range 2, x ^ i = x + 1 := by simp [geom_sum_succ'] #align geom_sum_two geom_sum_two @[simp] theorem zero_geom_sum : ∀ {n}, ∑ i ∈ range n, (0 : α) ^ i = if n = 0 then 0 else 1 | 0 => by simp | 1 => by simp | n + 2 => by rw [geom_sum_succ'] simp [zero_geom_sum] #align zero_geom_sum zero_geom_sum theorem one_geom_sum (n : ℕ) : ∑ i ∈ range n, (1 : α) ^ i = n := by simp #align one_geom_sum one_geom_sum -- porting note (#10618): simp can prove this -- @[simp] theorem op_geom_sum (x : α) (n : ℕ) : op (∑ i ∈ range n, x ^ i) = ∑ i ∈ range n, op x ^ i := by simp #align op_geom_sum op_geom_sum -- Porting note: linter suggested to change left hand side @[simp]
Mathlib/Algebra/GeomSum.lean
87
94
theorem op_geom_sum₂ (x y : α) (n : ℕ) : ∑ i ∈ range n, op y ^ (n - 1 - i) * op x ^ i = ∑ i ∈ range n, op y ^ i * op x ^ (n - 1 - i) := by
rw [← sum_range_reflect] refine sum_congr rfl fun j j_in => ?_ rw [mem_range, Nat.lt_iff_add_one_le] at j_in congr apply tsub_tsub_cancel_of_le exact le_tsub_of_add_le_right j_in
/- Copyright (c) 2022 Anatole Dedecker. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anatole Dedecker -/ import Mathlib.Topology.Connected.Basic /-! # Locally connected topological spaces A topological space is **locally connected** if each neighborhood filter admits a basis of connected *open* sets. Local connectivity is equivalent to each point having a basis of connected (not necessarily open) sets --- but in a non-trivial way, so we choose this definition and prove the equivalence later in `locallyConnectedSpace_iff_connected_basis`. -/ open Set Topology universe u v variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α] {s t u v : Set α} section LocallyConnectedSpace /-- A topological space is **locally connected** if each neighborhood filter admits a basis of connected *open* sets. Note that it is equivalent to each point having a basis of connected (non necessarily open) sets but in a non-trivial way, so we choose this definition and prove the equivalence later in `locallyConnectedSpace_iff_connected_basis`. -/ class LocallyConnectedSpace (α : Type*) [TopologicalSpace α] : Prop where /-- Open connected neighborhoods form a basis of the neighborhoods filter. -/ open_connected_basis : ∀ x, (𝓝 x).HasBasis (fun s : Set α => IsOpen s ∧ x ∈ s ∧ IsConnected s) id #align locally_connected_space LocallyConnectedSpace theorem locallyConnectedSpace_iff_open_connected_basis : LocallyConnectedSpace α ↔ ∀ x, (𝓝 x).HasBasis (fun s : Set α => IsOpen s ∧ x ∈ s ∧ IsConnected s) id := ⟨@LocallyConnectedSpace.open_connected_basis _ _, LocallyConnectedSpace.mk⟩ #align locally_connected_space_iff_open_connected_basis locallyConnectedSpace_iff_open_connected_basis
Mathlib/Topology/Connected/LocallyConnected.lean
41
52
theorem locallyConnectedSpace_iff_open_connected_subsets : LocallyConnectedSpace α ↔ ∀ x, ∀ U ∈ 𝓝 x, ∃ V : Set α, V ⊆ U ∧ IsOpen V ∧ x ∈ V ∧ IsConnected V := by
simp_rw [locallyConnectedSpace_iff_open_connected_basis] refine forall_congr' fun _ => ?_ constructor · intro h U hU rcases h.mem_iff.mp hU with ⟨V, hV, hVU⟩ exact ⟨V, hVU, hV⟩ · exact fun h => ⟨fun U => ⟨fun hU => let ⟨V, hVU, hV⟩ := h U hU ⟨V, hV, hVU⟩, fun ⟨V, ⟨hV, hxV, _⟩, hVU⟩ => mem_nhds_iff.mpr ⟨V, hVU, hV, hxV⟩⟩⟩
/- Copyright (c) 2019 Patrick Massot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot, Simon Hudon, Alice Laroche, Frédéric Dupuis, Jireh Loreaux -/ import Lean.Elab.Tactic.Location import Mathlib.Logic.Basic import Mathlib.Init.Order.Defs import Mathlib.Tactic.Conv import Mathlib.Init.Set import Lean.Elab.Tactic.Location set_option autoImplicit true namespace Mathlib.Tactic.PushNeg open Lean Meta Elab.Tactic Parser.Tactic variable (p q : Prop) (s : α → Prop) theorem not_not_eq : (¬ ¬ p) = p := propext not_not theorem not_and_eq : (¬ (p ∧ q)) = (p → ¬ q) := propext not_and theorem not_and_or_eq : (¬ (p ∧ q)) = (¬ p ∨ ¬ q) := propext not_and_or theorem not_or_eq : (¬ (p ∨ q)) = (¬ p ∧ ¬ q) := propext not_or theorem not_forall_eq : (¬ ∀ x, s x) = (∃ x, ¬ s x) := propext not_forall theorem not_exists_eq : (¬ ∃ x, s x) = (∀ x, ¬ s x) := propext not_exists theorem not_implies_eq : (¬ (p → q)) = (p ∧ ¬ q) := propext Classical.not_imp theorem not_ne_eq (x y : α) : (¬ (x ≠ y)) = (x = y) := ne_eq x y ▸ not_not_eq _ theorem not_iff : (¬ (p ↔ q)) = ((p ∧ ¬ q) ∨ (¬ p ∧ q)) := propext <| _root_.not_iff.trans <| iff_iff_and_or_not_and_not.trans <| by rw [not_not, or_comm] variable {β : Type u} [LinearOrder β] theorem not_le_eq (a b : β) : (¬ (a ≤ b)) = (b < a) := propext not_le theorem not_lt_eq (a b : β) : (¬ (a < b)) = (b ≤ a) := propext not_lt theorem not_ge_eq (a b : β) : (¬ (a ≥ b)) = (a < b) := propext not_le theorem not_gt_eq (a b : β) : (¬ (a > b)) = (a ≤ b) := propext not_lt
Mathlib/Tactic/PushNeg.lean
39
42
theorem not_nonempty_eq (s : Set γ) : (¬ s.Nonempty) = (s = ∅) := by
have A : ∀ (x : γ), ¬(x ∈ (∅ : Set γ)) := fun x ↦ id simp only [Set.Nonempty, not_exists, eq_iff_iff] exact ⟨fun h ↦ Set.ext (fun x ↦ by simp only [h x, false_iff, A]), fun h ↦ by rwa [h]⟩
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot -/ import Mathlib.Topology.Order #align_import topology.maps from "leanprover-community/mathlib"@"d91e7f7a7f1c7e9f0e18fdb6bde4f652004c735d" /-! # Specific classes of maps between topological spaces This file introduces the following properties of a map `f : X → Y` between topological spaces: * `IsOpenMap f` means the image of an open set under `f` is open. * `IsClosedMap f` means the image of a closed set under `f` is closed. (Open and closed maps need not be continuous.) * `Inducing f` means the topology on `X` is the one induced via `f` from the topology on `Y`. These behave like embeddings except they need not be injective. Instead, points of `X` which are identified by `f` are also inseparable in the topology on `X`. * `Embedding f` means `f` is inducing and also injective. Equivalently, `f` identifies `X` with a subspace of `Y`. * `OpenEmbedding f` means `f` is an embedding with open image, so it identifies `X` with an open subspace of `Y`. Equivalently, `f` is an embedding and an open map. * `ClosedEmbedding f` similarly means `f` is an embedding with closed image, so it identifies `X` with a closed subspace of `Y`. Equivalently, `f` is an embedding and a closed map. * `QuotientMap f` is the dual condition to `Embedding f`: `f` is surjective and the topology on `Y` is the one coinduced via `f` from the topology on `X`. Equivalently, `f` identifies `Y` with a quotient of `X`. Quotient maps are also sometimes known as identification maps. ## References * <https://en.wikipedia.org/wiki/Open_and_closed_maps> * <https://en.wikipedia.org/wiki/Embedding#General_topology> * <https://en.wikipedia.org/wiki/Quotient_space_(topology)#Quotient_map> ## Tags open map, closed map, embedding, quotient map, identification map -/ open Set Filter Function open TopologicalSpace Topology Filter variable {X : Type*} {Y : Type*} {Z : Type*} {ι : Type*} {f : X → Y} {g : Y → Z} section Inducing variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] theorem inducing_induced (f : X → Y) : @Inducing X Y (TopologicalSpace.induced f ‹_›) _ f := @Inducing.mk _ _ (TopologicalSpace.induced f ‹_›) _ _ rfl theorem inducing_id : Inducing (@id X) := ⟨induced_id.symm⟩ #align inducing_id inducing_id protected theorem Inducing.comp (hg : Inducing g) (hf : Inducing f) : Inducing (g ∘ f) := ⟨by rw [hf.induced, hg.induced, induced_compose]⟩ #align inducing.comp Inducing.comp theorem Inducing.of_comp_iff (hg : Inducing g) : Inducing (g ∘ f) ↔ Inducing f := by refine ⟨fun h ↦ ?_, hg.comp⟩ rw [inducing_iff, hg.induced, induced_compose, h.induced] #align inducing.inducing_iff Inducing.of_comp_iff theorem inducing_of_inducing_compose (hf : Continuous f) (hg : Continuous g) (hgf : Inducing (g ∘ f)) : Inducing f := ⟨le_antisymm (by rwa [← continuous_iff_le_induced]) (by rw [hgf.induced, ← induced_compose] exact induced_mono hg.le_induced)⟩ #align inducing_of_inducing_compose inducing_of_inducing_compose theorem inducing_iff_nhds : Inducing f ↔ ∀ x, 𝓝 x = comap f (𝓝 (f x)) := (inducing_iff _).trans (induced_iff_nhds_eq f) #align inducing_iff_nhds inducing_iff_nhds namespace Inducing theorem nhds_eq_comap (hf : Inducing f) : ∀ x : X, 𝓝 x = comap f (𝓝 <| f x) := inducing_iff_nhds.1 hf #align inducing.nhds_eq_comap Inducing.nhds_eq_comap theorem basis_nhds {p : ι → Prop} {s : ι → Set Y} (hf : Inducing f) {x : X} (h_basis : (𝓝 (f x)).HasBasis p s) : (𝓝 x).HasBasis p (preimage f ∘ s) := hf.nhds_eq_comap x ▸ h_basis.comap f
Mathlib/Topology/Maps.lean
97
99
theorem nhdsSet_eq_comap (hf : Inducing f) (s : Set X) : 𝓝ˢ s = comap f (𝓝ˢ (f '' s)) := by
simp only [nhdsSet, sSup_image, comap_iSup, hf.nhds_eq_comap, iSup_image]
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Jens Wagemaker, Aaron Anderson -/ import Mathlib.Algebra.EuclideanDomain.Basic import Mathlib.RingTheory.PrincipalIdealDomain import Mathlib.Algebra.GCDMonoid.Nat #align_import ring_theory.int.basic from "leanprover-community/mathlib"@"e655e4ea5c6d02854696f97494997ba4c31be802" /-! # Divisibility over ℕ and ℤ This file collects results for the integers and natural numbers that use ring theory in their proofs or cases of ℕ and ℤ being examples of structures in ring theory. ## Main statements * `Nat.factors_eq`: the multiset of elements of `Nat.factors` is equal to the factors given by the `UniqueFactorizationMonoid` instance ## Tags prime, irreducible, natural numbers, integers, normalization monoid, gcd monoid, greatest common divisor, prime factorization, prime factors, unique factorization, unique factors -/ namespace Int theorem gcd_eq_one_iff_coprime {a b : ℤ} : Int.gcd a b = 1 ↔ IsCoprime a b := by constructor · intro hg obtain ⟨ua, -, ha⟩ := exists_unit_of_abs a obtain ⟨ub, -, hb⟩ := exists_unit_of_abs b use Nat.gcdA (Int.natAbs a) (Int.natAbs b) * ua, Nat.gcdB (Int.natAbs a) (Int.natAbs b) * ub rw [mul_assoc, ← ha, mul_assoc, ← hb, mul_comm, mul_comm _ (Int.natAbs b : ℤ), ← Nat.gcd_eq_gcd_ab, ← gcd_eq_natAbs, hg, Int.ofNat_one] · rintro ⟨r, s, h⟩ by_contra hg obtain ⟨p, ⟨hp, ha, hb⟩⟩ := Nat.Prime.not_coprime_iff_dvd.mp hg apply Nat.Prime.not_dvd_one hp rw [← natCast_dvd_natCast, Int.ofNat_one, ← h] exact dvd_add ((natCast_dvd.mpr ha).mul_left _) ((natCast_dvd.mpr hb).mul_left _) #align int.gcd_eq_one_iff_coprime Int.gcd_eq_one_iff_coprime theorem coprime_iff_nat_coprime {a b : ℤ} : IsCoprime a b ↔ Nat.Coprime a.natAbs b.natAbs := by rw [← gcd_eq_one_iff_coprime, Nat.coprime_iff_gcd_eq_one, gcd_eq_natAbs] #align int.coprime_iff_nat_coprime Int.coprime_iff_nat_coprime /-- If `gcd a (m * n) ≠ 1`, then `gcd a m ≠ 1` or `gcd a n ≠ 1`. -/ theorem gcd_ne_one_iff_gcd_mul_right_ne_one {a : ℤ} {m n : ℕ} : a.gcd (m * n) ≠ 1 ↔ a.gcd m ≠ 1 ∨ a.gcd n ≠ 1 := by simp only [gcd_eq_one_iff_coprime, ← not_and_or, not_iff_not, IsCoprime.mul_right_iff] #align int.gcd_ne_one_iff_gcd_mul_right_ne_one Int.gcd_ne_one_iff_gcd_mul_right_ne_one theorem sq_of_gcd_eq_one {a b c : ℤ} (h : Int.gcd a b = 1) (heq : a * b = c ^ 2) : ∃ a0 : ℤ, a = a0 ^ 2 ∨ a = -a0 ^ 2 := by have h' : IsUnit (GCDMonoid.gcd a b) := by rw [← coe_gcd, h, Int.ofNat_one] exact isUnit_one obtain ⟨d, ⟨u, hu⟩⟩ := exists_associated_pow_of_mul_eq_pow h' heq use d rw [← hu] cases' Int.units_eq_one_or u with hu' hu' <;> · rw [hu'] simp #align int.sq_of_gcd_eq_one Int.sq_of_gcd_eq_one theorem sq_of_coprime {a b c : ℤ} (h : IsCoprime a b) (heq : a * b = c ^ 2) : ∃ a0 : ℤ, a = a0 ^ 2 ∨ a = -a0 ^ 2 := sq_of_gcd_eq_one (gcd_eq_one_iff_coprime.mpr h) heq #align int.sq_of_coprime Int.sq_of_coprime theorem natAbs_euclideanDomain_gcd (a b : ℤ) : Int.natAbs (EuclideanDomain.gcd a b) = Int.gcd a b := by apply Nat.dvd_antisymm <;> rw [← Int.natCast_dvd_natCast] · rw [Int.natAbs_dvd] exact Int.dvd_gcd (EuclideanDomain.gcd_dvd_left _ _) (EuclideanDomain.gcd_dvd_right _ _) · rw [Int.dvd_natAbs] exact EuclideanDomain.dvd_gcd Int.gcd_dvd_left Int.gcd_dvd_right #align int.nat_abs_euclidean_domain_gcd Int.natAbs_euclideanDomain_gcd end Int theorem Int.Prime.dvd_mul {m n : ℤ} {p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ m * n) : p ∣ m.natAbs ∨ p ∣ n.natAbs := by rwa [← hp.dvd_mul, ← Int.natAbs_mul, ← Int.natCast_dvd] #align int.prime.dvd_mul Int.Prime.dvd_mul
Mathlib/RingTheory/Int/Basic.lean
93
96
theorem Int.Prime.dvd_mul' {m n : ℤ} {p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ m * n) : (p : ℤ) ∣ m ∨ (p : ℤ) ∣ n := by
rw [Int.natCast_dvd, Int.natCast_dvd] exact Int.Prime.dvd_mul hp h
/- Copyright (c) 2019 Yury Kudriashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudriashov -/ import Mathlib.Algebra.Order.BigOperators.Ring.Finset import Mathlib.Analysis.Convex.Hull import Mathlib.LinearAlgebra.AffineSpace.Basis #align_import analysis.convex.combination from "leanprover-community/mathlib"@"92bd7b1ffeb306a89f450bee126ddd8a284c259d" /-! # Convex combinations This file defines convex combinations of points in a vector space. ## Main declarations * `Finset.centerMass`: Center of mass of a finite family of points. ## Implementation notes We divide by the sum of the weights in the definition of `Finset.centerMass` because of the way mathematical arguments go: one doesn't change weights, but merely adds some. This also makes a few lemmas unconditional on the sum of the weights being `1`. -/ open Set Function open scoped Classical open Pointwise universe u u' variable {R R' E F ι ι' α : Type*} [LinearOrderedField R] [LinearOrderedField R'] [AddCommGroup E] [AddCommGroup F] [LinearOrderedAddCommGroup α] [Module R E] [Module R F] [Module R α] [OrderedSMul R α] {s : Set E} /-- Center of mass of a finite collection of points with prescribed weights. Note that we require neither `0 ≤ w i` nor `∑ w = 1`. -/ def Finset.centerMass (t : Finset ι) (w : ι → R) (z : ι → E) : E := (∑ i ∈ t, w i)⁻¹ • ∑ i ∈ t, w i • z i #align finset.center_mass Finset.centerMass variable (i j : ι) (c : R) (t : Finset ι) (w : ι → R) (z : ι → E) open Finset
Mathlib/Analysis/Convex/Combination.lean
50
51
theorem Finset.centerMass_empty : (∅ : Finset ι).centerMass w z = 0 := by
simp only [centerMass, sum_empty, smul_zero]
/- 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.SetTheory.Cardinal.ToNat import Mathlib.Data.Nat.PartENat #align_import set_theory.cardinal.basic from "leanprover-community/mathlib"@"3ff3f2d6a3118b8711063de7111a0d77a53219a8" /-! # Projection from cardinal numbers to `PartENat` In this file we define the projection `Cardinal.toPartENat` and prove basic properties of this projection. -/ universe u v open Function variable {α : Type u} namespace Cardinal /-- This function sends finite cardinals to the corresponding natural, and infinite cardinals to `⊤`. -/ noncomputable def toPartENat : Cardinal →+o PartENat := .comp { (PartENat.withTopAddEquiv.symm : ℕ∞ →+ PartENat), (PartENat.withTopOrderIso.symm : ℕ∞ →o PartENat) with } toENat #align cardinal.to_part_enat Cardinal.toPartENat @[simp] theorem partENatOfENat_toENat (c : Cardinal) : (toENat c : PartENat) = toPartENat c := rfl @[simp] theorem toPartENat_natCast (n : ℕ) : toPartENat n = n := by simp only [← partENatOfENat_toENat, toENat_nat, PartENat.ofENat_coe] #align cardinal.to_part_enat_cast Cardinal.toPartENat_natCast theorem toPartENat_apply_of_lt_aleph0 {c : Cardinal} (h : c < ℵ₀) : toPartENat c = toNat c := by lift c to ℕ using h; simp #align cardinal.to_part_enat_apply_of_lt_aleph_0 Cardinal.toPartENat_apply_of_lt_aleph0 theorem toPartENat_eq_top {c : Cardinal} : toPartENat c = ⊤ ↔ ℵ₀ ≤ c := by rw [← partENatOfENat_toENat, ← PartENat.withTopEquiv_symm_top, ← toENat_eq_top, ← PartENat.withTopEquiv.symm.injective.eq_iff] simp #align to_part_enat_eq_top_iff_le_aleph_0 Cardinal.toPartENat_eq_top theorem toPartENat_apply_of_aleph0_le {c : Cardinal} (h : ℵ₀ ≤ c) : toPartENat c = ⊤ := congr_arg PartENat.ofENat (toENat_eq_top.2 h) #align cardinal.to_part_enat_apply_of_aleph_0_le Cardinal.toPartENat_apply_of_aleph0_le @[deprecated (since := "2024-02-15")] alias toPartENat_cast := toPartENat_natCast @[simp] theorem mk_toPartENat_of_infinite [h : Infinite α] : toPartENat #α = ⊤ := toPartENat_apply_of_aleph0_le (infinite_iff.1 h) #align cardinal.mk_to_part_enat_of_infinite Cardinal.mk_toPartENat_of_infinite @[simp] theorem aleph0_toPartENat : toPartENat ℵ₀ = ⊤ := toPartENat_apply_of_aleph0_le le_rfl #align cardinal.aleph_0_to_part_enat Cardinal.aleph0_toPartENat theorem toPartENat_surjective : Surjective toPartENat := fun x => PartENat.casesOn x ⟨ℵ₀, toPartENat_apply_of_aleph0_le le_rfl⟩ fun n => ⟨n, toPartENat_natCast n⟩ #align cardinal.to_part_enat_surjective Cardinal.toPartENat_surjective @[deprecated (since := "2024-02-15")] alias toPartENat_eq_top_iff_le_aleph0 := toPartENat_eq_top theorem toPartENat_strictMonoOn : StrictMonoOn toPartENat (Set.Iic ℵ₀) := PartENat.withTopOrderIso.symm.strictMono.comp_strictMonoOn toENat_strictMonoOn lemma toPartENat_le_iff_of_le_aleph0 {c c' : Cardinal} (h : c ≤ ℵ₀) : toPartENat c ≤ toPartENat c' ↔ c ≤ c' := by lift c to ℕ∞ using h simp_rw [← partENatOfENat_toENat, toENat_ofENat, enat_gc _, ← PartENat.withTopOrderIso.symm.le_iff_le, PartENat.ofENat_le, map_le_map_iff] #align to_part_enat_le_iff_le_of_le_aleph_0 Cardinal.toPartENat_le_iff_of_le_aleph0 lemma toPartENat_le_iff_of_lt_aleph0 {c c' : Cardinal} (hc' : c' < ℵ₀) : toPartENat c ≤ toPartENat c' ↔ c ≤ c' := by lift c' to ℕ using hc' simp_rw [← partENatOfENat_toENat, toENat_nat, ← toENat_le_nat, ← PartENat.withTopOrderIso.symm.le_iff_le, PartENat.ofENat_le, map_le_map_iff] #align to_part_enat_le_iff_le_of_lt_aleph_0 Cardinal.toPartENat_le_iff_of_lt_aleph0 lemma toPartENat_eq_iff_of_le_aleph0 {c c' : Cardinal} (hc : c ≤ ℵ₀) (hc' : c' ≤ ℵ₀) : toPartENat c = toPartENat c' ↔ c = c' := toPartENat_strictMonoOn.injOn.eq_iff hc hc' #align to_part_enat_eq_iff_eq_of_le_aleph_0 Cardinal.toPartENat_eq_iff_of_le_aleph0 theorem toPartENat_mono {c c' : Cardinal} (h : c ≤ c') : toPartENat c ≤ toPartENat c' := OrderHomClass.mono _ h #align cardinal.to_part_enat_mono Cardinal.toPartENat_mono theorem toPartENat_lift (c : Cardinal.{v}) : toPartENat (lift.{u, v} c) = toPartENat c := by simp only [← partENatOfENat_toENat, toENat_lift] #align cardinal.to_part_enat_lift Cardinal.toPartENat_lift
