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/- Copyright (c) 2022 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers, Heather Macbeth -/ import Mathlib.Analysis.InnerProductSpace.TwoDim import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic /-! # Oriented angles. This file defines oriented angles in real inner product spaces. ## Main definitions * `Orientation.oangle` is the oriented angle between two vectors with respect to an orientation. ## Implementation notes The definitions here use the `Real.angle` type, angles modulo `2 * π`. For some purposes, angles modulo `π` are more convenient, because results are true for such angles with less configuration dependence. Results that are only equalities modulo `π` can be represented modulo `2 * π` as equalities of `(2 : ℤ) • θ`. ## References * Evan Chen, Euclidean Geometry in Mathematical Olympiads. -/ noncomputable section open Module Complex open scoped Real RealInnerProductSpace ComplexConjugate namespace Orientation attribute [local instance] Complex.finrank_real_complex_fact variable {V V' : Type*} variable [NormedAddCommGroup V] [NormedAddCommGroup V'] variable [InnerProductSpace ℝ V] [InnerProductSpace ℝ V'] variable [Fact (finrank ℝ V = 2)] [Fact (finrank ℝ V' = 2)] (o : Orientation ℝ V (Fin 2)) local notation "ω" => o.areaForm /-- The oriented angle from `x` to `y`, modulo `2 * π`. If either vector is 0, this is 0. See `InnerProductGeometry.angle` for the corresponding unoriented angle definition. -/ def oangle (x y : V) : Real.Angle := Complex.arg (o.kahler x y) /-- Oriented angles are continuous when the vectors involved are nonzero. -/ @[fun_prop] theorem continuousAt_oangle {x : V × V} (hx1 : x.1 ≠ 0) (hx2 : x.2 ≠ 0) : ContinuousAt (fun y : V × V => o.oangle y.1 y.2) x := by refine (Complex.continuousAt_arg_coe_angle ?_).comp ?_ · exact o.kahler_ne_zero hx1 hx2 exact ((continuous_ofReal.comp continuous_inner).add ((continuous_ofReal.comp o.areaForm'.continuous₂).mul continuous_const)).continuousAt /-- If the first vector passed to `oangle` is 0, the result is 0. -/ @[simp] theorem oangle_zero_left (x : V) : o.oangle 0 x = 0 := by simp [oangle] /-- If the second vector passed to `oangle` is 0, the result is 0. -/ @[simp] theorem oangle_zero_right (x : V) : o.oangle x 0 = 0 := by simp [oangle] /-- If the two vectors passed to `oangle` are the same, the result is 0. -/ @[simp] theorem oangle_self (x : V) : o.oangle x x = 0 := by rw [oangle, kahler_apply_self, ← ofReal_pow] convert QuotientAddGroup.mk_zero (AddSubgroup.zmultiples (2 * π)) apply arg_ofReal_of_nonneg positivity /-- If the angle between two vectors is nonzero, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ 0 := by rintro rfl; simp at h /-- If the angle between two vectors is nonzero, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : y ≠ 0 := by rintro rfl; simp at h /-- If the angle between two vectors is nonzero, the vectors are not equal. -/ theorem ne_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ y := by rintro rfl; simp at h /-- If the angle between two vectors is `π`, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ 0 := o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `π`, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : y ≠ 0 := o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `π`, the vectors are not equal. -/ theorem ne_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ y := o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `π / 2`, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ 0 := o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `π / 2`, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : y ≠ 0 := o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `π / 2`, the vectors are not equal. -/ theorem ne_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ y := o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `-π / 2`, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) : x ≠ 0 := o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `-π / 2`, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) : y ≠ 0 := o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the angle between two vectors is `-π / 2`, the vectors are not equal. -/ theorem ne_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) : x ≠ y := o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0) /-- If the sign of the angle between two vectors is nonzero, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ 0 := o.left_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between two vectors is nonzero, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : y ≠ 0 := o.right_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between two vectors is nonzero, the vectors are not equal. -/ theorem ne_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ y := o.ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between two vectors is positive, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ 0 := o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- If the sign of the angle between two vectors is positive, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : y ≠ 0 := o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- If the sign of the angle between two vectors is positive, the vectors are not equal. -/ theorem ne_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ y := o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- If the sign of the angle between two vectors is negative, the first vector is nonzero. -/ theorem left_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ 0 := o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- If the sign of the angle between two vectors is negative, the second vector is nonzero. -/ theorem right_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : y ≠ 0 := o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- If the sign of the angle between two vectors is negative, the vectors are not equal. -/ theorem ne_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ y := o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0) /-- Swapping the two vectors passed to `oangle` negates the angle. -/ theorem oangle_rev (x y : V) : o.oangle y x = -o.oangle x y := by simp only [oangle, o.kahler_swap y x, Complex.arg_conj_coe_angle] /-- Adding the angles between two vectors in each order results in 0. -/ @[simp] theorem oangle_add_oangle_rev (x y : V) : o.oangle x y + o.oangle y x = 0 := by simp [o.oangle_rev y x] /-- Negating the first vector passed to `oangle` adds `π` to the angle. -/ theorem oangle_neg_left {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) : o.oangle (-x) y = o.oangle x y + π := by simp only [oangle, map_neg] convert Complex.arg_neg_coe_angle _ exact o.kahler_ne_zero hx hy /-- Negating the second vector passed to `oangle` adds `π` to the angle. -/ theorem oangle_neg_right {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) : o.oangle x (-y) = o.oangle x y + π := by simp only [oangle, map_neg] convert Complex.arg_neg_coe_angle _ exact o.kahler_ne_zero hx hy /-- Negating the first vector passed to `oangle` does not change twice the angle. -/ @[simp] theorem two_zsmul_oangle_neg_left (x y : V) : (2 : ℤ) • o.oangle (-x) y = (2 : ℤ) • o.oangle x y := by by_cases hx : x = 0 · simp [hx] · by_cases hy : y = 0 · simp [hy] · simp [o.oangle_neg_left hx hy] /-- Negating the second vector passed to `oangle` does not change twice the angle. -/ @[simp] theorem two_zsmul_oangle_neg_right (x y : V) : (2 : ℤ) • o.oangle x (-y) = (2 : ℤ) • o.oangle x y := by by_cases hx : x = 0 · simp [hx] · by_cases hy : y = 0 · simp [hy] · simp [o.oangle_neg_right hx hy] /-- Negating both vectors passed to `oangle` does not change the angle. -/ @[simp] theorem oangle_neg_neg (x y : V) : o.oangle (-x) (-y) = o.oangle x y := by simp [oangle] /-- Negating the first vector produces the same angle as negating the second vector. -/ theorem oangle_neg_left_eq_neg_right (x y : V) : o.oangle (-x) y = o.oangle x (-y) := by rw [← neg_neg y, oangle_neg_neg, neg_neg] /-- The angle between the negation of a nonzero vector and that vector is `π`. -/ @[simp] theorem oangle_neg_self_left {x : V} (hx : x ≠ 0) : o.oangle (-x) x = π := by simp [oangle_neg_left, hx] /-- The angle between a nonzero vector and its negation is `π`. -/ @[simp] theorem oangle_neg_self_right {x : V} (hx : x ≠ 0) : o.oangle x (-x) = π := by simp [oangle_neg_right, hx] /-- Twice the angle between the negation of a vector and that vector is 0. -/ theorem two_zsmul_oangle_neg_self_left (x : V) : (2 : ℤ) • o.oangle (-x) x = 0 := by by_cases hx : x = 0 <;> simp [hx] /-- Twice the angle between a vector and its negation is 0. -/ theorem two_zsmul_oangle_neg_self_right (x : V) : (2 : ℤ) • o.oangle x (-x) = 0 := by by_cases hx : x = 0 <;> simp [hx] /-- Adding the angles between two vectors in each order, with the first vector in each angle negated, results in 0. -/ @[simp] theorem oangle_add_oangle_rev_neg_left (x y : V) : o.oangle (-x) y + o.oangle (-y) x = 0 := by rw [oangle_neg_left_eq_neg_right, oangle_rev, neg_add_cancel] /-- Adding the angles between two vectors in each order, with the second vector in each angle negated, results in 0. -/ @[simp] theorem oangle_add_oangle_rev_neg_right (x y : V) : o.oangle x (-y) + o.oangle y (-x) = 0 := by rw [o.oangle_rev (-x), oangle_neg_left_eq_neg_right, add_neg_cancel] /-- Multiplying the first vector passed to `oangle` by a positive real does not change the angle. -/ @[simp] theorem oangle_smul_left_of_pos (x y : V) {r : ℝ} (hr : 0 < r) : o.oangle (r • x) y = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr] /-- Multiplying the second vector passed to `oangle` by a positive real does not change the angle. -/ @[simp] theorem oangle_smul_right_of_pos (x y : V) {r : ℝ} (hr : 0 < r) : o.oangle x (r • y) = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr] /-- Multiplying the first vector passed to `oangle` by a negative real produces the same angle as negating that vector. -/ @[simp] theorem oangle_smul_left_of_neg (x y : V) {r : ℝ} (hr : r < 0) : o.oangle (r • x) y = o.oangle (-x) y := by rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_left_of_pos _ _ (neg_pos_of_neg hr)] /-- Multiplying the second vector passed to `oangle` by a negative real produces the same angle as negating that vector. -/ @[simp] theorem oangle_smul_right_of_neg (x y : V) {r : ℝ} (hr : r < 0) : o.oangle x (r • y) = o.oangle x (-y) := by rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_right_of_pos _ _ (neg_pos_of_neg hr)] /-- The angle between a nonnegative multiple of a vector and that vector is 0. -/ @[simp] theorem oangle_smul_left_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle (r • x) x = 0 := by rcases hr.lt_or_eq with (h | h) · simp [h] · simp [h.symm] /-- The angle between a vector and a nonnegative multiple of that vector is 0. -/ @[simp] theorem oangle_smul_right_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle x (r • x) = 0 := by rcases hr.lt_or_eq with (h | h) · simp [h] · simp [h.symm] /-- The angle between two nonnegative multiples of the same vector is 0. -/ @[simp] theorem oangle_smul_smul_self_of_nonneg (x : V) {r₁ r₂ : ℝ} (hr₁ : 0 ≤ r₁) (hr₂ : 0 ≤ r₂) : o.oangle (r₁ • x) (r₂ • x) = 0 := by rcases hr₁.lt_or_eq with (h | h) · simp [h, hr₂] · simp [h.symm] /-- Multiplying the first vector passed to `oangle` by a nonzero real does not change twice the angle. -/ @[simp] theorem two_zsmul_oangle_smul_left_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) : (2 : ℤ) • o.oangle (r • x) y = (2 : ℤ) • o.oangle x y := by rcases hr.lt_or_lt with (h | h) <;> simp [h] /-- Multiplying the second vector passed to `oangle` by a nonzero real does not change twice the angle. -/ @[simp] theorem two_zsmul_oangle_smul_right_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) : (2 : ℤ) • o.oangle x (r • y) = (2 : ℤ) • o.oangle x y := by rcases hr.lt_or_lt with (h | h) <;> simp [h] /-- Twice the angle between a multiple of a vector and that vector is 0. -/ @[simp] theorem two_zsmul_oangle_smul_left_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle (r • x) x = 0 := by rcases lt_or_le r 0 with (h | h) <;> simp [h] /-- Twice the angle between a vector and a multiple of that vector is 0. -/ @[simp] theorem two_zsmul_oangle_smul_right_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle x (r • x) = 0 := by rcases lt_or_le r 0 with (h | h) <;> simp [h] /-- Twice the angle between two multiples of a vector is 0. -/ @[simp] theorem two_zsmul_oangle_smul_smul_self (x : V) {r₁ r₂ : ℝ} : (2 : ℤ) • o.oangle (r₁ • x) (r₂ • x) = 0 := by by_cases h : r₁ = 0 <;> simp [h] /-- If the spans of two vectors are equal, twice angles with those vectors on the left are equal. -/ theorem two_zsmul_oangle_left_of_span_eq {x y : V} (z : V) (h : (ℝ ∙ x) = ℝ ∙ y) : (2 : ℤ) • o.oangle x z = (2 : ℤ) • o.oangle y z := by rw [Submodule.span_singleton_eq_span_singleton] at h rcases h with ⟨r, rfl⟩ exact (o.two_zsmul_oangle_smul_left_of_ne_zero _ _ (Units.ne_zero _)).symm /-- If the spans of two vectors are equal, twice angles with those vectors on the right are equal. -/ theorem two_zsmul_oangle_right_of_span_eq (x : V) {y z : V} (h : (ℝ ∙ y) = ℝ ∙ z) : (2 : ℤ) • o.oangle x y = (2 : ℤ) • o.oangle x z := by rw [Submodule.span_singleton_eq_span_singleton] at h rcases h with ⟨r, rfl⟩ exact (o.two_zsmul_oangle_smul_right_of_ne_zero _ _ (Units.ne_zero _)).symm /-- If the spans of two pairs of vectors are equal, twice angles between those vectors are equal. -/ theorem two_zsmul_oangle_of_span_eq_of_span_eq {w x y z : V} (hwx : (ℝ ∙ w) = ℝ ∙ x) (hyz : (ℝ ∙ y) = ℝ ∙ z) : (2 : ℤ) • o.oangle w y = (2 : ℤ) • o.oangle x z := by rw [o.two_zsmul_oangle_left_of_span_eq y hwx, o.two_zsmul_oangle_right_of_span_eq x hyz] /-- The oriented angle between two vectors is zero if and only if the angle with the vectors swapped is zero. -/ theorem oangle_eq_zero_iff_oangle_rev_eq_zero {x y : V} : o.oangle x y = 0 ↔ o.oangle y x = 0 := by rw [oangle_rev, neg_eq_zero] /-- The oriented angle between two vectors is zero if and only if they are on the same ray. -/ theorem oangle_eq_zero_iff_sameRay {x y : V} : o.oangle x y = 0 ↔ SameRay ℝ x y := by rw [oangle, kahler_apply_apply, Complex.arg_coe_angle_eq_iff_eq_toReal, Real.Angle.toReal_zero, Complex.arg_eq_zero_iff] simpa using o.nonneg_inner_and_areaForm_eq_zero_iff_sameRay x y /-- The oriented angle between two vectors is `π` if and only if the angle with the vectors swapped is `π`. -/ theorem oangle_eq_pi_iff_oangle_rev_eq_pi {x y : V} : o.oangle x y = π ↔ o.oangle y x = π := by rw [oangle_rev, neg_eq_iff_eq_neg, Real.Angle.neg_coe_pi] /-- The oriented angle between two vectors is `π` if and only they are nonzero and the first is on the same ray as the negation of the second. -/ theorem oangle_eq_pi_iff_sameRay_neg {x y : V} : o.oangle x y = π ↔ x ≠ 0 ∧ y ≠ 0 ∧ SameRay ℝ x (-y) := by rw [← o.oangle_eq_zero_iff_sameRay] constructor · intro h
by_cases hx : x = 0; · simp [hx, Real.Angle.pi_ne_zero.symm] at h by_cases hy : y = 0; · simp [hy, Real.Angle.pi_ne_zero.symm] at h
Mathlib/Geometry/Euclidean/Angle/Oriented/Basic.lean
368
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/- Copyright (c) 2022 Kexing Ying. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kexing Ying -/ import Mathlib.Order.Interval.Set.Monotone import Mathlib.Probability.Process.HittingTime import Mathlib.Probability.Martingale.Basic import Mathlib.Tactic.AdaptationNote /-! # Doob's upcrossing estimate Given a discrete real-valued submartingale $(f_n)_{n \in \mathbb{N}}$, denoting by $U_N(a, b)$ the number of times $f_n$ crossed from below $a$ to above $b$ before time $N$, Doob's upcrossing estimate (also known as Doob's inequality) states that $$(b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[(f_N - a)^+].$$ Doob's upcrossing estimate is an important inequality and is central in proving the martingale convergence theorems. ## Main definitions * `MeasureTheory.upperCrossingTime a b f N n`: is the stopping time corresponding to `f` crossing above `b` the `n`-th time before time `N` (if this does not occur then the value is taken to be `N`). * `MeasureTheory.lowerCrossingTime a b f N n`: is the stopping time corresponding to `f` crossing below `a` the `n`-th time before time `N` (if this does not occur then the value is taken to be `N`). * `MeasureTheory.upcrossingStrat a b f N`: is the predictable process which is 1 if `n` is between a consecutive pair of lower and upper crossings and is 0 otherwise. Intuitively one might think of the `upcrossingStrat` as the strategy of buying 1 share whenever the process crosses below `a` for the first time after selling and selling 1 share whenever the process crosses above `b` for the first time after buying. * `MeasureTheory.upcrossingsBefore a b f N`: is the number of times `f` crosses from below `a` to above `b` before time `N`. * `MeasureTheory.upcrossings a b f`: is the number of times `f` crosses from below `a` to above `b`. This takes value in `ℝ≥0∞` and so is allowed to be `∞`. ## Main results * `MeasureTheory.Adapted.isStoppingTime_upperCrossingTime`: `upperCrossingTime` is a stopping time whenever the process it is associated to is adapted. * `MeasureTheory.Adapted.isStoppingTime_lowerCrossingTime`: `lowerCrossingTime` is a stopping time whenever the process it is associated to is adapted. * `MeasureTheory.Submartingale.mul_integral_upcrossingsBefore_le_integral_pos_part`: Doob's upcrossing estimate. * `MeasureTheory.Submartingale.mul_lintegral_upcrossings_le_lintegral_pos_part`: the inequality obtained by taking the supremum on both sides of Doob's upcrossing estimate. ### References We mostly follow the proof from [Kallenberg, *Foundations of modern probability*][kallenberg2021] -/ open TopologicalSpace Filter open scoped NNReal ENNReal MeasureTheory ProbabilityTheory Topology namespace MeasureTheory variable {Ω ι : Type*} {m0 : MeasurableSpace Ω} {μ : Measure Ω} /-! ## Proof outline In this section, we will denote by $U_N(a, b)$ the number of upcrossings of $(f_n)$ from below $a$ to above $b$ before time $N$. To define $U_N(a, b)$, we will construct two stopping times corresponding to when $(f_n)$ crosses below $a$ and above $b$. Namely, we define $$ \sigma_n := \inf \{n \ge \tau_n \mid f_n \le a\} \wedge N; $$ $$ \tau_{n + 1} := \inf \{n \ge \sigma_n \mid f_n \ge b\} \wedge N. $$ These are `lowerCrossingTime` and `upperCrossingTime` in our formalization which are defined using `MeasureTheory.hitting` allowing us to specify a starting and ending time. Then, we may simply define $U_N(a, b) := \sup \{n \mid \tau_n < N\}$. Fixing $a < b \in \mathbb{R}$, we will first prove the theorem in the special case that $0 \le f_0$ and $a \le f_N$. In particular, we will show $$ (b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[f_N]. $$ This is `MeasureTheory.integral_mul_upcrossingsBefore_le_integral` in our formalization. To prove this, we use the fact that given a non-negative, bounded, predictable process $(C_n)$ (i.e. $(C_{n + 1})$ is adapted), $(C \bullet f)_n := \sum_{k \le n} C_{k + 1}(f_{k + 1} - f_k)$ is a submartingale if $(f_n)$ is. Define $C_n := \sum_{k \le n} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)$. It is easy to see that $(1 - C_n)$ is non-negative, bounded and predictable, and hence, given a submartingale $(f_n)$, $(1 - C) \bullet f$ is also a submartingale. Thus, by the submartingale property, $0 \le \mathbb{E}[((1 - C) \bullet f)_0] \le \mathbb{E}[((1 - C) \bullet f)_N]$ implying $$ \mathbb{E}[(C \bullet f)_N] \le \mathbb{E}[(1 \bullet f)_N] = \mathbb{E}[f_N] - \mathbb{E}[f_0]. $$ Furthermore, \begin{align} (C \bullet f)_N & = \sum_{n \le N} \sum_{k \le N} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)(f_{n + 1} - f_n)\\ & = \sum_{k \le N} \sum_{n \le N} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)(f_{n + 1} - f_n)\\ & = \sum_{k \le N} (f_{\sigma_k + 1} - f_{\sigma_k} + f_{\sigma_k + 2} - f_{\sigma_k + 1} + \cdots + f_{\tau_{k + 1}} - f_{\tau_{k + 1} - 1})\\ & = \sum_{k \le N} (f_{\tau_{k + 1}} - f_{\sigma_k}) \ge \sum_{k < U_N(a, b)} (b - a) = (b - a) U_N(a, b) \end{align} where the inequality follows since for all $k < U_N(a, b)$, $f_{\tau_{k + 1}} - f_{\sigma_k} \ge b - a$ while for all $k > U_N(a, b)$, $f_{\tau_{k + 1}} = f_{\sigma_k} = f_N$ and $f_{\tau_{U_N(a, b) + 1}} - f_{\sigma_{U_N(a, b)}} = f_N - a \ge 0$. Hence, we have $$ (b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[(C \bullet f)_N] \le \mathbb{E}[f_N] - \mathbb{E}[f_0] \le \mathbb{E}[f_N], $$ as required. To obtain the general case, we simply apply the above to $((f_n - a)^+)_n$. -/ /-- `lowerCrossingTimeAux a f c N` is the first time `f` reached below `a` after time `c` before time `N`. -/ noncomputable def lowerCrossingTimeAux [Preorder ι] [InfSet ι] (a : ℝ) (f : ι → Ω → ℝ) (c N : ι) : Ω → ι := hitting f (Set.Iic a) c N /-- `upperCrossingTime a b f N n` is the first time before time `N`, `f` reaches above `b` after `f` reached below `a` for the `n - 1`-th time. -/ noncomputable def upperCrossingTime [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ) (N : ι) : ℕ → Ω → ι | 0 => ⊥ | n + 1 => fun ω => hitting f (Set.Ici b) (lowerCrossingTimeAux a f (upperCrossingTime a b f N n ω) N ω) N ω /-- `lowerCrossingTime a b f N n` is the first time before time `N`, `f` reaches below `a` after `f` reached above `b` for the `n`-th time. -/ noncomputable def lowerCrossingTime [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ) (N : ι) (n : ℕ) : Ω → ι := fun ω => hitting f (Set.Iic a) (upperCrossingTime a b f N n ω) N ω section variable [Preorder ι] [OrderBot ι] [InfSet ι] variable {a b : ℝ} {f : ι → Ω → ℝ} {N : ι} {n : ℕ} {ω : Ω} @[simp] theorem upperCrossingTime_zero : upperCrossingTime a b f N 0 = ⊥ := rfl @[simp] theorem lowerCrossingTime_zero : lowerCrossingTime a b f N 0 = hitting f (Set.Iic a) ⊥ N := rfl theorem upperCrossingTime_succ : upperCrossingTime a b f N (n + 1) ω = hitting f (Set.Ici b) (lowerCrossingTimeAux a f (upperCrossingTime a b f N n ω) N ω) N ω := by rw [upperCrossingTime] theorem upperCrossingTime_succ_eq (ω : Ω) : upperCrossingTime a b f N (n + 1) ω = hitting f (Set.Ici b) (lowerCrossingTime a b f N n ω) N ω := by simp only [upperCrossingTime_succ] rfl end section ConditionallyCompleteLinearOrderBot variable [ConditionallyCompleteLinearOrderBot ι] variable {a b : ℝ} {f : ι → Ω → ℝ} {N : ι} {n m : ℕ} {ω : Ω} theorem upperCrossingTime_le : upperCrossingTime a b f N n ω ≤ N := by cases n · simp only [upperCrossingTime_zero, Pi.bot_apply, bot_le] · simp only [upperCrossingTime_succ, hitting_le] @[simp] theorem upperCrossingTime_zero' : upperCrossingTime a b f ⊥ n ω = ⊥ := eq_bot_iff.2 upperCrossingTime_le theorem lowerCrossingTime_le : lowerCrossingTime a b f N n ω ≤ N := by simp only [lowerCrossingTime, hitting_le ω] theorem upperCrossingTime_le_lowerCrossingTime : upperCrossingTime a b f N n ω ≤ lowerCrossingTime a b f N n ω := by simp only [lowerCrossingTime, le_hitting upperCrossingTime_le ω] theorem lowerCrossingTime_le_upperCrossingTime_succ : lowerCrossingTime a b f N n ω ≤ upperCrossingTime a b f N (n + 1) ω := by rw [upperCrossingTime_succ] exact le_hitting lowerCrossingTime_le ω theorem lowerCrossingTime_mono (hnm : n ≤ m) : lowerCrossingTime a b f N n ω ≤ lowerCrossingTime a b f N m ω := by suffices Monotone fun n => lowerCrossingTime a b f N n ω by exact this hnm exact monotone_nat_of_le_succ fun n => le_trans lowerCrossingTime_le_upperCrossingTime_succ upperCrossingTime_le_lowerCrossingTime theorem upperCrossingTime_mono (hnm : n ≤ m) : upperCrossingTime a b f N n ω ≤ upperCrossingTime a b f N m ω := by suffices Monotone fun n => upperCrossingTime a b f N n ω by exact this hnm exact monotone_nat_of_le_succ fun n => le_trans upperCrossingTime_le_lowerCrossingTime lowerCrossingTime_le_upperCrossingTime_succ end ConditionallyCompleteLinearOrderBot variable {a b : ℝ} {f : ℕ → Ω → ℝ} {N : ℕ} {n m : ℕ} {ω : Ω} theorem stoppedValue_lowerCrossingTime (h : lowerCrossingTime a b f N n ω ≠ N) : stoppedValue f (lowerCrossingTime a b f N n) ω ≤ a := by obtain ⟨j, hj₁, hj₂⟩ := (hitting_le_iff_of_lt _ (lt_of_le_of_ne lowerCrossingTime_le h)).1 le_rfl exact stoppedValue_hitting_mem ⟨j, ⟨hj₁.1, le_trans hj₁.2 lowerCrossingTime_le⟩, hj₂⟩ theorem stoppedValue_upperCrossingTime (h : upperCrossingTime a b f N (n + 1) ω ≠ N) : b ≤ stoppedValue f (upperCrossingTime a b f N (n + 1)) ω := by obtain ⟨j, hj₁, hj₂⟩ := (hitting_le_iff_of_lt _ (lt_of_le_of_ne upperCrossingTime_le h)).1 le_rfl exact stoppedValue_hitting_mem ⟨j, ⟨hj₁.1, le_trans hj₁.2 (hitting_le _)⟩, hj₂⟩ theorem upperCrossingTime_lt_lowerCrossingTime (hab : a < b) (hn : lowerCrossingTime a b f N (n + 1) ω ≠ N) : upperCrossingTime a b f N (n + 1) ω < lowerCrossingTime a b f N (n + 1) ω := by refine lt_of_le_of_ne upperCrossingTime_le_lowerCrossingTime fun h => not_le.2 hab <| le_trans ?_ (stoppedValue_lowerCrossingTime hn) simp only [stoppedValue] rw [← h] exact stoppedValue_upperCrossingTime (h.symm ▸ hn) theorem lowerCrossingTime_lt_upperCrossingTime (hab : a < b) (hn : upperCrossingTime a b f N (n + 1) ω ≠ N) : lowerCrossingTime a b f N n ω < upperCrossingTime a b f N (n + 1) ω := by refine lt_of_le_of_ne lowerCrossingTime_le_upperCrossingTime_succ fun h => not_le.2 hab <| le_trans (stoppedValue_upperCrossingTime hn) ?_ simp only [stoppedValue] rw [← h] exact stoppedValue_lowerCrossingTime (h.symm ▸ hn) theorem upperCrossingTime_lt_succ (hab : a < b) (hn : upperCrossingTime a b f N (n + 1) ω ≠ N) : upperCrossingTime a b f N n ω < upperCrossingTime a b f N (n + 1) ω := lt_of_le_of_lt upperCrossingTime_le_lowerCrossingTime (lowerCrossingTime_lt_upperCrossingTime hab hn) theorem lowerCrossingTime_stabilize (hnm : n ≤ m) (hn : lowerCrossingTime a b f N n ω = N) : lowerCrossingTime a b f N m ω = N := le_antisymm lowerCrossingTime_le (le_trans (le_of_eq hn.symm) (lowerCrossingTime_mono hnm)) theorem upperCrossingTime_stabilize (hnm : n ≤ m) (hn : upperCrossingTime a b f N n ω = N) : upperCrossingTime a b f N m ω = N := le_antisymm upperCrossingTime_le (le_trans (le_of_eq hn.symm) (upperCrossingTime_mono hnm)) theorem lowerCrossingTime_stabilize' (hnm : n ≤ m) (hn : N ≤ lowerCrossingTime a b f N n ω) : lowerCrossingTime a b f N m ω = N := lowerCrossingTime_stabilize hnm (le_antisymm lowerCrossingTime_le hn) theorem upperCrossingTime_stabilize' (hnm : n ≤ m) (hn : N ≤ upperCrossingTime a b f N n ω) : upperCrossingTime a b f N m ω = N := upperCrossingTime_stabilize hnm (le_antisymm upperCrossingTime_le hn) -- `upperCrossingTime_bound_eq` provides an explicit bound theorem exists_upperCrossingTime_eq (f : ℕ → Ω → ℝ) (N : ℕ) (ω : Ω) (hab : a < b) : ∃ n, upperCrossingTime a b f N n ω = N := by by_contra h; push_neg at h have : StrictMono fun n => upperCrossingTime a b f N n ω := strictMono_nat_of_lt_succ fun n => upperCrossingTime_lt_succ hab (h _) obtain ⟨_, ⟨k, rfl⟩, hk⟩ : ∃ (m : _) (_ : m ∈ Set.range fun n => upperCrossingTime a b f N n ω), N < m := ⟨upperCrossingTime a b f N (N + 1) ω, ⟨N + 1, rfl⟩, lt_of_lt_of_le N.lt_succ_self (StrictMono.id_le this (N + 1))⟩ exact not_le.2 hk upperCrossingTime_le theorem upperCrossingTime_lt_bddAbove (hab : a < b) : BddAbove {n | upperCrossingTime a b f N n ω < N} := by obtain ⟨k, hk⟩ := exists_upperCrossingTime_eq f N ω hab refine ⟨k, fun n (hn : upperCrossingTime a b f N n ω < N) => ?_⟩ by_contra hn' exact hn.ne (upperCrossingTime_stabilize (not_le.1 hn').le hk) theorem upperCrossingTime_lt_nonempty (hN : 0 < N) : {n | upperCrossingTime a b f N n ω < N}.Nonempty := ⟨0, hN⟩ theorem upperCrossingTime_bound_eq (f : ℕ → Ω → ℝ) (N : ℕ) (ω : Ω) (hab : a < b) : upperCrossingTime a b f N N ω = N := by by_cases hN' : N < Nat.find (exists_upperCrossingTime_eq f N ω hab) · refine le_antisymm upperCrossingTime_le ?_ have hmono : StrictMonoOn (fun n => upperCrossingTime a b f N n ω) (Set.Iic (Nat.find (exists_upperCrossingTime_eq f N ω hab)).pred) := by refine strictMonoOn_Iic_of_lt_succ fun m hm => upperCrossingTime_lt_succ hab ?_ rw [Nat.lt_pred_iff] at hm convert Nat.find_min _ hm convert StrictMonoOn.Iic_id_le hmono N (Nat.le_sub_one_of_lt hN') · rw [not_lt] at hN' exact upperCrossingTime_stabilize hN' (Nat.find_spec (exists_upperCrossingTime_eq f N ω hab)) theorem upperCrossingTime_eq_of_bound_le (hab : a < b) (hn : N ≤ n) : upperCrossingTime a b f N n ω = N := le_antisymm upperCrossingTime_le (le_trans (upperCrossingTime_bound_eq f N ω hab).symm.le (upperCrossingTime_mono hn)) variable {ℱ : Filtration ℕ m0} theorem Adapted.isStoppingTime_crossing (hf : Adapted ℱ f) : IsStoppingTime ℱ (upperCrossingTime a b f N n) ∧ IsStoppingTime ℱ (lowerCrossingTime a b f N n) := by induction' n with k ih · refine ⟨isStoppingTime_const _ 0, ?_⟩ simp [hitting_isStoppingTime hf measurableSet_Iic] · obtain ⟨_, ih₂⟩ := ih have : IsStoppingTime ℱ (upperCrossingTime a b f N (k + 1)) := by intro n simp_rw [upperCrossingTime_succ_eq] exact isStoppingTime_hitting_isStoppingTime ih₂ (fun _ => lowerCrossingTime_le) measurableSet_Ici hf _ refine ⟨this, ?_⟩ intro n exact isStoppingTime_hitting_isStoppingTime this (fun _ => upperCrossingTime_le) measurableSet_Iic hf _ theorem Adapted.isStoppingTime_upperCrossingTime (hf : Adapted ℱ f) : IsStoppingTime ℱ (upperCrossingTime a b f N n) := hf.isStoppingTime_crossing.1 theorem Adapted.isStoppingTime_lowerCrossingTime (hf : Adapted ℱ f) : IsStoppingTime ℱ (lowerCrossingTime a b f N n) := hf.isStoppingTime_crossing.2 /-- `upcrossingStrat a b f N n` is 1 if `n` is between a consecutive pair of lower and upper crossings and is 0 otherwise. `upcrossingStrat` is shifted by one index so that it is adapted rather than predictable. -/ noncomputable def upcrossingStrat (a b : ℝ) (f : ℕ → Ω → ℝ) (N n : ℕ) (ω : Ω) : ℝ := ∑ k ∈ Finset.range N, (Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)).indicator 1 n theorem upcrossingStrat_nonneg : 0 ≤ upcrossingStrat a b f N n ω := Finset.sum_nonneg fun _ _ => Set.indicator_nonneg (fun _ _ => zero_le_one) _ theorem upcrossingStrat_le_one : upcrossingStrat a b f N n ω ≤ 1 := by rw [upcrossingStrat, ← Finset.indicator_biUnion_apply] · exact Set.indicator_le_self' (fun _ _ => zero_le_one) _ intro i _ j _ hij simp only [Set.Ico_disjoint_Ico] obtain hij' | hij' := lt_or_gt_of_ne hij · rw [min_eq_left (upperCrossingTime_mono (Nat.succ_le_succ hij'.le) : upperCrossingTime a b f N _ ω ≤ upperCrossingTime a b f N _ ω), max_eq_right (lowerCrossingTime_mono hij'.le : lowerCrossingTime a b f N _ _ ≤ lowerCrossingTime _ _ _ _ _ _)] refine le_trans upperCrossingTime_le_lowerCrossingTime (lowerCrossingTime_mono (Nat.succ_le_of_lt hij')) · rw [gt_iff_lt] at hij' rw [min_eq_right (upperCrossingTime_mono (Nat.succ_le_succ hij'.le) : upperCrossingTime a b f N _ ω ≤ upperCrossingTime a b f N _ ω), max_eq_left (lowerCrossingTime_mono hij'.le : lowerCrossingTime a b f N _ _ ≤ lowerCrossingTime _ _ _ _ _ _)] refine le_trans upperCrossingTime_le_lowerCrossingTime (lowerCrossingTime_mono (Nat.succ_le_of_lt hij')) theorem Adapted.upcrossingStrat_adapted (hf : Adapted ℱ f) : Adapted ℱ (upcrossingStrat a b f N) := by intro n change StronglyMeasurable[ℱ n] fun ω => ∑ k ∈ Finset.range N, ({n | lowerCrossingTime a b f N k ω ≤ n} ∩ {n | n < upperCrossingTime a b f N (k + 1) ω}).indicator 1 n refine Finset.stronglyMeasurable_sum _ fun i _ => stronglyMeasurable_const.indicator ((hf.isStoppingTime_lowerCrossingTime n).inter ?_) simp_rw [← not_le] exact (hf.isStoppingTime_upperCrossingTime n).compl theorem Submartingale.sum_upcrossingStrat_mul [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (a b : ℝ) (N : ℕ) : Submartingale (fun n : ℕ => ∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) ℱ μ := hf.sum_mul_sub hf.adapted.upcrossingStrat_adapted (fun _ _ => upcrossingStrat_le_one) fun _ _ => upcrossingStrat_nonneg theorem Submartingale.sum_sub_upcrossingStrat_mul [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (a b : ℝ) (N : ℕ) : Submartingale (fun n : ℕ => ∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)) ℱ μ := by refine hf.sum_mul_sub (fun n => (adapted_const ℱ 1 n).sub (hf.adapted.upcrossingStrat_adapted n)) (?_ : ∀ n ω, (1 - upcrossingStrat a b f N n) ω ≤ 1) ?_ · exact fun n ω => sub_le_self _ upcrossingStrat_nonneg · intro n ω simp [upcrossingStrat_le_one] theorem Submartingale.sum_mul_upcrossingStrat_le [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) : μ[∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)] ≤ μ[f n] - μ[f 0] := by have h₁ : (0 : ℝ) ≤ μ[∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)] := by have := (hf.sum_sub_upcrossingStrat_mul a b N).setIntegral_le (zero_le n) MeasurableSet.univ rw [setIntegral_univ, setIntegral_univ] at this refine le_trans ?_ this simp only [Finset.range_zero, Finset.sum_empty, integral_zero', le_refl] have h₂ : μ[∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)] = μ[∑ k ∈ Finset.range n, (f (k + 1) - f k)] - μ[∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)] := by simp only [sub_mul, one_mul, Finset.sum_sub_distrib, Pi.sub_apply, Finset.sum_apply, Pi.mul_apply] refine integral_sub (Integrable.sub (integrable_finset_sum _ fun i _ => hf.integrable _) (integrable_finset_sum _ fun i _ => hf.integrable _)) ?_ convert (hf.sum_upcrossingStrat_mul a b N).integrable n using 1 ext; simp rw [h₂, sub_nonneg] at h₁ refine le_trans h₁ ?_ simp_rw [Finset.sum_range_sub, integral_sub' (hf.integrable _) (hf.integrable _), le_refl] /-- The number of upcrossings (strictly) before time `N`. -/ noncomputable def upcrossingsBefore [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ) (N : ι) (ω : Ω) : ℕ := sSup {n | upperCrossingTime a b f N n ω < N} @[simp] theorem upcrossingsBefore_bot [Preorder ι] [OrderBot ι] [InfSet ι] {a b : ℝ} {f : ι → Ω → ℝ} {ω : Ω} : upcrossingsBefore a b f ⊥ ω = ⊥ := by simp [upcrossingsBefore] theorem upcrossingsBefore_zero : upcrossingsBefore a b f 0 ω = 0 := by simp [upcrossingsBefore] @[simp] theorem upcrossingsBefore_zero' : upcrossingsBefore a b f 0 = 0 := by ext ω; exact upcrossingsBefore_zero theorem upperCrossingTime_lt_of_le_upcrossingsBefore (hN : 0 < N) (hab : a < b) (hn : n ≤ upcrossingsBefore a b f N ω) : upperCrossingTime a b f N n ω < N := haveI : upperCrossingTime a b f N (upcrossingsBefore a b f N ω) ω < N := (upperCrossingTime_lt_nonempty hN).csSup_mem ((OrderBot.bddBelow _).finite_of_bddAbove (upperCrossingTime_lt_bddAbove hab)) lt_of_le_of_lt (upperCrossingTime_mono hn) this theorem upperCrossingTime_eq_of_upcrossingsBefore_lt (hab : a < b) (hn : upcrossingsBefore a b f N ω < n) : upperCrossingTime a b f N n ω = N := by refine le_antisymm upperCrossingTime_le (not_lt.1 ?_) convert not_mem_of_csSup_lt hn (upperCrossingTime_lt_bddAbove hab) using 1 theorem upcrossingsBefore_le (f : ℕ → Ω → ℝ) (ω : Ω) (hab : a < b) : upcrossingsBefore a b f N ω ≤ N := by by_cases hN : N = 0 · subst hN rw [upcrossingsBefore_zero] · refine csSup_le ⟨0, zero_lt_iff.2 hN⟩ fun n (hn : _ < N) => ?_ by_contra hnN exact hn.ne (upperCrossingTime_eq_of_bound_le hab (not_le.1 hnN).le) theorem crossing_eq_crossing_of_lowerCrossingTime_lt {M : ℕ} (hNM : N ≤ M) (h : lowerCrossingTime a b f N n ω < N) : upperCrossingTime a b f M n ω = upperCrossingTime a b f N n ω ∧ lowerCrossingTime a b f M n ω = lowerCrossingTime a b f N n ω := by have h' : upperCrossingTime a b f N n ω < N := lt_of_le_of_lt upperCrossingTime_le_lowerCrossingTime h induction' n with k ih · simp only [upperCrossingTime_zero, bot_eq_zero', eq_self_iff_true, lowerCrossingTime_zero, true_and, eq_comm] refine hitting_eq_hitting_of_exists hNM ?_ rw [lowerCrossingTime, hitting_lt_iff] at h · obtain ⟨j, hj₁, hj₂⟩ := h exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩ · exact le_rfl · specialize ih (lt_of_le_of_lt (lowerCrossingTime_mono (Nat.le_succ _)) h) (lt_of_le_of_lt (upperCrossingTime_mono (Nat.le_succ _)) h') have : upperCrossingTime a b f M k.succ ω = upperCrossingTime a b f N k.succ ω := by rw [upperCrossingTime_succ_eq, hitting_lt_iff] at h' · simp only [upperCrossingTime_succ_eq] obtain ⟨j, hj₁, hj₂⟩ := h' rw [eq_comm, ih.2] exact hitting_eq_hitting_of_exists hNM ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩ · exact le_rfl refine ⟨this, ?_⟩ simp only [lowerCrossingTime, eq_comm, this, Nat.succ_eq_add_one] refine hitting_eq_hitting_of_exists hNM ?_ rw [lowerCrossingTime, hitting_lt_iff _ le_rfl] at h obtain ⟨j, hj₁, hj₂⟩ := h exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩ theorem crossing_eq_crossing_of_upperCrossingTime_lt {M : ℕ} (hNM : N ≤ M) (h : upperCrossingTime a b f N (n + 1) ω < N) : upperCrossingTime a b f M (n + 1) ω = upperCrossingTime a b f N (n + 1) ω ∧ lowerCrossingTime a b f M n ω = lowerCrossingTime a b f N n ω := by have := (crossing_eq_crossing_of_lowerCrossingTime_lt hNM (lt_of_le_of_lt lowerCrossingTime_le_upperCrossingTime_succ h)).2 refine ⟨?_, this⟩ rw [upperCrossingTime_succ_eq, upperCrossingTime_succ_eq, eq_comm, this] refine hitting_eq_hitting_of_exists hNM ?_ rw [upperCrossingTime_succ_eq, hitting_lt_iff] at h · obtain ⟨j, hj₁, hj₂⟩ := h exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩ · exact le_rfl theorem upperCrossingTime_eq_upperCrossingTime_of_lt {M : ℕ} (hNM : N ≤ M) (h : upperCrossingTime a b f N n ω < N) : upperCrossingTime a b f M n ω = upperCrossingTime a b f N n ω := by cases n · simp · exact (crossing_eq_crossing_of_upperCrossingTime_lt hNM h).1 theorem upcrossingsBefore_mono (hab : a < b) : Monotone fun N ω => upcrossingsBefore a b f N ω := by intro N M hNM ω simp only [upcrossingsBefore] by_cases hemp : {n : ℕ | upperCrossingTime a b f N n ω < N}.Nonempty · refine csSup_le_csSup (upperCrossingTime_lt_bddAbove hab) hemp fun n hn => ?_ rw [Set.mem_setOf_eq, upperCrossingTime_eq_upperCrossingTime_of_lt hNM hn] exact lt_of_lt_of_le hn hNM · rw [Set.not_nonempty_iff_eq_empty] at hemp simp [hemp, csSup_empty, bot_eq_zero', zero_le'] theorem upcrossingsBefore_lt_of_exists_upcrossing (hab : a < b) {N₁ N₂ : ℕ} (hN₁ : N ≤ N₁) (hN₁' : f N₁ ω < a) (hN₂ : N₁ ≤ N₂) (hN₂' : b < f N₂ ω) : upcrossingsBefore a b f N ω < upcrossingsBefore a b f (N₂ + 1) ω := by refine lt_of_lt_of_le (Nat.lt_succ_self _) (le_csSup (upperCrossingTime_lt_bddAbove hab) ?_) rw [Set.mem_setOf_eq, upperCrossingTime_succ_eq, hitting_lt_iff _ le_rfl] refine ⟨N₂, ⟨?_, Nat.lt_succ_self _⟩, hN₂'.le⟩ rw [lowerCrossingTime, hitting_le_iff_of_lt _ (Nat.lt_succ_self _)] refine ⟨N₁, ⟨le_trans ?_ hN₁, hN₂⟩, hN₁'.le⟩ by_cases hN : 0 < N · have : upperCrossingTime a b f N (upcrossingsBefore a b f N ω) ω < N := Nat.sSup_mem (upperCrossingTime_lt_nonempty hN) (upperCrossingTime_lt_bddAbove hab) rw [upperCrossingTime_eq_upperCrossingTime_of_lt (hN₁.trans (hN₂.trans <| Nat.le_succ _)) this] exact this.le · rw [not_lt, Nat.le_zero] at hN rw [hN, upcrossingsBefore_zero, upperCrossingTime_zero, Pi.bot_apply, bot_eq_zero'] theorem lowerCrossingTime_lt_of_lt_upcrossingsBefore (hN : 0 < N) (hab : a < b) (hn : n < upcrossingsBefore a b f N ω) : lowerCrossingTime a b f N n ω < N := lt_of_le_of_lt lowerCrossingTime_le_upperCrossingTime_succ (upperCrossingTime_lt_of_le_upcrossingsBefore hN hab hn) theorem le_sub_of_le_upcrossingsBefore (hN : 0 < N) (hab : a < b) (hn : n < upcrossingsBefore a b f N ω) : b - a ≤ stoppedValue f (upperCrossingTime a b f N (n + 1)) ω - stoppedValue f (lowerCrossingTime a b f N n) ω := sub_le_sub (stoppedValue_upperCrossingTime (upperCrossingTime_lt_of_le_upcrossingsBefore hN hab hn).ne) (stoppedValue_lowerCrossingTime (lowerCrossingTime_lt_of_lt_upcrossingsBefore hN hab hn).ne) theorem sub_eq_zero_of_upcrossingsBefore_lt (hab : a < b) (hn : upcrossingsBefore a b f N ω < n) : stoppedValue f (upperCrossingTime a b f N (n + 1)) ω - stoppedValue f (lowerCrossingTime a b f N n) ω = 0 := by have : N ≤ upperCrossingTime a b f N n ω := by rw [upcrossingsBefore] at hn rw [← not_lt] exact fun h => not_le.2 hn (le_csSup (upperCrossingTime_lt_bddAbove hab) h) simp [stoppedValue, upperCrossingTime_stabilize' (Nat.le_succ n) this, lowerCrossingTime_stabilize' le_rfl (le_trans this upperCrossingTime_le_lowerCrossingTime)] theorem mul_upcrossingsBefore_le (hf : a ≤ f N ω) (hab : a < b) : (b - a) * upcrossingsBefore a b f N ω ≤ ∑ k ∈ Finset.range N, upcrossingStrat a b f N k ω * (f (k + 1) - f k) ω := by classical by_cases hN : N = 0 · simp [hN] simp_rw [upcrossingStrat, Finset.sum_mul, ← Set.indicator_mul_left _ _ (fun x ↦ (f (x + 1) - f x) ω), Pi.one_apply, Pi.sub_apply, one_mul] rw [Finset.sum_comm] have h₁ : ∀ k, ∑ n ∈ Finset.range N, (Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)).indicator (fun m => f (m + 1) ω - f m ω) n = stoppedValue f (upperCrossingTime a b f N (k + 1)) ω - stoppedValue f (lowerCrossingTime a b f N k) ω := by intro k rw [Finset.sum_indicator_eq_sum_filter, (_ : Finset.filter (fun i => i ∈ Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)) (Finset.range N) = Finset.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)), Finset.sum_Ico_eq_add_neg _ lowerCrossingTime_le_upperCrossingTime_succ, Finset.sum_range_sub fun n => f n ω, Finset.sum_range_sub fun n => f n ω, neg_sub, sub_add_sub_cancel] · rfl · ext i simp only [Set.mem_Ico, Finset.mem_filter, Finset.mem_range, Finset.mem_Ico, and_iff_right_iff_imp, and_imp] exact fun _ h => lt_of_lt_of_le h upperCrossingTime_le simp_rw [h₁] have h₂ : ∑ _k ∈ Finset.range (upcrossingsBefore a b f N ω), (b - a) ≤ ∑ k ∈ Finset.range N, (stoppedValue f (upperCrossingTime a b f N (k + 1)) ω - stoppedValue f (lowerCrossingTime a b f N k) ω) := by calc ∑ _k ∈ Finset.range (upcrossingsBefore a b f N ω), (b - a) ≤ ∑ k ∈ Finset.range (upcrossingsBefore a b f N ω), (stoppedValue f (upperCrossingTime a b f N (k + 1)) ω - stoppedValue f (lowerCrossingTime a b f N k) ω) := by refine Finset.sum_le_sum fun i hi => le_sub_of_le_upcrossingsBefore (zero_lt_iff.2 hN) hab ?_ rwa [Finset.mem_range] at hi _ ≤ ∑ k ∈ Finset.range N, (stoppedValue f (upperCrossingTime a b f N (k + 1)) ω - stoppedValue f (lowerCrossingTime a b f N k) ω) := by refine Finset.sum_le_sum_of_subset_of_nonneg (Finset.range_subset.2 (upcrossingsBefore_le f ω hab)) fun i _ hi => ?_ by_cases hi' : i = upcrossingsBefore a b f N ω · subst hi' simp only [stoppedValue] rw [upperCrossingTime_eq_of_upcrossingsBefore_lt hab (Nat.lt_succ_self _)] by_cases heq : lowerCrossingTime a b f N (upcrossingsBefore a b f N ω) ω = N · rw [heq, sub_self] · rw [sub_nonneg] exact le_trans (stoppedValue_lowerCrossingTime heq) hf · rw [sub_eq_zero_of_upcrossingsBefore_lt hab] rw [Finset.mem_range, not_lt] at hi exact lt_of_le_of_ne hi (Ne.symm hi') refine le_trans ?_ h₂ rw [Finset.sum_const, Finset.card_range, nsmul_eq_mul, mul_comm] theorem integral_mul_upcrossingsBefore_le_integral [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (hfN : ∀ ω, a ≤ f N ω) (hfzero : 0 ≤ f 0) (hab : a < b) : (b - a) * μ[upcrossingsBefore a b f N] ≤ μ[f N] := calc (b - a) * μ[upcrossingsBefore a b f N] ≤ μ[∑ k ∈ Finset.range N, upcrossingStrat a b f N k * (f (k + 1) - f k)] := by rw [← integral_const_mul] refine integral_mono_of_nonneg ?_ ((hf.sum_upcrossingStrat_mul a b N).integrable N) ?_ · exact Eventually.of_forall fun ω => mul_nonneg (sub_nonneg.2 hab.le) (Nat.cast_nonneg _) · filter_upwards with ω simpa using mul_upcrossingsBefore_le (hfN ω) hab _ ≤ μ[f N] - μ[f 0] := hf.sum_mul_upcrossingStrat_le _ ≤ μ[f N] := (sub_le_self_iff _).2 (integral_nonneg hfzero) theorem crossing_pos_eq (hab : a < b) : upperCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N n = upperCrossingTime a b f N n ∧ lowerCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N n = lowerCrossingTime a b f N n := by have hab' : 0 < b - a := sub_pos.2 hab have hf : ∀ ω i, b - a ≤ (f i ω - a)⁺ ↔ b ≤ f i ω := by intro i ω refine ⟨fun h => ?_, fun h => ?_⟩ · rwa [← sub_le_sub_iff_right a, ← posPart_eq_of_posPart_pos (lt_of_lt_of_le hab' h)] · rw [← sub_le_sub_iff_right a] at h rwa [posPart_eq_self.2 (le_trans hab'.le h)] have hf' (ω i) : (f i ω - a)⁺ ≤ 0 ↔ f i ω ≤ a := by rw [posPart_nonpos, sub_nonpos] induction' n with k ih · refine ⟨rfl, ?_⟩ simp +unfoldPartialApp only [lowerCrossingTime_zero, hitting, Set.mem_Icc, Set.mem_Iic] ext ω split_ifs with h₁ h₂ h₂ · simp_rw [hf'] · simp_rw [Set.mem_Iic, ← hf' _ _] at h₂ exact False.elim (h₂ h₁) · simp_rw [Set.mem_Iic, hf' _ _] at h₁ exact False.elim (h₁ h₂) · rfl · have : upperCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N (k + 1) = upperCrossingTime a b f N (k + 1) := by ext ω simp only [upperCrossingTime_succ_eq, ← ih.2, hitting, Set.mem_Ici, tsub_le_iff_right] split_ifs with h₁ h₂ h₂ · simp_rw [← sub_le_iff_le_add, hf ω] · refine False.elim (h₂ ?_) simp_all only [Set.mem_Ici, not_true_eq_false] · refine False.elim (h₁ ?_) simp_all only [Set.mem_Ici] · rfl refine ⟨this, ?_⟩ ext ω simp only [lowerCrossingTime, this, hitting, Set.mem_Iic] split_ifs with h₁ h₂ h₂ · simp_rw [hf' ω] · refine False.elim (h₂ ?_) simp_all only [Set.mem_Iic, not_true_eq_false] · refine False.elim (h₁ ?_) simp_all only [Set.mem_Iic] · rfl theorem upcrossingsBefore_pos_eq (hab : a < b) : upcrossingsBefore 0 (b - a) (fun n ω => (f n ω - a)⁺) N ω = upcrossingsBefore a b f N ω := by simp_rw [upcrossingsBefore, (crossing_pos_eq hab).1] theorem mul_integral_upcrossingsBefore_le_integral_pos_part_aux [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (hab : a < b) : (b - a) * μ[upcrossingsBefore a b f N] ≤ μ[fun ω => (f N ω - a)⁺] := by refine le_trans (le_of_eq ?_) (integral_mul_upcrossingsBefore_le_integral (hf.sub_martingale (martingale_const _ _ _)).pos (fun ω => posPart_nonneg _) (fun ω => posPart_nonneg _) (sub_pos.2 hab)) simp_rw [sub_zero, ← upcrossingsBefore_pos_eq hab] rfl /-- **Doob's upcrossing estimate**: given a real valued discrete submartingale `f` and real values `a` and `b`, we have `(b - a) * 𝔼[upcrossingsBefore a b f N] ≤ 𝔼[(f N - a)⁺]` where `upcrossingsBefore a b f N` is the number of times the process `f` crossed from below `a` to above `b` before the time `N`. -/ theorem Submartingale.mul_integral_upcrossingsBefore_le_integral_pos_part [IsFiniteMeasure μ] (a b : ℝ) (hf : Submartingale f ℱ μ) (N : ℕ) : (b - a) * μ[upcrossingsBefore a b f N] ≤ μ[fun ω => (f N ω - a)⁺] := by by_cases hab : a < b · exact mul_integral_upcrossingsBefore_le_integral_pos_part_aux hf hab · rw [not_lt, ← sub_nonpos] at hab exact le_trans (mul_nonpos_of_nonpos_of_nonneg hab (by positivity)) (integral_nonneg fun ω => posPart_nonneg _) /-! ### Variant of the upcrossing estimate Now, we would like to prove a variant of the upcrossing estimate obtained by taking the supremum over $N$ of the original upcrossing estimate. Namely, we want the inequality $$ (b - a) \sup_N \mathbb{E}[U_N(a, b)] \le \sup_N \mathbb{E}[f_N]. $$ This inequality is central for the martingale convergence theorem as it provides a uniform bound for the upcrossings. We note that on top of taking the supremum on both sides of the inequality, we had also used the monotone convergence theorem on the left hand side to take the supremum outside of the integral. To do this, we need to make sure $U_N(a, b)$ is measurable and integrable. Integrability is easy to check as $U_N(a, b) ≤ N$ and so it suffices to show measurability. Indeed, by noting that $$ U_N(a, b) = \sum_{i = 1}^N \mathbf{1}_{\{U_N(a, b) < N\}} $$ $U_N(a, b)$ is measurable as $\{U_N(a, b) < N\}$ is a measurable set since $U_N(a, b)$ is a stopping time. -/ theorem upcrossingsBefore_eq_sum (hab : a < b) : upcrossingsBefore a b f N ω = ∑ i ∈ Finset.Ico 1 (N + 1), {n | upperCrossingTime a b f N n ω < N}.indicator 1 i := by by_cases hN : N = 0 · simp [hN] rw [← Finset.sum_Ico_consecutive _ (Nat.succ_le_succ zero_le') (Nat.succ_le_succ (upcrossingsBefore_le f ω hab))] have h₁ : ∀ k ∈ Finset.Ico 1 (upcrossingsBefore a b f N ω + 1), {n : ℕ | upperCrossingTime a b f N n ω < N}.indicator 1 k = 1 := by rintro k hk rw [Finset.mem_Ico] at hk rw [Set.indicator_of_mem] · rfl · exact upperCrossingTime_lt_of_le_upcrossingsBefore (zero_lt_iff.2 hN) hab (Nat.lt_succ_iff.1 hk.2) have h₂ : ∀ k ∈ Finset.Ico (upcrossingsBefore a b f N ω + 1) (N + 1), {n : ℕ | upperCrossingTime a b f N n ω < N}.indicator 1 k = 0 := by rintro k hk rw [Finset.mem_Ico, Nat.succ_le_iff] at hk rw [Set.indicator_of_not_mem] simp only [Set.mem_setOf_eq, not_lt] exact (upperCrossingTime_eq_of_upcrossingsBefore_lt hab hk.1).symm.le rw [Finset.sum_congr rfl h₁, Finset.sum_congr rfl h₂, Finset.sum_const, Finset.sum_const, smul_eq_mul, mul_one, smul_eq_mul, mul_zero, Nat.card_Ico, Nat.add_succ_sub_one, add_zero, add_zero] theorem Adapted.measurable_upcrossingsBefore (hf : Adapted ℱ f) (hab : a < b) : Measurable (upcrossingsBefore a b f N) := by have : upcrossingsBefore a b f N = fun ω => ∑ i ∈ Finset.Ico 1 (N + 1), {n | upperCrossingTime a b f N n ω < N}.indicator 1 i := by ext ω exact upcrossingsBefore_eq_sum hab rw [this] exact Finset.measurable_sum _ fun i _ => Measurable.indicator measurable_const <| ℱ.le N _ (hf.isStoppingTime_upperCrossingTime.measurableSet_lt_of_pred N) theorem Adapted.integrable_upcrossingsBefore [IsFiniteMeasure μ] (hf : Adapted ℱ f) (hab : a < b) : Integrable (fun ω => (upcrossingsBefore a b f N ω : ℝ)) μ := haveI : ∀ᵐ ω ∂μ, ‖(upcrossingsBefore a b f N ω : ℝ)‖ ≤ N := by filter_upwards with ω rw [Real.norm_eq_abs, Nat.abs_cast, Nat.cast_le] exact upcrossingsBefore_le _ _ hab ⟨Measurable.aestronglyMeasurable (measurable_from_top.comp (hf.measurable_upcrossingsBefore hab)), hasFiniteIntegral_of_bounded this⟩ /-- The number of upcrossings of a realization of a stochastic process (`upcrossings` takes value in `ℝ≥0∞` and so is allowed to be `∞`). -/ noncomputable def upcrossings [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ) (ω : Ω) : ℝ≥0∞ := ⨆ N, (upcrossingsBefore a b f N ω : ℝ≥0∞) theorem Adapted.measurable_upcrossings (hf : Adapted ℱ f) (hab : a < b) : Measurable (upcrossings a b f) := .iSup fun _ => measurable_from_top.comp (hf.measurable_upcrossingsBefore hab) theorem upcrossings_lt_top_iff : upcrossings a b f ω < ∞ ↔ ∃ k, ∀ N, upcrossingsBefore a b f N ω ≤ k := by have : upcrossings a b f ω < ∞ ↔ ∃ k : ℝ≥0, upcrossings a b f ω ≤ k := by constructor · intro h lift upcrossings a b f ω to ℝ≥0 using h.ne with r hr exact ⟨r, le_rfl⟩ · rintro ⟨k, hk⟩ exact lt_of_le_of_lt hk ENNReal.coe_lt_top simp_rw [this, upcrossings, iSup_le_iff] constructor <;> rintro ⟨k, hk⟩ · obtain ⟨m, hm⟩ := exists_nat_ge k refine ⟨m, fun N => Nat.cast_le.1 ((hk N).trans ?_)⟩ rwa [← ENNReal.coe_natCast, ENNReal.coe_le_coe] · refine ⟨k, fun N => ?_⟩ simp only [ENNReal.coe_natCast, Nat.cast_le, hk N] /-- A variant of Doob's upcrossing estimate obtained by taking the supremum on both sides. -/ theorem Submartingale.mul_lintegral_upcrossings_le_lintegral_pos_part [IsFiniteMeasure μ] (a b : ℝ) (hf : Submartingale f ℱ μ) : ENNReal.ofReal (b - a) * ∫⁻ ω, upcrossings a b f ω ∂μ ≤ ⨆ N, ∫⁻ ω, ENNReal.ofReal ((f N ω - a)⁺) ∂μ := by by_cases hab : a < b · simp_rw [upcrossings] have : ∀ N, ∫⁻ ω, ENNReal.ofReal ((f N ω - a)⁺) ∂μ = ENNReal.ofReal (∫ ω, (f N ω - a)⁺ ∂μ) := by intro N rw [ofReal_integral_eq_lintegral_ofReal] · exact (hf.sub_martingale (martingale_const _ _ _)).pos.integrable _ · exact Eventually.of_forall fun ω => posPart_nonneg _ rw [lintegral_iSup'] · simp_rw [this, ENNReal.mul_iSup, iSup_le_iff] intro N rw [(by simp : ∫⁻ ω, upcrossingsBefore a b f N ω ∂μ = ∫⁻ ω, ↑(upcrossingsBefore a b f N ω : ℝ≥0) ∂μ), lintegral_coe_eq_integral, ← ENNReal.ofReal_mul (sub_pos.2 hab).le] · simp_rw [NNReal.coe_natCast] exact (ENNReal.ofReal_le_ofReal (hf.mul_integral_upcrossingsBefore_le_integral_pos_part a b N)).trans (le_iSup (α := ℝ≥0∞) _ N) · simp only [NNReal.coe_natCast, hf.adapted.integrable_upcrossingsBefore hab] · exact fun n => measurable_from_top.comp_aemeasurable (hf.adapted.measurable_upcrossingsBefore hab).aemeasurable · filter_upwards with ω N M hNM rw [Nat.cast_le] exact upcrossingsBefore_mono hab hNM ω · rw [not_lt, ← sub_nonpos] at hab rw [ENNReal.ofReal_of_nonpos hab, zero_mul] exact zero_le _ end MeasureTheory
Mathlib/Probability/Martingale/Upcrossing.lean
837
852
/- Copyright (c) 2015 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Multiset.ZeroCons /-! # Basic results on multisets -/ -- No algebra should be required assert_not_exists Monoid universe v open List Subtype Nat Function variable {α : Type*} {β : Type v} {γ : Type*} namespace Multiset /-! ### `Multiset.toList` -/ section ToList /-- Produces a list of the elements in the multiset using choice. -/ noncomputable def toList (s : Multiset α) := s.out @[simp, norm_cast] theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s := s.out_eq' @[simp] theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by rw [← coe_eq_zero, coe_toList] theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 := by simp @[simp] theorem toList_zero : (Multiset.toList 0 : List α) = [] := toList_eq_nil.mpr rfl @[simp] theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by rw [← mem_coe, coe_toList] @[simp] theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton] @[simp] theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] := Multiset.toList_eq_singleton_iff.2 rfl @[simp] theorem length_toList (s : Multiset α) : s.toList.length = card s := by rw [← coe_card, coe_toList] end ToList /-! ### Induction principles -/ /-- The strong induction principle for multisets. -/ @[elab_as_elim] def strongInductionOn {p : Multiset α → Sort*} (s : Multiset α) (ih : ∀ s, (∀ t < s, p t) → p s) : p s := (ih s) fun t _h => strongInductionOn t ih termination_by card s decreasing_by exact card_lt_card _h theorem strongInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) (H) : @strongInductionOn _ p s H = H s fun t _h => @strongInductionOn _ p t H := by rw [strongInductionOn] @[elab_as_elim] theorem case_strongInductionOn {p : Multiset α → Prop} (s : Multiset α) (h₀ : p 0) (h₁ : ∀ a s, (∀ t ≤ s, p t) → p (a ::ₘ s)) : p s := Multiset.strongInductionOn s fun s => Multiset.induction_on s (fun _ => h₀) fun _a _s _ ih => (h₁ _ _) fun _t h => ih _ <| lt_of_le_of_lt h <| lt_cons_self _ _ /-- Suppose that, given that `p t` can be defined on all supersets of `s` of cardinality less than `n`, one knows how to define `p s`. Then one can inductively define `p s` for all multisets `s` of cardinality less than `n`, starting from multisets of card `n` and iterating. This can be used either to define data, or to prove properties. -/ def strongDownwardInduction {p : Multiset α → Sort*} {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) (s : Multiset α) : card s ≤ n → p s := H s fun {t} ht _h => strongDownwardInduction H t ht termination_by n - card s decreasing_by simp_wf; have := (card_lt_card _h); omega theorem strongDownwardInduction_eq {p : Multiset α → Sort*} {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) (s : Multiset α) : strongDownwardInduction H s = H s fun ht _hst => strongDownwardInduction H _ ht := by rw [strongDownwardInduction] /-- Analogue of `strongDownwardInduction` with order of arguments swapped. -/ @[elab_as_elim] def strongDownwardInductionOn {p : Multiset α → Sort*} {n : ℕ} : ∀ s : Multiset α, (∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) → card s ≤ n → p s := fun s H => strongDownwardInduction H s theorem strongDownwardInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) : s.strongDownwardInductionOn H = H s fun {t} ht _h => t.strongDownwardInductionOn H ht := by dsimp only [strongDownwardInductionOn] rw [strongDownwardInduction] section Choose variable (p : α → Prop) [DecidablePred p] (l : Multiset α) /-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `chooseX p l hp` returns that `a` together with proofs of `a ∈ l` and `p a`. -/ def chooseX : ∀ _hp : ∃! a, a ∈ l ∧ p a, { a // a ∈ l ∧ p a } := Quotient.recOn l (fun l' ex_unique => List.chooseX p l' (ExistsUnique.exists ex_unique)) (by intros a b _ funext hp suffices all_equal : ∀ x y : { t // t ∈ b ∧ p t }, x = y by apply all_equal rintro ⟨x, px⟩ ⟨y, py⟩ rcases hp with ⟨z, ⟨_z_mem_l, _pz⟩, z_unique⟩ congr calc x = z := z_unique x px _ = y := (z_unique y py).symm ) /-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `choose p l hp` returns that `a`. -/ def choose (hp : ∃! a, a ∈ l ∧ p a) : α := chooseX p l hp theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) := (chooseX p l hp).property theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l := (choose_spec _ _ _).1 theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) := (choose_spec _ _ _).2 end Choose variable (α) in /-- The equivalence between lists and multisets of a subsingleton type. -/ def subsingletonEquiv [Subsingleton α] : List α ≃ Multiset α where toFun := ofList invFun := (Quot.lift id) fun (a b : List α) (h : a ~ b) => (List.ext_get h.length_eq) fun _ _ _ => Subsingleton.elim _ _ left_inv _ := rfl right_inv m := Quot.inductionOn m fun _ => rfl @[simp] theorem coe_subsingletonEquiv [Subsingleton α] : (subsingletonEquiv α : List α → Multiset α) = ofList := rfl section SizeOf set_option linter.deprecated false in @[deprecated "Deprecated without replacement." (since := "2025-02-07")] theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Multiset α} (hx : x ∈ s) : SizeOf.sizeOf x < SizeOf.sizeOf s := by induction s using Quot.inductionOn exact List.sizeOf_lt_sizeOf_of_mem hx end SizeOf end Multiset
Mathlib/Data/Multiset/Basic.lean
2,561
2,566
/- Copyright (c) 2016 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro -/ import Mathlib.Algebra.Order.Group.Abs import Mathlib.Algebra.Order.Ring.Basic import Mathlib.Algebra.Order.Ring.Int import Mathlib.Algebra.Ring.Divisibility.Basic import Mathlib.Algebra.Ring.Int.Units import Mathlib.Data.Nat.Cast.Order.Ring /-! # Absolute values in linear ordered rings. -/ variable {α : Type*} section LinearOrderedAddCommGroup variable [CommGroup α] [LinearOrder α] [IsOrderedMonoid α] @[to_additive] lemma mabs_zpow (n : ℤ) (a : α) : |a ^ n|ₘ = |a|ₘ ^ |n| := by obtain n0 | n0 := le_total 0 n · obtain ⟨n, rfl⟩ := Int.eq_ofNat_of_zero_le n0 simp only [mabs_pow, zpow_natCast, Nat.abs_cast] · obtain ⟨m, h⟩ := Int.eq_ofNat_of_zero_le (neg_nonneg.2 n0) rw [← mabs_inv, ← zpow_neg, ← abs_neg, h, zpow_natCast, Nat.abs_cast, zpow_natCast] exact mabs_pow m _ end LinearOrderedAddCommGroup lemma odd_abs [LinearOrder α] [Ring α] {a : α} : Odd (abs a) ↔ Odd a := by rcases abs_choice a with h | h <;> simp only [h, odd_neg] section LinearOrderedRing variable [Ring α] [LinearOrder α] [IsStrictOrderedRing α] {n : ℕ} {a b : α} @[simp] lemma abs_one : |(1 : α)| = 1 := abs_of_pos zero_lt_one lemma abs_two : |(2 : α)| = 2 := abs_of_pos zero_lt_two lemma abs_mul (a b : α) : |a * b| = |a| * |b| := by rw [abs_eq (mul_nonneg (abs_nonneg a) (abs_nonneg b))] rcases le_total a 0 with ha | ha <;> rcases le_total b 0 with hb | hb <;> simp only [abs_of_nonpos, abs_of_nonneg, true_or, or_true, eq_self_iff_true, neg_mul, mul_neg, neg_neg, *] /-- `abs` as a `MonoidWithZeroHom`. -/ def absHom : α →*₀ α where toFun := abs map_zero' := abs_zero map_one' := abs_one map_mul' := abs_mul @[simp] lemma abs_pow (a : α) (n : ℕ) : |a ^ n| = |a| ^ n := (absHom.toMonoidHom : α →* α).map_pow _ _ lemma pow_abs (a : α) (n : ℕ) : |a| ^ n = |a ^ n| := (abs_pow a n).symm lemma Even.pow_abs (hn : Even n) (a : α) : |a| ^ n = a ^ n := by rw [← abs_pow, abs_eq_self]; exact hn.pow_nonneg _ lemma abs_neg_one_pow (n : ℕ) : |(-1 : α) ^ n| = 1 := by rw [← pow_abs, abs_neg, abs_one, one_pow] lemma abs_pow_eq_one (a : α) (h : n ≠ 0) : |a ^ n| = 1 ↔ |a| = 1 := by convert pow_left_inj₀ (abs_nonneg a) zero_le_one h exacts [(pow_abs _ _).symm, (one_pow _).symm] omit [IsStrictOrderedRing α] in @[simp] lemma abs_mul_abs_self (a : α) : |a| * |a| = a * a := abs_by_cases (fun x => x * x = a * a) rfl (neg_mul_neg a a) @[simp] lemma abs_mul_self (a : α) : |a * a| = a * a := by rw [abs_mul, abs_mul_abs_self] lemma abs_eq_iff_mul_self_eq : |a| = |b| ↔ a * a = b * b := by rw [← abs_mul_abs_self, ← abs_mul_abs_self b] exact (mul_self_inj (abs_nonneg a) (abs_nonneg b)).symm lemma abs_lt_iff_mul_self_lt : |a| < |b| ↔ a * a < b * b := by rw [← abs_mul_abs_self, ← abs_mul_abs_self b] exact mul_self_lt_mul_self_iff (abs_nonneg a) (abs_nonneg b) lemma abs_le_iff_mul_self_le : |a| ≤ |b| ↔ a * a ≤ b * b := by rw [← abs_mul_abs_self, ← abs_mul_abs_self b] exact mul_self_le_mul_self_iff (abs_nonneg a) (abs_nonneg b) lemma abs_le_one_iff_mul_self_le_one : |a| ≤ 1 ↔ a * a ≤ 1 := by simpa only [abs_one, one_mul] using abs_le_iff_mul_self_le (a := a) (b := 1) omit [IsStrictOrderedRing α] in @[simp] lemma sq_abs (a : α) : |a| ^ 2 = a ^ 2 := by simpa only [sq] using abs_mul_abs_self a
lemma abs_sq (x : α) : |x ^ 2| = x ^ 2 := by simpa only [sq] using abs_mul_self x
Mathlib/Algebra/Order/Ring/Abs.lean
95
97
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Floris van Doorn -/ import Mathlib.Algebra.Order.SuccPred import Mathlib.Data.Sum.Order import Mathlib.SetTheory.Cardinal.Basic import Mathlib.Tactic.PPWithUniv /-! # Ordinals Ordinals are defined as equivalences of well-ordered sets under order isomorphism. They are endowed with a total order, where an ordinal is smaller than another one if it embeds into it as an initial segment (or, equivalently, in any way). This total order is well founded. ## Main definitions * `Ordinal`: the type of ordinals (in a given universe) * `Ordinal.type r`: given a well-founded order `r`, this is the corresponding ordinal * `Ordinal.typein r a`: given a well-founded order `r` on a type `α`, and `a : α`, the ordinal corresponding to all elements smaller than `a`. * `enum r ⟨o, h⟩`: given a well-order `r` on a type `α`, and an ordinal `o` strictly smaller than the ordinal corresponding to `r` (this is the assumption `h`), returns the `o`-th element of `α`. In other words, the elements of `α` can be enumerated using ordinals up to `type r`. * `Ordinal.card o`: the cardinality of an ordinal `o`. * `Ordinal.lift` lifts an ordinal in universe `u` to an ordinal in universe `max u v`. For a version registering additionally that this is an initial segment embedding, see `Ordinal.liftInitialSeg`. For a version registering that it is a principal segment embedding if `u < v`, see `Ordinal.liftPrincipalSeg`. * `Ordinal.omega0` or `ω` is the order type of `ℕ`. It is called this to match `Cardinal.aleph0` and so that the omega function can be named `Ordinal.omega`. This definition is universe polymorphic: `Ordinal.omega0.{u} : Ordinal.{u}` (contrast with `ℕ : Type`, which lives in a specific universe). In some cases the universe level has to be given explicitly. * `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that every element of `o₁` is smaller than every element of `o₂`. The main properties of addition (and the other operations on ordinals) are stated and proved in `Mathlib/SetTheory/Ordinal/Arithmetic.lean`. Here, we only introduce it and prove its basic properties to deduce the fact that the order on ordinals is total (and well founded). * `succ o` is the successor of the ordinal `o`. * `Cardinal.ord c`: when `c` is a cardinal, `ord c` is the smallest ordinal with this cardinality. It is the canonical way to represent a cardinal with an ordinal. A conditionally complete linear order with bot structure is registered on ordinals, where `⊥` is `0`, the ordinal corresponding to the empty type, and `Inf` is the minimum for nonempty sets and `0` for the empty set by convention. ## Notations * `ω` is a notation for the first infinite ordinal in the locale `Ordinal`. -/ assert_not_exists Module Field noncomputable section open Function Cardinal Set Equiv Order open scoped Cardinal InitialSeg universe u v w variable {α : Type u} {β : Type v} {γ : Type w} {r : α → α → Prop} {s : β → β → Prop} {t : γ → γ → Prop} /-! ### Definition of ordinals -/ /-- Bundled structure registering a well order on a type. Ordinals will be defined as a quotient of this type. -/ structure WellOrder : Type (u + 1) where /-- The underlying type of the order. -/ α : Type u /-- The underlying relation of the order. -/ r : α → α → Prop /-- The proposition that `r` is a well-ordering for `α`. -/ wo : IsWellOrder α r attribute [instance] WellOrder.wo namespace WellOrder instance inhabited : Inhabited WellOrder := ⟨⟨PEmpty, _, inferInstanceAs (IsWellOrder PEmpty EmptyRelation)⟩⟩ end WellOrder /-- Equivalence relation on well orders on arbitrary types in universe `u`, given by order isomorphism. -/ instance Ordinal.isEquivalent : Setoid WellOrder where r := fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≃r s) iseqv := ⟨fun _ => ⟨RelIso.refl _⟩, fun ⟨e⟩ => ⟨e.symm⟩, fun ⟨e₁⟩ ⟨e₂⟩ => ⟨e₁.trans e₂⟩⟩ /-- `Ordinal.{u}` is the type of well orders in `Type u`, up to order isomorphism. -/ @[pp_with_univ] def Ordinal : Type (u + 1) := Quotient Ordinal.isEquivalent /-- A "canonical" type order-isomorphic to the ordinal `o`, living in the same universe. This is defined through the axiom of choice. Use this over `Iio o` only when it is paramount to have a `Type u` rather than a `Type (u + 1)`. -/ def Ordinal.toType (o : Ordinal.{u}) : Type u := o.out.α instance hasWellFounded_toType (o : Ordinal) : WellFoundedRelation o.toType := ⟨o.out.r, o.out.wo.wf⟩ instance linearOrder_toType (o : Ordinal) : LinearOrder o.toType := @IsWellOrder.linearOrder _ o.out.r o.out.wo instance wellFoundedLT_toType_lt (o : Ordinal) : WellFoundedLT o.toType := o.out.wo.toIsWellFounded namespace Ordinal noncomputable instance (o : Ordinal) : SuccOrder o.toType := SuccOrder.ofLinearWellFoundedLT o.toType /-! ### Basic properties of the order type -/ /-- The order type of a well order is an ordinal. -/ def type (r : α → α → Prop) [wo : IsWellOrder α r] : Ordinal := ⟦⟨α, r, wo⟩⟧ /-- `typeLT α` is an abbreviation for the order type of the `<` relation of `α`. -/ scoped notation "typeLT " α:70 => @Ordinal.type α (· < ·) inferInstance instance zero : Zero Ordinal := ⟨type <| @EmptyRelation PEmpty⟩ instance inhabited : Inhabited Ordinal := ⟨0⟩ instance one : One Ordinal := ⟨type <| @EmptyRelation PUnit⟩ @[simp] theorem type_toType (o : Ordinal) : typeLT o.toType = o := o.out_eq theorem type_eq {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] : type r = type s ↔ Nonempty (r ≃r s) := Quotient.eq' theorem _root_.RelIso.ordinal_type_eq {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (h : r ≃r s) : type r = type s := type_eq.2 ⟨h⟩ theorem type_eq_zero_of_empty (r) [IsWellOrder α r] [IsEmpty α] : type r = 0 := (RelIso.relIsoOfIsEmpty r _).ordinal_type_eq @[simp] theorem type_eq_zero_iff_isEmpty [IsWellOrder α r] : type r = 0 ↔ IsEmpty α := ⟨fun h => let ⟨s⟩ := type_eq.1 h s.toEquiv.isEmpty, @type_eq_zero_of_empty α r _⟩ theorem type_ne_zero_iff_nonempty [IsWellOrder α r] : type r ≠ 0 ↔ Nonempty α := by simp theorem type_ne_zero_of_nonempty (r) [IsWellOrder α r] [h : Nonempty α] : type r ≠ 0 := type_ne_zero_iff_nonempty.2 h theorem type_pEmpty : type (@EmptyRelation PEmpty) = 0 := rfl theorem type_empty : type (@EmptyRelation Empty) = 0 := type_eq_zero_of_empty _ theorem type_eq_one_of_unique (r) [IsWellOrder α r] [Nonempty α] [Subsingleton α] : type r = 1 := by cases nonempty_unique α exact (RelIso.ofUniqueOfIrrefl r _).ordinal_type_eq @[simp] theorem type_eq_one_iff_unique [IsWellOrder α r] : type r = 1 ↔ Nonempty (Unique α) := ⟨fun h ↦ let ⟨s⟩ := type_eq.1 h; ⟨s.toEquiv.unique⟩, fun ⟨_⟩ ↦ type_eq_one_of_unique r⟩ theorem type_pUnit : type (@EmptyRelation PUnit) = 1 := rfl theorem type_unit : type (@EmptyRelation Unit) = 1 := rfl @[simp] theorem toType_empty_iff_eq_zero {o : Ordinal} : IsEmpty o.toType ↔ o = 0 := by rw [← @type_eq_zero_iff_isEmpty o.toType (· < ·), type_toType] instance isEmpty_toType_zero : IsEmpty (toType 0) := toType_empty_iff_eq_zero.2 rfl @[simp] theorem toType_nonempty_iff_ne_zero {o : Ordinal} : Nonempty o.toType ↔ o ≠ 0 := by rw [← @type_ne_zero_iff_nonempty o.toType (· < ·), type_toType] protected theorem one_ne_zero : (1 : Ordinal) ≠ 0 := type_ne_zero_of_nonempty _ instance nontrivial : Nontrivial Ordinal.{u} := ⟨⟨1, 0, Ordinal.one_ne_zero⟩⟩ /-- `Quotient.inductionOn` specialized to ordinals. Not to be confused with well-founded recursion `Ordinal.induction`. -/ @[elab_as_elim] theorem inductionOn {C : Ordinal → Prop} (o : Ordinal) (H : ∀ (α r) [IsWellOrder α r], C (type r)) : C o := Quot.inductionOn o fun ⟨α, r, wo⟩ => @H α r wo /-- `Quotient.inductionOn₂` specialized to ordinals. Not to be confused with well-founded recursion `Ordinal.induction`. -/ @[elab_as_elim] theorem inductionOn₂ {C : Ordinal → Ordinal → Prop} (o₁ o₂ : Ordinal) (H : ∀ (α r) [IsWellOrder α r] (β s) [IsWellOrder β s], C (type r) (type s)) : C o₁ o₂ := Quotient.inductionOn₂ o₁ o₂ fun ⟨α, r, wo₁⟩ ⟨β, s, wo₂⟩ => @H α r wo₁ β s wo₂ /-- `Quotient.inductionOn₃` specialized to ordinals. Not to be confused with well-founded recursion `Ordinal.induction`. -/ @[elab_as_elim] theorem inductionOn₃ {C : Ordinal → Ordinal → Ordinal → Prop} (o₁ o₂ o₃ : Ordinal) (H : ∀ (α r) [IsWellOrder α r] (β s) [IsWellOrder β s] (γ t) [IsWellOrder γ t], C (type r) (type s) (type t)) : C o₁ o₂ o₃ := Quotient.inductionOn₃ o₁ o₂ o₃ fun ⟨α, r, wo₁⟩ ⟨β, s, wo₂⟩ ⟨γ, t, wo₃⟩ => @H α r wo₁ β s wo₂ γ t wo₃ open Classical in /-- To prove a result on ordinals, it suffices to prove it for order types of well-orders. -/ @[elab_as_elim] theorem inductionOnWellOrder {C : Ordinal → Prop} (o : Ordinal) (H : ∀ (α) [LinearOrder α] [WellFoundedLT α], C (typeLT α)) : C o := inductionOn o fun α r wo ↦ @H α (linearOrderOfSTO r) wo.toIsWellFounded open Classical in /-- To define a function on ordinals, it suffices to define them on order types of well-orders. Since `LinearOrder` is data-carrying, `liftOnWellOrder_type` is not a definitional equality, unlike `Quotient.liftOn_mk` which is always def-eq. -/ def liftOnWellOrder {δ : Sort v} (o : Ordinal) (f : ∀ (α) [LinearOrder α] [WellFoundedLT α], δ) (c : ∀ (α) [LinearOrder α] [WellFoundedLT α] (β) [LinearOrder β] [WellFoundedLT β], typeLT α = typeLT β → f α = f β) : δ := Quotient.liftOn o (fun w ↦ @f w.α (linearOrderOfSTO w.r) w.wo.toIsWellFounded) fun w₁ w₂ h ↦ @c w₁.α (linearOrderOfSTO w₁.r) w₁.wo.toIsWellFounded w₂.α (linearOrderOfSTO w₂.r) w₂.wo.toIsWellFounded (Quotient.sound h) @[simp] theorem liftOnWellOrder_type {δ : Sort v} (f : ∀ (α) [LinearOrder α] [WellFoundedLT α], δ) (c : ∀ (α) [LinearOrder α] [WellFoundedLT α] (β) [LinearOrder β] [WellFoundedLT β], typeLT α = typeLT β → f α = f β) {γ} [LinearOrder γ] [WellFoundedLT γ] : liftOnWellOrder (typeLT γ) f c = f γ := by change Quotient.liftOn' ⟦_⟧ _ _ = _ rw [Quotient.liftOn'_mk] congr exact LinearOrder.ext_lt fun _ _ ↦ Iff.rfl /-! ### The order on ordinals -/ /-- For `Ordinal`: * less-equal is defined such that well orders `r` and `s` satisfy `type r ≤ type s` if there exists a function embedding `r` as an *initial* segment of `s`. * less-than is defined such that well orders `r` and `s` satisfy `type r < type s` if there exists a function embedding `r` as a *principal* segment of `s`. Note that most of the relevant results on initial and principal segments are proved in the `Order.InitialSeg` file. -/ instance partialOrder : PartialOrder Ordinal where le a b := Quotient.liftOn₂ a b (fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≼i s)) fun _ _ _ _ ⟨f⟩ ⟨g⟩ => propext ⟨fun ⟨h⟩ => ⟨f.symm.toInitialSeg.trans <| h.trans g.toInitialSeg⟩, fun ⟨h⟩ => ⟨f.toInitialSeg.trans <| h.trans g.symm.toInitialSeg⟩⟩ lt a b := Quotient.liftOn₂ a b (fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≺i s)) fun _ _ _ _ ⟨f⟩ ⟨g⟩ => propext ⟨fun ⟨h⟩ => ⟨PrincipalSeg.relIsoTrans f.symm <| h.transRelIso g⟩, fun ⟨h⟩ => ⟨PrincipalSeg.relIsoTrans f <| h.transRelIso g.symm⟩⟩ le_refl := Quot.ind fun ⟨_, _, _⟩ => ⟨InitialSeg.refl _⟩ le_trans a b c := Quotient.inductionOn₃ a b c fun _ _ _ ⟨f⟩ ⟨g⟩ => ⟨f.trans g⟩ lt_iff_le_not_le a b := Quotient.inductionOn₂ a b fun _ _ => ⟨fun ⟨f⟩ => ⟨⟨f⟩, fun ⟨g⟩ => (f.transInitial g).irrefl⟩, fun ⟨⟨f⟩, h⟩ => f.principalSumRelIso.recOn (fun g => ⟨g⟩) fun g => (h ⟨g.symm.toInitialSeg⟩).elim⟩ le_antisymm a b := Quotient.inductionOn₂ a b fun _ _ ⟨h₁⟩ ⟨h₂⟩ => Quot.sound ⟨InitialSeg.antisymm h₁ h₂⟩ instance : LinearOrder Ordinal := {inferInstanceAs (PartialOrder Ordinal) with le_total := fun a b => Quotient.inductionOn₂ a b fun ⟨_, r, _⟩ ⟨_, s, _⟩ => (InitialSeg.total r s).recOn (fun f => Or.inl ⟨f⟩) fun f => Or.inr ⟨f⟩ toDecidableLE := Classical.decRel _ } theorem _root_.InitialSeg.ordinal_type_le {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (h : r ≼i s) : type r ≤ type s := ⟨h⟩ theorem _root_.RelEmbedding.ordinal_type_le {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (h : r ↪r s) : type r ≤ type s := ⟨h.collapse⟩ theorem _root_.PrincipalSeg.ordinal_type_lt {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (h : r ≺i s) : type r < type s := ⟨h⟩ @[simp] protected theorem zero_le (o : Ordinal) : 0 ≤ o := inductionOn o fun _ r _ => (InitialSeg.ofIsEmpty _ r).ordinal_type_le instance : OrderBot Ordinal where bot := 0 bot_le := Ordinal.zero_le @[simp] theorem bot_eq_zero : (⊥ : Ordinal) = 0 := rfl instance instIsEmptyIioZero : IsEmpty (Iio (0 : Ordinal)) := by simp [← bot_eq_zero] @[simp] protected theorem le_zero {o : Ordinal} : o ≤ 0 ↔ o = 0 := le_bot_iff protected theorem pos_iff_ne_zero {o : Ordinal} : 0 < o ↔ o ≠ 0 := bot_lt_iff_ne_bot protected theorem not_lt_zero (o : Ordinal) : ¬o < 0 := not_lt_bot theorem eq_zero_or_pos : ∀ a : Ordinal, a = 0 ∨ 0 < a := eq_bot_or_bot_lt instance : ZeroLEOneClass Ordinal := ⟨Ordinal.zero_le _⟩ instance instNeZeroOne : NeZero (1 : Ordinal) := ⟨Ordinal.one_ne_zero⟩ theorem type_le_iff {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] : type r ≤ type s ↔ Nonempty (r ≼i s) := Iff.rfl theorem type_le_iff' {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] : type r ≤ type s ↔ Nonempty (r ↪r s) := ⟨fun ⟨f⟩ => ⟨f⟩, fun ⟨f⟩ => ⟨f.collapse⟩⟩ theorem type_lt_iff {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] : type r < type s ↔ Nonempty (r ≺i s) := Iff.rfl /-- Given two ordinals `α ≤ β`, then `initialSegToType α β` is the initial segment embedding of `α.toType` into `β.toType`. -/ def initialSegToType {α β : Ordinal} (h : α ≤ β) : α.toType ≤i β.toType := by apply Classical.choice (type_le_iff.mp _) rwa [type_toType, type_toType] /-- Given two ordinals `α < β`, then `principalSegToType α β` is the principal segment embedding of `α.toType` into `β.toType`. -/ def principalSegToType {α β : Ordinal} (h : α < β) : α.toType <i β.toType := by apply Classical.choice (type_lt_iff.mp _) rwa [type_toType, type_toType] /-! ### Enumerating elements in a well-order with ordinals -/ /-- The order type of an element inside a well order. This is registered as a principal segment embedding into the ordinals, with top `type r`. -/ def typein (r : α → α → Prop) [IsWellOrder α r] : @PrincipalSeg α Ordinal.{u} r (· < ·) := by refine ⟨RelEmbedding.ofMonotone _ fun a b ha ↦ ((PrincipalSeg.ofElement r a).codRestrict _ ?_ ?_).ordinal_type_lt, type r, fun a ↦ ⟨?_, ?_⟩⟩ · rintro ⟨c, hc⟩ exact trans hc ha · exact ha · rintro ⟨b, rfl⟩ exact (PrincipalSeg.ofElement _ _).ordinal_type_lt · refine inductionOn a ?_ rintro β s wo ⟨g⟩ exact ⟨_, g.subrelIso.ordinal_type_eq⟩ @[simp] theorem type_subrel (r : α → α → Prop) [IsWellOrder α r] (a : α) : type (Subrel r (r · a)) = typein r a := rfl @[simp] theorem top_typein (r : α → α → Prop) [IsWellOrder α r] : (typein r).top = type r := rfl theorem typein_lt_type (r : α → α → Prop) [IsWellOrder α r] (a : α) : typein r a < type r := (typein r).lt_top a theorem typein_lt_self {o : Ordinal} (i : o.toType) : typein (α := o.toType) (· < ·) i < o := by simp_rw [← type_toType o] apply typein_lt_type @[simp] theorem typein_top {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≺i s) : typein s f.top = type r := f.subrelIso.ordinal_type_eq @[simp] theorem typein_lt_typein (r : α → α → Prop) [IsWellOrder α r] {a b : α} : typein r a < typein r b ↔ r a b := (typein r).map_rel_iff @[simp] theorem typein_le_typein (r : α → α → Prop) [IsWellOrder α r] {a b : α} : typein r a ≤ typein r b ↔ ¬r b a := by rw [← not_lt, typein_lt_typein] theorem typein_injective (r : α → α → Prop) [IsWellOrder α r] : Injective (typein r) := (typein r).injective theorem typein_inj (r : α → α → Prop) [IsWellOrder α r] {a b} : typein r a = typein r b ↔ a = b := (typein_injective r).eq_iff theorem mem_range_typein_iff (r : α → α → Prop) [IsWellOrder α r] {o} : o ∈ Set.range (typein r) ↔ o < type r := (typein r).mem_range_iff_rel theorem typein_surj (r : α → α → Prop) [IsWellOrder α r] {o} (h : o < type r) : o ∈ Set.range (typein r) := (typein r).mem_range_of_rel_top h theorem typein_surjOn (r : α → α → Prop) [IsWellOrder α r] : Set.SurjOn (typein r) Set.univ (Set.Iio (type r)) := (typein r).surjOn /-- A well order `r` is order-isomorphic to the set of ordinals smaller than `type r`. `enum r ⟨o, h⟩` is the `o`-th element of `α` ordered by `r`. That is, `enum` maps an initial segment of the ordinals, those less than the order type of `r`, to the elements of `α`. -/ @[simps! symm_apply_coe] def enum (r : α → α → Prop) [IsWellOrder α r] : (· < · : Iio (type r) → Iio (type r) → Prop) ≃r r := (typein r).subrelIso @[simp] theorem typein_enum (r : α → α → Prop) [IsWellOrder α r] {o} (h : o < type r) : typein r (enum r ⟨o, h⟩) = o := (typein r).apply_subrelIso _ theorem enum_type {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : s ≺i r) {h : type s < type r} : enum r ⟨type s, h⟩ = f.top := (typein r).injective <| (typein_enum _ _).trans (typein_top _).symm @[simp] theorem enum_typein (r : α → α → Prop) [IsWellOrder α r] (a : α) : enum r ⟨typein r a, typein_lt_type r a⟩ = a := enum_type (PrincipalSeg.ofElement r a) theorem enum_lt_enum {r : α → α → Prop} [IsWellOrder α r] {o₁ o₂ : Iio (type r)} : r (enum r o₁) (enum r o₂) ↔ o₁ < o₂ := (enum _).map_rel_iff theorem enum_le_enum (r : α → α → Prop) [IsWellOrder α r] {o₁ o₂ : Iio (type r)} : ¬r (enum r o₁) (enum r o₂) ↔ o₂ ≤ o₁ := by rw [enum_lt_enum (r := r), not_lt] -- TODO: generalize to other well-orders @[simp] theorem enum_le_enum' (a : Ordinal) {o₁ o₂ : Iio (type (· < ·))} : enum (· < ·) o₁ ≤ enum (α := a.toType) (· < ·) o₂ ↔ o₁ ≤ o₂ := by rw [← enum_le_enum, not_lt] theorem enum_inj {r : α → α → Prop} [IsWellOrder α r] {o₁ o₂ : Iio (type r)} : enum r o₁ = enum r o₂ ↔ o₁ = o₂ := EmbeddingLike.apply_eq_iff_eq _ theorem enum_zero_le {r : α → α → Prop} [IsWellOrder α r] (h0 : 0 < type r) (a : α) : ¬r a (enum r ⟨0, h0⟩) := by rw [← enum_typein r a, enum_le_enum r] apply Ordinal.zero_le theorem enum_zero_le' {o : Ordinal} (h0 : 0 < o) (a : o.toType) : enum (α := o.toType) (· < ·) ⟨0, type_toType _ ▸ h0⟩ ≤ a := by rw [← not_lt] apply enum_zero_le theorem relIso_enum' {α β : Type u} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≃r s) (o : Ordinal) : ∀ (hr : o < type r) (hs : o < type s), f (enum r ⟨o, hr⟩) = enum s ⟨o, hs⟩ := by refine inductionOn o ?_; rintro γ t wo ⟨g⟩ ⟨h⟩ rw [enum_type g, enum_type (g.transRelIso f)]; rfl theorem relIso_enum {α β : Type u} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≃r s) (o : Ordinal) (hr : o < type r) : f (enum r ⟨o, hr⟩) = enum s ⟨o, hr.trans_eq (Quotient.sound ⟨f⟩)⟩ := relIso_enum' _ _ _ _ /-- The order isomorphism between ordinals less than `o` and `o.toType`. -/ @[simps! -isSimp] noncomputable def enumIsoToType (o : Ordinal) : Set.Iio o ≃o o.toType where toFun x := enum (α := o.toType) (· < ·) ⟨x.1, type_toType _ ▸ x.2⟩ invFun x := ⟨typein (α := o.toType) (· < ·) x, typein_lt_self x⟩ left_inv _ := Subtype.ext_val (typein_enum _ _) right_inv _ := enum_typein _ _ map_rel_iff' := enum_le_enum' _ instance small_Iio (o : Ordinal.{u}) : Small.{u} (Iio o) := ⟨_, ⟨(enumIsoToType _).toEquiv⟩⟩ instance small_Iic (o : Ordinal.{u}) : Small.{u} (Iic o) := by rw [← Iio_union_right] infer_instance instance small_Ico (a b : Ordinal.{u}) : Small.{u} (Ico a b) := small_subset Ico_subset_Iio_self instance small_Icc (a b : Ordinal.{u}) : Small.{u} (Icc a b) := small_subset Icc_subset_Iic_self instance small_Ioo (a b : Ordinal.{u}) : Small.{u} (Ioo a b) := small_subset Ioo_subset_Iio_self instance small_Ioc (a b : Ordinal.{u}) : Small.{u} (Ioc a b) := small_subset Ioc_subset_Iic_self /-- `o.toType` is an `OrderBot` whenever `o ≠ 0`. -/ def toTypeOrderBot {o : Ordinal} (ho : o ≠ 0) : OrderBot o.toType where bot := (enum (· < ·)) ⟨0, _⟩ bot_le := enum_zero_le' (by rwa [Ordinal.pos_iff_ne_zero]) /-- `o.toType` is an `OrderBot` whenever `0 < o`. -/ @[deprecated "use toTypeOrderBot" (since := "2025-02-13")] def toTypeOrderBotOfPos {o : Ordinal} (ho : 0 < o) : OrderBot o.toType where bot := (enum (· < ·)) ⟨0, _⟩ bot_le := enum_zero_le' ho theorem enum_zero_eq_bot {o : Ordinal} (ho : 0 < o) : enum (α := o.toType) (· < ·) ⟨0, by rwa [type_toType]⟩ = have H := toTypeOrderBot (o := o) (by rintro rfl; simp at ho) (⊥ : o.toType) := rfl theorem lt_wf : @WellFounded Ordinal (· < ·) := wellFounded_iff_wellFounded_subrel.mpr (·.induction_on fun ⟨_, _, wo⟩ ↦ RelHomClass.wellFounded (enum _) wo.wf) instance wellFoundedRelation : WellFoundedRelation Ordinal := ⟨(· < ·), lt_wf⟩ instance wellFoundedLT : WellFoundedLT Ordinal := ⟨lt_wf⟩ instance : ConditionallyCompleteLinearOrderBot Ordinal := WellFoundedLT.conditionallyCompleteLinearOrderBot _ /-- Reformulation of well founded induction on ordinals as a lemma that works with the `induction` tactic, as in `induction i using Ordinal.induction with | h i IH => ?_`. -/ theorem induction {p : Ordinal.{u} → Prop} (i : Ordinal.{u}) (h : ∀ j, (∀ k, k < j → p k) → p j) : p i := lt_wf.induction i h theorem typein_apply {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≼i s) (a : α) : typein s (f a) = typein r a := by rw [← f.transPrincipal_apply _ a, (f.transPrincipal _).eq] /-! ### Cardinality of ordinals -/ /-- The cardinal of an ordinal is the cardinality of any type on which a relation with that order type is defined. -/ def card : Ordinal → Cardinal := Quotient.map WellOrder.α fun _ _ ⟨e⟩ => ⟨e.toEquiv⟩ @[simp] theorem card_type (r : α → α → Prop) [IsWellOrder α r] : card (type r) = #α := rfl @[simp] theorem card_typein {r : α → α → Prop} [IsWellOrder α r] (x : α) : #{ y // r y x } = (typein r x).card := rfl theorem card_le_card {o₁ o₂ : Ordinal} : o₁ ≤ o₂ → card o₁ ≤ card o₂ := inductionOn o₁ fun _ _ _ => inductionOn o₂ fun _ _ _ ⟨⟨⟨f, _⟩, _⟩⟩ => ⟨f⟩ @[simp] theorem card_zero : card 0 = 0 := mk_eq_zero _ @[simp] theorem card_one : card 1 = 1 := mk_eq_one _ /-! ### Lifting ordinals to a higher universe -/ -- Porting note: Needed to add universe hint .{u} below /-- The universe lift operation for ordinals, which embeds `Ordinal.{u}` as a proper initial segment of `Ordinal.{v}` for `v > u`. For the initial segment version, see `liftInitialSeg`. -/ @[pp_with_univ] def lift (o : Ordinal.{v}) : Ordinal.{max v u} := Quotient.liftOn o (fun w => type <| ULift.down.{u} ⁻¹'o w.r) fun ⟨_, r, _⟩ ⟨_, s, _⟩ ⟨f⟩ => Quot.sound ⟨(RelIso.preimage Equiv.ulift r).trans <| f.trans (RelIso.preimage Equiv.ulift s).symm⟩ @[simp] theorem type_uLift (r : α → α → Prop) [IsWellOrder α r] : type (ULift.down ⁻¹'o r) = lift.{v} (type r) := rfl theorem _root_.RelIso.ordinal_lift_type_eq {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≃r s) : lift.{v} (type r) = lift.{u} (type s) := ((RelIso.preimage Equiv.ulift r).trans <| f.trans (RelIso.preimage Equiv.ulift s).symm).ordinal_type_eq @[simp] theorem type_preimage {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β ≃ α) : type (f ⁻¹'o r) = type r := (RelIso.preimage f r).ordinal_type_eq @[simp] theorem type_lift_preimage (r : α → α → Prop) [IsWellOrder α r] (f : β ≃ α) : lift.{u} (type (f ⁻¹'o r)) = lift.{v} (type r) := (RelIso.preimage f r).ordinal_lift_type_eq /-- `lift.{max u v, u}` equals `lift.{v, u}`. Unfortunately, the simp lemma doesn't seem to work. -/ theorem lift_umax : lift.{max u v, u} = lift.{v, u} := funext fun a => inductionOn a fun _ r _ => Quotient.sound ⟨(RelIso.preimage Equiv.ulift r).trans (RelIso.preimage Equiv.ulift r).symm⟩ /-- An ordinal lifted to a lower or equal universe equals itself. Unfortunately, the simp lemma doesn't work. -/ theorem lift_id' (a : Ordinal) : lift a = a := inductionOn a fun _ r _ => Quotient.sound ⟨RelIso.preimage Equiv.ulift r⟩ /-- An ordinal lifted to the same universe equals itself. -/ @[simp] theorem lift_id : ∀ a, lift.{u, u} a = a := lift_id'.{u, u} /-- An ordinal lifted to the zero universe equals itself. -/ @[simp] theorem lift_uzero (a : Ordinal.{u}) : lift.{0} a = a := lift_id' a theorem lift_type_le {α : Type u} {β : Type v} {r s} [IsWellOrder α r] [IsWellOrder β s] : lift.{max v w} (type r) ≤ lift.{max u w} (type s) ↔ Nonempty (r ≼i s) := by constructor <;> refine fun ⟨f⟩ ↦ ⟨?_⟩ · exact (RelIso.preimage Equiv.ulift r).symm.toInitialSeg.trans (f.trans (RelIso.preimage Equiv.ulift s).toInitialSeg) · exact (RelIso.preimage Equiv.ulift r).toInitialSeg.trans (f.trans (RelIso.preimage Equiv.ulift s).symm.toInitialSeg) theorem lift_type_eq {α : Type u} {β : Type v} {r s} [IsWellOrder α r] [IsWellOrder β s] : lift.{max v w} (type r) = lift.{max u w} (type s) ↔ Nonempty (r ≃r s) := by refine Quotient.eq'.trans ⟨?_, ?_⟩ <;> refine fun ⟨f⟩ ↦ ⟨?_⟩ · exact (RelIso.preimage Equiv.ulift r).symm.trans <| f.trans (RelIso.preimage Equiv.ulift s) · exact (RelIso.preimage Equiv.ulift r).trans <| f.trans (RelIso.preimage Equiv.ulift s).symm theorem lift_type_lt {α : Type u} {β : Type v} {r s} [IsWellOrder α r] [IsWellOrder β s] : lift.{max v w} (type r) < lift.{max u w} (type s) ↔ Nonempty (r ≺i s) := by constructor <;> refine fun ⟨f⟩ ↦ ⟨?_⟩ · exact (f.relIsoTrans (RelIso.preimage Equiv.ulift r).symm).transInitial (RelIso.preimage Equiv.ulift s).toInitialSeg · exact (f.relIsoTrans (RelIso.preimage Equiv.ulift r)).transInitial (RelIso.preimage Equiv.ulift s).symm.toInitialSeg @[simp] theorem lift_le {a b : Ordinal} : lift.{u, v} a ≤ lift.{u, v} b ↔ a ≤ b := inductionOn₂ a b fun α r _ β s _ => by rw [← lift_umax] exact lift_type_le.{_,_,u} @[simp] theorem lift_inj {a b : Ordinal} : lift.{u, v} a = lift.{u, v} b ↔ a = b := by simp_rw [le_antisymm_iff, lift_le] @[simp] theorem lift_lt {a b : Ordinal} : lift.{u, v} a < lift.{u, v} b ↔ a < b := by simp_rw [lt_iff_le_not_le, lift_le] @[simp] theorem lift_typein_top {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] (f : r ≺i s) : lift.{u} (typein s f.top) = lift (type r) := f.subrelIso.ordinal_lift_type_eq /-- Initial segment version of the lift operation on ordinals, embedding `Ordinal.{u}` in `Ordinal.{v}` as an initial segment when `u ≤ v`. -/ def liftInitialSeg : Ordinal.{v} ≤i Ordinal.{max u v} := by refine ⟨RelEmbedding.ofMonotone lift.{u} (by simp), fun a b ↦ Ordinal.inductionOn₂ a b fun α r _ β s _ h ↦ ?_⟩ rw [RelEmbedding.ofMonotone_coe, ← lift_id'.{max u v} (type s), ← lift_umax.{v, u}, lift_type_lt] at h obtain ⟨f⟩ := h use typein r f.top rw [RelEmbedding.ofMonotone_coe, ← lift_umax, lift_typein_top, lift_id'] @[simp] theorem liftInitialSeg_coe : (liftInitialSeg.{v, u} : Ordinal → Ordinal) = lift.{v, u} := rfl @[simp] theorem lift_lift (a : Ordinal.{u}) : lift.{w} (lift.{v} a) = lift.{max v w} a := (liftInitialSeg.trans liftInitialSeg).eq liftInitialSeg a @[simp] theorem lift_zero : lift 0 = 0 := type_eq_zero_of_empty _ @[simp] theorem lift_one : lift 1 = 1 := type_eq_one_of_unique _ @[simp] theorem lift_card (a) : Cardinal.lift.{u, v} (card a) = card (lift.{u} a) := inductionOn a fun _ _ _ => rfl theorem mem_range_lift_of_le {a : Ordinal.{u}} {b : Ordinal.{max u v}} (h : b ≤ lift.{v} a) : b ∈ Set.range lift.{v} := liftInitialSeg.mem_range_of_le h theorem le_lift_iff {a : Ordinal.{u}} {b : Ordinal.{max u v}} : b ≤ lift.{v} a ↔ ∃ a' ≤ a, lift.{v} a' = b := liftInitialSeg.le_apply_iff theorem lt_lift_iff {a : Ordinal.{u}} {b : Ordinal.{max u v}} : b < lift.{v} a ↔ ∃ a' < a, lift.{v} a' = b := liftInitialSeg.lt_apply_iff /-! ### The first infinite ordinal ω -/ /-- `ω` is the first infinite ordinal, defined as the order type of `ℕ`. -/ def omega0 : Ordinal.{u} := lift (typeLT ℕ) @[inherit_doc] scoped notation "ω" => Ordinal.omega0 /-- Note that the presence of this lemma makes `simp [omega0]` form a loop. -/ @[simp] theorem type_nat_lt : typeLT ℕ = ω := (lift_id _).symm @[simp] theorem card_omega0 : card ω = ℵ₀ := rfl @[simp] theorem lift_omega0 : lift ω = ω := lift_lift _ /-! ### Definition and first properties of addition on ordinals In this paragraph, we introduce the addition on ordinals, and prove just enough properties to deduce that the order on ordinals is total (and therefore well-founded). Further properties of the addition, together with properties of the other operations, are proved in `Mathlib/SetTheory/Ordinal/Arithmetic.lean`. -/ /-- `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that every element of `o₁` is smaller than every element of `o₂`. -/ instance add : Add Ordinal.{u} := ⟨fun o₁ o₂ => Quotient.liftOn₂ o₁ o₂ (fun ⟨_, r, _⟩ ⟨_, s, _⟩ => type (Sum.Lex r s)) fun _ _ _ _ ⟨f⟩ ⟨g⟩ => (RelIso.sumLexCongr f g).ordinal_type_eq⟩ instance addMonoidWithOne : AddMonoidWithOne Ordinal.{u} where add := (· + ·) zero := 0 one := 1 zero_add o := inductionOn o fun α _ _ => Eq.symm <| Quotient.sound ⟨⟨(emptySum PEmpty α).symm, Sum.lex_inr_inr⟩⟩ add_zero o := inductionOn o fun α _ _ => Eq.symm <| Quotient.sound ⟨⟨(sumEmpty α PEmpty).symm, Sum.lex_inl_inl⟩⟩ add_assoc o₁ o₂ o₃ := Quotient.inductionOn₃ o₁ o₂ o₃ fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ => Quot.sound ⟨⟨sumAssoc _ _ _, by intros a b rcases a with (⟨a | a⟩ | a) <;> rcases b with (⟨b | b⟩ | b) <;> simp only [sumAssoc_apply_inl_inl, sumAssoc_apply_inl_inr, sumAssoc_apply_inr, Sum.lex_inl_inl, Sum.lex_inr_inr, Sum.Lex.sep, Sum.lex_inr_inl]⟩⟩ nsmul := nsmulRec @[simp] theorem card_add (o₁ o₂ : Ordinal) : card (o₁ + o₂) = card o₁ + card o₂ := inductionOn o₁ fun _ __ => inductionOn o₂ fun _ _ _ => rfl @[simp] theorem type_sum_lex {α β : Type u} (r : α → α → Prop) (s : β → β → Prop) [IsWellOrder α r] [IsWellOrder β s] : type (Sum.Lex r s) = type r + type s := rfl @[simp] theorem card_nat (n : ℕ) : card.{u} n = n := by induction n <;> [simp; simp only [card_add, card_one, Nat.cast_succ, *]] @[simp] theorem card_ofNat (n : ℕ) [n.AtLeastTwo] : card.{u} ofNat(n) = OfNat.ofNat n := card_nat n instance instAddLeftMono : AddLeftMono Ordinal.{u} where elim c a b := by refine inductionOn₃ a b c fun α r _ β s _ γ t _ ⟨f⟩ ↦ (RelEmbedding.ofMonotone (Sum.recOn · Sum.inl (Sum.inr ∘ f)) ?_).ordinal_type_le simp [f.map_rel_iff] instance instAddRightMono : AddRightMono Ordinal.{u} where elim c a b := by refine inductionOn₃ a b c fun α r _ β s _ γ t _ ⟨f⟩ ↦ (RelEmbedding.ofMonotone (Sum.recOn · (Sum.inl ∘ f) Sum.inr) ?_).ordinal_type_le simp [f.map_rel_iff] theorem le_add_right (a b : Ordinal) : a ≤ a + b := by simpa only [add_zero] using add_le_add_left (Ordinal.zero_le b) a theorem le_add_left (a b : Ordinal) : a ≤ b + a := by simpa only [zero_add] using add_le_add_right (Ordinal.zero_le b) a theorem max_zero_left : ∀ a : Ordinal, max 0 a = a := max_bot_left theorem max_zero_right : ∀ a : Ordinal, max a 0 = a := max_bot_right @[simp] theorem max_eq_zero {a b : Ordinal} : max a b = 0 ↔ a = 0 ∧ b = 0 := max_eq_bot @[simp] theorem sInf_empty : sInf (∅ : Set Ordinal) = 0 := dif_neg Set.not_nonempty_empty /-! ### Successor order properties -/ private theorem succ_le_iff' {a b : Ordinal} : a + 1 ≤ b ↔ a < b := by refine inductionOn₂ a b fun α r _ β s _ ↦ ⟨?_, ?_⟩ <;> rintro ⟨f⟩ · refine ⟨((InitialSeg.leAdd _ _).trans f).toPrincipalSeg fun h ↦ ?_⟩ simpa using h (f (Sum.inr PUnit.unit)) · apply (RelEmbedding.ofMonotone (Sum.recOn · f fun _ ↦ f.top) ?_).ordinal_type_le simpa [f.map_rel_iff] using f.lt_top instance : NoMaxOrder Ordinal := ⟨fun _ => ⟨_, succ_le_iff'.1 le_rfl⟩⟩ instance : SuccOrder Ordinal.{u} := SuccOrder.ofSuccLeIff (fun o => o + 1) succ_le_iff' instance : SuccAddOrder Ordinal := ⟨fun _ => rfl⟩ @[simp] theorem add_one_eq_succ (o : Ordinal) : o + 1 = succ o := rfl @[simp] theorem succ_zero : succ (0 : Ordinal) = 1 := zero_add 1 -- Porting note: Proof used to be rfl @[simp] theorem succ_one : succ (1 : Ordinal) = 2 := by congr; simp only [Nat.unaryCast, zero_add] theorem add_succ (o₁ o₂ : Ordinal) : o₁ + succ o₂ = succ (o₁ + o₂) := (add_assoc _ _ _).symm theorem one_le_iff_ne_zero {o : Ordinal} : 1 ≤ o ↔ o ≠ 0 := by rw [Order.one_le_iff_pos, Ordinal.pos_iff_ne_zero] theorem succ_pos (o : Ordinal) : 0 < succ o := bot_lt_succ o theorem succ_ne_zero (o : Ordinal) : succ o ≠ 0 := ne_of_gt <| succ_pos o @[simp] theorem lt_one_iff_zero {a : Ordinal} : a < 1 ↔ a = 0 := by simpa using @lt_succ_bot_iff _ _ _ a _ _ theorem le_one_iff {a : Ordinal} : a ≤ 1 ↔ a = 0 ∨ a = 1 := by simpa using @le_succ_bot_iff _ _ _ a _ @[simp] theorem card_succ (o : Ordinal) : card (succ o) = card o + 1 := by simp only [← add_one_eq_succ, card_add, card_one] theorem natCast_succ (n : ℕ) : ↑n.succ = succ (n : Ordinal) := rfl instance uniqueIioOne : Unique (Iio (1 : Ordinal)) where default := ⟨0, zero_lt_one' Ordinal⟩ uniq a := Subtype.ext <| lt_one_iff_zero.1 a.2 @[simp] theorem Iio_one_default_eq : (default : Iio (1 : Ordinal)) = ⟨0, zero_lt_one' Ordinal⟩ := rfl instance uniqueToTypeOne : Unique (toType 1) where default := enum (α := toType 1) (· < ·) ⟨0, by simp⟩ uniq a := by rw [← enum_typein (α := toType 1) (· < ·) a] congr rw [← lt_one_iff_zero] apply typein_lt_self theorem one_toType_eq (x : toType 1) : x = enum (· < ·) ⟨0, by simp⟩ := Unique.eq_default x /-! ### Extra properties of typein and enum -/ -- TODO: use `enumIsoToType` for lemmas on `toType` rather than `enum` and `typein`. @[simp] theorem typein_one_toType (x : toType 1) : typein (α := toType 1) (· < ·) x = 0 := by rw [one_toType_eq x, typein_enum] theorem typein_le_typein' (o : Ordinal) {x y : o.toType} : typein (α := o.toType) (· < ·) x ≤ typein (α := o.toType) (· < ·) y ↔ x ≤ y := by simp theorem le_enum_succ {o : Ordinal} (a : (succ o).toType) : a ≤ enum (α := (succ o).toType) (· < ·) ⟨o, (type_toType _ ▸ lt_succ o)⟩ := by rw [← enum_typein (α := (succ o).toType) (· < ·) a, enum_le_enum', Subtype.mk_le_mk, ← lt_succ_iff] apply typein_lt_self /-! ### Universal ordinal -/ -- intended to be used with explicit universe parameters /-- `univ.{u v}` is the order type of the ordinals of `Type u` as a member of `Ordinal.{v}` (when `u < v`). It is an inaccessible cardinal. -/ @[pp_with_univ, nolint checkUnivs] def univ : Ordinal.{max (u + 1) v} := lift.{v, u + 1} (typeLT Ordinal) theorem univ_id : univ.{u, u + 1} = typeLT Ordinal := lift_id _ @[simp] theorem lift_univ : lift.{w} univ.{u, v} = univ.{u, max v w} := lift_lift _ theorem univ_umax : univ.{u, max (u + 1) v} = univ.{u, v} := congr_fun lift_umax _ /-- Principal segment version of the lift operation on ordinals, embedding `Ordinal.{u}` in `Ordinal.{v}` as a principal segment when `u < v`. -/ def liftPrincipalSeg : Ordinal.{u} <i Ordinal.{max (u + 1) v} := ⟨↑liftInitialSeg.{max (u + 1) v, u}, univ.{u, v}, by refine fun b => inductionOn b ?_; intro β s _ rw [univ, ← lift_umax]; constructor <;> intro h · obtain ⟨a, e⟩ := h rw [← e] refine inductionOn a ?_ intro α r _ exact lift_type_lt.{u, u + 1, max (u + 1) v}.2 ⟨typein r⟩ · rw [← lift_id (type s)] at h ⊢ obtain ⟨f⟩ := lift_type_lt.{_,_,v}.1 h obtain ⟨f, a, hf⟩ := f exists a revert hf -- Porting note: apply inductionOn does not work, refine does refine inductionOn a ?_ intro α r _ hf refine lift_type_eq.{u, max (u + 1) v, max (u + 1) v}.2 ⟨(RelIso.ofSurjective (RelEmbedding.ofMonotone ?_ ?_) ?_).symm⟩ · exact fun b => enum r ⟨f b, (hf _).1 ⟨_, rfl⟩⟩ · refine fun a b h => (typein_lt_typein r).1 ?_ rw [typein_enum, typein_enum] exact f.map_rel_iff.2 h · intro a' obtain ⟨b, e⟩ := (hf _).2 (typein_lt_type _ a') exists b simp only [RelEmbedding.ofMonotone_coe] simp [e]⟩ @[simp] theorem liftPrincipalSeg_coe : (liftPrincipalSeg.{u, v} : Ordinal → Ordinal) = lift.{max (u + 1) v} := rfl @[simp] theorem liftPrincipalSeg_top : (liftPrincipalSeg.{u, v}).top = univ.{u, v} := rfl theorem liftPrincipalSeg_top' : liftPrincipalSeg.{u, u + 1}.top = typeLT Ordinal := by simp only [liftPrincipalSeg_top, univ_id] end Ordinal /-! ### Representing a cardinal with an ordinal -/ namespace Cardinal open Ordinal @[simp] theorem mk_toType (o : Ordinal) : #o.toType = o.card := (Ordinal.card_type _).symm.trans <| by rw [Ordinal.type_toType] /-- The ordinal corresponding to a cardinal `c` is the least ordinal whose cardinal is `c`. For the order-embedding version, see `ord.order_embedding`. -/ def ord (c : Cardinal) : Ordinal := let F := fun α : Type u => ⨅ r : { r // IsWellOrder α r }, @type α r.1 r.2 Quot.liftOn c F (by suffices ∀ {α β}, α ≈ β → F α ≤ F β from fun α β h => (this h).antisymm (this (Setoid.symm h)) rintro α β ⟨f⟩ refine le_ciInf_iff'.2 fun i => ?_ haveI := @RelEmbedding.isWellOrder _ _ (f ⁻¹'o i.1) _ (↑(RelIso.preimage f i.1)) i.2 exact (ciInf_le' _ (Subtype.mk (f ⁻¹'o i.val) (@RelEmbedding.isWellOrder _ _ _ _ (↑(RelIso.preimage f i.1)) i.2))).trans_eq (Quot.sound ⟨RelIso.preimage f i.1⟩)) theorem ord_eq_Inf (α : Type u) : ord #α = ⨅ r : { r // IsWellOrder α r }, @type α r.1 r.2 := rfl theorem ord_eq (α) : ∃ (r : α → α → Prop) (wo : IsWellOrder α r), ord #α = @type α r wo := let ⟨r, wo⟩ := ciInf_mem fun r : { r // IsWellOrder α r } => @type α r.1 r.2 ⟨r.1, r.2, wo.symm⟩ theorem ord_le_type (r : α → α → Prop) [h : IsWellOrder α r] : ord #α ≤ type r := ciInf_le' _ (Subtype.mk r h) theorem ord_le {c o} : ord c ≤ o ↔ c ≤ o.card := inductionOn c fun α => Ordinal.inductionOn o fun β s _ => by let ⟨r, _, e⟩ := ord_eq α simp only [card_type]; constructor <;> intro h · rw [e] at h exact let ⟨f⟩ := h ⟨f.toEmbedding⟩ · obtain ⟨f⟩ := h have g := RelEmbedding.preimage f s haveI := RelEmbedding.isWellOrder g exact le_trans (ord_le_type _) g.ordinal_type_le theorem gc_ord_card : GaloisConnection ord card := fun _ _ => ord_le theorem lt_ord {c o} : o < ord c ↔ o.card < c := gc_ord_card.lt_iff_lt @[simp] theorem card_ord (c) : (ord c).card = c := c.inductionOn fun α ↦ let ⟨r, _, e⟩ := ord_eq α; e ▸ card_type r theorem card_surjective : Function.Surjective card := fun c ↦ ⟨_, card_ord c⟩ /-- Galois coinsertion between `Cardinal.ord` and `Ordinal.card`. -/ def gciOrdCard : GaloisCoinsertion ord card := gc_ord_card.toGaloisCoinsertion fun c => c.card_ord.le theorem ord_card_le (o : Ordinal) : o.card.ord ≤ o := gc_ord_card.l_u_le _ theorem lt_ord_succ_card (o : Ordinal) : o < (succ o.card).ord := lt_ord.2 <| lt_succ _ theorem card_le_iff {o : Ordinal} {c : Cardinal} : o.card ≤ c ↔ o < (succ c).ord := by rw [lt_ord, lt_succ_iff] /-- A variation on `Cardinal.lt_ord` using `≤`: If `o` is no greater than the initial ordinal of cardinality `c`, then its cardinal is no greater than `c`. The converse, however, is false (for instance, `o = ω+1` and `c = ℵ₀`). -/ lemma card_le_of_le_ord {o : Ordinal} {c : Cardinal} (ho : o ≤ c.ord) : o.card ≤ c := by rw [← card_ord c]; exact Ordinal.card_le_card ho @[mono] theorem ord_strictMono : StrictMono ord := gciOrdCard.strictMono_l @[mono] theorem ord_mono : Monotone ord := gc_ord_card.monotone_l @[simp] theorem ord_le_ord {c₁ c₂} : ord c₁ ≤ ord c₂ ↔ c₁ ≤ c₂ := gciOrdCard.l_le_l_iff @[simp] theorem ord_lt_ord {c₁ c₂} : ord c₁ < ord c₂ ↔ c₁ < c₂ := ord_strictMono.lt_iff_lt @[simp] theorem ord_zero : ord 0 = 0 := gc_ord_card.l_bot @[simp] theorem ord_nat (n : ℕ) : ord n = n := (ord_le.2 (card_nat n).ge).antisymm (by induction' n with n IH · apply Ordinal.zero_le · exact succ_le_of_lt (IH.trans_lt <| ord_lt_ord.2 <| Nat.cast_lt.2 (Nat.lt_succ_self n))) @[simp] theorem ord_one : ord 1 = 1 := by simpa using ord_nat 1 @[simp] theorem ord_ofNat (n : ℕ) [n.AtLeastTwo] : ord ofNat(n) = OfNat.ofNat n := ord_nat n @[simp] theorem ord_aleph0 : ord.{u} ℵ₀ = ω := le_antisymm (ord_le.2 le_rfl) <| le_of_forall_lt fun o h => by rcases Ordinal.lt_lift_iff.1 h with ⟨o, h', rfl⟩ rw [lt_ord, ← lift_card, lift_lt_aleph0, ← typein_enum (· < ·) h'] exact lt_aleph0_iff_fintype.2 ⟨Set.fintypeLTNat _⟩ @[simp] theorem lift_ord (c) : Ordinal.lift.{u,v} (ord c) = ord (lift.{u,v} c) := by refine le_antisymm (le_of_forall_lt fun a ha => ?_) ?_ · rcases Ordinal.lt_lift_iff.1 ha with ⟨a, _, rfl⟩ rwa [lt_ord, ← lift_card, lift_lt, ← lt_ord, ← Ordinal.lift_lt] · rw [ord_le, ← lift_card, card_ord] theorem mk_ord_toType (c : Cardinal) : #c.ord.toType = c := by simp theorem card_typein_lt (r : α → α → Prop) [IsWellOrder α r] (x : α) (h : ord #α = type r) : card (typein r x) < #α := by rw [← lt_ord, h] apply typein_lt_type theorem card_typein_toType_lt (c : Cardinal) (x : c.ord.toType) : card (typein (α := c.ord.toType) (· < ·) x) < c := by rw [← lt_ord] apply typein_lt_self theorem mk_Iio_ord_toType {c : Cardinal} (i : c.ord.toType) : #(Iio i) < c := card_typein_toType_lt c i theorem ord_injective : Injective ord := by intro c c' h rw [← card_ord c, ← card_ord c', h] @[simp] theorem ord_inj {a b : Cardinal} : a.ord = b.ord ↔ a = b := ord_injective.eq_iff @[simp] theorem ord_eq_zero {a : Cardinal} : a.ord = 0 ↔ a = 0 := ord_injective.eq_iff' ord_zero @[simp] theorem ord_eq_one {a : Cardinal} : a.ord = 1 ↔ a = 1 := ord_injective.eq_iff' ord_one @[simp] theorem omega0_le_ord {a : Cardinal} : ω ≤ a.ord ↔ ℵ₀ ≤ a := by rw [← ord_aleph0, ord_le_ord] @[simp] theorem ord_le_omega0 {a : Cardinal} : a.ord ≤ ω ↔ a ≤ ℵ₀ := by rw [← ord_aleph0, ord_le_ord] @[simp] theorem ord_lt_omega0 {a : Cardinal} : a.ord < ω ↔ a < ℵ₀ := le_iff_le_iff_lt_iff_lt.1 omega0_le_ord @[simp] theorem omega0_lt_ord {a : Cardinal} : ω < a.ord ↔ ℵ₀ < a := le_iff_le_iff_lt_iff_lt.1 ord_le_omega0 @[simp] theorem ord_eq_omega0 {a : Cardinal} : a.ord = ω ↔ a = ℵ₀ := ord_injective.eq_iff' ord_aleph0 /-- The ordinal corresponding to a cardinal `c` is the least ordinal whose cardinal is `c`. This is the order-embedding version. For the regular function, see `ord`. -/ def ord.orderEmbedding : Cardinal ↪o Ordinal := RelEmbedding.orderEmbeddingOfLTEmbedding (RelEmbedding.ofMonotone Cardinal.ord fun _ _ => Cardinal.ord_lt_ord.2) @[simp] theorem ord.orderEmbedding_coe : (ord.orderEmbedding : Cardinal → Ordinal) = ord := rfl -- intended to be used with explicit universe parameters /-- The cardinal `univ` is the cardinality of ordinal `univ`, or equivalently the cardinal of `Ordinal.{u}`, or `Cardinal.{u}`, as an element of `Cardinal.{v}` (when `u < v`). -/ @[pp_with_univ, nolint checkUnivs] def univ := lift.{v, u + 1} #Ordinal theorem univ_id : univ.{u, u + 1} = #Ordinal := lift_id _ @[simp] theorem lift_univ : lift.{w} univ.{u, v} = univ.{u, max v w} := lift_lift _ theorem univ_umax : univ.{u, max (u + 1) v} = univ.{u, v} := congr_fun lift_umax _ theorem lift_lt_univ (c : Cardinal) : lift.{u + 1, u} c < univ.{u, u + 1} := by simpa only [liftPrincipalSeg_coe, lift_ord, lift_succ, ord_le, succ_le_iff] using le_of_lt (liftPrincipalSeg.{u, u + 1}.lt_top (succ c).ord) theorem lift_lt_univ' (c : Cardinal) : lift.{max (u + 1) v, u} c < univ.{u, v} := by have := lift_lt.{_, max (u+1) v}.2 (lift_lt_univ c) rw [lift_lift, lift_univ, univ_umax.{u,v}] at this exact this @[simp] theorem ord_univ : ord univ.{u, v} = Ordinal.univ.{u, v} := by refine le_antisymm (ord_card_le _) <| le_of_forall_lt fun o h => lt_ord.2 ?_ have := liftPrincipalSeg.mem_range_of_rel_top (by simpa only [liftPrincipalSeg_coe] using h) rcases this with ⟨o, h'⟩ rw [← h', liftPrincipalSeg_coe, ← lift_card] apply lift_lt_univ' theorem lt_univ {c} : c < univ.{u, u + 1} ↔ ∃ c', c = lift.{u + 1, u} c' := ⟨fun h => by have := ord_lt_ord.2 h rw [ord_univ] at this obtain ⟨o, e⟩ := liftPrincipalSeg.mem_range_of_rel_top (by simpa only [liftPrincipalSeg_top]) have := card_ord c rw [← e, liftPrincipalSeg_coe, ← lift_card] at this exact ⟨_, this.symm⟩, fun ⟨_, e⟩ => e.symm ▸ lift_lt_univ _⟩ theorem lt_univ' {c} : c < univ.{u, v} ↔ ∃ c', c = lift.{max (u + 1) v, u} c' := ⟨fun h => by let ⟨a, h', e⟩ := lt_lift_iff.1 h rw [← univ_id] at h' rcases lt_univ.{u}.1 h' with ⟨c', rfl⟩ exact ⟨c', by simp only [e.symm, lift_lift]⟩, fun ⟨_, e⟩ => e.symm ▸ lift_lt_univ' _⟩ theorem small_iff_lift_mk_lt_univ {α : Type u} : Small.{v} α ↔ Cardinal.lift.{v+1,_} #α < univ.{v, max u (v + 1)} := by rw [lt_univ'] constructor · rintro ⟨β, e⟩ exact ⟨#β, lift_mk_eq.{u, _, v + 1}.2 e⟩ · rintro ⟨c, hc⟩ exact ⟨⟨c.out, lift_mk_eq.{u, _, v + 1}.1 (hc.trans (congr rfl c.mk_out.symm))⟩⟩ /-- If a cardinal `c` is non zero, then `c.ord.toType` has a least element. -/ noncomputable def toTypeOrderBot {c : Cardinal} (hc : c ≠ 0) : OrderBot c.ord.toType := Ordinal.toTypeOrderBot (fun h ↦ hc (ord_injective (by simpa using h))) end Cardinal namespace Ordinal @[simp] theorem card_univ : card univ.{u,v} = Cardinal.univ.{u,v} := rfl @[simp] theorem nat_le_card {o} {n : ℕ} : (n : Cardinal) ≤ card o ↔ (n : Ordinal) ≤ o := by rw [← Cardinal.ord_le, Cardinal.ord_nat] @[simp] theorem one_le_card {o} : 1 ≤ card o ↔ 1 ≤ o := by simpa using nat_le_card (n := 1) @[simp] theorem ofNat_le_card {o} {n : ℕ} [n.AtLeastTwo] : (ofNat(n) : Cardinal) ≤ card o ↔ (OfNat.ofNat n : Ordinal) ≤ o := nat_le_card @[simp] theorem aleph0_le_card {o} : ℵ₀ ≤ card o ↔ ω ≤ o := by rw [← ord_le, ord_aleph0] @[simp]
theorem card_lt_aleph0 {o} : card o < ℵ₀ ↔ o < ω := le_iff_le_iff_lt_iff_lt.1 aleph0_le_card
Mathlib/SetTheory/Ordinal/Basic.lean
1,285
1,286
/- 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.Finset.Powerset import Mathlib.Data.Fintype.EquivFin /-! # fintype instance for `Set α`, when `α` is a fintype -/ variable {α : Type*} open Finset instance Finset.fintype [Fintype α] : Fintype (Finset α) := ⟨univ.powerset, fun _ => Finset.mem_powerset.2 (Finset.subset_univ _)⟩ @[simp] theorem Fintype.card_finset [Fintype α] : Fintype.card (Finset α) = 2 ^ Fintype.card α := Finset.card_powerset Finset.univ namespace Finset variable [Fintype α] {s : Finset α} {k : ℕ} @[simp] lemma powerset_univ : (univ : Finset α).powerset = univ := coe_injective <| by simp [-coe_eq_univ] lemma filter_subset_univ [DecidableEq α] (s : Finset α) : ({t | t ⊆ s} : Finset _) = powerset s := by ext; simp @[simp] lemma powerset_eq_univ : s.powerset = univ ↔ s = univ := by rw [← Finset.powerset_univ, powerset_inj]
lemma mem_powersetCard_univ : s ∈ powersetCard k (univ : Finset α) ↔ #s = k :=
Mathlib/Data/Fintype/Powerset.lean
36
37
/- Copyright (c) 2019 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Yakov Pechersky -/ import Mathlib.Data.List.Nodup import Mathlib.Data.List.Infix import Mathlib.Data.Quot /-! # List rotation This file proves basic results about `List.rotate`, the list rotation. ## Main declarations * `List.IsRotated l₁ l₂`: States that `l₁` is a rotated version of `l₂`. * `List.cyclicPermutations l`: The list of all cyclic permutants of `l`, up to the length of `l`. ## Tags rotated, rotation, permutation, cycle -/ universe u variable {α : Type u} open Nat Function namespace List theorem rotate_mod (l : List α) (n : ℕ) : l.rotate (n % l.length) = l.rotate n := by simp [rotate] @[simp] theorem rotate_nil (n : ℕ) : ([] : List α).rotate n = [] := by simp [rotate] @[simp] theorem rotate_zero (l : List α) : l.rotate 0 = l := by simp [rotate] theorem rotate'_nil (n : ℕ) : ([] : List α).rotate' n = [] := by simp @[simp] theorem rotate'_zero (l : List α) : l.rotate' 0 = l := by cases l <;> rfl theorem rotate'_cons_succ (l : List α) (a : α) (n : ℕ) : (a :: l : List α).rotate' n.succ = (l ++ [a]).rotate' n := by simp [rotate']
Mathlib/Data/List/Rotate.lean
49
49
/- Copyright (c) 2020 Markus Himmel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Markus Himmel -/ import Mathlib.Algebra.Category.Grp.Colimits import Mathlib.Algebra.Category.Grp.Limits import Mathlib.Algebra.Category.Grp.ZModuleEquivalence import Mathlib.Algebra.Category.ModuleCat.Abelian import Mathlib.CategoryTheory.Adjunction.Limits import Mathlib.CategoryTheory.Limits.ConcreteCategory.Basic /-! # The category of abelian groups is abelian -/ open CategoryTheory Limits universe u noncomputable section namespace AddCommGrp variable {X Y Z : AddCommGrp.{u}} (f : X ⟶ Y) (g : Y ⟶ Z) /-- In the category of abelian groups, every monomorphism is normal. -/ def normalMono (_ : Mono f) : NormalMono f := equivalenceReflectsNormalMono (forget₂ (ModuleCat.{u} ℤ) AddCommGrp.{u}).inv <| ModuleCat.normalMono _ inferInstance /-- In the category of abelian groups, every epimorphism is normal. -/ def normalEpi (_ : Epi f) : NormalEpi f := equivalenceReflectsNormalEpi (forget₂ (ModuleCat.{u} ℤ) AddCommGrp.{u}).inv <| ModuleCat.normalEpi _ inferInstance /-- The category of abelian groups is abelian. -/ instance : Abelian AddCommGrp.{u} where normalMonoOfMono f hf := ⟨normalMono f hf⟩ normalEpiOfEpi f hf := ⟨normalEpi f hf⟩ end AddCommGrp
Mathlib/Algebra/Category/Grp/Abelian.lean
51
57
/- 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, Kim Morrison, Jens Wagemaker -/ import Mathlib.Algebra.Field.IsField import Mathlib.Algebra.Polynomial.Inductions import Mathlib.Algebra.Polynomial.Monic import Mathlib.Algebra.Ring.Regular import Mathlib.RingTheory.Multiplicity import Mathlib.Data.Nat.Lattice /-! # Division of univariate polynomials The main defs are `divByMonic` and `modByMonic`. The compatibility between these is given by `modByMonic_add_div`. We also define `rootMultiplicity`. -/ noncomputable section open Polynomial open Finset namespace Polynomial universe u v w z variable {R : Type u} {S : Type v} {T : Type w} {A : Type z} {a b : R} {n : ℕ} section Semiring variable [Semiring R] theorem X_dvd_iff {f : R[X]} : X ∣ f ↔ f.coeff 0 = 0 := ⟨fun ⟨g, hfg⟩ => by rw [hfg, coeff_X_mul_zero], fun hf => ⟨f.divX, by rw [← add_zero (X * f.divX), ← C_0, ← hf, X_mul_divX_add]⟩⟩ theorem X_pow_dvd_iff {f : R[X]} {n : ℕ} : X ^ n ∣ f ↔ ∀ d < n, f.coeff d = 0 := ⟨fun ⟨g, hgf⟩ d hd => by simp only [hgf, coeff_X_pow_mul', ite_eq_right_iff, not_le_of_lt hd, IsEmpty.forall_iff], fun hd => by induction n with | zero => simp [pow_zero, one_dvd] | succ n hn => obtain ⟨g, hgf⟩ := hn fun d : ℕ => fun H : d < n => hd _ (Nat.lt_succ_of_lt H) have := coeff_X_pow_mul g n 0 rw [zero_add, ← hgf, hd n (Nat.lt_succ_self n)] at this obtain ⟨k, hgk⟩ := Polynomial.X_dvd_iff.mpr this.symm use k rwa [pow_succ, mul_assoc, ← hgk]⟩ variable {p q : R[X]} theorem finiteMultiplicity_of_degree_pos_of_monic (hp : (0 : WithBot ℕ) < degree p) (hmp : Monic p) (hq : q ≠ 0) : FiniteMultiplicity p q := have zn0 : (0 : R) ≠ 1 := haveI := Nontrivial.of_polynomial_ne hq zero_ne_one ⟨natDegree q, fun ⟨r, hr⟩ => by have hp0 : p ≠ 0 := fun hp0 => by simp [hp0] at hp have hr0 : r ≠ 0 := fun hr0 => by subst hr0; simp [hq] at hr have hpn1 : leadingCoeff p ^ (natDegree q + 1) = 1 := by simp [show _ = _ from hmp] have hpn0' : leadingCoeff p ^ (natDegree q + 1) ≠ 0 := hpn1.symm ▸ zn0.symm have hpnr0 : leadingCoeff (p ^ (natDegree q + 1)) * leadingCoeff r ≠ 0 := by simp only [leadingCoeff_pow' hpn0', leadingCoeff_eq_zero, hpn1, one_pow, one_mul, Ne, hr0, not_false_eq_true] have hnp : 0 < natDegree p := Nat.cast_lt.1 <| by rw [← degree_eq_natDegree hp0]; exact hp have := congr_arg natDegree hr rw [natDegree_mul' hpnr0, natDegree_pow' hpn0', add_mul, add_assoc] at this exact ne_of_lt (lt_add_of_le_of_pos (le_mul_of_one_le_right (Nat.zero_le _) hnp) (add_pos_of_pos_of_nonneg (by rwa [one_mul]) (Nat.zero_le _))) this⟩ @[deprecated (since := "2024-11-30")] alias multiplicity_finite_of_degree_pos_of_monic := finiteMultiplicity_of_degree_pos_of_monic end Semiring section Ring variable [Ring R] {p q : R[X]} theorem div_wf_lemma (h : degree q ≤ degree p ∧ p ≠ 0) (hq : Monic q) : degree (p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) < degree p := have hp : leadingCoeff p ≠ 0 := mt leadingCoeff_eq_zero.1 h.2 have hq0 : q ≠ 0 := hq.ne_zero_of_polynomial_ne h.2 have hlt : natDegree q ≤ natDegree p := (Nat.cast_le (α := WithBot ℕ)).1 (by rw [← degree_eq_natDegree h.2, ← degree_eq_natDegree hq0]; exact h.1) degree_sub_lt (by rw [hq.degree_mul_comm, hq.degree_mul, degree_C_mul_X_pow _ hp, degree_eq_natDegree h.2, degree_eq_natDegree hq0, ← Nat.cast_add, tsub_add_cancel_of_le hlt]) h.2 (by rw [leadingCoeff_monic_mul hq, leadingCoeff_mul_X_pow, leadingCoeff_C]) /-- See `divByMonic`. -/ noncomputable def divModByMonicAux : ∀ (_p : R[X]) {q : R[X]}, Monic q → R[X] × R[X] | p, q, hq => letI := Classical.decEq R if h : degree q ≤ degree p ∧ p ≠ 0 then let z := C (leadingCoeff p) * X ^ (natDegree p - natDegree q) have _wf := div_wf_lemma h hq let dm := divModByMonicAux (p - q * z) hq ⟨z + dm.1, dm.2⟩ else ⟨0, p⟩ termination_by p => p /-- `divByMonic`, denoted as `p /ₘ q`, gives the quotient of `p` by a monic polynomial `q`. -/ def divByMonic (p q : R[X]) : R[X] := letI := Classical.decEq R if hq : Monic q then (divModByMonicAux p hq).1 else 0 /-- `modByMonic`, denoted as `p %ₘ q`, gives the remainder of `p` by a monic polynomial `q`. -/ def modByMonic (p q : R[X]) : R[X] := letI := Classical.decEq R if hq : Monic q then (divModByMonicAux p hq).2 else p @[inherit_doc] infixl:70 " /ₘ " => divByMonic @[inherit_doc] infixl:70 " %ₘ " => modByMonic theorem degree_modByMonic_lt [Nontrivial R] : ∀ (p : R[X]) {q : R[X]} (_hq : Monic q), degree (p %ₘ q) < degree q | p, q, hq => letI := Classical.decEq R if h : degree q ≤ degree p ∧ p ≠ 0 then by have _wf := div_wf_lemma ⟨h.1, h.2⟩ hq have := degree_modByMonic_lt (p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) hq unfold modByMonic at this ⊢ unfold divModByMonicAux dsimp rw [dif_pos hq] at this ⊢ rw [if_pos h] exact this else Or.casesOn (not_and_or.1 h) (by unfold modByMonic divModByMonicAux dsimp rw [dif_pos hq, if_neg h] exact lt_of_not_ge) (by intro hp unfold modByMonic divModByMonicAux dsimp rw [dif_pos hq, if_neg h, Classical.not_not.1 hp] exact lt_of_le_of_ne bot_le (Ne.symm (mt degree_eq_bot.1 hq.ne_zero))) termination_by p => p theorem natDegree_modByMonic_lt (p : R[X]) {q : R[X]} (hmq : Monic q) (hq : q ≠ 1) : natDegree (p %ₘ q) < q.natDegree := by by_cases hpq : p %ₘ q = 0 · rw [hpq, natDegree_zero, Nat.pos_iff_ne_zero] contrapose! hq exact eq_one_of_monic_natDegree_zero hmq hq · haveI := Nontrivial.of_polynomial_ne hpq exact natDegree_lt_natDegree hpq (degree_modByMonic_lt p hmq) @[simp] theorem zero_modByMonic (p : R[X]) : 0 %ₘ p = 0 := by classical unfold modByMonic divModByMonicAux dsimp by_cases hp : Monic p · rw [dif_pos hp, if_neg (mt And.right (not_not_intro rfl)), Prod.snd_zero] · rw [dif_neg hp] @[simp] theorem zero_divByMonic (p : R[X]) : 0 /ₘ p = 0 := by classical unfold divByMonic divModByMonicAux dsimp by_cases hp : Monic p · rw [dif_pos hp, if_neg (mt And.right (not_not_intro rfl)), Prod.fst_zero] · rw [dif_neg hp] @[simp] theorem modByMonic_zero (p : R[X]) : p %ₘ 0 = p := letI := Classical.decEq R if h : Monic (0 : R[X]) then by haveI := monic_zero_iff_subsingleton.mp h simp [eq_iff_true_of_subsingleton] else by unfold modByMonic divModByMonicAux; rw [dif_neg h] @[simp] theorem divByMonic_zero (p : R[X]) : p /ₘ 0 = 0 := letI := Classical.decEq R if h : Monic (0 : R[X]) then by haveI := monic_zero_iff_subsingleton.mp h simp [eq_iff_true_of_subsingleton] else by unfold divByMonic divModByMonicAux; rw [dif_neg h] theorem divByMonic_eq_of_not_monic (p : R[X]) (hq : ¬Monic q) : p /ₘ q = 0 := dif_neg hq theorem modByMonic_eq_of_not_monic (p : R[X]) (hq : ¬Monic q) : p %ₘ q = p := dif_neg hq theorem modByMonic_eq_self_iff [Nontrivial R] (hq : Monic q) : p %ₘ q = p ↔ degree p < degree q := ⟨fun h => h ▸ degree_modByMonic_lt _ hq, fun h => by classical have : ¬degree q ≤ degree p := not_le_of_gt h unfold modByMonic divModByMonicAux; dsimp; rw [dif_pos hq, if_neg (mt And.left this)]⟩ theorem degree_modByMonic_le (p : R[X]) {q : R[X]} (hq : Monic q) : degree (p %ₘ q) ≤ degree q := by nontriviality R exact (degree_modByMonic_lt _ hq).le theorem degree_modByMonic_le_left : degree (p %ₘ q) ≤ degree p := by nontriviality R by_cases hq : q.Monic · cases lt_or_ge (degree p) (degree q) · rw [(modByMonic_eq_self_iff hq).mpr ‹_›] · exact (degree_modByMonic_le p hq).trans ‹_› · rw [modByMonic_eq_of_not_monic p hq] theorem natDegree_modByMonic_le (p : Polynomial R) {g : Polynomial R} (hg : g.Monic) : natDegree (p %ₘ g) ≤ g.natDegree := natDegree_le_natDegree (degree_modByMonic_le p hg) theorem natDegree_modByMonic_le_left : natDegree (p %ₘ q) ≤ natDegree p := natDegree_le_natDegree degree_modByMonic_le_left theorem X_dvd_sub_C : X ∣ p - C (p.coeff 0) := by simp [X_dvd_iff, coeff_C] theorem modByMonic_eq_sub_mul_div : ∀ (p : R[X]) {q : R[X]} (_hq : Monic q), p %ₘ q = p - q * (p /ₘ q) | p, q, hq => letI := Classical.decEq R if h : degree q ≤ degree p ∧ p ≠ 0 then by have _wf := div_wf_lemma h hq have ih := modByMonic_eq_sub_mul_div (p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) hq unfold modByMonic divByMonic divModByMonicAux dsimp rw [dif_pos hq, if_pos h] rw [modByMonic, dif_pos hq] at ih refine ih.trans ?_ unfold divByMonic rw [dif_pos hq, dif_pos hq, if_pos h, mul_add, sub_add_eq_sub_sub] else by unfold modByMonic divByMonic divModByMonicAux dsimp rw [dif_pos hq, if_neg h, dif_pos hq, if_neg h, mul_zero, sub_zero] termination_by p => p theorem modByMonic_add_div (p : R[X]) {q : R[X]} (hq : Monic q) : p %ₘ q + q * (p /ₘ q) = p := eq_sub_iff_add_eq.1 (modByMonic_eq_sub_mul_div p hq) theorem divByMonic_eq_zero_iff [Nontrivial R] (hq : Monic q) : p /ₘ q = 0 ↔ degree p < degree q := ⟨fun h => by have := modByMonic_add_div p hq rwa [h, mul_zero, add_zero, modByMonic_eq_self_iff hq] at this, fun h => by classical have : ¬degree q ≤ degree p := not_le_of_gt h unfold divByMonic divModByMonicAux; dsimp; rw [dif_pos hq, if_neg (mt And.left this)]⟩ theorem degree_add_divByMonic (hq : Monic q) (h : degree q ≤ degree p) : degree q + degree (p /ₘ q) = degree p := by nontriviality R have hdiv0 : p /ₘ q ≠ 0 := by rwa [Ne, divByMonic_eq_zero_iff hq, not_lt] have hlc : leadingCoeff q * leadingCoeff (p /ₘ q) ≠ 0 := by rwa [Monic.def.1 hq, one_mul, Ne, leadingCoeff_eq_zero] have hmod : degree (p %ₘ q) < degree (q * (p /ₘ q)) := calc degree (p %ₘ q) < degree q := degree_modByMonic_lt _ hq _ ≤ _ := by rw [degree_mul' hlc, degree_eq_natDegree hq.ne_zero, degree_eq_natDegree hdiv0, ← Nat.cast_add, Nat.cast_le] exact Nat.le_add_right _ _ calc degree q + degree (p /ₘ q) = degree (q * (p /ₘ q)) := Eq.symm (degree_mul' hlc) _ = degree (p %ₘ q + q * (p /ₘ q)) := (degree_add_eq_right_of_degree_lt hmod).symm _ = _ := congr_arg _ (modByMonic_add_div _ hq) theorem degree_divByMonic_le (p q : R[X]) : degree (p /ₘ q) ≤ degree p := letI := Classical.decEq R if hp0 : p = 0 then by simp only [hp0, zero_divByMonic, le_refl] else if hq : Monic q then if h : degree q ≤ degree p then by haveI := Nontrivial.of_polynomial_ne hp0 rw [← degree_add_divByMonic hq h, degree_eq_natDegree hq.ne_zero, degree_eq_natDegree (mt (divByMonic_eq_zero_iff hq).1 (not_lt.2 h))] exact WithBot.coe_le_coe.2 (Nat.le_add_left _ _) else by unfold divByMonic divModByMonicAux simp [dif_pos hq, h, if_false, degree_zero, bot_le] else (divByMonic_eq_of_not_monic p hq).symm ▸ bot_le theorem degree_divByMonic_lt (p : R[X]) {q : R[X]} (hq : Monic q) (hp0 : p ≠ 0) (h0q : 0 < degree q) : degree (p /ₘ q) < degree p := if hpq : degree p < degree q then by haveI := Nontrivial.of_polynomial_ne hp0 rw [(divByMonic_eq_zero_iff hq).2 hpq, degree_eq_natDegree hp0] exact WithBot.bot_lt_coe _ else by haveI := Nontrivial.of_polynomial_ne hp0 rw [← degree_add_divByMonic hq (not_lt.1 hpq), degree_eq_natDegree hq.ne_zero, degree_eq_natDegree (mt (divByMonic_eq_zero_iff hq).1 hpq)] exact Nat.cast_lt.2 (Nat.lt_add_of_pos_left (Nat.cast_lt.1 <| by simpa [degree_eq_natDegree hq.ne_zero] using h0q)) theorem natDegree_divByMonic (f : R[X]) {g : R[X]} (hg : g.Monic) : natDegree (f /ₘ g) = natDegree f - natDegree g := by nontriviality R by_cases hfg : f /ₘ g = 0 · rw [hfg, natDegree_zero] rw [divByMonic_eq_zero_iff hg] at hfg rw [tsub_eq_zero_iff_le.mpr (natDegree_le_natDegree <| le_of_lt hfg)] have hgf := hfg rw [divByMonic_eq_zero_iff hg] at hgf push_neg at hgf have := degree_add_divByMonic hg hgf have hf : f ≠ 0 := by intro hf apply hfg rw [hf, zero_divByMonic] rw [degree_eq_natDegree hf, degree_eq_natDegree hg.ne_zero, degree_eq_natDegree hfg, ← Nat.cast_add, Nat.cast_inj] at this rw [← this, add_tsub_cancel_left] theorem div_modByMonic_unique {f g} (q r : R[X]) (hg : Monic g) (h : r + g * q = f ∧ degree r < degree g) : f /ₘ g = q ∧ f %ₘ g = r := by nontriviality R have h₁ : r - f %ₘ g = -g * (q - f /ₘ g) := eq_of_sub_eq_zero (by rw [← sub_eq_zero_of_eq (h.1.trans (modByMonic_add_div f hg).symm)] simp [mul_add, mul_comm, sub_eq_add_neg, add_comm, add_left_comm, add_assoc]) have h₂ : degree (r - f %ₘ g) = degree (g * (q - f /ₘ g)) := by simp [h₁] have h₄ : degree (r - f %ₘ g) < degree g := calc degree (r - f %ₘ g) ≤ max (degree r) (degree (f %ₘ g)) := degree_sub_le _ _ _ < degree g := max_lt_iff.2 ⟨h.2, degree_modByMonic_lt _ hg⟩ have h₅ : q - f /ₘ g = 0 := _root_.by_contradiction fun hqf => not_le_of_gt h₄ <| calc degree g ≤ degree g + degree (q - f /ₘ g) := by rw [degree_eq_natDegree hg.ne_zero, degree_eq_natDegree hqf] norm_cast exact Nat.le_add_right _ _ _ = degree (r - f %ₘ g) := by rw [h₂, degree_mul']; simpa [Monic.def.1 hg] exact ⟨Eq.symm <| eq_of_sub_eq_zero h₅, Eq.symm <| eq_of_sub_eq_zero <| by simpa [h₅] using h₁⟩ theorem map_mod_divByMonic [Ring S] (f : R →+* S) (hq : Monic q) : (p /ₘ q).map f = p.map f /ₘ q.map f ∧ (p %ₘ q).map f = p.map f %ₘ q.map f := by nontriviality S haveI : Nontrivial R := f.domain_nontrivial have : map f p /ₘ map f q = map f (p /ₘ q) ∧ map f p %ₘ map f q = map f (p %ₘ q) := div_modByMonic_unique ((p /ₘ q).map f) _ (hq.map f) ⟨Eq.symm <| by rw [← Polynomial.map_mul, ← Polynomial.map_add, modByMonic_add_div _ hq], calc _ ≤ degree (p %ₘ q) := degree_map_le _ < degree q := degree_modByMonic_lt _ hq _ = _ := Eq.symm <| degree_map_eq_of_leadingCoeff_ne_zero _ (by rw [Monic.def.1 hq, f.map_one]; exact one_ne_zero)⟩ exact ⟨this.1.symm, this.2.symm⟩ theorem map_divByMonic [Ring S] (f : R →+* S) (hq : Monic q) : (p /ₘ q).map f = p.map f /ₘ q.map f := (map_mod_divByMonic f hq).1 theorem map_modByMonic [Ring S] (f : R →+* S) (hq : Monic q) : (p %ₘ q).map f = p.map f %ₘ q.map f := (map_mod_divByMonic f hq).2 theorem modByMonic_eq_zero_iff_dvd (hq : Monic q) : p %ₘ q = 0 ↔ q ∣ p := ⟨fun h => by rw [← modByMonic_add_div p hq, h, zero_add]; exact dvd_mul_right _ _, fun h => by nontriviality R obtain ⟨r, hr⟩ := exists_eq_mul_right_of_dvd h by_contra hpq0 have hmod : p %ₘ q = q * (r - p /ₘ q) := by rw [modByMonic_eq_sub_mul_div _ hq, mul_sub, ← hr] have : degree (q * (r - p /ₘ q)) < degree q := hmod ▸ degree_modByMonic_lt _ hq have hrpq0 : leadingCoeff (r - p /ₘ q) ≠ 0 := fun h => hpq0 <| leadingCoeff_eq_zero.1 (by rw [hmod, leadingCoeff_eq_zero.1 h, mul_zero, leadingCoeff_zero]) have hlc : leadingCoeff q * leadingCoeff (r - p /ₘ q) ≠ 0 := by rwa [Monic.def.1 hq, one_mul] rw [degree_mul' hlc, degree_eq_natDegree hq.ne_zero, degree_eq_natDegree (mt leadingCoeff_eq_zero.2 hrpq0)] at this exact not_lt_of_ge (Nat.le_add_right _ _) (WithBot.coe_lt_coe.1 this)⟩ /-- See `Polynomial.mul_self_modByMonic` for the other multiplication order. That version, unlike this one, requires commutativity. -/ @[simp] lemma self_mul_modByMonic (hq : q.Monic) : (q * p) %ₘ q = 0 := by rw [modByMonic_eq_zero_iff_dvd hq] exact dvd_mul_right q p theorem map_dvd_map [Ring S] (f : R →+* S) (hf : Function.Injective f) {x y : R[X]} (hx : x.Monic) : x.map f ∣ y.map f ↔ x ∣ y := by rw [← modByMonic_eq_zero_iff_dvd hx, ← modByMonic_eq_zero_iff_dvd (hx.map f), ← map_modByMonic f hx] exact ⟨fun H => map_injective f hf <| by rw [H, Polynomial.map_zero], fun H => by rw [H, Polynomial.map_zero]⟩ @[simp] theorem modByMonic_one (p : R[X]) : p %ₘ 1 = 0 := (modByMonic_eq_zero_iff_dvd (by convert monic_one (R := R))).2 (one_dvd _) @[simp] theorem divByMonic_one (p : R[X]) : p /ₘ 1 = p := by conv_rhs => rw [← modByMonic_add_div p monic_one]; simp theorem sum_modByMonic_coeff (hq : q.Monic) {n : ℕ} (hn : q.degree ≤ n) : (∑ i : Fin n, monomial i ((p %ₘ q).coeff i)) = p %ₘ q := by nontriviality R exact (sum_fin (fun i c => monomial i c) (by simp) ((degree_modByMonic_lt _ hq).trans_le hn)).trans (sum_monomial_eq _) theorem mul_divByMonic_cancel_left (p : R[X]) {q : R[X]} (hmo : q.Monic) : q * p /ₘ q = p := by nontriviality R refine (div_modByMonic_unique _ 0 hmo ⟨by rw [zero_add], ?_⟩).1 rw [degree_zero] exact Ne.bot_lt fun h => hmo.ne_zero (degree_eq_bot.1 h) lemma coeff_divByMonic_X_sub_C_rec (p : R[X]) (a : R) (n : ℕ) : (p /ₘ (X - C a)).coeff n = coeff p (n + 1) + a * (p /ₘ (X - C a)).coeff (n + 1) := by nontriviality R have := monic_X_sub_C a set q := p /ₘ (X - C a) rw [← p.modByMonic_add_div this] have : degree (p %ₘ (X - C a)) < ↑(n + 1) := degree_X_sub_C a ▸ p.degree_modByMonic_lt this |>.trans_le <| WithBot.coe_le_coe.mpr le_add_self simp [q, sub_mul, add_sub, coeff_eq_zero_of_degree_lt this] theorem coeff_divByMonic_X_sub_C (p : R[X]) (a : R) (n : ℕ) : (p /ₘ (X - C a)).coeff n = ∑ i ∈ Icc (n + 1) p.natDegree, a ^ (i - (n + 1)) * p.coeff i := by wlog h : p.natDegree ≤ n generalizing n · refine Nat.decreasingInduction' (fun n hn _ ih ↦ ?_) (le_of_not_le h) ?_ · rw [coeff_divByMonic_X_sub_C_rec, ih, eq_comm, Icc_eq_cons_Ioc (Nat.succ_le.mpr hn), sum_cons, Nat.sub_self, pow_zero, one_mul, mul_sum] congr 1; refine sum_congr ?_ fun i hi ↦ ?_ · ext; simp [Nat.succ_le] rw [← mul_assoc, ← pow_succ', eq_comm, i.sub_succ', Nat.sub_add_cancel] apply Nat.le_sub_of_add_le rw [add_comm]; exact (mem_Icc.mp hi).1 · exact this _ le_rfl rw [Icc_eq_empty (Nat.lt_succ.mpr h).not_le, sum_empty] nontriviality R by_cases hp : p.natDegree = 0 · rw [(divByMonic_eq_zero_iff <| monic_X_sub_C a).mpr, coeff_zero] apply degree_lt_degree; rw [hp, natDegree_X_sub_C]; norm_num · apply coeff_eq_zero_of_natDegree_lt rw [natDegree_divByMonic p (monic_X_sub_C a), natDegree_X_sub_C] exact (Nat.pred_lt hp).trans_le h variable (R) in theorem not_isField : ¬IsField R[X] := by nontriviality R intro h letI := h.toField simpa using congr_arg natDegree (monic_X.eq_one_of_isUnit <| monic_X (R := R).ne_zero.isUnit) section multiplicity /-- An algorithm for deciding polynomial divisibility. The algorithm is "compute `p %ₘ q` and compare to `0`". See `Polynomial.modByMonic` for the algorithm that computes `%ₘ`. -/ def decidableDvdMonic [DecidableEq R] (p : R[X]) (hq : Monic q) : Decidable (q ∣ p) := decidable_of_iff (p %ₘ q = 0) (modByMonic_eq_zero_iff_dvd hq) theorem finiteMultiplicity_X_sub_C (a : R) (h0 : p ≠ 0) : FiniteMultiplicity (X - C a) p := by haveI := Nontrivial.of_polynomial_ne h0 refine finiteMultiplicity_of_degree_pos_of_monic ?_ (monic_X_sub_C _) h0 rw [degree_X_sub_C] decide @[deprecated (since := "2024-11-30")] alias multiplicity_X_sub_C_finite := finiteMultiplicity_X_sub_C /- Porting note: stripping out classical for decidability instance parameter might make for better ergonomics -/ /-- The largest power of `X - C a` which divides `p`. This *could be* computable via the divisibility algorithm `Polynomial.decidableDvdMonic`, as shown by `Polynomial.rootMultiplicity_eq_nat_find_of_nonzero` which has a computable RHS. -/ def rootMultiplicity (a : R) (p : R[X]) : ℕ := letI := Classical.decEq R if h0 : p = 0 then 0 else let _ : DecidablePred fun n : ℕ => ¬(X - C a) ^ (n + 1) ∣ p := fun n => have := decidableDvdMonic p ((monic_X_sub_C a).pow (n + 1)) inferInstanceAs (Decidable ¬_) Nat.find (finiteMultiplicity_X_sub_C a h0) /- Porting note: added the following due to diamond with decidableProp and decidableDvdMonic see also [Zulip] (https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/non-defeq.20aliased.20instance) -/ theorem rootMultiplicity_eq_nat_find_of_nonzero [DecidableEq R] {p : R[X]} (p0 : p ≠ 0) {a : R} : letI : DecidablePred fun n : ℕ => ¬(X - C a) ^ (n + 1) ∣ p := fun n => have := decidableDvdMonic p ((monic_X_sub_C a).pow (n + 1)) inferInstanceAs (Decidable ¬_) rootMultiplicity a p = Nat.find (finiteMultiplicity_X_sub_C a p0) := by dsimp [rootMultiplicity] cases Subsingleton.elim ‹DecidableEq R› (Classical.decEq R) rw [dif_neg p0] theorem rootMultiplicity_eq_multiplicity [DecidableEq R] (p : R[X]) (a : R) : rootMultiplicity a p = if p = 0 then 0 else multiplicity (X - C a) p := by simp only [rootMultiplicity, multiplicity, emultiplicity] split · rfl rename_i h simp only [finiteMultiplicity_X_sub_C a h, ↓reduceDIte] rw [← ENat.some_eq_coe, WithTop.untopD_coe] congr @[simp] theorem rootMultiplicity_zero {x : R} : rootMultiplicity x 0 = 0 := dif_pos rfl @[simp] theorem rootMultiplicity_C (r a : R) : rootMultiplicity a (C r) = 0 := by cases subsingleton_or_nontrivial R · rw [Subsingleton.elim (C r) 0, rootMultiplicity_zero] classical rw [rootMultiplicity_eq_multiplicity] split_ifs with hr · rfl have h : natDegree (C r) < natDegree (X - C a) := by simp simp_rw [multiplicity_eq_zero.mpr ((monic_X_sub_C a).not_dvd_of_natDegree_lt hr h)] theorem pow_rootMultiplicity_dvd (p : R[X]) (a : R) : (X - C a) ^ rootMultiplicity a p ∣ p := letI := Classical.decEq R if h : p = 0 then by simp [h] else by classical rw [rootMultiplicity_eq_multiplicity, if_neg h]; apply pow_multiplicity_dvd theorem pow_mul_divByMonic_rootMultiplicity_eq (p : R[X]) (a : R) : (X - C a) ^ rootMultiplicity a p * (p /ₘ (X - C a) ^ rootMultiplicity a p) = p := by have : Monic ((X - C a) ^ rootMultiplicity a p) := (monic_X_sub_C _).pow _ conv_rhs => rw [← modByMonic_add_div p this, (modByMonic_eq_zero_iff_dvd this).2 (pow_rootMultiplicity_dvd _ _)] simp theorem exists_eq_pow_rootMultiplicity_mul_and_not_dvd (p : R[X]) (hp : p ≠ 0) (a : R) : ∃ q : R[X], p = (X - C a) ^ p.rootMultiplicity a * q ∧ ¬ (X - C a) ∣ q := by classical rw [rootMultiplicity_eq_multiplicity, if_neg hp] apply (finiteMultiplicity_X_sub_C a hp).exists_eq_pow_mul_and_not_dvd end multiplicity end Ring section CommRing variable [CommRing R] {p p₁ p₂ q : R[X]} @[simp] theorem modByMonic_X_sub_C_eq_C_eval (p : R[X]) (a : R) : p %ₘ (X - C a) = C (p.eval a) := by nontriviality R have h : (p %ₘ (X - C a)).eval a = p.eval a := by rw [modByMonic_eq_sub_mul_div _ (monic_X_sub_C a), eval_sub, eval_mul, eval_sub, eval_X, eval_C, sub_self, zero_mul, sub_zero] have : degree (p %ₘ (X - C a)) < 1 := degree_X_sub_C a ▸ degree_modByMonic_lt p (monic_X_sub_C a) have : degree (p %ₘ (X - C a)) ≤ 0 := by revert this cases degree (p %ₘ (X - C a)) · exact fun _ => bot_le · exact fun h => WithBot.coe_le_coe.2 (Nat.le_of_lt_succ (WithBot.coe_lt_coe.1 h)) rw [eq_C_of_degree_le_zero this, eval_C] at h rw [eq_C_of_degree_le_zero this, h] theorem mul_divByMonic_eq_iff_isRoot : (X - C a) * (p /ₘ (X - C a)) = p ↔ IsRoot p a := .trans ⟨fun h => by rw [← h, eval_mul, eval_sub, eval_X, eval_C, sub_self, zero_mul], fun h => by conv_rhs => rw [← modByMonic_add_div p (monic_X_sub_C a)] rw [modByMonic_X_sub_C_eq_C_eval, h, C_0, zero_add]⟩ IsRoot.def.symm theorem dvd_iff_isRoot : X - C a ∣ p ↔ IsRoot p a := ⟨fun h => by rwa [← modByMonic_eq_zero_iff_dvd (monic_X_sub_C _), modByMonic_X_sub_C_eq_C_eval, ← C_0, C_inj] at h, fun h => ⟨p /ₘ (X - C a), by rw [mul_divByMonic_eq_iff_isRoot.2 h]⟩⟩ theorem X_sub_C_dvd_sub_C_eval : X - C a ∣ p - C (p.eval a) := by rw [dvd_iff_isRoot, IsRoot, eval_sub, eval_C, sub_self] -- TODO: generalize this to Ring. In general, 0 can be replaced by any element in the center of R. theorem modByMonic_X (p : R[X]) : p %ₘ X = C (p.eval 0) := by rw [← modByMonic_X_sub_C_eq_C_eval, C_0, sub_zero] theorem eval₂_modByMonic_eq_self_of_root [CommRing S] {f : R →+* S} {p q : R[X]} (hq : q.Monic) {x : S} (hx : q.eval₂ f x = 0) : (p %ₘ q).eval₂ f x = p.eval₂ f x := by rw [modByMonic_eq_sub_mul_div p hq, eval₂_sub, eval₂_mul, hx, zero_mul, sub_zero] theorem sub_dvd_eval_sub (a b : R) (p : R[X]) : a - b ∣ p.eval a - p.eval b := by suffices X - C b ∣ p - C (p.eval b) by simpa only [coe_evalRingHom, eval_sub, eval_X, eval_C] using (evalRingHom a).map_dvd this simp [dvd_iff_isRoot] @[simp] theorem rootMultiplicity_eq_zero_iff {p : R[X]} {x : R} : rootMultiplicity x p = 0 ↔ IsRoot p x → p = 0 := by classical simp only [rootMultiplicity_eq_multiplicity, ite_eq_left_iff, Nat.cast_zero, multiplicity_eq_zero, dvd_iff_isRoot, not_imp_not] theorem rootMultiplicity_eq_zero {p : R[X]} {x : R} (h : ¬IsRoot p x) : rootMultiplicity x p = 0 := rootMultiplicity_eq_zero_iff.2 fun h' => (h h').elim @[simp] theorem rootMultiplicity_pos' {p : R[X]} {x : R} : 0 < rootMultiplicity x p ↔ p ≠ 0 ∧ IsRoot p x := by rw [pos_iff_ne_zero, Ne, rootMultiplicity_eq_zero_iff, Classical.not_imp, and_comm] theorem rootMultiplicity_pos {p : R[X]} (hp : p ≠ 0) {x : R} : 0 < rootMultiplicity x p ↔ IsRoot p x := rootMultiplicity_pos'.trans (and_iff_right hp) theorem eval_divByMonic_pow_rootMultiplicity_ne_zero {p : R[X]} (a : R) (hp : p ≠ 0) : eval a (p /ₘ (X - C a) ^ rootMultiplicity a p) ≠ 0 := by classical haveI : Nontrivial R := Nontrivial.of_polynomial_ne hp rw [Ne, ← IsRoot, ← dvd_iff_isRoot] rintro ⟨q, hq⟩ have := pow_mul_divByMonic_rootMultiplicity_eq p a rw [hq, ← mul_assoc, ← pow_succ, rootMultiplicity_eq_multiplicity, if_neg hp] at this exact (finiteMultiplicity_of_degree_pos_of_monic (show (0 : WithBot ℕ) < degree (X - C a) by rw [degree_X_sub_C]; decide) (monic_X_sub_C _) hp).not_pow_dvd_of_multiplicity_lt (Nat.lt_succ_self _) (dvd_of_mul_right_eq _ this) /-- See `Polynomial.self_mul_modByMonic` for the other multiplication order. This version, unlike that one, requires commutativity. -/ @[simp] lemma mul_self_modByMonic (hq : q.Monic) : (p * q) %ₘ q = 0 := by rw [modByMonic_eq_zero_iff_dvd hq] exact dvd_mul_left q p lemma modByMonic_eq_of_dvd_sub (hq : q.Monic) (h : q ∣ p₁ - p₂) : p₁ %ₘ q = p₂ %ₘ q := by
nontriviality R obtain ⟨f, sub_eq⟩ := h refine (div_modByMonic_unique (p₂ /ₘ q + f) _ hq ⟨?_, degree_modByMonic_lt _ hq⟩).2 rw [sub_eq_iff_eq_add.mp sub_eq, mul_add, ← add_assoc, modByMonic_add_div _ hq, add_comm]
Mathlib/Algebra/Polynomial/Div.lean
664
667
/- 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.Minimal import Mathlib.Order.Zorn import Mathlib.Topology.ContinuousOn /-! # Irreducibility in topological spaces ## Main definitions * `IrreducibleSpace`: a typeclass applying to topological spaces, stating that the space is nonempty and does not admit a nontrivial pair of disjoint opens. * `IsIrreducible`: for a nonempty set in a topological space, the property that the set is an irreducible space in the subspace topology. ## On the definition of irreducible and connected sets/spaces In informal mathematics, irreducible spaces are assumed to be nonempty. We formalise the predicate without that assumption as `IsPreirreducible`. In other words, the only difference is whether the empty space counts as irreducible. 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 Topology variable {X : Type*} {Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {s t : Set X} section Preirreducible /-- A preirreducible set `s` is one where there is no non-trivial pair of disjoint opens on `s`. -/ def IsPreirreducible (s : Set X) : Prop := ∀ u v : Set X, IsOpen u → IsOpen v → (s ∩ u).Nonempty → (s ∩ v).Nonempty → (s ∩ (u ∩ v)).Nonempty /-- An irreducible set `s` is one that is nonempty and where there is no non-trivial pair of disjoint opens on `s`. -/ def IsIrreducible (s : Set X) : Prop := s.Nonempty ∧ IsPreirreducible s theorem IsIrreducible.nonempty (h : IsIrreducible s) : s.Nonempty := h.1 theorem IsIrreducible.isPreirreducible (h : IsIrreducible s) : IsPreirreducible s := h.2 theorem isPreirreducible_empty : IsPreirreducible (∅ : Set X) := fun _ _ _ _ _ ⟨_, h1, _⟩ => h1.elim theorem Set.Subsingleton.isPreirreducible (hs : s.Subsingleton) : IsPreirreducible s := fun _u _v _ _ ⟨_x, hxs, hxu⟩ ⟨y, hys, hyv⟩ => ⟨y, hys, hs hxs hys ▸ hxu, hyv⟩ theorem isPreirreducible_singleton {x} : IsPreirreducible ({x} : Set X) := subsingleton_singleton.isPreirreducible theorem isIrreducible_singleton {x} : IsIrreducible ({x} : Set X) := ⟨singleton_nonempty x, isPreirreducible_singleton⟩ theorem isPreirreducible_iff_closure : IsPreirreducible (closure s) ↔ IsPreirreducible s := forall₄_congr fun u v hu hv => by iterate 3 rw [closure_inter_open_nonempty_iff] exacts [hu.inter hv, hv, hu] theorem isIrreducible_iff_closure : IsIrreducible (closure s) ↔ IsIrreducible s :=
and_congr closure_nonempty_iff isPreirreducible_iff_closure protected alias ⟨_, IsPreirreducible.closure⟩ := isPreirreducible_iff_closure
Mathlib/Topology/Irreducible.lean
70
73
/- 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.Analysis.InnerProductSpace.Convex import Mathlib.Analysis.InnerProductSpace.PiL2 import Mathlib.Combinatorics.Additive.AP.Three.Defs import Mathlib.Combinatorics.Pigeonhole import Mathlib.Data.Complex.ExponentialBounds /-! # Behrend's bound on Roth numbers This file proves Behrend's lower bound on Roth numbers. This says that we can find a subset of `{1, ..., n}` of size `n / exp (O (sqrt (log n)))` which does not contain arithmetic progressions of length `3`. The idea is that the sphere (in the `n` dimensional Euclidean space) doesn't contain arithmetic progressions (literally) because the corresponding ball is strictly convex. Thus we can take integer points on that sphere and map them onto `ℕ` in a way that preserves arithmetic progressions (`Behrend.map`). ## Main declarations * `Behrend.sphere`: The intersection of the Euclidean sphere with the positive integer quadrant. This is the set that we will map on `ℕ`. * `Behrend.map`: Given a natural number `d`, `Behrend.map d : ℕⁿ → ℕ` reads off the coordinates as digits in base `d`. * `Behrend.card_sphere_le_rothNumberNat`: Implicit lower bound on Roth numbers in terms of `Behrend.sphere`. * `Behrend.roth_lower_bound`: Behrend's explicit lower bound on Roth numbers. ## References * [Bryan Gillespie, *Behrend’s Construction*] (http://www.epsilonsmall.com/resources/behrends-construction/behrend.pdf) * Behrend, F. A., "On sets of integers which contain no three terms in arithmetical progression" * [Wikipedia, *Salem-Spencer set*](https://en.wikipedia.org/wiki/Salem–Spencer_set) ## Tags 3AP-free, Salem-Spencer, Behrend construction, arithmetic progression, sphere, strictly convex -/ assert_not_exists IsConformalMap Conformal open Nat hiding log open Finset Metric Real open scoped Pointwise /-- The frontier of a closed strictly convex set only contains trivial arithmetic progressions. The idea is that an arithmetic progression is contained on a line and the frontier of a strictly convex set does not contain lines. -/ lemma threeAPFree_frontier {𝕜 E : Type*} [Field 𝕜] [LinearOrder 𝕜] [IsStrictOrderedRing 𝕜] [TopologicalSpace E] [AddCommMonoid E] [Module 𝕜 E] {s : Set E} (hs₀ : IsClosed s) (hs₁ : StrictConvex 𝕜 s) : ThreeAPFree (frontier s) := by intro a ha b hb c hc habc obtain rfl : (1 / 2 : 𝕜) • a + (1 / 2 : 𝕜) • c = b := by rwa [← smul_add, one_div, inv_smul_eq_iff₀ (show (2 : 𝕜) ≠ 0 by norm_num), two_smul] have := hs₁.eq (hs₀.frontier_subset ha) (hs₀.frontier_subset hc) one_half_pos one_half_pos (add_halves _) hb.2 simp [this, ← add_smul] ring_nf simp lemma threeAPFree_sphere {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [StrictConvexSpace ℝ E] (x : E) (r : ℝ) : ThreeAPFree (sphere x r) := by obtain rfl | hr := eq_or_ne r 0 · rw [sphere_zero] exact threeAPFree_singleton _ · convert threeAPFree_frontier isClosed_closedBall (strictConvex_closedBall ℝ x r) exact (frontier_closedBall _ hr).symm namespace Behrend variable {n d k N : ℕ} {x : Fin n → ℕ} /-! ### Turning the sphere into 3AP-free set We define `Behrend.sphere`, the intersection of the $L^2$ sphere with the positive quadrant of integer points. Because the $L^2$ closed ball is strictly convex, the $L^2$ sphere and `Behrend.sphere` are 3AP-free (`threeAPFree_sphere`). Then we can turn this set in `Fin n → ℕ` into a set in `ℕ` using `Behrend.map`, which preserves `ThreeAPFree` because it is an additive monoid homomorphism. -/ /-- The box `{0, ..., d - 1}^n` as a `Finset`. -/ def box (n d : ℕ) : Finset (Fin n → ℕ) := Fintype.piFinset fun _ => range d theorem mem_box : x ∈ box n d ↔ ∀ i, x i < d := by simp only [box, Fintype.mem_piFinset, mem_range] @[simp] theorem card_box : #(box n d) = d ^ n := by simp [box] @[simp] theorem box_zero : box (n + 1) 0 = ∅ := by simp [box] /-- The intersection of the sphere of radius `√k` with the integer points in the positive quadrant. -/ def sphere (n d k : ℕ) : Finset (Fin n → ℕ) := {x ∈ box n d | ∑ i, x i ^ 2 = k} theorem sphere_zero_subset : sphere n d 0 ⊆ 0 := fun x => by simp [sphere, funext_iff] @[simp] theorem sphere_zero_right (n k : ℕ) : sphere (n + 1) 0 k = ∅ := by simp [sphere] theorem sphere_subset_box : sphere n d k ⊆ box n d := filter_subset _ _ theorem norm_of_mem_sphere {x : Fin n → ℕ} (hx : x ∈ sphere n d k) : ‖(WithLp.equiv 2 _).symm ((↑) ∘ x : Fin n → ℝ)‖ = √↑k := by rw [EuclideanSpace.norm_eq] dsimp simp_rw [abs_cast, ← cast_pow, ← cast_sum, (mem_filter.1 hx).2] theorem sphere_subset_preimage_metric_sphere : (sphere n d k : Set (Fin n → ℕ)) ⊆ (fun x : Fin n → ℕ => (WithLp.equiv 2 _).symm ((↑) ∘ x : Fin n → ℝ)) ⁻¹' Metric.sphere (0 : PiLp 2 fun _ : Fin n => ℝ) (√↑k) := fun x hx => by rw [Set.mem_preimage, mem_sphere_zero_iff_norm, norm_of_mem_sphere hx] /-- The map that appears in Behrend's bound on Roth numbers. -/ @[simps] def map (d : ℕ) : (Fin n → ℕ) →+ ℕ where toFun a := ∑ i, a i * d ^ (i : ℕ) map_zero' := by simp_rw [Pi.zero_apply, zero_mul, sum_const_zero] map_add' a b := by simp_rw [Pi.add_apply, add_mul, sum_add_distrib] theorem map_zero (d : ℕ) (a : Fin 0 → ℕ) : map d a = 0 := by simp [map] theorem map_succ (a : Fin (n + 1) → ℕ) : map d a = a 0 + (∑ x : Fin n, a x.succ * d ^ (x : ℕ)) * d := by simp [map, Fin.sum_univ_succ, _root_.pow_succ, ← mul_assoc, ← sum_mul] theorem map_succ' (a : Fin (n + 1) → ℕ) : map d a = a 0 + map d (a ∘ Fin.succ) * d := map_succ _ theorem map_monotone (d : ℕ) : Monotone (map d : (Fin n → ℕ) → ℕ) := fun x y h => by dsimp; exact sum_le_sum fun i _ => Nat.mul_le_mul_right _ <| h i theorem map_mod (a : Fin n.succ → ℕ) : map d a % d = a 0 % d := by rw [map_succ, Nat.add_mul_mod_self_right] theorem map_eq_iff {x₁ x₂ : Fin n.succ → ℕ} (hx₁ : ∀ i, x₁ i < d) (hx₂ : ∀ i, x₂ i < d) : map d x₁ = map d x₂ ↔ x₁ 0 = x₂ 0 ∧ map d (x₁ ∘ Fin.succ) = map d (x₂ ∘ Fin.succ) := by refine ⟨fun h => ?_, fun h => by rw [map_succ', map_succ', h.1, h.2]⟩ have : x₁ 0 = x₂ 0 := by rw [← mod_eq_of_lt (hx₁ _), ← map_mod, ← mod_eq_of_lt (hx₂ _), ← map_mod, h] rw [map_succ, map_succ, this, add_right_inj, mul_eq_mul_right_iff] at h exact ⟨this, h.resolve_right (pos_of_gt (hx₁ 0)).ne'⟩ theorem map_injOn : {x : Fin n → ℕ | ∀ i, x i < d}.InjOn (map d) := by intro x₁ hx₁ x₂ hx₂ h induction n with | zero => simp [eq_iff_true_of_subsingleton] | succ n ih => ext i have x := (map_eq_iff hx₁ hx₂).1 h exact Fin.cases x.1 (congr_fun <| ih (fun _ => hx₁ _) (fun _ => hx₂ _) x.2) i theorem map_le_of_mem_box (hx : x ∈ box n d) : map (2 * d - 1) x ≤ ∑ i : Fin n, (d - 1) * (2 * d - 1) ^ (i : ℕ) := map_monotone (2 * d - 1) fun _ => Nat.le_sub_one_of_lt <| mem_box.1 hx _ nonrec theorem threeAPFree_sphere : ThreeAPFree (sphere n d k : Set (Fin n → ℕ)) := by set f : (Fin n → ℕ) →+ EuclideanSpace ℝ (Fin n) := { toFun := fun f => ((↑) : ℕ → ℝ) ∘ f map_zero' := funext fun _ => cast_zero map_add' := fun _ _ => funext fun _ => cast_add _ _ } refine ThreeAPFree.of_image (AddMonoidHomClass.isAddFreimanHom f (Set.mapsTo_image _ _)) cast_injective.comp_left.injOn (Set.subset_univ _) ?_ refine (threeAPFree_sphere 0 (√↑k)).mono (Set.image_subset_iff.2 fun x => ?_) rw [Set.mem_preimage, mem_sphere_zero_iff_norm] exact norm_of_mem_sphere theorem threeAPFree_image_sphere : ThreeAPFree ((sphere n d k).image (map (2 * d - 1)) : Set ℕ) := by rw [coe_image] apply ThreeAPFree.image' (α := Fin n → ℕ) (β := ℕ) (s := sphere n d k) (map (2 * d - 1)) (map_injOn.mono _) threeAPFree_sphere rw [Set.add_subset_iff] rintro a ha b hb i have hai := mem_box.1 (sphere_subset_box ha) i have hbi := mem_box.1 (sphere_subset_box hb) i rw [lt_tsub_iff_right, ← succ_le_iff, two_mul] exact (add_add_add_comm _ _ 1 1).trans_le (_root_.add_le_add hai hbi) theorem sum_sq_le_of_mem_box (hx : x ∈ box n d) : ∑ i : Fin n, x i ^ 2 ≤ n * (d - 1) ^ 2 := by rw [mem_box] at hx have : ∀ i, x i ^ 2 ≤ (d - 1) ^ 2 := fun i => Nat.pow_le_pow_left (Nat.le_sub_one_of_lt (hx i)) _ exact (sum_le_card_nsmul univ _ _ fun i _ => this i).trans (by rw [card_fin, smul_eq_mul]) theorem sum_eq : (∑ i : Fin n, d * (2 * d + 1) ^ (i : ℕ)) = ((2 * d + 1) ^ n - 1) / 2 := by refine (Nat.div_eq_of_eq_mul_left zero_lt_two ?_).symm rw [← sum_range fun i => d * (2 * d + 1) ^ (i : ℕ), ← mul_sum, mul_right_comm, mul_comm d, ← geom_sum_mul_add, add_tsub_cancel_right, mul_comm] theorem sum_lt : (∑ i : Fin n, d * (2 * d + 1) ^ (i : ℕ)) < (2 * d + 1) ^ n := sum_eq.trans_lt <| (Nat.div_le_self _ 2).trans_lt <| pred_lt (pow_pos (succ_pos _) _).ne' theorem card_sphere_le_rothNumberNat (n d k : ℕ) : #(sphere n d k) ≤ rothNumberNat ((2 * d - 1) ^ n) := by cases n · dsimp; refine (card_le_univ _).trans_eq ?_; rfl cases d · simp apply threeAPFree_image_sphere.le_rothNumberNat _ _ (card_image_of_injOn _) · simp only [subset_iff, mem_image, and_imp, forall_exists_index, mem_range, forall_apply_eq_imp_iff₂, sphere, mem_filter] rintro _ x hx _ rfl exact (map_le_of_mem_box hx).trans_lt sum_lt apply map_injOn.mono fun x => ?_ simp only [mem_coe, sphere, mem_filter, mem_box, and_imp, two_mul] exact fun h _ i => (h i).trans_le le_self_add /-! ### Optimization Now that we know how to turn the integer points of any sphere into a 3AP-free set, we find a sphere containing many integer points by the pigeonhole principle. This gives us an implicit bound that we then optimize by tweaking the parameters. The (almost) optimal parameters are `Behrend.nValue` and `Behrend.dValue`. -/ theorem exists_large_sphere_aux (n d : ℕ) : ∃ k ∈ range (n * (d - 1) ^ 2 + 1), (↑(d ^ n) / ((n * (d - 1) ^ 2 :) + 1) : ℝ) ≤ #(sphere n d k) := by refine exists_le_card_fiber_of_nsmul_le_card_of_maps_to (fun x hx => ?_) nonempty_range_succ ?_ · rw [mem_range, Nat.lt_succ_iff] exact sum_sq_le_of_mem_box hx · rw [card_range, _root_.nsmul_eq_mul, mul_div_assoc', cast_add_one, mul_div_cancel_left₀, card_box] exact (cast_add_one_pos _).ne' theorem exists_large_sphere (n d : ℕ) : ∃ k, ((d ^ n :) / (n * d ^ 2 :) : ℝ) ≤ #(sphere n d k) := by obtain ⟨k, -, hk⟩ := exists_large_sphere_aux n d refine ⟨k, ?_⟩ obtain rfl | hn := n.eq_zero_or_pos · simp obtain rfl | hd := d.eq_zero_or_pos · simp refine (div_le_div_of_nonneg_left ?_ ?_ ?_).trans hk · exact cast_nonneg _ · exact cast_add_one_pos _ simp only [← le_sub_iff_add_le', cast_mul, ← mul_sub, cast_pow, cast_sub hd, sub_sq, one_pow, cast_one, mul_one, sub_add, sub_sub_self] apply one_le_mul_of_one_le_of_one_le · rwa [one_le_cast] rw [_root_.le_sub_iff_add_le] norm_num exact one_le_cast.2 hd theorem bound_aux' (n d : ℕ) : ((d ^ n :) / (n * d ^ 2 :) : ℝ) ≤ rothNumberNat ((2 * d - 1) ^ n) := let ⟨_, h⟩ := exists_large_sphere n d h.trans <| cast_le.2 <| card_sphere_le_rothNumberNat _ _ _ theorem bound_aux (hd : d ≠ 0) (hn : 2 ≤ n) : (d ^ (n - 2 :) / n : ℝ) ≤ rothNumberNat ((2 * d - 1) ^ n) := by convert bound_aux' n d using 1 rw [cast_mul, cast_pow, mul_comm, ← div_div, pow_sub₀ _ _ hn, ← div_eq_mul_inv, cast_pow] rwa [cast_ne_zero] open scoped Filter Topology open Real section NumericalBounds theorem log_two_mul_two_le_sqrt_log_eight : log 2 * 2 ≤ √(log 8) := by have : (8 : ℝ) = 2 ^ ((3 : ℕ) : ℝ) := by rw [rpow_natCast]; norm_num rw [this, log_rpow zero_lt_two (3 : ℕ)] apply le_sqrt_of_sq_le rw [mul_pow, sq (log 2), mul_assoc, mul_comm] refine mul_le_mul_of_nonneg_right ?_ (log_nonneg one_le_two) rw [← le_div_iff₀] on_goal 1 => apply log_two_lt_d9.le.trans all_goals norm_num1 theorem two_div_one_sub_two_div_e_le_eight : 2 / (1 - 2 / exp 1) ≤ 8 := by rw [div_le_iff₀, mul_sub, mul_one, mul_div_assoc', le_sub_comm, div_le_iff₀ (exp_pos _)] · linarith [exp_one_gt_d9] rw [sub_pos, div_lt_one] <;> exact exp_one_gt_d9.trans' (by norm_num) theorem le_sqrt_log (hN : 4096 ≤ N) : log (2 / (1 - 2 / exp 1)) * (69 / 50) ≤ √(log ↑N) := by have : (12 : ℕ) * log 2 ≤ log N := by rw [← log_rpow zero_lt_two, rpow_natCast] exact log_le_log (by positivity) (mod_cast hN) refine (mul_le_mul_of_nonneg_right (log_le_log ?_ two_div_one_sub_two_div_e_le_eight) <| by norm_num1).trans ?_ · refine div_pos zero_lt_two ?_ rw [sub_pos, div_lt_one (exp_pos _)] exact exp_one_gt_d9.trans_le' (by norm_num1) have l8 : log 8 = (3 : ℕ) * log 2 := by rw [← log_rpow zero_lt_two, rpow_natCast] norm_num rw [l8] apply le_sqrt_of_sq_le (le_trans _ this) rw [mul_right_comm, mul_pow, sq (log 2), ← mul_assoc] apply mul_le_mul_of_nonneg_right _ (log_nonneg one_le_two) rw [← le_div_iff₀'] · exact log_two_lt_d9.le.trans (by norm_num1) exact sq_pos_of_ne_zero (by norm_num1) theorem exp_neg_two_mul_le {x : ℝ} (hx : 0 < x) : exp (-2 * x) < exp (2 - ⌈x⌉₊) / ⌈x⌉₊ := by have h₁ := ceil_lt_add_one hx.le have h₂ : 1 - x ≤ 2 - ⌈x⌉₊ := by linarith calc _ ≤ exp (1 - x) / (x + 1) := ?_ _ ≤ exp (2 - ⌈x⌉₊) / (x + 1) := by gcongr _ < _ := by gcongr rw [le_div_iff₀ (add_pos hx zero_lt_one), ← le_div_iff₀' (exp_pos _), ← exp_sub, neg_mul, sub_neg_eq_add, two_mul, sub_add_add_cancel, add_comm _ x] exact le_trans (le_add_of_nonneg_right zero_le_one) (add_one_le_exp _) theorem div_lt_floor {x : ℝ} (hx : 2 / (1 - 2 / exp 1) ≤ x) : x / exp 1 < (⌊x / 2⌋₊ : ℝ) := by apply lt_of_le_of_lt _ (sub_one_lt_floor _) have : 0 < 1 - 2 / exp 1 := by rw [sub_pos, div_lt_one (exp_pos _)] exact lt_of_le_of_lt (by norm_num) exp_one_gt_d9 rwa [le_sub_comm, div_eq_mul_one_div x, div_eq_mul_one_div x, ← mul_sub, div_sub', ← div_eq_mul_one_div, mul_div_assoc', one_le_div, ← div_le_iff₀ this] · exact zero_lt_two · exact two_ne_zero theorem ceil_lt_mul {x : ℝ} (hx : 50 / 19 ≤ x) : (⌈x⌉₊ : ℝ) < 1.38 * x := by refine (ceil_lt_add_one <| hx.trans' <| by norm_num).trans_le ?_ rw [← le_sub_iff_add_le', ← sub_one_mul] have : (1.38 : ℝ) = 69 / 50 := by norm_num rwa [this, show (69 / 50 - 1 : ℝ) = (50 / 19)⁻¹ by norm_num1, ← div_eq_inv_mul, one_le_div] norm_num1 end NumericalBounds /-- The (almost) optimal value of `n` in `Behrend.bound_aux`. -/ noncomputable def nValue (N : ℕ) : ℕ := ⌈√(log N)⌉₊ /-- The (almost) optimal value of `d` in `Behrend.bound_aux`. -/ noncomputable def dValue (N : ℕ) : ℕ := ⌊(N : ℝ) ^ (nValue N : ℝ)⁻¹ / 2⌋₊ theorem nValue_pos (hN : 2 ≤ N) : 0 < nValue N := ceil_pos.2 <| Real.sqrt_pos.2 <| log_pos <| one_lt_cast.2 <| hN
theorem three_le_nValue (hN : 64 ≤ N) : 3 ≤ nValue N := by rw [nValue, ← lt_iff_add_one_le, lt_ceil, cast_two] apply lt_sqrt_of_sq_lt have : (2 : ℝ) ^ ((6 : ℕ) : ℝ) ≤ N := by rw [rpow_natCast] exact (cast_le.2 hN).trans' (by norm_num1) apply lt_of_lt_of_le _ (log_le_log (rpow_pos_of_pos zero_lt_two _) this) rw [log_rpow zero_lt_two, ← div_lt_iff₀'] · exact log_two_gt_d9.trans_le' (by norm_num1)
Mathlib/Combinatorics/Additive/AP/Three/Behrend.lean
351
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/- Copyright (c) 2018 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Chris Hughes, Mario Carneiro -/ import Mathlib.Algebra.Field.IsField import Mathlib.Data.Fin.VecNotation import Mathlib.Data.Nat.Choose.Sum import Mathlib.LinearAlgebra.Finsupp.LinearCombination import Mathlib.RingTheory.Ideal.Maximal import Mathlib.Tactic.FinCases /-! # Ideals over a ring This file contains an assortment of definitions and results for `Ideal R`, the type of (left) ideals over a ring `R`. Note that over commutative rings, left ideals and two-sided ideals are equivalent. ## Implementation notes `Ideal R` is implemented using `Submodule R R`, where `•` is interpreted as `*`. ## TODO Support right ideals, and two-sided ideals over non-commutative rings. -/ variable {ι α β F : Type*} open Set Function open Pointwise section Semiring namespace Ideal variable {α : ι → Type*} [Π i, Semiring (α i)] (I : Π i, Ideal (α i)) section Pi /-- `Πᵢ Iᵢ` as an ideal of `Πᵢ Rᵢ`. -/ def pi : Ideal (Π i, α i) where carrier := { x | ∀ i, x i ∈ I i } zero_mem' i := (I i).zero_mem add_mem' ha hb i := (I i).add_mem (ha i) (hb i) smul_mem' a _b hb i := (I i).mul_mem_left (a i) (hb i) theorem mem_pi (x : Π i, α i) : x ∈ pi I ↔ ∀ i, x i ∈ I i := Iff.rfl instance (priority := low) [∀ i, (I i).IsTwoSided] : (pi I).IsTwoSided := ⟨fun _b hb i ↦ mul_mem_right _ _ (hb i)⟩ end Pi section Commute variable {α : Type*} [Semiring α] (I : Ideal α) {a b : α} theorem add_pow_mem_of_pow_mem_of_le_of_commute {m n k : ℕ} (ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hk : m + n ≤ k + 1) (hab : Commute a b) : (a + b) ^ k ∈ I := by simp_rw [hab.add_pow, ← Nat.cast_comm] apply I.sum_mem intro c _ apply mul_mem_left by_cases h : m ≤ c · rw [hab.pow_pow] exact I.mul_mem_left _ (I.pow_mem_of_pow_mem ha h) · refine I.mul_mem_left _ (I.pow_mem_of_pow_mem hb ?_) omega theorem add_pow_add_pred_mem_of_pow_mem_of_commute {m n : ℕ} (ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hab : Commute a b) : (a + b) ^ (m + n - 1) ∈ I := I.add_pow_mem_of_pow_mem_of_le_of_commute ha hb (by rw [← Nat.sub_le_iff_le_add]) hab end Commute end Ideal end Semiring section CommSemiring variable {a b : α} -- A separate namespace definition is needed because the variables were historically in a different -- order. namespace Ideal variable [CommSemiring α] (I : Ideal α) theorem add_pow_mem_of_pow_mem_of_le {m n k : ℕ} (ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hk : m + n ≤ k + 1) : (a + b) ^ k ∈ I := I.add_pow_mem_of_pow_mem_of_le_of_commute ha hb hk (Commute.all ..) theorem add_pow_add_pred_mem_of_pow_mem {m n : ℕ} (ha : a ^ m ∈ I) (hb : b ^ n ∈ I) : (a + b) ^ (m + n - 1) ∈ I := I.add_pow_add_pred_mem_of_pow_mem_of_commute ha hb (Commute.all ..) theorem pow_multiset_sum_mem_span_pow [DecidableEq α] (s : Multiset α) (n : ℕ) : s.sum ^ (Multiset.card s * n + 1) ∈ span ((s.map fun (x : α) ↦ x ^ (n + 1)).toFinset : Set α) := by induction' s using Multiset.induction_on with a s hs · simp simp only [Finset.coe_insert, Multiset.map_cons, Multiset.toFinset_cons, Multiset.sum_cons, Multiset.card_cons, add_pow] refine Submodule.sum_mem _ ?_ intro c _hc rw [mem_span_insert] by_cases h : n + 1 ≤ c · refine ⟨a ^ (c - (n + 1)) * s.sum ^ ((Multiset.card s + 1) * n + 1 - c) * ((Multiset.card s + 1) * n + 1).choose c, 0, Submodule.zero_mem _, ?_⟩ rw [mul_comm _ (a ^ (n + 1))] simp_rw [← mul_assoc] rw [← pow_add, add_zero, add_tsub_cancel_of_le h] · use 0 simp_rw [zero_mul, zero_add] refine ⟨_, ?_, rfl⟩ replace h : c ≤ n := Nat.lt_succ_iff.mp (not_le.mp h) have : (Multiset.card s + 1) * n + 1 - c = Multiset.card s * n + 1 + (n - c) := by rw [add_mul, one_mul, add_assoc, add_comm n 1, ← add_assoc, add_tsub_assoc_of_le h] rw [this, pow_add] simp_rw [mul_assoc, mul_comm (s.sum ^ (Multiset.card s * n + 1)), ← mul_assoc] exact mul_mem_left _ _ hs theorem sum_pow_mem_span_pow {ι} (s : Finset ι) (f : ι → α) (n : ℕ) : (∑ i ∈ s, f i) ^ (s.card * n + 1) ∈ span ((fun i => f i ^ (n + 1)) '' s) := by classical simpa only [Multiset.card_map, Multiset.map_map, comp_apply, Multiset.toFinset_map, Finset.coe_image, Finset.val_toFinset] using pow_multiset_sum_mem_span_pow (s.1.map f) n theorem span_pow_eq_top (s : Set α) (hs : span s = ⊤) (n : ℕ) : span ((fun (x : α) => x ^ n) '' s) = ⊤ := by rw [eq_top_iff_one] rcases n with - | n · obtain rfl | ⟨x, hx⟩ := eq_empty_or_nonempty s · rw [Set.image_empty, hs] trivial · exact subset_span ⟨_, hx, pow_zero _⟩ rw [eq_top_iff_one, span, Finsupp.mem_span_iff_linearCombination] at hs rcases hs with ⟨f, hf⟩ have hf : (f.support.sum fun a => f a * a) = 1 := hf -- Porting note: was `change ... at hf` have := sum_pow_mem_span_pow f.support (fun a => f a * a) n rw [hf, one_pow] at this refine span_le.mpr ?_ this rintro _ hx simp_rw [Set.mem_image] at hx rcases hx with ⟨x, _, rfl⟩ have : span ({(x : α) ^ (n + 1)} : Set α) ≤ span ((fun x : α => x ^ (n + 1)) '' s) := by rw [span_le, Set.singleton_subset_iff] exact subset_span ⟨x, x.prop, rfl⟩ refine this ?_ rw [mul_pow, mem_span_singleton] exact ⟨f x ^ (n + 1), mul_comm _ _⟩ theorem span_range_pow_eq_top (s : Set α) (hs : span s = ⊤) (n : s → ℕ) : span (Set.range fun x ↦ x.1 ^ n x) = ⊤ := by have ⟨t, hts, mem⟩ := Submodule.mem_span_finite_of_mem_span ((eq_top_iff_one _).mp hs) refine top_unique ((span_pow_eq_top _ ((eq_top_iff_one _).mpr mem) <| t.attach.sup fun x ↦ n ⟨x, hts x.2⟩).ge.trans <| span_le.mpr ?_) rintro _ ⟨x, hxt, rfl⟩ rw [← Nat.sub_add_cancel (Finset.le_sup <| t.mem_attach ⟨x, hxt⟩)] simp_rw [pow_add] exact mul_mem_left _ _ (subset_span ⟨_, rfl⟩) theorem prod_mem {ι : Type*} {f : ι → α} {s : Finset ι} (I : Ideal α) {i : ι} (hi : i ∈ s) (hfi : f i ∈ I) : ∏ i ∈ s, f i ∈ I := by classical rw [Finset.prod_eq_prod_diff_singleton_mul hi] exact Ideal.mul_mem_left _ _ hfi end Ideal end CommSemiring section DivisionSemiring variable {K : Type*} [DivisionSemiring K] (I : Ideal K) namespace Ideal variable (K) in /-- A bijection between (left) ideals of a division ring and `{0, 1}`, sending `⊥` to `0` and `⊤` to `1`. -/ def equivFinTwo [DecidableEq (Ideal K)] : Ideal K ≃ Fin 2 where toFun := fun I ↦ if I = ⊥ then 0 else 1 invFun := ![⊥, ⊤] left_inv := fun I ↦ by rcases eq_bot_or_top I with rfl | rfl <;> simp right_inv := fun i ↦ by fin_cases i <;> simp instance : Finite (Ideal K) := let _i := Classical.decEq (Ideal K); ⟨equivFinTwo K⟩ /-- Ideals of a `DivisionSemiring` are a simple order. Thanks to the way abbreviations work, this automatically gives an `IsSimpleModule K` instance. -/ instance isSimpleOrder : IsSimpleOrder (Ideal K) := ⟨eq_bot_or_top⟩ end Ideal end DivisionSemiring -- TODO: consider moving the lemmas below out of the `Ring` namespace since they are -- about `CommSemiring`s. namespace Ring variable {R : Type*} [CommSemiring R] theorem exists_not_isUnit_of_not_isField [Nontrivial R] (hf : ¬IsField R) : ∃ (x : R) (_hx : x ≠ (0 : R)), ¬IsUnit x := by have : ¬_ := fun h => hf ⟨exists_pair_ne R, mul_comm, h⟩ simp_rw [isUnit_iff_exists_inv] push_neg at this ⊢ obtain ⟨x, hx, not_unit⟩ := this exact ⟨x, hx, not_unit⟩ theorem not_isField_iff_exists_ideal_bot_lt_and_lt_top [Nontrivial R] : ¬IsField R ↔ ∃ I : Ideal R, ⊥ < I ∧ I < ⊤ := by constructor · intro h obtain ⟨x, nz, nu⟩ := exists_not_isUnit_of_not_isField h use Ideal.span {x} rw [bot_lt_iff_ne_bot, lt_top_iff_ne_top] exact ⟨mt Ideal.span_singleton_eq_bot.mp nz, mt Ideal.span_singleton_eq_top.mp nu⟩ · rintro ⟨I, bot_lt, lt_top⟩ hf obtain ⟨x, mem, ne_zero⟩ := SetLike.exists_of_lt bot_lt rw [Submodule.mem_bot] at ne_zero obtain ⟨y, hy⟩ := hf.mul_inv_cancel ne_zero rw [lt_top_iff_ne_top, Ne, Ideal.eq_top_iff_one, ← hy] at lt_top exact lt_top (I.mul_mem_right _ mem) theorem not_isField_iff_exists_prime [Nontrivial R] : ¬IsField R ↔ ∃ p : Ideal R, p ≠ ⊥ ∧ p.IsPrime := not_isField_iff_exists_ideal_bot_lt_and_lt_top.trans ⟨fun ⟨I, bot_lt, lt_top⟩ => let ⟨p, hp, le_p⟩ := I.exists_le_maximal (lt_top_iff_ne_top.mp lt_top) ⟨p, bot_lt_iff_ne_bot.mp (lt_of_lt_of_le bot_lt le_p), hp.isPrime⟩, fun ⟨p, ne_bot, Prime⟩ => ⟨p, bot_lt_iff_ne_bot.mpr ne_bot, lt_top_iff_ne_top.mpr Prime.1⟩⟩ /-- Also see `Ideal.isSimpleOrder` for the forward direction as an instance when `R` is a division (semi)ring. This result actually holds for all division semirings, but we lack the predicate to state it. -/ theorem isField_iff_isSimpleOrder_ideal : IsField R ↔ IsSimpleOrder (Ideal R) := by cases subsingleton_or_nontrivial R · exact ⟨fun h => (not_isField_of_subsingleton _ h).elim, fun h => (false_of_nontrivial_of_subsingleton <| Ideal R).elim⟩ rw [← not_iff_not, Ring.not_isField_iff_exists_ideal_bot_lt_and_lt_top, ← not_iff_not] push_neg simp_rw [lt_top_iff_ne_top, bot_lt_iff_ne_bot, ← or_iff_not_imp_left, not_ne_iff] exact ⟨fun h => ⟨h⟩, fun h => h.2⟩ /-- When a ring is not a field, the maximal ideals are nontrivial. -/ theorem ne_bot_of_isMaximal_of_not_isField [Nontrivial R] {M : Ideal R} (max : M.IsMaximal) (not_field : ¬IsField R) : M ≠ ⊥ := by rintro h rw [h] at max rcases max with ⟨⟨_h1, h2⟩⟩ obtain ⟨I, hIbot, hItop⟩ := not_isField_iff_exists_ideal_bot_lt_and_lt_top.mp not_field exact ne_of_lt hItop (h2 I hIbot) end Ring namespace Ideal variable {R : Type*} [CommSemiring R] [Nontrivial R] theorem bot_lt_of_maximal (M : Ideal R) [hm : M.IsMaximal] (non_field : ¬IsField R) : ⊥ < M := by rcases Ring.not_isField_iff_exists_ideal_bot_lt_and_lt_top.1 non_field with ⟨I, Ibot, Itop⟩ constructor; · simp intro mle apply lt_irrefl (⊤ : Ideal R) have : M = ⊥ := eq_bot_iff.mpr mle rw [← this] at Ibot rwa [hm.1.2 I Ibot] at Itop end Ideal
Mathlib/RingTheory/Ideal/Basic.lean
330
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/- Copyright (c) 2022 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Oleksandr Manzyuk -/ import Mathlib.CategoryTheory.Bicategory.Basic import Mathlib.CategoryTheory.Monoidal.Mon_ import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers /-! # The category of bimodule objects over a pair of monoid objects. -/ universe v₁ v₂ u₁ u₂ open CategoryTheory open CategoryTheory.MonoidalCategory variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory.{v₁} C] section open CategoryTheory.Limits variable [HasCoequalizers C] section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] theorem id_tensor_π_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Z ⊗ Y ⟶ W) (wh : (Z ◁ f) ≫ h = (Z ◁ g) ≫ h) : (Z ◁ coequalizer.π f g) ≫ (PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫ coequalizer.desc h wh = h := map_π_preserves_coequalizer_inv_desc (tensorLeft Z) f g h wh theorem id_tensor_π_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y) (f' g' : X' ⟶ Y') (p : Z ⊗ X ⟶ X') (q : Z ⊗ Y ⟶ Y') (wf : (Z ◁ f) ≫ q = p ≫ f') (wg : (Z ◁ g) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) : (Z ◁ coequalizer.π f g) ≫ (PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫ colimMap (parallelPairHom (Z ◁ f) (Z ◁ g) f' g' p q wf wg) ≫ coequalizer.desc h wh = q ≫ h := map_π_preserves_coequalizer_inv_colimMap_desc (tensorLeft Z) f g f' g' p q wf wg h wh end section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] theorem π_tensor_id_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Y ⊗ Z ⟶ W) (wh : (f ▷ Z) ≫ h = (g ▷ Z) ≫ h) : (coequalizer.π f g ▷ Z) ≫ (PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫ coequalizer.desc h wh = h := map_π_preserves_coequalizer_inv_desc (tensorRight Z) f g h wh theorem π_tensor_id_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y) (f' g' : X' ⟶ Y') (p : X ⊗ Z ⟶ X') (q : Y ⊗ Z ⟶ Y') (wf : (f ▷ Z) ≫ q = p ≫ f') (wg : (g ▷ Z) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) : (coequalizer.π f g ▷ Z) ≫ (PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫ colimMap (parallelPairHom (f ▷ Z) (g ▷ Z) f' g' p q wf wg) ≫ coequalizer.desc h wh = q ≫ h := map_π_preserves_coequalizer_inv_colimMap_desc (tensorRight Z) f g f' g' p q wf wg h wh end end /-- A bimodule object for a pair of monoid objects, all internal to some monoidal category. -/ structure Bimod (A B : Mon_ C) where /-- The underlying monoidal category -/ X : C /-- The left action of this bimodule object -/ actLeft : A.X ⊗ X ⟶ X one_actLeft : (A.one ▷ X) ≫ actLeft = (λ_ X).hom := by aesop_cat left_assoc : (A.mul ▷ X) ≫ actLeft = (α_ A.X A.X X).hom ≫ (A.X ◁ actLeft) ≫ actLeft := by aesop_cat /-- The right action of this bimodule object -/ actRight : X ⊗ B.X ⟶ X actRight_one : (X ◁ B.one) ≫ actRight = (ρ_ X).hom := by aesop_cat right_assoc : (X ◁ B.mul) ≫ actRight = (α_ X B.X B.X).inv ≫ (actRight ▷ B.X) ≫ actRight := by aesop_cat middle_assoc : (actLeft ▷ B.X) ≫ actRight = (α_ A.X X B.X).hom ≫ (A.X ◁ actRight) ≫ actLeft := by aesop_cat attribute [reassoc (attr := simp)] Bimod.one_actLeft Bimod.actRight_one Bimod.left_assoc Bimod.right_assoc Bimod.middle_assoc namespace Bimod variable {A B : Mon_ C} (M : Bimod A B) /-- A morphism of bimodule objects. -/ @[ext] structure Hom (M N : Bimod A B) where /-- The morphism between `M`'s monoidal category and `N`'s monoidal category -/ hom : M.X ⟶ N.X left_act_hom : M.actLeft ≫ hom = (A.X ◁ hom) ≫ N.actLeft := by aesop_cat right_act_hom : M.actRight ≫ hom = (hom ▷ B.X) ≫ N.actRight := by aesop_cat attribute [reassoc (attr := simp)] Hom.left_act_hom Hom.right_act_hom /-- The identity morphism on a bimodule object. -/ @[simps] def id' (M : Bimod A B) : Hom M M where hom := 𝟙 M.X instance homInhabited (M : Bimod A B) : Inhabited (Hom M M) := ⟨id' M⟩ /-- Composition of bimodule object morphisms. -/ @[simps] def comp {M N O : Bimod A B} (f : Hom M N) (g : Hom N O) : Hom M O where hom := f.hom ≫ g.hom instance : Category (Bimod A B) where Hom M N := Hom M N id := id' comp f g := comp f g @[ext] lemma hom_ext {M N : Bimod A B} (f g : M ⟶ N) (h : f.hom = g.hom) : f = g := Hom.ext h @[simp] theorem id_hom' (M : Bimod A B) : (𝟙 M : Hom M M).hom = 𝟙 M.X := rfl @[simp] theorem comp_hom' {M N K : Bimod A B} (f : M ⟶ N) (g : N ⟶ K) : (f ≫ g : Hom M K).hom = f.hom ≫ g.hom := rfl /-- Construct an isomorphism of bimodules by giving an isomorphism between the underlying objects and checking compatibility with left and right actions only in the forward direction. -/ @[simps] def isoOfIso {X Y : Mon_ C} {P Q : Bimod X Y} (f : P.X ≅ Q.X) (f_left_act_hom : P.actLeft ≫ f.hom = (X.X ◁ f.hom) ≫ Q.actLeft) (f_right_act_hom : P.actRight ≫ f.hom = (f.hom ▷ Y.X) ≫ Q.actRight) : P ≅ Q where hom := { hom := f.hom } inv := { hom := f.inv left_act_hom := by rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id, f_left_act_hom, ← Category.assoc, ← MonoidalCategory.whiskerLeft_comp, Iso.inv_hom_id, MonoidalCategory.whiskerLeft_id, Category.id_comp] right_act_hom := by rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id, f_right_act_hom, ← Category.assoc, ← comp_whiskerRight, Iso.inv_hom_id, MonoidalCategory.id_whiskerRight, Category.id_comp] } hom_inv_id := by ext; dsimp; rw [Iso.hom_inv_id] inv_hom_id := by ext; dsimp; rw [Iso.inv_hom_id] variable (A) /-- A monoid object as a bimodule over itself. -/ @[simps] def regular : Bimod A A where X := A.X actLeft := A.mul actRight := A.mul instance : Inhabited (Bimod A A) := ⟨regular A⟩ /-- The forgetful functor from bimodule objects to the ambient category. -/ def forget : Bimod A B ⥤ C where obj A := A.X map f := f.hom open CategoryTheory.Limits variable [HasCoequalizers C] namespace TensorBimod variable {R S T : Mon_ C} (P : Bimod R S) (Q : Bimod S T) /-- The underlying object of the tensor product of two bimodules. -/ noncomputable def X : C := coequalizer (P.actRight ▷ Q.X) ((α_ _ _ _).hom ≫ (P.X ◁ Q.actLeft)) section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] /-- Left action for the tensor product of two bimodules. -/ noncomputable def actLeft : R.X ⊗ X P Q ⟶ X P Q := (PreservesCoequalizer.iso (tensorLeft R.X) _ _).inv ≫ colimMap (parallelPairHom _ _ _ _ ((α_ _ _ _).inv ≫ ((α_ _ _ _).inv ▷ _) ≫ (P.actLeft ▷ S.X ▷ Q.X)) ((α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X)) (by dsimp simp only [Category.assoc] slice_lhs 1 2 => rw [associator_inv_naturality_middle] slice_rhs 3 4 => rw [← comp_whiskerRight, middle_assoc, comp_whiskerRight] monoidal) (by dsimp slice_lhs 1 1 => rw [MonoidalCategory.whiskerLeft_comp] slice_lhs 2 3 => rw [associator_inv_naturality_right] slice_lhs 3 4 => rw [whisker_exchange] monoidal)) theorem whiskerLeft_π_actLeft : (R.X ◁ coequalizer.π _ _) ≫ actLeft P Q = (α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X) ≫ coequalizer.π _ _ := by erw [map_π_preserves_coequalizer_inv_colimMap (tensorLeft _)] simp only [Category.assoc] theorem one_act_left' : (R.one ▷ _) ≫ actLeft P Q = (λ_ _).hom := by refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp [X] -- Porting note: had to replace `rw` by `erw` slice_lhs 1 2 => erw [whisker_exchange] slice_lhs 2 3 => rw [whiskerLeft_π_actLeft] slice_lhs 1 2 => rw [associator_inv_naturality_left] slice_lhs 2 3 => rw [← comp_whiskerRight, one_actLeft] slice_rhs 1 2 => rw [leftUnitor_naturality] monoidal theorem left_assoc' : (R.mul ▷ _) ≫ actLeft P Q = (α_ R.X R.X _).hom ≫ (R.X ◁ actLeft P Q) ≫ actLeft P Q := by refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp [X] slice_lhs 1 2 => rw [whisker_exchange] slice_lhs 2 3 => rw [whiskerLeft_π_actLeft] slice_lhs 1 2 => rw [associator_inv_naturality_left] slice_lhs 2 3 => rw [← comp_whiskerRight, left_assoc, comp_whiskerRight, comp_whiskerRight] slice_rhs 1 2 => rw [associator_naturality_right] slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, whiskerLeft_π_actLeft, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 4 5 => rw [whiskerLeft_π_actLeft] slice_rhs 3 4 => rw [associator_inv_naturality_middle] monoidal end section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] /-- Right action for the tensor product of two bimodules. -/ noncomputable def actRight : X P Q ⊗ T.X ⟶ X P Q := (PreservesCoequalizer.iso (tensorRight T.X) _ _).inv ≫ colimMap (parallelPairHom _ _ _ _ ((α_ _ _ _).hom ≫ (α_ _ _ _).hom ≫ (P.X ◁ S.X ◁ Q.actRight) ≫ (α_ _ _ _).inv) ((α_ _ _ _).hom ≫ (P.X ◁ Q.actRight)) (by dsimp slice_lhs 1 2 => rw [associator_naturality_left] slice_lhs 2 3 => rw [← whisker_exchange] simp) (by dsimp simp only [comp_whiskerRight, whisker_assoc, Category.assoc, Iso.inv_hom_id_assoc] slice_lhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, middle_assoc, MonoidalCategory.whiskerLeft_comp] simp)) theorem π_tensor_id_actRight : (coequalizer.π _ _ ▷ T.X) ≫ actRight P Q = (α_ _ _ _).hom ≫ (P.X ◁ Q.actRight) ≫ coequalizer.π _ _ := by erw [map_π_preserves_coequalizer_inv_colimMap (tensorRight _)] simp only [Category.assoc] theorem actRight_one' : (_ ◁ T.one) ≫ actRight P Q = (ρ_ _).hom := by refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp [X] -- Porting note: had to replace `rw` by `erw` slice_lhs 1 2 =>erw [← whisker_exchange] slice_lhs 2 3 => rw [π_tensor_id_actRight] slice_lhs 1 2 => rw [associator_naturality_right] slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, actRight_one] simp theorem right_assoc' : (_ ◁ T.mul) ≫ actRight P Q = (α_ _ T.X T.X).inv ≫ (actRight P Q ▷ T.X) ≫ actRight P Q := by refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp [X] -- Porting note: had to replace some `rw` by `erw` slice_lhs 1 2 => rw [← whisker_exchange] slice_lhs 2 3 => rw [π_tensor_id_actRight] slice_lhs 1 2 => rw [associator_naturality_right] slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, right_assoc, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 1 2 => rw [associator_inv_naturality_left] slice_rhs 2 3 => rw [← comp_whiskerRight, π_tensor_id_actRight, comp_whiskerRight, comp_whiskerRight] slice_rhs 4 5 => rw [π_tensor_id_actRight] simp end section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] theorem middle_assoc' : (actLeft P Q ▷ T.X) ≫ actRight P Q = (α_ R.X _ T.X).hom ≫ (R.X ◁ actRight P Q) ≫ actLeft P Q := by refine (cancel_epi ((tensorLeft _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp [X] slice_lhs 1 2 => rw [← comp_whiskerRight, whiskerLeft_π_actLeft, comp_whiskerRight, comp_whiskerRight] slice_lhs 3 4 => rw [π_tensor_id_actRight] slice_lhs 2 3 => rw [associator_naturality_left] -- Porting note: had to replace `rw` by `erw` slice_rhs 1 2 => rw [associator_naturality_middle] slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, π_tensor_id_actRight, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 4 5 => rw [whiskerLeft_π_actLeft] slice_rhs 3 4 => rw [associator_inv_naturality_right] slice_rhs 4 5 => rw [whisker_exchange] simp end end TensorBimod section variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] /-- Tensor product of two bimodule objects as a bimodule object. -/ @[simps] noncomputable def tensorBimod {X Y Z : Mon_ C} (M : Bimod X Y) (N : Bimod Y Z) : Bimod X Z where X := TensorBimod.X M N actLeft := TensorBimod.actLeft M N actRight := TensorBimod.actRight M N one_actLeft := TensorBimod.one_act_left' M N actRight_one := TensorBimod.actRight_one' M N left_assoc := TensorBimod.left_assoc' M N right_assoc := TensorBimod.right_assoc' M N middle_assoc := TensorBimod.middle_assoc' M N /-- Left whiskering for morphisms of bimodule objects. -/ @[simps] noncomputable def whiskerLeft {X Y Z : Mon_ C} (M : Bimod X Y) {N₁ N₂ : Bimod Y Z} (f : N₁ ⟶ N₂) : M.tensorBimod N₁ ⟶ M.tensorBimod N₂ where hom := colimMap (parallelPairHom _ _ _ _ (_ ◁ f.hom) (_ ◁ f.hom) (by rw [whisker_exchange]) (by simp only [Category.assoc, tensor_whiskerLeft, Iso.inv_hom_id_assoc, Iso.cancel_iso_hom_left] slice_lhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, Hom.left_act_hom] simp)) left_act_hom := by refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft] slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one, MonoidalCategory.whiskerLeft_comp] slice_rhs 2 3 => rw [TensorBimod.whiskerLeft_π_actLeft] slice_rhs 1 2 => rw [associator_inv_naturality_right] slice_rhs 2 3 => rw [whisker_exchange] simp right_act_hom := by refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight] slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, Hom.right_act_hom] slice_rhs 1 2 => rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one, comp_whiskerRight] slice_rhs 2 3 => rw [TensorBimod.π_tensor_id_actRight] simp /-- Right whiskering for morphisms of bimodule objects. -/ @[simps] noncomputable def whiskerRight {X Y Z : Mon_ C} {M₁ M₂ : Bimod X Y} (f : M₁ ⟶ M₂) (N : Bimod Y Z) : M₁.tensorBimod N ⟶ M₂.tensorBimod N where hom := colimMap (parallelPairHom _ _ _ _ (f.hom ▷ _ ▷ _) (f.hom ▷ _) (by rw [← comp_whiskerRight, Hom.right_act_hom, comp_whiskerRight]) (by slice_lhs 2 3 => rw [whisker_exchange] simp)) left_act_hom := by refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft] slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 2 3 => rw [← comp_whiskerRight, Hom.left_act_hom] slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one, MonoidalCategory.whiskerLeft_comp] slice_rhs 2 3 => rw [TensorBimod.whiskerLeft_π_actLeft] slice_rhs 1 2 => rw [associator_inv_naturality_middle] simp right_act_hom := by refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight] slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 2 3 => rw [whisker_exchange] slice_rhs 1 2 => rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one, comp_whiskerRight] slice_rhs 2 3 => rw [TensorBimod.π_tensor_id_actRight] simp end namespace AssociatorBimod variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] variable {R S T U : Mon_ C} (P : Bimod R S) (Q : Bimod S T) (L : Bimod T U) /-- An auxiliary morphism for the definition of the underlying morphism of the forward component of the associator isomorphism. -/ noncomputable def homAux : (P.tensorBimod Q).X ⊗ L.X ⟶ (P.tensorBimod (Q.tensorBimod L)).X := (PreservesCoequalizer.iso (tensorRight L.X) _ _).inv ≫ coequalizer.desc ((α_ _ _ _).hom ≫ (P.X ◁ coequalizer.π _ _) ≫ coequalizer.π _ _) (by dsimp; dsimp [TensorBimod.X] slice_lhs 1 2 => rw [associator_naturality_left] slice_lhs 2 3 => rw [← whisker_exchange] slice_lhs 3 4 => rw [coequalizer.condition] slice_lhs 2 3 => rw [associator_naturality_right] slice_lhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, TensorBimod.whiskerLeft_π_actLeft, MonoidalCategory.whiskerLeft_comp] simp) /-- The underlying morphism of the forward component of the associator isomorphism. -/ noncomputable def hom : ((P.tensorBimod Q).tensorBimod L).X ⟶ (P.tensorBimod (Q.tensorBimod L)).X := coequalizer.desc (homAux P Q L) (by dsimp [homAux] refine (cancel_epi ((tensorRight _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp [TensorBimod.X] slice_lhs 1 2 => rw [← comp_whiskerRight, TensorBimod.π_tensor_id_actRight, comp_whiskerRight, comp_whiskerRight] slice_lhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 2 3 => rw [associator_naturality_middle] slice_lhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.condition, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 1 2 => rw [associator_naturality_left] slice_rhs 2 3 => rw [← whisker_exchange] slice_rhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] simp) theorem hom_left_act_hom' : ((P.tensorBimod Q).tensorBimod L).actLeft ≫ hom P Q L = (R.X ◁ hom P Q L) ≫ (P.tensorBimod (Q.tensorBimod L)).actLeft := by dsimp; dsimp [hom, homAux] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ rw [tensorLeft_map] slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft] slice_lhs 3 4 => rw [coequalizer.π_desc] slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc, MonoidalCategory.whiskerLeft_comp] refine (cancel_epi ((tensorRight _ ⋙ tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp; dsimp [TensorBimod.X] slice_lhs 1 2 => rw [associator_inv_naturality_middle] slice_lhs 2 3 => rw [← comp_whiskerRight, TensorBimod.whiskerLeft_π_actLeft, comp_whiskerRight, comp_whiskerRight] slice_lhs 4 6 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 3 4 => rw [associator_naturality_left] slice_rhs 1 3 => rw [← MonoidalCategory.whiskerLeft_comp, ← MonoidalCategory.whiskerLeft_comp, π_tensor_id_preserves_coequalizer_inv_desc, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 3 4 => erw [TensorBimod.whiskerLeft_π_actLeft P (Q.tensorBimod L)] slice_rhs 2 3 => erw [associator_inv_naturality_right] slice_rhs 3 4 => erw [whisker_exchange] monoidal theorem hom_right_act_hom' : ((P.tensorBimod Q).tensorBimod L).actRight ≫ hom P Q L = (hom P Q L ▷ U.X) ≫ (P.tensorBimod (Q.tensorBimod L)).actRight := by dsimp; dsimp [hom, homAux] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ rw [tensorRight_map] slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight] slice_lhs 3 4 => rw [coequalizer.π_desc] slice_rhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc, comp_whiskerRight] refine (cancel_epi ((tensorRight _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp; dsimp [TensorBimod.X] slice_lhs 1 2 => rw [associator_naturality_left] slice_lhs 2 3 => rw [← whisker_exchange] slice_lhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 2 3 => rw [associator_naturality_right] slice_rhs 1 3 => rw [← comp_whiskerRight, ← comp_whiskerRight, π_tensor_id_preserves_coequalizer_inv_desc, comp_whiskerRight, comp_whiskerRight] slice_rhs 3 4 => erw [TensorBimod.π_tensor_id_actRight P (Q.tensorBimod L)] slice_rhs 2 3 => erw [associator_naturality_middle] dsimp slice_rhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, TensorBimod.π_tensor_id_actRight, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] monoidal /-- An auxiliary morphism for the definition of the underlying morphism of the inverse component of the associator isomorphism. -/ noncomputable def invAux : P.X ⊗ (Q.tensorBimod L).X ⟶ ((P.tensorBimod Q).tensorBimod L).X := (PreservesCoequalizer.iso (tensorLeft P.X) _ _).inv ≫ coequalizer.desc ((α_ _ _ _).inv ≫ (coequalizer.π _ _ ▷ L.X) ≫ coequalizer.π _ _) (by dsimp; dsimp [TensorBimod.X] slice_lhs 1 2 => rw [associator_inv_naturality_middle] rw [← Iso.inv_hom_id_assoc (α_ _ _ _) (P.X ◁ Q.actRight), comp_whiskerRight] slice_lhs 3 4 => rw [← comp_whiskerRight, Category.assoc, ← TensorBimod.π_tensor_id_actRight, comp_whiskerRight] slice_lhs 4 5 => rw [coequalizer.condition] slice_lhs 3 4 => rw [associator_naturality_left] slice_rhs 1 2 => rw [MonoidalCategory.whiskerLeft_comp] slice_rhs 2 3 => rw [associator_inv_naturality_right] slice_rhs 3 4 => rw [whisker_exchange] monoidal) /-- The underlying morphism of the inverse component of the associator isomorphism. -/ noncomputable def inv : (P.tensorBimod (Q.tensorBimod L)).X ⟶ ((P.tensorBimod Q).tensorBimod L).X := coequalizer.desc (invAux P Q L) (by dsimp [invAux] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp [TensorBimod.X] slice_lhs 1 2 => rw [whisker_exchange] slice_lhs 2 4 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_lhs 1 2 => rw [associator_inv_naturality_left] slice_lhs 2 3 => rw [← comp_whiskerRight, coequalizer.condition, comp_whiskerRight, comp_whiskerRight] slice_rhs 1 2 => rw [associator_naturality_right] slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, TensorBimod.whiskerLeft_π_actLeft, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 4 6 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_rhs 3 4 => rw [associator_inv_naturality_middle] monoidal) theorem hom_inv_id : hom P Q L ≫ inv P Q L = 𝟙 _ := by dsimp [hom, homAux, inv, invAux] apply coequalizer.hom_ext slice_lhs 1 2 => rw [coequalizer.π_desc] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ rw [tensorRight_map] slice_lhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 3 4 => rw [coequalizer.π_desc] slice_lhs 2 4 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_lhs 1 3 => rw [Iso.hom_inv_id_assoc] dsimp only [TensorBimod.X] slice_rhs 2 3 => rw [Category.comp_id] rfl theorem inv_hom_id : inv P Q L ≫ hom P Q L = 𝟙 _ := by dsimp [hom, homAux, inv, invAux] apply coequalizer.hom_ext slice_lhs 1 2 => rw [coequalizer.π_desc] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ rw [tensorLeft_map] slice_lhs 1 3 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_lhs 3 4 => rw [coequalizer.π_desc] slice_lhs 2 4 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 1 3 => rw [Iso.inv_hom_id_assoc] dsimp only [TensorBimod.X] slice_rhs 2 3 => rw [Category.comp_id] rfl end AssociatorBimod namespace LeftUnitorBimod variable {R S : Mon_ C} (P : Bimod R S) /-- The underlying morphism of the forward component of the left unitor isomorphism. -/ noncomputable def hom : TensorBimod.X (regular R) P ⟶ P.X := coequalizer.desc P.actLeft (by dsimp; rw [Category.assoc, left_assoc]) /-- The underlying morphism of the inverse component of the left unitor isomorphism. -/ noncomputable def inv : P.X ⟶ TensorBimod.X (regular R) P := (λ_ P.X).inv ≫ (R.one ▷ _) ≫ coequalizer.π _ _ theorem hom_inv_id : hom P ≫ inv P = 𝟙 _ := by dsimp only [hom, inv, TensorBimod.X] ext; dsimp slice_lhs 1 2 => rw [coequalizer.π_desc] slice_lhs 1 2 => rw [leftUnitor_inv_naturality] slice_lhs 2 3 => rw [whisker_exchange] slice_lhs 3 3 => rw [← Iso.inv_hom_id_assoc (α_ R.X R.X P.X) (R.X ◁ P.actLeft)] slice_lhs 4 6 => rw [← Category.assoc, ← coequalizer.condition] slice_lhs 2 3 => rw [associator_inv_naturality_left] slice_lhs 3 4 => rw [← comp_whiskerRight, Mon_.one_mul] slice_rhs 1 2 => rw [Category.comp_id] monoidal theorem inv_hom_id : inv P ≫ hom P = 𝟙 _ := by dsimp [hom, inv] slice_lhs 3 4 => rw [coequalizer.π_desc] rw [one_actLeft, Iso.inv_hom_id] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] theorem hom_left_act_hom' : ((regular R).tensorBimod P).actLeft ≫ hom P = (R.X ◁ hom P) ≫ P.actLeft := by dsimp; dsimp [hom, TensorBimod.actLeft, regular] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 4 => rw [id_tensor_π_preserves_coequalizer_inv_colimMap_desc] slice_lhs 2 3 => rw [left_assoc] slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc] rw [Iso.inv_hom_id_assoc] theorem hom_right_act_hom' : ((regular R).tensorBimod P).actRight ≫ hom P = (hom P ▷ S.X) ≫ P.actRight := by dsimp; dsimp [hom, TensorBimod.actRight, regular] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 4 => rw [π_tensor_id_preserves_coequalizer_inv_colimMap_desc] slice_rhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc] slice_rhs 1 2 => rw [middle_assoc] simp only [Category.assoc] end LeftUnitorBimod namespace RightUnitorBimod variable {R S : Mon_ C} (P : Bimod R S) /-- The underlying morphism of the forward component of the right unitor isomorphism. -/ noncomputable def hom : TensorBimod.X P (regular S) ⟶ P.X := coequalizer.desc P.actRight (by dsimp; rw [Category.assoc, right_assoc, Iso.hom_inv_id_assoc]) /-- The underlying morphism of the inverse component of the right unitor isomorphism. -/ noncomputable def inv : P.X ⟶ TensorBimod.X P (regular S) := (ρ_ P.X).inv ≫ (_ ◁ S.one) ≫ coequalizer.π _ _ theorem hom_inv_id : hom P ≫ inv P = 𝟙 _ := by dsimp only [hom, inv, TensorBimod.X] ext; dsimp slice_lhs 1 2 => rw [coequalizer.π_desc] slice_lhs 1 2 => rw [rightUnitor_inv_naturality] slice_lhs 2 3 => rw [← whisker_exchange] slice_lhs 3 4 => rw [coequalizer.condition] slice_lhs 2 3 => rw [associator_naturality_right] slice_lhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, Mon_.mul_one] slice_rhs 1 2 => rw [Category.comp_id] monoidal theorem inv_hom_id : inv P ≫ hom P = 𝟙 _ := by dsimp [hom, inv] slice_lhs 3 4 => rw [coequalizer.π_desc] rw [actRight_one, Iso.inv_hom_id] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] theorem hom_left_act_hom' : (P.tensorBimod (regular S)).actLeft ≫ hom P = (R.X ◁ hom P) ≫ P.actLeft := by dsimp; dsimp [hom, TensorBimod.actLeft, regular] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 4 => rw [id_tensor_π_preserves_coequalizer_inv_colimMap_desc] slice_lhs 2 3 => rw [middle_assoc] slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc] rw [Iso.inv_hom_id_assoc] theorem hom_right_act_hom' : (P.tensorBimod (regular S)).actRight ≫ hom P = (hom P ▷ S.X) ≫ P.actRight := by dsimp; dsimp [hom, TensorBimod.actRight, regular] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 4 => rw [π_tensor_id_preserves_coequalizer_inv_colimMap_desc] slice_lhs 2 3 => rw [right_assoc] slice_rhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc] rw [Iso.hom_inv_id_assoc] end RightUnitorBimod variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)] variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)] /-- The associator as a bimodule isomorphism. -/ noncomputable def associatorBimod {W X Y Z : Mon_ C} (L : Bimod W X) (M : Bimod X Y) (N : Bimod Y Z) : (L.tensorBimod M).tensorBimod N ≅ L.tensorBimod (M.tensorBimod N) := isoOfIso { hom := AssociatorBimod.hom L M N inv := AssociatorBimod.inv L M N hom_inv_id := AssociatorBimod.hom_inv_id L M N inv_hom_id := AssociatorBimod.inv_hom_id L M N } (AssociatorBimod.hom_left_act_hom' L M N) (AssociatorBimod.hom_right_act_hom' L M N) /-- The left unitor as a bimodule isomorphism. -/ noncomputable def leftUnitorBimod {X Y : Mon_ C} (M : Bimod X Y) : (regular X).tensorBimod M ≅ M := isoOfIso { hom := LeftUnitorBimod.hom M inv := LeftUnitorBimod.inv M hom_inv_id := LeftUnitorBimod.hom_inv_id M inv_hom_id := LeftUnitorBimod.inv_hom_id M } (LeftUnitorBimod.hom_left_act_hom' M) (LeftUnitorBimod.hom_right_act_hom' M) /-- The right unitor as a bimodule isomorphism. -/ noncomputable def rightUnitorBimod {X Y : Mon_ C} (M : Bimod X Y) : M.tensorBimod (regular Y) ≅ M := isoOfIso { hom := RightUnitorBimod.hom M inv := RightUnitorBimod.inv M hom_inv_id := RightUnitorBimod.hom_inv_id M inv_hom_id := RightUnitorBimod.inv_hom_id M } (RightUnitorBimod.hom_left_act_hom' M) (RightUnitorBimod.hom_right_act_hom' M) theorem whiskerLeft_id_bimod {X Y Z : Mon_ C} {M : Bimod X Y} {N : Bimod Y Z} : whiskerLeft M (𝟙 N) = 𝟙 (M.tensorBimod N) := by ext apply Limits.coequalizer.hom_ext dsimp only [tensorBimod_X, whiskerLeft_hom, id_hom'] simp only [MonoidalCategory.whiskerLeft_id, ι_colimMap, parallelPair_obj_one, parallelPairHom_app_one, Category.id_comp] erw [Category.comp_id] theorem id_whiskerRight_bimod {X Y Z : Mon_ C} {M : Bimod X Y} {N : Bimod Y Z} : whiskerRight (𝟙 M) N = 𝟙 (M.tensorBimod N) := by ext apply Limits.coequalizer.hom_ext dsimp only [tensorBimod_X, whiskerRight_hom, id_hom'] simp only [MonoidalCategory.id_whiskerRight, ι_colimMap, parallelPair_obj_one, parallelPairHom_app_one, Category.id_comp] erw [Category.comp_id] theorem whiskerLeft_comp_bimod {X Y Z : Mon_ C} (M : Bimod X Y) {N P Q : Bimod Y Z} (f : N ⟶ P) (g : P ⟶ Q) : whiskerLeft M (f ≫ g) = whiskerLeft M f ≫ whiskerLeft M g := by ext apply Limits.coequalizer.hom_ext simp theorem id_whiskerLeft_bimod {X Y : Mon_ C} {M N : Bimod X Y} (f : M ⟶ N) : whiskerLeft (regular X) f = (leftUnitorBimod M).hom ≫ f ≫ (leftUnitorBimod N).inv := by dsimp [tensorHom, regular, leftUnitorBimod] ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [LeftUnitorBimod.hom] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [LeftUnitorBimod.inv] slice_rhs 1 2 => rw [Hom.left_act_hom] slice_rhs 2 3 => rw [leftUnitor_inv_naturality] slice_rhs 3 4 => rw [whisker_exchange] slice_rhs 4 4 => rw [← Iso.inv_hom_id_assoc (α_ X.X X.X N.X) (X.X ◁ N.actLeft)] slice_rhs 5 7 => rw [← Category.assoc, ← coequalizer.condition] slice_rhs 3 4 => rw [associator_inv_naturality_left] slice_rhs 4 5 => rw [← comp_whiskerRight, Mon_.one_mul] have : (λ_ (X.X ⊗ N.X)).inv ≫ (α_ (𝟙_ C) X.X N.X).inv ≫ ((λ_ X.X).hom ▷ N.X) = 𝟙 _ := by monoidal slice_rhs 2 4 => rw [this] slice_rhs 1 2 => rw [Category.comp_id] theorem comp_whiskerLeft_bimod {W X Y Z : Mon_ C} (M : Bimod W X) (N : Bimod X Y) {P P' : Bimod Y Z} (f : P ⟶ P') : whiskerLeft (M.tensorBimod N) f = (associatorBimod M N P).hom ≫ whiskerLeft M (whiskerLeft N f) ≫ (associatorBimod M N P').inv := by dsimp [tensorHom, tensorBimod, associatorBimod] ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [TensorBimod.X, AssociatorBimod.hom] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.homAux, AssociatorBimod.inv] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ rw [tensorRight_map] slice_rhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_rhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one] slice_rhs 3 4 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.invAux] slice_rhs 2 2 => rw [MonoidalCategory.whiskerLeft_comp] slice_rhs 3 5 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_rhs 2 3 => rw [associator_inv_naturality_right] slice_rhs 1 3 => rw [Iso.hom_inv_id_assoc] slice_lhs 1 2 => rw [← whisker_exchange] rfl theorem comp_whiskerRight_bimod {X Y Z : Mon_ C} {M N P : Bimod X Y} (f : M ⟶ N) (g : N ⟶ P) (Q : Bimod Y Z) : whiskerRight (f ≫ g) Q = whiskerRight f Q ≫ whiskerRight g Q := by ext apply Limits.coequalizer.hom_ext simp theorem whiskerRight_id_bimod {X Y : Mon_ C} {M N : Bimod X Y} (f : M ⟶ N) : whiskerRight f (regular Y) = (rightUnitorBimod M).hom ≫ f ≫ (rightUnitorBimod N).inv := by dsimp [tensorHom, regular, rightUnitorBimod] ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [RightUnitorBimod.hom] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [RightUnitorBimod.inv] slice_rhs 1 2 => rw [Hom.right_act_hom] slice_rhs 2 3 => rw [rightUnitor_inv_naturality] slice_rhs 3 4 => rw [← whisker_exchange] slice_rhs 4 5 => rw [coequalizer.condition] slice_rhs 3 4 => rw [associator_naturality_right] slice_rhs 4 5 => rw [← MonoidalCategory.whiskerLeft_comp, Mon_.mul_one] simp theorem whiskerRight_comp_bimod {W X Y Z : Mon_ C} {M M' : Bimod W X} (f : M ⟶ M') (N : Bimod X Y) (P : Bimod Y Z) : whiskerRight f (N.tensorBimod P) = (associatorBimod M N P).inv ≫ whiskerRight (whiskerRight f N) P ≫ (associatorBimod M' N P).hom := by dsimp [tensorHom, tensorBimod, associatorBimod] ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [TensorBimod.X, AssociatorBimod.inv] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.invAux, AssociatorBimod.hom] refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_ rw [tensorLeft_map] slice_rhs 1 3 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_rhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_rhs 2 3 => rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one] slice_rhs 3 4 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.homAux] slice_rhs 2 2 => rw [comp_whiskerRight] slice_rhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_rhs 2 3 => rw [associator_naturality_left] slice_rhs 1 3 => rw [Iso.inv_hom_id_assoc] slice_lhs 1 2 => rw [whisker_exchange] rfl theorem whisker_assoc_bimod {W X Y Z : Mon_ C} (M : Bimod W X) {N N' : Bimod X Y} (f : N ⟶ N') (P : Bimod Y Z) : whiskerRight (whiskerLeft M f) P = (associatorBimod M N P).hom ≫ whiskerLeft M (whiskerRight f P) ≫ (associatorBimod M N' P).inv := by dsimp [tensorHom, tensorBimod, associatorBimod] ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [AssociatorBimod.hom] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.homAux] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ rw [tensorRight_map] slice_lhs 1 2 => rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one] slice_rhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_rhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one] dsimp [AssociatorBimod.inv] slice_rhs 3 4 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.invAux] slice_rhs 2 2 => rw [MonoidalCategory.whiskerLeft_comp] slice_rhs 3 5 => rw [id_tensor_π_preserves_coequalizer_inv_desc] slice_rhs 2 3 => rw [associator_inv_naturality_middle] slice_rhs 1 3 => rw [Iso.hom_inv_id_assoc] slice_lhs 1 1 => rw [comp_whiskerRight] theorem whisker_exchange_bimod {X Y Z : Mon_ C} {M N : Bimod X Y} {P Q : Bimod Y Z} (f : M ⟶ N) (g : P ⟶ Q) : whiskerLeft M g ≫ whiskerRight f Q = whiskerRight f P ≫ whiskerLeft N g := by ext apply coequalizer.hom_ext dsimp slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 2 3 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 1 2 => rw [whisker_exchange] slice_rhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] slice_rhs 2 3 => rw [ι_colimMap, parallelPairHom_app_one] simp only [Category.assoc] theorem pentagon_bimod {V W X Y Z : Mon_ C} (M : Bimod V W) (N : Bimod W X) (P : Bimod X Y) (Q : Bimod Y Z) : whiskerRight (associatorBimod M N P).hom Q ≫ (associatorBimod M (N.tensorBimod P) Q).hom ≫ whiskerLeft M (associatorBimod N P Q).hom = (associatorBimod (M.tensorBimod N) P Q).hom ≫ (associatorBimod M N (P.tensorBimod Q)).hom := by dsimp [associatorBimod] ext apply coequalizer.hom_ext dsimp dsimp only [AssociatorBimod.hom] slice_lhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 2 3 => rw [coequalizer.π_desc] slice_rhs 1 2 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.homAux] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc] slice_rhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_rhs 3 4 => rw [coequalizer.π_desc] refine (cancel_epi ((tensorRight _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp slice_lhs 1 2 => rw [← comp_whiskerRight, π_tensor_id_preserves_coequalizer_inv_desc, comp_whiskerRight, comp_whiskerRight] slice_lhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] dsimp only [TensorBimod.X] slice_lhs 2 3 => rw [associator_naturality_middle] slice_lhs 5 6 => rw [ι_colimMap, parallelPairHom_app_one] slice_lhs 4 5 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc] slice_lhs 3 4 => rw [← MonoidalCategory.whiskerLeft_comp, π_tensor_id_preserves_coequalizer_inv_desc, MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp] slice_rhs 1 2 => rw [associator_naturality_left] slice_rhs 2 3 => rw [← whisker_exchange] slice_rhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_rhs 2 3 => rw [associator_naturality_right] monoidal theorem triangle_bimod {X Y Z : Mon_ C} (M : Bimod X Y) (N : Bimod Y Z) : (associatorBimod M (regular Y) N).hom ≫ whiskerLeft M (leftUnitorBimod N).hom = whiskerRight (rightUnitorBimod M).hom N := by dsimp [associatorBimod, leftUnitorBimod, rightUnitorBimod] ext apply coequalizer.hom_ext dsimp dsimp [AssociatorBimod.hom] slice_lhs 1 2 => rw [coequalizer.π_desc] dsimp [AssociatorBimod.homAux] slice_rhs 1 2 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [RightUnitorBimod.hom] refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_ dsimp [regular] slice_lhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc] slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one] dsimp [LeftUnitorBimod.hom] slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc] slice_rhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc] slice_rhs 1 2 => rw [coequalizer.condition] simp only [Category.assoc]
/-- The bicategory of algebras (monoids) and bimodules, all internal to some monoidal category. -/ noncomputable def monBicategory : Bicategory (Mon_ C) where Hom X Y := Bimod X Y homCategory X Y := (inferInstance : Category (Bimod X Y)) id X := regular X comp M N := tensorBimod M N whiskerLeft L _ _ f := whiskerLeft L f whiskerRight f N := whiskerRight f N associator := associatorBimod leftUnitor := leftUnitorBimod rightUnitor := rightUnitorBimod whiskerLeft_id _ _ := whiskerLeft_id_bimod whiskerLeft_comp M _ _ _ f g := whiskerLeft_comp_bimod M f g id_whiskerLeft := id_whiskerLeft_bimod comp_whiskerLeft M N _ _ f := comp_whiskerLeft_bimod M N f id_whiskerRight _ _ := id_whiskerRight_bimod comp_whiskerRight f g Q := comp_whiskerRight_bimod f g Q whiskerRight_id := whiskerRight_id_bimod whiskerRight_comp := whiskerRight_comp_bimod whisker_assoc M _ _ f P := whisker_assoc_bimod M f P whisker_exchange := whisker_exchange_bimod pentagon := pentagon_bimod triangle := triangle_bimod end Bimod
Mathlib/CategoryTheory/Monoidal/Bimod.lean
955
981
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro -/ import Mathlib.Topology.Algebra.Constructions import Mathlib.Topology.Bases import Mathlib.Algebra.Order.Group.Nat import Mathlib.Topology.UniformSpace.Basic /-! # Theory of Cauchy filters in uniform spaces. Complete uniform spaces. Totally bounded subsets. -/ universe u v open Filter Function TopologicalSpace Topology Set UniformSpace Uniformity variable {α : Type u} {β : Type v} [uniformSpace : UniformSpace α] /-- A filter `f` is Cauchy if for every entourage `r`, there exists an `s ∈ f` such that `s × s ⊆ r`. This is a generalization of Cauchy sequences, because if `a : ℕ → α` then the filter of sets containing cofinitely many of the `a n` is Cauchy iff `a` is a Cauchy sequence. -/ def Cauchy (f : Filter α) := NeBot f ∧ f ×ˢ f ≤ 𝓤 α /-- A set `s` is called *complete*, if any Cauchy filter `f` such that `s ∈ f` has a limit in `s` (formally, it satisfies `f ≤ 𝓝 x` for some `x ∈ s`). -/ def IsComplete (s : Set α) := ∀ f, Cauchy f → f ≤ 𝓟 s → ∃ x ∈ s, f ≤ 𝓝 x theorem Filter.HasBasis.cauchy_iff {ι} {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s) {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ i, p i → ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s i := and_congr Iff.rfl <| (f.basis_sets.prod_self.le_basis_iff h).trans <| by simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm] theorem cauchy_iff' {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s := (𝓤 α).basis_sets.cauchy_iff theorem cauchy_iff {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s := cauchy_iff'.trans <| by simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm] lemma cauchy_iff_le {l : Filter α} [hl : l.NeBot] : Cauchy l ↔ l ×ˢ l ≤ 𝓤 α := by simp only [Cauchy, hl, true_and] theorem Cauchy.ultrafilter_of {l : Filter α} (h : Cauchy l) : Cauchy (@Ultrafilter.of _ l h.1 : Filter α) := by haveI := h.1 have := Ultrafilter.of_le l exact ⟨Ultrafilter.neBot _, (Filter.prod_mono this this).trans h.2⟩ theorem cauchy_map_iff {l : Filter β} {f : β → α} : Cauchy (l.map f) ↔ NeBot l ∧ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) := by rw [Cauchy, map_neBot_iff, prod_map_map_eq, Tendsto] theorem cauchy_map_iff' {l : Filter β} [hl : NeBot l] {f : β → α} : Cauchy (l.map f) ↔ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) := cauchy_map_iff.trans <| and_iff_right hl theorem Cauchy.mono {f g : Filter α} [hg : NeBot g] (h_c : Cauchy f) (h_le : g ≤ f) : Cauchy g := ⟨hg, le_trans (Filter.prod_mono h_le h_le) h_c.right⟩ theorem Cauchy.mono' {f g : Filter α} (h_c : Cauchy f) (_ : NeBot g) (h_le : g ≤ f) : Cauchy g := h_c.mono h_le theorem cauchy_nhds {a : α} : Cauchy (𝓝 a) := ⟨nhds_neBot, nhds_prod_eq.symm.trans_le (nhds_le_uniformity a)⟩ theorem cauchy_pure {a : α} : Cauchy (pure a) := cauchy_nhds.mono (pure_le_nhds a) theorem Filter.Tendsto.cauchy_map {l : Filter β} [NeBot l] {f : β → α} {a : α} (h : Tendsto f l (𝓝 a)) : Cauchy (map f l) := cauchy_nhds.mono h lemma Cauchy.mono_uniformSpace {u v : UniformSpace β} {F : Filter β} (huv : u ≤ v) (hF : Cauchy (uniformSpace := u) F) : Cauchy (uniformSpace := v) F := ⟨hF.1, hF.2.trans huv⟩ lemma cauchy_inf_uniformSpace {u v : UniformSpace β} {F : Filter β} : Cauchy (uniformSpace := u ⊓ v) F ↔ Cauchy (uniformSpace := u) F ∧ Cauchy (uniformSpace := v) F := by unfold Cauchy rw [inf_uniformity (u := u), le_inf_iff, and_and_left] lemma cauchy_iInf_uniformSpace {ι : Sort*} [Nonempty ι] {u : ι → UniformSpace β} {l : Filter β} : Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by unfold Cauchy rw [iInf_uniformity, le_iInf_iff, forall_and, forall_const] lemma cauchy_iInf_uniformSpace' {ι : Sort*} {u : ι → UniformSpace β} {l : Filter β} [l.NeBot] : Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by simp_rw [cauchy_iff_le (uniformSpace := _), iInf_uniformity, le_iInf_iff] lemma cauchy_comap_uniformSpace {u : UniformSpace β} {α} {f : α → β} {l : Filter α} : Cauchy (uniformSpace := comap f u) l ↔ Cauchy (map f l) := by simp only [Cauchy, map_neBot_iff, prod_map_map_eq, map_le_iff_le_comap] rfl lemma cauchy_prod_iff [UniformSpace β] {F : Filter (α × β)} : Cauchy F ↔ Cauchy (map Prod.fst F) ∧ Cauchy (map Prod.snd F) := by simp_rw [instUniformSpaceProd, ← cauchy_comap_uniformSpace, ← cauchy_inf_uniformSpace] theorem Cauchy.prod [UniformSpace β] {f : Filter α} {g : Filter β} (hf : Cauchy f) (hg : Cauchy g) : Cauchy (f ×ˢ g) := by have := hf.1; have := hg.1 simpa [cauchy_prod_iff, hf.1] using ⟨hf, hg⟩ /-- The common part of the proofs of `le_nhds_of_cauchy_adhp` and `SequentiallyComplete.le_nhds_of_seq_tendsto_nhds`: if for any entourage `s` one can choose a set `t ∈ f` of diameter `s` such that it contains a point `y` with `(x, y) ∈ s`, then `f` converges to `x`. -/ theorem le_nhds_of_cauchy_adhp_aux {f : Filter α} {x : α} (adhs : ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s ∧ ∃ y, (x, y) ∈ s ∧ y ∈ t) : f ≤ 𝓝 x := by -- Consider a neighborhood `s` of `x` intro s hs -- Take an entourage twice smaller than `s` rcases comp_mem_uniformity_sets (mem_nhds_uniformity_iff_right.1 hs) with ⟨U, U_mem, hU⟩ -- Take a set `t ∈ f`, `t × t ⊆ U`, and a point `y ∈ t` such that `(x, y) ∈ U` rcases adhs U U_mem with ⟨t, t_mem, ht, y, hxy, hy⟩ apply mem_of_superset t_mem -- Given a point `z ∈ t`, we have `(x, y) ∈ U` and `(y, z) ∈ t × t ⊆ U`, hence `z ∈ s` exact fun z hz => hU (prodMk_mem_compRel hxy (ht <| mk_mem_prod hy hz)) rfl /-- If `x` is an adherent (cluster) point for a Cauchy filter `f`, then it is a limit point for `f`. -/ theorem le_nhds_of_cauchy_adhp {f : Filter α} {x : α} (hf : Cauchy f) (adhs : ClusterPt x f) : f ≤ 𝓝 x := le_nhds_of_cauchy_adhp_aux (fun s hs => by obtain ⟨t, t_mem, ht⟩ : ∃ t ∈ f, t ×ˢ t ⊆ s := (cauchy_iff.1 hf).2 s hs use t, t_mem, ht exact forall_mem_nonempty_iff_neBot.2 adhs _ (inter_mem_inf (mem_nhds_left x hs) t_mem)) theorem le_nhds_iff_adhp_of_cauchy {f : Filter α} {x : α} (hf : Cauchy f) : f ≤ 𝓝 x ↔ ClusterPt x f := ⟨fun h => ClusterPt.of_le_nhds' h hf.1, le_nhds_of_cauchy_adhp hf⟩ nonrec theorem Cauchy.map [UniformSpace β] {f : Filter α} {m : α → β} (hf : Cauchy f) (hm : UniformContinuous m) : Cauchy (map m f) := ⟨hf.1.map _, calc map m f ×ˢ map m f = map (Prod.map m m) (f ×ˢ f) := Filter.prod_map_map_eq _ ≤ Filter.map (Prod.map m m) (𝓤 α) := map_mono hf.right _ ≤ 𝓤 β := hm⟩ nonrec theorem Cauchy.comap [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f) (hm : comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α) [NeBot (comap m f)] : Cauchy (comap m f) := ⟨‹_›, calc comap m f ×ˢ comap m f = comap (Prod.map m m) (f ×ˢ f) := prod_comap_comap_eq _ ≤ comap (Prod.map m m) (𝓤 β) := comap_mono hf.right _ ≤ 𝓤 α := hm⟩ theorem Cauchy.comap' [UniformSpace β] {f : Filter β} {m : α → β} (hf : Cauchy f) (hm : Filter.comap (fun p : α × α => (m p.1, m p.2)) (𝓤 β) ≤ 𝓤 α) (_ : NeBot (Filter.comap m f)) : Cauchy (Filter.comap m f) := hf.comap hm /-- Cauchy sequences. Usually defined on ℕ, but often it is also useful to say that a function defined on ℝ is Cauchy at +∞ to deduce convergence. Therefore, we define it in a type class that is general enough to cover both ℕ and ℝ, which are the main motivating examples. -/ def CauchySeq [Preorder β] (u : β → α) := Cauchy (atTop.map u) theorem CauchySeq.tendsto_uniformity [Preorder β] {u : β → α} (h : CauchySeq u) : Tendsto (Prod.map u u) atTop (𝓤 α) := by simpa only [Tendsto, prod_map_map_eq', prod_atTop_atTop_eq] using h.right theorem CauchySeq.nonempty [Preorder β] {u : β → α} (hu : CauchySeq u) : Nonempty β := @nonempty_of_neBot _ _ <| (map_neBot_iff _).1 hu.1 theorem CauchySeq.mem_entourage {β : Type*} [SemilatticeSup β] {u : β → α} (h : CauchySeq u) {V : Set (α × α)} (hV : V ∈ 𝓤 α) : ∃ k₀, ∀ i j, k₀ ≤ i → k₀ ≤ j → (u i, u j) ∈ V := by haveI := h.nonempty have := h.tendsto_uniformity; rw [← prod_atTop_atTop_eq] at this simpa [MapsTo] using atTop_basis.prod_self.tendsto_left_iff.1 this V hV theorem Filter.Tendsto.cauchySeq [SemilatticeSup β] [Nonempty β] {f : β → α} {x} (hx : Tendsto f atTop (𝓝 x)) : CauchySeq f := hx.cauchy_map theorem cauchySeq_const [SemilatticeSup β] [Nonempty β] (x : α) : CauchySeq fun _ : β => x := tendsto_const_nhds.cauchySeq theorem cauchySeq_iff_tendsto [Nonempty β] [SemilatticeSup β] {u : β → α} : CauchySeq u ↔ Tendsto (Prod.map u u) atTop (𝓤 α) := cauchy_map_iff'.trans <| by simp only [prod_atTop_atTop_eq, Prod.map_def] theorem CauchySeq.comp_tendsto {γ} [Preorder β] [SemilatticeSup γ] [Nonempty γ] {f : β → α} (hf : CauchySeq f) {g : γ → β} (hg : Tendsto g atTop atTop) : CauchySeq (f ∘ g) := ⟨inferInstance, le_trans (prod_le_prod.mpr ⟨Tendsto.comp le_rfl hg, Tendsto.comp le_rfl hg⟩) hf.2⟩ theorem CauchySeq.comp_injective [SemilatticeSup β] [NoMaxOrder β] [Nonempty β] {u : ℕ → α} (hu : CauchySeq u) {f : β → ℕ} (hf : Injective f) : CauchySeq (u ∘ f) := hu.comp_tendsto <| Nat.cofinite_eq_atTop ▸ hf.tendsto_cofinite.mono_left atTop_le_cofinite theorem Function.Bijective.cauchySeq_comp_iff {f : ℕ → ℕ} (hf : Bijective f) (u : ℕ → α) : CauchySeq (u ∘ f) ↔ CauchySeq u := by refine ⟨fun H => ?_, fun H => H.comp_injective hf.injective⟩ lift f to ℕ ≃ ℕ using hf simpa only [Function.comp_def, f.apply_symm_apply] using H.comp_injective f.symm.injective theorem CauchySeq.subseq_subseq_mem {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α} (hu : CauchySeq u) {f g : ℕ → ℕ} (hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, ((u ∘ f ∘ φ) n, (u ∘ g ∘ φ) n) ∈ V n := by rw [cauchySeq_iff_tendsto] at hu exact ((hu.comp <| hf.prod_atTop hg).comp tendsto_atTop_diagonal).subseq_mem hV -- todo: generalize this and other lemmas to a nonempty semilattice theorem cauchySeq_iff' {u : ℕ → α} : CauchySeq u ↔ ∀ V ∈ 𝓤 α, ∀ᶠ k in atTop, k ∈ Prod.map u u ⁻¹' V := cauchySeq_iff_tendsto theorem cauchySeq_iff {u : ℕ → α} : CauchySeq u ↔ ∀ V ∈ 𝓤 α, ∃ N, ∀ k ≥ N, ∀ l ≥ N, (u k, u l) ∈ V := by simp only [cauchySeq_iff', Filter.eventually_atTop_prod_self', mem_preimage, Prod.map_apply] theorem CauchySeq.prodMap {γ δ} [UniformSpace β] [Preorder γ] [Preorder δ] {u : γ → α} {v : δ → β} (hu : CauchySeq u) (hv : CauchySeq v) : CauchySeq (Prod.map u v) := by simpa only [CauchySeq, prod_map_map_eq', prod_atTop_atTop_eq] using hu.prod hv @[deprecated (since := "2025-03-10")] alias CauchySeq.prod_map := CauchySeq.prodMap theorem CauchySeq.prodMk {γ} [UniformSpace β] [Preorder γ] {u : γ → α} {v : γ → β} (hu : CauchySeq u) (hv : CauchySeq v) : CauchySeq fun x => (u x, v x) := haveI := hu.1.of_map (Cauchy.prod hu hv).mono (tendsto_map.prodMk tendsto_map) @[deprecated (since := "2025-03-10")] alias CauchySeq.prod := CauchySeq.prodMk theorem CauchySeq.eventually_eventually [Preorder β] {u : β → α} (hu : CauchySeq u) {V : Set (α × α)} (hV : V ∈ 𝓤 α) : ∀ᶠ k in atTop, ∀ᶠ l in atTop, (u k, u l) ∈ V := eventually_atTop_curry <| hu.tendsto_uniformity hV theorem UniformContinuous.comp_cauchySeq {γ} [UniformSpace β] [Preorder γ] {f : α → β} (hf : UniformContinuous f) {u : γ → α} (hu : CauchySeq u) : CauchySeq (f ∘ u) := hu.map hf theorem CauchySeq.subseq_mem {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α} (hu : CauchySeq u) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, (u <| φ (n + 1), u <| φ n) ∈ V n := by have : ∀ n, ∃ N, ∀ k ≥ N, ∀ l ≥ k, (u l, u k) ∈ V n := fun n => by rw [cauchySeq_iff] at hu rcases hu _ (hV n) with ⟨N, H⟩ exact ⟨N, fun k hk l hl => H _ (le_trans hk hl) _ hk⟩ obtain ⟨φ : ℕ → ℕ, φ_extr : StrictMono φ, hφ : ∀ n, ∀ l ≥ φ n, (u l, u <| φ n) ∈ V n⟩ := extraction_forall_of_eventually' this exact ⟨φ, φ_extr, fun n => hφ _ _ (φ_extr <| Nat.lt_add_one n).le⟩ theorem Filter.Tendsto.subseq_mem_entourage {V : ℕ → Set (α × α)} (hV : ∀ n, V n ∈ 𝓤 α) {u : ℕ → α} {a : α} (hu : Tendsto u atTop (𝓝 a)) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ (u (φ 0), a) ∈ V 0 ∧ ∀ n, (u <| φ (n + 1), u <| φ n) ∈ V (n + 1) := by rcases mem_atTop_sets.1 (hu (ball_mem_nhds a (symm_le_uniformity <| hV 0))) with ⟨n, hn⟩ rcases (hu.comp (tendsto_add_atTop_nat n)).cauchySeq.subseq_mem fun n => hV (n + 1) with ⟨φ, φ_mono, hφV⟩ exact ⟨fun k => φ k + n, φ_mono.add_const _, hn _ le_add_self, hφV⟩ /-- If a Cauchy sequence has a convergent subsequence, then it converges. -/ theorem tendsto_nhds_of_cauchySeq_of_subseq [Preorder β] {u : β → α} (hu : CauchySeq u) {ι : Type*} {f : ι → β} {p : Filter ι} [NeBot p] (hf : Tendsto f p atTop) {a : α} (ha : Tendsto (u ∘ f) p (𝓝 a)) : Tendsto u atTop (𝓝 a) := le_nhds_of_cauchy_adhp hu (ha.mapClusterPt.of_comp hf) /-- Any shift of a Cauchy sequence is also a Cauchy sequence. -/ theorem cauchySeq_shift {u : ℕ → α} (k : ℕ) : CauchySeq (fun n ↦ u (n + k)) ↔ CauchySeq u := by constructor <;> intro h · rw [cauchySeq_iff] at h ⊢ intro V mV obtain ⟨N, h⟩ := h V mV use N + k intro a ha b hb convert h (a - k) (Nat.le_sub_of_add_le ha) (b - k) (Nat.le_sub_of_add_le hb) <;> omega · exact h.comp_tendsto (tendsto_add_atTop_nat k) theorem Filter.HasBasis.cauchySeq_iff {γ} [Nonempty β] [SemilatticeSup β] {u : β → α} {p : γ → Prop} {s : γ → Set (α × α)} (h : (𝓤 α).HasBasis p s) : CauchySeq u ↔ ∀ i, p i → ∃ N, ∀ m, N ≤ m → ∀ n, N ≤ n → (u m, u n) ∈ s i := by rw [cauchySeq_iff_tendsto, ← prod_atTop_atTop_eq] refine (atTop_basis.prod_self.tendsto_iff h).trans ?_ simp only [exists_prop, true_and, MapsTo, preimage, subset_def, Prod.forall, mem_prod_eq, mem_setOf_eq, mem_Ici, and_imp, Prod.map, @forall_swap (_ ≤ _) β] theorem Filter.HasBasis.cauchySeq_iff' {γ} [Nonempty β] [SemilatticeSup β] {u : β → α} {p : γ → Prop} {s : γ → Set (α × α)} (H : (𝓤 α).HasBasis p s) : CauchySeq u ↔ ∀ i, p i → ∃ N, ∀ n ≥ N, (u n, u N) ∈ s i := by refine H.cauchySeq_iff.trans ⟨fun h i hi => ?_, fun h i hi => ?_⟩ · exact (h i hi).imp fun N hN n hn => hN n hn N le_rfl · rcases comp_symm_of_uniformity (H.mem_of_mem hi) with ⟨t, ht, ht', hts⟩ rcases H.mem_iff.1 ht with ⟨j, hj, hjt⟩ refine (h j hj).imp fun N hN m hm n hn => hts ⟨u N, hjt ?_, ht' <| hjt ?_⟩ exacts [hN m hm, hN n hn] theorem cauchySeq_of_controlled [SemilatticeSup β] [Nonempty β] (U : β → Set (α × α)) (hU : ∀ s ∈ 𝓤 α, ∃ n, U n ⊆ s) {f : β → α} (hf : ∀ ⦃N m n : β⦄, N ≤ m → N ≤ n → (f m, f n) ∈ U N) : CauchySeq f := cauchySeq_iff_tendsto.2 (by intro s hs rw [mem_map, mem_atTop_sets] obtain ⟨N, hN⟩ := hU s hs refine ⟨(N, N), fun mn hmn => ?_⟩ obtain ⟨m, n⟩ := mn exact hN (hf hmn.1 hmn.2))
theorem isComplete_iff_clusterPt {s : Set α} : IsComplete s ↔ ∀ l, Cauchy l → l ≤ 𝓟 s → ∃ x ∈ s, ClusterPt x l := forall₃_congr fun _ hl _ => exists_congr fun _ => and_congr_right fun _ => le_nhds_iff_adhp_of_cauchy hl theorem isComplete_iff_ultrafilter {s : Set α} : IsComplete s ↔ ∀ l : Ultrafilter α, Cauchy (l : Filter α) → ↑l ≤ 𝓟 s → ∃ x ∈ s, ↑l ≤ 𝓝 x := by refine ⟨fun h l => h l, fun H => isComplete_iff_clusterPt.2 fun l hl hls => ?_⟩ haveI := hl.1
Mathlib/Topology/UniformSpace/Cauchy.lean
316
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/- Copyright (c) 2020 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Algebra.Star.SelfAdjoint import Mathlib.LinearAlgebra.Dimension.StrongRankCondition import Mathlib.LinearAlgebra.FreeModule.Finite.Basic /-! # Quaternions In this file we define quaternions `ℍ[R]` over a commutative ring `R`, and define some algebraic structures on `ℍ[R]`. ## Main definitions * `QuaternionAlgebra R a b c`, `ℍ[R, a, b, c]` : [Bourbaki, *Algebra I*][bourbaki1989] with coefficients `a`, `b`, `c` (Many other references such as Wikipedia assume $\operatorname{char} R ≠ 2$ therefore one can complete the square and WLOG assume $b = 0$.) * `Quaternion R`, `ℍ[R]` : the space of quaternions, a.k.a. `QuaternionAlgebra R (-1) (0) (-1)`; * `Quaternion.normSq` : square of the norm of a quaternion; We also define the following algebraic structures on `ℍ[R]`: * `Ring ℍ[R, a, b, c]`, `StarRing ℍ[R, a, b, c]`, and `Algebra R ℍ[R, a, b, c]` : for any commutative ring `R`; * `Ring ℍ[R]`, `StarRing ℍ[R]`, and `Algebra R ℍ[R]` : for any commutative ring `R`; * `IsDomain ℍ[R]` : for a linear ordered commutative ring `R`; * `DivisionRing ℍ[R]` : for a linear ordered field `R`. ## Notation The following notation is available with `open Quaternion` or `open scoped Quaternion`. * `ℍ[R, c₁, c₂, c₃]` : `QuaternionAlgebra R c₁ c₂ c₃` * `ℍ[R, c₁, c₂]` : `QuaternionAlgebra R c₁ 0 c₂` * `ℍ[R]` : quaternions over `R`. ## Implementation notes We define quaternions over any ring `R`, not just `ℝ` to be able to deal with, e.g., integer or rational quaternions without using real numbers. In particular, all definitions in this file are computable. ## Tags quaternion -/ /-- Quaternion algebra over a type with fixed coefficients where $i^2 = a + bi$ and $j^2 = c$, denoted as `ℍ[R,a,b]`. Implemented as a structure with four fields: `re`, `imI`, `imJ`, and `imK`. -/ @[ext] structure QuaternionAlgebra (R : Type*) (a b c : R) where /-- Real part of a quaternion. -/ re : R /-- First imaginary part (i) of a quaternion. -/ imI : R /-- Second imaginary part (j) of a quaternion. -/ imJ : R /-- Third imaginary part (k) of a quaternion. -/ imK : R @[inherit_doc] scoped[Quaternion] notation "ℍ[" R "," a "," b "," c "]" => QuaternionAlgebra R a b c @[inherit_doc] scoped[Quaternion] notation "ℍ[" R "," a "," b "]" => QuaternionAlgebra R a 0 b namespace QuaternionAlgebra open Quaternion /-- The equivalence between a quaternion algebra over `R` and `R × R × R × R`. -/ @[simps] def equivProd {R : Type*} (c₁ c₂ c₃ : R) : ℍ[R,c₁,c₂,c₃] ≃ R × R × R × R where toFun a := ⟨a.1, a.2, a.3, a.4⟩ invFun a := ⟨a.1, a.2.1, a.2.2.1, a.2.2.2⟩ left_inv _ := rfl right_inv _ := rfl /-- The equivalence between a quaternion algebra over `R` and `Fin 4 → R`. -/ @[simps symm_apply] def equivTuple {R : Type*} (c₁ c₂ c₃ : R) : ℍ[R,c₁,c₂,c₃] ≃ (Fin 4 → R) where toFun a := ![a.1, a.2, a.3, a.4] invFun a := ⟨a 0, a 1, a 2, a 3⟩ left_inv _ := rfl right_inv f := by ext ⟨_, _ | _ | _ | _ | _ | ⟨⟩⟩ <;> rfl @[simp] theorem equivTuple_apply {R : Type*} (c₁ c₂ c₃ : R) (x : ℍ[R,c₁,c₂,c₃]) : equivTuple c₁ c₂ c₃ x = ![x.re, x.imI, x.imJ, x.imK] := rfl @[simp] theorem mk.eta {R : Type*} {c₁ c₂ c₃} (a : ℍ[R,c₁,c₂,c₃]) : mk a.1 a.2 a.3 a.4 = a := rfl variable {S T R : Type*} {c₁ c₂ c₃ : R} (r x y : R) (a b : ℍ[R,c₁,c₂,c₃]) instance [Subsingleton R] : Subsingleton ℍ[R, c₁, c₂, c₃] := (equivTuple c₁ c₂ c₃).subsingleton instance [Nontrivial R] : Nontrivial ℍ[R, c₁, c₂, c₃] := (equivTuple c₁ c₂ c₃).surjective.nontrivial section Zero variable [Zero R] /-- The imaginary part of a quaternion. Note that unless `c₂ = 0`, this definition is not particularly well-behaved; for instance, `QuaternionAlgebra.star_im` only says that the star of an imaginary quaternion is imaginary under this condition. -/ def im (x : ℍ[R,c₁,c₂,c₃]) : ℍ[R,c₁,c₂,c₃] := ⟨0, x.imI, x.imJ, x.imK⟩ @[simp] theorem im_re : a.im.re = 0 := rfl @[simp] theorem im_imI : a.im.imI = a.imI := rfl @[simp] theorem im_imJ : a.im.imJ = a.imJ := rfl @[simp] theorem im_imK : a.im.imK = a.imK := rfl @[simp] theorem im_idem : a.im.im = a.im := rfl /-- Coercion `R → ℍ[R,c₁,c₂,c₃]`. -/ @[coe] def coe (x : R) : ℍ[R,c₁,c₂,c₃] := ⟨x, 0, 0, 0⟩ instance : CoeTC R ℍ[R,c₁,c₂,c₃] := ⟨coe⟩ @[simp, norm_cast] theorem coe_re : (x : ℍ[R,c₁,c₂,c₃]).re = x := rfl @[simp, norm_cast] theorem coe_imI : (x : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[simp, norm_cast] theorem coe_imJ : (x : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[simp, norm_cast] theorem coe_imK : (x : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl theorem coe_injective : Function.Injective (coe : R → ℍ[R,c₁,c₂,c₃]) := fun _ _ h => congr_arg re h @[simp] theorem coe_inj {x y : R} : (x : ℍ[R,c₁,c₂,c₃]) = y ↔ x = y := coe_injective.eq_iff -- Porting note: removed `simps`, added simp lemmas manually. -- Should adjust `simps` to name properly, i.e. as `zero_re` rather than `instZero_zero_re`. instance : Zero ℍ[R,c₁,c₂,c₃] := ⟨⟨0, 0, 0, 0⟩⟩ @[scoped simp] theorem zero_re : (0 : ℍ[R,c₁,c₂,c₃]).re = 0 := rfl @[scoped simp] theorem zero_imI : (0 : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[scoped simp] theorem zero_imJ : (0 : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[scoped simp] theorem zero_imK : (0 : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl @[scoped simp] theorem zero_im : (0 : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[simp, norm_cast] theorem coe_zero : ((0 : R) : ℍ[R,c₁,c₂,c₃]) = 0 := rfl instance : Inhabited ℍ[R,c₁,c₂,c₃] := ⟨0⟩ section One variable [One R] -- Porting note: removed `simps`, added simp lemmas manually. Should adjust `simps` to name properly instance : One ℍ[R,c₁,c₂,c₃] := ⟨⟨1, 0, 0, 0⟩⟩ @[scoped simp] theorem one_re : (1 : ℍ[R,c₁,c₂,c₃]).re = 1 := rfl @[scoped simp] theorem one_imI : (1 : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[scoped simp] theorem one_imJ : (1 : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[scoped simp] theorem one_imK : (1 : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl @[scoped simp] theorem one_im : (1 : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[simp, norm_cast] theorem coe_one : ((1 : R) : ℍ[R,c₁,c₂,c₃]) = 1 := rfl end One end Zero section Add variable [Add R] -- Porting note: removed `simps`, added simp lemmas manually. Should adjust `simps` to name properly instance : Add ℍ[R,c₁,c₂,c₃] := ⟨fun a b => ⟨a.1 + b.1, a.2 + b.2, a.3 + b.3, a.4 + b.4⟩⟩ @[simp] theorem add_re : (a + b).re = a.re + b.re := rfl @[simp] theorem add_imI : (a + b).imI = a.imI + b.imI := rfl @[simp] theorem add_imJ : (a + b).imJ = a.imJ + b.imJ := rfl @[simp] theorem add_imK : (a + b).imK = a.imK + b.imK := rfl @[simp] theorem mk_add_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) : (mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂,c₃]) + mk b₁ b₂ b₃ b₄ = mk (a₁ + b₁) (a₂ + b₂) (a₃ + b₃) (a₄ + b₄) := rfl end Add section AddZeroClass variable [AddZeroClass R] @[simp] theorem add_im : (a + b).im = a.im + b.im := QuaternionAlgebra.ext (zero_add _).symm rfl rfl rfl @[simp, norm_cast] theorem coe_add : ((x + y : R) : ℍ[R,c₁,c₂,c₃]) = x + y := by ext <;> simp end AddZeroClass section Neg variable [Neg R] -- Porting note: removed `simps`, added simp lemmas manually. Should adjust `simps` to name properly instance : Neg ℍ[R,c₁,c₂,c₃] := ⟨fun a => ⟨-a.1, -a.2, -a.3, -a.4⟩⟩ @[simp] theorem neg_re : (-a).re = -a.re := rfl @[simp] theorem neg_imI : (-a).imI = -a.imI := rfl @[simp] theorem neg_imJ : (-a).imJ = -a.imJ := rfl @[simp] theorem neg_imK : (-a).imK = -a.imK := rfl @[simp] theorem neg_mk (a₁ a₂ a₃ a₄ : R) : -(mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂,c₃]) = ⟨-a₁, -a₂, -a₃, -a₄⟩ := rfl end Neg section AddGroup variable [AddGroup R] @[simp] theorem neg_im : (-a).im = -a.im := QuaternionAlgebra.ext neg_zero.symm rfl rfl rfl @[simp, norm_cast] theorem coe_neg : ((-x : R) : ℍ[R,c₁,c₂,c₃]) = -x := by ext <;> simp instance : Sub ℍ[R,c₁,c₂,c₃] := ⟨fun a b => ⟨a.1 - b.1, a.2 - b.2, a.3 - b.3, a.4 - b.4⟩⟩ @[simp] theorem sub_re : (a - b).re = a.re - b.re := rfl @[simp] theorem sub_imI : (a - b).imI = a.imI - b.imI := rfl @[simp] theorem sub_imJ : (a - b).imJ = a.imJ - b.imJ := rfl @[simp] theorem sub_imK : (a - b).imK = a.imK - b.imK := rfl @[simp] theorem sub_im : (a - b).im = a.im - b.im := QuaternionAlgebra.ext (sub_zero _).symm rfl rfl rfl @[simp] theorem mk_sub_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) : (mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂,c₃]) - mk b₁ b₂ b₃ b₄ = mk (a₁ - b₁) (a₂ - b₂) (a₃ - b₃) (a₄ - b₄) := rfl @[simp, norm_cast] theorem coe_im : (x : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[simp] theorem re_add_im : ↑a.re + a.im = a := QuaternionAlgebra.ext (add_zero _) (zero_add _) (zero_add _) (zero_add _) @[simp] theorem sub_self_im : a - a.im = a.re := QuaternionAlgebra.ext (sub_zero _) (sub_self _) (sub_self _) (sub_self _) @[simp] theorem sub_self_re : a - a.re = a.im := QuaternionAlgebra.ext (sub_self _) (sub_zero _) (sub_zero _) (sub_zero _) end AddGroup section Ring variable [Ring R] /-- Multiplication is given by * `1 * x = x * 1 = x`; * `i * i = c₁ + c₂ * i`; * `j * j = c₃`; * `i * j = k`, `j * i = c₂ * j - k`; * `k * k = - c₁ * c₃`; * `i * k = c₁ * j + c₂ * k`, `k * i = -c₁ * j`; * `j * k = c₂ * c₃ - c₃ * i`, `k * j = c₃ * i`. -/ instance : Mul ℍ[R,c₁,c₂,c₃] := ⟨fun a b => ⟨a.1 * b.1 + c₁ * a.2 * b.2 + c₃ * a.3 * b.3 + c₂ * c₃ * a.3 * b.4 - c₁ * c₃ * a.4 * b.4, a.1 * b.2 + a.2 * b.1 + c₂ * a.2 * b.2 - c₃ * a.3 * b.4 + c₃ * a.4 * b.3, a.1 * b.3 + c₁ * a.2 * b.4 + a.3 * b.1 + c₂ * a.3 * b.2 - c₁ * a.4 * b.2, a.1 * b.4 + a.2 * b.3 + c₂ * a.2 * b.4 - a.3 * b.2 + a.4 * b.1⟩⟩ @[simp] theorem mul_re : (a * b).re = a.1 * b.1 + c₁ * a.2 * b.2 + c₃ * a.3 * b.3 + c₂ * c₃ * a.3 * b.4 - c₁ * c₃ * a.4 * b.4 := rfl @[simp] theorem mul_imI : (a * b).imI = a.1 * b.2 + a.2 * b.1 + c₂ * a.2 * b.2 - c₃ * a.3 * b.4 + c₃ * a.4 * b.3 := rfl @[simp] theorem mul_imJ : (a * b).imJ = a.1 * b.3 + c₁ * a.2 * b.4 + a.3 * b.1 + c₂ * a.3 * b.2 - c₁ * a.4 * b.2 := rfl @[simp] theorem mul_imK : (a * b).imK = a.1 * b.4 + a.2 * b.3 + c₂ * a.2 * b.4 - a.3 * b.2 + a.4 * b.1 := rfl @[simp] theorem mk_mul_mk (a₁ a₂ a₃ a₄ b₁ b₂ b₃ b₄ : R) : (mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂,c₃]) * mk b₁ b₂ b₃ b₄ = mk (a₁ * b₁ + c₁ * a₂ * b₂ + c₃ * a₃ * b₃ + c₂ * c₃ * a₃ * b₄ - c₁ * c₃ * a₄ * b₄) (a₁ * b₂ + a₂ * b₁ + c₂ * a₂ * b₂ - c₃ * a₃ * b₄ + c₃ * a₄ * b₃) (a₁ * b₃ + c₁ * a₂ * b₄ + a₃ * b₁ + c₂ * a₃ * b₂ - c₁ * a₄ * b₂) (a₁ * b₄ + a₂ * b₃ + c₂ * a₂ * b₄ - a₃ * b₂ + a₄ * b₁) := rfl end Ring section SMul variable [SMul S R] [SMul T R] (s : S) instance : SMul S ℍ[R,c₁,c₂,c₃] where smul s a := ⟨s • a.1, s • a.2, s • a.3, s • a.4⟩ instance [SMul S T] [IsScalarTower S T R] : IsScalarTower S T ℍ[R,c₁,c₂,c₃] where smul_assoc s t x := by ext <;> exact smul_assoc _ _ _ instance [SMulCommClass S T R] : SMulCommClass S T ℍ[R,c₁,c₂,c₃] where smul_comm s t x := by ext <;> exact smul_comm _ _ _ @[simp] theorem smul_re : (s • a).re = s • a.re := rfl @[simp] theorem smul_imI : (s • a).imI = s • a.imI := rfl @[simp] theorem smul_imJ : (s • a).imJ = s • a.imJ := rfl @[simp] theorem smul_imK : (s • a).imK = s • a.imK := rfl @[simp] theorem smul_im {S} [CommRing R] [SMulZeroClass S R] (s : S) : (s • a).im = s • a.im := QuaternionAlgebra.ext (smul_zero s).symm rfl rfl rfl @[simp] theorem smul_mk (re im_i im_j im_k : R) : s • (⟨re, im_i, im_j, im_k⟩ : ℍ[R,c₁,c₂,c₃]) = ⟨s • re, s • im_i, s • im_j, s • im_k⟩ := rfl end SMul @[simp, norm_cast] theorem coe_smul [Zero R] [SMulZeroClass S R] (s : S) (r : R) : (↑(s • r) : ℍ[R,c₁,c₂,c₃]) = s • (r : ℍ[R,c₁,c₂,c₃]) := QuaternionAlgebra.ext rfl (smul_zero _).symm (smul_zero _).symm (smul_zero _).symm instance [AddCommGroup R] : AddCommGroup ℍ[R,c₁,c₂,c₃] := (equivProd c₁ c₂ c₃).injective.addCommGroup _ rfl (fun _ _ ↦ rfl) (fun _ ↦ rfl) (fun _ _ ↦ rfl) (fun _ _ ↦ rfl) (fun _ _ ↦ rfl) section AddCommGroupWithOne variable [AddCommGroupWithOne R] instance : AddCommGroupWithOne ℍ[R,c₁,c₂,c₃] where natCast n := ((n : R) : ℍ[R,c₁,c₂,c₃]) natCast_zero := by simp natCast_succ := by simp intCast n := ((n : R) : ℍ[R,c₁,c₂,c₃]) intCast_ofNat _ := congr_arg coe (Int.cast_natCast _) intCast_negSucc n := by change coe _ = -coe _ rw [Int.cast_negSucc, coe_neg] @[simp, norm_cast] theorem natCast_re (n : ℕ) : (n : ℍ[R,c₁,c₂,c₃]).re = n := rfl @[simp, norm_cast] theorem natCast_imI (n : ℕ) : (n : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[simp, norm_cast] theorem natCast_imJ (n : ℕ) : (n : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[simp, norm_cast] theorem natCast_imK (n : ℕ) : (n : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl @[simp, norm_cast] theorem natCast_im (n : ℕ) : (n : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[norm_cast] theorem coe_natCast (n : ℕ) : ↑(n : R) = (n : ℍ[R,c₁,c₂,c₃]) := rfl @[simp, norm_cast] theorem intCast_re (z : ℤ) : (z : ℍ[R,c₁,c₂,c₃]).re = z := rfl @[scoped simp] theorem ofNat_re (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℍ[R,c₁,c₂,c₃]).re = ofNat(n) := rfl @[scoped simp] theorem ofNat_imI (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[scoped simp] theorem ofNat_imJ (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[scoped simp] theorem ofNat_imK (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl @[scoped simp] theorem ofNat_im (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[simp, norm_cast] theorem intCast_imI (z : ℤ) : (z : ℍ[R,c₁,c₂,c₃]).imI = 0 := rfl @[simp, norm_cast] theorem intCast_imJ (z : ℤ) : (z : ℍ[R,c₁,c₂,c₃]).imJ = 0 := rfl @[simp, norm_cast] theorem intCast_imK (z : ℤ) : (z : ℍ[R,c₁,c₂,c₃]).imK = 0 := rfl @[simp, norm_cast] theorem intCast_im (z : ℤ) : (z : ℍ[R,c₁,c₂,c₃]).im = 0 := rfl @[norm_cast] theorem coe_intCast (z : ℤ) : ↑(z : R) = (z : ℍ[R,c₁,c₂,c₃]) := rfl end AddCommGroupWithOne -- For the remainder of the file we assume `CommRing R`. variable [CommRing R] instance instRing : Ring ℍ[R,c₁,c₂,c₃] where __ := inferInstanceAs (AddCommGroupWithOne ℍ[R,c₁,c₂,c₃]) left_distrib _ _ _ := by ext <;> simp <;> ring right_distrib _ _ _ := by ext <;> simp <;> ring zero_mul _ := by ext <;> simp mul_zero _ := by ext <;> simp mul_assoc _ _ _ := by ext <;> simp <;> ring one_mul _ := by ext <;> simp mul_one _ := by ext <;> simp @[norm_cast, simp] theorem coe_mul : ((x * y : R) : ℍ[R,c₁,c₂,c₃]) = x * y := by ext <;> simp @[norm_cast, simp] lemma coe_ofNat {n : ℕ} [n.AtLeastTwo]: ((ofNat(n) : R) : ℍ[R,c₁,c₂,c₃]) = (ofNat(n) : ℍ[R,c₁,c₂,c₃]) := by rfl -- TODO: add weaker `MulAction`, `DistribMulAction`, and `Module` instances (and repeat them -- for `ℍ[R]`) instance [CommSemiring S] [Algebra S R] : Algebra S ℍ[R,c₁,c₂,c₃] where smul := (· • ·) algebraMap := { toFun s := coe (algebraMap S R s) map_one' := by simp only [map_one, coe_one] map_zero' := by simp only [map_zero, coe_zero] map_mul' x y := by simp only [map_mul, coe_mul] map_add' x y := by simp only [map_add, coe_add] } smul_def' s x := by ext <;> simp [Algebra.smul_def] commutes' s x := by ext <;> simp [Algebra.commutes] theorem algebraMap_eq (r : R) : algebraMap R ℍ[R,c₁,c₂,c₃] r = ⟨r, 0, 0, 0⟩ := rfl theorem algebraMap_injective : (algebraMap R ℍ[R,c₁,c₂,c₃] : _ → _).Injective := fun _ _ ↦ by simp [algebraMap_eq] instance [NoZeroDivisors R] : NoZeroSMulDivisors R ℍ[R,c₁,c₂,c₃] := ⟨by rintro t ⟨a, b, c, d⟩ h rw [or_iff_not_imp_left] intro ht simpa [QuaternionAlgebra.ext_iff, ht] using h⟩ section variable (c₁ c₂ c₃) /-- `QuaternionAlgebra.re` as a `LinearMap` -/ @[simps] def reₗ : ℍ[R,c₁,c₂,c₃] →ₗ[R] R where toFun := re map_add' _ _ := rfl map_smul' _ _ := rfl /-- `QuaternionAlgebra.imI` as a `LinearMap` -/ @[simps] def imIₗ : ℍ[R,c₁,c₂,c₃] →ₗ[R] R where toFun := imI map_add' _ _ := rfl map_smul' _ _ := rfl /-- `QuaternionAlgebra.imJ` as a `LinearMap` -/ @[simps] def imJₗ : ℍ[R,c₁,c₂,c₃] →ₗ[R] R where toFun := imJ map_add' _ _ := rfl map_smul' _ _ := rfl /-- `QuaternionAlgebra.imK` as a `LinearMap` -/ @[simps] def imKₗ : ℍ[R,c₁,c₂,c₃] →ₗ[R] R where toFun := imK map_add' _ _ := rfl map_smul' _ _ := rfl /-- `QuaternionAlgebra.equivTuple` as a linear equivalence. -/ def linearEquivTuple : ℍ[R,c₁,c₂,c₃] ≃ₗ[R] Fin 4 → R := LinearEquiv.symm -- proofs are not `rfl` in the forward direction { (equivTuple c₁ c₂ c₃).symm with toFun := (equivTuple c₁ c₂ c₃).symm invFun := equivTuple c₁ c₂ c₃ map_add' := fun _ _ => rfl map_smul' := fun _ _ => rfl } @[simp] theorem coe_linearEquivTuple : ⇑(linearEquivTuple c₁ c₂ c₃) = equivTuple c₁ c₂ c₃ := rfl @[simp] theorem coe_linearEquivTuple_symm : ⇑(linearEquivTuple c₁ c₂ c₃).symm = (equivTuple c₁ c₂ c₃).symm := rfl /-- `ℍ[R, c₁, c₂, c₃]` has a basis over `R` given by `1`, `i`, `j`, and `k`. -/ noncomputable def basisOneIJK : Basis (Fin 4) R ℍ[R,c₁,c₂,c₃] := .ofEquivFun <| linearEquivTuple c₁ c₂ c₃ @[simp] theorem coe_basisOneIJK_repr (q : ℍ[R,c₁,c₂,c₃]) : ((basisOneIJK c₁ c₂ c₃).repr q) = ![q.re, q.imI, q.imJ, q.imK] := rfl instance : Module.Finite R ℍ[R,c₁,c₂,c₃] := .of_basis (basisOneIJK c₁ c₂ c₃) instance : Module.Free R ℍ[R,c₁,c₂,c₃] := .of_basis (basisOneIJK c₁ c₂ c₃) theorem rank_eq_four [StrongRankCondition R] : Module.rank R ℍ[R,c₁,c₂,c₃] = 4 := by rw [rank_eq_card_basis (basisOneIJK c₁ c₂ c₃), Fintype.card_fin] norm_num theorem finrank_eq_four [StrongRankCondition R] : Module.finrank R ℍ[R,c₁,c₂,c₃] = 4 := by rw [Module.finrank, rank_eq_four, Cardinal.toNat_ofNat] /-- There is a natural equivalence when swapping the first and third coefficients of a quaternion algebra if `c₂` is 0. -/ @[simps] def swapEquiv : ℍ[R,c₁,0,c₃] ≃ₐ[R] ℍ[R,c₃,0,c₁] where toFun t := ⟨t.1, t.3, t.2, -t.4⟩ invFun t := ⟨t.1, t.3, t.2, -t.4⟩ left_inv _ := by simp right_inv _ := by simp map_mul' _ _ := by ext <;> simp <;> ring map_add' _ _ := by ext <;> simp [add_comm] commutes' _ := by simp [algebraMap_eq] end @[norm_cast, simp] theorem coe_sub : ((x - y : R) : ℍ[R,c₁,c₂,c₃]) = x - y := (algebraMap R ℍ[R,c₁,c₂,c₃]).map_sub x y @[norm_cast, simp] theorem coe_pow (n : ℕ) : (↑(x ^ n) : ℍ[R,c₁,c₂,c₃]) = (x : ℍ[R,c₁,c₂,c₃]) ^ n := (algebraMap R ℍ[R,c₁,c₂,c₃]).map_pow x n theorem coe_commutes : ↑r * a = a * r := Algebra.commutes r a theorem coe_commute : Commute (↑r) a := coe_commutes r a theorem coe_mul_eq_smul : ↑r * a = r • a := (Algebra.smul_def r a).symm theorem mul_coe_eq_smul : a * r = r • a := by rw [← coe_commutes, coe_mul_eq_smul] @[norm_cast, simp] theorem coe_algebraMap : ⇑(algebraMap R ℍ[R,c₁,c₂,c₃]) = coe := rfl theorem smul_coe : x • (y : ℍ[R,c₁,c₂,c₃]) = ↑(x * y) := by rw [coe_mul, coe_mul_eq_smul] /-- Quaternion conjugate. -/ instance instStarQuaternionAlgebra : Star ℍ[R,c₁,c₂,c₃] where star a := ⟨a.1 + c₂ * a.2, -a.2, -a.3, -a.4⟩ @[simp] theorem re_star : (star a).re = a.re + c₂ * a.imI := rfl @[simp] theorem imI_star : (star a).imI = -a.imI := rfl @[simp] theorem imJ_star : (star a).imJ = -a.imJ := rfl @[simp] theorem imK_star : (star a).imK = -a.imK := rfl @[simp] theorem im_star : (star a).im = -a.im := QuaternionAlgebra.ext neg_zero.symm rfl rfl rfl @[simp] theorem star_mk (a₁ a₂ a₃ a₄ : R) : star (mk a₁ a₂ a₃ a₄ : ℍ[R,c₁,c₂,c₃]) = ⟨a₁ + c₂ * a₂, -a₂, -a₃, -a₄⟩ := rfl instance instStarRing : StarRing ℍ[R,c₁,c₂,c₃] where star_involutive x := by simp [Star.star] star_add a b := by ext <;> simp [add_comm] ; ring star_mul a b := by ext <;> simp <;> ring theorem self_add_star' : a + star a = ↑(2 * a.re + c₂ * a.imI) := by ext <;> simp [two_mul]; ring theorem self_add_star : a + star a = 2 * a.re + c₂ * a.imI := by simp [self_add_star'] theorem star_add_self' : star a + a = ↑(2 * a.re + c₂ * a.imI) := by rw [add_comm, self_add_star'] theorem star_add_self : star a + a = 2 * a.re + c₂ * a.imI := by rw [add_comm, self_add_star] theorem star_eq_two_re_sub : star a = ↑(2 * a.re + c₂ * a.imI) - a := eq_sub_iff_add_eq.2 a.star_add_self' lemma comm (r : R) (x : ℍ[R, c₁, c₂, c₃]) : r * x = x * r := by ext <;> simp [mul_comm] instance : IsStarNormal a := ⟨by rw [commute_iff_eq, a.star_eq_two_re_sub]; ext <;> simp <;> ring⟩ @[simp, norm_cast] theorem star_coe : star (x : ℍ[R,c₁,c₂,c₃]) = x := by ext <;> simp @[simp] theorem star_im : star a.im = -a.im + c₂ * a.imI := by ext <;> simp @[simp] theorem star_smul [Monoid S] [DistribMulAction S R] [SMulCommClass S R R] (s : S) (a : ℍ[R,c₁,c₂,c₃]) : star (s • a) = s • star a := QuaternionAlgebra.ext (by simp [mul_smul_comm]) (smul_neg _ _).symm (smul_neg _ _).symm (smul_neg _ _).symm /-- A version of `star_smul` for the special case when `c₂ = 0`, without `SMulCommClass S R R`. -/ theorem star_smul' [Monoid S] [DistribMulAction S R] (s : S) (a : ℍ[R,c₁,0,c₃]) : star (s • a) = s • star a := QuaternionAlgebra.ext (by simp) (smul_neg _ _).symm (smul_neg _ _).symm (smul_neg _ _).symm theorem eq_re_of_eq_coe {a : ℍ[R,c₁,c₂,c₃]} {x : R} (h : a = x) : a = a.re := by rw [h, coe_re] theorem eq_re_iff_mem_range_coe {a : ℍ[R,c₁,c₂,c₃]} : a = a.re ↔ a ∈ Set.range (coe : R → ℍ[R,c₁,c₂,c₃]) := ⟨fun h => ⟨a.re, h.symm⟩, fun ⟨_, h⟩ => eq_re_of_eq_coe h.symm⟩ section CharZero variable [NoZeroDivisors R] [CharZero R] @[simp] theorem star_eq_self {c₁ c₂ : R} {a : ℍ[R,c₁,c₂,c₃]} : star a = a ↔ a = a.re := by simp_all [QuaternionAlgebra.ext_iff, neg_eq_iff_add_eq_zero, add_self_eq_zero] theorem star_eq_neg {c₁ : R} {a : ℍ[R,c₁,0,c₃]} : star a = -a ↔ a.re = 0 := by simp [QuaternionAlgebra.ext_iff, eq_neg_iff_add_eq_zero] end CharZero -- Can't use `rw ← star_eq_self` in the proof without additional assumptions theorem star_mul_eq_coe : star a * a = (star a * a).re := by ext <;> simp <;> ring theorem mul_star_eq_coe : a * star a = (a * star a).re := by rw [← star_comm_self'] exact a.star_mul_eq_coe open MulOpposite /-- Quaternion conjugate as an `AlgEquiv` to the opposite ring. -/ def starAe : ℍ[R,c₁,c₂,c₃] ≃ₐ[R] ℍ[R,c₁,c₂,c₃]ᵐᵒᵖ := { starAddEquiv.trans opAddEquiv with toFun := op ∘ star invFun := star ∘ unop map_mul' := fun x y => by simp commutes' := fun r => by simp } @[simp] theorem coe_starAe : ⇑(starAe : ℍ[R,c₁,c₂,c₃] ≃ₐ[R] _) = op ∘ star := rfl end QuaternionAlgebra /-- Space of quaternions over a type, denoted as `ℍ[R]`. Implemented as a structure with four fields: `re`, `im_i`, `im_j`, and `im_k`. -/ def Quaternion (R : Type*) [Zero R] [One R] [Neg R] := QuaternionAlgebra R (-1) (0) (-1) @[inherit_doc] scoped[Quaternion] notation "ℍ[" R "]" => Quaternion R open Quaternion /-- The equivalence between the quaternions over `R` and `R × R × R × R`. -/ @[simps!] def Quaternion.equivProd (R : Type*) [Zero R] [One R] [Neg R] : ℍ[R] ≃ R × R × R × R := QuaternionAlgebra.equivProd _ _ _ /-- The equivalence between the quaternions over `R` and `Fin 4 → R`. -/ @[simps! symm_apply] def Quaternion.equivTuple (R : Type*) [Zero R] [One R] [Neg R] : ℍ[R] ≃ (Fin 4 → R) := QuaternionAlgebra.equivTuple _ _ _ @[simp] theorem Quaternion.equivTuple_apply (R : Type*) [Zero R] [One R] [Neg R] (x : ℍ[R]) : Quaternion.equivTuple R x = ![x.re, x.imI, x.imJ, x.imK] := rfl instance {R : Type*} [Zero R] [One R] [Neg R] [Subsingleton R] : Subsingleton ℍ[R] := inferInstanceAs (Subsingleton <| ℍ[R, -1, 0, -1]) instance {R : Type*} [Zero R] [One R] [Neg R] [Nontrivial R] : Nontrivial ℍ[R] := inferInstanceAs (Nontrivial <| ℍ[R, -1, 0, -1]) namespace Quaternion variable {S T R : Type*} [CommRing R] (r x y : R) (a b : ℍ[R]) /-- Coercion `R → ℍ[R]`. -/ @[coe] def coe : R → ℍ[R] := QuaternionAlgebra.coe instance : CoeTC R ℍ[R] := ⟨coe⟩ instance instRing : Ring ℍ[R] := QuaternionAlgebra.instRing instance : Inhabited ℍ[R] := inferInstanceAs <| Inhabited ℍ[R,-1, 0, -1] instance [SMul S R] : SMul S ℍ[R] := inferInstanceAs <| SMul S ℍ[R,-1, 0, -1] instance [SMul S T] [SMul S R] [SMul T R] [IsScalarTower S T R] : IsScalarTower S T ℍ[R] := inferInstanceAs <| IsScalarTower S T ℍ[R,-1,0,-1] instance [SMul S R] [SMul T R] [SMulCommClass S T R] : SMulCommClass S T ℍ[R] := inferInstanceAs <| SMulCommClass S T ℍ[R,-1,0,-1] protected instance algebra [CommSemiring S] [Algebra S R] : Algebra S ℍ[R] := inferInstanceAs <| Algebra S ℍ[R,-1,0,-1] instance : Star ℍ[R] := QuaternionAlgebra.instStarQuaternionAlgebra instance : StarRing ℍ[R] := QuaternionAlgebra.instStarRing instance : IsStarNormal a := inferInstanceAs <| IsStarNormal (R := ℍ[R,-1,0,-1]) a @[ext] theorem ext : a.re = b.re → a.imI = b.imI → a.imJ = b.imJ → a.imK = b.imK → a = b := QuaternionAlgebra.ext /-- The imaginary part of a quaternion. -/ nonrec def im (x : ℍ[R]) : ℍ[R] := x.im @[simp] theorem im_re : a.im.re = 0 := rfl @[simp] theorem im_imI : a.im.imI = a.imI := rfl @[simp] theorem im_imJ : a.im.imJ = a.imJ := rfl @[simp] theorem im_imK : a.im.imK = a.imK := rfl @[simp] theorem im_idem : a.im.im = a.im := rfl @[simp] nonrec theorem re_add_im : ↑a.re + a.im = a := a.re_add_im @[simp] nonrec theorem sub_self_im : a - a.im = a.re := a.sub_self_im @[simp] nonrec theorem sub_self_re : a - ↑a.re = a.im := a.sub_self_re @[simp, norm_cast] theorem coe_re : (x : ℍ[R]).re = x := rfl @[simp, norm_cast] theorem coe_imI : (x : ℍ[R]).imI = 0 := rfl @[simp, norm_cast] theorem coe_imJ : (x : ℍ[R]).imJ = 0 := rfl @[simp, norm_cast] theorem coe_imK : (x : ℍ[R]).imK = 0 := rfl @[simp, norm_cast] theorem coe_im : (x : ℍ[R]).im = 0 := rfl @[scoped simp] theorem zero_re : (0 : ℍ[R]).re = 0 := rfl @[scoped simp] theorem zero_imI : (0 : ℍ[R]).imI = 0 := rfl @[scoped simp] theorem zero_imJ : (0 : ℍ[R]).imJ = 0 := rfl @[scoped simp] theorem zero_imK : (0 : ℍ[R]).imK = 0 := rfl @[scoped simp] theorem zero_im : (0 : ℍ[R]).im = 0 := rfl @[simp, norm_cast] theorem coe_zero : ((0 : R) : ℍ[R]) = 0 := rfl @[scoped simp] theorem one_re : (1 : ℍ[R]).re = 1 := rfl @[scoped simp] theorem one_imI : (1 : ℍ[R]).imI = 0 := rfl @[scoped simp] theorem one_imJ : (1 : ℍ[R]).imJ = 0 := rfl @[scoped simp] theorem one_imK : (1 : ℍ[R]).imK = 0 := rfl @[scoped simp] theorem one_im : (1 : ℍ[R]).im = 0 := rfl @[simp, norm_cast] theorem coe_one : ((1 : R) : ℍ[R]) = 1 := rfl @[simp] theorem add_re : (a + b).re = a.re + b.re := rfl @[simp] theorem add_imI : (a + b).imI = a.imI + b.imI := rfl @[simp] theorem add_imJ : (a + b).imJ = a.imJ + b.imJ := rfl @[simp] theorem add_imK : (a + b).imK = a.imK + b.imK := rfl @[simp] nonrec theorem add_im : (a + b).im = a.im + b.im := a.add_im b @[simp, norm_cast] theorem coe_add : ((x + y : R) : ℍ[R]) = x + y := QuaternionAlgebra.coe_add x y @[simp] theorem neg_re : (-a).re = -a.re := rfl @[simp] theorem neg_imI : (-a).imI = -a.imI := rfl @[simp] theorem neg_imJ : (-a).imJ = -a.imJ := rfl @[simp] theorem neg_imK : (-a).imK = -a.imK := rfl @[simp] nonrec theorem neg_im : (-a).im = -a.im := a.neg_im @[simp, norm_cast] theorem coe_neg : ((-x : R) : ℍ[R]) = -x := QuaternionAlgebra.coe_neg x @[simp] theorem sub_re : (a - b).re = a.re - b.re := rfl @[simp] theorem sub_imI : (a - b).imI = a.imI - b.imI := rfl @[simp] theorem sub_imJ : (a - b).imJ = a.imJ - b.imJ := rfl @[simp] theorem sub_imK : (a - b).imK = a.imK - b.imK := rfl @[simp] nonrec theorem sub_im : (a - b).im = a.im - b.im := a.sub_im b @[simp, norm_cast] theorem coe_sub : ((x - y : R) : ℍ[R]) = x - y := QuaternionAlgebra.coe_sub x y @[simp] theorem mul_re : (a * b).re = a.re * b.re - a.imI * b.imI - a.imJ * b.imJ - a.imK * b.imK := (QuaternionAlgebra.mul_re a b).trans <| by simp [one_mul, neg_mul, sub_eq_add_neg, neg_neg] @[simp] theorem mul_imI : (a * b).imI = a.re * b.imI + a.imI * b.re + a.imJ * b.imK - a.imK * b.imJ := (QuaternionAlgebra.mul_imI a b).trans <| by ring @[simp] theorem mul_imJ : (a * b).imJ = a.re * b.imJ - a.imI * b.imK + a.imJ * b.re + a.imK * b.imI := (QuaternionAlgebra.mul_imJ a b).trans <| by ring @[simp] theorem mul_imK : (a * b).imK = a.re * b.imK + a.imI * b.imJ - a.imJ * b.imI + a.imK * b.re := (QuaternionAlgebra.mul_imK a b).trans <| by ring @[simp, norm_cast] theorem coe_mul : ((x * y : R) : ℍ[R]) = x * y := QuaternionAlgebra.coe_mul x y @[norm_cast, simp] theorem coe_pow (n : ℕ) : (↑(x ^ n) : ℍ[R]) = (x : ℍ[R]) ^ n := QuaternionAlgebra.coe_pow x n @[simp, norm_cast] theorem natCast_re (n : ℕ) : (n : ℍ[R]).re = n := rfl @[simp, norm_cast] theorem natCast_imI (n : ℕ) : (n : ℍ[R]).imI = 0 := rfl @[simp, norm_cast] theorem natCast_imJ (n : ℕ) : (n : ℍ[R]).imJ = 0 := rfl @[simp, norm_cast] theorem natCast_imK (n : ℕ) : (n : ℍ[R]).imK = 0 := rfl @[simp, norm_cast] theorem natCast_im (n : ℕ) : (n : ℍ[R]).im = 0 := rfl @[norm_cast] theorem coe_natCast (n : ℕ) : ↑(n : R) = (n : ℍ[R]) := rfl @[simp, norm_cast] theorem intCast_re (z : ℤ) : (z : ℍ[R]).re = z := rfl @[simp, norm_cast] theorem intCast_imI (z : ℤ) : (z : ℍ[R]).imI = 0 := rfl @[simp, norm_cast] theorem intCast_imJ (z : ℤ) : (z : ℍ[R]).imJ = 0 := rfl @[simp, norm_cast] theorem intCast_imK (z : ℤ) : (z : ℍ[R]).imK = 0 := rfl @[simp, norm_cast] theorem intCast_im (z : ℤ) : (z : ℍ[R]).im = 0 := rfl @[norm_cast] theorem coe_intCast (z : ℤ) : ↑(z : R) = (z : ℍ[R]) := rfl theorem coe_injective : Function.Injective (coe : R → ℍ[R]) := QuaternionAlgebra.coe_injective @[simp] theorem coe_inj {x y : R} : (x : ℍ[R]) = y ↔ x = y := coe_injective.eq_iff @[simp] theorem smul_re [SMul S R] (s : S) : (s • a).re = s • a.re := rfl @[simp] theorem smul_imI [SMul S R] (s : S) : (s • a).imI = s • a.imI := rfl @[simp] theorem smul_imJ [SMul S R] (s : S) : (s • a).imJ = s • a.imJ := rfl @[simp] theorem smul_imK [SMul S R] (s : S) : (s • a).imK = s • a.imK := rfl @[simp] nonrec theorem smul_im [SMulZeroClass S R] (s : S) : (s • a).im = s • a.im := a.smul_im s @[simp, norm_cast] theorem coe_smul [SMulZeroClass S R] (s : S) (r : R) : (↑(s • r) : ℍ[R]) = s • (r : ℍ[R]) := QuaternionAlgebra.coe_smul _ _ theorem coe_commutes : ↑r * a = a * r := QuaternionAlgebra.coe_commutes r a theorem coe_commute : Commute (↑r) a := QuaternionAlgebra.coe_commute r a theorem coe_mul_eq_smul : ↑r * a = r • a := QuaternionAlgebra.coe_mul_eq_smul r a theorem mul_coe_eq_smul : a * r = r • a := QuaternionAlgebra.mul_coe_eq_smul r a @[simp] theorem algebraMap_def : ⇑(algebraMap R ℍ[R]) = coe := rfl theorem algebraMap_injective : (algebraMap R ℍ[R] : _ → _).Injective := QuaternionAlgebra.algebraMap_injective theorem smul_coe : x • (y : ℍ[R]) = ↑(x * y) := QuaternionAlgebra.smul_coe x y instance : Module.Finite R ℍ[R] := inferInstanceAs <| Module.Finite R ℍ[R,-1,0,-1] instance : Module.Free R ℍ[R] := inferInstanceAs <| Module.Free R ℍ[R,-1,0,-1] theorem rank_eq_four [StrongRankCondition R] : Module.rank R ℍ[R] = 4 := QuaternionAlgebra.rank_eq_four _ _ _ theorem finrank_eq_four [StrongRankCondition R] : Module.finrank R ℍ[R] = 4 := QuaternionAlgebra.finrank_eq_four _ _ _ @[simp] theorem star_re : (star a).re = a.re := by rw [QuaternionAlgebra.re_star, zero_mul, add_zero] @[simp] theorem star_imI : (star a).imI = -a.imI := rfl @[simp] theorem star_imJ : (star a).imJ = -a.imJ := rfl @[simp] theorem star_imK : (star a).imK = -a.imK := rfl @[simp] theorem star_im : (star a).im = -a.im := a.im_star nonrec theorem self_add_star' : a + star a = ↑(2 * a.re) := by simp [a.self_add_star', Quaternion.coe] nonrec theorem self_add_star : a + star a = 2 * a.re := by simp [a.self_add_star, Quaternion.coe] nonrec theorem star_add_self' : star a + a = ↑(2 * a.re) := by simp [a.star_add_self', Quaternion.coe] nonrec theorem star_add_self : star a + a = 2 * a.re := by simp [a.star_add_self, Quaternion.coe] nonrec theorem star_eq_two_re_sub : star a = ↑(2 * a.re) - a := by simp [a.star_eq_two_re_sub, Quaternion.coe] @[simp, norm_cast] theorem star_coe : star (x : ℍ[R]) = x := QuaternionAlgebra.star_coe x @[simp] theorem im_star : star a.im = -a.im := by ext <;> simp @[simp] theorem star_smul [Monoid S] [DistribMulAction S R] (s : S) (a : ℍ[R]) : star (s • a) = s • star a := QuaternionAlgebra.star_smul' s a theorem eq_re_of_eq_coe {a : ℍ[R]} {x : R} (h : a = x) : a = a.re := QuaternionAlgebra.eq_re_of_eq_coe h theorem eq_re_iff_mem_range_coe {a : ℍ[R]} : a = a.re ↔ a ∈ Set.range (coe : R → ℍ[R]) := QuaternionAlgebra.eq_re_iff_mem_range_coe section CharZero variable [NoZeroDivisors R] [CharZero R] @[simp] theorem star_eq_self {a : ℍ[R]} : star a = a ↔ a = a.re := QuaternionAlgebra.star_eq_self @[simp] theorem star_eq_neg {a : ℍ[R]} : star a = -a ↔ a.re = 0 := QuaternionAlgebra.star_eq_neg end CharZero nonrec theorem star_mul_eq_coe : star a * a = (star a * a).re := a.star_mul_eq_coe nonrec theorem mul_star_eq_coe : a * star a = (a * star a).re := a.mul_star_eq_coe open MulOpposite /-- Quaternion conjugate as an `AlgEquiv` to the opposite ring. -/ def starAe : ℍ[R] ≃ₐ[R] ℍ[R]ᵐᵒᵖ := QuaternionAlgebra.starAe @[simp] theorem coe_starAe : ⇑(starAe : ℍ[R] ≃ₐ[R] ℍ[R]ᵐᵒᵖ) = op ∘ star := rfl /-- Square of the norm. -/ def normSq : ℍ[R] →*₀ R where toFun a := (a * star a).re map_zero' := by simp only [star_zero, zero_mul, zero_re] map_one' := by simp only [star_one, one_mul, one_re] map_mul' x y := coe_injective <| by conv_lhs => rw [← mul_star_eq_coe, star_mul, mul_assoc, ← mul_assoc y, y.mul_star_eq_coe, coe_commutes, ← mul_assoc, x.mul_star_eq_coe, ← coe_mul] theorem normSq_def : normSq a = (a * star a).re := rfl theorem normSq_def' : normSq a = a.1 ^ 2 + a.2 ^ 2 + a.3 ^ 2 + a.4 ^ 2 := by simp only [normSq_def, sq, mul_neg, sub_neg_eq_add, mul_re, star_re, star_imI, star_imJ, star_imK] theorem normSq_coe : normSq (x : ℍ[R]) = x ^ 2 := by rw [normSq_def, star_coe, ← coe_mul, coe_re, sq] @[simp] theorem normSq_star : normSq (star a) = normSq a := by simp [normSq_def'] @[norm_cast] theorem normSq_natCast (n : ℕ) : normSq (n : ℍ[R]) = (n : R) ^ 2 := by rw [← coe_natCast, normSq_coe] @[norm_cast] theorem normSq_intCast (z : ℤ) : normSq (z : ℍ[R]) = (z : R) ^ 2 := by rw [← coe_intCast, normSq_coe] @[simp] theorem normSq_neg : normSq (-a) = normSq a := by simp only [normSq_def, star_neg, neg_mul_neg] theorem self_mul_star : a * star a = normSq a := by rw [mul_star_eq_coe, normSq_def] theorem star_mul_self : star a * a = normSq a := by rw [star_comm_self, self_mul_star] theorem im_sq : a.im ^ 2 = -normSq a.im := by simp_rw [sq, ← star_mul_self, im_star, neg_mul, neg_neg] theorem coe_normSq_add : normSq (a + b) = normSq a + a * star b + b * star a + normSq b := by simp only [star_add, ← self_mul_star, mul_add, add_mul, add_assoc, add_left_comm] theorem normSq_smul (r : R) (q : ℍ[R]) : normSq (r • q) = r ^ 2 * normSq q := by simp only [normSq_def', smul_re, smul_imI, smul_imJ, smul_imK, mul_pow, mul_add, smul_eq_mul] theorem normSq_add (a b : ℍ[R]) : normSq (a + b) = normSq a + normSq b + 2 * (a * star b).re := calc normSq (a + b) = normSq a + (a * star b).re + ((b * star a).re + normSq b) := by simp_rw [normSq_def, star_add, add_mul, mul_add, add_re] _ = normSq a + normSq b + ((a * star b).re + (b * star a).re) := by abel _ = normSq a + normSq b + 2 * (a * star b).re := by rw [← add_re, ← star_mul_star a b, self_add_star', coe_re] end Quaternion namespace Quaternion variable {R : Type*} section LinearOrderedCommRing variable [CommRing R] [LinearOrder R] [IsStrictOrderedRing R] {a : ℍ[R]} @[simp] theorem normSq_eq_zero : normSq a = 0 ↔ a = 0 := by refine ⟨fun h => ?_, fun h => h.symm ▸ normSq.map_zero⟩ rw [normSq_def', add_eq_zero_iff_of_nonneg, add_eq_zero_iff_of_nonneg, add_eq_zero_iff_of_nonneg] at h · exact ext a 0 (pow_eq_zero h.1.1.1) (pow_eq_zero h.1.1.2) (pow_eq_zero h.1.2) (pow_eq_zero h.2) all_goals apply_rules [sq_nonneg, add_nonneg] theorem normSq_ne_zero : normSq a ≠ 0 ↔ a ≠ 0 := normSq_eq_zero.not @[simp] theorem normSq_nonneg : 0 ≤ normSq a := by rw [normSq_def'] apply_rules [sq_nonneg, add_nonneg] @[simp] theorem normSq_le_zero : normSq a ≤ 0 ↔ a = 0 := normSq_nonneg.le_iff_eq.trans normSq_eq_zero instance instNontrivial : Nontrivial ℍ[R] where exists_pair_ne := ⟨0, 1, mt (congr_arg QuaternionAlgebra.re) zero_ne_one⟩ instance : NoZeroDivisors ℍ[R] where eq_zero_or_eq_zero_of_mul_eq_zero {a b} hab := have : normSq a * normSq b = 0 := by rwa [← map_mul, normSq_eq_zero] (eq_zero_or_eq_zero_of_mul_eq_zero this).imp normSq_eq_zero.1 normSq_eq_zero.1 instance : IsDomain ℍ[R] := NoZeroDivisors.to_isDomain _ theorem sq_eq_normSq : a ^ 2 = normSq a ↔ a = a.re := by rw [← star_eq_self, ← star_mul_self, sq, mul_eq_mul_right_iff, eq_comm] exact or_iff_left_of_imp fun ha ↦ ha.symm ▸ star_zero _ theorem sq_eq_neg_normSq : a ^ 2 = -normSq a ↔ a.re = 0 := by simp_rw [← star_eq_neg] obtain rfl | hq0 := eq_or_ne a 0 · simp · rw [← star_mul_self, ← mul_neg, ← neg_sq, sq, mul_left_inj' (neg_ne_zero.mpr hq0), eq_comm] end LinearOrderedCommRing section Field variable [Field R] (a b : ℍ[R]) instance instNNRatCast : NNRatCast ℍ[R] where nnratCast q := (q : R) instance instRatCast : RatCast ℍ[R] where ratCast q := (q : R) @[simp, norm_cast] lemma re_nnratCast (q : ℚ≥0) : (q : ℍ[R]).re = q := rfl @[simp, norm_cast] lemma im_nnratCast (q : ℚ≥0) : (q : ℍ[R]).im = 0 := rfl @[simp, norm_cast] lemma imI_nnratCast (q : ℚ≥0) : (q : ℍ[R]).imI = 0 := rfl @[simp, norm_cast] lemma imJ_nnratCast (q : ℚ≥0) : (q : ℍ[R]).imJ = 0 := rfl @[simp, norm_cast] lemma imK_nnratCast (q : ℚ≥0) : (q : ℍ[R]).imK = 0 := rfl @[simp, norm_cast] lemma ratCast_re (q : ℚ) : (q : ℍ[R]).re = q := rfl @[simp, norm_cast] lemma ratCast_im (q : ℚ) : (q : ℍ[R]).im = 0 := rfl @[simp, norm_cast] lemma ratCast_imI (q : ℚ) : (q : ℍ[R]).imI = 0 := rfl @[simp, norm_cast] lemma ratCast_imJ (q : ℚ) : (q : ℍ[R]).imJ = 0 := rfl @[simp, norm_cast] lemma ratCast_imK (q : ℚ) : (q : ℍ[R]).imK = 0 := rfl @[norm_cast] lemma coe_nnratCast (q : ℚ≥0) : ↑(q : R) = (q : ℍ[R]) := rfl @[norm_cast] lemma coe_ratCast (q : ℚ) : ↑(q : R) = (q : ℍ[R]) := rfl variable [LinearOrder R] [IsStrictOrderedRing R] (a b : ℍ[R]) @[simps -isSimp] instance instInv : Inv ℍ[R] := ⟨fun a => (normSq a)⁻¹ • star a⟩ instance instGroupWithZero : GroupWithZero ℍ[R] := { Quaternion.instNontrivial with inv := Inv.inv inv_zero := by rw [instInv_inv, star_zero, smul_zero] mul_inv_cancel := fun a ha => by rw [instInv_inv, Algebra.mul_smul_comm (normSq a)⁻¹ a (star a), self_mul_star, smul_coe, inv_mul_cancel₀ (normSq_ne_zero.2 ha), coe_one] } @[norm_cast, simp] theorem coe_inv (x : R) : ((x⁻¹ : R) : ℍ[R]) = (↑x)⁻¹ := map_inv₀ (algebraMap R ℍ[R]) _ @[norm_cast, simp] theorem coe_div (x y : R) : ((x / y : R) : ℍ[R]) = x / y := map_div₀ (algebraMap R ℍ[R]) x y @[norm_cast, simp] theorem coe_zpow (x : R) (z : ℤ) : ((x ^ z : R) : ℍ[R]) = (x : ℍ[R]) ^ z := map_zpow₀ (algebraMap R ℍ[R]) x z instance instDivisionRing : DivisionRing ℍ[R] where __ := Quaternion.instRing __ := Quaternion.instGroupWithZero nnqsmul := (· • ·) qsmul := (· • ·) nnratCast_def _ := by rw [← coe_nnratCast, NNRat.cast_def, coe_div, coe_natCast, coe_natCast] ratCast_def _ := by rw [← coe_ratCast, Rat.cast_def, coe_div, coe_intCast, coe_natCast] nnqsmul_def _ _ := by rw [← coe_nnratCast, coe_mul_eq_smul]; ext <;> exact NNRat.smul_def .. qsmul_def _ _ := by rw [← coe_ratCast, coe_mul_eq_smul]; ext <;> exact Rat.smul_def .. theorem normSq_inv : normSq a⁻¹ = (normSq a)⁻¹ := map_inv₀ normSq _ theorem normSq_div : normSq (a / b) = normSq a / normSq b := map_div₀ normSq a b theorem normSq_zpow (z : ℤ) : normSq (a ^ z) = normSq a ^ z := map_zpow₀ normSq a z @[norm_cast] theorem normSq_ratCast (q : ℚ) : normSq (q : ℍ[R]) = (q : ℍ[R]) ^ 2 := by rw [← coe_ratCast, normSq_coe, coe_pow] end Field end Quaternion namespace Cardinal open Quaternion section QuaternionAlgebra variable {R : Type*} (c₁ c₂ c₃ : R) private theorem pow_four [Infinite R] : #R ^ 4 = #R := power_nat_eq (aleph0_le_mk R) <| by decide /-- The cardinality of a quaternion algebra, as a type. -/ theorem mk_quaternionAlgebra : #(ℍ[R,c₁,c₂,c₃]) = #R ^ 4 := by rw [mk_congr (QuaternionAlgebra.equivProd c₁ c₂ c₃)] simp only [mk_prod, lift_id] ring @[simp] theorem mk_quaternionAlgebra_of_infinite [Infinite R] : #(ℍ[R,c₁,c₂,c₃]) = #R := by rw [mk_quaternionAlgebra, pow_four] /-- The cardinality of a quaternion algebra, as a set. -/ theorem mk_univ_quaternionAlgebra : #(Set.univ : Set ℍ[R,c₁,c₂,c₃]) = #R ^ 4 := by rw [mk_univ, mk_quaternionAlgebra] theorem mk_univ_quaternionAlgebra_of_infinite [Infinite R] : #(Set.univ : Set ℍ[R,c₁,c₂,c₃]) = #R := by rw [mk_univ_quaternionAlgebra, pow_four] /-- Show the quaternion ⟨w, x, y, z⟩ as a string "{ re := w, imI := x, imJ := y, imK := z }". For the typical case of quaternions over ℝ, each component will show as a Cauchy sequence due to the way Real numbers are represented. -/ instance [Repr R] {a b c : R} : Repr ℍ[R, a, b, c] where reprPrec q _ := s!"\{ re := {repr q.re}, imI := {repr q.imI}, imJ := {repr q.imJ}, imK := {repr q.imK} }" end QuaternionAlgebra section Quaternion variable (R : Type*) [Zero R] [One R] [Neg R] /-- The cardinality of the quaternions, as a type. -/ @[simp] theorem mk_quaternion : #(ℍ[R]) = #R ^ 4 := mk_quaternionAlgebra _ _ _ theorem mk_quaternion_of_infinite [Infinite R] : #(ℍ[R]) = #R := mk_quaternionAlgebra_of_infinite _ _ _ /-- The cardinality of the quaternions, as a set. -/ theorem mk_univ_quaternion : #(Set.univ : Set ℍ[R]) = #R ^ 4 := mk_univ_quaternionAlgebra _ _ _ theorem mk_univ_quaternion_of_infinite [Infinite R] : #(Set.univ : Set ℍ[R]) = #R := mk_univ_quaternionAlgebra_of_infinite _ _ _ end Quaternion end Cardinal
Mathlib/Algebra/Quaternion.lean
1,355
1,361
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro -/ import Mathlib.Algebra.Algebra.Subalgebra.Lattice import Mathlib.Algebra.Algebra.Tower import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Algebra.MonoidAlgebra.Basic import Mathlib.Algebra.MonoidAlgebra.Support import Mathlib.Algebra.Regular.Pow import Mathlib.Data.Finsupp.Antidiagonal import Mathlib.Order.SymmDiff /-! # Multivariate polynomials This file defines polynomial rings over a base ring (or even semiring), with variables from a general type `σ` (which could be infinite). ## Important definitions Let `R` be a commutative ring (or a semiring) and let `σ` be an arbitrary type. This file creates the type `MvPolynomial σ R`, which mathematicians might denote $R[X_i : i \in σ]$. It is the type of multivariate (a.k.a. multivariable) polynomials, with variables corresponding to the terms in `σ`, and coefficients in `R`. ### Notation In the definitions below, we use the following notation: + `σ : Type*` (indexing the variables) + `R : Type*` `[CommSemiring R]` (the coefficients) + `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set. This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s` + `a : R` + `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians + `p : MvPolynomial σ R` ### Definitions * `MvPolynomial σ R` : the type of polynomials with variables of type `σ` and coefficients in the commutative semiring `R` * `monomial s a` : the monomial which mathematically would be denoted `a * X^s` * `C a` : the constant polynomial with value `a` * `X i` : the degree one monomial corresponding to i; mathematically this might be denoted `Xᵢ`. * `coeff s p` : the coefficient of `s` in `p`. ## Implementation notes Recall that if `Y` has a zero, then `X →₀ Y` is the type of functions from `X` to `Y` with finite support, i.e. such that only finitely many elements of `X` get sent to non-zero terms in `Y`. The definition of `MvPolynomial σ R` is `(σ →₀ ℕ) →₀ R`; here `σ →₀ ℕ` denotes the space of all monomials in the variables, and the function to `R` sends a monomial to its coefficient in the polynomial being represented. ## Tags polynomial, multivariate polynomial, multivariable polynomial -/ noncomputable section open Set Function Finsupp AddMonoidAlgebra open scoped Pointwise universe u v w x variable {R : Type u} {S₁ : Type v} {S₂ : Type w} {S₃ : Type x} /-- Multivariate polynomial, where `σ` is the index set of the variables and `R` is the coefficient ring -/ def MvPolynomial (σ : Type*) (R : Type*) [CommSemiring R] := AddMonoidAlgebra R (σ →₀ ℕ) namespace MvPolynomial -- Porting note: because of `MvPolynomial.C` and `MvPolynomial.X` this linter throws -- tons of warnings in this file, and it's easier to just disable them globally in the file variable {σ : Type*} {a a' a₁ a₂ : R} {e : ℕ} {n m : σ} {s : σ →₀ ℕ} section CommSemiring section Instances instance decidableEqMvPolynomial [CommSemiring R] [DecidableEq σ] [DecidableEq R] : DecidableEq (MvPolynomial σ R) := Finsupp.instDecidableEq instance commSemiring [CommSemiring R] : CommSemiring (MvPolynomial σ R) := AddMonoidAlgebra.commSemiring instance inhabited [CommSemiring R] : Inhabited (MvPolynomial σ R) := ⟨0⟩ instance distribuMulAction [Monoid R] [CommSemiring S₁] [DistribMulAction R S₁] : DistribMulAction R (MvPolynomial σ S₁) := AddMonoidAlgebra.distribMulAction instance smulZeroClass [CommSemiring S₁] [SMulZeroClass R S₁] : SMulZeroClass R (MvPolynomial σ S₁) := AddMonoidAlgebra.smulZeroClass instance faithfulSMul [CommSemiring S₁] [SMulZeroClass R S₁] [FaithfulSMul R S₁] : FaithfulSMul R (MvPolynomial σ S₁) := AddMonoidAlgebra.faithfulSMul instance module [Semiring R] [CommSemiring S₁] [Module R S₁] : Module R (MvPolynomial σ S₁) := AddMonoidAlgebra.module instance isScalarTower [CommSemiring S₂] [SMul R S₁] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂] [IsScalarTower R S₁ S₂] : IsScalarTower R S₁ (MvPolynomial σ S₂) := AddMonoidAlgebra.isScalarTower instance smulCommClass [CommSemiring S₂] [SMulZeroClass R S₂] [SMulZeroClass S₁ S₂] [SMulCommClass R S₁ S₂] : SMulCommClass R S₁ (MvPolynomial σ S₂) := AddMonoidAlgebra.smulCommClass instance isCentralScalar [CommSemiring S₁] [SMulZeroClass R S₁] [SMulZeroClass Rᵐᵒᵖ S₁] [IsCentralScalar R S₁] : IsCentralScalar R (MvPolynomial σ S₁) := AddMonoidAlgebra.isCentralScalar instance algebra [CommSemiring R] [CommSemiring S₁] [Algebra R S₁] : Algebra R (MvPolynomial σ S₁) := AddMonoidAlgebra.algebra instance isScalarTower_right [CommSemiring S₁] [DistribSMul R S₁] [IsScalarTower R S₁ S₁] : IsScalarTower R (MvPolynomial σ S₁) (MvPolynomial σ S₁) := AddMonoidAlgebra.isScalarTower_self _ instance smulCommClass_right [CommSemiring S₁] [DistribSMul R S₁] [SMulCommClass R S₁ S₁] : SMulCommClass R (MvPolynomial σ S₁) (MvPolynomial σ S₁) := AddMonoidAlgebra.smulCommClass_self _ /-- If `R` is a subsingleton, then `MvPolynomial σ R` has a unique element -/ instance unique [CommSemiring R] [Subsingleton R] : Unique (MvPolynomial σ R) := AddMonoidAlgebra.unique end Instances variable [CommSemiring R] [CommSemiring S₁] {p q : MvPolynomial σ R} /-- `monomial s a` is the monomial with coefficient `a` and exponents given by `s` -/ def monomial (s : σ →₀ ℕ) : R →ₗ[R] MvPolynomial σ R := AddMonoidAlgebra.lsingle s theorem one_def : (1 : MvPolynomial σ R) = monomial 0 1 := rfl theorem single_eq_monomial (s : σ →₀ ℕ) (a : R) : Finsupp.single s a = monomial s a := rfl theorem mul_def : p * q = p.sum fun m a => q.sum fun n b => monomial (m + n) (a * b) := AddMonoidAlgebra.mul_def /-- `C a` is the constant polynomial with value `a` -/ def C : R →+* MvPolynomial σ R := { singleZeroRingHom with toFun := monomial 0 } variable (R σ) @[simp] theorem algebraMap_eq : algebraMap R (MvPolynomial σ R) = C := rfl variable {R σ} /-- `X n` is the degree `1` monomial $X_n$. -/ def X (n : σ) : MvPolynomial σ R := monomial (Finsupp.single n 1) 1 theorem monomial_left_injective {r : R} (hr : r ≠ 0) : Function.Injective fun s : σ →₀ ℕ => monomial s r := Finsupp.single_left_injective hr @[simp] theorem monomial_left_inj {s t : σ →₀ ℕ} {r : R} (hr : r ≠ 0) : monomial s r = monomial t r ↔ s = t := Finsupp.single_left_inj hr theorem C_apply : (C a : MvPolynomial σ R) = monomial 0 a := rfl @[simp] theorem C_0 : C 0 = (0 : MvPolynomial σ R) := map_zero _ @[simp] theorem C_1 : C 1 = (1 : MvPolynomial σ R) := rfl theorem C_mul_monomial : C a * monomial s a' = monomial s (a * a') := by -- Porting note: this `show` feels like defeq abuse, but I can't find the appropriate lemmas show AddMonoidAlgebra.single _ _ * AddMonoidAlgebra.single _ _ = AddMonoidAlgebra.single _ _ simp [C_apply, single_mul_single] @[simp] theorem C_add : (C (a + a') : MvPolynomial σ R) = C a + C a' := Finsupp.single_add _ _ _ @[simp] theorem C_mul : (C (a * a') : MvPolynomial σ R) = C a * C a' := C_mul_monomial.symm @[simp] theorem C_pow (a : R) (n : ℕ) : (C (a ^ n) : MvPolynomial σ R) = C a ^ n := map_pow _ _ _ theorem C_injective (σ : Type*) (R : Type*) [CommSemiring R] : Function.Injective (C : R → MvPolynomial σ R) := Finsupp.single_injective _ theorem C_surjective {R : Type*} [CommSemiring R] (σ : Type*) [IsEmpty σ] : Function.Surjective (C : R → MvPolynomial σ R) := by refine fun p => ⟨p.toFun 0, Finsupp.ext fun a => ?_⟩ simp only [C_apply, ← single_eq_monomial, (Finsupp.ext isEmptyElim (α := σ) : a = 0), single_eq_same] rfl @[simp] theorem C_inj {σ : Type*} (R : Type*) [CommSemiring R] (r s : R) : (C r : MvPolynomial σ R) = C s ↔ r = s := (C_injective σ R).eq_iff @[simp] lemma C_eq_zero : (C a : MvPolynomial σ R) = 0 ↔ a = 0 := by rw [← map_zero C, C_inj] lemma C_ne_zero : (C a : MvPolynomial σ R) ≠ 0 ↔ a ≠ 0 := C_eq_zero.ne instance nontrivial_of_nontrivial (σ : Type*) (R : Type*) [CommSemiring R] [Nontrivial R] : Nontrivial (MvPolynomial σ R) := inferInstanceAs (Nontrivial <| AddMonoidAlgebra R (σ →₀ ℕ)) instance infinite_of_infinite (σ : Type*) (R : Type*) [CommSemiring R] [Infinite R] : Infinite (MvPolynomial σ R) := Infinite.of_injective C (C_injective _ _) instance infinite_of_nonempty (σ : Type*) (R : Type*) [Nonempty σ] [CommSemiring R] [Nontrivial R] : Infinite (MvPolynomial σ R) := Infinite.of_injective ((fun s : σ →₀ ℕ => monomial s 1) ∘ Finsupp.single (Classical.arbitrary σ)) <| (monomial_left_injective one_ne_zero).comp (Finsupp.single_injective _) theorem C_eq_coe_nat (n : ℕ) : (C ↑n : MvPolynomial σ R) = n := by induction n <;> simp [*] theorem C_mul' : MvPolynomial.C a * p = a • p := (Algebra.smul_def a p).symm theorem smul_eq_C_mul (p : MvPolynomial σ R) (a : R) : a • p = C a * p := C_mul'.symm theorem C_eq_smul_one : (C a : MvPolynomial σ R) = a • (1 : MvPolynomial σ R) := by rw [← C_mul', mul_one] theorem smul_monomial {S₁ : Type*} [SMulZeroClass S₁ R] (r : S₁) : r • monomial s a = monomial s (r • a) := Finsupp.smul_single _ _ _ theorem X_injective [Nontrivial R] : Function.Injective (X : σ → MvPolynomial σ R) := (monomial_left_injective one_ne_zero).comp (Finsupp.single_left_injective one_ne_zero) @[simp] theorem X_inj [Nontrivial R] (m n : σ) : X m = (X n : MvPolynomial σ R) ↔ m = n := X_injective.eq_iff theorem monomial_pow : monomial s a ^ e = monomial (e • s) (a ^ e) := AddMonoidAlgebra.single_pow e @[simp] theorem monomial_mul {s s' : σ →₀ ℕ} {a b : R} : monomial s a * monomial s' b = monomial (s + s') (a * b) := AddMonoidAlgebra.single_mul_single variable (σ R) /-- `fun s ↦ monomial s 1` as a homomorphism. -/ def monomialOneHom : Multiplicative (σ →₀ ℕ) →* MvPolynomial σ R := AddMonoidAlgebra.of _ _ variable {σ R} @[simp] theorem monomialOneHom_apply : monomialOneHom R σ s = (monomial s 1 : MvPolynomial σ R) := rfl theorem X_pow_eq_monomial : X n ^ e = monomial (Finsupp.single n e) (1 : R) := by simp [X, monomial_pow] theorem monomial_add_single : monomial (s + Finsupp.single n e) a = monomial s a * X n ^ e := by rw [X_pow_eq_monomial, monomial_mul, mul_one] theorem monomial_single_add : monomial (Finsupp.single n e + s) a = X n ^ e * monomial s a := by rw [X_pow_eq_monomial, monomial_mul, one_mul] theorem C_mul_X_pow_eq_monomial {s : σ} {a : R} {n : ℕ} : C a * X s ^ n = monomial (Finsupp.single s n) a := by rw [← zero_add (Finsupp.single s n), monomial_add_single, C_apply] theorem C_mul_X_eq_monomial {s : σ} {a : R} : C a * X s = monomial (Finsupp.single s 1) a := by rw [← C_mul_X_pow_eq_monomial, pow_one] @[simp] theorem monomial_zero {s : σ →₀ ℕ} : monomial s (0 : R) = 0 := Finsupp.single_zero _ @[simp] theorem monomial_zero' : (monomial (0 : σ →₀ ℕ) : R → MvPolynomial σ R) = C := rfl @[simp] theorem monomial_eq_zero {s : σ →₀ ℕ} {b : R} : monomial s b = 0 ↔ b = 0 := Finsupp.single_eq_zero @[simp] theorem sum_monomial_eq {A : Type*} [AddCommMonoid A] {u : σ →₀ ℕ} {r : R} {b : (σ →₀ ℕ) → R → A} (w : b u 0 = 0) : sum (monomial u r) b = b u r := Finsupp.sum_single_index w @[simp] theorem sum_C {A : Type*} [AddCommMonoid A] {b : (σ →₀ ℕ) → R → A} (w : b 0 0 = 0) : sum (C a) b = b 0 a := sum_monomial_eq w theorem monomial_sum_one {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) : (monomial (∑ i ∈ s, f i) 1 : MvPolynomial σ R) = ∏ i ∈ s, monomial (f i) 1 := map_prod (monomialOneHom R σ) (fun i => Multiplicative.ofAdd (f i)) s theorem monomial_sum_index {α : Type*} (s : Finset α) (f : α → σ →₀ ℕ) (a : R) : monomial (∑ i ∈ s, f i) a = C a * ∏ i ∈ s, monomial (f i) 1 := by rw [← monomial_sum_one, C_mul', ← (monomial _).map_smul, smul_eq_mul, mul_one] theorem monomial_finsupp_sum_index {α β : Type*} [Zero β] (f : α →₀ β) (g : α → β → σ →₀ ℕ) (a : R) : monomial (f.sum g) a = C a * f.prod fun a b => monomial (g a b) 1 := monomial_sum_index _ _ _ theorem monomial_eq_monomial_iff {α : Type*} (a₁ a₂ : α →₀ ℕ) (b₁ b₂ : R) : monomial a₁ b₁ = monomial a₂ b₂ ↔ a₁ = a₂ ∧ b₁ = b₂ ∨ b₁ = 0 ∧ b₂ = 0 := Finsupp.single_eq_single_iff _ _ _ _ theorem monomial_eq : monomial s a = C a * (s.prod fun n e => X n ^ e : MvPolynomial σ R) := by simp only [X_pow_eq_monomial, ← monomial_finsupp_sum_index, Finsupp.sum_single] @[simp] lemma prod_X_pow_eq_monomial : ∏ x ∈ s.support, X x ^ s x = monomial s (1 : R) := by simp only [monomial_eq, map_one, one_mul, Finsupp.prod] @[elab_as_elim] theorem induction_on_monomial {motive : MvPolynomial σ R → Prop} (C : ∀ a, motive (C a)) (mul_X : ∀ p n, motive p → motive (p * X n)) : ∀ s a, motive (monomial s a) := by intro s a apply @Finsupp.induction σ ℕ _ _ s · show motive (monomial 0 a) exact C a · intro n e p _hpn _he ih have : ∀ e : ℕ, motive (monomial p a * X n ^ e) := by intro e induction e with | zero => simp [ih] | succ e e_ih => simp [ih, pow_succ, (mul_assoc _ _ _).symm, mul_X, e_ih] simp [add_comm, monomial_add_single, this] /-- Analog of `Polynomial.induction_on'`. To prove something about mv_polynomials, it suffices to show the condition is closed under taking sums, and it holds for monomials. -/ @[elab_as_elim] theorem induction_on' {P : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (monomial : ∀ (u : σ →₀ ℕ) (a : R), P (monomial u a)) (add : ∀ p q : MvPolynomial σ R, P p → P q → P (p + q)) : P p := Finsupp.induction p (suffices P (MvPolynomial.monomial 0 0) by rwa [monomial_zero] at this show P (MvPolynomial.monomial 0 0) from monomial 0 0) fun _ _ _ _ha _hb hPf => add _ _ (monomial _ _) hPf /-- Similar to `MvPolynomial.induction_on` but only a weak form of `h_add` is required. In particular, this version only requires us to show that `motive` is closed under addition of nontrivial monomials not present in the support. -/ @[elab_as_elim] theorem monomial_add_induction_on {motive : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (C : ∀ a, motive (C a)) (monomial_add : ∀ (a : σ →₀ ℕ) (b : R) (f : MvPolynomial σ R), a ∉ f.support → b ≠ 0 → motive f → motive ((monomial a b) + f)) : motive p := Finsupp.induction p (C_0.rec <| C 0) monomial_add @[deprecated (since := "2025-03-11")] alias induction_on''' := monomial_add_induction_on /-- Similar to `MvPolynomial.induction_on` but only a yet weaker form of `h_add` is required. In particular, this version only requires us to show that `motive` is closed under addition of monomials not present in the support for which `motive` is already known to hold. -/ theorem induction_on'' {motive : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (C : ∀ a, motive (C a)) (monomial_add : ∀ (a : σ →₀ ℕ) (b : R) (f : MvPolynomial σ R), a ∉ f.support → b ≠ 0 → motive f → motive (monomial a b) → motive ((monomial a b) + f)) (mul_X : ∀ (p : MvPolynomial σ R) (n : σ), motive p → motive (p * MvPolynomial.X n)) : motive p := monomial_add_induction_on p C fun a b f ha hb hf => monomial_add a b f ha hb hf <| induction_on_monomial C mul_X a b /-- Analog of `Polynomial.induction_on`. If a property holds for any constant polynomial and is preserved under addition and multiplication by variables then it holds for all multivariate polynomials. -/ @[recursor 5] theorem induction_on {motive : MvPolynomial σ R → Prop} (p : MvPolynomial σ R) (C : ∀ a, motive (C a)) (add : ∀ p q, motive p → motive q → motive (p + q)) (mul_X : ∀ p n, motive p → motive (p * X n)) : motive p := induction_on'' p C (fun a b f _ha _hb hf hm => add (monomial a b) f hm hf) mul_X theorem ringHom_ext {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A} (hC : ∀ r, f (C r) = g (C r)) (hX : ∀ i, f (X i) = g (X i)) : f = g := by refine AddMonoidAlgebra.ringHom_ext' ?_ ?_ -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11041): this has high priority, but Lean still chooses `RingHom.ext`, why? -- probably because of the type synonym · ext x exact hC _ · apply Finsupp.mulHom_ext'; intros x -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11041): `Finsupp.mulHom_ext'` needs to have increased priority apply MonoidHom.ext_mnat exact hX _ /-- See note [partially-applied ext lemmas]. -/ @[ext 1100] theorem ringHom_ext' {A : Type*} [Semiring A] {f g : MvPolynomial σ R →+* A} (hC : f.comp C = g.comp C) (hX : ∀ i, f (X i) = g (X i)) : f = g := ringHom_ext (RingHom.ext_iff.1 hC) hX theorem hom_eq_hom [Semiring S₂] (f g : MvPolynomial σ R →+* S₂) (hC : f.comp C = g.comp C) (hX : ∀ n : σ, f (X n) = g (X n)) (p : MvPolynomial σ R) : f p = g p := RingHom.congr_fun (ringHom_ext' hC hX) p theorem is_id (f : MvPolynomial σ R →+* MvPolynomial σ R) (hC : f.comp C = C) (hX : ∀ n : σ, f (X n) = X n) (p : MvPolynomial σ R) : f p = p := hom_eq_hom f (RingHom.id _) hC hX p @[ext 1100] theorem algHom_ext' {A B : Type*} [CommSemiring A] [CommSemiring B] [Algebra R A] [Algebra R B] {f g : MvPolynomial σ A →ₐ[R] B} (h₁ : f.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A)) = g.comp (IsScalarTower.toAlgHom R A (MvPolynomial σ A))) (h₂ : ∀ i, f (X i) = g (X i)) : f = g := AlgHom.coe_ringHom_injective (MvPolynomial.ringHom_ext' (congr_arg AlgHom.toRingHom h₁) h₂) @[ext 1200] theorem algHom_ext {A : Type*} [Semiring A] [Algebra R A] {f g : MvPolynomial σ R →ₐ[R] A} (hf : ∀ i : σ, f (X i) = g (X i)) : f = g := AddMonoidAlgebra.algHom_ext' (mulHom_ext' fun X : σ => MonoidHom.ext_mnat (hf X)) @[simp] theorem algHom_C {A : Type*} [Semiring A] [Algebra R A] (f : MvPolynomial σ R →ₐ[R] A) (r : R) : f (C r) = algebraMap R A r := f.commutes r @[simp] theorem adjoin_range_X : Algebra.adjoin R (range (X : σ → MvPolynomial σ R)) = ⊤ := by set S := Algebra.adjoin R (range (X : σ → MvPolynomial σ R)) refine top_unique fun p hp => ?_; clear hp induction p using MvPolynomial.induction_on with | C => exact S.algebraMap_mem _ | add p q hp hq => exact S.add_mem hp hq | mul_X p i hp => exact S.mul_mem hp (Algebra.subset_adjoin <| mem_range_self _) @[ext] theorem linearMap_ext {M : Type*} [AddCommMonoid M] [Module R M] {f g : MvPolynomial σ R →ₗ[R] M} (h : ∀ s, f ∘ₗ monomial s = g ∘ₗ monomial s) : f = g := Finsupp.lhom_ext' h section Support /-- The finite set of all `m : σ →₀ ℕ` such that `X^m` has a non-zero coefficient. -/ def support (p : MvPolynomial σ R) : Finset (σ →₀ ℕ) := Finsupp.support p theorem finsupp_support_eq_support (p : MvPolynomial σ R) : Finsupp.support p = p.support := rfl theorem support_monomial [h : Decidable (a = 0)] : (monomial s a).support = if a = 0 then ∅ else {s} := by rw [← Subsingleton.elim (Classical.decEq R a 0) h] rfl theorem support_monomial_subset : (monomial s a).support ⊆ {s} := support_single_subset theorem support_add [DecidableEq σ] : (p + q).support ⊆ p.support ∪ q.support := Finsupp.support_add theorem support_X [Nontrivial R] : (X n : MvPolynomial σ R).support = {Finsupp.single n 1} := by classical rw [X, support_monomial, if_neg]; exact one_ne_zero theorem support_X_pow [Nontrivial R] (s : σ) (n : ℕ) : (X s ^ n : MvPolynomial σ R).support = {Finsupp.single s n} := by classical rw [X_pow_eq_monomial, support_monomial, if_neg (one_ne_zero' R)] @[simp] theorem support_zero : (0 : MvPolynomial σ R).support = ∅ := rfl theorem support_smul {S₁ : Type*} [SMulZeroClass S₁ R] {a : S₁} {f : MvPolynomial σ R} : (a • f).support ⊆ f.support := Finsupp.support_smul theorem support_sum {α : Type*} [DecidableEq σ] {s : Finset α} {f : α → MvPolynomial σ R} : (∑ x ∈ s, f x).support ⊆ s.biUnion fun x => (f x).support := Finsupp.support_finset_sum end Support section Coeff /-- The coefficient of the monomial `m` in the multi-variable polynomial `p`. -/ def coeff (m : σ →₀ ℕ) (p : MvPolynomial σ R) : R := @DFunLike.coe ((σ →₀ ℕ) →₀ R) _ _ _ p m @[simp] theorem mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∈ p.support ↔ p.coeff m ≠ 0 := by simp [support, coeff] theorem not_mem_support_iff {p : MvPolynomial σ R} {m : σ →₀ ℕ} : m ∉ p.support ↔ p.coeff m = 0 := by simp theorem sum_def {A} [AddCommMonoid A] {p : MvPolynomial σ R} {b : (σ →₀ ℕ) → R → A} : p.sum b = ∑ m ∈ p.support, b m (p.coeff m) := by simp [support, Finsupp.sum, coeff] theorem support_mul [DecidableEq σ] (p q : MvPolynomial σ R) : (p * q).support ⊆ p.support + q.support := AddMonoidAlgebra.support_mul p q @[ext] theorem ext (p q : MvPolynomial σ R) : (∀ m, coeff m p = coeff m q) → p = q := Finsupp.ext @[simp] theorem coeff_add (m : σ →₀ ℕ) (p q : MvPolynomial σ R) : coeff m (p + q) = coeff m p + coeff m q := add_apply p q m @[simp] theorem coeff_smul {S₁ : Type*} [SMulZeroClass S₁ R] (m : σ →₀ ℕ) (C : S₁) (p : MvPolynomial σ R) : coeff m (C • p) = C • coeff m p := smul_apply C p m @[simp] theorem coeff_zero (m : σ →₀ ℕ) : coeff m (0 : MvPolynomial σ R) = 0 := rfl @[simp] theorem coeff_zero_X (i : σ) : coeff 0 (X i : MvPolynomial σ R) = 0 := single_eq_of_ne fun h => by cases Finsupp.single_eq_zero.1 h /-- `MvPolynomial.coeff m` but promoted to an `AddMonoidHom`. -/ @[simps] def coeffAddMonoidHom (m : σ →₀ ℕ) : MvPolynomial σ R →+ R where toFun := coeff m map_zero' := coeff_zero m map_add' := coeff_add m variable (R) in /-- `MvPolynomial.coeff m` but promoted to a `LinearMap`. -/ @[simps] def lcoeff (m : σ →₀ ℕ) : MvPolynomial σ R →ₗ[R] R where toFun := coeff m map_add' := coeff_add m map_smul' := coeff_smul m theorem coeff_sum {X : Type*} (s : Finset X) (f : X → MvPolynomial σ R) (m : σ →₀ ℕ) : coeff m (∑ x ∈ s, f x) = ∑ x ∈ s, coeff m (f x) := map_sum (@coeffAddMonoidHom R σ _ _) _ s theorem monic_monomial_eq (m) : monomial m (1 : R) = (m.prod fun n e => X n ^ e : MvPolynomial σ R) := by simp [monomial_eq] @[simp] theorem coeff_monomial [DecidableEq σ] (m n) (a) : coeff m (monomial n a : MvPolynomial σ R) = if n = m then a else 0 := Finsupp.single_apply @[simp] theorem coeff_C [DecidableEq σ] (m) (a) : coeff m (C a : MvPolynomial σ R) = if 0 = m then a else 0 := Finsupp.single_apply lemma eq_C_of_isEmpty [IsEmpty σ] (p : MvPolynomial σ R) : p = C (p.coeff 0) := by obtain ⟨x, rfl⟩ := C_surjective σ p simp theorem coeff_one [DecidableEq σ] (m) : coeff m (1 : MvPolynomial σ R) = if 0 = m then 1 else 0 := coeff_C m 1 @[simp] theorem coeff_zero_C (a) : coeff 0 (C a : MvPolynomial σ R) = a := single_eq_same @[simp] theorem coeff_zero_one : coeff 0 (1 : MvPolynomial σ R) = 1 := coeff_zero_C 1 theorem coeff_X_pow [DecidableEq σ] (i : σ) (m) (k : ℕ) : coeff m (X i ^ k : MvPolynomial σ R) = if Finsupp.single i k = m then 1 else 0 := by have := coeff_monomial m (Finsupp.single i k) (1 : R) rwa [@monomial_eq _ _ (1 : R) (Finsupp.single i k) _, C_1, one_mul, Finsupp.prod_single_index] at this exact pow_zero _ theorem coeff_X' [DecidableEq σ] (i : σ) (m) : coeff m (X i : MvPolynomial σ R) = if Finsupp.single i 1 = m then 1 else 0 := by rw [← coeff_X_pow, pow_one] @[simp] theorem coeff_X (i : σ) : coeff (Finsupp.single i 1) (X i : MvPolynomial σ R) = 1 := by classical rw [coeff_X', if_pos rfl] @[simp] theorem coeff_C_mul (m) (a : R) (p : MvPolynomial σ R) : coeff m (C a * p) = a * coeff m p := by classical rw [mul_def, sum_C] · simp +contextual [sum_def, coeff_sum] simp theorem coeff_mul [DecidableEq σ] (p q : MvPolynomial σ R) (n : σ →₀ ℕ) : coeff n (p * q) = ∑ x ∈ Finset.antidiagonal n, coeff x.1 p * coeff x.2 q := AddMonoidAlgebra.mul_apply_antidiagonal p q _ _ Finset.mem_antidiagonal @[simp] theorem coeff_mul_monomial (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) : coeff (m + s) (p * monomial s r) = coeff m p * r := AddMonoidAlgebra.mul_single_apply_aux p _ _ _ _ fun _a _ => add_left_inj _ @[simp] theorem coeff_monomial_mul (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) : coeff (s + m) (monomial s r * p) = r * coeff m p := AddMonoidAlgebra.single_mul_apply_aux p _ _ _ _ fun _a _ => add_right_inj _ @[simp] theorem coeff_mul_X (m) (s : σ) (p : MvPolynomial σ R) : coeff (m + Finsupp.single s 1) (p * X s) = coeff m p := (coeff_mul_monomial _ _ _ _).trans (mul_one _) @[simp] theorem coeff_X_mul (m) (s : σ) (p : MvPolynomial σ R) : coeff (Finsupp.single s 1 + m) (X s * p) = coeff m p := (coeff_monomial_mul _ _ _ _).trans (one_mul _) lemma coeff_single_X_pow [DecidableEq σ] (s s' : σ) (n n' : ℕ) : (X (R := R) s ^ n).coeff (Finsupp.single s' n') = if s = s' ∧ n = n' ∨ n = 0 ∧ n' = 0 then 1 else 0 := by simp only [coeff_X_pow, single_eq_single_iff] @[simp] lemma coeff_single_X [DecidableEq σ] (s s' : σ) (n : ℕ) : (X s).coeff (R := R) (Finsupp.single s' n) = if n = 1 ∧ s = s' then 1 else 0 := by simpa [eq_comm, and_comm] using coeff_single_X_pow s s' 1 n @[simp] theorem support_mul_X (s : σ) (p : MvPolynomial σ R) : (p * X s).support = p.support.map (addRightEmbedding (Finsupp.single s 1)) := AddMonoidAlgebra.support_mul_single p _ (by simp) _ @[simp] theorem support_X_mul (s : σ) (p : MvPolynomial σ R) : (X s * p).support = p.support.map (addLeftEmbedding (Finsupp.single s 1)) := AddMonoidAlgebra.support_single_mul p _ (by simp) _ @[simp] theorem support_smul_eq {S₁ : Type*} [Semiring S₁] [Module S₁ R] [NoZeroSMulDivisors S₁ R] {a : S₁} (h : a ≠ 0) (p : MvPolynomial σ R) : (a • p).support = p.support := Finsupp.support_smul_eq h theorem support_sdiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) : p.support \ q.support ⊆ (p + q).support := by intro m hm simp only [Classical.not_not, mem_support_iff, Finset.mem_sdiff, Ne] at hm simp [hm.2, hm.1] open scoped symmDiff in theorem support_symmDiff_support_subset_support_add [DecidableEq σ] (p q : MvPolynomial σ R) : p.support ∆ q.support ⊆ (p + q).support := by rw [symmDiff_def, Finset.sup_eq_union] apply Finset.union_subset · exact support_sdiff_support_subset_support_add p q · rw [add_comm] exact support_sdiff_support_subset_support_add q p theorem coeff_mul_monomial' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) : coeff m (p * monomial s r) = if s ≤ m then coeff (m - s) p * r else 0 := by classical split_ifs with h · conv_rhs => rw [← coeff_mul_monomial _ s] congr with t rw [tsub_add_cancel_of_le h] · contrapose! h rw [← mem_support_iff] at h obtain ⟨j, -, rfl⟩ : ∃ j ∈ support p, j + s = m := by simpa [Finset.mem_add] using Finset.add_subset_add_left support_monomial_subset <| support_mul _ _ h exact le_add_left le_rfl theorem coeff_monomial_mul' (m) (s : σ →₀ ℕ) (r : R) (p : MvPolynomial σ R) : coeff m (monomial s r * p) = if s ≤ m then r * coeff (m - s) p else 0 := by -- note that if we allow `R` to be non-commutative we will have to duplicate the proof above. rw [mul_comm, mul_comm r] exact coeff_mul_monomial' _ _ _ _ theorem coeff_mul_X' [DecidableEq σ] (m) (s : σ) (p : MvPolynomial σ R) : coeff m (p * X s) = if s ∈ m.support then coeff (m - Finsupp.single s 1) p else 0 := by refine (coeff_mul_monomial' _ _ _ _).trans ?_ simp_rw [Finsupp.single_le_iff, Finsupp.mem_support_iff, Nat.succ_le_iff, pos_iff_ne_zero, mul_one] theorem coeff_X_mul' [DecidableEq σ] (m) (s : σ) (p : MvPolynomial σ R) : coeff m (X s * p) = if s ∈ m.support then coeff (m - Finsupp.single s 1) p else 0 := by refine (coeff_monomial_mul' _ _ _ _).trans ?_ simp_rw [Finsupp.single_le_iff, Finsupp.mem_support_iff, Nat.succ_le_iff, pos_iff_ne_zero, one_mul] theorem eq_zero_iff {p : MvPolynomial σ R} : p = 0 ↔ ∀ d, coeff d p = 0 := by rw [MvPolynomial.ext_iff] simp only [coeff_zero] theorem ne_zero_iff {p : MvPolynomial σ R} : p ≠ 0 ↔ ∃ d, coeff d p ≠ 0 := by rw [Ne, eq_zero_iff] push_neg rfl @[simp] theorem X_ne_zero [Nontrivial R] (s : σ) : X (R := R) s ≠ 0 := by rw [ne_zero_iff] use Finsupp.single s 1 simp only [coeff_X, ne_eq, one_ne_zero, not_false_eq_true] @[simp] theorem support_eq_empty {p : MvPolynomial σ R} : p.support = ∅ ↔ p = 0 := Finsupp.support_eq_empty @[simp] lemma support_nonempty {p : MvPolynomial σ R} : p.support.Nonempty ↔ p ≠ 0 := by rw [Finset.nonempty_iff_ne_empty, ne_eq, support_eq_empty] theorem exists_coeff_ne_zero {p : MvPolynomial σ R} (h : p ≠ 0) : ∃ d, coeff d p ≠ 0 := ne_zero_iff.mp h theorem C_dvd_iff_dvd_coeff (r : R) (φ : MvPolynomial σ R) : C r ∣ φ ↔ ∀ i, r ∣ φ.coeff i := by constructor
· rintro ⟨φ, rfl⟩ c rw [coeff_C_mul] apply dvd_mul_right
Mathlib/Algebra/MvPolynomial/Basic.lean
761
763
/- Copyright (c) 2016 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro -/ import Mathlib.Algebra.Order.GroupWithZero.Synonym import Mathlib.Algebra.Order.Ring.Canonical import Mathlib.Algebra.Ring.Hom.Defs import Mathlib.Algebra.Order.Monoid.WithTop /-! # Structures involving `*` and `0` on `WithTop` and `WithBot` The main results of this section are `WithTop.instOrderedCommSemiring` and `WithBot.instOrderedCommSemiring`. -/ variable {α : Type*} namespace WithTop variable [DecidableEq α] section MulZeroClass variable [MulZeroClass α] {a b : WithTop α} instance instMulZeroClass : MulZeroClass (WithTop α) where zero := 0 mul | (a : α), (b : α) => ↑(a * b) | (a : α), ⊤ => if a = 0 then 0 else ⊤ | ⊤, (b : α) => if b = 0 then 0 else ⊤ | ⊤, ⊤ => ⊤ mul_zero | (a : α) => congr_arg some <| mul_zero _ | ⊤ => if_pos rfl zero_mul | (b : α) => congr_arg some <| zero_mul _ | ⊤ => if_pos rfl @[simp, norm_cast] lemma coe_mul (a b : α) : (↑(a * b) : WithTop α) = a * b := rfl lemma mul_top' : ∀ (a : WithTop α), a * ⊤ = if a = 0 then 0 else ⊤ | (a : α) => if_congr coe_eq_zero.symm rfl rfl | ⊤ => (if_neg top_ne_zero).symm @[simp] lemma mul_top (h : a ≠ 0) : a * ⊤ = ⊤ := by rw [mul_top', if_neg h] lemma top_mul' : ∀ (b : WithTop α), ⊤ * b = if b = 0 then 0 else ⊤ | (b : α) => if_congr coe_eq_zero.symm rfl rfl | ⊤ => (if_neg top_ne_zero).symm @[simp] lemma top_mul (hb : b ≠ 0) : ⊤ * b = ⊤ := by rw [top_mul', if_neg hb] @[simp] lemma top_mul_top : (⊤ * ⊤ : WithTop α) = ⊤ := rfl lemma mul_def (a b : WithTop α) : a * b = if a = 0 ∨ b = 0 then 0 else WithTop.map₂ (· * ·) a b := by cases a <;> cases b <;> aesop lemma mul_eq_top_iff : a * b = ⊤ ↔ a ≠ 0 ∧ b = ⊤ ∨ a = ⊤ ∧ b ≠ 0 := by rw [mul_def]; aesop lemma mul_coe_eq_bind {b : α} (hb : b ≠ 0) : ∀ a, (a * b : WithTop α) = a.bind fun a ↦ ↑(a * b) | ⊤ => by simp [top_mul, hb]; rfl | (a : α) => rfl lemma coe_mul_eq_bind {a : α} (ha : a ≠ 0) : ∀ b, (a * b : WithTop α) = b.bind fun b ↦ ↑(a * b) | ⊤ => by simp [top_mul, ha]; rfl | (b : α) => rfl @[simp] lemma untopD_zero_mul (a b : WithTop α) : (a * b).untopD 0 = a.untopD 0 * b.untopD 0 := by by_cases ha : a = 0; · rw [ha, zero_mul, ← coe_zero, untopD_coe, zero_mul] by_cases hb : b = 0; · rw [hb, mul_zero, ← coe_zero, untopD_coe, mul_zero] induction a; · rw [top_mul hb, untopD_top, zero_mul] induction b; · rw [mul_top ha, untopD_top, mul_zero] rw [← coe_mul, untopD_coe, untopD_coe, untopD_coe] @[deprecated (since := "2025-02-06")] alias untop'_zero_mul := untopD_zero_mul theorem mul_ne_top {a b : WithTop α} (ha : a ≠ ⊤) (hb : b ≠ ⊤) : a * b ≠ ⊤ := by simp [mul_eq_top_iff, *] theorem mul_lt_top [LT α] {a b : WithTop α} (ha : a < ⊤) (hb : b < ⊤) : a * b < ⊤ := by rw [WithTop.lt_top_iff_ne_top] at * exact mul_ne_top ha hb instance instNoZeroDivisors [NoZeroDivisors α] : NoZeroDivisors (WithTop α) := by refine ⟨fun h₁ => Decidable.byContradiction fun h₂ => ?_⟩ rw [mul_def, if_neg h₂] at h₁ rcases Option.mem_map₂_iff.1 h₁ with ⟨a, b, (rfl : _ = _), (rfl : _ = _), hab⟩ exact h₂ ((eq_zero_or_eq_zero_of_mul_eq_zero hab).imp (congr_arg some) (congr_arg some)) end MulZeroClass /-- `Nontrivial α` is needed here as otherwise we have `1 * ⊤ = ⊤` but also `0 * ⊤ = 0`. -/ instance instMulZeroOneClass [MulZeroOneClass α] [Nontrivial α] : MulZeroOneClass (WithTop α) where __ := instMulZeroClass one_mul | ⊤ => mul_top (mt coe_eq_coe.1 one_ne_zero) | (a : α) => by rw [← coe_one, ← coe_mul, one_mul] mul_one | ⊤ => top_mul (mt coe_eq_coe.1 one_ne_zero) | (a : α) => by rw [← coe_one, ← coe_mul, mul_one] /-- A version of `WithTop.map` for `MonoidWithZeroHom`s. -/ @[simps -fullyApplied] protected def _root_.MonoidWithZeroHom.withTopMap {R S : Type*} [MulZeroOneClass R] [DecidableEq R] [Nontrivial R] [MulZeroOneClass S] [DecidableEq S] [Nontrivial S] (f : R →*₀ S) (hf : Function.Injective f) : WithTop R →*₀ WithTop S := { f.toZeroHom.withTopMap, f.toMonoidHom.toOneHom.withTopMap with toFun := WithTop.map f map_mul' := fun x y => by have : ∀ z, map f z = 0 ↔ z = 0 := fun z => (Option.map_injective hf).eq_iff' f.toZeroHom.withTopMap.map_zero rcases Decidable.eq_or_ne x 0 with (rfl | hx) · simp rcases Decidable.eq_or_ne y 0 with (rfl | hy) · simp induction' x with x · simp [hy, this] induction' y with y · have : (f x : WithTop S) ≠ 0 := by simpa [hf.eq_iff' (map_zero f)] using hx simp [mul_top hx, mul_top this] · simp [← coe_mul] } instance instSemigroupWithZero [SemigroupWithZero α] [NoZeroDivisors α] : SemigroupWithZero (WithTop α) where __ := instMulZeroClass mul_assoc a b c := by rcases eq_or_ne a 0 with (rfl | ha); · simp only [zero_mul] rcases eq_or_ne b 0 with (rfl | hb); · simp only [zero_mul, mul_zero] rcases eq_or_ne c 0 with (rfl | hc); · simp only [mul_zero] induction' a with a; · simp [hb, hc] induction' b with b; · simp [mul_top ha, top_mul hc] induction' c with c · rw [mul_top hb, mul_top ha] rw [← coe_zero, ne_eq, coe_eq_coe] at ha hb simp [ha, hb] simp only [← coe_mul, mul_assoc] section MonoidWithZero variable [MonoidWithZero α] [NoZeroDivisors α] [Nontrivial α] {x : WithTop α} {n : ℕ} instance instMonoidWithZero : MonoidWithZero (WithTop α) where __ := instMulZeroOneClass __ := instSemigroupWithZero npow n a := match a, n with | (a : α), n => ↑(a ^ n) | ⊤, 0 => 1 | ⊤, _n + 1 => ⊤ npow_zero a := by cases a <;> simp npow_succ n a := by cases n <;> cases a <;> simp [pow_succ] @[simp, norm_cast] lemma coe_pow (a : α) (n : ℕ) : (↑(a ^ n) : WithTop α) = a ^ n := rfl @[simp] lemma top_pow : ∀ {n : ℕ}, n ≠ 0 → (⊤ : WithTop α) ^ n = ⊤ | _ + 1, _ => rfl @[simp] lemma pow_eq_top_iff : x ^ n = ⊤ ↔ x = ⊤ ∧ n ≠ 0 := by induction x <;> cases n <;> simp [← coe_pow] lemma pow_ne_top_iff : x ^ n ≠ ⊤ ↔ x ≠ ⊤ ∨ n = 0 := by simp [pow_eq_top_iff, or_iff_not_imp_left] @[simp] lemma pow_lt_top_iff [Preorder α] : x ^ n < ⊤ ↔ x < ⊤ ∨ n = 0 := by simp_rw [WithTop.lt_top_iff_ne_top, pow_ne_top_iff] lemma eq_top_of_pow (n : ℕ) (hx : x ^ n = ⊤) : x = ⊤ := (pow_eq_top_iff.1 hx).1 lemma pow_ne_top (hx : x ≠ ⊤) : x ^ n ≠ ⊤ := pow_ne_top_iff.2 <| .inl hx lemma pow_lt_top [Preorder α] (hx : x < ⊤) : x ^ n < ⊤ := pow_lt_top_iff.2 <| .inl hx end MonoidWithZero instance instCommMonoidWithZero [CommMonoidWithZero α] [NoZeroDivisors α] [Nontrivial α] : CommMonoidWithZero (WithTop α) where __ := instMonoidWithZero mul_comm a b := by simp_rw [mul_def]; exact if_congr or_comm rfl (Option.map₂_comm mul_comm) instance instNonUnitalNonAssocSemiring [NonUnitalNonAssocSemiring α] [PartialOrder α] [CanonicallyOrderedAdd α] : NonUnitalNonAssocSemiring (WithTop α) where toAddCommMonoid := WithTop.addCommMonoid __ := WithTop.instMulZeroClass right_distrib a b c := by induction' c with c
· by_cases ha : a = 0 <;> simp [ha] · by_cases hc : c = 0; · simp [hc] simp only [mul_coe_eq_bind hc] cases a <;> cases b <;> try rfl exact congr_arg some (add_mul _ _ _) left_distrib c a b := by induction' c with c · by_cases ha : a = 0 <;> simp [ha]
Mathlib/Algebra/Order/Ring/WithTop.lean
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/- Copyright (c) 2024 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.Algebra.Small.Module import Mathlib.LinearAlgebra.FreeModule.Finite.Basic import Mathlib.LinearAlgebra.Isomorphisms import Mathlib.LinearAlgebra.TensorProduct.RightExactness import Mathlib.RingTheory.Finiteness.Projective import Mathlib.RingTheory.Localization.BaseChange import Mathlib.RingTheory.Noetherian.Basic import Mathlib.RingTheory.TensorProduct.Finite /-! # Finitely Presented Modules ## Main definition - `Module.FinitePresentation`: A module is finitely presented if it is generated by some finite set `s` and the kernel of the presentation `Rˢ → M` is also finitely generated. ## Main results - `Module.finitePresentation_iff_finite`: If `R` is noetherian, then f.p. iff f.g. on `R`-modules. Suppose `0 → K → M → N → 0` is an exact sequence of `R`-modules. - `Module.finitePresentation_of_surjective`: If `M` is f.p., `K` is f.g., then `N` is f.p. - `Module.FinitePresentation.fg_ker`: If `M` is f.g., `N` is f.p., then `K` is f.g. - `Module.finitePresentation_of_ker`: If `N` and `K` is f.p., then `M` is also f.p. - `Module.FinitePresentation.isLocalizedModule_map`: If `M` and `N` are `R`-modules and `M` is f.p., and `S` is a submonoid of `R`, then `Hom(Mₛ, Nₛ)` is the localization of `Hom(M, N)`. Also the instances finite + free => f.p. => finite are also provided ## TODO Suppose `S` is an `R`-algebra, `M` is an `S`-module. Then 1. If `S` is f.p., then `M` is `R`-f.p. implies `M` is `S`-f.p. 2. If `S` is both f.p. (as an algebra) and finite (as a module), then `M` is `S`-fp implies that `M` is `R`-f.p. 3. If `S` is f.p. as a module, then `S` is f.p. as an algebra. In particular, 4. `S` is f.p. as an `R`-module iff it is f.p. as an algebra and is finite as a module. For finitely presented algebras, see `Algebra.FinitePresentation` in file `Mathlib.RingTheory.FinitePresentation`. -/ open Finsupp section Semiring variable (R M) [Semiring R] [AddCommMonoid M] [Module R M] /-- A module is finitely presented if it is finitely generated by some set `s` and the kernel of the presentation `Rˢ → M` is also finitely generated. -/ class Module.FinitePresentation : Prop where out : ∃ (s : Finset M), Submodule.span R (s : Set M) = ⊤ ∧ (LinearMap.ker (Finsupp.linearCombination R ((↑) : s → M))).FG instance (priority := 100) [h : Module.FinitePresentation R M] : Module.Finite R M := by obtain ⟨s, hs₁, _⟩ := h exact ⟨s, hs₁⟩ end Semiring section Ring