Mathlib/SetTheory/Cardinal/PartENat.lean
108
109
theorem toPartENat_congr {β : Type v} (e : α ≃ β) : toPartENat #α = toPartENat #β := by
rw [← toPartENat_lift, lift_mk_eq.{_, _,v}.mpr ⟨e⟩, toPartENat_lift]
/- Copyright (c) 2022 Niels Voss. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Niels Voss -/ import Mathlib.FieldTheory.Finite.Basic import Mathlib.Order.Filter.Cofinite #align_import number_theory.fermat_psp from "leanprover-community/mathlib"@"c0439b4877c24a117bfdd9e32faf62eee9b115eb" /-! # Fermat Pseudoprimes In this file we define Fermat pseudoprimes: composite numbers that pass the Fermat primality test. A natural number `n` passes the Fermat primality test to base `b` (and is therefore deemed a "probable prime") if `n` divides `b ^ (n - 1) - 1`. `n` is a Fermat pseudoprime to base `b` if `n` is a composite number that passes the Fermat primality test to base `b` and is coprime with `b`. Fermat pseudoprimes can also be seen as composite numbers for which Fermat's little theorem holds true. Numbers which are Fermat pseudoprimes to all bases are known as Carmichael numbers (not yet defined in this file). ## Main Results The main definitions for this file are - `Nat.ProbablePrime`: A number `n` is a probable prime to base `b` if it passes the Fermat primality test; that is, if `n` divides `b ^ (n - 1) - 1` - `Nat.FermatPsp`: A number `n` is a pseudoprime to base `b` if it is a probable prime to base `b`, is composite, and is coprime with `b` (this last condition is automatically true if `n` divides `b ^ (n - 1) - 1`, but some sources include it in the definition). Note that all composite numbers are pseudoprimes to base 0 and 1, and that the definition of `Nat.ProbablePrime` in this file implies that all numbers are probable primes to bases 0 and 1, and that 0 and 1 are probable primes to any base. The main theorems are - `Nat.exists_infinite_pseudoprimes`: there are infinite pseudoprimes to any base `b ≥ 1` -/ namespace Nat /-- `n` is a probable prime to base `b` if `n` passes the Fermat primality test; that is, `n` divides `b ^ (n - 1) - 1`. This definition implies that all numbers are probable primes to base 0 or 1, and that 0 and 1 are probable primes to any base. -/ def ProbablePrime (n b : ℕ) : Prop := n ∣ b ^ (n - 1) - 1 #align fermat_psp.probable_prime Nat.ProbablePrime /-- `n` is a Fermat pseudoprime to base `b` if `n` is a probable prime to base `b` and is composite. By this definition, all composite natural numbers are pseudoprimes to base 0 and 1. This definition also permits `n` to be less than `b`, so that 4 is a pseudoprime to base 5, for example. -/ def FermatPsp (n b : ℕ) : Prop := ProbablePrime n b ∧ ¬n.Prime ∧ 1 < n #align fermat_psp Nat.FermatPsp instance decidableProbablePrime (n b : ℕ) : Decidable (ProbablePrime n b) := Nat.decidable_dvd _ _ #align fermat_psp.decidable_probable_prime Nat.decidableProbablePrime instance decidablePsp (n b : ℕ) : Decidable (FermatPsp n b) := And.decidable #align fermat_psp.decidable_psp Nat.decidablePsp /-- If `n` passes the Fermat primality test to base `b`, then `n` is coprime with `b`, assuming that `n` and `b` are both positive. -/ theorem coprime_of_probablePrime {n b : ℕ} (h : ProbablePrime n b) (h₁ : 1 ≤ n) (h₂ : 1 ≤ b) : Nat.Coprime n b := by by_cases h₃ : 2 ≤ n · -- To prove that `n` is coprime with `b`, we need to show that for all prime factors of `n`, -- we can derive a contradiction if `n` divides `b`. apply Nat.coprime_of_dvd -- If `k` is a prime number that divides both `n` and `b`, then we know that `n = m * k` and -- `b = j * k` for some natural numbers `m` and `j`. We substitute these into the hypothesis. rintro k hk ⟨m, rfl⟩ ⟨j, rfl⟩ -- Because prime numbers do not divide 1, it suffices to show that `k ∣ 1` to prove a -- contradiction apply Nat.Prime.not_dvd_one hk -- Since `n` divides `b ^ (n - 1) - 1`, `k` also divides `b ^ (n - 1) - 1` replace h := dvd_of_mul_right_dvd h -- Because `k` divides `b ^ (n - 1) - 1`, if we can show that `k` also divides `b ^ (n - 1)`, -- then we know `k` divides 1. rw [Nat.dvd_add_iff_right h, Nat.sub_add_cancel (Nat.one_le_pow _ _ h₂)] -- Since `k` divides `b`, `k` also divides any power of `b` except `b ^ 0`. Therefore, it -- suffices to show that `n - 1` isn't zero. However, we know that `n - 1` isn't zero because we -- assumed `2 ≤ n` when doing `by_cases`. refine dvd_of_mul_right_dvd (dvd_pow_self (k * j) ?_) omega -- If `n = 1`, then it follows trivially that `n` is coprime with `b`. · rw [show n = 1 by omega] norm_num #align fermat_psp.coprime_of_probable_prime Nat.coprime_of_probablePrime
Mathlib/NumberTheory/FermatPsp.lean
102
112
theorem probablePrime_iff_modEq (n : ℕ) {b : ℕ} (h : 1 ≤ b) : ProbablePrime n b ↔ b ^ (n - 1) ≡ 1 [MOD n] := by
have : 1 ≤ b ^ (n - 1) := one_le_pow_of_one_le h (n - 1) -- For exact mod_cast rw [Nat.ModEq.comm] constructor · intro h₁ apply Nat.modEq_of_dvd exact mod_cast h₁ · intro h₁ exact mod_cast Nat.ModEq.dvd h₁
/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.RingTheory.Algebraic import Mathlib.RingTheory.Localization.AtPrime import Mathlib.RingTheory.Localization.Integral #align_import ring_theory.ideal.over from "leanprover-community/mathlib"@"198cb64d5c961e1a8d0d3e219feb7058d5353861" /-! # Ideals over/under ideals This file concerns ideals lying over other ideals. Let `f : R →+* S` be a ring homomorphism (typically a ring extension), `I` an ideal of `R` and `J` an ideal of `S`. We say `J` lies over `I` (and `I` under `J`) if `I` is the `f`-preimage of `J`. This is expressed here by writing `I = J.comap f`. ## Implementation notes The proofs of the `comap_ne_bot` and `comap_lt_comap` families use an approach specific for their situation: we construct an element in `I.comap f` from the coefficients of a minimal polynomial. Once mathlib has more material on the localization at a prime ideal, the results can be proven using more general going-up/going-down theory. -/ variable {R : Type*} [CommRing R] namespace Ideal open Polynomial open Polynomial open Submodule section CommRing variable {S : Type*} [CommRing S] {f : R →+* S} {I J : Ideal S}
Mathlib/RingTheory/Ideal/Over.lean
44
48
theorem coeff_zero_mem_comap_of_root_mem_of_eval_mem {r : S} (hr : r ∈ I) {p : R[X]} (hp : p.eval₂ f r ∈ I) : p.coeff 0 ∈ I.comap f := by
rw [← p.divX_mul_X_add, eval₂_add, eval₂_C, eval₂_mul, eval₂_X] at hp refine mem_comap.mpr ((I.add_mem_iff_right ?_).mp hp) exact I.mul_mem_left _ hr
/- Copyright (c) 2019 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin -/ import Mathlib.LinearAlgebra.FiniteDimensional import Mathlib.RingTheory.IntegralClosure import Mathlib.RingTheory.Polynomial.IntegralNormalization #align_import ring_theory.algebraic from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2" /-! # Algebraic elements and algebraic extensions An element of an R-algebra is algebraic over R if it is the root of a nonzero polynomial. An R-algebra is algebraic over R if and only if all its elements are algebraic over R. The main result in this file proves transitivity of algebraicity: a tower of algebraic field extensions is algebraic. -/ universe u v w open scoped Classical open Polynomial section variable (R : Type u) {A : Type v} [CommRing R] [Ring A] [Algebra R A] /-- An element of an R-algebra is algebraic over R if it is a root of a nonzero polynomial with coefficients in R. -/ def IsAlgebraic (x : A) : Prop := ∃ p : R[X], p ≠ 0 ∧ aeval x p = 0 #align is_algebraic IsAlgebraic /-- An element of an R-algebra is transcendental over R if it is not algebraic over R. -/ def Transcendental (x : A) : Prop := ¬IsAlgebraic R x #align transcendental Transcendental theorem is_transcendental_of_subsingleton [Subsingleton R] (x : A) : Transcendental R x := fun ⟨p, h, _⟩ => h <| Subsingleton.elim p 0 #align is_transcendental_of_subsingleton is_transcendental_of_subsingleton variable {R} /-- A subalgebra is algebraic if all its elements are algebraic. -/ nonrec def Subalgebra.IsAlgebraic (S : Subalgebra R A) : Prop := ∀ x ∈ S, IsAlgebraic R x #align subalgebra.is_algebraic Subalgebra.IsAlgebraic variable (R A) /-- An algebra is algebraic if all its elements are algebraic. -/ protected class Algebra.IsAlgebraic : Prop := isAlgebraic : ∀ x : A, IsAlgebraic R x #align algebra.is_algebraic Algebra.IsAlgebraic variable {R A} lemma Algebra.isAlgebraic_def : Algebra.IsAlgebraic R A ↔ ∀ x : A, IsAlgebraic R x := ⟨fun ⟨h⟩ ↦ h, fun h ↦ ⟨h⟩⟩ /-- A subalgebra is algebraic if and only if it is algebraic as an algebra. -/ theorem Subalgebra.isAlgebraic_iff (S : Subalgebra R A) : S.IsAlgebraic ↔ @Algebra.IsAlgebraic R S _ _ S.algebra := by delta Subalgebra.IsAlgebraic rw [Subtype.forall', Algebra.isAlgebraic_def] refine forall_congr' fun x => exists_congr fun p => and_congr Iff.rfl ?_ have h : Function.Injective S.val := Subtype.val_injective conv_rhs => rw [← h.eq_iff, AlgHom.map_zero] rw [← aeval_algHom_apply, S.val_apply] #align subalgebra.is_algebraic_iff Subalgebra.isAlgebraic_iff /-- An algebra is algebraic if and only if it is algebraic as a subalgebra. -/ theorem Algebra.isAlgebraic_iff : Algebra.IsAlgebraic R A ↔ (⊤ : Subalgebra R A).IsAlgebraic := by delta Subalgebra.IsAlgebraic simp only [Algebra.isAlgebraic_def, Algebra.mem_top, forall_prop_of_true, iff_self_iff] #align algebra.is_algebraic_iff Algebra.isAlgebraic_iff theorem isAlgebraic_iff_not_injective {x : A} : IsAlgebraic R x ↔ ¬Function.Injective (Polynomial.aeval x : R[X] →ₐ[R] A) := by simp only [IsAlgebraic, injective_iff_map_eq_zero, not_forall, and_comm, exists_prop] #align is_algebraic_iff_not_injective isAlgebraic_iff_not_injective end section zero_ne_one variable {R : Type u} {S : Type*} {A : Type v} [CommRing R] variable [CommRing S] [Ring A] [Algebra R A] [Algebra R S] [Algebra S A] variable [IsScalarTower R S A] /-- An integral element of an algebra is algebraic. -/ theorem IsIntegral.isAlgebraic [Nontrivial R] {x : A} : IsIntegral R x → IsAlgebraic R x := fun ⟨p, hp, hpx⟩ => ⟨p, hp.ne_zero, hpx⟩ #align is_integral.is_algebraic IsIntegral.isAlgebraic instance Algebra.IsIntegral.isAlgebraic [Nontrivial R] [Algebra.IsIntegral R A] : Algebra.IsAlgebraic R A := ⟨fun a ↦ (Algebra.IsIntegral.isIntegral a).isAlgebraic⟩ theorem isAlgebraic_zero [Nontrivial R] : IsAlgebraic R (0 : A) := ⟨_, X_ne_zero, aeval_X 0⟩ #align is_algebraic_zero isAlgebraic_zero /-- An element of `R` is algebraic, when viewed as an element of the `R`-algebra `A`. -/ theorem isAlgebraic_algebraMap [Nontrivial R] (x : R) : IsAlgebraic R (algebraMap R A x) := ⟨_, X_sub_C_ne_zero x, by rw [_root_.map_sub, aeval_X, aeval_C, sub_self]⟩ #align is_algebraic_algebra_map isAlgebraic_algebraMap theorem isAlgebraic_one [Nontrivial R] : IsAlgebraic R (1 : A) := by rw [← _root_.map_one (algebraMap R A)] exact isAlgebraic_algebraMap 1 #align is_algebraic_one isAlgebraic_one
Mathlib/RingTheory/Algebraic.lean
118
120
theorem isAlgebraic_nat [Nontrivial R] (n : ℕ) : IsAlgebraic R (n : A) := by
rw [← map_natCast (_ : R →+* A) n] exact isAlgebraic_algebraMap (Nat.cast n)
/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.RingTheory.PrincipalIdealDomain #align_import ring_theory.bezout from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1" /-! # Bézout rings A Bézout ring (Bezout ring) is a ring whose finitely generated ideals are principal. Notable examples include principal ideal rings, valuation rings, and the ring of algebraic integers. ## Main results - `IsBezout.iff_span_pair_isPrincipal`: It suffices to verify every `span {x, y}` is principal. - `IsBezout.TFAE`: For a Bézout domain, noetherian ↔ PID ↔ UFD ↔ ACCP -/ universe u v variable {R : Type u} [CommRing R] namespace IsBezout theorem iff_span_pair_isPrincipal : IsBezout R ↔ ∀ x y : R, (Ideal.span {x, y} : Ideal R).IsPrincipal := by classical constructor · intro H x y; infer_instance · intro H constructor apply Submodule.fg_induction · exact fun _ => ⟨⟨_, rfl⟩⟩ · rintro _ _ ⟨⟨x, rfl⟩⟩ ⟨⟨y, rfl⟩⟩; rw [← Submodule.span_insert]; exact H _ _ #align is_bezout.iff_span_pair_is_principal IsBezout.iff_span_pair_isPrincipal
Mathlib/RingTheory/Bezout.lean
42
50
theorem _root_.Function.Surjective.isBezout {S : Type v} [CommRing S] (f : R →+* S) (hf : Function.Surjective f) [IsBezout R] : IsBezout S := by
rw [iff_span_pair_isPrincipal] intro x y obtain ⟨⟨x, rfl⟩, ⟨y, rfl⟩⟩ := hf x, hf y use f (gcd x y) trans Ideal.map f (Ideal.span {gcd x y}) · rw [span_gcd, Ideal.map_span, Set.image_insert_eq, Set.image_singleton] · rw [Ideal.map_span, Set.image_singleton]; rfl
/- Copyright (c) 2019 Amelia Livingston. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Amelia Livingston, Bryan Gin-ge Chen, Patrick Massot, Wen Yang, Johan Commelin -/ import Mathlib.Data.Set.Finite import Mathlib.Order.Partition.Finpartition #align_import data.setoid.partition from "leanprover-community/mathlib"@"b363547b3113d350d053abdf2884e9850a56b205" /-! # Equivalence relations: partitions This file comprises properties of equivalence relations viewed as partitions. There are two implementations of partitions here: * A collection `c : Set (Set α)` of sets is a partition of `α` if `∅ ∉ c` and each element `a : α` belongs to a unique set `b ∈ c`. This is expressed as `IsPartition c` * An indexed partition is a map `s : ι → α` whose image is a partition. This is expressed as `IndexedPartition s`. Of course both implementations are related to `Quotient` and `Setoid`. `Setoid.isPartition.partition` and `Finpartition.isPartition_parts` furnish a link between `Setoid.IsPartition` and `Finpartition`. ## TODO Could the design of `Finpartition` inform the one of `Setoid.IsPartition`? Maybe bundling it and changing it from `Set (Set α)` to `Set α` where `[Lattice α] [OrderBot α]` would make it more usable. ## Tags setoid, equivalence, iseqv, relation, equivalence relation, partition, equivalence class -/ namespace Setoid variable {α : Type*} /-- If x ∈ α is in 2 elements of a set of sets partitioning α, those 2 sets are equal. -/ theorem eq_of_mem_eqv_class {c : Set (Set α)} (H : ∀ a, ∃! b ∈ c, a ∈ b) {x b b'} (hc : b ∈ c) (hb : x ∈ b) (hc' : b' ∈ c) (hb' : x ∈ b') : b = b' := (H x).unique ⟨hc, hb⟩ ⟨hc', hb'⟩ #align setoid.eq_of_mem_eqv_class Setoid.eq_of_mem_eqv_class /-- Makes an equivalence relation from a set of sets partitioning α. -/ def mkClasses (c : Set (Set α)) (H : ∀ a, ∃! b ∈ c, a ∈ b) : Setoid α where r x y := ∀ s ∈ c, x ∈ s → y ∈ s iseqv.refl := fun _ _ _ hx => hx iseqv.symm := fun {x _y} h s hs hy => by obtain ⟨t, ⟨ht, hx⟩, _⟩ := H x rwa [eq_of_mem_eqv_class H hs hy ht (h t ht hx)] iseqv.trans := fun {_x y z} h1 h2 s hs hx => h2 s hs (h1 s hs hx) #align setoid.mk_classes Setoid.mkClasses /-- Makes the equivalence classes of an equivalence relation. -/ def classes (r : Setoid α) : Set (Set α) := { s | ∃ y, s = { x | r.Rel x y } } #align setoid.classes Setoid.classes theorem mem_classes (r : Setoid α) (y) : { x | r.Rel x y } ∈ r.classes := ⟨y, rfl⟩ #align setoid.mem_classes Setoid.mem_classes theorem classes_ker_subset_fiber_set {β : Type*} (f : α → β) : (Setoid.ker f).classes ⊆ Set.range fun y => { x | f x = y } := by rintro s ⟨x, rfl⟩ rw [Set.mem_range] exact ⟨f x, rfl⟩ #align setoid.classes_ker_subset_fiber_set Setoid.classes_ker_subset_fiber_set theorem finite_classes_ker {α β : Type*} [Finite β] (f : α → β) : (Setoid.ker f).classes.Finite := (Set.finite_range _).subset <| classes_ker_subset_fiber_set f #align setoid.finite_classes_ker Setoid.finite_classes_ker
Mathlib/Data/Setoid/Partition.lean
78
81
theorem card_classes_ker_le {α β : Type*} [Fintype β] (f : α → β) [Fintype (Setoid.ker f).classes] : Fintype.card (Setoid.ker f).classes ≤ Fintype.card β := by
classical exact le_trans (Set.card_le_card (classes_ker_subset_fiber_set f)) (Fintype.card_range_le _)
/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.RingTheory.Kaehler import Mathlib.RingTheory.Unramified.Basic /-! # Differential properties of formally unramified algebras We show that `R`-algebra `A` is formally unramified iff the Kaehler differentials vanish. -/ universe u namespace Algebra variable {R S : Type u} [CommRing R] [CommRing S] [Algebra R S] instance FormallyUnramified.subsingleton_kaehlerDifferential [FormallyUnramified R S] : Subsingleton (Ω[S⁄R]) := by rw [← not_nontrivial_iff_subsingleton] intro h obtain ⟨f₁, f₂, e⟩ := (KaehlerDifferential.endEquiv R S).injective.nontrivial apply e ext1 apply FormallyUnramified.lift_unique' _ _ _ _ (f₁.2.trans f₂.2.symm) rw [← AlgHom.toRingHom_eq_coe, AlgHom.ker_kerSquareLift] exact ⟨_, Ideal.cotangentIdeal_square _⟩ #align algebra.formally_unramified.subsingleton_kaehler_differential Algebra.FormallyUnramified.subsingleton_kaehlerDifferential
Mathlib/RingTheory/Unramified/Derivations.lean
35
47
theorem FormallyUnramified.iff_subsingleton_kaehlerDifferential : FormallyUnramified R S ↔ Subsingleton (Ω[S⁄R]) := by
constructor · intros; infer_instance · intro H constructor intro B _ _ I hI f₁ f₂ e letI := f₁.toRingHom.toAlgebra haveI := IsScalarTower.of_algebraMap_eq' f₁.comp_algebraMap.symm have := ((KaehlerDifferential.linearMapEquivDerivation R S).toEquiv.trans (derivationToSquareZeroEquivLift I hI)).surjective.subsingleton exact Subtype.ext_iff.mp (@Subsingleton.elim _ this ⟨f₁, rfl⟩ ⟨f₂, e.symm⟩)