section universe u v variable (R : Type u) (M : Type*) [Ring R] [AddCommGroup M] [Module R M] theorem Module.FinitePresentation.exists_fin [fp : Module.FinitePresentation R M] : ∃ (n : ℕ) (K : Submodule R (Fin n → R)) (_ : M ≃ₗ[R] (Fin n → R) ⧸ K), K.FG := by have ⟨ι, ⟨hι₁, hι₂⟩⟩ := fp
Mathlib/Algebra/Module/FinitePresentation.lean
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/- 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.Finset.Card import Mathlib.Data.Fintype.Basic /-! # Cardinalities of finite types This file defines the cardinality `Fintype.card α` as the number of elements in `(univ : Finset α)`. We also include some elementary results on the values of `Fintype.card` on specific types. ## Main declarations * `Fintype.card α`: Cardinality of a fintype. Equal to `Finset.univ.card`. * `Finite.surjective_of_injective`: an injective function from a finite type to itself is also surjective. -/ assert_not_exists Monoid open Function universe u v variable {α β γ : Type*} open Finset Function namespace Fintype /-- `card α` is the number of elements in `α`, defined when `α` is a fintype. -/ def card (α) [Fintype α] : ℕ := (@univ α _).card theorem subtype_card {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) : @card { x // p x } (Fintype.subtype s H) = #s := Multiset.card_pmap _ _ _ theorem card_of_subtype {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) [Fintype { x // p x }] : card { x // p x } = #s := by rw [← subtype_card s H] congr! @[simp] theorem card_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) : @Fintype.card p (ofFinset s H) = #s := Fintype.subtype_card s H theorem card_of_finset' {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) [Fintype p] : Fintype.card p = #s := by rw [← card_ofFinset s H]; congr! end Fintype namespace Fintype theorem ofEquiv_card [Fintype α] (f : α ≃ β) : @card β (ofEquiv α f) = card α := Multiset.card_map _ _ theorem card_congr {α β} [Fintype α] [Fintype β] (f : α ≃ β) : card α = card β := by rw [← ofEquiv_card f]; congr! @[congr] theorem card_congr' {α β} [Fintype α] [Fintype β] (h : α = β) : card α = card β := card_congr (by rw [h]) /-- Note: this lemma is specifically about `Fintype.ofSubsingleton`. For a statement about arbitrary `Fintype` instances, use either `Fintype.card_le_one_iff_subsingleton` or `Fintype.card_unique`. -/ theorem card_ofSubsingleton (a : α) [Subsingleton α] : @Fintype.card _ (ofSubsingleton a) = 1 := rfl @[simp] theorem card_unique [Unique α] [h : Fintype α] : Fintype.card α = 1 := Subsingleton.elim (ofSubsingleton default) h ▸ card_ofSubsingleton _ /-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about arbitrary `Fintype` instances, use `Fintype.card_eq_zero`. -/ theorem card_ofIsEmpty [IsEmpty α] : @Fintype.card α Fintype.ofIsEmpty = 0 := rfl end Fintype namespace Set variable {s t : Set α} -- We use an arbitrary `[Fintype s]` instance here, -- not necessarily coming from a `[Fintype α]`. @[simp] theorem toFinset_card {α : Type*} (s : Set α) [Fintype s] : s.toFinset.card = Fintype.card s := Multiset.card_map Subtype.val Finset.univ.val end Set @[simp] theorem Finset.card_univ [Fintype α] : #(univ : Finset α) = Fintype.card α := rfl theorem Finset.eq_univ_of_card [Fintype α] (s : Finset α) (hs : #s = Fintype.card α) : s = univ := eq_of_subset_of_card_le (subset_univ _) <| by rw [hs, Finset.card_univ] theorem Finset.card_eq_iff_eq_univ [Fintype α] (s : Finset α) : #s = Fintype.card α ↔ s = univ := ⟨s.eq_univ_of_card, by rintro rfl exact Finset.card_univ⟩ theorem Finset.card_le_univ [Fintype α] (s : Finset α) : #s ≤ Fintype.card α := card_le_card (subset_univ s) theorem Finset.card_lt_univ_of_not_mem [Fintype α] {s : Finset α} {x : α} (hx : x ∉ s) : #s < Fintype.card α := card_lt_card ⟨subset_univ s, not_forall.2 ⟨x, fun hx' => hx (hx' <| mem_univ x)⟩⟩ theorem Finset.card_lt_iff_ne_univ [Fintype α] (s : Finset α) : #s < Fintype.card α ↔ s ≠ Finset.univ := s.card_le_univ.lt_iff_ne.trans (not_congr s.card_eq_iff_eq_univ) theorem Finset.card_compl_lt_iff_nonempty [Fintype α] [DecidableEq α] (s : Finset α) : #sᶜ < Fintype.card α ↔ s.Nonempty := sᶜ.card_lt_iff_ne_univ.trans s.compl_ne_univ_iff_nonempty theorem Finset.card_univ_diff [DecidableEq α] [Fintype α] (s : Finset α) : #(univ \ s) = Fintype.card α - #s := Finset.card_sdiff (subset_univ s) theorem Finset.card_compl [DecidableEq α] [Fintype α] (s : Finset α) : #sᶜ = Fintype.card α - #s := Finset.card_univ_diff s @[simp] theorem Finset.card_add_card_compl [DecidableEq α] [Fintype α] (s : Finset α) : #s + #sᶜ = Fintype.card α := by rw [Finset.card_compl, ← Nat.add_sub_assoc (card_le_univ s), Nat.add_sub_cancel_left] @[simp] theorem Finset.card_compl_add_card [DecidableEq α] [Fintype α] (s : Finset α) : #sᶜ + #s = Fintype.card α := by rw [Nat.add_comm, card_add_card_compl] theorem Fintype.card_compl_set [Fintype α] (s : Set α) [Fintype s] [Fintype (↥sᶜ : Sort _)] : Fintype.card (↥sᶜ : Sort _) = Fintype.card α - Fintype.card s := by classical rw [← Set.toFinset_card, ← Set.toFinset_card, ← Finset.card_compl, Set.toFinset_compl] theorem Fintype.card_subtype_eq (y : α) [Fintype { x // x = y }] : Fintype.card { x // x = y } = 1 := Fintype.card_unique theorem Fintype.card_subtype_eq' (y : α) [Fintype { x // y = x }] : Fintype.card { x // y = x } = 1 := Fintype.card_unique theorem Fintype.card_empty : Fintype.card Empty = 0 := rfl theorem Fintype.card_pempty : Fintype.card PEmpty = 0 := rfl theorem Fintype.card_unit : Fintype.card Unit = 1 := rfl @[simp] theorem Fintype.card_punit : Fintype.card PUnit = 1 := rfl @[simp] theorem Fintype.card_bool : Fintype.card Bool = 2 := rfl @[simp] theorem Fintype.card_ulift (α : Type*) [Fintype α] : Fintype.card (ULift α) = Fintype.card α := Fintype.ofEquiv_card _ @[simp] theorem Fintype.card_plift (α : Type*) [Fintype α] : Fintype.card (PLift α) = Fintype.card α := Fintype.ofEquiv_card _ @[simp] theorem Fintype.card_orderDual (α : Type*) [Fintype α] : Fintype.card αᵒᵈ = Fintype.card α := rfl @[simp] theorem Fintype.card_lex (α : Type*) [Fintype α] : Fintype.card (Lex α) = Fintype.card α := rfl -- Note: The extra hypothesis `h` is there so that the rewrite lemma applies, -- no matter what instance of `Fintype (Set.univ : Set α)` is used. @[simp] theorem Fintype.card_setUniv [Fintype α] {h : Fintype (Set.univ : Set α)} : Fintype.card (Set.univ : Set α) = Fintype.card α := by apply Fintype.card_of_finset' simp @[simp] theorem Fintype.card_subtype_true [Fintype α] {h : Fintype {_a : α // True}} : @Fintype.card {_a // True} h = Fintype.card α := by apply Fintype.card_of_subtype simp /-- Given that `α ⊕ β` is a fintype, `α` is also a fintype. This is non-computable as it uses that `Sum.inl` is an injection, but there's no clear inverse if `α` is empty. -/ noncomputable def Fintype.sumLeft {α β} [Fintype (α ⊕ β)] : Fintype α := Fintype.ofInjective (Sum.inl : α → α ⊕ β) Sum.inl_injective /-- Given that `α ⊕ β` is a fintype, `β` is also a fintype. This is non-computable as it uses that `Sum.inr` is an injection, but there's no clear inverse if `β` is empty. -/ noncomputable def Fintype.sumRight {α β} [Fintype (α ⊕ β)] : Fintype β := Fintype.ofInjective (Sum.inr : β → α ⊕ β) Sum.inr_injective theorem Finite.exists_univ_list (α) [Finite α] : ∃ l : List α, l.Nodup ∧ ∀ x : α, x ∈ l := by cases nonempty_fintype α obtain ⟨l, e⟩ := Quotient.exists_rep (@univ α _).1 have := And.intro (@univ α _).2 (@mem_univ_val α _) exact ⟨_, by rwa [← e] at this⟩ theorem List.Nodup.length_le_card {α : Type*} [Fintype α] {l : List α} (h : l.Nodup) : l.length ≤ Fintype.card α := by classical exact List.toFinset_card_of_nodup h ▸ l.toFinset.card_le_univ namespace Fintype variable [Fintype α] [Fintype β] theorem card_le_of_injective (f : α → β) (hf : Function.Injective f) : card α ≤ card β := Finset.card_le_card_of_injOn f (fun _ _ => Finset.mem_univ _) fun _ _ _ _ h => hf h theorem card_le_of_embedding (f : α ↪ β) : card α ≤ card β := card_le_of_injective f f.2 theorem card_lt_of_injective_of_not_mem (f : α → β) (h : Function.Injective f) {b : β} (w : b ∉ Set.range f) : card α < card β := calc card α = (univ.map ⟨f, h⟩).card := (card_map _).symm _ < card β := Finset.card_lt_univ_of_not_mem (x := b) <| by rwa [← mem_coe, coe_map, coe_univ, Set.image_univ] theorem card_lt_of_injective_not_surjective (f : α → β) (h : Function.Injective f) (h' : ¬Function.Surjective f) : card α < card β := let ⟨_y, hy⟩ := not_forall.1 h' card_lt_of_injective_of_not_mem f h hy theorem card_le_of_surjective (f : α → β) (h : Function.Surjective f) : card β ≤ card α := card_le_of_injective _ (Function.injective_surjInv h) theorem card_range_le {α β : Type*} (f : α → β) [Fintype α] [Fintype (Set.range f)] : Fintype.card (Set.range f) ≤ Fintype.card α := Fintype.card_le_of_surjective (fun a => ⟨f a, by simp⟩) fun ⟨_, a, ha⟩ => ⟨a, by simpa using ha⟩ theorem card_range {α β F : Type*} [FunLike F α β] [EmbeddingLike F α β] (f : F) [Fintype α] [Fintype (Set.range f)] : Fintype.card (Set.range f) = Fintype.card α := Eq.symm <| Fintype.card_congr <| Equiv.ofInjective _ <| EmbeddingLike.injective f theorem card_eq_zero_iff : card α = 0 ↔ IsEmpty α := by rw [card, Finset.card_eq_zero, univ_eq_empty_iff] @[simp] theorem card_eq_zero [IsEmpty α] : card α = 0 := card_eq_zero_iff.2 ‹_› alias card_of_isEmpty := card_eq_zero /-- A `Fintype` with cardinality zero is equivalent to `Empty`. -/ def cardEqZeroEquivEquivEmpty : card α = 0 ≃ (α ≃ Empty) := (Equiv.ofIff card_eq_zero_iff).trans (Equiv.equivEmptyEquiv α).symm theorem card_pos_iff : 0 < card α ↔ Nonempty α := Nat.pos_iff_ne_zero.trans <| not_iff_comm.mp <| not_nonempty_iff.trans card_eq_zero_iff.symm theorem card_pos [h : Nonempty α] : 0 < card α := card_pos_iff.mpr h @[simp] theorem card_ne_zero [Nonempty α] : card α ≠ 0 := _root_.ne_of_gt card_pos instance [Nonempty α] : NeZero (card α) := ⟨card_ne_zero⟩ theorem existsUnique_iff_card_one {α} [Fintype α] (p : α → Prop) [DecidablePred p] : (∃! a : α, p a) ↔ #{x | p x} = 1 := by rw [Finset.card_eq_one] refine exists_congr fun x => ?_ simp only [forall_true_left, Subset.antisymm_iff, subset_singleton_iff', singleton_subset_iff, true_and, and_comm, mem_univ, mem_filter] @[deprecated (since := "2024-12-17")] alias exists_unique_iff_card_one := existsUnique_iff_card_one nonrec theorem two_lt_card_iff : 2 < card α ↔ ∃ a b c : α, a ≠ b ∧ a ≠ c ∧ b ≠ c := by simp_rw [← Finset.card_univ, two_lt_card_iff, mem_univ, true_and] theorem card_of_bijective {f : α → β} (hf : Bijective f) : card α = card β := card_congr (Equiv.ofBijective f hf) end Fintype namespace Finite variable [Finite α] theorem surjective_of_injective {f : α → α} (hinj : Injective f) : Surjective f := by intro x have := Classical.propDecidable cases nonempty_fintype α have h₁ : image f univ = univ := eq_of_subset_of_card_le (subset_univ _) ((card_image_of_injective univ hinj).symm ▸ le_rfl) have h₂ : x ∈ image f univ := h₁.symm ▸ mem_univ x obtain ⟨y, h⟩ := mem_image.1 h₂ exact ⟨y, h.2⟩ theorem injective_iff_surjective {f : α → α} : Injective f ↔ Surjective f := ⟨surjective_of_injective, fun hsurj => HasLeftInverse.injective ⟨surjInv hsurj, leftInverse_of_surjective_of_rightInverse (surjective_of_injective (injective_surjInv _)) (rightInverse_surjInv _)⟩⟩ theorem injective_iff_bijective {f : α → α} : Injective f ↔ Bijective f := by simp [Bijective, injective_iff_surjective] theorem surjective_iff_bijective {f : α → α} : Surjective f ↔ Bijective f := by simp [Bijective, injective_iff_surjective] theorem injective_iff_surjective_of_equiv {f : α → β} (e : α ≃ β) : Injective f ↔ Surjective f := have : Injective (e.symm ∘ f) ↔ Surjective (e.symm ∘ f) := injective_iff_surjective ⟨fun hinj => by simpa [Function.comp] using e.surjective.comp (this.1 (e.symm.injective.comp hinj)), fun hsurj => by simpa [Function.comp] using e.injective.comp (this.2 (e.symm.surjective.comp hsurj))⟩ alias ⟨_root_.Function.Injective.bijective_of_finite, _⟩ := injective_iff_bijective alias ⟨_root_.Function.Surjective.bijective_of_finite, _⟩ := surjective_iff_bijective alias ⟨_root_.Function.Injective.surjective_of_fintype, _root_.Function.Surjective.injective_of_fintype⟩ := injective_iff_surjective_of_equiv end Finite @[simp] theorem Fintype.card_coe (s : Finset α) [Fintype s] : Fintype.card s = #s := @Fintype.card_of_finset' _ _ _ (fun _ => Iff.rfl) (id _) /-- We can inflate a set `s` to any bigger size. -/ lemma Finset.exists_superset_card_eq [Fintype α] {n : ℕ} {s : Finset α} (hsn : #s ≤ n) (hnα : n ≤ Fintype.card α) : ∃ t, s ⊆ t ∧ #t = n := by simpa using exists_subsuperset_card_eq s.subset_univ hsn hnα @[simp] theorem Fintype.card_prop : Fintype.card Prop = 2 := rfl theorem set_fintype_card_le_univ [Fintype α] (s : Set α) [Fintype s] : Fintype.card s ≤ Fintype.card α := Fintype.card_le_of_embedding (Function.Embedding.subtype s) theorem set_fintype_card_eq_univ_iff [Fintype α] (s : Set α) [Fintype s] : Fintype.card s = Fintype.card α ↔ s = Set.univ := by rw [← Set.toFinset_card, Finset.card_eq_iff_eq_univ, ← Set.toFinset_univ, Set.toFinset_inj] theorem Fintype.card_subtype_le [Fintype α] (p : α → Prop) [Fintype {a // p a}] : Fintype.card { x // p x } ≤ Fintype.card α := Fintype.card_le_of_embedding (Function.Embedding.subtype _) lemma Fintype.card_subtype_lt [Fintype α] {p : α → Prop} [Fintype {a // p a}] {x : α} (hx : ¬p x) : Fintype.card { x // p x } < Fintype.card α := Fintype.card_lt_of_injective_of_not_mem (b := x) (↑) Subtype.coe_injective <| by rwa [Subtype.range_coe_subtype] theorem Fintype.card_subtype [Fintype α] (p : α → Prop) [Fintype {a // p a}] [DecidablePred p] : Fintype.card { x // p x } = #{x | p x} := by refine Fintype.card_of_subtype _ ?_ simp @[simp] theorem Fintype.card_subtype_compl [Fintype α] (p : α → Prop) [Fintype { x // p x }] [Fintype { x // ¬p x }] : Fintype.card { x // ¬p x } = Fintype.card α - Fintype.card { x // p x } := by classical rw [Fintype.card_of_subtype (Set.toFinset { x | p x }ᶜ), Set.toFinset_compl, Finset.card_compl, Fintype.card_of_subtype] <;> · intro simp only [Set.mem_toFinset, Set.mem_compl_iff, Set.mem_setOf] theorem Fintype.card_subtype_mono (p q : α → Prop) (h : p ≤ q) [Fintype { x // p x }] [Fintype { x // q x }] : Fintype.card { x // p x } ≤ Fintype.card { x // q x } := Fintype.card_le_of_embedding (Subtype.impEmbedding _ _ h) /-- If two subtypes of a fintype have equal cardinality, so do their complements. -/ theorem Fintype.card_compl_eq_card_compl [Finite α] (p q : α → Prop) [Fintype { x // p x }] [Fintype { x // ¬p x }] [Fintype { x // q x }] [Fintype { x // ¬q x }] (h : Fintype.card { x // p x } = Fintype.card { x // q x }) : Fintype.card { x // ¬p x } = Fintype.card { x // ¬q x } := by cases nonempty_fintype α simp only [Fintype.card_subtype_compl, h] theorem Fintype.card_quotient_le [Fintype α] (s : Setoid α) [DecidableRel ((· ≈ ·) : α → α → Prop)] : Fintype.card (Quotient s) ≤ Fintype.card α := Fintype.card_le_of_surjective _ Quotient.mk'_surjective theorem univ_eq_singleton_of_card_one {α} [Fintype α] (x : α) (h : Fintype.card α = 1) : (univ : Finset α) = {x} := by symm apply eq_of_subset_of_card_le (subset_univ {x}) apply le_of_eq simp [h, Finset.card_univ] namespace Finite variable [Finite α] theorem wellFounded_of_trans_of_irrefl (r : α → α → Prop) [IsTrans α r] [IsIrrefl α r] : WellFounded r := by classical cases nonempty_fintype α have (x y) (hxy : r x y) : #{z | r z x} < #{z | r z y} := Finset.card_lt_card <| by simp only [Finset.lt_iff_ssubset.symm, lt_iff_le_not_le, Finset.le_iff_subset, Finset.subset_iff, mem_filter, true_and, mem_univ, hxy] exact ⟨fun z hzx => _root_.trans hzx hxy, not_forall_of_exists_not ⟨x, Classical.not_imp.2 ⟨hxy, irrefl x⟩⟩⟩ exact Subrelation.wf (this _ _) (measure _).wf -- See note [lower instance priority] instance (priority := 100) to_wellFoundedLT [Preorder α] : WellFoundedLT α := ⟨wellFounded_of_trans_of_irrefl _⟩ -- See note [lower instance priority] instance (priority := 100) to_wellFoundedGT [Preorder α] : WellFoundedGT α := ⟨wellFounded_of_trans_of_irrefl _⟩ end Finite -- Shortcut instances to make sure those are found even in the presence of other instances -- See https://leanprover.zulipchat.com/#narrow/channel/287929-mathlib4/topic/WellFoundedLT.20Prop.20is.20not.20found.20when.20importing.20too.20much instance Bool.instWellFoundedLT : WellFoundedLT Bool := inferInstance instance Bool.instWellFoundedGT : WellFoundedGT Bool := inferInstance instance Prop.instWellFoundedLT : WellFoundedLT Prop := inferInstance instance Prop.instWellFoundedGT : WellFoundedGT Prop := inferInstance section Trunc /-- A `Fintype` with positive cardinality constructively contains an element. -/ def truncOfCardPos {α} [Fintype α] (h : 0 < Fintype.card α) : Trunc α := letI := Fintype.card_pos_iff.mp h truncOfNonemptyFintype α end Trunc /-- A custom induction principle for fintypes. The base case is a subsingleton type, and the induction step is for non-trivial types, and one can assume the hypothesis for smaller types (via `Fintype.card`). The major premise is `Fintype α`, so to use this with the `induction` tactic you have to give a name to that instance and use that name. -/ @[elab_as_elim] theorem Fintype.induction_subsingleton_or_nontrivial {P : ∀ (α) [Fintype α], Prop} (α : Type*) [Fintype α] (hbase : ∀ (α) [Fintype α] [Subsingleton α], P α) (hstep : ∀ (α) [Fintype α] [Nontrivial α], (∀ (β) [Fintype β], Fintype.card β < Fintype.card α → P β) → P α) : P α := by obtain ⟨n, hn⟩ : ∃ n, Fintype.card α = n := ⟨Fintype.card α, rfl⟩ induction' n using Nat.strong_induction_on with n ih generalizing α rcases subsingleton_or_nontrivial α with hsing | hnontriv · apply hbase · apply hstep intro β _ hlt rw [hn] at hlt exact ih (Fintype.card β) hlt _ rfl section Fin @[simp] theorem Fintype.card_fin (n : ℕ) : Fintype.card (Fin n) = n := List.length_finRange theorem Fintype.card_fin_lt_of_le {m n : ℕ} (h : m ≤ n) : Fintype.card {i : Fin n // i < m} = m := by conv_rhs => rw [← Fintype.card_fin m] apply Fintype.card_congr exact { toFun := fun ⟨⟨i, _⟩, hi⟩ ↦ ⟨i, hi⟩ invFun := fun ⟨i, hi⟩ ↦ ⟨⟨i, lt_of_lt_of_le hi h⟩, hi⟩ left_inv := fun i ↦ rfl right_inv := fun i ↦ rfl } theorem Finset.card_fin (n : ℕ) : #(univ : Finset (Fin n)) = n := by simp /-- `Fin` as a map from `ℕ` to `Type` is injective. Note that since this is a statement about equality of types, using it should be avoided if possible. -/ theorem fin_injective : Function.Injective Fin := fun m n h => (Fintype.card_fin m).symm.trans <| (Fintype.card_congr <| Equiv.cast h).trans (Fintype.card_fin n) theorem Fin.val_eq_val_of_heq {k l : ℕ} {i : Fin k} {j : Fin l} (h : HEq i j) : (i : ℕ) = (j : ℕ) := (Fin.heq_ext_iff (fin_injective (type_eq_of_heq h))).1 h /-- A reversed version of `Fin.cast_eq_cast` that is easier to rewrite with. -/ theorem Fin.cast_eq_cast' {n m : ℕ} (h : Fin n = Fin m) : _root_.cast h = Fin.cast (fin_injective h) := by cases fin_injective h rfl theorem card_finset_fin_le {n : ℕ} (s : Finset (Fin n)) : #s ≤ n := by simpa only [Fintype.card_fin] using s.card_le_univ end Fin
Mathlib/Data/Fintype/Card.lean
877
880
/- Copyright (c) 2019 Calle Sönne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Calle Sönne -/ import Mathlib.Analysis.SpecialFunctions.Trigonometric.Basic import Mathlib.Analysis.Normed.Group.AddCircle import Mathlib.Algebra.CharZero.Quotient import Mathlib.Topology.Instances.Sign /-! # The type of angles In this file we define `Real.Angle` to be the quotient group `ℝ/2πℤ` and prove a few simple lemmas about trigonometric functions and angles. -/ open Real noncomputable section namespace Real /-- The type of angles -/ def Angle : Type := AddCircle (2 * π) -- The `NormedAddCommGroup, Inhabited` instances should be constructed by a deriving handler. -- https://github.com/leanprover-community/mathlib4/issues/380 namespace Angle instance : NormedAddCommGroup Angle := inferInstanceAs (NormedAddCommGroup (AddCircle (2 * π))) instance : Inhabited Angle := inferInstanceAs (Inhabited (AddCircle (2 * π))) /-- The canonical map from `ℝ` to the quotient `Angle`. -/ @[coe] protected def coe (r : ℝ) : Angle := QuotientAddGroup.mk r instance : Coe ℝ Angle := ⟨Angle.coe⟩ instance : CircularOrder Real.Angle := QuotientAddGroup.circularOrder (hp' := ⟨by norm_num [pi_pos]⟩) @[continuity] theorem continuous_coe : Continuous ((↑) : ℝ → Angle) := continuous_quotient_mk' /-- Coercion `ℝ → Angle` as an additive homomorphism. -/ def coeHom : ℝ →+ Angle := QuotientAddGroup.mk' _ @[simp] theorem coe_coeHom : (coeHom : ℝ → Angle) = ((↑) : ℝ → Angle) := rfl /-- An induction principle to deduce results for `Angle` from those for `ℝ`, used with `induction θ using Real.Angle.induction_on`. -/ @[elab_as_elim] protected theorem induction_on {p : Angle → Prop} (θ : Angle) (h : ∀ x : ℝ, p x) : p θ := Quotient.inductionOn' θ h @[simp] theorem coe_zero : ↑(0 : ℝ) = (0 : Angle) := rfl @[simp] theorem coe_add (x y : ℝ) : ↑(x + y : ℝ) = (↑x + ↑y : Angle) := rfl @[simp] theorem coe_neg (x : ℝ) : ↑(-x : ℝ) = -(↑x : Angle) := rfl @[simp] theorem coe_sub (x y : ℝ) : ↑(x - y : ℝ) = (↑x - ↑y : Angle) := rfl theorem coe_nsmul (n : ℕ) (x : ℝ) : ↑(n • x : ℝ) = n • (↑x : Angle) := rfl theorem coe_zsmul (z : ℤ) (x : ℝ) : ↑(z • x : ℝ) = z • (↑x : Angle) := rfl theorem coe_eq_zero_iff {x : ℝ} : (x : Angle) = 0 ↔ ∃ n : ℤ, n • (2 * π) = x := AddCircle.coe_eq_zero_iff (2 * π) @[simp, norm_cast] theorem natCast_mul_eq_nsmul (x : ℝ) (n : ℕ) : ↑((n : ℝ) * x) = n • (↑x : Angle) := by simpa only [nsmul_eq_mul] using coeHom.map_nsmul x n @[simp, norm_cast] theorem intCast_mul_eq_zsmul (x : ℝ) (n : ℤ) : ↑((n : ℝ) * x : ℝ) = n • (↑x : Angle) := by simpa only [zsmul_eq_mul] using coeHom.map_zsmul x n theorem angle_eq_iff_two_pi_dvd_sub {ψ θ : ℝ} : (θ : Angle) = ψ ↔ ∃ k : ℤ, θ - ψ = 2 * π * k := by simp only [QuotientAddGroup.eq, AddSubgroup.zmultiples_eq_closure, AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm] rw [Angle.coe, Angle.coe, QuotientAddGroup.eq] simp only [AddSubgroup.zmultiples_eq_closure, AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm] @[simp] theorem coe_two_pi : ↑(2 * π : ℝ) = (0 : Angle) := angle_eq_iff_two_pi_dvd_sub.2 ⟨1, by rw [sub_zero, Int.cast_one, mul_one]⟩ @[simp] theorem neg_coe_pi : -(π : Angle) = π := by rw [← coe_neg, angle_eq_iff_two_pi_dvd_sub] use -1 simp [two_mul, sub_eq_add_neg] @[simp] theorem two_nsmul_coe_div_two (θ : ℝ) : (2 : ℕ) • (↑(θ / 2) : Angle) = θ := by rw [← coe_nsmul, two_nsmul, add_halves] @[simp] theorem two_zsmul_coe_div_two (θ : ℝ) : (2 : ℤ) • (↑(θ / 2) : Angle) = θ := by rw [← coe_zsmul, two_zsmul, add_halves] theorem two_nsmul_neg_pi_div_two : (2 : ℕ) • (↑(-π / 2) : Angle) = π := by rw [two_nsmul_coe_div_two, coe_neg, neg_coe_pi] theorem two_zsmul_neg_pi_div_two : (2 : ℤ) • (↑(-π / 2) : Angle) = π := by rw [two_zsmul, ← two_nsmul, two_nsmul_neg_pi_div_two] theorem sub_coe_pi_eq_add_coe_pi (θ : Angle) : θ - π = θ + π := by rw [sub_eq_add_neg, neg_coe_pi] @[simp] theorem two_nsmul_coe_pi : (2 : ℕ) • (π : Angle) = 0 := by simp [← natCast_mul_eq_nsmul] @[simp] theorem two_zsmul_coe_pi : (2 : ℤ) • (π : Angle) = 0 := by simp [← intCast_mul_eq_zsmul] @[simp] theorem coe_pi_add_coe_pi : (π : Real.Angle) + π = 0 := by rw [← two_nsmul, two_nsmul_coe_pi] theorem zsmul_eq_iff {ψ θ : Angle} {z : ℤ} (hz : z ≠ 0) : z • ψ = z • θ ↔ ∃ k : Fin z.natAbs, ψ = θ + (k : ℕ) • (2 * π / z : ℝ) := QuotientAddGroup.zmultiples_zsmul_eq_zsmul_iff hz theorem nsmul_eq_iff {ψ θ : Angle} {n : ℕ} (hz : n ≠ 0) : n • ψ = n • θ ↔ ∃ k : Fin n, ψ = θ + (k : ℕ) • (2 * π / n : ℝ) := QuotientAddGroup.zmultiples_nsmul_eq_nsmul_iff hz theorem two_zsmul_eq_iff {ψ θ : Angle} : (2 : ℤ) • ψ = (2 : ℤ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by have : Int.natAbs 2 = 2 := rfl rw [zsmul_eq_iff two_ne_zero, this, Fin.exists_fin_two, Fin.val_zero, Fin.val_one, zero_smul, add_zero, one_smul, Int.cast_two, mul_div_cancel_left₀ (_ : ℝ) two_ne_zero] theorem two_nsmul_eq_iff {ψ θ : Angle} : (2 : ℕ) • ψ = (2 : ℕ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by simp_rw [← natCast_zsmul, Nat.cast_ofNat, two_zsmul_eq_iff] theorem two_nsmul_eq_zero_iff {θ : Angle} : (2 : ℕ) • θ = 0 ↔ θ = 0 ∨ θ = π := by convert two_nsmul_eq_iff <;> simp theorem two_nsmul_ne_zero_iff {θ : Angle} : (2 : ℕ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← two_nsmul_eq_zero_iff] theorem two_zsmul_eq_zero_iff {θ : Angle} : (2 : ℤ) • θ = 0 ↔ θ = 0 ∨ θ = π := by simp_rw [two_zsmul, ← two_nsmul, two_nsmul_eq_zero_iff] theorem two_zsmul_ne_zero_iff {θ : Angle} : (2 : ℤ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← two_zsmul_eq_zero_iff] theorem eq_neg_self_iff {θ : Angle} : θ = -θ ↔ θ = 0 ∨ θ = π := by rw [← add_eq_zero_iff_eq_neg, ← two_nsmul, two_nsmul_eq_zero_iff] theorem ne_neg_self_iff {θ : Angle} : θ ≠ -θ ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← eq_neg_self_iff.not] theorem neg_eq_self_iff {θ : Angle} : -θ = θ ↔ θ = 0 ∨ θ = π := by rw [eq_comm, eq_neg_self_iff] theorem neg_ne_self_iff {θ : Angle} : -θ ≠ θ ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← neg_eq_self_iff.not] theorem two_nsmul_eq_pi_iff {θ : Angle} : (2 : ℕ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by have h : (π : Angle) = ((2 : ℕ) • (π / 2 : ℝ):) := by rw [two_nsmul, add_halves] nth_rw 1 [h] rw [coe_nsmul, two_nsmul_eq_iff] -- Porting note: `congr` didn't simplify the goal of iff of `Or`s convert Iff.rfl rw [add_comm, ← coe_add, ← sub_eq_zero, ← coe_sub, neg_div, ← neg_sub, sub_neg_eq_add, add_assoc, add_halves, ← two_mul, coe_neg, coe_two_pi, neg_zero] theorem two_zsmul_eq_pi_iff {θ : Angle} : (2 : ℤ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [two_zsmul, ← two_nsmul, two_nsmul_eq_pi_iff] theorem cos_eq_iff_coe_eq_or_eq_neg {θ ψ : ℝ} : cos θ = cos ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) = -ψ := by constructor · intro Hcos rw [← sub_eq_zero, cos_sub_cos, mul_eq_zero, mul_eq_zero, neg_eq_zero, eq_false (two_ne_zero' ℝ), false_or, sin_eq_zero_iff, sin_eq_zero_iff] at Hcos rcases Hcos with (⟨n, hn⟩ | ⟨n, hn⟩) · right rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), ← sub_eq_iff_eq_add] at hn rw [← hn, coe_sub, eq_neg_iff_add_eq_zero, sub_add_cancel, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero] · left rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), eq_sub_iff_add_eq] at hn rw [← hn, coe_add, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero, zero_add] · rw [angle_eq_iff_two_pi_dvd_sub, ← coe_neg, angle_eq_iff_two_pi_dvd_sub] rintro (⟨k, H⟩ | ⟨k, H⟩) · rw [← sub_eq_zero, cos_sub_cos, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero] rw [← sub_eq_zero, cos_sub_cos, ← sub_neg_eq_add, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul] theorem sin_eq_iff_coe_eq_or_add_eq_pi {θ ψ : ℝ} : sin θ = sin ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) + ψ = π := by constructor · intro Hsin rw [← cos_pi_div_two_sub, ← cos_pi_div_two_sub] at Hsin rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hsin with h | h · left rw [coe_sub, coe_sub] at h exact sub_right_inj.1 h right rw [coe_sub, coe_sub, eq_neg_iff_add_eq_zero, add_sub, sub_add_eq_add_sub, ← coe_add, add_halves, sub_sub, sub_eq_zero] at h exact h.symm · rw [angle_eq_iff_two_pi_dvd_sub, ← eq_sub_iff_add_eq, ← coe_sub, angle_eq_iff_two_pi_dvd_sub] rintro (⟨k, H⟩ | ⟨k, H⟩) · rw [← sub_eq_zero, sin_sub_sin, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul] have H' : θ + ψ = 2 * k * π + π := by rwa [← sub_add, sub_add_eq_add_sub, sub_eq_iff_eq_add, mul_assoc, mul_comm π _, ← mul_assoc] at H rw [← sub_eq_zero, sin_sub_sin, H', add_div, mul_assoc 2 _ π, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), cos_add_pi_div_two, sin_int_mul_pi, neg_zero, mul_zero] theorem cos_sin_inj {θ ψ : ℝ} (Hcos : cos θ = cos ψ) (Hsin : sin θ = sin ψ) : (θ : Angle) = ψ := by rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hcos with hc | hc; · exact hc rcases sin_eq_iff_coe_eq_or_add_eq_pi.mp Hsin with hs | hs; · exact hs rw [eq_neg_iff_add_eq_zero, hs] at hc obtain ⟨n, hn⟩ : ∃ n, n • _ = _ := QuotientAddGroup.leftRel_apply.mp (Quotient.exact' hc) rw [← neg_one_mul, add_zero, ← sub_eq_zero, zsmul_eq_mul, ← mul_assoc, ← sub_mul, mul_eq_zero, eq_false (ne_of_gt pi_pos), or_false, sub_neg_eq_add, ← Int.cast_zero, ← Int.cast_one, ← Int.cast_ofNat, ← Int.cast_mul, ← Int.cast_add, Int.cast_inj] at hn have : (n * 2 + 1) % (2 : ℤ) = 0 % (2 : ℤ) := congr_arg (· % (2 : ℤ)) hn rw [add_comm, Int.add_mul_emod_self_right] at this exact absurd this one_ne_zero /-- The sine of a `Real.Angle`. -/ def sin (θ : Angle) : ℝ := sin_periodic.lift θ @[simp] theorem sin_coe (x : ℝ) : sin (x : Angle) = Real.sin x := rfl @[continuity] theorem continuous_sin : Continuous sin := Real.continuous_sin.quotient_liftOn' _ /-- The cosine of a `Real.Angle`. -/ def cos (θ : Angle) : ℝ := cos_periodic.lift θ @[simp] theorem cos_coe (x : ℝ) : cos (x : Angle) = Real.cos x := rfl @[continuity] theorem continuous_cos : Continuous cos := Real.continuous_cos.quotient_liftOn' _ theorem cos_eq_real_cos_iff_eq_or_eq_neg {θ : Angle} {ψ : ℝ} : cos θ = Real.cos ψ ↔ θ = ψ ∨ θ = -ψ := by induction θ using Real.Angle.induction_on exact cos_eq_iff_coe_eq_or_eq_neg theorem cos_eq_iff_eq_or_eq_neg {θ ψ : Angle} : cos θ = cos ψ ↔ θ = ψ ∨ θ = -ψ := by induction ψ using Real.Angle.induction_on exact cos_eq_real_cos_iff_eq_or_eq_neg theorem sin_eq_real_sin_iff_eq_or_add_eq_pi {θ : Angle} {ψ : ℝ} : sin θ = Real.sin ψ ↔ θ = ψ ∨ θ + ψ = π := by induction θ using Real.Angle.induction_on exact sin_eq_iff_coe_eq_or_add_eq_pi theorem sin_eq_iff_eq_or_add_eq_pi {θ ψ : Angle} : sin θ = sin ψ ↔ θ = ψ ∨ θ + ψ = π := by induction ψ using Real.Angle.induction_on exact sin_eq_real_sin_iff_eq_or_add_eq_pi @[simp] theorem sin_zero : sin (0 : Angle) = 0 := by rw [← coe_zero, sin_coe, Real.sin_zero] theorem sin_coe_pi : sin (π : Angle) = 0 := by rw [sin_coe, Real.sin_pi] theorem sin_eq_zero_iff {θ : Angle} : sin θ = 0 ↔ θ = 0 ∨ θ = π := by nth_rw 1 [← sin_zero] rw [sin_eq_iff_eq_or_add_eq_pi] simp theorem sin_ne_zero_iff {θ : Angle} : sin θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← sin_eq_zero_iff] @[simp] theorem sin_neg (θ : Angle) : sin (-θ) = -sin θ := by induction θ using Real.Angle.induction_on exact Real.sin_neg _ theorem sin_antiperiodic : Function.Antiperiodic sin (π : Angle) := by intro θ induction θ using Real.Angle.induction_on exact Real.sin_antiperiodic _ @[simp] theorem sin_add_pi (θ : Angle) : sin (θ + π) = -sin θ := sin_antiperiodic θ @[simp] theorem sin_sub_pi (θ : Angle) : sin (θ - π) = -sin θ := sin_antiperiodic.sub_eq θ @[simp] theorem cos_zero : cos (0 : Angle) = 1 := by rw [← coe_zero, cos_coe, Real.cos_zero] theorem cos_coe_pi : cos (π : Angle) = -1 := by rw [cos_coe, Real.cos_pi] @[simp] theorem cos_neg (θ : Angle) : cos (-θ) = cos θ := by induction θ using Real.Angle.induction_on exact Real.cos_neg _ theorem cos_antiperiodic : Function.Antiperiodic cos (π : Angle) := by intro θ induction θ using Real.Angle.induction_on exact Real.cos_antiperiodic _ @[simp] theorem cos_add_pi (θ : Angle) : cos (θ + π) = -cos θ := cos_antiperiodic θ @[simp] theorem cos_sub_pi (θ : Angle) : cos (θ - π) = -cos θ := cos_antiperiodic.sub_eq θ theorem cos_eq_zero_iff {θ : Angle} : cos θ = 0 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [← cos_pi_div_two, ← cos_coe, cos_eq_iff_eq_or_eq_neg, ← coe_neg, ← neg_div] theorem sin_add (θ₁ θ₂ : Real.Angle) : sin (θ₁ + θ₂) = sin θ₁ * cos θ₂ + cos θ₁ * sin θ₂ := by induction θ₁ using Real.Angle.induction_on induction θ₂ using Real.Angle.induction_on exact Real.sin_add _ _ theorem cos_add (θ₁ θ₂ : Real.Angle) : cos (θ₁ + θ₂) = cos θ₁ * cos θ₂ - sin θ₁ * sin θ₂ := by induction θ₂ using Real.Angle.induction_on induction θ₁ using Real.Angle.induction_on exact Real.cos_add _ _ @[simp] theorem cos_sq_add_sin_sq (θ : Real.Angle) : cos θ ^ 2 + sin θ ^ 2 = 1 := by induction θ using Real.Angle.induction_on exact Real.cos_sq_add_sin_sq _ theorem sin_add_pi_div_two (θ : Angle) : sin (θ + ↑(π / 2)) = cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_add_pi_div_two _ theorem sin_sub_pi_div_two (θ : Angle) : sin (θ - ↑(π / 2)) = -cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_sub_pi_div_two _ theorem sin_pi_div_two_sub (θ : Angle) : sin (↑(π / 2) - θ) = cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_pi_div_two_sub _ theorem cos_add_pi_div_two (θ : Angle) : cos (θ + ↑(π / 2)) = -sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_add_pi_div_two _ theorem cos_sub_pi_div_two (θ : Angle) : cos (θ - ↑(π / 2)) = sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_sub_pi_div_two _ theorem cos_pi_div_two_sub (θ : Angle) : cos (↑(π / 2) - θ) = sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_pi_div_two_sub _ theorem abs_sin_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : |sin θ| = |sin ψ| := by rw [two_nsmul_eq_iff] at h rcases h with (rfl | rfl) · rfl · rw [sin_add_pi, abs_neg] theorem abs_sin_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : |sin θ| = |sin ψ| := by simp_rw [two_zsmul, ← two_nsmul] at h exact abs_sin_eq_of_two_nsmul_eq h theorem abs_cos_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : |cos θ| = |cos ψ| := by rw [two_nsmul_eq_iff] at h rcases h with (rfl | rfl) · rfl · rw [cos_add_pi, abs_neg] theorem abs_cos_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : |cos θ| = |cos ψ| := by simp_rw [two_zsmul, ← two_nsmul] at h exact abs_cos_eq_of_two_nsmul_eq h @[simp] theorem coe_toIcoMod (θ ψ : ℝ) : ↑(toIcoMod two_pi_pos ψ θ) = (θ : Angle) := by rw [angle_eq_iff_two_pi_dvd_sub] refine ⟨-toIcoDiv two_pi_pos ψ θ, ?_⟩ rw [toIcoMod_sub_self, zsmul_eq_mul, mul_comm] @[simp] theorem coe_toIocMod (θ ψ : ℝ) : ↑(toIocMod two_pi_pos ψ θ) = (θ : Angle) := by rw [angle_eq_iff_two_pi_dvd_sub] refine ⟨-toIocDiv two_pi_pos ψ θ, ?_⟩ rw [toIocMod_sub_self, zsmul_eq_mul, mul_comm] /-- Convert a `Real.Angle` to a real number in the interval `Ioc (-π) π`. -/ def toReal (θ : Angle) : ℝ := (toIocMod_periodic two_pi_pos (-π)).lift θ theorem toReal_coe (θ : ℝ) : (θ : Angle).toReal = toIocMod two_pi_pos (-π) θ := rfl theorem toReal_coe_eq_self_iff {θ : ℝ} : (θ : Angle).toReal = θ ↔ -π < θ ∧ θ ≤ π := by rw [toReal_coe, toIocMod_eq_self two_pi_pos] ring_nf rfl theorem toReal_coe_eq_self_iff_mem_Ioc {θ : ℝ} : (θ : Angle).toReal = θ ↔ θ ∈ Set.Ioc (-π) π := by rw [toReal_coe_eq_self_iff, ← Set.mem_Ioc] theorem toReal_injective : Function.Injective toReal := by intro θ ψ h induction θ using Real.Angle.induction_on induction ψ using Real.Angle.induction_on simpa [toReal_coe, toIocMod_eq_toIocMod, zsmul_eq_mul, mul_comm _ (2 * π), ← angle_eq_iff_two_pi_dvd_sub, eq_comm] using h @[simp] theorem toReal_inj {θ ψ : Angle} : θ.toReal = ψ.toReal ↔ θ = ψ := toReal_injective.eq_iff @[simp] theorem coe_toReal (θ : Angle) : (θ.toReal : Angle) = θ := by induction θ using Real.Angle.induction_on exact coe_toIocMod _ _ theorem neg_pi_lt_toReal (θ : Angle) : -π < θ.toReal := by induction θ using Real.Angle.induction_on exact left_lt_toIocMod _ _ _ theorem toReal_le_pi (θ : Angle) : θ.toReal ≤ π := by induction θ using Real.Angle.induction_on convert toIocMod_le_right two_pi_pos _ _ ring theorem abs_toReal_le_pi (θ : Angle) : |θ.toReal| ≤ π := abs_le.2 ⟨(neg_pi_lt_toReal _).le, toReal_le_pi _⟩ theorem toReal_mem_Ioc (θ : Angle) : θ.toReal ∈ Set.Ioc (-π) π := ⟨neg_pi_lt_toReal _, toReal_le_pi _⟩ @[simp] theorem toIocMod_toReal (θ : Angle) : toIocMod two_pi_pos (-π) θ.toReal = θ.toReal := by induction θ using Real.Angle.induction_on rw [toReal_coe] exact toIocMod_toIocMod _ _ _ _ @[simp] theorem toReal_zero : (0 : Angle).toReal = 0 := by rw [← coe_zero, toReal_coe_eq_self_iff] exact ⟨Left.neg_neg_iff.2 Real.pi_pos, Real.pi_pos.le⟩ @[simp] theorem toReal_eq_zero_iff {θ : Angle} : θ.toReal = 0 ↔ θ = 0 := by nth_rw 1 [← toReal_zero] exact toReal_inj @[simp] theorem toReal_pi : (π : Angle).toReal = π := by rw [toReal_coe_eq_self_iff] exact ⟨Left.neg_lt_self Real.pi_pos, le_refl _⟩ @[simp] theorem toReal_eq_pi_iff {θ : Angle} : θ.toReal = π ↔ θ = π := by rw [← toReal_inj, toReal_pi] theorem pi_ne_zero : (π : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_pi, toReal_zero] exact Real.pi_ne_zero @[simp] theorem toReal_pi_div_two : ((π / 2 : ℝ) : Angle).toReal = π / 2 := toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos] @[simp] theorem toReal_eq_pi_div_two_iff {θ : Angle} : θ.toReal = π / 2 ↔ θ = (π / 2 : ℝ) := by rw [← toReal_inj, toReal_pi_div_two] @[simp] theorem toReal_neg_pi_div_two : ((-π / 2 : ℝ) : Angle).toReal = -π / 2 := toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos] @[simp] theorem toReal_eq_neg_pi_div_two_iff {θ : Angle} : θ.toReal = -π / 2 ↔ θ = (-π / 2 : ℝ) := by rw [← toReal_inj, toReal_neg_pi_div_two] theorem pi_div_two_ne_zero : ((π / 2 : ℝ) : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_pi_div_two, toReal_zero] exact div_ne_zero Real.pi_ne_zero two_ne_zero theorem neg_pi_div_two_ne_zero : ((-π / 2 : ℝ) : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_neg_pi_div_two, toReal_zero] exact div_ne_zero (neg_ne_zero.2 Real.pi_ne_zero) two_ne_zero theorem abs_toReal_coe_eq_self_iff {θ : ℝ} : |(θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π := ⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h => (toReal_coe_eq_self_iff.2 ⟨(Left.neg_neg_iff.2 Real.pi_pos).trans_le h.1, h.2⟩).symm ▸ abs_eq_self.2 h.1⟩ theorem abs_toReal_neg_coe_eq_self_iff {θ : ℝ} : |(-θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π := by refine ⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h => ?_⟩ by_cases hnegpi : θ = π; · simp [hnegpi, Real.pi_pos.le] rw [← coe_neg, toReal_coe_eq_self_iff.2 ⟨neg_lt_neg (lt_of_le_of_ne h.2 hnegpi), (neg_nonpos.2 h.1).trans Real.pi_pos.le⟩, abs_neg, abs_eq_self.2 h.1] theorem abs_toReal_eq_pi_div_two_iff {θ : Angle} :
|θ.toReal| = π / 2 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [abs_eq (div_nonneg Real.pi_pos.le two_pos.le), ← neg_div, toReal_eq_pi_div_two_iff, toReal_eq_neg_pi_div_two_iff] theorem nsmul_toReal_eq_mul {n : ℕ} (h : n ≠ 0) {θ : Angle} : (n • θ).toReal = n * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / n) (π / n) := by
Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean
540
545
/- Copyright (c) 2020 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov -/ import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap import Mathlib.MeasureTheory.Integral.Bochner.FundThmCalculus import Mathlib.MeasureTheory.Integral.Bochner.Set deprecated_module (since := "2025-04-15")
Mathlib/MeasureTheory/Integral/SetIntegral.lean
621
625
/- Copyright (c) 2020 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Wrenna Robson -/ import Mathlib.Algebra.BigOperators.Group.Finset.Pi import Mathlib.Algebra.Polynomial.FieldDivision import Mathlib.LinearAlgebra.Vandermonde import Mathlib.RingTheory.Polynomial.Basic /-! # Lagrange interpolation ## Main definitions * In everything that follows, `s : Finset ι` is a finite set of indexes, with `v : ι → F` an indexing of the field over some type. We call the image of v on s the interpolation nodes, though strictly unique nodes are only defined when v is injective on s. * `Lagrange.basisDivisor x y`, with `x y : F`. These are the normalised irreducible factors of the Lagrange basis polynomials. They evaluate to `1` at `x` and `0` at `y` when `x` and `y` are distinct. * `Lagrange.basis v i` with `i : ι`: the Lagrange basis polynomial that evaluates to `1` at `v i` and `0` at `v j` for `i ≠ j`. * `Lagrange.interpolate v r` where `r : ι → F` is a function from the fintype to the field: the Lagrange interpolant that evaluates to `r i` at `x i` for all `i : ι`. The `r i` are the _values_ associated with the _nodes_`x i`. -/ open Polynomial section PolynomialDetermination namespace Polynomial variable {R : Type*} [CommRing R] [IsDomain R] {f g : R[X]} section Finset open Function Fintype open scoped Finset variable (s : Finset R) theorem eq_zero_of_degree_lt_of_eval_finset_eq_zero (degree_f_lt : f.degree < #s) (eval_f : ∀ x ∈ s, f.eval x = 0) : f = 0 := by rw [← mem_degreeLT] at degree_f_lt simp_rw [eval_eq_sum_degreeLTEquiv degree_f_lt] at eval_f rw [← degreeLTEquiv_eq_zero_iff_eq_zero degree_f_lt] exact Matrix.eq_zero_of_forall_index_sum_mul_pow_eq_zero (Injective.comp (Embedding.subtype _).inj' (equivFinOfCardEq (card_coe _)).symm.injective) fun _ => eval_f _ (Finset.coe_mem _) theorem eq_of_degree_sub_lt_of_eval_finset_eq (degree_fg_lt : (f - g).degree < #s) (eval_fg : ∀ x ∈ s, f.eval x = g.eval x) : f = g := by rw [← sub_eq_zero] refine eq_zero_of_degree_lt_of_eval_finset_eq_zero _ degree_fg_lt ?_ simp_rw [eval_sub, sub_eq_zero] exact eval_fg theorem eq_of_degrees_lt_of_eval_finset_eq (degree_f_lt : f.degree < #s) (degree_g_lt : g.degree < #s) (eval_fg : ∀ x ∈ s, f.eval x = g.eval x) : f = g := by rw [← mem_degreeLT] at degree_f_lt degree_g_lt refine eq_of_degree_sub_lt_of_eval_finset_eq _ ?_ eval_fg rw [← mem_degreeLT]; exact Submodule.sub_mem _ degree_f_lt degree_g_lt /-- Two polynomials, with the same degree and leading coefficient, which have the same evaluation on a set of distinct values with cardinality equal to the degree, are equal. -/ theorem eq_of_degree_le_of_eval_finset_eq (h_deg_le : f.degree ≤ #s) (h_deg_eq : f.degree = g.degree) (hlc : f.leadingCoeff = g.leadingCoeff) (h_eval : ∀ x ∈ s, f.eval x = g.eval x) : f = g := by rcases eq_or_ne f 0 with rfl | hf · rwa [degree_zero, eq_comm, degree_eq_bot, eq_comm] at h_deg_eq · exact eq_of_degree_sub_lt_of_eval_finset_eq s (lt_of_lt_of_le (degree_sub_lt h_deg_eq hf hlc) h_deg_le) h_eval end Finset section Indexed open Finset variable {ι : Type*} {v : ι → R} (s : Finset ι) theorem eq_zero_of_degree_lt_of_eval_index_eq_zero (hvs : Set.InjOn v s) (degree_f_lt : f.degree < #s) (eval_f : ∀ i ∈ s, f.eval (v i) = 0) : f = 0 := by classical rw [← card_image_of_injOn hvs] at degree_f_lt refine eq_zero_of_degree_lt_of_eval_finset_eq_zero _ degree_f_lt ?_ intro x hx rcases mem_image.mp hx with ⟨_, hj, rfl⟩ exact eval_f _ hj theorem eq_of_degree_sub_lt_of_eval_index_eq (hvs : Set.InjOn v s) (degree_fg_lt : (f - g).degree < #s) (eval_fg : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) : f = g := by rw [← sub_eq_zero] refine eq_zero_of_degree_lt_of_eval_index_eq_zero _ hvs degree_fg_lt ?_ simp_rw [eval_sub, sub_eq_zero] exact eval_fg theorem eq_of_degrees_lt_of_eval_index_eq (hvs : Set.InjOn v s) (degree_f_lt : f.degree < #s) (degree_g_lt : g.degree < #s) (eval_fg : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) : f = g := by refine eq_of_degree_sub_lt_of_eval_index_eq _ hvs ?_ eval_fg rw [← mem_degreeLT] at degree_f_lt degree_g_lt ⊢ exact Submodule.sub_mem _ degree_f_lt degree_g_lt theorem eq_of_degree_le_of_eval_index_eq (hvs : Set.InjOn v s) (h_deg_le : f.degree ≤ #s) (h_deg_eq : f.degree = g.degree) (hlc : f.leadingCoeff = g.leadingCoeff) (h_eval : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) : f = g := by rcases eq_or_ne f 0 with rfl | hf · rwa [degree_zero, eq_comm, degree_eq_bot, eq_comm] at h_deg_eq · exact eq_of_degree_sub_lt_of_eval_index_eq s hvs (lt_of_lt_of_le (degree_sub_lt h_deg_eq hf hlc) h_deg_le) h_eval end Indexed end Polynomial end PolynomialDetermination noncomputable section namespace Lagrange open Polynomial section BasisDivisor variable {F : Type*} [Field F] variable {x y : F} /-- `basisDivisor x y` is the unique linear or constant polynomial such that when evaluated at `x` it gives `1` and `y` it gives `0` (where when `x = y` it is identically `0`). Such polynomials are the building blocks for the Lagrange interpolants. -/ def basisDivisor (x y : F) : F[X] := C (x - y)⁻¹ * (X - C y) theorem basisDivisor_self : basisDivisor x x = 0 := by simp only [basisDivisor, sub_self, inv_zero, map_zero, zero_mul] theorem basisDivisor_inj (hxy : basisDivisor x y = 0) : x = y := by simp_rw [basisDivisor, mul_eq_zero, X_sub_C_ne_zero, or_false, C_eq_zero, inv_eq_zero, sub_eq_zero] at hxy exact hxy @[simp] theorem basisDivisor_eq_zero_iff : basisDivisor x y = 0 ↔ x = y := ⟨basisDivisor_inj, fun H => H ▸ basisDivisor_self⟩ theorem basisDivisor_ne_zero_iff : basisDivisor x y ≠ 0 ↔ x ≠ y := by rw [Ne, basisDivisor_eq_zero_iff] theorem degree_basisDivisor_of_ne (hxy : x ≠ y) : (basisDivisor x y).degree = 1 := by rw [basisDivisor, degree_mul, degree_X_sub_C, degree_C, zero_add] exact inv_ne_zero (sub_ne_zero_of_ne hxy) @[simp] theorem degree_basisDivisor_self : (basisDivisor x x).degree = ⊥ := by rw [basisDivisor_self, degree_zero] theorem natDegree_basisDivisor_self : (basisDivisor x x).natDegree = 0 := by rw [basisDivisor_self, natDegree_zero] theorem natDegree_basisDivisor_of_ne (hxy : x ≠ y) : (basisDivisor x y).natDegree = 1 := natDegree_eq_of_degree_eq_some (degree_basisDivisor_of_ne hxy) @[simp] theorem eval_basisDivisor_right : eval y (basisDivisor x y) = 0 := by simp only [basisDivisor, eval_mul, eval_C, eval_sub, eval_X, sub_self, mul_zero] theorem eval_basisDivisor_left_of_ne (hxy : x ≠ y) : eval x (basisDivisor x y) = 1 := by simp only [basisDivisor, eval_mul, eval_C, eval_sub, eval_X] exact inv_mul_cancel₀ (sub_ne_zero_of_ne hxy) end BasisDivisor section Basis variable {F : Type*} [Field F] {ι : Type*} [DecidableEq ι] variable {s : Finset ι} {v : ι → F} {i j : ι} open Finset /-- Lagrange basis polynomials indexed by `s : Finset ι`, defined at nodes `v i` for a map `v : ι → F`. For `i, j ∈ s`, `basis s v i` evaluates to 0 at `v j` for `i ≠ j`. When `v` is injective on `s`, `basis s v i` evaluates to 1 at `v i`. -/
protected def basis (s : Finset ι) (v : ι → F) (i : ι) : F[X] := ∏ j ∈ s.erase i, basisDivisor (v i) (v j)
Mathlib/LinearAlgebra/Lagrange.lean
195
197
/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Data.Bundle import Mathlib.Data.Set.Image import Mathlib.Topology.CompactOpen import Mathlib.Topology.PartialHomeomorph import Mathlib.Topology.Order.Basic /-! # Trivializations ## Main definitions ### Basic definitions * `Trivialization F p` : structure extending partial homeomorphisms, defining a local trivialization of a topological space `Z` with projection `p` and fiber `F`. * `Pretrivialization F proj` : trivialization as a partial equivalence, mainly used when the topology on the total space has not yet been defined. ### Operations on bundles We provide the following operations on `Trivialization`s. * `Trivialization.compHomeomorph`: given a local trivialization `e` of a fiber bundle `p : Z → B` and a homeomorphism `h : Z' ≃ₜ Z`, returns a local trivialization of the fiber bundle `p ∘ h`. ## Implementation notes Previously, in mathlib, there was a structure `topological_vector_bundle.trivialization` which extended another structure `topological_fiber_bundle.trivialization` by a linearity hypothesis. As of PR https://github.com/leanprover-community/mathlib3/pull/17359, we have changed this to a single structure `Trivialization` (no namespace), together with a mixin class `Trivialization.IsLinear`. This permits all the *data* of a vector bundle to be held at the level of fiber bundles, so that the same trivializations can underlie an object's structure as (say) a vector bundle over `ℂ` and as a vector bundle over `ℝ`, as well as its structure simply as a fiber bundle. This might be a little surprising, given the general trend of the library to ever-increased bundling. But in this case the typical motivation for more bundling does not apply: there is no algebraic or order structure on the whole type of linear (say) trivializations of a bundle. Indeed, since trivializations only have meaning on their base sets (taking junk values outside), the type of linear trivializations is not even particularly well-behaved. -/ open TopologicalSpace Filter Set Bundle Function open scoped Topology variable {B : Type*} (F : Type*) {E : B → Type*} variable {Z : Type*} [TopologicalSpace B] [TopologicalSpace F] {proj : Z → B} /-- This structure contains the information left for a local trivialization (which is implemented below as `Trivialization F proj`) if the total space has not been given a topology, but we have a topology on both the fiber and the base space. Through the construction `topological_fiber_prebundle F proj` it will be possible to promote a `Pretrivialization F proj` to a `Trivialization F proj`. -/ structure Pretrivialization (proj : Z → B) extends PartialEquiv Z (B × F) where open_target : IsOpen target baseSet : Set B open_baseSet : IsOpen baseSet source_eq : source = proj ⁻¹' baseSet target_eq : target = baseSet ×ˢ univ proj_toFun : ∀ p ∈ source, (toFun p).1 = proj p namespace Pretrivialization variable {F} variable (e : Pretrivialization F proj) {x : Z} /-- Coercion of a pretrivialization to a function. We don't use `e.toFun` in the `CoeFun` instance because it is actually `e.toPartialEquiv.toFun`, so `simp` will apply lemmas about `toPartialEquiv`. While we may want to switch to this behavior later, doing it mid-port will break a lot of proofs. -/ @[coe] def toFun' : Z → (B × F) := e.toFun instance : CoeFun (Pretrivialization F proj) fun _ => Z → B × F := ⟨toFun'⟩ @[ext] lemma ext' (e e' : Pretrivialization F proj) (h₁ : e.toPartialEquiv = e'.toPartialEquiv) (h₂ : e.baseSet = e'.baseSet) : e = e' := by cases e; cases e'; congr -- TODO: move `ext` here? lemma ext {e e' : Pretrivialization F proj} (h₁ : ∀ x, e x = e' x) (h₂ : ∀ x, e.toPartialEquiv.symm x = e'.toPartialEquiv.symm x) (h₃ : e.baseSet = e'.baseSet) : e = e' := by ext1 <;> [ext1; exact h₃] · apply h₁ · apply h₂ · rw [e.source_eq, e'.source_eq, h₃] /-- If the fiber is nonempty, then the projection also is. -/ lemma toPartialEquiv_injective [Nonempty F] : Injective (toPartialEquiv : Pretrivialization F proj → PartialEquiv Z (B × F)) := by refine fun e e' h ↦ ext' _ _ h ?_ simpa only [fst_image_prod, univ_nonempty, target_eq] using congr_arg (Prod.fst '' PartialEquiv.target ·) h @[simp, mfld_simps] theorem coe_coe : ⇑e.toPartialEquiv = e := rfl @[simp, mfld_simps] theorem coe_fst (ex : x ∈ e.source) : (e x).1 = proj x := e.proj_toFun x ex theorem mem_source : x ∈ e.source ↔ proj x ∈ e.baseSet := by rw [e.source_eq, mem_preimage] theorem coe_fst' (ex : proj x ∈ e.baseSet) : (e x).1 = proj x := e.coe_fst (e.mem_source.2 ex) protected theorem eqOn : EqOn (Prod.fst ∘ e) proj e.source := fun _ hx => e.coe_fst hx theorem mk_proj_snd (ex : x ∈ e.source) : (proj x, (e x).2) = e x := Prod.ext (e.coe_fst ex).symm rfl theorem mk_proj_snd' (ex : proj x ∈ e.baseSet) : (proj x, (e x).2) = e x := Prod.ext (e.coe_fst' ex).symm rfl /-- Composition of inverse and coercion from the subtype of the target. -/ def setSymm : e.target → Z := e.target.restrict e.toPartialEquiv.symm theorem mem_target {x : B × F} : x ∈ e.target ↔ x.1 ∈ e.baseSet := by rw [e.target_eq, prod_univ, mem_preimage] theorem proj_symm_apply {x : B × F} (hx : x ∈ e.target) : proj (e.toPartialEquiv.symm x) = x.1 := by have := (e.coe_fst (e.map_target hx)).symm rwa [← e.coe_coe, e.right_inv hx] at this theorem proj_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) : proj (e.toPartialEquiv.symm (b, x)) = b := e.proj_symm_apply (e.mem_target.2 hx) theorem proj_surjOn_baseSet [Nonempty F] : Set.SurjOn proj e.source e.baseSet := fun b hb => let ⟨y⟩ := ‹Nonempty F› ⟨e.toPartialEquiv.symm (b, y), e.toPartialEquiv.map_target <| e.mem_target.2 hb, e.proj_symm_apply' hb⟩ theorem apply_symm_apply {x : B × F} (hx : x ∈ e.target) : e (e.toPartialEquiv.symm x) = x := e.toPartialEquiv.right_inv hx theorem apply_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) : e (e.toPartialEquiv.symm (b, x)) = (b, x) := e.apply_symm_apply (e.mem_target.2 hx) theorem symm_apply_apply {x : Z} (hx : x ∈ e.source) : e.toPartialEquiv.symm (e x) = x := e.toPartialEquiv.left_inv hx @[simp, mfld_simps] theorem symm_apply_mk_proj {x : Z} (ex : x ∈ e.source) : e.toPartialEquiv.symm (proj x, (e x).2) = x := by rw [← e.coe_fst ex, ← e.coe_coe, e.left_inv ex] @[simp, mfld_simps] theorem preimage_symm_proj_baseSet : e.toPartialEquiv.symm ⁻¹' (proj ⁻¹' e.baseSet) ∩ e.target = e.target := by refine inter_eq_right.mpr fun x hx => ?_ simp only [mem_preimage, PartialEquiv.invFun_as_coe, e.proj_symm_apply hx] exact e.mem_target.mp hx @[simp, mfld_simps] theorem preimage_symm_proj_inter (s : Set B) : e.toPartialEquiv.symm ⁻¹' (proj ⁻¹' s) ∩ e.baseSet ×ˢ univ = (s ∩ e.baseSet) ×ˢ univ := by ext ⟨x, y⟩ suffices x ∈ e.baseSet → (proj (e.toPartialEquiv.symm (x, y)) ∈ s ↔ x ∈ s) by simpa only [prodMk_mem_set_prod_eq, mem_inter_iff, and_true, mem_univ, and_congr_left_iff] intro h rw [e.proj_symm_apply' h] theorem target_inter_preimage_symm_source_eq (e f : Pretrivialization F proj) : f.target ∩ f.toPartialEquiv.symm ⁻¹' e.source = (e.baseSet ∩ f.baseSet) ×ˢ univ := by rw [inter_comm, f.target_eq, e.source_eq, f.preimage_symm_proj_inter] theorem trans_source (e f : Pretrivialization F proj) : (f.toPartialEquiv.symm.trans e.toPartialEquiv).source = (e.baseSet ∩ f.baseSet) ×ˢ univ := by rw [PartialEquiv.trans_source, PartialEquiv.symm_source, e.target_inter_preimage_symm_source_eq] theorem symm_trans_symm (e e' : Pretrivialization F proj) : (e.toPartialEquiv.symm.trans e'.toPartialEquiv).symm = e'.toPartialEquiv.symm.trans e.toPartialEquiv := by rw [PartialEquiv.trans_symm_eq_symm_trans_symm, PartialEquiv.symm_symm] theorem symm_trans_source_eq (e e' : Pretrivialization F proj) : (e.toPartialEquiv.symm.trans e'.toPartialEquiv).source = (e.baseSet ∩ e'.baseSet) ×ˢ univ := by rw [PartialEquiv.trans_source, e'.source_eq, PartialEquiv.symm_source, e.target_eq, inter_comm, e.preimage_symm_proj_inter, inter_comm] theorem symm_trans_target_eq (e e' : Pretrivialization F proj) : (e.toPartialEquiv.symm.trans e'.toPartialEquiv).target = (e.baseSet ∩ e'.baseSet) ×ˢ univ := by rw [← PartialEquiv.symm_source, symm_trans_symm, symm_trans_source_eq, inter_comm] variable (e' : Pretrivialization F (π F E)) {b : B} {y : E b} @[simp] theorem coe_mem_source : ↑y ∈ e'.source ↔ b ∈ e'.baseSet := e'.mem_source @[simp, mfld_simps] theorem coe_coe_fst (hb : b ∈ e'.baseSet) : (e' y).1 = b := e'.coe_fst (e'.mem_source.2 hb) theorem mk_mem_target {x : B} {y : F} : (x, y) ∈ e'.target ↔ x ∈ e'.baseSet := e'.mem_target theorem symm_coe_proj {x : B} {y : F} (e' : Pretrivialization F (π F E)) (h : x ∈ e'.baseSet) : (e'.toPartialEquiv.symm (x, y)).1 = x := e'.proj_symm_apply' h section Zero variable [∀ x, Zero (E x)] open Classical in /-- A fiberwise inverse to `e`. This is the function `F → E b` that induces a local inverse `B × F → TotalSpace F E` of `e` on `e.baseSet`. It is defined to be `0` outside `e.baseSet`. -/ protected noncomputable def symm (e : Pretrivialization F (π F E)) (b : B) (y : F) : E b := if hb : b ∈ e.baseSet then cast (congr_arg E (e.proj_symm_apply' hb)) (e.toPartialEquiv.symm (b, y)).2 else 0 theorem symm_apply (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : e.symm b y = cast (congr_arg E (e.symm_coe_proj hb)) (e.toPartialEquiv.symm (b, y)).2 := dif_pos hb theorem symm_apply_of_not_mem (e : Pretrivialization F (π F E)) {b : B} (hb : b ∉ e.baseSet) (y : F) : e.symm b y = 0 := dif_neg hb theorem coe_symm_of_not_mem (e : Pretrivialization F (π F E)) {b : B} (hb : b ∉ e.baseSet) : (e.symm b : F → E b) = 0 := funext fun _ => dif_neg hb theorem mk_symm (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : TotalSpace.mk b (e.symm b y) = e.toPartialEquiv.symm (b, y) := by simp only [e.symm_apply hb, TotalSpace.mk_cast (e.proj_symm_apply' hb), TotalSpace.eta] theorem symm_proj_apply (e : Pretrivialization F (π F E)) (z : TotalSpace F E) (hz : z.proj ∈ e.baseSet) : e.symm z.proj (e z).2 = z.2 := by rw [e.symm_apply hz, cast_eq_iff_heq, e.mk_proj_snd' hz, e.symm_apply_apply (e.mem_source.mpr hz)] theorem symm_apply_apply_mk (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : E b) : e.symm b (e ⟨b, y⟩).2 = y := e.symm_proj_apply ⟨b, y⟩ hb theorem apply_mk_symm (e : Pretrivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : e ⟨b, e.symm b y⟩ = (b, y) := by rw [e.mk_symm hb, e.apply_symm_apply (e.mk_mem_target.mpr hb)] end Zero end Pretrivialization variable [TopologicalSpace Z] [TopologicalSpace (TotalSpace F E)] /-- A structure extending partial homeomorphisms, defining a local trivialization of a projection `proj : Z → B` with fiber `F`, as a partial homeomorphism between `Z` and `B × F` defined between two sets of the form `proj ⁻¹' baseSet` and `baseSet × F`, acting trivially on the first coordinate. -/ structure Trivialization (proj : Z → B) extends PartialHomeomorph Z (B × F) where baseSet : Set B open_baseSet : IsOpen baseSet source_eq : source = proj ⁻¹' baseSet target_eq : target = baseSet ×ˢ univ proj_toFun : ∀ p ∈ source, (toPartialHomeomorph p).1 = proj p namespace Trivialization variable {F} variable (e : Trivialization F proj) {x : Z} @[ext] lemma ext' (e e' : Trivialization F proj) (h₁ : e.toPartialHomeomorph = e'.toPartialHomeomorph) (h₂ : e.baseSet = e'.baseSet) : e = e' := by cases e; cases e'; congr /-- Coercion of a trivialization to a function. We don't use `e.toFun` in the `CoeFun` instance because it is actually `e.toPartialEquiv.toFun`, so `simp` will apply lemmas about `toPartialEquiv`. While we may want to switch to this behavior later, doing it mid-port will break a lot of proofs. -/ @[coe] def toFun' : Z → (B × F) := e.toFun /-- Natural identification as a `Pretrivialization`. -/ def toPretrivialization : Pretrivialization F proj := { e with } instance : CoeFun (Trivialization F proj) fun _ => Z → B × F := ⟨toFun'⟩ instance : Coe (Trivialization F proj) (Pretrivialization F proj) := ⟨toPretrivialization⟩ theorem toPretrivialization_injective : Function.Injective fun e : Trivialization F proj => e.toPretrivialization := fun e e' h => by ext1 exacts [PartialHomeomorph.toPartialEquiv_injective (congr_arg Pretrivialization.toPartialEquiv h), congr_arg Pretrivialization.baseSet h] @[simp, mfld_simps] theorem coe_coe : ⇑e.toPartialHomeomorph = e := rfl @[simp, mfld_simps] theorem coe_fst (ex : x ∈ e.source) : (e x).1 = proj x := e.proj_toFun x ex protected theorem eqOn : EqOn (Prod.fst ∘ e) proj e.source := fun _x hx => e.coe_fst hx theorem mem_source : x ∈ e.source ↔ proj x ∈ e.baseSet := by rw [e.source_eq, mem_preimage] theorem coe_fst' (ex : proj x ∈ e.baseSet) : (e x).1 = proj x := e.coe_fst (e.mem_source.2 ex) theorem mk_proj_snd (ex : x ∈ e.source) : (proj x, (e x).2) = e x := Prod.ext (e.coe_fst ex).symm rfl theorem mk_proj_snd' (ex : proj x ∈ e.baseSet) : (proj x, (e x).2) = e x := Prod.ext (e.coe_fst' ex).symm rfl theorem source_inter_preimage_target_inter (s : Set (B × F)) : e.source ∩ e ⁻¹' (e.target ∩ s) = e.source ∩ e ⁻¹' s := e.toPartialHomeomorph.source_inter_preimage_target_inter s @[simp, mfld_simps] theorem coe_mk (e : PartialHomeomorph Z (B × F)) (i j k l m) (x : Z) : (Trivialization.mk e i j k l m : Trivialization F proj) x = e x := rfl theorem mem_target {x : B × F} : x ∈ e.target ↔ x.1 ∈ e.baseSet := e.toPretrivialization.mem_target theorem map_target {x : B × F} (hx : x ∈ e.target) : e.toPartialHomeomorph.symm x ∈ e.source := e.toPartialHomeomorph.map_target hx theorem proj_symm_apply {x : B × F} (hx : x ∈ e.target) : proj (e.toPartialHomeomorph.symm x) = x.1 := e.toPretrivialization.proj_symm_apply hx theorem proj_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) : proj (e.toPartialHomeomorph.symm (b, x)) = b := e.toPretrivialization.proj_symm_apply' hx theorem proj_surjOn_baseSet [Nonempty F] : Set.SurjOn proj e.source e.baseSet := e.toPretrivialization.proj_surjOn_baseSet theorem apply_symm_apply {x : B × F} (hx : x ∈ e.target) : e (e.toPartialHomeomorph.symm x) = x := e.toPartialHomeomorph.right_inv hx theorem apply_symm_apply' {b : B} {x : F} (hx : b ∈ e.baseSet) : e (e.toPartialHomeomorph.symm (b, x)) = (b, x) := e.toPretrivialization.apply_symm_apply' hx @[simp, mfld_simps] theorem symm_apply_mk_proj (ex : x ∈ e.source) : e.toPartialHomeomorph.symm (proj x, (e x).2) = x := e.toPretrivialization.symm_apply_mk_proj ex theorem symm_trans_source_eq (e e' : Trivialization F proj) : (e.toPartialEquiv.symm.trans e'.toPartialEquiv).source = (e.baseSet ∩ e'.baseSet) ×ˢ univ := Pretrivialization.symm_trans_source_eq e.toPretrivialization e' theorem symm_trans_target_eq (e e' : Trivialization F proj) : (e.toPartialEquiv.symm.trans e'.toPartialEquiv).target = (e.baseSet ∩ e'.baseSet) ×ˢ univ := Pretrivialization.symm_trans_target_eq e.toPretrivialization e' theorem coe_fst_eventuallyEq_proj (ex : x ∈ e.source) : Prod.fst ∘ e =ᶠ[𝓝 x] proj := mem_nhds_iff.2 ⟨e.source, fun _y hy => e.coe_fst hy, e.open_source, ex⟩ theorem coe_fst_eventuallyEq_proj' (ex : proj x ∈ e.baseSet) : Prod.fst ∘ e =ᶠ[𝓝 x] proj := e.coe_fst_eventuallyEq_proj (e.mem_source.2 ex) theorem map_proj_nhds (ex : x ∈ e.source) : map proj (𝓝 x) = 𝓝 (proj x) := by rw [← e.coe_fst ex, ← map_congr (e.coe_fst_eventuallyEq_proj ex), ← map_map, ← e.coe_coe, e.map_nhds_eq ex, map_fst_nhds] theorem preimage_subset_source {s : Set B} (hb : s ⊆ e.baseSet) : proj ⁻¹' s ⊆ e.source := fun _p hp => e.mem_source.mpr (hb hp) theorem image_preimage_eq_prod_univ {s : Set B} (hb : s ⊆ e.baseSet) : e '' (proj ⁻¹' s) = s ×ˢ univ := Subset.antisymm (image_subset_iff.mpr fun p hp => ⟨(e.proj_toFun p (e.preimage_subset_source hb hp)).symm ▸ hp, trivial⟩) fun p hp => let hp' : p ∈ e.target := e.mem_target.mpr (hb hp.1) ⟨e.invFun p, mem_preimage.mpr ((e.proj_symm_apply hp').symm ▸ hp.1), e.apply_symm_apply hp'⟩ theorem tendsto_nhds_iff {α : Type*} {l : Filter α} {f : α → Z} {z : Z} (hz : z ∈ e.source) : Tendsto f l (𝓝 z) ↔ Tendsto (proj ∘ f) l (𝓝 (proj z)) ∧ Tendsto (fun x ↦ (e (f x)).2) l (𝓝 (e z).2) := by rw [e.nhds_eq_comap_inf_principal hz, tendsto_inf, tendsto_comap_iff, Prod.tendsto_iff, coe_coe, tendsto_principal, coe_fst _ hz] by_cases hl : ∀ᶠ x in l, f x ∈ e.source · simp only [hl, and_true] refine (tendsto_congr' ?_).and Iff.rfl exact hl.mono fun x ↦ e.coe_fst · simp only [hl, and_false, false_iff, not_and] rw [e.source_eq] at hl hz exact fun h _ ↦ hl <| h <| e.open_baseSet.mem_nhds hz theorem nhds_eq_inf_comap {z : Z} (hz : z ∈ e.source) : 𝓝 z = comap proj (𝓝 (proj z)) ⊓ comap (Prod.snd ∘ e) (𝓝 (e z).2) := by refine eq_of_forall_le_iff fun l ↦ ?_ rw [le_inf_iff, ← tendsto_iff_comap, ← tendsto_iff_comap] exact e.tendsto_nhds_iff hz /-- The preimage of a subset of the base set is homeomorphic to the product with the fiber. -/ def preimageHomeomorph {s : Set B} (hb : s ⊆ e.baseSet) : proj ⁻¹' s ≃ₜ s × F := (e.toPartialHomeomorph.homeomorphOfImageSubsetSource (e.preimage_subset_source hb) (e.image_preimage_eq_prod_univ hb)).trans ((Homeomorph.Set.prod s univ).trans ((Homeomorph.refl s).prodCongr (Homeomorph.Set.univ F))) @[simp] theorem preimageHomeomorph_apply {s : Set B} (hb : s ⊆ e.baseSet) (p : proj ⁻¹' s) : e.preimageHomeomorph hb p = (⟨proj p, p.2⟩, (e p).2) := Prod.ext (Subtype.ext (e.proj_toFun p (e.mem_source.mpr (hb p.2)))) rfl /-- Auxiliary definition to avoid looping in `dsimp` with `Trivialization.preimageHomeomorph_symm_apply`. -/ protected def preimageHomeomorph_symm_apply.aux {s : Set B} (hb : s ⊆ e.baseSet) := (e.preimageHomeomorph hb).symm @[simp] theorem preimageHomeomorph_symm_apply {s : Set B} (hb : s ⊆ e.baseSet) (p : s × F) : (e.preimageHomeomorph hb).symm p = ⟨e.symm (p.1, p.2), ((preimageHomeomorph_symm_apply.aux e hb) p).2⟩ := rfl /-- The source is homeomorphic to the product of the base set with the fiber. -/ def sourceHomeomorphBaseSetProd : e.source ≃ₜ e.baseSet × F := (Homeomorph.setCongr e.source_eq).trans (e.preimageHomeomorph subset_rfl) @[simp] theorem sourceHomeomorphBaseSetProd_apply (p : e.source) : e.sourceHomeomorphBaseSetProd p = (⟨proj p, e.mem_source.mp p.2⟩, (e p).2) := e.preimageHomeomorph_apply subset_rfl ⟨p, e.mem_source.mp p.2⟩ /-- Auxiliary definition to avoid looping in `dsimp` with `Trivialization.sourceHomeomorphBaseSetProd_symm_apply`. -/ protected def sourceHomeomorphBaseSetProd_symm_apply.aux := e.sourceHomeomorphBaseSetProd.symm @[simp] theorem sourceHomeomorphBaseSetProd_symm_apply (p : e.baseSet × F) : e.sourceHomeomorphBaseSetProd.symm p = ⟨e.symm (p.1, p.2), (sourceHomeomorphBaseSetProd_symm_apply.aux e p).2⟩ := rfl /-- Each fiber of a trivialization is homeomorphic to the specified fiber. -/ def preimageSingletonHomeomorph {b : B} (hb : b ∈ e.baseSet) : proj ⁻¹' {b} ≃ₜ F := .trans (e.preimageHomeomorph (Set.singleton_subset_iff.mpr hb)) <| .trans (.prodCongr (Homeomorph.homeomorphOfUnique ({b} : Set B) PUnit.{1}) (Homeomorph.refl F)) (Homeomorph.punitProd F) @[simp] theorem preimageSingletonHomeomorph_apply {b : B} (hb : b ∈ e.baseSet) (p : proj ⁻¹' {b}) : e.preimageSingletonHomeomorph hb p = (e p).2 := rfl @[simp] theorem preimageSingletonHomeomorph_symm_apply {b : B} (hb : b ∈ e.baseSet) (p : F) : (e.preimageSingletonHomeomorph hb).symm p = ⟨e.symm (b, p), by rw [mem_preimage, e.proj_symm_apply' hb, mem_singleton_iff]⟩ := rfl /-- In the domain of a bundle trivialization, the projection is continuous -/ theorem continuousAt_proj (ex : x ∈ e.source) : ContinuousAt proj x := (e.map_proj_nhds ex).le /-- Composition of a `Trivialization` and a `Homeomorph`. -/ protected def compHomeomorph {Z' : Type*} [TopologicalSpace Z'] (h : Z' ≃ₜ Z) : Trivialization F (proj ∘ h) where toPartialHomeomorph := h.toPartialHomeomorph.trans e.toPartialHomeomorph baseSet := e.baseSet open_baseSet := e.open_baseSet source_eq := by simp [source_eq, preimage_preimage, Function.comp_def] target_eq := by simp [target_eq] proj_toFun p hp := by have hp : h p ∈ e.source := by simpa using hp simp [hp] /-- Read off the continuity of a function `f : Z → X` at `z : Z` by transferring via a trivialization of `Z` containing `z`. -/ theorem continuousAt_of_comp_right {X : Type*} [TopologicalSpace X] {f : Z → X} {z : Z} (e : Trivialization F proj) (he : proj z ∈ e.baseSet) (hf : ContinuousAt (f ∘ e.toPartialEquiv.symm) (e z)) : ContinuousAt f z := by have hez : z ∈ e.toPartialEquiv.symm.target := by rw [PartialEquiv.symm_target, e.mem_source] exact he rwa [e.toPartialHomeomorph.symm.continuousAt_iff_continuousAt_comp_right hez, PartialHomeomorph.symm_symm] /-- Read off the continuity of a function `f : X → Z` at `x : X` by transferring via a trivialization of `Z` containing `f x`. -/ theorem continuousAt_of_comp_left {X : Type*} [TopologicalSpace X] {f : X → Z} {x : X} (e : Trivialization F proj) (hf_proj : ContinuousAt (proj ∘ f) x) (he : proj (f x) ∈ e.baseSet) (hf : ContinuousAt (e ∘ f) x) : ContinuousAt f x := by rw [e.continuousAt_iff_continuousAt_comp_left] · exact hf rw [e.source_eq, ← preimage_comp] exact hf_proj.preimage_mem_nhds (e.open_baseSet.mem_nhds he) variable (e' : Trivialization F (π F E)) {b : B} {y : E b} protected theorem continuousOn : ContinuousOn e' e'.source := e'.continuousOn_toFun theorem coe_mem_source : ↑y ∈ e'.source ↔ b ∈ e'.baseSet := e'.mem_source @[simp, mfld_simps] theorem coe_coe_fst (hb : b ∈ e'.baseSet) : (e' y).1 = b := e'.coe_fst (e'.mem_source.2 hb) theorem mk_mem_target {y : F} : (b, y) ∈ e'.target ↔ b ∈ e'.baseSet := e'.toPretrivialization.mem_target theorem symm_apply_apply {x : TotalSpace F E} (hx : x ∈ e'.source) : e'.toPartialHomeomorph.symm (e' x) = x := e'.toPartialEquiv.left_inv hx @[simp, mfld_simps] theorem symm_coe_proj {x : B} {y : F} (e : Trivialization F (π F E)) (h : x ∈ e.baseSet) : (e.toPartialHomeomorph.symm (x, y)).1 = x := e.proj_symm_apply' h section Zero variable [∀ x, Zero (E x)] /-- A fiberwise inverse to `e'`. The function `F → E x` that induces a local inverse `B × F → TotalSpace F E` of `e'` on `e'.baseSet`. It is defined to be `0` outside `e'.baseSet`. -/ protected noncomputable def symm (e : Trivialization F (π F E)) (b : B) (y : F) : E b := e.toPretrivialization.symm b y theorem symm_apply (e : Trivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : e.symm b y = cast (congr_arg E (e.symm_coe_proj hb)) (e.toPartialHomeomorph.symm (b, y)).2 := dif_pos hb theorem symm_apply_of_not_mem (e : Trivialization F (π F E)) {b : B} (hb : b ∉ e.baseSet) (y : F) : e.symm b y = 0 := dif_neg hb theorem mk_symm (e : Trivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : TotalSpace.mk b (e.symm b y) = e.toPartialHomeomorph.symm (b, y) := e.toPretrivialization.mk_symm hb y theorem symm_proj_apply (e : Trivialization F (π F E)) (z : TotalSpace F E) (hz : z.proj ∈ e.baseSet) : e.symm z.proj (e z).2 = z.2 := e.toPretrivialization.symm_proj_apply z hz theorem symm_apply_apply_mk (e : Trivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : E b) : e.symm b (e ⟨b, y⟩).2 = y := e.symm_proj_apply ⟨b, y⟩ hb theorem apply_mk_symm (e : Trivialization F (π F E)) {b : B} (hb : b ∈ e.baseSet) (y : F) : e ⟨b, e.symm b y⟩ = (b, y) := e.toPretrivialization.apply_mk_symm hb y theorem continuousOn_symm (e : Trivialization F (π F E)) : ContinuousOn (fun z : B × F => TotalSpace.mk' F z.1 (e.symm z.1 z.2)) (e.baseSet ×ˢ univ) := by have : ∀ z ∈ e.baseSet ×ˢ (univ : Set F), TotalSpace.mk z.1 (e.symm z.1 z.2) = e.toPartialHomeomorph.symm z := by rintro x ⟨hx : x.1 ∈ e.baseSet, _⟩ rw [e.mk_symm hx] refine ContinuousOn.congr ?_ this rw [← e.target_eq] exact e.toPartialHomeomorph.continuousOn_symm end Zero /-- If `e` is a `Trivialization` of `proj : Z → B` with fiber `F` and `h` is a homeomorphism `F ≃ₜ F'`, then `e.trans_fiber_homeomorph h` is the trivialization of `proj` with the fiber `F'` that sends `p : Z` to `((e p).1, h (e p).2)`. -/ def transFiberHomeomorph {F' : Type*} [TopologicalSpace F'] (e : Trivialization F proj) (h : F ≃ₜ F') : Trivialization F' proj where toPartialHomeomorph := e.toPartialHomeomorph.transHomeomorph <| (Homeomorph.refl _).prodCongr h baseSet := e.baseSet open_baseSet := e.open_baseSet source_eq := e.source_eq target_eq := by simp [target_eq, prod_univ, preimage_preimage] proj_toFun := e.proj_toFun @[simp] theorem transFiberHomeomorph_apply {F' : Type*} [TopologicalSpace F'] (e : Trivialization F proj) (h : F ≃ₜ F') (x : Z) : e.transFiberHomeomorph h x = ((e x).1, h (e x).2) := rfl /-- Coordinate transformation in the fiber induced by a pair of bundle trivializations. See also `Trivialization.coordChangeHomeomorph` for a version bundled as `F ≃ₜ F`. -/ def coordChange (e₁ e₂ : Trivialization F proj) (b : B) (x : F) : F := (e₂ <| e₁.toPartialHomeomorph.symm (b, x)).2 theorem mk_coordChange (e₁ e₂ : Trivialization F proj) {b : B} (h₁ : b ∈ e₁.baseSet) (h₂ : b ∈ e₂.baseSet) (x : F) : (b, e₁.coordChange e₂ b x) = e₂ (e₁.toPartialHomeomorph.symm (b, x)) := by refine Prod.ext ?_ rfl rw [e₂.coe_fst', ← e₁.coe_fst', e₁.apply_symm_apply' h₁] · rwa [e₁.proj_symm_apply' h₁] · rwa [e₁.proj_symm_apply' h₁] theorem coordChange_apply_snd (e₁ e₂ : Trivialization F proj) {p : Z} (h : proj p ∈ e₁.baseSet) : e₁.coordChange e₂ (proj p) (e₁ p).snd = (e₂ p).snd := by rw [coordChange, e₁.symm_apply_mk_proj (e₁.mem_source.2 h)] theorem coordChange_same_apply (e : Trivialization F proj) {b : B} (h : b ∈ e.baseSet) (x : F) : e.coordChange e b x = x := by rw [coordChange, e.apply_symm_apply' h] theorem coordChange_same (e : Trivialization F proj) {b : B} (h : b ∈ e.baseSet) : e.coordChange e b = id := funext <| e.coordChange_same_apply h theorem coordChange_coordChange (e₁ e₂ e₃ : Trivialization F proj) {b : B} (h₁ : b ∈ e₁.baseSet) (h₂ : b ∈ e₂.baseSet) (x : F) : e₂.coordChange e₃ b (e₁.coordChange e₂ b x) = e₁.coordChange e₃ b x := by rw [coordChange, e₁.mk_coordChange _ h₁ h₂, ← e₂.coe_coe, e₂.left_inv, coordChange] rwa [e₂.mem_source, e₁.proj_symm_apply' h₁] theorem continuous_coordChange (e₁ e₂ : Trivialization F proj) {b : B} (h₁ : b ∈ e₁.baseSet) (h₂ : b ∈ e₂.baseSet) : Continuous (e₁.coordChange e₂ b) := by refine continuous_snd.comp (e₂.toPartialHomeomorph.continuousOn.comp_continuous (e₁.toPartialHomeomorph.continuousOn_symm.comp_continuous ?_ ?_) ?_) · fun_prop · exact fun x => e₁.mem_target.2 h₁ · intro x rwa [e₂.mem_source, e₁.proj_symm_apply' h₁] /-- Coordinate transformation in the fiber induced by a pair of bundle trivializations, as a homeomorphism. -/ protected def coordChangeHomeomorph (e₁ e₂ : Trivialization F proj) {b : B} (h₁ : b ∈ e₁.baseSet) (h₂ : b ∈ e₂.baseSet) : F ≃ₜ F where toFun := e₁.coordChange e₂ b invFun := e₂.coordChange e₁ b left_inv x := by simp only [*, coordChange_coordChange, coordChange_same_apply] right_inv x := by simp only [*, coordChange_coordChange, coordChange_same_apply] continuous_toFun := e₁.continuous_coordChange e₂ h₁ h₂ continuous_invFun := e₂.continuous_coordChange e₁ h₂ h₁ @[simp] theorem coordChangeHomeomorph_coe (e₁ e₂ : Trivialization F proj) {b : B} (h₁ : b ∈ e₁.baseSet) (h₂ : b ∈ e₂.baseSet) : ⇑(e₁.coordChangeHomeomorph e₂ h₁ h₂) = e₁.coordChange e₂ b := rfl theorem isImage_preimage_prod (e : Trivialization F proj) (s : Set B) : e.toPartialHomeomorph.IsImage (proj ⁻¹' s) (s ×ˢ univ) := fun x hx => by simp [e.coe_fst', hx] /-- Restrict a `Trivialization` to an open set in the base. -/ protected def restrOpen (e : Trivialization F proj) (s : Set B) (hs : IsOpen s) : Trivialization F proj where toPartialHomeomorph := ((e.isImage_preimage_prod s).symm.restr (IsOpen.inter e.open_target (hs.prod isOpen_univ))).symm baseSet := e.baseSet ∩ s open_baseSet := IsOpen.inter e.open_baseSet hs source_eq := by simp [source_eq] target_eq := by simp [target_eq, prod_univ] proj_toFun p hp := e.proj_toFun p hp.1 section Piecewise theorem frontier_preimage (e : Trivialization F proj) (s : Set B) : e.source ∩ frontier (proj ⁻¹' s) = proj ⁻¹' (e.baseSet ∩ frontier s) := by rw [← (e.isImage_preimage_prod s).frontier.preimage_eq, frontier_prod_univ_eq, (e.isImage_preimage_prod _).preimage_eq, e.source_eq, preimage_inter] open Classical in /-- Given two bundle trivializations `e`, `e'` of `proj : Z → B` and a set `s : Set B` such that the base sets of `e` and `e'` intersect `frontier s` on the same set and `e p = e' p` whenever `proj p ∈ e.baseSet ∩ frontier s`, `e.piecewise e' s Hs Heq` is the bundle trivialization over `Set.ite s e.baseSet e'.baseSet` that is equal to `e` on `proj ⁻¹ s` and is equal to `e'` otherwise. -/ noncomputable def piecewise (e e' : Trivialization F proj) (s : Set B) (Hs : e.baseSet ∩ frontier s = e'.baseSet ∩ frontier s) (Heq : EqOn e e' <| proj ⁻¹' (e.baseSet ∩ frontier s)) : Trivialization F proj where toPartialHomeomorph := e.toPartialHomeomorph.piecewise e'.toPartialHomeomorph (proj ⁻¹' s) (s ×ˢ univ) (e.isImage_preimage_prod s) (e'.isImage_preimage_prod s) (by rw [e.frontier_preimage, e'.frontier_preimage, Hs]) (by rwa [e.frontier_preimage]) baseSet := s.ite e.baseSet e'.baseSet open_baseSet := e.open_baseSet.ite e'.open_baseSet Hs source_eq := by simp [source_eq] target_eq := by simp [target_eq, prod_univ] proj_toFun p := by rintro (⟨he, hs⟩ | ⟨he, hs⟩) <;> simp [*] /-- Given two bundle trivializations `e`, `e'` of a topological fiber bundle `proj : Z → B` over a linearly ordered base `B` and a point `a ∈ e.baseSet ∩ e'.baseSet` such that `e` equals `e'` on `proj ⁻¹' {a}`, `e.piecewise_le_of_eq e' a He He' Heq` is the bundle trivialization over `Set.ite (Iic a) e.baseSet e'.baseSet` that is equal to `e` on points `p` such that `proj p ≤ a` and is equal to `e'` otherwise. -/ noncomputable def piecewiseLeOfEq [LinearOrder B] [OrderTopology B] (e e' : Trivialization F proj) (a : B) (He : a ∈ e.baseSet) (He' : a ∈ e'.baseSet) (Heq : ∀ p, proj p = a → e p = e' p) : Trivialization F proj := e.piecewise e' (Iic a) (Set.ext fun x => and_congr_left_iff.2 fun hx => by obtain rfl : x = a := mem_singleton_iff.1 (frontier_Iic_subset _ hx) simp [He, He']) fun p hp => Heq p <| frontier_Iic_subset _ hp.2 /-- Given two bundle trivializations `e`, `e'` of a topological fiber bundle `proj : Z → B` over a linearly ordered base `B` and a point `a ∈ e.baseSet ∩ e'.baseSet`, `e.piecewise_le e' a He He'` is the bundle trivialization over `Set.ite (Iic a) e.baseSet e'.baseSet` that is equal to `e` on points `p` such that `proj p ≤ a` and is equal to `((e' p).1, h (e' p).2)` otherwise, where `h = e'.coord_change_homeomorph e _ _` is the homeomorphism of the fiber such that `h (e' p).2 = (e p).2` whenever `e p = a`. -/ noncomputable def piecewiseLe [LinearOrder B] [OrderTopology B] (e e' : Trivialization F proj) (a : B) (He : a ∈ e.baseSet) (He' : a ∈ e'.baseSet) : Trivialization F proj :=
e.piecewiseLeOfEq (e'.transFiberHomeomorph (e'.coordChangeHomeomorph e He' He)) a He He' <| by rintro p rfl
Mathlib/Topology/FiberBundle/Trivialization.lean
709
710
/- Copyright (c) 2022 Michael Stoll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Michael Stoll -/ import Mathlib.Algebra.CharP.Basic import Mathlib.Algebra.CharP.Lemmas import Mathlib.Data.Fintype.Units import Mathlib.GroupTheory.OrderOfElement /-! # Multiplicative characters of finite rings and fields Let `R` and `R'` be a commutative rings. A *multiplicative character* of `R` with values in `R'` is a morphism of monoids from the multiplicative monoid of `R` into that of `R'` that sends non-units to zero. We use the namespace `MulChar` for the definitions and results. ## Main results We show that the multiplicative characters form a group (if `R'` is commutative); see `MulChar.commGroup`. We also provide an equivalence with the homomorphisms `Rˣ →* R'ˣ`; see `MulChar.equivToUnitHom`. We define a multiplicative character to be *quadratic* if its values are among `0`, `1` and `-1`, and we prove some properties of quadratic characters. Finally, we show that the sum of all values of a nontrivial multiplicative character vanishes; see `MulChar.IsNontrivial.sum_eq_zero`. ## Tags multiplicative character -/ /-! ### Definitions related to multiplicative characters Even though the intended use is when domain and target of the characters are commutative rings, we define them in the more general setting when the domain is a commutative monoid and the target is a commutative monoid with zero. (We need a zero in the target, since non-units are supposed to map to zero.) In this setting, there is an equivalence between multiplicative characters `R → R'` and group homomorphisms `Rˣ → R'ˣ`, and the multiplicative characters have a natural structure as a commutative group. -/ section Defi -- The domain of our multiplicative characters variable (R : Type*) [CommMonoid R] -- The target variable (R' : Type*) [CommMonoidWithZero R'] /-- Define a structure for multiplicative characters. A multiplicative character from a commutative monoid `R` to a commutative monoid with zero `R'` is a homomorphism of (multiplicative) monoids that sends non-units to zero. -/ structure MulChar extends MonoidHom R R' where map_nonunit' : ∀ a : R, ¬IsUnit a → toFun a = 0 instance MulChar.instFunLike : FunLike (MulChar R R') R R' := ⟨fun χ => χ.toFun, fun χ₀ χ₁ h => by cases χ₀; cases χ₁; congr; apply MonoidHom.ext (fun _ => congr_fun h _)⟩ /-- This is the corresponding extension of `MonoidHomClass`. -/ class MulCharClass (F : Type*) (R R' : outParam Type*) [CommMonoid R] [CommMonoidWithZero R'] [FunLike F R R'] : Prop extends MonoidHomClass F R R' where map_nonunit : ∀ (χ : F) {a : R} (_ : ¬IsUnit a), χ a = 0 initialize_simps_projections MulChar (toFun → apply, -toMonoidHom) end Defi namespace MulChar attribute [scoped simp] MulCharClass.map_nonunit section Group -- The domain of our multiplicative characters variable {R : Type*} [CommMonoid R] -- The target variable {R' : Type*} [CommMonoidWithZero R'] variable (R R') in /-- The trivial multiplicative character. It takes the value `0` on non-units and the value `1` on units. -/ @[simps] noncomputable def trivial : MulChar R R' where toFun := by classical exact fun x => if IsUnit x then 1 else 0 map_nonunit' := by intro a ha simp only [ha, if_false] map_one' := by simp only [isUnit_one, if_true] map_mul' := by intro x y classical simp only [IsUnit.mul_iff, boole_mul] split_ifs <;> tauto @[simp] theorem coe_mk (f : R →* R') (hf) : (MulChar.mk f hf : R → R') = f := rfl /-- Extensionality. See `ext` below for the version that will actually be used. -/ theorem ext' {χ χ' : MulChar R R'} (h : ∀ a, χ a = χ' a) : χ = χ' := by cases χ cases χ' congr exact MonoidHom.ext h instance : MulCharClass (MulChar R R') R R' where map_mul χ := χ.map_mul' map_one χ := χ.map_one' map_nonunit χ := χ.map_nonunit' _ theorem map_nonunit (χ : MulChar R R') {a : R} (ha : ¬IsUnit a) : χ a = 0 := χ.map_nonunit' a ha /-- Extensionality. Since `MulChar`s always take the value zero on non-units, it is sufficient to compare the values on units. -/ @[ext] theorem ext {χ χ' : MulChar R R'} (h : ∀ a : Rˣ, χ a = χ' a) : χ = χ' := by apply ext' intro a by_cases ha : IsUnit a · exact h ha.unit · rw [map_nonunit χ ha, map_nonunit χ' ha] /-! ### Equivalence of multiplicative characters with homomorphisms on units We show that restriction / extension by zero gives an equivalence between `MulChar R R'` and `Rˣ →* R'ˣ`. -/ /-- Turn a `MulChar` into a homomorphism between the unit groups. -/ def toUnitHom (χ : MulChar R R') : Rˣ →* R'ˣ := Units.map χ theorem coe_toUnitHom (χ : MulChar R R') (a : Rˣ) : ↑(χ.toUnitHom a) = χ a := rfl /-- Turn a homomorphism between unit groups into a `MulChar`. -/ noncomputable def ofUnitHom (f : Rˣ →* R'ˣ) : MulChar R R' where toFun := by classical exact fun x => if hx : IsUnit x then f hx.unit else 0 map_one' := by have h1 : (isUnit_one.unit : Rˣ) = 1 := Units.eq_iff.mp rfl simp only [h1, dif_pos, Units.val_eq_one, map_one, isUnit_one] map_mul' := by classical intro x y by_cases hx : IsUnit x · simp only [hx, IsUnit.mul_iff, true_and, dif_pos] by_cases hy : IsUnit y · simp only [hy, dif_pos] have hm : (IsUnit.mul_iff.mpr ⟨hx, hy⟩).unit = hx.unit * hy.unit := Units.eq_iff.mp rfl rw [hm, map_mul] norm_cast · simp only [hy, not_false_iff, dif_neg, mul_zero] · simp only [hx, IsUnit.mul_iff, false_and, not_false_iff, dif_neg, zero_mul] map_nonunit' := by intro a ha simp only [ha, not_false_iff, dif_neg] theorem ofUnitHom_coe (f : Rˣ →* R'ˣ) (a : Rˣ) : ofUnitHom f ↑a = f a := by simp [ofUnitHom] /-- The equivalence between multiplicative characters and homomorphisms of unit groups. -/ noncomputable def equivToUnitHom : MulChar R R' ≃ (Rˣ →* R'ˣ) where toFun := toUnitHom invFun := ofUnitHom left_inv := by intro χ ext x rw [ofUnitHom_coe, coe_toUnitHom] right_inv := by intro f ext x simp only [coe_toUnitHom, ofUnitHom_coe] @[simp] theorem toUnitHom_eq (χ : MulChar R R') : toUnitHom χ = equivToUnitHom χ := rfl @[simp] theorem ofUnitHom_eq (χ : Rˣ →* R'ˣ) : ofUnitHom χ = equivToUnitHom.symm χ := rfl @[simp] theorem coe_equivToUnitHom (χ : MulChar R R') (a : Rˣ) : ↑(equivToUnitHom χ a) = χ a := coe_toUnitHom χ a @[simp] theorem equivToUnitHom_symm_coe (f : Rˣ →* R'ˣ) (a : Rˣ) : equivToUnitHom.symm f ↑a = f a := ofUnitHom_coe f a @[simp] lemma coe_toMonoidHom (χ : MulChar R R') (x : R) : χ.toMonoidHom x = χ x := rfl /-! ### Commutative group structure on multiplicative characters The multiplicative characters `R → R'` form a commutative group. -/ protected theorem map_one (χ : MulChar R R') : χ (1 : R) = 1 := χ.map_one' /-- If the domain has a zero (and is nontrivial), then `χ 0 = 0`. -/ protected theorem map_zero {R : Type*} [CommMonoidWithZero R] [Nontrivial R] (χ : MulChar R R') : χ (0 : R) = 0 := by rw [map_nonunit χ not_isUnit_zero] /-- We can convert a multiplicative character into a homomorphism of monoids with zero when the source has a zero and another element. -/ @[coe, simps] def toMonoidWithZeroHom {R : Type*} [CommMonoidWithZero R] [Nontrivial R] (χ : MulChar R R') : R →*₀ R' where toFun := χ.toFun map_zero' := χ.map_zero map_one' := χ.map_one' map_mul' := χ.map_mul' /-- If the domain is a ring `R`, then `χ (ringChar R) = 0`. -/ theorem map_ringChar {R : Type*} [CommSemiring R] [Nontrivial R] (χ : MulChar R R') : χ (ringChar R) = 0 := by rw [ringChar.Nat.cast_ringChar, χ.map_zero] noncomputable instance hasOne : One (MulChar R R') := ⟨trivial R R'⟩ noncomputable instance inhabited : Inhabited (MulChar R R') := ⟨1⟩ /-- Evaluation of the trivial character -/ @[simp] theorem one_apply_coe (a : Rˣ) : (1 : MulChar R R') a = 1 := by classical exact dif_pos a.isUnit /-- Evaluation of the trivial character -/ lemma one_apply {x : R} (hx : IsUnit x) : (1 : MulChar R R') x = 1 := one_apply_coe hx.unit /-- Multiplication of multiplicative characters. (This needs the target to be commutative.) -/ def mul (χ χ' : MulChar R R') : MulChar R R' := { χ.toMonoidHom * χ'.toMonoidHom with toFun := χ * χ' map_nonunit' := fun a ha => by simp only [map_nonunit χ ha, zero_mul, Pi.mul_apply] } instance hasMul : Mul (MulChar R R') := ⟨mul⟩ theorem mul_apply (χ χ' : MulChar R R') (a : R) : (χ * χ') a = χ a * χ' a := rfl @[simp] theorem coeToFun_mul (χ χ' : MulChar R R') : ⇑(χ * χ') = χ * χ' := rfl protected theorem one_mul (χ : MulChar R R') : (1 : MulChar R R') * χ = χ := by ext simp only [one_mul, Pi.mul_apply, MulChar.coeToFun_mul, MulChar.one_apply_coe] protected theorem mul_one (χ : MulChar R R') : χ * 1 = χ := by ext simp only [mul_one, Pi.mul_apply, MulChar.coeToFun_mul, MulChar.one_apply_coe] /-- The inverse of a multiplicative character. We define it as `inverse ∘ χ`. -/ noncomputable def inv (χ : MulChar R R') : MulChar R R' := { MonoidWithZero.inverse.toMonoidHom.comp χ.toMonoidHom with toFun := fun a => MonoidWithZero.inverse (χ a) map_nonunit' := fun a ha => by simp [map_nonunit _ ha] } noncomputable instance hasInv : Inv (MulChar R R') := ⟨inv⟩ /-- The inverse of a multiplicative character `χ`, applied to `a`, is the inverse of `χ a`. -/ theorem inv_apply_eq_inv (χ : MulChar R R') (a : R) : χ⁻¹ a = Ring.inverse (χ a) := Eq.refl <| inv χ a /-- The inverse of a multiplicative character `χ`, applied to `a`, is the inverse of `χ a`. Variant when the target is a field -/ theorem inv_apply_eq_inv' {R' : Type*} [CommGroupWithZero R'] (χ : MulChar R R') (a : R) : χ⁻¹ a = (χ a)⁻¹ := (inv_apply_eq_inv χ a).trans <| Ring.inverse_eq_inv (χ a) /-- When the domain has a zero, then the inverse of a multiplicative character `χ`, applied to `a`, is `χ` applied to the inverse of `a`. -/ theorem inv_apply {R : Type*} [CommMonoidWithZero R] (χ : MulChar R R') (a : R) : χ⁻¹ a = χ (Ring.inverse a) := by by_cases ha : IsUnit a · rw [inv_apply_eq_inv] have h := IsUnit.map χ ha apply_fun (χ a * ·) using IsUnit.mul_right_injective h dsimp only rw [Ring.mul_inverse_cancel _ h, ← map_mul, Ring.mul_inverse_cancel _ ha, map_one] · revert ha nontriviality R intro ha -- `nontriviality R` by itself doesn't do it rw [map_nonunit _ ha, Ring.inverse_non_unit a ha, MulChar.map_zero χ] /-- When the domain has a zero, then the inverse of a multiplicative character `χ`, applied to `a`, is `χ` applied to the inverse of `a`. -/ theorem inv_apply' {R : Type*} [CommGroupWithZero R] (χ : MulChar R R') (a : R) : χ⁻¹ a = χ a⁻¹ := (inv_apply χ a).trans <| congr_arg _ (Ring.inverse_eq_inv a) /-- The product of a character with its inverse is the trivial character. -/ theorem inv_mul (χ : MulChar R R') : χ⁻¹ * χ = 1 := by ext x rw [coeToFun_mul, Pi.mul_apply, inv_apply_eq_inv] simp only [Ring.inverse_mul_cancel _ (IsUnit.map χ x.isUnit)] rw [one_apply_coe] /-- The commutative group structure on `MulChar R R'`. -/ noncomputable instance commGroup : CommGroup (MulChar R R') := { one := 1 mul := (· * ·) inv := Inv.inv inv_mul_cancel := inv_mul mul_assoc := by intro χ₁ χ₂ χ₃ ext a simp only [mul_assoc, Pi.mul_apply, MulChar.coeToFun_mul] mul_comm := by intro χ₁ χ₂
ext a simp only [mul_comm, Pi.mul_apply, MulChar.coeToFun_mul] one_mul := MulChar.one_mul mul_one := MulChar.mul_one } /-- If `a` is a unit and `n : ℕ`, then `(χ ^ n) a = (χ a) ^ n`. -/ theorem pow_apply_coe (χ : MulChar R R') (n : ℕ) (a : Rˣ) : (χ ^ n) a = χ a ^ n := by induction n with | zero => rw [pow_zero, pow_zero, one_apply_coe] | succ n ih => rw [pow_succ, pow_succ, mul_apply, ih] /-- If `n` is positive, then `(χ ^ n) a = (χ a) ^ n`. -/ theorem pow_apply' (χ : MulChar R R') {n : ℕ} (hn : n ≠ 0) (a : R) : (χ ^ n) a = χ a ^ n := by
Mathlib/NumberTheory/MulChar/Basic.lean
334
346
/- Copyright (c) 2020 Aaron Anderson, Jalex Stark. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Jalex Stark -/ import Mathlib.Algebra.Polynomial.Expand import Mathlib.Algebra.Polynomial.Laurent import Mathlib.Algebra.Polynomial.Eval.SMul import Mathlib.LinearAlgebra.Matrix.Charpoly.Basic import Mathlib.LinearAlgebra.Matrix.Reindex import Mathlib.RingTheory.Polynomial.Nilpotent /-! # Characteristic polynomials We give methods for computing coefficients of the characteristic polynomial. ## Main definitions - `Matrix.charpoly_degree_eq_dim` proves that the degree of the characteristic polynomial over a nonzero ring is the dimension of the matrix - `Matrix.det_eq_sign_charpoly_coeff` proves that the determinant is the constant term of the characteristic polynomial, up to sign. - `Matrix.trace_eq_neg_charpoly_coeff` proves that the trace is the negative of the (d-1)th coefficient of the characteristic polynomial, where d is the dimension of the matrix. For a nonzero ring, this is the second-highest coefficient. - `Matrix.charpolyRev` the reverse of the characteristic polynomial. - `Matrix.reverse_charpoly` characterises the reverse of the characteristic polynomial. -/ noncomputable section universe u v w z open Finset Matrix Polynomial variable {R : Type u} [CommRing R] variable {n G : Type v} [DecidableEq n] [Fintype n] variable {α β : Type v} [DecidableEq α] variable {M : Matrix n n R} namespace Matrix theorem charmatrix_apply_natDegree [Nontrivial R] (i j : n) : (charmatrix M i j).natDegree = ite (i = j) 1 0 := by by_cases h : i = j <;> simp [h, ← degree_eq_iff_natDegree_eq_of_pos (Nat.succ_pos 0)] theorem charmatrix_apply_natDegree_le (i j : n) : (charmatrix M i j).natDegree ≤ ite (i = j) 1 0 := by split_ifs with h <;> simp [h, natDegree_X_le] variable (M) theorem charpoly_sub_diagonal_degree_lt : (M.charpoly - ∏ i : n, (X - C (M i i))).degree < ↑(Fintype.card n - 1) := by rw [charpoly, det_apply', ← insert_erase (mem_univ (Equiv.refl n)), sum_insert (not_mem_erase (Equiv.refl n) univ), add_comm] simp only [charmatrix_apply_eq, one_mul, Equiv.Perm.sign_refl, id, Int.cast_one,
Units.val_one, add_sub_cancel_right, Equiv.coe_refl] rw [← mem_degreeLT] apply Submodule.sum_mem (degreeLT R (Fintype.card n - 1)) intro c hc; rw [← C_eq_intCast, C_mul'] apply Submodule.smul_mem (degreeLT R (Fintype.card n - 1)) ↑↑(Equiv.Perm.sign c) rw [mem_degreeLT] apply lt_of_le_of_lt degree_le_natDegree _ rw [Nat.cast_lt] apply lt_of_le_of_lt _ (Equiv.Perm.fixed_point_card_lt_of_ne_one (ne_of_mem_erase hc)) apply le_trans (Polynomial.natDegree_prod_le univ fun i : n => charmatrix M (c i) i) _ rw [card_eq_sum_ones]; rw [sum_filter]; apply sum_le_sum intros apply charmatrix_apply_natDegree_le theorem charpoly_coeff_eq_prod_coeff_of_le {k : ℕ} (h : Fintype.card n - 1 ≤ k) : M.charpoly.coeff k = (∏ i : n, (X - C (M i i))).coeff k := by apply eq_of_sub_eq_zero; rw [← coeff_sub] apply Polynomial.coeff_eq_zero_of_degree_lt
Mathlib/LinearAlgebra/Matrix/Charpoly/Coeff.lean
61
78
/- Copyright (c) 2018 Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Robert Y. Lewis -/ import Mathlib.RingTheory.Valuation.Basic import Mathlib.NumberTheory.Padics.PadicNorm import Mathlib.Analysis.Normed.Field.Lemmas import Mathlib.Tactic.Peel import Mathlib.Topology.MetricSpace.Ultra.Basic /-! # p-adic numbers This file defines the `p`-adic numbers (rationals) `ℚ_[p]` as the completion of `ℚ` with respect to the `p`-adic norm. We show that the `p`-adic norm on `ℚ` extends to `ℚ_[p]`, that `ℚ` is embedded in `ℚ_[p]`, and that `ℚ_[p]` is Cauchy complete. ## Important definitions * `Padic` : the type of `p`-adic numbers * `padicNormE` : the rational valued `p`-adic norm on `ℚ_[p]` * `Padic.addValuation` : the additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ` ## Notation We introduce the notation `ℚ_[p]` for the `p`-adic numbers. ## Implementation notes Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically by taking `[Fact p.Prime]` as a type class argument. We use the same concrete Cauchy sequence construction that is used to construct `ℝ`. `ℚ_[p]` inherits a field structure from this construction. The extension of the norm on `ℚ` to `ℚ_[p]` is *not* analogous to extending the absolute value to `ℝ` and hence the proof that `ℚ_[p]` is complete is different from the proof that ℝ is complete. `padicNormE` is the rational-valued `p`-adic norm on `ℚ_[p]`. To instantiate `ℚ_[p]` as a normed field, we must cast this into an `ℝ`-valued norm. The `ℝ`-valued norm, using notation `‖ ‖` from normed spaces, is the canonical representation of this norm. `simp` prefers `padicNorm` to `padicNormE` when possible. Since `padicNormE` and `‖ ‖` have different types, `simp` does not rewrite one to the other. Coercions from `ℚ` to `ℚ_[p]` are set up to work with the `norm_cast` tactic. ## References * [F. Q. Gouvêa, *p-adic numbers*][gouvea1997] * [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019] * <https://en.wikipedia.org/wiki/P-adic_number> ## Tags p-adic, p adic, padic, norm, valuation, cauchy, completion, p-adic completion -/ noncomputable section open Nat padicNorm CauSeq CauSeq.Completion Metric /-- The type of Cauchy sequences of rationals with respect to the `p`-adic norm. -/ abbrev PadicSeq (p : ℕ) := CauSeq _ (padicNorm p) namespace PadicSeq section variable {p : ℕ} [Fact p.Prime] /-- The `p`-adic norm of the entries of a nonzero Cauchy sequence of rationals is eventually constant. -/ theorem stationary {f : CauSeq ℚ (padicNorm p)} (hf : ¬f ≈ 0) : ∃ N, ∀ m n, N ≤ m → N ≤ n → padicNorm p (f n) = padicNorm p (f m) := have : ∃ ε > 0, ∃ N1, ∀ j ≥ N1, ε ≤ padicNorm p (f j) := CauSeq.abv_pos_of_not_limZero <| not_limZero_of_not_congr_zero hf let ⟨ε, hε, N1, hN1⟩ := this let ⟨N2, hN2⟩ := CauSeq.cauchy₂ f hε ⟨max N1 N2, fun n m hn hm ↦ by have : padicNorm p (f n - f m) < ε := hN2 _ (max_le_iff.1 hn).2 _ (max_le_iff.1 hm).2 have : padicNorm p (f n - f m) < padicNorm p (f n) := lt_of_lt_of_le this <| hN1 _ (max_le_iff.1 hn).1 have : padicNorm p (f n - f m) < max (padicNorm p (f n)) (padicNorm p (f m)) := lt_max_iff.2 (Or.inl this) by_contra hne rw [← padicNorm.neg (f m)] at hne have hnam := add_eq_max_of_ne hne rw [padicNorm.neg, max_comm] at hnam rw [← hnam, sub_eq_add_neg, add_comm] at this apply _root_.lt_irrefl _ this⟩ /-- For all `n ≥ stationaryPoint f hf`, the `p`-adic norm of `f n` is the same. -/ def stationaryPoint {f : PadicSeq p} (hf : ¬f ≈ 0) : ℕ := Classical.choose <| stationary hf theorem stationaryPoint_spec {f : PadicSeq p} (hf : ¬f ≈ 0) : ∀ {m n}, stationaryPoint hf ≤ m → stationaryPoint hf ≤ n → padicNorm p (f n) = padicNorm p (f m) := @(Classical.choose_spec <| stationary hf) open Classical in /-- Since the norm of the entries of a Cauchy sequence is eventually stationary, we can lift the norm to sequences. -/ def norm (f : PadicSeq p) : ℚ := if hf : f ≈ 0 then 0 else padicNorm p (f (stationaryPoint hf)) theorem norm_zero_iff (f : PadicSeq p) : f.norm = 0 ↔ f ≈ 0 := by constructor · intro h by_contra hf unfold norm at h split_ifs at h apply hf intro ε hε exists stationaryPoint hf intro j hj have heq := stationaryPoint_spec hf le_rfl hj simpa [h, heq] · intro h simp [norm, h] end section Embedding open CauSeq variable {p : ℕ} [Fact p.Prime] theorem equiv_zero_of_val_eq_of_equiv_zero {f g : PadicSeq p} (h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) (hf : f ≈ 0) : g ≈ 0 := fun ε hε ↦ let ⟨i, hi⟩ := hf _ hε ⟨i, fun j hj ↦ by simpa [h] using hi _ hj⟩ theorem norm_nonzero_of_not_equiv_zero {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm ≠ 0 := hf ∘ f.norm_zero_iff.1 theorem norm_eq_norm_app_of_nonzero {f : PadicSeq p} (hf : ¬f ≈ 0) : ∃ k, f.norm = padicNorm p k ∧ k ≠ 0 := have heq : f.norm = padicNorm p (f <| stationaryPoint hf) := by simp [norm, hf] ⟨f <| stationaryPoint hf, heq, fun h ↦ norm_nonzero_of_not_equiv_zero hf (by simpa [h] using heq)⟩ theorem not_limZero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬LimZero (const (padicNorm p) q) := fun h' ↦ hq <| const_limZero.1 h' theorem not_equiv_zero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬const (padicNorm p) q ≈ 0 := fun h : LimZero (const (padicNorm p) q - 0) ↦ not_limZero_const_of_nonzero (p := p) hq <| by simpa using h theorem norm_nonneg (f : PadicSeq p) : 0 ≤ f.norm := by classical exact if hf : f ≈ 0 then by simp [hf, norm] else by simp [norm, hf, padicNorm.nonneg] /-- An auxiliary lemma for manipulating sequence indices. -/ theorem lift_index_left_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v2 v3 : ℕ) : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f (max (stationaryPoint hf) (max v2 v3))) := by apply stationaryPoint_spec hf · apply le_max_left · exact le_rfl /-- An auxiliary lemma for manipulating sequence indices. -/ theorem lift_index_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v3 : ℕ) : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f (max v1 (max (stationaryPoint hf) v3))) := by apply stationaryPoint_spec hf · apply le_trans · apply le_max_left _ v3 · apply le_max_right · exact le_rfl /-- An auxiliary lemma for manipulating sequence indices. -/ theorem lift_index_right {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v2 : ℕ) : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f (max v1 (max v2 (stationaryPoint hf)))) := by apply stationaryPoint_spec hf · apply le_trans · apply le_max_right v2 · apply le_max_right · exact le_rfl end Embedding section Valuation open CauSeq variable {p : ℕ} [Fact p.Prime] /-! ### Valuation on `PadicSeq` -/ open Classical in /-- The `p`-adic valuation on `ℚ` lifts to `PadicSeq p`. `Valuation f` is defined to be the valuation of the (`ℚ`-valued) stationary point of `f`. -/ def valuation (f : PadicSeq p) : ℤ := if hf : f ≈ 0 then 0 else padicValRat p (f (stationaryPoint hf)) theorem norm_eq_zpow_neg_valuation {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm = (p : ℚ) ^ (-f.valuation : ℤ) := by rw [norm, valuation, dif_neg hf, dif_neg hf, padicNorm, if_neg] intro H apply CauSeq.not_limZero_of_not_congr_zero hf intro ε hε use stationaryPoint hf intro n hn rw [stationaryPoint_spec hf le_rfl hn] simpa [H] using hε @[deprecated (since := "2024-12-10")] alias norm_eq_pow_val := norm_eq_zpow_neg_valuation theorem val_eq_iff_norm_eq {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) : f.valuation = g.valuation ↔ f.norm = g.norm := by rw [norm_eq_zpow_neg_valuation hf, norm_eq_zpow_neg_valuation hg, ← neg_inj, zpow_right_inj₀] · exact mod_cast (Fact.out : p.Prime).pos · exact mod_cast (Fact.out : p.Prime).ne_one end Valuation end PadicSeq section open PadicSeq -- Porting note: Commented out `padic_index_simp` tactic /- private unsafe def index_simp_core (hh hf hg : expr) (at_ : Interactive.Loc := Interactive.Loc.ns [none]) : tactic Unit := do let [v1, v2, v3] ← [hh, hf, hg].mapM fun n => tactic.mk_app `` stationary_point [n] <|> return n let e1 ← tactic.mk_app `` lift_index_left_left [hh, v2, v3] <|> return q(True) let e2 ← tactic.mk_app `` lift_index_left [hf, v1, v3] <|> return q(True) let e3 ← tactic.mk_app `` lift_index_right [hg, v1, v2] <|> return q(True) let sl ← [e1, e2, e3].foldlM (fun s e => simp_lemmas.add s e) simp_lemmas.mk when at_ (tactic.simp_target sl >> tactic.skip) let hs ← at_.get_locals hs (tactic.simp_hyp sl []) /-- This is a special-purpose tactic that lifts `padicNorm (f (stationary_point f))` to `padicNorm (f (max _ _ _))`. -/ unsafe def tactic.interactive.padic_index_simp (l : interactive.parse interactive.types.pexpr_list) (at_ : interactive.parse interactive.types.location) : tactic Unit := do let [h, f, g] ← l.mapM tactic.i_to_expr index_simp_core h f g at_ -/ end namespace PadicSeq section Embedding open CauSeq variable {p : ℕ} [hp : Fact p.Prime] theorem norm_mul (f g : PadicSeq p) : (f * g).norm = f.norm * g.norm := by classical exact if hf : f ≈ 0 then by have hg : f * g ≈ 0 := mul_equiv_zero' _ hf simp only [hf, hg, norm, dif_pos, zero_mul] else if hg : g ≈ 0 then by have hf : f * g ≈ 0 := mul_equiv_zero _ hg simp only [hf, hg, norm, dif_pos, mul_zero] else by unfold norm have hfg := mul_not_equiv_zero hf hg simp only [hfg, hf, hg, dite_false] -- Porting note: originally `padic_index_simp [hfg, hf, hg]` rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg] apply padicNorm.mul theorem eq_zero_iff_equiv_zero (f : PadicSeq p) : mk f = 0 ↔ f ≈ 0 := mk_eq theorem ne_zero_iff_nequiv_zero (f : PadicSeq p) : mk f ≠ 0 ↔ ¬f ≈ 0 := eq_zero_iff_equiv_zero _ |>.not theorem norm_const (q : ℚ) : norm (const (padicNorm p) q) = padicNorm p q := by obtain rfl | hq := eq_or_ne q 0 · simp [norm] · simp [norm, not_equiv_zero_const_of_nonzero hq] theorem norm_values_discrete (a : PadicSeq p) (ha : ¬a ≈ 0) : ∃ z : ℤ, a.norm = (p : ℚ) ^ (-z) := by let ⟨k, hk, hk'⟩ := norm_eq_norm_app_of_nonzero ha simpa [hk] using padicNorm.values_discrete hk' theorem norm_one : norm (1 : PadicSeq p) = 1 := by have h1 : ¬(1 : PadicSeq p) ≈ 0 := one_not_equiv_zero _ simp [h1, norm, hp.1.one_lt] private theorem norm_eq_of_equiv_aux {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g) (h : padicNorm p (f (stationaryPoint hf)) ≠ padicNorm p (g (stationaryPoint hg))) (hlt : padicNorm p (g (stationaryPoint hg)) < padicNorm p (f (stationaryPoint hf))) : False := by have hpn : 0 < padicNorm p (f (stationaryPoint hf)) - padicNorm p (g (stationaryPoint hg)) := sub_pos_of_lt hlt obtain ⟨N, hN⟩ := hfg _ hpn let i := max N (max (stationaryPoint hf) (stationaryPoint hg)) have hi : N ≤ i := le_max_left _ _ have hN' := hN _ hi -- Porting note: originally `padic_index_simp [N, hf, hg] at hN' h hlt` rw [lift_index_left hf N (stationaryPoint hg), lift_index_right hg N (stationaryPoint hf)] at hN' h hlt have hpne : padicNorm p (f i) ≠ padicNorm p (-g i) := by rwa [← padicNorm.neg (g i)] at h rw [CauSeq.sub_apply, sub_eq_add_neg, add_eq_max_of_ne hpne, padicNorm.neg, max_eq_left_of_lt hlt] at hN' have : padicNorm p (f i) < padicNorm p (f i) := by apply lt_of_lt_of_le hN' apply sub_le_self apply padicNorm.nonneg exact lt_irrefl _ this private theorem norm_eq_of_equiv {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g) : padicNorm p (f (stationaryPoint hf)) = padicNorm p (g (stationaryPoint hg)) := by by_contra h cases lt_or_le (padicNorm p (g (stationaryPoint hg))) (padicNorm p (f (stationaryPoint hf))) with | inl hlt => exact norm_eq_of_equiv_aux hf hg hfg h hlt | inr hle => apply norm_eq_of_equiv_aux hg hf (Setoid.symm hfg) (Ne.symm h) exact lt_of_le_of_ne hle h theorem norm_equiv {f g : PadicSeq p} (hfg : f ≈ g) : f.norm = g.norm := by classical exact if hf : f ≈ 0 then by have hg : g ≈ 0 := Setoid.trans (Setoid.symm hfg) hf simp [norm, hf, hg] else by have hg : ¬g ≈ 0 := hf ∘ Setoid.trans hfg unfold norm; split_ifs; exact norm_eq_of_equiv hf hg hfg private theorem norm_nonarchimedean_aux {f g : PadicSeq p} (hfg : ¬f + g ≈ 0) (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) : (f + g).norm ≤ max f.norm g.norm := by unfold norm; split_ifs -- Porting note: originally `padic_index_simp [hfg, hf, hg]` rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg] apply padicNorm.nonarchimedean theorem norm_nonarchimedean (f g : PadicSeq p) : (f + g).norm ≤ max f.norm g.norm := by classical exact if hfg : f + g ≈ 0 then by
have : 0 ≤ max f.norm g.norm := le_max_of_le_left (norm_nonneg _) simpa only [hfg, norm] else if hf : f ≈ 0 then by have hfg' : f + g ≈ g := by change LimZero (f - 0) at hf show LimZero (f + g - g); · simpa only [sub_zero, add_sub_cancel_right] using hf have hcfg : (f + g).norm = g.norm := norm_equiv hfg' have hcl : f.norm = 0 := (norm_zero_iff f).2 hf have : max f.norm g.norm = g.norm := by rw [hcl]; exact max_eq_right (norm_nonneg _) rw [this, hcfg] else
Mathlib/NumberTheory/Padics/PadicNumbers.lean
347
358
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Fin.VecNotation import Mathlib.Logic.Small.Basic import Mathlib.SetTheory.ZFC.PSet /-! # A model of ZFC In this file, we model Zermelo-Fraenkel set theory (+ choice) using Lean's underlying type theory, building on the pre-sets defined in `Mathlib.SetTheory.ZFC.PSet`. The theory of classes is developed in `Mathlib.SetTheory.ZFC.Class`. ## Main definitions * `ZFSet`: ZFC set. Defined as `PSet` quotiented by `PSet.Equiv`, the extensional equivalence. * `ZFSet.choice`: Axiom of choice. Proved from Lean's axiom of choice. * `ZFSet.omega`: The von Neumann ordinal `ω` as a `Set`. * `Classical.allZFSetDefinable`: All functions are classically definable. * `ZFSet.IsFunc` : Predicate that a ZFC set is a subset of `x × y` that can be considered as a ZFC function `x → y`. That is, each member of `x` is related by the ZFC set to exactly one member of `y`. * `ZFSet.funs`: ZFC set of ZFC functions `x → y`. * `ZFSet.Hereditarily p x`: Predicate that every set in the transitive closure of `x` has property `p`. ## Notes To avoid confusion between the Lean `Set` and the ZFC `Set`, docstrings in this file refer to them respectively as "`Set`" and "ZFC set". -/ universe u /-- The ZFC universe of sets consists of the type of pre-sets, quotiented by extensional equivalence. -/ @[pp_with_univ] def ZFSet : Type (u + 1) := Quotient PSet.setoid.{u} namespace ZFSet /-- Turns a pre-set into a ZFC set. -/ def mk : PSet → ZFSet := Quotient.mk'' @[simp] theorem mk_eq (x : PSet) : @Eq ZFSet ⟦x⟧ (mk x) := rfl @[simp] theorem mk_out : ∀ x : ZFSet, mk x.out = x := Quotient.out_eq /-- A set function is "definable" if it is the image of some n-ary `PSet` function. This isn't exactly definability, but is useful as a sufficient condition for functions that have a computable image. -/ class Definable (n) (f : (Fin n → ZFSet.{u}) → ZFSet.{u}) where /-- Turns a definable function into an n-ary `PSet` function. -/ out : (Fin n → PSet.{u}) → PSet.{u} /-- A set function `f` is the image of `Definable.out f`. -/ mk_out xs : mk (out xs) = f (mk <| xs ·) := by simp attribute [simp] Definable.mk_out /-- An abbrev of `ZFSet.Definable` for unary functions. -/ abbrev Definable₁ (f : ZFSet.{u} → ZFSet.{u}) := Definable 1 (fun s ↦ f (s 0)) /-- A simpler constructor for `ZFSet.Definable₁`. -/ abbrev Definable₁.mk {f : ZFSet.{u} → ZFSet.{u}} (out : PSet.{u} → PSet.{u}) (mk_out : ∀ x, ⟦out x⟧ = f ⟦x⟧) : Definable₁ f where out xs := out (xs 0) mk_out xs := mk_out (xs 0) /-- Turns a unary definable function into a unary `PSet` function. -/ abbrev Definable₁.out (f : ZFSet.{u} → ZFSet.{u}) [Definable₁ f] : PSet.{u} → PSet.{u} := fun x ↦ Definable.out (fun s ↦ f (s 0)) ![x] lemma Definable₁.mk_out {f : ZFSet.{u} → ZFSet.{u}} [Definable₁ f] {x : PSet} : .mk (out f x) = f (.mk x) := Definable.mk_out ![x] /-- An abbrev of `ZFSet.Definable` for binary functions. -/ abbrev Definable₂ (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) := Definable 2 (fun s ↦ f (s 0) (s 1)) /-- A simpler constructor for `ZFSet.Definable₂`. -/ abbrev Definable₂.mk {f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}} (out : PSet.{u} → PSet.{u} → PSet.{u}) (mk_out : ∀ x y, ⟦out x y⟧ = f ⟦x⟧ ⟦y⟧) : Definable₂ f where out xs := out (xs 0) (xs 1) mk_out xs := mk_out (xs 0) (xs 1) /-- Turns a binary definable function into a binary `PSet` function. -/ abbrev Definable₂.out (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) [Definable₂ f] : PSet.{u} → PSet.{u} → PSet.{u} := fun x y ↦ Definable.out (fun s ↦ f (s 0) (s 1)) ![x, y] lemma Definable₂.mk_out {f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}} [Definable₂ f] {x y : PSet} : .mk (out f x y) = f (.mk x) (.mk y) := Definable.mk_out ![x, y] instance (f) [Definable₁ f] (n g) [Definable n g] : Definable n (fun s ↦ f (g s)) where out xs := Definable₁.out f (Definable.out g xs) instance (f) [Definable₂ f] (n g₁ g₂) [Definable n g₁] [Definable n g₂] : Definable n (fun s ↦ f (g₁ s) (g₂ s)) where out xs := Definable₂.out f (Definable.out g₁ xs) (Definable.out g₂ xs) instance (n) (i) : Definable n (fun s ↦ s i) where out s := s i lemma Definable.out_equiv {n} (f : (Fin n → ZFSet.{u}) → ZFSet.{u}) [Definable n f] {xs ys : Fin n → PSet} (h : ∀ i, xs i ≈ ys i) : out f xs ≈ out f ys := by rw [← Quotient.eq_iff_equiv, mk_eq, mk_eq, mk_out, mk_out] exact congrArg _ (funext fun i ↦ Quotient.sound (h i)) lemma Definable₁.out_equiv (f : ZFSet.{u} → ZFSet.{u}) [Definable₁ f] {x y : PSet} (h : x ≈ y) : out f x ≈ out f y := Definable.out_equiv _ (by simp [h]) lemma Definable₂.out_equiv (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) [Definable₂ f] {x₁ y₁ x₂ y₂ : PSet} (h₁ : x₁ ≈ y₁) (h₂ : x₂ ≈ y₂) : out f x₁ x₂ ≈ out f y₁ y₂ := Definable.out_equiv _ (by simp [Fin.forall_fin_succ, h₁, h₂]) end ZFSet namespace Classical open PSet ZFSet /-- All functions are classically definable. -/ noncomputable def allZFSetDefinable {n} (F : (Fin n → ZFSet.{u}) → ZFSet.{u}) : Definable n F where out xs := (F (mk <| xs ·)).out end Classical namespace ZFSet open PSet theorem eq {x y : PSet} : mk x = mk y ↔ Equiv x y := Quotient.eq theorem sound {x y : PSet} (h : PSet.Equiv x y) : mk x = mk y := Quotient.sound h theorem exact {x y : PSet} : mk x = mk y → PSet.Equiv x y := Quotient.exact /-- The membership relation for ZFC sets is inherited from the membership relation for pre-sets. -/ protected def Mem : ZFSet → ZFSet → Prop := Quotient.lift₂ (· ∈ ·) fun _ _ _ _ hx hy => propext ((Mem.congr_left hx).trans (Mem.congr_right hy)) instance : Membership ZFSet ZFSet where mem t s := ZFSet.Mem s t @[simp] theorem mk_mem_iff {x y : PSet} : mk x ∈ mk y ↔ x ∈ y := Iff.rfl /-- Convert a ZFC set into a `Set` of ZFC sets -/ def toSet (u : ZFSet.{u}) : Set ZFSet.{u} := { x | x ∈ u } @[simp] theorem mem_toSet (a u : ZFSet.{u}) : a ∈ u.toSet ↔ a ∈ u := Iff.rfl instance small_toSet (x : ZFSet.{u}) : Small.{u} x.toSet := Quotient.inductionOn x fun a => by let f : a.Type → (mk a).toSet := fun i => ⟨mk <| a.Func i, func_mem a i⟩ suffices Function.Surjective f by exact small_of_surjective this rintro ⟨y, hb⟩ induction y using Quotient.inductionOn obtain ⟨i, h⟩ := hb exact ⟨i, Subtype.coe_injective (Quotient.sound h.symm)⟩ /-- A nonempty set is one that contains some element. -/ protected def Nonempty (u : ZFSet) : Prop := u.toSet.Nonempty theorem nonempty_def (u : ZFSet) : u.Nonempty ↔ ∃ x, x ∈ u := Iff.rfl theorem nonempty_of_mem {x u : ZFSet} (h : x ∈ u) : u.Nonempty := ⟨x, h⟩ @[simp] theorem nonempty_toSet_iff {u : ZFSet} : u.toSet.Nonempty ↔ u.Nonempty := Iff.rfl /-- `x ⊆ y` as ZFC sets means that all members of `x` are members of `y`. -/ protected def Subset (x y : ZFSet.{u}) := ∀ ⦃z⦄, z ∈ x → z ∈ y instance hasSubset : HasSubset ZFSet := ⟨ZFSet.Subset⟩ theorem subset_def {x y : ZFSet.{u}} : x ⊆ y ↔ ∀ ⦃z⦄, z ∈ x → z ∈ y := Iff.rfl instance : IsRefl ZFSet (· ⊆ ·) := ⟨fun _ _ => id⟩ instance : IsTrans ZFSet (· ⊆ ·) := ⟨fun _ _ _ hxy hyz _ ha => hyz (hxy ha)⟩ @[simp] theorem subset_iff : ∀ {x y : PSet}, mk x ⊆ mk y ↔ x ⊆ y | ⟨_, A⟩, ⟨_, _⟩ => ⟨fun h a => @h ⟦A a⟧ (Mem.mk A a), fun h z => Quotient.inductionOn z fun _ ⟨a, za⟩ => let ⟨b, ab⟩ := h a ⟨b, za.trans ab⟩⟩ @[simp] theorem toSet_subset_iff {x y : ZFSet} : x.toSet ⊆ y.toSet ↔ x ⊆ y := by simp [subset_def, Set.subset_def] @[ext] theorem ext {x y : ZFSet.{u}} : (∀ z : ZFSet.{u}, z ∈ x ↔ z ∈ y) → x = y := Quotient.inductionOn₂ x y fun _ _ h => Quotient.sound (Mem.ext fun w => h ⟦w⟧) theorem toSet_injective : Function.Injective toSet := fun _ _ h => ext <| Set.ext_iff.1 h @[simp] theorem toSet_inj {x y : ZFSet} : x.toSet = y.toSet ↔ x = y := toSet_injective.eq_iff instance : IsAntisymm ZFSet (· ⊆ ·) := ⟨fun _ _ hab hba => ext fun c => ⟨@hab c, @hba c⟩⟩ /-- The empty ZFC set -/ protected def empty : ZFSet := mk ∅ instance : EmptyCollection ZFSet := ⟨ZFSet.empty⟩ instance : Inhabited ZFSet := ⟨∅⟩ @[simp] theorem not_mem_empty (x) : x ∉ (∅ : ZFSet.{u}) := Quotient.inductionOn x PSet.not_mem_empty @[simp] theorem toSet_empty : toSet ∅ = ∅ := by simp [toSet] @[simp] theorem empty_subset (x : ZFSet.{u}) : (∅ : ZFSet) ⊆ x := Quotient.inductionOn x fun y => subset_iff.2 <| PSet.empty_subset y @[simp] theorem not_nonempty_empty : ¬ZFSet.Nonempty ∅ := by simp [ZFSet.Nonempty] @[simp] theorem nonempty_mk_iff {x : PSet} : (mk x).Nonempty ↔ x.Nonempty := by refine ⟨?_, fun ⟨a, h⟩ => ⟨mk a, h⟩⟩ rintro ⟨a, h⟩ induction a using Quotient.inductionOn exact ⟨_, h⟩ theorem eq_empty (x : ZFSet.{u}) : x = ∅ ↔ ∀ y : ZFSet.{u}, y ∉ x := by simp [ZFSet.ext_iff] theorem eq_empty_or_nonempty (u : ZFSet) : u = ∅ ∨ u.Nonempty := by rw [eq_empty, ← not_exists] apply em' /-- `Insert x y` is the set `{x} ∪ y` -/ protected def Insert : ZFSet → ZFSet → ZFSet := Quotient.map₂ PSet.insert fun _ _ uv ⟨_, _⟩ ⟨_, _⟩ ⟨αβ, βα⟩ => ⟨fun o => match o with | some a => let ⟨b, hb⟩ := αβ a ⟨some b, hb⟩ | none => ⟨none, uv⟩, fun o => match o with | some b => let ⟨a, ha⟩ := βα b ⟨some a, ha⟩ | none => ⟨none, uv⟩⟩ instance : Insert ZFSet ZFSet := ⟨ZFSet.Insert⟩ instance : Singleton ZFSet ZFSet := ⟨fun x => insert x ∅⟩ instance : LawfulSingleton ZFSet ZFSet := ⟨fun _ => rfl⟩ @[simp] theorem mem_insert_iff {x y z : ZFSet.{u}} : x ∈ insert y z ↔ x = y ∨ x ∈ z := Quotient.inductionOn₃ x y z fun _ _ _ => PSet.mem_insert_iff.trans (or_congr_left eq.symm) theorem mem_insert (x y : ZFSet) : x ∈ insert x y := mem_insert_iff.2 <| Or.inl rfl theorem mem_insert_of_mem {y z : ZFSet} (x) (h : z ∈ y) : z ∈ insert x y := mem_insert_iff.2 <| Or.inr h @[simp] theorem toSet_insert (x y : ZFSet) : (insert x y).toSet = insert x y.toSet := by ext simp @[simp] theorem mem_singleton {x y : ZFSet.{u}} : x ∈ @singleton ZFSet.{u} ZFSet.{u} _ y ↔ x = y := Quotient.inductionOn₂ x y fun _ _ => PSet.mem_singleton.trans eq.symm @[simp] theorem toSet_singleton (x : ZFSet) : ({x} : ZFSet).toSet = {x} := by ext simp theorem insert_nonempty (u v : ZFSet) : (insert u v).Nonempty := ⟨u, mem_insert u v⟩ theorem singleton_nonempty (u : ZFSet) : ZFSet.Nonempty {u} := insert_nonempty u ∅ theorem mem_pair {x y z : ZFSet.{u}} : x ∈ ({y, z} : ZFSet) ↔ x = y ∨ x = z := by simp @[simp] theorem pair_eq_singleton (x : ZFSet) : {x, x} = ({x} : ZFSet) := by ext simp @[simp] theorem pair_eq_singleton_iff {x y z : ZFSet} : ({x, y} : ZFSet) = {z} ↔ x = z ∧ y = z := by refine ⟨fun h ↦ ?_, ?_⟩ · rw [← mem_singleton, ← mem_singleton] simp [← h] · rintro ⟨rfl, rfl⟩ exact pair_eq_singleton y @[simp] theorem singleton_eq_pair_iff {x y z : ZFSet} : ({x} : ZFSet) = {y, z} ↔ x = y ∧ x = z := by rw [eq_comm, pair_eq_singleton_iff] simp_rw [eq_comm] /-- `omega` is the first infinite von Neumann ordinal -/ def omega : ZFSet := mk PSet.omega @[simp] theorem omega_zero : ∅ ∈ omega := ⟨⟨0⟩, Equiv.rfl⟩ @[simp] theorem omega_succ {n} : n ∈ omega.{u} → insert n n ∈ omega.{u} := Quotient.inductionOn n fun x ⟨⟨n⟩, h⟩ => ⟨⟨n + 1⟩, ZFSet.exact <| show insert (mk x) (mk x) = insert (mk <| ofNat n) (mk <| ofNat n) by rw [ZFSet.sound h] rfl⟩ /-- `{x ∈ a | p x}` is the set of elements in `a` satisfying `p` -/ protected def sep (p : ZFSet → Prop) : ZFSet → ZFSet := Quotient.map (PSet.sep fun y => p (mk y)) fun ⟨α, A⟩ ⟨β, B⟩ ⟨αβ, βα⟩ => ⟨fun ⟨a, pa⟩ => let ⟨b, hb⟩ := αβ a ⟨⟨b, by simpa only [mk_func, ← ZFSet.sound hb]⟩, hb⟩, fun ⟨b, pb⟩ => let ⟨a, ha⟩ := βα b ⟨⟨a, by simpa only [mk_func, ZFSet.sound ha]⟩, ha⟩⟩ -- Porting note: the { x | p x } notation appears to be disabled in Lean 4. instance : Sep ZFSet ZFSet := ⟨ZFSet.sep⟩ @[simp] theorem mem_sep {p : ZFSet.{u} → Prop} {x y : ZFSet.{u}} : y ∈ ZFSet.sep p x ↔ y ∈ x ∧ p y := Quotient.inductionOn₂ x y fun _ _ => PSet.mem_sep (p := p ∘ mk) fun _ _ h => (Quotient.sound h).subst @[simp] theorem sep_empty (p : ZFSet → Prop) : (∅ : ZFSet).sep p = ∅ := (eq_empty _).mpr fun _ h ↦ not_mem_empty _ (mem_sep.mp h).1 @[simp] theorem toSet_sep (a : ZFSet) (p : ZFSet → Prop) : (ZFSet.sep p a).toSet = { x ∈ a.toSet | p x } := by ext simp /-- The powerset operation, the collection of subsets of a ZFC set -/ def powerset : ZFSet → ZFSet := Quotient.map PSet.powerset fun ⟨_, A⟩ ⟨_, B⟩ ⟨αβ, βα⟩ => ⟨fun p => ⟨{ b | ∃ a, p a ∧ Equiv (A a) (B b) }, fun ⟨a, pa⟩ => let ⟨b, ab⟩ := αβ a ⟨⟨b, a, pa, ab⟩, ab⟩, fun ⟨_, a, pa, ab⟩ => ⟨⟨a, pa⟩, ab⟩⟩, fun q => ⟨{ a | ∃ b, q b ∧ Equiv (A a) (B b) }, fun ⟨_, b, qb, ab⟩ => ⟨⟨b, qb⟩, ab⟩, fun ⟨b, qb⟩ => let ⟨a, ab⟩ := βα b ⟨⟨a, b, qb, ab⟩, ab⟩⟩⟩ @[simp] theorem mem_powerset {x y : ZFSet.{u}} : y ∈ powerset x ↔ y ⊆ x := Quotient.inductionOn₂ x y fun _ _ => PSet.mem_powerset.trans subset_iff.symm theorem sUnion_lem {α β : Type u} (A : α → PSet) (B : β → PSet) (αβ : ∀ a, ∃ b, Equiv (A a) (B b)) : ∀ a, ∃ b, Equiv ((sUnion ⟨α, A⟩).Func a) ((sUnion ⟨β, B⟩).Func b) | ⟨a, c⟩ => by let ⟨b, hb⟩ := αβ a induction' ea : A a with γ Γ induction' eb : B b with δ Δ rw [ea, eb] at hb obtain ⟨γδ, δγ⟩ := hb let c : (A a).Type := c let ⟨d, hd⟩ := γδ (by rwa [ea] at c) use ⟨b, Eq.ndrec d (Eq.symm eb)⟩ change PSet.Equiv ((A a).Func c) ((B b).Func (Eq.ndrec d eb.symm)) match A a, B b, ea, eb, c, d, hd with | _, _, rfl, rfl, _, _, hd => exact hd /-- The union operator, the collection of elements of elements of a ZFC set -/ def sUnion : ZFSet → ZFSet := Quotient.map PSet.sUnion fun ⟨_, A⟩ ⟨_, B⟩ ⟨αβ, βα⟩ => ⟨sUnion_lem A B αβ, fun a => Exists.elim (sUnion_lem B A (fun b => Exists.elim (βα b) fun c hc => ⟨c, PSet.Equiv.symm hc⟩) a)
fun b hb => ⟨b, PSet.Equiv.symm hb⟩⟩ @[inherit_doc]
Mathlib/SetTheory/ZFC/Basic.lean
450
452
/- 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.MeasurableSpace.CountablyGenerated import Mathlib.MeasureTheory.Measure.MutuallySingular import Mathlib.MeasureTheory.Measure.Typeclasses.NoAtoms import Mathlib.MeasureTheory.Measure.Typeclasses.Probability import Mathlib.MeasureTheory.Measure.Typeclasses.SFinite /-! # 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 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) 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 _ _ _ @[simp] theorem dirac_apply' (a : α) (hs : MeasurableSet s) : dirac a s = s.indicator 1 a := toMeasure_apply _ _ hs @[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) @[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] @[simp] lemma dirac_ne_zero : dirac a ≠ 0 := fun h ↦ by simpa [h] using dirac_apply_of_mem (mem_univ a) theorem map_dirac {f : α → β} (hf : Measurable f) (a : α) : (dirac a).map f = dirac (f a) := by classical exact ext fun s hs => by simp [hs, map_apply hf hs, hf hs, indicator_apply] @[simp] 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 [*] /-- Two measures on a countable space are equal if they agree on singletons. -/
theorem ext_of_singleton [Countable α] {μ ν : Measure α} (h : ∀ a, μ {a} = ν {a}) : μ = ν := ext_of_sUnion_eq_univ (countable_range singleton) (by aesop) (by aesop) /-- Two measures on a countable space are equal if and only if they agree on singletons. -/ theorem ext_iff_singleton [Countable α] {μ ν : Measure α} : μ = ν ↔ ∀ a, μ {a} = ν {a} := ⟨fun h _ ↦ h ▸ rfl, ext_of_singleton⟩
Mathlib/MeasureTheory/Measure/Dirac.lean
87
92
/- Copyright (c) 2021 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison -/ import Mathlib.CategoryTheory.Preadditive.AdditiveFunctor import Mathlib.CategoryTheory.Monoidal.Functor /-! # Preadditive monoidal categories A monoidal category is `MonoidalPreadditive` if it is preadditive and tensor product of morphisms is linear in both factors. -/ noncomputable section namespace CategoryTheory open CategoryTheory.Limits open CategoryTheory.MonoidalCategory variable (C : Type*) [Category C] [Preadditive C] [MonoidalCategory C] /-- A category is `MonoidalPreadditive` if tensoring is additive in both factors. Note we don't `extend Preadditive C` here, as `Abelian C` already extends it, and we'll need to have both typeclasses sometimes. -/ class MonoidalPreadditive : Prop where whiskerLeft_zero : ∀ {X Y Z : C}, X ◁ (0 : Y ⟶ Z) = 0 := by aesop_cat zero_whiskerRight : ∀ {X Y Z : C}, (0 : Y ⟶ Z) ▷ X = 0 := by aesop_cat whiskerLeft_add : ∀ {X Y Z : C} (f g : Y ⟶ Z), X ◁ (f + g) = X ◁ f + X ◁ g := by aesop_cat add_whiskerRight : ∀ {X Y Z : C} (f g : Y ⟶ Z), (f + g) ▷ X = f ▷ X + g ▷ X := by aesop_cat attribute [simp] MonoidalPreadditive.whiskerLeft_zero MonoidalPreadditive.zero_whiskerRight attribute [simp] MonoidalPreadditive.whiskerLeft_add MonoidalPreadditive.add_whiskerRight variable {C} variable [MonoidalPreadditive C] namespace MonoidalPreadditive -- The priority setting will not be needed when we replace `𝟙 X ⊗ f` by `X ◁ f`. @[simp (low)] theorem tensor_zero {W X Y Z : C} (f : W ⟶ X) : f ⊗ (0 : Y ⟶ Z) = 0 := by simp [tensorHom_def] -- The priority setting will not be needed when we replace `f ⊗ 𝟙 X` by `f ▷ X`. @[simp (low)] theorem zero_tensor {W X Y Z : C} (f : Y ⟶ Z) : (0 : W ⟶ X) ⊗ f = 0 := by simp [tensorHom_def] theorem tensor_add {W X Y Z : C} (f : W ⟶ X) (g h : Y ⟶ Z) : f ⊗ (g + h) = f ⊗ g + f ⊗ h := by simp [tensorHom_def] theorem add_tensor {W X Y Z : C} (f g : W ⟶ X) (h : Y ⟶ Z) : (f + g) ⊗ h = f ⊗ h + g ⊗ h := by simp [tensorHom_def] end MonoidalPreadditive instance tensorLeft_additive (X : C) : (tensorLeft X).Additive where instance tensorRight_additive (X : C) : (tensorRight X).Additive where instance tensoringLeft_additive (X : C) : ((tensoringLeft C).obj X).Additive where instance tensoringRight_additive (X : C) : ((tensoringRight C).obj X).Additive where /-- A faithful additive monoidal functor to a monoidal preadditive category ensures that the domain is monoidal preadditive. -/ theorem monoidalPreadditive_of_faithful {D} [Category D] [Preadditive D] [MonoidalCategory D] (F : D ⥤ C) [F.Monoidal] [F.Faithful] [F.Additive] : MonoidalPreadditive D := { whiskerLeft_zero := by intros apply F.map_injective simp [Functor.Monoidal.map_whiskerLeft] zero_whiskerRight := by intros apply F.map_injective simp [Functor.Monoidal.map_whiskerRight] whiskerLeft_add := by intros apply F.map_injective simp only [Functor.Monoidal.map_whiskerLeft, Functor.map_add, Preadditive.comp_add, Preadditive.add_comp, MonoidalPreadditive.whiskerLeft_add] add_whiskerRight := by intros apply F.map_injective simp only [Functor.Monoidal.map_whiskerRight, Functor.map_add, Preadditive.comp_add, Preadditive.add_comp, MonoidalPreadditive.add_whiskerRight] } theorem whiskerLeft_sum (P : C) {Q R : C} {J : Type*} (s : Finset J) (g : J → (Q ⟶ R)) : P ◁ ∑ j ∈ s, g j = ∑ j ∈ s, P ◁ g j := map_sum ((tensoringLeft C).obj P).mapAddHom g s theorem sum_whiskerRight {Q R : C} {J : Type*} (s : Finset J) (g : J → (Q ⟶ R)) (P : C) : (∑ j ∈ s, g j) ▷ P = ∑ j ∈ s, g j ▷ P := map_sum ((tensoringRight C).obj P).mapAddHom g s theorem tensor_sum {P Q R S : C} {J : Type*} (s : Finset J) (f : P ⟶ Q) (g : J → (R ⟶ S)) : (f ⊗ ∑ j ∈ s, g j) = ∑ j ∈ s, f ⊗ g j := by simp only [tensorHom_def, whiskerLeft_sum, Preadditive.comp_sum] theorem sum_tensor {P Q R S : C} {J : Type*} (s : Finset J) (f : P ⟶ Q) (g : J → (R ⟶ S)) : (∑ j ∈ s, g j) ⊗ f = ∑ j ∈ s, g j ⊗ f := by simp only [tensorHom_def, sum_whiskerRight, Preadditive.sum_comp] -- In a closed monoidal category, this would hold because -- `tensorLeft X` is a left adjoint and hence preserves all colimits. -- In any case it is true in any preadditive category. instance (X : C) : PreservesFiniteBiproducts (tensorLeft X) where preserves {J} := let ⟨_⟩ := nonempty_fintype J { preserves := fun {f} => { preserves := fun {b} i => ⟨isBilimitOfTotal _ (by dsimp simp_rw [← id_tensorHom] simp only [← tensor_comp, Category.comp_id, ← tensor_sum, ← tensor_id, IsBilimit.total i])⟩ } } instance (X : C) : PreservesFiniteBiproducts (tensorRight X) where preserves {J} := let ⟨_⟩ := nonempty_fintype J { preserves := fun {f} => { preserves := fun {b} i => ⟨isBilimitOfTotal _ (by dsimp simp_rw [← tensorHom_id] simp only [← tensor_comp, Category.comp_id, ← sum_tensor, ← tensor_id, IsBilimit.total i])⟩ } } variable [HasFiniteBiproducts C] /-- The isomorphism showing how tensor product on the left distributes over direct sums. -/ def leftDistributor {J : Type} [Finite J] (X : C) (f : J → C) : X ⊗ ⨁ f ≅ ⨁ fun j => X ⊗ f j := (tensorLeft X).mapBiproduct f theorem leftDistributor_hom {J : Type} [Fintype J] (X : C) (f : J → C) : (leftDistributor X f).hom = ∑ j : J, (X ◁ biproduct.π f j) ≫ biproduct.ι (fun j => X ⊗ f j) j := by classical ext dsimp [leftDistributor, Functor.mapBiproduct, Functor.mapBicone] erw [biproduct.lift_π] simp only [Preadditive.sum_comp, Category.assoc, biproduct.ι_π, comp_dite, comp_zero, Finset.sum_dite_eq', Finset.mem_univ, ite_true, eqToHom_refl, Category.comp_id] theorem leftDistributor_inv {J : Type} [Fintype J] (X : C) (f : J → C) : (leftDistributor X f).inv = ∑ j : J, biproduct.π _ j ≫ (X ◁ biproduct.ι f j) := by classical ext dsimp [leftDistributor, Functor.mapBiproduct, Functor.mapBicone] simp only [Preadditive.comp_sum, biproduct.ι_π_assoc, dite_comp, zero_comp, Finset.sum_dite_eq, Finset.mem_univ, ite_true, eqToHom_refl, Category.id_comp, biproduct.ι_desc] @[reassoc (attr := simp)] theorem leftDistributor_hom_comp_biproduct_π {J : Type} [Finite J] (X : C) (f : J → C) (j : J) : (leftDistributor X f).hom ≫ biproduct.π _ j = X ◁ biproduct.π _ j := by classical cases nonempty_fintype J simp [leftDistributor_hom, Preadditive.sum_comp, biproduct.ι_π, comp_dite] @[reassoc (attr := simp)] theorem biproduct_ι_comp_leftDistributor_hom {J : Type} [Finite J] (X : C) (f : J → C) (j : J) : (X ◁ biproduct.ι _ j) ≫ (leftDistributor X f).hom = biproduct.ι (fun j => X ⊗ f j) j := by classical cases nonempty_fintype J simp [leftDistributor_hom, Preadditive.comp_sum, ← MonoidalCategory.whiskerLeft_comp_assoc, biproduct.ι_π, whiskerLeft_dite, dite_comp] @[reassoc (attr := simp)] theorem leftDistributor_inv_comp_biproduct_π {J : Type} [Finite J] (X : C) (f : J → C) (j : J) : (leftDistributor X f).inv ≫ (X ◁ biproduct.π _ j) = biproduct.π _ j := by classical cases nonempty_fintype J simp [leftDistributor_inv, Preadditive.sum_comp, ← MonoidalCategory.whiskerLeft_comp, biproduct.ι_π, whiskerLeft_dite, comp_dite] @[reassoc (attr := simp)] theorem biproduct_ι_comp_leftDistributor_inv {J : Type} [Finite J] (X : C) (f : J → C) (j : J) : biproduct.ι _ j ≫ (leftDistributor X f).inv = X ◁ biproduct.ι _ j := by classical cases nonempty_fintype J simp [leftDistributor_inv, Preadditive.comp_sum, ← id_tensor_comp, biproduct.ι_π_assoc, dite_comp] theorem leftDistributor_assoc {J : Type} [Finite J] (X Y : C) (f : J → C) : (asIso (𝟙 X) ⊗ leftDistributor Y f) ≪≫ leftDistributor X _ = (α_ X Y (⨁ f)).symm ≪≫ leftDistributor (X ⊗ Y) f ≪≫ biproduct.mapIso fun _ => α_ X Y _ := by classical cases nonempty_fintype J ext simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.trans_hom, Iso.symm_hom, asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, tensor_sum, id_tensor_comp, tensorIso_hom, leftDistributor_hom, biproduct.mapIso_hom, biproduct.ι_map, biproduct.ι_π, Finset.sum_dite_irrel, Finset.sum_dite_eq', Finset.sum_const_zero] simp_rw [← id_tensorHom] simp only [← id_tensor_comp, biproduct.ι_π] simp only [id_tensor_comp, tensor_dite, comp_dite] simp /-- The isomorphism showing how tensor product on the right distributes over direct sums. -/ def rightDistributor {J : Type} [Finite J] (f : J → C) (X : C) : (⨁ f) ⊗ X ≅ ⨁ fun j => f j ⊗ X := (tensorRight X).mapBiproduct f theorem rightDistributor_hom {J : Type} [Fintype J] (f : J → C) (X : C) : (rightDistributor f X).hom = ∑ j : J, (biproduct.π f j ▷ X) ≫ biproduct.ι (fun j => f j ⊗ X) j := by classical ext dsimp [rightDistributor, Functor.mapBiproduct, Functor.mapBicone] erw [biproduct.lift_π] simp only [Preadditive.sum_comp, Category.assoc, biproduct.ι_π, comp_dite, comp_zero, Finset.sum_dite_eq', Finset.mem_univ, eqToHom_refl, Category.comp_id, ite_true] theorem rightDistributor_inv {J : Type} [Fintype J] (f : J → C) (X : C) : (rightDistributor f X).inv = ∑ j : J, biproduct.π _ j ≫ (biproduct.ι f j ▷ X) := by classical ext dsimp [rightDistributor, Functor.mapBiproduct, Functor.mapBicone] simp only [biproduct.ι_desc, Preadditive.comp_sum, ne_eq, biproduct.ι_π_assoc, dite_comp, zero_comp, Finset.sum_dite_eq, Finset.mem_univ, eqToHom_refl, Category.id_comp, ite_true] @[reassoc (attr := simp)] theorem rightDistributor_hom_comp_biproduct_π {J : Type} [Finite J] (f : J → C) (X : C) (j : J) : (rightDistributor f X).hom ≫ biproduct.π _ j = biproduct.π _ j ▷ X := by classical cases nonempty_fintype J simp [rightDistributor_hom, Preadditive.sum_comp, biproduct.ι_π, comp_dite] @[reassoc (attr := simp)] theorem biproduct_ι_comp_rightDistributor_hom {J : Type} [Finite J] (f : J → C) (X : C) (j : J) : (biproduct.ι _ j ▷ X) ≫ (rightDistributor f X).hom = biproduct.ι (fun j => f j ⊗ X) j := by classical cases nonempty_fintype J simp [rightDistributor_hom, Preadditive.comp_sum, ← comp_whiskerRight_assoc, biproduct.ι_π, dite_whiskerRight, dite_comp] @[reassoc (attr := simp)] theorem rightDistributor_inv_comp_biproduct_π {J : Type} [Finite J] (f : J → C) (X : C) (j : J) : (rightDistributor f X).inv ≫ (biproduct.π _ j ▷ X) = biproduct.π _ j := by classical cases nonempty_fintype J simp [rightDistributor_inv, Preadditive.sum_comp, ← MonoidalCategory.comp_whiskerRight, biproduct.ι_π, dite_whiskerRight, comp_dite] @[reassoc (attr := simp)] theorem biproduct_ι_comp_rightDistributor_inv {J : Type} [Finite J] (f : J → C) (X : C) (j : J) : biproduct.ι _ j ≫ (rightDistributor f X).inv = biproduct.ι _ j ▷ X := by classical cases nonempty_fintype J simp [rightDistributor_inv, Preadditive.comp_sum, ← id_tensor_comp, biproduct.ι_π_assoc, dite_comp] theorem rightDistributor_assoc {J : Type} [Finite J] (f : J → C) (X Y : C) : (rightDistributor f X ⊗ asIso (𝟙 Y)) ≪≫ rightDistributor _ Y = α_ (⨁ f) X Y ≪≫ rightDistributor f (X ⊗ Y) ≪≫ biproduct.mapIso fun _ => (α_ _ X Y).symm := by classical cases nonempty_fintype J ext simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.symm_hom, Iso.trans_hom, asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, sum_tensor, comp_tensor_id, tensorIso_hom, rightDistributor_hom, biproduct.mapIso_hom, biproduct.ι_map, biproduct.ι_π, Finset.sum_dite_irrel, Finset.sum_dite_eq', Finset.sum_const_zero, Finset.mem_univ, if_true] simp_rw [← tensorHom_id] simp only [← comp_tensor_id, biproduct.ι_π, dite_tensor, comp_dite] simp theorem leftDistributor_rightDistributor_assoc {J : Type _} [Finite J] (X : C) (f : J → C) (Y : C) : (leftDistributor X f ⊗ asIso (𝟙 Y)) ≪≫ rightDistributor _ Y = α_ X (⨁ f) Y ≪≫ (asIso (𝟙 X) ⊗ rightDistributor _ Y) ≪≫ leftDistributor X _ ≪≫ biproduct.mapIso fun _ => (α_ _ _ _).symm := by classical cases nonempty_fintype J ext simp only [Category.comp_id, Category.assoc, eqToHom_refl, Iso.symm_hom, Iso.trans_hom, asIso_hom, comp_zero, comp_dite, Preadditive.sum_comp, Preadditive.comp_sum, sum_tensor, tensor_sum, comp_tensor_id, tensorIso_hom, leftDistributor_hom, rightDistributor_hom, biproduct.mapIso_hom, biproduct.ι_map, biproduct.ι_π, Finset.sum_dite_irrel, Finset.sum_dite_eq', Finset.sum_const_zero, Finset.mem_univ, if_true] simp_rw [← tensorHom_id, ← id_tensorHom] simp only [← comp_tensor_id, ← id_tensor_comp_assoc, Category.assoc, biproduct.ι_π, comp_dite, dite_comp, tensor_dite, dite_tensor] simp @[ext] theorem leftDistributor_ext_left {J : Type} [Finite J] {X Y : C} {f : J → C} {g h : X ⊗ ⨁ f ⟶ Y} (w : ∀ j, (X ◁ biproduct.ι f j) ≫ g = (X ◁ biproduct.ι f j) ≫ h) : g = h := by classical
cases nonempty_fintype J apply (cancel_epi (leftDistributor X f).inv).mp ext simp? [leftDistributor_inv, Preadditive.comp_sum_assoc, biproduct.ι_π_assoc, dite_comp] says simp only [leftDistributor_inv, Preadditive.comp_sum_assoc, biproduct.ι_π_assoc, dite_comp, zero_comp, Finset.sum_dite_eq, Finset.mem_univ, ↓reduceIte, eqToHom_refl, Category.id_comp] apply w @[ext] theorem leftDistributor_ext_right {J : Type} [Finite J] {X Y : C} {f : J → C} {g h : X ⟶ Y ⊗ ⨁ f}
Mathlib/CategoryTheory/Monoidal/Preadditive.lean
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/- Copyright (c) 2024 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Probability.Kernel.Composition.MapComap import Mathlib.Probability.Martingale.Convergence import Mathlib.Probability.Process.PartitionFiltration /-! # Kernel density Let `κ : Kernel α (γ × β)` and `ν : Kernel α γ` be two finite kernels with `Kernel.fst κ ≤ ν`, where `γ` has a countably generated σ-algebra (true in particular for standard Borel spaces). We build a function `density κ ν : α → γ → Set β → ℝ` jointly measurable in the first two arguments such that for all `a : α` and all measurable sets `s : Set β` and `A : Set γ`, `∫ x in A, density κ ν a x s ∂(ν a) = (κ a).real (A ×ˢ s)`. There are two main applications of this construction. * Disintegration of kernels: for `κ : Kernel α (γ × β)`, we want to build a kernel `η : Kernel (α × γ) β` such that `κ = fst κ ⊗ₖ η`. For `β = ℝ`, we can use the density of `κ` with respect to `fst κ` for intervals to build a kernel cumulative distribution function for `η`. The construction can then be extended to `β` standard Borel. * Radon-Nikodym theorem for kernels: for `κ ν : Kernel α γ`, we can use the density to build a Radon-Nikodym derivative of `κ` with respect to `ν`. We don't need `β` here but we can apply the density construction to `β = Unit`. The derivative construction will use `density` but will not be exactly equal to it because we will want to remove the `fst κ ≤ ν` assumption. ## Main definitions * `ProbabilityTheory.Kernel.density`: for `κ : Kernel α (γ × β)` and `ν : Kernel α γ` two finite kernels, `Kernel.density κ ν` is a function `α → γ → Set β → ℝ`. ## Main statements * `ProbabilityTheory.Kernel.setIntegral_density`: for all measurable sets `A : Set γ` and `s : Set β`, `∫ x in A, Kernel.density κ ν a x s ∂(ν a) = (κ a).real (A ×ˢ s)`. * `ProbabilityTheory.Kernel.measurable_density`: the function `p : α × γ ↦ Kernel.density κ ν p.1 p.2 s` is measurable. ## Construction of the density If we were interested only in a fixed `a : α`, then we could use the Radon-Nikodym derivative to build the density function `density κ ν`, as follows. ``` def density' (κ : Kernel α (γ × β)) (ν : kernel a γ) (a : α) (x : γ) (s : Set β) : ℝ := (((κ a).restrict (univ ×ˢ s)).fst.rnDeriv (ν a) x).toReal ``` However, we can't turn those functions for each `a` into a measurable function of the pair `(a, x)`. In order to obtain measurability through countability, we use the fact that the measurable space `γ` is countably generated. For each `n : ℕ`, we define (in the file `Mathlib.Probability.Process.PartitionFiltration`) a finite partition of `γ`, such that those partitions are finer as `n` grows, and the σ-algebra generated by the union of all partitions is the σ-algebra of `γ`. For `x : γ`, `countablePartitionSet n x` denotes the set in the partition such that `x ∈ countablePartitionSet n x`. For a given `n`, the function `densityProcess κ ν n : α → γ → Set β → ℝ` defined by `fun a x s ↦ (κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x)).toReal` has the desired property that `∫ x in A, densityProcess κ ν n a x s ∂(ν a) = (κ a (A ×ˢ s)).toReal` for all `A` in the σ-algebra generated by the partition at scale `n` and is measurable in `(a, x)`. `countableFiltration γ` is the filtration of those σ-algebras for all `n : ℕ`. The functions `densityProcess κ ν n` described here are a bounded `ν`-martingale for the filtration `countableFiltration γ`. By Doob's martingale L1 convergence theorem, that martingale converges to a limit, which has a product-measurable version and satisfies the integral equality for all `A` in `⨆ n, countableFiltration γ n`. Finally, the partitions were chosen such that that supremum is equal to the σ-algebra on `γ`, hence the equality holds for all measurable sets. We have obtained the desired density function. ## References The construction of the density process in this file follows the proof of Theorem 9.27 in [O. Kallenberg, Foundations of modern probability][kallenberg2021], adapted to use a countably generated hypothesis instead of specializing to `ℝ`. -/ open MeasureTheory Set Filter MeasurableSpace open scoped NNReal ENNReal MeasureTheory Topology ProbabilityTheory namespace ProbabilityTheory.Kernel variable {α β γ : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} [CountablyGenerated γ] {κ : Kernel α (γ × β)} {ν : Kernel α γ} section DensityProcess /-- An `ℕ`-indexed martingale that is a density for `κ` with respect to `ν` on the sets in `countablePartition γ n`. Used to define its limit `ProbabilityTheory.Kernel.density`, which is a density for those kernels for all measurable sets. -/ noncomputable def densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) (s : Set β) : ℝ := (κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x)).toReal lemma densityProcess_def (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (s : Set β) : (fun t ↦ densityProcess κ ν n a t s) = fun t ↦ (κ a (countablePartitionSet n t ×ˢ s) / ν a (countablePartitionSet n t)).toReal := rfl lemma measurable_densityProcess_countableFiltration_aux (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable[mα.prod (countableFiltration γ n)] (fun (p : α × γ) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) := by change Measurable[mα.prod (countableFiltration γ n)] ((fun (p : α × countablePartition γ n) ↦ κ p.1 (↑p.2 ×ˢ s) / ν p.1 p.2) ∘ (fun (p : α × γ) ↦ (p.1, ⟨countablePartitionSet n p.2, countablePartitionSet_mem n p.2⟩))) have h1 : @Measurable _ _ (mα.prod ⊤) _ (fun p : α × countablePartition γ n ↦ κ p.1 (↑p.2 ×ˢ s) / ν p.1 p.2) := by refine Measurable.div ?_ ?_ · refine measurable_from_prod_countable (fun t ↦ ?_) exact Kernel.measurable_coe _ ((measurableSet_countablePartition _ t.prop).prod hs) · refine measurable_from_prod_countable ?_ rintro ⟨t, ht⟩ exact Kernel.measurable_coe _ (measurableSet_countablePartition _ ht) refine h1.comp (measurable_fst.prodMk ?_) change @Measurable (α × γ) (countablePartition γ n) (mα.prod (countableFiltration γ n)) ⊤ ((fun c ↦ ⟨countablePartitionSet n c, countablePartitionSet_mem n c⟩) ∘ (fun p : α × γ ↦ p.2)) exact (measurable_countablePartitionSet_subtype n ⊤).comp measurable_snd lemma measurable_densityProcess_aux (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun (p : α × γ) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) := by refine Measurable.mono (measurable_densityProcess_countableFiltration_aux κ ν n hs) ?_ le_rfl exact sup_le_sup le_rfl (comap_mono ((countableFiltration γ).le _)) lemma measurable_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun (p : α × γ) ↦ densityProcess κ ν n p.1 p.2 s) := (measurable_densityProcess_aux κ ν n hs).ennreal_toReal -- The following two lemmas also work without the `( :)`, but they are slow. lemma measurable_densityProcess_left (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (x : γ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun a ↦ densityProcess κ ν n a x s) := ((measurable_densityProcess κ ν n hs).comp (measurable_id.prodMk measurable_const):) lemma measurable_densityProcess_right (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (a : α) (hs : MeasurableSet s) : Measurable (fun x ↦ densityProcess κ ν n a x s) := ((measurable_densityProcess κ ν n hs).comp (measurable_const.prodMk measurable_id):) lemma measurable_countableFiltration_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : Measurable[countableFiltration γ n] (fun x ↦ densityProcess κ ν n a x s) := by refine @Measurable.ennreal_toReal _ (countableFiltration γ n) _ ?_ exact (measurable_densityProcess_countableFiltration_aux κ ν n hs).comp measurable_prodMk_left lemma stronglyMeasurable_countableFiltration_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : StronglyMeasurable[countableFiltration γ n] (fun x ↦ densityProcess κ ν n a x s) := (measurable_countableFiltration_densityProcess κ ν n a hs).stronglyMeasurable lemma adapted_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (a : α) {s : Set β} (hs : MeasurableSet s) : Adapted (countableFiltration γ) (fun n x ↦ densityProcess κ ν n a x s) := fun n ↦ stronglyMeasurable_countableFiltration_densityProcess κ ν n a hs lemma densityProcess_nonneg (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) (s : Set β) : 0 ≤ densityProcess κ ν n a x s := ENNReal.toReal_nonneg lemma meas_countablePartitionSet_le_of_fst_le (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : κ a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := by calc κ a (countablePartitionSet n x ×ˢ s) ≤ fst κ a (countablePartitionSet n x) := by rw [fst_apply' _ _ (measurableSet_countablePartitionSet _ _)] refine measure_mono (fun x ↦ ?_) simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h _ ≤ ν a (countablePartitionSet n x) := hκν a _ lemma densityProcess_le_one (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν n a x s ≤ 1 := by refine ENNReal.toReal_le_of_le_ofReal zero_le_one (ENNReal.div_le_of_le_mul ?_) rw [ENNReal.ofReal_one, one_mul] exact meas_countablePartitionSet_le_of_fst_le hκν n a x s lemma eLpNorm_densityProcess_le (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (s : Set β) : eLpNorm (fun x ↦ densityProcess κ ν n a x s) 1 (ν a) ≤ ν a univ := by refine (eLpNorm_le_of_ae_bound (C := 1) (ae_of_all _ (fun x ↦ ?_))).trans ?_ · simp only [Real.norm_eq_abs, abs_of_nonneg (densityProcess_nonneg κ ν n a x s), densityProcess_le_one hκν n a x s] · simp lemma integrable_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : Integrable (fun x ↦ densityProcess κ ν n a x s) (ν a) := by rw [← memLp_one_iff_integrable] refine ⟨Measurable.aestronglyMeasurable ?_, ?_⟩ · exact measurable_densityProcess_right κ ν n a hs · exact (eLpNorm_densityProcess_le hκν n a s).trans_lt (measure_lt_top _ _) lemma setIntegral_densityProcess_of_mem (hκν : fst κ ≤ ν) [hν : IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) {u : Set γ} (hu : u ∈ countablePartition γ n) : ∫ x in u, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (u ×ˢ s) := by have : IsFiniteKernel κ := isFiniteKernel_of_isFiniteKernel_fst (h := isFiniteKernel_of_le hκν) have hu_meas : MeasurableSet u := measurableSet_countablePartition n hu simp_rw [densityProcess] rw [integral_toReal] rotate_left · refine Measurable.aemeasurable ?_ change Measurable ((fun (p : α × _) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) ∘ (fun x ↦ (a, x))) exact (measurable_densityProcess_aux κ ν n hs).comp measurable_prodMk_left · refine ae_of_all _ (fun x ↦ ?_) by_cases h0 : ν a (countablePartitionSet n x) = 0 · suffices κ a (countablePartitionSet n x ×ˢ s) = 0 by simp [h0, this] have h0' : fst κ a (countablePartitionSet n x) = 0 := le_antisymm ((hκν a _).trans h0.le) zero_le' rw [fst_apply' _ _ (measurableSet_countablePartitionSet _ _)] at h0' refine measure_mono_null (fun x ↦ ?_) h0' simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h · exact ENNReal.div_lt_top (measure_ne_top _ _) h0 congr have : ∫⁻ x in u, κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x) ∂(ν a) = ∫⁻ _ in u, κ a (u ×ˢ s) / ν a u ∂(ν a) := by refine setLIntegral_congr_fun hu_meas (ae_of_all _ (fun t ht ↦ ?_)) rw [countablePartitionSet_of_mem hu ht] rw [this] simp only [MeasureTheory.lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter] by_cases h0 : ν a u = 0 · simp only [h0, mul_zero] have h0' : fst κ a u = 0 := le_antisymm ((hκν a _).trans h0.le) zero_le' rw [fst_apply' _ _ hu_meas] at h0' refine (measure_mono_null ?_ h0').symm intro p simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h rw [div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel h0, mul_one] exact measure_ne_top _ _ open scoped Function in -- required for scoped `on` notation lemma setIntegral_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) {A : Set γ} (hA : MeasurableSet[countableFiltration γ n] A) : ∫ x in A, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (A ×ˢ s) := by have : IsFiniteKernel κ := isFiniteKernel_of_isFiniteKernel_fst (h := isFiniteKernel_of_le hκν) obtain ⟨S, hS_subset, rfl⟩ := (measurableSet_generateFrom_countablePartition_iff _ _).mp hA simp_rw [sUnion_eq_iUnion] have h_disj : Pairwise (Disjoint on fun i : S ↦ (i : Set γ)) := by intro u v huv #adaptation_note /-- nightly-2024-03-16 Previously `Function.onFun` unfolded in the following `simp only`, but now needs a `rw`. This may be a bug: a no import minimization may be required. simp only [Finset.coe_sort_coe, Function.onFun] -/ rw [Function.onFun] refine disjoint_countablePartition (hS_subset (by simp)) (hS_subset (by simp)) ?_ rwa [ne_eq, ← Subtype.ext_iff] rw [integral_iUnion, iUnion_prod_const, measureReal_def, measure_iUnion, ENNReal.tsum_toReal_eq (fun _ ↦ measure_ne_top _ _)] · congr with u rw [setIntegral_densityProcess_of_mem hκν _ _ hs (hS_subset (by simp))] rfl · intro u v huv simp only [Finset.coe_sort_coe, Set.disjoint_prod, disjoint_self, bot_eq_empty] exact Or.inl (h_disj huv) · exact fun _ ↦ (measurableSet_countablePartition n (hS_subset (by simp))).prod hs · exact fun _ ↦ measurableSet_countablePartition n (hS_subset (by simp)) · exact h_disj · exact (integrable_densityProcess hκν _ _ hs).integrableOn lemma integral_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : ∫ x, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (univ ×ˢ s) := by rw [← setIntegral_univ, setIntegral_densityProcess hκν _ _ hs MeasurableSet.univ] lemma setIntegral_densityProcess_of_le (hκν : fst κ ≤ ν) [IsFiniteKernel ν] {n m : ℕ} (hnm : n ≤ m) (a : α) {s : Set β} (hs : MeasurableSet s) {A : Set γ} (hA : MeasurableSet[countableFiltration γ n] A) : ∫ x in A, densityProcess κ ν m a x s ∂(ν a) = (κ a).real (A ×ˢ s) := setIntegral_densityProcess hκν m a hs ((countableFiltration γ).mono hnm A hA) lemma condExp_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] {i j : ℕ} (hij : i ≤ j) (a : α) {s : Set β} (hs : MeasurableSet s) : (ν a)[fun x ↦ densityProcess κ ν j a x s | countableFiltration γ i] =ᵐ[ν a] fun x ↦ densityProcess κ ν i a x s := by refine (ae_eq_condExp_of_forall_setIntegral_eq ?_ ?_ ?_ ?_ ?_).symm · exact integrable_densityProcess hκν j a hs · exact fun _ _ _ ↦ (integrable_densityProcess hκν _ _ hs).integrableOn · intro x hx _ rw [setIntegral_densityProcess hκν i a hs hx, setIntegral_densityProcess_of_le hκν hij a hs hx] · exact StronglyMeasurable.aestronglyMeasurable (stronglyMeasurable_countableFiltration_densityProcess κ ν i a hs) @[deprecated (since := "2025-01-21")] alias condexp_densityProcess := condExp_densityProcess lemma martingale_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : Martingale (fun n x ↦ densityProcess κ ν n a x s) (countableFiltration γ) (ν a) := ⟨adapted_densityProcess κ ν a hs, fun _ _ h ↦ condExp_densityProcess hκν h a hs⟩ lemma densityProcess_mono_set (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) {s s' : Set β} (h : s ⊆ s') : densityProcess κ ν n a x s ≤ densityProcess κ ν n a x s' := by unfold densityProcess obtain h₀ | h₀ := eq_or_ne (ν a (countablePartitionSet n x)) 0 · simp [h₀] · gcongr simp only [ne_eq, ENNReal.div_eq_top, h₀, and_false, false_or, not_and, not_not] exact eq_top_mono (meas_countablePartitionSet_le_of_fst_le hκν n a x s') lemma densityProcess_mono_kernel_left {κ' : Kernel α (γ × β)} (hκκ' : κ ≤ κ') (hκ'ν : fst κ' ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν n a x s ≤ densityProcess κ' ν n a x s := by unfold densityProcess by_cases h0 : ν a (countablePartitionSet n x) = 0 · rw [h0, ENNReal.toReal_div, ENNReal.toReal_div] simp have h_le : κ' a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := meas_countablePartitionSet_le_of_fst_le hκ'ν n a x s gcongr · simp only [ne_eq, ENNReal.div_eq_top, h0, and_false, false_or, not_and, not_not] exact fun h_top ↦ eq_top_mono h_le h_top · apply hκκ' lemma densityProcess_antitone_kernel_right {ν' : Kernel α γ} (hνν' : ν ≤ ν') (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν' n a x s ≤ densityProcess κ ν n a x s := by unfold densityProcess have h_le : κ a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := meas_countablePartitionSet_le_of_fst_le hκν n a x s by_cases h0 : ν a (countablePartitionSet n x) = 0 · simp [le_antisymm (h_le.trans h0.le) zero_le', h0] gcongr · simp only [ne_eq, ENNReal.div_eq_top, h0, and_false, false_or, not_and, not_not] exact fun h_top ↦ eq_top_mono h_le h_top · apply hνν' @[simp] lemma densityProcess_empty (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) : densityProcess κ ν n a x ∅ = 0 := by simp [densityProcess] lemma tendsto_densityProcess_atTop_empty_of_antitone (κ : Kernel α (γ × β)) (ν : Kernel α γ) [IsFiniteKernel κ] (n : ℕ) (a : α) (x : γ) (seq : ℕ → Set β) (hseq : Antitone seq) (hseq_iInter : ⋂ i, seq i = ∅) (hseq_meas : ∀ m, MeasurableSet (seq m)) : Tendsto (fun m ↦ densityProcess κ ν n a x (seq m)) atTop (𝓝 (densityProcess κ ν n a x ∅)) := by simp_rw [densityProcess] by_cases h0 : ν a (countablePartitionSet n x) = 0 · simp_rw [h0, ENNReal.toReal_div] simp refine (ENNReal.tendsto_toReal ?_).comp ?_ · rw [ne_eq, ENNReal.div_eq_top] push_neg simp refine ENNReal.Tendsto.div_const ?_ (.inr h0) have : Tendsto (fun m ↦ κ a (countablePartitionSet n x ×ˢ seq m)) atTop (𝓝 ((κ a) (⋂ n_1, countablePartitionSet n x ×ˢ seq n_1))) := by apply tendsto_measure_iInter_atTop · measurability · exact fun _ _ h ↦ prod_mono_right <| hseq h · exact ⟨0, measure_ne_top _ _⟩ simpa only [← prod_iInter, hseq_iInter] using this lemma tendsto_densityProcess_atTop_of_antitone (κ : Kernel α (γ × β)) (ν : Kernel α γ) [IsFiniteKernel κ] (n : ℕ) (a : α) (x : γ) (seq : ℕ → Set β) (hseq : Antitone seq) (hseq_iInter : ⋂ i, seq i = ∅) (hseq_meas : ∀ m, MeasurableSet (seq m)) : Tendsto (fun m ↦ densityProcess κ ν n a x (seq m)) atTop (𝓝 0) := by rw [← densityProcess_empty κ ν n a x] exact tendsto_densityProcess_atTop_empty_of_antitone κ ν n a x seq hseq hseq_iInter hseq_meas lemma tendsto_densityProcess_limitProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : ∀ᵐ x ∂(ν a), Tendsto (fun n ↦ densityProcess κ ν n a x s) atTop (𝓝 ((countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a) x)) := by refine Submartingale.ae_tendsto_limitProcess (martingale_densityProcess hκν a hs).submartingale (R := (ν a univ).toNNReal) (fun n ↦ ?_) refine (eLpNorm_densityProcess_le hκν n a s).trans_eq ?_ rw [ENNReal.coe_toNNReal] exact measure_ne_top _ _ lemma memL1_limitProcess_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : MemLp ((countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 (ν a) := by refine Submartingale.memLp_limitProcess (martingale_densityProcess hκν a hs).submartingale (R := (ν a univ).toNNReal) (fun n ↦ ?_) refine (eLpNorm_densityProcess_le hκν n a s).trans_eq ?_ rw [ENNReal.coe_toNNReal] exact measure_ne_top _ _ lemma tendsto_eLpNorm_one_densityProcess_limitProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : Tendsto (fun n ↦ eLpNorm ((fun x ↦ densityProcess κ ν n a x s) - (countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 (ν a)) atTop (𝓝 0) := by refine Submartingale.tendsto_eLpNorm_one_limitProcess ?_ ?_ · exact (martingale_densityProcess hκν a hs).submartingale · refine uniformIntegrable_of le_rfl ENNReal.one_ne_top ?_ ?_ · exact fun n ↦ (measurable_densityProcess_right κ ν n a hs).aestronglyMeasurable · refine fun ε _ ↦ ⟨2, fun n ↦ le_of_eq_of_le ?_ (?_ : 0 ≤ ENNReal.ofReal ε)⟩ · suffices {x | 2 ≤ ‖densityProcess κ ν n a x s‖₊} = ∅ by simp [this] ext x simp only [mem_setOf_eq, mem_empty_iff_false, iff_false, not_le] refine (?_ : _ ≤ (1 : ℝ≥0)).trans_lt one_lt_two rw [Real.nnnorm_of_nonneg (densityProcess_nonneg _ _ _ _ _ _)] exact mod_cast (densityProcess_le_one hκν _ _ _ _)
· simp lemma tendsto_eLpNorm_one_restrict_densityProcess_limitProcess [IsFiniteKernel ν] (hκν : fst κ ≤ ν) (a : α) {s : Set β} (hs : MeasurableSet s) (A : Set γ) : Tendsto (fun n ↦ eLpNorm ((fun x ↦ densityProcess κ ν n a x s) - (countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 ((ν a).restrict A)) atTop (𝓝 0) := tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds (tendsto_eLpNorm_one_densityProcess_limitProcess hκν a hs) (fun _ ↦ zero_le')
Mathlib/Probability/Kernel/Disintegration/Density.lean
411
419
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison -/ import Mathlib.Algebra.Polynomial.AlgebraMap import Mathlib.RingTheory.IsTensorProduct /-! # Base change of polynomial algebras Given `[CommSemiring R] [Semiring A] [Algebra R A]` we show `A[X] ≃ₐ[R] (A ⊗[R] R[X])`. -/ -- This file should not become entangled with `RingTheory/MatrixAlgebra`. assert_not_exists Matrix universe u v w open Polynomial TensorProduct open Algebra.TensorProduct (algHomOfLinearMapTensorProduct includeLeft) noncomputable section variable (R A : Type*) variable [CommSemiring R] variable [Semiring A] [Algebra R A] namespace PolyEquivTensor /-- (Implementation detail). The function underlying `A ⊗[R] R[X] →ₐ[R] A[X]`, as a bilinear function of two arguments. -/ def toFunBilinear : A →ₗ[A] R[X] →ₗ[R] A[X] := LinearMap.toSpanSingleton A _ (aeval (Polynomial.X : A[X])).toLinearMap theorem toFunBilinear_apply_apply (a : A) (p : R[X]) : toFunBilinear R A a p = a • (aeval X) p := rfl @[simp] theorem toFunBilinear_apply_eq_smul (a : A) (p : R[X]) : toFunBilinear R A a p = a • p.map (algebraMap R A) := rfl theorem toFunBilinear_apply_eq_sum (a : A) (p : R[X]) : toFunBilinear R A a p = p.sum fun n r ↦ monomial n (a * algebraMap R A r) := by conv_lhs => rw [toFunBilinear_apply_eq_smul, ← p.sum_monomial_eq, sum, Polynomial.map_sum] simp [Finset.smul_sum, sum, ← smul_eq_mul] /-- (Implementation detail). The function underlying `A ⊗[R] R[X] →ₐ[R] A[X]`, as a linear map. -/ def toFunLinear : A ⊗[R] R[X] →ₗ[R] A[X] := TensorProduct.lift (toFunBilinear R A) @[simp] theorem toFunLinear_tmul_apply (a : A) (p : R[X]) : toFunLinear R A (a ⊗ₜ[R] p) = toFunBilinear R A a p := rfl -- We apparently need to provide the decidable instance here -- in order to successfully rewrite by this lemma. theorem toFunLinear_mul_tmul_mul_aux_1 (p : R[X]) (k : ℕ) (h : Decidable ¬p.coeff k = 0) (a : A) : ite (¬coeff p k = 0) (a * (algebraMap R A) (coeff p k)) 0 = a * (algebraMap R A) (coeff p k) := by classical split_ifs <;> simp [*] theorem toFunLinear_mul_tmul_mul_aux_2 (k : ℕ) (a₁ a₂ : A) (p₁ p₂ : R[X]) : a₁ * a₂ * (algebraMap R A) ((p₁ * p₂).coeff k) = (Finset.antidiagonal k).sum fun x => a₁ * (algebraMap R A) (coeff p₁ x.1) * (a₂ * (algebraMap R A) (coeff p₂ x.2)) := by simp_rw [mul_assoc, Algebra.commutes, ← Finset.mul_sum, mul_assoc, ← Finset.mul_sum] congr simp_rw [Algebra.commutes (coeff p₂ _), coeff_mul, map_sum, RingHom.map_mul] theorem toFunLinear_mul_tmul_mul (a₁ a₂ : A) (p₁ p₂ : R[X]) : (toFunLinear R A) ((a₁ * a₂) ⊗ₜ[R] (p₁ * p₂)) = (toFunLinear R A) (a₁ ⊗ₜ[R] p₁) * (toFunLinear R A) (a₂ ⊗ₜ[R] p₂) := by classical simp only [toFunLinear_tmul_apply, toFunBilinear_apply_eq_sum] ext k simp_rw [coeff_sum, coeff_monomial, sum_def, Finset.sum_ite_eq', mem_support_iff, Ne] conv_rhs => rw [coeff_mul] simp_rw [finset_sum_coeff, coeff_monomial, Finset.sum_ite_eq', mem_support_iff, Ne, mul_ite, mul_zero, ite_mul, zero_mul] simp_rw [← ite_zero_mul (¬coeff p₁ _ = 0) (a₁ * (algebraMap R A) (coeff p₁ _))] simp_rw [← mul_ite_zero (¬coeff p₂ _ = 0) _ (_ * _)] simp_rw [toFunLinear_mul_tmul_mul_aux_1, toFunLinear_mul_tmul_mul_aux_2] theorem toFunLinear_one_tmul_one : toFunLinear R A (1 ⊗ₜ[R] 1) = 1 := by rw [toFunLinear_tmul_apply, toFunBilinear_apply_apply, Polynomial.aeval_one, one_smul] /-- (Implementation detail). The algebra homomorphism `A ⊗[R] R[X] →ₐ[R] A[X]`. -/ def toFunAlgHom : A ⊗[R] R[X] →ₐ[R] A[X] := algHomOfLinearMapTensorProduct (toFunLinear R A) (toFunLinear_mul_tmul_mul R A) (toFunLinear_one_tmul_one R A) @[simp] theorem toFunAlgHom_apply_tmul_eq_smul (a : A) (p : R[X]) : toFunAlgHom R A (a ⊗ₜ[R] p) = a • p.map (algebraMap R A) := rfl theorem toFunAlgHom_apply_tmul (a : A) (p : R[X]) : toFunAlgHom R A (a ⊗ₜ[R] p) = p.sum fun n r => monomial n (a * (algebraMap R A) r) := toFunBilinear_apply_eq_sum R A _ _ /-- (Implementation detail.) The bare function `A[X] → A ⊗[R] R[X]`. (We don't need to show that it's an algebra map, thankfully --- just that it's an inverse.) -/ def invFun (p : A[X]) : A ⊗[R] R[X] := p.eval₂ (includeLeft : A →ₐ[R] A ⊗[R] R[X]) ((1 : A) ⊗ₜ[R] (X : R[X])) @[simp] theorem invFun_add {p q} : invFun R A (p + q) = invFun R A p + invFun R A q := by simp only [invFun, eval₂_add] theorem invFun_monomial (n : ℕ) (a : A) : invFun R A (monomial n a) = (a ⊗ₜ[R] 1) * 1 ⊗ₜ[R] X ^ n := eval₂_monomial _ _ theorem left_inv (x : A ⊗ R[X]) : invFun R A ((toFunAlgHom R A) x) = x := by refine TensorProduct.induction_on x ?_ ?_ ?_ · simp [invFun] · intro a p dsimp only [invFun] rw [toFunAlgHom_apply_tmul, eval₂_sum] simp_rw [eval₂_monomial, AlgHom.coe_toRingHom, Algebra.TensorProduct.tmul_pow, one_pow, Algebra.TensorProduct.includeLeft_apply, Algebra.TensorProduct.tmul_mul_tmul, mul_one, one_mul, ← Algebra.commutes, ← Algebra.smul_def, smul_tmul, sum_def, ← tmul_sum] conv_rhs => rw [← sum_C_mul_X_pow_eq p] simp only [Algebra.smul_def] rfl · intro p q hp hq simp only [map_add, invFun_add, hp, hq] theorem right_inv (x : A[X]) : (toFunAlgHom R A) (invFun R A x) = x := by refine Polynomial.induction_on' x ?_ ?_ · intro p q hp hq simp only [invFun_add, map_add, hp, hq] · intro n a rw [invFun_monomial, Algebra.TensorProduct.tmul_pow, one_pow, Algebra.TensorProduct.tmul_mul_tmul, mul_one, one_mul, toFunAlgHom_apply_tmul, X_pow_eq_monomial, sum_monomial_index] <;> simp /-- (Implementation detail) The equivalence, ignoring the algebra structure, `(A ⊗[R] R[X]) ≃ A[X]`. -/ def equiv : A ⊗[R] R[X] ≃ A[X] where toFun := toFunAlgHom R A invFun := invFun R A left_inv := left_inv R A right_inv := right_inv R A end PolyEquivTensor open PolyEquivTensor /-- The `R`-algebra isomorphism `A[X] ≃ₐ[R] (A ⊗[R] R[X])`. -/ def polyEquivTensor : A[X] ≃ₐ[R] A ⊗[R] R[X] := AlgEquiv.symm { PolyEquivTensor.toFunAlgHom R A, PolyEquivTensor.equiv R A with } @[simp] theorem polyEquivTensor_apply (p : A[X]) : polyEquivTensor R A p = p.eval₂ (includeLeft : A →ₐ[R] A ⊗[R] R[X]) ((1 : A) ⊗ₜ[R] (X : R[X])) := rfl @[simp] theorem polyEquivTensor_symm_apply_tmul_eq_smul (a : A) (p : R[X]) : (polyEquivTensor R A).symm (a ⊗ₜ p) = a • p.map (algebraMap R A) := rfl theorem polyEquivTensor_symm_apply_tmul (a : A) (p : R[X]) : (polyEquivTensor R A).symm (a ⊗ₜ p) = p.sum fun n r => monomial n (a * algebraMap R A r) := toFunAlgHom_apply_tmul _ _ _ _ section variable (A : Type*) [CommSemiring A] [Algebra R A] /-- The `A`-algebra isomorphism `A[X] ≃ₐ[A] A ⊗[R] R[X]` (when `A` is commutative). -/ def polyEquivTensor' : A[X] ≃ₐ[A] A ⊗[R] R[X] where __ := polyEquivTensor R A commutes' a := by simp /-- `polyEquivTensor' R A` is the same as `polyEquivTensor R A` as a function. -/ @[simp] theorem coe_polyEquivTensor' : ⇑(polyEquivTensor' R A) = polyEquivTensor R A := rfl @[simp] theorem coe_polyEquivTensor'_symm : ⇑(polyEquivTensor' R A).symm = (polyEquivTensor R A).symm := rfl end /-- If `A` is an `R`-algebra, then `A[X]` is an `R[X]` algebra. This gives a diamond for `Algebra R[X] R[X][X]`, so this is not a global instance. -/ @[reducible] def Polynomial.algebra : Algebra R[X] A[X] := (mapRingHom (algebraMap R A)).toAlgebra' fun _ _ ↦ by ext; rw [coeff_mul, ← Finset.Nat.sum_antidiagonal_swap, coeff_mul]; simp [Algebra.commutes] attribute [local instance] Polynomial.algebra @[simp] theorem Polynomial.algebraMap_def : algebraMap R[X] A[X] = mapRingHom (algebraMap R A) := rfl instance : IsScalarTower R R[X] A[X] := .of_algebraMap_eq' (mapRingHom_comp_C _).symm instance [FaithfulSMul R A] : FaithfulSMul R[X] A[X] := (faithfulSMul_iff_algebraMap_injective ..).mpr (map_injective _ <| FaithfulSMul.algebraMap_injective ..) variable {S : Type*} [CommSemiring S] [Algebra R S] instance : Algebra.IsPushout R S R[X] S[X] where out := .of_equiv (polyEquivTensor' R S).symm fun _ ↦ (polyEquivTensor_symm_apply_tmul_eq_smul ..).trans <| one_smul .. instance : Algebra.IsPushout R R[X] S S[X] := .symm inferInstance
Mathlib/RingTheory/PolynomialAlgebra.lean
238
240
/- Copyright (c) 2017 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot, Kim Morrison, Mario Carneiro, Andrew Yang -/ import Mathlib.Topology.Category.TopCat.Limits.Products /-! # Pullbacks and pushouts in the category of topological spaces -/ open TopologicalSpace Topology open CategoryTheory open CategoryTheory.Limits universe v u w noncomputable section namespace TopCat variable {J : Type v} [Category.{w} J] section Pullback variable {X Y Z : TopCat.{u}} /-- The first projection from the pullback. -/ abbrev pullbackFst (f : X ⟶ Z) (g : Y ⟶ Z) : TopCat.of { p : X × Y // f p.1 = g p.2 } ⟶ X := ofHom ⟨Prod.fst ∘ Subtype.val, by fun_prop⟩ lemma pullbackFst_apply (f : X ⟶ Z) (g : Y ⟶ Z) (x) : pullbackFst f g x = x.1.1 := rfl /-- The second projection from the pullback. -/ abbrev pullbackSnd (f : X ⟶ Z) (g : Y ⟶ Z) : TopCat.of { p : X × Y // f p.1 = g p.2 } ⟶ Y := ofHom ⟨Prod.snd ∘ Subtype.val, by fun_prop⟩ lemma pullbackSnd_apply (f : X ⟶ Z) (g : Y ⟶ Z) (x) : pullbackSnd f g x = x.1.2 := rfl /-- The explicit pullback cone of `X, Y` given by `{ p : X × Y // f p.1 = g p.2 }`. -/ def pullbackCone (f : X ⟶ Z) (g : Y ⟶ Z) : PullbackCone f g := PullbackCone.mk (pullbackFst f g) (pullbackSnd f g) (by dsimp [pullbackFst, pullbackSnd, Function.comp_def] ext ⟨x, h⟩ simpa) /-- The constructed cone is a limit. -/ def pullbackConeIsLimit (f : X ⟶ Z) (g : Y ⟶ Z) : IsLimit (pullbackCone f g) := PullbackCone.isLimitAux' _ (by intro S constructor; swap · exact ofHom { toFun := fun x => ⟨⟨S.fst x, S.snd x⟩, by simpa using ConcreteCategory.congr_hom S.condition x⟩ continuous_toFun := by fun_prop } refine ⟨?_, ?_, ?_⟩ · delta pullbackCone ext a dsimp · delta pullbackCone ext a dsimp · intro m h₁ h₂ ext x -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11041): used to be `ext x`. apply Subtype.ext apply Prod.ext · simpa using ConcreteCategory.congr_hom h₁ x · simpa using ConcreteCategory.congr_hom h₂ x) /-- The pullback of two maps can be identified as a subspace of `X × Y`. -/ def pullbackIsoProdSubtype (f : X ⟶ Z) (g : Y ⟶ Z) : pullback f g ≅ TopCat.of { p : X × Y // f p.1 = g p.2 } := (limit.isLimit _).conePointUniqueUpToIso (pullbackConeIsLimit f g) @[reassoc (attr := simp)] theorem pullbackIsoProdSubtype_inv_fst (f : X ⟶ Z) (g : Y ⟶ Z) : (pullbackIsoProdSubtype f g).inv ≫ pullback.fst _ _ = pullbackFst f g := by simp [pullbackCone, pullbackIsoProdSubtype] theorem pullbackIsoProdSubtype_inv_fst_apply (f : X ⟶ Z) (g : Y ⟶ Z) (x : { p : X × Y // f p.1 = g p.2 }) : pullback.fst f g ((pullbackIsoProdSubtype f g).inv x) = (x : X × Y).fst := ConcreteCategory.congr_hom (pullbackIsoProdSubtype_inv_fst f g) x @[reassoc (attr := simp)] theorem pullbackIsoProdSubtype_inv_snd (f : X ⟶ Z) (g : Y ⟶ Z) : (pullbackIsoProdSubtype f g).inv ≫ pullback.snd _ _ = pullbackSnd f g := by simp [pullbackCone, pullbackIsoProdSubtype] theorem pullbackIsoProdSubtype_inv_snd_apply (f : X ⟶ Z) (g : Y ⟶ Z) (x : { p : X × Y // f p.1 = g p.2 }) : pullback.snd f g ((pullbackIsoProdSubtype f g).inv x) = (x : X × Y).snd := ConcreteCategory.congr_hom (pullbackIsoProdSubtype_inv_snd f g) x theorem pullbackIsoProdSubtype_hom_fst (f : X ⟶ Z) (g : Y ⟶ Z) : (pullbackIsoProdSubtype f g).hom ≫ pullbackFst f g = pullback.fst _ _ := by rw [← Iso.eq_inv_comp, pullbackIsoProdSubtype_inv_fst] theorem pullbackIsoProdSubtype_hom_snd (f : X ⟶ Z) (g : Y ⟶ Z) : (pullbackIsoProdSubtype f g).hom ≫ pullbackSnd f g = pullback.snd _ _ := by rw [← Iso.eq_inv_comp, pullbackIsoProdSubtype_inv_snd] theorem pullbackIsoProdSubtype_hom_apply {f : X ⟶ Z} {g : Y ⟶ Z} (x : ↑(pullback f g)) : (pullbackIsoProdSubtype f g).hom x = ⟨⟨pullback.fst f g x, pullback.snd f g x⟩, by simpa using CategoryTheory.congr_fun pullback.condition x⟩ := by apply Subtype.ext; apply Prod.ext exacts [ConcreteCategory.congr_hom (pullbackIsoProdSubtype_hom_fst f g) x, ConcreteCategory.congr_hom (pullbackIsoProdSubtype_hom_snd f g) x] theorem pullback_topology {X Y Z : TopCat.{u}} (f : X ⟶ Z) (g : Y ⟶ Z) : (pullback f g).str = induced (pullback.fst f g) X.str ⊓ induced (pullback.snd f g) Y.str := by let homeo := homeoOfIso (pullbackIsoProdSubtype f g) refine homeo.isInducing.eq_induced.trans ?_ change induced homeo (induced _ ( (induced Prod.fst X.str) ⊓ (induced Prod.snd Y.str))) = _ simp only [induced_compose, induced_inf] congr theorem range_pullback_to_prod {X Y Z : TopCat} (f : X ⟶ Z) (g : Y ⟶ Z) : Set.range (prod.lift (pullback.fst f g) (pullback.snd f g)) = { x | (Limits.prod.fst ≫ f) x = (Limits.prod.snd ≫ g) x } := by ext x constructor · rintro ⟨y, rfl⟩ simp only [← ConcreteCategory.comp_apply, Set.mem_setOf_eq] simp [pullback.condition] · rintro (h : f (_, _).1 = g (_, _).2) use (pullbackIsoProdSubtype f g).inv ⟨⟨_, _⟩, h⟩ apply Concrete.limit_ext rintro ⟨⟨⟩⟩ <;> rw [← ConcreteCategory.comp_apply, ← ConcreteCategory.comp_apply, limit.lift_π] <;> -- This used to be `simp` before https://github.com/leanprover/lean4/pull/2644 aesop_cat /-- The pullback along an embedding is (isomorphic to) the preimage. -/ noncomputable def pullbackHomeoPreimage {X Y Z : Type*} [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] (f : X → Z) (hf : Continuous f) (g : Y → Z) (hg : IsEmbedding g) : { p : X × Y // f p.1 = g p.2 } ≃ₜ f ⁻¹' Set.range g where toFun := fun x ↦ ⟨x.1.1, _, x.2.symm⟩ invFun := fun x ↦ ⟨⟨x.1, Exists.choose x.2⟩, (Exists.choose_spec x.2).symm⟩ left_inv := by intro x ext <;> dsimp apply hg.injective convert x.prop exact Exists.choose_spec (p := fun y ↦ g y = f (↑x : X × Y).1) _ right_inv := fun _ ↦ rfl continuous_toFun := by fun_prop continuous_invFun := by apply Continuous.subtype_mk refine continuous_subtype_val.prodMk <| hg.isInducing.continuous_iff.mpr ?_ convert hf.comp continuous_subtype_val ext x exact Exists.choose_spec x.2 theorem isInducing_pullback_to_prod {X Y Z : TopCat.{u}} (f : X ⟶ Z) (g : Y ⟶ Z) : IsInducing <| ⇑(prod.lift (pullback.fst f g) (pullback.snd f g)) := ⟨by simp [prod_topology, pullback_topology, induced_compose, ← coe_comp]⟩ @[deprecated (since := "2024-10-28")] alias inducing_pullback_to_prod := isInducing_pullback_to_prod theorem isEmbedding_pullback_to_prod {X Y Z : TopCat.{u}} (f : X ⟶ Z) (g : Y ⟶ Z) : IsEmbedding <| ⇑(prod.lift (pullback.fst f g) (pullback.snd f g)) := ⟨isInducing_pullback_to_prod f g, (TopCat.mono_iff_injective _).mp inferInstance⟩ @[deprecated (since := "2024-10-26")] alias embedding_pullback_to_prod := isEmbedding_pullback_to_prod /-- If the map `S ⟶ T` is mono, then there is a description of the image of `W ×ₛ X ⟶ Y ×ₜ Z`. -/ theorem range_pullback_map {W X Y Z S T : TopCat} (f₁ : W ⟶ S) (f₂ : X ⟶ S) (g₁ : Y ⟶ T) (g₂ : Z ⟶ T) (i₁ : W ⟶ Y) (i₂ : X ⟶ Z) (i₃ : S ⟶ T) [H₃ : Mono i₃] (eq₁ : f₁ ≫ i₃ = i₁ ≫ g₁) (eq₂ : f₂ ≫ i₃ = i₂ ≫ g₂) : Set.range (pullback.map f₁ f₂ g₁ g₂ i₁ i₂ i₃ eq₁ eq₂) = (pullback.fst g₁ g₂) ⁻¹' Set.range i₁ ∩ (pullback.snd g₁ g₂) ⁻¹' Set.range i₂ := by ext constructor · rintro ⟨y, rfl⟩ simp only [Set.mem_inter_iff, Set.mem_preimage, Set.mem_range] rw [← ConcreteCategory.comp_apply, ← ConcreteCategory.comp_apply] simp only [limit.lift_π, PullbackCone.mk_pt, PullbackCone.mk_π_app] exact ⟨exists_apply_eq_apply _ _, exists_apply_eq_apply _ _⟩ rintro ⟨⟨x₁, hx₁⟩, ⟨x₂, hx₂⟩⟩ have : f₁ x₁ = f₂ x₂ := by apply (TopCat.mono_iff_injective _).mp H₃ rw [← ConcreteCategory.comp_apply, eq₁, ← ConcreteCategory.comp_apply, eq₂, ConcreteCategory.comp_apply, ConcreteCategory.comp_apply, hx₁, hx₂, ← ConcreteCategory.comp_apply, pullback.condition, ConcreteCategory.comp_apply] use (pullbackIsoProdSubtype f₁ f₂).inv ⟨⟨x₁, x₂⟩, this⟩ apply Concrete.limit_ext rintro (_ | _ | _) <;> rw [← ConcreteCategory.comp_apply, ← ConcreteCategory.comp_apply] · simp [hx₁, ← limit.w _ WalkingCospan.Hom.inl] · simp [hx₁] · simp [hx₂] theorem pullback_fst_range {X Y S : TopCat} (f : X ⟶ S) (g : Y ⟶ S) : Set.range (pullback.fst f g) = { x : X | ∃ y : Y, f x = g y } := by ext x constructor · rintro ⟨y, rfl⟩ use pullback.snd f g y exact CategoryTheory.congr_fun pullback.condition y · rintro ⟨y, eq⟩ use (TopCat.pullbackIsoProdSubtype f g).inv ⟨⟨x, y⟩, eq⟩ rw [pullbackIsoProdSubtype_inv_fst_apply] theorem pullback_snd_range {X Y S : TopCat} (f : X ⟶ S) (g : Y ⟶ S) : Set.range (pullback.snd f g) = { y : Y | ∃ x : X, f x = g y } := by ext y constructor · rintro ⟨x, rfl⟩ use pullback.fst f g x exact CategoryTheory.congr_fun pullback.condition x · rintro ⟨x, eq⟩ use (TopCat.pullbackIsoProdSubtype f g).inv ⟨⟨x, y⟩, eq⟩ rw [pullbackIsoProdSubtype_inv_snd_apply] /-- If there is a diagram where the morphisms `W ⟶ Y` and `X ⟶ Z` are embeddings, then the induced morphism `W ×ₛ X ⟶ Y ×ₜ Z` is also an embedding. ``` W ⟶ Y ↘ ↘ S ⟶ T ↗ ↗ X ⟶ Z ``` -/ theorem pullback_map_isEmbedding {W X Y Z S T : TopCat.{u}} (f₁ : W ⟶ S) (f₂ : X ⟶ S) (g₁ : Y ⟶ T) (g₂ : Z ⟶ T) {i₁ : W ⟶ Y} {i₂ : X ⟶ Z} (H₁ : IsEmbedding i₁) (H₂ : IsEmbedding i₂) (i₃ : S ⟶ T) (eq₁ : f₁ ≫ i₃ = i₁ ≫ g₁) (eq₂ : f₂ ≫ i₃ = i₂ ≫ g₂) : IsEmbedding (pullback.map f₁ f₂ g₁ g₂ i₁ i₂ i₃ eq₁ eq₂) := by refine .of_comp (ContinuousMap.continuous_toFun _) (show Continuous (prod.lift (pullback.fst g₁ g₂) (pullback.snd g₁ g₂)) from ContinuousMap.continuous_toFun _) ?_ suffices IsEmbedding (prod.lift (pullback.fst f₁ f₂) (pullback.snd f₁ f₂) ≫ Limits.prod.map i₁ i₂) by simpa [← coe_comp] using this rw [coe_comp] exact (isEmbedding_prodMap H₁ H₂).comp (isEmbedding_pullback_to_prod _ _) @[deprecated (since := "2024-10-26")] alias pullback_map_embedding_of_embeddings := pullback_map_isEmbedding /-- If there is a diagram where the morphisms `W ⟶ Y` and `X ⟶ Z` are open embeddings, and `S ⟶ T` is mono, then the induced morphism `W ×ₛ X ⟶ Y ×ₜ Z` is also an open embedding. ``` W ⟶ Y ↘ ↘ S ⟶ T ↗ ↗ X ⟶ Z ``` -/ theorem pullback_map_isOpenEmbedding {W X Y Z S T : TopCat.{u}} (f₁ : W ⟶ S) (f₂ : X ⟶ S) (g₁ : Y ⟶ T) (g₂ : Z ⟶ T) {i₁ : W ⟶ Y} {i₂ : X ⟶ Z} (H₁ : IsOpenEmbedding i₁) (H₂ : IsOpenEmbedding i₂) (i₃ : S ⟶ T) [H₃ : Mono i₃] (eq₁ : f₁ ≫ i₃ = i₁ ≫ g₁) (eq₂ : f₂ ≫ i₃ = i₂ ≫ g₂) : IsOpenEmbedding (pullback.map f₁ f₂ g₁ g₂ i₁ i₂ i₃ eq₁ eq₂) := by constructor · apply pullback_map_isEmbedding f₁ f₂ g₁ g₂ H₁.isEmbedding H₂.isEmbedding i₃ eq₁ eq₂ · rw [range_pullback_map] apply IsOpen.inter <;> apply Continuous.isOpen_preimage · apply ContinuousMap.continuous_toFun · exact H₁.isOpen_range · apply ContinuousMap.continuous_toFun · exact H₂.isOpen_range lemma snd_isEmbedding_of_left {X Y S : TopCat} {f : X ⟶ S} (H : IsEmbedding f) (g : Y ⟶ S) : IsEmbedding <| ⇑(pullback.snd f g) := by convert (homeoOfIso (asIso (pullback.snd (𝟙 S) g))).isEmbedding.comp (pullback_map_isEmbedding (i₂ := 𝟙 Y) f g (𝟙 S) g H (homeoOfIso (Iso.refl _)).isEmbedding (𝟙 _) rfl (by simp)) simp [homeoOfIso, ← coe_comp] @[deprecated (since := "2024-10-26")] alias snd_embedding_of_left_embedding := snd_isEmbedding_of_left theorem fst_isEmbedding_of_right {X Y S : TopCat} (f : X ⟶ S) {g : Y ⟶ S} (H : IsEmbedding g) : IsEmbedding <| ⇑(pullback.fst f g) := by convert (homeoOfIso (asIso (pullback.fst f (𝟙 S)))).isEmbedding.comp (pullback_map_isEmbedding (i₁ := 𝟙 X) f g f (𝟙 _) (homeoOfIso (Iso.refl _)).isEmbedding H (𝟙 _) rfl (by simp)) simp [homeoOfIso, ← coe_comp] @[deprecated (since := "2024-10-26")] alias fst_embedding_of_right_embedding := fst_isEmbedding_of_right theorem isEmbedding_of_pullback {X Y S : TopCat} {f : X ⟶ S} {g : Y ⟶ S} (H₁ : IsEmbedding f) (H₂ : IsEmbedding g) : IsEmbedding (limit.π (cospan f g) WalkingCospan.one) := by convert H₂.comp (snd_isEmbedding_of_left H₁ g) rw [← coe_comp, ← limit.w _ WalkingCospan.Hom.inr] rfl
@[deprecated (since := "2024-10-26")] alias embedding_of_pullback_embeddings := isEmbedding_of_pullback theorem snd_isOpenEmbedding_of_left {X Y S : TopCat} {f : X ⟶ S} (H : IsOpenEmbedding f) (g : Y ⟶ S) : IsOpenEmbedding <| ⇑(pullback.snd f g) := by convert (homeoOfIso (asIso (pullback.snd (𝟙 S) g))).isOpenEmbedding.comp (pullback_map_isOpenEmbedding (i₂ := 𝟙 Y) f g (𝟙 _) g H (homeoOfIso (Iso.refl _)).isOpenEmbedding (𝟙 _) rfl (by simp)) simp [homeoOfIso, ← coe_comp] theorem fst_isOpenEmbedding_of_right {X Y S : TopCat} (f : X ⟶ S) {g : Y ⟶ S} (H : IsOpenEmbedding g) : IsOpenEmbedding <| ⇑(pullback.fst f g) := by
Mathlib/Topology/Category/TopCat/Limits/Pullbacks.lean
307
319
/- Copyright (c) 2019 Riccardo Brasca. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Riccardo Brasca, Paul Lezeau, Junyan Xu -/ import Mathlib.RingTheory.AdjoinRoot import Mathlib.FieldTheory.Minpoly.Field import Mathlib.RingTheory.Polynomial.GaussLemma /-! # Minimal polynomials over a GCD monoid This file specializes the theory of minpoly to the case of an algebra over a GCD monoid. ## Main results * `minpoly.isIntegrallyClosed_eq_field_fractions`: For integrally closed domains, the minimal polynomial over the ring is the same as the minimal polynomial over the fraction field. * `minpoly.isIntegrallyClosed_dvd` : For integrally closed domains, the minimal polynomial divides any primitive polynomial that has the integral element as root. * `IsIntegrallyClosed.Minpoly.unique` : The minimal polynomial of an element `x` is uniquely characterized by its defining property: if there is another monic polynomial of minimal degree that has `x` as a root, then this polynomial is equal to the minimal polynomial of `x`. -/ open Polynomial Set Function minpoly namespace minpoly variable {R S : Type*} [CommRing R] [CommRing S] [IsDomain R] [Algebra R S] section variable (K L : Type*) [Field K] [Algebra R K] [IsFractionRing R K] [CommRing L] [Nontrivial L] [Algebra R L] [Algebra S L] [Algebra K L] [IsScalarTower R K L] [IsScalarTower R S L] variable [IsIntegrallyClosed R] /-- For integrally closed domains, the minimal polynomial over the ring is the same as the minimal polynomial over the fraction field. See `minpoly.isIntegrallyClosed_eq_field_fractions'` if `S` is already a `K`-algebra. -/ theorem isIntegrallyClosed_eq_field_fractions [IsDomain S] {s : S} (hs : IsIntegral R s) : minpoly K (algebraMap S L s) = (minpoly R s).map (algebraMap R K) := by refine (eq_of_irreducible_of_monic ?_ ?_ ?_).symm · exact ((monic hs).irreducible_iff_irreducible_map_fraction_map).1 (irreducible hs) · rw [aeval_map_algebraMap, aeval_algebraMap_apply, aeval, map_zero]
· exact (monic hs).map _ /-- For integrally closed domains, the minimal polynomial over the ring is the same as the minimal polynomial over the fraction field. Compared to `minpoly.isIntegrallyClosed_eq_field_fractions`, this version is useful if the element is in a ring that is already a `K`-algebra. -/ theorem isIntegrallyClosed_eq_field_fractions' [IsDomain S] [Algebra K S] [IsScalarTower R K S]
Mathlib/FieldTheory/Minpoly/IsIntegrallyClosed.lean
50
55
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Yakov Pechersky, Eric Wieser -/ import Mathlib.Data.List.Basic /-! # Properties of `List.enum` ## Deprecation note Many lemmas in this file have been replaced by theorems in Lean4, in terms of `xs[i]?` and `xs[i]` rather than `get` and `get?`. The deprecated results here are unused in Mathlib. Any downstream users who can not easily adapt may remove the deprecations as needed. -/ namespace List variable {α : Type*} theorem forall_mem_zipIdx {l : List α} {n : ℕ} {p : α × ℕ → Prop} : (∀ x ∈ l.zipIdx n, p x) ↔ ∀ (i : ℕ) (_ : i < length l), p (l[i], n + i) := by simp only [forall_mem_iff_getElem, getElem_zipIdx, length_zipIdx]
/-- Variant of `forall_mem_zipIdx` with the `zipIdx` argument specialized to `0`. -/ theorem forall_mem_zipIdx' {l : List α} {p : α × ℕ → Prop} : (∀ x ∈ l.zipIdx, p x) ↔ ∀ (i : ℕ) (_ : i < length l), p (l[i], i) :=
Mathlib/Data/List/Enum.lean
28
30
/- Copyright (c) 2022 María Inés de Frutos-Fernández. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Chambert-Loir, María Inés de Frutos-Fernández -/ import Mathlib.Algebra.BigOperators.Finprod import Mathlib.Algebra.DirectSum.Decomposition import Mathlib.Algebra.GradedMonoid import Mathlib.Algebra.MvPolynomial.Basic import Mathlib.Algebra.Order.Monoid.Canonical.Defs import Mathlib.Data.Finsupp.Weight import Mathlib.RingTheory.GradedAlgebra.Basic /-! # Weighted homogeneous polynomials It is possible to assign weights (in a commutative additive monoid `M`) to the variables of a multivariate polynomial ring, so that monomials of the ring then have a weighted degree with respect to the weights of the variables. The weights are represented by a function `w : σ → M`, where `σ` are the indeterminates. A multivariate polynomial `φ` is weighted homogeneous of weighted degree `m : M` if all monomials occurring in `φ` have the same weighted degree `m`. ## Main definitions/lemmas * `weightedTotalDegree' w φ` : the weighted total degree of a multivariate polynomial with respect to the weights `w`, taking values in `WithBot M`. * `weightedTotalDegree w φ` : When `M` has a `⊥` element, we can define the weighted total degree of a multivariate polynomial as a function taking values in `M`. * `IsWeightedHomogeneous w φ m`: a predicate that asserts that `φ` is weighted homogeneous of weighted degree `m` with respect to the weights `w`. * `weightedHomogeneousSubmodule R w m`: the submodule of homogeneous polynomials of weighted degree `m`. * `weightedHomogeneousComponent w m`: the additive morphism that projects polynomials onto their summand that is weighted homogeneous of degree `n` with respect to `w`. * `sum_weightedHomogeneousComponent`: every polynomial is the sum of its weighted homogeneous components. -/ noncomputable section open Set Function Finset Finsupp AddMonoidAlgebra variable {R M : Type*} [CommSemiring R] namespace MvPolynomial variable {σ : Type*} section AddCommMonoid variable [AddCommMonoid M] /-! ### `weight` -/ section SemilatticeSup variable [SemilatticeSup M] /-- The weighted total degree of a multivariate polynomial, taking values in `WithBot M`. -/ def weightedTotalDegree' (w : σ → M) (p : MvPolynomial σ R) : WithBot M := p.support.sup fun s => weight w s /-- The `weightedTotalDegree'` of a polynomial `p` is `⊥` if and only if `p = 0`. -/ theorem weightedTotalDegree'_eq_bot_iff (w : σ → M) (p : MvPolynomial σ R) : weightedTotalDegree' w p = ⊥ ↔ p = 0 := by simp only [weightedTotalDegree', Finset.sup_eq_bot_iff, mem_support_iff, WithBot.coe_ne_bot, MvPolynomial.eq_zero_iff] exact forall_congr' fun _ => Classical.not_not /-- The `weightedTotalDegree'` of the zero polynomial is `⊥`. -/ theorem weightedTotalDegree'_zero (w : σ → M) : weightedTotalDegree' w (0 : MvPolynomial σ R) = ⊥ := by simp only [weightedTotalDegree', support_zero, Finset.sup_empty] section OrderBot variable [OrderBot M] /-- When `M` has a `⊥` element, we can define the weighted total degree of a multivariate polynomial as a function taking values in `M`. -/ def weightedTotalDegree (w : σ → M) (p : MvPolynomial σ R) : M := p.support.sup fun s => weight w s /-- This lemma relates `weightedTotalDegree` and `weightedTotalDegree'`. -/ theorem weightedTotalDegree_coe (w : σ → M) (p : MvPolynomial σ R) (hp : p ≠ 0) : weightedTotalDegree' w p = ↑(weightedTotalDegree w p) := by rw [Ne, ← weightedTotalDegree'_eq_bot_iff w p, ← Ne, WithBot.ne_bot_iff_exists] at hp obtain ⟨m, hm⟩ := hp apply le_antisymm · simp only [weightedTotalDegree, weightedTotalDegree', Finset.sup_le_iff, WithBot.coe_le_coe] intro b exact Finset.le_sup · simp only [weightedTotalDegree] have hm' : weightedTotalDegree' w p ≤ m := le_of_eq hm.symm rw [← hm] simpa [weightedTotalDegree'] using hm' /-- The `weightedTotalDegree` of the zero polynomial is `⊥`. -/ theorem weightedTotalDegree_zero (w : σ → M) : weightedTotalDegree w (0 : MvPolynomial σ R) = ⊥ := by simp only [weightedTotalDegree, support_zero, Finset.sup_empty] theorem le_weightedTotalDegree (w : σ → M) {φ : MvPolynomial σ R} {d : σ →₀ ℕ} (hd : d ∈ φ.support) : weight w d ≤ φ.weightedTotalDegree w := le_sup hd end OrderBot end SemilatticeSup /-- A multivariate polynomial `φ` is weighted homogeneous of weighted degree `m` if all monomials occurring in `φ` have weighted degree `m`. -/ def IsWeightedHomogeneous (w : σ → M) (φ : MvPolynomial σ R) (m : M) : Prop := ∀ ⦃d⦄, coeff d φ ≠ 0 → weight w d = m variable (R) /-- The submodule of homogeneous `MvPolynomial`s of degree `n`. -/ def weightedHomogeneousSubmodule (w : σ → M) (m : M) : Submodule R (MvPolynomial σ R) where carrier := { x | x.IsWeightedHomogeneous w m } smul_mem' r a ha c hc := by rw [coeff_smul] at hc exact ha (right_ne_zero_of_mul hc) zero_mem' _ hd := False.elim (hd <| coeff_zero _) add_mem' {a} {b} ha hb c hc := by rw [coeff_add] at hc obtain h | h : coeff c a ≠ 0 ∨ coeff c b ≠ 0 := by contrapose! hc simp only [hc, add_zero] · exact ha h · exact hb h @[simp] theorem mem_weightedHomogeneousSubmodule (w : σ → M) (m : M) (p : MvPolynomial σ R) : p ∈ weightedHomogeneousSubmodule R w m ↔ p.IsWeightedHomogeneous w m := Iff.rfl /-- The submodule `weightedHomogeneousSubmodule R w m` of homogeneous `MvPolynomial`s of degree `n` is equal to the `R`-submodule of all `p : (σ →₀ ℕ) →₀ R` such that `p.support ⊆ {d | weight w d = m}`. While equal, the former has a convenient definitional reduction. -/ theorem weightedHomogeneousSubmodule_eq_finsupp_supported (w : σ → M) (m : M) : weightedHomogeneousSubmodule R w m = Finsupp.supported R R { d | weight w d = m } := by ext x rw [mem_supported, Set.subset_def] simp only [Finsupp.mem_support_iff, mem_coe] rfl variable {R} /-- The submodule generated by products `Pm * Pn` of weighted homogeneous polynomials of degrees `m` and `n` is contained in the submodule of weighted homogeneous polynomials of degree `m + n`. -/ theorem weightedHomogeneousSubmodule_mul (w : σ → M) (m n : M) : weightedHomogeneousSubmodule R w m * weightedHomogeneousSubmodule R w n ≤ weightedHomogeneousSubmodule R w (m + n) := by classical rw [Submodule.mul_le] intro φ hφ ψ hψ c hc rw [coeff_mul] at hc obtain ⟨⟨d, e⟩, hde, H⟩ := Finset.exists_ne_zero_of_sum_ne_zero hc have aux : coeff d φ ≠ 0 ∧ coeff e ψ ≠ 0 := by contrapose! H by_cases h : coeff d φ = 0 <;> simp_all only [Ne, not_false_iff, zero_mul, mul_zero] rw [← mem_antidiagonal.mp hde, ← hφ aux.1, ← hψ aux.2, map_add] /-- Monomials are weighted homogeneous. -/ theorem isWeightedHomogeneous_monomial (w : σ → M) (d : σ →₀ ℕ) (r : R) {m : M} (hm : weight w d = m) : IsWeightedHomogeneous w (monomial d r) m := by classical intro c hc rw [coeff_monomial] at hc split_ifs at hc with h · subst c exact hm · contradiction /-- A polynomial of weightedTotalDegree `⊥` is weighted_homogeneous of degree `⊥`. -/ theorem isWeightedHomogeneous_of_total_degree_zero [SemilatticeSup M] [OrderBot M] (w : σ → M) {p : MvPolynomial σ R} (hp : weightedTotalDegree w p = (⊥ : M)) : IsWeightedHomogeneous w p (⊥ : M) := by intro d hd have h := weightedTotalDegree_coe w p (MvPolynomial.ne_zero_iff.mpr ⟨d, hd⟩) simp only [weightedTotalDegree', hp] at h rw [eq_bot_iff, ← WithBot.coe_le_coe, ← h] apply Finset.le_sup (mem_support_iff.mpr hd) /-- Constant polynomials are weighted homogeneous of degree 0. -/ theorem isWeightedHomogeneous_C (w : σ → M) (r : R) : IsWeightedHomogeneous w (C r : MvPolynomial σ R) 0 := isWeightedHomogeneous_monomial _ _ _ (map_zero _) variable (R) /-- 0 is weighted homogeneous of any degree. -/ theorem isWeightedHomogeneous_zero (w : σ → M) (m : M) : IsWeightedHomogeneous w (0 : MvPolynomial σ R) m := (weightedHomogeneousSubmodule R w m).zero_mem /-- 1 is weighted homogeneous of degree 0. -/ theorem isWeightedHomogeneous_one (w : σ → M) : IsWeightedHomogeneous w (1 : MvPolynomial σ R) 0 := isWeightedHomogeneous_C _ _ /-- An indeterminate `i : σ` is weighted homogeneous of degree `w i`. -/ theorem isWeightedHomogeneous_X (w : σ → M) (i : σ) : IsWeightedHomogeneous w (X i : MvPolynomial σ R) (w i) := by apply isWeightedHomogeneous_monomial simp only [weight, LinearMap.toAddMonoidHom_coe, linearCombination_single, one_nsmul] namespace IsWeightedHomogeneous variable {R} variable {φ ψ : MvPolynomial σ R} {m n : M} /-- The weighted degree of a weighted homogeneous polynomial controls its support. -/ theorem coeff_eq_zero {w : σ → M} (hφ : IsWeightedHomogeneous w φ n) (d : σ →₀ ℕ) (hd : weight w d ≠ n) : coeff d φ = 0 := by have aux := mt (@hφ d) hd rwa [Classical.not_not] at aux /-- The weighted degree of a nonzero weighted homogeneous polynomial is well-defined. -/ theorem inj_right {w : σ → M} (hφ : φ ≠ 0) (hm : IsWeightedHomogeneous w φ m) (hn : IsWeightedHomogeneous w φ n) : m = n := by obtain ⟨d, hd⟩ : ∃ d, coeff d φ ≠ 0 := exists_coeff_ne_zero hφ rw [← hm hd, ← hn hd] /-- The sum of two weighted homogeneous polynomials of degree `n` is weighted homogeneous of weighted degree `n`. -/ theorem add {w : σ → M} (hφ : IsWeightedHomogeneous w φ n) (hψ : IsWeightedHomogeneous w ψ n) : IsWeightedHomogeneous w (φ + ψ) n := (weightedHomogeneousSubmodule R w n).add_mem hφ hψ /-- The sum of weighted homogeneous polynomials of degree `n` is weighted homogeneous of weighted degree `n`. -/ theorem sum {ι : Type*} (s : Finset ι) (φ : ι → MvPolynomial σ R) (n : M) {w : σ → M} (h : ∀ i ∈ s, IsWeightedHomogeneous w (φ i) n) : IsWeightedHomogeneous w (∑ i ∈ s, φ i) n := (weightedHomogeneousSubmodule R w n).sum_mem h /-- The product of weighted homogeneous polynomials of weighted degrees `m` and `n` is weighted homogeneous of weighted degree `m + n`. -/ theorem mul {w : σ → M} (hφ : IsWeightedHomogeneous w φ m) (hψ : IsWeightedHomogeneous w ψ n) : IsWeightedHomogeneous w (φ * ψ) (m + n) := weightedHomogeneousSubmodule_mul w m n <| Submodule.mul_mem_mul hφ hψ theorem pow {w : σ → M} (hφ : IsWeightedHomogeneous w φ m) (n : ℕ) : IsWeightedHomogeneous w (φ ^ n) (n • m) := by induction n with | zero => rw [pow_zero, zero_smul]; exact isWeightedHomogeneous_one R w | succ n ih => rw [pow_succ, succ_nsmul]; exact ih.mul hφ /-- A product of weighted homogeneous polynomials is weighted homogeneous, with weighted degree equal to the sum of the weighted degrees. -/ theorem prod {ι : Type*} (s : Finset ι) (φ : ι → MvPolynomial σ R) (n : ι → M) {w : σ → M} : (∀ i ∈ s, IsWeightedHomogeneous w (φ i) (n i)) → IsWeightedHomogeneous w (∏ i ∈ s, φ i) (∑ i ∈ s, n i) := by classical refine Finset.induction_on s ?_ ?_ · intro simp only [isWeightedHomogeneous_one, Finset.sum_empty, Finset.prod_empty] · intro i s his IH h simp only [his, Finset.prod_insert, Finset.sum_insert, not_false_iff] apply (h i (Finset.mem_insert_self _ _)).mul (IH _) intro j hjs exact h j (Finset.mem_insert_of_mem hjs) /-- A non zero weighted homogeneous polynomial of weighted degree `n` has weighted total degree `n`. -/ theorem weighted_total_degree [SemilatticeSup M] {w : σ → M} (hφ : IsWeightedHomogeneous w φ n) (h : φ ≠ 0) : weightedTotalDegree' w φ = n := by simp only [weightedTotalDegree'] apply le_antisymm · simp only [Finset.sup_le_iff, mem_support_iff, WithBot.coe_le_coe] exact fun d hd => le_of_eq (hφ hd) · obtain ⟨d, hd⟩ : ∃ d, coeff d φ ≠ 0 := exists_coeff_ne_zero h simp only [← hφ hd, Finsupp.sum] replace hd := Finsupp.mem_support_iff.mpr hd apply Finset.le_sup hd
end IsWeightedHomogeneous variable {R} /-- The weighted homogeneous submodules form a graded monoid. -/ lemma WeightedHomogeneousSubmodule.gradedMonoid {w : σ → M} : SetLike.GradedMonoid (weightedHomogeneousSubmodule R w) where one_mem := isWeightedHomogeneous_one R w mul_mem _ _ _ _ := IsWeightedHomogeneous.mul /-- `weightedHomogeneousComponent w n φ` is the part of `φ` that is weighted homogeneous of weighted degree `n`, with respect to the weights `w`.
Mathlib/RingTheory/MvPolynomial/WeightedHomogeneous.lean
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/- Copyright (c) 2020 Frédéric Dupuis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Frédéric Dupuis -/ import Mathlib.Algebra.Algebra.Field import Mathlib.Algebra.BigOperators.Balance import Mathlib.Algebra.Order.BigOperators.Expect import Mathlib.Algebra.Order.Star.Basic import Mathlib.Analysis.CStarAlgebra.Basic import Mathlib.Analysis.Normed.Operator.ContinuousLinearMap import Mathlib.Data.Real.Sqrt import Mathlib.LinearAlgebra.Basis.VectorSpace /-! # `RCLike`: a typeclass for ℝ or ℂ This file defines the typeclass `RCLike` intended to have only two instances: ℝ and ℂ. It is meant for definitions and theorems which hold for both the real and the complex case, and in particular when the real case follows directly from the complex case by setting `re` to `id`, `im` to zero and so on. Its API follows closely that of ℂ. Applications include defining inner products and Hilbert spaces for both the real and complex case. One typically produces the definitions and proof for an arbitrary field of this typeclass, which basically amounts to doing the complex case, and the two cases then fall out immediately from the two instances of the class. The instance for `ℝ` is registered in this file. The instance for `ℂ` is declared in `Mathlib/Analysis/Complex/Basic.lean`. ## Implementation notes The coercion from reals into an `RCLike` field is done by registering `RCLike.ofReal` as a `CoeTC`. For this to work, we must proceed carefully to avoid problems involving circular coercions in the case `K=ℝ`; in particular, we cannot use the plain `Coe` and must set priorities carefully. This problem was already solved for `ℕ`, and we copy the solution detailed in `Mathlib/Data/Nat/Cast/Defs.lean`. See also Note [coercion into rings] for more details. In addition, several lemmas need to be set at priority 900 to make sure that they do not override their counterparts in `Mathlib/Analysis/Complex/Basic.lean` (which causes linter errors). A few lemmas requiring heavier imports are in `Mathlib/Analysis/RCLike/Lemmas.lean`. -/ open Fintype open scoped BigOperators ComplexConjugate section local notation "𝓚" => algebraMap ℝ _ /-- This typeclass captures properties shared by ℝ and ℂ, with an API that closely matches that of ℂ. -/ class RCLike (K : semiOutParam Type*) extends DenselyNormedField K, StarRing K, NormedAlgebra ℝ K, CompleteSpace K where /-- The real part as an additive monoid homomorphism -/ re : K →+ ℝ /-- The imaginary part as an additive monoid homomorphism -/ im : K →+ ℝ /-- Imaginary unit in `K`. Meant to be set to `0` for `K = ℝ`. -/ I : K I_re_ax : re I = 0 I_mul_I_ax : I = 0 ∨ I * I = -1 re_add_im_ax : ∀ z : K, 𝓚 (re z) + 𝓚 (im z) * I = z ofReal_re_ax : ∀ r : ℝ, re (𝓚 r) = r ofReal_im_ax : ∀ r : ℝ, im (𝓚 r) = 0 mul_re_ax : ∀ z w : K, re (z * w) = re z * re w - im z * im w mul_im_ax : ∀ z w : K, im (z * w) = re z * im w + im z * re w conj_re_ax : ∀ z : K, re (conj z) = re z conj_im_ax : ∀ z : K, im (conj z) = -im z conj_I_ax : conj I = -I norm_sq_eq_def_ax : ∀ z : K, ‖z‖ ^ 2 = re z * re z + im z * im z mul_im_I_ax : ∀ z : K, im z * im I = im z /-- only an instance in the `ComplexOrder` locale -/ [toPartialOrder : PartialOrder K] le_iff_re_im {z w : K} : z ≤ w ↔ re z ≤ re w ∧ im z = im w -- note we cannot put this in the `extends` clause [toDecidableEq : DecidableEq K] scoped[ComplexOrder] attribute [instance 100] RCLike.toPartialOrder attribute [instance 100] RCLike.toDecidableEq end variable {K E : Type*} [RCLike K] namespace RCLike /-- Coercion from `ℝ` to an `RCLike` field. -/ @[coe] abbrev ofReal : ℝ → K := Algebra.cast /- The priority must be set at 900 to ensure that coercions are tried in the right order. See Note [coercion into rings], or `Mathlib/Data/Nat/Cast/Basic.lean` for more details. -/ noncomputable instance (priority := 900) algebraMapCoe : CoeTC ℝ K := ⟨ofReal⟩ theorem ofReal_alg (x : ℝ) : (x : K) = x • (1 : K) := Algebra.algebraMap_eq_smul_one x theorem real_smul_eq_coe_mul (r : ℝ) (z : K) : r • z = (r : K) * z := Algebra.smul_def r z theorem real_smul_eq_coe_smul [AddCommGroup E] [Module K E] [Module ℝ E] [IsScalarTower ℝ K E] (r : ℝ) (x : E) : r • x = (r : K) • x := by rw [RCLike.ofReal_alg, smul_one_smul] theorem algebraMap_eq_ofReal : ⇑(algebraMap ℝ K) = ofReal := rfl @[simp, rclike_simps] theorem re_add_im (z : K) : (re z : K) + im z * I = z := RCLike.re_add_im_ax z @[simp, norm_cast, rclike_simps] theorem ofReal_re : ∀ r : ℝ, re (r : K) = r := RCLike.ofReal_re_ax @[simp, norm_cast, rclike_simps] theorem ofReal_im : ∀ r : ℝ, im (r : K) = 0 := RCLike.ofReal_im_ax @[simp, rclike_simps] theorem mul_re : ∀ z w : K, re (z * w) = re z * re w - im z * im w := RCLike.mul_re_ax @[simp, rclike_simps] theorem mul_im : ∀ z w : K, im (z * w) = re z * im w + im z * re w := RCLike.mul_im_ax theorem ext_iff {z w : K} : z = w ↔ re z = re w ∧ im z = im w := ⟨fun h => h ▸ ⟨rfl, rfl⟩, fun ⟨h₁, h₂⟩ => re_add_im z ▸ re_add_im w ▸ h₁ ▸ h₂ ▸ rfl⟩ theorem ext {z w : K} (hre : re z = re w) (him : im z = im w) : z = w := ext_iff.2 ⟨hre, him⟩ @[norm_cast] theorem ofReal_zero : ((0 : ℝ) : K) = 0 := algebraMap.coe_zero @[rclike_simps] theorem zero_re' : re (0 : K) = (0 : ℝ) := map_zero re @[norm_cast] theorem ofReal_one : ((1 : ℝ) : K) = 1 := map_one (algebraMap ℝ K) @[simp, rclike_simps] theorem one_re : re (1 : K) = 1 := by rw [← ofReal_one, ofReal_re] @[simp, rclike_simps] theorem one_im : im (1 : K) = 0 := by rw [← ofReal_one, ofReal_im] theorem ofReal_injective : Function.Injective ((↑) : ℝ → K) := (algebraMap ℝ K).injective @[norm_cast] theorem ofReal_inj {z w : ℝ} : (z : K) = (w : K) ↔ z = w := algebraMap.coe_inj -- replaced by `RCLike.ofNat_re` -- replaced by `RCLike.ofNat_im` theorem ofReal_eq_zero {x : ℝ} : (x : K) = 0 ↔ x = 0 := algebraMap.lift_map_eq_zero_iff x theorem ofReal_ne_zero {x : ℝ} : (x : K) ≠ 0 ↔ x ≠ 0 := ofReal_eq_zero.not @[rclike_simps, norm_cast] theorem ofReal_add (r s : ℝ) : ((r + s : ℝ) : K) = r + s := algebraMap.coe_add _ _ -- replaced by `RCLike.ofReal_ofNat` @[rclike_simps, norm_cast] theorem ofReal_neg (r : ℝ) : ((-r : ℝ) : K) = -r := algebraMap.coe_neg r @[rclike_simps, norm_cast] theorem ofReal_sub (r s : ℝ) : ((r - s : ℝ) : K) = r - s := map_sub (algebraMap ℝ K) r s @[rclike_simps, norm_cast] theorem ofReal_sum {α : Type*} (s : Finset α) (f : α → ℝ) : ((∑ i ∈ s, f i : ℝ) : K) = ∑ i ∈ s, (f i : K) := map_sum (algebraMap ℝ K) _ _ @[simp, rclike_simps, norm_cast] theorem ofReal_finsupp_sum {α M : Type*} [Zero M] (f : α →₀ M) (g : α → M → ℝ) : ((f.sum fun a b => g a b : ℝ) : K) = f.sum fun a b => (g a b : K) := map_finsuppSum (algebraMap ℝ K) f g @[rclike_simps, norm_cast] theorem ofReal_mul (r s : ℝ) : ((r * s : ℝ) : K) = r * s := algebraMap.coe_mul _ _ @[rclike_simps, norm_cast] theorem ofReal_pow (r : ℝ) (n : ℕ) : ((r ^ n : ℝ) : K) = (r : K) ^ n := map_pow (algebraMap ℝ K) r n @[rclike_simps, norm_cast] theorem ofReal_prod {α : Type*} (s : Finset α) (f : α → ℝ) : ((∏ i ∈ s, f i : ℝ) : K) = ∏ i ∈ s, (f i : K) := map_prod (algebraMap ℝ K) _ _ @[simp, rclike_simps, norm_cast] theorem ofReal_finsuppProd {α M : Type*} [Zero M] (f : α →₀ M) (g : α → M → ℝ) : ((f.prod fun a b => g a b : ℝ) : K) = f.prod fun a b => (g a b : K) := map_finsuppProd _ f g @[deprecated (since := "2025-04-06")] alias ofReal_finsupp_prod := ofReal_finsuppProd @[simp, norm_cast, rclike_simps] theorem real_smul_ofReal (r x : ℝ) : r • (x : K) = (r : K) * (x : K) := real_smul_eq_coe_mul _ _ @[rclike_simps] theorem re_ofReal_mul (r : ℝ) (z : K) : re (↑r * z) = r * re z := by simp only [mul_re, ofReal_im, zero_mul, ofReal_re, sub_zero] @[rclike_simps] theorem im_ofReal_mul (r : ℝ) (z : K) : im (↑r * z) = r * im z := by simp only [add_zero, ofReal_im, zero_mul, ofReal_re, mul_im] @[rclike_simps] theorem smul_re (r : ℝ) (z : K) : re (r • z) = r * re z := by rw [real_smul_eq_coe_mul, re_ofReal_mul] @[rclike_simps] theorem smul_im (r : ℝ) (z : K) : im (r • z) = r * im z := by rw [real_smul_eq_coe_mul, im_ofReal_mul] @[rclike_simps, norm_cast] theorem norm_ofReal (r : ℝ) : ‖(r : K)‖ = |r| := norm_algebraMap' K r /-! ### Characteristic zero -/ -- see Note [lower instance priority] /-- ℝ and ℂ are both of characteristic zero. -/ instance (priority := 100) charZero_rclike : CharZero K := (RingHom.charZero_iff (algebraMap ℝ K).injective).1 inferInstance @[rclike_simps, norm_cast] lemma ofReal_expect {α : Type*} (s : Finset α) (f : α → ℝ) : 𝔼 i ∈ s, f i = 𝔼 i ∈ s, (f i : K) := map_expect (algebraMap ..) .. @[norm_cast] lemma ofReal_balance {ι : Type*} [Fintype ι] (f : ι → ℝ) (i : ι) : ((balance f i : ℝ) : K) = balance ((↑) ∘ f) i := map_balance (algebraMap ..) .. @[simp] lemma ofReal_comp_balance {ι : Type*} [Fintype ι] (f : ι → ℝ) : ofReal ∘ balance f = balance (ofReal ∘ f : ι → K) := funext <| ofReal_balance _ /-! ### The imaginary unit, `I` -/ /-- The imaginary unit. -/ @[simp, rclike_simps] theorem I_re : re (I : K) = 0 := I_re_ax @[simp, rclike_simps] theorem I_im (z : K) : im z * im (I : K) = im z := mul_im_I_ax z @[simp, rclike_simps] theorem I_im' (z : K) : im (I : K) * im z = im z := by rw [mul_comm, I_im] @[rclike_simps] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11119): was `simp` theorem I_mul_re (z : K) : re (I * z) = -im z := by simp only [I_re, zero_sub, I_im', zero_mul, mul_re] theorem I_mul_I : (I : K) = 0 ∨ (I : K) * I = -1 := I_mul_I_ax variable (𝕜) in lemma I_eq_zero_or_im_I_eq_one : (I : K) = 0 ∨ im (I : K) = 1 := I_mul_I (K := K) |>.imp_right fun h ↦ by simpa [h] using (I_mul_re (I : K)).symm @[simp, rclike_simps] theorem conj_re (z : K) : re (conj z) = re z := RCLike.conj_re_ax z @[simp, rclike_simps] theorem conj_im (z : K) : im (conj z) = -im z := RCLike.conj_im_ax z @[simp, rclike_simps] theorem conj_I : conj (I : K) = -I := RCLike.conj_I_ax @[simp, rclike_simps] theorem conj_ofReal (r : ℝ) : conj (r : K) = (r : K) := by rw [ext_iff] simp only [ofReal_im, conj_im, eq_self_iff_true, conj_re, and_self_iff, neg_zero] -- replaced by `RCLike.conj_ofNat` theorem conj_nat_cast (n : ℕ) : conj (n : K) = n := map_natCast _ _ theorem conj_ofNat (n : ℕ) [n.AtLeastTwo] : conj (ofNat(n) : K) = ofNat(n) := map_ofNat _ _ @[rclike_simps, simp] theorem conj_neg_I : conj (-I) = (I : K) := by rw [map_neg, conj_I, neg_neg] theorem conj_eq_re_sub_im (z : K) : conj z = re z - im z * I := (congr_arg conj (re_add_im z).symm).trans <| by rw [map_add, map_mul, conj_I, conj_ofReal, conj_ofReal, mul_neg, sub_eq_add_neg] theorem sub_conj (z : K) : z - conj z = 2 * im z * I := calc z - conj z = re z + im z * I - (re z - im z * I) := by rw [re_add_im, ← conj_eq_re_sub_im] _ = 2 * im z * I := by rw [add_sub_sub_cancel, ← two_mul, mul_assoc] @[rclike_simps] theorem conj_smul (r : ℝ) (z : K) : conj (r • z) = r • conj z := by rw [conj_eq_re_sub_im, conj_eq_re_sub_im, smul_re, smul_im, ofReal_mul, ofReal_mul, real_smul_eq_coe_mul r (_ - _), mul_sub, mul_assoc] theorem add_conj (z : K) : z + conj z = 2 * re z := calc z + conj z = re z + im z * I + (re z - im z * I) := by rw [re_add_im, conj_eq_re_sub_im] _ = 2 * re z := by rw [add_add_sub_cancel, two_mul] theorem re_eq_add_conj (z : K) : ↑(re z) = (z + conj z) / 2 := by rw [add_conj, mul_div_cancel_left₀ (re z : K) two_ne_zero] theorem im_eq_conj_sub (z : K) : ↑(im z) = I * (conj z - z) / 2 := by rw [← neg_inj, ← ofReal_neg, ← I_mul_re, re_eq_add_conj, map_mul, conj_I, ← neg_div, ← mul_neg, neg_sub, mul_sub, neg_mul, sub_eq_add_neg] open List in /-- There are several equivalent ways to say that a number `z` is in fact a real number. -/ theorem is_real_TFAE (z : K) : TFAE [conj z = z, ∃ r : ℝ, (r : K) = z, ↑(re z) = z, im z = 0] := by tfae_have 1 → 4 | h => by rw [← @ofReal_inj K, im_eq_conj_sub, h, sub_self, mul_zero, zero_div, ofReal_zero] tfae_have 4 → 3 | h => by conv_rhs => rw [← re_add_im z, h, ofReal_zero, zero_mul, add_zero] tfae_have 3 → 2 := fun h => ⟨_, h⟩ tfae_have 2 → 1 := fun ⟨r, hr⟩ => hr ▸ conj_ofReal _ tfae_finish theorem conj_eq_iff_real {z : K} : conj z = z ↔ ∃ r : ℝ, z = (r : K) := calc _ ↔ ∃ r : ℝ, (r : K) = z := (is_real_TFAE z).out 0 1 _ ↔ _ := by simp only [eq_comm] theorem conj_eq_iff_re {z : K} : conj z = z ↔ (re z : K) = z := (is_real_TFAE z).out 0 2 theorem conj_eq_iff_im {z : K} : conj z = z ↔ im z = 0 := (is_real_TFAE z).out 0 3 @[simp] theorem star_def : (Star.star : K → K) = conj := rfl variable (K) /-- Conjugation as a ring equivalence. This is used to convert the inner product into a sesquilinear product. -/ abbrev conjToRingEquiv : K ≃+* Kᵐᵒᵖ := starRingEquiv variable {K} {z : K} /-- The norm squared function. -/ def normSq : K →*₀ ℝ where toFun z := re z * re z + im z * im z map_zero' := by simp only [add_zero, mul_zero, map_zero] map_one' := by simp only [one_im, add_zero, mul_one, one_re, mul_zero] map_mul' z w := by simp only [mul_im, mul_re] ring theorem normSq_apply (z : K) : normSq z = re z * re z + im z * im z := rfl theorem norm_sq_eq_def {z : K} : ‖z‖ ^ 2 = re z * re z + im z * im z := norm_sq_eq_def_ax z theorem normSq_eq_def' (z : K) : normSq z = ‖z‖ ^ 2 := norm_sq_eq_def.symm @[rclike_simps] theorem normSq_zero : normSq (0 : K) = 0 := normSq.map_zero @[rclike_simps] theorem normSq_one : normSq (1 : K) = 1 := normSq.map_one theorem normSq_nonneg (z : K) : 0 ≤ normSq z := add_nonneg (mul_self_nonneg _) (mul_self_nonneg _) @[rclike_simps] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11119): was `simp` theorem normSq_eq_zero {z : K} : normSq z = 0 ↔ z = 0 := map_eq_zero _ @[simp, rclike_simps] theorem normSq_pos {z : K} : 0 < normSq z ↔ z ≠ 0 := by rw [lt_iff_le_and_ne, Ne, eq_comm]; simp [normSq_nonneg] @[simp, rclike_simps] theorem normSq_neg (z : K) : normSq (-z) = normSq z := by simp only [normSq_eq_def', norm_neg] @[simp, rclike_simps] theorem normSq_conj (z : K) : normSq (conj z) = normSq z := by simp only [normSq_apply, neg_mul, mul_neg, neg_neg, rclike_simps] @[rclike_simps] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11119): was `simp` theorem normSq_mul (z w : K) : normSq (z * w) = normSq z * normSq w := map_mul _ z w theorem normSq_add (z w : K) : normSq (z + w) = normSq z + normSq w + 2 * re (z * conj w) := by simp only [normSq_apply, map_add, rclike_simps] ring theorem re_sq_le_normSq (z : K) : re z * re z ≤ normSq z := le_add_of_nonneg_right (mul_self_nonneg _) theorem im_sq_le_normSq (z : K) : im z * im z ≤ normSq z := le_add_of_nonneg_left (mul_self_nonneg _) theorem mul_conj (z : K) : z * conj z = ‖z‖ ^ 2 := by apply ext <;> simp [← ofReal_pow, norm_sq_eq_def, mul_comm] theorem conj_mul (z : K) : conj z * z = ‖z‖ ^ 2 := by rw [mul_comm, mul_conj] lemma inv_eq_conj (hz : ‖z‖ = 1) : z⁻¹ = conj z := inv_eq_of_mul_eq_one_left <| by simp_rw [conj_mul, hz, algebraMap.coe_one, one_pow] theorem normSq_sub (z w : K) : normSq (z - w) = normSq z + normSq w - 2 * re (z * conj w) := by simp only [normSq_add, sub_eq_add_neg, map_neg, mul_neg, normSq_neg, map_neg] theorem sqrt_normSq_eq_norm {z : K} : √(normSq z) = ‖z‖ := by rw [normSq_eq_def', Real.sqrt_sq (norm_nonneg _)] /-! ### Inversion -/ @[rclike_simps, norm_cast] theorem ofReal_inv (r : ℝ) : ((r⁻¹ : ℝ) : K) = (r : K)⁻¹ := map_inv₀ _ r theorem inv_def (z : K) : z⁻¹ = conj z * ((‖z‖ ^ 2)⁻¹ : ℝ) := by rcases eq_or_ne z 0 with (rfl | h₀) · simp · apply inv_eq_of_mul_eq_one_right rw [← mul_assoc, mul_conj, ofReal_inv, ofReal_pow, mul_inv_cancel₀] simpa @[simp, rclike_simps] theorem inv_re (z : K) : re z⁻¹ = re z / normSq z := by rw [inv_def, normSq_eq_def', mul_comm, re_ofReal_mul, conj_re, div_eq_inv_mul] @[simp, rclike_simps] theorem inv_im (z : K) : im z⁻¹ = -im z / normSq z := by rw [inv_def, normSq_eq_def', mul_comm, im_ofReal_mul, conj_im, div_eq_inv_mul] theorem div_re (z w : K) : re (z / w) = re z * re w / normSq w + im z * im w / normSq w := by simp only [div_eq_mul_inv, mul_assoc, sub_eq_add_neg, neg_mul, mul_neg, neg_neg, map_neg, rclike_simps] theorem div_im (z w : K) : im (z / w) = im z * re w / normSq w - re z * im w / normSq w := by simp only [div_eq_mul_inv, mul_assoc, sub_eq_add_neg, add_comm, neg_mul, mul_neg, map_neg, rclike_simps] @[rclike_simps] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11119): was `simp` theorem conj_inv (x : K) : conj x⁻¹ = (conj x)⁻¹ := star_inv₀ _
lemma conj_div (x y : K) : conj (x / y) = conj x / conj y := map_div' conj conj_inv _ _
Mathlib/Analysis/RCLike/Basic.lean
476
477
/- Copyright (c) 2021 Shing Tak Lam. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Shing Tak Lam -/ import Mathlib.Topology.Order.ProjIcc import Mathlib.Topology.ContinuousMap.Ordered import Mathlib.Topology.CompactOpen import Mathlib.Topology.UnitInterval /-! # Homotopy between functions In this file, we define a homotopy between two functions `f₀` and `f₁`. First we define `ContinuousMap.Homotopy` between the two functions, with no restrictions on the intermediate maps. Then, as in the formalisation in HOL-Analysis, we define `ContinuousMap.HomotopyWith f₀ f₁ P`, for homotopies between `f₀` and `f₁`, where the intermediate maps satisfy the predicate `P`. Finally, we define `ContinuousMap.HomotopyRel f₀ f₁ S`, for homotopies between `f₀` and `f₁` which are fixed on `S`. ## Definitions * `ContinuousMap.Homotopy f₀ f₁` is the type of homotopies between `f₀` and `f₁`. * `ContinuousMap.HomotopyWith f₀ f₁ P` is the type of homotopies between `f₀` and `f₁`, where the intermediate maps satisfy the predicate `P`. * `ContinuousMap.HomotopyRel f₀ f₁ S` is the type of homotopies between `f₀` and `f₁` which are fixed on `S`. For each of the above, we have * `refl f`, which is the constant homotopy from `f` to `f`. * `symm F`, which reverses the homotopy `F`. For example, if `F : ContinuousMap.Homotopy f₀ f₁`, then `F.symm : ContinuousMap.Homotopy f₁ f₀`. * `trans F G`, which concatenates the homotopies `F` and `G`. For example, if `F : ContinuousMap.Homotopy f₀ f₁` and `G : ContinuousMap.Homotopy f₁ f₂`, then `F.trans G : ContinuousMap.Homotopy f₀ f₂`. We also define the relations * `ContinuousMap.Homotopic f₀ f₁` is defined to be `Nonempty (ContinuousMap.Homotopy f₀ f₁)` * `ContinuousMap.HomotopicWith f₀ f₁ P` is defined to be `Nonempty (ContinuousMap.HomotopyWith f₀ f₁ P)` * `ContinuousMap.HomotopicRel f₀ f₁ P` is defined to be `Nonempty (ContinuousMap.HomotopyRel f₀ f₁ P)` and for `ContinuousMap.homotopic` and `ContinuousMap.homotopic_rel`, we also define the `setoid` and `quotient` in `C(X, Y)` by these relations. ## References - [HOL-Analysis formalisation](https://isabelle.in.tum.de/library/HOL/HOL-Analysis/Homotopy.html) -/ noncomputable section universe u v w x variable {F : Type*} {X : Type u} {Y : Type v} {Z : Type w} {Z' : Type x} {ι : Type*} variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace Z'] open unitInterval namespace ContinuousMap /-- `ContinuousMap.Homotopy f₀ f₁` is the type of homotopies from `f₀` to `f₁`. When possible, instead of parametrizing results over `(f : Homotopy f₀ f₁)`, you should parametrize over `{F : Type*} [HomotopyLike F f₀ f₁] (f : F)`. When you extend this structure, make sure to extend `ContinuousMap.HomotopyLike`. -/ structure Homotopy (f₀ f₁ : C(X, Y)) extends C(I × X, Y) where /-- value of the homotopy at 0 -/ map_zero_left : ∀ x, toFun (0, x) = f₀ x /-- value of the homotopy at 1 -/ map_one_left : ∀ x, toFun (1, x) = f₁ x section /-- `ContinuousMap.HomotopyLike F f₀ f₁` states that `F` is a type of homotopies between `f₀` and `f₁`. You should extend this class when you extend `ContinuousMap.Homotopy`. -/ class HomotopyLike {X Y : outParam Type*} [TopologicalSpace X] [TopologicalSpace Y] (F : Type*) (f₀ f₁ : outParam <| C(X, Y)) [FunLike F (I × X) Y] : Prop extends ContinuousMapClass F (I × X) Y where /-- value of the homotopy at 0 -/ map_zero_left (f : F) : ∀ x, f (0, x) = f₀ x /-- value of the homotopy at 1 -/ map_one_left (f : F) : ∀ x, f (1, x) = f₁ x end namespace Homotopy section variable {f₀ f₁ : C(X, Y)} instance instFunLike : FunLike (Homotopy f₀ f₁) (I × X) Y where coe f := f.toFun coe_injective' f g h := by obtain ⟨⟨_, _⟩, _⟩ := f obtain ⟨⟨_, _⟩, _⟩ := g congr instance : HomotopyLike (Homotopy f₀ f₁) f₀ f₁ where map_continuous f := f.continuous_toFun map_zero_left f := f.map_zero_left map_one_left f := f.map_one_left @[ext] theorem ext {F G : Homotopy f₀ f₁} (h : ∀ x, F x = G x) : F = G := DFunLike.ext _ _ h /-- See Note [custom simps projection]. We need to specify this projection explicitly in this case, because it is a composition of multiple projections. -/ def Simps.apply (F : Homotopy f₀ f₁) : I × X → Y := F initialize_simps_projections Homotopy (toFun → apply, -toContinuousMap) /-- Deprecated. Use `map_continuous` instead. -/ protected theorem continuous (F : Homotopy f₀ f₁) : Continuous F := F.continuous_toFun @[simp] theorem apply_zero (F : Homotopy f₀ f₁) (x : X) : F (0, x) = f₀ x := F.map_zero_left x @[simp] theorem apply_one (F : Homotopy f₀ f₁) (x : X) : F (1, x) = f₁ x := F.map_one_left x @[simp] theorem coe_toContinuousMap (F : Homotopy f₀ f₁) : ⇑F.toContinuousMap = F := rfl /-- Currying a homotopy to a continuous function from `I` to `C(X, Y)`. -/ def curry (F : Homotopy f₀ f₁) : C(I, C(X, Y)) := F.toContinuousMap.curry @[simp] theorem curry_apply (F : Homotopy f₀ f₁) (t : I) (x : X) : F.curry t x = F (t, x) := rfl /-- Continuously extending a curried homotopy to a function from `ℝ` to `C(X, Y)`. -/ def extend (F : Homotopy f₀ f₁) : C(ℝ, C(X, Y)) := F.curry.IccExtend zero_le_one theorem extend_apply_of_le_zero (F : Homotopy f₀ f₁) {t : ℝ} (ht : t ≤ 0) (x : X) : F.extend t x = f₀ x := by rw [← F.apply_zero] exact ContinuousMap.congr_fun (Set.IccExtend_of_le_left (zero_le_one' ℝ) F.curry ht) x theorem extend_apply_of_one_le (F : Homotopy f₀ f₁) {t : ℝ} (ht : 1 ≤ t) (x : X) : F.extend t x = f₁ x := by rw [← F.apply_one] exact ContinuousMap.congr_fun (Set.IccExtend_of_right_le (zero_le_one' ℝ) F.curry ht) x theorem extend_apply_coe (F : Homotopy f₀ f₁) (t : I) (x : X) : F.extend t x = F (t, x) := ContinuousMap.congr_fun (Set.IccExtend_val (zero_le_one' ℝ) F.curry t) x @[simp] theorem extend_apply_of_mem_I (F : Homotopy f₀ f₁) {t : ℝ} (ht : t ∈ I) (x : X) : F.extend t x = F (⟨t, ht⟩, x) := ContinuousMap.congr_fun (Set.IccExtend_of_mem (zero_le_one' ℝ) F.curry ht) x protected theorem congr_fun {F G : Homotopy f₀ f₁} (h : F = G) (x : I × X) : F x = G x :=
ContinuousMap.congr_fun (congr_arg _ h) x protected theorem congr_arg (F : Homotopy f₀ f₁) {x y : I × X} (h : x = y) : F x = F y := F.toContinuousMap.congr_arg h
Mathlib/Topology/Homotopy/Basic.lean
172
175
/- 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.Analysis.Asymptotics.Lemmas import Mathlib.Analysis.Normed.Module.Basic /-! # Asymptotic equivalence up to a constant In this file we define `Asymptotics.IsTheta l f g` (notation: `f =Θ[l] g`) as `f =O[l] g ∧ g =O[l] f`, then prove basic properties of this equivalence relation. -/ open Filter open Topology namespace Asymptotics variable {α : Type*} {β : Type*} {E : Type*} {F : Type*} {G : Type*} {E' : Type*} {F' : Type*} {G' : Type*} {E'' : Type*} {F'' : Type*} {G'' : Type*} {R : Type*} {R' : Type*} {𝕜 : Type*} {𝕜' : Type*} variable [Norm E] [Norm F] [Norm G] variable [SeminormedAddCommGroup E'] [SeminormedAddCommGroup F'] [SeminormedAddCommGroup G'] [NormedAddCommGroup E''] [NormedAddCommGroup F''] [NormedAddCommGroup G''] [SeminormedRing R] [SeminormedRing R'] variable [NormedField 𝕜] [NormedField 𝕜'] variable {c c' c₁ c₂ : ℝ} {f : α → E} {g : α → F} {k : α → G} variable {f' : α → E'} {g' : α → F'} {k' : α → G'} variable {f'' : α → E''} {g'' : α → F''} variable {l l' : Filter α} /-- We say that `f` is `Θ(g)` along a filter `l` (notation: `f =Θ[l] g`) if `f =O[l] g` and `g =O[l] f`. -/ def IsTheta (l : Filter α) (f : α → E) (g : α → F) : Prop := IsBigO l f g ∧ IsBigO l g f @[inherit_doc] notation:100 f " =Θ[" l "] " g:100 => IsTheta l f g theorem IsBigO.antisymm (h₁ : f =O[l] g) (h₂ : g =O[l] f) : f =Θ[l] g := ⟨h₁, h₂⟩ lemma IsTheta.isBigO (h : f =Θ[l] g) : f =O[l] g := h.1 lemma IsTheta.isBigO_symm (h : f =Θ[l] g) : g =O[l] f := h.2 @[refl] theorem isTheta_refl (f : α → E) (l : Filter α) : f =Θ[l] f := ⟨isBigO_refl _ _, isBigO_refl _ _⟩ theorem isTheta_rfl : f =Θ[l] f := isTheta_refl _ _ @[symm] nonrec theorem IsTheta.symm (h : f =Θ[l] g) : g =Θ[l] f := h.symm theorem isTheta_comm : f =Θ[l] g ↔ g =Θ[l] f := ⟨fun h ↦ h.symm, fun h ↦ h.symm⟩ @[trans] theorem IsTheta.trans {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g) (h₂ : g =Θ[l] k) : f =Θ[l] k := ⟨h₁.1.trans h₂.1, h₂.2.trans h₁.2⟩ instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsTheta l) (IsTheta l) := ⟨IsTheta.trans⟩ @[trans] theorem IsBigO.trans_isTheta {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =O[l] g) (h₂ : g =Θ[l] k) : f =O[l] k := h₁.trans h₂.1 instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsBigO l) (IsTheta l) (IsBigO l) := ⟨IsBigO.trans_isTheta⟩ @[trans] theorem IsTheta.trans_isBigO {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g) (h₂ : g =O[l] k) : f =O[l] k := h₁.1.trans h₂ instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsBigO l) (IsBigO l) := ⟨IsTheta.trans_isBigO⟩ @[trans] theorem IsLittleO.trans_isTheta {f : α → E} {g : α → F} {k : α → G'} (h₁ : f =o[l] g) (h₂ : g =Θ[l] k) : f =o[l] k := h₁.trans_isBigO h₂.1 instance : Trans (α := α → E) (β := α → F') (γ := α → G') (IsLittleO l) (IsTheta l) (IsLittleO l) := ⟨IsLittleO.trans_isTheta⟩ @[trans] theorem IsTheta.trans_isLittleO {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g) (h₂ : g =o[l] k) : f =o[l] k := h₁.1.trans_isLittleO h₂ instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsLittleO l) (IsLittleO l) := ⟨IsTheta.trans_isLittleO⟩ @[trans] theorem IsTheta.trans_eventuallyEq {f : α → E} {g₁ g₂ : α → F} (h : f =Θ[l] g₁) (hg : g₁ =ᶠ[l] g₂) : f =Θ[l] g₂ := ⟨h.1.trans_eventuallyEq hg, hg.symm.trans_isBigO h.2⟩ instance : Trans (α := α → E) (β := α → F) (γ := α → F) (IsTheta l) (EventuallyEq l) (IsTheta l) := ⟨IsTheta.trans_eventuallyEq⟩ @[trans] theorem _root_.Filter.EventuallyEq.trans_isTheta {f₁ f₂ : α → E} {g : α → F} (hf : f₁ =ᶠ[l] f₂) (h : f₂ =Θ[l] g) : f₁ =Θ[l] g := ⟨hf.trans_isBigO h.1, h.2.trans_eventuallyEq hf.symm⟩ instance : Trans (α := α → E) (β := α → E) (γ := α → F) (EventuallyEq l) (IsTheta l) (IsTheta l) := ⟨EventuallyEq.trans_isTheta⟩ lemma _root_.Filter.EventuallyEq.isTheta {f g : α → E} (h : f =ᶠ[l] g) : f =Θ[l] g := h.trans_isTheta isTheta_rfl @[simp] theorem isTheta_bot : f =Θ[⊥] g := by simp [IsTheta] @[simp] theorem isTheta_norm_left : (fun x ↦ ‖f' x‖) =Θ[l] g ↔ f' =Θ[l] g := by simp [IsTheta] @[simp] theorem isTheta_norm_right : (f =Θ[l] fun x ↦ ‖g' x‖) ↔ f =Θ[l] g' := by simp [IsTheta] alias ⟨IsTheta.of_norm_left, IsTheta.norm_left⟩ := isTheta_norm_left alias ⟨IsTheta.of_norm_right, IsTheta.norm_right⟩ := isTheta_norm_right theorem IsTheta.of_norm_eventuallyEq_norm (h : (fun x ↦ ‖f x‖) =ᶠ[l] fun x ↦ ‖g x‖) : f =Θ[l] g := ⟨.of_bound' h.le, .of_bound' h.symm.le⟩ @[deprecated (since := "2025-01-03")] alias isTheta_of_norm_eventuallyEq := IsTheta.of_norm_eventuallyEq_norm theorem IsTheta.of_norm_eventuallyEq {g : α → ℝ} (h : (fun x ↦ ‖f' x‖) =ᶠ[l] g) : f' =Θ[l] g := of_norm_eventuallyEq_norm <| h.mono fun x hx ↦ by simp only [← hx, norm_norm] @[deprecated (since := "2025-01-03")] alias isTheta_of_norm_eventuallyEq' := IsTheta.of_norm_eventuallyEq theorem IsTheta.isLittleO_congr_left (h : f' =Θ[l] g') : f' =o[l] k ↔ g' =o[l] k := ⟨h.symm.trans_isLittleO, h.trans_isLittleO⟩ theorem IsTheta.isLittleO_congr_right (h : g' =Θ[l] k') : f =o[l] g' ↔ f =o[l] k' := ⟨fun H ↦ H.trans_isTheta h, fun H ↦ H.trans_isTheta h.symm⟩ theorem IsTheta.isBigO_congr_left (h : f' =Θ[l] g') : f' =O[l] k ↔ g' =O[l] k := ⟨h.symm.trans_isBigO, h.trans_isBigO⟩ theorem IsTheta.isBigO_congr_right (h : g' =Θ[l] k') : f =O[l] g' ↔ f =O[l] k' := ⟨fun H ↦ H.trans_isTheta h, fun H ↦ H.trans_isTheta h.symm⟩ lemma IsTheta.isTheta_congr_left (h : f' =Θ[l] g') : f' =Θ[l] k ↔ g' =Θ[l] k := h.isBigO_congr_left.and h.isBigO_congr_right lemma IsTheta.isTheta_congr_right (h : f' =Θ[l] g') : k =Θ[l] f' ↔ k =Θ[l] g' := h.isBigO_congr_right.and h.isBigO_congr_left theorem IsTheta.mono (h : f =Θ[l] g) (hl : l' ≤ l) : f =Θ[l'] g := ⟨h.1.mono hl, h.2.mono hl⟩ theorem IsTheta.sup (h : f' =Θ[l] g') (h' : f' =Θ[l'] g') : f' =Θ[l ⊔ l'] g' := ⟨h.1.sup h'.1, h.2.sup h'.2⟩ @[simp] theorem isTheta_sup : f' =Θ[l ⊔ l'] g' ↔ f' =Θ[l] g' ∧ f' =Θ[l'] g' := ⟨fun h ↦ ⟨h.mono le_sup_left, h.mono le_sup_right⟩, fun h ↦ h.1.sup h.2⟩ theorem IsTheta.eq_zero_iff (h : f'' =Θ[l] g'') : ∀ᶠ x in l, f'' x = 0 ↔ g'' x = 0 := h.1.eq_zero_imp.mp <| h.2.eq_zero_imp.mono fun _ ↦ Iff.intro theorem IsTheta.tendsto_zero_iff (h : f'' =Θ[l] g'') : Tendsto f'' l (𝓝 0) ↔ Tendsto g'' l (𝓝 0) := by simp only [← isLittleO_one_iff ℝ, h.isLittleO_congr_left] theorem IsTheta.tendsto_norm_atTop_iff (h : f' =Θ[l] g') : Tendsto (norm ∘ f') l atTop ↔ Tendsto (norm ∘ g') l atTop := by simp only [Function.comp_def, ← isLittleO_const_left_of_ne (one_ne_zero' ℝ), h.isLittleO_congr_right] theorem IsTheta.isBoundedUnder_le_iff (h : f' =Θ[l] g') : IsBoundedUnder (· ≤ ·) l (norm ∘ f') ↔ IsBoundedUnder (· ≤ ·) l (norm ∘ g') := by simp only [← isBigO_const_of_ne (one_ne_zero' ℝ), h.isBigO_congr_left] theorem IsTheta.smul [NormedSpace 𝕜 E'] [NormedSpace 𝕜' F'] {f₁ : α → 𝕜} {f₂ : α → 𝕜'} {g₁ : α → E'} {g₂ : α → F'} (hf : f₁ =Θ[l] f₂) (hg : g₁ =Θ[l] g₂) : (fun x ↦ f₁ x • g₁ x) =Θ[l] fun x ↦ f₂ x • g₂ x := ⟨hf.1.smul hg.1, hf.2.smul hg.2⟩ theorem IsTheta.mul {f₁ f₂ : α → 𝕜} {g₁ g₂ : α → 𝕜'} (h₁ : f₁ =Θ[l] g₁) (h₂ : f₂ =Θ[l] g₂) : (fun x ↦ f₁ x * f₂ x) =Θ[l] fun x ↦ g₁ x * g₂ x := h₁.smul h₂ theorem IsTheta.listProd {ι : Type*} {L : List ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'} (h : ∀ i ∈ L, f i =Θ[l] g i) : (fun x ↦ (L.map (f · x)).prod) =Θ[l] (fun x ↦ (L.map (g · x)).prod) := ⟨.listProd fun i hi ↦ (h i hi).isBigO, .listProd fun i hi ↦ (h i hi).symm.isBigO⟩ theorem IsTheta.multisetProd {ι : Type*} {s : Multiset ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'} (h : ∀ i ∈ s, f i =Θ[l] g i) : (fun x ↦ (s.map (f · x)).prod) =Θ[l] (fun x ↦ (s.map (g · x)).prod) := ⟨.multisetProd fun i hi ↦ (h i hi).isBigO, .multisetProd fun i hi ↦ (h i hi).symm.isBigO⟩ theorem IsTheta.finsetProd {ι : Type*} {s : Finset ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'} (h : ∀ i ∈ s, f i =Θ[l] g i) : (∏ i ∈ s, f i ·) =Θ[l] (∏ i ∈ s, g i ·) := ⟨.finsetProd fun i hi ↦ (h i hi).isBigO, .finsetProd fun i hi ↦ (h i hi).symm.isBigO⟩ theorem IsTheta.inv {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) : (fun x ↦ (f x)⁻¹) =Θ[l] fun x ↦ (g x)⁻¹ := ⟨h.2.inv_rev h.1.eq_zero_imp, h.1.inv_rev h.2.eq_zero_imp⟩ @[simp] theorem isTheta_inv {f : α → 𝕜} {g : α → 𝕜'} : ((fun x ↦ (f x)⁻¹) =Θ[l] fun x ↦ (g x)⁻¹) ↔ f =Θ[l] g := ⟨fun h ↦ by simpa only [inv_inv] using h.inv, IsTheta.inv⟩ theorem IsTheta.div {f₁ f₂ : α → 𝕜} {g₁ g₂ : α → 𝕜'} (h₁ : f₁ =Θ[l] g₁) (h₂ : f₂ =Θ[l] g₂) : (fun x ↦ f₁ x / f₂ x) =Θ[l] fun x ↦ g₁ x / g₂ x := by simpa only [div_eq_mul_inv] using h₁.mul h₂.inv theorem IsTheta.pow {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) (n : ℕ) : (fun x ↦ f x ^ n) =Θ[l] fun x ↦ g x ^ n := ⟨h.1.pow n, h.2.pow n⟩ theorem IsTheta.zpow {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) (n : ℤ) : (fun x ↦ f x ^ n) =Θ[l] fun x ↦ g x ^ n := by cases n · simpa only [Int.ofNat_eq_coe, zpow_natCast] using h.pow _ · simpa only [zpow_negSucc] using (h.pow _).inv theorem isTheta_const_const {c₁ : E''} {c₂ : F''} (h₁ : c₁ ≠ 0) (h₂ : c₂ ≠ 0) : (fun _ : α ↦ c₁) =Θ[l] fun _ ↦ c₂ := ⟨isBigO_const_const _ h₂ _, isBigO_const_const _ h₁ _⟩ @[simp] theorem isTheta_const_const_iff [NeBot l] {c₁ : E''} {c₂ : F''} : ((fun _ : α ↦ c₁) =Θ[l] fun _ ↦ c₂) ↔ (c₁ = 0 ↔ c₂ = 0) := by simpa only [IsTheta, isBigO_const_const_iff, ← iff_def] using Iff.comm @[simp] theorem isTheta_zero_left : (fun _ ↦ (0 : E')) =Θ[l] g'' ↔ g'' =ᶠ[l] 0 := by simp only [IsTheta, isBigO_zero, isBigO_zero_right_iff, true_and] @[simp] theorem isTheta_zero_right : (f'' =Θ[l] fun _ ↦ (0 : F')) ↔ f'' =ᶠ[l] 0 := isTheta_comm.trans isTheta_zero_left theorem isTheta_const_smul_left [NormedSpace 𝕜 E'] {c : 𝕜} (hc : c ≠ 0) : (fun x ↦ c • f' x) =Θ[l] g ↔ f' =Θ[l] g := and_congr (isBigO_const_smul_left hc) (isBigO_const_smul_right hc) alias ⟨IsTheta.of_const_smul_left, IsTheta.const_smul_left⟩ := isTheta_const_smul_left theorem isTheta_const_smul_right [NormedSpace 𝕜 F'] {c : 𝕜} (hc : c ≠ 0) : (f =Θ[l] fun x ↦ c • g' x) ↔ f =Θ[l] g' := and_congr (isBigO_const_smul_right hc) (isBigO_const_smul_left hc) alias ⟨IsTheta.of_const_smul_right, IsTheta.const_smul_right⟩ := isTheta_const_smul_right theorem isTheta_const_mul_left {c : 𝕜} {f : α → 𝕜} (hc : c ≠ 0) : (fun x ↦ c * f x) =Θ[l] g ↔ f =Θ[l] g := by simpa only [← smul_eq_mul] using isTheta_const_smul_left hc alias ⟨IsTheta.of_const_mul_left, IsTheta.const_mul_left⟩ := isTheta_const_mul_left theorem isTheta_const_mul_right {c : 𝕜} {g : α → 𝕜} (hc : c ≠ 0) : (f =Θ[l] fun x ↦ c * g x) ↔ f =Θ[l] g := by simpa only [← smul_eq_mul] using isTheta_const_smul_right hc
alias ⟨IsTheta.of_const_mul_right, IsTheta.const_mul_right⟩ := isTheta_const_mul_right
Mathlib/Analysis/Asymptotics/Theta.lean
280
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/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen, Filippo A. E. Nuccio -/ import Mathlib.Algebra.EuclideanDomain.Basic import Mathlib.RingTheory.FractionalIdeal.Basic import Mathlib.RingTheory.IntegralClosure.IsIntegral.Basic import Mathlib.RingTheory.LocalRing.Basic import Mathlib.RingTheory.PrincipalIdealDomain import Mathlib.Tactic.FieldSimp /-! # More operations on fractional ideals ## Main definitions * `map` is the pushforward of a fractional ideal along an algebra morphism Let `K` be the localization of `R` at `R⁰ = R \ {0}` (i.e. the field of fractions). * `FractionalIdeal R⁰ K` is the type of fractional ideals in the field of fractions * `Div (FractionalIdeal R⁰ K)` instance: the ideal quotient `I / J` (typically written $I : J$, but a `:` operator cannot be defined) ## Main statement * `isNoetherian` states that every fractional ideal of a noetherian integral domain is noetherian ## References * https://en.wikipedia.org/wiki/Fractional_ideal ## Tags fractional ideal, fractional ideals, invertible ideal -/ open IsLocalization Pointwise nonZeroDivisors namespace FractionalIdeal open Set Submodule variable {R : Type*} [CommRing R] {S : Submonoid R} {P : Type*} [CommRing P] variable [Algebra R P] section variable {P' : Type*} [CommRing P'] [Algebra R P'] variable {P'' : Type*} [CommRing P''] [Algebra R P''] theorem _root_.IsFractional.map (g : P →ₐ[R] P') {I : Submodule R P} : IsFractional S I → IsFractional S (Submodule.map g.toLinearMap I) | ⟨a, a_nonzero, hI⟩ => ⟨a, a_nonzero, fun b hb => by obtain ⟨b', b'_mem, hb'⟩ := Submodule.mem_map.mp hb rw [AlgHom.toLinearMap_apply] at hb' obtain ⟨x, hx⟩ := hI b' b'_mem use x rw [← g.commutes, hx, map_smul, hb']⟩ /-- `I.map g` is the pushforward of the fractional ideal `I` along the algebra morphism `g` -/ def map (g : P →ₐ[R] P') : FractionalIdeal S P → FractionalIdeal S P' := fun I => ⟨Submodule.map g.toLinearMap I, I.isFractional.map g⟩ @[simp, norm_cast] theorem coe_map (g : P →ₐ[R] P') (I : FractionalIdeal S P) : ↑(map g I) = Submodule.map g.toLinearMap I := rfl @[simp] theorem mem_map {I : FractionalIdeal S P} {g : P →ₐ[R] P'} {y : P'} : y ∈ I.map g ↔ ∃ x, x ∈ I ∧ g x = y := Submodule.mem_map variable (I J : FractionalIdeal S P) (g : P →ₐ[R] P') @[simp] theorem map_id : I.map (AlgHom.id _ _) = I := coeToSubmodule_injective (Submodule.map_id (I : Submodule R P)) @[simp] theorem map_comp (g' : P' →ₐ[R] P'') : I.map (g'.comp g) = (I.map g).map g' := coeToSubmodule_injective (Submodule.map_comp g.toLinearMap g'.toLinearMap I) @[simp, norm_cast] theorem map_coeIdeal (I : Ideal R) : (I : FractionalIdeal S P).map g = I := by ext x simp only [mem_coeIdeal] constructor · rintro ⟨_, ⟨y, hy, rfl⟩, rfl⟩ exact ⟨y, hy, (g.commutes y).symm⟩ · rintro ⟨y, hy, rfl⟩ exact ⟨_, ⟨y, hy, rfl⟩, g.commutes y⟩ @[simp] protected theorem map_one : (1 : FractionalIdeal S P).map g = 1 := map_coeIdeal g ⊤ @[simp] protected theorem map_zero : (0 : FractionalIdeal S P).map g = 0 := map_coeIdeal g 0 @[simp] protected theorem map_add : (I + J).map g = I.map g + J.map g := coeToSubmodule_injective (Submodule.map_sup _ _ _) @[simp] protected theorem map_mul : (I * J).map g = I.map g * J.map g := by simp only [mul_def] exact coeToSubmodule_injective (Submodule.map_mul _ _ _) @[simp] theorem map_map_symm (g : P ≃ₐ[R] P') : (I.map (g : P →ₐ[R] P')).map (g.symm : P' →ₐ[R] P) = I := by rw [← map_comp, g.symm_comp, map_id] @[simp] theorem map_symm_map (I : FractionalIdeal S P') (g : P ≃ₐ[R] P') : (I.map (g.symm : P' →ₐ[R] P)).map (g : P →ₐ[R] P') = I := by rw [← map_comp, g.comp_symm, map_id] theorem map_mem_map {f : P →ₐ[R] P'} (h : Function.Injective f) {x : P} {I : FractionalIdeal S P} : f x ∈ map f I ↔ x ∈ I := mem_map.trans ⟨fun ⟨_, hx', x'_eq⟩ => h x'_eq ▸ hx', fun h => ⟨x, h, rfl⟩⟩ theorem map_injective (f : P →ₐ[R] P') (h : Function.Injective f) : Function.Injective (map f : FractionalIdeal S P → FractionalIdeal S P') := fun _ _ hIJ => ext fun _ => (map_mem_map h).symm.trans (hIJ.symm ▸ map_mem_map h) /-- If `g` is an equivalence, `map g` is an isomorphism -/ def mapEquiv (g : P ≃ₐ[R] P') : FractionalIdeal S P ≃+* FractionalIdeal S P' where toFun := map g invFun := map g.symm map_add' I J := FractionalIdeal.map_add I J _ map_mul' I J := FractionalIdeal.map_mul I J _ left_inv I := by rw [← map_comp, AlgEquiv.symm_comp, map_id] right_inv I := by rw [← map_comp, AlgEquiv.comp_symm, map_id] @[simp] theorem coeFun_mapEquiv (g : P ≃ₐ[R] P') : (mapEquiv g : FractionalIdeal S P → FractionalIdeal S P') = map g := rfl @[simp] theorem mapEquiv_apply (g : P ≃ₐ[R] P') (I : FractionalIdeal S P) : mapEquiv g I = map (↑g) I := rfl @[simp] theorem mapEquiv_symm (g : P ≃ₐ[R] P') : ((mapEquiv g).symm : FractionalIdeal S P' ≃+* _) = mapEquiv g.symm := rfl @[simp] theorem mapEquiv_refl : mapEquiv AlgEquiv.refl = RingEquiv.refl (FractionalIdeal S P) := RingEquiv.ext fun x => by simp theorem isFractional_span_iff {s : Set P} : IsFractional S (span R s) ↔ ∃ a ∈ S, ∀ b : P, b ∈ s → IsInteger R (a • b) := ⟨fun ⟨a, a_mem, h⟩ => ⟨a, a_mem, fun b hb => h b (subset_span hb)⟩, fun ⟨a, a_mem, h⟩ => ⟨a, a_mem, fun _ hb => span_induction (hx := hb) h (by rw [smul_zero] exact isInteger_zero) (fun x y _ _ hx hy => by rw [smul_add] exact isInteger_add hx hy) fun s x _ hx => by rw [smul_comm] exact isInteger_smul hx⟩⟩ theorem isFractional_of_fg [IsLocalization S P] {I : Submodule R P} (hI : I.FG) : IsFractional S I := by rcases hI with ⟨I, rfl⟩ rcases exist_integer_multiples_of_finset S I with ⟨⟨s, hs1⟩, hs⟩ rw [isFractional_span_iff] exact ⟨s, hs1, hs⟩ theorem mem_span_mul_finite_of_mem_mul {I J : FractionalIdeal S P} {x : P} (hx : x ∈ I * J) : ∃ T T' : Finset P, (T : Set P) ⊆ I ∧ (T' : Set P) ⊆ J ∧ x ∈ span R (T * T' : Set P) := Submodule.mem_span_mul_finite_of_mem_mul (by simpa using mem_coe.mpr hx) variable (S) in theorem coeIdeal_fg (inj : Function.Injective (algebraMap R P)) (I : Ideal R) : FG ((I : FractionalIdeal S P) : Submodule R P) ↔ I.FG := coeSubmodule_fg _ inj _ theorem fg_unit (I : (FractionalIdeal S P)ˣ) : FG (I : Submodule R P) := Submodule.fg_unit <| Units.map (coeSubmoduleHom S P).toMonoidHom I theorem fg_of_isUnit (I : FractionalIdeal S P) (h : IsUnit I) : FG (I : Submodule R P) := fg_unit h.unit theorem _root_.Ideal.fg_of_isUnit (inj : Function.Injective (algebraMap R P)) (I : Ideal R) (h : IsUnit (I : FractionalIdeal S P)) : I.FG := by rw [← coeIdeal_fg S inj I] exact FractionalIdeal.fg_of_isUnit (R := R) I h variable (S P P') variable [IsLocalization S P] [IsLocalization S P'] /-- `canonicalEquiv f f'` is the canonical equivalence between the fractional ideals in `P` and in `P'`, which are both localizations of `R` at `S`. -/ noncomputable irreducible_def canonicalEquiv : FractionalIdeal S P ≃+* FractionalIdeal S P' := mapEquiv { ringEquivOfRingEquiv P P' (RingEquiv.refl R) (show S.map _ = S by rw [RingEquiv.toMonoidHom_refl, Submonoid.map_id]) with commutes' := fun _ => ringEquivOfRingEquiv_eq _ _ } @[simp] theorem mem_canonicalEquiv_apply {I : FractionalIdeal S P} {x : P'} : x ∈ canonicalEquiv S P P' I ↔ ∃ y ∈ I, IsLocalization.map P' (RingHom.id R) (fun y (hy : y ∈ S) => show RingHom.id R y ∈ S from hy) (y : P) = x := by rw [canonicalEquiv, mapEquiv_apply, mem_map] exact ⟨fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩, fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩⟩ @[simp] theorem canonicalEquiv_symm : (canonicalEquiv S P P').symm = canonicalEquiv S P' P := RingEquiv.ext fun I => SetLike.ext_iff.mpr fun x => by rw [mem_canonicalEquiv_apply, canonicalEquiv, mapEquiv_symm, mapEquiv_apply, mem_map] exact ⟨fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩, fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩⟩ theorem canonicalEquiv_flip (I) : canonicalEquiv S P P' (canonicalEquiv S P' P I) = I := by rw [← canonicalEquiv_symm, RingEquiv.symm_apply_apply] @[simp] theorem canonicalEquiv_canonicalEquiv (P'' : Type*) [CommRing P''] [Algebra R P''] [IsLocalization S P''] (I : FractionalIdeal S P) : canonicalEquiv S P' P'' (canonicalEquiv S P P' I) = canonicalEquiv S P P'' I := by ext simp only [IsLocalization.map_map, RingHomInvPair.comp_eq₂, mem_canonicalEquiv_apply, exists_prop, exists_exists_and_eq_and] theorem canonicalEquiv_trans_canonicalEquiv (P'' : Type*) [CommRing P''] [Algebra R P''] [IsLocalization S P''] : (canonicalEquiv S P P').trans (canonicalEquiv S P' P'') = canonicalEquiv S P P'' := RingEquiv.ext (canonicalEquiv_canonicalEquiv S P P' P'') @[simp] theorem canonicalEquiv_coeIdeal (I : Ideal R) : canonicalEquiv S P P' I = I := by ext simp [IsLocalization.map_eq] @[simp] theorem canonicalEquiv_self : canonicalEquiv S P P = RingEquiv.refl _ := by rw [← canonicalEquiv_trans_canonicalEquiv S P P] convert (canonicalEquiv S P P).symm_trans_self exact (canonicalEquiv_symm S P P).symm end section IsFractionRing /-! ### `IsFractionRing` section This section concerns fractional ideals in the field of fractions, i.e. the type `FractionalIdeal R⁰ K` where `IsFractionRing R K`. -/ variable {K K' : Type*} [Field K] [Field K'] variable [Algebra R K] [IsFractionRing R K] [Algebra R K'] [IsFractionRing R K'] variable {I J : FractionalIdeal R⁰ K} (h : K →ₐ[R] K') /-- Nonzero fractional ideals contain a nonzero integer. -/ theorem exists_ne_zero_mem_isInteger [Nontrivial R] (hI : I ≠ 0) : ∃ x, x ≠ 0 ∧ algebraMap R K x ∈ I := by obtain ⟨y : K, y_mem, y_not_mem⟩ := SetLike.exists_of_lt (by simpa only using bot_lt_iff_ne_bot.mpr hI) have y_ne_zero : y ≠ 0 := by simpa using y_not_mem obtain ⟨z, ⟨x, hx⟩⟩ := exists_integer_multiple R⁰ y refine ⟨x, ?_, ?_⟩ · rw [Ne, ← @IsFractionRing.to_map_eq_zero_iff R _ K, hx, Algebra.smul_def] exact mul_ne_zero (IsFractionRing.to_map_ne_zero_of_mem_nonZeroDivisors z.2) y_ne_zero · rw [hx] exact smul_mem _ _ y_mem theorem map_ne_zero [Nontrivial R] (hI : I ≠ 0) : I.map h ≠ 0 := by obtain ⟨x, x_ne_zero, hx⟩ := exists_ne_zero_mem_isInteger hI contrapose! x_ne_zero with map_eq_zero refine IsFractionRing.to_map_eq_zero_iff.mp (eq_zero_iff.mp map_eq_zero _ (mem_map.mpr ?_)) exact ⟨algebraMap R K x, hx, h.commutes x⟩ @[simp] theorem map_eq_zero_iff [Nontrivial R] : I.map h = 0 ↔ I = 0 := ⟨not_imp_not.mp (map_ne_zero _), fun hI => hI.symm ▸ FractionalIdeal.map_zero h⟩ theorem coeIdeal_injective : Function.Injective (fun (I : Ideal R) ↦ (I : FractionalIdeal R⁰ K)) := coeIdeal_injective' le_rfl theorem coeIdeal_inj {I J : Ideal R} : (I : FractionalIdeal R⁰ K) = (J : FractionalIdeal R⁰ K) ↔ I = J := coeIdeal_inj' le_rfl @[simp] theorem coeIdeal_eq_zero {I : Ideal R} : (I : FractionalIdeal R⁰ K) = 0 ↔ I = ⊥ := coeIdeal_eq_zero' le_rfl theorem coeIdeal_ne_zero {I : Ideal R} : (I : FractionalIdeal R⁰ K) ≠ 0 ↔ I ≠ ⊥ := coeIdeal_ne_zero' le_rfl @[simp] theorem coeIdeal_eq_one {I : Ideal R} : (I : FractionalIdeal R⁰ K) = 1 ↔ I = 1 := by simpa only [Ideal.one_eq_top] using coeIdeal_inj theorem coeIdeal_ne_one {I : Ideal R} : (I : FractionalIdeal R⁰ K) ≠ 1 ↔ I ≠ 1 := not_iff_not.mpr coeIdeal_eq_one theorem num_eq_zero_iff [Nontrivial R] {I : FractionalIdeal R⁰ K} : I.num = 0 ↔ I = 0 := ⟨fun h ↦ zero_of_num_eq_bot zero_not_mem_nonZeroDivisors h, fun h ↦ h ▸ num_zero_eq (IsFractionRing.injective R K)⟩ end IsFractionRing section Quotient /-! ### `quotient` section This section defines the ideal quotient of fractional ideals. In this section we need that each non-zero `y : R` has an inverse in the localization, i.e. that the localization is a field. We satisfy this assumption by taking `S = nonZeroDivisors R`, `R`'s localization at which is a field because `R` is a domain. -/ variable {R₁ : Type*} [CommRing R₁] {K : Type*} [Field K] variable [Algebra R₁ K] instance : Nontrivial (FractionalIdeal R₁⁰ K) := ⟨⟨0, 1, fun h => have this : (1 : K) ∈ (0 : FractionalIdeal R₁⁰ K) := by rw [← (algebraMap R₁ K).map_one] simpa only [h] using coe_mem_one R₁⁰ 1 one_ne_zero ((mem_zero_iff _).mp this)⟩⟩ theorem ne_zero_of_mul_eq_one (I J : FractionalIdeal R₁⁰ K) (h : I * J = 1) : I ≠ 0 := fun hI => zero_ne_one' (FractionalIdeal R₁⁰ K) (by convert h simp [hI]) variable [IsFractionRing R₁ K] [IsDomain R₁] theorem _root_.IsFractional.div_of_nonzero {I J : Submodule R₁ K} : IsFractional R₁⁰ I → IsFractional R₁⁰ J → J ≠ 0 → IsFractional R₁⁰ (I / J) | ⟨aI, haI, hI⟩, ⟨aJ, haJ, hJ⟩, h => by obtain ⟨y, mem_J, not_mem_zero⟩ := SetLike.exists_of_lt (show 0 < J by simpa only using bot_lt_iff_ne_bot.mpr h) obtain ⟨y', hy'⟩ := hJ y mem_J use aI * y' constructor · apply (nonZeroDivisors R₁).mul_mem haI (mem_nonZeroDivisors_iff_ne_zero.mpr _) intro y'_eq_zero have : algebraMap R₁ K aJ * y = 0 := by rw [← Algebra.smul_def, ← hy', y'_eq_zero, RingHom.map_zero] have y_zero := (mul_eq_zero.mp this).resolve_left (mt ((injective_iff_map_eq_zero (algebraMap R₁ K)).1 (IsFractionRing.injective _ _) _) (mem_nonZeroDivisors_iff_ne_zero.mp haJ)) apply not_mem_zero simpa intro b hb convert hI _ (hb _ (Submodule.smul_mem _ aJ mem_J)) using 1 rw [← hy', mul_comm b, ← Algebra.smul_def, mul_smul] theorem fractional_div_of_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) : IsFractional R₁⁰ (I / J : Submodule R₁ K) := I.isFractional.div_of_nonzero J.isFractional fun H => h <| coeToSubmodule_injective <| H.trans coe_zero.symm open Classical in noncomputable instance : Div (FractionalIdeal R₁⁰ K) := ⟨fun I J => if h : J = 0 then 0 else ⟨I / J, fractional_div_of_nonzero h⟩⟩ variable {I J : FractionalIdeal R₁⁰ K} @[simp] theorem div_zero {I : FractionalIdeal R₁⁰ K} : I / 0 = 0 := dif_pos rfl theorem div_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) : I / J = ⟨I / J, fractional_div_of_nonzero h⟩ := dif_neg h @[simp] theorem coe_div {I J : FractionalIdeal R₁⁰ K} (hJ : J ≠ 0) : (↑(I / J) : Submodule R₁ K) = ↑I / (↑J : Submodule R₁ K) := congr_arg _ (dif_neg hJ) theorem mem_div_iff_of_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) {x} : x ∈ I / J ↔ ∀ y ∈ J, x * y ∈ I := by rw [div_nonzero h] exact Submodule.mem_div_iff_forall_mul_mem theorem mul_one_div_le_one {I : FractionalIdeal R₁⁰ K} : I * (1 / I) ≤ 1 := by by_cases hI : I = 0 · rw [hI, div_zero, mul_zero] exact zero_le 1 · rw [← coe_le_coe, coe_mul, coe_div hI, coe_one] apply Submodule.mul_one_div_le_one theorem le_self_mul_one_div {I : FractionalIdeal R₁⁰ K} (hI : I ≤ (1 : FractionalIdeal R₁⁰ K)) : I ≤ I * (1 / I) := by by_cases hI_nz : I = 0 · rw [hI_nz, div_zero, mul_zero] · rw [← coe_le_coe, coe_mul, coe_div hI_nz, coe_one] rw [← coe_le_coe, coe_one] at hI exact Submodule.le_self_mul_one_div hI theorem le_div_iff_of_nonzero {I J J' : FractionalIdeal R₁⁰ K} (hJ' : J' ≠ 0) : I ≤ J / J' ↔ ∀ x ∈ I, ∀ y ∈ J', x * y ∈ J := ⟨fun h _ hx => (mem_div_iff_of_nonzero hJ').mp (h hx), fun h x hx => (mem_div_iff_of_nonzero hJ').mpr (h x hx)⟩ theorem le_div_iff_mul_le {I J J' : FractionalIdeal R₁⁰ K} (hJ' : J' ≠ 0) : I ≤ J / J' ↔ I * J' ≤ J := by rw [div_nonzero hJ'] -- Porting note: this used to be { convert; rw }, flipped the order. rw [← coe_le_coe (I := I * J') (J := J), coe_mul] exact Submodule.le_div_iff_mul_le @[simp] theorem div_one {I : FractionalIdeal R₁⁰ K} : I / 1 = I := by rw [div_nonzero (one_ne_zero' (FractionalIdeal R₁⁰ K))] ext constructor <;> intro h · simpa using mem_div_iff_forall_mul_mem.mp h 1 ((algebraMap R₁ K).map_one ▸ coe_mem_one R₁⁰ 1) · apply mem_div_iff_forall_mul_mem.mpr rintro y ⟨y', _, rfl⟩ -- Porting note: this used to be { convert; rw }, flipped the order. rw [mul_comm, Algebra.linearMap_apply, ← Algebra.smul_def] exact Submodule.smul_mem _ y' h theorem eq_one_div_of_mul_eq_one_right (I J : FractionalIdeal R₁⁰ K) (h : I * J = 1) : J = 1 / I := by have hI : I ≠ 0 := ne_zero_of_mul_eq_one I J h suffices h' : I * (1 / I) = 1 from congr_arg Units.inv <| @Units.ext _ _ (Units.mkOfMulEqOne _ _ h) (Units.mkOfMulEqOne _ _ h') rfl apply le_antisymm · apply mul_le.mpr _ intro x hx y hy rw [mul_comm] exact (mem_div_iff_of_nonzero hI).mp hy x hx rw [← h] apply mul_left_mono I apply (le_div_iff_of_nonzero hI).mpr _ intro y hy x hx rw [mul_comm] exact mul_mem_mul hy hx theorem mul_div_self_cancel_iff {I : FractionalIdeal R₁⁰ K} : I * (1 / I) = 1 ↔ ∃ J, I * J = 1 := ⟨fun h => ⟨1 / I, h⟩, fun ⟨J, hJ⟩ => by rwa [← eq_one_div_of_mul_eq_one_right I J hJ]⟩ variable {K' : Type*} [Field K'] [Algebra R₁ K'] [IsFractionRing R₁ K'] @[simp] protected theorem map_div (I J : FractionalIdeal R₁⁰ K) (h : K ≃ₐ[R₁] K') : (I / J).map (h : K →ₐ[R₁] K') = I.map h / J.map h := by by_cases H : J = 0 · rw [H, div_zero, FractionalIdeal.map_zero, div_zero] · -- Porting note: `simp` wouldn't apply these lemmas so do them manually using `rw` rw [← coeToSubmodule_inj, div_nonzero H, div_nonzero (map_ne_zero _ H)] simp [Submodule.map_div] -- Porting note: doesn't need to be @[simp] because this follows from `map_one` and `map_div` theorem map_one_div (I : FractionalIdeal R₁⁰ K) (h : K ≃ₐ[R₁] K') : (1 / I).map (h : K →ₐ[R₁] K') = 1 / I.map h := by rw [FractionalIdeal.map_div, FractionalIdeal.map_one] end Quotient section Field variable {R₁ K L : Type*} [CommRing R₁] [Field K] [Field L] variable [Algebra R₁ K] [IsFractionRing R₁ K] [Algebra K L] [IsFractionRing K L] theorem eq_zero_or_one (I : FractionalIdeal K⁰ L) : I = 0 ∨ I = 1 := by rw [or_iff_not_imp_left] intro hI simp_rw [@SetLike.ext_iff _ _ _ I 1, mem_one_iff] intro x constructor · intro x_mem obtain ⟨n, d, rfl⟩ := IsLocalization.mk'_surjective K⁰ x refine ⟨n / d, ?_⟩ rw [map_div₀, IsFractionRing.mk'_eq_div] · rintro ⟨x, rfl⟩ obtain ⟨y, y_ne, y_mem⟩ := exists_ne_zero_mem_isInteger hI rw [← div_mul_cancel₀ x y_ne, RingHom.map_mul, ← Algebra.smul_def] exact smul_mem (M := L) I (x / y) y_mem theorem eq_zero_or_one_of_isField (hF : IsField R₁) (I : FractionalIdeal R₁⁰ K) : I = 0 ∨ I = 1 := letI : Field R₁ := hF.toField eq_zero_or_one I end Field section PrincipalIdeal variable {R₁ : Type*} [CommRing R₁] {K : Type*} [Field K] variable [Algebra R₁ K] [IsFractionRing R₁ K] variable (R₁) /-- `FractionalIdeal.span_finset R₁ s f` is the fractional ideal of `R₁` generated by `f '' s`. -/ -- Porting note: `@[simps]` generated a `Subtype.val` coercion instead of a -- `FractionalIdeal.coeToSubmodule` coercion def spanFinset {ι : Type*} (s : Finset ι) (f : ι → K) : FractionalIdeal R₁⁰ K := ⟨Submodule.span R₁ (f '' s), by obtain ⟨a', ha'⟩ := IsLocalization.exist_integer_multiples R₁⁰ s f refine ⟨a', a'.2, fun x hx => Submodule.span_induction ?_ ?_ ?_ ?_ hx⟩ · rintro _ ⟨i, hi, rfl⟩ exact ha' i hi · rw [smul_zero] exact IsLocalization.isInteger_zero · intro x y _ _ hx hy rw [smul_add] exact IsLocalization.isInteger_add hx hy · intro c x _ hx rw [smul_comm] exact IsLocalization.isInteger_smul hx⟩ @[simp] lemma spanFinset_coe {ι : Type*} (s : Finset ι) (f : ι → K) : (spanFinset R₁ s f : Submodule R₁ K) = Submodule.span R₁ (f '' s) := rfl variable {R₁} @[simp] theorem spanFinset_eq_zero {ι : Type*} {s : Finset ι} {f : ι → K} : spanFinset R₁ s f = 0 ↔ ∀ j ∈ s, f j = 0 := by simp only [← coeToSubmodule_inj, spanFinset_coe, coe_zero, Submodule.span_eq_bot, Set.mem_image, Finset.mem_coe, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] theorem spanFinset_ne_zero {ι : Type*} {s : Finset ι} {f : ι → K} : spanFinset R₁ s f ≠ 0 ↔ ∃ j ∈ s, f j ≠ 0 := by simp open Submodule.IsPrincipal variable [IsLocalization S P] theorem isFractional_span_singleton (x : P) : IsFractional S (span R {x} : Submodule R P) := let ⟨a, ha⟩ := exists_integer_multiple S x isFractional_span_iff.mpr ⟨a, a.2, fun _ hx' => (Set.mem_singleton_iff.mp hx').symm ▸ ha⟩ variable (S) /-- `spanSingleton x` is the fractional ideal generated by `x` if `0 ∉ S` -/ irreducible_def spanSingleton (x : P) : FractionalIdeal S P := ⟨span R {x}, isFractional_span_singleton x⟩ -- local attribute [semireducible] span_singleton @[simp] theorem coe_spanSingleton (x : P) : (spanSingleton S x : Submodule R P) = span R {x} := by rw [spanSingleton] rfl @[simp] theorem mem_spanSingleton {x y : P} : x ∈ spanSingleton S y ↔ ∃ z : R, z • y = x := by rw [spanSingleton] exact Submodule.mem_span_singleton theorem mem_spanSingleton_self (x : P) : x ∈ spanSingleton S x := (mem_spanSingleton S).mpr ⟨1, one_smul _ _⟩ variable (P) in /-- A version of `FractionalIdeal.den_mul_self_eq_num` in terms of fractional ideals. -/ theorem den_mul_self_eq_num' (I : FractionalIdeal S P) : spanSingleton S (algebraMap R P I.den) * I = I.num := by apply coeToSubmodule_injective dsimp only rw [coe_mul, ← smul_eq_mul, coe_spanSingleton, smul_eq_mul, Submodule.span_singleton_mul] convert I.den_mul_self_eq_num using 1 ext rw [mem_smul_pointwise_iff_exists, mem_smul_pointwise_iff_exists] simp [smul_eq_mul, Algebra.smul_def, Submonoid.smul_def] variable {S} @[simp] theorem spanSingleton_le_iff_mem {x : P} {I : FractionalIdeal S P} : spanSingleton S x ≤ I ↔ x ∈ I := by rw [← coe_le_coe, coe_spanSingleton, Submodule.span_singleton_le_iff_mem, mem_coe] theorem spanSingleton_eq_spanSingleton [NoZeroSMulDivisors R P] {x y : P} : spanSingleton S x = spanSingleton S y ↔ ∃ z : Rˣ, z • x = y := by rw [← Submodule.span_singleton_eq_span_singleton, spanSingleton, spanSingleton] exact Subtype.mk_eq_mk theorem eq_spanSingleton_of_principal (I : FractionalIdeal S P) [IsPrincipal (I : Submodule R P)] : I = spanSingleton S (generator (I : Submodule R P)) := by -- Porting note: this used to be `coeToSubmodule_injective (span_singleton_generator ↑I).symm` -- but Lean 4 struggled to unify everything. Turned it into an explicit `rw`. rw [spanSingleton, ← coeToSubmodule_inj, coe_mk, span_singleton_generator] theorem isPrincipal_iff (I : FractionalIdeal S P) : IsPrincipal (I : Submodule R P) ↔ ∃ x, I = spanSingleton S x := ⟨fun _ => ⟨generator (I : Submodule R P), eq_spanSingleton_of_principal I⟩, fun ⟨x, hx⟩ => { principal := ⟨x, Eq.trans (congr_arg _ hx) (coe_spanSingleton _ x)⟩ }⟩ @[simp] theorem spanSingleton_zero : spanSingleton S (0 : P) = 0 := by ext simp [Submodule.mem_span_singleton, eq_comm] theorem spanSingleton_eq_zero_iff {y : P} : spanSingleton S y = 0 ↔ y = 0 := ⟨fun h => span_eq_bot.mp (by simpa using congr_arg Subtype.val h : span R {y} = ⊥) y (mem_singleton y), fun h => by simp [h]⟩ theorem spanSingleton_ne_zero_iff {y : P} : spanSingleton S y ≠ 0 ↔ y ≠ 0 := not_congr spanSingleton_eq_zero_iff @[simp] theorem spanSingleton_one : spanSingleton S (1 : P) = 1 := by ext refine (mem_spanSingleton S).trans ((exists_congr ?_).trans (mem_one_iff S).symm) intro x' rw [Algebra.smul_def, mul_one] @[simp] theorem spanSingleton_mul_spanSingleton (x y : P) : spanSingleton S x * spanSingleton S y = spanSingleton S (x * y) := by apply coeToSubmodule_injective simp only [coe_mul, coe_spanSingleton, span_mul_span, singleton_mul_singleton] @[simp] theorem spanSingleton_pow (x : P) (n : ℕ) : spanSingleton S x ^ n = spanSingleton S (x ^ n) := by induction' n with n hn · rw [pow_zero, pow_zero, spanSingleton_one] · rw [pow_succ, hn, spanSingleton_mul_spanSingleton, pow_succ] @[simp] theorem coeIdeal_span_singleton (x : R) : (↑(Ideal.span {x} : Ideal R) : FractionalIdeal S P) = spanSingleton S (algebraMap R P x) := by ext y refine (mem_coeIdeal S).trans (Iff.trans ?_ (mem_spanSingleton S).symm) constructor · rintro ⟨y', hy', rfl⟩ obtain ⟨x', rfl⟩ := Submodule.mem_span_singleton.mp hy' use x' rw [smul_eq_mul, RingHom.map_mul, Algebra.smul_def] · rintro ⟨y', rfl⟩ refine ⟨y' * x, Submodule.mem_span_singleton.mpr ⟨y', rfl⟩, ?_⟩ rw [RingHom.map_mul, Algebra.smul_def] @[simp] theorem canonicalEquiv_spanSingleton {P'} [CommRing P'] [Algebra R P'] [IsLocalization S P'] (x : P) : canonicalEquiv S P P' (spanSingleton S x) = spanSingleton S (IsLocalization.map P' (RingHom.id R) (fun y (hy : y ∈ S) => show RingHom.id R y ∈ S from hy) x) := by apply SetLike.ext_iff.mpr intro y constructor <;> intro h · rw [mem_spanSingleton] obtain ⟨x', hx', rfl⟩ := (mem_canonicalEquiv_apply _ _ _).mp h obtain ⟨z, rfl⟩ := (mem_spanSingleton _).mp hx' use z rw [IsLocalization.map_smul, RingHom.id_apply] · rw [mem_canonicalEquiv_apply] obtain ⟨z, rfl⟩ := (mem_spanSingleton _).mp h use z • x use (mem_spanSingleton _).mpr ⟨z, rfl⟩ simp [IsLocalization.map_smul] theorem mem_singleton_mul {x y : P} {I : FractionalIdeal S P} : y ∈ spanSingleton S x * I ↔ ∃ y' ∈ I, y = x * y' := by constructor · intro h refine FractionalIdeal.mul_induction_on h ?_ ?_ · intro x' hx' y' hy' obtain ⟨a, ha⟩ := (mem_spanSingleton S).mp hx' use a • y', Submodule.smul_mem (I : Submodule R P) a hy' rw [← ha, Algebra.mul_smul_comm, Algebra.smul_mul_assoc] · rintro _ _ ⟨y, hy, rfl⟩ ⟨y', hy', rfl⟩ exact ⟨y + y', Submodule.add_mem (I : Submodule R P) hy hy', (mul_add _ _ _).symm⟩ · rintro ⟨y', hy', rfl⟩ exact mul_mem_mul ((mem_spanSingleton S).mpr ⟨1, one_smul _ _⟩) hy' variable (K) in theorem mk'_mul_coeIdeal_eq_coeIdeal {I J : Ideal R₁} {x y : R₁} (hy : y ∈ R₁⁰) : spanSingleton R₁⁰ (IsLocalization.mk' K x ⟨y, hy⟩) * I = (J : FractionalIdeal R₁⁰ K) ↔ Ideal.span {x} * I = Ideal.span {y} * J := by have : spanSingleton R₁⁰ (IsLocalization.mk' _ (1 : R₁) ⟨y, hy⟩) * spanSingleton R₁⁰ (algebraMap R₁ K y) = 1 := by rw [spanSingleton_mul_spanSingleton, mul_comm, ← IsLocalization.mk'_eq_mul_mk'_one, IsLocalization.mk'_self, spanSingleton_one] let y' : (FractionalIdeal R₁⁰ K)ˣ := Units.mkOfMulEqOne _ _ this have coe_y' : ↑y' = spanSingleton R₁⁰ (IsLocalization.mk' K (1 : R₁) ⟨y, hy⟩) := rfl refine Iff.trans ?_ (y'.mul_right_inj.trans coeIdeal_inj) rw [coe_y', coeIdeal_mul, coeIdeal_span_singleton, coeIdeal_mul, coeIdeal_span_singleton, ← mul_assoc, spanSingleton_mul_spanSingleton, ← mul_assoc, spanSingleton_mul_spanSingleton, mul_comm (mk' _ _ _), ← IsLocalization.mk'_eq_mul_mk'_one, mul_comm (mk' _ _ _), ← IsLocalization.mk'_eq_mul_mk'_one, IsLocalization.mk'_self, spanSingleton_one, one_mul] theorem spanSingleton_mul_coeIdeal_eq_coeIdeal {I J : Ideal R₁} {z : K} : spanSingleton R₁⁰ z * (I : FractionalIdeal R₁⁰ K) = J ↔ Ideal.span {((IsLocalization.sec R₁⁰ z).1 : R₁)} * I = Ideal.span {((IsLocalization.sec R₁⁰ z).2 : R₁)} * J := by rw [← mk'_mul_coeIdeal_eq_coeIdeal K (IsLocalization.sec R₁⁰ z).2.prop, IsLocalization.mk'_sec K z] variable [IsDomain R₁] theorem one_div_spanSingleton (x : K) : 1 / spanSingleton R₁⁰ x = spanSingleton R₁⁰ x⁻¹ := by classical exact if h : x = 0 then by simp [h] else (eq_one_div_of_mul_eq_one_right _ _ (by simp [h])).symm @[simp] theorem div_spanSingleton (J : FractionalIdeal R₁⁰ K) (d : K) : J / spanSingleton R₁⁰ d = spanSingleton R₁⁰ d⁻¹ * J := by rw [← one_div_spanSingleton] by_cases hd : d = 0 · simp only [hd, spanSingleton_zero, div_zero, zero_mul] have h_spand : spanSingleton R₁⁰ d ≠ 0 := mt spanSingleton_eq_zero_iff.mp hd apply le_antisymm · intro x hx dsimp only [val_eq_coe] at hx ⊢ -- Porting note: get rid of the partially applied `coe`s rw [coe_div h_spand, Submodule.mem_div_iff_forall_mul_mem] at hx specialize hx d (mem_spanSingleton_self R₁⁰ d) have h_xd : x = d⁻¹ * (x * d) := by field_simp rw [coe_mul, one_div_spanSingleton, h_xd] exact Submodule.mul_mem_mul (mem_spanSingleton_self R₁⁰ _) hx · rw [le_div_iff_mul_le h_spand, mul_assoc, mul_left_comm, one_div_spanSingleton, spanSingleton_mul_spanSingleton, inv_mul_cancel₀ hd, spanSingleton_one, mul_one] theorem exists_eq_spanSingleton_mul (I : FractionalIdeal R₁⁰ K) : ∃ (a : R₁) (aI : Ideal R₁), a ≠ 0 ∧ I = spanSingleton R₁⁰ (algebraMap R₁ K a)⁻¹ * aI := by obtain ⟨a_inv, nonzero, ha⟩ := I.isFractional have nonzero := mem_nonZeroDivisors_iff_ne_zero.mp nonzero have map_a_nonzero : algebraMap R₁ K a_inv ≠ 0 := mt IsFractionRing.to_map_eq_zero_iff.mp nonzero refine ⟨a_inv, Submodule.comap (Algebra.linearMap R₁ K) ↑(spanSingleton R₁⁰ (algebraMap R₁ K a_inv) * I), nonzero, ext fun x => Iff.trans ⟨?_, ?_⟩ mem_singleton_mul.symm⟩ · intro hx obtain ⟨x', hx'⟩ := ha x hx rw [Algebra.smul_def] at hx' refine ⟨algebraMap R₁ K x', (mem_coeIdeal _).mpr ⟨x', mem_singleton_mul.mpr ?_, rfl⟩, ?_⟩ · exact ⟨x, hx, hx'⟩ · rw [hx', ← mul_assoc, inv_mul_cancel₀ map_a_nonzero, one_mul] · rintro ⟨y, hy, rfl⟩ obtain ⟨x', hx', rfl⟩ := (mem_coeIdeal _).mp hy obtain ⟨y', hy', hx'⟩ := mem_singleton_mul.mp hx' rw [Algebra.linearMap_apply] at hx' rwa [hx', ← mul_assoc, inv_mul_cancel₀ map_a_nonzero, one_mul] /-- If `I` is a nonzero fractional ideal, `a ∈ R`, and `J` is an ideal of `R` such that `I = a⁻¹J`, then `J` is nonzero. -/ theorem ideal_factor_ne_zero {R} [CommRing R] {K : Type*} [Field K] [Algebra R K] [IsFractionRing R K] {I : FractionalIdeal R⁰ K} (hI : I ≠ 0) {a : R} {J : Ideal R} (haJ : I = spanSingleton R⁰ ((algebraMap R K) a)⁻¹ * ↑J) : J ≠ 0 := fun h ↦ by rw [h, Ideal.zero_eq_bot, coeIdeal_bot, MulZeroClass.mul_zero] at haJ exact hI haJ /-- If `I` is a nonzero fractional ideal, `a ∈ R`, and `J` is an ideal of `R` such that `I = a⁻¹J`, then `a` is nonzero. -/ theorem constant_factor_ne_zero {R} [CommRing R] {K : Type*} [Field K] [Algebra R K] [IsFractionRing R K] {I : FractionalIdeal R⁰ K} (hI : I ≠ 0) {a : R} {J : Ideal R} (haJ : I = spanSingleton R⁰ ((algebraMap R K) a)⁻¹ * ↑J) : (Ideal.span {a} : Ideal R) ≠ 0 := fun h ↦ by rw [Ideal.zero_eq_bot, Ideal.span_singleton_eq_bot] at h rw [h, RingHom.map_zero, inv_zero, spanSingleton_zero, MulZeroClass.zero_mul] at haJ exact hI haJ instance isPrincipal {R} [CommRing R] [IsDomain R] [IsPrincipalIdealRing R] [Algebra R K] [IsFractionRing R K] (I : FractionalIdeal R⁰ K) : (I : Submodule R K).IsPrincipal := by obtain ⟨a, aI, -, ha⟩ := exists_eq_spanSingleton_mul I use (algebraMap R K a)⁻¹ * algebraMap R K (generator aI) suffices I = spanSingleton R⁰ ((algebraMap R K a)⁻¹ * algebraMap R K (generator aI)) by rw [spanSingleton] at this exact congr_arg Subtype.val this conv_lhs => rw [ha, ← span_singleton_generator aI] rw [Ideal.submodule_span_eq, coeIdeal_span_singleton (generator aI), spanSingleton_mul_spanSingleton] theorem le_spanSingleton_mul_iff {x : P} {I J : FractionalIdeal S P} : I ≤ spanSingleton S x * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI := show (∀ {zI} (_ : zI ∈ I), zI ∈ spanSingleton _ x * J) ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI by simp only [mem_singleton_mul, eq_comm] theorem spanSingleton_mul_le_iff {x : P} {I J : FractionalIdeal S P} : spanSingleton _ x * I ≤ J ↔ ∀ z ∈ I, x * z ∈ J := by simp only [mul_le, mem_singleton_mul, mem_spanSingleton] constructor · intro h zI hzI exact h x ⟨1, one_smul _ _⟩ zI hzI · rintro h _ ⟨z, rfl⟩ zI hzI rw [Algebra.smul_mul_assoc] exact Submodule.smul_mem J.1 _ (h zI hzI) theorem eq_spanSingleton_mul {x : P} {I J : FractionalIdeal S P} : I = spanSingleton _ x * J ↔ (∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI) ∧ ∀ z ∈ J, x * z ∈ I := by simp only [le_antisymm_iff, le_spanSingleton_mul_iff, spanSingleton_mul_le_iff] theorem num_le (I : FractionalIdeal S P) : (I.num : FractionalIdeal S P) ≤ I := by rw [← I.den_mul_self_eq_num', spanSingleton_mul_le_iff] intro _ h rw [← Algebra.smul_def] exact Submodule.smul_mem _ _ h end PrincipalIdeal variable {R₁ : Type*} [CommRing R₁] variable {K : Type*} [Field K] [Algebra R₁ K] theorem isNoetherian_zero : IsNoetherian R₁ (0 : FractionalIdeal R₁⁰ K) := isNoetherian_submodule.mpr fun I (hI : I ≤ (0 : FractionalIdeal R₁⁰ K)) => by rw [coe_zero, le_bot_iff] at hI rw [hI] exact fg_bot theorem isNoetherian_iff {I : FractionalIdeal R₁⁰ K} : IsNoetherian R₁ I ↔ ∀ J ≤ I, (J : Submodule R₁ K).FG := isNoetherian_submodule.trans ⟨fun h _ hJ => h _ hJ, fun h J hJ => h ⟨J, isFractional_of_le hJ⟩ hJ⟩ theorem isNoetherian_coeIdeal [IsNoetherianRing R₁] (I : Ideal R₁) : IsNoetherian R₁ (I : FractionalIdeal R₁⁰ K) := by rw [isNoetherian_iff] intro J hJ obtain ⟨J, rfl⟩ := le_one_iff_exists_coeIdeal.mp (le_trans hJ coeIdeal_le_one) exact (IsNoetherian.noetherian J).map _ variable [IsFractionRing R₁ K] [IsDomain R₁] theorem isNoetherian_spanSingleton_inv_to_map_mul (x : R₁) {I : FractionalIdeal R₁⁰ K} (hI : IsNoetherian R₁ I) : IsNoetherian R₁ (spanSingleton R₁⁰ (algebraMap R₁ K x)⁻¹ * I : FractionalIdeal R₁⁰ K) := by classical by_cases hx : x = 0 · rw [hx, RingHom.map_zero, inv_zero, spanSingleton_zero, zero_mul] exact isNoetherian_zero have h_gx : algebraMap R₁ K x ≠ 0 := mt ((injective_iff_map_eq_zero (algebraMap R₁ K)).mp (IsFractionRing.injective _ _) x) hx have h_spanx : spanSingleton R₁⁰ (algebraMap R₁ K x) ≠ 0 := spanSingleton_ne_zero_iff.mpr h_gx rw [isNoetherian_iff] at hI ⊢ intro J hJ rw [← div_spanSingleton, le_div_iff_mul_le h_spanx] at hJ obtain ⟨s, hs⟩ := hI _ hJ use s * {(algebraMap R₁ K x)⁻¹} rw [Finset.coe_mul, Finset.coe_singleton, ← span_mul_span, hs, ← coe_spanSingleton R₁⁰, ← coe_mul, mul_assoc, spanSingleton_mul_spanSingleton, mul_inv_cancel₀ h_gx, spanSingleton_one, mul_one] /-- Every fractional ideal of a noetherian integral domain is noetherian. -/ theorem isNoetherian [IsNoetherianRing R₁] (I : FractionalIdeal R₁⁰ K) : IsNoetherian R₁ I := by obtain ⟨d, J, _, rfl⟩ := exists_eq_spanSingleton_mul I apply isNoetherian_spanSingleton_inv_to_map_mul apply isNoetherian_coeIdeal section Adjoin variable (S) variable [IsLocalization S P] (x : P) /-- `A[x]` is a fractional ideal for every integral `x`. -/ theorem isFractional_adjoin_integral (hx : IsIntegral R x) : IsFractional S (Subalgebra.toSubmodule (Algebra.adjoin R ({x} : Set P))) := isFractional_of_fg hx.fg_adjoin_singleton /-- `FractionalIdeal.adjoinIntegral (S : Submonoid R) x hx` is `R[x]` as a fractional ideal, where `hx` is a proof that `x : P` is integral over `R`. -/ -- Porting note: `@[simps]` generated a `Subtype.val` coercion instead of a -- `FractionalIdeal.coeToSubmodule` coercion def adjoinIntegral (hx : IsIntegral R x) : FractionalIdeal S P := ⟨_, isFractional_adjoin_integral S x hx⟩ @[simp] theorem adjoinIntegral_coe (hx : IsIntegral R x) : (adjoinIntegral S x hx : Submodule R P) = (Subalgebra.toSubmodule (Algebra.adjoin R ({x} : Set P))) := rfl theorem mem_adjoinIntegral_self (hx : IsIntegral R x) : x ∈ adjoinIntegral S x hx := Algebra.subset_adjoin (Set.mem_singleton x) end Adjoin end FractionalIdeal
Mathlib/RingTheory/FractionalIdeal/Operations.lean
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/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.CategoryTheory.Limits.Shapes.Pullback.CommSq import Mathlib.CategoryTheory.Limits.Shapes.StrictInitial import Mathlib.CategoryTheory.Limits.Types.Shapes import Mathlib.Topology.Category.TopCat.Limits.Pullbacks import Mathlib.CategoryTheory.Limits.FunctorCategory.Basic import Mathlib.CategoryTheory.Limits.Constructions.FiniteProductsOfBinaryProducts import Mathlib.CategoryTheory.Limits.VanKampen /-! # Extensive categories ## Main definitions - `CategoryTheory.FinitaryExtensive`: A category is (finitary) extensive if it has finite coproducts, and binary coproducts are van Kampen. ## Main Results - `CategoryTheory.hasStrictInitialObjects_of_finitaryExtensive`: The initial object in extensive categories is strict. - `CategoryTheory.FinitaryExtensive.mono_inr_of_isColimit`: Coproduct injections are monic in extensive categories. - `CategoryTheory.BinaryCofan.isPullback_initial_to_of_isVanKampen`: In extensive categories, sums are disjoint, i.e. the pullback of `X ⟶ X ⨿ Y` and `Y ⟶ X ⨿ Y` is the initial object. - `CategoryTheory.types.finitaryExtensive`: The category of types is extensive. - `CategoryTheory.FinitaryExtensive_TopCat`: The category `Top` is extensive. - `CategoryTheory.FinitaryExtensive_functor`: The category `C ⥤ D` is extensive if `D` has all pullbacks and is extensive. - `CategoryTheory.FinitaryExtensive.isVanKampen_finiteCoproducts`: Finite coproducts in a finitary extensive category are van Kampen. ## TODO Show that the following are finitary extensive: - `Scheme` - `AffineScheme` (`CommRingᵒᵖ`) ## References - https://ncatlab.org/nlab/show/extensive+category - [Carboni et al, Introduction to extensive and distributive categories][CARBONI1993145] -/ open CategoryTheory.Limits Topology namespace CategoryTheory universe v' u' v u v'' u'' variable {J : Type v'} [Category.{u'} J] {C : Type u} [Category.{v} C] variable {D : Type u''} [Category.{v''} D] section Extensive variable {X Y : C} /-- A category has pullback of inclusions if it has all pullbacks along coproduct injections. -/ class HasPullbacksOfInclusions (C : Type u) [Category.{v} C] [HasBinaryCoproducts C] : Prop where [hasPullbackInl : ∀ {X Y Z : C} (f : Z ⟶ X ⨿ Y), HasPullback coprod.inl f] attribute [instance] HasPullbacksOfInclusions.hasPullbackInl /-- A functor preserves pullback of inclusions if it preserves all pullbacks along coproduct injections. -/ class PreservesPullbacksOfInclusions {C : Type*} [Category C] {D : Type*} [Category D] (F : C ⥤ D) [HasBinaryCoproducts C] where [preservesPullbackInl : ∀ {X Y Z : C} (f : Z ⟶ X ⨿ Y), PreservesLimit (cospan coprod.inl f) F] attribute [instance] PreservesPullbacksOfInclusions.preservesPullbackInl /-- A category is (finitary) pre-extensive if it has finite coproducts, and binary coproducts are universal. -/ class FinitaryPreExtensive (C : Type u) [Category.{v} C] : Prop where [hasFiniteCoproducts : HasFiniteCoproducts C] [hasPullbacksOfInclusions : HasPullbacksOfInclusions C] /-- In a finitary extensive category, all coproducts are van Kampen -/ universal' : ∀ {X Y : C} (c : BinaryCofan X Y), IsColimit c → IsUniversalColimit c attribute [instance] FinitaryPreExtensive.hasFiniteCoproducts attribute [instance] FinitaryPreExtensive.hasPullbacksOfInclusions /-- A category is (finitary) extensive if it has finite coproducts, and binary coproducts are van Kampen. -/ class FinitaryExtensive (C : Type u) [Category.{v} C] : Prop where [hasFiniteCoproducts : HasFiniteCoproducts C] [hasPullbacksOfInclusions : HasPullbacksOfInclusions C] /-- In a finitary extensive category, all coproducts are van Kampen -/ van_kampen' : ∀ {X Y : C} (c : BinaryCofan X Y), IsColimit c → IsVanKampenColimit c attribute [instance] FinitaryExtensive.hasFiniteCoproducts attribute [instance] FinitaryExtensive.hasPullbacksOfInclusions theorem FinitaryExtensive.vanKampen [FinitaryExtensive C] {F : Discrete WalkingPair ⥤ C} (c : Cocone F) (hc : IsColimit c) : IsVanKampenColimit c := by let X := F.obj ⟨WalkingPair.left⟩ let Y := F.obj ⟨WalkingPair.right⟩ have : F = pair X Y := by apply Functor.hext · rintro ⟨⟨⟩⟩ <;> rfl · rintro ⟨⟨⟩⟩ ⟨j⟩ ⟨⟨rfl : _ = j⟩⟩ <;> simp [X, Y] clear_value X Y subst this exact FinitaryExtensive.van_kampen' c hc namespace HasPullbacksOfInclusions instance (priority := 100) [HasBinaryCoproducts C] [HasPullbacks C] : HasPullbacksOfInclusions C := ⟨⟩ variable [HasBinaryCoproducts C] [HasPullbacksOfInclusions C] {X Y Z : C} (f : Z ⟶ X ⨿ Y) instance preservesPullbackInl' : HasPullback f coprod.inl := hasPullback_symmetry _ _ instance hasPullbackInr' : HasPullback f coprod.inr := by have : IsPullback (𝟙 _) (f ≫ (coprod.braiding X Y).hom) f (coprod.braiding Y X).hom := IsPullback.of_horiz_isIso ⟨by simp⟩ have := (IsPullback.of_hasPullback (f ≫ (coprod.braiding X Y).hom) coprod.inl).paste_horiz this simp only [coprod.braiding_hom, Category.comp_id, colimit.ι_desc, BinaryCofan.mk_pt, BinaryCofan.ι_app_left, BinaryCofan.mk_inl] at this exact ⟨⟨⟨_, this.isLimit⟩⟩⟩ instance hasPullbackInr : HasPullback coprod.inr f := hasPullback_symmetry _ _ end HasPullbacksOfInclusions namespace PreservesPullbacksOfInclusions variable {D : Type*} [Category D] [HasBinaryCoproducts C] (F : C ⥤ D) noncomputable instance (priority := 100) [PreservesLimitsOfShape WalkingCospan F] : PreservesPullbacksOfInclusions F := ⟨⟩ variable [PreservesPullbacksOfInclusions F] {X Y Z : C} (f : Z ⟶ X ⨿ Y) noncomputable instance preservesPullbackInl' : PreservesLimit (cospan f coprod.inl) F := preservesPullback_symmetry _ _ _ noncomputable instance preservesPullbackInr' : PreservesLimit (cospan f coprod.inr) F := by apply preservesLimit_of_iso_diagram (K₁ := cospan (f ≫ (coprod.braiding X Y).hom) coprod.inl) apply cospanExt (Iso.refl _) (Iso.refl _) (coprod.braiding X Y).symm <;> simp noncomputable instance preservesPullbackInr : PreservesLimit (cospan coprod.inr f) F := preservesPullback_symmetry _ _ _ end PreservesPullbacksOfInclusions instance (priority := 100) FinitaryExtensive.toFinitaryPreExtensive [FinitaryExtensive C] : FinitaryPreExtensive C := ⟨fun c hc ↦ (FinitaryExtensive.van_kampen' c hc).isUniversal⟩ theorem FinitaryExtensive.mono_inr_of_isColimit [FinitaryExtensive C] {c : BinaryCofan X Y} (hc : IsColimit c) : Mono c.inr := BinaryCofan.mono_inr_of_isVanKampen (FinitaryExtensive.vanKampen c hc) theorem FinitaryExtensive.mono_inl_of_isColimit [FinitaryExtensive C] {c : BinaryCofan X Y} (hc : IsColimit c) : Mono c.inl := FinitaryExtensive.mono_inr_of_isColimit (BinaryCofan.isColimitFlip hc) instance [FinitaryExtensive C] (X Y : C) : Mono (coprod.inl : X ⟶ X ⨿ Y) := (FinitaryExtensive.mono_inl_of_isColimit (coprodIsCoprod X Y) :) instance [FinitaryExtensive C] (X Y : C) : Mono (coprod.inr : Y ⟶ X ⨿ Y) := (FinitaryExtensive.mono_inr_of_isColimit (coprodIsCoprod X Y) :) theorem FinitaryExtensive.isPullback_initial_to_binaryCofan [FinitaryExtensive C] {c : BinaryCofan X Y} (hc : IsColimit c) : IsPullback (initial.to _) (initial.to _) c.inl c.inr := BinaryCofan.isPullback_initial_to_of_isVanKampen (FinitaryExtensive.vanKampen c hc) instance (priority := 100) hasStrictInitialObjects_of_finitaryPreExtensive [FinitaryPreExtensive C] : HasStrictInitialObjects C := hasStrictInitial_of_isUniversal (FinitaryPreExtensive.universal' _ ((BinaryCofan.isColimit_iff_isIso_inr initialIsInitial _).mpr (by dsimp infer_instance)).some) theorem finitaryExtensive_iff_of_isTerminal (C : Type u) [Category.{v} C] [HasFiniteCoproducts C] [HasPullbacksOfInclusions C] (T : C) (HT : IsTerminal T) (c₀ : BinaryCofan T T) (hc₀ : IsColimit c₀) : FinitaryExtensive C ↔ IsVanKampenColimit c₀ := by refine ⟨fun H => H.van_kampen' c₀ hc₀, fun H => ?_⟩ constructor simp_rw [BinaryCofan.isVanKampen_iff] at H ⊢ intro X Y c hc X' Y' c' αX αY f hX hY obtain ⟨d, hd, hd'⟩ := Limits.BinaryCofan.IsColimit.desc' hc (HT.from _ ≫ c₀.inl) (HT.from _ ≫ c₀.inr) rw [H c' (αX ≫ HT.from _) (αY ≫ HT.from _) (f ≫ d) (by rw [← reassoc_of% hX, hd, Category.assoc]) (by rw [← reassoc_of% hY, hd', Category.assoc])] obtain ⟨hl, hr⟩ := (H c (HT.from _) (HT.from _) d hd.symm hd'.symm).mp ⟨hc⟩ rw [hl.paste_vert_iff hX.symm, hr.paste_vert_iff hY.symm] instance types.finitaryExtensive : FinitaryExtensive (Type u) := by classical rw [finitaryExtensive_iff_of_isTerminal (Type u) PUnit Types.isTerminalPunit _ (Types.binaryCoproductColimit _ _)] apply BinaryCofan.isVanKampen_mk _ _ (fun X Y => Types.binaryCoproductColimit X Y) _ fun f g => (Limits.Types.pullbackLimitCone f g).2 · intros _ _ _ _ f hαX hαY constructor · refine ⟨⟨hαX.symm⟩, ⟨PullbackCone.isLimitAux' _ ?_⟩⟩ intro s have : ∀ x, ∃! y, s.fst x = Sum.inl y := by intro x rcases h : s.fst x with val | val · simp only [Types.binaryCoproductCocone_pt, Functor.const_obj_obj, Sum.inl.injEq, existsUnique_eq'] · apply_fun f at h cases ((congr_fun s.condition x).symm.trans h).trans (congr_fun hαY val :).symm delta ExistsUnique at this choose l hl hl' using this exact ⟨l, (funext hl).symm, Types.isTerminalPunit.hom_ext _ _, fun {l'} h₁ _ => funext fun x => hl' x (l' x) (congr_fun h₁ x).symm⟩ · refine ⟨⟨hαY.symm⟩, ⟨PullbackCone.isLimitAux' _ ?_⟩⟩ intro s have : ∀ x, ∃! y, s.fst x = Sum.inr y := by intro x rcases h : s.fst x with val | val · apply_fun f at h cases ((congr_fun s.condition x).symm.trans h).trans (congr_fun hαX val :).symm · simp only [Types.binaryCoproductCocone_pt, Functor.const_obj_obj, Sum.inr.injEq, existsUnique_eq'] delta ExistsUnique at this choose l hl hl' using this exact ⟨l, (funext hl).symm, Types.isTerminalPunit.hom_ext _ _, fun {l'} h₁ _ => funext fun x => hl' x (l' x) (congr_fun h₁ x).symm⟩ · intro Z f dsimp [Limits.Types.binaryCoproductCocone] delta Types.PullbackObj have : ∀ x, f x = Sum.inl PUnit.unit ∨ f x = Sum.inr PUnit.unit := by intro x rcases f x with (⟨⟨⟩⟩ | ⟨⟨⟩⟩) exacts [Or.inl rfl, Or.inr rfl] let eX : { p : Z × PUnit // f p.fst = Sum.inl p.snd } ≃ { x : Z // f x = Sum.inl PUnit.unit } := ⟨fun p => ⟨p.1.1, by convert p.2⟩, fun x => ⟨⟨_, _⟩, x.2⟩, fun _ => by ext; rfl, fun _ => by ext; rfl⟩ let eY : { p : Z × PUnit // f p.fst = Sum.inr p.snd } ≃ { x : Z // f x = Sum.inr PUnit.unit } := ⟨fun p => ⟨p.1.1, p.2.trans (congr_arg Sum.inr <| Subsingleton.elim _ _)⟩, fun x => ⟨⟨_, _⟩, x.2⟩, fun _ => by ext; rfl, fun _ => by ext; rfl⟩ fapply BinaryCofan.isColimitMk · exact fun s x => dite _ (fun h => s.inl <| eX.symm ⟨x, h⟩) fun h => s.inr <| eY.symm ⟨x, (this x).resolve_left h⟩ · intro s ext ⟨⟨x, ⟨⟩⟩, _⟩ dsimp split_ifs <;> rfl · intro s ext ⟨⟨x, ⟨⟩⟩, hx⟩ dsimp split_ifs with h · cases h.symm.trans hx · rfl · intro s m e₁ e₂ ext x split_ifs · rw [← e₁] rfl · rw [← e₂] rfl section TopCat /-- (Implementation) An auxiliary lemma for the proof that `TopCat` is finitary extensive. -/ noncomputable def finitaryExtensiveTopCatAux (Z : TopCat.{u}) (f : Z ⟶ TopCat.of (PUnit.{u + 1} ⊕ PUnit.{u + 1})) : IsColimit (BinaryCofan.mk (TopCat.pullbackFst f (TopCat.binaryCofan (TopCat.of PUnit) (TopCat.of PUnit)).inl) (TopCat.pullbackFst f (TopCat.binaryCofan (TopCat.of PUnit) (TopCat.of PUnit)).inr)) := by have h₁ : Set.range (TopCat.pullbackFst f (TopCat.binaryCofan (.of PUnit) (.of PUnit)).inl) = f ⁻¹' Set.range Sum.inl := by apply le_antisymm · rintro _ ⟨x, rfl⟩; exact ⟨PUnit.unit, x.2.symm⟩ · rintro x ⟨⟨⟩, hx⟩; refine ⟨⟨⟨x, PUnit.unit⟩, hx.symm⟩, rfl⟩ have h₂ : Set.range (TopCat.pullbackFst f (TopCat.binaryCofan (.of PUnit) (.of PUnit)).inr) = f ⁻¹' Set.range Sum.inr := by apply le_antisymm · rintro _ ⟨x, rfl⟩; exact ⟨PUnit.unit, x.2.symm⟩ · rintro x ⟨⟨⟩, hx⟩; refine ⟨⟨⟨x, PUnit.unit⟩, hx.symm⟩, rfl⟩ refine ((TopCat.binaryCofan_isColimit_iff _).mpr ⟨?_, ?_, ?_⟩).some · refine ⟨(Homeomorph.prodPUnit Z).isEmbedding.comp .subtypeVal, ?_⟩ convert f.hom.2.1 _ isOpen_range_inl · refine ⟨(Homeomorph.prodPUnit Z).isEmbedding.comp .subtypeVal, ?_⟩ convert f.hom.2.1 _ isOpen_range_inr · convert Set.isCompl_range_inl_range_inr.preimage f instance finitaryExtensive_TopCat : FinitaryExtensive TopCat.{u} := by rw [finitaryExtensive_iff_of_isTerminal TopCat.{u} _ TopCat.isTerminalPUnit _ (TopCat.binaryCofanIsColimit _ _)] apply BinaryCofan.isVanKampen_mk _ _ (fun X Y => TopCat.binaryCofanIsColimit X Y) _ fun f g => TopCat.pullbackConeIsLimit f g · intro X' Y' αX αY f hαX hαY constructor · refine ⟨⟨hαX.symm⟩, ⟨PullbackCone.isLimitAux' _ ?_⟩⟩ intro s have : ∀ x, ∃! y, s.fst x = Sum.inl y := by intro x rcases h : s.fst x with val | val · exact ⟨val, rfl, fun y h => Sum.inl_injective h.symm⟩ · apply_fun f at h cases ((ConcreteCategory.congr_hom s.condition x).symm.trans h).trans (ConcreteCategory.congr_hom hαY val :).symm delta ExistsUnique at this choose l hl hl' using this refine ⟨TopCat.ofHom ⟨l, ?_⟩, TopCat.ext fun a => (hl a).symm, TopCat.isTerminalPUnit.hom_ext _ _, fun {l'} h₁ _ => TopCat.ext fun x => hl' x (l' x) (ConcreteCategory.congr_hom h₁ x).symm⟩ apply (IsEmbedding.inl (X := X') (Y := Y')).isInducing.continuous_iff.mpr convert s.fst.hom.2 using 1 exact (funext hl).symm · refine ⟨⟨hαY.symm⟩, ⟨PullbackCone.isLimitAux' _ ?_⟩⟩ intro s have : ∀ x, ∃! y, s.fst x = Sum.inr y := by intro x rcases h : s.fst x with val | val · apply_fun f at h cases ((ConcreteCategory.congr_hom s.condition x).symm.trans h).trans (ConcreteCategory.congr_hom hαX val :).symm · exact ⟨val, rfl, fun y h => Sum.inr_injective h.symm⟩ delta ExistsUnique at this choose l hl hl' using this refine ⟨TopCat.ofHom ⟨l, ?_⟩, TopCat.ext fun a => (hl a).symm, TopCat.isTerminalPUnit.hom_ext _ _, fun {l'} h₁ _ => TopCat.ext fun x => hl' x (l' x) (ConcreteCategory.congr_hom h₁ x).symm⟩ apply (IsEmbedding.inr (X := X') (Y := Y')).isInducing.continuous_iff.mpr convert s.fst.hom.2 using 1 exact (funext hl).symm · intro Z f exact finitaryExtensiveTopCatAux Z f end TopCat section Functor theorem finitaryExtensive_of_reflective [HasFiniteCoproducts D] [HasPullbacksOfInclusions D] [FinitaryExtensive C] {Gl : C ⥤ D} {Gr : D ⥤ C} (adj : Gl ⊣ Gr) [Gr.Full] [Gr.Faithful] [∀ X Y (f : X ⟶ Gl.obj Y), HasPullback (Gr.map f) (adj.unit.app Y)] [∀ X Y (f : X ⟶ Gl.obj Y), PreservesLimit (cospan (Gr.map f) (adj.unit.app Y)) Gl] [PreservesPullbacksOfInclusions Gl] : FinitaryExtensive D := by have : PreservesColimitsOfSize Gl := adj.leftAdjoint_preservesColimits constructor intros X Y c hc apply (IsVanKampenColimit.precompose_isIso_iff (isoWhiskerLeft _ (asIso adj.counit) ≪≫ Functor.rightUnitor _).hom).mp have : ∀ (Z : C) (i : Discrete WalkingPair) (f : Z ⟶ (colimit.cocone (pair X Y ⋙ Gr)).pt), PreservesLimit (cospan f ((colimit.cocone (pair X Y ⋙ Gr)).ι.app i)) Gl := by have : pair X Y ⋙ Gr = pair (Gr.obj X) (Gr.obj Y) := by apply Functor.hext · rintro ⟨⟨⟩⟩ <;> rfl · rintro ⟨⟨⟩⟩ ⟨j⟩ ⟨⟨rfl : _ = j⟩⟩ <;> simp rw [this] rintro Z ⟨_|_⟩ f <;> dsimp <;> infer_instance refine ((FinitaryExtensive.vanKampen _ (colimit.isColimit <| pair X Y ⋙ _)).map_reflective adj).of_iso (IsColimit.uniqueUpToIso ?_ ?_) · exact isColimitOfPreserves Gl (colimit.isColimit _) · exact (IsColimit.precomposeHomEquiv _ _).symm hc instance finitaryExtensive_functor [HasPullbacks C] [FinitaryExtensive C] : FinitaryExtensive (D ⥤ C) := haveI : HasFiniteCoproducts (D ⥤ C) := ⟨fun _ => Limits.functorCategoryHasColimitsOfShape⟩ ⟨fun c hc => isVanKampenColimit_of_evaluation _ c fun _ => FinitaryExtensive.vanKampen _ <| isColimitOfPreserves _ hc⟩ instance {C} [Category C] {D} [Category D] (F : C ⥤ D) {X Y Z : C} (f : X ⟶ Z) (g : Y ⟶ Z) [IsIso f] : PreservesLimit (cospan f g) F := have := hasPullback_of_left_iso f g preservesLimit_of_preserves_limit_cone (IsPullback.of_hasPullback f g).isLimit ((isLimitMapConePullbackConeEquiv _ pullback.condition).symm (IsPullback.of_vert_isIso ⟨by simp only [← F.map_comp, pullback.condition]⟩).isLimit) instance {C} [Category C] {D} [Category D] (F : C ⥤ D) {X Y Z : C} (f : X ⟶ Z) (g : Y ⟶ Z) [IsIso g] : PreservesLimit (cospan f g) F := preservesPullback_symmetry _ _ _ theorem finitaryExtensive_of_preserves_and_reflects (F : C ⥤ D) [FinitaryExtensive D] [HasFiniteCoproducts C] [HasPullbacksOfInclusions C] [PreservesPullbacksOfInclusions F] [ReflectsLimitsOfShape WalkingCospan F] [PreservesColimitsOfShape (Discrete WalkingPair) F] [ReflectsColimitsOfShape (Discrete WalkingPair) F] : FinitaryExtensive C := by constructor intros X Y c hc refine IsVanKampenColimit.of_iso ?_ (hc.uniqueUpToIso (coprodIsCoprod X Y)).symm have (i : Discrete WalkingPair) (Z : C) (f : Z ⟶ X ⨿ Y) : PreservesLimit (cospan f ((BinaryCofan.mk coprod.inl coprod.inr).ι.app i)) F := by rcases i with ⟨_|_⟩ <;> dsimp <;> infer_instance refine (FinitaryExtensive.vanKampen _ (isColimitOfPreserves F (coprodIsCoprod X Y))).of_mapCocone F theorem finitaryExtensive_of_preserves_and_reflects_isomorphism (F : C ⥤ D) [FinitaryExtensive D] [HasFiniteCoproducts C] [HasPullbacks C] [PreservesLimitsOfShape WalkingCospan F] [PreservesColimitsOfShape (Discrete WalkingPair) F] [F.ReflectsIsomorphisms] : FinitaryExtensive C := by haveI : ReflectsLimitsOfShape WalkingCospan F := reflectsLimitsOfShape_of_reflectsIsomorphisms haveI : ReflectsColimitsOfShape (Discrete WalkingPair) F := reflectsColimitsOfShape_of_reflectsIsomorphisms exact finitaryExtensive_of_preserves_and_reflects F end Functor section FiniteCoproducts theorem FinitaryPreExtensive.isUniversal_finiteCoproducts_Fin [FinitaryPreExtensive C] {n : ℕ}
{F : Discrete (Fin n) ⥤ C} {c : Cocone F} (hc : IsColimit c) : IsUniversalColimit c := by let f : Fin n → C := F.obj ∘ Discrete.mk have : F = Discrete.functor f := Functor.hext (fun _ ↦ rfl) (by rintro ⟨i⟩ ⟨j⟩ ⟨⟨rfl : i = j⟩⟩; simp [f]) clear_value f subst this induction n with | zero => exact (isVanKampenColimit_of_isEmpty _ hc).isUniversal
Mathlib/CategoryTheory/Extensive.lean
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/- 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, Simon Hudon, Mario Carneiro -/ import Aesop import Mathlib.Algebra.Group.Defs import Mathlib.Data.Nat.Init import Mathlib.Data.Int.Init import Mathlib.Logic.Function.Iterate import Mathlib.Tactic.SimpRw import Mathlib.Tactic.SplitIfs /-! # Basic lemmas about semigroups, monoids, and groups This file lists various basic lemmas about semigroups, monoids, and groups. Most proofs are one-liners from the corresponding axioms. For the definitions of semigroups, monoids and groups, see `Algebra/Group/Defs.lean`. -/ assert_not_exists MonoidWithZero DenselyOrdered open Function variable {α β G M : Type*} section ite variable [Pow α β] @[to_additive (attr := simp) dite_smul] lemma pow_dite (p : Prop) [Decidable p] (a : α) (b : p → β) (c : ¬ p → β) : a ^ (if h : p then b h else c h) = if h : p then a ^ b h else a ^ c h := by split_ifs <;> rfl @[to_additive (attr := simp) smul_dite] lemma dite_pow (p : Prop) [Decidable p] (a : p → α) (b : ¬ p → α) (c : β) : (if h : p then a h else b h) ^ c = if h : p then a h ^ c else b h ^ c := by split_ifs <;> rfl @[to_additive (attr := simp) ite_smul] lemma pow_ite (p : Prop) [Decidable p] (a : α) (b c : β) : a ^ (if p then b else c) = if p then a ^ b else a ^ c := pow_dite _ _ _ _ @[to_additive (attr := simp) smul_ite] lemma ite_pow (p : Prop) [Decidable p] (a b : α) (c : β) : (if p then a else b) ^ c = if p then a ^ c else b ^ c := dite_pow _ _ _ _ set_option linter.existingAttributeWarning false in attribute [to_additive (attr := simp)] dite_smul smul_dite ite_smul smul_ite end ite section Semigroup variable [Semigroup α] @[to_additive] instance Semigroup.to_isAssociative : Std.Associative (α := α) (· * ·) := ⟨mul_assoc⟩ /-- Composing two multiplications on the left by `y` then `x` is equal to a multiplication on the left by `x * y`. -/ @[to_additive (attr := simp) "Composing two additions on the left by `y` then `x` is equal to an addition on the left by `x + y`."] theorem comp_mul_left (x y : α) : (x * ·) ∘ (y * ·) = (x * y * ·) := by ext z simp [mul_assoc] /-- Composing two multiplications on the right by `y` and `x` is equal to a multiplication on the right by `y * x`. -/ @[to_additive (attr := simp) "Composing two additions on the right by `y` and `x` is equal to an addition on the right by `y + x`."] theorem comp_mul_right (x y : α) : (· * x) ∘ (· * y) = (· * (y * x)) := by ext z simp [mul_assoc] end Semigroup @[to_additive] instance CommMagma.to_isCommutative [CommMagma G] : Std.Commutative (α := G) (· * ·) := ⟨mul_comm⟩ section MulOneClass variable [MulOneClass M] @[to_additive] theorem ite_mul_one {P : Prop} [Decidable P] {a b : M} : ite P (a * b) 1 = ite P a 1 * ite P b 1 := by by_cases h : P <;> simp [h] @[to_additive] theorem ite_one_mul {P : Prop} [Decidable P] {a b : M} : ite P 1 (a * b) = ite P 1 a * ite P 1 b := by by_cases h : P <;> simp [h] @[to_additive] theorem eq_one_iff_eq_one_of_mul_eq_one {a b : M} (h : a * b = 1) : a = 1 ↔ b = 1 := by constructor <;> (rintro rfl; simpa using h) @[to_additive] theorem one_mul_eq_id : ((1 : M) * ·) = id := funext one_mul @[to_additive] theorem mul_one_eq_id : (· * (1 : M)) = id := funext mul_one end MulOneClass section CommSemigroup variable [CommSemigroup G] @[to_additive] theorem mul_left_comm (a b c : G) : a * (b * c) = b * (a * c) := by rw [← mul_assoc, mul_comm a, mul_assoc] @[to_additive] theorem mul_right_comm (a b c : G) : a * b * c = a * c * b := by rw [mul_assoc, mul_comm b, mul_assoc] @[to_additive] theorem mul_mul_mul_comm (a b c d : G) : a * b * (c * d) = a * c * (b * d) := by simp only [mul_left_comm, mul_assoc] @[to_additive] theorem mul_rotate (a b c : G) : a * b * c = b * c * a := by simp only [mul_left_comm, mul_comm] @[to_additive] theorem mul_rotate' (a b c : G) : a * (b * c) = b * (c * a) := by simp only [mul_left_comm, mul_comm] end CommSemigroup attribute [local simp] mul_assoc sub_eq_add_neg section Monoid variable [Monoid M] {a b : M} {m n : ℕ} @[to_additive boole_nsmul] lemma pow_boole (P : Prop) [Decidable P] (a : M) : (a ^ if P then 1 else 0) = if P then a else 1 := by simp only [pow_ite, pow_one, pow_zero] @[to_additive nsmul_add_sub_nsmul] lemma pow_mul_pow_sub (a : M) (h : m ≤ n) : a ^ m * a ^ (n - m) = a ^ n := by rw [← pow_add, Nat.add_comm, Nat.sub_add_cancel h] @[to_additive sub_nsmul_nsmul_add] lemma pow_sub_mul_pow (a : M) (h : m ≤ n) : a ^ (n - m) * a ^ m = a ^ n := by rw [← pow_add, Nat.sub_add_cancel h] @[to_additive sub_one_nsmul_add] lemma mul_pow_sub_one (hn : n ≠ 0) (a : M) : a * a ^ (n - 1) = a ^ n := by rw [← pow_succ', Nat.sub_add_cancel <| Nat.one_le_iff_ne_zero.2 hn] @[to_additive add_sub_one_nsmul] lemma pow_sub_one_mul (hn : n ≠ 0) (a : M) : a ^ (n - 1) * a = a ^ n := by rw [← pow_succ, Nat.sub_add_cancel <| Nat.one_le_iff_ne_zero.2 hn] /-- If `x ^ n = 1`, then `x ^ m` is the same as `x ^ (m % n)` -/ @[to_additive nsmul_eq_mod_nsmul "If `n • x = 0`, then `m • x` is the same as `(m % n) • x`"] lemma pow_eq_pow_mod (m : ℕ) (ha : a ^ n = 1) : a ^ m = a ^ (m % n) := by calc a ^ m = a ^ (m % n + n * (m / n)) := by rw [Nat.mod_add_div] _ = a ^ (m % n) := by simp [pow_add, pow_mul, ha] @[to_additive] lemma pow_mul_pow_eq_one : ∀ n, a * b = 1 → a ^ n * b ^ n = 1 | 0, _ => by simp | n + 1, h => calc a ^ n.succ * b ^ n.succ = a ^ n * a * (b * b ^ n) := by rw [pow_succ, pow_succ'] _ = a ^ n * (a * b) * b ^ n := by simp only [mul_assoc] _ = 1 := by simp [h, pow_mul_pow_eq_one] @[to_additive (attr := simp)] lemma mul_left_iterate (a : M) : ∀ n : ℕ, (a * ·)^[n] = (a ^ n * ·) | 0 => by ext; simp | n + 1 => by ext; simp [pow_succ, mul_left_iterate] @[to_additive (attr := simp)] lemma mul_right_iterate (a : M) : ∀ n : ℕ, (· * a)^[n] = (· * a ^ n) | 0 => by ext; simp | n + 1 => by ext; simp [pow_succ', mul_right_iterate] @[to_additive] lemma mul_left_iterate_apply_one (a : M) : (a * ·)^[n] 1 = a ^ n := by simp [mul_right_iterate] @[to_additive] lemma mul_right_iterate_apply_one (a : M) : (· * a)^[n] 1 = a ^ n := by simp [mul_right_iterate] @[to_additive (attr := simp)] lemma pow_iterate (k : ℕ) : ∀ n : ℕ, (fun x : M ↦ x ^ k)^[n] = (· ^ k ^ n) | 0 => by ext; simp | n + 1 => by ext; simp [pow_iterate, Nat.pow_succ', pow_mul] end Monoid section CommMonoid variable [CommMonoid M] {x y z : M} @[to_additive] theorem inv_unique (hy : x * y = 1) (hz : x * z = 1) : y = z := left_inv_eq_right_inv (Trans.trans (mul_comm _ _) hy) hz @[to_additive nsmul_add] lemma mul_pow (a b : M) : ∀ n, (a * b) ^ n = a ^ n * b ^ n | 0 => by rw [pow_zero, pow_zero, pow_zero, one_mul] | n + 1 => by rw [pow_succ', pow_succ', pow_succ', mul_pow, mul_mul_mul_comm] end CommMonoid section LeftCancelMonoid variable [Monoid M] [IsLeftCancelMul M] {a b : M} @[to_additive (attr := simp)] theorem mul_eq_left : a * b = a ↔ b = 1 := calc a * b = a ↔ a * b = a * 1 := by rw [mul_one] _ ↔ b = 1 := mul_left_cancel_iff @[deprecated (since := "2025-03-05")] alias mul_right_eq_self := mul_eq_left @[deprecated (since := "2025-03-05")] alias add_right_eq_self := add_eq_left set_option linter.existingAttributeWarning false in attribute [to_additive existing] mul_right_eq_self @[to_additive (attr := simp)] theorem left_eq_mul : a = a * b ↔ b = 1 := eq_comm.trans mul_eq_left @[deprecated (since := "2025-03-05")] alias self_eq_mul_right := left_eq_mul @[deprecated (since := "2025-03-05")] alias self_eq_add_right := left_eq_add set_option linter.existingAttributeWarning false in attribute [to_additive existing] self_eq_mul_right @[to_additive] theorem mul_ne_left : a * b ≠ a ↔ b ≠ 1 := mul_eq_left.not @[deprecated (since := "2025-03-05")] alias mul_right_ne_self := mul_ne_left @[deprecated (since := "2025-03-05")] alias add_right_ne_self := add_ne_left set_option linter.existingAttributeWarning false in attribute [to_additive existing] mul_right_ne_self @[to_additive] theorem left_ne_mul : a ≠ a * b ↔ b ≠ 1 := left_eq_mul.not @[deprecated (since := "2025-03-05")] alias self_ne_mul_right := left_ne_mul @[deprecated (since := "2025-03-05")] alias self_ne_add_right := left_ne_add set_option linter.existingAttributeWarning false in attribute [to_additive existing] self_ne_mul_right end LeftCancelMonoid section RightCancelMonoid variable [RightCancelMonoid M] {a b : M} @[to_additive (attr := simp)] theorem mul_eq_right : a * b = b ↔ a = 1 := calc a * b = b ↔ a * b = 1 * b := by rw [one_mul] _ ↔ a = 1 := mul_right_cancel_iff @[deprecated (since := "2025-03-05")] alias mul_left_eq_self := mul_eq_right @[deprecated (since := "2025-03-05")] alias add_left_eq_self := add_eq_right set_option linter.existingAttributeWarning false in attribute [to_additive existing] mul_left_eq_self @[to_additive (attr := simp)] theorem right_eq_mul : b = a * b ↔ a = 1 := eq_comm.trans mul_eq_right @[deprecated (since := "2025-03-05")] alias self_eq_mul_left := right_eq_mul @[deprecated (since := "2025-03-05")] alias self_eq_add_left := right_eq_add set_option linter.existingAttributeWarning false in attribute [to_additive existing] self_eq_mul_left @[to_additive] theorem mul_ne_right : a * b ≠ b ↔ a ≠ 1 := mul_eq_right.not @[deprecated (since := "2025-03-05")] alias mul_left_ne_self := mul_ne_right @[deprecated (since := "2025-03-05")] alias add_left_ne_self := add_ne_right set_option linter.existingAttributeWarning false in attribute [to_additive existing] mul_left_ne_self @[to_additive] theorem right_ne_mul : b ≠ a * b ↔ a ≠ 1 := right_eq_mul.not @[deprecated (since := "2025-03-05")] alias self_ne_mul_left := right_ne_mul @[deprecated (since := "2025-03-05")] alias self_ne_add_left := right_ne_add set_option linter.existingAttributeWarning false in attribute [to_additive existing] self_ne_mul_left end RightCancelMonoid section CancelCommMonoid variable [CancelCommMonoid α] {a b c d : α} @[to_additive] lemma eq_iff_eq_of_mul_eq_mul (h : a * b = c * d) : a = c ↔ b = d := by aesop @[to_additive] lemma ne_iff_ne_of_mul_eq_mul (h : a * b = c * d) : a ≠ c ↔ b ≠ d := by aesop end CancelCommMonoid section InvolutiveInv variable [InvolutiveInv G] {a b : G} @[to_additive (attr := simp)] theorem inv_involutive : Function.Involutive (Inv.inv : G → G) := inv_inv @[to_additive (attr := simp)] theorem inv_surjective : Function.Surjective (Inv.inv : G → G) := inv_involutive.surjective @[to_additive] theorem inv_injective : Function.Injective (Inv.inv : G → G) := inv_involutive.injective @[to_additive (attr := simp)] theorem inv_inj : a⁻¹ = b⁻¹ ↔ a = b := inv_injective.eq_iff @[to_additive] theorem inv_eq_iff_eq_inv : a⁻¹ = b ↔ a = b⁻¹ := ⟨fun h => h ▸ (inv_inv a).symm, fun h => h.symm ▸ inv_inv b⟩ variable (G) @[to_additive] theorem inv_comp_inv : Inv.inv ∘ Inv.inv = @id G := inv_involutive.comp_self @[to_additive] theorem leftInverse_inv : LeftInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ := inv_inv @[to_additive] theorem rightInverse_inv : RightInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ := inv_inv end InvolutiveInv section DivInvMonoid variable [DivInvMonoid G] @[to_additive] theorem mul_one_div (x y : G) : x * (1 / y) = x / y := by rw [div_eq_mul_inv, one_mul, div_eq_mul_inv] @[to_additive, field_simps] -- The attributes are out of order on purpose theorem mul_div_assoc' (a b c : G) : a * (b / c) = a * b / c := (mul_div_assoc _ _ _).symm @[to_additive] theorem mul_div (a b c : G) : a * (b / c) = a * b / c := by simp only [mul_assoc, div_eq_mul_inv] @[to_additive] theorem div_eq_mul_one_div (a b : G) : a / b = a * (1 / b) := by rw [div_eq_mul_inv, one_div] end DivInvMonoid section DivInvOneMonoid variable [DivInvOneMonoid G] @[to_additive (attr := simp)] theorem div_one (a : G) : a / 1 = a := by simp [div_eq_mul_inv] @[to_additive] theorem one_div_one : (1 : G) / 1 = 1 := div_one _ end DivInvOneMonoid section DivisionMonoid variable [DivisionMonoid α] {a b c d : α} attribute [local simp] mul_assoc div_eq_mul_inv @[to_additive] theorem eq_inv_of_mul_eq_one_right (h : a * b = 1) : b = a⁻¹ := (inv_eq_of_mul_eq_one_right h).symm @[to_additive] theorem eq_one_div_of_mul_eq_one_left (h : b * a = 1) : b = 1 / a := by rw [eq_inv_of_mul_eq_one_left h, one_div] @[to_additive] theorem eq_one_div_of_mul_eq_one_right (h : a * b = 1) : b = 1 / a := by rw [eq_inv_of_mul_eq_one_right h, one_div] @[to_additive] theorem eq_of_div_eq_one (h : a / b = 1) : a = b := inv_injective <| inv_eq_of_mul_eq_one_right <| by rwa [← div_eq_mul_inv] @[to_additive] lemma eq_of_inv_mul_eq_one (h : a⁻¹ * b = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h @[to_additive] lemma eq_of_mul_inv_eq_one (h : a * b⁻¹ = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h @[to_additive] theorem div_ne_one_of_ne : a ≠ b → a / b ≠ 1 := mt eq_of_div_eq_one variable (a b c) @[to_additive] theorem one_div_mul_one_div_rev : 1 / a * (1 / b) = 1 / (b * a) := by simp @[to_additive] theorem inv_div_left : a⁻¹ / b = (b * a)⁻¹ := by simp @[to_additive (attr := simp)] theorem inv_div : (a / b)⁻¹ = b / a := by simp @[to_additive] theorem one_div_div : 1 / (a / b) = b / a := by simp @[to_additive] theorem one_div_one_div : 1 / (1 / a) = a := by simp @[to_additive] theorem div_eq_div_iff_comm : a / b = c / d ↔ b / a = d / c := inv_inj.symm.trans <| by simp only [inv_div] @[to_additive] instance (priority := 100) DivisionMonoid.toDivInvOneMonoid : DivInvOneMonoid α := { DivisionMonoid.toDivInvMonoid with inv_one := by simpa only [one_div, inv_inv] using (inv_div (1 : α) 1).symm } @[to_additive (attr := simp)] lemma inv_pow (a : α) : ∀ n : ℕ, a⁻¹ ^ n = (a ^ n)⁻¹ | 0 => by rw [pow_zero, pow_zero, inv_one] | n + 1 => by rw [pow_succ', pow_succ, inv_pow _ n, mul_inv_rev] -- the attributes are intentionally out of order. `smul_zero` proves `zsmul_zero`. @[to_additive zsmul_zero, simp] lemma one_zpow : ∀ n : ℤ, (1 : α) ^ n = 1 | (n : ℕ) => by rw [zpow_natCast, one_pow] | .negSucc n => by rw [zpow_negSucc, one_pow, inv_one] @[to_additive (attr := simp) neg_zsmul] lemma zpow_neg (a : α) : ∀ n : ℤ, a ^ (-n) = (a ^ n)⁻¹ | (_ + 1 : ℕ) => DivInvMonoid.zpow_neg' _ _ | 0 => by simp | Int.negSucc n => by rw [zpow_negSucc, inv_inv, ← zpow_natCast] rfl @[to_additive neg_one_zsmul_add] lemma mul_zpow_neg_one (a b : α) : (a * b) ^ (-1 : ℤ) = b ^ (-1 : ℤ) * a ^ (-1 : ℤ) := by simp only [zpow_neg, zpow_one, mul_inv_rev] @[to_additive zsmul_neg] lemma inv_zpow (a : α) : ∀ n : ℤ, a⁻¹ ^ n = (a ^ n)⁻¹ | (n : ℕ) => by rw [zpow_natCast, zpow_natCast, inv_pow] | .negSucc n => by rw [zpow_negSucc, zpow_negSucc, inv_pow] @[to_additive (attr := simp) zsmul_neg'] lemma inv_zpow' (a : α) (n : ℤ) : a⁻¹ ^ n = a ^ (-n) := by rw [inv_zpow, zpow_neg] @[to_additive nsmul_zero_sub] lemma one_div_pow (a : α) (n : ℕ) : (1 / a) ^ n = 1 / a ^ n := by simp only [one_div, inv_pow] @[to_additive zsmul_zero_sub] lemma one_div_zpow (a : α) (n : ℤ) : (1 / a) ^ n = 1 / a ^ n := by simp only [one_div, inv_zpow] variable {a b c} @[to_additive (attr := simp)] theorem inv_eq_one : a⁻¹ = 1 ↔ a = 1 := inv_injective.eq_iff' inv_one @[to_additive (attr := simp)] theorem one_eq_inv : 1 = a⁻¹ ↔ a = 1 := eq_comm.trans inv_eq_one @[to_additive] theorem inv_ne_one : a⁻¹ ≠ 1 ↔ a ≠ 1 := inv_eq_one.not @[to_additive] theorem eq_of_one_div_eq_one_div (h : 1 / a = 1 / b) : a = b := by rw [← one_div_one_div a, h, one_div_one_div] -- Note that `mul_zsmul` and `zpow_mul` have the primes swapped -- when additivised since their argument order, -- and therefore the more "natural" choice of lemma, is reversed. @[to_additive mul_zsmul'] lemma zpow_mul (a : α) : ∀ m n : ℤ, a ^ (m * n) = (a ^ m) ^ n | (m : ℕ), (n : ℕ) => by rw [zpow_natCast, zpow_natCast, ← pow_mul, ← zpow_natCast] rfl | (m : ℕ), .negSucc n => by rw [zpow_natCast, zpow_negSucc, ← pow_mul, Int.ofNat_mul_negSucc, zpow_neg, inv_inj, ← zpow_natCast] | .negSucc m, (n : ℕ) => by rw [zpow_natCast, zpow_negSucc, ← inv_pow, ← pow_mul, Int.negSucc_mul_ofNat, zpow_neg, inv_pow, inv_inj, ← zpow_natCast] | .negSucc m, .negSucc n => by rw [zpow_negSucc, zpow_negSucc, Int.negSucc_mul_negSucc, inv_pow, inv_inv, ← pow_mul, ← zpow_natCast] rfl @[to_additive mul_zsmul] lemma zpow_mul' (a : α) (m n : ℤ) : a ^ (m * n) = (a ^ n) ^ m := by rw [Int.mul_comm, zpow_mul] @[to_additive] theorem zpow_comm (a : α) (m n : ℤ) : (a ^ m) ^ n = (a ^ n) ^ m := by rw [← zpow_mul, zpow_mul'] variable (a b c) @[to_additive, field_simps] -- The attributes are out of order on purpose theorem div_div_eq_mul_div : a / (b / c) = a * c / b := by simp @[to_additive (attr := simp)] theorem div_inv_eq_mul : a / b⁻¹ = a * b := by simp @[to_additive] theorem div_mul_eq_div_div_swap : a / (b * c) = a / c / b := by simp only [mul_assoc, mul_inv_rev, div_eq_mul_inv] end DivisionMonoid section DivisionCommMonoid variable [DivisionCommMonoid α] (a b c d : α) attribute [local simp] mul_assoc mul_comm mul_left_comm div_eq_mul_inv @[to_additive neg_add] theorem mul_inv : (a * b)⁻¹ = a⁻¹ * b⁻¹ := by simp @[to_additive] theorem inv_div' : (a / b)⁻¹ = a⁻¹ / b⁻¹ := by simp @[to_additive] theorem div_eq_inv_mul : a / b = b⁻¹ * a := by simp @[to_additive] theorem inv_mul_eq_div : a⁻¹ * b = b / a := by simp @[to_additive] lemma inv_div_comm (a b : α) : a⁻¹ / b = b⁻¹ / a := by simp @[to_additive] theorem inv_mul' : (a * b)⁻¹ = a⁻¹ / b := by simp @[to_additive] theorem inv_div_inv : a⁻¹ / b⁻¹ = b / a := by simp @[to_additive] theorem inv_inv_div_inv : (a⁻¹ / b⁻¹)⁻¹ = a / b := by simp @[to_additive] theorem one_div_mul_one_div : 1 / a * (1 / b) = 1 / (a * b) := by simp @[to_additive] theorem div_right_comm : a / b / c = a / c / b := by simp @[to_additive, field_simps] theorem div_div : a / b / c = a / (b * c) := by simp @[to_additive] theorem div_mul : a / b * c = a / (b / c) := by simp @[to_additive] theorem mul_div_left_comm : a * (b / c) = b * (a / c) := by simp @[to_additive] theorem mul_div_right_comm : a * b / c = a / c * b := by simp @[to_additive] theorem div_mul_eq_div_div : a / (b * c) = a / b / c := by simp @[to_additive, field_simps] theorem div_mul_eq_mul_div : a / b * c = a * c / b := by simp @[to_additive] theorem one_div_mul_eq_div : 1 / a * b = b / a := by simp @[to_additive] theorem mul_comm_div : a / b * c = a * (c / b) := by simp @[to_additive] theorem div_mul_comm : a / b * c = c / b * a := by simp @[to_additive] theorem div_mul_eq_div_mul_one_div : a / (b * c) = a / b * (1 / c) := by simp @[to_additive] theorem div_div_div_eq : a / b / (c / d) = a * d / (b * c) := by simp @[to_additive] theorem div_div_div_comm : a / b / (c / d) = a / c / (b / d) := by simp @[to_additive] theorem div_mul_div_comm : a / b * (c / d) = a * c / (b * d) := by simp @[to_additive] theorem mul_div_mul_comm : a * b / (c * d) = a / c * (b / d) := by simp @[to_additive zsmul_add] lemma mul_zpow : ∀ n : ℤ, (a * b) ^ n = a ^ n * b ^ n | (n : ℕ) => by simp_rw [zpow_natCast, mul_pow] | .negSucc n => by simp_rw [zpow_negSucc, ← inv_pow, mul_inv, mul_pow] @[to_additive nsmul_sub] lemma div_pow (a b : α) (n : ℕ) : (a / b) ^ n = a ^ n / b ^ n := by simp only [div_eq_mul_inv, mul_pow, inv_pow] @[to_additive zsmul_sub] lemma div_zpow (a b : α) (n : ℤ) : (a / b) ^ n = a ^ n / b ^ n := by simp only [div_eq_mul_inv, mul_zpow, inv_zpow] attribute [field_simps] div_pow div_zpow end DivisionCommMonoid section Group variable [Group G] {a b c d : G} {n : ℤ} @[to_additive (attr := simp)] theorem div_eq_inv_self : a / b = b⁻¹ ↔ a = 1 := by rw [div_eq_mul_inv, mul_eq_right] @[to_additive] theorem mul_left_surjective (a : G) : Surjective (a * ·) := fun x ↦ ⟨a⁻¹ * x, mul_inv_cancel_left a x⟩ @[to_additive] theorem mul_right_surjective (a : G) : Function.Surjective fun x ↦ x * a := fun x ↦ ⟨x * a⁻¹, inv_mul_cancel_right x a⟩ @[to_additive] theorem eq_mul_inv_of_mul_eq (h : a * c = b) : a = b * c⁻¹ := by simp [h.symm] @[to_additive] theorem eq_inv_mul_of_mul_eq (h : b * a = c) : a = b⁻¹ * c := by simp [h.symm] @[to_additive] theorem inv_mul_eq_of_eq_mul (h : b = a * c) : a⁻¹ * b = c := by simp [h] @[to_additive] theorem mul_inv_eq_of_eq_mul (h : a = c * b) : a * b⁻¹ = c := by simp [h] @[to_additive] theorem eq_mul_of_mul_inv_eq (h : a * c⁻¹ = b) : a = b * c := by simp [h.symm] @[to_additive] theorem eq_mul_of_inv_mul_eq (h : b⁻¹ * a = c) : a = b * c := by simp [h.symm, mul_inv_cancel_left] @[to_additive] theorem mul_eq_of_eq_inv_mul (h : b = a⁻¹ * c) : a * b = c := by rw [h, mul_inv_cancel_left] @[to_additive] theorem mul_eq_of_eq_mul_inv (h : a = c * b⁻¹) : a * b = c := by simp [h] @[to_additive] theorem mul_eq_one_iff_eq_inv : a * b = 1 ↔ a = b⁻¹ := ⟨eq_inv_of_mul_eq_one_left, fun h ↦ by rw [h, inv_mul_cancel]⟩ @[to_additive] theorem mul_eq_one_iff_inv_eq : a * b = 1 ↔ a⁻¹ = b := by rw [mul_eq_one_iff_eq_inv, inv_eq_iff_eq_inv] /-- Variant of `mul_eq_one_iff_eq_inv` with swapped equality. -/ @[to_additive] theorem mul_eq_one_iff_eq_inv' : a * b = 1 ↔ b = a⁻¹ := by rw [mul_eq_one_iff_inv_eq, eq_comm] /-- Variant of `mul_eq_one_iff_inv_eq` with swapped equality. -/ @[to_additive] theorem mul_eq_one_iff_inv_eq' : a * b = 1 ↔ b⁻¹ = a := by rw [mul_eq_one_iff_eq_inv, eq_comm] @[to_additive] theorem eq_inv_iff_mul_eq_one : a = b⁻¹ ↔ a * b = 1 := mul_eq_one_iff_eq_inv.symm @[to_additive] theorem inv_eq_iff_mul_eq_one : a⁻¹ = b ↔ a * b = 1 := mul_eq_one_iff_inv_eq.symm @[to_additive] theorem eq_mul_inv_iff_mul_eq : a = b * c⁻¹ ↔ a * c = b := ⟨fun h ↦ by rw [h, inv_mul_cancel_right], fun h ↦ by rw [← h, mul_inv_cancel_right]⟩ @[to_additive] theorem eq_inv_mul_iff_mul_eq : a = b⁻¹ * c ↔ b * a = c := ⟨fun h ↦ by rw [h, mul_inv_cancel_left], fun h ↦ by rw [← h, inv_mul_cancel_left]⟩ @[to_additive] theorem inv_mul_eq_iff_eq_mul : a⁻¹ * b = c ↔ b = a * c := ⟨fun h ↦ by rw [← h, mul_inv_cancel_left], fun h ↦ by rw [h, inv_mul_cancel_left]⟩ @[to_additive] theorem mul_inv_eq_iff_eq_mul : a * b⁻¹ = c ↔ a = c * b := ⟨fun h ↦ by rw [← h, inv_mul_cancel_right], fun h ↦ by rw [h, mul_inv_cancel_right]⟩ @[to_additive] theorem mul_inv_eq_one : a * b⁻¹ = 1 ↔ a = b := by rw [mul_eq_one_iff_eq_inv, inv_inv] @[to_additive] theorem inv_mul_eq_one : a⁻¹ * b = 1 ↔ a = b := by rw [mul_eq_one_iff_eq_inv, inv_inj] @[to_additive (attr := simp)] theorem conj_eq_one_iff : a * b * a⁻¹ = 1 ↔ b = 1 := by rw [mul_inv_eq_one, mul_eq_left] @[to_additive] theorem div_left_injective : Function.Injective fun a ↦ a / b := by -- FIXME this could be by `simpa`, but it fails. This is probably a bug in `simpa`. simp only [div_eq_mul_inv] exact fun a a' h ↦ mul_left_injective b⁻¹ h @[to_additive] theorem div_right_injective : Function.Injective fun a ↦ b / a := by -- FIXME see above simp only [div_eq_mul_inv] exact fun a a' h ↦ inv_injective (mul_right_injective b h) @[to_additive (attr := simp)] lemma div_mul_cancel_right (a b : G) : a / (b * a) = b⁻¹ := by rw [← inv_div, mul_div_cancel_right] @[to_additive (attr := simp)] theorem mul_div_mul_right_eq_div (a b c : G) : a * c / (b * c) = a / b := by rw [div_mul_eq_div_div_swap]; simp only [mul_left_inj, eq_self_iff_true, mul_div_cancel_right] @[to_additive eq_sub_of_add_eq] theorem eq_div_of_mul_eq' (h : a * c = b) : a = b / c := by simp [← h] @[to_additive sub_eq_of_eq_add] theorem div_eq_of_eq_mul'' (h : a = c * b) : a / b = c := by simp [h] @[to_additive] theorem eq_mul_of_div_eq (h : a / c = b) : a = b * c := by simp [← h] @[to_additive] theorem mul_eq_of_eq_div (h : a = c / b) : a * b = c := by simp [h] @[to_additive (attr := simp)] theorem div_right_inj : a / b = a / c ↔ b = c := div_right_injective.eq_iff @[to_additive (attr := simp)] theorem div_left_inj : b / a = c / a ↔ b = c := by rw [div_eq_mul_inv, div_eq_mul_inv] exact mul_left_inj _ @[to_additive (attr := simp)] theorem div_mul_div_cancel (a b c : G) : a / b * (b / c) = a / c := by rw [← mul_div_assoc, div_mul_cancel] @[to_additive (attr := simp)] theorem div_div_div_cancel_right (a b c : G) : a / c / (b / c) = a / b := by rw [← inv_div c b, div_inv_eq_mul, div_mul_div_cancel] @[to_additive] theorem div_eq_one : a / b = 1 ↔ a = b := ⟨eq_of_div_eq_one, fun h ↦ by rw [h, div_self']⟩ alias ⟨_, div_eq_one_of_eq⟩ := div_eq_one alias ⟨_, sub_eq_zero_of_eq⟩ := sub_eq_zero @[to_additive] theorem div_ne_one : a / b ≠ 1 ↔ a ≠ b := not_congr div_eq_one @[to_additive (attr := simp)] theorem div_eq_self : a / b = a ↔ b = 1 := by rw [div_eq_mul_inv, mul_eq_left, inv_eq_one] @[to_additive eq_sub_iff_add_eq] theorem eq_div_iff_mul_eq' : a = b / c ↔ a * c = b := by rw [div_eq_mul_inv, eq_mul_inv_iff_mul_eq] @[to_additive] theorem div_eq_iff_eq_mul : a / b = c ↔ a = c * b := by rw [div_eq_mul_inv, mul_inv_eq_iff_eq_mul] @[to_additive] theorem eq_iff_eq_of_div_eq_div (H : a / b = c / d) : a = b ↔ c = d := by rw [← div_eq_one, H, div_eq_one] @[to_additive] theorem leftInverse_div_mul_left (c : G) : Function.LeftInverse (fun x ↦ x / c) fun x ↦ x * c := fun x ↦ mul_div_cancel_right x c @[to_additive] theorem leftInverse_mul_left_div (c : G) : Function.LeftInverse (fun x ↦ x * c) fun x ↦ x / c := fun x ↦ div_mul_cancel x c @[to_additive] theorem leftInverse_mul_right_inv_mul (c : G) : Function.LeftInverse (fun x ↦ c * x) fun x ↦ c⁻¹ * x := fun x ↦ mul_inv_cancel_left c x @[to_additive] theorem leftInverse_inv_mul_mul_right (c : G) : Function.LeftInverse (fun x ↦ c⁻¹ * x) fun x ↦ c * x := fun x ↦ inv_mul_cancel_left c x @[to_additive (attr := simp) natAbs_nsmul_eq_zero] lemma pow_natAbs_eq_one : a ^ n.natAbs = 1 ↔ a ^ n = 1 := by cases n <;> simp @[to_additive sub_nsmul] lemma pow_sub (a : G) {m n : ℕ} (h : n ≤ m) : a ^ (m - n) = a ^ m * (a ^ n)⁻¹ := eq_mul_inv_of_mul_eq <| by rw [← pow_add, Nat.sub_add_cancel h] @[to_additive sub_nsmul_neg] theorem inv_pow_sub (a : G) {m n : ℕ} (h : n ≤ m) : a⁻¹ ^ (m - n) = (a ^ m)⁻¹ * a ^ n := by rw [pow_sub a⁻¹ h, inv_pow, inv_pow, inv_inv] @[to_additive add_one_zsmul] lemma zpow_add_one (a : G) : ∀ n : ℤ, a ^ (n + 1) = a ^ n * a | (n : ℕ) => by simp only [← Int.natCast_succ, zpow_natCast, pow_succ] | -1 => by simp [Int.add_left_neg] | .negSucc (n + 1) => by rw [zpow_negSucc, pow_succ', mul_inv_rev, inv_mul_cancel_right] rw [Int.negSucc_eq, Int.neg_add, Int.neg_add_cancel_right] exact zpow_negSucc _ _ @[to_additive sub_one_zsmul] lemma zpow_sub_one (a : G) (n : ℤ) : a ^ (n - 1) = a ^ n * a⁻¹ := calc a ^ (n - 1) = a ^ (n - 1) * a * a⁻¹ := (mul_inv_cancel_right _ _).symm _ = a ^ n * a⁻¹ := by rw [← zpow_add_one, Int.sub_add_cancel] @[to_additive add_zsmul] lemma zpow_add (a : G) (m n : ℤ) : a ^ (m + n) = a ^ m * a ^ n := by induction n with | hz => simp | hp n ihn => simp only [← Int.add_assoc, zpow_add_one, ihn, mul_assoc] | hn n ihn => rw [zpow_sub_one, ← mul_assoc, ← ihn, ← zpow_sub_one, Int.add_sub_assoc] @[to_additive one_add_zsmul] lemma zpow_one_add (a : G) (n : ℤ) : a ^ (1 + n) = a * a ^ n := by rw [zpow_add, zpow_one] @[to_additive add_zsmul_self] lemma mul_self_zpow (a : G) (n : ℤ) : a * a ^ n = a ^ (n + 1) := by rw [Int.add_comm, zpow_add, zpow_one] @[to_additive add_self_zsmul] lemma mul_zpow_self (a : G) (n : ℤ) : a ^ n * a = a ^ (n + 1) := (zpow_add_one ..).symm @[to_additive sub_zsmul] lemma zpow_sub (a : G) (m n : ℤ) : a ^ (m - n) = a ^ m * (a ^ n)⁻¹ := by rw [Int.sub_eq_add_neg, zpow_add, zpow_neg] @[to_additive natCast_sub_natCast_zsmul] lemma zpow_natCast_sub_natCast (a : G) (m n : ℕ) : a ^ (m - n : ℤ) = a ^ m / a ^ n := by simpa [div_eq_mul_inv] using zpow_sub a m n @[to_additive natCast_sub_one_zsmul] lemma zpow_natCast_sub_one (a : G) (n : ℕ) : a ^ (n - 1 : ℤ) = a ^ n / a := by simpa [div_eq_mul_inv] using zpow_sub a n 1 @[to_additive one_sub_natCast_zsmul] lemma zpow_one_sub_natCast (a : G) (n : ℕ) : a ^ (1 - n : ℤ) = a / a ^ n := by simpa [div_eq_mul_inv] using zpow_sub a 1 n @[to_additive] lemma zpow_mul_comm (a : G) (m n : ℤ) : a ^ m * a ^ n = a ^ n * a ^ m := by rw [← zpow_add, Int.add_comm, zpow_add] theorem zpow_eq_zpow_emod {x : G} (m : ℤ) {n : ℤ} (h : x ^ n = 1) : x ^ m = x ^ (m % n) := calc x ^ m = x ^ (m % n + n * (m / n)) := by rw [Int.emod_add_ediv] _ = x ^ (m % n) := by simp [zpow_add, zpow_mul, h] theorem zpow_eq_zpow_emod' {x : G} (m : ℤ) {n : ℕ} (h : x ^ n = 1) : x ^ m = x ^ (m % (n : ℤ)) := zpow_eq_zpow_emod m (by simpa) @[to_additive (attr := simp)] lemma zpow_iterate (k : ℤ) : ∀ n : ℕ, (fun x : G ↦ x ^ k)^[n] = (· ^ k ^ n) | 0 => by ext; simp [Int.pow_zero] | n + 1 => by ext; simp [zpow_iterate, Int.pow_succ', zpow_mul] /-- To show a property of all powers of `g` it suffices to show it is closed under multiplication by `g` and `g⁻¹` on the left. For subgroups generated by more than one element, see `Subgroup.closure_induction_left`. -/ @[to_additive "To show a property of all multiples of `g` it suffices to show it is closed under addition by `g` and `-g` on the left. For additive subgroups generated by more than one element, see `AddSubgroup.closure_induction_left`."] lemma zpow_induction_left {g : G} {P : G → Prop} (h_one : P (1 : G)) (h_mul : ∀ a, P a → P (g * a)) (h_inv : ∀ a, P a → P (g⁻¹ * a)) (n : ℤ) : P (g ^ n) := by induction n with | hz => rwa [zpow_zero] | hp n ih => rw [Int.add_comm, zpow_add, zpow_one] exact h_mul _ ih | hn n ih => rw [Int.sub_eq_add_neg, Int.add_comm, zpow_add, zpow_neg_one] exact h_inv _ ih /-- To show a property of all powers of `g` it suffices to show it is closed under multiplication by `g` and `g⁻¹` on the right. For subgroups generated by more than one element, see `Subgroup.closure_induction_right`. -/ @[to_additive "To show a property of all multiples of `g` it suffices to show it is closed under addition by `g` and `-g` on the right. For additive subgroups generated by more than one element, see `AddSubgroup.closure_induction_right`."] lemma zpow_induction_right {g : G} {P : G → Prop} (h_one : P (1 : G)) (h_mul : ∀ a, P a → P (a * g)) (h_inv : ∀ a, P a → P (a * g⁻¹)) (n : ℤ) : P (g ^ n) := by induction n with | hz => rwa [zpow_zero] | hp n ih => rw [zpow_add_one] exact h_mul _ ih | hn n ih => rw [zpow_sub_one] exact h_inv _ ih end Group section CommGroup