/- Copyright (c) 2019 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen -/ import Mathlib.LinearAlgebra.Matrix.Reindex import Mathlib.LinearAlgebra.Matrix.ToLin #align_import linear_algebra.matrix.basis from "leanprover-community/mathlib"@"6c263e4bfc2e6714de30f22178b4d0ca4d149a76" /-! # Bases and matrices This file defines the map `Basis.toMatrix` that sends a family of vectors to the matrix of their coordinates with respect to some basis. ## Main definitions * `Basis.toMatrix e v` is the matrix whose `i, j`th entry is `e.repr (v j) i` * `basis.toMatrixEquiv` is `Basis.toMatrix` bundled as a linear equiv ## Main results * `LinearMap.toMatrix_id_eq_basis_toMatrix`: `LinearMap.toMatrix b c id` is equal to `Basis.toMatrix b c` * `Basis.toMatrix_mul_toMatrix`: multiplying `Basis.toMatrix` with another `Basis.toMatrix` gives a `Basis.toMatrix` ## Tags matrix, basis -/ noncomputable section open LinearMap Matrix Set Submodule open Matrix section BasisToMatrix variable {ι ι' κ κ' : Type*} variable {R M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M] variable {R₂ M₂ : Type*} [CommRing R₂] [AddCommGroup M₂] [Module R₂ M₂] open Function Matrix /-- From a basis `e : ι → M` and a family of vectors `v : ι' → M`, make the matrix whose columns are the vectors `v i` written in the basis `e`. -/ def Basis.toMatrix (e : Basis ι R M) (v : ι' → M) : Matrix ι ι' R := fun i j => e.repr (v j) i #align basis.to_matrix Basis.toMatrix variable (e : Basis ι R M) (v : ι' → M) (i : ι) (j : ι') namespace Basis theorem toMatrix_apply : e.toMatrix v i j = e.repr (v j) i := rfl #align basis.to_matrix_apply Basis.toMatrix_apply theorem toMatrix_transpose_apply : (e.toMatrix v)ᵀ j = e.repr (v j) := funext fun _ => rfl #align basis.to_matrix_transpose_apply Basis.toMatrix_transpose_apply theorem toMatrix_eq_toMatrix_constr [Fintype ι] [DecidableEq ι] (v : ι → M) : e.toMatrix v = LinearMap.toMatrix e e (e.constr ℕ v) := by ext rw [Basis.toMatrix_apply, LinearMap.toMatrix_apply, Basis.constr_basis] #align basis.to_matrix_eq_to_matrix_constr Basis.toMatrix_eq_toMatrix_constr -- TODO (maybe) Adjust the definition of `Basis.toMatrix` to eliminate the transpose. theorem coePiBasisFun.toMatrix_eq_transpose [Finite ι] : ((Pi.basisFun R ι).toMatrix : Matrix ι ι R → Matrix ι ι R) = Matrix.transpose := by ext M i j rfl #align basis.coe_pi_basis_fun.to_matrix_eq_transpose Basis.coePiBasisFun.toMatrix_eq_transpose @[simp] theorem toMatrix_self [DecidableEq ι] : e.toMatrix e = 1 := by unfold Basis.toMatrix ext i j simp [Basis.equivFun, Matrix.one_apply, Finsupp.single_apply, eq_comm] #align basis.to_matrix_self Basis.toMatrix_self theorem toMatrix_update [DecidableEq ι'] (x : M) : e.toMatrix (Function.update v j x) = Matrix.updateColumn (e.toMatrix v) j (e.repr x) := by ext i' k rw [Basis.toMatrix, Matrix.updateColumn_apply, e.toMatrix_apply] split_ifs with h · rw [h, update_same j x v] · rw [update_noteq h] #align basis.to_matrix_update Basis.toMatrix_update /-- The basis constructed by `unitsSMul` has vectors given by a diagonal matrix. -/ @[simp] theorem toMatrix_unitsSMul [DecidableEq ι] (e : Basis ι R₂ M₂) (w : ι → R₂ˣ) : e.toMatrix (e.unitsSMul w) = diagonal ((↑) ∘ w) := by ext i j by_cases h : i = j · simp [h, toMatrix_apply, unitsSMul_apply, Units.smul_def] · simp [h, toMatrix_apply, unitsSMul_apply, Units.smul_def, Ne.symm h] #align basis.to_matrix_units_smul Basis.toMatrix_unitsSMul /-- The basis constructed by `isUnitSMul` has vectors given by a diagonal matrix. -/ @[simp] theorem toMatrix_isUnitSMul [DecidableEq ι] (e : Basis ι R₂ M₂) {w : ι → R₂} (hw : ∀ i, IsUnit (w i)) : e.toMatrix (e.isUnitSMul hw) = diagonal w := e.toMatrix_unitsSMul _ #align basis.to_matrix_is_unit_smul Basis.toMatrix_isUnitSMul @[simp] theorem sum_toMatrix_smul_self [Fintype ι] : ∑ i : ι, e.toMatrix v i j • e i = v j := by simp_rw [e.toMatrix_apply, e.sum_repr] #align basis.sum_to_matrix_smul_self Basis.sum_toMatrix_smul_self theorem toMatrix_smul {R₁ S : Type*} [CommRing R₁] [Ring S] [Algebra R₁ S] [Fintype ι] [DecidableEq ι] (x : S) (b : Basis ι R₁ S) (w : ι → S) : (b.toMatrix (x • w)) = (Algebra.leftMulMatrix b x) * (b.toMatrix w) := by ext rw [Basis.toMatrix_apply, Pi.smul_apply, smul_eq_mul, ← Algebra.leftMulMatrix_mulVec_repr] rfl
Mathlib/LinearAlgebra/Matrix/Basis.lean
124
128
theorem toMatrix_map_vecMul {S : Type*} [Ring S] [Algebra R S] [Fintype ι] (b : Basis ι R S) (v : ι' → S) : b ᵥ* ((b.toMatrix v).map <| algebraMap R S) = v := by
ext i simp_rw [vecMul, dotProduct, Matrix.map_apply, ← Algebra.commutes, ← Algebra.smul_def, sum_toMatrix_smul_self]
/- Copyright (c) 2021 Ivan Sadofschi Costa. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Ivan Sadofschi Costa -/ import Mathlib.Data.Finsupp.Defs #align_import data.finsupp.fin from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c" /-! # `cons` and `tail` for maps `Fin n →₀ M` We interpret maps `Fin n →₀ M` as `n`-tuples of elements of `M`, We define the following operations: * `Finsupp.tail` : the tail of a map `Fin (n + 1) →₀ M`, i.e., its last `n` entries; * `Finsupp.cons` : adding an element at the beginning of an `n`-tuple, to get an `n + 1`-tuple; In this context, we prove some usual properties of `tail` and `cons`, analogous to those of `Data.Fin.Tuple.Basic`. -/ noncomputable section namespace Finsupp variable {n : ℕ} (i : Fin n) {M : Type*} [Zero M] (y : M) (t : Fin (n + 1) →₀ M) (s : Fin n →₀ M) /-- `tail` for maps `Fin (n + 1) →₀ M`. See `Fin.tail` for more details. -/ def tail (s : Fin (n + 1) →₀ M) : Fin n →₀ M := Finsupp.equivFunOnFinite.symm (Fin.tail s) #align finsupp.tail Finsupp.tail /-- `cons` for maps `Fin n →₀ M`. See `Fin.cons` for more details. -/ def cons (y : M) (s : Fin n →₀ M) : Fin (n + 1) →₀ M := Finsupp.equivFunOnFinite.symm (Fin.cons y s : Fin (n + 1) → M) #align finsupp.cons Finsupp.cons theorem tail_apply : tail t i = t i.succ := rfl #align finsupp.tail_apply Finsupp.tail_apply @[simp] theorem cons_zero : cons y s 0 = y := rfl #align finsupp.cons_zero Finsupp.cons_zero @[simp] theorem cons_succ : cons y s i.succ = s i := -- Porting note: was Fin.cons_succ _ _ _ rfl #align finsupp.cons_succ Finsupp.cons_succ @[simp] theorem tail_cons : tail (cons y s) = s := ext fun k => by simp only [tail_apply, cons_succ] #align finsupp.tail_cons Finsupp.tail_cons @[simp] theorem cons_tail : cons (t 0) (tail t) = t := by ext a by_cases c_a : a = 0 · rw [c_a, cons_zero] · rw [← Fin.succ_pred a c_a, cons_succ, ← tail_apply] #align finsupp.cons_tail Finsupp.cons_tail @[simp] theorem cons_zero_zero : cons 0 (0 : Fin n →₀ M) = 0 := by ext a by_cases c : a = 0 · simp [c] · rw [← Fin.succ_pred a c, cons_succ] simp #align finsupp.cons_zero_zero Finsupp.cons_zero_zero variable {s} {y}
Mathlib/Data/Finsupp/Fin.lean
78
80
theorem cons_ne_zero_of_left (h : y ≠ 0) : cons y s ≠ 0 := by
contrapose! h with c rw [← cons_zero y s, c, Finsupp.coe_zero, Pi.zero_apply]
/- 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]
Mathlib/Analysis/Analytic/Inverse.lean
73
74
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]
/- Copyright (c) 2023 Matthew Robert Ballard. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Matthew Robert Ballard -/ import Mathlib.Algebra.Divisibility.Units import Mathlib.Algebra.Order.Ring.Nat import Mathlib.Tactic.Common /-! # The maximal power of one natural number dividing another Here we introduce `p.maxPowDiv n` which returns the maximal `k : ℕ` for which `p ^ k ∣ n` with the convention that `maxPowDiv 1 n = 0` for all `n`. We prove enough about `maxPowDiv` in this file to show equality with `Nat.padicValNat` in `padicValNat.padicValNat_eq_maxPowDiv`. The implementation of `maxPowDiv` improves on the speed of `padicValNat`. -/ namespace Nat open Nat /-- Tail recursive function which returns the largest `k : ℕ` such that `p ^ k ∣ n` for any `p : ℕ`. `padicValNat_eq_maxPowDiv` allows the code generator to use this definition for `padicValNat` -/ def maxPowDiv (p n : ℕ) : ℕ := go 0 p n where go (k p n : ℕ) : ℕ := if 1 < p ∧ 0 < n ∧ n % p = 0 then go (k+1) p (n / p) else k termination_by n decreasing_by apply Nat.div_lt_self <;> tauto attribute [inherit_doc maxPowDiv] maxPowDiv.go end Nat namespace Nat.maxPowDiv theorem go_succ {k p n : ℕ} : go (k+1) p n = go k p n + 1 := by induction k, p, n using go.induct case case1 h ih => unfold go simp only [if_pos h] exact ih case case2 h => unfold go simp only [if_neg h] @[simp]
Mathlib/Data/Nat/MaxPowDiv.lean
57
60
theorem zero_base {n : ℕ} : maxPowDiv 0 n = 0 := by
dsimp [maxPowDiv] rw [maxPowDiv.go] simp
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Johannes Hölzl -/ import Mathlib.Dynamics.Ergodic.MeasurePreserving import Mathlib.MeasureTheory.Function.SimpleFunc import Mathlib.MeasureTheory.Measure.MutuallySingular import Mathlib.MeasureTheory.Measure.Count import Mathlib.Topology.IndicatorConstPointwise import Mathlib.MeasureTheory.Constructions.BorelSpace.Real #align_import measure_theory.integral.lebesgue from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520" /-! # Lower Lebesgue integral for `ℝ≥0∞`-valued functions We define the lower Lebesgue integral of an `ℝ≥0∞`-valued function. ## Notation We introduce the following notation for the lower Lebesgue integral of a function `f : α → ℝ≥0∞`. * `∫⁻ x, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` with respect to a measure `μ`; * `∫⁻ x, f x`: integral of a function `f : α → ℝ≥0∞` with respect to the canonical measure `volume` on `α`; * `∫⁻ x in s, f x ∂μ`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect to a measure `μ`, defined as `∫⁻ x, f x ∂(μ.restrict s)`; * `∫⁻ x in s, f x`: integral of a function `f : α → ℝ≥0∞` over a set `s` with respect to the canonical measure `volume`, defined as `∫⁻ x, f x ∂(volume.restrict s)`. -/ assert_not_exists NormedSpace set_option autoImplicit true noncomputable section open Set hiding restrict restrict_apply open Filter ENNReal open Function (support) open scoped Classical open Topology NNReal ENNReal MeasureTheory namespace MeasureTheory local infixr:25 " →ₛ " => SimpleFunc variable {α β γ δ : Type*} section Lintegral open SimpleFunc variable {m : MeasurableSpace α} {μ ν : Measure α} /-- The **lower Lebesgue integral** of a function `f` with respect to a measure `μ`. -/ irreducible_def lintegral {_ : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) : ℝ≥0∞ := ⨆ (g : α →ₛ ℝ≥0∞) (_ : ⇑g ≤ f), g.lintegral μ #align measure_theory.lintegral MeasureTheory.lintegral /-! In the notation for integrals, an expression like `∫⁻ x, g ‖x‖ ∂μ` will not be parsed correctly, and needs parentheses. We do not set the binding power of `r` to `0`, because then `∫⁻ x, f x = 0` will be parsed incorrectly. -/ @[inherit_doc MeasureTheory.lintegral] notation3 "∫⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => lintegral μ r @[inherit_doc MeasureTheory.lintegral] notation3 "∫⁻ "(...)", "r:60:(scoped f => lintegral volume f) => r @[inherit_doc MeasureTheory.lintegral] notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => lintegral (Measure.restrict μ s) r @[inherit_doc MeasureTheory.lintegral] notation3"∫⁻ "(...)" in "s", "r:60:(scoped f => lintegral (Measure.restrict volume s) f) => r theorem SimpleFunc.lintegral_eq_lintegral {m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (μ : Measure α) : ∫⁻ a, f a ∂μ = f.lintegral μ := by rw [MeasureTheory.lintegral] exact le_antisymm (iSup₂_le fun g hg => lintegral_mono hg <| le_rfl) (le_iSup₂_of_le f le_rfl le_rfl) #align measure_theory.simple_func.lintegral_eq_lintegral MeasureTheory.SimpleFunc.lintegral_eq_lintegral @[mono] theorem lintegral_mono' {m : MeasurableSpace α} ⦃μ ν : Measure α⦄ (hμν : μ ≤ ν) ⦃f g : α → ℝ≥0∞⦄ (hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂ν := by rw [lintegral, lintegral] exact iSup_mono fun φ => iSup_mono' fun hφ => ⟨le_trans hφ hfg, lintegral_mono (le_refl φ) hμν⟩ #align measure_theory.lintegral_mono' MeasureTheory.lintegral_mono' -- workaround for the known eta-reduction issue with `@[gcongr]` @[gcongr] theorem lintegral_mono_fn' ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) (h2 : μ ≤ ν) : lintegral μ f ≤ lintegral ν g := lintegral_mono' h2 hfg theorem lintegral_mono ⦃f g : α → ℝ≥0∞⦄ (hfg : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ := lintegral_mono' (le_refl μ) hfg #align measure_theory.lintegral_mono MeasureTheory.lintegral_mono -- workaround for the known eta-reduction issue with `@[gcongr]` @[gcongr] theorem lintegral_mono_fn ⦃f g : α → ℝ≥0∞⦄ (hfg : ∀ x, f x ≤ g x) : lintegral μ f ≤ lintegral μ g := lintegral_mono hfg theorem lintegral_mono_nnreal {f g : α → ℝ≥0} (h : f ≤ g) : ∫⁻ a, f a ∂μ ≤ ∫⁻ a, g a ∂μ := lintegral_mono fun a => ENNReal.coe_le_coe.2 (h a) #align measure_theory.lintegral_mono_nnreal MeasureTheory.lintegral_mono_nnreal
Mathlib/MeasureTheory/Integral/Lebesgue.lean
114
120
theorem iSup_lintegral_measurable_le_eq_lintegral (f : α → ℝ≥0∞) : ⨆ (g : α → ℝ≥0∞) (_ : Measurable g) (_ : g ≤ f), ∫⁻ a, g a ∂μ = ∫⁻ a, f a ∂μ := by
apply le_antisymm · exact iSup_le fun i => iSup_le fun _ => iSup_le fun h'i => lintegral_mono h'i · rw [lintegral] refine iSup₂_le fun i hi => le_iSup₂_of_le i i.measurable <| le_iSup_of_le hi ?_ exact le_of_eq (i.lintegral_eq_lintegral _).symm
/- Copyright (c) 2022 Rishikesh Vaishnav. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rishikesh Vaishnav -/ import Mathlib.MeasureTheory.Measure.Typeclasses #align_import probability.conditional_probability from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a" /-! # Conditional Probability This file defines conditional probability and includes basic results relating to it. Given some measure `μ` defined on a measure space on some type `Ω` and some `s : Set Ω`, we define the measure of `μ` conditioned on `s` as the restricted measure scaled by the inverse of the measure of `s`: `cond μ s = (μ s)⁻¹ • μ.restrict s`. The scaling ensures that this is a probability measure (when `μ` is a finite measure). From this definition, we derive the "axiomatic" definition of conditional probability based on application: for any `s t : Set Ω`, we have `μ[t|s] = (μ s)⁻¹ * μ (s ∩ t)`. ## Main Statements * `cond_cond_eq_cond_inter`: conditioning on one set and then another is equivalent to conditioning on their intersection. * `cond_eq_inv_mul_cond_mul`: Bayes' Theorem, `μ[t|s] = (μ s)⁻¹ * μ[s|t] * (μ t)`. ## Notations This file uses the notation `μ[|s]` the measure of `μ` conditioned on `s`, and `μ[t|s]` for the probability of `t` given `s` under `μ` (equivalent to the application `μ[|s] t`). These notations are contained in the locale `ProbabilityTheory`. ## Implementation notes Because we have the alternative measure restriction application principles `Measure.restrict_apply` and `Measure.restrict_apply'`, which require measurability of the restricted and restricting sets, respectively, many of the theorems here will have corresponding alternatives as well. For the sake of brevity, we've chosen to only go with `Measure.restrict_apply'` for now, but the alternative theorems can be added if needed. Use of `@[simp]` generally follows the rule of removing conditions on a measure when possible. Hypotheses that are used to "define" a conditional distribution by requiring that the conditioning set has non-zero measure should be named using the abbreviation "c" (which stands for "conditionable") rather than "nz". For example `(hci : μ (s ∩ t) ≠ 0)` (rather than `hnzi`) should be used for a hypothesis ensuring that `μ[|s ∩ t]` is defined. ## Tags conditional, conditioned, bayes -/ noncomputable section open ENNReal MeasureTheory MeasureTheory.Measure MeasurableSpace Set variable {Ω Ω' α : Type*} {m : MeasurableSpace Ω} {m' : MeasurableSpace Ω'} (μ : Measure Ω) {s t : Set Ω} namespace ProbabilityTheory section Definitions /-- The conditional probability measure of measure `μ` on set `s` is `μ` restricted to `s` and scaled by the inverse of `μ s` (to make it a probability measure): `(μ s)⁻¹ • μ.restrict s`. -/ def cond (s : Set Ω) : Measure Ω := (μ s)⁻¹ • μ.restrict s #align probability_theory.cond ProbabilityTheory.cond end Definitions @[inherit_doc] scoped notation μ "[" s "|" t "]" => ProbabilityTheory.cond μ t s @[inherit_doc] scoped notation:max μ "[|" t "]" => ProbabilityTheory.cond μ t /-- The conditional probability measure of measure `μ` on `{ω | X ω = x}`. It is `μ` restricted to `{ω | X ω = x}` and scaled by the inverse of `μ {ω | X ω = x}` (to make it a probability measure): `(μ {ω | X ω = x})⁻¹ • μ.restrict {ω | X ω = x}`. -/ scoped notation:max μ "[|" X " ← " x "]" => μ[|X ⁻¹' {x}] /-- The conditional probability measure of any measure on any set of finite positive measure is a probability measure. -/ theorem cond_isProbabilityMeasure_of_finite (hcs : μ s ≠ 0) (hs : μ s ≠ ∞) : IsProbabilityMeasure μ[|s] := ⟨by unfold ProbabilityTheory.cond simp only [Measure.coe_smul, Pi.smul_apply, MeasurableSet.univ, Measure.restrict_apply, Set.univ_inter, smul_eq_mul] exact ENNReal.inv_mul_cancel hcs hs⟩ /-- The conditional probability measure of any finite measure on any set of positive measure is a probability measure. -/ theorem cond_isProbabilityMeasure [IsFiniteMeasure μ] (hcs : μ s ≠ 0) : IsProbabilityMeasure μ[|s] := cond_isProbabilityMeasure_of_finite μ hcs (measure_ne_top μ s) #align probability_theory.cond_is_probability_measure ProbabilityTheory.cond_isProbabilityMeasure instance cond_isFiniteMeasure : IsFiniteMeasure μ[|s] := by constructor simp only [Measure.coe_smul, Pi.smul_apply, MeasurableSet.univ, Measure.restrict_apply, Set.univ_inter, smul_eq_mul, ProbabilityTheory.cond, ← ENNReal.div_eq_inv_mul] exact ENNReal.div_self_le_one.trans_lt ENNReal.one_lt_top theorem cond_toMeasurable_eq : μ[|(toMeasurable μ s)] = μ[|s] := by unfold cond by_cases hnt : μ s = ∞ · simp [hnt] · simp [Measure.restrict_toMeasurable hnt] variable {μ} in lemma cond_absolutelyContinuous : μ[|s] ≪ μ := smul_absolutelyContinuous.trans restrict_le_self.absolutelyContinuous variable {μ} in lemma absolutelyContinuous_cond_univ [IsFiniteMeasure μ] : μ ≪ μ[|univ] := by rw [cond, restrict_univ] refine absolutelyContinuous_smul ?_ simp [measure_ne_top] section Bayes @[simp] theorem cond_empty : μ[|∅] = 0 := by simp [cond] #align probability_theory.cond_empty ProbabilityTheory.cond_empty @[simp] theorem cond_univ [IsProbabilityMeasure μ] : μ[|Set.univ] = μ := by simp [cond, measure_univ, Measure.restrict_univ] #align probability_theory.cond_univ ProbabilityTheory.cond_univ @[simp] lemma cond_eq_zero (hμs : μ s ≠ ⊤) : μ[|s] = 0 ↔ μ s = 0 := by simp [cond, hμs] lemma cond_eq_zero_of_meas_eq_zero (hμs : μ s = 0) : μ[|s] = 0 := by simp [hμs] /-- The axiomatic definition of conditional probability derived from a measure-theoretic one. -/