variable [CommGroup G] {a b c d : G}
Mathlib/Algebra/Group/Basic.lean
920
921
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro -/ import Mathlib.MeasureTheory.Measure.Comap import Mathlib.MeasureTheory.Measure.QuasiMeasurePreserving /-! # Restricting a measure to a subset or a subtype Given a measure `μ` on a type `α` and a subset `s` of `α`, we define a measure `μ.restrict s` as the restriction of `μ` to `s` (still as a measure on `α`). We investigate how this notion interacts with usual operations on measures (sum, pushforward, pullback), and on sets (inclusion, union, Union). We also study the relationship between the restriction of a measure to a subtype (given by the pullback under `Subtype.val`) and the restriction to a set as above. -/ open scoped ENNReal NNReal Topology open Set MeasureTheory Measure Filter MeasurableSpace ENNReal Function variable {R α β δ γ ι : Type*} namespace MeasureTheory variable {m0 : MeasurableSpace α} [MeasurableSpace β] [MeasurableSpace γ] variable {μ μ₁ μ₂ μ₃ ν ν' ν₁ ν₂ : Measure α} {s s' t : Set α} namespace Measure /-! ### Restricting a measure -/ /-- Restrict a measure `μ` to a set `s` as an `ℝ≥0∞`-linear map. -/ noncomputable def restrictₗ {m0 : MeasurableSpace α} (s : Set α) : Measure α →ₗ[ℝ≥0∞] Measure α := liftLinear (OuterMeasure.restrict s) fun μ s' hs' t => by suffices μ (s ∩ t) = μ (s ∩ t ∩ s') + μ ((s ∩ t) \ s') by simpa [← Set.inter_assoc, Set.inter_comm _ s, ← inter_diff_assoc] exact le_toOuterMeasure_caratheodory _ _ hs' _ /-- Restrict a measure `μ` to a set `s`. -/ noncomputable def restrict {_m0 : MeasurableSpace α} (μ : Measure α) (s : Set α) : Measure α := restrictₗ s μ @[simp] theorem restrictₗ_apply {_m0 : MeasurableSpace α} (s : Set α) (μ : Measure α) : restrictₗ s μ = μ.restrict s := rfl /-- This lemma shows that `restrict` and `toOuterMeasure` commute. Note that the LHS has a restrict on measures and the RHS has a restrict on outer measures. -/ theorem restrict_toOuterMeasure_eq_toOuterMeasure_restrict (h : MeasurableSet s) : (μ.restrict s).toOuterMeasure = OuterMeasure.restrict s μ.toOuterMeasure := by simp_rw [restrict, restrictₗ, liftLinear, LinearMap.coe_mk, AddHom.coe_mk, toMeasure_toOuterMeasure, OuterMeasure.restrict_trim h, μ.trimmed] theorem restrict_apply₀ (ht : NullMeasurableSet t (μ.restrict s)) : μ.restrict s t = μ (t ∩ s) := by rw [← restrictₗ_apply, restrictₗ, liftLinear_apply₀ _ ht, OuterMeasure.restrict_apply, coe_toOuterMeasure] /-- If `t` is a measurable set, then the measure of `t` with respect to the restriction of the measure to `s` equals the outer measure of `t ∩ s`. An alternate version requiring that `s` be measurable instead of `t` exists as `Measure.restrict_apply'`. -/ @[simp] theorem restrict_apply (ht : MeasurableSet t) : μ.restrict s t = μ (t ∩ s) := restrict_apply₀ ht.nullMeasurableSet /-- Restriction of a measure to a subset is monotone both in set and in measure. -/ theorem restrict_mono' {_m0 : MeasurableSpace α} ⦃s s' : Set α⦄ ⦃μ ν : Measure α⦄ (hs : s ≤ᵐ[μ] s') (hμν : μ ≤ ν) : μ.restrict s ≤ ν.restrict s' := Measure.le_iff.2 fun t ht => calc μ.restrict s t = μ (t ∩ s) := restrict_apply ht _ ≤ μ (t ∩ s') := (measure_mono_ae <| hs.mono fun _x hx ⟨hxt, hxs⟩ => ⟨hxt, hx hxs⟩) _ ≤ ν (t ∩ s') := le_iff'.1 hμν (t ∩ s') _ = ν.restrict s' t := (restrict_apply ht).symm /-- Restriction of a measure to a subset is monotone both in set and in measure. -/ @[mono, gcongr] theorem restrict_mono {_m0 : MeasurableSpace α} ⦃s s' : Set α⦄ (hs : s ⊆ s') ⦃μ ν : Measure α⦄ (hμν : μ ≤ ν) : μ.restrict s ≤ ν.restrict s' := restrict_mono' (ae_of_all _ hs) hμν @[gcongr] theorem restrict_mono_measure {_ : MeasurableSpace α} {μ ν : Measure α} (h : μ ≤ ν) (s : Set α) : μ.restrict s ≤ ν.restrict s := restrict_mono subset_rfl h @[gcongr] theorem restrict_mono_set {_ : MeasurableSpace α} (μ : Measure α) {s t : Set α} (h : s ⊆ t) : μ.restrict s ≤ μ.restrict t := restrict_mono h le_rfl theorem restrict_mono_ae (h : s ≤ᵐ[μ] t) : μ.restrict s ≤ μ.restrict t := restrict_mono' h (le_refl μ) theorem restrict_congr_set (h : s =ᵐ[μ] t) : μ.restrict s = μ.restrict t := le_antisymm (restrict_mono_ae h.le) (restrict_mono_ae h.symm.le) /-- If `s` is a measurable set, then the outer measure of `t` with respect to the restriction of the measure to `s` equals the outer measure of `t ∩ s`. This is an alternate version of `Measure.restrict_apply`, requiring that `s` is measurable instead of `t`. -/ @[simp] theorem restrict_apply' (hs : MeasurableSet s) : μ.restrict s t = μ (t ∩ s) := by rw [← toOuterMeasure_apply, Measure.restrict_toOuterMeasure_eq_toOuterMeasure_restrict hs, OuterMeasure.restrict_apply s t _, toOuterMeasure_apply] theorem restrict_apply₀' (hs : NullMeasurableSet s μ) : μ.restrict s t = μ (t ∩ s) := by rw [← restrict_congr_set hs.toMeasurable_ae_eq, restrict_apply' (measurableSet_toMeasurable _ _), measure_congr ((ae_eq_refl t).inter hs.toMeasurable_ae_eq)] theorem restrict_le_self : μ.restrict s ≤ μ := Measure.le_iff.2 fun t ht => calc μ.restrict s t = μ (t ∩ s) := restrict_apply ht _ ≤ μ t := measure_mono inter_subset_left variable (μ) theorem restrict_eq_self (h : s ⊆ t) : μ.restrict t s = μ s := (le_iff'.1 restrict_le_self s).antisymm <| calc μ s ≤ μ (toMeasurable (μ.restrict t) s ∩ t) := measure_mono (subset_inter (subset_toMeasurable _ _) h) _ = μ.restrict t s := by rw [← restrict_apply (measurableSet_toMeasurable _ _), measure_toMeasurable] @[simp] theorem restrict_apply_self (s : Set α) : (μ.restrict s) s = μ s := restrict_eq_self μ Subset.rfl variable {μ} theorem restrict_apply_univ (s : Set α) : μ.restrict s univ = μ s := by rw [restrict_apply MeasurableSet.univ, Set.univ_inter] theorem le_restrict_apply (s t : Set α) : μ (t ∩ s) ≤ μ.restrict s t := calc μ (t ∩ s) = μ.restrict s (t ∩ s) := (restrict_eq_self μ inter_subset_right).symm _ ≤ μ.restrict s t := measure_mono inter_subset_left theorem restrict_apply_le (s t : Set α) : μ.restrict s t ≤ μ t := Measure.le_iff'.1 restrict_le_self _ theorem restrict_apply_superset (h : s ⊆ t) : μ.restrict s t = μ s := ((measure_mono (subset_univ _)).trans_eq <| restrict_apply_univ _).antisymm ((restrict_apply_self μ s).symm.trans_le <| measure_mono h) @[simp] theorem restrict_add {_m0 : MeasurableSpace α} (μ ν : Measure α) (s : Set α) : (μ + ν).restrict s = μ.restrict s + ν.restrict s := (restrictₗ s).map_add μ ν @[simp] theorem restrict_zero {_m0 : MeasurableSpace α} (s : Set α) : (0 : Measure α).restrict s = 0 := (restrictₗ s).map_zero @[simp] theorem restrict_smul {_m0 : MeasurableSpace α} {R : Type*} [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] (c : R) (μ : Measure α) (s : Set α) : (c • μ).restrict s = c • μ.restrict s := by simpa only [smul_one_smul] using (restrictₗ s).map_smul (c • 1) μ theorem restrict_restrict₀ (hs : NullMeasurableSet s (μ.restrict t)) : (μ.restrict t).restrict s = μ.restrict (s ∩ t) := ext fun u hu => by simp only [Set.inter_assoc, restrict_apply hu, restrict_apply₀ (hu.nullMeasurableSet.inter hs)] @[simp] theorem restrict_restrict (hs : MeasurableSet s) : (μ.restrict t).restrict s = μ.restrict (s ∩ t) := restrict_restrict₀ hs.nullMeasurableSet theorem restrict_restrict_of_subset (h : s ⊆ t) : (μ.restrict t).restrict s = μ.restrict s := by ext1 u hu rw [restrict_apply hu, restrict_apply hu, restrict_eq_self] exact inter_subset_right.trans h theorem restrict_restrict₀' (ht : NullMeasurableSet t μ) : (μ.restrict t).restrict s = μ.restrict (s ∩ t) := ext fun u hu => by simp only [restrict_apply hu, restrict_apply₀' ht, inter_assoc] theorem restrict_restrict' (ht : MeasurableSet t) : (μ.restrict t).restrict s = μ.restrict (s ∩ t) := restrict_restrict₀' ht.nullMeasurableSet theorem restrict_comm (hs : MeasurableSet s) : (μ.restrict t).restrict s = (μ.restrict s).restrict t := by rw [restrict_restrict hs, restrict_restrict' hs, inter_comm] theorem restrict_apply_eq_zero (ht : MeasurableSet t) : μ.restrict s t = 0 ↔ μ (t ∩ s) = 0 := by rw [restrict_apply ht] theorem measure_inter_eq_zero_of_restrict (h : μ.restrict s t = 0) : μ (t ∩ s) = 0 := nonpos_iff_eq_zero.1 (h ▸ le_restrict_apply _ _) theorem restrict_apply_eq_zero' (hs : MeasurableSet s) : μ.restrict s t = 0 ↔ μ (t ∩ s) = 0 := by rw [restrict_apply' hs] @[simp] theorem restrict_eq_zero : μ.restrict s = 0 ↔ μ s = 0 := by rw [← measure_univ_eq_zero, restrict_apply_univ] /-- If `μ s ≠ 0`, then `μ.restrict s ≠ 0`, in terms of `NeZero` instances. -/ instance restrict.neZero [NeZero (μ s)] : NeZero (μ.restrict s) := ⟨mt restrict_eq_zero.mp <| NeZero.ne _⟩ theorem restrict_zero_set {s : Set α} (h : μ s = 0) : μ.restrict s = 0 := restrict_eq_zero.2 h @[simp] theorem restrict_empty : μ.restrict ∅ = 0 := restrict_zero_set measure_empty @[simp] theorem restrict_univ : μ.restrict univ = μ := ext fun s hs => by simp [hs] theorem restrict_inter_add_diff₀ (s : Set α) (ht : NullMeasurableSet t μ) : μ.restrict (s ∩ t) + μ.restrict (s \ t) = μ.restrict s := by ext1 u hu simp only [add_apply, restrict_apply hu, ← inter_assoc, diff_eq] exact measure_inter_add_diff₀ (u ∩ s) ht theorem restrict_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ.restrict (s ∩ t) + μ.restrict (s \ t) = μ.restrict s := restrict_inter_add_diff₀ s ht.nullMeasurableSet theorem restrict_union_add_inter₀ (s : Set α) (ht : NullMeasurableSet t μ) : μ.restrict (s ∪ t) + μ.restrict (s ∩ t) = μ.restrict s + μ.restrict t := by rw [← restrict_inter_add_diff₀ (s ∪ t) ht, union_inter_cancel_right, union_diff_right, ← restrict_inter_add_diff₀ s ht, add_comm, ← add_assoc, add_right_comm] theorem restrict_union_add_inter (s : Set α) (ht : MeasurableSet t) : μ.restrict (s ∪ t) + μ.restrict (s ∩ t) = μ.restrict s + μ.restrict t := restrict_union_add_inter₀ s ht.nullMeasurableSet theorem restrict_union_add_inter' (hs : MeasurableSet s) (t : Set α) : μ.restrict (s ∪ t) + μ.restrict (s ∩ t) = μ.restrict s + μ.restrict t := by simpa only [union_comm, inter_comm, add_comm] using restrict_union_add_inter t hs theorem restrict_union₀ (h : AEDisjoint μ s t) (ht : NullMeasurableSet t μ) : μ.restrict (s ∪ t) = μ.restrict s + μ.restrict t := by simp [← restrict_union_add_inter₀ s ht, restrict_zero_set h] theorem restrict_union (h : Disjoint s t) (ht : MeasurableSet t) : μ.restrict (s ∪ t) = μ.restrict s + μ.restrict t := restrict_union₀ h.aedisjoint ht.nullMeasurableSet theorem restrict_union' (h : Disjoint s t) (hs : MeasurableSet s) : μ.restrict (s ∪ t) = μ.restrict s + μ.restrict t := by rw [union_comm, restrict_union h.symm hs, add_comm] @[simp] theorem restrict_add_restrict_compl (hs : MeasurableSet s) : μ.restrict s + μ.restrict sᶜ = μ := by rw [← restrict_union (@disjoint_compl_right (Set α) _ _) hs.compl, union_compl_self, restrict_univ] @[simp] theorem restrict_compl_add_restrict (hs : MeasurableSet s) : μ.restrict sᶜ + μ.restrict s = μ := by rw [add_comm, restrict_add_restrict_compl hs] theorem restrict_union_le (s s' : Set α) : μ.restrict (s ∪ s') ≤ μ.restrict s + μ.restrict s' := le_iff.2 fun t ht ↦ by simpa [ht, inter_union_distrib_left] using measure_union_le (t ∩ s) (t ∩ s') theorem restrict_iUnion_apply_ae [Countable ι] {s : ι → Set α} (hd : Pairwise (AEDisjoint μ on s)) (hm : ∀ i, NullMeasurableSet (s i) μ) {t : Set α} (ht : MeasurableSet t) : μ.restrict (⋃ i, s i) t = ∑' i, μ.restrict (s i) t := by simp only [restrict_apply, ht, inter_iUnion] exact measure_iUnion₀ (hd.mono fun i j h => h.mono inter_subset_right inter_subset_right) fun i => ht.nullMeasurableSet.inter (hm i) theorem restrict_iUnion_apply [Countable ι] {s : ι → Set α} (hd : Pairwise (Disjoint on s)) (hm : ∀ i, MeasurableSet (s i)) {t : Set α} (ht : MeasurableSet t) : μ.restrict (⋃ i, s i) t = ∑' i, μ.restrict (s i) t := restrict_iUnion_apply_ae hd.aedisjoint (fun i => (hm i).nullMeasurableSet) ht theorem restrict_iUnion_apply_eq_iSup [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) {t : Set α} (ht : MeasurableSet t) : μ.restrict (⋃ i, s i) t = ⨆ i, μ.restrict (s i) t := by simp only [restrict_apply ht, inter_iUnion] rw [Directed.measure_iUnion] exacts [hd.mono_comp _ fun s₁ s₂ => inter_subset_inter_right _] /-- The restriction of the pushforward measure is the pushforward of the restriction. For a version assuming only `AEMeasurable`, see `restrict_map_of_aemeasurable`. -/ theorem restrict_map {f : α → β} (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) : (μ.map f).restrict s = (μ.restrict <| f ⁻¹' s).map f := ext fun t ht => by simp [*, hf ht] theorem restrict_toMeasurable (h : μ s ≠ ∞) : μ.restrict (toMeasurable μ s) = μ.restrict s := ext fun t ht => by rw [restrict_apply ht, restrict_apply ht, inter_comm, measure_toMeasurable_inter ht h, inter_comm] theorem restrict_eq_self_of_ae_mem {_m0 : MeasurableSpace α} ⦃s : Set α⦄ ⦃μ : Measure α⦄ (hs : ∀ᵐ x ∂μ, x ∈ s) : μ.restrict s = μ := calc μ.restrict s = μ.restrict univ := restrict_congr_set (eventuallyEq_univ.mpr hs) _ = μ := restrict_univ theorem restrict_congr_meas (hs : MeasurableSet s) : μ.restrict s = ν.restrict s ↔ ∀ t ⊆ s, MeasurableSet t → μ t = ν t := ⟨fun H t hts ht => by rw [← inter_eq_self_of_subset_left hts, ← restrict_apply ht, H, restrict_apply ht], fun H => ext fun t ht => by rw [restrict_apply ht, restrict_apply ht, H _ inter_subset_right (ht.inter hs)]⟩ theorem restrict_congr_mono (hs : s ⊆ t) (h : μ.restrict t = ν.restrict t) : μ.restrict s = ν.restrict s := by rw [← restrict_restrict_of_subset hs, h, restrict_restrict_of_subset hs] /-- If two measures agree on all measurable subsets of `s` and `t`, then they agree on all measurable subsets of `s ∪ t`. -/ theorem restrict_union_congr : μ.restrict (s ∪ t) = ν.restrict (s ∪ t) ↔ μ.restrict s = ν.restrict s ∧ μ.restrict t = ν.restrict t := by refine ⟨fun h ↦ ⟨restrict_congr_mono subset_union_left h, restrict_congr_mono subset_union_right h⟩, ?_⟩ rintro ⟨hs, ht⟩ ext1 u hu simp only [restrict_apply hu, inter_union_distrib_left] rcases exists_measurable_superset₂ μ ν (u ∩ s) with ⟨US, hsub, hm, hμ, hν⟩ calc μ (u ∩ s ∪ u ∩ t) = μ (US ∪ u ∩ t) := measure_union_congr_of_subset hsub hμ.le Subset.rfl le_rfl _ = μ US + μ ((u ∩ t) \ US) := (measure_add_diff hm.nullMeasurableSet _).symm _ = restrict μ s u + restrict μ t (u \ US) := by simp only [restrict_apply, hu, hu.diff hm, hμ, ← inter_comm t, inter_diff_assoc] _ = restrict ν s u + restrict ν t (u \ US) := by rw [hs, ht] _ = ν US + ν ((u ∩ t) \ US) := by simp only [restrict_apply, hu, hu.diff hm, hν, ← inter_comm t, inter_diff_assoc] _ = ν (US ∪ u ∩ t) := measure_add_diff hm.nullMeasurableSet _ _ = ν (u ∩ s ∪ u ∩ t) := .symm <| measure_union_congr_of_subset hsub hν.le Subset.rfl le_rfl theorem restrict_finset_biUnion_congr {s : Finset ι} {t : ι → Set α} : μ.restrict (⋃ i ∈ s, t i) = ν.restrict (⋃ i ∈ s, t i) ↔ ∀ i ∈ s, μ.restrict (t i) = ν.restrict (t i) := by classical induction' s using Finset.induction_on with i s _ hs; · simp simp only [forall_eq_or_imp, iUnion_iUnion_eq_or_left, Finset.mem_insert] rw [restrict_union_congr, ← hs] theorem restrict_iUnion_congr [Countable ι] {s : ι → Set α} : μ.restrict (⋃ i, s i) = ν.restrict (⋃ i, s i) ↔ ∀ i, μ.restrict (s i) = ν.restrict (s i) := by refine ⟨fun h i => restrict_congr_mono (subset_iUnion _ _) h, fun h => ?_⟩ ext1 t ht have D : Directed (· ⊆ ·) fun t : Finset ι => ⋃ i ∈ t, s i := Monotone.directed_le fun t₁ t₂ ht => biUnion_subset_biUnion_left ht rw [iUnion_eq_iUnion_finset] simp only [restrict_iUnion_apply_eq_iSup D ht, restrict_finset_biUnion_congr.2 fun i _ => h i] theorem restrict_biUnion_congr {s : Set ι} {t : ι → Set α} (hc : s.Countable) : μ.restrict (⋃ i ∈ s, t i) = ν.restrict (⋃ i ∈ s, t i) ↔ ∀ i ∈ s, μ.restrict (t i) = ν.restrict (t i) := by haveI := hc.toEncodable simp only [biUnion_eq_iUnion, SetCoe.forall', restrict_iUnion_congr] theorem restrict_sUnion_congr {S : Set (Set α)} (hc : S.Countable) : μ.restrict (⋃₀ S) = ν.restrict (⋃₀ S) ↔ ∀ s ∈ S, μ.restrict s = ν.restrict s := by rw [sUnion_eq_biUnion, restrict_biUnion_congr hc] /-- This lemma shows that `Inf` and `restrict` commute for measures. -/ theorem restrict_sInf_eq_sInf_restrict {m0 : MeasurableSpace α} {m : Set (Measure α)} (hm : m.Nonempty) (ht : MeasurableSet t) : (sInf m).restrict t = sInf ((fun μ : Measure α => μ.restrict t) '' m) := by ext1 s hs simp_rw [sInf_apply hs, restrict_apply hs, sInf_apply (MeasurableSet.inter hs ht), Set.image_image, restrict_toOuterMeasure_eq_toOuterMeasure_restrict ht, ← Set.image_image _ toOuterMeasure, ← OuterMeasure.restrict_sInf_eq_sInf_restrict _ (hm.image _), OuterMeasure.restrict_apply] theorem exists_mem_of_measure_ne_zero_of_ae (hs : μ s ≠ 0) {p : α → Prop} (hp : ∀ᵐ x ∂μ.restrict s, p x) : ∃ x, x ∈ s ∧ p x := by rw [← μ.restrict_apply_self, ← frequently_ae_mem_iff] at hs exact (hs.and_eventually hp).exists /-- If a quasi measure preserving map `f` maps a set `s` to a set `t`, then it is quasi measure preserving with respect to the restrictions of the measures. -/ theorem QuasiMeasurePreserving.restrict {ν : Measure β} {f : α → β} (hf : QuasiMeasurePreserving f μ ν) {t : Set β} (hmaps : MapsTo f s t) : QuasiMeasurePreserving f (μ.restrict s) (ν.restrict t) where measurable := hf.measurable absolutelyContinuous := by refine AbsolutelyContinuous.mk fun u hum ↦ ?_ suffices ν (u ∩ t) = 0 → μ (f ⁻¹' u ∩ s) = 0 by simpa [hum, hf.measurable, hf.measurable hum] refine fun hu ↦ measure_mono_null ?_ (hf.preimage_null hu) rw [preimage_inter] gcongr assumption /-! ### Extensionality results -/ /-- Two measures are equal if they have equal restrictions on a spanning collection of sets (formulated using `Union`). -/ theorem ext_iff_of_iUnion_eq_univ [Countable ι] {s : ι → Set α} (hs : ⋃ i, s i = univ) : μ = ν ↔ ∀ i, μ.restrict (s i) = ν.restrict (s i) := by rw [← restrict_iUnion_congr, hs, restrict_univ, restrict_univ] alias ⟨_, ext_of_iUnion_eq_univ⟩ := ext_iff_of_iUnion_eq_univ /-- Two measures are equal if they have equal restrictions on a spanning collection of sets (formulated using `biUnion`). -/ theorem ext_iff_of_biUnion_eq_univ {S : Set ι} {s : ι → Set α} (hc : S.Countable) (hs : ⋃ i ∈ S, s i = univ) : μ = ν ↔ ∀ i ∈ S, μ.restrict (s i) = ν.restrict (s i) := by rw [← restrict_biUnion_congr hc, hs, restrict_univ, restrict_univ] alias ⟨_, ext_of_biUnion_eq_univ⟩ := ext_iff_of_biUnion_eq_univ /-- Two measures are equal if they have equal restrictions on a spanning collection of sets (formulated using `sUnion`). -/ theorem ext_iff_of_sUnion_eq_univ {S : Set (Set α)} (hc : S.Countable) (hs : ⋃₀ S = univ) : μ = ν ↔ ∀ s ∈ S, μ.restrict s = ν.restrict s := ext_iff_of_biUnion_eq_univ hc <| by rwa [← sUnion_eq_biUnion] alias ⟨_, ext_of_sUnion_eq_univ⟩ := ext_iff_of_sUnion_eq_univ theorem ext_of_generateFrom_of_cover {S T : Set (Set α)} (h_gen : ‹_› = generateFrom S) (hc : T.Countable) (h_inter : IsPiSystem S) (hU : ⋃₀ T = univ) (htop : ∀ t ∈ T, μ t ≠ ∞) (ST_eq : ∀ t ∈ T, ∀ s ∈ S, μ (s ∩ t) = ν (s ∩ t)) (T_eq : ∀ t ∈ T, μ t = ν t) : μ = ν := by refine ext_of_sUnion_eq_univ hc hU fun t ht => ?_ ext1 u hu simp only [restrict_apply hu] induction u, hu using induction_on_inter h_gen h_inter with | empty => simp only [Set.empty_inter, measure_empty] | basic u hu => exact ST_eq _ ht _ hu | compl u hu ihu => have := T_eq t ht rw [Set.inter_comm] at ihu ⊢ rwa [← measure_inter_add_diff t hu, ← measure_inter_add_diff t hu, ← ihu, ENNReal.add_right_inj] at this exact ne_top_of_le_ne_top (htop t ht) (measure_mono Set.inter_subset_left) | iUnion f hfd hfm ihf => simp only [← restrict_apply (hfm _), ← restrict_apply (MeasurableSet.iUnion hfm)] at ihf ⊢ simp only [measure_iUnion hfd hfm, ihf] /-- Two measures are equal if they are equal on the π-system generating the σ-algebra, and they are both finite on an increasing spanning sequence of sets in the π-system. This lemma is formulated using `sUnion`. -/ theorem ext_of_generateFrom_of_cover_subset {S T : Set (Set α)} (h_gen : ‹_› = generateFrom S) (h_inter : IsPiSystem S) (h_sub : T ⊆ S) (hc : T.Countable) (hU : ⋃₀ T = univ) (htop : ∀ s ∈ T, μ s ≠ ∞) (h_eq : ∀ s ∈ S, μ s = ν s) : μ = ν := by refine ext_of_generateFrom_of_cover h_gen hc h_inter hU htop ?_ fun t ht => h_eq t (h_sub ht) intro t ht s hs; rcases (s ∩ t).eq_empty_or_nonempty with H | H · simp only [H, measure_empty] · exact h_eq _ (h_inter _ hs _ (h_sub ht) H) /-- Two measures are equal if they are equal on the π-system generating the σ-algebra, and they are both finite on an increasing spanning sequence of sets in the π-system. This lemma is formulated using `iUnion`. `FiniteSpanningSetsIn.ext` is a reformulation of this lemma. -/ theorem ext_of_generateFrom_of_iUnion (C : Set (Set α)) (B : ℕ → Set α) (hA : ‹_› = generateFrom C) (hC : IsPiSystem C) (h1B : ⋃ i, B i = univ) (h2B : ∀ i, B i ∈ C) (hμB : ∀ i, μ (B i) ≠ ∞) (h_eq : ∀ s ∈ C, μ s = ν s) : μ = ν := by refine ext_of_generateFrom_of_cover_subset hA hC ?_ (countable_range B) h1B ?_ h_eq · rintro _ ⟨i, rfl⟩ apply h2B · rintro _ ⟨i, rfl⟩ apply hμB @[simp] theorem restrict_sum (μ : ι → Measure α) {s : Set α} (hs : MeasurableSet s) : (sum μ).restrict s = sum fun i => (μ i).restrict s := ext fun t ht => by simp only [sum_apply, restrict_apply, ht, ht.inter hs] @[simp] theorem restrict_sum_of_countable [Countable ι] (μ : ι → Measure α) (s : Set α) : (sum μ).restrict s = sum fun i => (μ i).restrict s := by ext t ht simp_rw [sum_apply _ ht, restrict_apply ht, sum_apply_of_countable] lemma AbsolutelyContinuous.restrict (h : μ ≪ ν) (s : Set α) : μ.restrict s ≪ ν.restrict s := by refine Measure.AbsolutelyContinuous.mk (fun t ht htν ↦ ?_) rw [restrict_apply ht] at htν ⊢ exact h htν theorem restrict_iUnion_ae [Countable ι] {s : ι → Set α} (hd : Pairwise (AEDisjoint μ on s)) (hm : ∀ i, NullMeasurableSet (s i) μ) : μ.restrict (⋃ i, s i) = sum fun i => μ.restrict (s i) := ext fun t ht => by simp only [sum_apply _ ht, restrict_iUnion_apply_ae hd hm ht] theorem restrict_iUnion [Countable ι] {s : ι → Set α} (hd : Pairwise (Disjoint on s)) (hm : ∀ i, MeasurableSet (s i)) : μ.restrict (⋃ i, s i) = sum fun i => μ.restrict (s i) := restrict_iUnion_ae hd.aedisjoint fun i => (hm i).nullMeasurableSet theorem restrict_iUnion_le [Countable ι] {s : ι → Set α} : μ.restrict (⋃ i, s i) ≤ sum fun i => μ.restrict (s i) := le_iff.2 fun t ht ↦ by simpa [ht, inter_iUnion] using measure_iUnion_le (t ∩ s ·) end Measure @[simp] theorem ae_restrict_iUnion_eq [Countable ι] (s : ι → Set α) : ae (μ.restrict (⋃ i, s i)) = ⨆ i, ae (μ.restrict (s i)) := le_antisymm ((ae_sum_eq fun i => μ.restrict (s i)) ▸ ae_mono restrict_iUnion_le) <| iSup_le fun i => ae_mono <| restrict_mono (subset_iUnion s i) le_rfl @[simp] theorem ae_restrict_union_eq (s t : Set α) : ae (μ.restrict (s ∪ t)) = ae (μ.restrict s) ⊔ ae (μ.restrict t) := by simp [union_eq_iUnion, iSup_bool_eq] theorem ae_restrict_biUnion_eq (s : ι → Set α) {t : Set ι} (ht : t.Countable) : ae (μ.restrict (⋃ i ∈ t, s i)) = ⨆ i ∈ t, ae (μ.restrict (s i)) := by haveI := ht.to_subtype rw [biUnion_eq_iUnion, ae_restrict_iUnion_eq, ← iSup_subtype''] theorem ae_restrict_biUnion_finset_eq (s : ι → Set α) (t : Finset ι) : ae (μ.restrict (⋃ i ∈ t, s i)) = ⨆ i ∈ t, ae (μ.restrict (s i)) := ae_restrict_biUnion_eq s t.countable_toSet theorem ae_restrict_iUnion_iff [Countable ι] (s : ι → Set α) (p : α → Prop) : (∀ᵐ x ∂μ.restrict (⋃ i, s i), p x) ↔ ∀ i, ∀ᵐ x ∂μ.restrict (s i), p x := by simp theorem ae_restrict_union_iff (s t : Set α) (p : α → Prop) : (∀ᵐ x ∂μ.restrict (s ∪ t), p x) ↔ (∀ᵐ x ∂μ.restrict s, p x) ∧ ∀ᵐ x ∂μ.restrict t, p x := by simp theorem ae_restrict_biUnion_iff (s : ι → Set α) {t : Set ι} (ht : t.Countable) (p : α → Prop) : (∀ᵐ x ∂μ.restrict (⋃ i ∈ t, s i), p x) ↔ ∀ i ∈ t, ∀ᵐ x ∂μ.restrict (s i), p x := by simp_rw [Filter.Eventually, ae_restrict_biUnion_eq s ht, mem_iSup] @[simp] theorem ae_restrict_biUnion_finset_iff (s : ι → Set α) (t : Finset ι) (p : α → Prop) : (∀ᵐ x ∂μ.restrict (⋃ i ∈ t, s i), p x) ↔ ∀ i ∈ t, ∀ᵐ x ∂μ.restrict (s i), p x := by simp_rw [Filter.Eventually, ae_restrict_biUnion_finset_eq s, mem_iSup] theorem ae_eq_restrict_iUnion_iff [Countable ι] (s : ι → Set α) (f g : α → δ) : f =ᵐ[μ.restrict (⋃ i, s i)] g ↔ ∀ i, f =ᵐ[μ.restrict (s i)] g := by simp_rw [EventuallyEq, ae_restrict_iUnion_eq, eventually_iSup] theorem ae_eq_restrict_biUnion_iff (s : ι → Set α) {t : Set ι} (ht : t.Countable) (f g : α → δ) : f =ᵐ[μ.restrict (⋃ i ∈ t, s i)] g ↔ ∀ i ∈ t, f =ᵐ[μ.restrict (s i)] g := by simp_rw [ae_restrict_biUnion_eq s ht, EventuallyEq, eventually_iSup] theorem ae_eq_restrict_biUnion_finset_iff (s : ι → Set α) (t : Finset ι) (f g : α → δ) : f =ᵐ[μ.restrict (⋃ i ∈ t, s i)] g ↔ ∀ i ∈ t, f =ᵐ[μ.restrict (s i)] g := ae_eq_restrict_biUnion_iff s t.countable_toSet f g open scoped Interval in theorem ae_restrict_uIoc_eq [LinearOrder α] (a b : α) : ae (μ.restrict (Ι a b)) = ae (μ.restrict (Ioc a b)) ⊔ ae (μ.restrict (Ioc b a)) := by simp only [uIoc_eq_union, ae_restrict_union_eq] open scoped Interval in /-- See also `MeasureTheory.ae_uIoc_iff`. -/ theorem ae_restrict_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} : (∀ᵐ x ∂μ.restrict (Ι a b), P x) ↔ (∀ᵐ x ∂μ.restrict (Ioc a b), P x) ∧ ∀ᵐ x ∂μ.restrict (Ioc b a), P x := by rw [ae_restrict_uIoc_eq, eventually_sup] theorem ae_restrict_iff₀ {p : α → Prop} (hp : NullMeasurableSet { x | p x } (μ.restrict s)) : (∀ᵐ x ∂μ.restrict s, p x) ↔ ∀ᵐ x ∂μ, x ∈ s → p x := by simp only [ae_iff, ← compl_setOf, Measure.restrict_apply₀ hp.compl] rw [iff_iff_eq]; congr with x; simp [and_comm] theorem ae_restrict_iff {p : α → Prop} (hp : MeasurableSet { x | p x }) : (∀ᵐ x ∂μ.restrict s, p x) ↔ ∀ᵐ x ∂μ, x ∈ s → p x := ae_restrict_iff₀ hp.nullMeasurableSet theorem ae_imp_of_ae_restrict {s : Set α} {p : α → Prop} (h : ∀ᵐ x ∂μ.restrict s, p x) : ∀ᵐ x ∂μ, x ∈ s → p x := by simp only [ae_iff] at h ⊢ simpa [setOf_and, inter_comm] using measure_inter_eq_zero_of_restrict h theorem ae_restrict_iff'₀ {p : α → Prop} (hs : NullMeasurableSet s μ) : (∀ᵐ x ∂μ.restrict s, p x) ↔ ∀ᵐ x ∂μ, x ∈ s → p x := by simp only [ae_iff, ← compl_setOf, restrict_apply₀' hs] rw [iff_iff_eq]; congr with x; simp [and_comm] theorem ae_restrict_iff' {p : α → Prop} (hs : MeasurableSet s) : (∀ᵐ x ∂μ.restrict s, p x) ↔ ∀ᵐ x ∂μ, x ∈ s → p x := ae_restrict_iff'₀ hs.nullMeasurableSet theorem _root_.Filter.EventuallyEq.restrict {f g : α → δ} {s : Set α} (hfg : f =ᵐ[μ] g) : f =ᵐ[μ.restrict s] g := by -- note that we cannot use `ae_restrict_iff` since we do not require measurability refine hfg.filter_mono ?_ rw [Measure.ae_le_iff_absolutelyContinuous] exact Measure.absolutelyContinuous_of_le Measure.restrict_le_self theorem ae_restrict_mem₀ (hs : NullMeasurableSet s μ) : ∀ᵐ x ∂μ.restrict s, x ∈ s := (ae_restrict_iff'₀ hs).2 (Filter.Eventually.of_forall fun _ => id) theorem ae_restrict_mem (hs : MeasurableSet s) : ∀ᵐ x ∂μ.restrict s, x ∈ s := ae_restrict_mem₀ hs.nullMeasurableSet theorem ae_restrict_of_forall_mem {μ : Measure α} {s : Set α} (hs : MeasurableSet s) {p : α → Prop} (h : ∀ x ∈ s, p x) : ∀ᵐ (x : α) ∂μ.restrict s, p x := (ae_restrict_mem hs).mono h theorem ae_restrict_of_ae {s : Set α} {p : α → Prop} (h : ∀ᵐ x ∂μ, p x) : ∀ᵐ x ∂μ.restrict s, p x := h.filter_mono (ae_mono Measure.restrict_le_self) theorem ae_restrict_of_ae_restrict_of_subset {s t : Set α} {p : α → Prop} (hst : s ⊆ t) (h : ∀ᵐ x ∂μ.restrict t, p x) : ∀ᵐ x ∂μ.restrict s, p x := h.filter_mono (ae_mono <| Measure.restrict_mono hst (le_refl μ)) theorem ae_of_ae_restrict_of_ae_restrict_compl (t : Set α) {p : α → Prop} (ht : ∀ᵐ x ∂μ.restrict t, p x) (htc : ∀ᵐ x ∂μ.restrict tᶜ, p x) : ∀ᵐ x ∂μ, p x := nonpos_iff_eq_zero.1 <| calc μ { x | ¬p x } ≤ μ ({ x | ¬p x } ∩ t) + μ ({ x | ¬p x } ∩ tᶜ) := measure_le_inter_add_diff _ _ _ _ ≤ μ.restrict t { x | ¬p x } + μ.restrict tᶜ { x | ¬p x } := add_le_add (le_restrict_apply _ _) (le_restrict_apply _ _) _ = 0 := by rw [ae_iff.1 ht, ae_iff.1 htc, zero_add] theorem mem_map_restrict_ae_iff {β} {s : Set α} {t : Set β} {f : α → β} (hs : MeasurableSet s) : t ∈ Filter.map f (ae (μ.restrict s)) ↔ μ ((f ⁻¹' t)ᶜ ∩ s) = 0 := by rw [mem_map, mem_ae_iff, Measure.restrict_apply' hs] theorem ae_add_measure_iff {p : α → Prop} {ν} : (∀ᵐ x ∂μ + ν, p x) ↔ (∀ᵐ x ∂μ, p x) ∧ ∀ᵐ x ∂ν, p x := add_eq_zero theorem ae_eq_comp' {ν : Measure β} {f : α → β} {g g' : β → δ} (hf : AEMeasurable f μ) (h : g =ᵐ[ν] g') (h2 : μ.map f ≪ ν) : g ∘ f =ᵐ[μ] g' ∘ f := (tendsto_ae_map hf).mono_right h2.ae_le h theorem Measure.QuasiMeasurePreserving.ae_eq_comp {ν : Measure β} {f : α → β} {g g' : β → δ} (hf : QuasiMeasurePreserving f μ ν) (h : g =ᵐ[ν] g') : g ∘ f =ᵐ[μ] g' ∘ f := ae_eq_comp' hf.aemeasurable h hf.absolutelyContinuous theorem ae_eq_comp {f : α → β} {g g' : β → δ} (hf : AEMeasurable f μ) (h : g =ᵐ[μ.map f] g') : g ∘ f =ᵐ[μ] g' ∘ f := ae_eq_comp' hf h AbsolutelyContinuous.rfl @[to_additive] theorem div_ae_eq_one {β} [Group β] (f g : α → β) : f / g =ᵐ[μ] 1 ↔ f =ᵐ[μ] g := by refine ⟨fun h ↦ h.mono fun x hx ↦ ?_, fun h ↦ h.mono fun x hx ↦ ?_⟩ · rwa [Pi.div_apply, Pi.one_apply, div_eq_one] at hx · rwa [Pi.div_apply, Pi.one_apply, div_eq_one] @[to_additive sub_nonneg_ae] lemma one_le_div_ae {β : Type*} [Group β] [LE β] [MulRightMono β] (f g : α → β) : 1 ≤ᵐ[μ] g / f ↔ f ≤ᵐ[μ] g := by refine ⟨fun h ↦ h.mono fun a ha ↦ ?_, fun h ↦ h.mono fun a ha ↦ ?_⟩ · rwa [Pi.one_apply, Pi.div_apply, one_le_div'] at ha · rwa [Pi.one_apply, Pi.div_apply, one_le_div'] theorem le_ae_restrict : ae μ ⊓ 𝓟 s ≤ ae (μ.restrict s) := fun _s hs => eventually_inf_principal.2 (ae_imp_of_ae_restrict hs) @[simp] theorem ae_restrict_eq (hs : MeasurableSet s) : ae (μ.restrict s) = ae μ ⊓ 𝓟 s := by ext t simp only [mem_inf_principal, mem_ae_iff, restrict_apply_eq_zero' hs, compl_setOf, Classical.not_imp, fun a => and_comm (a := a ∈ s) (b := ¬a ∈ t)] rfl lemma ae_restrict_le : ae (μ.restrict s) ≤ ae μ := ae_mono restrict_le_self theorem ae_restrict_eq_bot {s} : ae (μ.restrict s) = ⊥ ↔ μ s = 0 := ae_eq_bot.trans restrict_eq_zero theorem ae_restrict_neBot {s} : (ae <| μ.restrict s).NeBot ↔ μ s ≠ 0 := neBot_iff.trans ae_restrict_eq_bot.not theorem self_mem_ae_restrict {s} (hs : MeasurableSet s) : s ∈ ae (μ.restrict s) := by simp only [ae_restrict_eq hs, exists_prop, mem_principal, mem_inf_iff] exact ⟨_, univ_mem, s, Subset.rfl, (univ_inter s).symm⟩ /-- If two measurable sets are ae_eq then any proposition that is almost everywhere true on one is almost everywhere true on the other -/ theorem ae_restrict_of_ae_eq_of_ae_restrict {s t} (hst : s =ᵐ[μ] t) {p : α → Prop} : (∀ᵐ x ∂μ.restrict s, p x) → ∀ᵐ x ∂μ.restrict t, p x := by simp [Measure.restrict_congr_set hst] /-- If two measurable sets are ae_eq then any proposition that is almost everywhere true on one is almost everywhere true on the other -/ theorem ae_restrict_congr_set {s t} (hst : s =ᵐ[μ] t) {p : α → Prop} : (∀ᵐ x ∂μ.restrict s, p x) ↔ ∀ᵐ x ∂μ.restrict t, p x := ⟨ae_restrict_of_ae_eq_of_ae_restrict hst, ae_restrict_of_ae_eq_of_ae_restrict hst.symm⟩ lemma NullMeasurable.measure_preimage_eq_measure_restrict_preimage_of_ae_compl_eq_const {β : Type*} [MeasurableSpace β] {b : β} {f : α → β} {s : Set α} (f_mble : NullMeasurable f (μ.restrict s)) (hs : f =ᵐ[Measure.restrict μ sᶜ] (fun _ ↦ b)) {t : Set β} (t_mble : MeasurableSet t) (ht : b ∉ t) :
μ (f ⁻¹' t) = μ.restrict s (f ⁻¹' t) := by rw [Measure.restrict_apply₀ (f_mble t_mble)] rw [EventuallyEq, ae_iff, Measure.restrict_apply₀] at hs
Mathlib/MeasureTheory/Measure/Restrict.lean
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/- Copyright (c) 2018 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau -/ import Mathlib.RingTheory.Ideal.Operations /-! # Maps on modules and ideals Main definitions include `Ideal.map`, `Ideal.comap`, `RingHom.ker`, `Module.annihilator` and `Submodule.annihilator`. -/ assert_not_exists Basis -- See `RingTheory.Ideal.Basis` Submodule.hasQuotient -- See `RingTheory.Ideal.Quotient.Operations` universe u v w x open Pointwise namespace Ideal section MapAndComap variable {R : Type u} {S : Type v} section Semiring variable {F : Type*} [Semiring R] [Semiring S] variable [FunLike F R S] variable (f : F) variable {I J : Ideal R} {K L : Ideal S} /-- `I.map f` is the span of the image of the ideal `I` under `f`, which may be bigger than the image itself. -/ def map (I : Ideal R) : Ideal S := span (f '' I) /-- `I.comap f` is the preimage of `I` under `f`. -/ def comap [RingHomClass F R S] (I : Ideal S) : Ideal R where carrier := f ⁻¹' I add_mem' {x y} hx hy := by simp only [Set.mem_preimage, SetLike.mem_coe, map_add f] at hx hy ⊢ exact add_mem hx hy zero_mem' := by simp only [Set.mem_preimage, map_zero, SetLike.mem_coe, Submodule.zero_mem] smul_mem' c x hx := by simp only [smul_eq_mul, Set.mem_preimage, map_mul, SetLike.mem_coe] at * exact mul_mem_left I _ hx @[simp] theorem coe_comap [RingHomClass F R S] (I : Ideal S) : (comap f I : Set R) = f ⁻¹' I := rfl lemma comap_coe [RingHomClass F R S] (I : Ideal S) : I.comap (f : R →+* S) = I.comap f := rfl lemma map_coe [RingHomClass F R S] (I : Ideal R) : I.map (f : R →+* S) = I.map f := rfl variable {f} theorem map_mono (h : I ≤ J) : map f I ≤ map f J := span_mono <| Set.image_subset _ h theorem mem_map_of_mem (f : F) {I : Ideal R} {x : R} (h : x ∈ I) : f x ∈ map f I := subset_span ⟨x, h, rfl⟩ theorem apply_coe_mem_map (f : F) (I : Ideal R) (x : I) : f x ∈ I.map f := mem_map_of_mem f x.2 theorem map_le_iff_le_comap [RingHomClass F R S] : map f I ≤ K ↔ I ≤ comap f K := span_le.trans Set.image_subset_iff @[simp] theorem mem_comap [RingHomClass F R S] {x} : x ∈ comap f K ↔ f x ∈ K := Iff.rfl theorem comap_mono [RingHomClass F R S] (h : K ≤ L) : comap f K ≤ comap f L := Set.preimage_mono fun _ hx => h hx variable (f) theorem comap_ne_top [RingHomClass F R S] (hK : K ≠ ⊤) : comap f K ≠ ⊤ := (ne_top_iff_one _).2 <| by rw [mem_comap, map_one]; exact (ne_top_iff_one _).1 hK lemma exists_ideal_comap_le_prime {S} [CommSemiring S] [FunLike F R S] [RingHomClass F R S] {f : F} (P : Ideal R) [P.IsPrime] (I : Ideal S) (le : I.comap f ≤ P) : ∃ Q ≥ I, Q.IsPrime ∧ Q.comap f ≤ P := have ⟨Q, hQ, hIQ, disj⟩ := I.exists_le_prime_disjoint (P.primeCompl.map f) <| Set.disjoint_left.mpr fun _ ↦ by rintro hI ⟨r, hp, rfl⟩; exact hp (le hI) ⟨Q, hIQ, hQ, fun r hp' ↦ of_not_not fun hp ↦ Set.disjoint_left.mp disj hp' ⟨_, hp, rfl⟩⟩ variable {G : Type*} [FunLike G S R] theorem map_le_comap_of_inv_on [RingHomClass G S R] (g : G) (I : Ideal R) (hf : Set.LeftInvOn g f I) : I.map f ≤ I.comap g := by refine Ideal.span_le.2 ?_ rintro x ⟨x, hx, rfl⟩ rw [SetLike.mem_coe, mem_comap, hf hx] exact hx theorem comap_le_map_of_inv_on [RingHomClass F R S] (g : G) (I : Ideal S) (hf : Set.LeftInvOn g f (f ⁻¹' I)) : I.comap f ≤ I.map g := fun x (hx : f x ∈ I) => hf hx ▸ Ideal.mem_map_of_mem g hx /-- The `Ideal` version of `Set.image_subset_preimage_of_inverse`. -/ theorem map_le_comap_of_inverse [RingHomClass G S R] (g : G) (I : Ideal R) (h : Function.LeftInverse g f) : I.map f ≤ I.comap g := map_le_comap_of_inv_on _ _ _ <| h.leftInvOn _ variable [RingHomClass F R S] instance (priority := low) [K.IsTwoSided] : (comap f K).IsTwoSided := ⟨fun b ha ↦ by rw [mem_comap, map_mul]; exact mul_mem_right _ _ ha⟩ /-- The `Ideal` version of `Set.preimage_subset_image_of_inverse`. -/ theorem comap_le_map_of_inverse (g : G) (I : Ideal S) (h : Function.LeftInverse g f) : I.comap f ≤ I.map g := comap_le_map_of_inv_on _ _ _ <| h.leftInvOn _ instance IsPrime.comap [hK : K.IsPrime] : (comap f K).IsPrime := ⟨comap_ne_top _ hK.1, fun {x y} => by simp only [mem_comap, map_mul]; apply hK.2⟩ variable (I J K L) theorem map_top : map f ⊤ = ⊤ := (eq_top_iff_one _).2 <| subset_span ⟨1, trivial, map_one f⟩ theorem gc_map_comap : GaloisConnection (Ideal.map f) (Ideal.comap f) := fun _ _ => Ideal.map_le_iff_le_comap @[simp] theorem comap_id : I.comap (RingHom.id R) = I := Ideal.ext fun _ => Iff.rfl @[simp] lemma comap_idₐ {R S : Type*} [CommSemiring R] [Semiring S] [Algebra R S] (I : Ideal S) : Ideal.comap (AlgHom.id R S) I = I := I.comap_id @[simp] theorem map_id : I.map (RingHom.id R) = I := (gc_map_comap (RingHom.id R)).l_unique GaloisConnection.id comap_id @[simp] lemma map_idₐ {R S : Type*} [CommSemiring R] [Semiring S] [Algebra R S] (I : Ideal S) : Ideal.map (AlgHom.id R S) I = I := I.map_id theorem comap_comap {T : Type*} [Semiring T] {I : Ideal T} (f : R →+* S) (g : S →+* T) : (I.comap g).comap f = I.comap (g.comp f) := rfl lemma comap_comapₐ {R A B C : Type*} [CommSemiring R] [Semiring A] [Algebra R A] [Semiring B] [Algebra R B] [Semiring C] [Algebra R C] {I : Ideal C} (f : A →ₐ[R] B) (g : B →ₐ[R] C) : (I.comap g).comap f = I.comap (g.comp f) := I.comap_comap f.toRingHom g.toRingHom theorem map_map {T : Type*} [Semiring T] {I : Ideal R} (f : R →+* S) (g : S →+* T) : (I.map f).map g = I.map (g.comp f) := ((gc_map_comap f).compose (gc_map_comap g)).l_unique (gc_map_comap (g.comp f)) fun _ => comap_comap _ _ lemma map_mapₐ {R A B C : Type*} [CommSemiring R] [Semiring A] [Algebra R A] [Semiring B] [Algebra R B] [Semiring C] [Algebra R C] {I : Ideal A} (f : A →ₐ[R] B) (g : B →ₐ[R] C) : (I.map f).map g = I.map (g.comp f) := I.map_map f.toRingHom g.toRingHom theorem map_span (f : F) (s : Set R) : map f (span s) = span (f '' s) := by refine (Submodule.span_eq_of_le _ ?_ ?_).symm · rintro _ ⟨x, hx, rfl⟩; exact mem_map_of_mem f (subset_span hx) · rw [map_le_iff_le_comap, span_le, coe_comap, ← Set.image_subset_iff] exact subset_span variable {f I J K L} theorem map_le_of_le_comap : I ≤ K.comap f → I.map f ≤ K := (gc_map_comap f).l_le theorem le_comap_of_map_le : I.map f ≤ K → I ≤ K.comap f := (gc_map_comap f).le_u theorem le_comap_map : I ≤ (I.map f).comap f := (gc_map_comap f).le_u_l _ theorem map_comap_le : (K.comap f).map f ≤ K := (gc_map_comap f).l_u_le _ @[simp] theorem comap_top : (⊤ : Ideal S).comap f = ⊤ := (gc_map_comap f).u_top @[simp] theorem comap_eq_top_iff {I : Ideal S} : I.comap f = ⊤ ↔ I = ⊤ := ⟨fun h => I.eq_top_iff_one.mpr (map_one f ▸ mem_comap.mp ((I.comap f).eq_top_iff_one.mp h)), fun h => by rw [h, comap_top]⟩ @[simp] theorem map_bot : (⊥ : Ideal R).map f = ⊥ := (gc_map_comap f).l_bot theorem ne_bot_of_map_ne_bot (hI : map f I ≠ ⊥) : I ≠ ⊥ := fun h => hI (Eq.mpr (congrArg (fun I ↦ map f I = ⊥) h) map_bot) variable (f I J K L) @[simp] theorem map_comap_map : ((I.map f).comap f).map f = I.map f := (gc_map_comap f).l_u_l_eq_l I @[simp] theorem comap_map_comap : ((K.comap f).map f).comap f = K.comap f := (gc_map_comap f).u_l_u_eq_u K theorem map_sup : (I ⊔ J).map f = I.map f ⊔ J.map f := (gc_map_comap f : GaloisConnection (map f) (comap f)).l_sup theorem comap_inf : comap f (K ⊓ L) = comap f K ⊓ comap f L := rfl variable {ι : Sort*} theorem map_iSup (K : ι → Ideal R) : (iSup K).map f = ⨆ i, (K i).map f := (gc_map_comap f : GaloisConnection (map f) (comap f)).l_iSup theorem comap_iInf (K : ι → Ideal S) : (iInf K).comap f = ⨅ i, (K i).comap f := (gc_map_comap f : GaloisConnection (map f) (comap f)).u_iInf theorem map_sSup (s : Set (Ideal R)) : (sSup s).map f = ⨆ I ∈ s, (I : Ideal R).map f := (gc_map_comap f : GaloisConnection (map f) (comap f)).l_sSup theorem comap_sInf (s : Set (Ideal S)) : (sInf s).comap f = ⨅ I ∈ s, (I : Ideal S).comap f := (gc_map_comap f : GaloisConnection (map f) (comap f)).u_sInf theorem comap_sInf' (s : Set (Ideal S)) : (sInf s).comap f = ⨅ I ∈ comap f '' s, I := _root_.trans (comap_sInf f s) (by rw [iInf_image]) /-- Variant of `Ideal.IsPrime.comap` where ideal is explicit rather than implicit. -/ theorem comap_isPrime [H : IsPrime K] : IsPrime (comap f K) := H.comap f variable {I J K L} theorem map_inf_le : map f (I ⊓ J) ≤ map f I ⊓ map f J := (gc_map_comap f : GaloisConnection (map f) (comap f)).monotone_l.map_inf_le _ _ theorem le_comap_sup : comap f K ⊔ comap f L ≤ comap f (K ⊔ L) := (gc_map_comap f : GaloisConnection (map f) (comap f)).monotone_u.le_map_sup _ _ -- TODO: Should these be simp lemmas? theorem _root_.element_smul_restrictScalars {R S M} [CommSemiring R] [CommSemiring S] [Algebra R S] [AddCommMonoid M] [Module R M] [Module S M] [IsScalarTower R S M] (r : R) (N : Submodule S M) : (algebraMap R S r • N).restrictScalars R = r • N.restrictScalars R := SetLike.coe_injective (congrArg (· '' _) (funext (algebraMap_smul S r))) theorem smul_restrictScalars {R S M} [CommSemiring R] [CommSemiring S] [Algebra R S] [AddCommMonoid M] [Module R M] [Module S M] [IsScalarTower R S M] (I : Ideal R) (N : Submodule S M) : (I.map (algebraMap R S) • N).restrictScalars R = I • N.restrictScalars R := by simp_rw [map, Submodule.span_smul_eq, ← Submodule.coe_set_smul, Submodule.set_smul_eq_iSup, ← element_smul_restrictScalars, iSup_image] exact map_iSup₂ (Submodule.restrictScalarsLatticeHom R S M) _ @[simp] theorem smul_top_eq_map {R S : Type*} [CommSemiring R] [CommSemiring S] [Algebra R S] (I : Ideal R) : I • (⊤ : Submodule R S) = (I.map (algebraMap R S)).restrictScalars R := Eq.trans (smul_restrictScalars I (⊤ : Ideal S)).symm <| congrArg _ <| Eq.trans (Ideal.smul_eq_mul _ _) (Ideal.mul_top _) @[simp] theorem coe_restrictScalars {R S : Type*} [Semiring R] [Semiring S] [Module R S] [IsScalarTower R S S] (I : Ideal S) : (I.restrictScalars R : Set S) = ↑I := rfl /-- The smallest `S`-submodule that contains all `x ∈ I * y ∈ J` is also the smallest `R`-submodule that does so. -/ @[simp] theorem restrictScalars_mul {R S : Type*} [Semiring R] [Semiring S] [Module R S] [IsScalarTower R S S] (I J : Ideal S) : (I * J).restrictScalars R = I.restrictScalars R * J.restrictScalars R := rfl section Surjective section variable (hf : Function.Surjective f) include hf open Function theorem map_comap_of_surjective (I : Ideal S) : map f (comap f I) = I := le_antisymm (map_le_iff_le_comap.2 le_rfl) fun s hsi => let ⟨r, hfrs⟩ := hf s hfrs ▸ (mem_map_of_mem f <| show f r ∈ I from hfrs.symm ▸ hsi) /-- `map` and `comap` are adjoint, and the composition `map f ∘ comap f` is the identity -/ def giMapComap : GaloisInsertion (map f) (comap f) := GaloisInsertion.monotoneIntro (gc_map_comap f).monotone_u (gc_map_comap f).monotone_l (fun _ => le_comap_map) (map_comap_of_surjective _ hf) theorem map_surjective_of_surjective : Surjective (map f) := (giMapComap f hf).l_surjective theorem comap_injective_of_surjective : Injective (comap f) := (giMapComap f hf).u_injective theorem map_sup_comap_of_surjective (I J : Ideal S) : (I.comap f ⊔ J.comap f).map f = I ⊔ J := (giMapComap f hf).l_sup_u _ _ theorem map_iSup_comap_of_surjective (K : ι → Ideal S) : (⨆ i, (K i).comap f).map f = iSup K := (giMapComap f hf).l_iSup_u _ theorem map_inf_comap_of_surjective (I J : Ideal S) : (I.comap f ⊓ J.comap f).map f = I ⊓ J := (giMapComap f hf).l_inf_u _ _ theorem map_iInf_comap_of_surjective (K : ι → Ideal S) : (⨅ i, (K i).comap f).map f = iInf K := (giMapComap f hf).l_iInf_u _ theorem mem_image_of_mem_map_of_surjective {I : Ideal R} {y} (H : y ∈ map f I) : y ∈ f '' I := Submodule.span_induction (hx := H) (fun _ => id) ⟨0, I.zero_mem, map_zero f⟩ (fun _ _ _ _ ⟨x1, hx1i, hxy1⟩ ⟨x2, hx2i, hxy2⟩ => ⟨x1 + x2, I.add_mem hx1i hx2i, hxy1 ▸ hxy2 ▸ map_add f _ _⟩) fun c _ _ ⟨x, hxi, hxy⟩ => let ⟨d, hdc⟩ := hf c ⟨d * x, I.mul_mem_left _ hxi, hdc ▸ hxy ▸ map_mul f _ _⟩ theorem mem_map_iff_of_surjective {I : Ideal R} {y} : y ∈ map f I ↔ ∃ x, x ∈ I ∧ f x = y := ⟨fun h => (Set.mem_image _ _ _).2 (mem_image_of_mem_map_of_surjective f hf h), fun ⟨_, hx⟩ => hx.right ▸ mem_map_of_mem f hx.left⟩ theorem le_map_of_comap_le_of_surjective : comap f K ≤ I → K ≤ map f I := fun h => map_comap_of_surjective f hf K ▸ map_mono h end theorem map_comap_eq_self_of_equiv {E : Type*} [EquivLike E R S] [RingEquivClass E R S] (e : E) (I : Ideal S) : map e (comap e I) = I := I.map_comap_of_surjective e (EquivLike.surjective e) theorem map_eq_submodule_map (f : R →+* S) [h : RingHomSurjective f] (I : Ideal R) : I.map f = Submodule.map f.toSemilinearMap I := Submodule.ext fun _ => mem_map_iff_of_surjective f h.1 instance (priority := low) (f : R →+* S) [RingHomSurjective f] (I : Ideal R) [I.IsTwoSided] : (I.map f).IsTwoSided where mul_mem_of_left b ha := by rw [map_eq_submodule_map] at ha ⊢ obtain ⟨a, ha, rfl⟩ := ha obtain ⟨b, rfl⟩ := f.surjective b rw [RingHom.coe_toSemilinearMap, ← map_mul] exact ⟨_, I.mul_mem_right _ ha, rfl⟩ open Function in theorem IsMaximal.comap_piEvalRingHom {ι : Type*} {R : ι → Type*} [∀ i, Semiring (R i)] {i : ι} {I : Ideal (R i)} (h : I.IsMaximal) : (I.comap <| Pi.evalRingHom R i).IsMaximal := by refine isMaximal_iff.mpr ⟨I.ne_top_iff_one.mp h.ne_top, fun J x le hxI hxJ ↦ ?_⟩ have ⟨r, y, hy, eq⟩ := h.exists_inv hxI classical convert J.add_mem (J.mul_mem_left (update 0 i r) hxJ) (b := update 1 i y) (le <| by apply update_self i y 1 ▸ hy) ext j obtain rfl | ne := eq_or_ne j i · simpa [eq_comm] using eq · simp [update_of_ne ne] theorem comap_le_comap_iff_of_surjective (hf : Function.Surjective f) (I J : Ideal S) : comap f I ≤ comap f J ↔ I ≤ J := ⟨fun h => (map_comap_of_surjective f hf I).symm.le.trans (map_le_of_le_comap h), fun h => le_comap_of_map_le ((map_comap_of_surjective f hf I).le.trans h)⟩ /-- The map on ideals induced by a surjective map preserves inclusion. -/ def orderEmbeddingOfSurjective (hf : Function.Surjective f) : Ideal S ↪o Ideal R where toFun := comap f inj' _ _ eq := SetLike.ext' (Set.preimage_injective.mpr hf <| SetLike.ext'_iff.mp eq) map_rel_iff' := comap_le_comap_iff_of_surjective _ hf .. theorem map_eq_top_or_isMaximal_of_surjective (hf : Function.Surjective f) {I : Ideal R} (H : IsMaximal I) : map f I = ⊤ ∨ IsMaximal (map f I) := or_iff_not_imp_left.2 fun ne_top ↦ ⟨⟨ne_top, fun _J hJ ↦ comap_injective_of_surjective f hf <| H.1.2 _ (le_comap_map.trans_lt <| (orderEmbeddingOfSurjective f hf).strictMono hJ)⟩⟩ end Surjective section Injective theorem comap_bot_le_of_injective (hf : Function.Injective f) : comap f ⊥ ≤ I := by refine le_trans (fun x hx => ?_) bot_le rw [mem_comap, Submodule.mem_bot, ← map_zero f] at hx exact Eq.symm (hf hx) ▸ Submodule.zero_mem ⊥ theorem comap_bot_of_injective (hf : Function.Injective f) : Ideal.comap f ⊥ = ⊥ := le_bot_iff.mp (Ideal.comap_bot_le_of_injective f hf) end Injective /-- If `f : R ≃+* S` is a ring isomorphism and `I : Ideal R`, then `map f.symm (map f I) = I`. -/ @[simp] theorem map_of_equiv {I : Ideal R} (f : R ≃+* S) : (I.map (f : R →+* S)).map (f.symm : S →+* R) = I := by rw [← RingEquiv.toRingHom_eq_coe, ← RingEquiv.toRingHom_eq_coe, map_map, RingEquiv.toRingHom_eq_coe, RingEquiv.toRingHom_eq_coe, RingEquiv.symm_comp, map_id] /-- If `f : R ≃+* S` is a ring isomorphism and `I : Ideal R`, then `comap f (comap f.symm I) = I`. -/ @[simp] theorem comap_of_equiv {I : Ideal R} (f : R ≃+* S) : (I.comap (f.symm : S →+* R)).comap (f : R →+* S) = I := by rw [← RingEquiv.toRingHom_eq_coe, ← RingEquiv.toRingHom_eq_coe, comap_comap, RingEquiv.toRingHom_eq_coe, RingEquiv.toRingHom_eq_coe, RingEquiv.symm_comp, comap_id] /-- If `f : R ≃+* S` is a ring isomorphism and `I : Ideal R`, then `map f I = comap f.symm I`. -/ theorem map_comap_of_equiv {I : Ideal R} (f : R ≃+* S) : I.map (f : R →+* S) = I.comap f.symm := le_antisymm (Ideal.map_le_comap_of_inverse _ _ _ (Equiv.left_inv' _)) (Ideal.comap_le_map_of_inverse _ _ _ (Equiv.right_inv' _)) /-- If `f : R ≃+* S` is a ring isomorphism and `I : Ideal R`, then `comap f.symm I = map f I`. -/ @[simp] theorem comap_symm {I : Ideal R} (f : R ≃+* S) : I.comap f.symm = I.map f := (map_comap_of_equiv f).symm /-- If `f : R ≃+* S` is a ring isomorphism and `I : Ideal R`, then `map f.symm I = comap f I`. -/ @[simp] theorem map_symm {I : Ideal S} (f : R ≃+* S) : I.map f.symm = I.comap f := map_comap_of_equiv (RingEquiv.symm f) @[simp] theorem symm_apply_mem_of_equiv_iff {I : Ideal R} {f : R ≃+* S} {y : S} : f.symm y ∈ I ↔ y ∈ I.map f := by rw [← comap_symm, mem_comap] @[simp] theorem apply_mem_of_equiv_iff {I : Ideal R} {f : R ≃+* S} {x : R} : f x ∈ I.map f ↔ x ∈ I := by rw [← comap_symm, Ideal.mem_comap, f.symm_apply_apply] theorem mem_map_of_equiv {E : Type*} [EquivLike E R S] [RingEquivClass E R S] (e : E) {I : Ideal R} (y : S) : y ∈ map e I ↔ ∃ x ∈ I, e x = y := by constructor · intro h simp_rw [show map e I = _ from map_comap_of_equiv (e : R ≃+* S)] at h exact ⟨(e : R ≃+* S).symm y, h, (e : R ≃+* S).apply_symm_apply y⟩ · rintro ⟨x, hx, rfl⟩ exact mem_map_of_mem e hx section Bijective variable (hf : Function.Bijective f) {I : Ideal R} {K : Ideal S} include hf /-- Special case of the correspondence theorem for isomorphic rings -/ def relIsoOfBijective : Ideal S ≃o Ideal R where toFun := comap f invFun := map f left_inv := map_comap_of_surjective _ hf.2 right_inv J := le_antisymm (fun _ h ↦ have ⟨y, hy, eq⟩ := (mem_map_iff_of_surjective _ hf.2).mp h; hf.1 eq ▸ hy) le_comap_map map_rel_iff' {_ _} := by refine ⟨fun h ↦ ?_, comap_mono⟩ have := map_mono (f := f) h simpa only [Equiv.coe_fn_mk, map_comap_of_surjective f hf.2] using this theorem comap_le_iff_le_map : comap f K ≤ I ↔ K ≤ map f I := ⟨fun h => le_map_of_comap_le_of_surjective f hf.right h, fun h => (relIsoOfBijective f hf).right_inv I ▸ comap_mono h⟩ lemma comap_map_of_bijective : (I.map f).comap f = I := le_antisymm ((comap_le_iff_le_map f hf).mpr fun _ ↦ id) le_comap_map theorem isMaximal_map_iff_of_bijective : IsMaximal (map f I) ↔ IsMaximal I := by simpa only [isMaximal_def] using (relIsoOfBijective _ hf).symm.isCoatom_iff _ theorem isMaximal_comap_iff_of_bijective : IsMaximal (comap f K) ↔ IsMaximal K := by simpa only [isMaximal_def] using (relIsoOfBijective _ hf).isCoatom_iff _ alias ⟨_, IsMaximal.map_bijective⟩ := isMaximal_map_iff_of_bijective alias ⟨_, IsMaximal.comap_bijective⟩ := isMaximal_comap_iff_of_bijective /-- A ring isomorphism sends a maximal ideal to a maximal ideal. -/ instance map_isMaximal_of_equiv {E : Type*} [EquivLike E R S] [RingEquivClass E R S] (e : E) {p : Ideal R} [hp : p.IsMaximal] : (map e p).IsMaximal := hp.map_bijective e (EquivLike.bijective e) /-- The pullback of a maximal ideal under a ring isomorphism is a maximal ideal. -/ instance comap_isMaximal_of_equiv {E : Type*} [EquivLike E R S] [RingEquivClass E R S] (e : E) {p : Ideal S} [hp : p.IsMaximal] : (comap e p).IsMaximal := hp.comap_bijective e (EquivLike.bijective e) theorem isMaximal_iff_of_bijective : (⊥ : Ideal R).IsMaximal ↔ (⊥ : Ideal S).IsMaximal := ⟨fun h ↦ map_bot (f := f) ▸ h.map_bijective f hf, fun h ↦ have e := RingEquiv.ofBijective f hf map_bot (f := e.symm) ▸ h.map_bijective _ e.symm.bijective⟩ @[deprecated (since := "2024-12-07")] alias map.isMaximal := IsMaximal.map_bijective @[deprecated (since := "2024-12-07")] alias comap.isMaximal := IsMaximal.comap_bijective @[deprecated (since := "2024-12-07")] alias RingEquiv.bot_maximal_iff := isMaximal_iff_of_bijective end Bijective end Semiring section Ring variable {F : Type*} [Ring R] [Ring S] variable [FunLike F R S] [RingHomClass F R S] (f : F) {I : Ideal R} section Surjective theorem comap_map_of_surjective (hf : Function.Surjective f) (I : Ideal R) : comap f (map f I) = I ⊔ comap f ⊥ := le_antisymm (fun r h => let ⟨s, hsi, hfsr⟩ := mem_image_of_mem_map_of_surjective f hf h Submodule.mem_sup.2 ⟨s, hsi, r - s, (Submodule.mem_bot S).2 <| by rw [map_sub, hfsr, sub_self], add_sub_cancel s r⟩) (sup_le (map_le_iff_le_comap.1 le_rfl) (comap_mono bot_le)) /-- Correspondence theorem -/ def relIsoOfSurjective (hf : Function.Surjective f) : Ideal S ≃o { p : Ideal R // comap f ⊥ ≤ p } where toFun J := ⟨comap f J, comap_mono bot_le⟩ invFun I := map f I.1 left_inv J := map_comap_of_surjective f hf J right_inv I := Subtype.eq <| show comap f (map f I.1) = I.1 from (comap_map_of_surjective f hf I).symm ▸ le_antisymm (sup_le le_rfl I.2) le_sup_left map_rel_iff' {I1 I2} := ⟨fun H => map_comap_of_surjective f hf I1 ▸ map_comap_of_surjective f hf I2 ▸ map_mono H, comap_mono⟩ -- May not hold if `R` is a semiring: consider `ℕ →+* ZMod 2`. theorem comap_isMaximal_of_surjective (hf : Function.Surjective f) {K : Ideal S} [H : IsMaximal K] : IsMaximal (comap f K) := by refine ⟨⟨comap_ne_top _ H.1.1, fun J hJ => ?_⟩⟩ suffices map f J = ⊤ by have := congr_arg (comap f) this rw [comap_top, comap_map_of_surjective _ hf, eq_top_iff] at this rw [eq_top_iff] exact le_trans this (sup_le (le_of_eq rfl) (le_trans (comap_mono bot_le) (le_of_lt hJ))) refine H.1.2 (map f J) (lt_of_le_of_ne (le_map_of_comap_le_of_surjective _ hf (le_of_lt hJ)) fun h => ne_of_lt hJ (_root_.trans (congr_arg (comap f) h) ?_)) rw [comap_map_of_surjective _ hf, sup_eq_left] exact le_trans (comap_mono bot_le) (le_of_lt hJ) end Surjective end Ring section CommRing variable {F : Type*} [CommSemiring R] [CommSemiring S] variable [FunLike F R S] [rc : RingHomClass F R S] variable (f : F) variable (I J : Ideal R) (K L : Ideal S) protected theorem map_mul {R} [Semiring R] [FunLike F R S] [RingHomClass F R S] (f : F) (I J : Ideal R) : map f (I * J) = map f I * map f J := le_antisymm (map_le_iff_le_comap.2 <| mul_le.2 fun r hri s hsj => show (f (r * s)) ∈ map f I * map f J by rw [map_mul]; exact mul_mem_mul (mem_map_of_mem f hri) (mem_map_of_mem f hsj)) (span_mul_span (↑f '' ↑I) (↑f '' ↑J) ▸ (span_le.2 <| Set.iUnion₂_subset fun _ ⟨r, hri, hfri⟩ => Set.iUnion₂_subset fun _ ⟨s, hsj, hfsj⟩ => Set.singleton_subset_iff.2 <| hfri ▸ hfsj ▸ by rw [← map_mul]; exact mem_map_of_mem f (mul_mem_mul hri hsj))) /-- The pushforward `Ideal.map` as a (semi)ring homomorphism. -/ @[simps] def mapHom : Ideal R →+* Ideal S where toFun := map f map_mul' := Ideal.map_mul f map_one' := by simp only [one_eq_top]; exact Ideal.map_top f map_add' I J := Ideal.map_sup f I J map_zero' := Ideal.map_bot protected theorem map_pow (n : ℕ) : map f (I ^ n) = map f I ^ n := map_pow (mapHom f) I n theorem comap_radical : comap f (radical K) = radical (comap f K) := by ext simp [radical] variable {K} theorem IsRadical.comap (hK : K.IsRadical) : (comap f K).IsRadical := by rw [← hK.radical, comap_radical] apply radical_isRadical variable {I J L} theorem map_radical_le : map f (radical I) ≤ radical (map f I) := map_le_iff_le_comap.2 fun r ⟨n, hrni⟩ => ⟨n, map_pow f r n ▸ mem_map_of_mem f hrni⟩ theorem le_comap_mul : comap f K * comap f L ≤ comap f (K * L) := map_le_iff_le_comap.1 <| (Ideal.map_mul f (comap f K) (comap f L)).symm ▸ mul_mono (map_le_iff_le_comap.2 <| le_rfl) (map_le_iff_le_comap.2 <| le_rfl) theorem le_comap_pow (n : ℕ) : K.comap f ^ n ≤ (K ^ n).comap f := by induction' n with n n_ih · rw [pow_zero, pow_zero, Ideal.one_eq_top, Ideal.one_eq_top] exact rfl.le · rw [pow_succ, pow_succ] exact (Ideal.mul_mono_left n_ih).trans (Ideal.le_comap_mul f) lemma disjoint_map_primeCompl_iff_comap_le {S : Type*} [Semiring S] {f : R →+* S} {p : Ideal R} {I : Ideal S} [p.IsPrime] : Disjoint (I : Set S) (p.primeCompl.map f) ↔ I.comap f ≤ p := by rw [disjoint_comm] simp [Set.disjoint_iff, Set.ext_iff, Ideal.primeCompl, not_imp_not, SetLike.le_def] /-- For a prime ideal `p` of `R`, `p` extended to `S` and restricted back to `R` is `p` if and only if `p` is the restriction of a prime in `S`. -/ lemma comap_map_eq_self_iff_of_isPrime {S : Type*} [CommSemiring S] {f : R →+* S} (p : Ideal R) [p.IsPrime] : (p.map f).comap f = p ↔ (∃ (q : Ideal S), q.IsPrime ∧ q.comap f = p) := by refine ⟨fun hp ↦ ?_, ?_⟩ · obtain ⟨q, hq₁, hq₂, hq₃⟩ := Ideal.exists_le_prime_disjoint _ _ (disjoint_map_primeCompl_iff_comap_le.mpr hp.le) exact ⟨q, hq₁, le_antisymm (disjoint_map_primeCompl_iff_comap_le.mp hq₃) (map_le_iff_le_comap.mp hq₂)⟩ · rintro ⟨q, hq, rfl⟩ simp end CommRing end MapAndComap end Ideal namespace RingHom variable {R : Type u} {S : Type v} {T : Type w} section Semiring variable {F : Type*} {G : Type*} [Semiring R] [Semiring S] [Semiring T] variable [FunLike F R S] [rcf : RingHomClass F R S] [FunLike G T S] [rcg : RingHomClass G T S] variable (f : F) (g : G) /-- Kernel of a ring homomorphism as an ideal of the domain. -/ def ker : Ideal R := Ideal.comap f ⊥ instance (priority := low) : (ker f).IsTwoSided := inferInstanceAs (Ideal.comap f ⊥).IsTwoSided variable {f} in /-- An element is in the kernel if and only if it maps to zero. -/ @[simp] theorem mem_ker {r} : r ∈ ker f ↔ f r = 0 := by rw [ker, Ideal.mem_comap, Submodule.mem_bot] theorem ker_eq : (ker f : Set R) = Set.preimage f {0} := rfl theorem ker_eq_comap_bot (f : F) : ker f = Ideal.comap f ⊥ := rfl theorem comap_ker (f : S →+* R) (g : T →+* S) : (ker f).comap g = ker (f.comp g) := by rw [RingHom.ker_eq_comap_bot, Ideal.comap_comap, RingHom.ker_eq_comap_bot] /-- If the target is not the zero ring, then one is not in the kernel. -/ theorem not_one_mem_ker [Nontrivial S] (f : F) : (1 : R) ∉ ker f := by rw [mem_ker, map_one] exact one_ne_zero theorem ker_ne_top [Nontrivial S] (f : F) : ker f ≠ ⊤ := (Ideal.ne_top_iff_one _).mpr <| not_one_mem_ker f lemma _root_.Pi.ker_ringHom {ι : Type*} {R : ι → Type*} [∀ i, Semiring (R i)] (φ : ∀ i, S →+* R i) : ker (Pi.ringHom φ) = ⨅ i, ker (φ i) := by ext x simp [mem_ker, Ideal.mem_iInf, funext_iff] @[simp] theorem ker_rangeSRestrict (f : R →+* S) : ker f.rangeSRestrict = ker f := Ideal.ext fun _ ↦ Subtype.ext_iff @[simp] theorem ker_coe_equiv (f : R ≃+* S) : ker (f : R →+* S) = ⊥ := by ext; simp theorem ker_coe_toRingHom : ker (f : R →+* S) = ker f := rfl @[simp] theorem ker_equiv {F' : Type*} [EquivLike F' R S] [RingEquivClass F' R S] (f : F') : ker f = ⊥ := by ext; simp lemma ker_equiv_comp (f : R →+* S) (e : S ≃+* T) : ker (e.toRingHom.comp f) = RingHom.ker f := by rw [← RingHom.comap_ker, RingEquiv.toRingHom_eq_coe, RingHom.ker_coe_equiv, RingHom.ker] end Semiring section Ring variable {F : Type*} [Ring R] [Semiring S] [FunLike F R S] [rc : RingHomClass F R S] (f : F) theorem injective_iff_ker_eq_bot : Function.Injective f ↔ ker f = ⊥ := by rw [SetLike.ext'_iff, ker_eq, Set.ext_iff] exact injective_iff_map_eq_zero' f
theorem ker_eq_bot_iff_eq_zero : ker f = ⊥ ↔ ∀ x, f x = 0 → x = 0 := by rw [← injective_iff_map_eq_zero f, injective_iff_ker_eq_bot]
Mathlib/RingTheory/Ideal/Maps.lean
715
716
/- Copyright (c) 2022 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn -/ import Mathlib.Analysis.Calculus.ContDiff.Basic import Mathlib.Analysis.Calculus.ParametricIntegral import Mathlib.MeasureTheory.Integral.Prod import Mathlib.MeasureTheory.Function.LocallyIntegrable import Mathlib.MeasureTheory.Group.Integral import Mathlib.MeasureTheory.Group.Prod import Mathlib.MeasureTheory.Integral.IntervalIntegral.Basic /-! # Convolution of functions This file defines the convolution on two functions, i.e. `x ↦ ∫ f(t)g(x - t) ∂t`. In the general case, these functions can be vector-valued, and have an arbitrary (additive) group as domain. We use a continuous bilinear operation `L` on these function values as "multiplication". The domain must be equipped with a Haar measure `μ` (though many individual results have weaker conditions on `μ`). For many applications we can take `L = ContinuousLinearMap.lsmul ℝ ℝ` or `L = ContinuousLinearMap.mul ℝ ℝ`. We also define `ConvolutionExists` and `ConvolutionExistsAt` to state that the convolution is well-defined (everywhere or at a single point). These conditions are needed for pointwise computations (e.g. `ConvolutionExistsAt.distrib_add`), but are generally not strong enough for any local (or global) properties of the convolution. For this we need stronger assumptions on `f` and/or `g`, and generally if we impose stronger conditions on one of the functions, we can impose weaker conditions on the other. We have proven many of the properties of the convolution assuming one of these functions has compact support (in which case the other function only needs to be locally integrable). We still need to prove the properties for other pairs of conditions (e.g. both functions are rapidly decreasing) # Design Decisions We use a bilinear map `L` to "multiply" the two functions in the integrand. This generality has several advantages * This allows us to compute the total derivative of the convolution, in case the functions are multivariate. The total derivative is again a convolution, but where the codomains of the functions can be higher-dimensional. See `HasCompactSupport.hasFDerivAt_convolution_right`. * This allows us to use `@[to_additive]` everywhere (which would not be possible if we would use `mul`/`smul` in the integral, since `@[to_additive]` will incorrectly also try to additivize those definitions). * We need to support the case where at least one of the functions is vector-valued, but if we use `smul` to multiply the functions, that would be an asymmetric definition. # Main Definitions * `MeasureTheory.convolution f g L μ x = (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ` is the convolution of `f` and `g` w.r.t. the continuous bilinear map `L` and measure `μ`. * `MeasureTheory.ConvolutionExistsAt f g x L μ` states that the convolution `(f ⋆[L, μ] g) x` is well-defined (i.e. the integral exists). * `MeasureTheory.ConvolutionExists f g L μ` states that the convolution `f ⋆[L, μ] g` is well-defined at each point. # Main Results * `HasCompactSupport.hasFDerivAt_convolution_right` and `HasCompactSupport.hasFDerivAt_convolution_left`: we can compute the total derivative of the convolution as a convolution with the total derivative of the right (left) function. * `HasCompactSupport.contDiff_convolution_right` and `HasCompactSupport.contDiff_convolution_left`: the convolution is `𝒞ⁿ` if one of the functions is `𝒞ⁿ` with compact support and the other function in locally integrable. Versions of these statements for functions depending on a parameter are also given. * `MeasureTheory.convolution_tendsto_right`: Given a sequence of nonnegative normalized functions whose support tends to a small neighborhood around `0`, the convolution tends to the right argument. This is specialized to bump functions in `ContDiffBump.convolution_tendsto_right`. # Notation The following notations are localized in the locale `Convolution`: * `f ⋆[L, μ] g` for the convolution. Note: you have to use parentheses to apply the convolution to an argument: `(f ⋆[L, μ] g) x`. * `f ⋆[L] g := f ⋆[L, volume] g` * `f ⋆ g := f ⋆[lsmul ℝ ℝ] g` # To do * Existence and (uniform) continuity of the convolution if one of the maps is in `ℒ^p` and the other in `ℒ^q` with `1 / p + 1 / q = 1`. This might require a generalization of `MeasureTheory.MemLp.smul` where `smul` is generalized to a continuous bilinear map. (see e.g. [Fremlin, *Measure Theory* (volume 2)][fremlin_vol2], 255K) * The convolution is an `AEStronglyMeasurable` function (see e.g. [Fremlin, *Measure Theory* (volume 2)][fremlin_vol2], 255I). * Prove properties about the convolution if both functions are rapidly decreasing. * Use `@[to_additive]` everywhere (this likely requires changes in `to_additive`) -/ open Set Function Filter MeasureTheory MeasureTheory.Measure TopologicalSpace open Bornology ContinuousLinearMap Metric Topology open scoped Pointwise NNReal Filter universe u𝕜 uG uE uE' uE'' uF uF' uF'' uP variable {𝕜 : Type u𝕜} {G : Type uG} {E : Type uE} {E' : Type uE'} {E'' : Type uE''} {F : Type uF} {F' : Type uF'} {F'' : Type uF''} {P : Type uP} variable [NormedAddCommGroup E] [NormedAddCommGroup E'] [NormedAddCommGroup E''] [NormedAddCommGroup F] {f f' : G → E} {g g' : G → E'} {x x' : G} {y y' : E} namespace MeasureTheory section NontriviallyNormedField variable [NontriviallyNormedField 𝕜] variable [NormedSpace 𝕜 E] [NormedSpace 𝕜 E'] [NormedSpace 𝕜 E''] [NormedSpace 𝕜 F] variable (L : E →L[𝕜] E' →L[𝕜] F) section NoMeasurability variable [AddGroup G] [TopologicalSpace G] theorem convolution_integrand_bound_right_of_le_of_subset {C : ℝ} (hC : ∀ i, ‖g i‖ ≤ C) {x t : G} {s u : Set G} (hx : x ∈ s) (hu : -tsupport g + s ⊆ u) : ‖L (f t) (g (x - t))‖ ≤ u.indicator (fun t => ‖L‖ * ‖f t‖ * C) t := by -- Porting note: had to add `f := _` refine le_indicator (f := fun t ↦ ‖L (f t) (g (x - t))‖) (fun t _ => ?_) (fun t ht => ?_) t · apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl] · have : x - t ∉ support g := by refine mt (fun hxt => hu ?_) ht refine ⟨_, Set.neg_mem_neg.mpr (subset_closure hxt), _, hx, ?_⟩ simp only [neg_sub, sub_add_cancel] simp only [nmem_support.mp this, (L _).map_zero, norm_zero, le_rfl] theorem _root_.HasCompactSupport.convolution_integrand_bound_right_of_subset (hcg : HasCompactSupport g) (hg : Continuous g) {x t : G} {s u : Set G} (hx : x ∈ s) (hu : -tsupport g + s ⊆ u) : ‖L (f t) (g (x - t))‖ ≤ u.indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖) t := by refine convolution_integrand_bound_right_of_le_of_subset _ (fun i => ?_) hx hu exact le_ciSup (hg.norm.bddAbove_range_of_hasCompactSupport hcg.norm) _ theorem _root_.HasCompactSupport.convolution_integrand_bound_right (hcg : HasCompactSupport g) (hg : Continuous g) {x t : G} {s : Set G} (hx : x ∈ s) : ‖L (f t) (g (x - t))‖ ≤ (-tsupport g + s).indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖) t := hcg.convolution_integrand_bound_right_of_subset L hg hx Subset.rfl theorem _root_.Continuous.convolution_integrand_fst [ContinuousSub G] (hg : Continuous g) (t : G) : Continuous fun x => L (f t) (g (x - t)) := L.continuous₂.comp₂ continuous_const <| hg.comp <| continuous_id.sub continuous_const theorem _root_.HasCompactSupport.convolution_integrand_bound_left (hcf : HasCompactSupport f) (hf : Continuous f) {x t : G} {s : Set G} (hx : x ∈ s) : ‖L (f (x - t)) (g t)‖ ≤ (-tsupport f + s).indicator (fun t => (‖L‖ * ⨆ i, ‖f i‖) * ‖g t‖) t := by convert hcf.convolution_integrand_bound_right L.flip hf hx using 1 simp_rw [L.opNorm_flip, mul_right_comm] end NoMeasurability section Measurability variable [MeasurableSpace G] {μ ν : Measure G} /-- The convolution of `f` and `g` exists at `x` when the function `t ↦ L (f t) (g (x - t))` is integrable. There are various conditions on `f` and `g` to prove this. -/ def ConvolutionExistsAt [Sub G] (f : G → E) (g : G → E') (x : G) (L : E →L[𝕜] E' →L[𝕜] F) (μ : Measure G := by volume_tac) : Prop := Integrable (fun t => L (f t) (g (x - t))) μ /-- The convolution of `f` and `g` exists when the function `t ↦ L (f t) (g (x - t))` is integrable for all `x : G`. There are various conditions on `f` and `g` to prove this. -/ def ConvolutionExists [Sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F) (μ : Measure G := by volume_tac) : Prop := ∀ x : G, ConvolutionExistsAt f g x L μ section ConvolutionExists variable {L} in theorem ConvolutionExistsAt.integrable [Sub G] {x : G} (h : ConvolutionExistsAt f g x L μ) : Integrable (fun t => L (f t) (g (x - t))) μ := h section Group variable [AddGroup G] theorem AEStronglyMeasurable.convolution_integrand' [MeasurableAdd₂ G] [MeasurableNeg G] (hf : AEStronglyMeasurable f ν) (hg : AEStronglyMeasurable g <| map (fun p : G × G => p.1 - p.2) (μ.prod ν)) : AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) := L.aestronglyMeasurable_comp₂ hf.snd <| hg.comp_measurable measurable_sub section variable [MeasurableAdd G] [MeasurableNeg G] theorem AEStronglyMeasurable.convolution_integrand_snd' (hf : AEStronglyMeasurable f μ) {x : G} (hg : AEStronglyMeasurable g <| map (fun t => x - t) μ) : AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ := L.aestronglyMeasurable_comp₂ hf <| hg.comp_measurable <| measurable_id.const_sub x theorem AEStronglyMeasurable.convolution_integrand_swap_snd' {x : G} (hf : AEStronglyMeasurable f <| map (fun t => x - t) μ) (hg : AEStronglyMeasurable g μ) : AEStronglyMeasurable (fun t => L (f (x - t)) (g t)) μ := L.aestronglyMeasurable_comp₂ (hf.comp_measurable <| measurable_id.const_sub x) hg /-- A sufficient condition to prove that `f ⋆[L, μ] g` exists. We assume that `f` is integrable on a set `s` and `g` is bounded and ae strongly measurable on `x₀ - s` (note that both properties hold if `g` is continuous with compact support). -/ theorem _root_.BddAbove.convolutionExistsAt' {x₀ : G} {s : Set G} (hbg : BddAbove ((fun i => ‖g i‖) '' ((fun t => -t + x₀) ⁻¹' s))) (hs : MeasurableSet s) (h2s : (support fun t => L (f t) (g (x₀ - t))) ⊆ s) (hf : IntegrableOn f s μ) (hmg : AEStronglyMeasurable g <| map (fun t => x₀ - t) (μ.restrict s)) : ConvolutionExistsAt f g x₀ L μ := by rw [ConvolutionExistsAt] rw [← integrableOn_iff_integrable_of_support_subset h2s] set s' := (fun t => -t + x₀) ⁻¹' s have : ∀ᵐ t : G ∂μ.restrict s, ‖L (f t) (g (x₀ - t))‖ ≤ s.indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i : s', ‖g i‖) t := by filter_upwards refine le_indicator (fun t ht => ?_) fun t ht => ?_ · apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl] refine (le_ciSup_set hbg <| mem_preimage.mpr ?_) rwa [neg_sub, sub_add_cancel] · have : t ∉ support fun t => L (f t) (g (x₀ - t)) := mt (fun h => h2s h) ht rw [nmem_support.mp this, norm_zero] refine Integrable.mono' ?_ ?_ this · rw [integrable_indicator_iff hs]; exact ((hf.norm.const_mul _).mul_const _).integrableOn · exact hf.aestronglyMeasurable.convolution_integrand_snd' L hmg /-- If `‖f‖ *[μ] ‖g‖` exists, then `f *[L, μ] g` exists. -/ theorem ConvolutionExistsAt.of_norm' {x₀ : G} (h : ConvolutionExistsAt (fun x => ‖f x‖) (fun x => ‖g x‖) x₀ (mul ℝ ℝ) μ) (hmf : AEStronglyMeasurable f μ) (hmg : AEStronglyMeasurable g <| map (fun t => x₀ - t) μ) : ConvolutionExistsAt f g x₀ L μ := by refine (h.const_mul ‖L‖).mono' (hmf.convolution_integrand_snd' L hmg) (Eventually.of_forall fun x => ?_) rw [mul_apply', ← mul_assoc] apply L.le_opNorm₂ @[deprecated (since := "2025-02-07")] alias ConvolutionExistsAt.ofNorm' := ConvolutionExistsAt.of_norm' end section Left variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ] theorem AEStronglyMeasurable.convolution_integrand_snd (hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ) (x : G) : AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ := hf.convolution_integrand_snd' L <| hg.mono_ac <| (quasiMeasurePreserving_sub_left_of_right_invariant μ x).absolutelyContinuous theorem AEStronglyMeasurable.convolution_integrand_swap_snd (hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ) (x : G) : AEStronglyMeasurable (fun t => L (f (x - t)) (g t)) μ := (hf.mono_ac (quasiMeasurePreserving_sub_left_of_right_invariant μ x).absolutelyContinuous).convolution_integrand_swap_snd' L hg /-- If `‖f‖ *[μ] ‖g‖` exists, then `f *[L, μ] g` exists. -/ theorem ConvolutionExistsAt.of_norm {x₀ : G} (h : ConvolutionExistsAt (fun x => ‖f x‖) (fun x => ‖g x‖) x₀ (mul ℝ ℝ) μ) (hmf : AEStronglyMeasurable f μ) (hmg : AEStronglyMeasurable g μ) : ConvolutionExistsAt f g x₀ L μ := h.of_norm' L hmf <| hmg.mono_ac (quasiMeasurePreserving_sub_left_of_right_invariant μ x₀).absolutelyContinuous @[deprecated (since := "2025-02-07")] alias ConvolutionExistsAt.ofNorm := ConvolutionExistsAt.of_norm end Left section Right variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ] [SFinite ν] theorem AEStronglyMeasurable.convolution_integrand (hf : AEStronglyMeasurable f ν) (hg : AEStronglyMeasurable g μ) : AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) := hf.convolution_integrand' L <| hg.mono_ac (quasiMeasurePreserving_sub_of_right_invariant μ ν).absolutelyContinuous theorem Integrable.convolution_integrand (hf : Integrable f ν) (hg : Integrable g μ) : Integrable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) := by have h_meas : AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) := hf.aestronglyMeasurable.convolution_integrand L hg.aestronglyMeasurable have h2_meas : AEStronglyMeasurable (fun y : G => ∫ x : G, ‖L (f y) (g (x - y))‖ ∂μ) ν := h_meas.prod_swap.norm.integral_prod_right' simp_rw [integrable_prod_iff' h_meas] refine ⟨Eventually.of_forall fun t => (L (f t)).integrable_comp (hg.comp_sub_right t), ?_⟩ refine Integrable.mono' ?_ h2_meas (Eventually.of_forall fun t => (?_ : _ ≤ ‖L‖ * ‖f t‖ * ∫ x, ‖g (x - t)‖ ∂μ)) · simp only [integral_sub_right_eq_self (‖g ·‖)] exact (hf.norm.const_mul _).mul_const _ · simp_rw [← integral_const_mul] rw [Real.norm_of_nonneg (by positivity)] exact integral_mono_of_nonneg (Eventually.of_forall fun t => norm_nonneg _) ((hg.comp_sub_right t).norm.const_mul _) (Eventually.of_forall fun t => L.le_opNorm₂ _ _) theorem Integrable.ae_convolution_exists (hf : Integrable f ν) (hg : Integrable g μ) : ∀ᵐ x ∂μ, ConvolutionExistsAt f g x L ν := ((integrable_prod_iff <| hf.aestronglyMeasurable.convolution_integrand L hg.aestronglyMeasurable).mp <| hf.convolution_integrand L hg).1 end Right variable [TopologicalSpace G] [IsTopologicalAddGroup G] [BorelSpace G] theorem _root_.HasCompactSupport.convolutionExistsAt {x₀ : G} (h : HasCompactSupport fun t => L (f t) (g (x₀ - t))) (hf : LocallyIntegrable f μ) (hg : Continuous g) : ConvolutionExistsAt f g x₀ L μ := by let u := (Homeomorph.neg G).trans (Homeomorph.addRight x₀) let v := (Homeomorph.neg G).trans (Homeomorph.addLeft x₀) apply ((u.isCompact_preimage.mpr h).bddAbove_image hg.norm.continuousOn).convolutionExistsAt' L isClosed_closure.measurableSet subset_closure (hf.integrableOn_isCompact h) have A : AEStronglyMeasurable (g ∘ v) (μ.restrict (tsupport fun t : G => L (f t) (g (x₀ - t)))) := by apply (hg.comp v.continuous).continuousOn.aestronglyMeasurable_of_isCompact h exact (isClosed_tsupport _).measurableSet convert ((v.continuous.measurable.measurePreserving (μ.restrict (tsupport fun t => L (f t) (g (x₀ - t))))).aestronglyMeasurable_comp_iff v.measurableEmbedding).1 A ext x simp only [v, Homeomorph.neg, sub_eq_add_neg, val_toAddUnits_apply, Homeomorph.trans_apply, Equiv.neg_apply, Equiv.toFun_as_coe, Homeomorph.homeomorph_mk_coe, Equiv.coe_fn_mk, Homeomorph.coe_addLeft] theorem _root_.HasCompactSupport.convolutionExists_right (hcg : HasCompactSupport g) (hf : LocallyIntegrable f μ) (hg : Continuous g) : ConvolutionExists f g L μ := by intro x₀ refine HasCompactSupport.convolutionExistsAt L ?_ hf hg refine (hcg.comp_homeomorph (Homeomorph.subLeft x₀)).mono ?_ refine fun t => mt fun ht : g (x₀ - t) = 0 => ?_ simp_rw [ht, (L _).map_zero] theorem _root_.HasCompactSupport.convolutionExists_left_of_continuous_right (hcf : HasCompactSupport f) (hf : LocallyIntegrable f μ) (hg : Continuous g) : ConvolutionExists f g L μ := by intro x₀ refine HasCompactSupport.convolutionExistsAt L ?_ hf hg refine hcf.mono ?_ refine fun t => mt fun ht : f t = 0 => ?_ simp_rw [ht, L.map_zero₂] end Group section CommGroup variable [AddCommGroup G] section MeasurableGroup variable [MeasurableNeg G] [IsAddLeftInvariant μ] /-- A sufficient condition to prove that `f ⋆[L, μ] g` exists. We assume that the integrand has compact support and `g` is bounded on this support (note that both properties hold if `g` is continuous with compact support). We also require that `f` is integrable on the support of the integrand, and that both functions are strongly measurable. This is a variant of `BddAbove.convolutionExistsAt'` in an abelian group with a left-invariant measure. This allows us to state the boundedness and measurability of `g` in a more natural way. -/ theorem _root_.BddAbove.convolutionExistsAt [MeasurableAdd₂ G] [SFinite μ] {x₀ : G} {s : Set G} (hbg : BddAbove ((fun i => ‖g i‖) '' ((fun t => x₀ - t) ⁻¹' s))) (hs : MeasurableSet s) (h2s : (support fun t => L (f t) (g (x₀ - t))) ⊆ s) (hf : IntegrableOn f s μ) (hmg : AEStronglyMeasurable g μ) : ConvolutionExistsAt f g x₀ L μ := by refine BddAbove.convolutionExistsAt' L ?_ hs h2s hf ?_ · simp_rw [← sub_eq_neg_add, hbg] · have : AEStronglyMeasurable g (map (fun t : G => x₀ - t) μ) := hmg.mono_ac (quasiMeasurePreserving_sub_left_of_right_invariant μ x₀).absolutelyContinuous apply this.mono_measure exact map_mono restrict_le_self (measurable_const.sub measurable_id') variable {L} [MeasurableAdd G] [IsNegInvariant μ] theorem convolutionExistsAt_flip : ConvolutionExistsAt g f x L.flip μ ↔ ConvolutionExistsAt f g x L μ := by simp_rw [ConvolutionExistsAt, ← integrable_comp_sub_left (fun t => L (f t) (g (x - t))) x, sub_sub_cancel, flip_apply] theorem ConvolutionExistsAt.integrable_swap (h : ConvolutionExistsAt f g x L μ) : Integrable (fun t => L (f (x - t)) (g t)) μ := by convert h.comp_sub_left x simp_rw [sub_sub_self] theorem convolutionExistsAt_iff_integrable_swap : ConvolutionExistsAt f g x L μ ↔ Integrable (fun t => L (f (x - t)) (g t)) μ := convolutionExistsAt_flip.symm end MeasurableGroup variable [TopologicalSpace G] [IsTopologicalAddGroup G] [BorelSpace G] variable [IsAddLeftInvariant μ] [IsNegInvariant μ] theorem _root_.HasCompactSupport.convolutionExists_left (hcf : HasCompactSupport f) (hf : Continuous f) (hg : LocallyIntegrable g μ) : ConvolutionExists f g L μ := fun x₀ => convolutionExistsAt_flip.mp <| hcf.convolutionExists_right L.flip hg hf x₀ @[deprecated (since := "2025-02-06")] alias _root_.HasCompactSupport.convolutionExistsLeft := HasCompactSupport.convolutionExists_left theorem _root_.HasCompactSupport.convolutionExists_right_of_continuous_left (hcg : HasCompactSupport g) (hf : Continuous f) (hg : LocallyIntegrable g μ) : ConvolutionExists f g L μ := fun x₀ => convolutionExistsAt_flip.mp <| hcg.convolutionExists_left_of_continuous_right L.flip hg hf x₀ @[deprecated (since := "2025-02-06")] alias _root_.HasCompactSupport.convolutionExistsRightOfContinuousLeft := HasCompactSupport.convolutionExists_right_of_continuous_left end CommGroup end ConvolutionExists variable [NormedSpace ℝ F] /-- The convolution of two functions `f` and `g` with respect to a continuous bilinear map `L` and measure `μ`. It is defined to be `(f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ`. -/ noncomputable def convolution [Sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F) (μ : Measure G := by volume_tac) : G → F := fun x => ∫ t, L (f t) (g (x - t)) ∂μ /-- The convolution of two functions with respect to a bilinear operation `L` and a measure `μ`. -/ scoped[Convolution] notation:67 f " ⋆[" L:67 ", " μ:67 "] " g:66 => convolution f g L μ /-- The convolution of two functions with respect to a bilinear operation `L` and the volume. -/ scoped[Convolution] notation:67 f " ⋆[" L:67 "]" g:66 => convolution f g L MeasureSpace.volume /-- The convolution of two real-valued functions with respect to volume. -/ scoped[Convolution] notation:67 f " ⋆ " g:66 => convolution f g (ContinuousLinearMap.lsmul ℝ ℝ) MeasureSpace.volume open scoped Convolution theorem convolution_def [Sub G] : (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ := rfl /-- The definition of convolution where the bilinear operator is scalar multiplication. Note: it often helps the elaborator to give the type of the convolution explicitly. -/ theorem convolution_lsmul [Sub G] {f : G → 𝕜} {g : G → F} : (f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f t • g (x - t) ∂μ := rfl /-- The definition of convolution where the bilinear operator is multiplication. -/ theorem convolution_mul [Sub G] [NormedSpace ℝ 𝕜] {f : G → 𝕜} {g : G → 𝕜} : (f ⋆[mul 𝕜 𝕜, μ] g) x = ∫ t, f t * g (x - t) ∂μ := rfl section Group variable {L} [AddGroup G] theorem smul_convolution [SMulCommClass ℝ 𝕜 F] {y : 𝕜} : y • f ⋆[L, μ] g = y • (f ⋆[L, μ] g) := by ext; simp only [Pi.smul_apply, convolution_def, ← integral_smul, L.map_smul₂] theorem convolution_smul [SMulCommClass ℝ 𝕜 F] {y : 𝕜} : f ⋆[L, μ] y • g = y • (f ⋆[L, μ] g) := by ext; simp only [Pi.smul_apply, convolution_def, ← integral_smul, (L _).map_smul] @[simp] theorem zero_convolution : 0 ⋆[L, μ] g = 0 := by ext simp_rw [convolution_def, Pi.zero_apply, L.map_zero₂, integral_zero] @[simp] theorem convolution_zero : f ⋆[L, μ] 0 = 0 := by ext simp_rw [convolution_def, Pi.zero_apply, (L _).map_zero, integral_zero] theorem ConvolutionExistsAt.distrib_add {x : G} (hfg : ConvolutionExistsAt f g x L μ) (hfg' : ConvolutionExistsAt f g' x L μ) : (f ⋆[L, μ] (g + g')) x = (f ⋆[L, μ] g) x + (f ⋆[L, μ] g') x := by simp only [convolution_def, (L _).map_add, Pi.add_apply, integral_add hfg hfg'] theorem ConvolutionExists.distrib_add (hfg : ConvolutionExists f g L μ) (hfg' : ConvolutionExists f g' L μ) : f ⋆[L, μ] (g + g') = f ⋆[L, μ] g + f ⋆[L, μ] g' := by ext x exact (hfg x).distrib_add (hfg' x) theorem ConvolutionExistsAt.add_distrib {x : G} (hfg : ConvolutionExistsAt f g x L μ) (hfg' : ConvolutionExistsAt f' g x L μ) : ((f + f') ⋆[L, μ] g) x = (f ⋆[L, μ] g) x + (f' ⋆[L, μ] g) x := by simp only [convolution_def, L.map_add₂, Pi.add_apply, integral_add hfg hfg'] theorem ConvolutionExists.add_distrib (hfg : ConvolutionExists f g L μ) (hfg' : ConvolutionExists f' g L μ) : (f + f') ⋆[L, μ] g = f ⋆[L, μ] g + f' ⋆[L, μ] g := by ext x exact (hfg x).add_distrib (hfg' x) theorem convolution_mono_right {f g g' : G → ℝ} (hfg : ConvolutionExistsAt f g x (lsmul ℝ ℝ) μ) (hfg' : ConvolutionExistsAt f g' x (lsmul ℝ ℝ) μ) (hf : ∀ x, 0 ≤ f x) (hg : ∀ x, g x ≤ g' x) : (f ⋆[lsmul ℝ ℝ, μ] g) x ≤ (f ⋆[lsmul ℝ ℝ, μ] g') x := by apply integral_mono hfg hfg' simp only [lsmul_apply, Algebra.id.smul_eq_mul] intro t apply mul_le_mul_of_nonneg_left (hg _) (hf _) theorem convolution_mono_right_of_nonneg {f g g' : G → ℝ} (hfg' : ConvolutionExistsAt f g' x (lsmul ℝ ℝ) μ) (hf : ∀ x, 0 ≤ f x) (hg : ∀ x, g x ≤ g' x) (hg' : ∀ x, 0 ≤ g' x) : (f ⋆[lsmul ℝ ℝ, μ] g) x ≤ (f ⋆[lsmul ℝ ℝ, μ] g') x := by by_cases H : ConvolutionExistsAt f g x (lsmul ℝ ℝ) μ · exact convolution_mono_right H hfg' hf hg have : (f ⋆[lsmul ℝ ℝ, μ] g) x = 0 := integral_undef H rw [this] exact integral_nonneg fun y => mul_nonneg (hf y) (hg' (x - y)) variable (L) theorem convolution_congr [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ] (h1 : f =ᵐ[μ] f') (h2 : g =ᵐ[μ] g') : f ⋆[L, μ] g = f' ⋆[L, μ] g' := by ext x apply integral_congr_ae exact (h1.prodMk <| h2.comp_tendsto (quasiMeasurePreserving_sub_left_of_right_invariant μ x).tendsto_ae).fun_comp ↿fun x y ↦ L x y theorem support_convolution_subset_swap : support (f ⋆[L, μ] g) ⊆ support g + support f := by intro x h2x by_contra hx apply h2x simp_rw [Set.mem_add, ← exists_and_left, not_exists, not_and_or, nmem_support] at hx rw [convolution_def] convert integral_zero G F using 2 ext t rcases hx (x - t) t with (h | h | h) · rw [h, (L _).map_zero] · rw [h, L.map_zero₂] · exact (h <| sub_add_cancel x t).elim section variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ] theorem Integrable.integrable_convolution (hf : Integrable f μ) (hg : Integrable g μ) : Integrable (f ⋆[L, μ] g) μ := (hf.convolution_integrand L hg).integral_prod_left end variable [TopologicalSpace G] variable [IsTopologicalAddGroup G] protected theorem _root_.HasCompactSupport.convolution [T2Space G] (hcf : HasCompactSupport f) (hcg : HasCompactSupport g) : HasCompactSupport (f ⋆[L, μ] g) := (hcg.isCompact.add hcf).of_isClosed_subset isClosed_closure <| closure_minimal ((support_convolution_subset_swap L).trans <| add_subset_add subset_closure subset_closure) (hcg.isCompact.add hcf).isClosed variable [BorelSpace G] [TopologicalSpace P] /-- The convolution `f * g` is continuous if `f` is locally integrable and `g` is continuous and compactly supported. Version where `g` depends on an additional parameter in a subset `s` of a parameter space `P` (and the compact support `k` is independent of the parameter in `s`). -/ theorem continuousOn_convolution_right_with_param {g : P → G → E'} {s : Set P} {k : Set G} (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ) (hg : ContinuousOn (↿g) (s ×ˢ univ)) : ContinuousOn (fun q : P × G => (f ⋆[L, μ] g q.1) q.2) (s ×ˢ univ) := by /- First get rid of the case where the space is not locally compact. Then `g` vanishes everywhere and the conclusion is trivial. -/ by_cases H : ∀ p ∈ s, ∀ x, g p x = 0 · apply (continuousOn_const (c := 0)).congr rintro ⟨p, x⟩ ⟨hp, -⟩ apply integral_eq_zero_of_ae (Eventually.of_forall (fun y ↦ ?_)) simp [H p hp _] have : LocallyCompactSpace G := by push_neg at H rcases H with ⟨p, hp, x, hx⟩ have A : support (g p) ⊆ k := support_subset_iff'.2 (fun y hy ↦ hgs p y hp hy) have B : Continuous (g p) := by refine hg.comp_continuous (.prodMk_right _) fun x => ?_ simpa only [prodMk_mem_set_prod_eq, mem_univ, and_true] using hp rcases eq_zero_or_locallyCompactSpace_of_support_subset_isCompact_of_addGroup hk A B with H|H · simp [H] at hx · exact H /- Since `G` is locally compact, one may thicken `k` a little bit into a larger compact set `(-k) + t`, outside of which all functions that appear in the convolution vanish. Then we can apply a continuity statement for integrals depending on a parameter, with respect to locally integrable functions and compactly supported continuous functions. -/ rintro ⟨q₀, x₀⟩ ⟨hq₀, -⟩ obtain ⟨t, t_comp, ht⟩ : ∃ t, IsCompact t ∧ t ∈ 𝓝 x₀ := exists_compact_mem_nhds x₀ let k' : Set G := (-k) +ᵥ t have k'_comp : IsCompact k' := IsCompact.vadd_set hk.neg t_comp let g' : (P × G) → G → E' := fun p x ↦ g p.1 (p.2 - x) let s' : Set (P × G) := s ×ˢ t have A : ContinuousOn g'.uncurry (s' ×ˢ univ) := by have : g'.uncurry = g.uncurry ∘ (fun w ↦ (w.1.1, w.1.2 - w.2)) := by ext y; rfl rw [this] refine hg.comp (by fun_prop) ?_ simp +contextual [s', MapsTo] have B : ContinuousOn (fun a ↦ ∫ x, L (f x) (g' a x) ∂μ) s' := by apply continuousOn_integral_bilinear_of_locally_integrable_of_compact_support L k'_comp A _ (hf.integrableOn_isCompact k'_comp) rintro ⟨p, x⟩ y ⟨hp, hx⟩ hy apply hgs p _ hp contrapose! hy exact ⟨y - x, by simpa using hy, x, hx, by simp⟩ apply ContinuousWithinAt.mono_of_mem_nhdsWithin (B (q₀, x₀) ⟨hq₀, mem_of_mem_nhds ht⟩) exact mem_nhdsWithin_prod_iff.2 ⟨s, self_mem_nhdsWithin, t, nhdsWithin_le_nhds ht, Subset.rfl⟩ /-- The convolution `f * g` is continuous if `f` is locally integrable and `g` is continuous and compactly supported. Version where `g` depends on an additional parameter in an open subset `s` of a parameter space `P` (and the compact support `k` is independent of the parameter in `s`), given in terms of compositions with an additional continuous map. -/ theorem continuousOn_convolution_right_with_param_comp {s : Set P} {v : P → G} (hv : ContinuousOn v s) {g : P → G → E'} {k : Set G} (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ) (hg : ContinuousOn (↿g) (s ×ˢ univ)) : ContinuousOn (fun x => (f ⋆[L, μ] g x) (v x)) s := by apply (continuousOn_convolution_right_with_param L hk hgs hf hg).comp (continuousOn_id.prodMk hv) intro x hx simp only [hx, prodMk_mem_set_prod_eq, mem_univ, and_self_iff, _root_.id] /-- The convolution is continuous if one function is locally integrable and the other has compact support and is continuous. -/ theorem _root_.HasCompactSupport.continuous_convolution_right (hcg : HasCompactSupport g) (hf : LocallyIntegrable f μ) (hg : Continuous g) : Continuous (f ⋆[L, μ] g) := by rw [continuous_iff_continuousOn_univ] let g' : G → G → E' := fun _ q => g q have : ContinuousOn (↿g') (univ ×ˢ univ) := (hg.comp continuous_snd).continuousOn exact continuousOn_convolution_right_with_param_comp L (continuous_iff_continuousOn_univ.1 continuous_id) hcg (fun p x _ hx => image_eq_zero_of_nmem_tsupport hx) hf this /-- The convolution is continuous if one function is integrable and the other is bounded and continuous. -/ theorem _root_.BddAbove.continuous_convolution_right_of_integrable [FirstCountableTopology G] [SecondCountableTopologyEither G E'] (hbg : BddAbove (range fun x => ‖g x‖)) (hf : Integrable f μ) (hg : Continuous g) : Continuous (f ⋆[L, μ] g) := by refine continuous_iff_continuousAt.mpr fun x₀ => ?_ have : ∀ᶠ x in 𝓝 x₀, ∀ᵐ t : G ∂μ, ‖L (f t) (g (x - t))‖ ≤ ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖ := by filter_upwards with x; filter_upwards with t apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl, le_ciSup hbg (x - t)] refine continuousAt_of_dominated ?_ this ?_ ?_ · exact Eventually.of_forall fun x => hf.aestronglyMeasurable.convolution_integrand_snd' L hg.aestronglyMeasurable · exact (hf.norm.const_mul _).mul_const _ · exact Eventually.of_forall fun t => (L.continuous₂.comp₂ continuous_const <| hg.comp <| continuous_id.sub continuous_const).continuousAt end Group section CommGroup variable [AddCommGroup G] theorem support_convolution_subset : support (f ⋆[L, μ] g) ⊆ support f + support g := (support_convolution_subset_swap L).trans (add_comm _ _).subset variable [IsAddLeftInvariant μ] [IsNegInvariant μ] section Measurable variable [MeasurableNeg G] variable [MeasurableAdd G] /-- Commutativity of convolution -/ theorem convolution_flip : g ⋆[L.flip, μ] f = f ⋆[L, μ] g := by ext1 x simp_rw [convolution_def] rw [← integral_sub_left_eq_self _ μ x] simp_rw [sub_sub_self, flip_apply] /-- The symmetric definition of convolution. -/ theorem convolution_eq_swap : (f ⋆[L, μ] g) x = ∫ t, L (f (x - t)) (g t) ∂μ := by rw [← convolution_flip]; rfl /-- The symmetric definition of convolution where the bilinear operator is scalar multiplication. -/ theorem convolution_lsmul_swap {f : G → 𝕜} {g : G → F} : (f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f (x - t) • g t ∂μ := convolution_eq_swap _ /-- The symmetric definition of convolution where the bilinear operator is multiplication. -/ theorem convolution_mul_swap [NormedSpace ℝ 𝕜] {f : G → 𝕜} {g : G → 𝕜} : (f ⋆[mul 𝕜 𝕜, μ] g) x = ∫ t, f (x - t) * g t ∂μ := convolution_eq_swap _ /-- The convolution of two even functions is also even. -/ theorem convolution_neg_of_neg_eq (h1 : ∀ᵐ x ∂μ, f (-x) = f x) (h2 : ∀ᵐ x ∂μ, g (-x) = g x) : (f ⋆[L, μ] g) (-x) = (f ⋆[L, μ] g) x := calc ∫ t : G, (L (f t)) (g (-x - t)) ∂μ = ∫ t : G, (L (f (-t))) (g (x + t)) ∂μ := by apply integral_congr_ae filter_upwards [h1, (eventually_add_left_iff μ x).2 h2] with t ht h't simp_rw [ht, ← h't, neg_add'] _ = ∫ t : G, (L (f t)) (g (x - t)) ∂μ := by rw [← integral_neg_eq_self] simp only [neg_neg, ← sub_eq_add_neg] end Measurable variable [TopologicalSpace G] variable [IsTopologicalAddGroup G] variable [BorelSpace G] theorem _root_.HasCompactSupport.continuous_convolution_left (hcf : HasCompactSupport f) (hf : Continuous f) (hg : LocallyIntegrable g μ) : Continuous (f ⋆[L, μ] g) := by rw [← convolution_flip] exact hcf.continuous_convolution_right L.flip hg hf theorem _root_.BddAbove.continuous_convolution_left_of_integrable [FirstCountableTopology G] [SecondCountableTopologyEither G E] (hbf : BddAbove (range fun x => ‖f x‖)) (hf : Continuous f) (hg : Integrable g μ) : Continuous (f ⋆[L, μ] g) := by rw [← convolution_flip] exact hbf.continuous_convolution_right_of_integrable L.flip hg hf end CommGroup section NormedAddCommGroup variable [SeminormedAddCommGroup G] /-- Compute `(f ⋆ g) x₀` if the support of the `f` is within `Metric.ball 0 R`, and `g` is constant on `Metric.ball x₀ R`. We can simplify the RHS further if we assume `f` is integrable, but also if `L = (•)` or more generally if `L` has an `AntilipschitzWith`-condition. -/ theorem convolution_eq_right' {x₀ : G} {R : ℝ} (hf : support f ⊆ ball (0 : G) R) (hg : ∀ x ∈ ball x₀ R, g x = g x₀) : (f ⋆[L, μ] g) x₀ = ∫ t, L (f t) (g x₀) ∂μ := by have h2 : ∀ t, L (f t) (g (x₀ - t)) = L (f t) (g x₀) := fun t ↦ by by_cases ht : t ∈ support f · have h2t := hf ht rw [mem_ball_zero_iff] at h2t specialize hg (x₀ - t) rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg rw [hg h2t] · rw [nmem_support] at ht simp_rw [ht, L.map_zero₂] simp_rw [convolution_def, h2] variable [BorelSpace G] [SecondCountableTopology G] variable [IsAddLeftInvariant μ] [SFinite μ] /-- Approximate `(f ⋆ g) x₀` if the support of the `f` is bounded within a ball, and `g` is near `g x₀` on a ball with the same radius around `x₀`. See `dist_convolution_le` for a special case. We can simplify the second argument of `dist` further if we add some extra type-classes on `E` and `𝕜` or if `L` is scalar multiplication. -/ theorem dist_convolution_le' {x₀ : G} {R ε : ℝ} {z₀ : E'} (hε : 0 ≤ ε) (hif : Integrable f μ) (hf : support f ⊆ ball (0 : G) R) (hmg : AEStronglyMeasurable g μ) (hg : ∀ x ∈ ball x₀ R, dist (g x) z₀ ≤ ε) : dist ((f ⋆[L, μ] g : G → F) x₀) (∫ t, L (f t) z₀ ∂μ) ≤ (‖L‖ * ∫ x, ‖f x‖ ∂μ) * ε := by have hfg : ConvolutionExistsAt f g x₀ L μ := by refine BddAbove.convolutionExistsAt L ?_ Metric.isOpen_ball.measurableSet (Subset.trans ?_ hf) hif.integrableOn hmg swap; · refine fun t => mt fun ht : f t = 0 => ?_; simp_rw [ht, L.map_zero₂] rw [bddAbove_def] refine ⟨‖z₀‖ + ε, ?_⟩ rintro _ ⟨x, hx, rfl⟩ refine norm_le_norm_add_const_of_dist_le (hg x ?_) rwa [mem_ball_iff_norm, norm_sub_rev, ← mem_ball_zero_iff] have h2 : ∀ t, dist (L (f t) (g (x₀ - t))) (L (f t) z₀) ≤ ‖L (f t)‖ * ε := by intro t; by_cases ht : t ∈ support f · have h2t := hf ht rw [mem_ball_zero_iff] at h2t specialize hg (x₀ - t) rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg refine ((L (f t)).dist_le_opNorm _ _).trans ?_ exact mul_le_mul_of_nonneg_left (hg h2t) (norm_nonneg _) · rw [nmem_support] at ht simp_rw [ht, L.map_zero₂, L.map_zero, norm_zero, zero_mul, dist_self] rfl simp_rw [convolution_def] simp_rw [dist_eq_norm] at h2 ⊢ rw [← integral_sub hfg.integrable]; swap; · exact (L.flip z₀).integrable_comp hif refine (norm_integral_le_of_norm_le ((L.integrable_comp hif).norm.mul_const ε) (Eventually.of_forall h2)).trans ?_ rw [integral_mul_const] refine mul_le_mul_of_nonneg_right ?_ hε have h3 : ∀ t, ‖L (f t)‖ ≤ ‖L‖ * ‖f t‖ := by intro t exact L.le_opNorm (f t) refine (integral_mono (L.integrable_comp hif).norm (hif.norm.const_mul _) h3).trans_eq ?_ rw [integral_const_mul] variable [NormedSpace ℝ E] [NormedSpace ℝ E'] [CompleteSpace E'] /-- Approximate `f ⋆ g` if the support of the `f` is bounded within a ball, and `g` is near `g x₀` on a ball with the same radius around `x₀`. This is a special case of `dist_convolution_le'` where `L` is `(•)`, `f` has integral 1 and `f` is nonnegative. -/ theorem dist_convolution_le {f : G → ℝ} {x₀ : G} {R ε : ℝ} {z₀ : E'} (hε : 0 ≤ ε) (hf : support f ⊆ ball (0 : G) R) (hnf : ∀ x, 0 ≤ f x) (hintf : ∫ x, f x ∂μ = 1) (hmg : AEStronglyMeasurable g μ) (hg : ∀ x ∈ ball x₀ R, dist (g x) z₀ ≤ ε) : dist ((f ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) z₀ ≤ ε := by have hif : Integrable f μ := integrable_of_integral_eq_one hintf convert (dist_convolution_le' (lsmul ℝ ℝ) hε hif hf hmg hg).trans _ · simp_rw [lsmul_apply, integral_smul_const, hintf, one_smul] · simp_rw [Real.norm_of_nonneg (hnf _), hintf, mul_one] exact (mul_le_mul_of_nonneg_right opNorm_lsmul_le hε).trans_eq (one_mul ε) /-- `(φ i ⋆ g i) (k i)` tends to `z₀` as `i` tends to some filter `l` if * `φ` is a sequence of nonnegative functions with integral `1` as `i` tends to `l`; * The support of `φ` tends to small neighborhoods around `(0 : G)` as `i` tends to `l`; * `g i` is `mu`-a.e. strongly measurable as `i` tends to `l`; * `g i x` tends to `z₀` as `(i, x)` tends to `l ×ˢ 𝓝 x₀`; * `k i` tends to `x₀`. See also `ContDiffBump.convolution_tendsto_right`. -/ theorem convolution_tendsto_right {ι} {g : ι → G → E'} {l : Filter ι} {x₀ : G} {z₀ : E'} {φ : ι → G → ℝ} {k : ι → G} (hnφ : ∀ᶠ i in l, ∀ x, 0 ≤ φ i x) (hiφ : ∀ᶠ i in l, ∫ x, φ i x ∂μ = 1) -- todo: we could weaken this to "the integral tends to 1" (hφ : Tendsto (fun n => support (φ n)) l (𝓝 0).smallSets) (hmg : ∀ᶠ i in l, AEStronglyMeasurable (g i) μ) (hcg : Tendsto (uncurry g) (l ×ˢ 𝓝 x₀) (𝓝 z₀)) (hk : Tendsto k l (𝓝 x₀)) : Tendsto (fun i : ι => (φ i ⋆[lsmul ℝ ℝ, μ] g i : G → E') (k i)) l (𝓝 z₀) := by simp_rw [tendsto_smallSets_iff] at hφ rw [Metric.tendsto_nhds] at hcg ⊢ simp_rw [Metric.eventually_prod_nhds_iff] at hcg intro ε hε have h2ε : 0 < ε / 3 := div_pos hε (by norm_num) obtain ⟨p, hp, δ, hδ, hgδ⟩ := hcg _ h2ε dsimp only [uncurry] at hgδ have h2k := hk.eventually (ball_mem_nhds x₀ <| half_pos hδ) have h2φ := hφ (ball (0 : G) _) <| ball_mem_nhds _ (half_pos hδ) filter_upwards [hp, h2k, h2φ, hnφ, hiφ, hmg] with i hpi hki hφi hnφi hiφi hmgi have hgi : dist (g i (k i)) z₀ < ε / 3 := hgδ hpi (hki.trans <| half_lt_self hδ) have h1 : ∀ x' ∈ ball (k i) (δ / 2), dist (g i x') (g i (k i)) ≤ ε / 3 + ε / 3 := by intro x' hx' refine (dist_triangle_right _ _ _).trans (add_le_add (hgδ hpi ?_).le hgi.le) exact ((dist_triangle _ _ _).trans_lt (add_lt_add hx'.out hki)).trans_eq (add_halves δ) have := dist_convolution_le (add_pos h2ε h2ε).le hφi hnφi hiφi hmgi h1 refine ((dist_triangle _ _ _).trans_lt (add_lt_add_of_le_of_lt this hgi)).trans_eq ?_ field_simp; ring_nf end NormedAddCommGroup end Measurability end NontriviallyNormedField open scoped Convolution section RCLike variable [RCLike 𝕜] variable [NormedSpace 𝕜 E] variable [NormedSpace 𝕜 E'] variable [NormedSpace 𝕜 E''] variable [NormedSpace ℝ F] [NormedSpace 𝕜 F] variable {n : ℕ∞} variable [MeasurableSpace G] {μ ν : Measure G} variable (L : E →L[𝕜] E' →L[𝕜] F) section Assoc variable [CompleteSpace F] variable [NormedAddCommGroup F'] [NormedSpace ℝ F'] [NormedSpace 𝕜 F'] [CompleteSpace F'] variable [NormedAddCommGroup F''] [NormedSpace ℝ F''] [NormedSpace 𝕜 F''] [CompleteSpace F''] variable {k : G → E''} variable (L₂ : F →L[𝕜] E'' →L[𝕜] F') variable (L₃ : E →L[𝕜] F'' →L[𝕜] F') variable (L₄ : E' →L[𝕜] E'' →L[𝕜] F'') variable [AddGroup G] variable [SFinite μ] [SFinite ν] [IsAddRightInvariant μ] theorem integral_convolution [MeasurableAdd₂ G] [MeasurableNeg G] [NormedSpace ℝ E] [NormedSpace ℝ E'] [CompleteSpace E] [CompleteSpace E'] (hf : Integrable f ν) (hg : Integrable g μ) : ∫ x, (f ⋆[L, ν] g) x ∂μ = L (∫ x, f x ∂ν) (∫ x, g x ∂μ) := by refine (integral_integral_swap (by apply hf.convolution_integrand L hg)).trans ?_ simp_rw [integral_comp_comm _ (hg.comp_sub_right _), integral_sub_right_eq_self] exact (L.flip (∫ x, g x ∂μ)).integral_comp_comm hf variable [MeasurableAdd₂ G] [IsAddRightInvariant ν] [MeasurableNeg G] /-- Convolution is associative. This has a weak but inconvenient integrability condition. See also `MeasureTheory.convolution_assoc`. -/ theorem convolution_assoc' (hL : ∀ (x : E) (y : E') (z : E''), L₂ (L x y) z = L₃ x (L₄ y z)) {x₀ : G} (hfg : ∀ᵐ y ∂μ, ConvolutionExistsAt f g y L ν) (hgk : ∀ᵐ x ∂ν, ConvolutionExistsAt g k x L₄ μ) (hi : Integrable (uncurry fun x y => (L₃ (f y)) ((L₄ (g (x - y))) (k (x₀ - x)))) (μ.prod ν)) : ((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ := calc ((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = ∫ t, L₂ (∫ s, L (f s) (g (t - s)) ∂ν) (k (x₀ - t)) ∂μ := rfl _ = ∫ t, ∫ s, L₂ (L (f s) (g (t - s))) (k (x₀ - t)) ∂ν ∂μ := (integral_congr_ae (hfg.mono fun t ht => ((L₂.flip (k (x₀ - t))).integral_comp_comm ht).symm)) _ = ∫ t, ∫ s, L₃ (f s) (L₄ (g (t - s)) (k (x₀ - t))) ∂ν ∂μ := by simp_rw [hL] _ = ∫ s, ∫ t, L₃ (f s) (L₄ (g (t - s)) (k (x₀ - t))) ∂μ ∂ν := by rw [integral_integral_swap hi] _ = ∫ s, ∫ u, L₃ (f s) (L₄ (g u) (k (x₀ - s - u))) ∂μ ∂ν := by congr; ext t rw [eq_comm, ← integral_sub_right_eq_self _ t] simp_rw [sub_sub_sub_cancel_right] _ = ∫ s, L₃ (f s) (∫ u, L₄ (g u) (k (x₀ - s - u)) ∂μ) ∂ν := by refine integral_congr_ae ?_ refine ((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht => ?_ exact (L₃ (f t)).integral_comp_comm ht _ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ := rfl /-- Convolution is associative. This requires that * all maps are a.e. strongly measurable w.r.t one of the measures * `f ⋆[L, ν] g` exists almost everywhere * `‖g‖ ⋆[μ] ‖k‖` exists almost everywhere * `‖f‖ ⋆[ν] (‖g‖ ⋆[μ] ‖k‖)` exists at `x₀` -/ theorem convolution_assoc (hL : ∀ (x : E) (y : E') (z : E''), L₂ (L x y) z = L₃ x (L₄ y z)) {x₀ : G} (hf : AEStronglyMeasurable f ν) (hg : AEStronglyMeasurable g μ) (hk : AEStronglyMeasurable k μ) (hfg : ∀ᵐ y ∂μ, ConvolutionExistsAt f g y L ν) (hgk : ∀ᵐ x ∂ν, ConvolutionExistsAt (fun x => ‖g x‖) (fun x => ‖k x‖) x (mul ℝ ℝ) μ) (hfgk : ConvolutionExistsAt (fun x => ‖f x‖) ((fun x => ‖g x‖) ⋆[mul ℝ ℝ, μ] fun x => ‖k x‖) x₀ (mul ℝ ℝ) ν) : ((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ := by refine convolution_assoc' L L₂ L₃ L₄ hL hfg (hgk.mono fun x hx => hx.of_norm L₄ hg hk) ?_ -- the following is similar to `Integrable.convolution_integrand` have h_meas : AEStronglyMeasurable (uncurry fun x y => L₃ (f y) (L₄ (g x) (k (x₀ - y - x)))) (μ.prod ν) := by refine L₃.aestronglyMeasurable_comp₂ hf.snd ?_ refine L₄.aestronglyMeasurable_comp₂ hg.fst ?_ refine (hk.mono_ac ?_).comp_measurable ((measurable_const.sub measurable_snd).sub measurable_fst) refine QuasiMeasurePreserving.absolutelyContinuous ?_ refine QuasiMeasurePreserving.prod_of_left ((measurable_const.sub measurable_snd).sub measurable_fst) (Eventually.of_forall fun y => ?_) dsimp only exact quasiMeasurePreserving_sub_left_of_right_invariant μ _ have h2_meas : AEStronglyMeasurable (fun y => ∫ x, ‖L₃ (f y) (L₄ (g x) (k (x₀ - y - x)))‖ ∂μ) ν := h_meas.prod_swap.norm.integral_prod_right' have h3 : map (fun z : G × G => (z.1 - z.2, z.2)) (μ.prod ν) = μ.prod ν := (measurePreserving_sub_prod μ ν).map_eq suffices Integrable (uncurry fun x y => L₃ (f y) (L₄ (g x) (k (x₀ - y - x)))) (μ.prod ν) by rw [← h3] at this convert this.comp_measurable (measurable_sub.prodMk measurable_snd) ext ⟨x, y⟩ simp +unfoldPartialApp only [uncurry, Function.comp_apply, sub_sub_sub_cancel_right] simp_rw [integrable_prod_iff' h_meas] refine ⟨((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht => (L₃ (f t)).integrable_comp <| ht.of_norm L₄ hg hk, ?_⟩ refine (hfgk.const_mul (‖L₃‖ * ‖L₄‖)).mono' h2_meas (((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht => ?_) simp_rw [convolution_def, mul_apply', mul_mul_mul_comm ‖L₃‖ ‖L₄‖, ← integral_const_mul] rw [Real.norm_of_nonneg (by positivity)] refine integral_mono_of_nonneg (Eventually.of_forall fun t => norm_nonneg _) ((ht.const_mul _).const_mul _) (Eventually.of_forall fun s => ?_) simp only [← mul_assoc ‖L₄‖] apply_rules [ContinuousLinearMap.le_of_opNorm₂_le_of_le, le_rfl] end Assoc variable [NormedAddCommGroup G] [BorelSpace G] theorem convolution_precompR_apply {g : G → E'' →L[𝕜] E'} (hf : LocallyIntegrable f μ) (hcg : HasCompactSupport g) (hg : Continuous g) (x₀ : G) (x : E'') : (f ⋆[L.precompR E'', μ] g) x₀ x = (f ⋆[L, μ] fun a => g a x) x₀ := by have := hcg.convolutionExists_right (L.precompR E'' :) hf hg x₀ simp_rw [convolution_def, ContinuousLinearMap.integral_apply this] rfl variable [NormedSpace 𝕜 G] [SFinite μ] [IsAddLeftInvariant μ] /-- Compute the total derivative of `f ⋆ g` if `g` is `C^1` with compact support and `f` is locally integrable. To write down the total derivative as a convolution, we use `ContinuousLinearMap.precompR`. -/
theorem _root_.HasCompactSupport.hasFDerivAt_convolution_right (hcg : HasCompactSupport g) (hf : LocallyIntegrable f μ) (hg : ContDiff 𝕜 1 g) (x₀ : G) : HasFDerivAt (f ⋆[L, μ] g) ((f ⋆[L.precompR G, μ] fderiv 𝕜 g) x₀) x₀ := by rcases hcg.eq_zero_or_finiteDimensional 𝕜 hg.continuous with (rfl | fin_dim) · have : fderiv 𝕜 (0 : G → E') = 0 := fderiv_const (0 : E') simp only [this, convolution_zero, Pi.zero_apply] exact hasFDerivAt_const (0 : F) x₀ have : ProperSpace G := FiniteDimensional.proper_rclike 𝕜 G set L' := L.precompR G have h1 : ∀ᶠ x in 𝓝 x₀, AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ := Eventually.of_forall (hf.aestronglyMeasurable.convolution_integrand_snd L hg.continuous.aestronglyMeasurable) have h2 : ∀ x, AEStronglyMeasurable (fun t => L' (f t) (fderiv 𝕜 g (x - t))) μ := hf.aestronglyMeasurable.convolution_integrand_snd L' (hg.continuous_fderiv le_rfl).aestronglyMeasurable have h3 : ∀ x t, HasFDerivAt (fun x => g (x - t)) (fderiv 𝕜 g (x - t)) x := fun x t ↦ by simpa using (hg.differentiable le_rfl).differentiableAt.hasFDerivAt.comp x ((hasFDerivAt_id x).sub (hasFDerivAt_const t x)) let K' := -tsupport (fderiv 𝕜 g) + closedBall x₀ 1 have hK' : IsCompact K' := (hcg.fderiv 𝕜).neg.add (isCompact_closedBall x₀ 1) apply hasFDerivAt_integral_of_dominated_of_fderiv_le zero_lt_one h1 _ (h2 x₀) · filter_upwards with t x hx using (hcg.fderiv 𝕜).convolution_integrand_bound_right L' (hg.continuous_fderiv le_rfl) (ball_subset_closedBall hx) · rw [integrable_indicator_iff hK'.measurableSet] exact ((hf.integrableOn_isCompact hK').norm.const_mul _).mul_const _ · exact Eventually.of_forall fun t x _ => (L _).hasFDerivAt.comp x (h3 x t) · exact hcg.convolutionExists_right L hf hg.continuous x₀ theorem _root_.HasCompactSupport.hasFDerivAt_convolution_left [IsNegInvariant μ] (hcf : HasCompactSupport f) (hf : ContDiff 𝕜 1 f) (hg : LocallyIntegrable g μ) (x₀ : G) : HasFDerivAt (f ⋆[L, μ] g) ((fderiv 𝕜 f ⋆[L.precompL G, μ] g) x₀) x₀ := by simp +singlePass only [← convolution_flip] exact hcf.hasFDerivAt_convolution_right L.flip hg hf x₀ end RCLike section Real /-! The one-variable case -/ variable [RCLike 𝕜] variable [NormedSpace 𝕜 E]
Mathlib/Analysis/Convolution.lean
956
999
/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Normed.Group.InfiniteSum import Mathlib.Topology.Instances.ENNReal.Lemmas /-! # Continuity of series of functions We show that series of functions are continuous when each individual function in the series is and additionally suitable uniform summable bounds are satisfied, in `continuous_tsum`. For smoothness of series of functions, see the file `Analysis.Calculus.SmoothSeries`. -/ open Set Metric TopologicalSpace Function Filter open scoped Topology NNReal variable {α β F : Type*} [NormedAddCommGroup F] [CompleteSpace F] {u : α → ℝ} /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version relative to a set, with general index set. -/ theorem tendstoUniformlyOn_tsum {f : α → β → F} (hu : Summable u) {s : Set β} (hfu : ∀ n x, x ∈ s → ‖f n x‖ ≤ u n) : TendstoUniformlyOn (fun t : Finset α => fun x => ∑ n ∈ t, f n x) (fun x => ∑' n, f n x) atTop s := by refine tendstoUniformlyOn_iff.2 fun ε εpos => ?_ filter_upwards [(tendsto_order.1 (tendsto_tsum_compl_atTop_zero u)).2 _ εpos] with t ht x hx have A : Summable fun n => ‖f n x‖ := .of_nonneg_of_le (fun _ ↦ norm_nonneg _) (fun n => hfu n x hx) hu rw [dist_eq_norm, ← A.of_norm.sum_add_tsum_subtype_compl t, add_sub_cancel_left] apply lt_of_le_of_lt _ ht apply (norm_tsum_le_tsum_norm (A.subtype _)).trans exact (A.subtype _).tsum_le_tsum (fun n => hfu _ _ hx) (hu.subtype _) /-- An infinite sum of functions with summable sup norm is the uniform limit of its partial sums. Version relative to a set, with index set `ℕ`. -/ theorem tendstoUniformlyOn_tsum_nat {f : ℕ → β → F} {u : ℕ → ℝ} (hu : Summable u) {s : Set β} (hfu : ∀ n x, x ∈ s → ‖f n x‖ ≤ u n) : TendstoUniformlyOn (fun N => fun x => ∑ n ∈ Finset.range N, f n x) (fun x => ∑' n, f n x) atTop s := fun v hv => tendsto_finset_range.eventually (tendstoUniformlyOn_tsum hu hfu v hv) /-- An infinite sum of functions with eventually summable sup norm is the uniform limit of its partial sums. Version relative to a set, with general index set. -/ theorem tendstoUniformlyOn_tsum_of_cofinite_eventually {ι : Type*} {f : ι → β → F} {u : ι → ℝ} (hu : Summable u) {s : Set β} (hfu : ∀ᶠ n in cofinite, ∀ x ∈ s, ‖f n x‖ ≤ u n) : TendstoUniformlyOn (fun t x => ∑ n ∈ t, f n x) (fun x => ∑' n, f n x) atTop s := by classical refine tendstoUniformlyOn_iff.2 fun ε εpos => ?_ have := (tendsto_order.1 (tendsto_tsum_compl_atTop_zero u)).2 _ εpos simp only [not_forall, Classical.not_imp, not_le, gt_iff_lt, eventually_atTop, ge_iff_le, Finset.le_eq_subset] at * obtain ⟨t, ht⟩ := this rw [eventually_iff_exists_mem] at hfu obtain ⟨N, hN, HN⟩ := hfu refine ⟨hN.toFinset ∪ t, fun n hn x hx => ?_⟩ have A : Summable fun n => ‖f n x‖ := by apply Summable.add_compl (s := hN.toFinset) Summable.of_finite apply Summable.of_nonneg_of_le (fun _ ↦ norm_nonneg _) _ (hu.subtype _) simp only [comp_apply, Subtype.forall, Set.mem_compl_iff, Finset.mem_coe] aesop rw [dist_eq_norm, ← A.of_norm.sum_add_tsum_subtype_compl n, add_sub_cancel_left] apply lt_of_le_of_lt _ (ht n (Finset.union_subset_right hn)) apply (norm_tsum_le_tsum_norm (A.subtype _)).trans apply (A.subtype _).tsum_le_tsum _ (hu.subtype _)
simp only [comp_apply, Subtype.forall, imp_false] apply fun i hi => HN i ?_ x hx have : ¬ i ∈ hN.toFinset := fun hg ↦ hi (Finset.union_subset_left hn hg) aesop theorem tendstoUniformlyOn_tsum_nat_eventually {α F : Type*} [NormedAddCommGroup F] [CompleteSpace F] {f : ℕ → α → F} {u : ℕ → ℝ} (hu : Summable u) {s : Set α}
Mathlib/Analysis/NormedSpace/FunctionSeries.lean
70
76
/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Yaël Dillies -/ import Mathlib.Order.Cover import Mathlib.Order.Interval.Finset.Defs /-! # Intervals as finsets This file provides basic results about all the `Finset.Ixx`, which are defined in `Order.Interval.Finset.Defs`. In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of, respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly functions whose domain is a locally finite order. In particular, this file proves: * `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿` * `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖` * `monotone_iff_forall_wcovBy`: Characterization of monotone functions * `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions ## TODO This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general, what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure. Complete the API. See https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235 for some ideas. -/ assert_not_exists MonoidWithZero Finset.sum open Function OrderDual open FinsetInterval variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α} namespace Finset section Preorder variable [Preorder α] section LocallyFiniteOrder variable [LocallyFiniteOrder α] @[simp] theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc @[simp] theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico @[simp] theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc -- TODO: This is nonsense. A locally finite order is never densely ordered @[simp] theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo] @[simp] theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff] @[simp] theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff] @[simp] theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff] -- TODO: This is nonsense. A locally finite order is never densely ordered @[simp] theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff] alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff @[simp] theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ := eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2) @[simp] theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ := Icc_eq_empty h.not_le @[simp] theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ := Ico_eq_empty h.not_lt @[simp] theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ := Ioc_eq_empty h.not_lt @[simp] theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ := Ioo_eq_empty h.not_lt theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl] theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl] theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl] theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl] theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1 theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1 theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2 theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2 @[gcongr] theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by simpa [← coe_subset] using Set.Icc_subset_Icc ha hb @[gcongr] theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by simpa [← coe_subset] using Set.Ico_subset_Ico ha hb @[gcongr] theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb @[gcongr] theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb @[gcongr] theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b := Icc_subset_Icc h le_rfl @[gcongr] theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b := Ico_subset_Ico h le_rfl @[gcongr] theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b := Ioc_subset_Ioc h le_rfl @[gcongr] theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b := Ioo_subset_Ioo h le_rfl @[gcongr] theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ := Icc_subset_Icc le_rfl h @[gcongr] theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ := Ico_subset_Ico le_rfl h @[gcongr] theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ := Ioc_subset_Ioc le_rfl h @[gcongr] theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ := Ioo_subset_Ioo le_rfl h theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by rw [← coe_subset, coe_Ico, coe_Ioo] exact Set.Ico_subset_Ioo_left h theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by rw [← coe_subset, coe_Ioc, coe_Ioo] exact Set.Ioc_subset_Ioo_right h theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by rw [← coe_subset, coe_Icc, coe_Ico] exact Set.Icc_subset_Ico_right h theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by rw [← coe_subset, coe_Ioo, coe_Ico] exact Set.Ioo_subset_Ico_self theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by rw [← coe_subset, coe_Ioo, coe_Ioc] exact Set.Ioo_subset_Ioc_self theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by rw [← coe_subset, coe_Ico, coe_Icc] exact Set.Ico_subset_Icc_self theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by rw [← coe_subset, coe_Ioc, coe_Icc] exact Set.Ioc_subset_Icc_self theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b := Ioo_subset_Ico_self.trans Ico_subset_Icc_self theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁] theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁] theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁] theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ := (Icc_subset_Ico_iff h₁.dual).trans and_comm --TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff` theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ := by rw [← coe_ssubset, coe_Icc, coe_Icc] exact Set.Icc_ssubset_Icc_left hI ha hb theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ := by rw [← coe_ssubset, coe_Icc, coe_Icc] exact Set.Icc_ssubset_Icc_right hI ha hb @[simp] theorem Ioc_disjoint_Ioc_of_le {d : α} (hbc : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) := disjoint_left.2 fun _ h1 h2 ↦ not_and_of_not_left _ ((mem_Ioc.1 h1).2.trans hbc).not_lt (mem_Ioc.1 h2) variable (a) theorem Ico_self : Ico a a = ∅ := Ico_eq_empty <| lt_irrefl _ theorem Ioc_self : Ioc a a = ∅ := Ioc_eq_empty <| lt_irrefl _ theorem Ioo_self : Ioo a a = ∅ := Ioo_eq_empty <| lt_irrefl _ variable {a} /-- A set with upper and lower bounds in a locally finite order is a fintype -/ def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s) (hb : b ∈ upperBounds s) : Fintype s := Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩ section Filter theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) : {x ∈ Ico a b | x < c} = ∅ := filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) : {x ∈ Ico a b | x < c} = Ico a b := filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) : {x ∈ Ico a b | x < c} = Ico a c := by ext x rw [mem_filter, mem_Ico, mem_Ico, and_right_comm] exact and_iff_left_of_imp fun h => h.2.trans_le hcb theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) : {x ∈ Ico a b | c ≤ x} = Ico a b := filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1 theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] : {x ∈ Ico a b | b ≤ x} = ∅ := filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) : {x ∈ Ico a b | c ≤ x} = Ico c b := by ext x rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm] exact and_iff_right_of_imp fun h => hac.trans h.1 theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) : {x ∈ Icc a b | x < c} = Icc a b := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) : {x ∈ Ioc a b | x < c} = Ioc a b := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α} [DecidablePred (· < c)] (h : a < c) : {x ∈ Iic a | x < c} = Iic a := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h variable (a b) [Fintype α] theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] : ({j | a < j ∧ j < b} : Finset _) = Ioo a b := by ext; simp theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] : ({j | a < j ∧ j ≤ b} : Finset _) = Ioc a b := by ext; simp theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] : ({j | a ≤ j ∧ j < b} : Finset _) = Ico a b := by ext; simp theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] : ({j | a ≤ j ∧ j ≤ b} : Finset _) = Icc a b := by ext; simp end Filter end LocallyFiniteOrder section LocallyFiniteOrderTop variable [LocallyFiniteOrderTop α] @[simp] theorem Ioi_eq_empty : Ioi a = ∅ ↔ IsMax a := by rw [← coe_eq_empty, coe_Ioi, Set.Ioi_eq_empty_iff] @[simp] alias ⟨_, _root_.IsMax.finsetIoi_eq⟩ := Ioi_eq_empty @[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty] theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ∅ := Ioi_eq_empty.mpr isMax_top @[simp] theorem Ici_bot [OrderBot α] [Fintype α] : Ici (⊥ : α) = univ := by ext a; simp only [mem_Ici, bot_le, mem_univ] @[simp, aesop safe apply (rule_sets := [finsetNonempty])] lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩ lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ioi_of_not_isMax⟩ := nonempty_Ioi @[simp] theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a := by simp [← coe_subset] @[gcongr] alias ⟨_, _root_.GCongr.Finset.Ici_subset_Ici⟩ := Ici_subset_Ici @[simp] theorem Ici_ssubset_Ici : Ici a ⊂ Ici b ↔ b < a := by simp [← coe_ssubset] @[gcongr] alias ⟨_, _root_.GCongr.Finset.Ici_ssubset_Ici⟩ := Ici_ssubset_Ici @[gcongr] theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := by simpa [← coe_subset] using Set.Ioi_subset_Ioi h @[gcongr] theorem Ioi_ssubset_Ioi (h : a < b) : Ioi b ⊂ Ioi a := by simpa [← coe_ssubset] using Set.Ioi_ssubset_Ioi h variable [LocallyFiniteOrder α] theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := by simpa [← coe_subset] using Set.Icc_subset_Ici_self theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := by simpa [← coe_subset] using Set.Ico_subset_Ici_self theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := by simpa [← coe_subset] using Set.Ioc_subset_Ioi_self theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := by simpa [← coe_subset] using Set.Ioo_subset_Ioi_self theorem Ioc_subset_Ici_self : Ioc a b ⊆ Ici a := Ioc_subset_Icc_self.trans Icc_subset_Ici_self theorem Ioo_subset_Ici_self : Ioo a b ⊆ Ici a := Ioo_subset_Ico_self.trans Ico_subset_Ici_self end LocallyFiniteOrderTop section LocallyFiniteOrderBot variable [LocallyFiniteOrderBot α] @[simp] theorem Iio_eq_empty : Iio a = ∅ ↔ IsMin a := Ioi_eq_empty (α := αᵒᵈ) @[simp] alias ⟨_, _root_.IsMin.finsetIio_eq⟩ := Iio_eq_empty @[simp] lemma Iio_nonempty : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [nonempty_iff_ne_empty] theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ∅ := Iio_eq_empty.mpr isMin_bot @[simp] theorem Iic_top [OrderTop α] [Fintype α] : Iic (⊤ : α) = univ := by ext a; simp only [mem_Iic, le_top, mem_univ] @[simp, aesop safe apply (rule_sets := [finsetNonempty])] lemma nonempty_Iic : (Iic a).Nonempty := ⟨a, mem_Iic.2 le_rfl⟩ lemma nonempty_Iio : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [Finset.Nonempty] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Iio_of_not_isMin⟩ := nonempty_Iio @[simp] theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b := by simp [← coe_subset] @[gcongr] alias ⟨_, _root_.GCongr.Finset.Iic_subset_Iic⟩ := Iic_subset_Iic @[simp] theorem Iic_ssubset_Iic : Iic a ⊂ Iic b ↔ a < b := by simp [← coe_ssubset] @[gcongr] alias ⟨_, _root_.GCongr.Finset.Iic_ssubset_Iic⟩ := Iic_ssubset_Iic @[gcongr] theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := by simpa [← coe_subset] using Set.Iio_subset_Iio h @[gcongr] theorem Iio_ssubset_Iio (h : a < b) : Iio a ⊂ Iio b := by simpa [← coe_ssubset] using Set.Iio_ssubset_Iio h variable [LocallyFiniteOrder α] theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := by simpa [← coe_subset] using Set.Icc_subset_Iic_self theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := by simpa [← coe_subset] using Set.Ioc_subset_Iic_self theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := by simpa [← coe_subset] using Set.Ico_subset_Iio_self theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := by simpa [← coe_subset] using Set.Ioo_subset_Iio_self theorem Ico_subset_Iic_self : Ico a b ⊆ Iic b := Ico_subset_Icc_self.trans Icc_subset_Iic_self theorem Ioo_subset_Iic_self : Ioo a b ⊆ Iic b := Ioo_subset_Ioc_self.trans Ioc_subset_Iic_self theorem Iic_disjoint_Ioc (h : a ≤ b) : Disjoint (Iic a) (Ioc b c) := disjoint_left.2 fun _ hax hbcx ↦ (mem_Iic.1 hax).not_lt <| lt_of_le_of_lt h (mem_Ioc.1 hbcx).1 /-- An equivalence between `Finset.Iic a` and `Set.Iic a`. -/ def _root_.Equiv.IicFinsetSet (a : α) : Iic a ≃ Set.Iic a where toFun b := ⟨b.1, coe_Iic a ▸ mem_coe.2 b.2⟩ invFun b := ⟨b.1, by rw [← mem_coe, coe_Iic a]; exact b.2⟩ left_inv := fun _ ↦ rfl right_inv := fun _ ↦ rfl end LocallyFiniteOrderBot section LocallyFiniteOrderTop variable [LocallyFiniteOrderTop α] {a : α} theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := by simpa [← coe_subset] using Set.Ioi_subset_Ici_self theorem _root_.BddBelow.finite {s : Set α} (hs : BddBelow s) : s.Finite := let ⟨a, ha⟩ := hs (Ici a).finite_toSet.subset fun _ hx => mem_Ici.2 <| ha hx theorem _root_.Set.Infinite.not_bddBelow {s : Set α} : s.Infinite → ¬BddBelow s := mt BddBelow.finite variable [Fintype α] theorem filter_lt_eq_Ioi [DecidablePred (a < ·)] : ({x | a < x} : Finset _) = Ioi a := by ext; simp theorem filter_le_eq_Ici [DecidablePred (a ≤ ·)] : ({x | a ≤ x} : Finset _) = Ici a := by ext; simp end LocallyFiniteOrderTop section LocallyFiniteOrderBot variable [LocallyFiniteOrderBot α] {a : α} theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := by simpa [← coe_subset] using Set.Iio_subset_Iic_self theorem _root_.BddAbove.finite {s : Set α} (hs : BddAbove s) : s.Finite := hs.dual.finite theorem _root_.Set.Infinite.not_bddAbove {s : Set α} : s.Infinite → ¬BddAbove s := mt BddAbove.finite variable [Fintype α] theorem filter_gt_eq_Iio [DecidablePred (· < a)] : ({x | x < a} : Finset _) = Iio a := by ext; simp theorem filter_ge_eq_Iic [DecidablePred (· ≤ a)] : ({x | x ≤ a} : Finset _) = Iic a := by ext; simp end LocallyFiniteOrderBot section LocallyFiniteOrder variable [LocallyFiniteOrder α] @[simp] theorem Icc_bot [OrderBot α] : Icc (⊥ : α) a = Iic a := rfl @[simp] theorem Icc_top [OrderTop α] : Icc a (⊤ : α) = Ici a := rfl @[simp] theorem Ico_bot [OrderBot α] : Ico (⊥ : α) a = Iio a := rfl @[simp] theorem Ioc_top [OrderTop α] : Ioc a (⊤ : α) = Ioi a := rfl theorem Icc_bot_top [BoundedOrder α] [Fintype α] : Icc (⊥ : α) (⊤ : α) = univ := by rw [Icc_bot, Iic_top] end LocallyFiniteOrder variable [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α] theorem disjoint_Ioi_Iio (a : α) : Disjoint (Ioi a) (Iio a) := disjoint_left.2 fun _ hab hba => (mem_Ioi.1 hab).not_lt <| mem_Iio.1 hba end Preorder section PartialOrder variable [PartialOrder α] [LocallyFiniteOrder α] {a b c : α} @[simp] theorem Icc_self (a : α) : Icc a a = {a} := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_self] @[simp] theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_eq_singleton_iff] theorem Ico_disjoint_Ico_consecutive (a b c : α) : Disjoint (Ico a b) (Ico b c) := disjoint_left.2 fun _ hab hbc => (mem_Ico.mp hab).2.not_le (mem_Ico.mp hbc).1 @[simp] theorem Ici_top [OrderTop α] : Ici (⊤ : α) = {⊤} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩ @[simp] theorem Iic_bot [OrderBot α] : Iic (⊥ : α) = {⊥} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩ section DecidableEq variable [DecidableEq α] @[simp] theorem Icc_erase_left (a b : α) : (Icc a b).erase a = Ioc a b := by simp [← coe_inj] @[simp] theorem Icc_erase_right (a b : α) : (Icc a b).erase b = Ico a b := by simp [← coe_inj] @[simp] theorem Ico_erase_left (a b : α) : (Ico a b).erase a = Ioo a b := by simp [← coe_inj] @[simp] theorem Ioc_erase_right (a b : α) : (Ioc a b).erase b = Ioo a b := by simp [← coe_inj] @[simp] theorem Icc_diff_both (a b : α) : Icc a b \ {a, b} = Ioo a b := by simp [← coe_inj] @[simp] theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by rw [← coe_inj, coe_insert, coe_Icc, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ico_union_right h] @[simp] theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by rw [← coe_inj, coe_insert, coe_Ioc, coe_Icc, Set.insert_eq, Set.union_comm, Set.Ioc_union_left h] @[simp] theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by rw [← coe_inj, coe_insert, coe_Ioo, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ioo_union_left h] @[simp] theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by rw [← coe_inj, coe_insert, coe_Ioo, coe_Ioc, Set.insert_eq, Set.union_comm, Set.Ioo_union_right h] @[simp] theorem Icc_diff_Ico_self (h : a ≤ b) : Icc a b \ Ico a b = {b} := by simp [← coe_inj, h] @[simp] theorem Icc_diff_Ioc_self (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by simp [← coe_inj, h] @[simp] theorem Icc_diff_Ioo_self (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by simp [← coe_inj, h] @[simp] theorem Ico_diff_Ioo_self (h : a < b) : Ico a b \ Ioo a b = {a} := by simp [← coe_inj, h] @[simp] theorem Ioc_diff_Ioo_self (h : a < b) : Ioc a b \ Ioo a b = {b} := by simp [← coe_inj, h] @[simp] theorem Ico_inter_Ico_consecutive (a b c : α) : Ico a b ∩ Ico b c = ∅ := (Ico_disjoint_Ico_consecutive a b c).eq_bot end DecidableEq -- Those lemmas are purposefully the other way around /-- `Finset.cons` version of `Finset.Ico_insert_right`. -/ theorem Icc_eq_cons_Ico (h : a ≤ b) : Icc a b = (Ico a b).cons b right_not_mem_Ico := by classical rw [cons_eq_insert, Ico_insert_right h] /-- `Finset.cons` version of `Finset.Ioc_insert_left`. -/ theorem Icc_eq_cons_Ioc (h : a ≤ b) : Icc a b = (Ioc a b).cons a left_not_mem_Ioc := by classical rw [cons_eq_insert, Ioc_insert_left h] /-- `Finset.cons` version of `Finset.Ioo_insert_right`. -/ theorem Ioc_eq_cons_Ioo (h : a < b) : Ioc a b = (Ioo a b).cons b right_not_mem_Ioo := by classical rw [cons_eq_insert, Ioo_insert_right h] /-- `Finset.cons` version of `Finset.Ioo_insert_left`. -/ theorem Ico_eq_cons_Ioo (h : a < b) : Ico a b = (Ioo a b).cons a left_not_mem_Ioo := by classical rw [cons_eq_insert, Ioo_insert_left h] theorem Ico_filter_le_left {a b : α} [DecidablePred (· ≤ a)] (hab : a < b) : {x ∈ Ico a b | x ≤ a} = {a} := by ext x rw [mem_filter, mem_Ico, mem_singleton, and_right_comm, ← le_antisymm_iff, eq_comm] exact and_iff_left_of_imp fun h => h.le.trans_lt hab theorem card_Ico_eq_card_Icc_sub_one (a b : α) : #(Ico a b) = #(Icc a b) - 1 := by classical by_cases h : a ≤ b · rw [Icc_eq_cons_Ico h, card_cons] exact (Nat.add_sub_cancel _ _).symm · rw [Ico_eq_empty fun h' => h h'.le, Icc_eq_empty h, card_empty, Nat.zero_sub] theorem card_Ioc_eq_card_Icc_sub_one (a b : α) : #(Ioc a b) = #(Icc a b) - 1 := @card_Ico_eq_card_Icc_sub_one αᵒᵈ _ _ _ _ theorem card_Ioo_eq_card_Ico_sub_one (a b : α) : #(Ioo a b) = #(Ico a b) - 1 := by classical by_cases h : a < b · rw [Ico_eq_cons_Ioo h, card_cons] exact (Nat.add_sub_cancel _ _).symm · rw [Ioo_eq_empty h, Ico_eq_empty h, card_empty, Nat.zero_sub] theorem card_Ioo_eq_card_Ioc_sub_one (a b : α) : #(Ioo a b) = #(Ioc a b) - 1 := @card_Ioo_eq_card_Ico_sub_one αᵒᵈ _ _ _ _ theorem card_Ioo_eq_card_Icc_sub_two (a b : α) : #(Ioo a b) = #(Icc a b) - 2 := by rw [card_Ioo_eq_card_Ico_sub_one, card_Ico_eq_card_Icc_sub_one] rfl end PartialOrder section Prod variable {β : Type*} section sectL lemma uIcc_map_sectL [Lattice α] [Lattice β] [LocallyFiniteOrder α] [LocallyFiniteOrder β] [DecidableLE (α × β)] (a b : α) (c : β) : (uIcc a b).map (.sectL _ c) = uIcc (a, c) (b, c) := by aesop (add safe forward [le_antisymm]) variable [Preorder α] [PartialOrder β] [LocallyFiniteOrder α] [LocallyFiniteOrder β] [DecidableLE (α × β)] (a b : α) (c : β) lemma Icc_map_sectL : (Icc a b).map (.sectL _ c) = Icc (a, c) (b, c) := by aesop (add safe forward [le_antisymm]) lemma Ioc_map_sectL : (Ioc a b).map (.sectL _ c) = Ioc (a, c) (b, c) := by aesop (add safe forward [le_antisymm, le_of_lt]) lemma Ico_map_sectL : (Ico a b).map (.sectL _ c) = Ico (a, c) (b, c) := by aesop (add safe forward [le_antisymm, le_of_lt]) lemma Ioo_map_sectL : (Ioo a b).map (.sectL _ c) = Ioo (a, c) (b, c) := by aesop (add safe forward [le_antisymm, le_of_lt]) end sectL section sectR lemma uIcc_map_sectR [Lattice α] [Lattice β] [LocallyFiniteOrder α] [LocallyFiniteOrder β] [DecidableLE (α × β)] (c : α) (a b : β) : (uIcc a b).map (.sectR c _) = uIcc (c, a) (c, b) := by aesop (add safe forward [le_antisymm]) variable [PartialOrder α] [Preorder β] [LocallyFiniteOrder α] [LocallyFiniteOrder β] [DecidableLE (α × β)] (c : α) (a b : β) lemma Icc_map_sectR : (Icc a b).map (.sectR c _) = Icc (c, a) (c, b) := by aesop (add safe forward [le_antisymm]) lemma Ioc_map_sectR : (Ioc a b).map (.sectR c _) = Ioc (c, a) (c, b) := by aesop (add safe forward [le_antisymm, le_of_lt]) lemma Ico_map_sectR : (Ico a b).map (.sectR c _) = Ico (c, a) (c, b) := by aesop (add safe forward [le_antisymm, le_of_lt]) lemma Ioo_map_sectR : (Ioo a b).map (.sectR c _) = Ioo (c, a) (c, b) := by aesop (add safe forward [le_antisymm, le_of_lt]) end sectR end Prod section BoundedPartialOrder variable [PartialOrder α] section OrderTop variable [LocallyFiniteOrderTop α] @[simp] theorem Ici_erase [DecidableEq α] (a : α) : (Ici a).erase a = Ioi a := by ext simp_rw [Finset.mem_erase, mem_Ici, mem_Ioi, lt_iff_le_and_ne, and_comm, ne_comm] @[simp] theorem Ioi_insert [DecidableEq α] (a : α) : insert a (Ioi a) = Ici a := by ext simp_rw [Finset.mem_insert, mem_Ici, mem_Ioi, le_iff_lt_or_eq, or_comm, eq_comm] theorem not_mem_Ioi_self {b : α} : b ∉ Ioi b := fun h => lt_irrefl _ (mem_Ioi.1 h) -- Purposefully written the other way around /-- `Finset.cons` version of `Finset.Ioi_insert`. -/ theorem Ici_eq_cons_Ioi (a : α) : Ici a = (Ioi a).cons a not_mem_Ioi_self := by classical rw [cons_eq_insert, Ioi_insert] theorem card_Ioi_eq_card_Ici_sub_one (a : α) : #(Ioi a) = #(Ici a) - 1 := by rw [Ici_eq_cons_Ioi, card_cons, Nat.add_sub_cancel_right] end OrderTop section OrderBot variable [LocallyFiniteOrderBot α] @[simp] theorem Iic_erase [DecidableEq α] (b : α) : (Iic b).erase b = Iio b := by ext simp_rw [Finset.mem_erase, mem_Iic, mem_Iio, lt_iff_le_and_ne, and_comm] @[simp] theorem Iio_insert [DecidableEq α] (b : α) : insert b (Iio b) = Iic b := by ext simp_rw [Finset.mem_insert, mem_Iic, mem_Iio, le_iff_lt_or_eq, or_comm] theorem not_mem_Iio_self {b : α} : b ∉ Iio b := fun h => lt_irrefl _ (mem_Iio.1 h) -- Purposefully written the other way around /-- `Finset.cons` version of `Finset.Iio_insert`. -/ theorem Iic_eq_cons_Iio (b : α) : Iic b = (Iio b).cons b not_mem_Iio_self := by classical rw [cons_eq_insert, Iio_insert] theorem card_Iio_eq_card_Iic_sub_one (a : α) : #(Iio a) = #(Iic a) - 1 := by rw [Iic_eq_cons_Iio, card_cons, Nat.add_sub_cancel_right] end OrderBot end BoundedPartialOrder section SemilatticeSup variable [SemilatticeSup α] [LocallyFiniteOrderBot α] -- TODO: Why does `id_eq` simplify the LHS here but not the LHS of `Finset.sup_Iic`? lemma sup'_Iic (a : α) : (Iic a).sup' nonempty_Iic id = a := le_antisymm (sup'_le _ _ fun _ ↦ mem_Iic.1) <| le_sup' (f := id) <| mem_Iic.2 <| le_refl a @[simp] lemma sup_Iic [OrderBot α] (a : α) : (Iic a).sup id = a := le_antisymm (Finset.sup_le fun _ ↦ mem_Iic.1) <| le_sup (f := id) <| mem_Iic.2 <| le_refl a lemma image_subset_Iic_sup [OrderBot α] [DecidableEq α] (f : ι → α) (s : Finset ι) : s.image f ⊆ Iic (s.sup f) := by refine fun i hi ↦ mem_Iic.2 ?_ obtain ⟨j, hj, rfl⟩ := mem_image.1 hi exact le_sup hj lemma subset_Iic_sup_id [OrderBot α] (s : Finset α) : s ⊆ Iic (s.sup id) := fun _ h ↦ mem_Iic.2 <| le_sup (f := id) h end SemilatticeSup section SemilatticeInf variable [SemilatticeInf α] [LocallyFiniteOrderTop α] lemma inf'_Ici (a : α) : (Ici a).inf' nonempty_Ici id = a := ge_antisymm (le_inf' _ _ fun _ ↦ mem_Ici.1) <| inf'_le (f := id) <| mem_Ici.2 <| le_refl a @[simp] lemma inf_Ici [OrderTop α] (a : α) : (Ici a).inf id = a := le_antisymm (inf_le (f := id) <| mem_Ici.2 <| le_refl a) <| Finset.le_inf fun _ ↦ mem_Ici.1 end SemilatticeInf section LinearOrder variable [LinearOrder α] section LocallyFiniteOrder variable [LocallyFiniteOrder α] theorem Ico_subset_Ico_iff {a₁ b₁ a₂ b₂ : α} (h : a₁ < b₁) : Ico a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by rw [← coe_subset, coe_Ico, coe_Ico, Set.Ico_subset_Ico_iff h] theorem Ico_union_Ico_eq_Ico {a b c : α} (hab : a ≤ b) (hbc : b ≤ c) : Ico a b ∪ Ico b c = Ico a c := by rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico_eq_Ico hab hbc] @[simp] theorem Ioc_union_Ioc_eq_Ioc {a b c : α} (h₁ : a ≤ b) (h₂ : b ≤ c) : Ioc a b ∪ Ioc b c = Ioc a c := by rw [← coe_inj, coe_union, coe_Ioc, coe_Ioc, coe_Ioc, Set.Ioc_union_Ioc_eq_Ioc h₁ h₂] theorem Ico_subset_Ico_union_Ico {a b c : α} : Ico a c ⊆ Ico a b ∪ Ico b c := by rw [← coe_subset, coe_union, coe_Ico, coe_Ico, coe_Ico] exact Set.Ico_subset_Ico_union_Ico theorem Ico_union_Ico' {a b c d : α} (hcb : c ≤ b) (had : a ≤ d) : Ico a b ∪ Ico c d = Ico (min a c) (max b d) := by rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico' hcb had] theorem Ico_union_Ico {a b c d : α} (h₁ : min a b ≤ max c d) (h₂ : min c d ≤ max a b) : Ico a b ∪ Ico c d = Ico (min a c) (max b d) := by rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico h₁ h₂] theorem Ico_inter_Ico {a b c d : α} : Ico a b ∩ Ico c d = Ico (max a c) (min b d) := by rw [← coe_inj, coe_inter, coe_Ico, coe_Ico, coe_Ico, Set.Ico_inter_Ico] theorem Ioc_inter_Ioc {a b c d : α} : Ioc a b ∩ Ioc c d = Ioc (max a c) (min b d) := by rw [← coe_inj] push_cast exact Set.Ioc_inter_Ioc @[simp] theorem Ico_filter_lt (a b c : α) : {x ∈ Ico a b | x < c} = Ico a (min b c) := by cases le_total b c with | inl h => rw [Ico_filter_lt_of_right_le h, min_eq_left h] | inr h => rw [Ico_filter_lt_of_le_right h, min_eq_right h] @[simp] theorem Ico_filter_le (a b c : α) : {x ∈ Ico a b | c ≤ x} = Ico (max a c) b := by cases le_total a c with | inl h => rw [Ico_filter_le_of_left_le h, max_eq_right h] | inr h => rw [Ico_filter_le_of_le_left h, max_eq_left h] @[simp] theorem Ioo_filter_lt (a b c : α) : {x ∈ Ioo a b | x < c} = Ioo a (min b c) := by ext simp [and_assoc] @[simp] theorem Iio_filter_lt {α} [LinearOrder α] [LocallyFiniteOrderBot α] (a b : α) : {x ∈ Iio a | x < b} = Iio (min a b) := by ext simp [and_assoc] @[simp] theorem Ico_diff_Ico_left (a b c : α) : Ico a b \ Ico a c = Ico (max a c) b := by cases le_total a c with | inl h => ext x rw [mem_sdiff, mem_Ico, mem_Ico, mem_Ico, max_eq_right h, and_right_comm, not_and, not_lt] exact and_congr_left' ⟨fun hx => hx.2 hx.1, fun hx => ⟨h.trans hx, fun _ => hx⟩⟩ | inr h => rw [Ico_eq_empty_of_le h, sdiff_empty, max_eq_left h] @[simp] theorem Ico_diff_Ico_right (a b c : α) : Ico a b \ Ico c b = Ico a (min b c) := by cases le_total b c with | inl h => rw [Ico_eq_empty_of_le h, sdiff_empty, min_eq_left h] | inr h => ext x rw [mem_sdiff, mem_Ico, mem_Ico, mem_Ico, min_eq_right h, and_assoc, not_and', not_le] exact and_congr_right' ⟨fun hx => hx.2 hx.1, fun hx => ⟨hx.trans_le h, fun _ => hx⟩⟩ @[simp] theorem Ioc_disjoint_Ioc : Disjoint (Ioc a₁ a₂) (Ioc b₁ b₂) ↔ min a₂ b₂ ≤ max a₁ b₁ := by simp_rw [disjoint_iff_inter_eq_empty, Ioc_inter_Ioc, Ioc_eq_empty_iff, not_lt] section LocallyFiniteOrderBot variable [LocallyFiniteOrderBot α] theorem Iic_diff_Ioc : Iic b \ Ioc a b = Iic (a ⊓ b) := by rw [← coe_inj] push_cast exact Set.Iic_diff_Ioc theorem Iic_diff_Ioc_self_of_le (hab : a ≤ b) : Iic b \ Ioc a b = Iic a := by rw [Iic_diff_Ioc, min_eq_left hab] theorem Iic_union_Ioc_eq_Iic (h : a ≤ b) : Iic a ∪ Ioc a b = Iic b := by rw [← coe_inj] push_cast exact Set.Iic_union_Ioc_eq_Iic h end LocallyFiniteOrderBot end LocallyFiniteOrder section LocallyFiniteOrderBot variable [LocallyFiniteOrderBot α] {s : Set α} theorem _root_.Set.Infinite.exists_gt (hs : s.Infinite) : ∀ a, ∃ b ∈ s, a < b := not_bddAbove_iff.1 hs.not_bddAbove theorem _root_.Set.infinite_iff_exists_gt [Nonempty α] : s.Infinite ↔ ∀ a, ∃ b ∈ s, a < b := ⟨Set.Infinite.exists_gt, Set.infinite_of_forall_exists_gt⟩ end LocallyFiniteOrderBot section LocallyFiniteOrderTop variable [LocallyFiniteOrderTop α] {s : Set α} theorem _root_.Set.Infinite.exists_lt (hs : s.Infinite) : ∀ a, ∃ b ∈ s, b < a := not_bddBelow_iff.1 hs.not_bddBelow theorem _root_.Set.infinite_iff_exists_lt [Nonempty α] : s.Infinite ↔ ∀ a, ∃ b ∈ s, b < a := ⟨Set.Infinite.exists_lt, Set.infinite_of_forall_exists_lt⟩ end LocallyFiniteOrderTop variable [Fintype α] [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α] theorem Ioi_disjUnion_Iio (a : α) : (Ioi a).disjUnion (Iio a) (disjoint_Ioi_Iio a) = ({a} : Finset α)ᶜ := by ext simp [eq_comm] end LinearOrder section Lattice variable [Lattice α] [LocallyFiniteOrder α] {a a₁ a₂ b b₁ b₂ x : α} theorem uIcc_toDual (a b : α) : [[toDual a, toDual b]] = [[a, b]].map toDual.toEmbedding := Icc_toDual (a ⊔ b) (a ⊓ b) @[simp] theorem uIcc_of_le (h : a ≤ b) : [[a, b]] = Icc a b := by rw [uIcc, inf_eq_left.2 h, sup_eq_right.2 h] @[simp] theorem uIcc_of_ge (h : b ≤ a) : [[a, b]] = Icc b a := by rw [uIcc, inf_eq_right.2 h, sup_eq_left.2 h] theorem uIcc_comm (a b : α) : [[a, b]] = [[b, a]] := by rw [uIcc, uIcc, inf_comm, sup_comm] theorem uIcc_self : [[a, a]] = {a} := by simp [uIcc] @[simp] theorem nonempty_uIcc : Finset.Nonempty [[a, b]] := nonempty_Icc.2 inf_le_sup theorem Icc_subset_uIcc : Icc a b ⊆ [[a, b]] := Icc_subset_Icc inf_le_left le_sup_right theorem Icc_subset_uIcc' : Icc b a ⊆ [[a, b]] := Icc_subset_Icc inf_le_right le_sup_left theorem left_mem_uIcc : a ∈ [[a, b]] := mem_Icc.2 ⟨inf_le_left, le_sup_left⟩ theorem right_mem_uIcc : b ∈ [[a, b]] := mem_Icc.2 ⟨inf_le_right, le_sup_right⟩ theorem mem_uIcc_of_le (ha : a ≤ x) (hb : x ≤ b) : x ∈ [[a, b]] := Icc_subset_uIcc <| mem_Icc.2 ⟨ha, hb⟩ theorem mem_uIcc_of_ge (hb : b ≤ x) (ha : x ≤ a) : x ∈ [[a, b]] := Icc_subset_uIcc' <| mem_Icc.2 ⟨hb, ha⟩ theorem uIcc_subset_uIcc (h₁ : a₁ ∈ [[a₂, b₂]]) (h₂ : b₁ ∈ [[a₂, b₂]]) : [[a₁, b₁]] ⊆ [[a₂, b₂]] := by rw [mem_uIcc] at h₁ h₂ exact Icc_subset_Icc (_root_.le_inf h₁.1 h₂.1) (_root_.sup_le h₁.2 h₂.2) theorem uIcc_subset_Icc (ha : a₁ ∈ Icc a₂ b₂) (hb : b₁ ∈ Icc a₂ b₂) : [[a₁, b₁]] ⊆ Icc a₂ b₂ := by rw [mem_Icc] at ha hb exact Icc_subset_Icc (_root_.le_inf ha.1 hb.1) (_root_.sup_le ha.2 hb.2) theorem uIcc_subset_uIcc_iff_mem : [[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₁ ∈ [[a₂, b₂]] ∧ b₁ ∈ [[a₂, b₂]] := ⟨fun h => ⟨h left_mem_uIcc, h right_mem_uIcc⟩, fun h => uIcc_subset_uIcc h.1 h.2⟩ theorem uIcc_subset_uIcc_iff_le' : [[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₂ ⊓ b₂ ≤ a₁ ⊓ b₁ ∧ a₁ ⊔ b₁ ≤ a₂ ⊔ b₂ := Icc_subset_Icc_iff inf_le_sup