Mathlib/Probability/ConditionalProbability.lean
143
144
theorem cond_apply (hms : MeasurableSet s) (t : Set Ω) : μ[t|s] = (μ s)⁻¹ * μ (s ∩ t) := by
rw [cond, Measure.smul_apply, Measure.restrict_apply' hms, Set.inter_comm, smul_eq_mul]
/- Copyright (c) 2020 Scott Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Scott Morrison, Johan Commelin -/ import Mathlib.LinearAlgebra.FiniteDimensional import Mathlib.LinearAlgebra.TensorProduct.Tower import Mathlib.RingTheory.Adjoin.Basic import Mathlib.LinearAlgebra.DirectSum.Finsupp #align_import ring_theory.tensor_product from "leanprover-community/mathlib"@"88fcdc3da43943f5b01925deddaa5bf0c0e85e4e" /-! # The tensor product of R-algebras This file provides results about the multiplicative structure on `A ⊗[R] B` when `R` is a commutative (semi)ring and `A` and `B` are both `R`-algebras. On these tensor products, multiplication is characterized by `(a₁ ⊗ₜ b₁) * (a₂ ⊗ₜ b₂) = (a₁ * a₂) ⊗ₜ (b₁ * b₂)`. ## Main declarations - `LinearMap.baseChange A f` is the `A`-linear map `A ⊗ f`, for an `R`-linear map `f`. - `Algebra.TensorProduct.semiring`: the ring structure on `A ⊗[R] B` for two `R`-algebras `A`, `B`. - `Algebra.TensorProduct.leftAlgebra`: the `S`-algebra structure on `A ⊗[R] B`, for when `A` is additionally an `S` algebra. - the structure isomorphisms * `Algebra.TensorProduct.lid : R ⊗[R] A ≃ₐ[R] A` * `Algebra.TensorProduct.rid : A ⊗[R] R ≃ₐ[S] A` (usually used with `S = R` or `S = A`) * `Algebra.TensorProduct.comm : A ⊗[R] B ≃ₐ[R] B ⊗[R] A` * `Algebra.TensorProduct.assoc : ((A ⊗[R] B) ⊗[R] C) ≃ₐ[R] (A ⊗[R] (B ⊗[R] C))` - `Algebra.TensorProduct.liftEquiv`: a universal property for the tensor product of algebras. ## References * [C. Kassel, *Quantum Groups* (§II.4)][Kassel1995] -/ suppress_compilation open scoped TensorProduct open TensorProduct namespace LinearMap open TensorProduct /-! ### The base-change of a linear map of `R`-modules to a linear map of `A`-modules -/ section Semiring variable {R A B M N P : Type*} [CommSemiring R] variable [Semiring A] [Algebra R A] [Semiring B] [Algebra R B] variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P] variable [Module R M] [Module R N] [Module R P] variable (r : R) (f g : M →ₗ[R] N) variable (A) /-- `baseChange A f` for `f : M →ₗ[R] N` is the `A`-linear map `A ⊗[R] M →ₗ[A] A ⊗[R] N`. This "base change" operation is also known as "extension of scalars". -/ def baseChange (f : M →ₗ[R] N) : A ⊗[R] M →ₗ[A] A ⊗[R] N := AlgebraTensorModule.map (LinearMap.id : A →ₗ[A] A) f #align linear_map.base_change LinearMap.baseChange variable {A} @[simp] theorem baseChange_tmul (a : A) (x : M) : f.baseChange A (a ⊗ₜ x) = a ⊗ₜ f x := rfl #align linear_map.base_change_tmul LinearMap.baseChange_tmul theorem baseChange_eq_ltensor : (f.baseChange A : A ⊗ M → A ⊗ N) = f.lTensor A := rfl #align linear_map.base_change_eq_ltensor LinearMap.baseChange_eq_ltensor @[simp] theorem baseChange_add : (f + g).baseChange A = f.baseChange A + g.baseChange A := by ext -- Porting note: added `-baseChange_tmul` simp [baseChange_eq_ltensor, -baseChange_tmul] #align linear_map.base_change_add LinearMap.baseChange_add @[simp] theorem baseChange_zero : baseChange A (0 : M →ₗ[R] N) = 0 := by ext simp [baseChange_eq_ltensor] #align linear_map.base_change_zero LinearMap.baseChange_zero @[simp] theorem baseChange_smul : (r • f).baseChange A = r • f.baseChange A := by ext simp [baseChange_tmul] #align linear_map.base_change_smul LinearMap.baseChange_smul @[simp] lemma baseChange_id : (.id : M →ₗ[R] M).baseChange A = .id := by ext; simp lemma baseChange_comp (g : N →ₗ[R] P) : (g ∘ₗ f).baseChange A = g.baseChange A ∘ₗ f.baseChange A := by ext; simp variable (R M) in @[simp] lemma baseChange_one : (1 : Module.End R M).baseChange A = 1 := baseChange_id lemma baseChange_mul (f g : Module.End R M) : (f * g).baseChange A = f.baseChange A * g.baseChange A := by ext; simp variable (R A M N) /-- `baseChange` as a linear map. When `M = N`, this is true more strongly as `Module.End.baseChangeHom`. -/ @[simps] def baseChangeHom : (M →ₗ[R] N) →ₗ[R] A ⊗[R] M →ₗ[A] A ⊗[R] N where toFun := baseChange A map_add' := baseChange_add map_smul' := baseChange_smul #align linear_map.base_change_hom LinearMap.baseChangeHom /-- `baseChange` as an `AlgHom`. -/ @[simps!] def _root_.Module.End.baseChangeHom : Module.End R M →ₐ[R] Module.End A (A ⊗[R] M) := .ofLinearMap (LinearMap.baseChangeHom _ _ _ _) (baseChange_one _ _) baseChange_mul lemma baseChange_pow (f : Module.End R M) (n : ℕ) : (f ^ n).baseChange A = f.baseChange A ^ n := map_pow (Module.End.baseChangeHom _ _ _) f n end Semiring section Ring variable {R A B M N : Type*} [CommRing R] variable [Ring A] [Algebra R A] [Ring B] [Algebra R B] variable [AddCommGroup M] [Module R M] [AddCommGroup N] [Module R N] variable (f g : M →ₗ[R] N) @[simp]
Mathlib/RingTheory/TensorProduct/Basic.lean
148
151
theorem baseChange_sub : (f - g).baseChange A = f.baseChange A - g.baseChange A := by
ext -- Porting note: `tmul_sub` wasn't needed in mathlib3 simp [baseChange_eq_ltensor, tmul_sub]
/- Copyright (c) 2022 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson -/ import Mathlib.ModelTheory.Substructures #align_import model_theory.finitely_generated from "leanprover-community/mathlib"@"0602c59878ff3d5f71dea69c2d32ccf2e93e5398" /-! # Finitely Generated First-Order Structures This file defines what it means for a first-order (sub)structure to be finitely or countably generated, similarly to other finitely-generated objects in the algebra library. ## Main Definitions * `FirstOrder.Language.Substructure.FG` indicates that a substructure is finitely generated. * `FirstOrder.Language.Structure.FG` indicates that a structure is finitely generated. * `FirstOrder.Language.Substructure.CG` indicates that a substructure is countably generated. * `FirstOrder.Language.Structure.CG` indicates that a structure is countably generated. ## TODO Develop a more unified definition of finite generation using the theory of closure operators, or use this definition of finite generation to define the others. -/ open FirstOrder Set namespace FirstOrder namespace Language open Structure variable {L : Language} {M : Type*} [L.Structure M] namespace Substructure /-- A substructure of `M` is finitely generated if it is the closure of a finite subset of `M`. -/ def FG (N : L.Substructure M) : Prop := ∃ S : Finset M, closure L S = N #align first_order.language.substructure.fg FirstOrder.Language.Substructure.FG theorem fg_def {N : L.Substructure M} : N.FG ↔ ∃ S : Set M, S.Finite ∧ closure L S = N := ⟨fun ⟨t, h⟩ => ⟨_, Finset.finite_toSet t, h⟩, by rintro ⟨t', h, rfl⟩ rcases Finite.exists_finset_coe h with ⟨t, rfl⟩ exact ⟨t, rfl⟩⟩ #align first_order.language.substructure.fg_def FirstOrder.Language.Substructure.fg_def
Mathlib/ModelTheory/FinitelyGenerated.lean
52
60
theorem fg_iff_exists_fin_generating_family {N : L.Substructure M} : N.FG ↔ ∃ (n : ℕ) (s : Fin n → M), closure L (range s) = N := by
rw [fg_def] constructor · rintro ⟨S, Sfin, hS⟩ obtain ⟨n, f, rfl⟩ := Sfin.fin_embedding exact ⟨n, f, hS⟩ · rintro ⟨n, s, hs⟩ exact ⟨range s, finite_range s, hs⟩
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Johannes Hölzl, Yury G. Kudryashov, Patrick Massot -/ import Mathlib.Algebra.GeomSum import Mathlib.Order.Filter.Archimedean import Mathlib.Order.Iterate import Mathlib.Topology.Algebra.Algebra import Mathlib.Topology.Algebra.InfiniteSum.Real #align_import analysis.specific_limits.basic from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2" /-! # A collection of specific limit computations This file, by design, is independent of `NormedSpace` in the import hierarchy. It contains important specific limit computations in metric spaces, in ordered rings/fields, and in specific instances of these such as `ℝ`, `ℝ≥0` and `ℝ≥0∞`. -/ noncomputable section open scoped Classical open Set Function Filter Finset Metric open scoped Classical open Topology Nat uniformity NNReal ENNReal variable {α : Type*} {β : Type*} {ι : Type*} theorem tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) := tendsto_inv_atTop_zero.comp tendsto_natCast_atTop_atTop #align tendsto_inverse_at_top_nhds_0_nat tendsto_inverse_atTop_nhds_zero_nat @[deprecated (since := "2024-01-31")] alias tendsto_inverse_atTop_nhds_0_nat := tendsto_inverse_atTop_nhds_zero_nat theorem tendsto_const_div_atTop_nhds_zero_nat (C : ℝ) : Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by simpa only [mul_zero] using tendsto_const_nhds.mul tendsto_inverse_atTop_nhds_zero_nat #align tendsto_const_div_at_top_nhds_0_nat tendsto_const_div_atTop_nhds_zero_nat @[deprecated (since := "2024-01-31")] alias tendsto_const_div_atTop_nhds_0_nat := tendsto_const_div_atTop_nhds_zero_nat theorem tendsto_one_div_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ 1/(n : ℝ)) atTop (𝓝 0) := tendsto_const_div_atTop_nhds_zero_nat 1 @[deprecated (since := "2024-01-31")] alias tendsto_one_div_atTop_nhds_0_nat := tendsto_one_div_atTop_nhds_zero_nat theorem NNReal.tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by rw [← NNReal.tendsto_coe] exact _root_.tendsto_inverse_atTop_nhds_zero_nat #align nnreal.tendsto_inverse_at_top_nhds_0_nat NNReal.tendsto_inverse_atTop_nhds_zero_nat @[deprecated (since := "2024-01-31")] alias NNReal.tendsto_inverse_atTop_nhds_0_nat := NNReal.tendsto_inverse_atTop_nhds_zero_nat theorem NNReal.tendsto_const_div_atTop_nhds_zero_nat (C : ℝ≥0) : Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by simpa using tendsto_const_nhds.mul NNReal.tendsto_inverse_atTop_nhds_zero_nat #align nnreal.tendsto_const_div_at_top_nhds_0_nat NNReal.tendsto_const_div_atTop_nhds_zero_nat @[deprecated (since := "2024-01-31")] alias NNReal.tendsto_const_div_atTop_nhds_0_nat := NNReal.tendsto_const_div_atTop_nhds_zero_nat theorem tendsto_one_div_add_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ 1 / ((n : ℝ) + 1)) atTop (𝓝 0) := suffices Tendsto (fun n : ℕ ↦ 1 / (↑(n + 1) : ℝ)) atTop (𝓝 0) by simpa (tendsto_add_atTop_iff_nat 1).2 (_root_.tendsto_const_div_atTop_nhds_zero_nat 1) #align tendsto_one_div_add_at_top_nhds_0_nat tendsto_one_div_add_atTop_nhds_zero_nat @[deprecated (since := "2024-01-31")] alias tendsto_one_div_add_atTop_nhds_0_nat := tendsto_one_div_add_atTop_nhds_zero_nat
Mathlib/Analysis/SpecificLimits/Basic.lean
74
79
theorem NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜] [Algebra ℝ≥0 𝕜] [TopologicalSpace 𝕜] [ContinuousSMul ℝ≥0 𝕜] : Tendsto (algebraMap ℝ≥0 𝕜 ∘ fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
convert (continuous_algebraMap ℝ≥0 𝕜).continuousAt.tendsto.comp tendsto_inverse_atTop_nhds_zero_nat rw [map_zero]
/- 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.Analysis.Convex.Basic import Mathlib.Topology.Algebra.Group.Basic import Mathlib.Topology.Order.Basic #align_import analysis.convex.strict from "leanprover-community/mathlib"@"84dc0bd6619acaea625086d6f53cb35cdd554219" /-! # Strictly convex sets This file defines strictly convex sets. A set is strictly convex if the open segment between any two distinct points lies in its interior. -/ open Set open Convex Pointwise variable {𝕜 𝕝 E F β : Type*} open Function Set open Convex section OrderedSemiring variable [OrderedSemiring 𝕜] [TopologicalSpace E] [TopologicalSpace F] section AddCommMonoid variable [AddCommMonoid E] [AddCommMonoid F] section SMul variable (𝕜) variable [SMul 𝕜 E] [SMul 𝕜 F] (s : Set E) /-- A set is strictly convex if the open segment between any two distinct points lies is in its interior. This basically means "convex and not flat on the boundary". -/ def StrictConvex : Prop := s.Pairwise fun x y => ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • x + b • y ∈ interior s #align strict_convex StrictConvex variable {𝕜 s} variable {x y : E} {a b : 𝕜} theorem strictConvex_iff_openSegment_subset : StrictConvex 𝕜 s ↔ s.Pairwise fun x y => openSegment 𝕜 x y ⊆ interior s := forall₅_congr fun _ _ _ _ _ => (openSegment_subset_iff 𝕜).symm #align strict_convex_iff_open_segment_subset strictConvex_iff_openSegment_subset theorem StrictConvex.openSegment_subset (hs : StrictConvex 𝕜 s) (hx : x ∈ s) (hy : y ∈ s) (h : x ≠ y) : openSegment 𝕜 x y ⊆ interior s := strictConvex_iff_openSegment_subset.1 hs hx hy h #align strict_convex.open_segment_subset StrictConvex.openSegment_subset theorem strictConvex_empty : StrictConvex 𝕜 (∅ : Set E) := pairwise_empty _ #align strict_convex_empty strictConvex_empty
Mathlib/Analysis/Convex/Strict.lean
67
70
theorem strictConvex_univ : StrictConvex 𝕜 (univ : Set E) := by
intro x _ y _ _ a b _ _ _ rw [interior_univ] exact mem_univ _
/- Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Bhavik Mehta -/ import Mathlib.Analysis.Convex.Extreme import Mathlib.Analysis.Convex.Function import Mathlib.Topology.Algebra.Module.Basic import Mathlib.Topology.Order.OrderClosed #align_import analysis.convex.exposed from "leanprover-community/mathlib"@"48024901a8e2a462363650c50d62248a77cbcab3" /-! # Exposed sets This file defines exposed sets and exposed points for sets in a real vector space. An exposed subset of `A` is a subset of `A` that is the set of all maximal points of a functional (a continuous linear map `E → 𝕜`) over `A`. By convention, `∅` is an exposed subset of all sets. This allows for better functoriality of the definition (the intersection of two exposed subsets is exposed, faces of a polytope form a bounded lattice). This is an analytic notion of "being on the side of". It is stronger than being extreme (see `IsExposed.isExtreme`), but weaker (for exposed points) than being a vertex. An exposed set of `A` is sometimes called a "face of `A`", but we decided to reserve this terminology to the more specific notion of a face of a polytope (sometimes hopefully soon out on mathlib!). ## Main declarations * `IsExposed 𝕜 A B`: States that `B` is an exposed set of `A` (in the literature, `A` is often implicit). * `IsExposed.isExtreme`: An exposed set is also extreme. ## References See chapter 8 of [Barry Simon, *Convexity*][simon2011] ## TODO Define intrinsic frontier/interior and prove the lemmas related to exposed sets and points. Generalise to Locally Convex Topological Vector Spaces™ More not-yet-PRed stuff is available on the branch `sperner_again`. -/ open scoped Classical open Affine open Set section PreorderSemiring variable (𝕜 : Type*) {E : Type*} [TopologicalSpace 𝕜] [Semiring 𝕜] [Preorder 𝕜] [AddCommMonoid E] [TopologicalSpace E] [Module 𝕜 E] {A B : Set E} /-- A set `B` is exposed with respect to `A` iff it maximizes some functional over `A` (and contains all points maximizing it). Written `IsExposed 𝕜 A B`. -/ def IsExposed (A B : Set E) : Prop := B.Nonempty → ∃ l : E →L[𝕜] 𝕜, B = { x ∈ A | ∀ y ∈ A, l y ≤ l x } #align is_exposed IsExposed end PreorderSemiring section OrderedRing variable {𝕜 : Type*} {E : Type*} [TopologicalSpace 𝕜] [OrderedRing 𝕜] [AddCommMonoid E] [TopologicalSpace E] [Module 𝕜 E] {l : E →L[𝕜] 𝕜} {A B C : Set E} {X : Finset E} {x : E} /-- A useful way to build exposed sets from intersecting `A` with halfspaces (modelled by an inequality with a functional). -/ def ContinuousLinearMap.toExposed (l : E →L[𝕜] 𝕜) (A : Set E) : Set E := { x ∈ A | ∀ y ∈ A, l y ≤ l x } #align continuous_linear_map.to_exposed ContinuousLinearMap.toExposed theorem ContinuousLinearMap.toExposed.isExposed : IsExposed 𝕜 A (l.toExposed A) := fun _ => ⟨l, rfl⟩ #align continuous_linear_map.to_exposed.is_exposed ContinuousLinearMap.toExposed.isExposed theorem isExposed_empty : IsExposed 𝕜 A ∅ := fun ⟨_, hx⟩ => by exfalso exact hx #align is_exposed_empty isExposed_empty namespace IsExposed protected theorem subset (hAB : IsExposed 𝕜 A B) : B ⊆ A := by rintro x hx obtain ⟨_, rfl⟩ := hAB ⟨x, hx⟩ exact hx.1 #align is_exposed.subset IsExposed.subset @[refl] protected theorem refl (A : Set E) : IsExposed 𝕜 A A := fun ⟨_, _⟩ => ⟨0, Subset.antisymm (fun _ hx => ⟨hx, fun _ _ => le_refl 0⟩) fun _ hx => hx.1⟩ #align is_exposed.refl IsExposed.refl protected theorem antisymm (hB : IsExposed 𝕜 A B) (hA : IsExposed 𝕜 B A) : A = B := hA.subset.antisymm hB.subset #align is_exposed.antisymm IsExposed.antisymm /-! `IsExposed` is *not* transitive: Consider a (topologically) open cube with vertices `A₀₀₀, ..., A₁₁₁` and add to it the triangle `A₀₀₀A₀₀₁A₀₁₀`. Then `A₀₀₁A₀₁₀` is an exposed subset of `A₀₀₀A₀₀₁A₀₁₀` which is an exposed subset of the cube, but `A₀₀₁A₀₁₀` is not itself an exposed subset of the cube. -/ protected theorem mono (hC : IsExposed 𝕜 A C) (hBA : B ⊆ A) (hCB : C ⊆ B) : IsExposed 𝕜 B C := by rintro ⟨w, hw⟩ obtain ⟨l, rfl⟩ := hC ⟨w, hw⟩ exact ⟨l, Subset.antisymm (fun x hx => ⟨hCB hx, fun y hy => hx.2 y (hBA hy)⟩) fun x hx => ⟨hBA hx.1, fun y hy => (hw.2 y hy).trans (hx.2 w (hCB hw))⟩⟩ #align is_exposed.mono IsExposed.mono /-- If `B` is a nonempty exposed subset of `A`, then `B` is the intersection of `A` with some closed halfspace. The converse is *not* true. It would require that the corresponding open halfspace doesn't intersect `A`. -/
Mathlib/Analysis/Convex/Exposed.lean
117
122
theorem eq_inter_halfspace' {A B : Set E} (hAB : IsExposed 𝕜 A B) (hB : B.Nonempty) : ∃ l : E →L[𝕜] 𝕜, ∃ a, B = { x ∈ A | a ≤ l x } := by
obtain ⟨l, rfl⟩ := hAB hB obtain ⟨w, hw⟩ := hB exact ⟨l, l w, Subset.antisymm (fun x hx => ⟨hx.1, hx.2 w hw.1⟩) fun x hx => ⟨hx.1, fun y hy => (hw.2 y hy).trans hx.2⟩⟩