theorem uIcc_subset_uIcc_right (h : x ∈ [[a, b]]) : [[x, b]] ⊆ [[a, b]] := uIcc_subset_uIcc h right_mem_uIcc
Mathlib/Order/Interval/Finset/Basic.lean
1,005
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/- Copyright (c) 2020 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Algebra.Module.Basic import Mathlib.LinearAlgebra.AffineSpace.AffineEquiv /-! # Midpoint of a segment ## Main definitions * `midpoint R x y`: midpoint of the segment `[x, y]`. We define it for `x` and `y` in a module over a ring `R` with invertible `2`. * `AddMonoidHom.ofMapMidpoint`: construct an `AddMonoidHom` given a map `f` such that `f` sends zero to zero and midpoints to midpoints. ## Main theorems * `midpoint_eq_iff`: `z` is the midpoint of `[x, y]` if and only if `x + y = z + z`, * `midpoint_unique`: `midpoint R x y` does not depend on `R`; * `midpoint x y` is linear both in `x` and `y`; * `pointReflection_midpoint_left`, `pointReflection_midpoint_right`: `Equiv.pointReflection (midpoint R x y)` swaps `x` and `y`. We do not mark most lemmas as `@[simp]` because it is hard to tell which side is simpler. ## Tags midpoint, AddMonoidHom -/ open AffineMap AffineEquiv section variable (R : Type*) {V V' P P' : Type*} [Ring R] [Invertible (2 : R)] [AddCommGroup V] [Module R V] [AddTorsor V P] [AddCommGroup V'] [Module R V'] [AddTorsor V' P'] /-- `midpoint x y` is the midpoint of the segment `[x, y]`. -/ def midpoint (x y : P) : P := lineMap x y (⅟ 2 : R) variable {R} {x y z : P} @[simp] theorem AffineMap.map_midpoint (f : P →ᵃ[R] P') (a b : P) : f (midpoint R a b) = midpoint R (f a) (f b) := f.apply_lineMap a b _ @[simp] theorem AffineEquiv.map_midpoint (f : P ≃ᵃ[R] P') (a b : P) : f (midpoint R a b) = midpoint R (f a) (f b) := f.apply_lineMap a b _ theorem AffineEquiv.pointReflection_midpoint_left (x y : P) : pointReflection R (midpoint R x y) x = y := by rw [midpoint, pointReflection_apply, lineMap_apply, vadd_vsub, vadd_vadd, ← add_smul, ← two_mul, mul_invOf_self, one_smul, vsub_vadd] @[simp] theorem Equiv.pointReflection_midpoint_left (x y : P) : (Equiv.pointReflection (midpoint R x y)) x = y := by rw [midpoint, pointReflection_apply, lineMap_apply, vadd_vsub, vadd_vadd, ← add_smul, ← two_mul, mul_invOf_self, one_smul, vsub_vadd] theorem midpoint_comm (x y : P) : midpoint R x y = midpoint R y x := by rw [midpoint, ← lineMap_apply_one_sub, one_sub_invOf_two, midpoint] theorem AffineEquiv.pointReflection_midpoint_right (x y : P) : pointReflection R (midpoint R x y) y = x := by rw [midpoint_comm, AffineEquiv.pointReflection_midpoint_left] @[simp] theorem Equiv.pointReflection_midpoint_right (x y : P) : (Equiv.pointReflection (midpoint R x y)) y = x := by rw [midpoint_comm, Equiv.pointReflection_midpoint_left] theorem midpoint_vsub_midpoint (p₁ p₂ p₃ p₄ : P) : midpoint R p₁ p₂ -ᵥ midpoint R p₃ p₄ = midpoint R (p₁ -ᵥ p₃) (p₂ -ᵥ p₄) := lineMap_vsub_lineMap _ _ _ _ _ theorem midpoint_vadd_midpoint (v v' : V) (p p' : P) : midpoint R v v' +ᵥ midpoint R p p' = midpoint R (v +ᵥ p) (v' +ᵥ p') := lineMap_vadd_lineMap _ _ _ _ _ theorem midpoint_eq_iff {x y z : P} : midpoint R x y = z ↔ pointReflection R z x = y := eq_comm.trans ((injective_pointReflection_left_of_module R x).eq_iff' (AffineEquiv.pointReflection_midpoint_left x y)).symm @[simp] theorem midpoint_pointReflection_left (x y : P) : midpoint R (Equiv.pointReflection x y) y = x := midpoint_eq_iff.2 <| Equiv.pointReflection_involutive _ _ @[simp] theorem midpoint_pointReflection_right (x y : P) : midpoint R y (Equiv.pointReflection x y) = x := midpoint_eq_iff.2 rfl nonrec lemma AffineEquiv.midpoint_pointReflection_left (x y : P) : midpoint R (pointReflection R x y) y = x := midpoint_pointReflection_left x y nonrec lemma AffineEquiv.midpoint_pointReflection_right (x y : P) : midpoint R y (pointReflection R x y) = x := midpoint_pointReflection_right x y @[simp] theorem midpoint_vsub_left (p₁ p₂ : P) : midpoint R p₁ p₂ -ᵥ p₁ = (⅟ 2 : R) • (p₂ -ᵥ p₁) := lineMap_vsub_left _ _ _ @[simp] theorem midpoint_vsub_right (p₁ p₂ : P) : midpoint R p₁ p₂ -ᵥ p₂ = (⅟ 2 : R) • (p₁ -ᵥ p₂) := by rw [midpoint_comm, midpoint_vsub_left] @[simp] theorem left_vsub_midpoint (p₁ p₂ : P) : p₁ -ᵥ midpoint R p₁ p₂ = (⅟ 2 : R) • (p₁ -ᵥ p₂) := left_vsub_lineMap _ _ _ @[simp] theorem right_vsub_midpoint (p₁ p₂ : P) : p₂ -ᵥ midpoint R p₁ p₂ = (⅟ 2 : R) • (p₂ -ᵥ p₁) := by rw [midpoint_comm, left_vsub_midpoint] theorem midpoint_vsub (p₁ p₂ p : P) : midpoint R p₁ p₂ -ᵥ p = (⅟ 2 : R) • (p₁ -ᵥ p) + (⅟ 2 : R) • (p₂ -ᵥ p) := by rw [← vsub_sub_vsub_cancel_right p₁ p p₂, smul_sub, sub_eq_add_neg, ← smul_neg, neg_vsub_eq_vsub_rev, add_assoc, invOf_two_smul_add_invOf_two_smul, ← vadd_vsub_assoc, midpoint_comm, midpoint, lineMap_apply] theorem vsub_midpoint (p₁ p₂ p : P) : p -ᵥ midpoint R p₁ p₂ = (⅟ 2 : R) • (p -ᵥ p₁) + (⅟ 2 : R) • (p -ᵥ p₂) := by rw [← neg_vsub_eq_vsub_rev, midpoint_vsub, neg_add, ← smul_neg, ← smul_neg, neg_vsub_eq_vsub_rev, neg_vsub_eq_vsub_rev] @[simp] theorem midpoint_sub_left (v₁ v₂ : V) : midpoint R v₁ v₂ - v₁ = (⅟ 2 : R) • (v₂ - v₁) := midpoint_vsub_left v₁ v₂ @[simp] theorem midpoint_sub_right (v₁ v₂ : V) : midpoint R v₁ v₂ - v₂ = (⅟ 2 : R) • (v₁ - v₂) := midpoint_vsub_right v₁ v₂ @[simp] theorem left_sub_midpoint (v₁ v₂ : V) : v₁ - midpoint R v₁ v₂ = (⅟ 2 : R) • (v₁ - v₂) := left_vsub_midpoint v₁ v₂ @[simp] theorem right_sub_midpoint (v₁ v₂ : V) : v₂ - midpoint R v₁ v₂ = (⅟ 2 : R) • (v₂ - v₁) := right_vsub_midpoint v₁ v₂ variable (R) @[simp] theorem midpoint_eq_left_iff {x y : P} : midpoint R x y = x ↔ x = y := by rw [midpoint_eq_iff, pointReflection_self] @[simp] theorem left_eq_midpoint_iff {x y : P} : x = midpoint R x y ↔ x = y := by rw [eq_comm, midpoint_eq_left_iff] @[simp] theorem midpoint_eq_right_iff {x y : P} : midpoint R x y = y ↔ x = y := by rw [midpoint_comm, midpoint_eq_left_iff, eq_comm] @[simp] theorem right_eq_midpoint_iff {x y : P} : y = midpoint R x y ↔ x = y := by rw [eq_comm, midpoint_eq_right_iff] theorem midpoint_eq_midpoint_iff_vsub_eq_vsub {x x' y y' : P} : midpoint R x y = midpoint R x' y' ↔ x -ᵥ x' = y' -ᵥ y := by rw [← @vsub_eq_zero_iff_eq V, midpoint_vsub_midpoint, midpoint_eq_iff, pointReflection_apply, vsub_eq_sub, zero_sub, vadd_eq_add, add_zero, neg_eq_iff_eq_neg, neg_vsub_eq_vsub_rev] theorem midpoint_eq_iff' {x y z : P} : midpoint R x y = z ↔ Equiv.pointReflection z x = y := midpoint_eq_iff /-- `midpoint` does not depend on the ring `R`. -/ theorem midpoint_unique (R' : Type*) [Ring R'] [Invertible (2 : R')] [Module R' V] (x y : P) : midpoint R x y = midpoint R' x y := (midpoint_eq_iff' R).2 <| (midpoint_eq_iff' R').1 rfl @[simp] theorem midpoint_self (x : P) : midpoint R x x = x := lineMap_same_apply _ _ @[simp] theorem midpoint_add_self (x y : V) : midpoint R x y + midpoint R x y = x + y := calc midpoint R x y +ᵥ midpoint R x y = midpoint R x y +ᵥ midpoint R y x := by rw [midpoint_comm] _ = x + y := by rw [midpoint_vadd_midpoint, vadd_eq_add, vadd_eq_add, add_comm, midpoint_self] theorem midpoint_zero_add (x y : V) : midpoint R 0 (x + y) = midpoint R x y := (midpoint_eq_midpoint_iff_vsub_eq_vsub R).2 <| by simp [sub_add_eq_sub_sub_swap] theorem midpoint_eq_smul_add (x y : V) : midpoint R x y = (⅟ 2 : R) • (x + y) := by rw [midpoint_eq_iff, pointReflection_apply, vsub_eq_sub, vadd_eq_add, sub_add_eq_add_sub, ← two_smul R, smul_smul, mul_invOf_self, one_smul, add_sub_cancel_left] @[simp] theorem midpoint_self_neg (x : V) : midpoint R x (-x) = 0 := by rw [midpoint_eq_smul_add, add_neg_cancel, smul_zero] @[simp] theorem midpoint_neg_self (x : V) : midpoint R (-x) x = 0 := by simpa using midpoint_self_neg R (-x) @[simp] theorem midpoint_sub_add (x y : V) : midpoint R (x - y) (x + y) = x := by rw [sub_eq_add_neg, ← vadd_eq_add, ← vadd_eq_add, ← midpoint_vadd_midpoint]; simp @[simp] theorem midpoint_add_sub (x y : V) : midpoint R (x + y) (x - y) = x := by rw [midpoint_comm]; simp end namespace AddMonoidHom variable (R R' : Type*) {E F : Type*} [Ring R] [Invertible (2 : R)] [AddCommGroup E] [Module R E] [Ring R'] [Invertible (2 : R')] [AddCommGroup F] [Module R' F] /-- A map `f : E → F` sending zero to zero and midpoints to midpoints is an `AddMonoidHom`. -/ def ofMapMidpoint (f : E → F) (h0 : f 0 = 0) (hm : ∀ x y, f (midpoint R x y) = midpoint R' (f x) (f y)) : E →+ F where toFun := f map_zero' := h0 map_add' x y := calc
f (x + y) = f 0 + f (x + y) := by rw [h0, zero_add]
Mathlib/LinearAlgebra/AffineSpace/Midpoint.lean
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/- Copyright (c) 2024 David Loeffler. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: David Loeffler -/ import Mathlib.NumberTheory.LSeries.AbstractFuncEq import Mathlib.NumberTheory.ModularForms.JacobiTheta.Bounds import Mathlib.Analysis.SpecialFunctions.Gamma.Deligne import Mathlib.NumberTheory.LSeries.MellinEqDirichlet import Mathlib.NumberTheory.LSeries.Basic import Mathlib.Analysis.Complex.RemovableSingularity /-! # Even Hurwitz zeta functions In this file we study the functions on `ℂ` which are the meromorphic continuation of the following series (convergent for `1 < re s`), where `a ∈ ℝ` is a parameter: `hurwitzZetaEven a s = 1 / 2 * ∑' n : ℤ, 1 / |n + a| ^ s` and `cosZeta a s = ∑' n : ℕ, cos (2 * π * a * n) / |n| ^ s`. Note that the term for `n = -a` in the first sum is omitted if `a` is an integer, and the term for `n = 0` is omitted in the second sum (always). Of course, we cannot *define* these functions by the above formulae (since existence of the meromorphic continuation is not at all obvious); we in fact construct them as Mellin transforms of various versions of the Jacobi theta function. We also define completed versions of these functions with nicer functional equations (satisfying `completedHurwitzZetaEven a s = Gammaℝ s * hurwitzZetaEven a s`, and similarly for `cosZeta`); and modified versions with a subscript `0`, which are entire functions differing from the above by multiples of `1 / s` and `1 / (1 - s)`. ## Main definitions and theorems * `hurwitzZetaEven` and `cosZeta`: the zeta functions * `completedHurwitzZetaEven` and `completedCosZeta`: completed variants * `differentiableAt_hurwitzZetaEven` and `differentiableAt_cosZeta`: differentiability away from `s = 1` * `completedHurwitzZetaEven_one_sub`: the functional equation `completedHurwitzZetaEven a (1 - s) = completedCosZeta a s` * `hasSum_int_hurwitzZetaEven` and `hasSum_nat_cosZeta`: relation between the zeta functions and the corresponding Dirichlet series for `1 < re s`. -/ noncomputable section open Complex Filter Topology Asymptotics Real Set MeasureTheory namespace HurwitzZeta section kernel_defs /-! ## Definitions and elementary properties of kernels -/ /-- Even Hurwitz zeta kernel (function whose Mellin transform will be the even part of the completed Hurwit zeta function). See `evenKernel_def` for the defining formula, and `hasSum_int_evenKernel` for an expression as a sum over `ℤ`. -/ @[irreducible] def evenKernel (a : UnitAddCircle) (x : ℝ) : ℝ := (show Function.Periodic (fun ξ : ℝ ↦ rexp (-π * ξ ^ 2 * x) * re (jacobiTheta₂ (ξ * I * x) (I * x))) 1 by intro ξ simp only [ofReal_add, ofReal_one, add_mul, one_mul, jacobiTheta₂_add_left'] have : cexp (-↑π * I * ((I * ↑x) + 2 * (↑ξ * I * ↑x))) = rexp (π * (x + 2 * ξ * x)) := by ring_nf simp [I_sq] rw [this, re_ofReal_mul, ← mul_assoc, ← Real.exp_add] congr ring).lift a lemma evenKernel_def (a x : ℝ) : ↑(evenKernel ↑a x) = cexp (-π * a ^ 2 * x) * jacobiTheta₂ (a * I * x) (I * x) := by simp [evenKernel, re_eq_add_conj, jacobiTheta₂_conj, ← mul_two, mul_div_cancel_right₀ _ (two_ne_zero' ℂ)] /-- For `x ≤ 0` the defining sum diverges, so the kernel is 0. -/ lemma evenKernel_undef (a : UnitAddCircle) {x : ℝ} (hx : x ≤ 0) : evenKernel a x = 0 := by induction a using QuotientAddGroup.induction_on with | H a' => simp [← ofReal_inj, evenKernel_def, jacobiTheta₂_undef _ (by simpa : (I * ↑x).im ≤ 0)] /-- Cosine Hurwitz zeta kernel. See `cosKernel_def` for the defining formula, and `hasSum_int_cosKernel` for expression as a sum. -/ @[irreducible] def cosKernel (a : UnitAddCircle) (x : ℝ) : ℝ := (show Function.Periodic (fun ξ : ℝ ↦ re (jacobiTheta₂ ξ (I * x))) 1 by intro ξ; simp [jacobiTheta₂_add_left]).lift a lemma cosKernel_def (a x : ℝ) : ↑(cosKernel ↑a x) = jacobiTheta₂ a (I * x) := by simp [cosKernel, re_eq_add_conj, jacobiTheta₂_conj, ← mul_two, mul_div_cancel_right₀ _ (two_ne_zero' ℂ)] lemma cosKernel_undef (a : UnitAddCircle) {x : ℝ} (hx : x ≤ 0) : cosKernel a x = 0 := by induction a using QuotientAddGroup.induction_on with | H => simp [← ofReal_inj, cosKernel_def, jacobiTheta₂_undef _ (by simpa : (I * ↑x).im ≤ 0)] /-- For `a = 0`, both kernels agree. -/ lemma evenKernel_eq_cosKernel_of_zero : evenKernel 0 = cosKernel 0 := by ext1 x simp [← QuotientAddGroup.mk_zero, ← ofReal_inj, evenKernel_def, cosKernel_def] @[simp] lemma evenKernel_neg (a : UnitAddCircle) (x : ℝ) : evenKernel (-a) x = evenKernel a x := by induction a using QuotientAddGroup.induction_on with | H => simp [← QuotientAddGroup.mk_neg, ← ofReal_inj, evenKernel_def, jacobiTheta₂_neg_left] @[simp] lemma cosKernel_neg (a : UnitAddCircle) (x : ℝ) : cosKernel (-a) x = cosKernel a x := by induction a using QuotientAddGroup.induction_on with | H => simp [← QuotientAddGroup.mk_neg, ← ofReal_inj, cosKernel_def] lemma continuousOn_evenKernel (a : UnitAddCircle) : ContinuousOn (evenKernel a) (Ioi 0) := by induction a using QuotientAddGroup.induction_on with | H a' => apply continuous_re.comp_continuousOn (f := fun x ↦ (evenKernel a' x : ℂ)) simp only [evenKernel_def] refine continuousOn_of_forall_continuousAt (fun x hx ↦ .mul (by fun_prop) ?_) exact (continuousAt_jacobiTheta₂ (a' * I * x) <| by simpa).comp (f := fun u : ℝ ↦ (a' * I * u, I * u)) (by fun_prop) lemma continuousOn_cosKernel (a : UnitAddCircle) : ContinuousOn (cosKernel a) (Ioi 0) := by induction a using QuotientAddGroup.induction_on with | H a' => apply continuous_re.comp_continuousOn (f := fun x ↦ (cosKernel a' x : ℂ)) simp only [cosKernel_def] refine continuousOn_of_forall_continuousAt (fun x hx ↦ ?_) exact (continuousAt_jacobiTheta₂ a' <| by simpa).comp (f := fun u : ℝ ↦ ((a' : ℂ), I * u)) (by fun_prop) lemma evenKernel_functional_equation (a : UnitAddCircle) (x : ℝ) : evenKernel a x = 1 / x ^ (1 / 2 : ℝ) * cosKernel a (1 / x) := by rcases le_or_lt x 0 with hx | hx · rw [evenKernel_undef _ hx, cosKernel_undef, mul_zero] exact div_nonpos_of_nonneg_of_nonpos zero_le_one hx induction a using QuotientAddGroup.induction_on with | H a => rw [← ofReal_inj, ofReal_mul, evenKernel_def, cosKernel_def, jacobiTheta₂_functional_equation] have h1 : I * ↑(1 / x) = -1 / (I * x) := by push_cast rw [← div_div, mul_one_div, div_I, neg_one_mul, neg_neg] have hx' : I * x ≠ 0 := mul_ne_zero I_ne_zero (ofReal_ne_zero.mpr hx.ne') have h2 : a * I * x / (I * x) = a := by rw [div_eq_iff hx'] ring have h3 : 1 / (-I * (I * x)) ^ (1 / 2 : ℂ) = 1 / ↑(x ^ (1 / 2 : ℝ)) := by rw [neg_mul, ← mul_assoc, I_mul_I, neg_one_mul, neg_neg,ofReal_cpow hx.le, ofReal_div, ofReal_one, ofReal_ofNat] have h4 : -π * I * (a * I * x) ^ 2 / (I * x) = - (-π * a ^ 2 * x) := by rw [mul_pow, mul_pow, I_sq, div_eq_iff hx'] ring rw [h1, h2, h3, h4, ← mul_assoc, mul_comm (cexp _), mul_assoc _ (cexp _) (cexp _), ← Complex.exp_add, neg_add_cancel, Complex.exp_zero, mul_one, ofReal_div, ofReal_one] end kernel_defs section asymp /-! ## Formulae for the kernels as sums -/ lemma hasSum_int_evenKernel (a : ℝ) {t : ℝ} (ht : 0 < t) : HasSum (fun n : ℤ ↦ rexp (-π * (n + a) ^ 2 * t)) (evenKernel a t) := by rw [← hasSum_ofReal, evenKernel_def] have (n : ℤ) : cexp (-(π * (n + a) ^ 2 * t)) = cexp (-(π * a ^ 2 * t)) * jacobiTheta₂_term n (a * I * t) (I * t) := by rw [jacobiTheta₂_term, ← Complex.exp_add] ring_nf simp simpa [this] using (hasSum_jacobiTheta₂_term _ (by simpa)).mul_left _ lemma hasSum_int_cosKernel (a : ℝ) {t : ℝ} (ht : 0 < t) : HasSum (fun n : ℤ ↦ cexp (2 * π * I * a * n) * rexp (-π * n ^ 2 * t)) ↑(cosKernel a t) := by rw [cosKernel_def a t] have (n : ℤ) : cexp (2 * π * I * a * n) * cexp (-(π * n ^ 2 * t)) = jacobiTheta₂_term n a (I * ↑t) := by rw [jacobiTheta₂_term, ← Complex.exp_add] ring_nf simp [sub_eq_add_neg] simpa [this] using hasSum_jacobiTheta₂_term _ (by simpa) /-- Modified version of `hasSum_int_evenKernel` omitting the constant term at `∞`. -/ lemma hasSum_int_evenKernel₀ (a : ℝ) {t : ℝ} (ht : 0 < t) : HasSum (fun n : ℤ ↦ if n + a = 0 then 0 else rexp (-π * (n + a) ^ 2 * t)) (evenKernel a t - if (a : UnitAddCircle) = 0 then 1 else 0) := by haveI := Classical.propDecidable -- speed up instance search for `if / then / else` simp_rw [AddCircle.coe_eq_zero_iff, zsmul_one] split_ifs with h · obtain ⟨k, rfl⟩ := h simpa [← Int.cast_add, add_eq_zero_iff_eq_neg] using hasSum_ite_sub_hasSum (hasSum_int_evenKernel (k : ℝ) ht) (-k) · suffices ∀ (n : ℤ), n + a ≠ 0 by simpa [this] using hasSum_int_evenKernel a ht contrapose! h let ⟨n, hn⟩ := h exact ⟨-n, by simpa [neg_eq_iff_add_eq_zero]⟩ lemma hasSum_int_cosKernel₀ (a : ℝ) {t : ℝ} (ht : 0 < t) : HasSum (fun n : ℤ ↦ if n = 0 then 0 else cexp (2 * π * I * a * n) * rexp (-π * n ^ 2 * t)) (↑(cosKernel a t) - 1) := by simpa using hasSum_ite_sub_hasSum (hasSum_int_cosKernel a ht) 0 lemma hasSum_nat_cosKernel₀ (a : ℝ) {t : ℝ} (ht : 0 < t) : HasSum (fun n : ℕ ↦ 2 * Real.cos (2 * π * a * (n + 1)) * rexp (-π * (n + 1) ^ 2 * t)) (cosKernel a t - 1) := by rw [← hasSum_ofReal, ofReal_sub, ofReal_one] have := (hasSum_int_cosKernel a ht).nat_add_neg rw [← hasSum_nat_add_iff' 1] at this simp_rw [Finset.sum_range_one, Nat.cast_zero, neg_zero, Int.cast_zero, zero_pow two_ne_zero, mul_zero, zero_mul, Complex.exp_zero, Real.exp_zero, ofReal_one, mul_one, Int.cast_neg, Int.cast_natCast, neg_sq, ← add_mul, add_sub_assoc, ← sub_sub, sub_self, zero_sub, ← sub_eq_add_neg, mul_neg] at this refine this.congr_fun fun n ↦ ?_ push_cast rw [Complex.cos, mul_div_cancel₀ _ two_ne_zero] congr 3 <;> ring /-! ## Asymptotics of the kernels as `t → ∞` -/ /-- The function `evenKernel a - L` has exponential decay at `+∞`, where `L = 1` if `a = 0` and `L = 0` otherwise. -/ lemma isBigO_atTop_evenKernel_sub (a : UnitAddCircle) : ∃ p : ℝ, 0 < p ∧ (evenKernel a · - (if a = 0 then 1 else 0)) =O[atTop] (rexp <| -p * ·) := by induction a using QuotientAddGroup.induction_on with | H b => obtain ⟨p, hp, hp'⟩ := HurwitzKernelBounds.isBigO_atTop_F_int_zero_sub b refine ⟨p, hp, (EventuallyEq.isBigO ?_).trans hp'⟩ filter_upwards [eventually_gt_atTop 0] with t h simp [← (hasSum_int_evenKernel b h).tsum_eq, HurwitzKernelBounds.F_int, HurwitzKernelBounds.f_int] /-- The function `cosKernel a - 1` has exponential decay at `+∞`, for any `a`. -/ lemma isBigO_atTop_cosKernel_sub (a : UnitAddCircle) : ∃ p, 0 < p ∧ IsBigO atTop (cosKernel a · - 1) (fun x ↦ Real.exp (-p * x)) := by induction a using QuotientAddGroup.induction_on with | H a => obtain ⟨p, hp, hp'⟩ := HurwitzKernelBounds.isBigO_atTop_F_nat_zero_sub zero_le_one refine ⟨p, hp, (Eventually.isBigO ?_).trans (hp'.const_mul_left 2)⟩ filter_upwards [eventually_gt_atTop 0] with t ht simp only [eq_false_intro one_ne_zero, if_false, sub_zero, ← (hasSum_nat_cosKernel₀ a ht).tsum_eq, HurwitzKernelBounds.F_nat] apply tsum_of_norm_bounded ((HurwitzKernelBounds.summable_f_nat 0 1 ht).hasSum.mul_left 2) intro n rw [norm_mul, norm_mul, norm_two, mul_assoc, mul_le_mul_iff_of_pos_left two_pos, norm_of_nonneg (exp_pos _).le, HurwitzKernelBounds.f_nat, pow_zero, one_mul, Real.norm_eq_abs] exact mul_le_of_le_one_left (exp_pos _).le (abs_cos_le_one _) end asymp section FEPair /-! ## Construction of a FE-pair -/ /-- A `WeakFEPair` structure with `f = evenKernel a` and `g = cosKernel a`. -/ def hurwitzEvenFEPair (a : UnitAddCircle) : WeakFEPair ℂ where f := ofReal ∘ evenKernel a g := ofReal ∘ cosKernel a hf_int := (continuous_ofReal.comp_continuousOn (continuousOn_evenKernel a)).locallyIntegrableOn measurableSet_Ioi hg_int := (continuous_ofReal.comp_continuousOn (continuousOn_cosKernel a)).locallyIntegrableOn measurableSet_Ioi k := 1 / 2 hk := one_half_pos ε := 1 hε := one_ne_zero f₀ := if a = 0 then 1 else 0 hf_top r := by let ⟨v, hv, hv'⟩ := isBigO_atTop_evenKernel_sub a rw [← isBigO_norm_left] at hv' ⊢ conv at hv' => enter [2, x]; rw [← norm_real, ofReal_sub, apply_ite ((↑) : ℝ → ℂ), ofReal_one, ofReal_zero] exact hv'.trans (isLittleO_exp_neg_mul_rpow_atTop hv _).isBigO g₀ := 1 hg_top r := by obtain ⟨p, hp, hp'⟩ := isBigO_atTop_cosKernel_sub a simpa using isBigO_ofReal_left.mpr <| hp'.trans (isLittleO_exp_neg_mul_rpow_atTop hp r).isBigO h_feq x hx := by simp [← ofReal_mul, evenKernel_functional_equation, inv_rpow (le_of_lt hx)] @[simp] lemma hurwitzEvenFEPair_zero_symm : (hurwitzEvenFEPair 0).symm = hurwitzEvenFEPair 0 := by unfold hurwitzEvenFEPair WeakFEPair.symm congr 1 <;> simp [evenKernel_eq_cosKernel_of_zero] @[simp] lemma hurwitzEvenFEPair_neg (a : UnitAddCircle) : hurwitzEvenFEPair (-a) = hurwitzEvenFEPair a := by unfold hurwitzEvenFEPair congr 1 <;> simp [Function.comp_def] /-! ## Definition of the completed even Hurwitz zeta function -/ /-- The meromorphic function of `s` which agrees with `1 / 2 * Gamma (s / 2) * π ^ (-s / 2) * ∑' (n : ℤ), 1 / |n + a| ^ s` for `1 < re s`. -/ def completedHurwitzZetaEven (a : UnitAddCircle) (s : ℂ) : ℂ := ((hurwitzEvenFEPair a).Λ (s / 2)) / 2 /-- The entire function differing from `completedHurwitzZetaEven a s` by a linear combination of `1 / s` and `1 / (1 - s)`. -/ def completedHurwitzZetaEven₀ (a : UnitAddCircle) (s : ℂ) : ℂ := ((hurwitzEvenFEPair a).Λ₀ (s / 2)) / 2 lemma completedHurwitzZetaEven_eq (a : UnitAddCircle) (s : ℂ) : completedHurwitzZetaEven a s = completedHurwitzZetaEven₀ a s - (if a = 0 then 1 else 0) / s - 1 / (1 - s) := by rw [completedHurwitzZetaEven, WeakFEPair.Λ, sub_div, sub_div] congr 1 · change completedHurwitzZetaEven₀ a s - (1 / (s / 2)) • (if a = 0 then 1 else 0) / 2 = completedHurwitzZetaEven₀ a s - (if a = 0 then 1 else 0) / s rw [smul_eq_mul, mul_comm, mul_div_assoc, div_div, div_mul_cancel₀ _ two_ne_zero, mul_one_div] · change (1 / (↑(1 / 2 : ℝ) - s / 2)) • 1 / 2 = 1 / (1 - s) push_cast rw [smul_eq_mul, mul_one, ← sub_div, div_div, div_mul_cancel₀ _ two_ne_zero] /-- The meromorphic function of `s` which agrees with `Gamma (s / 2) * π ^ (-s / 2) * ∑' n : ℕ, cos (2 * π * a * n) / n ^ s` for `1 < re s`. -/ def completedCosZeta (a : UnitAddCircle) (s : ℂ) : ℂ := ((hurwitzEvenFEPair a).symm.Λ (s / 2)) / 2 /-- The entire function differing from `completedCosZeta a s` by a linear combination of `1 / s` and `1 / (1 - s)`. -/ def completedCosZeta₀ (a : UnitAddCircle) (s : ℂ) : ℂ := ((hurwitzEvenFEPair a).symm.Λ₀ (s / 2)) / 2 lemma completedCosZeta_eq (a : UnitAddCircle) (s : ℂ) : completedCosZeta a s = completedCosZeta₀ a s - 1 / s - (if a = 0 then 1 else 0) / (1 - s) := by rw [completedCosZeta, WeakFEPair.Λ, sub_div, sub_div] congr 1 · rw [completedCosZeta₀, WeakFEPair.symm, hurwitzEvenFEPair, smul_eq_mul, mul_one, div_div, div_mul_cancel₀ _ (two_ne_zero' ℂ)] · simp_rw [WeakFEPair.symm, hurwitzEvenFEPair, push_cast, inv_one, smul_eq_mul, mul_comm _ (if _ then _ else _), mul_div_assoc, div_div, ← sub_div, div_mul_cancel₀ _ (two_ne_zero' ℂ), mul_one_div] /-! ## Parity and functional equations -/ @[simp] lemma completedHurwitzZetaEven_neg (a : UnitAddCircle) (s : ℂ) : completedHurwitzZetaEven (-a) s = completedHurwitzZetaEven a s := by simp [completedHurwitzZetaEven] @[simp] lemma completedHurwitzZetaEven₀_neg (a : UnitAddCircle) (s : ℂ) : completedHurwitzZetaEven₀ (-a) s = completedHurwitzZetaEven₀ a s := by simp [completedHurwitzZetaEven₀] @[simp] lemma completedCosZeta_neg (a : UnitAddCircle) (s : ℂ) : completedCosZeta (-a) s = completedCosZeta a s := by simp [completedCosZeta] @[simp] lemma completedCosZeta₀_neg (a : UnitAddCircle) (s : ℂ) : completedCosZeta₀ (-a) s = completedCosZeta₀ a s := by simp [completedCosZeta₀] /-- Functional equation for the even Hurwitz zeta function. -/ lemma completedHurwitzZetaEven_one_sub (a : UnitAddCircle) (s : ℂ) : completedHurwitzZetaEven a (1 - s) = completedCosZeta a s := by rw [completedHurwitzZetaEven, completedCosZeta, sub_div, (by norm_num : (1 / 2 : ℂ) = ↑(1 / 2 : ℝ)), (by rfl : (1 / 2 : ℝ) = (hurwitzEvenFEPair a).k), (hurwitzEvenFEPair a).functional_equation (s / 2), (by rfl : (hurwitzEvenFEPair a).ε = 1), one_smul] /-- Functional equation for the even Hurwitz zeta function with poles removed. -/ lemma completedHurwitzZetaEven₀_one_sub (a : UnitAddCircle) (s : ℂ) : completedHurwitzZetaEven₀ a (1 - s) = completedCosZeta₀ a s := by rw [completedHurwitzZetaEven₀, completedCosZeta₀, sub_div, (by norm_num : (1 / 2 : ℂ) = ↑(1 / 2 : ℝ)), (by rfl : (1 / 2 : ℝ) = (hurwitzEvenFEPair a).k), (hurwitzEvenFEPair a).functional_equation₀ (s / 2), (by rfl : (hurwitzEvenFEPair a).ε = 1), one_smul] /-- Functional equation for the even Hurwitz zeta function (alternative form). -/ lemma completedCosZeta_one_sub (a : UnitAddCircle) (s : ℂ) : completedCosZeta a (1 - s) = completedHurwitzZetaEven a s := by rw [← completedHurwitzZetaEven_one_sub, sub_sub_cancel] /-- Functional equation for the even Hurwitz zeta function with poles removed (alternative form). -/ lemma completedCosZeta₀_one_sub (a : UnitAddCircle) (s : ℂ) : completedCosZeta₀ a (1 - s) = completedHurwitzZetaEven₀ a s := by rw [← completedHurwitzZetaEven₀_one_sub, sub_sub_cancel] end FEPair /-! ## Differentiability and residues -/ section FEPair /-- The even Hurwitz completed zeta is differentiable away from `s = 0` and `s = 1` (and also at `s = 0` if `a ≠ 0`) -/ lemma differentiableAt_completedHurwitzZetaEven (a : UnitAddCircle) {s : ℂ} (hs : s ≠ 0 ∨ a ≠ 0) (hs' : s ≠ 1) : DifferentiableAt ℂ (completedHurwitzZetaEven a) s := by refine (((hurwitzEvenFEPair a).differentiableAt_Λ ?_ (Or.inl ?_)).comp s (differentiableAt_id.div_const _)).div_const _ · rcases hs with h | h <;> simp [hurwitzEvenFEPair, h] · change s / 2 ≠ ↑(1 / 2 : ℝ) rw [ofReal_div, ofReal_one, ofReal_ofNat] exact hs' ∘ (div_left_inj' two_ne_zero).mp lemma differentiable_completedHurwitzZetaEven₀ (a : UnitAddCircle) : Differentiable ℂ (completedHurwitzZetaEven₀ a) := ((hurwitzEvenFEPair a).differentiable_Λ₀.comp (differentiable_id.div_const _)).div_const _ /-- The difference of two completed even Hurwitz zeta functions is differentiable at `s = 1`. -/ lemma differentiableAt_one_completedHurwitzZetaEven_sub_completedHurwitzZetaEven (a b : UnitAddCircle) : DifferentiableAt ℂ (fun s ↦ completedHurwitzZetaEven a s - completedHurwitzZetaEven b s) 1 := by have (s) : completedHurwitzZetaEven a s - completedHurwitzZetaEven b s = completedHurwitzZetaEven₀ a s - completedHurwitzZetaEven₀ b s - ((if a = 0 then 1 else 0) - (if b = 0 then 1 else 0)) / s := by simp_rw [completedHurwitzZetaEven_eq, sub_div] abel rw [funext this] refine .sub ?_ <| (differentiable_const _ _).div (differentiable_id _) one_ne_zero apply DifferentiableAt.sub <;> apply differentiable_completedHurwitzZetaEven₀ lemma differentiableAt_completedCosZeta (a : UnitAddCircle) {s : ℂ} (hs : s ≠ 0) (hs' : s ≠ 1 ∨ a ≠ 0) : DifferentiableAt ℂ (completedCosZeta a) s := by refine (((hurwitzEvenFEPair a).symm.differentiableAt_Λ (Or.inl ?_) ?_).comp s (differentiableAt_id.div_const _)).div_const _ · exact div_ne_zero_iff.mpr ⟨hs, two_ne_zero⟩ · change s / 2 ≠ ↑(1 / 2 : ℝ) ∨ (if a = 0 then 1 else 0) = 0 refine Or.imp (fun h ↦ ?_) (fun ha ↦ ?_) hs' · simpa [push_cast] using h ∘ (div_left_inj' two_ne_zero).mp · simpa lemma differentiable_completedCosZeta₀ (a : UnitAddCircle) : Differentiable ℂ (completedCosZeta₀ a) := ((hurwitzEvenFEPair a).symm.differentiable_Λ₀.comp (differentiable_id.div_const _)).div_const _ private lemma tendsto_div_two_punctured_nhds (a : ℂ) : Tendsto (fun s : ℂ ↦ s / 2) (𝓝[≠] a) (𝓝[≠] (a / 2)) := le_of_eq ((Homeomorph.mulRight₀ _ (inv_ne_zero (two_ne_zero' ℂ))).map_punctured_nhds_eq a) /-- The residue of `completedHurwitzZetaEven a s` at `s = 1` is equal to `1`. -/ lemma completedHurwitzZetaEven_residue_one (a : UnitAddCircle) : Tendsto (fun s ↦ (s - 1) * completedHurwitzZetaEven a s) (𝓝[≠] 1) (𝓝 1) := by have h1 : Tendsto (fun s : ℂ ↦ (s - ↑(1 / 2 : ℝ)) * _) (𝓝[≠] ↑(1 / 2 : ℝ)) (𝓝 ((1 : ℂ) * (1 : ℂ))) := (hurwitzEvenFEPair a).Λ_residue_k simp only [push_cast, one_mul] at h1 refine (h1.comp <| tendsto_div_two_punctured_nhds 1).congr (fun s ↦ ?_) rw [completedHurwitzZetaEven, Function.comp_apply, ← sub_div, div_mul_eq_mul_div, mul_div_assoc] /-- The residue of `completedHurwitzZetaEven a s` at `s = 0` is equal to `-1` if `a = 0`, and `0` otherwise. -/ lemma completedHurwitzZetaEven_residue_zero (a : UnitAddCircle) : Tendsto (fun s ↦ s * completedHurwitzZetaEven a s) (𝓝[≠] 0) (𝓝 (if a = 0 then -1 else 0)) := by have h1 : Tendsto (fun s : ℂ ↦ s * _) (𝓝[≠] 0) (𝓝 (-(if a = 0 then 1 else 0))) := (hurwitzEvenFEPair a).Λ_residue_zero have : -(if a = 0 then (1 : ℂ) else 0) = (if a = 0 then -1 else 0) := by { split_ifs <;> simp } simp only [this, push_cast, one_mul] at h1 refine (h1.comp <| zero_div (2 : ℂ) ▸ (tendsto_div_two_punctured_nhds 0)).congr (fun s ↦ ?_) simp [completedHurwitzZetaEven, div_mul_eq_mul_div, mul_div_assoc] lemma completedCosZeta_residue_zero (a : UnitAddCircle) :
Tendsto (fun s ↦ s * completedCosZeta a s) (𝓝[≠] 0) (𝓝 (-1)) := by have h1 : Tendsto (fun s : ℂ ↦ s * _) (𝓝[≠] 0) (𝓝 (-1)) := (hurwitzEvenFEPair a).symm.Λ_residue_zero refine (h1.comp <| zero_div (2 : ℂ) ▸ (tendsto_div_two_punctured_nhds 0)).congr (fun s ↦ ?_) simp [completedCosZeta, div_mul_eq_mul_div, mul_div_assoc] end FEPair
Mathlib/NumberTheory/LSeries/HurwitzZetaEven.lean
471
478
/- Copyright (c) 2021 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov, Alex Kontorovich -/ import Mathlib.Data.Set.Piecewise import Mathlib.Order.Filter.Tendsto import Mathlib.Order.Filter.Bases.Finite /-! # (Co)product of a family of filters In this file we define two filters on `Π i, α i` and prove some basic properties of these filters. * `Filter.pi (f : Π i, Filter (α i))` to be the maximal filter on `Π i, α i` such that `∀ i, Filter.Tendsto (Function.eval i) (Filter.pi f) (f i)`. It is defined as `Π i, Filter.comap (Function.eval i) (f i)`. This is a generalization of `Filter.prod` to indexed products. * `Filter.coprodᵢ (f : Π i, Filter (α i))`: a generalization of `Filter.coprod`; it is the supremum of `comap (eval i) (f i)`. -/ open Set Function Filter namespace Filter variable {ι : Type*} {α : ι → Type*} {f f₁ f₂ : (i : ι) → Filter (α i)} {s : (i : ι) → Set (α i)} {p : ∀ i, α i → Prop} section Pi theorem tendsto_eval_pi (f : ∀ i, Filter (α i)) (i : ι) : Tendsto (eval i) (pi f) (f i) := tendsto_iInf' i tendsto_comap theorem tendsto_pi {β : Type*} {m : β → ∀ i, α i} {l : Filter β} : Tendsto m l (pi f) ↔ ∀ i, Tendsto (fun x => m x i) l (f i) := by simp only [pi, tendsto_iInf, tendsto_comap_iff]; rfl /-- If a function tends to a product `Filter.pi f` of filters, then its `i`-th component tends to `f i`. See also `Filter.Tendsto.apply_nhds` for the special case of converging to a point in a product of topological spaces. -/ alias ⟨Tendsto.apply, _⟩ := tendsto_pi theorem le_pi {g : Filter (∀ i, α i)} : g ≤ pi f ↔ ∀ i, Tendsto (eval i) g (f i) := tendsto_pi @[mono] theorem pi_mono (h : ∀ i, f₁ i ≤ f₂ i) : pi f₁ ≤ pi f₂ := iInf_mono fun i => comap_mono <| h i theorem mem_pi_of_mem (i : ι) {s : Set (α i)} (hs : s ∈ f i) : eval i ⁻¹' s ∈ pi f := mem_iInf_of_mem i <| preimage_mem_comap hs theorem pi_mem_pi {I : Set ι} (hI : I.Finite) (h : ∀ i ∈ I, s i ∈ f i) : I.pi s ∈ pi f := by rw [pi_def, biInter_eq_iInter] refine mem_iInf_of_iInter hI (fun i => ?_) Subset.rfl exact preimage_mem_comap (h i i.2) theorem mem_pi {s : Set (∀ i, α i)} : s ∈ pi f ↔ ∃ I : Set ι, I.Finite ∧ ∃ t : ∀ i, Set (α i), (∀ i, t i ∈ f i) ∧ I.pi t ⊆ s := by constructor · simp only [pi, mem_iInf', mem_comap, pi_def] rintro ⟨I, If, V, hVf, -, rfl, -⟩ choose t htf htV using hVf exact ⟨I, If, t, htf, iInter₂_mono fun i _ => htV i⟩ · rintro ⟨I, If, t, htf, hts⟩ exact mem_of_superset (pi_mem_pi If fun i _ => htf i) hts theorem mem_pi' {s : Set (∀ i, α i)} : s ∈ pi f ↔ ∃ I : Finset ι, ∃ t : ∀ i, Set (α i), (∀ i, t i ∈ f i) ∧ Set.pi (↑I) t ⊆ s := mem_pi.trans exists_finite_iff_finset theorem mem_of_pi_mem_pi [∀ i, NeBot (f i)] {I : Set ι} (h : I.pi s ∈ pi f) {i : ι} (hi : i ∈ I) : s i ∈ f i := by classical rcases mem_pi.1 h with ⟨I', -, t, htf, hts⟩ refine mem_of_superset (htf i) fun x hx => ?_ have : ∀ i, (t i).Nonempty := fun i => nonempty_of_mem (htf i) choose g hg using this have : update g i x ∈ I'.pi t := fun j _ => by rcases eq_or_ne j i with (rfl | hne) <;> simp [*] simpa using hts this i hi @[simp] theorem pi_mem_pi_iff [∀ i, NeBot (f i)] {I : Set ι} (hI : I.Finite) : I.pi s ∈ pi f ↔ ∀ i ∈ I, s i ∈ f i := ⟨fun h _i hi => mem_of_pi_mem_pi h hi, pi_mem_pi hI⟩ theorem Eventually.eval_pi {i : ι} (hf : ∀ᶠ x : α i in f i, p i x) : ∀ᶠ x : ∀ i : ι, α i in pi f, p i (x i) := (tendsto_eval_pi _ _).eventually hf theorem eventually_pi [Finite ι] (hf : ∀ i, ∀ᶠ x in f i, p i x) : ∀ᶠ x : ∀ i, α i in pi f, ∀ i, p i (x i) := eventually_all.2 fun _i => (hf _).eval_pi theorem hasBasis_pi {ι' : ι → Type*} {s : ∀ i, ι' i → Set (α i)} {p : ∀ i, ι' i → Prop} (h : ∀ i, (f i).HasBasis (p i) (s i)) : (pi f).HasBasis (fun If : Set ι × ∀ i, ι' i => If.1.Finite ∧ ∀ i ∈ If.1, p i (If.2 i)) fun If : Set ι × ∀ i, ι' i => If.1.pi fun i => s i <| If.2 i := by simpa [Set.pi_def] using hasBasis_iInf' fun i => (h i).comap (eval i : (∀ j, α j) → α i) theorem hasBasis_pi_same_index {κ : Type*} {p : κ → Prop} {s : Π i : ι, κ → Set (α i)} (h : ∀ i : ι, (f i).HasBasis p (s i)) (h_dir : ∀ I : Set ι, ∀ k : ι → κ, I.Finite → (∀ i ∈ I, p (k i)) → ∃ k₀, p k₀ ∧ ∀ i ∈ I, s i k₀ ⊆ s i (k i)) : (pi f).HasBasis (fun Ik : Set ι × κ ↦ Ik.1.Finite ∧ p Ik.2) (fun Ik ↦ Ik.1.pi (fun i ↦ s i Ik.2)) := by refine hasBasis_pi h |>.to_hasBasis ?_ ?_ · rintro ⟨I, k⟩ ⟨hI, hk⟩ rcases h_dir I k hI hk with ⟨k₀, hk₀, hk₀'⟩ exact ⟨⟨I, k₀⟩, ⟨hI, hk₀⟩, Set.pi_mono hk₀'⟩ · rintro ⟨I, k⟩ ⟨hI, hk⟩ exact ⟨⟨I, fun _ ↦ k⟩, ⟨hI, fun _ _ ↦ hk⟩, subset_rfl⟩ theorem HasBasis.pi_self {α : Type*} {κ : Type*} {f : Filter α} {p : κ → Prop} {s : κ → Set α} (h : f.HasBasis p s) : (pi fun _ ↦ f).HasBasis (fun Ik : Set ι × κ ↦ Ik.1.Finite ∧ p Ik.2) (fun Ik ↦ Ik.1.pi (fun _ ↦ s Ik.2)) := by refine hasBasis_pi_same_index (fun _ ↦ h) (fun I k hI hk ↦ ?_) rcases h.mem_iff.mp (biInter_mem hI |>.mpr fun i hi ↦ h.mem_of_mem (hk i hi)) with ⟨k₀, hk₀, hk₀'⟩ exact ⟨k₀, hk₀, fun i hi ↦ hk₀'.trans (biInter_subset_of_mem hi)⟩ theorem le_pi_principal (s : (i : ι) → Set (α i)) : 𝓟 (univ.pi s) ≤ pi fun i ↦ 𝓟 (s i) := le_pi.2 fun i ↦ tendsto_principal_principal.2 fun _f hf ↦ hf i trivial /-- The indexed product of finitely many principal filters is the principal filter corresponding to the cylinder `Set.univ.pi s`. If the index type is infinite, then `mem_pi_principal` and `hasBasis_pi_principal` may be useful. -/ @[simp] theorem pi_principal [Finite ι] (s : (i : ι) → Set (α i)) : pi (fun i ↦ 𝓟 (s i)) = 𝓟 (univ.pi s) := by simp [Filter.pi, Set.pi_def]
/-- The indexed product of a (possibly, infinite) family of principal filters is generated by the finite `Set.pi` cylinders.
Mathlib/Order/Filter/Pi.lean
138
139
/- Copyright (c) 2024 Antoine Chambert-Loir. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Chambert-Loir -/ import Mathlib.LinearAlgebra.DirectSum.Finsupp import Mathlib.Algebra.MvPolynomial.Eval import Mathlib.RingTheory.TensorProduct.Basic import Mathlib.Algebra.MvPolynomial.Equiv import Mathlib.RingTheory.IsTensorProduct /-! # Tensor Product of (multivariate) polynomial rings Let `Semiring R`, `Algebra R S` and `Module R N`. * `MvPolynomial.rTensor` gives the linear equivalence `MvPolynomial σ S ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ (S ⊗[R] N)` characterized, for `p : MvPolynomial σ S`, `n : N` and `d : σ →₀ ℕ`, by `rTensor (p ⊗ₜ[R] n) d = (coeff d p) ⊗ₜ[R] n` * `MvPolynomial.scalarRTensor` gives the linear equivalence `MvPolynomial σ R ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ N` such that `MvPolynomial.scalarRTensor (p ⊗ₜ[R] n) d = coeff d p • n` for `p : MvPolynomial σ R`, `n : N` and `d : σ →₀ ℕ`, by * `MvPolynomial.rTensorAlgHom`, the algebra morphism from the tensor product of a polynomial algebra by an algebra to a polynomial algebra * `MvPolynomial.rTensorAlgEquiv`, `MvPolynomial.scalarRTensorAlgEquiv`, the tensor product of a polynomial algebra by an algebra is algebraically equivalent to a polynomial algebra ## TODO : * `MvPolynomial.rTensor` could be phrased in terms of `AddMonoidAlgebra`, and `MvPolynomial.rTensor` then has `smul` by the polynomial algebra. * `MvPolynomial.rTensorAlgHom` and `MvPolynomial.scalarRTensorAlgEquiv` are morphisms for the algebra structure by `MvPolynomial σ R`. -/ universe u v noncomputable section namespace MvPolynomial open DirectSum TensorProduct open Set LinearMap Submodule variable {R : Type u} {N : Type v} [CommSemiring R] variable {σ : Type*} variable {S : Type*} [CommSemiring S] [Algebra R S] section Module variable [DecidableEq σ] variable [AddCommMonoid N] [Module R N] /-- The tensor product of a polynomial ring by a module is linearly equivalent to a Finsupp of a tensor product -/ noncomputable def rTensor : MvPolynomial σ S ⊗[R] N ≃ₗ[S] (σ →₀ ℕ) →₀ (S ⊗[R] N) := TensorProduct.finsuppLeft' _ _ _ _ _ lemma rTensor_apply_tmul (p : MvPolynomial σ S) (n : N) : rTensor (p ⊗ₜ[R] n) = p.sum (fun i m ↦ Finsupp.single i (m ⊗ₜ[R] n)) := TensorProduct.finsuppLeft_apply_tmul p n lemma rTensor_apply_tmul_apply (p : MvPolynomial σ S) (n : N) (d : σ →₀ ℕ) : rTensor (p ⊗ₜ[R] n) d = (coeff d p) ⊗ₜ[R] n :=
TensorProduct.finsuppLeft_apply_tmul_apply p n d lemma rTensor_apply_monomial_tmul (e : σ →₀ ℕ) (s : S) (n : N) (d : σ →₀ ℕ) :
Mathlib/RingTheory/TensorProduct/MvPolynomial.lean
75
77
/- Copyright (c) 2024 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou -/ import Mathlib.CategoryTheory.Limits.Shapes.Products import Mathlib.CategoryTheory.Limits.Shapes.Pullback.CommSq import Mathlib.CategoryTheory.Limits.Shapes.Pullback.HasPullback import Mathlib.AlgebraicTopology.RelativeCellComplex.AttachCells /-! # Construction for the small object argument Given a family of morphisms `f i : A i ⟶ B i` in a category `C`, we define a functor `SmallObject.functor f : Arrow S ⥤ Arrow S` which sends an object given by arrow `πX : X ⟶ S` to the pushout `functorObj f πX`: ``` ∐ functorObjSrcFamily f πX ⟶ X | | | | v v ∐ functorObjTgtFamily f πX ⟶ functorObj f πX ``` where the morphism on the left is a coproduct (of copies of maps `f i`) indexed by a type `FunctorObjIndex f πX` which parametrizes the diagrams of the form ``` A i ⟶ X | | | | v v B i ⟶ S ``` The morphism `ιFunctorObj f πX : X ⟶ functorObj f πX` is part of a natural transformation `SmallObject.ε f : 𝟭 (Arrow C) ⟶ functor f S`. The main idea in this construction is that for any commutative square as above, there may not exist a lifting `B i ⟶ X`, but the construction provides a tautological morphism `B i ⟶ functorObj f πX` (see `SmallObject.ιFunctorObj_extension`). ## References - https://ncatlab.org/nlab/show/small+object+argument -/ universe t w v u namespace CategoryTheory open Category Limits HomotopicalAlgebra namespace SmallObject variable {C : Type u} [Category.{v} C] {I : Type w} {A B : I → C} (f : ∀ i, A i ⟶ B i) section variable {S X : C} (πX : X ⟶ S) /-- Given a family of morphisms `f i : A i ⟶ B i` and a morphism `πX : X ⟶ S`, this type parametrizes the commutative squares with a morphism `f i` on the left and `πX` in the right. -/ structure FunctorObjIndex where /-- an element in the index type -/ i : I /-- the top morphism in the square -/ t : A i ⟶ X /-- the bottom morphism in the square -/ b : B i ⟶ S w : t ≫ πX = f i ≫ b attribute [reassoc (attr := simp)] FunctorObjIndex.w variable [HasColimitsOfShape (Discrete (FunctorObjIndex f πX)) C] /-- The family of objects `A x.i` parametrized by `x : FunctorObjIndex f πX`. -/ abbrev functorObjSrcFamily (x : FunctorObjIndex f πX) : C := A x.i /-- The family of objects `B x.i` parametrized by `x : FunctorObjIndex f πX`. -/ abbrev functorObjTgtFamily (x : FunctorObjIndex f πX) : C := B x.i /-- The family of the morphisms `f x.i : A x.i ⟶ B x.i` parametrized by `x : FunctorObjIndex f πX`. -/ abbrev functorObjLeftFamily (x : FunctorObjIndex f πX) : functorObjSrcFamily f πX x ⟶ functorObjTgtFamily f πX x := f x.i /-- The top morphism in the pushout square in the definition of `pushoutObj f πX`. -/ noncomputable abbrev functorObjTop : ∐ functorObjSrcFamily f πX ⟶ X := Limits.Sigma.desc (fun x => x.t) /-- The left morphism in the pushout square in the definition of `pushoutObj f πX`. -/ noncomputable abbrev functorObjLeft : ∐ functorObjSrcFamily f πX ⟶ ∐ functorObjTgtFamily f πX := Limits.Sigma.map (functorObjLeftFamily f πX) variable [HasPushout (functorObjTop f πX) (functorObjLeft f πX)] /-- The functor `SmallObject.functor f : Arrow C ⥤ Arrow C` that is part of the small object argument for a family of morphisms `f`, on an object given as a morphism `πX : X ⟶ S`. -/ noncomputable abbrev functorObj : C := pushout (functorObjTop f πX) (functorObjLeft f πX) /-- The canonical morphism `X ⟶ functorObj f πX`. -/ noncomputable abbrev ιFunctorObj : X ⟶ functorObj f πX := pushout.inl _ _ /-- The canonical morphism `∐ (functorObjTgtFamily f πX) ⟶ functorObj f πX`. -/ noncomputable abbrev ρFunctorObj : ∐ functorObjTgtFamily f πX ⟶ functorObj f πX := pushout.inr _ _ @[reassoc] lemma functorObj_comm : functorObjTop f πX ≫ ιFunctorObj f πX = functorObjLeft f πX ≫ ρFunctorObj f πX := pushout.condition lemma functorObj_isPushout : IsPushout (functorObjTop f πX) (functorObjLeft f πX) (ιFunctorObj f πX) (ρFunctorObj f πX) := IsPushout.of_hasPushout _ _ @[reassoc] lemma FunctorObjIndex.comm (x : FunctorObjIndex f πX) : f x.i ≫ Sigma.ι (functorObjTgtFamily f πX) x ≫ ρFunctorObj f πX = x.t ≫ ιFunctorObj f πX := by simpa using (Sigma.ι (functorObjSrcFamily f πX) x ≫= functorObj_comm f πX).symm /-- The canonical projection on the base object. -/ noncomputable abbrev π'FunctorObj : ∐ functorObjTgtFamily f πX ⟶ S := Sigma.desc (fun x => x.b) /-- The canonical projection on the base object. -/ noncomputable def πFunctorObj : functorObj f πX ⟶ S := pushout.desc πX (π'FunctorObj f πX) (by ext; simp [π'FunctorObj]) @[reassoc (attr := simp)] lemma ρFunctorObj_π : ρFunctorObj f πX ≫ πFunctorObj f πX = π'FunctorObj f πX := by simp [πFunctorObj] @[reassoc (attr := simp)] lemma ιFunctorObj_πFunctorObj : ιFunctorObj f πX ≫ πFunctorObj f πX = πX := by simp [ιFunctorObj, πFunctorObj] /-- The morphism `ιFunctorObj f πX : X ⟶ functorObj f πX` is obtained by attaching `f`-cells. -/ @[simps] noncomputable def attachCellsιFunctorObj : AttachCells.{max v w} f (ιFunctorObj f πX) where ι := FunctorObjIndex f πX π x := x.i isColimit₁ := coproductIsCoproduct _ isColimit₂ := coproductIsCoproduct _ m := functorObjLeft f πX g₁ := functorObjTop f πX g₂ := ρFunctorObj f πX isPushout := IsPushout.of_hasPushout (functorObjTop f πX) (functorObjLeft f πX) cofan₁ := _ cofan₂ := _ section Small variable [LocallySmall.{t} C] [Small.{t} I] instance : Small.{t} (FunctorObjIndex f πX) := by let φ (x : FunctorObjIndex f πX) : Σ (i : Shrink.{t} I), Shrink.{t} ((A ((equivShrink _).symm i) ⟶ X) × (B ((equivShrink _).symm i) ⟶ S)) := ⟨equivShrink _ x.i, equivShrink _ ⟨eqToHom (by simp) ≫ x.t, eqToHom (by simp) ≫ x.b⟩⟩ have hφ : Function.Injective φ := by rintro ⟨i₁, t₁, b₁, _⟩ ⟨i₂, t₂, b₂, _⟩ h obtain rfl : i₁ = i₂ := by simpa [φ] using congr_arg Sigma.fst h simpa [cancel_epi, φ] using h exact small_of_injective hφ instance : Small.{t} (attachCellsιFunctorObj f πX).ι := by dsimp infer_instance /-- The morphism `ιFunctorObj f πX : X ⟶ functorObj f πX` is obtained by attaching `f`-cells, and the index type can be chosen to be in `Type t` if the category is `t`-locally small and the index type for `f` is `t`-small. -/ noncomputable def attachCellsιFunctorObjOfSmall : AttachCells.{t} f (ιFunctorObj f πX) := (attachCellsιFunctorObj f πX).reindex (equivShrink.{t} _).symm end Small section variable {S T X Y : C} {πX : X ⟶ S} {πY : Y ⟶ T} (τ : Arrow.mk πX ⟶ Arrow.mk πY) [HasColimitsOfShape (Discrete (FunctorObjIndex f πX)) C] [HasColimitsOfShape (Discrete (FunctorObjIndex f πY)) C] /-- The canonical morphism `∐ (functorObjSrcFamily f πX) ⟶ ∐ (functorObjSrcFamily f πY)` induced by a morphism `Arrow.mk πX ⟶ Arrow.mk πY`. -/ noncomputable def functorMapSrc : ∐ (functorObjSrcFamily f πX) ⟶ ∐ functorObjSrcFamily f πY := Sigma.map' (fun x => FunctorObjIndex.mk x.i (x.t ≫ τ.left) (x.b ≫ τ.right) (by simp)) (fun _ => 𝟙 _)
@[reassoc] lemma ι_functorMapSrc (i : I) (t : A i ⟶ X) (b : B i ⟶ S) (w : t ≫ πX = f i ≫ b) (b' : B i ⟶ T) (hb' : b ≫ τ.right = b') (t' : A i ⟶ Y) (ht' : t ≫ τ.left = t') :
Mathlib/CategoryTheory/SmallObject/Construction.lean
201
205
/- Copyright (c) 2020 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne, Sébastien Gouëzel -/ import Mathlib.Analysis.NormedSpace.IndicatorFunction import Mathlib.Data.Fintype.Order import Mathlib.MeasureTheory.Function.AEEqFun import Mathlib.MeasureTheory.Function.LpSeminorm.Defs import Mathlib.MeasureTheory.Function.SpecialFunctions.Basic import Mathlib.MeasureTheory.Integral.Lebesgue.Countable import Mathlib.MeasureTheory.Integral.Lebesgue.Sub /-! # Basic theorems about ℒp space -/ noncomputable section open TopologicalSpace MeasureTheory Filter open scoped NNReal ENNReal Topology ComplexConjugate variable {α ε ε' E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α} [NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G] [ENorm ε] [ENorm ε'] namespace MeasureTheory section Lp section Top theorem MemLp.eLpNorm_lt_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) : eLpNorm f p μ < ∞ := hfp.2 @[deprecated (since := "2025-02-21")] alias Memℒp.eLpNorm_lt_top := MemLp.eLpNorm_lt_top theorem MemLp.eLpNorm_ne_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) : eLpNorm f p μ ≠ ∞ := ne_of_lt hfp.2 @[deprecated (since := "2025-02-21")] alias Memℒp.eLpNorm_ne_top := MemLp.eLpNorm_ne_top theorem lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top {f : α → ε} (hq0_lt : 0 < q) (hfq : eLpNorm' f q μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ q ∂μ < ∞ := by rw [lintegral_rpow_enorm_eq_rpow_eLpNorm' hq0_lt] exact ENNReal.rpow_lt_top_of_nonneg (le_of_lt hq0_lt) (ne_of_lt hfq) @[deprecated (since := "2025-01-17")] alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm'_lt_top' := lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top theorem lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) (hfp : eLpNorm f p μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ p.toReal ∂μ < ∞ := by apply lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top · exact ENNReal.toReal_pos hp_ne_zero hp_ne_top · simpa [eLpNorm_eq_eLpNorm' hp_ne_zero hp_ne_top] using hfp @[deprecated (since := "2025-01-17")] alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm_lt_top := lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top theorem eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) : eLpNorm f p μ < ∞ ↔ ∫⁻ a, (‖f a‖ₑ) ^ p.toReal ∂μ < ∞ := ⟨lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top hp_ne_zero hp_ne_top, by intro h have hp' := ENNReal.toReal_pos hp_ne_zero hp_ne_top have : 0 < 1 / p.toReal := div_pos zero_lt_one hp' simpa [eLpNorm_eq_lintegral_rpow_enorm hp_ne_zero hp_ne_top] using ENNReal.rpow_lt_top_of_nonneg (le_of_lt this) (ne_of_lt h)⟩ @[deprecated (since := "2025-02-04")] alias eLpNorm_lt_top_iff_lintegral_rpow_nnnorm_lt_top := eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top end Top section Zero @[simp] theorem eLpNorm'_exponent_zero {f : α → ε} : eLpNorm' f 0 μ = 1 := by rw [eLpNorm', div_zero, ENNReal.rpow_zero] @[simp] theorem eLpNorm_exponent_zero {f : α → ε} : eLpNorm f 0 μ = 0 := by simp [eLpNorm] @[simp] theorem memLp_zero_iff_aestronglyMeasurable [TopologicalSpace ε] {f : α → ε} : MemLp f 0 μ ↔ AEStronglyMeasurable f μ := by simp [MemLp, eLpNorm_exponent_zero] @[deprecated (since := "2025-02-21")] alias memℒp_zero_iff_aestronglyMeasurable := memLp_zero_iff_aestronglyMeasurable section ENormedAddMonoid variable {ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε] @[simp] theorem eLpNorm'_zero (hp0_lt : 0 < q) : eLpNorm' (0 : α → ε) q μ = 0 := by simp [eLpNorm'_eq_lintegral_enorm, hp0_lt] @[simp] theorem eLpNorm'_zero' (hq0_ne : q ≠ 0) (hμ : μ ≠ 0) : eLpNorm' (0 : α → ε) q μ = 0 := by rcases le_or_lt 0 q with hq0 | hq_neg · exact eLpNorm'_zero (lt_of_le_of_ne hq0 hq0_ne.symm) · simp [eLpNorm'_eq_lintegral_enorm, ENNReal.rpow_eq_zero_iff, hμ, hq_neg] @[simp] theorem eLpNormEssSup_zero : eLpNormEssSup (0 : α → ε) μ = 0 := by simp [eLpNormEssSup, ← bot_eq_zero', essSup_const_bot] @[simp] theorem eLpNorm_zero : eLpNorm (0 : α → ε) p μ = 0 := by by_cases h0 : p = 0 · simp [h0] by_cases h_top : p = ∞ · simp only [h_top, eLpNorm_exponent_top, eLpNormEssSup_zero] rw [← Ne] at h0 simp [eLpNorm_eq_eLpNorm' h0 h_top, ENNReal.toReal_pos h0 h_top] @[simp] theorem eLpNorm_zero' : eLpNorm (fun _ : α => (0 : ε)) p μ = 0 := eLpNorm_zero @[simp] lemma MemLp.zero : MemLp (0 : α → ε) p μ := ⟨aestronglyMeasurable_zero, by rw [eLpNorm_zero]; exact ENNReal.coe_lt_top⟩ @[simp] lemma MemLp.zero' : MemLp (fun _ : α => (0 : ε)) p μ := MemLp.zero @[deprecated (since := "2025-02-21")] alias Memℒp.zero' := MemLp.zero' @[deprecated (since := "2025-01-21")] alias zero_memℒp := MemLp.zero @[deprecated (since := "2025-01-21")] alias zero_mem_ℒp := MemLp.zero' variable [MeasurableSpace α] theorem eLpNorm'_measure_zero_of_pos {f : α → ε} (hq_pos : 0 < q) : eLpNorm' f q (0 : Measure α) = 0 := by simp [eLpNorm', hq_pos] theorem eLpNorm'_measure_zero_of_exponent_zero {f : α → ε} : eLpNorm' f 0 (0 : Measure α) = 1 := by simp [eLpNorm'] theorem eLpNorm'_measure_zero_of_neg {f : α → ε} (hq_neg : q < 0) : eLpNorm' f q (0 : Measure α) = ∞ := by simp [eLpNorm', hq_neg] end ENormedAddMonoid @[simp] theorem eLpNormEssSup_measure_zero {f : α → ε} : eLpNormEssSup f (0 : Measure α) = 0 := by simp [eLpNormEssSup] @[simp] theorem eLpNorm_measure_zero {f : α → ε} : eLpNorm f p (0 : Measure α) = 0 := by by_cases h0 : p = 0 · simp [h0] by_cases h_top : p = ∞ · simp [h_top] rw [← Ne] at h0 simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm', ENNReal.toReal_pos h0 h_top] section ContinuousENorm variable {ε : Type*} [TopologicalSpace ε] [ContinuousENorm ε] @[simp] lemma memLp_measure_zero {f : α → ε} : MemLp f p (0 : Measure α) := by simp [MemLp] @[deprecated (since := "2025-02-21")] alias memℒp_measure_zero := memLp_measure_zero end ContinuousENorm end Zero section Neg @[simp] theorem eLpNorm'_neg (f : α → F) (q : ℝ) (μ : Measure α) : eLpNorm' (-f) q μ = eLpNorm' f q μ := by simp [eLpNorm'_eq_lintegral_enorm]
@[simp] theorem eLpNorm_neg (f : α → F) (p : ℝ≥0∞) (μ : Measure α) : eLpNorm (-f) p μ = eLpNorm f p μ := by
Mathlib/MeasureTheory/Function/LpSeminorm/Basic.lean
183
184
/- Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel -/ import Mathlib.Data.ENNReal.Real import Mathlib.Tactic.Bound.Attribute import Mathlib.Topology.Bornology.Basic import Mathlib.Topology.EMetricSpace.Defs import Mathlib.Topology.UniformSpace.Basic /-! ## Pseudo-metric spaces This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the condition `dist x y = 0 → x = y`. Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform spaces and topological spaces. For example: open and closed sets, compactness, completeness, continuity and uniform continuity. ## Main definitions * `Dist α`: Endows a space `α` with a function `dist a b`. * `PseudoMetricSpace α`: A space endowed with a distance function, which can be zero even if the two elements are non-equal. * `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`. * `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded. * `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`. Additional useful definitions: * `nndist a b`: `dist` as a function to the non-negative reals. * `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`. * `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`. TODO (anyone): Add "Main results" section. ## Tags pseudo_metric, dist -/ assert_not_exists compactSpace_uniformity open Set Filter TopologicalSpace Bornology open scoped ENNReal NNReal Uniformity Topology universe u v w variable {α : Type u} {β : Type v} {X ι : Type*} theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε := ⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩ /-- Construct a uniform structure from a distance function and metric space axioms -/ def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α := .ofFun dist dist_self dist_comm dist_triangle ofDist_aux /-- Construct a bornology from a distance function and metric space axioms. -/ abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x) (dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α := Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C } ⟨0, fun _ hx _ => hx.elim⟩ (fun _ ⟨c, hc⟩ _ h => ⟨c, fun _ hx _ hy => hc (h hx) (h hy)⟩) (fun s hs t ht => by rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩ · rwa [empty_union] rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩ · rwa [union_empty] rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C · refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩ simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb) rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩ refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim (fun hz => (hs hx hz).trans (le_max_left _ _)) (fun hz => (dist_triangle x y z).trans <| (add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩) fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩ /-- The distance function (given an ambient metric space on `α`), which returns a nonnegative real number `dist x y` given `x y : α`. -/ @[ext] class Dist (α : Type*) where /-- Distance between two points -/ dist : α → α → ℝ export Dist (dist) -- the uniform structure and the emetric space structure are embedded in the metric space structure -- to avoid instance diamond issues. See Note [forgetful inheritance]. /-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/ private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y := have : 0 ≤ 2 * dist x y := calc 0 = dist x x := (dist_self _).symm _ ≤ dist x y + dist y x := dist_triangle _ _ _ _ = 2 * dist x y := by rw [two_mul, dist_comm] nonneg_of_mul_nonneg_right this two_pos /-- A pseudometric space is a type endowed with a `ℝ`-valued distance `dist` satisfying reflexivity `dist x x = 0`, commutativity `dist x y = dist y x`, and the triangle inequality `dist x z ≤ dist x y + dist y z`. Note that we do not require `dist x y = 0 → x = y`. See metric spaces (`MetricSpace`) for the similar class with that stronger assumption. Any pseudometric space is a topological space and a uniform space (see `TopologicalSpace`, `UniformSpace`), where the topology and uniformity come from the metric. Note that a T1 pseudometric space is just a metric space. We make the uniformity/topology part of the data instead of deriving it from the metric. This eg ensures that we do not get a diamond when doing `[PseudoMetricSpace α] [PseudoMetricSpace β] : TopologicalSpace (α × β)`: The product metric and product topology agree, but not definitionally so. See Note [forgetful inheritance]. -/ class PseudoMetricSpace (α : Type u) : Type u extends Dist α where dist_self : ∀ x : α, dist x x = 0 dist_comm : ∀ x y : α, dist x y = dist y x dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z /-- Extended distance between two points -/ edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩ edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y) := by intros x y; exact ENNReal.coe_nnreal_eq _ toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets : (Bornology.cobounded α).sets = { s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl /-- Two pseudo metric space structures with the same distance function coincide. -/ @[ext] theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α} (h : m.toDist = m'.toDist) : m = m' := by let d := m.toDist obtain ⟨_, _, _, _, hed, _, hU, _, hB⟩ := m let d' := m'.toDist obtain ⟨_, _, _, _, hed', _, hU', _, hB'⟩ := m' obtain rfl : d = d' := h congr · ext x y : 2 rw [hed, hed'] · exact UniformSpace.ext (hU.trans hU'.symm) · ext : 2 rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB'] variable [PseudoMetricSpace α] attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology -- see Note [lower instance priority] instance (priority := 200) PseudoMetricSpace.toEDist : EDist α := ⟨PseudoMetricSpace.edist⟩ /-- Construct a pseudo-metric space structure whose underlying topological space structure (definitionally) agrees which a pre-existing topology which is compatible with a given distance function. -/ def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) (H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) : PseudoMetricSpace α := { dist := dist dist_self := dist_self dist_comm := dist_comm dist_triangle := dist_triangle toUniformSpace := (UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <| TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦ ((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm uniformity_dist := rfl toBornology := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets := rfl } @[simp] theorem dist_self (x : α) : dist x x = 0 := PseudoMetricSpace.dist_self x theorem dist_comm (x y : α) : dist x y = dist y x := PseudoMetricSpace.dist_comm x y theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) := PseudoMetricSpace.edist_dist x y @[bound] theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z := PseudoMetricSpace.dist_triangle x y z theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by rw [dist_comm z]; apply dist_triangle theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by rw [dist_comm y]; apply dist_triangle theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w := calc dist x w ≤ dist x z + dist z w := dist_triangle x z w _ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _ theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) : dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by rw [add_left_comm, dist_comm x₁, ← add_assoc] apply dist_triangle4 theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) : dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by rw [add_right_comm, dist_comm y₁] apply dist_triangle4 theorem dist_triangle8 (a b c d e f g h : α) : dist a h ≤ dist a b + dist b c + dist c d + dist d e + dist e f + dist f g + dist g h := by apply le_trans (dist_triangle4 a f g h) apply add_le_add_right (add_le_add_right _ (dist f g)) (dist g h) apply le_trans (dist_triangle4 a d e f) apply add_le_add_right (add_le_add_right _ (dist d e)) (dist e f) exact dist_triangle4 a b c d theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _ theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y := abs_sub_le_iff.2 ⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩ @[bound] theorem dist_nonneg {x y : α} : 0 ≤ dist x y := dist_nonneg' dist dist_self dist_comm dist_triangle namespace Mathlib.Meta.Positivity open Lean Meta Qq Function /-- Extension for the `positivity` tactic: distances are nonnegative. -/ @[positivity Dist.dist _ _] def evalDist : PositivityExt where eval {u α} _zα _pα e := do match u, α, e with | 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) => let _inst ← synthInstanceQ q(PseudoMetricSpace $β) assertInstancesCommute pure (.nonnegative q(dist_nonneg)) | _, _, _ => throwError "not dist" end Mathlib.Meta.Positivity example {x y : α} : 0 ≤ dist x y := by positivity @[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg /-- A version of `Dist` that takes value in `ℝ≥0`. -/ class NNDist (α : Type*) where /-- Nonnegative distance between two points -/ nndist : α → α → ℝ≥0 export NNDist (nndist) -- see Note [lower instance priority] /-- Distance as a nonnegative real number. -/ instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α := ⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩ /-- Express `dist` in terms of `nndist` -/ theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl @[simp, norm_cast] theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl /-- Express `edist` in terms of `nndist` -/ theorem edist_nndist (x y : α) : edist x y = nndist x y := by rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal] /-- Express `nndist` in terms of `edist` -/ theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by simp [edist_nndist] @[simp, norm_cast] theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y := (edist_nndist x y).symm @[simp, norm_cast] theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by rw [edist_nndist, ENNReal.coe_lt_coe] @[simp, norm_cast] theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by rw [edist_nndist, ENNReal.coe_le_coe] /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ := (edist_dist x y).symm ▸ ENNReal.ofReal_lt_top /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ := (edist_lt_top x y).ne /-- `nndist x x` vanishes -/ @[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a) @[simp, norm_cast] theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c := Iff.rfl @[simp, norm_cast] theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c := Iff.rfl @[simp] theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg] @[simp] theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) : edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr] /-- Express `nndist` in terms of `dist` -/ theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by rw [dist_nndist, Real.toNNReal_coe] theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y /-- Triangle inequality for the nonnegative distance -/ theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z := dist_triangle _ _ _ theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y := dist_triangle_left _ _ _ theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z := dist_triangle_right _ _ _ /-- Express `dist` in terms of `edist` -/ theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg] namespace Metric -- instantiate pseudometric space as a topology variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α} /-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/ def ball (x : α) (ε : ℝ) : Set α := { y | dist y x < ε } @[simp] theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε := Iff.rfl theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball] theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε := dist_nonneg.trans_lt hy theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by rwa [mem_ball, dist_self] @[simp] theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε := ⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩ @[simp] theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt] @[simp] theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty] /-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also contains it. See also `exists_lt_subset_ball`. -/ theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by simp only [mem_ball] at h ⊢ exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩ theorem ball_eq_ball (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε := rfl theorem ball_eq_ball' (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.1 p.2 < ε } = Metric.ball x ε := by ext simp [dist_comm, UniformSpace.ball] @[simp] theorem iUnion_ball_nat (x : α) : ⋃ n : ℕ, ball x n = univ := iUnion_eq_univ_iff.2 fun y => exists_nat_gt (dist y x) @[simp] theorem iUnion_ball_nat_succ (x : α) : ⋃ n : ℕ, ball x (n + 1) = univ := iUnion_eq_univ_iff.2 fun y => (exists_nat_gt (dist y x)).imp fun _ h => h.trans (lt_add_one _) /-- `closedBall x ε` is the set of all points `y` with `dist y x ≤ ε` -/ def closedBall (x : α) (ε : ℝ) := { y | dist y x ≤ ε } @[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall] /-- `sphere x ε` is the set of all points `y` with `dist y x = ε` -/ def sphere (x : α) (ε : ℝ) := { y | dist y x = ε } @[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere] theorem ne_of_mem_sphere (h : y ∈ sphere x ε) (hε : ε ≠ 0) : y ≠ x := ne_of_mem_of_not_mem h <| by simpa using hε.symm theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε := dist_nonneg.trans_eq hy @[simp] theorem sphere_eq_empty_of_neg (hε : ε < 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _y hy => (nonneg_of_mem_sphere hy).not_lt hε theorem sphere_eq_empty_of_subsingleton [Subsingleton α] (hε : ε ≠ 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _ h => ne_of_mem_sphere h hε (Subsingleton.elim _ _) instance sphere_isEmpty_of_subsingleton [Subsingleton α] [NeZero ε] : IsEmpty (sphere x ε) := by rw [sphere_eq_empty_of_subsingleton (NeZero.ne ε)]; infer_instance theorem closedBall_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 ≤ ε) : closedBall x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem ball_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 < ε) : ball x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by rwa [mem_closedBall, dist_self] @[simp] theorem nonempty_closedBall : (closedBall x ε).Nonempty ↔ 0 ≤ ε := ⟨fun ⟨_x, hx⟩ => dist_nonneg.trans hx, fun h => ⟨x, mem_closedBall_self h⟩⟩ @[simp] theorem closedBall_eq_empty : closedBall x ε = ∅ ↔ ε < 0 := by rw [← not_nonempty_iff_eq_empty, nonempty_closedBall, not_le] /-- Closed balls and spheres coincide when the radius is non-positive -/ theorem closedBall_eq_sphere_of_nonpos (hε : ε ≤ 0) : closedBall x ε = sphere x ε := Set.ext fun _ => (hε.trans dist_nonneg).le_iff_eq theorem ball_subset_closedBall : ball x ε ⊆ closedBall x ε := fun _y hy => mem_closedBall.2 (le_of_lt hy) theorem sphere_subset_closedBall : sphere x ε ⊆ closedBall x ε := fun _ => le_of_eq lemma sphere_subset_ball {r R : ℝ} (h : r < R) : sphere x r ⊆ ball x R := fun _x hx ↦ (mem_sphere.1 hx).trans_lt h theorem closedBall_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (closedBall x δ) (ball y ε) := Set.disjoint_left.mpr fun _a ha1 ha2 => (h.trans <| dist_triangle_left _ _ _).not_lt <| add_lt_add_of_le_of_lt ha1 ha2 theorem ball_disjoint_closedBall (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (closedBall y ε) := (closedBall_disjoint_ball <| by rwa [add_comm, dist_comm]).symm theorem ball_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (ball y ε) := (closedBall_disjoint_ball h).mono_left ball_subset_closedBall theorem closedBall_disjoint_closedBall (h : δ + ε < dist x y) : Disjoint (closedBall x δ) (closedBall y ε) := Set.disjoint_left.mpr fun _a ha1 ha2 => h.not_le <| (dist_triangle_left _ _ _).trans <| add_le_add ha1 ha2 theorem sphere_disjoint_ball : Disjoint (sphere x ε) (ball x ε) := Set.disjoint_left.mpr fun _y hy₁ hy₂ => absurd hy₁ <| ne_of_lt hy₂ @[simp] theorem ball_union_sphere : ball x ε ∪ sphere x ε = closedBall x ε := Set.ext fun _y => (@le_iff_lt_or_eq ℝ _ _ _).symm @[simp] theorem sphere_union_ball : sphere x ε ∪ ball x ε = closedBall x ε := by rw [union_comm, ball_union_sphere] @[simp] theorem closedBall_diff_sphere : closedBall x ε \ sphere x ε = ball x ε := by rw [← ball_union_sphere, Set.union_diff_cancel_right sphere_disjoint_ball.symm.le_bot] @[simp] theorem closedBall_diff_ball : closedBall x ε \ ball x ε = sphere x ε := by rw [← ball_union_sphere, Set.union_diff_cancel_left sphere_disjoint_ball.symm.le_bot] theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε := by rw [mem_ball', mem_ball] theorem mem_closedBall_comm : x ∈ closedBall y ε ↔ y ∈ closedBall x ε := by rw [mem_closedBall', mem_closedBall] theorem mem_sphere_comm : x ∈ sphere y ε ↔ y ∈ sphere x ε := by rw [mem_sphere', mem_sphere] @[gcongr] theorem ball_subset_ball (h : ε₁ ≤ ε₂) : ball x ε₁ ⊆ ball x ε₂ := fun _y yx => lt_of_lt_of_le (mem_ball.1 yx) h theorem closedBall_eq_bInter_ball : closedBall x ε = ⋂ δ > ε, ball x δ := by ext y; rw [mem_closedBall, ← forall_lt_iff_le', mem_iInter₂]; rfl theorem ball_subset_ball' (h : ε₁ + dist x y ≤ ε₂) : ball x ε₁ ⊆ ball y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ < ε₁ + dist x y := add_lt_add_right (mem_ball.1 hz) _ _ ≤ ε₂ := h @[gcongr] theorem closedBall_subset_closedBall (h : ε₁ ≤ ε₂) : closedBall x ε₁ ⊆ closedBall x ε₂ := fun _y (yx : _ ≤ ε₁) => le_trans yx h theorem closedBall_subset_closedBall' (h : ε₁ + dist x y ≤ ε₂) : closedBall x ε₁ ⊆ closedBall y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _ _ ≤ ε₂ := h theorem closedBall_subset_ball (h : ε₁ < ε₂) : closedBall x ε₁ ⊆ ball x ε₂ := fun y (yh : dist y x ≤ ε₁) => lt_of_le_of_lt yh h theorem closedBall_subset_ball' (h : ε₁ + dist x y < ε₂) : closedBall x ε₁ ⊆ ball y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _ _ < ε₂ := h theorem dist_le_add_of_nonempty_closedBall_inter_closedBall (h : (closedBall x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y ≤ ε₁ + ε₂ := let ⟨z, hz⟩ := h calc dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _ _ ≤ ε₁ + ε₂ := add_le_add hz.1 hz.2 theorem dist_lt_add_of_nonempty_closedBall_inter_ball (h : (closedBall x ε₁ ∩ ball y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := let ⟨z, hz⟩ := h calc dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _ _ < ε₁ + ε₂ := add_lt_add_of_le_of_lt hz.1 hz.2 theorem dist_lt_add_of_nonempty_ball_inter_closedBall (h : (ball x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := by rw [inter_comm] at h rw [add_comm, dist_comm] exact dist_lt_add_of_nonempty_closedBall_inter_ball h theorem dist_lt_add_of_nonempty_ball_inter_ball (h : (ball x ε₁ ∩ ball y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := dist_lt_add_of_nonempty_closedBall_inter_ball <| h.mono (inter_subset_inter ball_subset_closedBall Subset.rfl) @[simp] theorem iUnion_closedBall_nat (x : α) : ⋃ n : ℕ, closedBall x n = univ := iUnion_eq_univ_iff.2 fun y => exists_nat_ge (dist y x) theorem iUnion_inter_closedBall_nat (s : Set α) (x : α) : ⋃ n : ℕ, s ∩ closedBall x n = s := by rw [← inter_iUnion, iUnion_closedBall_nat, inter_univ] theorem ball_subset (h : dist x y ≤ ε₂ - ε₁) : ball x ε₁ ⊆ ball y ε₂ := fun z zx => by rw [← add_sub_cancel ε₁ ε₂] exact lt_of_le_of_lt (dist_triangle z x y) (add_lt_add_of_lt_of_le zx h) theorem ball_half_subset (y) (h : y ∈ ball x (ε / 2)) : ball y (ε / 2) ⊆ ball x ε := ball_subset <| by rw [sub_self_div_two]; exact le_of_lt h theorem exists_ball_subset_ball (h : y ∈ ball x ε) : ∃ ε' > 0, ball y ε' ⊆ ball x ε := ⟨_, sub_pos.2 h, ball_subset <| by rw [sub_sub_self]⟩ /-- If a property holds for all points in closed balls of arbitrarily large radii, then it holds for all points. -/ theorem forall_of_forall_mem_closedBall (p : α → Prop) (x : α) (H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ closedBall x R, p y) (y : α) : p y := by obtain ⟨R, hR, h⟩ : ∃ R ≥ dist y x, ∀ z : α, z ∈ closedBall x R → p z := frequently_iff.1 H (Ici_mem_atTop (dist y x)) exact h _ hR /-- If a property holds for all points in balls of arbitrarily large radii, then it holds for all points. -/ theorem forall_of_forall_mem_ball (p : α → Prop) (x : α) (H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ ball x R, p y) (y : α) : p y := by obtain ⟨R, hR, h⟩ : ∃ R > dist y x, ∀ z : α, z ∈ ball x R → p z := frequently_iff.1 H (Ioi_mem_atTop (dist y x)) exact h _ hR theorem isBounded_iff {s : Set α} : IsBounded s ↔ ∃ C : ℝ, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := by rw [isBounded_def, ← Filter.mem_sets, @PseudoMetricSpace.cobounded_sets α, mem_setOf_eq, compl_compl] theorem isBounded_iff_eventually {s : Set α} : IsBounded s ↔ ∀ᶠ C in atTop, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := isBounded_iff.trans ⟨fun ⟨C, h⟩ => eventually_atTop.2 ⟨C, fun _C' hC' _x hx _y hy => (h hx hy).trans hC'⟩, Eventually.exists⟩ theorem isBounded_iff_exists_ge {s : Set α} (c : ℝ) : IsBounded s ↔ ∃ C, c ≤ C ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := ⟨fun h => ((eventually_ge_atTop c).and (isBounded_iff_eventually.1 h)).exists, fun h => isBounded_iff.2 <| h.imp fun _ => And.right⟩ theorem isBounded_iff_nndist {s : Set α} : IsBounded s ↔ ∃ C : ℝ≥0, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → nndist x y ≤ C := by simp only [isBounded_iff_exists_ge 0, NNReal.exists, ← NNReal.coe_le_coe, ← dist_nndist, NNReal.coe_mk, exists_prop] theorem toUniformSpace_eq : ‹PseudoMetricSpace α›.toUniformSpace = .ofDist dist dist_self dist_comm dist_triangle := UniformSpace.ext PseudoMetricSpace.uniformity_dist theorem uniformity_basis_dist : (𝓤 α).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { p : α × α | dist p.1 p.2 < ε } := by rw [toUniformSpace_eq] exact UniformSpace.hasBasis_ofFun (exists_gt _) _ _ _ _ _ /-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers accumulating to zero, then `f i`-neighborhoods of the diagonal form a basis of `𝓤 α`. For specific bases see `uniformity_basis_dist`, `uniformity_basis_dist_inv_nat_succ`, and `uniformity_basis_dist_inv_nat_pos`. -/ protected theorem mk_uniformity_basis {β : Type*} {p : β → Prop} {f : β → ℝ} (hf₀ : ∀ i, p i → 0 < f i) (hf : ∀ ⦃ε⦄, 0 < ε → ∃ i, p i ∧ f i ≤ ε) : (𝓤 α).HasBasis p fun i => { p : α × α | dist p.1 p.2 < f i } := by refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩ constructor · rintro ⟨ε, ε₀, hε⟩ rcases hf ε₀ with ⟨i, hi, H⟩ exact ⟨i, hi, fun x (hx : _ < _) => hε <| lt_of_lt_of_le hx H⟩ · exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, H⟩ theorem uniformity_basis_dist_rat : (𝓤 α).HasBasis (fun r : ℚ => 0 < r) fun r => { p : α × α | dist p.1 p.2 < r } := Metric.mk_uniformity_basis (fun _ => Rat.cast_pos.2) fun _ε hε => let ⟨r, hr0, hrε⟩ := exists_rat_btwn hε ⟨r, Rat.cast_pos.1 hr0, hrε.le⟩ theorem uniformity_basis_dist_inv_nat_succ : (𝓤 α).HasBasis (fun _ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / (↑n + 1) } := Metric.mk_uniformity_basis (fun n _ => div_pos zero_lt_one <| Nat.cast_add_one_pos n) fun _ε ε0 => (exists_nat_one_div_lt ε0).imp fun _n hn => ⟨trivial, le_of_lt hn⟩ theorem uniformity_basis_dist_inv_nat_pos : (𝓤 α).HasBasis (fun n : ℕ => 0 < n) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / ↑n } := Metric.mk_uniformity_basis (fun _ hn => div_pos zero_lt_one <| Nat.cast_pos.2 hn) fun _ ε0 => let ⟨n, hn⟩ := exists_nat_one_div_lt ε0 ⟨n + 1, Nat.succ_pos n, mod_cast hn.le⟩ theorem uniformity_basis_dist_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < r ^ n } := Metric.mk_uniformity_basis (fun _ _ => pow_pos h0 _) fun _ε ε0 => let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1 ⟨n, trivial, hn.le⟩ theorem uniformity_basis_dist_lt {R : ℝ} (hR : 0 < R) : (𝓤 α).HasBasis (fun r : ℝ => 0 < r ∧ r < R) fun r => { p : α × α | dist p.1 p.2 < r } := Metric.mk_uniformity_basis (fun _ => And.left) fun r hr => ⟨min r (R / 2), ⟨lt_min hr (half_pos hR), min_lt_iff.2 <| Or.inr (half_lt_self hR)⟩, min_le_left _ _⟩ /-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers accumulating to zero, then closed neighborhoods of the diagonal of sizes `{f i | p i}` form a basis of `𝓤 α`. Currently we have only one specific basis `uniformity_basis_dist_le` based on this constructor. More can be easily added if needed in the future. -/ protected theorem mk_uniformity_basis_le {β : Type*} {p : β → Prop} {f : β → ℝ} (hf₀ : ∀ x, p x → 0 < f x) (hf : ∀ ε, 0 < ε → ∃ x, p x ∧ f x ≤ ε) : (𝓤 α).HasBasis p fun x => { p : α × α | dist p.1 p.2 ≤ f x } := by refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩ constructor · rintro ⟨ε, ε₀, hε⟩ rcases exists_between ε₀ with ⟨ε', hε'⟩ rcases hf ε' hε'.1 with ⟨i, hi, H⟩ exact ⟨i, hi, fun x (hx : _ ≤ _) => hε <| lt_of_le_of_lt (le_trans hx H) hε'.2⟩ · exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, fun x (hx : _ < _) => H (mem_setOf.2 hx.le)⟩ /-- Constant size closed neighborhoods of the diagonal form a basis of the uniformity filter. -/ theorem uniformity_basis_dist_le : (𝓤 α).HasBasis ((0 : ℝ) < ·) fun ε => { p : α × α | dist p.1 p.2 ≤ ε } := Metric.mk_uniformity_basis_le (fun _ => id) fun ε ε₀ => ⟨ε, ε₀, le_refl ε⟩ theorem uniformity_basis_dist_le_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 ≤ r ^ n } := Metric.mk_uniformity_basis_le (fun _ _ => pow_pos h0 _) fun _ε ε0 => let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1 ⟨n, trivial, hn.le⟩ theorem mem_uniformity_dist {s : Set (α × α)} : s ∈ 𝓤 α ↔ ∃ ε > 0, ∀ ⦃a b : α⦄, dist a b < ε → (a, b) ∈ s := uniformity_basis_dist.mem_uniformity_iff /-- A constant size neighborhood of the diagonal is an entourage. -/ theorem dist_mem_uniformity {ε : ℝ} (ε0 : 0 < ε) : { p : α × α | dist p.1 p.2 < ε } ∈ 𝓤 α := mem_uniformity_dist.2 ⟨ε, ε0, fun _ _ ↦ id⟩ theorem uniformContinuous_iff [PseudoMetricSpace β] {f : α → β} : UniformContinuous f ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃a b : α⦄, dist a b < δ → dist (f a) (f b) < ε := uniformity_basis_dist.uniformContinuous_iff uniformity_basis_dist theorem uniformContinuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} : UniformContinuousOn f s ↔ ∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y < δ → dist (f x) (f y) < ε := Metric.uniformity_basis_dist.uniformContinuousOn_iff Metric.uniformity_basis_dist theorem uniformContinuousOn_iff_le [PseudoMetricSpace β] {f : α → β} {s : Set α} : UniformContinuousOn f s ↔ ∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y ≤ δ → dist (f x) (f y) ≤ ε := Metric.uniformity_basis_dist_le.uniformContinuousOn_iff Metric.uniformity_basis_dist_le theorem nhds_basis_ball : (𝓝 x).HasBasis (0 < ·) (ball x) := nhds_basis_uniformity uniformity_basis_dist theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ ε > 0, ball x ε ⊆ s := nhds_basis_ball.mem_iff theorem eventually_nhds_iff {p : α → Prop} : (∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ ⦃y⦄, dist y x < ε → p y := mem_nhds_iff theorem eventually_nhds_iff_ball {p : α → Prop} : (∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ y ∈ ball x ε, p y := mem_nhds_iff /-- A version of `Filter.eventually_prod_iff` where the first filter consists of neighborhoods in a pseudo-metric space. -/ theorem eventually_nhds_prod_iff {f : Filter ι} {x₀ : α} {p : α × ι → Prop} : (∀ᶠ x in 𝓝 x₀ ×ˢ f, p x) ↔ ∃ ε > (0 : ℝ), ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧ ∀ ⦃x⦄, dist x x₀ < ε → ∀ ⦃i⦄, pa i → p (x, i) := by refine (nhds_basis_ball.prod f.basis_sets).eventually_iff.trans ?_ simp only [Prod.exists, forall_prod_set, id, mem_ball, and_assoc, exists_and_left, and_imp] rfl /-- A version of `Filter.eventually_prod_iff` where the second filter consists of neighborhoods in a pseudo-metric space. -/ theorem eventually_prod_nhds_iff {f : Filter ι} {x₀ : α} {p : ι × α → Prop} : (∀ᶠ x in f ×ˢ 𝓝 x₀, p x) ↔ ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧ ∃ ε > 0, ∀ ⦃i⦄, pa i → ∀ ⦃x⦄, dist x x₀ < ε → p (i, x) := by rw [eventually_swap_iff, Metric.eventually_nhds_prod_iff] constructor <;> · rintro ⟨a1, a2, a3, a4, a5⟩ exact ⟨a3, a4, a1, a2, fun _ b1 b2 b3 => a5 b3 b1⟩ theorem nhds_basis_closedBall : (𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) (closedBall x) := nhds_basis_uniformity uniformity_basis_dist_le theorem nhds_basis_ball_inv_nat_succ : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (1 / (↑n + 1)) := nhds_basis_uniformity uniformity_basis_dist_inv_nat_succ theorem nhds_basis_ball_inv_nat_pos : (𝓝 x).HasBasis (fun n => 0 < n) fun n : ℕ => ball x (1 / ↑n) := nhds_basis_uniformity uniformity_basis_dist_inv_nat_pos theorem nhds_basis_ball_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (r ^ n) := nhds_basis_uniformity (uniformity_basis_dist_pow h0 h1) theorem nhds_basis_closedBall_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => closedBall x (r ^ n) := nhds_basis_uniformity (uniformity_basis_dist_le_pow h0 h1) theorem isOpen_iff : IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ball x ε ⊆ s := by simp only [isOpen_iff_mem_nhds, mem_nhds_iff] @[simp] theorem isOpen_ball : IsOpen (ball x ε) := isOpen_iff.2 fun _ => exists_ball_subset_ball theorem ball_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : ball x ε ∈ 𝓝 x := isOpen_ball.mem_nhds (mem_ball_self ε0) theorem closedBall_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : closedBall x ε ∈ 𝓝 x := mem_of_superset (ball_mem_nhds x ε0) ball_subset_closedBall theorem closedBall_mem_nhds_of_mem {x c : α} {ε : ℝ} (h : x ∈ ball c ε) : closedBall c ε ∈ 𝓝 x := mem_of_superset (isOpen_ball.mem_nhds h) ball_subset_closedBall theorem nhdsWithin_basis_ball {s : Set α} : (𝓝[s] x).HasBasis (fun ε : ℝ => 0 < ε) fun ε => ball x ε ∩ s := nhdsWithin_hasBasis nhds_basis_ball s theorem mem_nhdsWithin_iff {t : Set α} : s ∈ 𝓝[t] x ↔ ∃ ε > 0, ball x ε ∩ t ⊆ s := nhdsWithin_basis_ball.mem_iff theorem tendsto_nhdsWithin_nhdsWithin [PseudoMetricSpace β] {t : Set β} {f : α → β} {a b} : Tendsto f (𝓝[s] a) (𝓝[t] b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → f x ∈ t ∧ dist (f x) b < ε := (nhdsWithin_basis_ball.tendsto_iff nhdsWithin_basis_ball).trans <| by simp only [inter_comm _ s, inter_comm _ t, mem_inter_iff, and_imp, gt_iff_lt, mem_ball] theorem tendsto_nhdsWithin_nhds [PseudoMetricSpace β] {f : α → β} {a b} : Tendsto f (𝓝[s] a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) b < ε := by rw [← nhdsWithin_univ b, tendsto_nhdsWithin_nhdsWithin] simp only [mem_univ, true_and] theorem tendsto_nhds_nhds [PseudoMetricSpace β] {f : α → β} {a b} : Tendsto f (𝓝 a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) b < ε := nhds_basis_ball.tendsto_iff nhds_basis_ball theorem continuousAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} : ContinuousAt f a ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) (f a) < ε := by rw [ContinuousAt, tendsto_nhds_nhds] theorem continuousWithinAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} {s : Set α} : ContinuousWithinAt f s a ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) (f a) < ε := by rw [ContinuousWithinAt, tendsto_nhdsWithin_nhds] theorem continuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} : ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∃ δ > 0, ∀ a ∈ s, dist a b < δ → dist (f a) (f b) < ε := by simp [ContinuousOn, continuousWithinAt_iff] theorem continuous_iff [PseudoMetricSpace β] {f : α → β} : Continuous f ↔ ∀ b, ∀ ε > 0, ∃ δ > 0, ∀ a, dist a b < δ → dist (f a) (f b) < ε := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_nhds theorem tendsto_nhds {f : Filter β} {u : β → α} {a : α} : Tendsto u f (𝓝 a) ↔ ∀ ε > 0, ∀ᶠ x in f, dist (u x) a < ε := nhds_basis_ball.tendsto_right_iff theorem continuousAt_iff' [TopologicalSpace β] {f : β → α} {b : β} : ContinuousAt f b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝 b, dist (f x) (f b) < ε := by rw [ContinuousAt, tendsto_nhds] theorem continuousWithinAt_iff' [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} : ContinuousWithinAt f s b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by rw [ContinuousWithinAt, tendsto_nhds] theorem continuousOn_iff' [TopologicalSpace β] {f : β → α} {s : Set β} : ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by simp [ContinuousOn, continuousWithinAt_iff'] theorem continuous_iff' [TopologicalSpace β] {f : β → α} : Continuous f ↔ ∀ (a), ∀ ε > 0, ∀ᶠ x in 𝓝 a, dist (f x) (f a) < ε := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds theorem tendsto_atTop [Nonempty β] [SemilatticeSup β] {u : β → α} {a : α} : Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n ≥ N, dist (u n) a < ε := (atTop_basis.tendsto_iff nhds_basis_ball).trans <| by simp only [true_and, mem_ball, mem_Ici] /-- A variant of `tendsto_atTop` that uses `∃ N, ∀ n > N, ...` rather than `∃ N, ∀ n ≥ N, ...` -/ theorem tendsto_atTop' [Nonempty β] [SemilatticeSup β] [NoMaxOrder β] {u : β → α} {a : α} : Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n > N, dist (u n) a < ε := (atTop_basis_Ioi.tendsto_iff nhds_basis_ball).trans <| by simp only [true_and, gt_iff_lt, mem_Ioi, mem_ball] theorem isOpen_singleton_iff {α : Type*} [PseudoMetricSpace α] {x : α} : IsOpen ({x} : Set α) ↔ ∃ ε > 0, ∀ y, dist y x < ε → y = x := by simp [isOpen_iff, subset_singleton_iff, mem_ball] theorem _root_.Dense.exists_dist_lt {s : Set α} (hs : Dense s) (x : α) {ε : ℝ} (hε : 0 < ε) : ∃ y ∈ s, dist x y < ε := by have : (ball x ε).Nonempty := by simp [hε] simpa only [mem_ball'] using hs.exists_mem_open isOpen_ball this nonrec theorem _root_.DenseRange.exists_dist_lt {β : Type*} {f : β → α} (hf : DenseRange f) (x : α) {ε : ℝ} (hε : 0 < ε) : ∃ y, dist x (f y) < ε := exists_range_iff.1 (hf.exists_dist_lt x hε) /-- (Pseudo) metric space has discrete `UniformSpace` structure iff the distances between distinct points are uniformly bounded away from zero. -/ protected lemma uniformSpace_eq_bot : ‹PseudoMetricSpace α›.toUniformSpace = ⊥ ↔ ∃ r : ℝ, 0 < r ∧ Pairwise (r ≤ dist · · : α → α → Prop) := by simp only [uniformity_basis_dist.uniformSpace_eq_bot, mem_setOf_eq, not_lt] end Metric open Metric /-- If the distances between distinct points in a (pseudo) metric space are uniformly bounded away from zero, then the space has discrete topology. -/ lemma DiscreteTopology.of_forall_le_dist {α} [PseudoMetricSpace α] {r : ℝ} (hpos : 0 < r) (hr : Pairwise (r ≤ dist · · : α → α → Prop)) : DiscreteTopology α := ⟨by rw [Metric.uniformSpace_eq_bot.2 ⟨r, hpos, hr⟩, UniformSpace.toTopologicalSpace_bot]⟩ /- Instantiate a pseudometric space as a pseudoemetric space. Before we can state the instance, we need to show that the uniform structure coming from the edistance and the distance coincide. -/ theorem Metric.uniformity_edist_aux {α} (d : α → α → ℝ≥0) : ⨅ ε > (0 : ℝ), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } = ⨅ ε > (0 : ℝ≥0∞), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } := by simp only [le_antisymm_iff, le_iInf_iff, le_principal_iff] refine ⟨fun ε hε => ?_, fun ε hε => ?_⟩ · rcases ENNReal.lt_iff_exists_nnreal_btwn.1 hε with ⟨ε', ε'0, ε'ε⟩ refine mem_iInf_of_mem (ε' : ℝ) (mem_iInf_of_mem (ENNReal.coe_pos.1 ε'0) ?_) exact fun x hx => lt_trans (ENNReal.coe_lt_coe.2 hx) ε'ε · lift ε to ℝ≥0 using le_of_lt hε refine mem_iInf_of_mem (ε : ℝ≥0∞) (mem_iInf_of_mem (ENNReal.coe_pos.2 hε) ?_) exact fun _ => ENNReal.coe_lt_coe.1 theorem Metric.uniformity_edist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | edist p.1 p.2 < ε } := by simp only [PseudoMetricSpace.uniformity_dist, dist_nndist, edist_nndist, Metric.uniformity_edist_aux] -- see Note [lower instance priority] /-- A pseudometric space induces a pseudoemetric space -/ instance (priority := 100) PseudoMetricSpace.toPseudoEMetricSpace : PseudoEMetricSpace α := { ‹PseudoMetricSpace α› with edist_self := by simp [edist_dist] edist_comm := fun _ _ => by simp only [edist_dist, dist_comm] edist_triangle := fun x y z => by simp only [edist_dist, ← ENNReal.ofReal_add, dist_nonneg] rw [ENNReal.ofReal_le_ofReal_iff _] · exact dist_triangle _ _ _ · simpa using add_le_add (dist_nonneg : 0 ≤ dist x y) dist_nonneg uniformity_edist := Metric.uniformity_edist } /-- In a pseudometric space, an open ball of infinite radius is the whole space -/ theorem Metric.eball_top_eq_univ (x : α) : EMetric.ball x ∞ = Set.univ := Set.eq_univ_iff_forall.mpr fun y => edist_lt_top y x /-- Balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_ball {x : α} {ε : ℝ} : EMetric.ball x (ENNReal.ofReal ε) = ball x ε := by ext y simp only [EMetric.mem_ball, mem_ball, edist_dist] exact ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg /-- Balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_ball_nnreal {x : α} {ε : ℝ≥0} : EMetric.ball x ε = ball x ε := by rw [← Metric.emetric_ball] simp /-- Closed balls defined using the distance or the edistance coincide -/ theorem Metric.emetric_closedBall {x : α} {ε : ℝ} (h : 0 ≤ ε) : EMetric.closedBall x (ENNReal.ofReal ε) = closedBall x ε := by ext y; simp [edist_le_ofReal h] /-- Closed balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_closedBall_nnreal {x : α} {ε : ℝ≥0} : EMetric.closedBall x ε = closedBall x ε := by rw [← Metric.emetric_closedBall ε.coe_nonneg, ENNReal.ofReal_coe_nnreal] @[simp] theorem Metric.emetric_ball_top (x : α) : EMetric.ball x ⊤ = univ := eq_univ_of_forall fun _ => edist_lt_top _ _ /-- Build a new pseudometric space from an old one where the bundled uniform structure is provably (but typically non-definitionaly) equal to some given uniform structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceUniformity {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : PseudoMetricSpace α := { m with toUniformSpace := U uniformity_dist := H.trans PseudoMetricSpace.uniformity_dist } theorem PseudoMetricSpace.replaceUniformity_eq {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : m.replaceUniformity H = m := by ext rfl -- ensure that the bornology is unchanged when replacing the uniformity. example {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : (PseudoMetricSpace.replaceUniformity m H).toBornology = m.toBornology := by with_reducible_and_instances rfl /-- Build a new pseudo metric space from an old one where the bundled topological structure is provably (but typically non-definitionaly) equal to some given topological structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceTopology {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ) (H : U = m.toUniformSpace.toTopologicalSpace) : PseudoMetricSpace γ := @PseudoMetricSpace.replaceUniformity γ (m.toUniformSpace.replaceTopology H) m rfl theorem PseudoMetricSpace.replaceTopology_eq {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ) (H : U = m.toUniformSpace.toTopologicalSpace) : m.replaceTopology H = m := by ext rfl /-- One gets a pseudometric space from an emetric space if the edistance is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the uniformity are defeq in the pseudometric space and the pseudoemetric space. In this definition, the distance is given separately, to be able to prescribe some expression which is not defeq to the push-forward of the edistance to reals. See note [reducible non-instances]. -/ abbrev PseudoEMetricSpace.toPseudoMetricSpaceOfDist {α : Type u} [e : PseudoEMetricSpace α] (dist : α → α → ℝ) (edist_ne_top : ∀ x y : α, edist x y ≠ ⊤) (h : ∀ x y, dist x y = ENNReal.toReal (edist x y)) : PseudoMetricSpace α where dist := dist dist_self x := by simp [h] dist_comm x y := by simp [h, edist_comm] dist_triangle x y z := by simp only [h] exact ENNReal.toReal_le_add (edist_triangle _ _ _) (edist_ne_top _ _) (edist_ne_top _ _) edist := edist edist_dist _ _ := by simp only [h, ENNReal.ofReal_toReal (edist_ne_top _ _)] toUniformSpace := e.toUniformSpace uniformity_dist := e.uniformity_edist.trans <| by simpa only [ENNReal.coe_toNNReal (edist_ne_top _ _), h] using (Metric.uniformity_edist_aux fun x y : α => (edist x y).toNNReal).symm /-- One gets a pseudometric space from an emetric space if the edistance is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the uniformity are defeq in the pseudometric space and the emetric space. -/ abbrev PseudoEMetricSpace.toPseudoMetricSpace {α : Type u} [PseudoEMetricSpace α] (h : ∀ x y : α, edist x y ≠ ⊤) : PseudoMetricSpace α := PseudoEMetricSpace.toPseudoMetricSpaceOfDist (fun x y => ENNReal.toReal (edist x y)) h fun _ _ => rfl /-- Build a new pseudometric space from an old one where the bundled bornology structure is provably (but typically non-definitionaly) equal to some given bornology structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceBornology {α} [B : Bornology α] (m : PseudoMetricSpace α) (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : PseudoMetricSpace α := { m with toBornology := B cobounded_sets := Set.ext <| compl_surjective.forall.2 fun s => (H s).trans <| by rw [isBounded_iff, mem_setOf_eq, compl_compl] } theorem PseudoMetricSpace.replaceBornology_eq {α} [m : PseudoMetricSpace α] [B : Bornology α] (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : PseudoMetricSpace.replaceBornology _ H = m := by ext rfl -- ensure that the uniformity is unchanged when replacing the bornology. example {α} [B : Bornology α] (m : PseudoMetricSpace α) (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : (PseudoMetricSpace.replaceBornology m H).toUniformSpace = m.toUniformSpace := by with_reducible_and_instances rfl section Real /-- Instantiate the reals as a pseudometric space. -/ instance Real.pseudoMetricSpace : PseudoMetricSpace ℝ where dist x y := |x - y| dist_self := by simp [abs_zero] dist_comm _ _ := abs_sub_comm _ _ dist_triangle _ _ _ := abs_sub_le _ _ _ theorem Real.dist_eq (x y : ℝ) : dist x y = |x - y| := rfl theorem Real.nndist_eq (x y : ℝ) : nndist x y = Real.nnabs (x - y) := rfl theorem Real.nndist_eq' (x y : ℝ) : nndist x y = Real.nnabs (y - x) := nndist_comm _ _ theorem Real.dist_0_eq_abs (x : ℝ) : dist x 0 = |x| := by simp [Real.dist_eq] theorem Real.sub_le_dist (x y : ℝ) : x - y ≤ dist x y := by rw [Real.dist_eq, le_abs] exact Or.inl (le_refl _) theorem Real.ball_eq_Ioo (x r : ℝ) : ball x r = Ioo (x - r) (x + r) := Set.ext fun y => by rw [mem_ball, dist_comm, Real.dist_eq, abs_sub_lt_iff, mem_Ioo, ← sub_lt_iff_lt_add', sub_lt_comm] theorem Real.closedBall_eq_Icc {x r : ℝ} : closedBall x r = Icc (x - r) (x + r) := by ext y rw [mem_closedBall, dist_comm, Real.dist_eq, abs_sub_le_iff, mem_Icc, ← sub_le_iff_le_add', sub_le_comm] theorem Real.Ioo_eq_ball (x y : ℝ) : Ioo x y = ball ((x + y) / 2) ((y - x) / 2) := by rw [Real.ball_eq_Ioo, ← sub_div, add_comm, ← sub_add, add_sub_cancel_left, add_self_div_two, ← add_div, add_assoc, add_sub_cancel, add_self_div_two] theorem Real.Icc_eq_closedBall (x y : ℝ) : Icc x y = closedBall ((x + y) / 2) ((y - x) / 2) := by rw [Real.closedBall_eq_Icc, ← sub_div, add_comm, ← sub_add, add_sub_cancel_left, add_self_div_two, ← add_div, add_assoc, add_sub_cancel, add_self_div_two] theorem Metric.uniformity_eq_comap_nhds_zero : 𝓤 α = comap (fun p : α × α => dist p.1 p.2) (𝓝 (0 : ℝ)) := by ext s simp only [mem_uniformity_dist, (nhds_basis_ball.comap _).mem_iff] simp [subset_def, Real.dist_0_eq_abs] theorem tendsto_uniformity_iff_dist_tendsto_zero {f : ι → α × α} {p : Filter ι} : Tendsto f p (𝓤 α) ↔ Tendsto (fun x => dist (f x).1 (f x).2) p (𝓝 0) := by rw [Metric.uniformity_eq_comap_nhds_zero, tendsto_comap_iff, Function.comp_def] theorem Filter.Tendsto.congr_dist {f₁ f₂ : ι → α} {p : Filter ι} {a : α} (h₁ : Tendsto f₁ p (𝓝 a)) (h : Tendsto (fun x => dist (f₁ x) (f₂ x)) p (𝓝 0)) : Tendsto f₂ p (𝓝 a) := h₁.congr_uniformity <| tendsto_uniformity_iff_dist_tendsto_zero.2 h alias tendsto_of_tendsto_of_dist := Filter.Tendsto.congr_dist theorem tendsto_iff_of_dist {f₁ f₂ : ι → α} {p : Filter ι} {a : α} (h : Tendsto (fun x => dist (f₁ x) (f₂ x)) p (𝓝 0)) : Tendsto f₁ p (𝓝 a) ↔ Tendsto f₂ p (𝓝 a) := Uniform.tendsto_congr <| tendsto_uniformity_iff_dist_tendsto_zero.2 h end Real theorem PseudoMetricSpace.dist_eq_of_dist_zero (x : α) {y z : α} (h : dist y z = 0) : dist x y = dist x z := dist_comm y x ▸ dist_comm z x ▸ sub_eq_zero.1 (abs_nonpos_iff.1 (h ▸ abs_dist_sub_le y z x)) theorem dist_dist_dist_le_left (x y z : α) : dist (dist x z) (dist y z) ≤ dist x y := abs_dist_sub_le .. theorem dist_dist_dist_le_right (x y z : α) : dist (dist x y) (dist x z) ≤ dist y z := by simpa only [dist_comm x] using dist_dist_dist_le_left y z x theorem dist_dist_dist_le (x y x' y' : α) : dist (dist x y) (dist x' y') ≤ dist x x' + dist y y' := (dist_triangle _ _ _).trans <| add_le_add (dist_dist_dist_le_left _ _ _) (dist_dist_dist_le_right _ _ _) theorem nhds_comap_dist (a : α) : ((𝓝 (0 : ℝ)).comap (dist · a)) = 𝓝 a := by simp only [@nhds_eq_comap_uniformity α, Metric.uniformity_eq_comap_nhds_zero, comap_comap, Function.comp_def, dist_comm] theorem tendsto_iff_dist_tendsto_zero {f : β → α} {x : Filter β} {a : α} : Tendsto f x (𝓝 a) ↔ Tendsto (fun b => dist (f b) a) x (𝓝 0) := by rw [← nhds_comap_dist a, tendsto_comap_iff, Function.comp_def] namespace Metric variable {x y z : α} {ε ε₁ ε₂ : ℝ} {s : Set α} theorem ball_subset_interior_closedBall : ball x ε ⊆ interior (closedBall x ε) := interior_maximal ball_subset_closedBall isOpen_ball /-- ε-characterization of the closure in pseudometric spaces -/ theorem mem_closure_iff {s : Set α} {a : α} : a ∈ closure s ↔ ∀ ε > 0, ∃ b ∈ s, dist a b < ε := (mem_closure_iff_nhds_basis nhds_basis_ball).trans <| by simp only [mem_ball, dist_comm] theorem mem_closure_range_iff {e : β → α} {a : α} : a ∈ closure (range e) ↔ ∀ ε > 0, ∃ k : β, dist a (e k) < ε := by simp only [mem_closure_iff, exists_range_iff] theorem mem_closure_range_iff_nat {e : β → α} {a : α} : a ∈ closure (range e) ↔ ∀ n : ℕ, ∃ k : β, dist a (e k) < 1 / ((n : ℝ) + 1) := (mem_closure_iff_nhds_basis nhds_basis_ball_inv_nat_succ).trans <| by simp only [mem_ball, dist_comm, exists_range_iff, forall_const] theorem mem_of_closed' {s : Set α} (hs : IsClosed s) {a : α} : a ∈ s ↔ ∀ ε > 0, ∃ b ∈ s, dist a b < ε := by simpa only [hs.closure_eq] using @mem_closure_iff _ _ s a theorem dense_iff {s : Set α} : Dense s ↔ ∀ x, ∀ r > 0, (ball x r ∩ s).Nonempty := forall_congr' fun x => by simp only [mem_closure_iff, Set.Nonempty, exists_prop, mem_inter_iff, mem_ball', and_comm] theorem dense_iff_iUnion_ball (s : Set α) : Dense s ↔ ∀ r > 0, ⋃ c ∈ s, ball c r = univ := by simp_rw [eq_univ_iff_forall, mem_iUnion, exists_prop, mem_ball, Dense, mem_closure_iff, forall_comm (α := α)] theorem denseRange_iff {f : β → α} : DenseRange f ↔ ∀ x, ∀ r > 0, ∃ y, dist x (f y) < r := forall_congr' fun x => by simp only [mem_closure_iff, exists_range_iff] end Metric open Additive Multiplicative instance : PseudoMetricSpace (Additive α) := ‹_› instance : PseudoMetricSpace (Multiplicative α) := ‹_› section variable [PseudoMetricSpace X] @[simp] theorem nndist_ofMul (a b : X) : nndist (ofMul a) (ofMul b) = nndist a b := rfl @[simp] theorem nndist_ofAdd (a b : X) : nndist (ofAdd a) (ofAdd b) = nndist a b := rfl @[simp] theorem nndist_toMul (a b : Additive X) : nndist a.toMul b.toMul = nndist a b := rfl @[simp] theorem nndist_toAdd (a b : Multiplicative X) : nndist a.toAdd b.toAdd = nndist a b := rfl end open OrderDual instance : PseudoMetricSpace αᵒᵈ := ‹_› section variable [PseudoMetricSpace X] @[simp] theorem nndist_toDual (a b : X) : nndist (toDual a) (toDual b) = nndist a b := rfl @[simp] theorem nndist_ofDual (a b : Xᵒᵈ) : nndist (ofDual a) (ofDual b) = nndist a b := rfl end
Mathlib/Topology/MetricSpace/Pseudo/Defs.lean
1,357
1,357
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Abhimanyu Pallavi Sudhir -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Order.CauSeq.BigOperators import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Complex.BigOperators import Mathlib.Data.Complex.Norm import Mathlib.Data.Nat.Choose.Sum /-! # Exponential Function This file contains the definitions of the real and complex exponential function. ## Main definitions * `Complex.exp`: The complex exponential function, defined via its Taylor series * `Real.exp`: The real exponential function, defined as the real part of the complex exponential -/ open CauSeq Finset IsAbsoluteValue open scoped ComplexConjugate namespace Complex theorem isCauSeq_norm_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ := let ⟨n, hn⟩ := exists_nat_gt ‖z‖ have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0)) (by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div, norm_natCast] gcongr exact le_trans hm (Nat.le_succ _) @[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp noncomputable section theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial := (isCauSeq_norm_exp z).of_abv /-- The Cauchy sequence consisting of partial sums of the Taylor series of the complex exponential function -/ @[pp_nodot] def exp' (z : ℂ) : CauSeq ℂ (‖·‖) := ⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩ /-- The complex exponential function, defined via its Taylor series -/ @[pp_nodot] def exp (z : ℂ) : ℂ := CauSeq.lim (exp' z) /-- scoped notation for the complex exponential function -/ scoped notation "cexp" => Complex.exp end end Complex namespace Real open Complex noncomputable section /-- The real exponential function, defined as the real part of the complex exponential -/ @[pp_nodot] nonrec def exp (x : ℝ) : ℝ := (exp x).re /-- scoped notation for the real exponential function -/ scoped notation "rexp" => Real.exp end end Real namespace Complex variable (x y : ℂ) @[simp] theorem exp_zero : exp 0 = 1 := by rw [exp] refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩ convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε rcases j with - | j · exact absurd hj (not_le_of_gt zero_lt_one) · dsimp [exp'] induction' j with j ih · dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl] · rw [← ih (by simp [Nat.succ_le_succ])] simp only [sum_range_succ, pow_succ] simp theorem exp_add : exp (x + y) = exp x * exp y := by have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) = ∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial * (y ^ (i - k) / (i - k).factorial) := by intro j refine Finset.sum_congr rfl fun m _ => ?_ rw [add_pow, div_eq_mul_inv, sum_mul] refine Finset.sum_congr rfl fun I hi => ?_ have h₁ : (m.choose I : ℂ) ≠ 0 := Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi)))) have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi) rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv] simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹, mul_comm (m.choose I : ℂ)] rw [inv_mul_cancel₀ h₁] simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm] simp_rw [exp, exp', lim_mul_lim] apply (lim_eq_lim_of_equiv _).symm simp only [hj] exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y) /-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ := { toFun := fun z => exp z.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℂ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℂ) expMonoidHom f s lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _ theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n | 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero] | Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul] @[simp] theorem exp_ne_zero : exp x ≠ 0 := fun h => zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp theorem exp_neg : exp (-x) = (exp x)⁻¹ := by rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by cases n · simp [exp_nat_mul] · simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul] @[simp] theorem exp_conj : exp (conj x) = conj (exp x) := by dsimp [exp] rw [← lim_conj] refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_) dsimp [exp', Function.comp_def, cauSeqConj] rw [map_sum (starRingEnd _)] refine sum_congr rfl fun n _ => ?_ rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal] @[simp] theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x := conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal] @[simp, norm_cast] theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x := ofReal_exp_ofReal_re _ @[simp] theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im] theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x := rfl end Complex namespace Real open Complex variable (x y : ℝ) @[simp] theorem exp_zero : exp 0 = 1 := by simp [Real.exp] nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp] /-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ := { toFun := fun x => exp x.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℝ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℝ) expMonoidHom f s lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _ nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n := ofReal_injective (by simp [exp_nat_mul]) @[simp] nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h => exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ := ofReal_injective <| by simp [exp_neg] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] open IsAbsoluteValue Nat theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x := calc ∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp only [exp', const_apply, re_sum] norm_cast refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_ positivity _ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re] lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x := calc x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! := single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n) _ ≤ exp x := sum_le_exp_of_nonneg hx _ theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x := calc 1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one, ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one, cast_succ, add_right_inj] ring_nf _ ≤ exp x := sum_le_exp_of_nonneg hx 3 private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x := (by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le) private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by rcases eq_or_lt_of_le hx with (rfl | h) · simp exact (add_one_lt_exp_of_pos h).le theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx] @[bound] theorem exp_pos (x : ℝ) : 0 < exp x := (le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by rw [← neg_neg x, Real.exp_neg] exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h))) @[bound] lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le @[simp] theorem abs_exp (x : ℝ) : |exp x| = exp x := abs_of_pos (exp_pos _) lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *] @[mono] theorem exp_strictMono : StrictMono exp := fun x y h => by rw [← sub_add_cancel y x, Real.exp_add] exact (lt_mul_iff_one_lt_left (exp_pos _)).2 (lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith))) @[gcongr] theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h @[mono] theorem exp_monotone : Monotone exp := exp_strictMono.monotone @[gcongr, bound] theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h @[simp] theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y := exp_strictMono.lt_iff_lt @[simp] theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y := exp_strictMono.le_iff_le theorem exp_injective : Function.Injective exp := exp_strictMono.injective @[simp] theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y := exp_injective.eq_iff @[simp] theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 := exp_injective.eq_iff' exp_zero @[simp] theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp] @[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff @[simp] theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp] @[simp] theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 := exp_zero ▸ exp_le_exp @[simp] theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x := exp_zero ▸ exp_le_exp end Real namespace Complex theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α] (n j : ℕ) (hn : 0 < n) : (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) := calc (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) = ∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;> simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le] _ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by simp_rw [one_div] gcongr rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm] exact Nat.factorial_mul_pow_le_factorial _ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow] _ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by have h₁ : (n.succ : α) ≠ 1 := @Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn)) have h₂ : (n.succ : α) ≠ 0 := by positivity have h₃ : (n.factorial * n : α) ≠ 0 := by positivity have h₄ : (n.succ - 1 : α) = n := by simp rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α), ← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α), mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm] _ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr rw [Complex.norm_pow] exact pow_le_one₀ (norm_nonneg _) hx _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by simp [abs_mul, abv_pow abs, abs_div, ← mul_sum] _ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by gcongr exact sum_div_factorial_le _ _ hn theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 let k := j - n have hj : j = n + k := (add_tsub_cancel_of_le hj).symm rw [hj, sum_range_add_sub_sum_range] calc ‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤ ∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ := IsAbsoluteValue.abv_sum _ _ _ _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by simp [norm_natCast, Complex.norm_pow] _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_ _ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_ _ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_ · gcongr exact mod_cast Nat.factorial_mul_pow_le_factorial · refine Finset.sum_congr rfl fun _ _ => ?_ simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc] · rw [← mul_sum] gcongr simp_rw [← div_pow] rw [geom_sum_eq, div_le_iff_of_neg] · trans (-1 : ℝ) · linarith · simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left] positivity · linarith · linarith theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ := calc ‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ] _ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial] theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 := calc ‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial] _ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial] _ = ‖x‖ ^ 2 := by rw [mul_one] lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ _ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj] refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_ congr with i simp [Complex.norm_pow] _ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by gcongr exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _ lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _ rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr with i hi · rw [Complex.norm_pow] · simp _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by rw [← mul_sum] _ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by congr 1 refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm · intro a ha simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true] simp only [mem_range] at ha rwa [← lt_tsub_iff_right] · intro a ha b hb hab simpa using hab · intro b hb simp only [mem_range, exists_prop] simp only [mem_filter, mem_range] at hb refine ⟨b - n, ?_, ?_⟩ · rw [tsub_lt_tsub_iff_right hb.2] exact hb.1 · rw [tsub_add_cancel_of_le hb.2] · simp _ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by gcongr refine Real.sum_le_exp_of_nonneg ?_ _ exact norm_nonneg _ @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum := norm_exp_sub_sum_le_exp_norm_sub_sum @[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp := norm_exp_sub_sum_le_norm_mul_exp end Complex namespace Real open Complex Finset nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) : |exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx convert exp_bound hxc hn using 2 <;> norm_cast theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) : Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) + x ^ n * (n + 1) / (n.factorial * n) := by have h3 : |x| = x := by simpa have h4 : |x| ≤ 1 := by rwa [h3] have h' := Real.exp_bound h4 hn rw [h3] at h' have h'' := (abs_sub_le_iff.1 h').1 have t := sub_le_iff_le_add'.1 h'' simpa [mul_div_assoc] using t theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by rw [← sq_abs] have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_sub_id_le this /-- A finite initial segment of the exponential series, followed by an arbitrary tail. For fixed `n` this is just a linear map wrt `r`, and each map is a simple linear function of the previous (see `expNear_succ`), with `expNear n x r ⟶ exp x` as `n ⟶ ∞`, for any `r`. -/ noncomputable def expNear (n : ℕ) (x r : ℝ) : ℝ := (∑ m ∈ range n, x ^ m / m.factorial) + x ^ n / n.factorial * r @[simp] theorem expNear_zero (x r) : expNear 0 x r = r := by simp [expNear] @[simp] theorem expNear_succ (n x r) : expNear (n + 1) x r = expNear n x (1 + x / (n + 1) * r) := by simp [expNear, range_succ, mul_add, add_left_comm, add_assoc, pow_succ, div_eq_mul_inv, mul_inv, Nat.factorial] ac_rfl theorem expNear_sub (n x r₁ r₂) : expNear n x r₁ - expNear n x r₂ = x ^ n / n.factorial * (r₁ - r₂) := by simp [expNear, mul_sub] theorem exp_approx_end (n m : ℕ) (x : ℝ) (e₁ : n + 1 = m) (h : |x| ≤ 1) : |exp x - expNear m x 0| ≤ |x| ^ m / m.factorial * ((m + 1) / m) := by simp only [expNear, mul_zero, add_zero] convert exp_bound (n := m) h ?_ using 1 · field_simp [mul_comm] · omega theorem exp_approx_succ {n} {x a₁ b₁ : ℝ} (m : ℕ) (e₁ : n + 1 = m) (a₂ b₂ : ℝ) (e : |1 + x / m * a₂ - a₁| ≤ b₁ - |x| / m * b₂) (h : |exp x - expNear m x a₂| ≤ |x| ^ m / m.factorial * b₂) : |exp x - expNear n x a₁| ≤ |x| ^ n / n.factorial * b₁ := by refine (abs_sub_le _ _ _).trans ((add_le_add_right h _).trans ?_) subst e₁; rw [expNear_succ, expNear_sub, abs_mul] convert mul_le_mul_of_nonneg_left (a := |x| ^ n / ↑(Nat.factorial n)) (le_sub_iff_add_le'.1 e) ?_ using 1 · simp [mul_add, pow_succ', div_eq_mul_inv, abs_mul, abs_inv, ← pow_abs, mul_inv, Nat.factorial] ac_rfl · simp [div_nonneg, abs_nonneg] theorem exp_approx_end' {n} {x a b : ℝ} (m : ℕ) (e₁ : n + 1 = m) (rm : ℝ) (er : ↑m = rm) (h : |x| ≤ 1) (e : |1 - a| ≤ b - |x| / rm * ((rm + 1) / rm)) : |exp x - expNear n x a| ≤ |x| ^ n / n.factorial * b := by subst er exact exp_approx_succ _ e₁ _ _ (by simpa using e) (exp_approx_end _ _ _ e₁ h) theorem exp_1_approx_succ_eq {n} {a₁ b₁ : ℝ} {m : ℕ} (en : n + 1 = m) {rm : ℝ} (er : ↑m = rm) (h : |exp 1 - expNear m 1 ((a₁ - 1) * rm)| ≤ |1| ^ m / m.factorial * (b₁ * rm)) : |exp 1 - expNear n 1 a₁| ≤ |1| ^ n / n.factorial * b₁ := by subst er refine exp_approx_succ _ en _ _ ?_ h field_simp [show (m : ℝ) ≠ 0 by norm_cast; omega] theorem exp_approx_start (x a b : ℝ) (h : |exp x - expNear 0 x a| ≤ |x| ^ 0 / Nat.factorial 0 * b) : |exp x - a| ≤ b := by simpa using h theorem exp_bound_div_one_sub_of_interval' {x : ℝ} (h1 : 0 < x) (h2 : x < 1) : Real.exp x < 1 / (1 - x) := by have H : 0 < 1 - (1 + x + x ^ 2) * (1 - x) := calc 0 < x ^ 3 := by positivity _ = 1 - (1 + x + x ^ 2) * (1 - x) := by ring calc exp x ≤ _ := exp_bound' h1.le h2.le zero_lt_three _ ≤ 1 + x + x ^ 2 := by -- Porting note: was `norm_num [Finset.sum] <;> nlinarith` -- This proof should be restored after the norm_num plugin for big operators is ported. -- (It may also need the positivity extensions in https://github.com/leanprover-community/mathlib4/pull/3907.) rw [show 3 = 1 + 1 + 1 from rfl] repeat rw [Finset.sum_range_succ] norm_num [Nat.factorial] nlinarith _ < 1 / (1 - x) := by rw [lt_div_iff₀] <;> nlinarith theorem exp_bound_div_one_sub_of_interval {x : ℝ} (h1 : 0 ≤ x) (h2 : x < 1) : Real.exp x ≤ 1 / (1 - x) := by rcases eq_or_lt_of_le h1 with (rfl | h1) · simp · exact (exp_bound_div_one_sub_of_interval' h1 h2).le theorem add_one_lt_exp {x : ℝ} (hx : x ≠ 0) : x + 1 < Real.exp x := by obtain hx | hx := hx.symm.lt_or_lt · exact add_one_lt_exp_of_pos hx obtain h' | h' := le_or_lt 1 (-x) · linarith [x.exp_pos] have hx' : 0 < x + 1 := by linarith simpa [add_comm, exp_neg, inv_lt_inv₀ (exp_pos _) hx'] using exp_bound_div_one_sub_of_interval' (neg_pos.2 hx) h' theorem add_one_le_exp (x : ℝ) : x + 1 ≤ Real.exp x := by obtain rfl | hx := eq_or_ne x 0 · simp · exact (add_one_lt_exp hx).le lemma one_sub_lt_exp_neg {x : ℝ} (hx : x ≠ 0) : 1 - x < exp (-x) := (sub_eq_neg_add _ _).trans_lt <| add_one_lt_exp <| neg_ne_zero.2 hx lemma one_sub_le_exp_neg (x : ℝ) : 1 - x ≤ exp (-x) := (sub_eq_neg_add _ _).trans_le <| add_one_le_exp _ theorem one_sub_div_pow_le_exp_neg {n : ℕ} {t : ℝ} (ht' : t ≤ n) : (1 - t / n) ^ n ≤ exp (-t) := by rcases eq_or_ne n 0 with (rfl | hn) · simp rwa [Nat.cast_zero] at ht' calc (1 - t / n) ^ n ≤ rexp (-(t / n)) ^ n := by gcongr · exact sub_nonneg.2 <| div_le_one_of_le₀ ht' n.cast_nonneg · exact one_sub_le_exp_neg _ _ = rexp (-t) := by rw [← Real.exp_nat_mul, mul_neg, mul_comm, div_mul_cancel₀]; positivity lemma le_inv_mul_exp (x : ℝ) {c : ℝ} (hc : 0 < c) : x ≤ c⁻¹ * exp (c * x) := by rw [le_inv_mul_iff₀ hc] calc c * x _ ≤ c * x + 1 := le_add_of_nonneg_right zero_le_one _ ≤ _ := Real.add_one_le_exp (c * x) end Real namespace Mathlib.Meta.Positivity open Lean.Meta Qq /-- Extension for the `positivity` tactic: `Real.exp` is always positive. -/ @[positivity Real.exp _] def evalExp : PositivityExt where eval {u α} _ _ e := do match u, α, e with | 0, ~q(ℝ), ~q(Real.exp $a) => assertInstancesCommute pure (.positive q(Real.exp_pos $a)) | _, _, _ => throwError "not Real.exp" end Mathlib.Meta.Positivity namespace Complex @[simp] theorem norm_exp_ofReal (x : ℝ) : ‖exp x‖ = Real.exp x := by rw [← ofReal_exp] exact Complex.norm_of_nonneg (le_of_lt (Real.exp_pos _)) @[deprecated (since := "2025-02-16")] alias abs_exp_ofReal := norm_exp_ofReal end Complex
Mathlib/Data/Complex/Exponential.lean
1,096
1,096
/- Copyright (c) 2023 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Analysis.RCLike.Basic import Mathlib.Dynamics.BirkhoffSum.Average /-! # Birkhoff average in a normed space In this file we prove some lemmas about the Birkhoff average (`birkhoffAverage`) of a function which takes values in a normed space over `ℝ` or `ℂ`. At the time of writing, all lemmas in this file are motivated by the proof of the von Neumann Mean Ergodic Theorem, see `LinearIsometry.tendsto_birkhoffAverage_orthogonalProjection`. -/ open Function Set Filter open scoped Topology ENNReal Uniformity section variable {α E : Type*} /-- The Birkhoff averages of a function `g` over the orbit of a fixed point `x` of `f` tend to `g x` as `N → ∞`. In fact, they are equal to `g x` for all `N ≠ 0`, see `Function.IsFixedPt.birkhoffAverage_eq`. TODO: add a version for a periodic orbit. -/ theorem Function.IsFixedPt.tendsto_birkhoffAverage (R : Type*) [DivisionSemiring R] [CharZero R] [AddCommMonoid E] [TopologicalSpace E] [Module R E] {f : α → α} {x : α} (h : f.IsFixedPt x) (g : α → E) : Tendsto (birkhoffAverage R f g · x) atTop (𝓝 (g x)) := tendsto_const_nhds.congr' <| (eventually_ne_atTop 0).mono fun _n hn ↦ (h.birkhoffAverage_eq R g hn).symm variable [NormedAddCommGroup E] theorem dist_birkhoffSum_apply_birkhoffSum (f : α → α) (g : α → E) (n : ℕ) (x : α) : dist (birkhoffSum f g n (f x)) (birkhoffSum f g n x) = dist (g (f^[n] x)) (g x) := by simp only [dist_eq_norm, birkhoffSum_apply_sub_birkhoffSum] theorem dist_birkhoffSum_birkhoffSum_le (f : α → α) (g : α → E) (n : ℕ) (x y : α) : dist (birkhoffSum f g n x) (birkhoffSum f g n y) ≤ ∑ k ∈ Finset.range n, dist (g (f^[k] x)) (g (f^[k] y)) := dist_sum_sum_le _ _ _ variable (𝕜 : Type*) [RCLike 𝕜] [Module 𝕜 E] [IsBoundedSMul 𝕜 E] theorem dist_birkhoffAverage_birkhoffAverage (f : α → α) (g : α → E) (n : ℕ) (x y : α) : dist (birkhoffAverage 𝕜 f g n x) (birkhoffAverage 𝕜 f g n y) = dist (birkhoffSum f g n x) (birkhoffSum f g n y) / n := by simp [birkhoffAverage, dist_smul₀, div_eq_inv_mul] theorem dist_birkhoffAverage_birkhoffAverage_le (f : α → α) (g : α → E) (n : ℕ) (x y : α) : dist (birkhoffAverage 𝕜 f g n x) (birkhoffAverage 𝕜 f g n y) ≤ (∑ k ∈ Finset.range n, dist (g (f^[k] x)) (g (f^[k] y))) / n := (dist_birkhoffAverage_birkhoffAverage _ _ _ _ _ _).trans_le <| by gcongr; apply dist_birkhoffSum_birkhoffSum_le theorem dist_birkhoffAverage_apply_birkhoffAverage (f : α → α) (g : α → E) (n : ℕ) (x : α) : dist (birkhoffAverage 𝕜 f g n (f x)) (birkhoffAverage 𝕜 f g n x) = dist (g (f^[n] x)) (g x) / n := by simp [dist_birkhoffAverage_birkhoffAverage, dist_birkhoffSum_apply_birkhoffSum] /-- If a function `g` is bounded along the positive orbit of `x` under `f`, then the difference between Birkhoff averages of `g` along the orbit of `f x` and along the orbit of `x` tends to zero. See also `tendsto_birkhoffAverage_apply_sub_birkhoffAverage'`. -/
theorem tendsto_birkhoffAverage_apply_sub_birkhoffAverage {f : α → α} {g : α → E} {x : α} (h : Bornology.IsBounded (range (g <| f^[·] x))) : Tendsto (fun n ↦ birkhoffAverage 𝕜 f g n (f x) - birkhoffAverage 𝕜 f g n x) atTop (𝓝 0) := by rcases Metric.isBounded_range_iff.1 h with ⟨C, hC⟩ have : Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := tendsto_const_nhds.div_atTop tendsto_natCast_atTop_atTop refine squeeze_zero_norm (fun n ↦ ?_) this rw [← dist_eq_norm, dist_birkhoffAverage_apply_birkhoffAverage] gcongr exact hC n 0
Mathlib/Dynamics/BirkhoffSum/NormedSpace.lean
75
84
/- Copyright (c) 2020 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Floris van Doorn -/ import Mathlib.Geometry.Manifold.MFDeriv.Defs import Mathlib.Geometry.Manifold.ContMDiff.Defs /-! # Basic properties of the manifold Fréchet derivative In this file, we show various properties of the manifold Fréchet derivative, mimicking the API for Fréchet derivatives. - basic properties of unique differentiability sets - various general lemmas about the manifold Fréchet derivative - deducing differentiability from smoothness, - deriving continuity from differentiability on manifolds, - congruence lemmas for derivatives on manifolds - composition lemmas and the chain rule -/ noncomputable section assert_not_exists tangentBundleCore open scoped Topology Manifold open Set Bundle ChartedSpace section DerivativesProperties /-! ### Unique differentiability sets in manifolds -/ variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H) {M : Type*} [TopologicalSpace M] [ChartedSpace H M] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'} {M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M'] {E'' : Type*} [NormedAddCommGroup E''] [NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H''] {I'' : ModelWithCorners 𝕜 E'' H''} {M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M''] {f f₁ : M → M'} {x : M} {s t : Set M} {g : M' → M''} {u : Set M'} theorem uniqueMDiffWithinAt_univ : UniqueMDiffWithinAt I univ x := by unfold UniqueMDiffWithinAt simp only [preimage_univ, univ_inter] exact I.uniqueDiffOn _ (mem_range_self _) variable {I} theorem uniqueMDiffWithinAt_iff_inter_range {s : Set M} {x : M} : UniqueMDiffWithinAt I s x ↔ UniqueDiffWithinAt 𝕜 ((extChartAt I x).symm ⁻¹' s ∩ range I) ((extChartAt I x) x) := Iff.rfl theorem uniqueMDiffWithinAt_iff {s : Set M} {x : M} : UniqueMDiffWithinAt I s x ↔ UniqueDiffWithinAt 𝕜 ((extChartAt I x).symm ⁻¹' s ∩ (extChartAt I x).target) ((extChartAt I x) x) := by apply uniqueDiffWithinAt_congr rw [nhdsWithin_inter, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq] nonrec theorem UniqueMDiffWithinAt.mono_nhds {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x) (ht : 𝓝[s] x ≤ 𝓝[t] x) : UniqueMDiffWithinAt I t x := hs.mono_nhds <| by simpa only [← map_extChartAt_nhdsWithin] using Filter.map_mono ht theorem UniqueMDiffWithinAt.mono_of_mem_nhdsWithin {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝[s] x) : UniqueMDiffWithinAt I t x := hs.mono_nhds (nhdsWithin_le_iff.2 ht) @[deprecated (since := "2024-10-31")] alias UniqueMDiffWithinAt.mono_of_mem := UniqueMDiffWithinAt.mono_of_mem_nhdsWithin theorem UniqueMDiffWithinAt.mono (h : UniqueMDiffWithinAt I s x) (st : s ⊆ t) : UniqueMDiffWithinAt I t x := UniqueDiffWithinAt.mono h <| inter_subset_inter (preimage_mono st) (Subset.refl _) theorem UniqueMDiffWithinAt.inter' (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝[s] x) : UniqueMDiffWithinAt I (s ∩ t) x := hs.mono_of_mem_nhdsWithin (Filter.inter_mem self_mem_nhdsWithin ht) theorem UniqueMDiffWithinAt.inter (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝 x) : UniqueMDiffWithinAt I (s ∩ t) x := hs.inter' (nhdsWithin_le_nhds ht) theorem IsOpen.uniqueMDiffWithinAt (hs : IsOpen s) (xs : x ∈ s) : UniqueMDiffWithinAt I s x := (uniqueMDiffWithinAt_univ I).mono_of_mem_nhdsWithin <| nhdsWithin_le_nhds <| hs.mem_nhds xs theorem UniqueMDiffOn.inter (hs : UniqueMDiffOn I s) (ht : IsOpen t) : UniqueMDiffOn I (s ∩ t) := fun _x hx => UniqueMDiffWithinAt.inter (hs _ hx.1) (ht.mem_nhds hx.2) theorem IsOpen.uniqueMDiffOn (hs : IsOpen s) : UniqueMDiffOn I s := fun _x hx => hs.uniqueMDiffWithinAt hx theorem uniqueMDiffOn_univ : UniqueMDiffOn I (univ : Set M) := isOpen_univ.uniqueMDiffOn nonrec theorem UniqueMDiffWithinAt.prod {x : M} {y : M'} {s t} (hs : UniqueMDiffWithinAt I s x) (ht : UniqueMDiffWithinAt I' t y) : UniqueMDiffWithinAt (I.prod I') (s ×ˢ t) (x, y) := by refine (hs.prod ht).mono ?_ rw [ModelWithCorners.range_prod, ← prod_inter_prod] rfl theorem UniqueMDiffOn.prod {s : Set M} {t : Set M'} (hs : UniqueMDiffOn I s) (ht : UniqueMDiffOn I' t) : UniqueMDiffOn (I.prod I') (s ×ˢ t) := fun x h ↦ (hs x.1 h.1).prod (ht x.2 h.2) theorem MDifferentiableWithinAt.mono (hst : s ⊆ t) (h : MDifferentiableWithinAt I I' f t x) : MDifferentiableWithinAt I I' f s x := ⟨ContinuousWithinAt.mono h.1 hst, DifferentiableWithinAt.mono h.differentiableWithinAt_writtenInExtChartAt (inter_subset_inter_left _ (preimage_mono hst))⟩ theorem mdifferentiableWithinAt_univ : MDifferentiableWithinAt I I' f univ x ↔ MDifferentiableAt I I' f x := by simp_rw [MDifferentiableWithinAt, MDifferentiableAt, ChartedSpace.LiftPropAt] theorem mdifferentiableWithinAt_inter (ht : t ∈ 𝓝 x) : MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by rw [MDifferentiableWithinAt, MDifferentiableWithinAt, differentiableWithinAt_localInvariantProp.liftPropWithinAt_inter ht] theorem mdifferentiableWithinAt_inter' (ht : t ∈ 𝓝[s] x) : MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by rw [MDifferentiableWithinAt, MDifferentiableWithinAt, differentiableWithinAt_localInvariantProp.liftPropWithinAt_inter' ht] theorem MDifferentiableAt.mdifferentiableWithinAt (h : MDifferentiableAt I I' f x) : MDifferentiableWithinAt I I' f s x := MDifferentiableWithinAt.mono (subset_univ _) (mdifferentiableWithinAt_univ.2 h) theorem MDifferentiableWithinAt.mdifferentiableAt (h : MDifferentiableWithinAt I I' f s x) (hs : s ∈ 𝓝 x) : MDifferentiableAt I I' f x := by have : s = univ ∩ s := by rw [univ_inter] rwa [this, mdifferentiableWithinAt_inter hs, mdifferentiableWithinAt_univ] at h theorem MDifferentiableOn.mono (h : MDifferentiableOn I I' f t) (st : s ⊆ t) : MDifferentiableOn I I' f s := fun x hx => (h x (st hx)).mono st theorem mdifferentiableOn_univ : MDifferentiableOn I I' f univ ↔ MDifferentiable I I' f := by simp only [MDifferentiableOn, mdifferentiableWithinAt_univ, mfld_simps]; rfl theorem MDifferentiableOn.mdifferentiableAt (h : MDifferentiableOn I I' f s) (hx : s ∈ 𝓝 x) : MDifferentiableAt I I' f x := (h x (mem_of_mem_nhds hx)).mdifferentiableAt hx theorem MDifferentiable.mdifferentiableOn (h : MDifferentiable I I' f) : MDifferentiableOn I I' f s := (mdifferentiableOn_univ.2 h).mono (subset_univ _) theorem mdifferentiableOn_of_locally_mdifferentiableOn (h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ MDifferentiableOn I I' f (s ∩ u)) : MDifferentiableOn I I' f s := by intro x xs rcases h x xs with ⟨t, t_open, xt, ht⟩ exact (mdifferentiableWithinAt_inter (t_open.mem_nhds xt)).1 (ht x ⟨xs, xt⟩) theorem MDifferentiable.mdifferentiableAt (hf : MDifferentiable I I' f) : MDifferentiableAt I I' f x := hf x /-! ### Relating differentiability in a manifold and differentiability in the model space through extended charts -/ theorem mdifferentiableWithinAt_iff_target_inter {f : M → M'} {s : Set M} {x : M} : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ DifferentiableWithinAt 𝕜 (writtenInExtChartAt I I' x f) ((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' s) ((extChartAt I x) x) := by rw [mdifferentiableWithinAt_iff'] refine and_congr Iff.rfl (exists_congr fun f' => ?_) rw [inter_comm] simp only [HasFDerivWithinAt, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq] /-- One can reformulate smoothness within a set at a point as continuity within this set at this point, and smoothness in the corresponding extended chart. -/ theorem mdifferentiableWithinAt_iff : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ DifferentiableWithinAt 𝕜 (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm) ((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x) := by simp_rw [MDifferentiableWithinAt, ChartedSpace.liftPropWithinAt_iff']; rfl /-- One can reformulate smoothness within a set at a point as continuity within this set at this point, and smoothness in the corresponding extended chart. This form states smoothness of `f` written in such a way that the set is restricted to lie within the domain/codomain of the corresponding charts. Even though this expression is more complicated than the one in `mdifferentiableWithinAt_iff`, it is a smaller set, but their germs at `extChartAt I x x` are equal. It is sometimes useful to rewrite using this in the goal. -/ theorem mdifferentiableWithinAt_iff_target_inter' : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ DifferentiableWithinAt 𝕜 (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm) ((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' (f x)).source)) (extChartAt I x x) := by simp only [MDifferentiableWithinAt, liftPropWithinAt_iff'] exact and_congr_right fun hc => differentiableWithinAt_congr_nhds <| hc.nhdsWithin_extChartAt_symm_preimage_inter_range /-- One can reformulate smoothness within a set at a point as continuity within this set at this point, and smoothness in the corresponding extended chart in the target. -/ theorem mdifferentiableWithinAt_iff_target : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ MDifferentiableWithinAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) s x := by simp_rw [MDifferentiableWithinAt, liftPropWithinAt_iff', ← and_assoc] have cont : ContinuousWithinAt f s x ∧ ContinuousWithinAt (extChartAt I' (f x) ∘ f) s x ↔ ContinuousWithinAt f s x := and_iff_left_of_imp <| (continuousAt_extChartAt _).comp_continuousWithinAt simp_rw [cont, DifferentiableWithinAtProp, extChartAt, PartialHomeomorph.extend, PartialEquiv.coe_trans, ModelWithCorners.toPartialEquiv_coe, PartialHomeomorph.coe_coe, modelWithCornersSelf_coe, chartAt_self_eq, PartialHomeomorph.refl_apply] rfl theorem mdifferentiableAt_iff_target {x : M} : MDifferentiableAt I I' f x ↔ ContinuousAt f x ∧ MDifferentiableAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) x := by rw [← mdifferentiableWithinAt_univ, ← mdifferentiableWithinAt_univ, mdifferentiableWithinAt_iff_target, continuousWithinAt_univ] section IsManifold variable {e : PartialHomeomorph M H} {e' : PartialHomeomorph M' H'} open IsManifold theorem mdifferentiableWithinAt_iff_source_of_mem_maximalAtlas [IsManifold I 1 M] (he : e ∈ maximalAtlas I 1 M) (hx : x ∈ e.source) : MDifferentiableWithinAt I I' f s x ↔ MDifferentiableWithinAt 𝓘(𝕜, E) I' (f ∘ (e.extend I).symm) ((e.extend I).symm ⁻¹' s ∩ range I) (e.extend I x) := by have h2x := hx; rw [← e.extend_source (I := I)] at h2x simp_rw [MDifferentiableWithinAt, differentiableWithinAt_localInvariantProp.liftPropWithinAt_indep_chart_source he hx, StructureGroupoid.liftPropWithinAt_self_source, e.extend_symm_continuousWithinAt_comp_right_iff, differentiableWithinAtProp_self_source, DifferentiableWithinAtProp, Function.comp, e.left_inv hx, (e.extend I).left_inv h2x] rfl theorem mdifferentiableWithinAt_iff_source_of_mem_source [IsManifold I 1 M] {x' : M} (hx' : x' ∈ (chartAt H x).source) : MDifferentiableWithinAt I I' f s x' ↔ MDifferentiableWithinAt 𝓘(𝕜, E) I' (f ∘ (extChartAt I x).symm) ((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x') := mdifferentiableWithinAt_iff_source_of_mem_maximalAtlas (chart_mem_maximalAtlas x) hx' theorem mdifferentiableAt_iff_source_of_mem_source [IsManifold I 1 M] {x' : M} (hx' : x' ∈ (chartAt H x).source) : MDifferentiableAt I I' f x' ↔ MDifferentiableWithinAt 𝓘(𝕜, E) I' (f ∘ (extChartAt I x).symm) (range I) (extChartAt I x x') := by simp_rw [← mdifferentiableWithinAt_univ, mdifferentiableWithinAt_iff_source_of_mem_source hx', preimage_univ, univ_inter] theorem mdifferentiableWithinAt_iff_target_of_mem_source [IsManifold I' 1 M'] {x : M} {y : M'} (hy : f x ∈ (chartAt H' y).source) : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ MDifferentiableWithinAt I 𝓘(𝕜, E') (extChartAt I' y ∘ f) s x := by simp_rw [MDifferentiableWithinAt] rw [differentiableWithinAt_localInvariantProp.liftPropWithinAt_indep_chart_target (chart_mem_maximalAtlas y) hy, and_congr_right] intro hf simp_rw [StructureGroupoid.liftPropWithinAt_self_target] simp_rw [((chartAt H' y).continuousAt hy).comp_continuousWithinAt hf] rw [← extChartAt_source I'] at hy simp_rw [(continuousAt_extChartAt' hy).comp_continuousWithinAt hf] rfl theorem mdifferentiableAt_iff_target_of_mem_source [IsManifold I' 1 M'] {x : M} {y : M'} (hy : f x ∈ (chartAt H' y).source) : MDifferentiableAt I I' f x ↔ ContinuousAt f x ∧ MDifferentiableAt I 𝓘(𝕜, E') (extChartAt I' y ∘ f) x := by rw [← mdifferentiableWithinAt_univ, mdifferentiableWithinAt_iff_target_of_mem_source hy, continuousWithinAt_univ, ← mdifferentiableWithinAt_univ] variable [IsManifold I 1 M] [IsManifold I' 1 M'] theorem mdifferentiableWithinAt_iff_of_mem_maximalAtlas {x : M} (he : e ∈ maximalAtlas I 1 M) (he' : e' ∈ maximalAtlas I' 1 M') (hx : x ∈ e.source) (hy : f x ∈ e'.source) : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ DifferentiableWithinAt 𝕜 (e'.extend I' ∘ f ∘ (e.extend I).symm) ((e.extend I).symm ⁻¹' s ∩ range I) (e.extend I x) := differentiableWithinAt_localInvariantProp.liftPropWithinAt_indep_chart he hx he' hy /-- An alternative formulation of `mdifferentiableWithinAt_iff_of_mem_maximalAtlas` if the set if `s` lies in `e.source`. -/ theorem mdifferentiableWithinAt_iff_image {x : M} (he : e ∈ maximalAtlas I 1 M) (he' : e' ∈ maximalAtlas I' 1 M') (hs : s ⊆ e.source) (hx : x ∈ e.source) (hy : f x ∈ e'.source) : MDifferentiableWithinAt I I' f s x ↔ ContinuousWithinAt f s x ∧ DifferentiableWithinAt 𝕜 (e'.extend I' ∘ f ∘ (e.extend I).symm) (e.extend I '' s) (e.extend I x) := by rw [mdifferentiableWithinAt_iff_of_mem_maximalAtlas he he' hx hy, and_congr_right_iff] refine fun _ => differentiableWithinAt_congr_nhds ?_ simp_rw [nhdsWithin_eq_iff_eventuallyEq, e.extend_symm_preimage_inter_range_eventuallyEq hs hx] /-- One can reformulate smoothness within a set at a point as continuity within this set at this point, and smoothness in any chart containing that point. -/ theorem mdifferentiableWithinAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) : MDifferentiableWithinAt I I' f s x' ↔ ContinuousWithinAt f s x' ∧ DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) ((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x') := mdifferentiableWithinAt_iff_of_mem_maximalAtlas (chart_mem_maximalAtlas x) (chart_mem_maximalAtlas y) hx hy /-- One can reformulate smoothness within a set at a point as continuity within this set at this point, and smoothness in any chart containing that point. Version requiring differentiability in the target instead of `range I`. -/ theorem mdifferentiableWithinAt_iff_of_mem_source' {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) : MDifferentiableWithinAt I I' f s x' ↔ ContinuousWithinAt f s x' ∧ DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) ((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' y).source)) (extChartAt I x x') := by refine (mdifferentiableWithinAt_iff_of_mem_source hx hy).trans ?_ rw [← extChartAt_source I] at hx rw [← extChartAt_source I'] at hy rw [and_congr_right_iff] set e := extChartAt I x; set e' := extChartAt I' (f x) refine fun hc => differentiableWithinAt_congr_nhds ?_ rw [← e.image_source_inter_eq', ← map_extChartAt_nhdsWithin_eq_image' hx, ← map_extChartAt_nhdsWithin' hx, inter_comm, nhdsWithin_inter_of_mem] exact hc (extChartAt_source_mem_nhds' hy) theorem mdifferentiableAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) : MDifferentiableAt I I' f x' ↔ ContinuousAt f x' ∧ DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (range I) (extChartAt I x x') := (mdifferentiableWithinAt_iff_of_mem_source hx hy).trans <| by rw [continuousWithinAt_univ, preimage_univ, univ_inter] theorem mdifferentiableOn_iff_of_mem_maximalAtlas (he : e ∈ maximalAtlas I 1 M) (he' : e' ∈ maximalAtlas I' 1 M') (hs : s ⊆ e.source) (h2s : MapsTo f s e'.source) : MDifferentiableOn I I' f s ↔ ContinuousOn f s ∧ DifferentiableOn 𝕜 (e'.extend I' ∘ f ∘ (e.extend I).symm) (e.extend I '' s) := by simp_rw [ContinuousOn, DifferentiableOn, Set.forall_mem_image, ← forall_and, MDifferentiableOn] exact forall₂_congr fun x hx => mdifferentiableWithinAt_iff_image he he' hs (hs hx) (h2s hx) /-- Differentiability on a set is equivalent to differentiability in the extended charts. -/ theorem mdifferentiableOn_iff_of_mem_maximalAtlas' (he : e ∈ maximalAtlas I 1 M) (he' : e' ∈ maximalAtlas I' 1 M') (hs : s ⊆ e.source) (h2s : MapsTo f s e'.source) : MDifferentiableOn I I' f s ↔ DifferentiableOn 𝕜 (e'.extend I' ∘ f ∘ (e.extend I).symm) (e.extend I '' s) := (mdifferentiableOn_iff_of_mem_maximalAtlas he he' hs h2s).trans <| and_iff_right_of_imp fun h ↦ (e.continuousOn_writtenInExtend_iff hs h2s).1 h.continuousOn /-- If the set where you want `f` to be smooth lies entirely in a single chart, and `f` maps it into a single chart, the smoothness of `f` on that set can be expressed by purely looking in these charts.
Note: this lemma uses `extChartAt I x '' s` instead of `(extChartAt I x).symm ⁻¹' s` to ensure that this set lies in `(extChartAt I x).target`. -/ theorem mdifferentiableOn_iff_of_subset_source {x : M} {y : M'} (hs : s ⊆ (chartAt H x).source) (h2s : MapsTo f s (chartAt H' y).source) : MDifferentiableOn I I' f s ↔ ContinuousOn f s ∧ DifferentiableOn 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (extChartAt I x '' s) := mdifferentiableOn_iff_of_mem_maximalAtlas (chart_mem_maximalAtlas x) (chart_mem_maximalAtlas y) hs h2s
Mathlib/Geometry/Manifold/MFDeriv/Basic.lean
370
378
/- Copyright (c) 2022 Bolton Bailey. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Bolton Bailey, Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne -/ import Mathlib.Algebra.BigOperators.Field import Mathlib.Analysis.SpecialFunctions.Pow.Real import Mathlib.Data.Int.Log /-! # Real logarithm base `b` In this file we define `Real.logb` to be the logarithm of a real number in a given base `b`. We define this as the division of the natural logarithms of the argument and the base, so that we have a globally defined function with `logb b 0 = 0`, `logb b (-x) = logb b x` `logb 0 x = 0` and `logb (-b) x = logb b x`. We prove some basic properties of this function and its relation to `rpow`. ## Tags logarithm, continuity -/ open Set Filter Function open Topology noncomputable section namespace Real variable {b x y : ℝ} /-- The real logarithm in a given base. As with the natural logarithm, we define `logb b x` to be `logb b |x|` for `x < 0`, and `0` for `x = 0`. -/ @[pp_nodot] noncomputable def logb (b x : ℝ) : ℝ := log x / log b theorem log_div_log : log x / log b = logb b x := rfl @[simp] theorem logb_zero : logb b 0 = 0 := by simp [logb] @[simp] theorem logb_one : logb b 1 = 0 := by simp [logb] theorem logb_zero_left : logb 0 x = 0 := by simp only [← log_div_log, log_zero, div_zero] @[simp] theorem logb_zero_left_eq_zero : logb 0 = 0 := by ext; rw [logb_zero_left, Pi.zero_apply] theorem logb_one_left : logb 1 x = 0 := by simp only [← log_div_log, log_one, div_zero] @[simp] theorem logb_one_left_eq_zero : logb 1 = 0 := by ext; rw [logb_one_left, Pi.zero_apply] @[simp] lemma logb_self_eq_one (hb : 1 < b) : logb b b = 1 := div_self (log_pos hb).ne' lemma logb_self_eq_one_iff : logb b b = 1 ↔ b ≠ 0 ∧ b ≠ 1 ∧ b ≠ -1 := Iff.trans ⟨fun h h' => by simp [logb, h'] at h, div_self⟩ log_ne_zero @[simp] theorem logb_abs (x : ℝ) : logb b |x| = logb b x := by rw [logb, logb, log_abs] @[simp] theorem logb_neg_eq_logb (x : ℝ) : logb b (-x) = logb b x := by rw [← logb_abs x, ← logb_abs (-x), abs_neg] theorem logb_mul (hx : x ≠ 0) (hy : y ≠ 0) : logb b (x * y) = logb b x + logb b y := by simp_rw [logb, log_mul hx hy, add_div] theorem logb_div (hx : x ≠ 0) (hy : y ≠ 0) : logb b (x / y) = logb b x - logb b y := by simp_rw [logb, log_div hx hy, sub_div] @[simp] theorem logb_inv (x : ℝ) : logb b x⁻¹ = -logb b x := by simp [logb, neg_div] theorem inv_logb (a b : ℝ) : (logb a b)⁻¹ = logb b a := by simp_rw [logb, inv_div] theorem inv_logb_mul_base {a b : ℝ} (h₁ : a ≠ 0) (h₂ : b ≠ 0) (c : ℝ) : (logb (a * b) c)⁻¹ = (logb a c)⁻¹ + (logb b c)⁻¹ := by simp_rw [inv_logb]; exact logb_mul h₁ h₂
theorem inv_logb_div_base {a b : ℝ} (h₁ : a ≠ 0) (h₂ : b ≠ 0) (c : ℝ) : (logb (a / b) c)⁻¹ = (logb a c)⁻¹ - (logb b c)⁻¹ := by
Mathlib/Analysis/SpecialFunctions/Log/Base.lean
87
89
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Kenny Lau, Johan Commelin, Mario Carneiro, Kevin Buzzard, Amelia Livingston, Yury Kudryashov -/ import Mathlib.Algebra.BigOperators.Group.Multiset.Defs import Mathlib.Algebra.FreeMonoid.Basic import Mathlib.Algebra.Group.Idempotent import Mathlib.Algebra.Group.Nat.Hom import Mathlib.Algebra.Group.Submonoid.MulOpposite import Mathlib.Algebra.Group.Submonoid.Operations import Mathlib.Data.Fintype.EquivFin import Mathlib.Data.Int.Basic /-! # Submonoids: membership criteria In this file we prove various facts about membership in a submonoid: * `pow_mem`, `nsmul_mem`: if `x ∈ S` where `S` is a multiplicative (resp., additive) submonoid and `n` is a natural number, then `x^n` (resp., `n • x`) belongs to `S`; * `mem_iSup_of_directed`, `coe_iSup_of_directed`, `mem_sSup_of_directedOn`, `coe_sSup_of_directedOn`: the supremum of a directed collection of submonoid is their union. * `sup_eq_range`, `mem_sup`: supremum of two submonoids `S`, `T` of a commutative monoid is the set of products; * `closure_singleton_eq`, `mem_closure_singleton`, `mem_closure_pair`: the multiplicative (resp., additive) closure of `{x}` consists of powers (resp., natural multiples) of `x`, and a similar result holds for the closure of `{x, y}`. ## Tags submonoid, submonoids -/ assert_not_exists MonoidWithZero variable {M A B : Type*} section Assoc variable [Monoid M] [SetLike B M] [SubmonoidClass B M] {S : B} end Assoc section NonAssoc variable [MulOneClass M] open Set namespace Submonoid -- TODO: this section can be generalized to `[SubmonoidClass B M] [CompleteLattice B]` -- such that `CompleteLattice.LE` coincides with `SetLike.LE` @[to_additive] theorem mem_iSup_of_directed {ι} [hι : Nonempty ι] {S : ι → Submonoid M} (hS : Directed (· ≤ ·) S) {x : M} : (x ∈ ⨆ i, S i) ↔ ∃ i, x ∈ S i := by refine ⟨?_, fun ⟨i, hi⟩ ↦ le_iSup S i hi⟩ suffices x ∈ closure (⋃ i, (S i : Set M)) → ∃ i, x ∈ S i by simpa only [closure_iUnion, closure_eq (S _)] using this refine closure_induction (fun _ ↦ mem_iUnion.1) ?_ ?_ · exact hι.elim fun i ↦ ⟨i, (S i).one_mem⟩ · rintro x y - - ⟨i, hi⟩ ⟨j, hj⟩ rcases hS i j with ⟨k, hki, hkj⟩ exact ⟨k, (S k).mul_mem (hki hi) (hkj hj)⟩ @[to_additive] theorem coe_iSup_of_directed {ι} [Nonempty ι] {S : ι → Submonoid M} (hS : Directed (· ≤ ·) S) : ((⨆ i, S i : Submonoid M) : Set M) = ⋃ i, S i := Set.ext fun x ↦ by simp [mem_iSup_of_directed hS] @[to_additive] theorem mem_sSup_of_directedOn {S : Set (Submonoid M)} (Sne : S.Nonempty) (hS : DirectedOn (· ≤ ·) S) {x : M} : x ∈ sSup S ↔ ∃ s ∈ S, x ∈ s := by haveI : Nonempty S := Sne.to_subtype simp [sSup_eq_iSup', mem_iSup_of_directed hS.directed_val, SetCoe.exists, Subtype.coe_mk] @[to_additive] theorem coe_sSup_of_directedOn {S : Set (Submonoid M)} (Sne : S.Nonempty) (hS : DirectedOn (· ≤ ·) S) : (↑(sSup S) : Set M) = ⋃ s ∈ S, ↑s := Set.ext fun x => by simp [mem_sSup_of_directedOn Sne hS] @[to_additive] theorem mem_sup_left {S T : Submonoid M} : ∀ {x : M}, x ∈ S → x ∈ S ⊔ T := by rw [← SetLike.le_def] exact le_sup_left @[to_additive] theorem mem_sup_right {S T : Submonoid M} : ∀ {x : M}, x ∈ T → x ∈ S ⊔ T := by rw [← SetLike.le_def] exact le_sup_right @[to_additive] theorem mul_mem_sup {S T : Submonoid M} {x y : M} (hx : x ∈ S) (hy : y ∈ T) : x * y ∈ S ⊔ T := (S ⊔ T).mul_mem (mem_sup_left hx) (mem_sup_right hy) @[to_additive] theorem mem_iSup_of_mem {ι : Sort*} {S : ι → Submonoid M} (i : ι) : ∀ {x : M}, x ∈ S i → x ∈ iSup S := by rw [← SetLike.le_def] exact le_iSup _ _ @[to_additive] theorem mem_sSup_of_mem {S : Set (Submonoid M)} {s : Submonoid M} (hs : s ∈ S) : ∀ {x : M}, x ∈ s → x ∈ sSup S := by rw [← SetLike.le_def] exact le_sSup hs /-- An induction principle for elements of `⨆ i, S i`. If `C` holds for `1` and all elements of `S i` for all `i`, and is preserved under multiplication, then it holds for all elements of the supremum of `S`. -/ @[to_additive (attr := elab_as_elim) " An induction principle for elements of `⨆ i, S i`. If `C` holds for `0` and all elements of `S i` for all `i`, and is preserved under addition, then it holds for all elements of the supremum of `S`. "] theorem iSup_induction {ι : Sort*} (S : ι → Submonoid M) {motive : M → Prop} {x : M} (hx : x ∈ ⨆ i, S i) (mem : ∀ (i), ∀ x ∈ S i, motive x) (one : motive 1) (mul : ∀ x y, motive x → motive y → motive (x * y)) : motive x := by rw [iSup_eq_closure] at hx refine closure_induction (fun x hx => ?_) one (fun _ _ _ _ ↦ mul _ _) hx obtain ⟨i, hi⟩ := Set.mem_iUnion.mp hx exact mem _ _ hi /-- A dependent version of `Submonoid.iSup_induction`. -/ @[to_additive (attr := elab_as_elim) "A dependent version of `AddSubmonoid.iSup_induction`. "] theorem iSup_induction' {ι : Sort*} (S : ι → Submonoid M) {motive : ∀ x, (x ∈ ⨆ i, S i) → Prop} (mem : ∀ (i), ∀ (x) (hxS : x ∈ S i), motive x (mem_iSup_of_mem i hxS)) (one : motive 1 (one_mem _)) (mul : ∀ x y hx hy, motive x hx → motive y hy → motive (x * y) (mul_mem ‹_› ‹_›)) {x : M} (hx : x ∈ ⨆ i, S i) : motive x hx := by
refine Exists.elim (?_ : ∃ Hx, motive x Hx) fun (hx : x ∈ ⨆ i, S i) (hc : motive x hx) => hc refine @iSup_induction _ _ ι S (fun m => ∃ hm, motive m hm) _ hx (fun i x hx => ?_) ?_ fun x y => ?_ · exact ⟨_, mem _ _ hx⟩
Mathlib/Algebra/Group/Submonoid/Membership.lean
131
134
/- 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.Algebra.Order.Group.Nat import Mathlib.Data.Countable.Basic import Mathlib.Data.Finset.Max import Mathlib.Data.Fintype.Pigeonhole import Mathlib.Logic.Encodable.Basic import Mathlib.Order.Interval.Finset.Defs import Mathlib.Order.SuccPred.Archimedean /-! # Linear locally finite orders We prove that a `LinearOrder` which is a `LocallyFiniteOrder` also verifies * `SuccOrder` * `PredOrder` * `IsSuccArchimedean` * `IsPredArchimedean` * `Countable` Furthermore, we show that there is an `OrderIso` between such an order and a subset of `ℤ`. ## Main definitions * `toZ i0 i`: in a linear order on which we can define predecessors and successors and which is succ-archimedean, we can assign a unique integer `toZ i0 i` to each element `i : ι` while respecting the order, starting from `toZ i0 i0 = 0`. ## Main results Results about linear locally finite orders: * `LinearLocallyFiniteOrder.SuccOrder`: a linear locally finite order has a successor function. * `LinearLocallyFiniteOrder.PredOrder`: a linear locally finite order has a predecessor function. * `LinearLocallyFiniteOrder.isSuccArchimedean`: a linear locally finite order is succ-archimedean. * `LinearOrder.pred_archimedean_of_succ_archimedean`: a succ-archimedean linear order is also pred-archimedean. * `countable_of_linear_succ_pred_arch` : a succ-archimedean linear order is countable. About `toZ`: * `orderIsoRangeToZOfLinearSuccPredArch`: `toZ` defines an `OrderIso` between `ι` and its range. * `orderIsoNatOfLinearSuccPredArch`: if the order has a bot but no top, `toZ` defines an `OrderIso` between `ι` and `ℕ`. * `orderIsoIntOfLinearSuccPredArch`: if the order has neither bot nor top, `toZ` defines an `OrderIso` between `ι` and `ℤ`. * `orderIsoRangeOfLinearSuccPredArch`: if the order has both a bot and a top, `toZ` gives an `OrderIso` between `ι` and `Finset.range ((toZ ⊥ ⊤).toNat + 1)`. -/ open Order variable {ι : Type*} [LinearOrder ι] namespace LinearOrder variable [SuccOrder ι] [PredOrder ι] instance (priority := 100) isPredArchimedean_of_isSuccArchimedean [IsSuccArchimedean ι] : IsPredArchimedean ι where exists_pred_iterate_of_le {i j} hij := by have h_exists := exists_succ_iterate_of_le hij obtain ⟨n, hn_eq, hn_lt_ne⟩ : ∃ n, succ^[n] i = j ∧ ∀ m < n, succ^[m] i ≠ j := ⟨Nat.find h_exists, Nat.find_spec h_exists, fun m hmn ↦ Nat.find_min h_exists hmn⟩ refine ⟨n, ?_⟩ rw [← hn_eq] cases n with | zero => simp only [Function.iterate_zero, id] | succ n => rw [pred_succ_iterate_of_not_isMax] rw [Nat.succ_sub_succ_eq_sub, tsub_zero] suffices succ^[n] i < succ^[n.succ] i from not_isMax_of_lt this refine lt_of_le_of_ne ?_ ?_ · rw [Function.iterate_succ_apply'] exact le_succ _ · rw [hn_eq] exact hn_lt_ne _ (Nat.lt_succ_self n) instance isSuccArchimedean_of_isPredArchimedean [IsPredArchimedean ι] : IsSuccArchimedean ι := inferInstanceAs (IsSuccArchimedean ιᵒᵈᵒᵈ) /-- In a linear `SuccOrder` that's also a `PredOrder`, `IsSuccArchimedean` and `IsPredArchimedean` are equivalent. -/ theorem isSuccArchimedean_iff_isPredArchimedean : IsSuccArchimedean ι ↔ IsPredArchimedean ι where mp _ := isPredArchimedean_of_isSuccArchimedean mpr _ := isSuccArchimedean_of_isPredArchimedean end LinearOrder namespace LinearLocallyFiniteOrder /-- Successor in a linear order. This defines a true successor only when `i` is isolated from above, i.e. when `i` is not the greatest lower bound of `(i, ∞)`. -/ noncomputable def succFn (i : ι) : ι := (exists_glb_Ioi i).choose
theorem succFn_spec (i : ι) : IsGLB (Set.Ioi i) (succFn i) := (exists_glb_Ioi i).choose_spec theorem le_succFn (i : ι) : i ≤ succFn i := by
Mathlib/Order/SuccPred/LinearLocallyFinite.lean
103
106
/- Copyright (c) 2021 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov, Alex Kontorovich, Heather Macbeth -/ import Mathlib.MeasureTheory.Group.Action import Mathlib.MeasureTheory.Group.Pointwise import Mathlib.MeasureTheory.Integral.Lebesgue.Map import Mathlib.MeasureTheory.Integral.Bochner.Set /-! # Fundamental domain of a group action A set `s` is said to be a *fundamental domain* of an action of a group `G` on a measurable space `α` with respect to a measure `μ` if * `s` is a measurable set; * the sets `g • s` over all `g : G` cover almost all points of the whole space; * the sets `g • s`, are pairwise a.e. disjoint, i.e., `μ (g₁ • s ∩ g₂ • s) = 0` whenever `g₁ ≠ g₂`; we require this for `g₂ = 1` in the definition, then deduce it for any two `g₁ ≠ g₂`. In this file we prove that in case of a countable group `G` and a measure preserving action, any two fundamental domains have the same measure, and for a `G`-invariant function, its integrals over any two fundamental domains are equal to each other. We also generate additive versions of all theorems in this file using the `to_additive` attribute. * We define the `HasFundamentalDomain` typeclass, in particular to be able to define the `covolume` of a quotient of `α` by a group `G`, which under reasonable conditions does not depend on the choice of fundamental domain. * We define the `QuotientMeasureEqMeasurePreimage` typeclass to describe a situation in which a measure `μ` on `α ⧸ G` can be computed by taking a measure `ν` on `α` of the intersection of the pullback with a fundamental domain. ## Main declarations * `MeasureTheory.IsFundamentalDomain`: Predicate for a set to be a fundamental domain of the action of a group * `MeasureTheory.fundamentalFrontier`: Fundamental frontier of a set under the action of a group. Elements of `s` that belong to some other translate of `s`. * `MeasureTheory.fundamentalInterior`: Fundamental interior of a set under the action of a group. Elements of `s` that do not belong to any other translate of `s`. -/ open scoped ENNReal Pointwise Topology NNReal ENNReal MeasureTheory open MeasureTheory MeasureTheory.Measure Set Function TopologicalSpace Filter namespace MeasureTheory /-- A measurable set `s` is a *fundamental domain* for an additive action of an additive group `G` on a measurable space `α` with respect to a measure `α` if the sets `g +ᵥ s`, `g : G`, are pairwise a.e. disjoint and cover the whole space. -/ structure IsAddFundamentalDomain (G : Type*) {α : Type*} [Zero G] [VAdd G α] [MeasurableSpace α] (s : Set α) (μ : Measure α := by volume_tac) : Prop where protected nullMeasurableSet : NullMeasurableSet s μ protected ae_covers : ∀ᵐ x ∂μ, ∃ g : G, g +ᵥ x ∈ s protected aedisjoint : Pairwise <| (AEDisjoint μ on fun g : G => g +ᵥ s) /-- A measurable set `s` is a *fundamental domain* for an action of a group `G` on a measurable space `α` with respect to a measure `α` if the sets `g • s`, `g : G`, are pairwise a.e. disjoint and cover the whole space. -/ @[to_additive IsAddFundamentalDomain] structure IsFundamentalDomain (G : Type*) {α : Type*} [One G] [SMul G α] [MeasurableSpace α] (s : Set α) (μ : Measure α := by volume_tac) : Prop where protected nullMeasurableSet : NullMeasurableSet s μ protected ae_covers : ∀ᵐ x ∂μ, ∃ g : G, g • x ∈ s protected aedisjoint : Pairwise <| (AEDisjoint μ on fun g : G => g • s) variable {G H α β E : Type*} namespace IsFundamentalDomain variable [Group G] [Group H] [MulAction G α] [MeasurableSpace α] [MulAction H β] [MeasurableSpace β] [NormedAddCommGroup E] {s t : Set α} {μ : Measure α} /-- If for each `x : α`, exactly one of `g • x`, `g : G`, belongs to a measurable set `s`, then `s` is a fundamental domain for the action of `G` on `α`. -/ @[to_additive "If for each `x : α`, exactly one of `g +ᵥ x`, `g : G`, belongs to a measurable set `s`, then `s` is a fundamental domain for the additive action of `G` on `α`."] theorem mk' (h_meas : NullMeasurableSet s μ) (h_exists : ∀ x : α, ∃! g : G, g • x ∈ s) : IsFundamentalDomain G s μ where nullMeasurableSet := h_meas ae_covers := Eventually.of_forall fun x => (h_exists x).exists aedisjoint a b hab := Disjoint.aedisjoint <| disjoint_left.2 fun x hxa hxb => by rw [mem_smul_set_iff_inv_smul_mem] at hxa hxb exact hab (inv_injective <| (h_exists x).unique hxa hxb) /-- For `s` to be a fundamental domain, it's enough to check `MeasureTheory.AEDisjoint (g • s) s` for `g ≠ 1`. -/ @[to_additive "For `s` to be a fundamental domain, it's enough to check `MeasureTheory.AEDisjoint (g +ᵥ s) s` for `g ≠ 0`."] theorem mk'' (h_meas : NullMeasurableSet s μ) (h_ae_covers : ∀ᵐ x ∂μ, ∃ g : G, g • x ∈ s) (h_ae_disjoint : ∀ g, g ≠ (1 : G) → AEDisjoint μ (g • s) s) (h_qmp : ∀ g : G, QuasiMeasurePreserving ((g • ·) : α → α) μ μ) : IsFundamentalDomain G s μ where nullMeasurableSet := h_meas ae_covers := h_ae_covers aedisjoint := pairwise_aedisjoint_of_aedisjoint_forall_ne_one h_ae_disjoint h_qmp /-- If a measurable space has a finite measure `μ` and a countable group `G` acts quasi-measure-preservingly, then to show that a set `s` is a fundamental domain, it is sufficient to check that its translates `g • s` are (almost) disjoint and that the sum `∑' g, μ (g • s)` is sufficiently large. -/ @[to_additive "If a measurable space has a finite measure `μ` and a countable additive group `G` acts quasi-measure-preservingly, then to show that a set `s` is a fundamental domain, it is sufficient to check that its translates `g +ᵥ s` are (almost) disjoint and that the sum `∑' g, μ (g +ᵥ s)` is sufficiently large."] theorem mk_of_measure_univ_le [IsFiniteMeasure μ] [Countable G] (h_meas : NullMeasurableSet s μ) (h_ae_disjoint : ∀ g ≠ (1 : G), AEDisjoint μ (g • s) s) (h_qmp : ∀ g : G, QuasiMeasurePreserving (g • · : α → α) μ μ) (h_measure_univ_le : μ (univ : Set α) ≤ ∑' g : G, μ (g • s)) : IsFundamentalDomain G s μ := have aedisjoint : Pairwise (AEDisjoint μ on fun g : G => g • s) := pairwise_aedisjoint_of_aedisjoint_forall_ne_one h_ae_disjoint h_qmp { nullMeasurableSet := h_meas aedisjoint ae_covers := by replace h_meas : ∀ g : G, NullMeasurableSet (g • s) μ := fun g => by rw [← inv_inv g, ← preimage_smul]; exact h_meas.preimage (h_qmp g⁻¹) have h_meas' : NullMeasurableSet {a | ∃ g : G, g • a ∈ s} μ := by rw [← iUnion_smul_eq_setOf_exists]; exact .iUnion h_meas rw [ae_iff_measure_eq h_meas', ← iUnion_smul_eq_setOf_exists] refine le_antisymm (measure_mono <| subset_univ _) ?_ rw [measure_iUnion₀ aedisjoint h_meas] exact h_measure_univ_le } @[to_additive] theorem iUnion_smul_ae_eq (h : IsFundamentalDomain G s μ) : ⋃ g : G, g • s =ᵐ[μ] univ := eventuallyEq_univ.2 <| h.ae_covers.mono fun _ ⟨g, hg⟩ => mem_iUnion.2 ⟨g⁻¹, _, hg, inv_smul_smul _ _⟩ @[to_additive] theorem measure_ne_zero [Countable G] [SMulInvariantMeasure G α μ] (hμ : μ ≠ 0) (h : IsFundamentalDomain G s μ) : μ s ≠ 0 := by have hc := measure_univ_pos.mpr hμ contrapose! hc rw [← measure_congr h.iUnion_smul_ae_eq] refine le_trans (measure_iUnion_le _) ?_ simp_rw [measure_smul, hc, tsum_zero, le_refl] @[to_additive] theorem mono (h : IsFundamentalDomain G s μ) {ν : Measure α} (hle : ν ≪ μ) : IsFundamentalDomain G s ν := ⟨h.1.mono_ac hle, hle h.2, h.aedisjoint.mono fun _ _ h => hle h⟩ @[to_additive] theorem preimage_of_equiv {ν : Measure β} (h : IsFundamentalDomain G s μ) {f : β → α} (hf : QuasiMeasurePreserving f ν μ) {e : G → H} (he : Bijective e) (hef : ∀ g, Semiconj f (e g • ·) (g • ·)) : IsFundamentalDomain H (f ⁻¹' s) ν where nullMeasurableSet := h.nullMeasurableSet.preimage hf ae_covers := (hf.ae h.ae_covers).mono fun x ⟨g, hg⟩ => ⟨e g, by rwa [mem_preimage, hef g x]⟩ aedisjoint a b hab := by lift e to G ≃ H using he have : (e.symm a⁻¹)⁻¹ ≠ (e.symm b⁻¹)⁻¹ := by simp [hab] have := (h.aedisjoint this).preimage hf simp only [Semiconj] at hef simpa only [onFun, ← preimage_smul_inv, preimage_preimage, ← hef, e.apply_symm_apply, inv_inv] using this @[to_additive] theorem image_of_equiv {ν : Measure β} (h : IsFundamentalDomain G s μ) (f : α ≃ β) (hf : QuasiMeasurePreserving f.symm ν μ) (e : H ≃ G) (hef : ∀ g, Semiconj f (e g • ·) (g • ·)) : IsFundamentalDomain H (f '' s) ν := by rw [f.image_eq_preimage] refine h.preimage_of_equiv hf e.symm.bijective fun g x => ?_ rcases f.surjective x with ⟨x, rfl⟩ rw [← hef _ _, f.symm_apply_apply, f.symm_apply_apply, e.apply_symm_apply] @[to_additive] theorem pairwise_aedisjoint_of_ac {ν} (h : IsFundamentalDomain G s μ) (hν : ν ≪ μ) : Pairwise fun g₁ g₂ : G => AEDisjoint ν (g₁ • s) (g₂ • s) := h.aedisjoint.mono fun _ _ H => hν H @[to_additive] theorem smul_of_comm {G' : Type*} [Group G'] [MulAction G' α] [MeasurableSpace G'] [MeasurableSMul G' α] [SMulInvariantMeasure G' α μ] [SMulCommClass G' G α] (h : IsFundamentalDomain G s μ) (g : G') : IsFundamentalDomain G (g • s) μ := h.image_of_equiv (MulAction.toPerm g) (measurePreserving_smul _ _).quasiMeasurePreserving (Equiv.refl _) <| smul_comm g variable [MeasurableSpace G] [MeasurableSMul G α] [SMulInvariantMeasure G α μ] @[to_additive] theorem nullMeasurableSet_smul (h : IsFundamentalDomain G s μ) (g : G) : NullMeasurableSet (g • s) μ := h.nullMeasurableSet.smul g @[to_additive] theorem restrict_restrict (h : IsFundamentalDomain G s μ) (g : G) (t : Set α) : (μ.restrict t).restrict (g • s) = μ.restrict (g • s ∩ t) := restrict_restrict₀ ((h.nullMeasurableSet_smul g).mono restrict_le_self) @[to_additive] theorem smul (h : IsFundamentalDomain G s μ) (g : G) : IsFundamentalDomain G (g • s) μ := h.image_of_equiv (MulAction.toPerm g) (measurePreserving_smul _ _).quasiMeasurePreserving ⟨fun g' => g⁻¹ * g' * g, fun g' => g * g' * g⁻¹, fun g' => by simp [mul_assoc], fun g' => by simp [mul_assoc]⟩ fun g' x => by simp [smul_smul, mul_assoc] variable [Countable G] {ν : Measure α} @[to_additive] theorem sum_restrict_of_ac (h : IsFundamentalDomain G s μ) (hν : ν ≪ μ) : (sum fun g : G => ν.restrict (g • s)) = ν := by rw [← restrict_iUnion_ae (h.aedisjoint.mono fun i j h => hν h) fun g => (h.nullMeasurableSet_smul g).mono_ac hν, restrict_congr_set (hν h.iUnion_smul_ae_eq), restrict_univ] @[to_additive] theorem lintegral_eq_tsum_of_ac (h : IsFundamentalDomain G s μ) (hν : ν ≪ μ) (f : α → ℝ≥0∞) : ∫⁻ x, f x ∂ν = ∑' g : G, ∫⁻ x in g • s, f x ∂ν := by rw [← lintegral_sum_measure, h.sum_restrict_of_ac hν] @[to_additive] theorem sum_restrict (h : IsFundamentalDomain G s μ) : (sum fun g : G => μ.restrict (g • s)) = μ := h.sum_restrict_of_ac (refl _) @[to_additive] theorem lintegral_eq_tsum (h : IsFundamentalDomain G s μ) (f : α → ℝ≥0∞) : ∫⁻ x, f x ∂μ = ∑' g : G, ∫⁻ x in g • s, f x ∂μ := h.lintegral_eq_tsum_of_ac (refl _) f @[to_additive] theorem lintegral_eq_tsum' (h : IsFundamentalDomain G s μ) (f : α → ℝ≥0∞) : ∫⁻ x, f x ∂μ = ∑' g : G, ∫⁻ x in s, f (g⁻¹ • x) ∂μ := calc ∫⁻ x, f x ∂μ = ∑' g : G, ∫⁻ x in g • s, f x ∂μ := h.lintegral_eq_tsum f _ = ∑' g : G, ∫⁻ x in g⁻¹ • s, f x ∂μ := ((Equiv.inv G).tsum_eq _).symm _ = ∑' g : G, ∫⁻ x in s, f (g⁻¹ • x) ∂μ := tsum_congr fun g => Eq.symm <| (measurePreserving_smul g⁻¹ μ).setLIntegral_comp_emb (measurableEmbedding_const_smul _) _ _ @[to_additive] lemma lintegral_eq_tsum'' (h : IsFundamentalDomain G s μ) (f : α → ℝ≥0∞) : ∫⁻ x, f x ∂μ = ∑' g : G, ∫⁻ x in s, f (g • x) ∂μ := (lintegral_eq_tsum' h f).trans ((Equiv.inv G).tsum_eq (fun g ↦ ∫⁻ (x : α) in s, f (g • x) ∂μ)) @[to_additive] theorem setLIntegral_eq_tsum (h : IsFundamentalDomain G s μ) (f : α → ℝ≥0∞) (t : Set α) : ∫⁻ x in t, f x ∂μ = ∑' g : G, ∫⁻ x in t ∩ g • s, f x ∂μ := calc
∫⁻ x in t, f x ∂μ = ∑' g : G, ∫⁻ x in g • s, f x ∂μ.restrict t := h.lintegral_eq_tsum_of_ac restrict_le_self.absolutelyContinuous _ _ = ∑' g : G, ∫⁻ x in t ∩ g • s, f x ∂μ := by simp only [h.restrict_restrict, inter_comm]
Mathlib/MeasureTheory/Group/FundamentalDomain.lean
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/- Copyright (c) 2018 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau -/ import Mathlib.Algebra.Module.NatInt import Mathlib.GroupTheory.Abelianization import Mathlib.GroupTheory.FreeGroup.Basic /-! # Free abelian groups The free abelian group on a type `α`, defined as the abelianisation of the free group on `α`. The free abelian group on `α` can be abstractly defined as the left adjoint of the forgetful functor from abelian groups to types. Alternatively, one could define it as the functions `α → ℤ` which send all but finitely many `(a : α)` to `0`, under pointwise addition. In this file, it is defined as the abelianisation of the free group on `α`. All the constructions and theorems required to show the adjointness of the construction and the forgetful functor are proved in this file, but the category-theoretic adjunction statement is in `Algebra.Category.Group.Adjunctions`. ## Main definitions Here we use the following variables: `(α β : Type*) (A : Type*) [AddCommGroup A]` * `FreeAbelianGroup α` : the free abelian group on a type `α`. As an abelian group it is `α →₀ ℤ`, the functions from `α` to `ℤ` such that all but finitely many elements get mapped to zero, however this is not how it is implemented. * `lift f : FreeAbelianGroup α →+ A` : the group homomorphism induced by the map `f : α → A`. * `map (f : α → β) : FreeAbelianGroup α →+ FreeAbelianGroup β` : functoriality of `FreeAbelianGroup`. * `instance [Monoid α] : Semigroup (FreeAbelianGroup α)` * `instance [CommMonoid α] : CommRing (FreeAbelianGroup α)` It has been suggested that we would be better off refactoring this file and using `Finsupp` instead. ## Implementation issues The definition is `def FreeAbelianGroup : Type u := Additive <| Abelianization <| FreeGroup α`. Chris Hughes has suggested that this all be rewritten in terms of `Finsupp`. Johan Commelin has written all the API relating the definition to `Finsupp` in the lean-liquid repo. The lemmas `map_pure`, `map_of`, `map_zero`, `map_add`, `map_neg` and `map_sub` are proved about the `Functor.map` `<$>` construction, and need `α` and `β` to be in the same universe. But `FreeAbelianGroup.map (f : α → β)` is defined to be the `AddGroup` homomorphism `FreeAbelianGroup α →+ FreeAbelianGroup β` (with `α` and `β` now allowed to be in different universes), so `(map f).map_add` etc can be used to prove that `FreeAbelianGroup.map` preserves addition. The functions `map_id`, `map_id_apply`, `map_comp`, `map_comp_apply` and `map_of_apply` are about `FreeAbelianGroup.map`. -/ universe u v variable (α : Type u) /-- If `α` is a type, then `FreeAbelianGroup α` is the free abelian group generated by `α`. This is an abelian group equipped with a function `FreeAbelianGroup.of : α → FreeAbelianGroup α` which has the following universal property: if `G` is any abelian group, and `f : α → G` is any function, then this function is the composite of `FreeAbelianGroup.of` and a unique group homomorphism `FreeAbelianGroup.lift f : FreeAbelianGroup α →+ G`. A typical element of `FreeAbelianGroup α` is a formal sum of elements of `α` and their formal inverses. For example if `x` and `y` are terms of type `α` then `x + x + x - y` is a "typical" element of `FreeAbelianGroup α`. In particular if `α` is empty then `FreeAbelianGroup α` is isomorphic to the trivial group, and if `α` has one term then `FreeAbelianGroup α` is isomorphic to `ℤ`. One can think of `FreeAbelianGroup α` as the functions `α →₀ ℤ` with finite support, and addition given pointwise. TODO: rename to `FreeAddCommGroup` and introduce a multiplicative version -/ def FreeAbelianGroup : Type u := Additive <| Abelianization <| FreeGroup α -- FIXME: this is super broken, because the functions have type `Additive .. → ..` -- instead of `FreeAbelianGroup α → ..` and those are not defeq! instance FreeAbelianGroup.addCommGroup : AddCommGroup (FreeAbelianGroup α) := @Additive.addCommGroup _ <| Abelianization.commGroup _ instance : Inhabited (FreeAbelianGroup α) := ⟨0⟩ instance [IsEmpty α] : Unique (FreeAbelianGroup α) := by unfold FreeAbelianGroup; infer_instance variable {α} namespace FreeAbelianGroup /-- The canonical map from `α` to `FreeAbelianGroup α`. -/ def of (x : α) : FreeAbelianGroup α := Additive.ofMul <| Abelianization.of <| FreeGroup.of x /-- The map `FreeAbelianGroup α →+ A` induced by a map of types `α → A`. -/ def lift {β : Type v} [AddCommGroup β] : (α → β) ≃ (FreeAbelianGroup α →+ β) := (@FreeGroup.lift _ (Multiplicative β) _).trans <| (@Abelianization.lift _ _ (Multiplicative β) _).trans MonoidHom.toAdditive namespace lift variable {β : Type v} [AddCommGroup β] (f : α → β) open FreeAbelianGroup -- Porting note: needed to add `(β := Multiplicative β)` and `using 1`. @[simp] protected theorem of (x : α) : lift f (of x) = f x := by convert Abelianization.lift.of (FreeGroup.lift f (β := Multiplicative β)) (FreeGroup.of x) using 1 exact (FreeGroup.lift.of (β := Multiplicative β)).symm protected theorem unique (g : FreeAbelianGroup α →+ β) (hg : ∀ x, g (of x) = f x) {x} : g x = lift f x := DFunLike.congr_fun (lift.symm_apply_eq.mp (funext hg : g ∘ of = f)) _ /-- See note [partially-applied ext lemmas]. -/ @[ext high] protected theorem ext (g h : FreeAbelianGroup α →+ β) (H : ∀ x, g (of x) = h (of x)) : g = h := lift.symm.injective <| funext H theorem map_hom {α β γ} [AddCommGroup β] [AddCommGroup γ] (a : FreeAbelianGroup α) (f : α → β) (g : β →+ γ) : g (lift f a) = lift (g ∘ f) a := by show (g.comp (lift f)) a = lift (g ∘ f) a apply lift.unique intro a show g ((lift f) (of a)) = g (f a) simp only [(· ∘ ·), lift.of] end lift section open scoped Classical in theorem of_injective : Function.Injective (of : α → FreeAbelianGroup α) := fun x y hoxy ↦ Classical.by_contradiction fun hxy : x ≠ y ↦ let f : FreeAbelianGroup α →+ ℤ := lift fun z ↦ if x = z then (1 : ℤ) else 0 have hfx1 : f (of x) = 1 := (lift.of _ _).trans <| if_pos rfl have hfy1 : f (of y) = 1 := hoxy ▸ hfx1 have hfy0 : f (of y) = 0 := (lift.of _ _).trans <| if_neg hxy one_ne_zero <| hfy1.symm.trans hfy0 @[simp] theorem of_ne_zero (x : α) : of x ≠ 0 := by intro h let f : FreeAbelianGroup α →+ ℤ := lift 1 have hfx : f (of x) = 1 := lift.of _ _ have hf0 : f (of x) = 0 := by rw [h, map_zero] exact one_ne_zero <| hfx.symm.trans hf0 @[simp] theorem zero_ne_of (x : α) : 0 ≠ of x := of_ne_zero _ |>.symm instance [Nonempty α] : Nontrivial (FreeAbelianGroup α) where exists_pair_ne := let ⟨x⟩ := ‹Nonempty α›; ⟨0, of x, zero_ne_of _⟩ end attribute [local instance] QuotientGroup.leftRel @[elab_as_elim] protected theorem induction_on {C : FreeAbelianGroup α → Prop} (z : FreeAbelianGroup α) (C0 : C 0) (C1 : ∀ x, C <| of x) (Cn : ∀ x, C (of x) → C (-of x)) (Cp : ∀ x y, C x → C y → C (x + y)) : C z := Quotient.inductionOn' z fun x ↦ Quot.inductionOn x fun L ↦ List.recOn L C0 fun ⟨x, b⟩ _ ih ↦ Bool.recOn b (Cp _ _ (Cn _ (C1 x)) ih) (Cp _ _ (C1 x) ih) theorem lift.add' {α β} [AddCommGroup β] (a : FreeAbelianGroup α) (f g : α → β) : lift (f + g) a = lift f a + lift g a := by refine FreeAbelianGroup.induction_on a ?_ ?_ ?_ ?_ · simp only [(lift _).map_zero, zero_add] · intro x simp only [lift.of, Pi.add_apply] · intro x _ simp only [map_neg, lift.of, Pi.add_apply, neg_add] · intro x y hx hy simp only [(lift _).map_add, hx, hy, add_add_add_comm] /-- If `g : FreeAbelianGroup X` and `A` is an abelian group then `liftAddGroupHom g` is the additive group homomorphism sending a function `X → A` to the term of type `A` corresponding to the evaluation of the induced map `FreeAbelianGroup X → A` at `g`. -/ @[simps!] def liftAddGroupHom {α} (β) [AddCommGroup β] (a : FreeAbelianGroup α) : (α → β) →+ β := AddMonoidHom.mk' (fun f ↦ lift f a) (lift.add' a) theorem lift_neg' {β} [AddCommGroup β] (f : α → β) : lift (-f) = -lift f := AddMonoidHom.ext fun _ ↦ (liftAddGroupHom _ _ : (α → β) →+ β).map_neg _ section Monad variable {β : Type u} instance : Monad FreeAbelianGroup.{u} where pure α := of α bind x f := lift f x @[elab_as_elim] protected theorem induction_on' {C : FreeAbelianGroup α → Prop} (z : FreeAbelianGroup α) (C0 : C 0) (C1 : ∀ x, C <| pure x) (Cn : ∀ x, C (pure x) → C (-pure x)) (Cp : ∀ x y, C x → C y → C (x + y)) : C z := FreeAbelianGroup.induction_on z C0 C1 Cn Cp @[simp] theorem map_pure (f : α → β) (x : α) : f <$> (pure x : FreeAbelianGroup α) = pure (f x) := rfl @[simp] protected theorem map_zero (f : α → β) : f <$> (0 : FreeAbelianGroup α) = 0 := (lift (of ∘ f)).map_zero @[simp] protected theorem map_add (f : α → β) (x y : FreeAbelianGroup α) : f <$> (x + y) = f <$> x + f <$> y := (lift _).map_add _ _ @[simp] protected theorem map_neg (f : α → β) (x : FreeAbelianGroup α) : f <$> (-x) = -f <$> x := map_neg (lift <| of ∘ f) _ @[simp] protected theorem map_sub (f : α → β) (x y : FreeAbelianGroup α) : f <$> (x - y) = f <$> x - f <$> y := map_sub (lift <| of ∘ f) _ _ @[simp] theorem map_of (f : α → β) (y : α) : f <$> of y = of (f y) := rfl theorem pure_bind (f : α → FreeAbelianGroup β) (x) : pure x >>= f = f x := lift.of _ _ @[simp] theorem zero_bind (f : α → FreeAbelianGroup β) : 0 >>= f = 0 := (lift f).map_zero @[simp] theorem add_bind (f : α → FreeAbelianGroup β) (x y : FreeAbelianGroup α) : x + y >>= f = (x >>= f) + (y >>= f) := (lift _).map_add _ _ @[simp] theorem neg_bind (f : α → FreeAbelianGroup β) (x : FreeAbelianGroup α) : -x >>= f = -(x >>= f) := map_neg (lift f) _ @[simp] theorem sub_bind (f : α → FreeAbelianGroup β) (x y : FreeAbelianGroup α) : x - y >>= f = (x >>= f) - (y >>= f) := map_sub (lift f) _ _ @[simp] theorem pure_seq (f : α → β) (x : FreeAbelianGroup α) : pure f <*> x = f <$> x := pure_bind _ _ @[simp] theorem zero_seq (x : FreeAbelianGroup α) : (0 : FreeAbelianGroup (α → β)) <*> x = 0 := zero_bind _ @[simp] theorem add_seq (f g : FreeAbelianGroup (α → β)) (x : FreeAbelianGroup α) : f + g <*> x = (f <*> x) + (g <*> x) := add_bind _ _ _ @[simp] theorem neg_seq (f : FreeAbelianGroup (α → β)) (x : FreeAbelianGroup α) : -f <*> x = -(f <*> x) := neg_bind _ _ @[simp] theorem sub_seq (f g : FreeAbelianGroup (α → β)) (x : FreeAbelianGroup α) : f - g <*> x = (f <*> x) - (g <*> x) := sub_bind _ _ _ /-- If `f : FreeAbelianGroup (α → β)`, then `f <*>` is an additive morphism `FreeAbelianGroup α →+ FreeAbelianGroup β`. -/ def seqAddGroupHom (f : FreeAbelianGroup (α → β)) : FreeAbelianGroup α →+ FreeAbelianGroup β := AddMonoidHom.mk' (f <*> ·) fun x y ↦ show lift (· <$> (x + y)) _ = _ by simp only [FreeAbelianGroup.map_add] exact lift.add' f _ _ @[simp] theorem seq_zero (f : FreeAbelianGroup (α → β)) : f <*> 0 = 0 := (seqAddGroupHom f).map_zero @[simp] theorem seq_add (f : FreeAbelianGroup (α → β)) (x y : FreeAbelianGroup α) : f <*> x + y = (f <*> x) + (f <*> y) := (seqAddGroupHom f).map_add x y @[simp] theorem seq_neg (f : FreeAbelianGroup (α → β)) (x : FreeAbelianGroup α) : f <*> -x = -(f <*> x) := (seqAddGroupHom f).map_neg x @[simp] theorem seq_sub (f : FreeAbelianGroup (α → β)) (x y : FreeAbelianGroup α) : f <*> x - y = (f <*> x) - (f <*> y) := (seqAddGroupHom f).map_sub x y instance : LawfulMonad FreeAbelianGroup.{u} := LawfulMonad.mk' (id_map := fun x ↦ FreeAbelianGroup.induction_on' x (FreeAbelianGroup.map_zero id) (map_pure id) (fun x ih ↦ by rw [FreeAbelianGroup.map_neg, ih]) fun x y ihx ihy ↦ by rw [FreeAbelianGroup.map_add, ihx, ihy]) (pure_bind := fun x f ↦ pure_bind f x) (bind_assoc := fun x f g ↦ FreeAbelianGroup.induction_on' x (by iterate 3 rw [zero_bind]) (fun x ↦ by iterate 2 rw [pure_bind]) (fun x ih ↦ by iterate 3 rw [neg_bind] <;> try rw [ih]) fun x y ihx ihy ↦ by iterate 3 rw [add_bind] <;> try rw [ihx, ihy]) instance : CommApplicative FreeAbelianGroup.{u} where commutative_prod x y := by refine FreeAbelianGroup.induction_on' x ?_ ?_ ?_ ?_ · rw [FreeAbelianGroup.map_zero, zero_seq, seq_zero] · intro p rw [map_pure, pure_seq] exact FreeAbelianGroup.induction_on' y (by rw [FreeAbelianGroup.map_zero, FreeAbelianGroup.map_zero, zero_seq]) (fun q ↦ by rw [map_pure, map_pure, pure_seq, map_pure]) (fun q ih ↦ by rw [FreeAbelianGroup.map_neg, FreeAbelianGroup.map_neg, neg_seq, ih]) fun y₁ y₂ ih1 ih2 ↦ by rw [FreeAbelianGroup.map_add, FreeAbelianGroup.map_add, add_seq, ih1, ih2] · intro p ih rw [FreeAbelianGroup.map_neg, neg_seq, seq_neg, ih] · intro x₁ x₂ ih1 ih2 rw [FreeAbelianGroup.map_add, add_seq, seq_add, ih1, ih2] end Monad universe w variable {β : Type v} {γ : Type w} /-- The additive group homomorphism `FreeAbelianGroup α →+ FreeAbelianGroup β` induced from a map `α → β`. -/ def map (f : α → β) : FreeAbelianGroup α →+ FreeAbelianGroup β := lift (of ∘ f) theorem lift_comp {α} {β} {γ} [AddCommGroup γ] (f : α → β) (g : β → γ) (x : FreeAbelianGroup α) : lift (g ∘ f) x = lift g (map f x) := by induction x using FreeAbelianGroup.induction_on with | C0 => simp only [map_zero] | C1 => simp only [lift.of, map, Function.comp] | Cn _ h => simp only [h, AddMonoidHom.map_neg] | Cp _ _ h₁ h₂ => simp only [h₁, h₂, AddMonoidHom.map_add] theorem map_id : map id = AddMonoidHom.id (FreeAbelianGroup α) := Eq.symm <| lift.ext _ _ fun _ ↦ lift.unique of (AddMonoidHom.id _) fun _ ↦ AddMonoidHom.id_apply _ _ theorem map_id_apply (x : FreeAbelianGroup α) : map id x = x := by rw [map_id] rfl theorem map_comp {f : α → β} {g : β → γ} : map (g ∘ f) = (map g).comp (map f) := Eq.symm <| lift.ext _ _ fun _ ↦ by simp [map] theorem map_comp_apply {f : α → β} {g : β → γ} (x : FreeAbelianGroup α) : map (g ∘ f) x = (map g) ((map f) x) := by rw [map_comp] rfl -- version of map_of which uses `map` @[simp] theorem map_of_apply {f : α → β} (a : α) : map f (of a) = of (f a) := rfl variable (α) section Mul variable [Mul α] instance mul : Mul (FreeAbelianGroup α) := ⟨fun x ↦ lift fun x₂ ↦ lift (fun x₁ ↦ of (x₁ * x₂)) x⟩ variable {α} theorem mul_def (x y : FreeAbelianGroup α) : x * y = lift (fun x₂ ↦ lift (fun x₁ ↦ of (x₁ * x₂)) x) y := rfl @[simp] theorem of_mul_of (x y : α) : of x * of y = of (x * y) := by rw [mul_def, lift.of, lift.of] theorem of_mul (x y : α) : of (x * y) = of x * of y := Eq.symm <| of_mul_of x y instance distrib : Distrib (FreeAbelianGroup α) := { FreeAbelianGroup.mul α, FreeAbelianGroup.addCommGroup α with left_distrib := fun _ _ _ ↦ (lift _).map_add _ _ right_distrib := fun x y z ↦ by simp only [(· * ·), Mul.mul, map_add, ← Pi.add_def, lift.add'] } instance nonUnitalNonAssocRing : NonUnitalNonAssocRing (FreeAbelianGroup α) := { FreeAbelianGroup.distrib, FreeAbelianGroup.addCommGroup _ with zero_mul := fun a ↦ by have h : 0 * a + 0 * a = 0 * a := by simp [← add_mul] simpa using h mul_zero := fun _ ↦ rfl }
end Mul
Mathlib/GroupTheory/FreeAbelianGroup.lean
416
417
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Johan Commelin -/ import Mathlib.Algebra.Algebra.RestrictScalars import Mathlib.Algebra.Algebra.Subalgebra.Lattice import Mathlib.Algebra.Module.Rat import Mathlib.GroupTheory.MonoidLocalization.Basic import Mathlib.LinearAlgebra.TensorProduct.Tower /-! # 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] -/ assert_not_exists Equiv.Perm.cycleType 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) in /-- `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 @[simp] theorem baseChange_tmul (a : A) (x : M) : f.baseChange A (a ⊗ₜ x) = a ⊗ₜ f x := rfl theorem baseChange_eq_ltensor : (f.baseChange A : A ⊗ M → A ⊗ N) = f.lTensor A := rfl @[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] @[simp] theorem baseChange_zero : baseChange A (0 : M →ₗ[R] N) = 0 := by ext simp [baseChange_eq_ltensor] @[simp] theorem baseChange_smul : (r • f).baseChange A = r • f.baseChange A := by ext simp [baseChange_tmul] @[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 A e` for `e : M ≃ₗ[R] N` is the `A`-linear map `A ⊗[R] M ≃ₗ[A] A ⊗[R] N`. -/ def _root_.LinearEquiv.baseChange (e : M ≃ₗ[R] N) : A ⊗[R] M ≃ₗ[A] A ⊗[R] N := AlgebraTensorModule.congr (.refl _ _) e /-- `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 /-- `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] theorem baseChange_sub : (f - g).baseChange A = f.baseChange A - g.baseChange A := by ext simp [baseChange_eq_ltensor, tmul_sub] @[simp] theorem baseChange_neg : (-f).baseChange A = -f.baseChange A := by ext simp [baseChange_eq_ltensor, tmul_neg] end Ring section liftBaseChange variable {R M N} (A) [CommSemiring R] [CommSemiring A] [Algebra R A] [AddCommMonoid M] variable [AddCommMonoid N] [Module R M] [Module R N] [Module A N] [IsScalarTower R A N] /-- If `M` is an `R`-module and `N` is an `A`-module, then `A`-linear maps `A ⊗[R] M →ₗ[A] N` correspond to `R` linear maps `M →ₗ[R] N` by composing with `M → A ⊗ M`, `x ↦ 1 ⊗ x`. -/ noncomputable def liftBaseChangeEquiv : (M →ₗ[R] N) ≃ₗ[A] (A ⊗[R] M →ₗ[A] N) := (LinearMap.ringLmapEquivSelf _ _ _).symm.trans (AlgebraTensorModule.lift.equiv _ _ _ _ _ _) /-- If `N` is an `A` module, we may lift a linear map `M →ₗ[R] N` to `A ⊗[R] M →ₗ[A] N` -/ noncomputable abbrev liftBaseChange (l : M →ₗ[R] N) : A ⊗[R] M →ₗ[A] N := LinearMap.liftBaseChangeEquiv A l @[simp] lemma liftBaseChange_tmul (l : M →ₗ[R] N) (x y) : l.liftBaseChange A (x ⊗ₜ y) = x • l y := rfl lemma liftBaseChange_one_tmul (l : M →ₗ[R] N) (y) : l.liftBaseChange A (1 ⊗ₜ y) = l y := by simp @[simp] lemma liftBaseChangeEquiv_symm_apply (l : A ⊗[R] M →ₗ[A] N) (x) : (liftBaseChangeEquiv A).symm l x = l (1 ⊗ₜ x) := rfl lemma liftBaseChange_comp {P} [AddCommMonoid P] [Module A P] [Module R P] [IsScalarTower R A P] (l : M →ₗ[R] N) (l' : N →ₗ[A] P) : l' ∘ₗ l.liftBaseChange A = (l'.restrictScalars R ∘ₗ l).liftBaseChange A := by ext simp @[simp] lemma range_liftBaseChange (l : M →ₗ[R] N) : LinearMap.range (l.liftBaseChange A) = Submodule.span A (LinearMap.range l) := by apply le_antisymm · rintro _ ⟨x, rfl⟩ induction x using TensorProduct.induction_on · simp · rw [LinearMap.liftBaseChange_tmul] exact Submodule.smul_mem _ _ (Submodule.subset_span ⟨_, rfl⟩) · rw [map_add] exact add_mem ‹_› ‹_› · rw [Submodule.span_le] rintro _ ⟨x, rfl⟩ exact ⟨1 ⊗ₜ x, by simp⟩ end liftBaseChange end LinearMap namespace Module.End open LinearMap variable (R M N : Type*) [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid N] [Module R N] /-- The map `LinearMap.lTensorHom` which sends `f ↦ 1 ⊗ f` as a morphism of algebras. -/ @[simps!] noncomputable def lTensorAlgHom : Module.End R M →ₐ[R] Module.End R (N ⊗[R] M) := .ofLinearMap (lTensorHom (M := N)) (lTensor_id N M) (lTensor_mul N) /-- The map `LinearMap.rTensorHom` which sends `f ↦ f ⊗ 1` as a morphism of algebras. -/ @[simps!] noncomputable def rTensorAlgHom : Module.End R M →ₐ[R] Module.End R (M ⊗[R] N) := .ofLinearMap (rTensorHom (M := N)) (rTensor_id N M) (rTensor_mul N) end Module.End namespace Algebra namespace TensorProduct universe uR uS uA uB uC uD uE uF variable {R : Type uR} {S : Type uS} variable {A : Type uA} {B : Type uB} {C : Type uC} {D : Type uD} {E : Type uE} {F : Type uF} /-! ### The `R`-algebra structure on `A ⊗[R] B` -/ section AddCommMonoidWithOne variable [CommSemiring R] variable [AddCommMonoidWithOne A] [Module R A] variable [AddCommMonoidWithOne B] [Module R B] instance : One (A ⊗[R] B) where one := 1 ⊗ₜ 1 theorem one_def : (1 : A ⊗[R] B) = (1 : A) ⊗ₜ (1 : B) := rfl instance instAddCommMonoidWithOne : AddCommMonoidWithOne (A ⊗[R] B) where natCast n := n ⊗ₜ 1 natCast_zero := by simp natCast_succ n := by simp [add_tmul, one_def] add_comm := add_comm theorem natCast_def (n : ℕ) : (n : A ⊗[R] B) = (n : A) ⊗ₜ (1 : B) := rfl theorem natCast_def' (n : ℕ) : (n : A ⊗[R] B) = (1 : A) ⊗ₜ (n : B) := by rw [natCast_def, ← nsmul_one, smul_tmul, nsmul_one] end AddCommMonoidWithOne section NonUnitalNonAssocSemiring variable [CommSemiring R] variable [NonUnitalNonAssocSemiring A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonUnitalNonAssocSemiring B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] /-- (Implementation detail) The multiplication map on `A ⊗[R] B`, as an `R`-bilinear map. -/ @[irreducible] def mul : A ⊗[R] B →ₗ[R] A ⊗[R] B →ₗ[R] A ⊗[R] B := TensorProduct.map₂ (LinearMap.mul R A) (LinearMap.mul R B) unseal mul in @[simp] theorem mul_apply (a₁ a₂ : A) (b₁ b₂ : B) : mul (a₁ ⊗ₜ[R] b₁) (a₂ ⊗ₜ[R] b₂) = (a₁ * a₂) ⊗ₜ[R] (b₁ * b₂) := rfl -- providing this instance separately makes some downstream code substantially faster instance instMul : Mul (A ⊗[R] B) where mul a b := mul a b unseal mul in @[simp] theorem tmul_mul_tmul (a₁ a₂ : A) (b₁ b₂ : B) : a₁ ⊗ₜ[R] b₁ * a₂ ⊗ₜ[R] b₂ = (a₁ * a₂) ⊗ₜ[R] (b₁ * b₂) := rfl unseal mul in theorem _root_.SemiconjBy.tmul {a₁ a₂ a₃ : A} {b₁ b₂ b₃ : B} (ha : SemiconjBy a₁ a₂ a₃) (hb : SemiconjBy b₁ b₂ b₃) : SemiconjBy (a₁ ⊗ₜ[R] b₁) (a₂ ⊗ₜ[R] b₂) (a₃ ⊗ₜ[R] b₃) := congr_arg₂ (· ⊗ₜ[R] ·) ha.eq hb.eq nonrec theorem _root_.Commute.tmul {a₁ a₂ : A} {b₁ b₂ : B} (ha : Commute a₁ a₂) (hb : Commute b₁ b₂) : Commute (a₁ ⊗ₜ[R] b₁) (a₂ ⊗ₜ[R] b₂) := ha.tmul hb instance instNonUnitalNonAssocSemiring : NonUnitalNonAssocSemiring (A ⊗[R] B) where left_distrib a b c := by simp [HMul.hMul, Mul.mul] right_distrib a b c := by simp [HMul.hMul, Mul.mul] zero_mul a := by simp [HMul.hMul, Mul.mul] mul_zero a := by simp [HMul.hMul, Mul.mul] -- we want `isScalarTower_right` to take priority since it's better for unification elsewhere instance (priority := 100) isScalarTower_right [Monoid S] [DistribMulAction S A] [IsScalarTower S A A] [SMulCommClass R S A] : IsScalarTower S (A ⊗[R] B) (A ⊗[R] B) where smul_assoc r x y := by change r • x * y = r • (x * y) induction y with | zero => simp [smul_zero] | tmul a b => induction x with | zero => simp [smul_zero] | tmul a' b' => dsimp rw [TensorProduct.smul_tmul', TensorProduct.smul_tmul', tmul_mul_tmul, smul_mul_assoc] | add x y hx hy => simp [smul_add, add_mul _, *] | add x y hx hy => simp [smul_add, mul_add _, *] -- we want `Algebra.to_smulCommClass` to take priority since it's better for unification elsewhere instance (priority := 100) sMulCommClass_right [Monoid S] [DistribMulAction S A] [SMulCommClass S A A] [SMulCommClass R S A] : SMulCommClass S (A ⊗[R] B) (A ⊗[R] B) where smul_comm r x y := by change r • (x * y) = x * r • y induction y with | zero => simp [smul_zero] | tmul a b => induction x with | zero => simp [smul_zero] | tmul a' b' => dsimp rw [TensorProduct.smul_tmul', TensorProduct.smul_tmul', tmul_mul_tmul, mul_smul_comm] | add x y hx hy => simp [smul_add, add_mul _, *] | add x y hx hy => simp [smul_add, mul_add _, *] end NonUnitalNonAssocSemiring section NonAssocSemiring variable [CommSemiring R] variable [NonAssocSemiring A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonAssocSemiring B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] protected theorem one_mul (x : A ⊗[R] B) : mul (1 ⊗ₜ 1) x = x := by refine TensorProduct.induction_on x ?_ ?_ ?_ <;> simp +contextual protected theorem mul_one (x : A ⊗[R] B) : mul x (1 ⊗ₜ 1) = x := by refine TensorProduct.induction_on x ?_ ?_ ?_ <;> simp +contextual instance instNonAssocSemiring : NonAssocSemiring (A ⊗[R] B) where one_mul := Algebra.TensorProduct.one_mul mul_one := Algebra.TensorProduct.mul_one toNonUnitalNonAssocSemiring := instNonUnitalNonAssocSemiring __ := instAddCommMonoidWithOne end NonAssocSemiring section NonUnitalSemiring variable [CommSemiring R] variable [NonUnitalSemiring A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonUnitalSemiring B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] unseal mul in protected theorem mul_assoc (x y z : A ⊗[R] B) : mul (mul x y) z = mul x (mul y z) := by -- restate as an equality of morphisms so that we can use `ext` suffices LinearMap.llcomp R _ _ _ mul ∘ₗ mul = (LinearMap.llcomp R _ _ _ LinearMap.lflip <| LinearMap.llcomp R _ _ _ mul.flip ∘ₗ mul).flip by exact DFunLike.congr_fun (DFunLike.congr_fun (DFunLike.congr_fun this x) y) z ext xa xb ya yb za zb exact congr_arg₂ (· ⊗ₜ ·) (mul_assoc xa ya za) (mul_assoc xb yb zb) instance instNonUnitalSemiring : NonUnitalSemiring (A ⊗[R] B) where mul_assoc := Algebra.TensorProduct.mul_assoc end NonUnitalSemiring section Semiring variable [CommSemiring R] variable [Semiring A] [Algebra R A] variable [Semiring B] [Algebra R B] variable [Semiring C] [Algebra R C] instance instSemiring : Semiring (A ⊗[R] B) where left_distrib a b c := by simp [HMul.hMul, Mul.mul] right_distrib a b c := by simp [HMul.hMul, Mul.mul] zero_mul a := by simp [HMul.hMul, Mul.mul] mul_zero a := by simp [HMul.hMul, Mul.mul] mul_assoc := Algebra.TensorProduct.mul_assoc one_mul := Algebra.TensorProduct.one_mul mul_one := Algebra.TensorProduct.mul_one natCast_zero := AddMonoidWithOne.natCast_zero natCast_succ := AddMonoidWithOne.natCast_succ @[simp] theorem tmul_pow (a : A) (b : B) (k : ℕ) : a ⊗ₜ[R] b ^ k = (a ^ k) ⊗ₜ[R] (b ^ k) := by induction' k with k ih · simp [one_def] · simp [pow_succ, ih] /-- The ring morphism `A →+* A ⊗[R] B` sending `a` to `a ⊗ₜ 1`. -/ @[simps] def includeLeftRingHom : A →+* A ⊗[R] B where toFun a := a ⊗ₜ 1 map_zero' := by simp map_add' := by simp [add_tmul] map_one' := rfl map_mul' := by simp variable [CommSemiring S] [Algebra S A] instance leftAlgebra [SMulCommClass R S A] : Algebra S (A ⊗[R] B) := { commutes' := fun r x => by dsimp only [RingHom.toFun_eq_coe, RingHom.comp_apply, includeLeftRingHom_apply] rw [algebraMap_eq_smul_one, ← smul_tmul', ← one_def, mul_smul_comm, smul_mul_assoc, mul_one, one_mul] smul_def' := fun r x => by dsimp only [RingHom.toFun_eq_coe, RingHom.comp_apply, includeLeftRingHom_apply] rw [algebraMap_eq_smul_one, ← smul_tmul', smul_mul_assoc, ← one_def, one_mul] algebraMap := TensorProduct.includeLeftRingHom.comp (algebraMap S A) } example : (Semiring.toNatAlgebra : Algebra ℕ (ℕ ⊗[ℕ] B)) = leftAlgebra := rfl -- This is for the `undergrad.yaml` list. /-- The tensor product of two `R`-algebras is an `R`-algebra. -/ instance instAlgebra : Algebra R (A ⊗[R] B) := inferInstance @[simp] theorem algebraMap_apply [SMulCommClass R S A] (r : S) : algebraMap S (A ⊗[R] B) r = (algebraMap S A) r ⊗ₜ 1 := rfl theorem algebraMap_apply' (r : R) : algebraMap R (A ⊗[R] B) r = 1 ⊗ₜ algebraMap R B r := by rw [algebraMap_apply, Algebra.algebraMap_eq_smul_one, Algebra.algebraMap_eq_smul_one, smul_tmul] /-- The `R`-algebra morphism `A →ₐ[R] A ⊗[R] B` sending `a` to `a ⊗ₜ 1`. -/ def includeLeft [SMulCommClass R S A] : A →ₐ[S] A ⊗[R] B := { includeLeftRingHom with commutes' := by simp } @[simp] theorem includeLeft_apply [SMulCommClass R S A] (a : A) : (includeLeft : A →ₐ[S] A ⊗[R] B) a = a ⊗ₜ 1 := rfl /-- The algebra morphism `B →ₐ[R] A ⊗[R] B` sending `b` to `1 ⊗ₜ b`. -/ def includeRight : B →ₐ[R] A ⊗[R] B where toFun b := 1 ⊗ₜ b map_zero' := by simp map_add' := by simp [tmul_add] map_one' := rfl map_mul' := by simp commutes' r := by simp only [algebraMap_apply'] @[simp] theorem includeRight_apply (b : B) : (includeRight : B →ₐ[R] A ⊗[R] B) b = 1 ⊗ₜ b := rfl theorem includeLeftRingHom_comp_algebraMap : (includeLeftRingHom.comp (algebraMap R A) : R →+* A ⊗[R] B) = includeRight.toRingHom.comp (algebraMap R B) := by ext simp section ext variable [Algebra R S] [Algebra S C] [IsScalarTower R S A] [IsScalarTower R S C] /-- A version of `TensorProduct.ext` for `AlgHom`. Using this as the `@[ext]` lemma instead of `Algebra.TensorProduct.ext'` allows `ext` to apply lemmas specific to `A →ₐ[S] _` and `B →ₐ[R] _`; notably this allows recursion into nested tensor products of algebras. See note [partially-applied ext lemmas]. -/ @[ext high] theorem ext ⦃f g : (A ⊗[R] B) →ₐ[S] C⦄ (ha : f.comp includeLeft = g.comp includeLeft) (hb : (f.restrictScalars R).comp includeRight = (g.restrictScalars R).comp includeRight) : f = g := by apply AlgHom.toLinearMap_injective ext a b have := congr_arg₂ HMul.hMul (AlgHom.congr_fun ha a) (AlgHom.congr_fun hb b) dsimp at * rwa [← map_mul, ← map_mul, tmul_mul_tmul, one_mul, mul_one] at this theorem ext' {g h : A ⊗[R] B →ₐ[S] C} (H : ∀ a b, g (a ⊗ₜ b) = h (a ⊗ₜ b)) : g = h := ext (AlgHom.ext fun _ => H _ _) (AlgHom.ext fun _ => H _ _) end ext end Semiring section AddCommGroupWithOne variable [CommSemiring R] variable [AddCommGroupWithOne A] [Module R A] variable [AddCommGroupWithOne B] [Module R B] instance instAddCommGroupWithOne : AddCommGroupWithOne (A ⊗[R] B) where toAddCommGroup := TensorProduct.addCommGroup __ := instAddCommMonoidWithOne intCast z := z ⊗ₜ (1 : B) intCast_ofNat n := by simp [natCast_def] intCast_negSucc n := by simp [natCast_def, add_tmul, neg_tmul, one_def] theorem intCast_def (z : ℤ) : (z : A ⊗[R] B) = (z : A) ⊗ₜ (1 : B) := rfl end AddCommGroupWithOne section NonUnitalNonAssocRing variable [CommRing R] variable [NonUnitalNonAssocRing A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonUnitalNonAssocRing B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] instance instNonUnitalNonAssocRing : NonUnitalNonAssocRing (A ⊗[R] B) where toAddCommGroup := TensorProduct.addCommGroup __ := instNonUnitalNonAssocSemiring end NonUnitalNonAssocRing section NonAssocRing variable [CommRing R] variable [NonAssocRing A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonAssocRing B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] instance instNonAssocRing : NonAssocRing (A ⊗[R] B) where toAddCommGroup := TensorProduct.addCommGroup __ := instNonAssocSemiring __ := instAddCommGroupWithOne end NonAssocRing section NonUnitalRing variable [CommRing R] variable [NonUnitalRing A] [Module R A] [SMulCommClass R A A] [IsScalarTower R A A] variable [NonUnitalRing B] [Module R B] [SMulCommClass R B B] [IsScalarTower R B B] instance instNonUnitalRing : NonUnitalRing (A ⊗[R] B) where toAddCommGroup := TensorProduct.addCommGroup __ := instNonUnitalSemiring end NonUnitalRing section CommSemiring variable [CommSemiring R] variable [CommSemiring A] [Algebra R A] variable [CommSemiring B] [Algebra R B] instance instCommSemiring : CommSemiring (A ⊗[R] B) where toSemiring := inferInstance mul_comm x y := by refine TensorProduct.induction_on x ?_ ?_ ?_ · simp · intro a₁ b₁ refine TensorProduct.induction_on y ?_ ?_ ?_ · simp · intro a₂ b₂ simp [mul_comm] · intro a₂ b₂ ha hb simp [mul_add, add_mul, ha, hb] · intro x₁ x₂ h₁ h₂ simp [mul_add, add_mul, h₁, h₂] end CommSemiring section Ring variable [CommRing R] variable [Ring A] [Algebra R A] variable [Ring B] [Algebra R B] instance instRing : Ring (A ⊗[R] B) where toSemiring := instSemiring __ := TensorProduct.addCommGroup __ := instNonAssocRing theorem intCast_def' (z : ℤ) : (z : A ⊗[R] B) = (1 : A) ⊗ₜ (z : B) := by rw [intCast_def, ← zsmul_one, smul_tmul, zsmul_one] -- verify there are no diamonds example : (instRing : Ring (A ⊗[R] B)).toAddCommGroup = addCommGroup := by with_reducible_and_instances rfl -- fails at `with_reducible_and_instances rfl` https://github.com/leanprover-community/mathlib4/issues/10906 example : (Ring.toIntAlgebra _ : Algebra ℤ (ℤ ⊗[ℤ] B)) = leftAlgebra := rfl end Ring section CommRing variable [CommRing R] variable [CommRing A] [Algebra R A] variable [CommRing B] [Algebra R B] instance instCommRing : CommRing (A ⊗[R] B) := { toRing := inferInstance mul_comm := mul_comm } end CommRing section RightAlgebra variable [CommSemiring R] variable [Semiring A] [Algebra R A] variable [CommSemiring B] [Algebra R B] /-- `S ⊗[R] T` has a `T`-algebra structure. This is not a global instance or else the action of `S` on `S ⊗[R] S` would be ambiguous. -/ abbrev rightAlgebra : Algebra B (A ⊗[R] B) := includeRight.toRingHom.toAlgebra' fun b x => by suffices LinearMap.mulLeft R (includeRight b) = LinearMap.mulRight R (includeRight b) from congr($this x) ext xa xb simp [mul_comm] attribute [local instance] TensorProduct.rightAlgebra instance right_isScalarTower : IsScalarTower R B (A ⊗[R] B) := IsScalarTower.of_algebraMap_eq fun r => (Algebra.TensorProduct.includeRight.commutes r).symm end RightAlgebra /-- Verify that typeclass search finds the ring structure on `A ⊗[ℤ] B` when `A` and `B` are merely rings, by treating both as `ℤ`-algebras. -/ example [Ring A] [Ring B] : Ring (A ⊗[ℤ] B) := by infer_instance /-- Verify that typeclass search finds the comm_ring structure on `A ⊗[ℤ] B` when `A` and `B` are merely comm_rings, by treating both as `ℤ`-algebras. -/ example [CommRing A] [CommRing B] : CommRing (A ⊗[ℤ] B) := by infer_instance /-! We now build the structure maps for the symmetric monoidal category of `R`-algebras. -/ section Monoidal section variable [CommSemiring R] [CommSemiring S] [Algebra R S] variable [Semiring A] [Algebra R A] [Algebra S A] [IsScalarTower R S A] variable [Semiring B] [Algebra R B] variable [Semiring C] [Algebra S C] variable [Semiring D] [Algebra R D] /-- To check a linear map preserves multiplication, it suffices to check it on pure tensors. See `algHomOfLinearMapTensorProduct` for a bundled version. -/ lemma _root_.LinearMap.map_mul_of_map_mul_tmul {f : A ⊗[R] B →ₗ[S] C} (hf : ∀ (a₁ a₂ : A) (b₁ b₂ : B), f ((a₁ * a₂) ⊗ₜ (b₁ * b₂)) = f (a₁ ⊗ₜ b₁) * f (a₂ ⊗ₜ b₂)) (x y : A ⊗[R] B) : f (x * y) = f x * f y := f.map_mul_iff.2 (by -- these instances are needed by the statement of `ext`, but not by the current definition. letI : Algebra R C := RestrictScalars.algebra R S C letI : IsScalarTower R S C := RestrictScalars.isScalarTower R S C ext dsimp exact hf _ _ _ _) x y /-- Build an algebra morphism from a linear map out of a tensor product, and evidence that on pure tensors, it preserves multiplication and the identity. Note that we state `h_one` using `1 ⊗ₜ[R] 1` instead of `1` so that lemmas about `f` applied to pure tensors can be directly applied by the caller (without needing `TensorProduct.one_def`). -/ def algHomOfLinearMapTensorProduct (f : A ⊗[R] B →ₗ[S] C) (h_mul : ∀ (a₁ a₂ : A) (b₁ b₂ : B), f ((a₁ * a₂) ⊗ₜ (b₁ * b₂)) = f (a₁ ⊗ₜ b₁) * f (a₂ ⊗ₜ b₂)) (h_one : f (1 ⊗ₜ[R] 1) = 1) : A ⊗[R] B →ₐ[S] C := AlgHom.ofLinearMap f h_one (f.map_mul_of_map_mul_tmul h_mul) @[simp] theorem algHomOfLinearMapTensorProduct_apply (f h_mul h_one x) : (algHomOfLinearMapTensorProduct f h_mul h_one : A ⊗[R] B →ₐ[S] C) x = f x := rfl /-- Build an algebra equivalence from a linear equivalence out of a tensor product, and evidence that on pure tensors, it preserves multiplication and the identity. Note that we state `h_one` using `1 ⊗ₜ[R] 1` instead of `1` so that lemmas about `f` applied to pure tensors can be directly applied by the caller (without needing `TensorProduct.one_def`). -/ def algEquivOfLinearEquivTensorProduct (f : A ⊗[R] B ≃ₗ[S] C) (h_mul : ∀ (a₁ a₂ : A) (b₁ b₂ : B), f ((a₁ * a₂) ⊗ₜ (b₁ * b₂)) = f (a₁ ⊗ₜ b₁) * f (a₂ ⊗ₜ b₂)) (h_one : f (1 ⊗ₜ[R] 1) = 1) : A ⊗[R] B ≃ₐ[S] C := { algHomOfLinearMapTensorProduct (f : A ⊗[R] B →ₗ[S] C) h_mul h_one, f with } @[simp] theorem algEquivOfLinearEquivTensorProduct_apply (f h_mul h_one x) : (algEquivOfLinearEquivTensorProduct f h_mul h_one : A ⊗[R] B ≃ₐ[S] C) x = f x := rfl variable [Algebra R C] /-- Build an algebra equivalence from a linear equivalence out of a triple tensor product, and evidence of multiplicativity on pure tensors. -/ def algEquivOfLinearEquivTripleTensorProduct (f : (A ⊗[R] B) ⊗[R] C ≃ₗ[R] D) (h_mul : ∀ (a₁ a₂ : A) (b₁ b₂ : B) (c₁ c₂ : C), f ((a₁ * a₂) ⊗ₜ (b₁ * b₂) ⊗ₜ (c₁ * c₂)) = f (a₁ ⊗ₜ b₁ ⊗ₜ c₁) * f (a₂ ⊗ₜ b₂ ⊗ₜ c₂)) (h_one : f (((1 : A) ⊗ₜ[R] (1 : B)) ⊗ₜ[R] (1 : C)) = 1) : (A ⊗[R] B) ⊗[R] C ≃ₐ[R] D := AlgEquiv.ofLinearEquiv f h_one <| f.map_mul_iff.2 <| by ext dsimp exact h_mul _ _ _ _ _ _ @[simp] theorem algEquivOfLinearEquivTripleTensorProduct_apply (f h_mul h_one x) : (algEquivOfLinearEquivTripleTensorProduct f h_mul h_one : (A ⊗[R] B) ⊗[R] C ≃ₐ[R] D) x = f x := rfl section lift variable [IsScalarTower R S C] /-- The forward direction of the universal property of tensor products of algebras; any algebra morphism from the tensor product can be factored as the product of two algebra morphisms that commute. See `Algebra.TensorProduct.liftEquiv` for the fact that every morphism factors this way. -/ def lift (f : A →ₐ[S] C) (g : B →ₐ[R] C) (hfg : ∀ x y, Commute (f x) (g y)) : (A ⊗[R] B) →ₐ[S] C := algHomOfLinearMapTensorProduct (AlgebraTensorModule.lift <| letI restr : (C →ₗ[S] C) →ₗ[S] _ := { toFun := (·.restrictScalars R) map_add' := fun _ _ => LinearMap.ext fun _ => rfl map_smul' := fun _ _ => LinearMap.ext fun _ => rfl } LinearMap.flip <| (restr ∘ₗ LinearMap.mul S C ∘ₗ f.toLinearMap).flip ∘ₗ g) (fun a₁ a₂ b₁ b₂ => show f (a₁ * a₂) * g (b₁ * b₂) = f a₁ * g b₁ * (f a₂ * g b₂) by rw [map_mul, map_mul, (hfg a₂ b₁).mul_mul_mul_comm]) (show f 1 * g 1 = 1 by rw [map_one, map_one, one_mul]) @[simp] theorem lift_tmul (f : A →ₐ[S] C) (g : B →ₐ[R] C) (hfg : ∀ x y, Commute (f x) (g y)) (a : A) (b : B) : lift f g hfg (a ⊗ₜ b) = f a * g b := rfl @[simp] theorem lift_includeLeft_includeRight : lift includeLeft includeRight (fun _ _ => (Commute.one_right _).tmul (Commute.one_left _)) = .id S (A ⊗[R] B) := by ext <;> simp @[simp] theorem lift_comp_includeLeft (f : A →ₐ[S] C) (g : B →ₐ[R] C) (hfg : ∀ x y, Commute (f x) (g y)) : (lift f g hfg).comp includeLeft = f := AlgHom.ext <| by simp @[simp] theorem lift_comp_includeRight (f : A →ₐ[S] C) (g : B →ₐ[R] C) (hfg : ∀ x y, Commute (f x) (g y)) : ((lift f g hfg).restrictScalars R).comp includeRight = g := AlgHom.ext <| by simp /-- The universal property of the tensor product of algebras. Pairs of algebra morphisms that commute are equivalent to algebra morphisms from the tensor product. This is `Algebra.TensorProduct.lift` as an equivalence. See also `GradedTensorProduct.liftEquiv` for an alternative commutativity requirement for graded algebra. -/ @[simps] def liftEquiv : {fg : (A →ₐ[S] C) × (B →ₐ[R] C) // ∀ x y, Commute (fg.1 x) (fg.2 y)} ≃ ((A ⊗[R] B) →ₐ[S] C) where toFun fg := lift fg.val.1 fg.val.2 fg.prop invFun f' := ⟨(f'.comp includeLeft, (f'.restrictScalars R).comp includeRight), fun _ _ => ((Commute.one_right _).tmul (Commute.one_left _)).map f'⟩ left_inv fg := by ext <;> simp right_inv f' := by ext <;> simp end lift end variable [CommSemiring R] [CommSemiring S] [Algebra R S] variable [Semiring A] [Algebra R A] [Algebra S A] [IsScalarTower R S A] variable [Semiring B] [Algebra R B] variable [Semiring C] [Algebra R C] [Algebra S C] [IsScalarTower R S C] variable [Semiring D] [Algebra R D] variable [Semiring E] [Algebra R E] [Algebra S E] [IsScalarTower R S E] variable [Semiring F] [Algebra R F] section variable (R A) /-- The base ring is a left identity for the tensor product of algebra, up to algebra isomorphism. -/ protected nonrec def lid : R ⊗[R] A ≃ₐ[R] A := algEquivOfLinearEquivTensorProduct (TensorProduct.lid R A) (by simp only [mul_smul, lid_tmul, Algebra.smul_mul_assoc, Algebra.mul_smul_comm] simp_rw [← mul_smul, mul_comm] simp) (by simp [Algebra.smul_def]) @[simp] theorem lid_toLinearEquiv : (TensorProduct.lid R A).toLinearEquiv = _root_.TensorProduct.lid R A := rfl variable {R} {A} in @[simp] theorem lid_tmul (r : R) (a : A) : TensorProduct.lid R A (r ⊗ₜ a) = r • a := rfl variable {A} in @[simp] theorem lid_symm_apply (a : A) : (TensorProduct.lid R A).symm a = 1 ⊗ₜ a := rfl variable (S) /-- The base ring is a right identity for the tensor product of algebra, up to algebra isomorphism. Note that if `A` is commutative this can be instantiated with `S = A`. -/ protected nonrec def rid : A ⊗[R] R ≃ₐ[S] A := algEquivOfLinearEquivTensorProduct (AlgebraTensorModule.rid R S A) (fun a₁ a₂ r₁ r₂ => smul_mul_smul_comm r₁ a₁ r₂ a₂ |>.symm) (one_smul R _) @[simp] theorem rid_toLinearEquiv : (TensorProduct.rid R S A).toLinearEquiv = AlgebraTensorModule.rid R S A := rfl variable {R A} in @[simp] theorem rid_tmul (r : R) (a : A) : TensorProduct.rid R S A (a ⊗ₜ r) = r • a := rfl variable {A} in @[simp] theorem rid_symm_apply (a : A) : (TensorProduct.rid R S A).symm a = a ⊗ₜ 1 := rfl section CompatibleSMul variable (R S A B : Type*) [CommSemiring R] [CommSemiring S] [Semiring A] [Semiring B] variable [Algebra R A] [Algebra R B] [Algebra S A] [Algebra S B] variable [SMulCommClass R S A] [CompatibleSMul R S A B] /-- If A and B are both R- and S-algebras and their actions on them commute, and if the S-action on `A ⊗[R] B` can switch between the two factors, then there is a canonical S-algebra homomorphism from `A ⊗[S] B` to `A ⊗[R] B`. -/ def mapOfCompatibleSMul : A ⊗[S] B →ₐ[S] A ⊗[R] B := .ofLinearMap (_root_.TensorProduct.mapOfCompatibleSMul R S A B) rfl fun x ↦ x.induction_on (by simp) (fun _ _ y ↦ y.induction_on (by simp) (by simp) fun _ _ h h' ↦ by simp only [mul_add, map_add, h, h']) fun _ _ h h' _ ↦ by simp only [add_mul, map_add, h, h'] @[simp] theorem mapOfCompatibleSMul_tmul (m n) : mapOfCompatibleSMul R S A B (m ⊗ₜ n) = m ⊗ₜ n := rfl theorem mapOfCompatibleSMul_surjective : Function.Surjective (mapOfCompatibleSMul R S A B) := _root_.TensorProduct.mapOfCompatibleSMul_surjective R S A B attribute [local instance] SMulCommClass.symm /-- `mapOfCompatibleSMul R S A B` is also A-linear. -/ def mapOfCompatibleSMul' : A ⊗[S] B →ₐ[R] A ⊗[R] B := .ofLinearMap (_root_.TensorProduct.mapOfCompatibleSMul' R S A B) rfl (map_mul <| mapOfCompatibleSMul R S A B) /-- If the R- and S-actions on A and B satisfy `CompatibleSMul` both ways, then `A ⊗[S] B` is canonically isomorphic to `A ⊗[R] B`. -/ def equivOfCompatibleSMul [CompatibleSMul S R A B] : A ⊗[S] B ≃ₐ[S] A ⊗[R] B where __ := mapOfCompatibleSMul R S A B invFun := mapOfCompatibleSMul S R A B __ := _root_.TensorProduct.equivOfCompatibleSMul R S A B variable [Algebra R S] [CompatibleSMul R S S A] [CompatibleSMul S R S A] omit [SMulCommClass R S A] /-- If the R- and S- action on S and A satisfy `CompatibleSMul` both ways, then `S ⊗[R] A` is canonically isomorphic to `A`. -/ def lidOfCompatibleSMul : S ⊗[R] A ≃ₐ[S] A := (equivOfCompatibleSMul R S S A).symm.trans (TensorProduct.lid _ _) theorem lidOfCompatibleSMul_tmul (s a) : lidOfCompatibleSMul R S A (s ⊗ₜ[R] a) = s • a := rfl instance {R M N : Type*} [CommSemiring R] [AddCommGroup M] [AddCommGroup N] [Module R M] [Module R N] [Module ℚ M] [Module ℚ N] : CompatibleSMul R ℚ M N where smul_tmul q m n := by suffices q.den • ((q • m) ⊗ₜ[R] n) = q.den • (m ⊗ₜ[R] (q • n)) from smul_right_injective (M ⊗[R] N) (c := q.den) q.den_nz <| by norm_cast rw [smul_tmul', ← tmul_smul, ← smul_assoc, ← smul_assoc, nsmul_eq_mul, Rat.den_mul_eq_num] norm_cast rw [smul_tmul] end CompatibleSMul section variable (B) unseal mul in /-- The tensor product of R-algebras is commutative, up to algebra isomorphism. -/ protected def comm : A ⊗[R] B ≃ₐ[R] B ⊗[R] A := algEquivOfLinearEquivTensorProduct (_root_.TensorProduct.comm R A B) (fun _ _ _ _ => rfl) rfl @[simp] theorem comm_toLinearEquiv : (Algebra.TensorProduct.comm R A B).toLinearEquiv = _root_.TensorProduct.comm R A B := rfl variable {A B} in @[simp] theorem comm_tmul (a : A) (b : B) : TensorProduct.comm R A B (a ⊗ₜ b) = b ⊗ₜ a :=
rfl variable {A B} in
Mathlib/RingTheory/TensorProduct/Basic.lean
901
903
/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Yaël Dillies -/ import Mathlib.Order.Cover import Mathlib.Order.Interval.Finset.Defs /-! # Intervals as finsets This file provides basic results about all the `Finset.Ixx`, which are defined in `Order.Interval.Finset.Defs`. In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of, respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly functions whose domain is a locally finite order. In particular, this file proves: * `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿` * `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖` * `monotone_iff_forall_wcovBy`: Characterization of monotone functions * `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions ## TODO This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general, what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure. Complete the API. See https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235 for some ideas. -/ assert_not_exists MonoidWithZero Finset.sum open Function OrderDual open FinsetInterval variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α} namespace Finset section Preorder variable [Preorder α] section LocallyFiniteOrder variable [LocallyFiniteOrder α] @[simp] theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc @[simp] theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico @[simp] theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc] @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc -- TODO: This is nonsense. A locally finite order is never densely ordered @[simp] theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo] @[simp] theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff] @[simp] theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff] @[simp] theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff] -- TODO: This is nonsense. A locally finite order is never densely ordered @[simp] theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff] alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff @[simp] theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ := eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2) @[simp] theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ := Icc_eq_empty h.not_le @[simp] theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ := Ico_eq_empty h.not_lt @[simp] theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ := Ioc_eq_empty h.not_lt @[simp] theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ := Ioo_eq_empty h.not_lt theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl] theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl] theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl] theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl] theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1 theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1 theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2 theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2 @[gcongr] theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by simpa [← coe_subset] using Set.Icc_subset_Icc ha hb @[gcongr] theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by simpa [← coe_subset] using Set.Ico_subset_Ico ha hb @[gcongr] theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb @[gcongr] theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb @[gcongr] theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b := Icc_subset_Icc h le_rfl @[gcongr] theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b := Ico_subset_Ico h le_rfl @[gcongr] theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b := Ioc_subset_Ioc h le_rfl @[gcongr] theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b := Ioo_subset_Ioo h le_rfl @[gcongr] theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ := Icc_subset_Icc le_rfl h @[gcongr] theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ := Ico_subset_Ico le_rfl h @[gcongr] theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ := Ioc_subset_Ioc le_rfl h @[gcongr] theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ := Ioo_subset_Ioo le_rfl h theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by rw [← coe_subset, coe_Ico, coe_Ioo] exact Set.Ico_subset_Ioo_left h theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by rw [← coe_subset, coe_Ioc, coe_Ioo] exact Set.Ioc_subset_Ioo_right h theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by rw [← coe_subset, coe_Icc, coe_Ico] exact Set.Icc_subset_Ico_right h theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by rw [← coe_subset, coe_Ioo, coe_Ico] exact Set.Ioo_subset_Ico_self theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by rw [← coe_subset, coe_Ioo, coe_Ioc] exact Set.Ioo_subset_Ioc_self theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by rw [← coe_subset, coe_Ico, coe_Icc] exact Set.Ico_subset_Icc_self theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by rw [← coe_subset, coe_Ioc, coe_Icc] exact Set.Ioc_subset_Icc_self theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b := Ioo_subset_Ico_self.trans Ico_subset_Icc_self theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁] theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁] theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁] theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ := (Icc_subset_Ico_iff h₁.dual).trans and_comm --TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff` theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ := by rw [← coe_ssubset, coe_Icc, coe_Icc] exact Set.Icc_ssubset_Icc_left hI ha hb theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ := by rw [← coe_ssubset, coe_Icc, coe_Icc] exact Set.Icc_ssubset_Icc_right hI ha hb @[simp] theorem Ioc_disjoint_Ioc_of_le {d : α} (hbc : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) := disjoint_left.2 fun _ h1 h2 ↦ not_and_of_not_left _ ((mem_Ioc.1 h1).2.trans hbc).not_lt (mem_Ioc.1 h2) variable (a) theorem Ico_self : Ico a a = ∅ := Ico_eq_empty <| lt_irrefl _ theorem Ioc_self : Ioc a a = ∅ := Ioc_eq_empty <| lt_irrefl _ theorem Ioo_self : Ioo a a = ∅ := Ioo_eq_empty <| lt_irrefl _ variable {a} /-- A set with upper and lower bounds in a locally finite order is a fintype -/ def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s) (hb : b ∈ upperBounds s) : Fintype s := Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩ section Filter theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) : {x ∈ Ico a b | x < c} = ∅ := filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) : {x ∈ Ico a b | x < c} = Ico a b := filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) : {x ∈ Ico a b | x < c} = Ico a c := by ext x rw [mem_filter, mem_Ico, mem_Ico, and_right_comm] exact and_iff_left_of_imp fun h => h.2.trans_le hcb theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) : {x ∈ Ico a b | c ≤ x} = Ico a b := filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1 theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] : {x ∈ Ico a b | b ≤ x} = ∅ := filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) : {x ∈ Ico a b | c ≤ x} = Ico c b := by ext x rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm] exact and_iff_right_of_imp fun h => hac.trans h.1 theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) : {x ∈ Icc a b | x < c} = Icc a b := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) : {x ∈ Ioc a b | x < c} = Ioc a b := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α} [DecidablePred (· < c)] (h : a < c) : {x ∈ Iic a | x < c} = Iic a := filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h variable (a b) [Fintype α] theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] : ({j | a < j ∧ j < b} : Finset _) = Ioo a b := by ext; simp theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] : ({j | a < j ∧ j ≤ b} : Finset _) = Ioc a b := by ext; simp theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] : ({j | a ≤ j ∧ j < b} : Finset _) = Ico a b := by ext; simp theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] : ({j | a ≤ j ∧ j ≤ b} : Finset _) = Icc a b := by ext; simp end Filter end LocallyFiniteOrder section LocallyFiniteOrderTop variable [LocallyFiniteOrderTop α] @[simp] theorem Ioi_eq_empty : Ioi a = ∅ ↔ IsMax a := by rw [← coe_eq_empty, coe_Ioi, Set.Ioi_eq_empty_iff] @[simp] alias ⟨_, _root_.IsMax.finsetIoi_eq⟩ := Ioi_eq_empty @[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty] theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ∅ := Ioi_eq_empty.mpr isMax_top @[simp] theorem Ici_bot [OrderBot α] [Fintype α] : Ici (⊥ : α) = univ := by ext a; simp only [mem_Ici, bot_le, mem_univ] @[simp, aesop safe apply (rule_sets := [finsetNonempty])] lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩ lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.nonempty_Ioi_of_not_isMax⟩ := nonempty_Ioi @[simp] theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a := by
Mathlib/Order/Interval/Finset/Basic.lean
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/- Copyright (c) 2023 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.RingTheory.DedekindDomain.Ideal import Mathlib.RingTheory.Discriminant import Mathlib.RingTheory.DedekindDomain.IntegralClosure import Mathlib.NumberTheory.KummerDedekind import Mathlib.RingTheory.IntegralClosure.IntegralRestrict import Mathlib.RingTheory.Trace.Quotient /-! # The different ideal ## Main definition - `Submodule.traceDual`: The dual `L`-sub `B`-module under the trace form. - `FractionalIdeal.dual`: The dual fractional ideal under the trace form. - `differentIdeal`: The different ideal of an extension of integral domains. ## Main results - `conductor_mul_differentIdeal`: If `L = K[x]`, with `x` integral over `A`, then `𝔣 * 𝔇 = (f'(x))` with `f` being the minimal polynomial of `x`. - `aeval_derivative_mem_differentIdeal`: If `L = K[x]`, with `x` integral over `A`, then `f'(x) ∈ 𝔇` with `f` being the minimal polynomial of `x`. ## TODO - Show properties of the different ideal -/ universe u attribute [local instance] FractionRing.liftAlgebra FractionRing.isScalarTower_liftAlgebra variable (A K : Type*) {L : Type u} {B} [CommRing A] [Field K] [CommRing B] [Field L] variable [Algebra A K] [Algebra B L] [Algebra A B] [Algebra K L] [Algebra A L] variable [IsScalarTower A K L] [IsScalarTower A B L] open nonZeroDivisors IsLocalization Matrix Algebra section BIsDomain /-- Under the AKLB setting, `Iᵛ := traceDual A K (I : Submodule B L)` is the `Submodule B L` such that `x ∈ Iᵛ ↔ ∀ y ∈ I, Tr(x, y) ∈ A` -/ noncomputable def Submodule.traceDual (I : Submodule B L) : Submodule B L where __ := (traceForm K L).dualSubmodule (I.restrictScalars A) smul_mem' c x hx a ha := by rw [traceForm_apply, smul_mul_assoc, mul_comm, ← smul_mul_assoc, mul_comm] exact hx _ (Submodule.smul_mem _ c ha) variable {A K} local notation:max I:max "ᵛ" => Submodule.traceDual A K I namespace Submodule lemma mem_traceDual {I : Submodule B L} {x} : x ∈ Iᵛ ↔ ∀ a ∈ I, traceForm K L x a ∈ (algebraMap A K).range := forall₂_congr fun _ _ ↦ mem_one lemma le_traceDual_iff_map_le_one {I J : Submodule B L} : I ≤ Jᵛ ↔ ((I * J : Submodule B L).restrictScalars A).map ((trace K L).restrictScalars A) ≤ 1 := by rw [Submodule.map_le_iff_le_comap, Submodule.restrictScalars_mul, Submodule.mul_le] simp [SetLike.le_def, mem_traceDual] lemma le_traceDual_mul_iff {I J J' : Submodule B L} : I ≤ (J * J')ᵛ ↔ I * J ≤ J'ᵛ := by simp_rw [le_traceDual_iff_map_le_one, mul_assoc] lemma le_traceDual {I J : Submodule B L} : I ≤ Jᵛ ↔ I * J ≤ 1ᵛ := by rw [← le_traceDual_mul_iff, mul_one] lemma le_traceDual_comm {I J : Submodule B L} : I ≤ Jᵛ ↔ J ≤ Iᵛ := by rw [le_traceDual, mul_comm, ← le_traceDual] lemma le_traceDual_traceDual {I : Submodule B L} : I ≤ Iᵛᵛ := le_traceDual_comm.mpr le_rfl @[simp] lemma traceDual_bot : (⊥ : Submodule B L)ᵛ = ⊤ := by ext; simpa [mem_traceDual, -RingHom.mem_range] using zero_mem _ open scoped Classical in lemma traceDual_top' : (⊤ : Submodule B L)ᵛ = if ((LinearMap.range (Algebra.trace K L)).restrictScalars A ≤ 1) then ⊤ else ⊥ := by classical split_ifs with h · rw [_root_.eq_top_iff] exact fun _ _ _ _ ↦ h ⟨_, rfl⟩ · simp only [SetLike.le_def, restrictScalars_mem, LinearMap.mem_range, mem_one, forall_exists_index, forall_apply_eq_imp_iff, not_forall, not_exists] at h obtain ⟨b, hb⟩ := h simp_rw [eq_bot_iff, SetLike.le_def, mem_bot, mem_traceDual, mem_top, true_implies, traceForm_apply, RingHom.mem_range] contrapose! hb with hx' obtain ⟨c, hc, hc0⟩ := hx' simpa [hc0] using hc (c⁻¹ * b) variable [IsDomain A] [IsFractionRing A K] [FiniteDimensional K L] [Algebra.IsSeparable K L] lemma traceDual_top [Decidable (IsField A)] : (⊤ : Submodule B L)ᵛ = if IsField A then ⊤ else ⊥ := by convert traceDual_top' rw [← IsFractionRing.surjective_iff_isField (R := A) (K := K), LinearMap.range_eq_top.mpr (Algebra.trace_surjective K L), ← RingHom.range_eq_top, _root_.eq_top_iff] simp [SetLike.le_def] end Submodule open Submodule variable [IsFractionRing A K] variable (A K) in lemma map_equiv_traceDual [IsDomain A] [IsFractionRing B L] [IsDomain B] [FaithfulSMul A B] (I : Submodule B (FractionRing B)) : (traceDual A (FractionRing A) I).map (FractionRing.algEquiv B L) = traceDual A K (I.map (FractionRing.algEquiv B L)) := by show Submodule.map (FractionRing.algEquiv B L).toLinearEquiv.toLinearMap _ = traceDual A K (I.map (FractionRing.algEquiv B L).toLinearEquiv.toLinearMap) rw [Submodule.map_equiv_eq_comap_symm, Submodule.map_equiv_eq_comap_symm] ext x simp only [AlgEquiv.toLinearEquiv_symm, AlgEquiv.toLinearEquiv_toLinearMap, traceDual, traceForm_apply, Submodule.mem_comap, AlgEquiv.toLinearMap_apply, Submodule.mem_mk, AddSubmonoid.mem_mk, AddSubsemigroup.mem_mk, Set.mem_setOf_eq] apply (FractionRing.algEquiv B L).forall_congr simp only [restrictScalars_mem, traceForm_apply, AlgEquiv.toEquiv_eq_coe, EquivLike.coe_coe, mem_comap, AlgEquiv.toLinearMap_apply, AlgEquiv.symm_apply_apply] refine fun {y} ↦ (forall_congr' fun hy ↦ ?_) rw [Algebra.trace_eq_of_equiv_equiv (FractionRing.algEquiv A K).toRingEquiv (FractionRing.algEquiv B L).toRingEquiv] swap · apply IsLocalization.ringHom_ext (M := A⁰); ext simp only [AlgEquiv.toRingEquiv_eq_coe, AlgEquiv.toRingEquiv_toRingHom, RingHom.coe_comp, RingHom.coe_coe, Function.comp_apply, AlgEquiv.commutes, ← IsScalarTower.algebraMap_apply] rw [IsScalarTower.algebraMap_apply A B (FractionRing B), AlgEquiv.commutes, ← IsScalarTower.algebraMap_apply] simp only [AlgEquiv.toRingEquiv_eq_coe, map_mul, AlgEquiv.coe_ringEquiv, AlgEquiv.apply_symm_apply, ← AlgEquiv.symm_toRingEquiv, mem_one, AlgEquiv.algebraMap_eq_apply] variable [IsIntegrallyClosed A] lemma Submodule.mem_traceDual_iff_isIntegral {I : Submodule B L} {x} : x ∈ Iᵛ ↔ ∀ a ∈ I, IsIntegral A (traceForm K L x a) := forall₂_congr fun _ _ ↦ mem_one.trans IsIntegrallyClosed.isIntegral_iff.symm variable [FiniteDimensional K L] [IsIntegralClosure B A L] lemma Submodule.one_le_traceDual_one : (1 : Submodule B L) ≤ 1ᵛ := by rw [le_traceDual_iff_map_le_one, mul_one, one_eq_range] rintro _ ⟨x, ⟨x, rfl⟩, rfl⟩ rw [mem_one] apply IsIntegrallyClosed.isIntegral_iff.mp apply isIntegral_trace rw [IsIntegralClosure.isIntegral_iff (A := B)] exact ⟨_, rfl⟩ variable [Algebra.IsSeparable K L] /-- If `b` is an `A`-integral basis of `L` with discriminant `b`, then `d • a * x` is integral over `A` for all `a ∈ I` and `x ∈ Iᵛ`. -/ lemma isIntegral_discr_mul_of_mem_traceDual (I : Submodule B L) {ι} [DecidableEq ι] [Fintype ι] {b : Basis ι K L} (hb : ∀ i, IsIntegral A (b i)) {a x : L} (ha : a ∈ I) (hx : x ∈ Iᵛ) : IsIntegral A ((discr K b) • a * x) := by have hinv : IsUnit (traceMatrix K b).det := by simpa [← discr_def] using discr_isUnit_of_basis _ b have H := mulVec_cramer (traceMatrix K b) fun i => trace K L (x * a * b i) have : Function.Injective (traceMatrix K b).mulVec := by rwa [mulVec_injective_iff_isUnit, isUnit_iff_isUnit_det] rw [← traceMatrix_of_basis_mulVec, ← mulVec_smul, this.eq_iff, traceMatrix_of_basis_mulVec] at H rw [← b.equivFun.symm_apply_apply (_ * _), b.equivFun_symm_apply] apply IsIntegral.sum intro i _ rw [smul_mul_assoc, b.equivFun.map_smul, discr_def, mul_comm, ← H, Algebra.smul_def] refine RingHom.IsIntegralElem.mul _ ?_ (hb _) apply IsIntegral.algebraMap rw [cramer_apply] apply IsIntegral.det intros j k rw [updateCol_apply] split · rw [mul_assoc] rw [mem_traceDual_iff_isIntegral] at hx apply hx have ⟨y, hy⟩ := (IsIntegralClosure.isIntegral_iff (A := B)).mp (hb j) rw [mul_comm, ← hy, ← Algebra.smul_def] exact I.smul_mem _ (ha) · exact isIntegral_trace (RingHom.IsIntegralElem.mul _ (hb j) (hb k)) variable (A K) variable [IsDomain A] [IsFractionRing B L] [Nontrivial B] [NoZeroDivisors B] namespace FractionalIdeal open scoped Classical in /-- The dual of a non-zero fractional ideal is the dual of the submodule under the traceform. -/ noncomputable def dual (I : FractionalIdeal B⁰ L) : FractionalIdeal B⁰ L := if hI : I = 0 then 0 else ⟨Iᵛ, by classical have ⟨s, b, hb⟩ := FiniteDimensional.exists_is_basis_integral A K L obtain ⟨x, hx, hx'⟩ := exists_ne_zero_mem_isInteger hI have ⟨y, hy⟩ := (IsIntegralClosure.isIntegral_iff (A := B)).mp (IsIntegral.algebraMap (B := L) (discr_isIntegral K hb)) refine ⟨y * x, mem_nonZeroDivisors_iff_ne_zero.mpr (mul_ne_zero ?_ hx), fun z hz ↦ ?_⟩ · rw [← (IsIntegralClosure.algebraMap_injective B A L).ne_iff, hy, RingHom.map_zero, ← (algebraMap K L).map_zero, (algebraMap K L).injective.ne_iff] exact discr_not_zero_of_basis K b · convert isIntegral_discr_mul_of_mem_traceDual I hb hx' hz using 1 · ext w; exact (IsIntegralClosure.isIntegral_iff (A := B)).symm · rw [Algebra.smul_def, RingHom.map_mul, hy, ← Algebra.smul_def]⟩ end FractionalIdeal end BIsDomain variable [IsDomain A] [IsFractionRing A K] [FiniteDimensional K L] [Algebra.IsSeparable K L] [IsIntegralClosure B A L] namespace FractionalIdeal variable [IsFractionRing B L] [IsIntegrallyClosed A] open Submodule local notation:max I:max "ᵛ" => Submodule.traceDual A K I variable [IsDedekindDomain B] {I J : FractionalIdeal B⁰ L} lemma coe_dual (hI : I ≠ 0) : (dual A K I : Submodule B L) = Iᵛ := by rw [dual, dif_neg hI, coe_mk] variable (B L) @[simp] lemma coe_dual_one : (dual A K (1 : FractionalIdeal B⁰ L) : Submodule B L) = 1ᵛ := by rw [← coe_one, coe_dual] exact one_ne_zero @[simp] lemma dual_zero : dual A K (0 : FractionalIdeal B⁰ L) = 0 := by rw [dual, dif_pos rfl] variable {A K L B} lemma mem_dual (hI : I ≠ 0) {x} : x ∈ dual A K I ↔ ∀ a ∈ I, traceForm K L x a ∈ (algebraMap A K).range := by rw [dual, dif_neg hI]; exact forall₂_congr fun _ _ ↦ mem_one variable (A K) lemma dual_ne_zero (hI : I ≠ 0) : dual A K I ≠ 0 := by obtain ⟨b, hb, hb'⟩ := I.prop suffices algebraMap B L b ∈ dual A K I by intro e rw [e, mem_zero_iff, ← (algebraMap B L).map_zero, (IsIntegralClosure.algebraMap_injective B A L).eq_iff] at this exact mem_nonZeroDivisors_iff_ne_zero.mp hb this rw [mem_dual hI] intro a ha apply IsIntegrallyClosed.isIntegral_iff.mp apply isIntegral_trace dsimp convert hb' a ha using 1 · ext w exact IsIntegralClosure.isIntegral_iff (A := B) · exact (Algebra.smul_def _ _).symm variable {A K} @[simp] lemma dual_eq_zero_iff : dual A K I = 0 ↔ I = 0 := ⟨not_imp_not.mp (dual_ne_zero A K), fun e ↦ e.symm ▸ dual_zero A K L B⟩ lemma dual_ne_zero_iff : dual A K I ≠ 0 ↔ I ≠ 0 := dual_eq_zero_iff.not variable (A K) lemma le_dual_inv_aux (hI : I ≠ 0) (hIJ : I * J ≤ 1) : J ≤ dual A K I := by rw [dual, dif_neg hI] intro x hx y hy rw [mem_one] apply IsIntegrallyClosed.isIntegral_iff.mp apply isIntegral_trace rw [IsIntegralClosure.isIntegral_iff (A := B)] have ⟨z, _, hz⟩ := hIJ (FractionalIdeal.mul_mem_mul hy hx) rw [mul_comm] at hz exact ⟨z, hz⟩ lemma one_le_dual_one : 1 ≤ dual A K (1 : FractionalIdeal B⁰ L) := le_dual_inv_aux A K one_ne_zero (by rw [one_mul]) lemma le_dual_iff (hJ : J ≠ 0) : I ≤ dual A K J ↔ I * J ≤ dual A K 1 := by by_cases hI : I = 0 · simp [hI, zero_le] rw [← coe_le_coe, ← coe_le_coe, coe_mul, coe_dual A K hJ, coe_dual_one, le_traceDual] variable (I) lemma inv_le_dual : I⁻¹ ≤ dual A K I := by classical exact if hI : I = 0 then by simp [hI] else le_dual_inv_aux A K hI (le_of_eq (mul_inv_cancel₀ hI)) lemma dual_inv_le : (dual A K I)⁻¹ ≤ I := by by_cases hI : I = 0; · simp [hI] convert mul_right_mono ((dual A K I)⁻¹) (mul_left_mono I (inv_le_dual A K I)) using 1 · simp only [mul_inv_cancel₀ hI, one_mul] · simp only [mul_inv_cancel₀ (dual_ne_zero A K (hI := hI)), mul_assoc, mul_one] lemma dual_eq_mul_inv : dual A K I = dual A K 1 * I⁻¹ := by by_cases hI : I = 0; · simp [hI] apply le_antisymm · suffices dual A K I * I ≤ dual A K 1 by convert mul_right_mono I⁻¹ this using 1; simp only [mul_inv_cancel₀ hI, mul_one, mul_assoc] rw [← le_dual_iff A K hI] rw [le_dual_iff A K hI, mul_assoc, inv_mul_cancel₀ hI, mul_one] variable {I} lemma dual_div_dual : dual A K J / dual A K I = I / J := by rw [dual_eq_mul_inv A K J, dual_eq_mul_inv A K I, mul_div_mul_comm, div_self, one_mul] · exact inv_div_inv J I · simp only [ne_eq, dual_eq_zero_iff, one_ne_zero, not_false_eq_true] lemma dual_mul_self (hI : I ≠ 0) : dual A K I * I = dual A K 1 := by rw [dual_eq_mul_inv, mul_assoc, inv_mul_cancel₀ hI, mul_one] lemma self_mul_dual (hI : I ≠ 0) : I * dual A K I = dual A K 1 := by rw [mul_comm, dual_mul_self A K hI] lemma dual_inv : dual A K I⁻¹ = dual A K 1 * I := by rw [dual_eq_mul_inv, inv_inv] variable (I) @[simp] lemma dual_dual : dual A K (dual A K I) = I := by rw [dual_eq_mul_inv, dual_eq_mul_inv A K (I := I), mul_inv, inv_inv, ← mul_assoc, mul_inv_cancel₀, one_mul] rw [dual_ne_zero_iff] exact one_ne_zero variable {I} @[simp] lemma dual_le_dual (hI : I ≠ 0) (hJ : J ≠ 0) : dual A K I ≤ dual A K J ↔ J ≤ I := by nth_rewrite 2 [← dual_dual A K I] rw [le_dual_iff A K hJ, le_dual_iff A K (I := J) (by rwa [dual_ne_zero_iff]), mul_comm] variable {A K} lemma dual_involutive : Function.Involutive (dual A K : FractionalIdeal B⁰ L → FractionalIdeal B⁰ L) := dual_dual A K lemma dual_injective : Function.Injective (dual A K : FractionalIdeal B⁰ L → FractionalIdeal B⁰ L) := dual_involutive.injective end FractionalIdeal variable (B) variable [IsIntegrallyClosed A] [IsDedekindDomain B] /-- The different ideal of an extension of integral domains `B/A` is the inverse of the dual of `A` as an ideal of `B`. See `coeIdeal_differentIdeal` and `coeSubmodule_differentIdeal`. -/ def differentIdeal [NoZeroSMulDivisors A B] : Ideal B := (1 / Submodule.traceDual A (FractionRing A) 1 : Submodule B (FractionRing B)).comap (Algebra.linearMap B (FractionRing B)) lemma coeSubmodule_differentIdeal_fractionRing [NoZeroSMulDivisors A B] [Algebra.IsIntegral A B] [Algebra.IsSeparable (FractionRing A) (FractionRing B)] [FiniteDimensional (FractionRing A) (FractionRing B)] : coeSubmodule (FractionRing B) (differentIdeal A B) = 1 / Submodule.traceDual A (FractionRing A) 1 := by have : IsIntegralClosure B A (FractionRing B) := IsIntegralClosure.of_isIntegrallyClosed _ _ _ rw [coeSubmodule, differentIdeal, Submodule.map_comap_eq, inf_eq_right] have := FractionalIdeal.dual_inv_le (A := A) (K := FractionRing A) (1 : FractionalIdeal B⁰ (FractionRing B)) have : _ ≤ ((1 : FractionalIdeal B⁰ (FractionRing B)) : Submodule B (FractionRing B)) := this simp only [← one_div, FractionalIdeal.val_eq_coe] at this rw [FractionalIdeal.coe_div (FractionalIdeal.dual_ne_zero _ _ _), FractionalIdeal.coe_dual] at this · simpa only [FractionalIdeal.coe_one, Submodule.one_eq_range] using this · exact one_ne_zero · exact one_ne_zero section variable [IsFractionRing B L] lemma coeSubmodule_differentIdeal [NoZeroSMulDivisors A B] : coeSubmodule L (differentIdeal A B) = 1 / Submodule.traceDual A K 1 := by have : (FractionRing.algEquiv B L).toLinearEquiv.comp (Algebra.linearMap B (FractionRing B)) = Algebra.linearMap B L := by ext; simp rw [coeSubmodule, ← this] have H : RingHom.comp (algebraMap (FractionRing A) (FractionRing B)) ↑(FractionRing.algEquiv A K).symm.toRingEquiv = RingHom.comp ↑(FractionRing.algEquiv B L).symm.toRingEquiv (algebraMap K L) := by apply IsLocalization.ringHom_ext A⁰ ext simp only [AlgEquiv.toRingEquiv_eq_coe, RingHom.coe_comp, RingHom.coe_coe, AlgEquiv.coe_ringEquiv, Function.comp_apply, AlgEquiv.commutes, ← IsScalarTower.algebraMap_apply] rw [IsScalarTower.algebraMap_apply A B L, AlgEquiv.commutes, ← IsScalarTower.algebraMap_apply] have : Algebra.IsSeparable (FractionRing A) (FractionRing B) := Algebra.IsSeparable.of_equiv_equiv _ _ H have : FiniteDimensional (FractionRing A) (FractionRing B) := Module.Finite.of_equiv_equiv _ _ H have : Algebra.IsIntegral A B := IsIntegralClosure.isIntegral_algebra _ L simp only [AlgEquiv.toLinearEquiv_toLinearMap, Submodule.map_comp] rw [← coeSubmodule, coeSubmodule_differentIdeal_fractionRing _ _, Submodule.map_div, ← AlgEquiv.toAlgHom_toLinearMap, Submodule.map_one] congr 1 refine (map_equiv_traceDual A K _).trans ?_ congr 1 ext simp variable (L) lemma coeIdeal_differentIdeal [NoZeroSMulDivisors A B] : ↑(differentIdeal A B) = (FractionalIdeal.dual A K (1 : FractionalIdeal B⁰ L))⁻¹ := by apply FractionalIdeal.coeToSubmodule_injective simp only [FractionalIdeal.coe_div (FractionalIdeal.dual_ne_zero _ _ (@one_ne_zero (FractionalIdeal B⁰ L) _ _ _)), FractionalIdeal.coe_coeIdeal, coeSubmodule_differentIdeal A K, inv_eq_one_div, FractionalIdeal.coe_dual_one, FractionalIdeal.coe_one] variable {A K B L} open Submodule lemma differentialIdeal_le_fractionalIdeal_iff {I : FractionalIdeal B⁰ L} (hI : I ≠ 0) [NoZeroSMulDivisors A B] : differentIdeal A B ≤ I ↔ (((I⁻¹ :) : Submodule B L).restrictScalars A).map ((Algebra.trace K L).restrictScalars A) ≤ 1 := by rw [coeIdeal_differentIdeal A K L B, FractionalIdeal.inv_le_comm (by simp) hI, ← FractionalIdeal.coe_le_coe, FractionalIdeal.coe_dual_one] refine le_traceDual_iff_map_le_one.trans ?_ simp lemma differentialIdeal_le_iff {I : Ideal B} (hI : I ≠ ⊥) [NoZeroSMulDivisors A B] : differentIdeal A B ≤ I ↔ (((I⁻¹ : FractionalIdeal B⁰ L) : Submodule B L).restrictScalars A).map ((Algebra.trace K L).restrictScalars A) ≤ 1 := (FractionalIdeal.coeIdeal_le_coeIdeal _).symm.trans (differentialIdeal_le_fractionalIdeal_iff (I := (I : FractionalIdeal B⁰ L)) (by simpa)) variable (A K) open Pointwise Polynomial in lemma traceForm_dualSubmodule_adjoin {x : L} (hx : Algebra.adjoin K {x} = ⊤) (hAx : IsIntegral A x) : (traceForm K L).dualSubmodule (Subalgebra.toSubmodule (Algebra.adjoin A {x})) = (aeval x (derivative <| minpoly K x) : L)⁻¹ • (Subalgebra.toSubmodule (Algebra.adjoin A {x})) := by classical have hKx : IsIntegral K x := Algebra.IsIntegral.isIntegral x let pb := (Algebra.adjoin.powerBasis' hKx).map ((Subalgebra.equivOfEq _ _ hx).trans (Subalgebra.topEquiv)) have pbgen : pb.gen = x := by simp [pb] have hpb : ⇑(LinearMap.BilinForm.dualBasis (traceForm K L) _ pb.basis) = _ := _root_.funext (traceForm_dualBasis_powerBasis_eq pb) have : (Subalgebra.toSubmodule (Algebra.adjoin A {x})) = Submodule.span A (Set.range pb.basis) := by rw [← span_range_natDegree_eq_adjoin (minpoly.monic hAx) (minpoly.aeval _ _)] congr; ext y have : natDegree (minpoly A x) = natDegree (minpoly K x) := by rw [minpoly.isIntegrallyClosed_eq_field_fractions' K hAx, (minpoly.monic hAx).natDegree_map] simp only [Finset.coe_image, Finset.coe_range, Set.mem_image, Set.mem_Iio, Set.mem_range, pb.basis_eq_pow, pbgen] simp only [PowerBasis.map_dim, adjoin.powerBasis'_dim, this] exact ⟨fun ⟨a, b, c⟩ ↦ ⟨⟨a, b⟩, c⟩, fun ⟨⟨a, b⟩, c⟩ ↦ ⟨a, b, c⟩⟩ clear_value pb conv_lhs => rw [this] rw [← span_coeff_minpolyDiv hAx, LinearMap.BilinForm.dualSubmodule_span_of_basis, Submodule.smul_span, hpb] show _ = Submodule.span A (_ '' _) simp only [← Set.range_comp, smul_eq_mul, div_eq_inv_mul, pbgen, minpolyDiv_eq_of_isIntegrallyClosed K hAx] apply le_antisymm <;> rw [Submodule.span_le] · rintro _ ⟨i, rfl⟩; exact Submodule.subset_span ⟨i, rfl⟩ · rintro _ ⟨i, rfl⟩ by_cases hi : i < pb.dim · exact Submodule.subset_span ⟨⟨i, hi⟩, rfl⟩ · rw [Function.comp_apply, coeff_eq_zero_of_natDegree_lt, mul_zero] · exact zero_mem _ rw [← pb.natDegree_minpoly, pbgen, ← natDegree_minpolyDiv_succ hKx, ← Nat.succ_eq_add_one] at hi exact le_of_not_lt hi end variable (L) {B} open Polynomial Pointwise in lemma conductor_mul_differentIdeal [NoZeroSMulDivisors A B] (x : B) (hx : Algebra.adjoin K {algebraMap B L x} = ⊤) :
(conductor A x) * differentIdeal A B = Ideal.span {aeval x (derivative (minpoly A x))} := by classical have hAx : IsIntegral A x := IsIntegralClosure.isIntegral A L x haveI := IsIntegralClosure.isFractionRing_of_finite_extension A K L B apply FractionalIdeal.coeIdeal_injective (K := L) simp only [FractionalIdeal.coeIdeal_mul, FractionalIdeal.coeIdeal_span_singleton]
Mathlib/RingTheory/DedekindDomain/Different.lean
528
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/- Copyright (c) 2018 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Data.Fintype.Lattice import Mathlib.Data.Fintype.Sum import Mathlib.Topology.Homeomorph.Lemmas import Mathlib.Topology.MetricSpace.Antilipschitz /-! # Isometries We define isometries, i.e., maps between emetric spaces that preserve the edistance (on metric spaces, these are exactly the maps that preserve distances), and prove their basic properties. We also introduce isometric bijections. Since a lot of elementary properties don't require `eq_of_dist_eq_zero` we start setting up the theory for `PseudoMetricSpace` and we specialize to `MetricSpace` when needed. -/ open Topology noncomputable section universe u v w variable {ι : Type*} {α : Type u} {β : Type v} {γ : Type w} open Function Set open scoped Topology ENNReal /-- An isometry (also known as isometric embedding) is a map preserving the edistance between pseudoemetric spaces, or equivalently the distance between pseudometric space. -/ def Isometry [PseudoEMetricSpace α] [PseudoEMetricSpace β] (f : α → β) : Prop := ∀ x1 x2 : α, edist (f x1) (f x2) = edist x1 x2 /-- On pseudometric spaces, a map is an isometry if and only if it preserves nonnegative distances. -/ theorem isometry_iff_nndist_eq [PseudoMetricSpace α] [PseudoMetricSpace β] {f : α → β} : Isometry f ↔ ∀ x y, nndist (f x) (f y) = nndist x y := by simp only [Isometry, edist_nndist, ENNReal.coe_inj] /-- On pseudometric spaces, a map is an isometry if and only if it preserves distances. -/ theorem isometry_iff_dist_eq [PseudoMetricSpace α] [PseudoMetricSpace β] {f : α → β} : Isometry f ↔ ∀ x y, dist (f x) (f y) = dist x y := by simp only [isometry_iff_nndist_eq, ← coe_nndist, NNReal.coe_inj] /-- An isometry preserves distances. -/ alias ⟨Isometry.dist_eq, _⟩ := isometry_iff_dist_eq /-- A map that preserves distances is an isometry -/ alias ⟨_, Isometry.of_dist_eq⟩ := isometry_iff_dist_eq /-- An isometry preserves non-negative distances. -/ alias ⟨Isometry.nndist_eq, _⟩ := isometry_iff_nndist_eq /-- A map that preserves non-negative distances is an isometry. -/ alias ⟨_, Isometry.of_nndist_eq⟩ := isometry_iff_nndist_eq namespace Isometry section PseudoEmetricIsometry variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] [PseudoEMetricSpace γ] variable {f : α → β} {x : α} /-- An isometry preserves edistances. -/ theorem edist_eq (hf : Isometry f) (x y : α) : edist (f x) (f y) = edist x y := hf x y theorem lipschitz (h : Isometry f) : LipschitzWith 1 f := LipschitzWith.of_edist_le fun x y => (h x y).le theorem antilipschitz (h : Isometry f) : AntilipschitzWith 1 f := fun x y => by simp only [h x y, ENNReal.coe_one, one_mul, le_refl] /-- Any map on a subsingleton is an isometry -/ @[nontriviality] theorem _root_.isometry_subsingleton [Subsingleton α] : Isometry f := fun x y => by rw [Subsingleton.elim x y]; simp /-- The identity is an isometry -/ theorem _root_.isometry_id : Isometry (id : α → α) := fun _ _ => rfl theorem prodMap {δ} [PseudoEMetricSpace δ] {f : α → β} {g : γ → δ} (hf : Isometry f) (hg : Isometry g) : Isometry (Prod.map f g) := fun x y => by simp only [Prod.edist_eq, Prod.map_fst, hf.edist_eq, Prod.map_snd, hg.edist_eq] @[deprecated (since := "2025-04-18")] alias prod_map := prodMap protected theorem piMap {ι} [Fintype ι] {α β : ι → Type*} [∀ i, PseudoEMetricSpace (α i)] [∀ i, PseudoEMetricSpace (β i)] (f : ∀ i, α i → β i) (hf : ∀ i, Isometry (f i)) : Isometry (Pi.map f) := fun x y => by simp only [edist_pi_def, (hf _).edist_eq, Pi.map_apply] /-- The composition of isometries is an isometry. -/ theorem comp {g : β → γ} {f : α → β} (hg : Isometry g) (hf : Isometry f) : Isometry (g ∘ f) := fun _ _ => (hg _ _).trans (hf _ _) /-- An isometry from a metric space is a uniform continuous map -/ protected theorem uniformContinuous (hf : Isometry f) : UniformContinuous f := hf.lipschitz.uniformContinuous /-- An isometry from a metric space is a uniform inducing map -/ theorem isUniformInducing (hf : Isometry f) : IsUniformInducing f := hf.antilipschitz.isUniformInducing hf.uniformContinuous theorem tendsto_nhds_iff {ι : Type*} {f : α → β} {g : ι → α} {a : Filter ι} {b : α} (hf : Isometry f) : Filter.Tendsto g a (𝓝 b) ↔ Filter.Tendsto (f ∘ g) a (𝓝 (f b)) := hf.isUniformInducing.isInducing.tendsto_nhds_iff /-- An isometry is continuous. -/ protected theorem continuous (hf : Isometry f) : Continuous f := hf.lipschitz.continuous /-- The right inverse of an isometry is an isometry. -/ theorem right_inv {f : α → β} {g : β → α} (h : Isometry f) (hg : RightInverse g f) : Isometry g := fun x y => by rw [← h, hg _, hg _] theorem preimage_emetric_closedBall (h : Isometry f) (x : α) (r : ℝ≥0∞) : f ⁻¹' EMetric.closedBall (f x) r = EMetric.closedBall x r := by ext y simp [h.edist_eq] theorem preimage_emetric_ball (h : Isometry f) (x : α) (r : ℝ≥0∞) : f ⁻¹' EMetric.ball (f x) r = EMetric.ball x r := by ext y simp [h.edist_eq] /-- Isometries preserve the diameter in pseudoemetric spaces. -/ theorem ediam_image (hf : Isometry f) (s : Set α) : EMetric.diam (f '' s) = EMetric.diam s := eq_of_forall_ge_iff fun d => by simp only [EMetric.diam_le_iff, forall_mem_image, hf.edist_eq] theorem ediam_range (hf : Isometry f) : EMetric.diam (range f) = EMetric.diam (univ : Set α) := by rw [← image_univ] exact hf.ediam_image univ theorem mapsTo_emetric_ball (hf : Isometry f) (x : α) (r : ℝ≥0∞) : MapsTo f (EMetric.ball x r) (EMetric.ball (f x) r) := (hf.preimage_emetric_ball x r).ge theorem mapsTo_emetric_closedBall (hf : Isometry f) (x : α) (r : ℝ≥0∞) : MapsTo f (EMetric.closedBall x r) (EMetric.closedBall (f x) r) := (hf.preimage_emetric_closedBall x r).ge /-- The injection from a subtype is an isometry -/ theorem _root_.isometry_subtype_coe {s : Set α} : Isometry ((↑) : s → α) := fun _ _ => rfl theorem comp_continuousOn_iff {γ} [TopologicalSpace γ] (hf : Isometry f) {g : γ → α} {s : Set γ} : ContinuousOn (f ∘ g) s ↔ ContinuousOn g s := hf.isUniformInducing.isInducing.continuousOn_iff.symm theorem comp_continuous_iff {γ} [TopologicalSpace γ] (hf : Isometry f) {g : γ → α} : Continuous (f ∘ g) ↔ Continuous g := hf.isUniformInducing.isInducing.continuous_iff.symm end PseudoEmetricIsometry --section section EmetricIsometry variable [EMetricSpace α] [PseudoEMetricSpace β] {f : α → β} /-- An isometry from an emetric space is injective -/ protected theorem injective (h : Isometry f) : Injective f := h.antilipschitz.injective /-- An isometry from an emetric space is a uniform embedding -/ lemma isUniformEmbedding (hf : Isometry f) : IsUniformEmbedding f := hf.antilipschitz.isUniformEmbedding hf.lipschitz.uniformContinuous /-- An isometry from an emetric space is an embedding -/ theorem isEmbedding (hf : Isometry f) : IsEmbedding f := hf.isUniformEmbedding.isEmbedding @[deprecated (since := "2024-10-26")] alias embedding := isEmbedding /-- An isometry from a complete emetric space is a closed embedding -/ theorem isClosedEmbedding [CompleteSpace α] [EMetricSpace γ] {f : α → γ} (hf : Isometry f) : IsClosedEmbedding f := hf.antilipschitz.isClosedEmbedding hf.lipschitz.uniformContinuous end EmetricIsometry --section section PseudoMetricIsometry variable [PseudoMetricSpace α] [PseudoMetricSpace β] {f : α → β} /-- An isometry preserves the diameter in pseudometric spaces. -/ theorem diam_image (hf : Isometry f) (s : Set α) : Metric.diam (f '' s) = Metric.diam s := by rw [Metric.diam, Metric.diam, hf.ediam_image] theorem diam_range (hf : Isometry f) : Metric.diam (range f) = Metric.diam (univ : Set α) := by rw [← image_univ] exact hf.diam_image univ theorem preimage_setOf_dist (hf : Isometry f) (x : α) (p : ℝ → Prop) : f ⁻¹' { y | p (dist y (f x)) } = { y | p (dist y x) } := by ext y simp [hf.dist_eq] theorem preimage_closedBall (hf : Isometry f) (x : α) (r : ℝ) : f ⁻¹' Metric.closedBall (f x) r = Metric.closedBall x r := hf.preimage_setOf_dist x (· ≤ r) theorem preimage_ball (hf : Isometry f) (x : α) (r : ℝ) : f ⁻¹' Metric.ball (f x) r = Metric.ball x r := hf.preimage_setOf_dist x (· < r) theorem preimage_sphere (hf : Isometry f) (x : α) (r : ℝ) : f ⁻¹' Metric.sphere (f x) r = Metric.sphere x r := hf.preimage_setOf_dist x (· = r) theorem mapsTo_ball (hf : Isometry f) (x : α) (r : ℝ) : MapsTo f (Metric.ball x r) (Metric.ball (f x) r) := (hf.preimage_ball x r).ge theorem mapsTo_sphere (hf : Isometry f) (x : α) (r : ℝ) : MapsTo f (Metric.sphere x r) (Metric.sphere (f x) r) := (hf.preimage_sphere x r).ge theorem mapsTo_closedBall (hf : Isometry f) (x : α) (r : ℝ) : MapsTo f (Metric.closedBall x r) (Metric.closedBall (f x) r) := (hf.preimage_closedBall x r).ge end PseudoMetricIsometry -- section end Isometry -- namespace /-- A uniform embedding from a uniform space to a metric space is an isometry with respect to the induced metric space structure on the source space. -/ theorem IsUniformEmbedding.to_isometry {α β} [UniformSpace α] [MetricSpace β] {f : α → β} (h : IsUniformEmbedding f) : (letI := h.comapMetricSpace f; Isometry f) := let _ := h.comapMetricSpace f Isometry.of_dist_eq fun _ _ => rfl /-- An embedding from a topological space to a metric space is an isometry with respect to the induced metric space structure on the source space. -/ theorem Topology.IsEmbedding.to_isometry {α β} [TopologicalSpace α] [MetricSpace β] {f : α → β} (h : IsEmbedding f) : (letI := h.comapMetricSpace f; Isometry f) := let _ := h.comapMetricSpace f Isometry.of_dist_eq fun _ _ => rfl @[deprecated (since := "2024-10-26")] alias Embedding.to_isometry := IsEmbedding.to_isometry theorem PseudoEMetricSpace.isometry_induced (f : α → β) [m : PseudoEMetricSpace β] : letI := m.induced f; Isometry f := fun _ _ ↦ rfl theorem PsuedoMetricSpace.isometry_induced (f : α → β) [m : PseudoMetricSpace β] : letI := m.induced f; Isometry f := fun _ _ ↦ rfl theorem EMetricSpace.isometry_induced (f : α → β) (hf : f.Injective) [m : EMetricSpace β] : letI := m.induced f hf; Isometry f := fun _ _ ↦ rfl theorem MetricSpace.isometry_induced (f : α → β) (hf : f.Injective) [m : MetricSpace β] : letI := m.induced f hf; Isometry f := fun _ _ ↦ rfl -- such a bijection need not exist /-- `α` and `β` are isometric if there is an isometric bijection between them. -/ structure IsometryEquiv (α : Type u) (β : Type v) [PseudoEMetricSpace α] [PseudoEMetricSpace β] extends α ≃ β where isometry_toFun : Isometry toFun @[inherit_doc] infixl:25 " ≃ᵢ " => IsometryEquiv namespace IsometryEquiv section PseudoEMetricSpace variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] [PseudoEMetricSpace γ] -- TODO: add `IsometryEquivClass` theorem toEquiv_injective : Injective (toEquiv : (α ≃ᵢ β) → (α ≃ β)) | ⟨_, _⟩, ⟨_, _⟩, rfl => rfl @[simp] theorem toEquiv_inj {e₁ e₂ : α ≃ᵢ β} : e₁.toEquiv = e₂.toEquiv ↔ e₁ = e₂ := toEquiv_injective.eq_iff instance : EquivLike (α ≃ᵢ β) α β where coe e := e.toEquiv inv e := e.toEquiv.symm left_inv e := e.left_inv right_inv e := e.right_inv coe_injective' _ _ h _ := toEquiv_injective <| DFunLike.ext' h theorem coe_eq_toEquiv (h : α ≃ᵢ β) (a : α) : h a = h.toEquiv a := rfl @[simp] theorem coe_toEquiv (h : α ≃ᵢ β) : ⇑h.toEquiv = h := rfl @[simp] theorem coe_mk (e : α ≃ β) (h) : ⇑(mk e h) = e := rfl protected theorem isometry (h : α ≃ᵢ β) : Isometry h := h.isometry_toFun protected theorem bijective (h : α ≃ᵢ β) : Bijective h := h.toEquiv.bijective protected theorem injective (h : α ≃ᵢ β) : Injective h := h.toEquiv.injective protected theorem surjective (h : α ≃ᵢ β) : Surjective h := h.toEquiv.surjective protected theorem edist_eq (h : α ≃ᵢ β) (x y : α) : edist (h x) (h y) = edist x y := h.isometry.edist_eq x y protected theorem dist_eq {α β : Type*} [PseudoMetricSpace α] [PseudoMetricSpace β] (h : α ≃ᵢ β) (x y : α) : dist (h x) (h y) = dist x y := h.isometry.dist_eq x y protected theorem nndist_eq {α β : Type*} [PseudoMetricSpace α] [PseudoMetricSpace β] (h : α ≃ᵢ β) (x y : α) : nndist (h x) (h y) = nndist x y := h.isometry.nndist_eq x y protected theorem continuous (h : α ≃ᵢ β) : Continuous h := h.isometry.continuous @[simp] theorem ediam_image (h : α ≃ᵢ β) (s : Set α) : EMetric.diam (h '' s) = EMetric.diam s := h.isometry.ediam_image s @[ext] theorem ext ⦃h₁ h₂ : α ≃ᵢ β⦄ (H : ∀ x, h₁ x = h₂ x) : h₁ = h₂ := DFunLike.ext _ _ H /-- Alternative constructor for isometric bijections, taking as input an isometry, and a right inverse. -/ def mk' {α : Type u} [EMetricSpace α] (f : α → β) (g : β → α) (hfg : ∀ x, f (g x) = x) (hf : Isometry f) : α ≃ᵢ β where toFun := f invFun := g left_inv _ := hf.injective <| hfg _ right_inv := hfg isometry_toFun := hf /-- The identity isometry of a space. -/ protected def refl (α : Type*) [PseudoEMetricSpace α] : α ≃ᵢ α := { Equiv.refl α with isometry_toFun := isometry_id } /-- The composition of two isometric isomorphisms, as an isometric isomorphism. -/ protected def trans (h₁ : α ≃ᵢ β) (h₂ : β ≃ᵢ γ) : α ≃ᵢ γ := { Equiv.trans h₁.toEquiv h₂.toEquiv with isometry_toFun := h₂.isometry_toFun.comp h₁.isometry_toFun } @[simp] theorem trans_apply (h₁ : α ≃ᵢ β) (h₂ : β ≃ᵢ γ) (x : α) : h₁.trans h₂ x = h₂ (h₁ x) := rfl /-- The inverse of an isometric isomorphism, as an isometric isomorphism. -/ protected def symm (h : α ≃ᵢ β) : β ≃ᵢ α where isometry_toFun := h.isometry.right_inv h.right_inv toEquiv := h.toEquiv.symm /-- See Note [custom simps projection]. We need to specify this projection explicitly in this case, because it is a composition of multiple projections. -/ def Simps.apply (h : α ≃ᵢ β) : α → β := h /-- See Note [custom simps projection] -/ def Simps.symm_apply (h : α ≃ᵢ β) : β → α := h.symm initialize_simps_projections IsometryEquiv (toFun → apply, invFun → symm_apply) @[simp] theorem symm_symm (h : α ≃ᵢ β) : h.symm.symm = h := rfl theorem symm_bijective : Bijective (IsometryEquiv.symm : (α ≃ᵢ β) → β ≃ᵢ α) := Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩ @[simp] theorem apply_symm_apply (h : α ≃ᵢ β) (y : β) : h (h.symm y) = y := h.toEquiv.apply_symm_apply y @[simp] theorem symm_apply_apply (h : α ≃ᵢ β) (x : α) : h.symm (h x) = x := h.toEquiv.symm_apply_apply x theorem symm_apply_eq (h : α ≃ᵢ β) {x : α} {y : β} : h.symm y = x ↔ y = h x := h.toEquiv.symm_apply_eq theorem eq_symm_apply (h : α ≃ᵢ β) {x : α} {y : β} : x = h.symm y ↔ h x = y := h.toEquiv.eq_symm_apply theorem symm_comp_self (h : α ≃ᵢ β) : (h.symm : β → α) ∘ h = id := funext h.left_inv theorem self_comp_symm (h : α ≃ᵢ β) : (h : α → β) ∘ h.symm = id := funext h.right_inv theorem range_eq_univ (h : α ≃ᵢ β) : range h = univ := by simp theorem image_symm (h : α ≃ᵢ β) : image h.symm = preimage h := image_eq_preimage_of_inverse h.symm.toEquiv.left_inv h.symm.toEquiv.right_inv theorem preimage_symm (h : α ≃ᵢ β) : preimage h.symm = image h := (image_eq_preimage_of_inverse h.toEquiv.left_inv h.toEquiv.right_inv).symm @[simp] theorem symm_trans_apply (h₁ : α ≃ᵢ β) (h₂ : β ≃ᵢ γ) (x : γ) : (h₁.trans h₂).symm x = h₁.symm (h₂.symm x) := rfl theorem ediam_univ (h : α ≃ᵢ β) : EMetric.diam (univ : Set α) = EMetric.diam (univ : Set β) := by rw [← h.range_eq_univ, h.isometry.ediam_range] @[simp] theorem ediam_preimage (h : α ≃ᵢ β) (s : Set β) : EMetric.diam (h ⁻¹' s) = EMetric.diam s := by rw [← image_symm, ediam_image] @[simp] theorem preimage_emetric_ball (h : α ≃ᵢ β) (x : β) (r : ℝ≥0∞) : h ⁻¹' EMetric.ball x r = EMetric.ball (h.symm x) r := by rw [← h.isometry.preimage_emetric_ball (h.symm x) r, h.apply_symm_apply] @[simp] theorem preimage_emetric_closedBall (h : α ≃ᵢ β) (x : β) (r : ℝ≥0∞) : h ⁻¹' EMetric.closedBall x r = EMetric.closedBall (h.symm x) r := by rw [← h.isometry.preimage_emetric_closedBall (h.symm x) r, h.apply_symm_apply] @[simp] theorem image_emetric_ball (h : α ≃ᵢ β) (x : α) (r : ℝ≥0∞) : h '' EMetric.ball x r = EMetric.ball (h x) r := by rw [← h.preimage_symm, h.symm.preimage_emetric_ball, symm_symm] @[simp] theorem image_emetric_closedBall (h : α ≃ᵢ β) (x : α) (r : ℝ≥0∞) : h '' EMetric.closedBall x r = EMetric.closedBall (h x) r := by rw [← h.preimage_symm, h.symm.preimage_emetric_closedBall, symm_symm] /-- The (bundled) homeomorphism associated to an isometric isomorphism. -/ @[simps toEquiv] protected def toHomeomorph (h : α ≃ᵢ β) : α ≃ₜ β where continuous_toFun := h.continuous continuous_invFun := h.symm.continuous toEquiv := h.toEquiv @[simp] theorem coe_toHomeomorph (h : α ≃ᵢ β) : ⇑h.toHomeomorph = h := rfl @[simp] theorem coe_toHomeomorph_symm (h : α ≃ᵢ β) : ⇑h.toHomeomorph.symm = h.symm := rfl @[simp] theorem comp_continuousOn_iff {γ} [TopologicalSpace γ] (h : α ≃ᵢ β) {f : γ → α} {s : Set γ} : ContinuousOn (h ∘ f) s ↔ ContinuousOn f s := h.toHomeomorph.comp_continuousOn_iff _ _ @[simp] theorem comp_continuous_iff {γ} [TopologicalSpace γ] (h : α ≃ᵢ β) {f : γ → α} : Continuous (h ∘ f) ↔ Continuous f := h.toHomeomorph.comp_continuous_iff @[simp] theorem comp_continuous_iff' {γ} [TopologicalSpace γ] (h : α ≃ᵢ β) {f : β → γ} : Continuous (f ∘ h) ↔ Continuous f := h.toHomeomorph.comp_continuous_iff' /-- The group of isometries. -/ instance : Group (α ≃ᵢ α) where one := IsometryEquiv.refl _ mul e₁ e₂ := e₂.trans e₁ inv := IsometryEquiv.symm mul_assoc _ _ _ := rfl one_mul _ := ext fun _ => rfl mul_one _ := ext fun _ => rfl inv_mul_cancel e := ext e.symm_apply_apply @[simp] theorem coe_one : ⇑(1 : α ≃ᵢ α) = id := rfl @[simp] theorem coe_mul (e₁ e₂ : α ≃ᵢ α) : ⇑(e₁ * e₂) = e₁ ∘ e₂ := rfl theorem mul_apply (e₁ e₂ : α ≃ᵢ α) (x : α) : (e₁ * e₂) x = e₁ (e₂ x) := rfl @[simp] theorem inv_apply_self (e : α ≃ᵢ α) (x : α) : e⁻¹ (e x) = x := e.symm_apply_apply x @[simp] theorem apply_inv_self (e : α ≃ᵢ α) (x : α) : e (e⁻¹ x) = x := e.apply_symm_apply x theorem completeSpace_iff (e : α ≃ᵢ β) : CompleteSpace α ↔ CompleteSpace β := by simp only [completeSpace_iff_isComplete_univ, ← e.range_eq_univ, ← image_univ, isComplete_image_iff e.isometry.isUniformInducing] protected theorem completeSpace [CompleteSpace β] (e : α ≃ᵢ β) : CompleteSpace α := e.completeSpace_iff.2 ‹_› /-- The natural isometry `∀ i, Y i ≃ᵢ ∀ j, Y (e.symm j)` obtained from a bijection `ι ≃ ι'` of
fintypes. `Equiv.piCongrLeft'` as an `IsometryEquiv`. -/ @[simps!] def piCongrLeft' {ι' : Type*} [Fintype ι] [Fintype ι'] {Y : ι → Type*}
Mathlib/Topology/MetricSpace/Isometry.lean
495
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/- Copyright (c) 2014 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura, Jeremy Avigad -/ import Mathlib.Logic.Basic import Mathlib.Logic.Function.Defs import Mathlib.Order.Defs.LinearOrder /-! # Booleans This file proves various trivial lemmas about booleans and their relation to decidable propositions. ## Tags bool, boolean, Bool, De Morgan -/ namespace Bool section /-! This section contains lemmas about booleans which were present in core Lean 3. The remainder of this file contains lemmas about booleans from mathlib 3. -/ theorem true_eq_false_eq_False : ¬true = false := by decide theorem false_eq_true_eq_False : ¬false = true := by decide theorem eq_false_eq_not_eq_true (b : Bool) : (¬b = true) = (b = false) := by simp theorem eq_true_eq_not_eq_false (b : Bool) : (¬b = false) = (b = true) := by simp theorem eq_false_of_not_eq_true {b : Bool} : ¬b = true → b = false := Eq.mp (eq_false_eq_not_eq_true b) theorem eq_true_of_not_eq_false {b : Bool} : ¬b = false → b = true := Eq.mp (eq_true_eq_not_eq_false b) theorem and_eq_true_eq_eq_true_and_eq_true (a b : Bool) : ((a && b) = true) = (a = true ∧ b = true) := by simp theorem or_eq_true_eq_eq_true_or_eq_true (a b : Bool) : ((a || b) = true) = (a = true ∨ b = true) := by simp theorem not_eq_true_eq_eq_false (a : Bool) : (not a = true) = (a = false) := by cases a <;> simp #adaptation_note /-- nightly-2024-03-05 this is no longer a simp lemma, as the LHS simplifies. -/ theorem and_eq_false_eq_eq_false_or_eq_false (a b : Bool) : ((a && b) = false) = (a = false ∨ b = false) := by cases a <;> cases b <;> simp theorem or_eq_false_eq_eq_false_and_eq_false (a b : Bool) : ((a || b) = false) = (a = false ∧ b = false) := by cases a <;> cases b <;> simp theorem not_eq_false_eq_eq_true (a : Bool) : (not a = false) = (a = true) := by cases a <;> simp theorem coe_false : ↑false = False := by simp theorem coe_true : ↑true = True := by simp theorem coe_sort_false : (false : Prop) = False := by simp theorem coe_sort_true : (true : Prop) = True := by simp theorem decide_iff (p : Prop) [d : Decidable p] : decide p = true ↔ p := by simp theorem decide_true {p : Prop} [Decidable p] : p → decide p := (decide_iff p).2 theorem of_decide_true {p : Prop} [Decidable p] : decide p → p := (decide_iff p).1 theorem bool_iff_false {b : Bool} : ¬b ↔ b = false := by cases b <;> decide theorem bool_eq_false {b : Bool} : ¬b → b = false := bool_iff_false.1 theorem decide_false_iff (p : Prop) {_ : Decidable p} : decide p = false ↔ ¬p := bool_iff_false.symm.trans (not_congr (decide_iff _)) theorem decide_false {p : Prop} [Decidable p] : ¬p → decide p = false := (decide_false_iff p).2 theorem of_decide_false {p : Prop} [Decidable p] : decide p = false → ¬p := (decide_false_iff p).1 theorem decide_congr {p q : Prop} [Decidable p] [Decidable q] (h : p ↔ q) : decide p = decide q := decide_eq_decide.mpr h theorem coe_xor_iff (a b : Bool) : xor a b ↔ Xor' (a = true) (b = true) := by cases a <;> cases b <;> decide end theorem dichotomy (b : Bool) : b = false ∨ b = true := by cases b <;> simp theorem not_ne_id : not ≠ id := fun h ↦ false_ne_true <| congrFun h true theorem or_inl {a b : Bool} (H : a) : a || b := by simp [H] theorem or_inr {a b : Bool} (H : b) : a || b := by cases a <;> simp [H] theorem and_elim_left : ∀ {a b : Bool}, a && b → a := by decide theorem and_intro : ∀ {a b : Bool}, a → b → a && b := by decide theorem and_elim_right : ∀ {a b : Bool}, a && b → b := by decide lemma eq_not_iff : ∀ {a b : Bool}, a = !b ↔ a ≠ b := by decide lemma not_eq_iff : ∀ {a b : Bool}, !a = b ↔ a ≠ b := by decide theorem ne_not {a b : Bool} : a ≠ !b ↔ a = b := not_eq_not lemma not_ne_self : ∀ b : Bool, (!b) ≠ b := by decide lemma self_ne_not : ∀ b : Bool, b ≠ !b := by decide lemma eq_or_eq_not : ∀ a b, a = b ∨ a = !b := by decide -- TODO naming issue: these two `not` are different. theorem not_iff_not : ∀ {b : Bool}, !b ↔ ¬b := by simp theorem eq_true_of_not_eq_false' {a : Bool} : !a = false → a = true := by cases a <;> decide theorem eq_false_of_not_eq_true' {a : Bool} : !a = true → a = false := by cases a <;> decide theorem bne_eq_xor : bne = xor := by funext a b; revert a b; decide attribute [simp] xor_assoc theorem xor_iff_ne : ∀ {x y : Bool}, xor x y = true ↔ x ≠ y := by decide /-! ### De Morgan's laws for booleans -/ instance linearOrder : LinearOrder Bool where le_refl := by decide le_trans := by decide le_antisymm := by decide le_total := by decide toDecidableLE := inferInstance toDecidableEq := inferInstance toDecidableLT := inferInstance lt_iff_le_not_le := by decide max_def := by decide min_def := by decide theorem lt_iff : ∀ {x y : Bool}, x < y ↔ x = false ∧ y = true := by decide @[simp] theorem false_lt_true : false < true := lt_iff.2 ⟨rfl, rfl⟩ theorem le_iff_imp : ∀ {x y : Bool}, x ≤ y ↔ x → y := by decide theorem and_le_left : ∀ x y : Bool, (x && y) ≤ x := by decide theorem and_le_right : ∀ x y : Bool, (x && y) ≤ y := by decide theorem le_and : ∀ {x y z : Bool}, x ≤ y → x ≤ z → x ≤ (y && z) := by decide theorem left_le_or : ∀ x y : Bool, x ≤ (x || y) := by decide theorem right_le_or : ∀ x y : Bool, y ≤ (x || y) := by decide theorem or_le : ∀ {x y z}, x ≤ z → y ≤ z → (x || y) ≤ z := by decide /-- convert a `ℕ` to a `Bool`, `0 -> false`, everything else -> `true` -/ def ofNat (n : Nat) : Bool := decide (n ≠ 0) @[simp] lemma toNat_beq_zero (b : Bool) : (b.toNat == 0) = !b := by cases b <;> rfl @[simp] lemma toNat_bne_zero (b : Bool) : (b.toNat != 0) = b := by simp [bne] @[simp] lemma toNat_beq_one (b : Bool) : (b.toNat == 1) = b := by cases b <;> rfl @[simp] lemma toNat_bne_one (b : Bool) : (b.toNat != 1) = !b := by simp [bne] theorem ofNat_le_ofNat {n m : Nat} (h : n ≤ m) : ofNat n ≤ ofNat m := by simp only [ofNat, ne_eq, _root_.decide_not] cases Nat.decEq n 0 with | isTrue hn => rw [_root_.decide_eq_true hn]; exact Bool.false_le _ | isFalse hn => cases Nat.decEq m 0 with | isFalse hm => rw [_root_.decide_eq_false hm]; exact Bool.le_true _ | isTrue hm => subst hm; have h := Nat.le_antisymm h (Nat.zero_le n); contradiction theorem toNat_le_toNat {b₀ b₁ : Bool} (h : b₀ ≤ b₁) : toNat b₀ ≤ toNat b₁ := by cases b₀ <;> cases b₁ <;> simp_all +decide theorem ofNat_toNat (b : Bool) : ofNat (toNat b) = b := by cases b <;> rfl @[simp] theorem injective_iff {α : Sort*} {f : Bool → α} : Function.Injective f ↔ f false ≠ f true := ⟨fun Hinj Heq ↦ false_ne_true (Hinj Heq), fun H x y hxy ↦ by cases x <;> cases y · rfl · exact (H hxy).elim · exact (H hxy.symm).elim · rfl⟩ /-- **Kaminski's Equation** -/ theorem apply_apply_apply (f : Bool → Bool) (x : Bool) : f (f (f x)) = f x := by cases x <;> cases h₁ : f true <;> cases h₂ : f false <;> simp only [h₁, h₂] /-- `xor3 x y c` is `((x XOR y) XOR c)`. -/ protected def xor3 (x y c : Bool) := xor (xor x y) c /-- `carry x y c` is `x && y || x && c || y && c`. -/ protected def carry (x y c : Bool) := x && y || x && c || y && c end Bool
Mathlib/Data/Bool/Basic.lean