/- 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.Algebra.Group.Basic import Mathlib.Algebra.Group.Nat import Mathlib.Init.Data.Nat.Lemmas #align_import data.nat.psub from "leanprover-community/mathlib"@"70d50ecfd4900dd6d328da39ab7ebd516abe4025" /-! # Partial predecessor and partial subtraction on the natural numbers The usual definition of natural number subtraction (`Nat.sub`) returns 0 as a "garbage value" for `a - b` when `a < b`. Similarly, `Nat.pred 0` is defined to be `0`. The functions in this file wrap the result in an `Option` type instead: ## Main definitions - `Nat.ppred`: a partial predecessor operation - `Nat.psub`: a partial subtraction operation -/ namespace Nat /-- Partial predecessor operation. Returns `ppred n = some m` if `n = m + 1`, otherwise `none`. -/ def ppred : ℕ → Option ℕ | 0 => none | n + 1 => some n #align nat.ppred Nat.ppred @[simp] theorem ppred_zero : ppred 0 = none := rfl @[simp] theorem ppred_succ {n : ℕ} : ppred (succ n) = some n := rfl /-- Partial subtraction operation. Returns `psub m n = some k` if `m = n + k`, otherwise `none`. -/ def psub (m : ℕ) : ℕ → Option ℕ | 0 => some m | n + 1 => psub m n >>= ppred #align nat.psub Nat.psub @[simp] theorem psub_zero {m : ℕ} : psub m 0 = some m := rfl @[simp] theorem psub_succ {m n : ℕ} : psub m (succ n) = psub m n >>= ppred := rfl
Mathlib/Data/Nat/PSub.lean
54
54
theorem pred_eq_ppred (n : ℕ) : pred n = (ppred n).getD 0 := by
cases n <;> 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 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] #align list.rdrop_while_concat List.rdropWhile_concat @[simp] theorem rdropWhile_concat_pos (x : α) (h : p x) : rdropWhile p (l ++ [x]) = rdropWhile p l := by rw [rdropWhile_concat, if_pos h] #align list.rdrop_while_concat_pos List.rdropWhile_concat_pos @[simp] theorem rdropWhile_concat_neg (x : α) (h : ¬p x) : rdropWhile p (l ++ [x]) = l ++ [x] := by rw [rdropWhile_concat, if_neg h] #align list.rdrop_while_concat_neg List.rdropWhile_concat_neg
Mathlib/Data/List/DropRight.lean
121
122
theorem rdropWhile_singleton (x : α) : rdropWhile p [x] = if p x then [] else [x] := by
rw [← nil_append [x], rdropWhile_concat, rdropWhile_nil]
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Kenny Lau -/ import Mathlib.Data.List.Forall2 #align_import data.list.zip from "leanprover-community/mathlib"@"134625f523e737f650a6ea7f0c82a6177e45e622" /-! # zip & unzip This file provides results about `List.zipWith`, `List.zip` and `List.unzip` (definitions are in core Lean). `zipWith f l₁ l₂` applies `f : α → β → γ` pointwise to a list `l₁ : List α` and `l₂ : List β`. It applies, until one of the lists is exhausted. For example, `zipWith f [0, 1, 2] [6.28, 31] = [f 0 6.28, f 1 31]`. `zip` is `zipWith` applied to `Prod.mk`. For example, `zip [a₁, a₂] [b₁, b₂, b₃] = [(a₁, b₁), (a₂, b₂)]`. `unzip` undoes `zip`. For example, `unzip [(a₁, b₁), (a₂, b₂)] = ([a₁, a₂], [b₁, b₂])`. -/ -- Make sure we don't import algebra assert_not_exists Monoid universe u open Nat namespace List variable {α : Type u} {β γ δ ε : Type*} #align list.zip_with_cons_cons List.zipWith_cons_cons #align list.zip_cons_cons List.zip_cons_cons #align list.zip_with_nil_left List.zipWith_nil_left #align list.zip_with_nil_right List.zipWith_nil_right #align list.zip_with_eq_nil_iff List.zipWith_eq_nil_iff #align list.zip_nil_left List.zip_nil_left #align list.zip_nil_right List.zip_nil_right @[simp] theorem zip_swap : ∀ (l₁ : List α) (l₂ : List β), (zip l₁ l₂).map Prod.swap = zip l₂ l₁ | [], l₂ => zip_nil_right.symm | l₁, [] => by rw [zip_nil_right]; rfl | a :: l₁, b :: l₂ => by simp only [zip_cons_cons, map_cons, zip_swap l₁ l₂, Prod.swap_prod_mk] #align list.zip_swap List.zip_swap #align list.length_zip_with List.length_zipWith #align list.length_zip List.length_zip theorem forall_zipWith {f : α → β → γ} {p : γ → Prop} : ∀ {l₁ : List α} {l₂ : List β}, length l₁ = length l₂ → (Forall p (zipWith f l₁ l₂) ↔ Forall₂ (fun x y => p (f x y)) l₁ l₂) | [], [], _ => by simp | a :: l₁, b :: l₂, h => by simp only [length_cons, succ_inj'] at h simp [forall_zipWith h] #align list.all₂_zip_with List.forall_zipWith theorem lt_length_left_of_zipWith {f : α → β → γ} {i : ℕ} {l : List α} {l' : List β} (h : i < (zipWith f l l').length) : i < l.length := by rw [length_zipWith] at h; omega #align list.lt_length_left_of_zip_with List.lt_length_left_of_zipWith theorem lt_length_right_of_zipWith {f : α → β → γ} {i : ℕ} {l : List α} {l' : List β} (h : i < (zipWith f l l').length) : i < l'.length := by rw [length_zipWith] at h; omega #align list.lt_length_right_of_zip_with List.lt_length_right_of_zipWith theorem lt_length_left_of_zip {i : ℕ} {l : List α} {l' : List β} (h : i < (zip l l').length) : i < l.length := lt_length_left_of_zipWith h #align list.lt_length_left_of_zip List.lt_length_left_of_zip theorem lt_length_right_of_zip {i : ℕ} {l : List α} {l' : List β} (h : i < (zip l l').length) : i < l'.length := lt_length_right_of_zipWith h #align list.lt_length_right_of_zip List.lt_length_right_of_zip #align list.zip_append List.zip_append #align list.zip_map List.zip_map #align list.zip_map_left List.zip_map_left #align list.zip_map_right List.zip_map_right #align list.zip_with_map List.zipWith_map #align list.zip_with_map_left List.zipWith_map_left #align list.zip_with_map_right List.zipWith_map_right #align list.zip_map' List.zip_map' #align list.map_zip_with List.map_zipWith theorem mem_zip {a b} : ∀ {l₁ : List α} {l₂ : List β}, (a, b) ∈ zip l₁ l₂ → a ∈ l₁ ∧ b ∈ l₂ | _ :: l₁, _ :: l₂, h => by cases' h with _ _ _ h · simp · have := mem_zip h exact ⟨Mem.tail _ this.1, Mem.tail _ this.2⟩ #align list.mem_zip List.mem_zip #align list.map_fst_zip List.map_fst_zip #align list.map_snd_zip List.map_snd_zip #align list.unzip_nil List.unzip_nil #align list.unzip_cons List.unzip_cons theorem unzip_eq_map : ∀ l : List (α × β), unzip l = (l.map Prod.fst, l.map Prod.snd) | [] => rfl | (a, b) :: l => by simp only [unzip_cons, map_cons, unzip_eq_map l] #align list.unzip_eq_map List.unzip_eq_map
Mathlib/Data/List/Zip.lean
109
109
theorem unzip_left (l : List (α × β)) : (unzip l).1 = l.map Prod.fst := by
simp only [unzip_eq_map]
/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Algebra.GroupWithZero.Invertible import Mathlib.Algebra.Ring.Defs #align_import algebra.invertible from "leanprover-community/mathlib"@"722b3b152ddd5e0cf21c0a29787c76596cb6b422" /-! # Theorems about invertible elements in rings -/ universe u variable {α : Type u} /-- `-⅟a` is the inverse of `-a` -/ def invertibleNeg [Mul α] [One α] [HasDistribNeg α] (a : α) [Invertible a] : Invertible (-a) := ⟨-⅟ a, by simp, by simp⟩ #align invertible_neg invertibleNeg @[simp] theorem invOf_neg [Monoid α] [HasDistribNeg α] (a : α) [Invertible a] [Invertible (-a)] : ⅟ (-a) = -⅟ a := invOf_eq_right_inv (by simp) #align inv_of_neg invOf_neg @[simp] theorem one_sub_invOf_two [Ring α] [Invertible (2 : α)] : 1 - (⅟ 2 : α) = ⅟ 2 := (isUnit_of_invertible (2 : α)).mul_right_inj.1 <| by rw [mul_sub, mul_invOf_self, mul_one, ← one_add_one_eq_two, add_sub_cancel_right] #align one_sub_inv_of_two one_sub_invOf_two @[simp] theorem invOf_two_add_invOf_two [NonAssocSemiring α] [Invertible (2 : α)] : (⅟ 2 : α) + (⅟ 2 : α) = 1 := by rw [← two_mul, mul_invOf_self] #align inv_of_two_add_inv_of_two invOf_two_add_invOf_two theorem pos_of_invertible_cast [Semiring α] [Nontrivial α] (n : ℕ) [Invertible (n : α)] : 0 < n := Nat.zero_lt_of_ne_zero fun h => nonzero_of_invertible (n : α) (h ▸ Nat.cast_zero) theorem invOf_add_invOf [Semiring α] (a b : α) [Invertible a] [Invertible b] : ⅟a + ⅟b = ⅟a * (a + b) * ⅟b:= by rw [mul_add, invOf_mul_self, add_mul, one_mul, mul_assoc, mul_invOf_self, mul_one, add_comm] /-- A version of `inv_sub_inv'` for `invOf`. -/
Mathlib/Algebra/Ring/Invertible.lean
49
51
theorem invOf_sub_invOf [Ring α] (a b : α) [Invertible a] [Invertible b] : ⅟a - ⅟b = ⅟a * (b - a) * ⅟b := by
rw [mul_sub, invOf_mul_self, sub_mul, one_mul, mul_assoc, mul_invOf_self, mul_one]
/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.AlgebraicGeometry.Morphisms.Basic import Mathlib.Topology.Spectral.Hom import Mathlib.AlgebraicGeometry.Limits #align_import algebraic_geometry.morphisms.quasi_compact from "leanprover-community/mathlib"@"5dc6092d09e5e489106865241986f7f2ad28d4c8" /-! # Quasi-compact morphisms A morphism of schemes is quasi-compact if the preimages of quasi-compact open sets are quasi-compact. It suffices to check that preimages of affine open sets are compact (`quasiCompact_iff_forall_affine`). -/ noncomputable section open CategoryTheory CategoryTheory.Limits Opposite TopologicalSpace universe u open scoped AlgebraicGeometry namespace AlgebraicGeometry variable {X Y : Scheme.{u}} (f : X ⟶ Y) /-- A morphism is "quasi-compact" if the underlying map of topological spaces is, i.e. if the preimages of quasi-compact open sets are quasi-compact. -/ @[mk_iff] class QuasiCompact (f : X ⟶ Y) : Prop where /-- Preimage of compact open set under a quasi-compact morphism between schemes is compact. -/ isCompact_preimage : ∀ U : Set Y.carrier, IsOpen U → IsCompact U → IsCompact (f.1.base ⁻¹' U) #align algebraic_geometry.quasi_compact AlgebraicGeometry.QuasiCompact theorem quasiCompact_iff_spectral : QuasiCompact f ↔ IsSpectralMap f.1.base := ⟨fun ⟨h⟩ => ⟨by continuity, h⟩, fun h => ⟨h.2⟩⟩ #align algebraic_geometry.quasi_compact_iff_spectral AlgebraicGeometry.quasiCompact_iff_spectral /-- The `AffineTargetMorphismProperty` corresponding to `QuasiCompact`, asserting that the domain is a quasi-compact scheme. -/ def QuasiCompact.affineProperty : AffineTargetMorphismProperty := fun X _ _ _ => CompactSpace X.carrier #align algebraic_geometry.quasi_compact.affine_property AlgebraicGeometry.QuasiCompact.affineProperty instance (priority := 900) quasiCompactOfIsIso {X Y : Scheme} (f : X ⟶ Y) [IsIso f] : QuasiCompact f := by constructor intro U _ hU' convert hU'.image (inv f.1.base).continuous_toFun using 1 rw [Set.image_eq_preimage_of_inverse] · delta Function.LeftInverse exact IsIso.inv_hom_id_apply f.1.base · exact IsIso.hom_inv_id_apply f.1.base #align algebraic_geometry.quasi_compact_of_is_iso AlgebraicGeometry.quasiCompactOfIsIso instance quasiCompactComp {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) [QuasiCompact f] [QuasiCompact g] : QuasiCompact (f ≫ g) := by constructor intro U hU hU' rw [Scheme.comp_val_base, TopCat.coe_comp, Set.preimage_comp] apply QuasiCompact.isCompact_preimage · exact Continuous.isOpen_preimage (by -- Porting note: `continuity` failed -- see https://github.com/leanprover-community/mathlib4/issues/5030 exact Scheme.Hom.continuous g) _ hU apply QuasiCompact.isCompact_preimage <;> assumption #align algebraic_geometry.quasi_compact_comp AlgebraicGeometry.quasiCompactComp theorem isCompact_open_iff_eq_finset_affine_union {X : Scheme} (U : Set X.carrier) : IsCompact U ∧ IsOpen U ↔ ∃ s : Set X.affineOpens, s.Finite ∧ U = ⋃ (i : X.affineOpens) (_ : i ∈ s), i := by apply Opens.IsBasis.isCompact_open_iff_eq_finite_iUnion (fun (U : X.affineOpens) => (U : Opens X.carrier)) · rw [Subtype.range_coe]; exact isBasis_affine_open X · exact fun i => i.2.isCompact #align algebraic_geometry.is_compact_open_iff_eq_finset_affine_union AlgebraicGeometry.isCompact_open_iff_eq_finset_affine_union theorem isCompact_open_iff_eq_basicOpen_union {X : Scheme} [IsAffine X] (U : Set X.carrier) : IsCompact U ∧ IsOpen U ↔ ∃ s : Set (X.presheaf.obj (op ⊤)), s.Finite ∧ U = ⋃ (i : X.presheaf.obj (op ⊤)) (_ : i ∈ s), X.basicOpen i := (isBasis_basicOpen X).isCompact_open_iff_eq_finite_iUnion _ (fun _ => ((topIsAffineOpen _).basicOpenIsAffine _).isCompact) _ #align algebraic_geometry.is_compact_open_iff_eq_basic_open_union AlgebraicGeometry.isCompact_open_iff_eq_basicOpen_union
Mathlib/AlgebraicGeometry/Morphisms/QuasiCompact.lean
97
105
theorem quasiCompact_iff_forall_affine : QuasiCompact f ↔ ∀ U : Opens Y.carrier, IsAffineOpen U → IsCompact (f.1.base ⁻¹' (U : Set Y.carrier)) := by
rw [quasiCompact_iff] refine ⟨fun H U hU => H U U.isOpen hU.isCompact, ?_⟩ intro H U hU hU' obtain ⟨S, hS, rfl⟩ := (isCompact_open_iff_eq_finset_affine_union U).mp ⟨hU', hU⟩ simp only [Set.preimage_iUnion] exact Set.Finite.isCompact_biUnion hS (fun i _ => H i i.prop)
/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jan-David Salchow, Sébastien Gouëzel, Jean Lo, Yury Kudryashov, Frédéric Dupuis, Heather Macbeth -/ import Mathlib.Topology.Algebra.Ring.Basic import Mathlib.Topology.Algebra.MulAction import Mathlib.Topology.Algebra.UniformGroup import Mathlib.Topology.ContinuousFunction.Basic import Mathlib.Topology.UniformSpace.UniformEmbedding import Mathlib.Algebra.Algebra.Defs import Mathlib.LinearAlgebra.Projection import Mathlib.LinearAlgebra.Pi import Mathlib.LinearAlgebra.Finsupp #align_import topology.algebra.module.basic from "leanprover-community/mathlib"@"6285167a053ad0990fc88e56c48ccd9fae6550eb" /-! # Theory of topological modules and continuous linear maps. We use the class `ContinuousSMul` for topological (semi) modules and topological vector spaces. In this file we define continuous (semi-)linear maps, as semilinear maps between topological modules which are continuous. The set of continuous semilinear maps between the topological `R₁`-module `M` and `R₂`-module `M₂` with respect to the `RingHom` `σ` is denoted by `M →SL[σ] M₂`. Plain linear maps are denoted by `M →L[R] M₂` and star-linear maps by `M →L⋆[R] M₂`. The corresponding notation for equivalences is `M ≃SL[σ] M₂`, `M ≃L[R] M₂` and `M ≃L⋆[R] M₂`. -/ open LinearMap (ker range) open Topology Filter Pointwise universe u v w u' section variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M] [AddCommGroup M] [Module R M] theorem ContinuousSMul.of_nhds_zero [TopologicalRing R] [TopologicalAddGroup M] (hmul : Tendsto (fun p : R × M => p.1 • p.2) (𝓝 0 ×ˢ 𝓝 0) (𝓝 0)) (hmulleft : ∀ m : M, Tendsto (fun a : R => a • m) (𝓝 0) (𝓝 0)) (hmulright : ∀ a : R, Tendsto (fun m : M => a • m) (𝓝 0) (𝓝 0)) : ContinuousSMul R M where continuous_smul := by refine continuous_of_continuousAt_zero₂ (AddMonoidHom.smul : R →+ M →+ M) ?_ ?_ ?_ <;> simpa [ContinuousAt, nhds_prod_eq] #align has_continuous_smul.of_nhds_zero ContinuousSMul.of_nhds_zero end section variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M] [AddCommGroup M] [ContinuousAdd M] [Module R M] [ContinuousSMul R M] /-- If `M` is a topological module over `R` and `0` is a limit of invertible elements of `R`, then `⊤` is the only submodule of `M` with a nonempty interior. This is the case, e.g., if `R` is a nontrivially normed field. -/ theorem Submodule.eq_top_of_nonempty_interior' [NeBot (𝓝[{ x : R | IsUnit x }] 0)] (s : Submodule R M) (hs : (interior (s : Set M)).Nonempty) : s = ⊤ := by rcases hs with ⟨y, hy⟩ refine Submodule.eq_top_iff'.2 fun x => ?_ rw [mem_interior_iff_mem_nhds] at hy have : Tendsto (fun c : R => y + c • x) (𝓝[{ x : R | IsUnit x }] 0) (𝓝 (y + (0 : R) • x)) := tendsto_const_nhds.add ((tendsto_nhdsWithin_of_tendsto_nhds tendsto_id).smul tendsto_const_nhds) rw [zero_smul, add_zero] at this obtain ⟨_, hu : y + _ • _ ∈ s, u, rfl⟩ := nonempty_of_mem (inter_mem (Filter.mem_map.1 (this hy)) self_mem_nhdsWithin) have hy' : y ∈ ↑s := mem_of_mem_nhds hy rwa [s.add_mem_iff_right hy', ← Units.smul_def, s.smul_mem_iff' u] at hu #align submodule.eq_top_of_nonempty_interior' Submodule.eq_top_of_nonempty_interior' variable (R M) /-- Let `R` be a topological ring such that zero is not an isolated point (e.g., a nontrivially normed field, see `NormedField.punctured_nhds_neBot`). Let `M` be a nontrivial module over `R` such that `c • x = 0` implies `c = 0 ∨ x = 0`. Then `M` has no isolated points. We formulate this using `NeBot (𝓝[≠] x)`. This lemma is not an instance because Lean would need to find `[ContinuousSMul ?m_1 M]` with unknown `?m_1`. We register this as an instance for `R = ℝ` in `Real.punctured_nhds_module_neBot`. One can also use `haveI := Module.punctured_nhds_neBot R M` in a proof. -/
Mathlib/Topology/Algebra/Module/Basic.lean
86
94
theorem Module.punctured_nhds_neBot [Nontrivial M] [NeBot (𝓝[≠] (0 : R))] [NoZeroSMulDivisors R M] (x : M) : NeBot (𝓝[≠] x) := by
rcases exists_ne (0 : M) with ⟨y, hy⟩ suffices Tendsto (fun c : R => x + c • y) (𝓝[≠] 0) (𝓝[≠] x) from this.neBot refine Tendsto.inf ?_ (tendsto_principal_principal.2 <| ?_) · convert tendsto_const_nhds.add ((@tendsto_id R _).smul_const y) rw [zero_smul, add_zero] · intro c hc simpa [hy] using hc
/- 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.HomologicalComplex import Mathlib.AlgebraicTopology.SimplicialObject import Mathlib.CategoryTheory.Abelian.Basic #align_import algebraic_topology.Moore_complex from "leanprover-community/mathlib"@"0bd2ea37bcba5769e14866170f251c9bc64e35d7" /-! ## Moore complex We construct the normalized Moore complex, as a functor `SimplicialObject C ⥤ ChainComplex C ℕ`, for any abelian category `C`. The `n`-th object is intersection of the kernels of `X.δ i : X.obj n ⟶ X.obj (n-1)`, for `i = 1, ..., n`. The differentials are induced from `X.δ 0`, which maps each of these intersections of kernels to the next. This functor is one direction of the Dold-Kan equivalence, which we're still working towards. ### References * https://stacks.math.columbia.edu/tag/0194 * https://ncatlab.org/nlab/show/Moore+complex -/ universe v u noncomputable section open CategoryTheory CategoryTheory.Limits open Opposite namespace AlgebraicTopology variable {C : Type*} [Category C] [Abelian C] attribute [local instance] Abelian.hasPullbacks /-! The definitions in this namespace are all auxiliary definitions for `NormalizedMooreComplex` and should usually only be accessed via that. -/ namespace NormalizedMooreComplex open CategoryTheory.Subobject variable (X : SimplicialObject C) /-- The normalized Moore complex in degree `n`, as a subobject of `X n`. -/ def objX : ∀ n : ℕ, Subobject (X.obj (op (SimplexCategory.mk n))) | 0 => ⊤ | n + 1 => Finset.univ.inf fun k : Fin (n + 1) => kernelSubobject (X.δ k.succ) set_option linter.uppercaseLean3 false in #align algebraic_topology.normalized_Moore_complex.obj_X AlgebraicTopology.NormalizedMooreComplex.objX theorem objX_zero : objX X 0 = ⊤ := rfl theorem objX_add_one (n) : objX X (n + 1) = Finset.univ.inf fun k : Fin (n + 1) => kernelSubobject (X.δ k.succ) := rfl attribute [eqns objX_zero objX_add_one] objX attribute [simp] objX /-- The differentials in the normalized Moore complex. -/ @[simp] def objD : ∀ n : ℕ, (objX X (n + 1) : C) ⟶ (objX X n : C) | 0 => Subobject.arrow _ ≫ X.δ (0 : Fin 2) ≫ inv (⊤ : Subobject _).arrow | n + 1 => by -- The differential is `Subobject.arrow _ ≫ X.δ (0 : Fin (n+3))`, -- factored through the intersection of the kernels. refine factorThru _ (arrow _ ≫ X.δ (0 : Fin (n + 3))) ?_ -- We now need to show that it factors! -- A morphism factors through an intersection of subobjects if it factors through each. refine (finset_inf_factors _).mpr fun i _ => ?_ -- A morphism `f` factors through the kernel of `g` exactly if `f ≫ g = 0`. apply kernelSubobject_factors dsimp [objX] -- Use a simplicial identity erw [Category.assoc, ← X.δ_comp_δ (Fin.zero_le i.succ)] -- We can rewrite the arrow out of the intersection of all the kernels as a composition -- of a morphism we don't care about with the arrow out of the kernel of `X.δ i.succ.succ`. rw [← factorThru_arrow _ _ (finset_inf_arrow_factors Finset.univ _ i.succ (by simp)), Category.assoc, kernelSubobject_arrow_comp_assoc, zero_comp, comp_zero] set_option linter.uppercaseLean3 false in #align algebraic_topology.normalized_Moore_complex.obj_d AlgebraicTopology.NormalizedMooreComplex.objD
Mathlib/AlgebraicTopology/MooreComplex.lean
100
111
theorem d_squared (n : ℕ) : objD X (n + 1) ≫ objD X n = 0 := by
-- It's a pity we need to do a case split here; -- after the first erw the proofs are almost identical rcases n with _ | n <;> dsimp [objD] · erw [Subobject.factorThru_arrow_assoc, Category.assoc, ← X.δ_comp_δ_assoc (Fin.zero_le (0 : Fin 2)), ← factorThru_arrow _ _ (finset_inf_arrow_factors Finset.univ _ (0 : Fin 2) (by simp)), Category.assoc, kernelSubobject_arrow_comp_assoc, zero_comp, comp_zero] · erw [factorThru_right, factorThru_eq_zero, factorThru_arrow_assoc, Category.assoc, ← X.δ_comp_δ (Fin.zero_le (0 : Fin (n + 3))), ← factorThru_arrow _ _ (finset_inf_arrow_factors Finset.univ _ (0 : Fin (n + 3)) (by simp)), Category.assoc, kernelSubobject_arrow_comp_assoc, zero_comp, comp_zero]
/- Copyright (c) 2019 Alexander Bentkamp. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Alexander Bentkamp, Yury Kudriashov -/ import Mathlib.Analysis.Convex.Combination import Mathlib.Analysis.Convex.Function import Mathlib.Tactic.FieldSimp #align_import analysis.convex.jensen from "leanprover-community/mathlib"@"bfad3f455b388fbcc14c49d0cac884f774f14d20" /-! # Jensen's inequality and maximum principle for convex functions In this file, we prove the finite Jensen inequality and the finite maximum principle for convex functions. The integral versions are to be found in `Analysis.Convex.Integral`. ## Main declarations Jensen's inequalities: * `ConvexOn.map_centerMass_le`, `ConvexOn.map_sum_le`: Convex Jensen's inequality. The image of a convex combination of points under a convex function is less than the convex combination of the images. * `ConcaveOn.le_map_centerMass`, `ConcaveOn.le_map_sum`: Concave Jensen's inequality. * `StrictConvexOn.map_sum_lt`: Convex strict Jensen inequality. * `StrictConcaveOn.lt_map_sum`: Concave strict Jensen inequality. As corollaries, we get: * `StrictConvexOn.map_sum_eq_iff`: Equality case of the convex Jensen inequality. * `StrictConcaveOn.map_sum_eq_iff`: Equality case of the concave Jensen inequality. * `ConvexOn.exists_ge_of_mem_convexHull`: Maximum principle for convex functions. * `ConcaveOn.exists_le_of_mem_convexHull`: Minimum principle for concave functions. -/ open Finset LinearMap Set open scoped Classical open Convex Pointwise variable {𝕜 E F β ι : Type*} /-! ### Jensen's inequality -/ section Jensen variable [LinearOrderedField 𝕜] [AddCommGroup E] [OrderedAddCommGroup β] [Module 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β} {t : Finset ι} {w : ι → 𝕜} {p : ι → E} {v : 𝕜} {q : E} /-- Convex **Jensen's inequality**, `Finset.centerMass` version. -/ theorem ConvexOn.map_centerMass_le (hf : ConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i) (h₁ : 0 < ∑ i ∈ t, w i) (hmem : ∀ i ∈ t, p i ∈ s) : f (t.centerMass w p) ≤ t.centerMass w (f ∘ p) := by have hmem' : ∀ i ∈ t, (p i, (f ∘ p) i) ∈ { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } := fun i hi => ⟨hmem i hi, le_rfl⟩ convert (hf.convex_epigraph.centerMass_mem h₀ h₁ hmem').2 <;> simp only [centerMass, Function.comp, Prod.smul_fst, Prod.fst_sum, Prod.smul_snd, Prod.snd_sum] #align convex_on.map_center_mass_le ConvexOn.map_centerMass_le /-- Concave **Jensen's inequality**, `Finset.centerMass` version. -/ theorem ConcaveOn.le_map_centerMass (hf : ConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i) (h₁ : 0 < ∑ i ∈ t, w i) (hmem : ∀ i ∈ t, p i ∈ s) : t.centerMass w (f ∘ p) ≤ f (t.centerMass w p) := ConvexOn.map_centerMass_le (β := βᵒᵈ) hf h₀ h₁ hmem #align concave_on.le_map_center_mass ConcaveOn.le_map_centerMass /-- Convex **Jensen's inequality**, `Finset.sum` version. -/
Mathlib/Analysis/Convex/Jensen.lean
69
72
theorem ConvexOn.map_sum_le (hf : ConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i) (h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) : f (∑ i ∈ t, w i • p i) ≤ ∑ i ∈ t, w i • f (p i) := by
simpa only [centerMass, h₁, inv_one, one_smul] using hf.map_centerMass_le h₀ (h₁.symm ▸ zero_lt_one) hmem
/- Copyright (c) 2022 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Data.Set.Pointwise.SMul import Mathlib.Topology.MetricSpace.Isometry import Mathlib.Topology.MetricSpace.Lipschitz #align_import topology.metric_space.isometric_smul from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156" /-! # Group actions by isometries In this file we define two typeclasses: - `IsometricSMul M X` says that `M` multiplicatively acts on a (pseudo extended) metric space `X` by isometries; - `IsometricVAdd` is an additive version of `IsometricSMul`. We also prove basic facts about isometric actions and define bundled isometries `IsometryEquiv.constSMul`, `IsometryEquiv.mulLeft`, `IsometryEquiv.mulRight`, `IsometryEquiv.divLeft`, `IsometryEquiv.divRight`, and `IsometryEquiv.inv`, as well as their additive versions. If `G` is a group, then `IsometricSMul G G` means that `G` has a left-invariant metric while `IsometricSMul Gᵐᵒᵖ G` means that `G` has a right-invariant metric. For a commutative group, these two notions are equivalent. A group with a right-invariant metric can be also represented as a `NormedGroup`. -/ open Set open ENNReal Pointwise universe u v w variable (M : Type u) (G : Type v) (X : Type w) /-- An additive action is isometric if each map `x ↦ c +ᵥ x` is an isometry. -/ class IsometricVAdd [PseudoEMetricSpace X] [VAdd M X] : Prop where protected isometry_vadd : ∀ c : M, Isometry ((c +ᵥ ·) : X → X) #align has_isometric_vadd IsometricVAdd /-- A multiplicative action is isometric if each map `x ↦ c • x` is an isometry. -/ @[to_additive] class IsometricSMul [PseudoEMetricSpace X] [SMul M X] : Prop where protected isometry_smul : ∀ c : M, Isometry ((c • ·) : X → X) #align has_isometric_smul IsometricSMul -- Porting note: Lean 4 doesn't support `[]` in classes, so make a lemma instead of `export`ing @[to_additive] theorem isometry_smul {M : Type u} (X : Type w) [PseudoEMetricSpace X] [SMul M X] [IsometricSMul M X] (c : M) : Isometry (c • · : X → X) := IsometricSMul.isometry_smul c @[to_additive] instance (priority := 100) IsometricSMul.to_continuousConstSMul [PseudoEMetricSpace X] [SMul M X] [IsometricSMul M X] : ContinuousConstSMul M X := ⟨fun c => (isometry_smul X c).continuous⟩ #align has_isometric_smul.to_has_continuous_const_smul IsometricSMul.to_continuousConstSMul #align has_isometric_vadd.to_has_continuous_const_vadd IsometricVAdd.to_continuousConstVAdd @[to_additive] instance (priority := 100) IsometricSMul.opposite_of_comm [PseudoEMetricSpace X] [SMul M X] [SMul Mᵐᵒᵖ X] [IsCentralScalar M X] [IsometricSMul M X] : IsometricSMul Mᵐᵒᵖ X := ⟨fun c x y => by simpa only [← op_smul_eq_smul] using isometry_smul X c.unop x y⟩ #align has_isometric_smul.opposite_of_comm IsometricSMul.opposite_of_comm #align has_isometric_vadd.opposite_of_comm IsometricVAdd.opposite_of_comm variable {M G X} section EMetric variable [PseudoEMetricSpace X] [Group G] [MulAction G X] [IsometricSMul G X] @[to_additive (attr := simp)] theorem edist_smul_left [SMul M X] [IsometricSMul M X] (c : M) (x y : X) : edist (c • x) (c • y) = edist x y := isometry_smul X c x y #align edist_smul_left edist_smul_left #align edist_vadd_left edist_vadd_left @[to_additive (attr := simp)] theorem ediam_smul [SMul M X] [IsometricSMul M X] (c : M) (s : Set X) : EMetric.diam (c • s) = EMetric.diam s := (isometry_smul _ _).ediam_image s #align ediam_smul ediam_smul #align ediam_vadd ediam_vadd @[to_additive] theorem isometry_mul_left [Mul M] [PseudoEMetricSpace M] [IsometricSMul M M] (a : M) : Isometry (a * ·) := isometry_smul M a #align isometry_mul_left isometry_mul_left #align isometry_add_left isometry_add_left @[to_additive (attr := simp)] theorem edist_mul_left [Mul M] [PseudoEMetricSpace M] [IsometricSMul M M] (a b c : M) : edist (a * b) (a * c) = edist b c := isometry_mul_left a b c #align edist_mul_left edist_mul_left #align edist_add_left edist_add_left @[to_additive] theorem isometry_mul_right [Mul M] [PseudoEMetricSpace M] [IsometricSMul Mᵐᵒᵖ M] (a : M) : Isometry fun x => x * a := isometry_smul M (MulOpposite.op a) #align isometry_mul_right isometry_mul_right #align isometry_add_right isometry_add_right @[to_additive (attr := simp)] theorem edist_mul_right [Mul M] [PseudoEMetricSpace M] [IsometricSMul Mᵐᵒᵖ M] (a b c : M) : edist (a * c) (b * c) = edist a b := isometry_mul_right c a b #align edist_mul_right edist_mul_right #align edist_add_right edist_add_right @[to_additive (attr := simp)] theorem edist_div_right [DivInvMonoid M] [PseudoEMetricSpace M] [IsometricSMul Mᵐᵒᵖ M] (a b c : M) : edist (a / c) (b / c) = edist a b := by simp only [div_eq_mul_inv, edist_mul_right] #align edist_div_right edist_div_right #align edist_sub_right edist_sub_right @[to_additive (attr := simp)]
Mathlib/Topology/MetricSpace/IsometricSMul.lean
128
131
theorem edist_inv_inv [PseudoEMetricSpace G] [IsometricSMul G G] [IsometricSMul Gᵐᵒᵖ G] (a b : G) : edist a⁻¹ b⁻¹ = edist a b := by
rw [← edist_mul_left a, ← edist_mul_right _ _ b, mul_right_inv, one_mul, inv_mul_cancel_right, edist_comm]
/- 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.Multiset.Nodup #align_import data.multiset.dedup from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853" /-! # Erasing duplicates in a multiset. -/ namespace Multiset open List variable {α β : Type*} [DecidableEq α] /-! ### dedup -/ /-- `dedup s` removes duplicates from `s`, yielding a `nodup` multiset. -/ def dedup (s : Multiset α) : Multiset α := Quot.liftOn s (fun l => (l.dedup : Multiset α)) fun _ _ p => Quot.sound p.dedup #align multiset.dedup Multiset.dedup @[simp] theorem coe_dedup (l : List α) : @dedup α _ l = l.dedup := rfl #align multiset.coe_dedup Multiset.coe_dedup @[simp] theorem dedup_zero : @dedup α _ 0 = 0 := rfl #align multiset.dedup_zero Multiset.dedup_zero @[simp] theorem mem_dedup {a : α} {s : Multiset α} : a ∈ dedup s ↔ a ∈ s := Quot.induction_on s fun _ => List.mem_dedup #align multiset.mem_dedup Multiset.mem_dedup @[simp] theorem dedup_cons_of_mem {a : α} {s : Multiset α} : a ∈ s → dedup (a ::ₘ s) = dedup s := Quot.induction_on s fun _ m => @congr_arg _ _ _ _ ofList <| List.dedup_cons_of_mem m #align multiset.dedup_cons_of_mem Multiset.dedup_cons_of_mem @[simp] theorem dedup_cons_of_not_mem {a : α} {s : Multiset α} : a ∉ s → dedup (a ::ₘ s) = a ::ₘ dedup s := Quot.induction_on s fun _ m => congr_arg ofList <| List.dedup_cons_of_not_mem m #align multiset.dedup_cons_of_not_mem Multiset.dedup_cons_of_not_mem theorem dedup_le (s : Multiset α) : dedup s ≤ s := Quot.induction_on s fun _ => (dedup_sublist _).subperm #align multiset.dedup_le Multiset.dedup_le theorem dedup_subset (s : Multiset α) : dedup s ⊆ s := subset_of_le <| dedup_le _ #align multiset.dedup_subset Multiset.dedup_subset theorem subset_dedup (s : Multiset α) : s ⊆ dedup s := fun _ => mem_dedup.2 #align multiset.subset_dedup Multiset.subset_dedup @[simp] theorem dedup_subset' {s t : Multiset α} : dedup s ⊆ t ↔ s ⊆ t := ⟨Subset.trans (subset_dedup _), Subset.trans (dedup_subset _)⟩ #align multiset.dedup_subset' Multiset.dedup_subset' @[simp] theorem subset_dedup' {s t : Multiset α} : s ⊆ dedup t ↔ s ⊆ t := ⟨fun h => Subset.trans h (dedup_subset _), fun h => Subset.trans h (subset_dedup _)⟩ #align multiset.subset_dedup' Multiset.subset_dedup' @[simp] theorem nodup_dedup (s : Multiset α) : Nodup (dedup s) := Quot.induction_on s List.nodup_dedup #align multiset.nodup_dedup Multiset.nodup_dedup theorem dedup_eq_self {s : Multiset α} : dedup s = s ↔ Nodup s := ⟨fun e => e ▸ nodup_dedup s, Quot.induction_on s fun _ h => congr_arg ofList h.dedup⟩ #align multiset.dedup_eq_self Multiset.dedup_eq_self alias ⟨_, Nodup.dedup⟩ := dedup_eq_self #align multiset.nodup.dedup Multiset.Nodup.dedup theorem count_dedup (m : Multiset α) (a : α) : m.dedup.count a = if a ∈ m then 1 else 0 := Quot.induction_on m fun _ => by simp only [quot_mk_to_coe'', coe_dedup, mem_coe, List.mem_dedup, coe_nodup, coe_count] apply List.count_dedup _ _ #align multiset.count_dedup Multiset.count_dedup @[simp] theorem dedup_idem {m : Multiset α} : m.dedup.dedup = m.dedup := Quot.induction_on m fun _ => @congr_arg _ _ _ _ ofList List.dedup_idem #align multiset.dedup_idempotent Multiset.dedup_idem theorem dedup_eq_zero {s : Multiset α} : dedup s = 0 ↔ s = 0 := ⟨fun h => eq_zero_of_subset_zero <| h ▸ subset_dedup _, fun h => h.symm ▸ dedup_zero⟩ #align multiset.dedup_eq_zero Multiset.dedup_eq_zero @[simp] theorem dedup_singleton {a : α} : dedup ({a} : Multiset α) = {a} := (nodup_singleton _).dedup #align multiset.dedup_singleton Multiset.dedup_singleton theorem le_dedup {s t : Multiset α} : s ≤ dedup t ↔ s ≤ t ∧ Nodup s := ⟨fun h => ⟨le_trans h (dedup_le _), nodup_of_le h (nodup_dedup _)⟩, fun ⟨l, d⟩ => (le_iff_subset d).2 <| Subset.trans (subset_of_le l) (subset_dedup _)⟩ #align multiset.le_dedup Multiset.le_dedup theorem le_dedup_self {s : Multiset α} : s ≤ dedup s ↔ Nodup s := by rw [le_dedup, and_iff_right le_rfl] #align multiset.le_dedup_self Multiset.le_dedup_self
Mathlib/Data/Multiset/Dedup.lean
116
117
theorem dedup_ext {s t : Multiset α} : dedup s = dedup t ↔ ∀ a, a ∈ s ↔ a ∈ t := by
simp [Nodup.ext]
/- Copyright (c) 2020 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin -/ import Mathlib.Algebra.MvPolynomial.Expand import Mathlib.FieldTheory.Finite.Basic import Mathlib.RingTheory.MvPolynomial.Basic #align_import field_theory.finite.polynomial from "leanprover-community/mathlib"@"5aa3c1de9f3c642eac76e11071c852766f220fd0" /-! ## Polynomials over finite fields -/ namespace MvPolynomial variable {σ : Type*} /-- A polynomial over the integers is divisible by `n : ℕ` if and only if it is zero over `ZMod n`. -/ theorem C_dvd_iff_zmod (n : ℕ) (φ : MvPolynomial σ ℤ) : C (n : ℤ) ∣ φ ↔ map (Int.castRingHom (ZMod n)) φ = 0 := C_dvd_iff_map_hom_eq_zero _ _ (CharP.intCast_eq_zero_iff (ZMod n) n) _ set_option linter.uppercaseLean3 false in #align mv_polynomial.C_dvd_iff_zmod MvPolynomial.C_dvd_iff_zmod section frobenius variable {p : ℕ} [Fact p.Prime] theorem frobenius_zmod (f : MvPolynomial σ (ZMod p)) : frobenius _ p f = expand p f := by apply induction_on f · intro a; rw [expand_C, frobenius_def, ← C_pow, ZMod.pow_card] · simp only [AlgHom.map_add, RingHom.map_add]; intro _ _ hf hg; rw [hf, hg] · simp only [expand_X, RingHom.map_mul, AlgHom.map_mul] intro _ _ hf; rw [hf, frobenius_def] #align mv_polynomial.frobenius_zmod MvPolynomial.frobenius_zmod theorem expand_zmod (f : MvPolynomial σ (ZMod p)) : expand p f = f ^ p := (frobenius_zmod _).symm #align mv_polynomial.expand_zmod MvPolynomial.expand_zmod end frobenius end MvPolynomial namespace MvPolynomial noncomputable section open scoped Classical open Set LinearMap Submodule variable {K : Type*} {σ : Type*} section Indicator variable [Fintype K] [Fintype σ] /-- Over a field, this is the indicator function as an `MvPolynomial`. -/ def indicator [CommRing K] (a : σ → K) : MvPolynomial σ K := ∏ n, (1 - (X n - C (a n)) ^ (Fintype.card K - 1)) #align mv_polynomial.indicator MvPolynomial.indicator section CommRing variable [CommRing K] theorem eval_indicator_apply_eq_one (a : σ → K) : eval a (indicator a) = 1 := by nontriviality have : 0 < Fintype.card K - 1 := tsub_pos_of_lt Fintype.one_lt_card simp only [indicator, map_prod, map_sub, map_one, map_pow, eval_X, eval_C, sub_self, zero_pow this.ne', sub_zero, Finset.prod_const_one] #align mv_polynomial.eval_indicator_apply_eq_one MvPolynomial.eval_indicator_apply_eq_one
Mathlib/FieldTheory/Finite/Polynomial.lean
79
88
theorem degrees_indicator (c : σ → K) : degrees (indicator c) ≤ ∑ s : σ, (Fintype.card K - 1) • {s} := by
rw [indicator] refine le_trans (degrees_prod _ _) (Finset.sum_le_sum fun s _ => ?_) refine le_trans (degrees_sub _ _) ?_ rw [degrees_one, ← bot_eq_zero, bot_sup_eq] refine le_trans (degrees_pow _ _) (nsmul_le_nsmul_right ?_ _) refine le_trans (degrees_sub _ _) ?_ rw [degrees_C, ← bot_eq_zero, sup_bot_eq] exact degrees_X' _
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl -/ import Mathlib.Topology.Order.MonotoneContinuity import Mathlib.Topology.Algebra.Order.LiminfLimsup import Mathlib.Topology.Instances.NNReal import Mathlib.Topology.EMetricSpace.Lipschitz import Mathlib.Topology.Metrizable.Basic import Mathlib.Topology.Order.T5 #align_import topology.instances.ennreal from "leanprover-community/mathlib"@"ec4b2eeb50364487f80421c0b4c41328a611f30d" /-! # Topology on extended non-negative reals -/ noncomputable section open Set Filter Metric Function open scoped Classical Topology ENNReal NNReal Filter variable {α : Type*} {β : Type*} {γ : Type*} namespace ENNReal variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0} {x y z : ℝ≥0∞} {ε ε₁ ε₂ : ℝ≥0∞} {s : Set ℝ≥0∞} section TopologicalSpace open TopologicalSpace /-- Topology on `ℝ≥0∞`. Note: this is different from the `EMetricSpace` topology. The `EMetricSpace` topology has `IsOpen {∞}`, while this topology doesn't have singleton elements. -/ instance : TopologicalSpace ℝ≥0∞ := Preorder.topology ℝ≥0∞ instance : OrderTopology ℝ≥0∞ := ⟨rfl⟩ -- short-circuit type class inference instance : T2Space ℝ≥0∞ := inferInstance instance : T5Space ℝ≥0∞ := inferInstance instance : T4Space ℝ≥0∞ := inferInstance instance : SecondCountableTopology ℝ≥0∞ := orderIsoUnitIntervalBirational.toHomeomorph.embedding.secondCountableTopology instance : MetrizableSpace ENNReal := orderIsoUnitIntervalBirational.toHomeomorph.embedding.metrizableSpace theorem embedding_coe : Embedding ((↑) : ℝ≥0 → ℝ≥0∞) := coe_strictMono.embedding_of_ordConnected <| by rw [range_coe']; exact ordConnected_Iio #align ennreal.embedding_coe ENNReal.embedding_coe theorem isOpen_ne_top : IsOpen { a : ℝ≥0∞ | a ≠ ∞ } := isOpen_ne #align ennreal.is_open_ne_top ENNReal.isOpen_ne_top
Mathlib/Topology/Instances/ENNReal.lean
60
62
theorem isOpen_Ico_zero : IsOpen (Ico 0 b) := by
rw [ENNReal.Ico_eq_Iio] exact isOpen_Iio
/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.LinearAlgebra.Matrix.BilinearForm import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly import Mathlib.LinearAlgebra.Determinant import Mathlib.LinearAlgebra.FiniteDimensional import Mathlib.LinearAlgebra.Vandermonde import Mathlib.LinearAlgebra.Trace import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure import Mathlib.FieldTheory.PrimitiveElement import Mathlib.FieldTheory.Galois import Mathlib.RingTheory.PowerBasis import Mathlib.FieldTheory.Minpoly.MinpolyDiv #align_import ring_theory.trace from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1" /-! # Trace for (finite) ring extensions. Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`, the trace of the linear map given by multiplying by `s` gives information about the roots of the minimal polynomial of `s` over `R`. ## Main definitions * `Algebra.trace R S x`: the trace of an element `s` of an `R`-algebra `S` * `Algebra.traceForm R S`: bilinear form sending `x`, `y` to the trace of `x * y` * `Algebra.traceMatrix R b`: the matrix whose `(i j)`-th element is the trace of `b i * b j`. * `Algebra.embeddingsMatrix A C b : Matrix κ (B →ₐ[A] C) C` is the matrix whose `(i, σ)` coefficient is `σ (b i)`. * `Algebra.embeddingsMatrixReindex A C b e : Matrix κ κ C` is the matrix whose `(i, j)` coefficient is `σⱼ (b i)`, where `σⱼ : B →ₐ[A] C` is the embedding corresponding to `j : κ` given by a bijection `e : κ ≃ (B →ₐ[A] C)`. ## Main results * `trace_algebraMap_of_basis`, `trace_algebraMap`: if `x : K`, then `Tr_{L/K} x = [L : K] x` * `trace_trace_of_basis`, `trace_trace`: `Tr_{L/K} (Tr_{F/L} x) = Tr_{F/K} x` * `trace_eq_sum_roots`: the trace of `x : K(x)` is the sum of all conjugate roots of `x` * `trace_eq_sum_embeddings`: the trace of `x : K(x)` is the sum of all embeddings of `x` into an algebraically closed field * `traceForm_nondegenerate`: the trace form over a separable extension is a nondegenerate bilinear form * `traceForm_dualBasis_powerBasis_eq`: The dual basis of a powerbasis `{1, x, x²...}` under the trace form is `aᵢ / f'(x)`, with `f` being the minpoly of `x` and `f / (X - x) = ∑ aᵢxⁱ`. ## Implementation notes Typically, the trace is defined specifically for finite field extensions. The 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 trace for left multiplication (`Algebra.leftMulMatrix`, i.e. `LinearMap.mulLeft`). For now, the definitions assume `S` is commutative, so the choice doesn't matter anyway. ## References * https://en.wikipedia.org/wiki/Field_trace -/ universe u v w z variable {R S T : Type*} [CommRing R] [CommRing S] [CommRing T] variable [Algebra R S] [Algebra R T] variable {K L : Type*} [Field K] [Field L] [Algebra K L] variable {ι κ : Type w} [Fintype ι] open FiniteDimensional open LinearMap (BilinForm) open LinearMap open Matrix open scoped Matrix namespace Algebra variable (b : Basis ι R S) variable (R S) /-- The trace of an element `s` of an `R`-algebra is the trace of `(s * ·)`, as an `R`-linear map. -/ noncomputable def trace : S →ₗ[R] R := (LinearMap.trace R S).comp (lmul R S).toLinearMap #align algebra.trace Algebra.trace variable {S} -- Not a `simp` lemma since there are more interesting ways to rewrite `trace R S x`, -- for example `trace_trace` theorem trace_apply (x) : trace R S x = LinearMap.trace R S (lmul R S x) := rfl #align algebra.trace_apply Algebra.trace_apply theorem trace_eq_zero_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) : trace R S = 0 := by ext s; simp [trace_apply, LinearMap.trace, h] #align algebra.trace_eq_zero_of_not_exists_basis Algebra.trace_eq_zero_of_not_exists_basis variable {R} -- Can't be a `simp` lemma because it depends on a choice of basis theorem trace_eq_matrix_trace [DecidableEq ι] (b : Basis ι R S) (s : S) : trace R S s = Matrix.trace (Algebra.leftMulMatrix b s) := by rw [trace_apply, LinearMap.trace_eq_matrix_trace _ b, ← toMatrix_lmul_eq]; rfl #align algebra.trace_eq_matrix_trace Algebra.trace_eq_matrix_trace /-- If `x` is in the base field `K`, then the trace is `[L : K] * x`. -/ theorem trace_algebraMap_of_basis (x : R) : trace R S (algebraMap R S x) = Fintype.card ι • x := by haveI := Classical.decEq ι rw [trace_apply, LinearMap.trace_eq_matrix_trace R b, Matrix.trace] convert Finset.sum_const x simp [-coe_lmul_eq_mul] #align algebra.trace_algebra_map_of_basis Algebra.trace_algebraMap_of_basis /-- If `x` is in the base field `K`, then the trace is `[L : K] * x`. (If `L` is not finite-dimensional over `K`, then `trace` and `finrank` return `0`.) -/ @[simp]
Mathlib/RingTheory/Trace.lean
128
131
theorem trace_algebraMap (x : K) : trace K L (algebraMap K L x) = finrank K L • x := by
by_cases H : ∃ s : Finset L, Nonempty (Basis s K L) · rw [trace_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some] · simp [trace_eq_zero_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis_finset H]
/- Copyright (c) 2024 Riccardo Brasca. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Riccardo Brasca -/ import Mathlib.NumberTheory.NumberField.ClassNumber import Mathlib.NumberTheory.Cyclotomic.Rat import Mathlib.NumberTheory.Cyclotomic.Embeddings /-! # Cyclotomic fields whose ring of integers is a PID. We prove that `ℤ [ζₚ]` is a PID for specific values of `p`. The result holds for `p ≤ 19`, but the proof is more and more involved. ## Main results * `three_pid`: If `IsCyclotomicExtension {3} ℚ K` then `𝓞 K` is a principal ideal domain. * `five_pid`: If `IsCyclotomicExtension {5} ℚ K` then `𝓞 K` is a principal ideal domain. -/ universe u namespace IsCyclotomicExtension.Rat open NumberField Polynomial InfinitePlace Nat Real cyclotomic variable (K : Type u) [Field K] [NumberField K] /-- If `IsCyclotomicExtension {3} ℚ K` then `𝓞 K` is a principal ideal domain. -/
Mathlib/NumberTheory/Cyclotomic/PID.lean
30
41
theorem three_pid [IsCyclotomicExtension {3} ℚ K] : IsPrincipalIdealRing (𝓞 K) := by
apply RingOfIntegers.isPrincipalIdealRing_of_abs_discr_lt rw [absdiscr_prime 3 K, IsCyclotomicExtension.finrank (n := 3) K (irreducible_rat (by norm_num)), nrComplexPlaces_eq_totient_div_two 3, totient_prime PNat.prime_three] simp only [Int.reduceNeg, PNat.val_ofNat, succ_sub_succ_eq_sub, tsub_zero, zero_lt_two, Nat.div_self, pow_one, cast_ofNat, neg_mul, one_mul, abs_neg, Int.cast_abs, Int.cast_ofNat, factorial_two, gt_iff_lt, abs_of_pos (show (0 : ℝ) < 3 by norm_num)] suffices (2 * (3 / 4) * (2 ^ 2 / 2)) ^ 2 < (2 * (π / 4) * (2 ^ 2 / 2)) ^ 2 from lt_trans (by norm_num) this gcongr exact pi_gt_three
/- Copyright (c) 2017 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura -/ import Mathlib.Mathport.Rename #align_import init.meta.well_founded_tactics from "leanprover-community/lean"@"855e5b74e3a52a40552e8f067169d747d48743fd" -- Porting note: meta code used to implement well-founded recursion is not ported theorem Nat.lt_add_of_zero_lt_left (a b : Nat) (h : 0 < b) : a < a + b := show a + 0 < a + b by apply Nat.add_lt_add_left assumption #align nat.lt_add_of_zero_lt_left Nat.lt_add_of_zero_lt_left
Mathlib/Init/Meta/WellFoundedTactics.lean
18
18
theorem Nat.zero_lt_one_add (a : Nat) : 0 < 1 + a := by
simp [Nat.one_add]
/- 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
Mathlib/RingTheory/Norm.lean
72
73
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
/- Copyright (c) 2021 Aaron Anderson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Gabin Kolly -/ import Mathlib.Order.Closure import Mathlib.ModelTheory.Semantics import Mathlib.ModelTheory.Encoding #align_import model_theory.substructures from "leanprover-community/mathlib"@"0602c59878ff3d5f71dea69c2d32ccf2e93e5398" /-! # First-Order Substructures This file defines substructures of first-order structures in a similar manner to the various substructures appearing in the algebra library. ## Main Definitions * A `FirstOrder.Language.Substructure` is defined so that `L.Substructure M` is the type of all substructures of the `L`-structure `M`. * `FirstOrder.Language.Substructure.closure` is defined so that if `s : Set M`, `closure L s` is the least substructure of `M` containing `s`. * `FirstOrder.Language.Substructure.comap` is defined so that `s.comap f` is the preimage of the substructure `s` under the homomorphism `f`, as a substructure. * `FirstOrder.Language.Substructure.map` is defined so that `s.map f` is the image of the substructure `s` under the homomorphism `f`, as a substructure. * `FirstOrder.Language.Hom.range` is defined so that `f.range` is the range of the homomorphism `f`, as a substructure. * `FirstOrder.Language.Hom.domRestrict` and `FirstOrder.Language.Hom.codRestrict` restrict the domain and codomain respectively of first-order homomorphisms to substructures. * `FirstOrder.Language.Embedding.domRestrict` and `FirstOrder.Language.Embedding.codRestrict` restrict the domain and codomain respectively of first-order embeddings to substructures. * `FirstOrder.Language.Substructure.inclusion` is the inclusion embedding between substructures. ## Main Results * `L.Substructure M` forms a `CompleteLattice`. -/ universe u v w namespace FirstOrder namespace Language variable {L : Language.{u, v}} {M : Type w} {N P : Type*} variable [L.Structure M] [L.Structure N] [L.Structure P] open FirstOrder Cardinal open Structure Cardinal section ClosedUnder open Set variable {n : ℕ} (f : L.Functions n) (s : Set M) /-- Indicates that a set in a given structure is a closed under a function symbol. -/ def ClosedUnder : Prop := ∀ x : Fin n → M, (∀ i : Fin n, x i ∈ s) → funMap f x ∈ s #align first_order.language.closed_under FirstOrder.Language.ClosedUnder variable (L) @[simp] theorem closedUnder_univ : ClosedUnder f (univ : Set M) := fun _ _ => mem_univ _ #align first_order.language.closed_under_univ FirstOrder.Language.closedUnder_univ variable {L f s} {t : Set M} namespace ClosedUnder theorem inter (hs : ClosedUnder f s) (ht : ClosedUnder f t) : ClosedUnder f (s ∩ t) := fun x h => mem_inter (hs x fun i => mem_of_mem_inter_left (h i)) (ht x fun i => mem_of_mem_inter_right (h i)) #align first_order.language.closed_under.inter FirstOrder.Language.ClosedUnder.inter theorem inf (hs : ClosedUnder f s) (ht : ClosedUnder f t) : ClosedUnder f (s ⊓ t) := hs.inter ht #align first_order.language.closed_under.inf FirstOrder.Language.ClosedUnder.inf variable {S : Set (Set M)} theorem sInf (hS : ∀ s, s ∈ S → ClosedUnder f s) : ClosedUnder f (sInf S) := fun x h s hs => hS s hs x fun i => h i s hs #align first_order.language.closed_under.Inf FirstOrder.Language.ClosedUnder.sInf end ClosedUnder end ClosedUnder variable (L) (M) /-- A substructure of a structure `M` is a set closed under application of function symbols. -/ structure Substructure where carrier : Set M fun_mem : ∀ {n}, ∀ f : L.Functions n, ClosedUnder f carrier #align first_order.language.substructure FirstOrder.Language.Substructure #align first_order.language.substructure.carrier FirstOrder.Language.Substructure.carrier #align first_order.language.substructure.fun_mem FirstOrder.Language.Substructure.fun_mem variable {L} {M} namespace Substructure attribute [coe] Substructure.carrier instance instSetLike : SetLike (L.Substructure M) M := ⟨Substructure.carrier, fun p q h => by cases p; cases q; congr⟩ #align first_order.language.substructure.set_like FirstOrder.Language.Substructure.instSetLike /-- See Note [custom simps projection] -/ def Simps.coe (S : L.Substructure M) : Set M := S #align first_order.language.substructure.simps.coe FirstOrder.Language.Substructure.Simps.coe initialize_simps_projections Substructure (carrier → coe) @[simp] theorem mem_carrier {s : L.Substructure M} {x : M} : x ∈ s.carrier ↔ x ∈ s := Iff.rfl #align first_order.language.substructure.mem_carrier FirstOrder.Language.Substructure.mem_carrier /-- Two substructures are equal if they have the same elements. -/ @[ext] theorem ext {S T : L.Substructure M} (h : ∀ x, x ∈ S ↔ x ∈ T) : S = T := SetLike.ext h #align first_order.language.substructure.ext FirstOrder.Language.Substructure.ext /-- Copy a substructure replacing `carrier` with a set that is equal to it. -/ protected def copy (S : L.Substructure M) (s : Set M) (hs : s = S) : L.Substructure M where carrier := s fun_mem _ f := hs.symm ▸ S.fun_mem _ f #align first_order.language.substructure.copy FirstOrder.Language.Substructure.copy end Substructure variable {S : L.Substructure M}
Mathlib/ModelTheory/Substructures.lean
140
144
theorem Term.realize_mem {α : Type*} (t : L.Term α) (xs : α → M) (h : ∀ a, xs a ∈ S) : t.realize xs ∈ S := by
induction' t with a n f ts ih · exact h a · exact Substructure.fun_mem _ _ _ ih
/- 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.Data.Set.Image import Mathlib.Order.SuccPred.Relation import Mathlib.Topology.Clopen import Mathlib.Topology.Irreducible #align_import topology.connected from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903" /-! # Connected subsets of topological spaces In this file we define connected subsets of a topological spaces and various other properties and classes related to connectivity. ## Main definitions We define the following properties for sets in a topological space: * `IsConnected`: a nonempty set that has no non-trivial open partition. See also the section below in the module doc. * `connectedComponent` is the connected component of an element in the space. We also have a class stating that the whole space satisfies that property: `ConnectedSpace` ## On the definition of connected sets/spaces In informal mathematics, connected spaces are assumed to be nonempty. We formalise the predicate without that assumption as `IsPreconnected`. In other words, the only difference is whether the empty space counts as connected. There are good reasons to consider the empty space to be “too simple to be simple” See also https://ncatlab.org/nlab/show/too+simple+to+be+simple, and in particular https://ncatlab.org/nlab/show/too+simple+to+be+simple#relationship_to_biased_definitions. -/ open Set Function Topology TopologicalSpace Relation open scoped Classical universe u v variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α] {s t u v : Set α} section Preconnected /-- A preconnected set is one where there is no non-trivial open partition. -/ def IsPreconnected (s : Set α) : Prop := ∀ u v : Set α, IsOpen u → IsOpen v → s ⊆ u ∪ v → (s ∩ u).Nonempty → (s ∩ v).Nonempty → (s ∩ (u ∩ v)).Nonempty #align is_preconnected IsPreconnected /-- A connected set is one that is nonempty and where there is no non-trivial open partition. -/ def IsConnected (s : Set α) : Prop := s.Nonempty ∧ IsPreconnected s #align is_connected IsConnected theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty := h.1 #align is_connected.nonempty IsConnected.nonempty theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s := h.2 #align is_connected.is_preconnected IsConnected.isPreconnected theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s := fun _ _ hu hv _ => H _ _ hu hv #align is_preirreducible.is_preconnected IsPreirreducible.isPreconnected theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s := ⟨H.nonempty, H.isPreirreducible.isPreconnected⟩ #align is_irreducible.is_connected IsIrreducible.isConnected theorem isPreconnected_empty : IsPreconnected (∅ : Set α) := isPreirreducible_empty.isPreconnected #align is_preconnected_empty isPreconnected_empty theorem isConnected_singleton {x} : IsConnected ({x} : Set α) := isIrreducible_singleton.isConnected #align is_connected_singleton isConnected_singleton theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) := isConnected_singleton.isPreconnected #align is_preconnected_singleton isPreconnected_singleton theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s := hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton #align set.subsingleton.is_preconnected Set.Subsingleton.isPreconnected /-- If any point of a set is joined to a fixed point by a preconnected subset, then the original set is preconnected as well. -/ theorem isPreconnected_of_forall {s : Set α} (x : α) (H : ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by rintro u v hu hv hs ⟨z, zs, zu⟩ ⟨y, ys, yv⟩ have xs : x ∈ s := by rcases H y ys with ⟨t, ts, xt, -, -⟩ exact ts xt -- Porting note (#11215): TODO: use `wlog xu : x ∈ u := hs xs using u v y z, v u z y` cases hs xs with | inl xu => rcases H y ys with ⟨t, ts, xt, yt, ht⟩ have := ht u v hu hv (ts.trans hs) ⟨x, xt, xu⟩ ⟨y, yt, yv⟩ exact this.imp fun z hz => ⟨ts hz.1, hz.2⟩ | inr xv => rcases H z zs with ⟨t, ts, xt, zt, ht⟩ have := ht v u hv hu (ts.trans <| by rwa [union_comm]) ⟨x, xt, xv⟩ ⟨z, zt, zu⟩ exact this.imp fun _ h => ⟨ts h.1, h.2.2, h.2.1⟩ #align is_preconnected_of_forall isPreconnected_of_forall /-- If any two points of a set are contained in a preconnected subset, then the original set is preconnected as well. -/ theorem isPreconnected_of_forall_pair {s : Set α} (H : ∀ x ∈ s, ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩) exacts [isPreconnected_empty, isPreconnected_of_forall x fun y => H x hx y] #align is_preconnected_of_forall_pair isPreconnected_of_forall_pair /-- A union of a family of preconnected sets with a common point is preconnected as well. -/
Mathlib/Topology/Connected/Basic.lean
124
128
theorem isPreconnected_sUnion (x : α) (c : Set (Set α)) (H1 : ∀ s ∈ c, x ∈ s) (H2 : ∀ s ∈ c, IsPreconnected s) : IsPreconnected (⋃₀ c) := by
apply isPreconnected_of_forall x rintro y ⟨s, sc, ys⟩ exact ⟨s, subset_sUnion_of_mem sc, H1 s sc, ys, H2 s sc⟩
/- Copyright (c) 2022 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers -/ import Mathlib.Analysis.Convex.Between import Mathlib.Analysis.Convex.StrictConvexSpace import Mathlib.Analysis.NormedSpace.AffineIsometry #align_import analysis.convex.strict_convex_between from "leanprover-community/mathlib"@"e1730698f86560a342271c0471e4cb72d021aabf" /-! # Betweenness in affine spaces for strictly convex spaces This file proves results about betweenness for points in an affine space for a strictly convex space. -/ open Metric open scoped Convex variable {V P : Type*} [NormedAddCommGroup V] [NormedSpace ℝ V] variable [StrictConvexSpace ℝ V] section PseudoMetricSpace variable [PseudoMetricSpace P] [NormedAddTorsor V P] theorem Sbtw.dist_lt_max_dist (p : P) {p₁ p₂ p₃ : P} (h : Sbtw ℝ p₁ p₂ p₃) : dist p₂ p < max (dist p₁ p) (dist p₃ p) := by have hp₁p₃ : p₁ -ᵥ p ≠ p₃ -ᵥ p := by simpa using h.left_ne_right rw [Sbtw, ← wbtw_vsub_const_iff p, Wbtw, affineSegment_eq_segment, ← insert_endpoints_openSegment, Set.mem_insert_iff, Set.mem_insert_iff] at h rcases h with ⟨h | h | h, hp₂p₁, hp₂p₃⟩ · rw [vsub_left_cancel_iff] at h exact False.elim (hp₂p₁ h) · rw [vsub_left_cancel_iff] at h exact False.elim (hp₂p₃ h) · rw [openSegment_eq_image, Set.mem_image] at h rcases h with ⟨r, ⟨hr0, hr1⟩, hr⟩ simp_rw [@dist_eq_norm_vsub V, ← hr] exact norm_combo_lt_of_ne (le_max_left _ _) (le_max_right _ _) hp₁p₃ (sub_pos.2 hr1) hr0 (by abel) #align sbtw.dist_lt_max_dist Sbtw.dist_lt_max_dist theorem Wbtw.dist_le_max_dist (p : P) {p₁ p₂ p₃ : P} (h : Wbtw ℝ p₁ p₂ p₃) : dist p₂ p ≤ max (dist p₁ p) (dist p₃ p) := by by_cases hp₁ : p₂ = p₁; · simp [hp₁] by_cases hp₃ : p₂ = p₃; · simp [hp₃] have hs : Sbtw ℝ p₁ p₂ p₃ := ⟨h, hp₁, hp₃⟩ exact (hs.dist_lt_max_dist _).le #align wbtw.dist_le_max_dist Wbtw.dist_le_max_dist /-- Given three collinear points, two (not equal) with distance `r` from `p` and one with distance at most `r` from `p`, the third point is weakly between the other two points. -/
Mathlib/Analysis/Convex/StrictConvexBetween.lean
56
72
theorem Collinear.wbtw_of_dist_eq_of_dist_le {p p₁ p₂ p₃ : P} {r : ℝ} (h : Collinear ℝ ({p₁, p₂, p₃} : Set P)) (hp₁ : dist p₁ p = r) (hp₂ : dist p₂ p ≤ r) (hp₃ : dist p₃ p = r) (hp₁p₃ : p₁ ≠ p₃) : Wbtw ℝ p₁ p₂ p₃ := by
rcases h.wbtw_or_wbtw_or_wbtw with (hw | hw | hw) · exact hw · by_cases hp₃p₂ : p₃ = p₂ · simp [hp₃p₂] have hs : Sbtw ℝ p₂ p₃ p₁ := ⟨hw, hp₃p₂, hp₁p₃.symm⟩ have hs' := hs.dist_lt_max_dist p rw [hp₁, hp₃, lt_max_iff, lt_self_iff_false, or_false_iff] at hs' exact False.elim (hp₂.not_lt hs') · by_cases hp₁p₂ : p₁ = p₂ · simp [hp₁p₂] have hs : Sbtw ℝ p₃ p₁ p₂ := ⟨hw, hp₁p₃, hp₁p₂⟩ have hs' := hs.dist_lt_max_dist p rw [hp₁, hp₃, lt_max_iff, lt_self_iff_false, false_or_iff] at hs' exact False.elim (hp₂.not_lt hs')
/- Copyright (c) 2022 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Data.Finset.Prod import Mathlib.Data.Set.Finite #align_import data.finset.n_ary from "leanprover-community/mathlib"@"eba7871095e834365616b5e43c8c7bb0b37058d0" /-! # N-ary images of finsets This file defines `Finset.image₂`, the binary image of finsets. This is the finset version of `Set.image2`. This is mostly useful to define pointwise operations. ## Notes This file is very similar to `Data.Set.NAry`, `Order.Filter.NAry` and `Data.Option.NAry`. Please keep them in sync. We do not define `Finset.image₃` as its only purpose would be to prove properties of `Finset.image₂` and `Set.image2` already fulfills this task. -/ open Function Set variable {α α' β β' γ γ' δ δ' ε ε' ζ ζ' ν : Type*} namespace Finset variable [DecidableEq α'] [DecidableEq β'] [DecidableEq γ] [DecidableEq γ'] [DecidableEq δ] [DecidableEq δ'] [DecidableEq ε] [DecidableEq ε'] {f f' : α → β → γ} {g g' : α → β → γ → δ} {s s' : Finset α} {t t' : Finset β} {u u' : Finset γ} {a a' : α} {b b' : β} {c : γ} /-- The image of a binary function `f : α → β → γ` as a function `Finset α → Finset β → Finset γ`. Mathematically this should be thought of as the image of the corresponding function `α × β → γ`. -/ def image₂ (f : α → β → γ) (s : Finset α) (t : Finset β) : Finset γ := (s ×ˢ t).image <| uncurry f #align finset.image₂ Finset.image₂ @[simp] theorem mem_image₂ : c ∈ image₂ f s t ↔ ∃ a ∈ s, ∃ b ∈ t, f a b = c := by simp [image₂, and_assoc] #align finset.mem_image₂ Finset.mem_image₂ @[simp, norm_cast] theorem coe_image₂ (f : α → β → γ) (s : Finset α) (t : Finset β) : (image₂ f s t : Set γ) = Set.image2 f s t := Set.ext fun _ => mem_image₂ #align finset.coe_image₂ Finset.coe_image₂ theorem card_image₂_le (f : α → β → γ) (s : Finset α) (t : Finset β) : (image₂ f s t).card ≤ s.card * t.card := card_image_le.trans_eq <| card_product _ _ #align finset.card_image₂_le Finset.card_image₂_le theorem card_image₂_iff : (image₂ f s t).card = s.card * t.card ↔ (s ×ˢ t : Set (α × β)).InjOn fun x => f x.1 x.2 := by rw [← card_product, ← coe_product] exact card_image_iff #align finset.card_image₂_iff Finset.card_image₂_iff theorem card_image₂ (hf : Injective2 f) (s : Finset α) (t : Finset β) : (image₂ f s t).card = s.card * t.card := (card_image_of_injective _ hf.uncurry).trans <| card_product _ _ #align finset.card_image₂ Finset.card_image₂ theorem mem_image₂_of_mem (ha : a ∈ s) (hb : b ∈ t) : f a b ∈ image₂ f s t := mem_image₂.2 ⟨a, ha, b, hb, rfl⟩ #align finset.mem_image₂_of_mem Finset.mem_image₂_of_mem theorem mem_image₂_iff (hf : Injective2 f) : f a b ∈ image₂ f s t ↔ a ∈ s ∧ b ∈ t := by rw [← mem_coe, coe_image₂, mem_image2_iff hf, mem_coe, mem_coe] #align finset.mem_image₂_iff Finset.mem_image₂_iff
Mathlib/Data/Finset/NAry.lean
77
79
theorem image₂_subset (hs : s ⊆ s') (ht : t ⊆ t') : image₂ f s t ⊆ image₂ f s' t' := by
rw [← coe_subset, coe_image₂, coe_image₂] exact image2_subset hs ht
/- Copyright (c) 2020 Kyle Miller. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kyle Miller -/ import Mathlib.Algebra.BigOperators.Ring import Mathlib.Combinatorics.SimpleGraph.Dart import Mathlib.Combinatorics.SimpleGraph.Finite import Mathlib.Data.ZMod.Parity #align_import combinatorics.simple_graph.degree_sum from "leanprover-community/mathlib"@"90659cbe25e59ec302e2fb92b00e9732160cc620" /-! # Degree-sum formula and handshaking lemma The degree-sum formula is that the sum of the degrees of the vertices in a finite graph is equal to twice the number of edges. The handshaking lemma, a corollary, is that the number of odd-degree vertices is even. ## Main definitions - `SimpleGraph.sum_degrees_eq_twice_card_edges` is the degree-sum formula. - `SimpleGraph.even_card_odd_degree_vertices` is the handshaking lemma. - `SimpleGraph.odd_card_odd_degree_vertices_ne` is that the number of odd-degree vertices different from a given odd-degree vertex is odd. - `SimpleGraph.exists_ne_odd_degree_of_exists_odd_degree` is that the existence of an odd-degree vertex implies the existence of another one. ## Implementation notes We give a combinatorial proof by using the facts that (1) the map from darts to vertices is such that each fiber has cardinality the degree of the corresponding vertex and that (2) the map from darts to edges is 2-to-1. ## Tags simple graphs, sums, degree-sum formula, handshaking lemma -/ open Finset namespace SimpleGraph universe u variable {V : Type u} (G : SimpleGraph V) section DegreeSum variable [Fintype V] [DecidableRel G.Adj] -- Porting note: Changed to `Fintype (Sym2 V)` to match Combinatorics.SimpleGraph.Basic variable [Fintype (Sym2 V)] theorem dart_fst_fiber [DecidableEq V] (v : V) : (univ.filter fun d : G.Dart => d.fst = v) = univ.image (G.dartOfNeighborSet v) := by ext d simp only [mem_image, true_and_iff, mem_filter, SetCoe.exists, mem_univ, exists_prop_of_true] constructor · rintro rfl exact ⟨_, d.adj, by ext <;> rfl⟩ · rintro ⟨e, he, rfl⟩ rfl #align simple_graph.dart_fst_fiber SimpleGraph.dart_fst_fiber theorem dart_fst_fiber_card_eq_degree [DecidableEq V] (v : V) : (univ.filter fun d : G.Dart => d.fst = v).card = G.degree v := by simpa only [dart_fst_fiber, Finset.card_univ, card_neighborSet_eq_degree] using card_image_of_injective univ (G.dartOfNeighborSet_injective v) #align simple_graph.dart_fst_fiber_card_eq_degree SimpleGraph.dart_fst_fiber_card_eq_degree
Mathlib/Combinatorics/SimpleGraph/DegreeSum.lean
73
76
theorem dart_card_eq_sum_degrees : Fintype.card G.Dart = ∑ v, G.degree v := by
haveI := Classical.decEq V simp only [← card_univ, ← dart_fst_fiber_card_eq_degree] exact card_eq_sum_card_fiberwise (by simp)
/- Copyright (c) 2022 Xavier Roblot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Alex J. Best, Xavier Roblot -/ import Mathlib.Analysis.Complex.Polynomial import Mathlib.NumberTheory.NumberField.Norm import Mathlib.NumberTheory.NumberField.Basic import Mathlib.RingTheory.Norm import Mathlib.Topology.Instances.Complex import Mathlib.RingTheory.RootsOfUnity.Basic #align_import number_theory.number_field.embeddings from "leanprover-community/mathlib"@"caa58cbf5bfb7f81ccbaca4e8b8ac4bc2b39cc1c" /-! # Embeddings of number fields This file defines the embeddings of a number field into an algebraic closed field. ## Main Definitions and Results * `NumberField.Embeddings.range_eval_eq_rootSet_minpoly`: let `x ∈ K` with `K` number field and let `A` be an algebraic closed field of char. 0, then the images of `x` by the embeddings of `K` in `A` are exactly the roots in `A` of the minimal polynomial of `x` over `ℚ`. * `NumberField.Embeddings.pow_eq_one_of_norm_eq_one`: an algebraic integer whose conjugates are all of norm one is a root of unity. * `NumberField.InfinitePlace`: the type of infinite places of a number field `K`. * `NumberField.InfinitePlace.mk_eq_iff`: two complex embeddings define the same infinite place iff they are equal or complex conjugates. * `NumberField.InfinitePlace.prod_eq_abs_norm`: the infinite part of the product formula, that is for `x ∈ K`, we have `Π_w ‖x‖_w = |norm(x)|` where the product is over the infinite place `w` and `‖·‖_w` is the normalized absolute value for `w`. ## Tags number field, embeddings, places, infinite places -/ open scoped Classical namespace NumberField.Embeddings section Fintype open FiniteDimensional variable (K : Type*) [Field K] [NumberField K] variable (A : Type*) [Field A] [CharZero A] /-- There are finitely many embeddings of a number field. -/ noncomputable instance : Fintype (K →+* A) := Fintype.ofEquiv (K →ₐ[ℚ] A) RingHom.equivRatAlgHom.symm variable [IsAlgClosed A] /-- The number of embeddings of a number field is equal to its finrank. -/ theorem card : Fintype.card (K →+* A) = finrank ℚ K := by rw [Fintype.ofEquiv_card RingHom.equivRatAlgHom.symm, AlgHom.card] #align number_field.embeddings.card NumberField.Embeddings.card instance : Nonempty (K →+* A) := by rw [← Fintype.card_pos_iff, NumberField.Embeddings.card K A] exact FiniteDimensional.finrank_pos end Fintype section Roots open Set Polynomial variable (K A : Type*) [Field K] [NumberField K] [Field A] [Algebra ℚ A] [IsAlgClosed A] (x : K) /-- Let `A` be an algebraically closed field and let `x ∈ K`, with `K` a number field. The images of `x` by the embeddings of `K` in `A` are exactly the roots in `A` of the minimal polynomial of `x` over `ℚ`. -/ theorem range_eval_eq_rootSet_minpoly : (range fun φ : K →+* A => φ x) = (minpoly ℚ x).rootSet A := by convert (NumberField.isAlgebraic K).range_eval_eq_rootSet_minpoly A x using 1 ext a exact ⟨fun ⟨φ, hφ⟩ => ⟨φ.toRatAlgHom, hφ⟩, fun ⟨φ, hφ⟩ => ⟨φ.toRingHom, hφ⟩⟩ #align number_field.embeddings.range_eval_eq_root_set_minpoly NumberField.Embeddings.range_eval_eq_rootSet_minpoly end Roots section Bounded open FiniteDimensional Polynomial Set variable {K : Type*} [Field K] [NumberField K] variable {A : Type*} [NormedField A] [IsAlgClosed A] [NormedAlgebra ℚ A] theorem coeff_bdd_of_norm_le {B : ℝ} {x : K} (h : ∀ φ : K →+* A, ‖φ x‖ ≤ B) (i : ℕ) : ‖(minpoly ℚ x).coeff i‖ ≤ max B 1 ^ finrank ℚ K * (finrank ℚ K).choose (finrank ℚ K / 2) := by have hx := IsSeparable.isIntegral ℚ x rw [← norm_algebraMap' A, ← coeff_map (algebraMap ℚ A)] refine coeff_bdd_of_roots_le _ (minpoly.monic hx) (IsAlgClosed.splits_codomain _) (minpoly.natDegree_le x) (fun z hz => ?_) i classical rw [← Multiset.mem_toFinset] at hz obtain ⟨φ, rfl⟩ := (range_eval_eq_rootSet_minpoly K A x).symm.subset hz exact h φ #align number_field.embeddings.coeff_bdd_of_norm_le NumberField.Embeddings.coeff_bdd_of_norm_le variable (K A) /-- Let `B` be a real number. The set of algebraic integers in `K` whose conjugates are all smaller in norm than `B` is finite. -/
Mathlib/NumberTheory/NumberField/Embeddings.lean
105
115
theorem finite_of_norm_le (B : ℝ) : {x : K | IsIntegral ℤ x ∧ ∀ φ : K →+* A, ‖φ x‖ ≤ B}.Finite := by
let C := Nat.ceil (max B 1 ^ finrank ℚ K * (finrank ℚ K).choose (finrank ℚ K / 2)) have := bUnion_roots_finite (algebraMap ℤ K) (finrank ℚ K) (finite_Icc (-C : ℤ) C) refine this.subset fun x hx => ?_; simp_rw [mem_iUnion] have h_map_ℚ_minpoly := minpoly.isIntegrallyClosed_eq_field_fractions' ℚ hx.1 refine ⟨_, ⟨?_, fun i => ?_⟩, mem_rootSet.2 ⟨minpoly.ne_zero hx.1, minpoly.aeval ℤ x⟩⟩ · rw [← (minpoly.monic hx.1).natDegree_map (algebraMap ℤ ℚ), ← h_map_ℚ_minpoly] exact minpoly.natDegree_le x rw [mem_Icc, ← abs_le, ← @Int.cast_le ℝ] refine (Eq.trans_le ?_ <| coeff_bdd_of_norm_le hx.2 i).trans (Nat.le_ceil _) rw [h_map_ℚ_minpoly, coeff_map, eq_intCast, Int.norm_cast_rat, Int.norm_eq_abs, Int.cast_abs]
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov -/ import Mathlib.Order.Filter.Basic import Mathlib.Topology.Bases import Mathlib.Data.Set.Accumulate import Mathlib.Topology.Bornology.Basic import Mathlib.Topology.LocallyFinite /-! # Compact sets and compact spaces ## Main definitions We define the following properties for sets in a topological space: * `IsCompact`: a set such that each open cover has a finite subcover. This is defined in mathlib using filters. The main property of a compact set is `IsCompact.elim_finite_subcover`. * `CompactSpace`: typeclass stating that the whole space is a compact set. * `NoncompactSpace`: a space that is not a compact space. ## Main results * `isCompact_univ_pi`: **Tychonov's theorem** - an arbitrary product of compact sets is compact. -/ open Set Filter Topology TopologicalSpace Classical Function universe u v variable {X : Type u} {Y : Type v} {ι : Type*} variable [TopologicalSpace X] [TopologicalSpace Y] {s t : Set X} -- compact sets section Compact lemma IsCompact.exists_clusterPt (hs : IsCompact s) {f : Filter X} [NeBot f] (hf : f ≤ 𝓟 s) : ∃ x ∈ s, ClusterPt x f := hs hf lemma IsCompact.exists_mapClusterPt {ι : Type*} (hs : IsCompact s) {f : Filter ι} [NeBot f] {u : ι → X} (hf : Filter.map u f ≤ 𝓟 s) : ∃ x ∈ s, MapClusterPt x f u := hs hf /-- The complement to a compact set belongs to a filter `f` if it belongs to each filter `𝓝 x ⊓ f`, `x ∈ s`. -/ theorem IsCompact.compl_mem_sets (hs : IsCompact s) {f : Filter X} (hf : ∀ x ∈ s, sᶜ ∈ 𝓝 x ⊓ f) : sᶜ ∈ f := by contrapose! hf simp only [not_mem_iff_inf_principal_compl, compl_compl, inf_assoc] at hf ⊢ exact @hs _ hf inf_le_right #align is_compact.compl_mem_sets IsCompact.compl_mem_sets /-- The complement to a compact set belongs to a filter `f` if each `x ∈ s` has a neighborhood `t` within `s` such that `tᶜ` belongs to `f`. -/ theorem IsCompact.compl_mem_sets_of_nhdsWithin (hs : IsCompact s) {f : Filter X} (hf : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, tᶜ ∈ f) : sᶜ ∈ f := by refine hs.compl_mem_sets fun x hx => ?_ rcases hf x hx with ⟨t, ht, hst⟩ replace ht := mem_inf_principal.1 ht apply mem_inf_of_inter ht hst rintro x ⟨h₁, h₂⟩ hs exact h₂ (h₁ hs) #align is_compact.compl_mem_sets_of_nhds_within IsCompact.compl_mem_sets_of_nhdsWithin /-- If `p : Set X → Prop` is stable under restriction and union, and each point `x` of a compact set `s` has a neighborhood `t` within `s` such that `p t`, then `p s` holds. -/ @[elab_as_elim] theorem IsCompact.induction_on (hs : IsCompact s) {p : Set X → Prop} (he : p ∅) (hmono : ∀ ⦃s t⦄, s ⊆ t → p t → p s) (hunion : ∀ ⦃s t⦄, p s → p t → p (s ∪ t)) (hnhds : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, p t) : p s := by let f : Filter X := comk p he (fun _t ht _s hsub ↦ hmono hsub ht) (fun _s hs _t ht ↦ hunion hs ht) have : sᶜ ∈ f := hs.compl_mem_sets_of_nhdsWithin (by simpa [f] using hnhds) rwa [← compl_compl s] #align is_compact.induction_on IsCompact.induction_on /-- The intersection of a compact set and a closed set is a compact set. -/
Mathlib/Topology/Compactness/Compact.lean
79
85
theorem IsCompact.inter_right (hs : IsCompact s) (ht : IsClosed t) : IsCompact (s ∩ t) := by
intro f hnf hstf obtain ⟨x, hsx, hx⟩ : ∃ x ∈ s, ClusterPt x f := hs (le_trans hstf (le_principal_iff.2 inter_subset_left)) have : x ∈ t := ht.mem_of_nhdsWithin_neBot <| hx.mono <| le_trans hstf (le_principal_iff.2 inter_subset_right) exact ⟨x, ⟨hsx, this⟩, hx⟩