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/- Copyright (c) 2022 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Patrick Massot, Yury Kudryashov, Kevin H. Wilson, Heather Macbeth -/ import Mathlib.Order.Filter.Tendsto /-! # Product and coproduct filters In this file we define `Filter.prod f g` (notation: `f ×ˢ g`) and `Filter.coprod f g`. The product of two filters is the largest filter `l` such that `Filter.Tendsto Prod.fst l f` and `Filter.Tendsto Prod.snd l g`. ## Implementation details The product filter cannot be defined using the monad structure on filters. For example: ```lean F := do {x ← seq, y ← top, return (x, y)} G := do {y ← top, x ← seq, return (x, y)} ``` hence: ```lean s ∈ F ↔ ∃ n, [n..∞] × univ ⊆ s s ∈ G ↔ ∀ i:ℕ, ∃ n, [n..∞] × {i} ⊆ s ``` Now `⋃ i, [i..∞] × {i}` is in `G` but not in `F`. As product filter we want to have `F` as result. ## Notations * `f ×ˢ g` : `Filter.prod f g`, localized in `Filter`. -/ open Set open Filter namespace Filter variable {α β γ δ : Type*} {ι : Sort*} section Prod variable {s : Set α} {t : Set β} {f : Filter α} {g : Filter β} theorem prod_mem_prod (hs : s ∈ f) (ht : t ∈ g) : s ×ˢ t ∈ f ×ˢ g := inter_mem_inf (preimage_mem_comap hs) (preimage_mem_comap ht) theorem mem_prod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} : s ∈ f ×ˢ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ×ˢ t₂ ⊆ s := by constructor · rintro ⟨t₁, ⟨s₁, hs₁, hts₁⟩, t₂, ⟨s₂, hs₂, hts₂⟩, rfl⟩ exact ⟨s₁, hs₁, s₂, hs₂, fun p ⟨h, h'⟩ => ⟨hts₁ h, hts₂ h'⟩⟩ · rintro ⟨t₁, ht₁, t₂, ht₂, h⟩ exact mem_inf_of_inter (preimage_mem_comap ht₁) (preimage_mem_comap ht₂) h @[simp] theorem compl_diagonal_mem_prod {l₁ l₂ : Filter α} : (diagonal α)ᶜ ∈ l₁ ×ˢ l₂ ↔ Disjoint l₁ l₂ := by simp only [mem_prod_iff, Filter.disjoint_iff, prod_subset_compl_diagonal_iff_disjoint] @[simp] theorem prod_mem_prod_iff [f.NeBot] [g.NeBot] : s ×ˢ t ∈ f ×ˢ g ↔ s ∈ f ∧ t ∈ g := ⟨fun h => let ⟨_s', hs', _t', ht', H⟩ := mem_prod_iff.1 h (prod_subset_prod_iff.1 H).elim (fun ⟨hs's, ht't⟩ => ⟨mem_of_superset hs' hs's, mem_of_superset ht' ht't⟩) fun h => h.elim (fun hs'e => absurd hs'e (nonempty_of_mem hs').ne_empty) fun ht'e => absurd ht'e (nonempty_of_mem ht').ne_empty, fun h => prod_mem_prod h.1 h.2⟩ theorem mem_prod_principal {s : Set (α × β)} : s ∈ f ×ˢ 𝓟 t ↔ { a | ∀ b ∈ t, (a, b) ∈ s } ∈ f := by rw [← @exists_mem_subset_iff _ f, mem_prod_iff] refine exists_congr fun u => Iff.rfl.and ⟨?_, fun h => ⟨t, mem_principal_self t, ?_⟩⟩ · rintro ⟨v, v_in, hv⟩ a a_in b b_in exact hv (mk_mem_prod a_in <| v_in b_in) · rintro ⟨x, y⟩ ⟨hx, hy⟩ exact h hx y hy theorem mem_prod_top {s : Set (α × β)} : s ∈ f ×ˢ (⊤ : Filter β) ↔ { a | ∀ b, (a, b) ∈ s } ∈ f := by rw [← principal_univ, mem_prod_principal] simp only [mem_univ, forall_true_left] theorem eventually_prod_principal_iff {p : α × β → Prop} {s : Set β} : (∀ᶠ x : α × β in f ×ˢ 𝓟 s, p x) ↔ ∀ᶠ x : α in f, ∀ y : β, y ∈ s → p (x, y) := by rw [eventually_iff, eventually_iff, mem_prod_principal] simp only [mem_setOf_eq] theorem comap_prod (f : α → β × γ) (b : Filter β) (c : Filter γ) : comap f (b ×ˢ c) = comap (Prod.fst ∘ f) b ⊓ comap (Prod.snd ∘ f) c := by rw [prod_eq_inf, comap_inf, Filter.comap_comap, Filter.comap_comap] theorem comap_prodMap_prod (f : α → β) (g : γ → δ) (lb : Filter β) (ld : Filter δ) : comap (Prod.map f g) (lb ×ˢ ld) = comap f lb ×ˢ comap g ld := by simp [prod_eq_inf, comap_comap, Function.comp_def] theorem prod_top : f ×ˢ (⊤ : Filter β) = f.comap Prod.fst := by rw [prod_eq_inf, comap_top, inf_top_eq] theorem top_prod : (⊤ : Filter α) ×ˢ g = g.comap Prod.snd := by rw [prod_eq_inf, comap_top, top_inf_eq] theorem sup_prod (f₁ f₂ : Filter α) (g : Filter β) : (f₁ ⊔ f₂) ×ˢ g = (f₁ ×ˢ g) ⊔ (f₂ ×ˢ g) := by simp only [prod_eq_inf, comap_sup, inf_sup_right] theorem prod_sup (f : Filter α) (g₁ g₂ : Filter β) : f ×ˢ (g₁ ⊔ g₂) = (f ×ˢ g₁) ⊔ (f ×ˢ g₂) := by simp only [prod_eq_inf, comap_sup, inf_sup_left] theorem eventually_prod_iff {p : α × β → Prop} : (∀ᶠ x in f ×ˢ g, p x) ↔ ∃ pa : α → Prop, (∀ᶠ x in f, pa x) ∧ ∃ pb : β → Prop, (∀ᶠ y in g, pb y) ∧ ∀ {x}, pa x → ∀ {y}, pb y → p (x, y) := by simpa only [Set.prod_subset_iff] using @mem_prod_iff α β p f g theorem tendsto_fst : Tendsto Prod.fst (f ×ˢ g) f := tendsto_inf_left tendsto_comap theorem tendsto_snd : Tendsto Prod.snd (f ×ˢ g) g := tendsto_inf_right tendsto_comap /-- If a function tends to a product `g ×ˢ h` of filters, then its first component tends to `g`. See also `Filter.Tendsto.fst_nhds` for the special case of converging to a point in a product of two topological spaces. -/ theorem Tendsto.fst {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) : Tendsto (fun a ↦ (m a).1) f g := tendsto_fst.comp H /-- If a function tends to a product `g ×ˢ h` of filters, then its second component tends to `h`. See also `Filter.Tendsto.snd_nhds` for the special case of converging to a point in a product of two topological spaces. -/ theorem Tendsto.snd {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) : Tendsto (fun a ↦ (m a).2) f h := tendsto_snd.comp H theorem Tendsto.prodMk {h : Filter γ} {m₁ : α → β} {m₂ : α → γ} (h₁ : Tendsto m₁ f g) (h₂ : Tendsto m₂ f h) : Tendsto (fun x => (m₁ x, m₂ x)) f (g ×ˢ h) := tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩ @[deprecated (since := "2025-03-10")] alias Tendsto.prod_mk := Tendsto.prodMk theorem tendsto_prod_swap : Tendsto (Prod.swap : α × β → β × α) (f ×ˢ g) (g ×ˢ f) := tendsto_snd.prodMk tendsto_fst theorem Eventually.prod_inl {la : Filter α} {p : α → Prop} (h : ∀ᶠ x in la, p x) (lb : Filter β) : ∀ᶠ x in la ×ˢ lb, p (x : α × β).1 := tendsto_fst.eventually h theorem Eventually.prod_inr {lb : Filter β} {p : β → Prop} (h : ∀ᶠ x in lb, p x) (la : Filter α) : ∀ᶠ x in la ×ˢ lb, p (x : α × β).2 := tendsto_snd.eventually h theorem Eventually.prod_mk {la : Filter α} {pa : α → Prop} (ha : ∀ᶠ x in la, pa x) {lb : Filter β} {pb : β → Prop} (hb : ∀ᶠ y in lb, pb y) : ∀ᶠ p in la ×ˢ lb, pa (p : α × β).1 ∧ pb p.2 := (ha.prod_inl lb).and (hb.prod_inr la) theorem EventuallyEq.prodMap {δ} {la : Filter α} {fa ga : α → γ} (ha : fa =ᶠ[la] ga) {lb : Filter β} {fb gb : β → δ} (hb : fb =ᶠ[lb] gb) : Prod.map fa fb =ᶠ[la ×ˢ lb] Prod.map ga gb := (Eventually.prod_mk ha hb).mono fun _ h => Prod.ext h.1 h.2 @[deprecated (since := "2025-03-10")] alias EventuallyEq.prod_map := EventuallyEq.prodMap theorem EventuallyLE.prodMap {δ} [LE γ] [LE δ] {la : Filter α} {fa ga : α → γ} (ha : fa ≤ᶠ[la] ga) {lb : Filter β} {fb gb : β → δ} (hb : fb ≤ᶠ[lb] gb) : Prod.map fa fb ≤ᶠ[la ×ˢ lb] Prod.map ga gb := Eventually.prod_mk ha hb @[deprecated (since := "2025-03-10")] alias EventuallyLE.prod_map := EventuallyLE.prodMap theorem Eventually.curry {la : Filter α} {lb : Filter β} {p : α × β → Prop} (h : ∀ᶠ x in la ×ˢ lb, p x) : ∀ᶠ x in la, ∀ᶠ y in lb, p (x, y) := by rcases eventually_prod_iff.1 h with ⟨pa, ha, pb, hb, h⟩ exact ha.mono fun a ha => hb.mono fun b hb => h ha hb protected lemma Frequently.uncurry {la : Filter α} {lb : Filter β} {p : α → β → Prop} (h : ∃ᶠ x in la, ∃ᶠ y in lb, p x y) : ∃ᶠ xy in la ×ˢ lb, p xy.1 xy.2 := mt (fun h ↦ by simpa only [not_frequently] using h.curry) h lemma Frequently.of_curry {la : Filter α} {lb : Filter β} {p : α × β → Prop} (h : ∃ᶠ x in la, ∃ᶠ y in lb, p (x, y)) : ∃ᶠ xy in la ×ˢ lb, p xy := h.uncurry /-- A fact that is eventually true about all pairs `l ×ˢ l` is eventually true about all diagonal pairs `(i, i)` -/ theorem Eventually.diag_of_prod {p : α × α → Prop} (h : ∀ᶠ i in f ×ˢ f, p i) : ∀ᶠ i in f, p (i, i) := by obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h apply (ht.and hs).mono fun x hx => hst hx.1 hx.2 theorem Eventually.diag_of_prod_left {f : Filter α} {g : Filter γ} {p : (α × α) × γ → Prop} : (∀ᶠ x in (f ×ˢ f) ×ˢ g, p x) → ∀ᶠ x : α × γ in f ×ˢ g, p ((x.1, x.1), x.2) := by intro h obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h exact (ht.diag_of_prod.prod_mk hs).mono fun x hx => by simp only [hst hx.1 hx.2] theorem Eventually.diag_of_prod_right {f : Filter α} {g : Filter γ} {p : α × γ × γ → Prop} : (∀ᶠ x in f ×ˢ (g ×ˢ g), p x) → ∀ᶠ x : α × γ in f ×ˢ g, p (x.1, x.2, x.2) := by intro h obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h exact (ht.prod_mk hs.diag_of_prod).mono fun x hx => by simp only [hst hx.1 hx.2] theorem tendsto_diag : Tendsto (fun i => (i, i)) f (f ×ˢ f) := tendsto_iff_eventually.mpr fun _ hpr => hpr.diag_of_prod theorem prod_iInf_left [Nonempty ι] {f : ι → Filter α} {g : Filter β} : (⨅ i, f i) ×ˢ g = ⨅ i, f i ×ˢ g := by simp only [prod_eq_inf, comap_iInf, iInf_inf] theorem prod_iInf_right [Nonempty ι] {f : Filter α} {g : ι → Filter β} : (f ×ˢ ⨅ i, g i) = ⨅ i, f ×ˢ g i := by simp only [prod_eq_inf, comap_iInf, inf_iInf] @[mono, gcongr] theorem prod_mono {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) : f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ := inf_le_inf (comap_mono hf) (comap_mono hg) @[gcongr] theorem prod_mono_left (g : Filter β) {f₁ f₂ : Filter α} (hf : f₁ ≤ f₂) : f₁ ×ˢ g ≤ f₂ ×ˢ g := Filter.prod_mono hf rfl.le @[gcongr] theorem prod_mono_right (f : Filter α) {g₁ g₂ : Filter β} (hf : g₁ ≤ g₂) : f ×ˢ g₁ ≤ f ×ˢ g₂ := Filter.prod_mono rfl.le hf theorem prod_comap_comap_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x} {f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : β₁ → α₁} {m₂ : β₂ → α₂} : comap m₁ f₁ ×ˢ comap m₂ f₂ = comap (fun p : β₁ × β₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := by simp only [prod_eq_inf, comap_comap, comap_inf, Function.comp_def] theorem prod_comm' : f ×ˢ g = comap Prod.swap (g ×ˢ f) := by simp only [prod_eq_inf, comap_comap, Function.comp_def, inf_comm, Prod.swap, comap_inf] theorem prod_comm : f ×ˢ g = map (fun p : β × α => (p.2, p.1)) (g ×ˢ f) := by rw [prod_comm', ← map_swap_eq_comap_swap] rfl theorem mem_prod_iff_left {s : Set (α × β)} : s ∈ f ×ˢ g ↔ ∃ t ∈ f, ∀ᶠ y in g, ∀ x ∈ t, (x, y) ∈ s := by simp only [mem_prod_iff, prod_subset_iff] refine exists_congr fun _ => Iff.rfl.and <| Iff.trans ?_ exists_mem_subset_iff exact exists_congr fun _ => Iff.rfl.and forall₂_swap theorem mem_prod_iff_right {s : Set (α × β)} : s ∈ f ×ˢ g ↔ ∃ t ∈ g, ∀ᶠ x in f, ∀ y ∈ t, (x, y) ∈ s := by rw [prod_comm, mem_map, mem_prod_iff_left]; rfl @[simp] theorem map_fst_prod (f : Filter α) (g : Filter β) [NeBot g] : map Prod.fst (f ×ˢ g) = f := by ext s simp only [mem_map, mem_prod_iff_left, mem_preimage, eventually_const, ← subset_def, exists_mem_subset_iff] @[simp] theorem map_snd_prod (f : Filter α) (g : Filter β) [NeBot f] : map Prod.snd (f ×ˢ g) = g := by rw [prod_comm, map_map]; apply map_fst_prod @[simp] theorem prod_le_prod {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] : f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ ↔ f₁ ≤ f₂ ∧ g₁ ≤ g₂ := ⟨fun h => ⟨map_fst_prod f₁ g₁ ▸ tendsto_fst.mono_left h, map_snd_prod f₁ g₁ ▸ tendsto_snd.mono_left h⟩, fun h => prod_mono h.1 h.2⟩ @[simp] theorem prod_inj {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] : f₁ ×ˢ g₁ = f₂ ×ˢ g₂ ↔ f₁ = f₂ ∧ g₁ = g₂ := by refine ⟨fun h => ?_, fun h => h.1 ▸ h.2 ▸ rfl⟩ have hle : f₁ ≤ f₂ ∧ g₁ ≤ g₂ := prod_le_prod.1 h.le haveI := neBot_of_le hle.1; haveI := neBot_of_le hle.2 exact ⟨hle.1.antisymm <| (prod_le_prod.1 h.ge).1, hle.2.antisymm <| (prod_le_prod.1 h.ge).2⟩ theorem eventually_swap_iff {p : α × β → Prop} : (∀ᶠ x : α × β in f ×ˢ g, p x) ↔ ∀ᶠ y : β × α in g ×ˢ f, p y.swap := by rw [prod_comm]; rfl theorem prod_assoc (f : Filter α) (g : Filter β) (h : Filter γ) : map (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) = f ×ˢ (g ×ˢ h) := by simp_rw [← comap_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc, Function.comp_def, Equiv.prodAssoc_symm_apply] theorem prod_assoc_symm (f : Filter α) (g : Filter β) (h : Filter γ) : map (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) = (f ×ˢ g) ×ˢ h := by simp_rw [map_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc, Function.comp_def, Equiv.prodAssoc_apply] theorem tendsto_prodAssoc {h : Filter γ} : Tendsto (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) (f ×ˢ (g ×ˢ h)) := (prod_assoc f g h).le theorem tendsto_prodAssoc_symm {h : Filter γ} : Tendsto (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) ((f ×ˢ g) ×ˢ h) := (prod_assoc_symm f g h).le /-- A useful lemma when dealing with uniformities. -/ theorem map_swap4_prod {h : Filter γ} {k : Filter δ} : map (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k)) = (f ×ˢ h) ×ˢ (g ×ˢ k) := by simp_rw [map_swap4_eq_comap, prod_eq_inf, comap_inf, comap_comap]; ac_rfl theorem tendsto_swap4_prod {h : Filter γ} {k : Filter δ} : Tendsto (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k)) ((f ×ˢ h) ×ˢ (g ×ˢ k)) := map_swap4_prod.le theorem prod_map_map_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x} {f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : α₁ → β₁} {m₂ : α₂ → β₂} : map m₁ f₁ ×ˢ map m₂ f₂ = map (fun p : α₁ × α₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := le_antisymm (fun s hs => let ⟨s₁, hs₁, s₂, hs₂, h⟩ := mem_prod_iff.mp hs mem_of_superset (prod_mem_prod (image_mem_map hs₁) (image_mem_map hs₂)) <| by rwa [prod_image_image_eq, image_subset_iff]) ((tendsto_map.comp tendsto_fst).prodMk (tendsto_map.comp tendsto_snd)) theorem prod_map_map_eq' {α₁ : Type*} {α₂ : Type*} {β₁ : Type*} {β₂ : Type*} (f : α₁ → α₂) (g : β₁ → β₂) (F : Filter α₁) (G : Filter β₁) : map f F ×ˢ map g G = map (Prod.map f g) (F ×ˢ G) := prod_map_map_eq
theorem prod_map_left (f : α → β) (F : Filter α) (G : Filter γ) : map f F ×ˢ G = map (Prod.map f id) (F ×ˢ G) := by rw [← prod_map_map_eq', map_id]
Mathlib/Order/Filter/Prod.lean
327
330
/- Copyright (c) 2020 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.FormalMultilinearSeries import Mathlib.Analysis.SpecificLimits.Normed import Mathlib.Logic.Equiv.Fin.Basic import Mathlib.Tactic.Bound.Attribute import Mathlib.Topology.Algebra.InfiniteSum.Module /-! # Analytic functions A function is analytic in one dimension around `0` if it can be written as a converging power series `Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not always possible in nonzero characteristic (in characteristic 2, the previous example has no symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition, and we only require the existence of a converging series. The general framework is important to say that the exponential map on bounded operators on a Banach space is analytic, as well as the inverse on invertible operators. ## Main definitions Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n` for `n : ℕ`. * `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially. * `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n` is bounded above, then `r ≤ p.radius`; * `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`, `p.isLittleO_one_of_lt_radius`, `p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then `‖p n‖ * r ^ n` tends to zero exponentially; * `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then `r < p.radius`; * `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`. * `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`. Additionally, let `f` be a function from `E` to `F`. * `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`, `f (x + y) = ∑'_n pₙ yⁿ`. * `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds `HasFPowerSeriesOnBall f p x r`. * `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`. * `AnalyticOnNhd 𝕜 f s`: the function `f` is analytic at every point of `s`. We also define versions of `HasFPowerSeriesOnBall`, `AnalyticAt`, and `AnalyticOnNhd` restricted to a set, similar to `ContinuousWithinAt`. See `Mathlib.Analysis.Analytic.Within` for basic properties. * `AnalyticWithinAt 𝕜 f s x` means a power series at `x` converges to `f` on `𝓝[s ∪ {x}] x`. * `AnalyticOn 𝕜 f s t` means `∀ x ∈ t, AnalyticWithinAt 𝕜 f s x`. We develop the basic properties of these notions, notably: * If a function admits a power series, it is continuous (see `HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and `AnalyticAt.continuousAt`). * In a complete space, the sum of a formal power series with positive radius is well defined on the disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`. ## Implementation details We only introduce the radius of convergence of a power series, as `p.radius`. For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent) notion, describing the polydisk of convergence. This notion is more specific, and not necessary to build the general theory. We do not define it here. -/ noncomputable section variable {𝕜 E F G : Type*} open Topology NNReal Filter ENNReal Set Asymptotics namespace FormalMultilinearSeries variable [Semiring 𝕜] [AddCommMonoid E] [AddCommMonoid F] [Module 𝕜 E] [Module 𝕜 F] variable [TopologicalSpace E] [TopologicalSpace F] variable [ContinuousAdd E] [ContinuousAdd F] variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F] /-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A priori, it only behaves well when `‖x‖ < p.radius`. -/ protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F := ∑' n : ℕ, p n fun _ => x /-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum `Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/ def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F := ∑ k ∈ Finset.range n, p k fun _ : Fin k => x /-- The partial sums of a formal multilinear series are continuous. -/ theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) : Continuous (p.partialSum n) := by unfold partialSum fun_prop end FormalMultilinearSeries /-! ### The radius of a formal multilinear series -/ variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] namespace FormalMultilinearSeries variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} /-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ` converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these definitions are *not* equivalent in general. -/ def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ := ⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞) /-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) : (r : ℝ≥0∞) ≤ p.radius := le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h /-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) : (r : ℝ≥0∞) ≤ p.radius := p.le_radius_of_bound C fun n => mod_cast h n /-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : ↑r ≤ p.radius := Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC => p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n) theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) : ↑r ≤ p.radius := p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius := p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => h.le_tsum' _ theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius := p.le_radius_of_summable_nnnorm <| by simp only [← coe_nnnorm] at h exact mod_cast h theorem radius_eq_top_of_forall_nnreal_isBigO (h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r) theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ := p.radius_eq_top_of_forall_nnreal_isBigO fun r => (isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) : p.radius = ∞ := p.radius_eq_top_of_eventually_eq_zero <| mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩ @[simp] theorem constFormalMultilinearSeries_radius {v : F} : (constFormalMultilinearSeries 𝕜 E v).radius = ⊤ := (constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1 (by simp [constFormalMultilinearSeries]) /-- `0` has infinite radius of convergence -/ @[simp] lemma zero_radius : (0 : FormalMultilinearSeries 𝕜 E F).radius = ∞ := by rw [← constFormalMultilinearSeries_zero] exact constFormalMultilinearSeries_radius /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially: for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/ theorem isLittleO_of_lt_radius (h : ↑r < p.radius) : ∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4 rw [this] -- Porting note: was -- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4] simp only [radius, lt_iSup_iff] at h rcases h with ⟨t, C, hC, rt⟩ rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt rw [← div_lt_one this] at rt refine ⟨_, rt, C, Or.inr zero_lt_one, fun n => ?_⟩ calc |‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by field_simp [mul_right_comm, abs_mul] _ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/ theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) : (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) := let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially: for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/ theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp (p.isLittleO_of_lt_radius h) rcases this with ⟨a, ha, C, hC, H⟩ exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩ /-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/ theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1) (hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5) rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩ rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀ lift a to ℝ≥0 using ha.1.le have : (r : ℝ) < r / a := by simpa only [div_one] using (div_lt_div_iff_of_pos_left h₀ zero_lt_one ha.1).2 ha.2 norm_cast at this rw [← ENNReal.coe_lt_coe] at this refine this.trans_le (p.le_radius_of_bound C fun n => ?_) rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff₀ (pow_pos ha.1 n)] exact (le_abs_self _).trans (hp n) /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C := let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h ⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one₀ ha.1.le ha.2.le)⟩ /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n := let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h ⟨C, hC, fun n => Iff.mpr (le_div_iff₀ (pow_pos h0 _)) (hp n)⟩ /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C := let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h ⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩ theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ} (h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius := p.le_radius_of_isBigO (h.isBigO_one _) theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F) (hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius := p.le_radius_of_tendsto hs.tendsto_atTop_zero theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E} (h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n := fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs) theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) : Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _)) hp ((summable_geometric_of_lt_one ha.1.le ha.2).mul_left _) theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by rw [mem_emetric_ball_zero_iff] at hx refine .of_nonneg_of_le (fun _ ↦ norm_nonneg _) (fun n ↦ ((p n).le_opNorm _).trans_eq ?_) (p.summable_norm_mul_pow hx) simp theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) : Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by rw [← NNReal.summable_coe] push_cast exact p.summable_norm_mul_pow h protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x := (p.summable_norm_apply hx).of_norm theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F) (hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r) theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) : p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by constructor · intro h r obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius (show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top) refine .of_norm_bounded (fun n ↦ (C : ℝ) * a ^ n) ((summable_geometric_of_lt_one ha.1.le ha.2).mul_left _) fun n ↦ ?_ specialize hp n rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))] · exact p.radius_eq_top_of_summable_norm /-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/ theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) : ∃ (C r : _) (_ : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩ have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0] rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩ refine ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => ?_⟩ rw [inv_pow, ← div_eq_mul_inv] exact hCp n lemma radius_le_of_le {𝕜' E' F' : Type*} [NontriviallyNormedField 𝕜'] [NormedAddCommGroup E'] [NormedSpace 𝕜' E'] [NormedAddCommGroup F'] [NormedSpace 𝕜' F'] {p : FormalMultilinearSeries 𝕜 E F} {q : FormalMultilinearSeries 𝕜' E' F'} (h : ∀ n, ‖p n‖ ≤ ‖q n‖) : q.radius ≤ p.radius := by apply le_of_forall_nnreal_lt (fun r hr ↦ ?_) rcases norm_mul_pow_le_of_lt_radius _ hr with ⟨C, -, hC⟩ apply le_radius_of_bound _ C (fun n ↦ ?_) apply le_trans _ (hC n) gcongr exact h n /-- The radius of the sum of two formal series is at least the minimum of their two radii. -/ theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) : min p.radius q.radius ≤ (p + q).radius := by refine ENNReal.le_of_forall_nnreal_lt fun r hr => ?_ rw [lt_min_iff] at hr have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO refine (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => ?_).trans this) rw [← add_mul, norm_mul, norm_mul, norm_norm] exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _) @[simp] theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by simp only [radius, neg_apply, norm_neg] theorem radius_le_smul {p : FormalMultilinearSeries 𝕜 E F} {c : 𝕜} : p.radius ≤ (c • p).radius := by simp only [radius, smul_apply] refine iSup_mono fun r ↦ iSup_mono' fun C ↦ ⟨‖c‖ * C, iSup_mono' fun h ↦ ?_⟩ simp only [le_refl, exists_prop, and_true] intro n rw [norm_smul c (p n), mul_assoc] gcongr exact h n theorem radius_smul_eq (p : FormalMultilinearSeries 𝕜 E F) {c : 𝕜} (hc : c ≠ 0) : (c • p).radius = p.radius := by apply eq_of_le_of_le _ radius_le_smul exact radius_le_smul.trans_eq (congr_arg _ <| inv_smul_smul₀ hc p) @[simp] theorem radius_shift (p : FormalMultilinearSeries 𝕜 E F) : p.shift.radius = p.radius := by simp only [radius, shift, Nat.succ_eq_add_one, ContinuousMultilinearMap.curryRight_norm] congr ext r apply eq_of_le_of_le · apply iSup_mono' intro C use ‖p 0‖ ⊔ (C * r) apply iSup_mono' intro h simp only [le_refl, le_sup_iff, exists_prop, and_true] intro n rcases n with - | m · simp right rw [pow_succ, ← mul_assoc] apply mul_le_mul_of_nonneg_right (h m) zero_le_coe · apply iSup_mono' intro C use ‖p 1‖ ⊔ C / r apply iSup_mono' intro h simp only [le_refl, le_sup_iff, exists_prop, and_true] intro n cases eq_zero_or_pos r with | inl hr => rw [hr] cases n <;> simp | inr hr => right rw [← NNReal.coe_pos] at hr specialize h (n + 1) rw [le_div_iff₀ hr] rwa [pow_succ, ← mul_assoc] at h @[simp] theorem radius_unshift (p : FormalMultilinearSeries 𝕜 E (E →L[𝕜] F)) (z : F) : (p.unshift z).radius = p.radius := by rw [← radius_shift, unshift_shift] protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) := (p.summable hx).hasSum theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F) (f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by refine ENNReal.le_of_forall_nnreal_lt fun r hr => ?_ apply le_radius_of_isBigO apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO refine IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ ?_) (isBigO_refl _ _) refine IsBigOWith.of_bound (Eventually.of_forall fun n => ?_) simpa only [norm_norm] using f.norm_compContinuousMultilinearMap_le (p n) end FormalMultilinearSeries /-! ### Expanding a function as a power series -/ section variable {f g : E → F} {p pf : FormalMultilinearSeries 𝕜 E F} {s t : Set E} {x : E} {r r' : ℝ≥0∞} /-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as a power series on the ball of radius `r > 0` around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `‖y‖ < r`. -/ structure HasFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (r : ℝ≥0∞) : Prop where r_le : r ≤ p.radius r_pos : 0 < r hasSum : ∀ {y}, y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) /-- Analogue of `HasFPowerSeriesOnBall` where convergence is required only on a set `s`. We also require convergence at `x` as the behavior of this notion is very bad otherwise. -/ structure HasFPowerSeriesWithinOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (s : Set E) (x : E) (r : ℝ≥0∞) : Prop where /-- `p` converges on `ball 0 r` -/ r_le : r ≤ p.radius /-- The radius of convergence is positive -/ r_pos : 0 < r /-- `p converges to f` within `s` -/ hasSum : ∀ {y}, x + y ∈ insert x s → y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) /-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as a power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a neighborhood of `0`. -/ def HasFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) := ∃ r, HasFPowerSeriesOnBall f p x r /-- Analogue of `HasFPowerSeriesAt` where convergence is required only on a set `s`. -/ def HasFPowerSeriesWithinAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (s : Set E) (x : E) := ∃ r, HasFPowerSeriesWithinOnBall f p s x r -- Teach the `bound` tactic that power series have positive radius attribute [bound_forward] HasFPowerSeriesOnBall.r_pos HasFPowerSeriesWithinOnBall.r_pos variable (𝕜) /-- Given a function `f : E → F`, we say that `f` is analytic at `x` if it admits a convergent power series expansion around `x`. -/ @[fun_prop] def AnalyticAt (f : E → F) (x : E) := ∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesAt f p x /-- `f` is analytic within `s` at `x` if it has a power series at `x` that converges on `𝓝[s] x` -/ def AnalyticWithinAt (f : E → F) (s : Set E) (x : E) : Prop := ∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesWithinAt f p s x /-- Given a function `f : E → F`, we say that `f` is analytic on a set `s` if it is analytic around every point of `s`. -/ def AnalyticOnNhd (f : E → F) (s : Set E) := ∀ x, x ∈ s → AnalyticAt 𝕜 f x /-- `f` is analytic within `s` if it is analytic within `s` at each point of `s`. Note that this is weaker than `AnalyticOnNhd 𝕜 f s`, as `f` is allowed to be arbitrary outside `s`. -/ def AnalyticOn (f : E → F) (s : Set E) : Prop := ∀ x ∈ s, AnalyticWithinAt 𝕜 f s x /-! ### `HasFPowerSeriesOnBall` and `HasFPowerSeriesWithinOnBall` -/ variable {𝕜} theorem HasFPowerSeriesOnBall.hasFPowerSeriesAt (hf : HasFPowerSeriesOnBall f p x r) : HasFPowerSeriesAt f p x := ⟨r, hf⟩ theorem HasFPowerSeriesAt.analyticAt (hf : HasFPowerSeriesAt f p x) : AnalyticAt 𝕜 f x := ⟨p, hf⟩ theorem HasFPowerSeriesOnBall.analyticAt (hf : HasFPowerSeriesOnBall f p x r) : AnalyticAt 𝕜 f x := hf.hasFPowerSeriesAt.analyticAt theorem HasFPowerSeriesWithinOnBall.hasFPowerSeriesWithinAt (hf : HasFPowerSeriesWithinOnBall f p s x r) : HasFPowerSeriesWithinAt f p s x := ⟨r, hf⟩ theorem HasFPowerSeriesWithinAt.analyticWithinAt (hf : HasFPowerSeriesWithinAt f p s x) : AnalyticWithinAt 𝕜 f s x := ⟨p, hf⟩ theorem HasFPowerSeriesWithinOnBall.analyticWithinAt (hf : HasFPowerSeriesWithinOnBall f p s x r) : AnalyticWithinAt 𝕜 f s x := hf.hasFPowerSeriesWithinAt.analyticWithinAt /-- If a function `f` has a power series `p` around `x`, then the function `z ↦ f (z - y)` has the same power series around `x + y`. -/ theorem HasFPowerSeriesOnBall.comp_sub (hf : HasFPowerSeriesOnBall f p x r) (y : E) : HasFPowerSeriesOnBall (fun z => f (z - y)) p (x + y) r := { r_le := hf.r_le r_pos := hf.r_pos hasSum := fun {z} hz => by convert hf.hasSum hz using 2 abel } theorem HasFPowerSeriesWithinOnBall.hasSum_sub (hf : HasFPowerSeriesWithinOnBall f p s x r) {y : E} (hy : y ∈ (insert x s) ∩ EMetric.ball x r) : HasSum (fun n : ℕ => p n fun _ => y - x) (f y) := by have : y - x ∈ EMetric.ball (0 : E) r := by simpa [edist_eq_enorm_sub] using hy.2 have := hf.hasSum (by simpa only [add_sub_cancel] using hy.1) this simpa only [add_sub_cancel] theorem HasFPowerSeriesOnBall.hasSum_sub (hf : HasFPowerSeriesOnBall f p x r) {y : E} (hy : y ∈ EMetric.ball x r) : HasSum (fun n : ℕ => p n fun _ => y - x) (f y) := by have : y - x ∈ EMetric.ball (0 : E) r := by simpa [edist_eq_enorm_sub] using hy simpa only [add_sub_cancel] using hf.hasSum this theorem HasFPowerSeriesOnBall.radius_pos (hf : HasFPowerSeriesOnBall f p x r) : 0 < p.radius := lt_of_lt_of_le hf.r_pos hf.r_le theorem HasFPowerSeriesWithinOnBall.radius_pos (hf : HasFPowerSeriesWithinOnBall f p s x r) : 0 < p.radius := lt_of_lt_of_le hf.r_pos hf.r_le theorem HasFPowerSeriesAt.radius_pos (hf : HasFPowerSeriesAt f p x) : 0 < p.radius := let ⟨_, hr⟩ := hf hr.radius_pos theorem HasFPowerSeriesWithinOnBall.of_le (hf : HasFPowerSeriesWithinOnBall f p s x r) (r'_pos : 0 < r') (hr : r' ≤ r) : HasFPowerSeriesWithinOnBall f p s x r' := ⟨le_trans hr hf.1, r'_pos, fun hy h'y => hf.hasSum hy (EMetric.ball_subset_ball hr h'y)⟩ theorem HasFPowerSeriesOnBall.mono (hf : HasFPowerSeriesOnBall f p x r) (r'_pos : 0 < r') (hr : r' ≤ r) : HasFPowerSeriesOnBall f p x r' := ⟨le_trans hr hf.1, r'_pos, fun hy => hf.hasSum (EMetric.ball_subset_ball hr hy)⟩ lemma HasFPowerSeriesWithinOnBall.congr {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} {r : ℝ≥0∞} (h : HasFPowerSeriesWithinOnBall f p s x r) (h' : EqOn g f (s ∩ EMetric.ball x r)) (h'' : g x = f x) : HasFPowerSeriesWithinOnBall g p s x r := by refine ⟨h.r_le, h.r_pos, ?_⟩ intro y hy h'y convert h.hasSum hy h'y using 1 simp only [mem_insert_iff, add_eq_left] at hy rcases hy with rfl | hy · simpa using h'' · apply h' refine ⟨hy, ?_⟩ simpa [edist_eq_enorm_sub] using h'y /-- Variant of `HasFPowerSeriesWithinOnBall.congr` in which one requests equality on `insert x s` instead of separating `x` and `s`. -/ lemma HasFPowerSeriesWithinOnBall.congr' {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} {r : ℝ≥0∞} (h : HasFPowerSeriesWithinOnBall f p s x r) (h' : EqOn g f (insert x s ∩ EMetric.ball x r)) : HasFPowerSeriesWithinOnBall g p s x r := by refine ⟨h.r_le, h.r_pos, fun {y} hy h'y ↦ ?_⟩ convert h.hasSum hy h'y using 1 exact h' ⟨hy, by simpa [edist_eq_enorm_sub] using h'y⟩ lemma HasFPowerSeriesWithinAt.congr {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} (h : HasFPowerSeriesWithinAt f p s x) (h' : g =ᶠ[𝓝[s] x] f) (h'' : g x = f x) : HasFPowerSeriesWithinAt g p s x := by rcases h with ⟨r, hr⟩ obtain ⟨ε, εpos, hε⟩ : ∃ ε > 0, EMetric.ball x ε ∩ s ⊆ {y | g y = f y} := EMetric.mem_nhdsWithin_iff.1 h' let r' := min r ε refine ⟨r', ?_⟩ have := hr.of_le (r' := r') (by simp [r', εpos, hr.r_pos]) (min_le_left _ _) apply this.congr _ h'' intro z hz exact hε ⟨EMetric.ball_subset_ball (min_le_right _ _) hz.2, hz.1⟩ theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r) (hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r := { r_le := hf.r_le r_pos := hf.r_pos hasSum := fun {y} hy => by convert hf.hasSum hy using 1 apply hg.symm simpa [edist_eq_enorm_sub] using hy } theorem HasFPowerSeriesAt.congr (hf : HasFPowerSeriesAt f p x) (hg : f =ᶠ[𝓝 x] g) : HasFPowerSeriesAt g p x := by rcases hf with ⟨r₁, h₁⟩ rcases EMetric.mem_nhds_iff.mp hg with ⟨r₂, h₂pos, h₂⟩ exact ⟨min r₁ r₂, (h₁.mono (lt_min h₁.r_pos h₂pos) inf_le_left).congr fun y hy => h₂ (EMetric.ball_subset_ball inf_le_right hy)⟩ theorem HasFPowerSeriesWithinOnBall.unique (hf : HasFPowerSeriesWithinOnBall f p s x r) (hg : HasFPowerSeriesWithinOnBall g p s x r) : (insert x s ∩ EMetric.ball x r).EqOn f g := fun _ hy ↦ (hf.hasSum_sub hy).unique (hg.hasSum_sub hy) theorem HasFPowerSeriesOnBall.unique (hf : HasFPowerSeriesOnBall f p x r) (hg : HasFPowerSeriesOnBall g p x r) : (EMetric.ball x r).EqOn f g := fun _ hy ↦ (hf.hasSum_sub hy).unique (hg.hasSum_sub hy) protected theorem HasFPowerSeriesWithinAt.eventually (hf : HasFPowerSeriesWithinAt f p s x) : ∀ᶠ r : ℝ≥0∞ in 𝓝[>] 0, HasFPowerSeriesWithinOnBall f p s x r := let ⟨_, hr⟩ := hf mem_of_superset (Ioo_mem_nhdsGT hr.r_pos) fun _ hr' => hr.of_le hr'.1 hr'.2.le protected theorem HasFPowerSeriesAt.eventually (hf : HasFPowerSeriesAt f p x) : ∀ᶠ r : ℝ≥0∞ in 𝓝[>] 0, HasFPowerSeriesOnBall f p x r := let ⟨_, hr⟩ := hf mem_of_superset (Ioo_mem_nhdsGT hr.r_pos) fun _ hr' => hr.mono hr'.1 hr'.2.le theorem HasFPowerSeriesOnBall.eventually_hasSum (hf : HasFPowerSeriesOnBall f p x r) : ∀ᶠ y in 𝓝 0, HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) := by filter_upwards [EMetric.ball_mem_nhds (0 : E) hf.r_pos] using fun _ => hf.hasSum theorem HasFPowerSeriesAt.eventually_hasSum (hf : HasFPowerSeriesAt f p x) : ∀ᶠ y in 𝓝 0, HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) := let ⟨_, hr⟩ := hf hr.eventually_hasSum theorem HasFPowerSeriesOnBall.eventually_hasSum_sub (hf : HasFPowerSeriesOnBall f p x r) : ∀ᶠ y in 𝓝 x, HasSum (fun n : ℕ => p n fun _ : Fin n => y - x) (f y) := by filter_upwards [EMetric.ball_mem_nhds x hf.r_pos] with y using hf.hasSum_sub theorem HasFPowerSeriesAt.eventually_hasSum_sub (hf : HasFPowerSeriesAt f p x) : ∀ᶠ y in 𝓝 x, HasSum (fun n : ℕ => p n fun _ : Fin n => y - x) (f y) := let ⟨_, hr⟩ := hf hr.eventually_hasSum_sub theorem HasFPowerSeriesOnBall.eventually_eq_zero (hf : HasFPowerSeriesOnBall f (0 : FormalMultilinearSeries 𝕜 E F) x r) : ∀ᶠ z in 𝓝 x, f z = 0 := by filter_upwards [hf.eventually_hasSum_sub] with z hz using hz.unique hasSum_zero theorem HasFPowerSeriesAt.eventually_eq_zero (hf : HasFPowerSeriesAt f (0 : FormalMultilinearSeries 𝕜 E F) x) : ∀ᶠ z in 𝓝 x, f z = 0 := let ⟨_, hr⟩ := hf hr.eventually_eq_zero @[simp] lemma hasFPowerSeriesWithinOnBall_univ : HasFPowerSeriesWithinOnBall f p univ x r ↔ HasFPowerSeriesOnBall f p x r := by constructor · intro h refine ⟨h.r_le, h.r_pos, fun {y} m ↦ h.hasSum (by simp) m⟩ · intro h exact ⟨h.r_le, h.r_pos, fun {y} _ m => h.hasSum m⟩ @[simp] lemma hasFPowerSeriesWithinAt_univ : HasFPowerSeriesWithinAt f p univ x ↔ HasFPowerSeriesAt f p x := by simp only [HasFPowerSeriesWithinAt, hasFPowerSeriesWithinOnBall_univ, HasFPowerSeriesAt] lemma HasFPowerSeriesWithinOnBall.mono (hf : HasFPowerSeriesWithinOnBall f p s x r) (h : t ⊆ s) : HasFPowerSeriesWithinOnBall f p t x r where r_le := hf.r_le r_pos := hf.r_pos hasSum hy h'y := hf.hasSum (insert_subset_insert h hy) h'y lemma HasFPowerSeriesOnBall.hasFPowerSeriesWithinOnBall (hf : HasFPowerSeriesOnBall f p x r) : HasFPowerSeriesWithinOnBall f p s x r := by rw [← hasFPowerSeriesWithinOnBall_univ] at hf exact hf.mono (subset_univ _) lemma HasFPowerSeriesWithinAt.mono (hf : HasFPowerSeriesWithinAt f p s x) (h : t ⊆ s) : HasFPowerSeriesWithinAt f p t x := by obtain ⟨r, hp⟩ := hf exact ⟨r, hp.mono h⟩ lemma HasFPowerSeriesAt.hasFPowerSeriesWithinAt (hf : HasFPowerSeriesAt f p x) : HasFPowerSeriesWithinAt f p s x := by rw [← hasFPowerSeriesWithinAt_univ] at hf apply hf.mono (subset_univ _) theorem HasFPowerSeriesWithinAt.mono_of_mem_nhdsWithin (h : HasFPowerSeriesWithinAt f p s x) (hst : s ∈ 𝓝[t] x) : HasFPowerSeriesWithinAt f p t x := by rcases h with ⟨r, hr⟩ rcases EMetric.mem_nhdsWithin_iff.1 hst with ⟨r', r'_pos, hr'⟩ refine ⟨min r r', ?_⟩ have Z := hr.of_le (by simp [r'_pos, hr.r_pos]) (min_le_left r r') refine ⟨Z.r_le, Z.r_pos, fun {y} hy h'y ↦ ?_⟩ apply Z.hasSum ?_ h'y simp only [mem_insert_iff, add_eq_left] at hy rcases hy with rfl | hy · simp apply mem_insert_of_mem _ (hr' ?_) simp only [EMetric.mem_ball, edist_eq_enorm_sub, sub_zero, lt_min_iff, mem_inter_iff, add_sub_cancel_left, hy, and_true] at h'y ⊢ exact h'y.2 @[deprecated (since := "2024-10-31")] alias HasFPowerSeriesWithinAt.mono_of_mem := HasFPowerSeriesWithinAt.mono_of_mem_nhdsWithin @[simp] lemma hasFPowerSeriesWithinOnBall_insert_self : HasFPowerSeriesWithinOnBall f p (insert x s) x r ↔ HasFPowerSeriesWithinOnBall f p s x r := by refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩ <;> exact ⟨h.r_le, h.r_pos, fun {y} ↦ by simpa only [insert_idem] using h.hasSum (y := y)⟩ @[simp] theorem hasFPowerSeriesWithinAt_insert {y : E} : HasFPowerSeriesWithinAt f p (insert y s) x ↔ HasFPowerSeriesWithinAt f p s x := by rcases eq_or_ne x y with rfl | hy · simp [HasFPowerSeriesWithinAt] · refine ⟨fun h ↦ h.mono (subset_insert _ _), fun h ↦ ?_⟩ apply HasFPowerSeriesWithinAt.mono_of_mem_nhdsWithin h rw [nhdsWithin_insert_of_ne hy] exact self_mem_nhdsWithin theorem HasFPowerSeriesWithinOnBall.coeff_zero (hf : HasFPowerSeriesWithinOnBall f pf s x r) (v : Fin 0 → E) : pf 0 v = f x := by have v_eq : v = fun i => 0 := Subsingleton.elim _ _ have zero_mem : (0 : E) ∈ EMetric.ball (0 : E) r := by simp [hf.r_pos] have : ∀ i, i ≠ 0 → (pf i fun _ => 0) = 0 := by intro i hi have : 0 < i := pos_iff_ne_zero.2 hi exact ContinuousMultilinearMap.map_coord_zero _ (⟨0, this⟩ : Fin i) rfl have A := (hf.hasSum (by simp) zero_mem).unique (hasSum_single _ this) simpa [v_eq] using A.symm theorem HasFPowerSeriesOnBall.coeff_zero (hf : HasFPowerSeriesOnBall f pf x r) (v : Fin 0 → E) : pf 0 v = f x := by rw [← hasFPowerSeriesWithinOnBall_univ] at hf exact hf.coeff_zero v theorem HasFPowerSeriesWithinAt.coeff_zero (hf : HasFPowerSeriesWithinAt f pf s x) (v : Fin 0 → E) : pf 0 v = f x := let ⟨_, hrf⟩ := hf hrf.coeff_zero v theorem HasFPowerSeriesAt.coeff_zero (hf : HasFPowerSeriesAt f pf x) (v : Fin 0 → E) : pf 0 v = f x := let ⟨_, hrf⟩ := hf hrf.coeff_zero v /-! ### Analytic functions -/ @[simp] theorem analyticOn_empty : AnalyticOn 𝕜 f ∅ := by intro; simp @[simp] theorem analyticOnNhd_empty : AnalyticOnNhd 𝕜 f ∅ := by intro; simp @[simp] lemma analyticWithinAt_univ : AnalyticWithinAt 𝕜 f univ x ↔ AnalyticAt 𝕜 f x := by simp [AnalyticWithinAt, AnalyticAt] @[simp] lemma analyticOn_univ {f : E → F} : AnalyticOn 𝕜 f univ ↔ AnalyticOnNhd 𝕜 f univ := by simp only [AnalyticOn, analyticWithinAt_univ, AnalyticOnNhd] lemma AnalyticWithinAt.mono (hf : AnalyticWithinAt 𝕜 f s x) (h : t ⊆ s) : AnalyticWithinAt 𝕜 f t x := by obtain ⟨p, hp⟩ := hf exact ⟨p, hp.mono h⟩ lemma AnalyticAt.analyticWithinAt (hf : AnalyticAt 𝕜 f x) : AnalyticWithinAt 𝕜 f s x := by rw [← analyticWithinAt_univ] at hf apply hf.mono (subset_univ _) lemma AnalyticOnNhd.analyticOn (hf : AnalyticOnNhd 𝕜 f s) : AnalyticOn 𝕜 f s := fun x hx ↦ (hf x hx).analyticWithinAt lemma AnalyticWithinAt.congr_of_eventuallyEq {f g : E → F} {s : Set E} {x : E} (hf : AnalyticWithinAt 𝕜 f s x) (hs : g =ᶠ[𝓝[s] x] f) (hx : g x = f x) : AnalyticWithinAt 𝕜 g s x := by rcases hf with ⟨p, hp⟩ exact ⟨p, hp.congr hs hx⟩ lemma AnalyticWithinAt.congr_of_eventuallyEq_insert {f g : E → F} {s : Set E} {x : E} (hf : AnalyticWithinAt 𝕜 f s x) (hs : g =ᶠ[𝓝[insert x s] x] f) : AnalyticWithinAt 𝕜 g s x := by apply hf.congr_of_eventuallyEq (nhdsWithin_mono x (subset_insert x s) hs) apply mem_of_mem_nhdsWithin (mem_insert x s) hs lemma AnalyticWithinAt.congr {f g : E → F} {s : Set E} {x : E} (hf : AnalyticWithinAt 𝕜 f s x) (hs : EqOn g f s) (hx : g x = f x) : AnalyticWithinAt 𝕜 g s x := hf.congr_of_eventuallyEq hs.eventuallyEq_nhdsWithin hx lemma AnalyticOn.congr {f g : E → F} {s : Set E} (hf : AnalyticOn 𝕜 f s) (hs : EqOn g f s) : AnalyticOn 𝕜 g s := fun x m ↦ (hf x m).congr hs (hs m) theorem AnalyticAt.congr (hf : AnalyticAt 𝕜 f x) (hg : f =ᶠ[𝓝 x] g) : AnalyticAt 𝕜 g x := let ⟨_, hpf⟩ := hf (hpf.congr hg).analyticAt theorem analyticAt_congr (h : f =ᶠ[𝓝 x] g) : AnalyticAt 𝕜 f x ↔ AnalyticAt 𝕜 g x := ⟨fun hf ↦ hf.congr h, fun hg ↦ hg.congr h.symm⟩ theorem AnalyticOnNhd.mono {s t : Set E} (hf : AnalyticOnNhd 𝕜 f t) (hst : s ⊆ t) : AnalyticOnNhd 𝕜 f s := fun z hz => hf z (hst hz) theorem AnalyticOnNhd.congr' (hf : AnalyticOnNhd 𝕜 f s) (hg : f =ᶠ[𝓝ˢ s] g) : AnalyticOnNhd 𝕜 g s := fun z hz => (hf z hz).congr (mem_nhdsSet_iff_forall.mp hg z hz) theorem analyticOnNhd_congr' (h : f =ᶠ[𝓝ˢ s] g) : AnalyticOnNhd 𝕜 f s ↔ AnalyticOnNhd 𝕜 g s := ⟨fun hf => hf.congr' h, fun hg => hg.congr' h.symm⟩ theorem AnalyticOnNhd.congr (hs : IsOpen s) (hf : AnalyticOnNhd 𝕜 f s) (hg : s.EqOn f g) : AnalyticOnNhd 𝕜 g s := hf.congr' <| mem_nhdsSet_iff_forall.mpr (fun _ hz => eventuallyEq_iff_exists_mem.mpr ⟨s, hs.mem_nhds hz, hg⟩) theorem analyticOnNhd_congr (hs : IsOpen s) (h : s.EqOn f g) : AnalyticOnNhd 𝕜 f s ↔ AnalyticOnNhd 𝕜 g s := ⟨fun hf => hf.congr hs h, fun hg => hg.congr hs h.symm⟩ theorem AnalyticWithinAt.mono_of_mem_nhdsWithin (h : AnalyticWithinAt 𝕜 f s x) (hst : s ∈ 𝓝[t] x) : AnalyticWithinAt 𝕜 f t x := by rcases h with ⟨p, hp⟩ exact ⟨p, hp.mono_of_mem_nhdsWithin hst⟩ @[deprecated (since := "2024-10-31")] alias AnalyticWithinAt.mono_of_mem := AnalyticWithinAt.mono_of_mem_nhdsWithin lemma AnalyticOn.mono {f : E → F} {s t : Set E} (h : AnalyticOn 𝕜 f t) (hs : s ⊆ t) : AnalyticOn 𝕜 f s := fun _ m ↦ (h _ (hs m)).mono hs @[simp] theorem analyticWithinAt_insert {f : E → F} {s : Set E} {x y : E} : AnalyticWithinAt 𝕜 f (insert y s) x ↔ AnalyticWithinAt 𝕜 f s x := by simp [AnalyticWithinAt] /-! ### Composition with linear maps -/ /-- If a function `f` has a power series `p` on a ball within a set and `g` is linear, then `g ∘ f` has the power series `g ∘ p` on the same ball. -/ theorem ContinuousLinearMap.comp_hasFPowerSeriesWithinOnBall (g : F →L[𝕜] G) (h : HasFPowerSeriesWithinOnBall f p s x r) : HasFPowerSeriesWithinOnBall (g ∘ f) (g.compFormalMultilinearSeries p) s x r where r_le := h.r_le.trans (p.radius_le_radius_continuousLinearMap_comp _) r_pos := h.r_pos hasSum hy h'y := by simpa only [ContinuousLinearMap.compFormalMultilinearSeries_apply, ContinuousLinearMap.compContinuousMultilinearMap_coe, Function.comp_apply] using g.hasSum (h.hasSum hy h'y) /-- If a function `f` has a power series `p` on a ball and `g` is linear, then `g ∘ f` has the power series `g ∘ p` on the same ball. -/ theorem ContinuousLinearMap.comp_hasFPowerSeriesOnBall (g : F →L[𝕜] G) (h : HasFPowerSeriesOnBall f p x r) : HasFPowerSeriesOnBall (g ∘ f) (g.compFormalMultilinearSeries p) x r := by rw [← hasFPowerSeriesWithinOnBall_univ] at h ⊢ exact g.comp_hasFPowerSeriesWithinOnBall h /-- If a function `f` is analytic on a set `s` and `g` is linear, then `g ∘ f` is analytic on `s`. -/ theorem ContinuousLinearMap.comp_analyticOn (g : F →L[𝕜] G) (h : AnalyticOn 𝕜 f s) : AnalyticOn 𝕜 (g ∘ f) s := by rintro x hx rcases h x hx with ⟨p, r, hp⟩ exact ⟨g.compFormalMultilinearSeries p, r, g.comp_hasFPowerSeriesWithinOnBall hp⟩ /-- If a function `f` is analytic on a set `s` and `g` is linear, then `g ∘ f` is analytic on `s`. -/ theorem ContinuousLinearMap.comp_analyticOnNhd {s : Set E} (g : F →L[𝕜] G) (h : AnalyticOnNhd 𝕜 f s) : AnalyticOnNhd 𝕜 (g ∘ f) s := by rintro x hx rcases h x hx with ⟨p, r, hp⟩ exact ⟨g.compFormalMultilinearSeries p, r, g.comp_hasFPowerSeriesOnBall hp⟩ /-! ### Relation between analytic function and the partial sums of its power series -/ theorem HasFPowerSeriesWithinOnBall.tendsto_partialSum (hf : HasFPowerSeriesWithinOnBall f p s x r) {y : E} (hy : y ∈ EMetric.ball (0 : E) r) (h'y : x + y ∈ insert x s) : Tendsto (fun n => p.partialSum n y) atTop (𝓝 (f (x + y))) := (hf.hasSum h'y hy).tendsto_sum_nat theorem HasFPowerSeriesOnBall.tendsto_partialSum (hf : HasFPowerSeriesOnBall f p x r) {y : E} (hy : y ∈ EMetric.ball (0 : E) r) : Tendsto (fun n => p.partialSum n y) atTop (𝓝 (f (x + y))) := (hf.hasSum hy).tendsto_sum_nat theorem HasFPowerSeriesAt.tendsto_partialSum (hf : HasFPowerSeriesAt f p x) : ∀ᶠ y in 𝓝 0, Tendsto (fun n => p.partialSum n y) atTop (𝓝 (f (x + y))) := by rcases hf with ⟨r, hr⟩ filter_upwards [EMetric.ball_mem_nhds (0 : E) hr.r_pos] with y hy exact hr.tendsto_partialSum hy open Finset in /-- If a function admits a power series expansion within a ball, then the partial sums `p.partialSum n z` converge to `f (x + y)` as `n → ∞` and `z → y`. Note that `x + z` doesn't need to belong to the set where the power series expansion holds. -/ theorem HasFPowerSeriesWithinOnBall.tendsto_partialSum_prod {y : E} (hf : HasFPowerSeriesWithinOnBall f p s x r) (hy : y ∈ EMetric.ball (0 : E) r) (h'y : x + y ∈ insert x s) : Tendsto (fun (z : ℕ × E) ↦ p.partialSum z.1 z.2) (atTop ×ˢ 𝓝 y) (𝓝 (f (x + y))) := by have A : Tendsto (fun (z : ℕ × E) ↦ p.partialSum z.1 y) (atTop ×ˢ 𝓝 y) (𝓝 (f (x + y))) := by apply (hf.tendsto_partialSum hy h'y).comp tendsto_fst suffices Tendsto (fun (z : ℕ × E) ↦ p.partialSum z.1 z.2 - p.partialSum z.1 y) (atTop ×ˢ 𝓝 y) (𝓝 0) by simpa using A.add this apply Metric.tendsto_nhds.2 (fun ε εpos ↦ ?_) obtain ⟨r', yr', r'r⟩ : ∃ (r' : ℝ≥0), ‖y‖₊ < r' ∧ r' < r := by simp [edist_zero_eq_enorm] at hy simpa using ENNReal.lt_iff_exists_nnreal_btwn.1 hy have yr'_2 : ‖y‖ < r' := by simpa [← coe_nnnorm] using yr' have S : Summable fun n ↦ ‖p n‖ * ↑r' ^ n := p.summable_norm_mul_pow (r'r.trans_le hf.r_le) obtain ⟨k, hk⟩ : ∃ k, ∑' (n : ℕ), ‖p (n + k)‖ * ↑r' ^ (n + k) < ε / 4 := by have : Tendsto (fun k ↦ ∑' n, ‖p (n + k)‖ * ↑r' ^ (n + k)) atTop (𝓝 0) := by apply _root_.tendsto_sum_nat_add (f := fun n ↦ ‖p n‖ * ↑r' ^ n) exact ((tendsto_order.1 this).2 _ (by linarith)).exists have A : ∀ᶠ (z : ℕ × E) in atTop ×ˢ 𝓝 y, dist (p.partialSum k z.2) (p.partialSum k y) < ε / 4 := by have : ContinuousAt (fun z ↦ p.partialSum k z) y := (p.partialSum_continuous k).continuousAt exact tendsto_snd (Metric.tendsto_nhds.1 this.tendsto (ε / 4) (by linarith)) have B : ∀ᶠ (z : ℕ × E) in atTop ×ˢ 𝓝 y, ‖z.2‖₊ < r' := by suffices ∀ᶠ (z : E) in 𝓝 y, ‖z‖₊ < r' from tendsto_snd this have : Metric.ball 0 r' ∈ 𝓝 y := Metric.isOpen_ball.mem_nhds (by simpa using yr'_2) filter_upwards [this] with a ha using by simpa [← coe_nnnorm] using ha have C : ∀ᶠ (z : ℕ × E) in atTop ×ˢ 𝓝 y, k ≤ z.1 := tendsto_fst (Ici_mem_atTop _) filter_upwards [A, B, C] rintro ⟨n, z⟩ hz h'z hkn simp only [dist_eq_norm, sub_zero] at hz ⊢ have I (w : E) (hw : ‖w‖₊ < r') : ‖∑ i ∈ Ico k n, p i (fun _ ↦ w)‖ ≤ ε / 4 := calc ‖∑ i ∈ Ico k n, p i (fun _ ↦ w)‖ _ = ‖∑ i ∈ range (n - k), p (i + k) (fun _ ↦ w)‖ := by rw [sum_Ico_eq_sum_range] congr with i rw [add_comm k] _ ≤ ∑ i ∈ range (n - k), ‖p (i + k) (fun _ ↦ w)‖ := norm_sum_le _ _ _ ≤ ∑ i ∈ range (n - k), ‖p (i + k)‖ * ‖w‖ ^ (i + k) := by gcongr with i _hi; exact ((p (i + k)).le_opNorm _).trans_eq (by simp) _ ≤ ∑ i ∈ range (n - k), ‖p (i + k)‖ * ↑r' ^ (i + k) := by gcongr with i _hi; simpa [← coe_nnnorm] using hw.le _ ≤ ∑' i, ‖p (i + k)‖ * ↑r' ^ (i + k) := by apply Summable.sum_le_tsum _ (fun i _hi ↦ by positivity) apply ((_root_.summable_nat_add_iff k).2 S) _ ≤ ε / 4 := hk.le calc ‖p.partialSum n z - p.partialSum n y‖ _ = ‖∑ i ∈ range n, p i (fun _ ↦ z) - ∑ i ∈ range n, p i (fun _ ↦ y)‖ := rfl _ = ‖(∑ i ∈ range k, p i (fun _ ↦ z) + ∑ i ∈ Ico k n, p i (fun _ ↦ z)) - (∑ i ∈ range k, p i (fun _ ↦ y) + ∑ i ∈ Ico k n, p i (fun _ ↦ y))‖ := by simp [sum_range_add_sum_Ico _ hkn] _ = ‖(p.partialSum k z - p.partialSum k y) + (∑ i ∈ Ico k n, p i (fun _ ↦ z)) + (- ∑ i ∈ Ico k n, p i (fun _ ↦ y))‖ := by congr 1 simp only [FormalMultilinearSeries.partialSum] abel _ ≤ ‖p.partialSum k z - p.partialSum k y‖ + ‖∑ i ∈ Ico k n, p i (fun _ ↦ z)‖ + ‖- ∑ i ∈ Ico k n, p i (fun _ ↦ y)‖ := norm_add₃_le _ ≤ ε / 4 + ε / 4 + ε / 4 := by gcongr · exact I _ h'z · simp only [norm_neg]; exact I _ yr' _ < ε := by linarith /-- If a function admits a power series on a ball, then the partial sums `p.partialSum n z` converges to `f (x + y)` as `n → ∞` and `z → y`. -/ theorem HasFPowerSeriesOnBall.tendsto_partialSum_prod {y : E} (hf : HasFPowerSeriesOnBall f p x r) (hy : y ∈ EMetric.ball (0 : E) r) : Tendsto (fun (z : ℕ × E) ↦ p.partialSum z.1 z.2) (atTop ×ˢ 𝓝 y) (𝓝 (f (x + y))) := (hf.hasFPowerSeriesWithinOnBall (s := univ)).tendsto_partialSum_prod hy (by simp) /-- If a function admits a power series expansion, then it is exponentially close to the partial sums of this power series on strict subdisks of the disk of convergence. This version provides an upper estimate that decreases both in `‖y‖` and `n`. See also `HasFPowerSeriesWithinOnBall.uniform_geometric_approx` for a weaker version. -/ theorem HasFPowerSeriesWithinOnBall.uniform_geometric_approx' {r' : ℝ≥0} (hf : HasFPowerSeriesWithinOnBall f p s x r) (h : (r' : ℝ≥0∞) < r) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, x + y ∈ insert x s → ‖f (x + y) - p.partialSum n y‖ ≤ C * (a * (‖y‖ / r')) ^ n := by obtain ⟨a, ha, C, hC, hp⟩ : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r' : ℝ) ^ n ≤ C * a ^ n := p.norm_mul_pow_le_mul_pow_of_lt_radius (h.trans_le hf.r_le) refine ⟨a, ha, C / (1 - a), div_pos hC (sub_pos.2 ha.2), fun y hy n ys => ?_⟩ have yr' : ‖y‖ < r' := by rw [ball_zero_eq] at hy exact hy have hr'0 : 0 < (r' : ℝ) := (norm_nonneg _).trans_lt yr' have : y ∈ EMetric.ball (0 : E) r := by refine mem_emetric_ball_zero_iff.2 (lt_trans ?_ h) simpa [enorm] using yr' rw [norm_sub_rev, ← mul_div_right_comm] have ya : a * (‖y‖ / ↑r') ≤ a := mul_le_of_le_one_right ha.1.le (div_le_one_of_le₀ yr'.le r'.coe_nonneg) suffices ‖p.partialSum n y - f (x + y)‖ ≤ C * (a * (‖y‖ / r')) ^ n / (1 - a * (‖y‖ / r')) by refine this.trans ?_ have : 0 < a := ha.1 gcongr apply_rules [sub_pos.2, ha.2] apply norm_sub_le_of_geometric_bound_of_hasSum (ya.trans_lt ha.2) _ (hf.hasSum ys this) intro n calc ‖(p n) fun _ : Fin n => y‖ _ ≤ ‖p n‖ * ∏ _i : Fin n, ‖y‖ := ContinuousMultilinearMap.le_opNorm _ _ _ = ‖p n‖ * (r' : ℝ) ^ n * (‖y‖ / r') ^ n := by field_simp [mul_right_comm] _ ≤ C * a ^ n * (‖y‖ / r') ^ n := by gcongr ?_ * _; apply hp _ ≤ C * (a * (‖y‖ / r')) ^ n := by rw [mul_pow, mul_assoc] /-- If a function admits a power series expansion, then it is exponentially close to the partial sums of this power series on strict subdisks of the disk of convergence. This version provides an upper estimate that decreases both in `‖y‖` and `n`. See also `HasFPowerSeriesOnBall.uniform_geometric_approx` for a weaker version. -/ theorem HasFPowerSeriesOnBall.uniform_geometric_approx' {r' : ℝ≥0} (hf : HasFPowerSeriesOnBall f p x r) (h : (r' : ℝ≥0∞) < r) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, ‖f (x + y) - p.partialSum n y‖ ≤ C * (a * (‖y‖ / r')) ^ n := by rw [← hasFPowerSeriesWithinOnBall_univ] at hf simpa using hf.uniform_geometric_approx' h /-- If a function admits a power series expansion within a set in a ball, then it is exponentially close to the partial sums of this power series on strict subdisks of the disk of convergence. -/ theorem HasFPowerSeriesWithinOnBall.uniform_geometric_approx {r' : ℝ≥0} (hf : HasFPowerSeriesWithinOnBall f p s x r) (h : (r' : ℝ≥0∞) < r) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, x + y ∈ insert x s → ‖f (x + y) - p.partialSum n y‖ ≤ C * a ^ n := by obtain ⟨a, ha, C, hC, hp⟩ : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, x + y ∈ insert x s → ‖f (x + y) - p.partialSum n y‖ ≤ C * (a * (‖y‖ / r')) ^ n := hf.uniform_geometric_approx' h refine ⟨a, ha, C, hC, fun y hy n ys => (hp y hy n ys).trans ?_⟩ have yr' : ‖y‖ < r' := by rwa [ball_zero_eq] at hy have := ha.1.le -- needed to discharge a side goal on the next line gcongr exact mul_le_of_le_one_right ha.1.le (div_le_one_of_le₀ yr'.le r'.coe_nonneg) /-- If a function admits a power series expansion, then it is exponentially close to the partial sums of this power series on strict subdisks of the disk of convergence. -/ theorem HasFPowerSeriesOnBall.uniform_geometric_approx {r' : ℝ≥0} (hf : HasFPowerSeriesOnBall f p x r) (h : (r' : ℝ≥0∞) < r) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, ‖f (x + y) - p.partialSum n y‖ ≤ C * a ^ n := by rw [← hasFPowerSeriesWithinOnBall_univ] at hf simpa using hf.uniform_geometric_approx h /-- Taylor formula for an analytic function within a set, `IsBigO` version. -/ theorem HasFPowerSeriesWithinAt.isBigO_sub_partialSum_pow (hf : HasFPowerSeriesWithinAt f p s x) (n : ℕ) : (fun y : E => f (x + y) - p.partialSum n y) =O[𝓝[(x + ·)⁻¹' insert x s] 0] fun y => ‖y‖ ^ n := by rcases hf with ⟨r, hf⟩ rcases ENNReal.lt_iff_exists_nnreal_btwn.1 hf.r_pos with ⟨r', r'0, h⟩
obtain ⟨a, -, C, -, hp⟩ : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ y ∈ Metric.ball (0 : E) r', ∀ n, x + y ∈ insert x s → ‖f (x + y) - p.partialSum n y‖ ≤ C * (a * (‖y‖ / r')) ^ n := hf.uniform_geometric_approx' h
Mathlib/Analysis/Analytic/Basic.lean
1,033
1,035
/- Copyright (c) 2020 Paul van Wamelen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Paul van Wamelen -/ import Mathlib.Data.Int.NatPrime import Mathlib.Data.ZMod.Basic import Mathlib.RingTheory.Int.Basic import Mathlib.Tactic.FieldSimp /-! # Pythagorean Triples The main result is the classification of Pythagorean triples. The final result is for general Pythagorean triples. It follows from the more interesting relatively prime case. We use the "rational parametrization of the circle" method for the proof. The parametrization maps the point `(x / z, y / z)` to the slope of the line through `(-1 , 0)` and `(x / z, y / z)`. This quickly shows that `(x / z, y / z) = (2 * m * n / (m ^ 2 + n ^ 2), (m ^ 2 - n ^ 2) / (m ^ 2 + n ^ 2))` where `m / n` is the slope. In order to identify numerators and denominators we now need results showing that these are coprime. This is easy except for the prime 2. In order to deal with that we have to analyze the parity of `x`, `y`, `m` and `n` and eliminate all the impossible cases. This takes up the bulk of the proof below. -/ assert_not_exists TwoSidedIdeal theorem sq_ne_two_fin_zmod_four (z : ZMod 4) : z * z ≠ 2 := by change Fin 4 at z fin_cases z <;> decide theorem Int.sq_ne_two_mod_four (z : ℤ) : z * z % 4 ≠ 2 := by suffices ¬z * z % (4 : ℕ) = 2 % (4 : ℕ) by exact this rw [← ZMod.intCast_eq_intCast_iff'] simpa using sq_ne_two_fin_zmod_four _ noncomputable section /-- Three integers `x`, `y`, and `z` form a Pythagorean triple if `x * x + y * y = z * z`. -/ def PythagoreanTriple (x y z : ℤ) : Prop := x * x + y * y = z * z /-- Pythagorean triples are interchangeable, i.e `x * x + y * y = y * y + x * x = z * z`. This comes from additive commutativity. -/ theorem pythagoreanTriple_comm {x y z : ℤ} : PythagoreanTriple x y z ↔ PythagoreanTriple y x z := by delta PythagoreanTriple rw [add_comm] /-- The zeroth Pythagorean triple is all zeros. -/ theorem PythagoreanTriple.zero : PythagoreanTriple 0 0 0 := by simp only [PythagoreanTriple, zero_mul, zero_add] namespace PythagoreanTriple variable {x y z : ℤ} theorem eq (h : PythagoreanTriple x y z) : x * x + y * y = z * z := h @[symm] theorem symm (h : PythagoreanTriple x y z) : PythagoreanTriple y x z := by rwa [pythagoreanTriple_comm] /-- A triple is still a triple if you multiply `x`, `y` and `z` by a constant `k`. -/ theorem mul (h : PythagoreanTriple x y z) (k : ℤ) : PythagoreanTriple (k * x) (k * y) (k * z) := calc k * x * (k * x) + k * y * (k * y) = k ^ 2 * (x * x + y * y) := by ring _ = k ^ 2 * (z * z) := by rw [h.eq] _ = k * z * (k * z) := by ring /-- `(k*x, k*y, k*z)` is a Pythagorean triple if and only if `(x, y, z)` is also a triple. -/ theorem mul_iff (k : ℤ) (hk : k ≠ 0) : PythagoreanTriple (k * x) (k * y) (k * z) ↔ PythagoreanTriple x y z := by refine ⟨?_, fun h => h.mul k⟩ simp only [PythagoreanTriple] intro h rw [← mul_left_inj' (mul_ne_zero hk hk)] convert h using 1 <;> ring /-- A Pythagorean triple `x, y, z` is “classified” if there exist integers `k, m, n` such that either * `x = k * (m ^ 2 - n ^ 2)` and `y = k * (2 * m * n)`, or * `x = k * (2 * m * n)` and `y = k * (m ^ 2 - n ^ 2)`. -/ @[nolint unusedArguments] def IsClassified (_ : PythagoreanTriple x y z) := ∃ k m n : ℤ, (x = k * (m ^ 2 - n ^ 2) ∧ y = k * (2 * m * n) ∨ x = k * (2 * m * n) ∧ y = k * (m ^ 2 - n ^ 2)) ∧ Int.gcd m n = 1 /-- A primitive Pythagorean triple `x, y, z` is a Pythagorean triple with `x` and `y` coprime. Such a triple is “primitively classified” if there exist coprime integers `m, n` such that either * `x = m ^ 2 - n ^ 2` and `y = 2 * m * n`, or * `x = 2 * m * n` and `y = m ^ 2 - n ^ 2`. -/ @[nolint unusedArguments] def IsPrimitiveClassified (_ : PythagoreanTriple x y z) := ∃ m n : ℤ, (x = m ^ 2 - n ^ 2 ∧ y = 2 * m * n ∨ x = 2 * m * n ∧ y = m ^ 2 - n ^ 2) ∧ Int.gcd m n = 1 ∧ (m % 2 = 0 ∧ n % 2 = 1 ∨ m % 2 = 1 ∧ n % 2 = 0) variable (h : PythagoreanTriple x y z) include h theorem mul_isClassified (k : ℤ) (hc : h.IsClassified) : (h.mul k).IsClassified := by obtain ⟨l, m, n, ⟨⟨rfl, rfl⟩ | ⟨rfl, rfl⟩, co⟩⟩ := hc · use k * l, m, n apply And.intro _ co left constructor <;> ring · use k * l, m, n apply And.intro _ co right constructor <;> ring theorem even_odd_of_coprime (hc : Int.gcd x y = 1) : x % 2 = 0 ∧ y % 2 = 1 ∨ x % 2 = 1 ∧ y % 2 = 0 := by rcases Int.emod_two_eq_zero_or_one x with hx | hx <;> rcases Int.emod_two_eq_zero_or_one y with hy | hy -- x even, y even · exfalso apply Nat.not_coprime_of_dvd_of_dvd (by decide : 1 < 2) _ _ hc · apply Int.natCast_dvd.1 apply Int.dvd_of_emod_eq_zero hx · apply Int.natCast_dvd.1 apply Int.dvd_of_emod_eq_zero hy -- x even, y odd · left exact ⟨hx, hy⟩ -- x odd, y even · right exact ⟨hx, hy⟩ -- x odd, y odd · exfalso obtain ⟨x0, y0, rfl, rfl⟩ : ∃ x0 y0, x = x0 * 2 + 1 ∧ y = y0 * 2 + 1 := by obtain ⟨x0, hx2⟩ := exists_eq_mul_left_of_dvd (Int.dvd_self_sub_of_emod_eq hx) obtain ⟨y0, hy2⟩ := exists_eq_mul_left_of_dvd (Int.dvd_self_sub_of_emod_eq hy) rw [sub_eq_iff_eq_add] at hx2 hy2 exact ⟨x0, y0, hx2, hy2⟩ apply Int.sq_ne_two_mod_four z rw [show z * z = 4 * (x0 * x0 + x0 + y0 * y0 + y0) + 2 by rw [← h.eq] ring] simp only [Int.add_emod, Int.mul_emod_right, zero_add] decide theorem gcd_dvd : (Int.gcd x y : ℤ) ∣ z := by by_cases h0 : Int.gcd x y = 0 · have hx : x = 0 := by apply Int.natAbs_eq_zero.mp apply Nat.eq_zero_of_gcd_eq_zero_left h0 have hy : y = 0 := by apply Int.natAbs_eq_zero.mp apply Nat.eq_zero_of_gcd_eq_zero_right h0 have hz : z = 0 := by simpa only [PythagoreanTriple, hx, hy, add_zero, zero_eq_mul, mul_zero, or_self_iff] using h simp only [hz, dvd_zero] obtain ⟨k, x0, y0, _, h2, rfl, rfl⟩ : ∃ (k : ℕ) (x0 y0 : _), 0 < k ∧ Int.gcd x0 y0 = 1 ∧ x = x0 * k ∧ y = y0 * k := Int.exists_gcd_one' (Nat.pos_of_ne_zero h0) rw [Int.gcd_mul_right, h2, Int.natAbs_natCast, one_mul] rw [← Int.pow_dvd_pow_iff two_ne_zero, sq z, ← h.eq] rw [(by ring : x0 * k * (x0 * k) + y0 * k * (y0 * k) = (k : ℤ) ^ 2 * (x0 * x0 + y0 * y0))] exact dvd_mul_right _ _ theorem normalize : PythagoreanTriple (x / Int.gcd x y) (y / Int.gcd x y) (z / Int.gcd x y) := by by_cases h0 : Int.gcd x y = 0 · have hx : x = 0 := by apply Int.natAbs_eq_zero.mp apply Nat.eq_zero_of_gcd_eq_zero_left h0 have hy : y = 0 := by apply Int.natAbs_eq_zero.mp apply Nat.eq_zero_of_gcd_eq_zero_right h0 have hz : z = 0 := by simpa only [PythagoreanTriple, hx, hy, add_zero, zero_eq_mul, mul_zero, or_self_iff] using h simp only [hx, hy, hz] exact zero rcases h.gcd_dvd with ⟨z0, rfl⟩ obtain ⟨k, x0, y0, k0, h2, rfl, rfl⟩ : ∃ (k : ℕ) (x0 y0 : _), 0 < k ∧ Int.gcd x0 y0 = 1 ∧ x = x0 * k ∧ y = y0 * k := Int.exists_gcd_one' (Nat.pos_of_ne_zero h0) have hk : (k : ℤ) ≠ 0 := by norm_cast rwa [pos_iff_ne_zero] at k0 rw [Int.gcd_mul_right, h2, Int.natAbs_natCast, one_mul] at h ⊢ rw [mul_comm x0, mul_comm y0, mul_iff k hk] at h rwa [Int.mul_ediv_cancel _ hk, Int.mul_ediv_cancel _ hk, Int.mul_ediv_cancel_left _ hk] theorem isClassified_of_isPrimitiveClassified (hp : h.IsPrimitiveClassified) : h.IsClassified := by obtain ⟨m, n, H⟩ := hp use 1, m, n omega theorem isClassified_of_normalize_isPrimitiveClassified (hc : h.normalize.IsPrimitiveClassified) : h.IsClassified := by convert h.normalize.mul_isClassified (Int.gcd x y) (isClassified_of_isPrimitiveClassified h.normalize hc) <;> rw [Int.mul_ediv_cancel'] · exact Int.gcd_dvd_left · exact Int.gcd_dvd_right · exact h.gcd_dvd theorem ne_zero_of_coprime (hc : Int.gcd x y = 1) : z ≠ 0 := by suffices 0 < z * z by rintro rfl norm_num at this rw [← h.eq, ← sq, ← sq] have hc' : Int.gcd x y ≠ 0 := by rw [hc] exact one_ne_zero rcases Int.ne_zero_of_gcd hc' with hxz | hyz · apply lt_add_of_pos_of_le (sq_pos_of_ne_zero hxz) (sq_nonneg y) · apply lt_add_of_le_of_pos (sq_nonneg x) (sq_pos_of_ne_zero hyz) theorem isPrimitiveClassified_of_coprime_of_zero_left (hc : Int.gcd x y = 1) (hx : x = 0) : h.IsPrimitiveClassified := by subst x change Nat.gcd 0 (Int.natAbs y) = 1 at hc rw [Nat.gcd_zero_left (Int.natAbs y)] at hc rcases Int.natAbs_eq y with hy | hy · use 1, 0 rw [hy, hc, Int.gcd_zero_right] decide · use 0, 1 rw [hy, hc, Int.gcd_zero_left] decide theorem coprime_of_coprime (hc : Int.gcd x y = 1) : Int.gcd y z = 1 := by by_contra H obtain ⟨p, hp, hpy, hpz⟩ := Nat.Prime.not_coprime_iff_dvd.mp H apply hp.not_dvd_one rw [← hc] apply Nat.dvd_gcd (Int.Prime.dvd_natAbs_of_coe_dvd_sq hp _ _) hpy rw [sq, eq_sub_of_add_eq h] rw [← Int.natCast_dvd] at hpy hpz exact dvd_sub (hpz.mul_right _) (hpy.mul_right _) end PythagoreanTriple section circleEquivGen /-! ### A parametrization of the unit circle For the classification of Pythagorean triples, we will use a parametrization of the unit circle. -/ variable {K : Type*} [Field K] /-- A parameterization of the unit circle that is useful for classifying Pythagorean triples. (To be applied in the case where `K = ℚ`.) -/ def circleEquivGen (hk : ∀ x : K, 1 + x ^ 2 ≠ 0) : K ≃ { p : K × K // p.1 ^ 2 + p.2 ^ 2 = 1 ∧ p.2 ≠ -1 } where toFun x := ⟨⟨2 * x / (1 + x ^ 2), (1 - x ^ 2) / (1 + x ^ 2)⟩, by field_simp [hk x, div_pow] ring, by simp only [Ne, div_eq_iff (hk x), neg_mul, one_mul, neg_add, sub_eq_add_neg, add_left_inj] simpa only [eq_neg_iff_add_eq_zero, one_pow] using hk 1⟩ invFun p := (p : K × K).1 / ((p : K × K).2 + 1) left_inv x := by have h2 : (1 + 1 : K) = 2 := by norm_num have h3 : (2 : K) ≠ 0 := by convert hk 1 rw [one_pow 2, h2] field_simp [hk x, h2, add_assoc, add_comm, add_sub_cancel, mul_comm] right_inv := fun ⟨⟨x, y⟩, hxy, hy⟩ => by change x ^ 2 + y ^ 2 = 1 at hxy have h2 : y + 1 ≠ 0 := mt eq_neg_of_add_eq_zero_left hy have h3 : (y + 1) ^ 2 + x ^ 2 = 2 * (y + 1) := by rw [(add_neg_eq_iff_eq_add.mpr hxy.symm).symm] ring have h4 : (2 : K) ≠ 0 := by convert hk 1 rw [one_pow 2] ring simp only [Prod.mk_inj, Subtype.mk_eq_mk] constructor · field_simp [h3] ring · field_simp [h3] rw [← add_neg_eq_iff_eq_add.mpr hxy.symm] ring @[simp] theorem circleEquivGen_apply (hk : ∀ x : K, 1 + x ^ 2 ≠ 0) (x : K) : (circleEquivGen hk x : K × K) = ⟨2 * x / (1 + x ^ 2), (1 - x ^ 2) / (1 + x ^ 2)⟩ := rfl @[simp] theorem circleEquivGen_symm_apply (hk : ∀ x : K, 1 + x ^ 2 ≠ 0) (v : { p : K × K // p.1 ^ 2 + p.2 ^ 2 = 1 ∧ p.2 ≠ -1 }) : (circleEquivGen hk).symm v = (v : K × K).1 / ((v : K × K).2 + 1) := rfl end circleEquivGen private theorem coprime_sq_sub_sq_add_of_even_odd {m n : ℤ} (h : Int.gcd m n = 1) (hm : m % 2 = 0) (hn : n % 2 = 1) : Int.gcd (m ^ 2 - n ^ 2) (m ^ 2 + n ^ 2) = 1 := by by_contra H obtain ⟨p, hp, hp1, hp2⟩ := Nat.Prime.not_coprime_iff_dvd.mp H rw [← Int.natCast_dvd] at hp1 hp2 have h2m : (p : ℤ) ∣ 2 * m ^ 2 := by convert dvd_add hp2 hp1 using 1 ring have h2n : (p : ℤ) ∣ 2 * n ^ 2 := by convert dvd_sub hp2 hp1 using 1 ring have hmc : p = 2 ∨ p ∣ Int.natAbs m := prime_two_or_dvd_of_dvd_two_mul_pow_self_two hp h2m have hnc : p = 2 ∨ p ∣ Int.natAbs n := prime_two_or_dvd_of_dvd_two_mul_pow_self_two hp h2n by_cases h2 : p = 2 · have h3 : (m ^ 2 + n ^ 2) % 2 = 1 := by simp only [sq, Int.add_emod, Int.mul_emod, hm, hn, dvd_refl, Int.emod_emod_of_dvd] decide have h4 : (m ^ 2 + n ^ 2) % 2 = 0 := by apply Int.emod_eq_zero_of_dvd rwa [h2] at hp2 rw [h4] at h3 exact zero_ne_one h3 · apply hp.not_dvd_one rw [← h] exact Nat.dvd_gcd (Or.resolve_left hmc h2) (Or.resolve_left hnc h2) private theorem coprime_sq_sub_sq_add_of_odd_even {m n : ℤ} (h : Int.gcd m n = 1) (hm : m % 2 = 1) (hn : n % 2 = 0) : Int.gcd (m ^ 2 - n ^ 2) (m ^ 2 + n ^ 2) = 1 := by
rw [Int.gcd, ← Int.natAbs_neg (m ^ 2 - n ^ 2)] rw [(by ring : -(m ^ 2 - n ^ 2) = n ^ 2 - m ^ 2), add_comm] apply coprime_sq_sub_sq_add_of_even_odd _ hn hm; rwa [Int.gcd_comm] private theorem coprime_sq_sub_mul_of_even_odd {m n : ℤ} (h : Int.gcd m n = 1) (hm : m % 2 = 0) (hn : n % 2 = 1) : Int.gcd (m ^ 2 - n ^ 2) (2 * m * n) = 1 := by by_contra H obtain ⟨p, hp, hp1, hp2⟩ := Nat.Prime.not_coprime_iff_dvd.mp H rw [← Int.natCast_dvd] at hp1 hp2 have hnp : ¬(p : ℤ) ∣ Int.gcd m n := by rw [h] norm_cast exact mt Nat.dvd_one.mp (Nat.Prime.ne_one hp) rcases Int.Prime.dvd_mul hp hp2 with hp2m | hpn · rw [Int.natAbs_mul] at hp2m rcases (Nat.Prime.dvd_mul hp).mp hp2m with hp2 | hpm · have hp2' : p = 2 := (Nat.le_of_dvd zero_lt_two hp2).antisymm hp.two_le revert hp1 rw [hp2'] apply mt Int.emod_eq_zero_of_dvd simp only [sq, Nat.cast_ofNat, Int.sub_emod, Int.mul_emod, hm, hn, mul_zero, EuclideanDomain.zero_mod, mul_one, zero_sub] decide apply mt (Int.dvd_coe_gcd (Int.natCast_dvd.mpr hpm)) hnp apply or_self_iff.mp apply Int.Prime.dvd_mul' hp
Mathlib/NumberTheory/PythagoreanTriples.lean
330
355
/- Copyright (c) 2023 Xavier Roblot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Xavier Roblot -/ import Mathlib.LinearAlgebra.Matrix.Gershgorin import Mathlib.NumberTheory.NumberField.CanonicalEmbedding.ConvexBody import Mathlib.NumberTheory.NumberField.Units.Basic /-! # Dirichlet theorem on the group of units of a number field This file is devoted to the proof of Dirichlet unit theorem that states that the group of units `(𝓞 K)ˣ` of units of the ring of integers `𝓞 K` of a number field `K` modulo its torsion subgroup is a free `ℤ`-module of rank `card (InfinitePlace K) - 1`. ## Main definitions * `NumberField.Units.rank`: the unit rank of the number field `K`. * `NumberField.Units.fundSystem`: a fundamental system of units of `K`. * `NumberField.Units.basisModTorsion`: a `ℤ`-basis of `(𝓞 K)ˣ ⧸ (torsion K)` as an additive `ℤ`-module. ## Main results * `NumberField.Units.rank_modTorsion`: the `ℤ`-rank of `(𝓞 K)ˣ ⧸ (torsion K)` is equal to `card (InfinitePlace K) - 1`. * `NumberField.Units.exist_unique_eq_mul_prod`: **Dirichlet Unit Theorem**. Any unit of `𝓞 K` can be written uniquely as the product of a root of unity and powers of the units of the fundamental system `fundSystem`. ## Tags number field, units, Dirichlet unit theorem -/ open scoped NumberField noncomputable section open NumberField NumberField.InfinitePlace NumberField.Units variable (K : Type*) [Field K] namespace NumberField.Units.dirichletUnitTheorem /-! ### Dirichlet Unit Theorem We define a group morphism from `(𝓞 K)ˣ` to `logSpace K`, defined as `{w : InfinitePlace K // w ≠ w₀} → ℝ` where `w₀` is a distinguished (arbitrary) infinite place, prove that its kernel is the torsion subgroup (see `logEmbedding_eq_zero_iff`) and that its image, called `unitLattice`, is a full `ℤ`-lattice. It follows that `unitLattice` is a free `ℤ`-module (see `instModuleFree_unitLattice`) of rank `card (InfinitePlaces K) - 1` (see `unitLattice_rank`). To prove that the `unitLattice` is a full `ℤ`-lattice, we need to prove that it is discrete (see `unitLattice_inter_ball_finite`) and that it spans the full space over `ℝ` (see `unitLattice_span_eq_top`); this is the main part of the proof, see the section `span_top` below for more details. -/ open Finset variable {K} section NumberField variable [NumberField K] /-- The distinguished infinite place. -/ def w₀ : InfinitePlace K := (inferInstance : Nonempty (InfinitePlace K)).some variable (K) in /-- The `logSpace` is defined as `{w : InfinitePlace K // w ≠ w₀} → ℝ` where `w₀` is the distinguished infinite place. -/ abbrev logSpace := {w : InfinitePlace K // w ≠ w₀} → ℝ variable (K) in /-- The logarithmic embedding of the units (seen as an `Additive` group). -/ def _root_.NumberField.Units.logEmbedding : Additive ((𝓞 K)ˣ) →+ logSpace K := { toFun := fun x w => mult w.val * Real.log (w.val ↑x.toMul) map_zero' := by simp; rfl map_add' := fun _ _ => by simp [Real.log_mul, mul_add]; rfl } @[simp] theorem logEmbedding_component (x : (𝓞 K)ˣ) (w : {w : InfinitePlace K // w ≠ w₀}) : (logEmbedding K (Additive.ofMul x)) w = mult w.val * Real.log (w.val x) := rfl open scoped Classical in theorem sum_logEmbedding_component (x : (𝓞 K)ˣ) : ∑ w, logEmbedding K (Additive.ofMul x) w = - mult (w₀ : InfinitePlace K) * Real.log (w₀ (x : K)) := by have h := sum_mult_mul_log x rw [Fintype.sum_eq_add_sum_subtype_ne _ w₀, add_comm, add_eq_zero_iff_eq_neg, ← neg_mul] at h simpa [logEmbedding_component] using h end NumberField theorem mult_log_place_eq_zero {x : (𝓞 K)ˣ} {w : InfinitePlace K} : mult w * Real.log (w x) = 0 ↔ w x = 1 := by rw [mul_eq_zero, or_iff_right, Real.log_eq_zero, or_iff_right, or_iff_left] · linarith [(apply_nonneg _ _ : 0 ≤ w x)] · simp only [ne_eq, map_eq_zero, coe_ne_zero x, not_false_eq_true] · refine (ne_of_gt ?_) rw [mult]; split_ifs <;> norm_num variable [NumberField K] theorem logEmbedding_eq_zero_iff {x : (𝓞 K)ˣ} : logEmbedding K (Additive.ofMul x) = 0 ↔ x ∈ torsion K := by rw [mem_torsion] refine ⟨fun h w => ?_, fun h => ?_⟩ · by_cases hw : w = w₀ · suffices -mult w₀ * Real.log (w₀ (x : K)) = 0 by rw [neg_mul, neg_eq_zero, ← hw] at this exact mult_log_place_eq_zero.mp this rw [← sum_logEmbedding_component, sum_eq_zero] exact fun w _ => congrFun h w · exact mult_log_place_eq_zero.mp (congrFun h ⟨w, hw⟩) · ext w rw [logEmbedding_component, h w.val, Real.log_one, mul_zero, Pi.zero_apply] open scoped Classical in theorem logEmbedding_component_le {r : ℝ} {x : (𝓞 K)ˣ} (hr : 0 ≤ r) (h : ‖logEmbedding K x‖ ≤ r) (w : {w : InfinitePlace K // w ≠ w₀}) : |logEmbedding K (Additive.ofMul x) w| ≤ r := by lift r to NNReal using hr simp_rw [Pi.norm_def, NNReal.coe_le_coe, Finset.sup_le_iff, ← NNReal.coe_le_coe] at h exact h w (mem_univ _) open scoped Classical in theorem log_le_of_logEmbedding_le {r : ℝ} {x : (𝓞 K)ˣ} (hr : 0 ≤ r) (h : ‖logEmbedding K (Additive.ofMul x)‖ ≤ r) (w : InfinitePlace K) : |Real.log (w x)| ≤ (Fintype.card (InfinitePlace K)) * r := by have tool : ∀ x : ℝ, 0 ≤ x → x ≤ mult w * x := fun x hx => by nth_rw 1 [← one_mul x] refine mul_le_mul ?_ le_rfl hx ?_ all_goals { rw [mult]; split_ifs <;> norm_num } by_cases hw : w = w₀ · have hyp := congr_arg (‖·‖) (sum_logEmbedding_component x).symm replace hyp := (le_of_eq hyp).trans (norm_sum_le _ _) simp_rw [norm_mul, norm_neg, Real.norm_eq_abs, Nat.abs_cast] at hyp refine (le_trans ?_ hyp).trans ?_ · rw [← hw] exact tool _ (abs_nonneg _) · refine (sum_le_card_nsmul univ _ _ (fun w _ => logEmbedding_component_le hr h w)).trans ?_ rw [nsmul_eq_mul] refine mul_le_mul ?_ le_rfl hr (Fintype.card (InfinitePlace K)).cast_nonneg simp · have hyp := logEmbedding_component_le hr h ⟨w, hw⟩ rw [logEmbedding_component, abs_mul, Nat.abs_cast] at hyp refine (le_trans ?_ hyp).trans ?_ · exact tool _ (abs_nonneg _) · nth_rw 1 [← one_mul r] exact mul_le_mul (Nat.one_le_cast.mpr Fintype.card_pos) (le_of_eq rfl) hr (Nat.cast_nonneg _) variable (K) /-- The lattice formed by the image of the logarithmic embedding. -/ noncomputable def _root_.NumberField.Units.unitLattice : Submodule ℤ (logSpace K) := Submodule.map (logEmbedding K).toIntLinearMap ⊤ open scoped Classical in theorem unitLattice_inter_ball_finite (r : ℝ) : ((unitLattice K : Set (logSpace K)) ∩ Metric.closedBall 0 r).Finite := by obtain hr | hr := lt_or_le r 0 · convert Set.finite_empty rw [Metric.closedBall_eq_empty.mpr hr] exact Set.inter_empty _ · suffices {x : (𝓞 K)ˣ | IsIntegral ℤ (x : K) ∧ ∀ (φ : K →+* ℂ), ‖φ x‖ ≤ Real.exp ((Fintype.card (InfinitePlace K)) * r)}.Finite by refine (Set.Finite.image (logEmbedding K) this).subset ?_ rintro _ ⟨⟨x, ⟨_, rfl⟩⟩, hx⟩ refine ⟨x, ⟨x.val.prop, (le_iff_le _ _).mp (fun w => (Real.log_le_iff_le_exp ?_).mp ?_)⟩, rfl⟩ · exact pos_iff.mpr (coe_ne_zero x) · rw [mem_closedBall_zero_iff] at hx exact (le_abs_self _).trans (log_le_of_logEmbedding_le hr hx w) refine Set.Finite.of_finite_image ?_ (coe_injective K).injOn refine (Embeddings.finite_of_norm_le K ℂ (Real.exp ((Fintype.card (InfinitePlace K)) * r))).subset ?_ rintro _ ⟨x, ⟨⟨h_int, h_le⟩, rfl⟩⟩ exact ⟨h_int, h_le⟩ section span_top /-! #### Section `span_top` In this section, we prove that the span over `ℝ` of the `unitLattice` is equal to the full space. For this, we construct for each infinite place `w₁ ≠ w₀` a unit `u_w₁` of `K` such that, for all infinite places `w` such that `w ≠ w₁`, we have `Real.log w (u_w₁) < 0` (and thus `Real.log w₁ (u_w₁) > 0`). It follows then from a determinant computation (using `Matrix.det_ne_zero_of_sum_col_lt_diag`) that the image by `logEmbedding` of these units is a `ℝ`-linearly independent family. The unit `u_w₁` is obtained by constructing a sequence `seq n` of nonzero algebraic integers that is strictly decreasing at infinite places distinct from `w₁` and of norm `≤ B`. Since there are finitely many ideals of norm `≤ B`, there exists two term in the sequence defining the same ideal and their quotient is the desired unit `u_w₁` (see `exists_unit`). -/ open NumberField.mixedEmbedding NNReal variable (w₁ : InfinitePlace K) {B : ℕ} (hB : minkowskiBound K 1 < (convexBodyLTFactor K) * B) include hB in /-- This result shows that there always exists a next term in the sequence. -/ theorem seq_next {x : 𝓞 K} (hx : x ≠ 0) : ∃ y : 𝓞 K, y ≠ 0 ∧ (∀ w, w ≠ w₁ → w y < w x) ∧ |Algebra.norm ℚ (y : K)| ≤ B := by have hx' := RingOfIntegers.coe_ne_zero_iff.mpr hx let f : InfinitePlace K → ℝ≥0 := fun w => ⟨(w x) / 2, div_nonneg (AbsoluteValue.nonneg _ _) (by norm_num)⟩ suffices ∀ w, w ≠ w₁ → f w ≠ 0 by obtain ⟨g, h_geqf, h_gprod⟩ := adjust_f K B this obtain ⟨y, h_ynz, h_yle⟩ := exists_ne_zero_mem_ringOfIntegers_lt K (f := g) (by rw [convexBodyLT_volume]; convert hB; exact congr_arg ((↑) : NNReal → ENNReal) h_gprod) refine ⟨y, h_ynz, fun w hw => (h_geqf w hw ▸ h_yle w).trans ?_, ?_⟩ · rw [← Rat.cast_le (K := ℝ), Rat.cast_natCast] calc _ = ∏ w : InfinitePlace K, w (algebraMap _ K y) ^ mult w := (prod_eq_abs_norm (algebraMap _ K y)).symm _ ≤ ∏ w : InfinitePlace K, (g w : ℝ) ^ mult w := by gcongr with w; exact (h_yle w).le _ ≤ (B : ℝ) := by simp_rw [← NNReal.coe_pow, ← NNReal.coe_prod] exact le_of_eq (congr_arg toReal h_gprod) · refine div_lt_self ?_ (by norm_num) exact pos_iff.mpr hx' intro _ _ rw [ne_eq, Nonneg.mk_eq_zero, div_eq_zero_iff, map_eq_zero, not_or] exact ⟨hx', by norm_num⟩ /-- An infinite sequence of nonzero algebraic integers of `K` satisfying the following properties: • `seq n` is nonzero; • for `w : InfinitePlace K`, `w ≠ w₁ → w (seq n+1) < w (seq n)`; • `∣norm (seq n)∣ ≤ B`. -/ def seq : ℕ → { x : 𝓞 K // x ≠ 0 } | 0 => ⟨1, by norm_num⟩ | n + 1 => ⟨(seq_next K w₁ hB (seq n).prop).choose, (seq_next K w₁ hB (seq n).prop).choose_spec.1⟩ /-- The terms of the sequence are nonzero. -/ theorem seq_ne_zero (n : ℕ) : algebraMap (𝓞 K) K (seq K w₁ hB n) ≠ 0 := RingOfIntegers.coe_ne_zero_iff.mpr (seq K w₁ hB n).prop /-- The sequence is strictly decreasing at infinite places distinct from `w₁`. -/ theorem seq_decreasing {n m : ℕ} (h : n < m) (w : InfinitePlace K) (hw : w ≠ w₁) : w (algebraMap (𝓞 K) K (seq K w₁ hB m)) < w (algebraMap (𝓞 K) K (seq K w₁ hB n)) := by induction m with | zero => exfalso exact Nat.not_succ_le_zero n h | succ m m_ih => cases eq_or_lt_of_le (Nat.le_of_lt_succ h) with | inl hr => rw [hr] exact (seq_next K w₁ hB (seq K w₁ hB m).prop).choose_spec.2.1 w hw | inr hr => refine lt_trans ?_ (m_ih hr) exact (seq_next K w₁ hB (seq K w₁ hB m).prop).choose_spec.2.1 w hw /-- The terms of the sequence have norm bounded by `B`. -/ theorem seq_norm_le (n : ℕ) : Int.natAbs (Algebra.norm ℤ (seq K w₁ hB n : 𝓞 K)) ≤ B := by cases n with | zero => have : 1 ≤ B := by contrapose! hB simp only [Nat.lt_one_iff.mp hB, CharP.cast_eq_zero, mul_zero, zero_le] simp only [ne_eq, seq, map_one, Int.natAbs_one, this] | succ n => rw [← Nat.cast_le (α := ℚ), Int.cast_natAbs, Int.cast_abs, Algebra.coe_norm_int] exact (seq_next K w₁ hB (seq K w₁ hB n).prop).choose_spec.2.2 /-- Construct a unit associated to the place `w₁`. The family, for `w₁ ≠ w₀`, formed by the image by the `logEmbedding` of these units is `ℝ`-linearly independent, see `unitLattice_span_eq_top`. -/ theorem exists_unit (w₁ : InfinitePlace K) : ∃ u : (𝓞 K)ˣ, ∀ w : InfinitePlace K, w ≠ w₁ → Real.log (w u) < 0 := by obtain ⟨B, hB⟩ : ∃ B : ℕ, minkowskiBound K 1 < (convexBodyLTFactor K) * B := by conv => congr; ext; rw [mul_comm] exact ENNReal.exists_nat_mul_gt (ENNReal.coe_ne_zero.mpr (convexBodyLTFactor_ne_zero K)) (ne_of_lt (minkowskiBound_lt_top K 1)) rsuffices ⟨n, m, hnm, h⟩ : ∃ n m, n < m ∧ (Ideal.span ({ (seq K w₁ hB n : 𝓞 K) }) = Ideal.span ({ (seq K w₁ hB m : 𝓞 K) })) · have hu := Ideal.span_singleton_eq_span_singleton.mp h refine ⟨hu.choose, fun w hw => Real.log_neg ?_ ?_⟩ · exact pos_iff.mpr (coe_ne_zero _) · calc _ = w (algebraMap (𝓞 K) K (seq K w₁ hB m) * (algebraMap (𝓞 K) K (seq K w₁ hB n))⁻¹) := by rw [← congr_arg (algebraMap (𝓞 K) K) hu.choose_spec, mul_comm, map_mul (algebraMap _ _), ← mul_assoc, inv_mul_cancel₀ (seq_ne_zero K w₁ hB n), one_mul] _ = w (algebraMap (𝓞 K) K (seq K w₁ hB m)) * w (algebraMap (𝓞 K) K (seq K w₁ hB n))⁻¹ := map_mul _ _ _ _ < 1 := by rw [map_inv₀, mul_inv_lt_iff₀' (pos_iff.mpr (seq_ne_zero K w₁ hB n)), mul_one] exact seq_decreasing K w₁ hB hnm w hw refine Set.Finite.exists_lt_map_eq_of_forall_mem (t := {I : Ideal (𝓞 K) | Ideal.absNorm I ≤ B}) (fun n ↦ ?_) (Ideal.finite_setOf_absNorm_le B) rw [Set.mem_setOf_eq, Ideal.absNorm_span_singleton] exact seq_norm_le K w₁ hB n theorem unitLattice_span_eq_top : Submodule.span ℝ (unitLattice K : Set (logSpace K)) = ⊤ := by classical refine le_antisymm le_top ?_ -- The standard basis let B := Pi.basisFun ℝ {w : InfinitePlace K // w ≠ w₀}
-- The image by log_embedding of the family of units constructed above let v := fun w : { w : InfinitePlace K // w ≠ w₀ } => logEmbedding K (Additive.ofMul (exists_unit K w).choose) -- To prove the result, it is enough to prove that the family `v` is linearly independent suffices B.det v ≠ 0 by rw [← isUnit_iff_ne_zero, ← is_basis_iff_det] at this rw [← this.2] refine Submodule.span_monotone fun _ ⟨w, hw⟩ ↦ ⟨(exists_unit K w).choose, trivial, hw⟩ rw [Basis.det_apply] -- We use a specific lemma to prove that this determinant is nonzero refine det_ne_zero_of_sum_col_lt_diag (fun w => ?_) simp_rw [Real.norm_eq_abs, B, Basis.coePiBasisFun.toMatrix_eq_transpose, Matrix.transpose_apply] rw [← sub_pos, sum_congr rfl (fun x hx => abs_of_neg ?_), sum_neg_distrib, sub_neg_eq_add, sum_erase_eq_sub (mem_univ _), ← add_comm_sub] · refine add_pos_of_nonneg_of_pos ?_ ?_ · rw [sub_nonneg] exact le_abs_self _ · rw [sum_logEmbedding_component (exists_unit K w).choose] refine mul_pos_of_neg_of_neg ?_ ((exists_unit K w).choose_spec _ w.prop.symm) rw [mult]; split_ifs <;> norm_num · refine mul_neg_of_pos_of_neg ?_ ((exists_unit K w).choose_spec x ?_) · rw [mult]; split_ifs <;> norm_num · exact Subtype.ext_iff_val.not.mp (ne_of_mem_erase hx) end span_top end dirichletUnitTheorem
Mathlib/NumberTheory/NumberField/Units/DirichletTheorem.lean
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/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro -/ import Mathlib.MeasureTheory.MeasurableSpace.MeasurablyGenerated import Mathlib.MeasureTheory.Measure.NullMeasurable import Mathlib.Order.Interval.Set.Monotone /-! # Measure spaces The definition of a measure and a measure space are in `MeasureTheory.MeasureSpaceDef`, with only a few basic properties. This file provides many more properties of these objects. This separation allows the measurability tactic to import only the file `MeasureSpaceDef`, and to be available in `MeasureSpace` (through `MeasurableSpace`). Given a measurable space `α`, a measure on `α` is a function that sends measurable sets to the extended nonnegative reals that satisfies the following conditions: 1. `μ ∅ = 0`; 2. `μ` is countably additive. This means that the measure of a countable union of pairwise disjoint sets is equal to the measure of the individual sets. Every measure can be canonically extended to an outer measure, so that it assigns values to all subsets, not just the measurable subsets. On the other hand, a measure that is countably additive on measurable sets can be restricted to measurable sets to obtain a measure. In this file a measure is defined to be an outer measure that is countably additive on measurable sets, with the additional assumption that the outer measure is the canonical extension of the restricted measure. Measures on `α` form a complete lattice, and are closed under scalar multiplication with `ℝ≥0∞`. Given a measure, the null sets are the sets where `μ s = 0`, where `μ` denotes the corresponding outer measure (so `s` might not be measurable). We can then define the completion of `μ` as the measure on the least `σ`-algebra that also contains all null sets, by defining the measure to be `0` on the null sets. ## Main statements * `completion` is the completion of a measure to all null measurable sets. * `Measure.ofMeasurable` and `OuterMeasure.toMeasure` are two important ways to define a measure. ## Implementation notes Given `μ : Measure α`, `μ s` is the value of the *outer measure* applied to `s`. This conveniently allows us to apply the measure to sets without proving that they are measurable. We get countable subadditivity for all sets, but only countable additivity for measurable sets. You often don't want to define a measure via its constructor. Two ways that are sometimes more convenient: * `Measure.ofMeasurable` is a way to define a measure by only giving its value on measurable sets and proving the properties (1) and (2) mentioned above. * `OuterMeasure.toMeasure` is a way of obtaining a measure from an outer measure by showing that all measurable sets in the measurable space are Carathéodory measurable. To prove that two measures are equal, there are multiple options: * `ext`: two measures are equal if they are equal on all measurable sets. * `ext_of_generateFrom_of_iUnion`: two measures are equal if they are equal on a π-system generating the measurable sets, if the π-system contains a spanning increasing sequence of sets where the measures take finite value (in particular the measures are σ-finite). This is a special case of the more general `ext_of_generateFrom_of_cover` * `ext_of_generate_finite`: two finite measures are equal if they are equal on a π-system generating the measurable sets. This is a special case of `ext_of_generateFrom_of_iUnion` using `C ∪ {univ}`, but is easier to work with. A `MeasureSpace` is a class that is a measurable space with a canonical measure. The measure is denoted `volume`. ## References * <https://en.wikipedia.org/wiki/Measure_(mathematics)> * <https://en.wikipedia.org/wiki/Complete_measure> * <https://en.wikipedia.org/wiki/Almost_everywhere> ## Tags measure, almost everywhere, measure space, completion, null set, null measurable set -/ noncomputable section open Set open Filter hiding map open Function MeasurableSpace Topology Filter ENNReal NNReal Interval MeasureTheory open scoped symmDiff variable {α β γ δ ι R R' : Type*} namespace MeasureTheory section variable {m : MeasurableSpace α} {μ μ₁ μ₂ : Measure α} {s s₁ s₂ t : Set α} instance ae_isMeasurablyGenerated : IsMeasurablyGenerated (ae μ) := ⟨fun _s hs => let ⟨t, hst, htm, htμ⟩ := exists_measurable_superset_of_null hs ⟨tᶜ, compl_mem_ae_iff.2 htμ, htm.compl, compl_subset_comm.1 hst⟩⟩ /-- See also `MeasureTheory.ae_restrict_uIoc_iff`. -/ theorem ae_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} : (∀ᵐ x ∂μ, x ∈ Ι a b → P x) ↔ (∀ᵐ x ∂μ, x ∈ Ioc a b → P x) ∧ ∀ᵐ x ∂μ, x ∈ Ioc b a → P x := by simp only [uIoc_eq_union, mem_union, or_imp, eventually_and] theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ := measure_union₀ h.nullMeasurableSet hd.aedisjoint theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ := measure_union₀' h.nullMeasurableSet hd.aedisjoint theorem measure_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ (s ∩ t) + μ (s \ t) = μ s := measure_inter_add_diff₀ _ ht.nullMeasurableSet theorem measure_diff_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s \ t) + μ (s ∩ t) = μ s := (add_comm _ _).trans (measure_inter_add_diff s ht) theorem measure_diff_eq_top (hs : μ s = ∞) (ht : μ t ≠ ∞) : μ (s \ t) = ∞ := by contrapose! hs exact ((measure_mono (subset_diff_union s t)).trans_lt ((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.2 ⟨hs.lt_top, ht.lt_top⟩))).ne theorem measure_union_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by rw [← measure_inter_add_diff (s ∪ t) ht, Set.union_inter_cancel_right, union_diff_right, ← measure_inter_add_diff s ht] ac_rfl theorem measure_union_add_inter' (hs : MeasurableSet s) (t : Set α) : μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by rw [union_comm, inter_comm, measure_union_add_inter t hs, add_comm] lemma measure_symmDiff_eq (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) : μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by simpa only [symmDiff_def, sup_eq_union] using measure_union₀ (ht.diff hs) disjoint_sdiff_sdiff.aedisjoint lemma measure_symmDiff_le (s t u : Set α) : μ (s ∆ u) ≤ μ (s ∆ t) + μ (t ∆ u) := le_trans (μ.mono <| symmDiff_triangle s t u) (measure_union_le (s ∆ t) (t ∆ u)) theorem measure_symmDiff_eq_top (hs : μ s ≠ ∞) (ht : μ t = ∞) : μ (s ∆ t) = ∞ := measure_mono_top subset_union_right (measure_diff_eq_top ht hs) theorem measure_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ := measure_add_measure_compl₀ h.nullMeasurableSet theorem measure_biUnion₀ {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.Pairwise (AEDisjoint μ on f)) (h : ∀ b ∈ s, NullMeasurableSet (f b) μ) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := by haveI := hs.toEncodable rw [biUnion_eq_iUnion] exact measure_iUnion₀ (hd.on_injective Subtype.coe_injective fun x => x.2) fun x => h x x.2 theorem measure_biUnion {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.PairwiseDisjoint f) (h : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := measure_biUnion₀ hs hd.aedisjoint fun b hb => (h b hb).nullMeasurableSet theorem measure_sUnion₀ {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise (AEDisjoint μ)) (h : ∀ s ∈ S, NullMeasurableSet s μ) : μ (⋃₀ S) = ∑' s : S, μ s := by rw [sUnion_eq_biUnion, measure_biUnion₀ hs hd h] theorem measure_sUnion {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise Disjoint) (h : ∀ s ∈ S, MeasurableSet s) : μ (⋃₀ S) = ∑' s : S, μ s := by rw [sUnion_eq_biUnion, measure_biUnion hs hd h] theorem measure_biUnion_finset₀ {s : Finset ι} {f : ι → Set α} (hd : Set.Pairwise (↑s) (AEDisjoint μ on f)) (hm : ∀ b ∈ s, NullMeasurableSet (f b) μ) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := by rw [← Finset.sum_attach, Finset.attach_eq_univ, ← tsum_fintype] exact measure_biUnion₀ s.countable_toSet hd hm theorem measure_biUnion_finset {s : Finset ι} {f : ι → Set α} (hd : PairwiseDisjoint (↑s) f) (hm : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := measure_biUnion_finset₀ hd.aedisjoint fun b hb => (hm b hb).nullMeasurableSet /-- The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least the sum of the measures of the sets. -/ theorem tsum_meas_le_meas_iUnion_of_disjoint₀ {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α) {As : ι → Set α} (As_mble : ∀ i : ι, NullMeasurableSet (As i) μ) (As_disj : Pairwise (AEDisjoint μ on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := by rw [ENNReal.tsum_eq_iSup_sum, iSup_le_iff] intro s simp only [← measure_biUnion_finset₀ (fun _i _hi _j _hj hij => As_disj hij) fun i _ => As_mble i] gcongr exact iUnion_subset fun _ ↦ Subset.rfl /-- The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of the measures of the sets. -/ theorem tsum_meas_le_meas_iUnion_of_disjoint {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α) {As : ι → Set α} (As_mble : ∀ i : ι, MeasurableSet (As i)) (As_disj : Pairwise (Disjoint on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := tsum_meas_le_meas_iUnion_of_disjoint₀ μ (fun i ↦ (As_mble i).nullMeasurableSet) (fun _ _ h ↦ Disjoint.aedisjoint (As_disj h)) /-- If `s` is a countable set, then the measure of its preimage can be found as the sum of measures of the fibers `f ⁻¹' {y}`. -/ theorem tsum_measure_preimage_singleton {s : Set β} (hs : s.Countable) {f : α → β} (hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑' b : s, μ (f ⁻¹' {↑b})) = μ (f ⁻¹' s) := by rw [← Set.biUnion_preimage_singleton, measure_biUnion hs (pairwiseDisjoint_fiber f s) hf] lemma measure_preimage_eq_zero_iff_of_countable {s : Set β} {f : α → β} (hs : s.Countable) : μ (f ⁻¹' s) = 0 ↔ ∀ x ∈ s, μ (f ⁻¹' {x}) = 0 := by rw [← biUnion_preimage_singleton, measure_biUnion_null_iff hs] /-- If `s` is a `Finset`, then the measure of its preimage can be found as the sum of measures of the fibers `f ⁻¹' {y}`. -/ theorem sum_measure_preimage_singleton (s : Finset β) {f : α → β} (hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑ b ∈ s, μ (f ⁻¹' {b})) = μ (f ⁻¹' ↑s) := by simp only [← measure_biUnion_finset (pairwiseDisjoint_fiber f s) hf, Finset.set_biUnion_preimage_singleton] @[simp] lemma sum_measure_singleton {s : Finset α} [MeasurableSingletonClass α] : ∑ x ∈ s, μ {x} = μ s := by trans ∑ x ∈ s, μ (id ⁻¹' {x}) · simp rw [sum_measure_preimage_singleton] · simp · simp theorem measure_diff_null' (h : μ (s₁ ∩ s₂) = 0) : μ (s₁ \ s₂) = μ s₁ := measure_congr <| diff_ae_eq_self.2 h theorem measure_add_diff (hs : NullMeasurableSet s μ) (t : Set α) : μ s + μ (t \ s) = μ (s ∪ t) := by rw [← measure_union₀' hs disjoint_sdiff_right.aedisjoint, union_diff_self] theorem measure_diff' (s : Set α) (hm : NullMeasurableSet t μ) (h_fin : μ t ≠ ∞) : μ (s \ t) = μ (s ∪ t) - μ t := ENNReal.eq_sub_of_add_eq h_fin <| by rw [add_comm, measure_add_diff hm, union_comm] theorem measure_diff (h : s₂ ⊆ s₁) (h₂ : NullMeasurableSet s₂ μ) (h_fin : μ s₂ ≠ ∞) : μ (s₁ \ s₂) = μ s₁ - μ s₂ := by rw [measure_diff' _ h₂ h_fin, union_eq_self_of_subset_right h] theorem le_measure_diff : μ s₁ - μ s₂ ≤ μ (s₁ \ s₂) := tsub_le_iff_left.2 <| (measure_le_inter_add_diff μ s₁ s₂).trans <| by gcongr; apply inter_subset_right /-- If the measure of the symmetric difference of two sets is finite, then one has infinite measure if and only if the other one does. -/ theorem measure_eq_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s = ∞ ↔ μ t = ∞ := by suffices h : ∀ u v, μ (u ∆ v) ≠ ∞ → μ u = ∞ → μ v = ∞ from ⟨h s t hμst, h t s (symmDiff_comm s t ▸ hμst)⟩ intro u v hμuv hμu by_contra! hμv apply hμuv rw [Set.symmDiff_def, eq_top_iff] calc ∞ = μ u - μ v := by rw [ENNReal.sub_eq_top_iff.2 ⟨hμu, hμv⟩] _ ≤ μ (u \ v) := le_measure_diff _ ≤ μ (u \ v ∪ v \ u) := measure_mono subset_union_left /-- If the measure of the symmetric difference of two sets is finite, then one has finite measure if and only if the other one does. -/ theorem measure_ne_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s ≠ ∞ ↔ μ t ≠ ∞ := (measure_eq_top_iff_of_symmDiff hμst).ne theorem measure_diff_lt_of_lt_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞) {ε : ℝ≥0∞} (h : μ t < μ s + ε) : μ (t \ s) < ε := by rw [measure_diff hst hs hs']; rw [add_comm] at h exact ENNReal.sub_lt_of_lt_add (measure_mono hst) h theorem measure_diff_le_iff_le_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞) {ε : ℝ≥0∞} : μ (t \ s) ≤ ε ↔ μ t ≤ μ s + ε := by rw [measure_diff hst hs hs', tsub_le_iff_left] theorem measure_eq_measure_of_null_diff {s t : Set α} (hst : s ⊆ t) (h_nulldiff : μ (t \ s) = 0) : μ s = μ t := measure_congr <| EventuallyLE.antisymm (HasSubset.Subset.eventuallyLE hst) (ae_le_set.mpr h_nulldiff) theorem measure_eq_measure_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ ∧ μ s₂ = μ s₃ := by have le12 : μ s₁ ≤ μ s₂ := measure_mono h12 have le23 : μ s₂ ≤ μ s₃ := measure_mono h23 have key : μ s₃ ≤ μ s₁ := calc μ s₃ = μ (s₃ \ s₁ ∪ s₁) := by rw [diff_union_of_subset (h12.trans h23)] _ ≤ μ (s₃ \ s₁) + μ s₁ := measure_union_le _ _ _ = μ s₁ := by simp only [h_nulldiff, zero_add] exact ⟨le12.antisymm (le23.trans key), le23.antisymm (key.trans le12)⟩ theorem measure_eq_measure_smaller_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ := (measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).1 theorem measure_eq_measure_larger_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₂ = μ s₃ := (measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).2 lemma measure_compl₀ (h : NullMeasurableSet s μ) (hs : μ s ≠ ∞) : μ sᶜ = μ Set.univ - μ s := by rw [← measure_add_measure_compl₀ h, ENNReal.add_sub_cancel_left hs] theorem measure_compl (h₁ : MeasurableSet s) (h_fin : μ s ≠ ∞) : μ sᶜ = μ univ - μ s := measure_compl₀ h₁.nullMeasurableSet h_fin lemma measure_inter_conull' (ht : μ (s \ t) = 0) : μ (s ∩ t) = μ s := by rw [← diff_compl, measure_diff_null']; rwa [← diff_eq] lemma measure_inter_conull (ht : μ tᶜ = 0) : μ (s ∩ t) = μ s := by rw [← diff_compl, measure_diff_null ht] @[simp] theorem union_ae_eq_left_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] s ↔ t ≤ᵐ[μ] s := by rw [ae_le_set] refine ⟨fun h => by simpa only [union_diff_left] using (ae_eq_set.mp h).1, fun h => eventuallyLE_antisymm_iff.mpr ⟨by rwa [ae_le_set, union_diff_left], HasSubset.Subset.eventuallyLE subset_union_left⟩⟩ @[simp] theorem union_ae_eq_right_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] t ↔ s ≤ᵐ[μ] t := by rw [union_comm, union_ae_eq_left_iff_ae_subset] theorem ae_eq_of_ae_subset_of_measure_ge (h₁ : s ≤ᵐ[μ] t) (h₂ : μ t ≤ μ s) (hsm : NullMeasurableSet s μ) (ht : μ t ≠ ∞) : s =ᵐ[μ] t := by refine eventuallyLE_antisymm_iff.mpr ⟨h₁, ae_le_set.mpr ?_⟩ replace h₂ : μ t = μ s := h₂.antisymm (measure_mono_ae h₁) replace ht : μ s ≠ ∞ := h₂ ▸ ht rw [measure_diff' t hsm ht, measure_congr (union_ae_eq_left_iff_ae_subset.mpr h₁), h₂, tsub_self] /-- If `s ⊆ t`, `μ t ≤ μ s`, `μ t ≠ ∞`, and `s` is measurable, then `s =ᵐ[μ] t`. -/ theorem ae_eq_of_subset_of_measure_ge (h₁ : s ⊆ t) (h₂ : μ t ≤ μ s) (hsm : NullMeasurableSet s μ) (ht : μ t ≠ ∞) : s =ᵐ[μ] t := ae_eq_of_ae_subset_of_measure_ge (HasSubset.Subset.eventuallyLE h₁) h₂ hsm ht theorem measure_iUnion_congr_of_subset {ι : Sort*} [Countable ι] {s : ι → Set α} {t : ι → Set α} (hsub : ∀ i, s i ⊆ t i) (h_le : ∀ i, μ (t i) ≤ μ (s i)) : μ (⋃ i, s i) = μ (⋃ i, t i) := by refine le_antisymm (by gcongr; apply hsub) ?_ rcases Classical.em (∃ i, μ (t i) = ∞) with (⟨i, hi⟩ | htop) · calc μ (⋃ i, t i) ≤ ∞ := le_top _ ≤ μ (s i) := hi ▸ h_le i _ ≤ μ (⋃ i, s i) := measure_mono <| subset_iUnion _ _ push_neg at htop set M := toMeasurable μ have H : ∀ b, (M (t b) ∩ M (⋃ b, s b) : Set α) =ᵐ[μ] M (t b) := by refine fun b => ae_eq_of_subset_of_measure_ge inter_subset_left ?_ ?_ ?_ · calc μ (M (t b)) = μ (t b) := measure_toMeasurable _ _ ≤ μ (s b) := h_le b _ ≤ μ (M (t b) ∩ M (⋃ b, s b)) := measure_mono <| subset_inter ((hsub b).trans <| subset_toMeasurable _ _) ((subset_iUnion _ _).trans <| subset_toMeasurable _ _) · measurability · rw [measure_toMeasurable] exact htop b calc μ (⋃ b, t b) ≤ μ (⋃ b, M (t b)) := measure_mono (iUnion_mono fun b => subset_toMeasurable _ _) _ = μ (⋃ b, M (t b) ∩ M (⋃ b, s b)) := measure_congr (EventuallyEq.countable_iUnion H).symm _ ≤ μ (M (⋃ b, s b)) := measure_mono (iUnion_subset fun b => inter_subset_right) _ = μ (⋃ b, s b) := measure_toMeasurable _ theorem measure_union_congr_of_subset {t₁ t₂ : Set α} (hs : s₁ ⊆ s₂) (hsμ : μ s₂ ≤ μ s₁) (ht : t₁ ⊆ t₂) (htμ : μ t₂ ≤ μ t₁) : μ (s₁ ∪ t₁) = μ (s₂ ∪ t₂) := by rw [union_eq_iUnion, union_eq_iUnion] exact measure_iUnion_congr_of_subset (Bool.forall_bool.2 ⟨ht, hs⟩) (Bool.forall_bool.2 ⟨htμ, hsμ⟩) @[simp] theorem measure_iUnion_toMeasurable {ι : Sort*} [Countable ι] (s : ι → Set α) : μ (⋃ i, toMeasurable μ (s i)) = μ (⋃ i, s i) := Eq.symm <| measure_iUnion_congr_of_subset (fun _i => subset_toMeasurable _ _) fun _i ↦ (measure_toMeasurable _).le theorem measure_biUnion_toMeasurable {I : Set β} (hc : I.Countable) (s : β → Set α) : μ (⋃ b ∈ I, toMeasurable μ (s b)) = μ (⋃ b ∈ I, s b) := by haveI := hc.toEncodable simp only [biUnion_eq_iUnion, measure_iUnion_toMeasurable] @[simp] theorem measure_toMeasurable_union : μ (toMeasurable μ s ∪ t) = μ (s ∪ t) := Eq.symm <| measure_union_congr_of_subset (subset_toMeasurable _ _) (measure_toMeasurable _).le Subset.rfl le_rfl @[simp] theorem measure_union_toMeasurable : μ (s ∪ toMeasurable μ t) = μ (s ∪ t) := Eq.symm <| measure_union_congr_of_subset Subset.rfl le_rfl (subset_toMeasurable _ _) (measure_toMeasurable _).le theorem sum_measure_le_measure_univ {s : Finset ι} {t : ι → Set α} (h : ∀ i ∈ s, NullMeasurableSet (t i) μ) (H : Set.Pairwise s (AEDisjoint μ on t)) : (∑ i ∈ s, μ (t i)) ≤ μ (univ : Set α) := by rw [← measure_biUnion_finset₀ H h] exact measure_mono (subset_univ _) theorem tsum_measure_le_measure_univ {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (H : Pairwise (AEDisjoint μ on s)) : ∑' i, μ (s i) ≤ μ (univ : Set α) := by rw [ENNReal.tsum_eq_iSup_sum] exact iSup_le fun s => sum_measure_le_measure_univ (fun i _hi => hs i) fun i _hi j _hj hij => H hij /-- Pigeonhole principle for measure spaces: if `∑' i, μ (s i) > μ univ`, then one of the intersections `s i ∩ s j` is not empty. -/ theorem exists_nonempty_inter_of_measure_univ_lt_tsum_measure {m : MeasurableSpace α} (μ : Measure α) {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (H : μ (univ : Set α) < ∑' i, μ (s i)) : ∃ i j, i ≠ j ∧ (s i ∩ s j).Nonempty := by contrapose! H apply tsum_measure_le_measure_univ hs intro i j hij exact (disjoint_iff_inter_eq_empty.mpr (H i j hij)).aedisjoint /-- Pigeonhole principle for measure spaces: if `s` is a `Finset` and `∑ i ∈ s, μ (t i) > μ univ`, then one of the intersections `t i ∩ t j` is not empty. -/ theorem exists_nonempty_inter_of_measure_univ_lt_sum_measure {m : MeasurableSpace α} (μ : Measure α) {s : Finset ι} {t : ι → Set α} (h : ∀ i ∈ s, NullMeasurableSet (t i) μ) (H : μ (univ : Set α) < ∑ i ∈ s, μ (t i)) : ∃ i ∈ s, ∃ j ∈ s, ∃ _h : i ≠ j, (t i ∩ t j).Nonempty := by contrapose! H apply sum_measure_le_measure_univ h intro i hi j hj hij exact (disjoint_iff_inter_eq_empty.mpr (H i hi j hj hij)).aedisjoint /-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`, then `s` intersects `t`. Version assuming that `t` is measurable. -/ theorem nonempty_inter_of_measure_lt_add {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α} (ht : MeasurableSet t) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) : (s ∩ t).Nonempty := by rw [← Set.not_disjoint_iff_nonempty_inter] contrapose! h calc μ s + μ t = μ (s ∪ t) := (measure_union h ht).symm _ ≤ μ u := measure_mono (union_subset h's h't) /-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`, then `s` intersects `t`. Version assuming that `s` is measurable. -/ theorem nonempty_inter_of_measure_lt_add' {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α} (hs : MeasurableSet s) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) : (s ∩ t).Nonempty := by rw [add_comm] at h rw [inter_comm] exact nonempty_inter_of_measure_lt_add μ hs h't h's h /-- Continuity from below: the measure of the union of a directed sequence of (not necessarily measurable) sets is the supremum of the measures. -/ theorem _root_.Directed.measure_iUnion [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) : μ (⋃ i, s i) = ⨆ i, μ (s i) := by -- WLOG, `ι = ℕ` rcases Countable.exists_injective_nat ι with ⟨e, he⟩ generalize ht : Function.extend e s ⊥ = t replace hd : Directed (· ⊆ ·) t := ht ▸ hd.extend_bot he suffices μ (⋃ n, t n) = ⨆ n, μ (t n) by simp only [← ht, Function.apply_extend μ, ← iSup_eq_iUnion, iSup_extend_bot he, Function.comp_def, Pi.bot_apply, bot_eq_empty, measure_empty] at this exact this.trans (iSup_extend_bot he _) clear! ι -- The `≥` inequality is trivial refine le_antisymm ?_ (iSup_le fun i ↦ measure_mono <| subset_iUnion _ _) -- Choose `T n ⊇ t n` of the same measure, put `Td n = disjointed T` set T : ℕ → Set α := fun n => toMeasurable μ (t n) set Td : ℕ → Set α := disjointed T have hm : ∀ n, MeasurableSet (Td n) := .disjointed fun n ↦ measurableSet_toMeasurable _ _ calc μ (⋃ n, t n) = μ (⋃ n, Td n) := by rw [iUnion_disjointed, measure_iUnion_toMeasurable] _ ≤ ∑' n, μ (Td n) := measure_iUnion_le _ _ = ⨆ I : Finset ℕ, ∑ n ∈ I, μ (Td n) := ENNReal.tsum_eq_iSup_sum _ ≤ ⨆ n, μ (t n) := iSup_le fun I => by rcases hd.finset_le I with ⟨N, hN⟩ calc (∑ n ∈ I, μ (Td n)) = μ (⋃ n ∈ I, Td n) := (measure_biUnion_finset ((disjoint_disjointed T).set_pairwise I) fun n _ => hm n).symm _ ≤ μ (⋃ n ∈ I, T n) := measure_mono (iUnion₂_mono fun n _hn => disjointed_subset _ _) _ = μ (⋃ n ∈ I, t n) := measure_biUnion_toMeasurable I.countable_toSet _ _ ≤ μ (t N) := measure_mono (iUnion₂_subset hN) _ ≤ ⨆ n, μ (t n) := le_iSup (μ ∘ t) N /-- Continuity from below: the measure of the union of a monotone family of sets is equal to the supremum of their measures. The theorem assumes that the `atTop` filter on the index set is countably generated, so it works for a family indexed by a countable type, as well as `ℝ`. -/ theorem _root_.Monotone.measure_iUnion [Preorder ι] [IsDirected ι (· ≤ ·)] [(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s) : μ (⋃ i, s i) = ⨆ i, μ (s i) := by cases isEmpty_or_nonempty ι with | inl _ => simp | inr _ => rcases exists_seq_monotone_tendsto_atTop_atTop ι with ⟨x, hxm, hx⟩ rw [← hs.iUnion_comp_tendsto_atTop hx, ← Monotone.iSup_comp_tendsto_atTop _ hx] exacts [(hs.comp hxm).directed_le.measure_iUnion, fun _ _ h ↦ measure_mono (hs h)] theorem _root_.Antitone.measure_iUnion [Preorder ι] [IsDirected ι (· ≥ ·)] [(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s) : μ (⋃ i, s i) = ⨆ i, μ (s i) := hs.dual_left.measure_iUnion /-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the supremum of the measures of the partial unions. -/ theorem measure_iUnion_eq_iSup_accumulate [Preorder ι] [IsDirected ι (· ≤ ·)] [(atTop : Filter ι).IsCountablyGenerated] {f : ι → Set α} : μ (⋃ i, f i) = ⨆ i, μ (Accumulate f i) := by rw [← iUnion_accumulate] exact monotone_accumulate.measure_iUnion theorem measure_biUnion_eq_iSup {s : ι → Set α} {t : Set ι} (ht : t.Countable) (hd : DirectedOn ((· ⊆ ·) on s) t) : μ (⋃ i ∈ t, s i) = ⨆ i ∈ t, μ (s i) := by haveI := ht.to_subtype rw [biUnion_eq_iUnion, hd.directed_val.measure_iUnion, ← iSup_subtype''] /-- **Continuity from above**: the measure of the intersection of a directed downwards countable family of measurable sets is the infimum of the measures. -/ theorem _root_.Directed.measure_iInter [Countable ι] {s : ι → Set α} (h : ∀ i, NullMeasurableSet (s i) μ) (hd : Directed (· ⊇ ·) s) (hfin : ∃ i, μ (s i) ≠ ∞) : μ (⋂ i, s i) = ⨅ i, μ (s i) := by rcases hfin with ⟨k, hk⟩ have : ∀ t ⊆ s k, μ t ≠ ∞ := fun t ht => ne_top_of_le_ne_top hk (measure_mono ht) rw [← ENNReal.sub_sub_cancel hk (iInf_le (fun i => μ (s i)) k), ENNReal.sub_iInf, ← ENNReal.sub_sub_cancel hk (measure_mono (iInter_subset _ k)), ← measure_diff (iInter_subset _ k) (.iInter h) (this _ (iInter_subset _ k)), diff_iInter, Directed.measure_iUnion] · congr 1 refine le_antisymm (iSup_mono' fun i => ?_) (iSup_mono fun i => le_measure_diff) rcases hd i k with ⟨j, hji, hjk⟩ use j rw [← measure_diff hjk (h _) (this _ hjk)] gcongr · exact hd.mono_comp _ fun _ _ => diff_subset_diff_right /-- **Continuity from above**: the measure of the intersection of a monotone family of measurable sets indexed by a type with countably generated `atBot` filter is equal to the infimum of the measures. -/ theorem _root_.Monotone.measure_iInter [Preorder ι] [IsDirected ι (· ≥ ·)] [(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s) (hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) : μ (⋂ i, s i) = ⨅ i, μ (s i) := by refine le_antisymm (le_iInf fun i ↦ measure_mono <| iInter_subset _ _) ?_ have := hfin.nonempty rcases exists_seq_antitone_tendsto_atTop_atBot ι with ⟨x, hxm, hx⟩ calc ⨅ i, μ (s i) ≤ ⨅ n, μ (s (x n)) := le_iInf_comp (μ ∘ s) x _ = μ (⋂ n, s (x n)) := by refine .symm <| (hs.comp_antitone hxm).directed_ge.measure_iInter (fun n ↦ hsm _) ?_ rcases hfin with ⟨k, hk⟩ rcases (hx.eventually_le_atBot k).exists with ⟨n, hn⟩ exact ⟨n, ne_top_of_le_ne_top hk <| measure_mono <| hs hn⟩ _ ≤ μ (⋂ i, s i) := by refine measure_mono <| iInter_mono' fun i ↦ ?_ rcases (hx.eventually_le_atBot i).exists with ⟨n, hn⟩ exact ⟨n, hs hn⟩ /-- **Continuity from above**: the measure of the intersection of an antitone family of measurable sets indexed by a type with countably generated `atTop` filter is equal to the infimum of the measures. -/ theorem _root_.Antitone.measure_iInter [Preorder ι] [IsDirected ι (· ≤ ·)] [(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s) (hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) : μ (⋂ i, s i) = ⨅ i, μ (s i) := hs.dual_left.measure_iInter hsm hfin /-- Continuity from above: the measure of the intersection of a sequence of measurable sets is the infimum of the measures of the partial intersections. -/ theorem measure_iInter_eq_iInf_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α} [Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)] {f : ι → Set α} (h : ∀ i, NullMeasurableSet (f i) μ) (hfin : ∃ i, μ (f i) ≠ ∞) : μ (⋂ i, f i) = ⨅ i, μ (⋂ j ≤ i, f j) := by rw [← Antitone.measure_iInter] · rw [iInter_comm] exact congrArg μ <| iInter_congr fun i ↦ (biInf_const nonempty_Ici).symm · exact fun i j h ↦ biInter_mono (Iic_subset_Iic.2 h) fun _ _ ↦ Set.Subset.rfl · exact fun i ↦ .biInter (to_countable _) fun _ _ ↦ h _ · refine hfin.imp fun k hk ↦ ne_top_of_le_ne_top hk <| measure_mono <| iInter₂_subset k ?_ rfl /-- Continuity from below: the measure of the union of an increasing sequence of (not necessarily measurable) sets is the limit of the measures. -/ theorem tendsto_measure_iUnion_atTop [Preorder ι] [IsCountablyGenerated (atTop : Filter ι)] {s : ι → Set α} (hm : Monotone s) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋃ n, s n))) := by refine .of_neBot_imp fun h ↦ ?_ have := (atTop_neBot_iff.1 h).2 rw [hm.measure_iUnion] exact tendsto_atTop_iSup fun n m hnm => measure_mono <| hm hnm theorem tendsto_measure_iUnion_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)] {s : ι → Set α} (hm : Antitone s) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋃ n, s n))) := tendsto_measure_iUnion_atTop (ι := ιᵒᵈ) hm.dual_left /-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the limit of the measures of the partial unions. -/ theorem tendsto_measure_iUnion_accumulate {α ι : Type*} [Preorder ι] [IsCountablyGenerated (atTop : Filter ι)] {_ : MeasurableSpace α} {μ : Measure α} {f : ι → Set α} : Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by refine .of_neBot_imp fun h ↦ ?_ have := (atTop_neBot_iff.1 h).2 rw [measure_iUnion_eq_iSup_accumulate] exact tendsto_atTop_iSup fun i j hij ↦ by gcongr /-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable sets is the limit of the measures. -/ theorem tendsto_measure_iInter_atTop [Preorder ι] [IsCountablyGenerated (atTop : Filter ι)] {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Antitone s) (hf : ∃ i, μ (s i) ≠ ∞) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋂ n, s n))) := by refine .of_neBot_imp fun h ↦ ?_ have := (atTop_neBot_iff.1 h).2 rw [hm.measure_iInter hs hf] exact tendsto_atTop_iInf fun n m hnm => measure_mono <| hm hnm /-- Continuity from above: the measure of the intersection of an increasing sequence of measurable sets is the limit of the measures. -/ theorem tendsto_measure_iInter_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)] {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Monotone s) (hf : ∃ i, μ (s i) ≠ ∞) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋂ n, s n))) := tendsto_measure_iInter_atTop (ι := ιᵒᵈ) hs hm.dual_left hf /-- Continuity from above: the measure of the intersection of a sequence of measurable sets such that one has finite measure is the limit of the measures of the partial intersections. -/ theorem tendsto_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α} [Countable ι] [Preorder ι] {f : ι → Set α} (hm : ∀ i, NullMeasurableSet (f i) μ) (hf : ∃ i, μ (f i) ≠ ∞) : Tendsto (fun i ↦ μ (⋂ j ≤ i, f j)) atTop (𝓝 (μ (⋂ i, f i))) := by refine .of_neBot_imp fun hne ↦ ?_ cases atTop_neBot_iff.mp hne rw [measure_iInter_eq_iInf_measure_iInter_le hm hf] exact tendsto_atTop_iInf fun i j hij ↦ measure_mono <| biInter_subset_biInter_left fun k hki ↦ le_trans hki hij /-- Some version of continuity of a measure in the empty set using the intersection along a set of sets. -/ theorem exists_measure_iInter_lt {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α} [SemilatticeSup ι] [Countable ι] {f : ι → Set α} (hm : ∀ i, NullMeasurableSet (f i) μ) {ε : ℝ≥0∞} (hε : 0 < ε) (hfin : ∃ i, μ (f i) ≠ ∞) (hfem : ⋂ n, f n = ∅) : ∃ m, μ (⋂ n ≤ m, f n) < ε := by let F m := μ (⋂ n ≤ m, f n) have hFAnti : Antitone F := fun i j hij => measure_mono (biInter_subset_biInter_left fun k hki => le_trans hki hij) suffices Filter.Tendsto F Filter.atTop (𝓝 0) by rw [@ENNReal.tendsto_atTop_zero_iff_lt_of_antitone _ (nonempty_of_exists hfin) _ _ hFAnti] at this exact this ε hε have hzero : μ (⋂ n, f n) = 0 := by simp only [hfem, measure_empty] rw [← hzero] exact tendsto_measure_iInter_le hm hfin /-- The measure of the intersection of a decreasing sequence of measurable sets indexed by a linear order with first countable topology is the limit of the measures. -/ theorem tendsto_measure_biInter_gt {ι : Type*} [LinearOrder ι] [TopologicalSpace ι] [OrderTopology ι] [DenselyOrdered ι] [FirstCountableTopology ι] {s : ι → Set α} {a : ι} (hs : ∀ r > a, NullMeasurableSet (s r) μ) (hm : ∀ i j, a < i → i ≤ j → s i ⊆ s j) (hf : ∃ r > a, μ (s r) ≠ ∞) : Tendsto (μ ∘ s) (𝓝[Ioi a] a) (𝓝 (μ (⋂ r > a, s r))) := by have : (atBot : Filter (Ioi a)).IsCountablyGenerated := by rw [← comap_coe_Ioi_nhdsGT] infer_instance simp_rw [← map_coe_Ioi_atBot, tendsto_map'_iff, ← mem_Ioi, biInter_eq_iInter] apply tendsto_measure_iInter_atBot · rwa [Subtype.forall] · exact fun i j h ↦ hm i j i.2 h · simpa only [Subtype.exists, exists_prop] theorem measure_if {x : β} {t : Set β} {s : Set α} [Decidable (x ∈ t)] : μ (if x ∈ t then s else ∅) = indicator t (fun _ => μ s) x := by split_ifs with h <;> simp [h] end section OuterMeasure variable [ms : MeasurableSpace α] {s t : Set α} /-- Obtain a measure by giving an outer measure where all sets in the σ-algebra are Carathéodory measurable. -/ def OuterMeasure.toMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) : Measure α := Measure.ofMeasurable (fun s _ => m s) m.empty fun _f hf hd => m.iUnion_eq_of_caratheodory (fun i => h _ (hf i)) hd theorem le_toOuterMeasure_caratheodory (μ : Measure α) : ms ≤ μ.toOuterMeasure.caratheodory := fun _s hs _t => (measure_inter_add_diff _ hs).symm @[simp] theorem toMeasure_toOuterMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) : (m.toMeasure h).toOuterMeasure = m.trim := rfl @[simp] theorem toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α} (hs : MeasurableSet s) : m.toMeasure h s = m s := m.trim_eq hs theorem le_toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) (s : Set α) : m s ≤ m.toMeasure h s := m.le_trim s theorem toMeasure_apply₀ (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α} (hs : NullMeasurableSet s (m.toMeasure h)) : m.toMeasure h s = m s := by refine le_antisymm ?_ (le_toMeasure_apply _ _ _) rcases hs.exists_measurable_subset_ae_eq with ⟨t, hts, htm, heq⟩ calc m.toMeasure h s = m.toMeasure h t := measure_congr heq.symm _ = m t := toMeasure_apply m h htm _ ≤ m s := m.mono hts @[simp] theorem toOuterMeasure_toMeasure {μ : Measure α} : μ.toOuterMeasure.toMeasure (le_toOuterMeasure_caratheodory _) = μ := Measure.ext fun _s => μ.toOuterMeasure.trim_eq @[simp] theorem boundedBy_measure (μ : Measure α) : OuterMeasure.boundedBy μ = μ.toOuterMeasure := μ.toOuterMeasure.boundedBy_eq_self end OuterMeasure section variable {m0 : MeasurableSpace α} {mβ : MeasurableSpace β} [MeasurableSpace γ] variable {μ μ₁ μ₂ μ₃ ν ν' ν₁ ν₂ : Measure α} {s s' t : Set α} namespace Measure /-- If `u` is a superset of `t` with the same (finite) measure (both sets possibly non-measurable), then for any measurable set `s` one also has `μ (t ∩ s) = μ (u ∩ s)`. -/ theorem measure_inter_eq_of_measure_eq {s t u : Set α} (hs : MeasurableSet s) (h : μ t = μ u) (htu : t ⊆ u) (ht_ne_top : μ t ≠ ∞) : μ (t ∩ s) = μ (u ∩ s) := by rw [h] at ht_ne_top refine le_antisymm (by gcongr) ?_ have A : μ (u ∩ s) + μ (u \ s) ≤ μ (t ∩ s) + μ (u \ s) := calc μ (u ∩ s) + μ (u \ s) = μ u := measure_inter_add_diff _ hs _ = μ t := h.symm _ = μ (t ∩ s) + μ (t \ s) := (measure_inter_add_diff _ hs).symm _ ≤ μ (t ∩ s) + μ (u \ s) := by gcongr have B : μ (u \ s) ≠ ∞ := (lt_of_le_of_lt (measure_mono diff_subset) ht_ne_top.lt_top).ne exact ENNReal.le_of_add_le_add_right B A /-- The measurable superset `toMeasurable μ t` of `t` (which has the same measure as `t`) satisfies, for any measurable set `s`, the equality `μ (toMeasurable μ t ∩ s) = μ (u ∩ s)`. Here, we require that the measure of `t` is finite. The conclusion holds without this assumption when the measure is s-finite (for example when it is σ-finite), see `measure_toMeasurable_inter_of_sFinite`. -/ theorem measure_toMeasurable_inter {s t : Set α} (hs : MeasurableSet s) (ht : μ t ≠ ∞) : μ (toMeasurable μ t ∩ s) = μ (t ∩ s) := (measure_inter_eq_of_measure_eq hs (measure_toMeasurable t).symm (subset_toMeasurable μ t) ht).symm /-! ### The `ℝ≥0∞`-module of measures -/ instance instZero {_ : MeasurableSpace α} : Zero (Measure α) := ⟨{ toOuterMeasure := 0 m_iUnion := fun _f _hf _hd => tsum_zero.symm trim_le := OuterMeasure.trim_zero.le }⟩ @[simp] theorem zero_toOuterMeasure {_m : MeasurableSpace α} : (0 : Measure α).toOuterMeasure = 0 := rfl @[simp, norm_cast] theorem coe_zero {_m : MeasurableSpace α} : ⇑(0 : Measure α) = 0 := rfl @[simp] lemma _root_.MeasureTheory.OuterMeasure.toMeasure_zero [ms : MeasurableSpace α] (h : ms ≤ (0 : OuterMeasure α).caratheodory) : (0 : OuterMeasure α).toMeasure h = 0 := by ext s hs simp [hs] @[simp] lemma _root_.MeasureTheory.OuterMeasure.toMeasure_eq_zero {ms : MeasurableSpace α} {μ : OuterMeasure α} (h : ms ≤ μ.caratheodory) : μ.toMeasure h = 0 ↔ μ = 0 where mp hμ := by ext s; exact le_bot_iff.1 <| (le_toMeasure_apply _ _ _).trans_eq congr($hμ s) mpr := by rintro rfl; simp @[nontriviality] lemma apply_eq_zero_of_isEmpty [IsEmpty α] {_ : MeasurableSpace α} (μ : Measure α) (s : Set α) : μ s = 0 := by rw [eq_empty_of_isEmpty s, measure_empty] instance instSubsingleton [IsEmpty α] {m : MeasurableSpace α} : Subsingleton (Measure α) := ⟨fun μ ν => by ext1 s _; rw [apply_eq_zero_of_isEmpty, apply_eq_zero_of_isEmpty]⟩ theorem eq_zero_of_isEmpty [IsEmpty α] {_m : MeasurableSpace α} (μ : Measure α) : μ = 0 := Subsingleton.elim μ 0 instance instInhabited {_ : MeasurableSpace α} : Inhabited (Measure α) := ⟨0⟩ instance instAdd {_ : MeasurableSpace α} : Add (Measure α) := ⟨fun μ₁ μ₂ => { toOuterMeasure := μ₁.toOuterMeasure + μ₂.toOuterMeasure m_iUnion := fun s hs hd => show μ₁ (⋃ i, s i) + μ₂ (⋃ i, s i) = ∑' i, (μ₁ (s i) + μ₂ (s i)) by rw [ENNReal.tsum_add, measure_iUnion hd hs, measure_iUnion hd hs] trim_le := by rw [OuterMeasure.trim_add, μ₁.trimmed, μ₂.trimmed] }⟩ @[simp] theorem add_toOuterMeasure {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) : (μ₁ + μ₂).toOuterMeasure = μ₁.toOuterMeasure + μ₂.toOuterMeasure := rfl @[simp, norm_cast] theorem coe_add {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) : ⇑(μ₁ + μ₂) = μ₁ + μ₂ := rfl theorem add_apply {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) (s : Set α) : (μ₁ + μ₂) s = μ₁ s + μ₂ s := rfl section SMul variable [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] variable [SMul R' ℝ≥0∞] [IsScalarTower R' ℝ≥0∞ ℝ≥0∞] instance instSMul {_ : MeasurableSpace α} : SMul R (Measure α) := ⟨fun c μ => { toOuterMeasure := c • μ.toOuterMeasure m_iUnion := fun s hs hd => by simp only [OuterMeasure.smul_apply, coe_toOuterMeasure, ENNReal.tsum_const_smul, measure_iUnion hd hs] trim_le := by rw [OuterMeasure.trim_smul, μ.trimmed] }⟩ @[simp] theorem smul_toOuterMeasure {_m : MeasurableSpace α} (c : R) (μ : Measure α) : (c • μ).toOuterMeasure = c • μ.toOuterMeasure := rfl @[simp, norm_cast] theorem coe_smul {_m : MeasurableSpace α} (c : R) (μ : Measure α) : ⇑(c • μ) = c • ⇑μ := rfl @[simp] theorem smul_apply {_m : MeasurableSpace α} (c : R) (μ : Measure α) (s : Set α) : (c • μ) s = c • μ s := rfl instance instSMulCommClass [SMulCommClass R R' ℝ≥0∞] {_ : MeasurableSpace α} : SMulCommClass R R' (Measure α) := ⟨fun _ _ _ => ext fun _ _ => smul_comm _ _ _⟩ instance instIsScalarTower [SMul R R'] [IsScalarTower R R' ℝ≥0∞] {_ : MeasurableSpace α} : IsScalarTower R R' (Measure α) := ⟨fun _ _ _ => ext fun _ _ => smul_assoc _ _ _⟩ instance instIsCentralScalar [SMul Rᵐᵒᵖ ℝ≥0∞] [IsCentralScalar R ℝ≥0∞] {_ : MeasurableSpace α} : IsCentralScalar R (Measure α) := ⟨fun _ _ => ext fun _ _ => op_smul_eq_smul _ _⟩ end SMul instance instNoZeroSMulDivisors [Zero R] [SMulWithZero R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] [NoZeroSMulDivisors R ℝ≥0∞] : NoZeroSMulDivisors R (Measure α) where eq_zero_or_eq_zero_of_smul_eq_zero h := by simpa [Ne, ext_iff', forall_or_left] using h instance instMulAction [Monoid R] [MulAction R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] {_ : MeasurableSpace α} : MulAction R (Measure α) := Injective.mulAction _ toOuterMeasure_injective smul_toOuterMeasure instance instAddCommMonoid {_ : MeasurableSpace α} : AddCommMonoid (Measure α) := toOuterMeasure_injective.addCommMonoid toOuterMeasure zero_toOuterMeasure add_toOuterMeasure fun _ _ => smul_toOuterMeasure _ _ /-- Coercion to function as an additive monoid homomorphism. -/ def coeAddHom {_ : MeasurableSpace α} : Measure α →+ Set α → ℝ≥0∞ where toFun := (⇑) map_zero' := coe_zero map_add' := coe_add @[simp] theorem coeAddHom_apply {_ : MeasurableSpace α} (μ : Measure α) : coeAddHom μ = ⇑μ := rfl @[simp] theorem coe_finset_sum {_m : MeasurableSpace α} (I : Finset ι) (μ : ι → Measure α) : ⇑(∑ i ∈ I, μ i) = ∑ i ∈ I, ⇑(μ i) := map_sum coeAddHom μ I theorem finset_sum_apply {m : MeasurableSpace α} (I : Finset ι) (μ : ι → Measure α) (s : Set α) : (∑ i ∈ I, μ i) s = ∑ i ∈ I, μ i s := by rw [coe_finset_sum, Finset.sum_apply] instance instDistribMulAction [Monoid R] [DistribMulAction R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] {_ : MeasurableSpace α} : DistribMulAction R (Measure α) := Injective.distribMulAction ⟨⟨toOuterMeasure, zero_toOuterMeasure⟩, add_toOuterMeasure⟩ toOuterMeasure_injective smul_toOuterMeasure instance instModule [Semiring R] [Module R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] {_ : MeasurableSpace α} : Module R (Measure α) := Injective.module R ⟨⟨toOuterMeasure, zero_toOuterMeasure⟩, add_toOuterMeasure⟩ toOuterMeasure_injective smul_toOuterMeasure @[simp] theorem coe_nnreal_smul_apply {_m : MeasurableSpace α} (c : ℝ≥0) (μ : Measure α) (s : Set α) : (c • μ) s = c * μ s := rfl @[simp] theorem nnreal_smul_coe_apply {_m : MeasurableSpace α} (c : ℝ≥0) (μ : Measure α) (s : Set α) : c • μ s = c * μ s := by rfl theorem ae_smul_measure {p : α → Prop} [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] (h : ∀ᵐ x ∂μ, p x) (c : R) : ∀ᵐ x ∂c • μ, p x := ae_iff.2 <| by rw [smul_apply, ae_iff.1 h, ← smul_one_smul ℝ≥0∞, smul_zero] theorem ae_smul_measure_le [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] (c : R) : ae (c • μ) ≤ ae μ := fun _ h ↦ ae_smul_measure h c section SMulWithZero variable {R : Type*} [Zero R] [SMulWithZero R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] [NoZeroSMulDivisors R ℝ≥0∞] {c : R} {p : α → Prop} lemma ae_smul_measure_iff (hc : c ≠ 0) {μ : Measure α} : (∀ᵐ x ∂c • μ, p x) ↔ ∀ᵐ x ∂μ, p x := by simp [ae_iff, hc] @[simp] lemma ae_smul_measure_eq (hc : c ≠ 0) (μ : Measure α) : ae (c • μ) = ae μ := by ext; exact ae_smul_measure_iff hc end SMulWithZero theorem measure_eq_left_of_subset_of_measure_add_eq {s t : Set α} (h : (μ + ν) t ≠ ∞) (h' : s ⊆ t) (h'' : (μ + ν) s = (μ + ν) t) : μ s = μ t := by refine le_antisymm (measure_mono h') ?_ have : μ t + ν t ≤ μ s + ν t := calc μ t + ν t = μ s + ν s := h''.symm _ ≤ μ s + ν t := by gcongr apply ENNReal.le_of_add_le_add_right _ this exact ne_top_of_le_ne_top h (le_add_left le_rfl) theorem measure_eq_right_of_subset_of_measure_add_eq {s t : Set α} (h : (μ + ν) t ≠ ∞) (h' : s ⊆ t) (h'' : (μ + ν) s = (μ + ν) t) : ν s = ν t := by rw [add_comm] at h'' h exact measure_eq_left_of_subset_of_measure_add_eq h h' h'' theorem measure_toMeasurable_add_inter_left {s t : Set α} (hs : MeasurableSet s) (ht : (μ + ν) t ≠ ∞) : μ (toMeasurable (μ + ν) t ∩ s) = μ (t ∩ s) := by refine (measure_inter_eq_of_measure_eq hs ?_ (subset_toMeasurable _ _) ?_).symm · refine measure_eq_left_of_subset_of_measure_add_eq ?_ (subset_toMeasurable _ _) (measure_toMeasurable t).symm rwa [measure_toMeasurable t] · simp only [not_or, ENNReal.add_eq_top, Pi.add_apply, Ne, coe_add] at ht exact ht.1 theorem measure_toMeasurable_add_inter_right {s t : Set α} (hs : MeasurableSet s) (ht : (μ + ν) t ≠ ∞) : ν (toMeasurable (μ + ν) t ∩ s) = ν (t ∩ s) := by rw [add_comm] at ht ⊢ exact measure_toMeasurable_add_inter_left hs ht /-! ### The complete lattice of measures -/ /-- Measures are partially ordered. -/ instance instPartialOrder {_ : MeasurableSpace α} : PartialOrder (Measure α) where le m₁ m₂ := ∀ s, m₁ s ≤ m₂ s le_refl _ _ := le_rfl le_trans _ _ _ h₁ h₂ s := le_trans (h₁ s) (h₂ s) le_antisymm _ _ h₁ h₂ := ext fun s _ => le_antisymm (h₁ s) (h₂ s) theorem toOuterMeasure_le : μ₁.toOuterMeasure ≤ μ₂.toOuterMeasure ↔ μ₁ ≤ μ₂ := .rfl theorem le_iff : μ₁ ≤ μ₂ ↔ ∀ s, MeasurableSet s → μ₁ s ≤ μ₂ s := outerMeasure_le_iff theorem le_intro (h : ∀ s, MeasurableSet s → s.Nonempty → μ₁ s ≤ μ₂ s) : μ₁ ≤ μ₂ := le_iff.2 fun s hs ↦ s.eq_empty_or_nonempty.elim (by rintro rfl; simp) (h s hs) theorem le_iff' : μ₁ ≤ μ₂ ↔ ∀ s, μ₁ s ≤ μ₂ s := .rfl theorem lt_iff : μ < ν ↔ μ ≤ ν ∧ ∃ s, MeasurableSet s ∧ μ s < ν s := lt_iff_le_not_le.trans <| and_congr Iff.rfl <| by simp only [le_iff, not_forall, not_le, exists_prop] theorem lt_iff' : μ < ν ↔ μ ≤ ν ∧ ∃ s, μ s < ν s := lt_iff_le_not_le.trans <| and_congr Iff.rfl <| by simp only [le_iff', not_forall, not_le] instance instAddLeftMono {_ : MeasurableSpace α} : AddLeftMono (Measure α) := ⟨fun _ν _μ₁ _μ₂ hμ s => add_le_add_left (hμ s) _⟩ protected theorem le_add_left (h : μ ≤ ν) : μ ≤ ν' + ν := fun s => le_add_left (h s) protected theorem le_add_right (h : μ ≤ ν) : μ ≤ ν + ν' := fun s => le_add_right (h s) section sInf variable {m : Set (Measure α)} theorem sInf_caratheodory (s : Set α) (hs : MeasurableSet s) : MeasurableSet[(sInf (toOuterMeasure '' m)).caratheodory] s := by rw [OuterMeasure.sInf_eq_boundedBy_sInfGen] refine OuterMeasure.boundedBy_caratheodory fun t => ?_ simp only [OuterMeasure.sInfGen, le_iInf_iff, forall_mem_image, measure_eq_iInf t, coe_toOuterMeasure] intro μ hμ u htu _hu have hm : ∀ {s t}, s ⊆ t → OuterMeasure.sInfGen (toOuterMeasure '' m) s ≤ μ t := by intro s t hst rw [OuterMeasure.sInfGen_def, iInf_image] exact iInf₂_le_of_le μ hμ <| measure_mono hst rw [← measure_inter_add_diff u hs] exact add_le_add (hm <| inter_subset_inter_left _ htu) (hm <| diff_subset_diff_left htu) instance {_ : MeasurableSpace α} : InfSet (Measure α) := ⟨fun m => (sInf (toOuterMeasure '' m)).toMeasure <| sInf_caratheodory⟩ theorem sInf_apply (hs : MeasurableSet s) : sInf m s = sInf (toOuterMeasure '' m) s := toMeasure_apply _ _ hs private theorem measure_sInf_le (h : μ ∈ m) : sInf m ≤ μ := have : sInf (toOuterMeasure '' m) ≤ μ.toOuterMeasure := sInf_le (mem_image_of_mem _ h) le_iff.2 fun s hs => by rw [sInf_apply hs]; exact this s private theorem measure_le_sInf (h : ∀ μ' ∈ m, μ ≤ μ') : μ ≤ sInf m := have : μ.toOuterMeasure ≤ sInf (toOuterMeasure '' m) := le_sInf <| forall_mem_image.2 fun _ hμ ↦ toOuterMeasure_le.2 <| h _ hμ le_iff.2 fun s hs => by rw [sInf_apply hs]; exact this s instance instCompleteSemilatticeInf {_ : MeasurableSpace α} : CompleteSemilatticeInf (Measure α) := { (by infer_instance : PartialOrder (Measure α)), (by infer_instance : InfSet (Measure α)) with sInf_le := fun _s _a => measure_sInf_le le_sInf := fun _s _a => measure_le_sInf } instance instCompleteLattice {_ : MeasurableSpace α} : CompleteLattice (Measure α) := { completeLatticeOfCompleteSemilatticeInf (Measure α) with top := { toOuterMeasure := ⊤, m_iUnion := by intro f _ _ refine (measure_iUnion_le _).antisymm ?_ if hne : (⋃ i, f i).Nonempty then rw [OuterMeasure.top_apply hne] exact le_top else simp_all [Set.not_nonempty_iff_eq_empty] trim_le := le_top }, le_top := fun _ => toOuterMeasure_le.mp le_top bot := 0 bot_le := fun _a _s => bot_le } end sInf lemma inf_apply {s : Set α} (hs : MeasurableSet s) : (μ ⊓ ν) s = sInf {m | ∃ t, m = μ (t ∩ s) + ν (tᶜ ∩ s)} := by -- `(μ ⊓ ν) s` is defined as `⊓ (t : ℕ → Set α) (ht : s ⊆ ⋃ n, t n), ∑' n, μ (t n) ⊓ ν (t n)` rw [← sInf_pair, Measure.sInf_apply hs, OuterMeasure.sInf_apply (image_nonempty.2 <| insert_nonempty μ {ν})] refine le_antisymm (le_sInf fun m ⟨t, ht₁⟩ ↦ ?_) (le_iInf₂ fun t' ht' ↦ ?_) · subst ht₁ -- We first show `(μ ⊓ ν) s ≤ μ (t ∩ s) + ν (tᶜ ∩ s)` for any `t : Set α` -- For this, define the sequence `t' : ℕ → Set α` where `t' 0 = t ∩ s`, `t' 1 = tᶜ ∩ s` and -- `∅` otherwise. Then, we have by construction -- `(μ ⊓ ν) s ≤ ∑' n, μ (t' n) ⊓ ν (t' n) ≤ μ (t' 0) + ν (t' 1) = μ (t ∩ s) + ν (tᶜ ∩ s)`. set t' : ℕ → Set α := fun n ↦ if n = 0 then t ∩ s else if n = 1 then tᶜ ∩ s else ∅ with ht' refine (iInf₂_le t' fun x hx ↦ ?_).trans ?_ · by_cases hxt : x ∈ t · refine mem_iUnion.2 ⟨0, ?_⟩ simp [hx, hxt] · refine mem_iUnion.2 ⟨1, ?_⟩ simp [hx, hxt] · simp only [iInf_image, coe_toOuterMeasure, iInf_pair] rw [tsum_eq_add_tsum_ite 0, tsum_eq_add_tsum_ite 1, if_neg zero_ne_one.symm, ENNReal.summable.tsum_eq_zero_iff.2 _, add_zero] · exact add_le_add (inf_le_left.trans <| by simp [ht']) (inf_le_right.trans <| by simp [ht']) · simp only [ite_eq_left_iff] intro n hn₁ hn₀ simp only [ht', if_neg hn₀, if_neg hn₁, measure_empty, iInf_pair, le_refl, inf_of_le_left] · simp only [iInf_image, coe_toOuterMeasure, iInf_pair] -- Conversely, fixing `t' : ℕ → Set α` such that `s ⊆ ⋃ n, t' n`, we construct `t : Set α` -- for which `μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n, μ (t' n) ⊓ ν (t' n)`. -- Denoting `I := {n | μ (t' n) ≤ ν (t' n)}`, we set `t = ⋃ n ∈ I, t' n`. -- Clearly `μ (t ∩ s) ≤ ∑' n ∈ I, μ (t' n)` and `ν (tᶜ ∩ s) ≤ ∑' n ∉ I, ν (t' n)`, so -- `μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n ∈ I, μ (t' n) + ∑' n ∉ I, ν (t' n)` -- where the RHS equals `∑' n, μ (t' n) ⊓ ν (t' n)` by the choice of `I`. set t := ⋃ n ∈ {k : ℕ | μ (t' k) ≤ ν (t' k)}, t' n with ht suffices hadd : μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n, μ (t' n) ⊓ ν (t' n) by exact le_trans (sInf_le ⟨t, rfl⟩) hadd have hle₁ : μ (t ∩ s) ≤ ∑' (n : {k | μ (t' k) ≤ ν (t' k)}), μ (t' n) := (measure_mono inter_subset_left).trans <| measure_biUnion_le _ (to_countable _) _ have hcap : tᶜ ∩ s ⊆ ⋃ n ∈ {k | ν (t' k) < μ (t' k)}, t' n := by simp_rw [ht, compl_iUnion] refine fun x ⟨hx₁, hx₂⟩ ↦ mem_iUnion₂.2 ?_ obtain ⟨i, hi⟩ := mem_iUnion.1 <| ht' hx₂ refine ⟨i, ?_, hi⟩ by_contra h simp only [mem_setOf_eq, not_lt] at h exact mem_iInter₂.1 hx₁ i h hi have hle₂ : ν (tᶜ ∩ s) ≤ ∑' (n : {k | ν (t' k) < μ (t' k)}), ν (t' n) := (measure_mono hcap).trans (measure_biUnion_le ν (to_countable {k | ν (t' k) < μ (t' k)}) _) refine (add_le_add hle₁ hle₂).trans ?_ have heq : {k | μ (t' k) ≤ ν (t' k)} ∪ {k | ν (t' k) < μ (t' k)} = univ := by ext k; simp [le_or_lt] conv in ∑' (n : ℕ), μ (t' n) ⊓ ν (t' n) => rw [← tsum_univ, ← heq] rw [ENNReal.summable.tsum_union_disjoint (f := fun n ↦ μ (t' n) ⊓ ν (t' n)) ?_ ENNReal.summable] · refine add_le_add (tsum_congr ?_).le (tsum_congr ?_).le · rw [Subtype.forall] intro n hn; simpa · rw [Subtype.forall] intro n hn rw [mem_setOf_eq] at hn simp [le_of_lt hn] · rw [Set.disjoint_iff] rintro k ⟨hk₁, hk₂⟩ rw [mem_setOf_eq] at hk₁ hk₂ exact False.elim <| hk₂.not_le hk₁ @[simp] theorem _root_.MeasureTheory.OuterMeasure.toMeasure_top : (⊤ : OuterMeasure α).toMeasure (by rw [OuterMeasure.top_caratheodory]; exact le_top) = (⊤ : Measure α) := toOuterMeasure_toMeasure (μ := ⊤) @[simp] theorem toOuterMeasure_top {_ : MeasurableSpace α} : (⊤ : Measure α).toOuterMeasure = (⊤ : OuterMeasure α) := rfl @[simp] theorem top_add : ⊤ + μ = ⊤ := top_unique <| Measure.le_add_right le_rfl @[simp] theorem add_top : μ + ⊤ = ⊤ := top_unique <| Measure.le_add_left le_rfl protected theorem zero_le {_m0 : MeasurableSpace α} (μ : Measure α) : 0 ≤ μ := bot_le theorem nonpos_iff_eq_zero' : μ ≤ 0 ↔ μ = 0 := μ.zero_le.le_iff_eq @[simp] theorem measure_univ_eq_zero : μ univ = 0 ↔ μ = 0 := ⟨fun h => bot_unique fun s => (h ▸ measure_mono (subset_univ s) : μ s ≤ 0), fun h => h.symm ▸ rfl⟩ theorem measure_univ_ne_zero : μ univ ≠ 0 ↔ μ ≠ 0 := measure_univ_eq_zero.not instance [NeZero μ] : NeZero (μ univ) := ⟨measure_univ_ne_zero.2 <| NeZero.ne μ⟩ @[simp] theorem measure_univ_pos : 0 < μ univ ↔ μ ≠ 0 := pos_iff_ne_zero.trans measure_univ_ne_zero lemma nonempty_of_neZero (μ : Measure α) [NeZero μ] : Nonempty α := (isEmpty_or_nonempty α).resolve_left fun h ↦ by simpa [eq_empty_of_isEmpty] using NeZero.ne (μ univ) section Sum variable {f : ι → Measure α} /-- Sum of an indexed family of measures. -/ noncomputable def sum (f : ι → Measure α) : Measure α := (OuterMeasure.sum fun i => (f i).toOuterMeasure).toMeasure <| le_trans (le_iInf fun _ => le_toOuterMeasure_caratheodory _) (OuterMeasure.le_sum_caratheodory _) theorem le_sum_apply (f : ι → Measure α) (s : Set α) : ∑' i, f i s ≤ sum f s := le_toMeasure_apply _ _ _ @[simp] theorem sum_apply (f : ι → Measure α) {s : Set α} (hs : MeasurableSet s) : sum f s = ∑' i, f i s := toMeasure_apply _ _ hs theorem sum_apply₀ (f : ι → Measure α) {s : Set α} (hs : NullMeasurableSet s (sum f)) : sum f s = ∑' i, f i s := by apply le_antisymm ?_ (le_sum_apply _ _) rcases hs.exists_measurable_subset_ae_eq with ⟨t, ts, t_meas, ht⟩ calc sum f s = sum f t := measure_congr ht.symm _ = ∑' i, f i t := sum_apply _ t_meas _ ≤ ∑' i, f i s := ENNReal.tsum_le_tsum fun i ↦ measure_mono ts /-! For the next theorem, the countability assumption is necessary. For a counterexample, consider an uncountable space, with a distinguished point `x₀`, and the sigma-algebra made of countable sets not containing `x₀`, and their complements. All points but `x₀` are measurable. Consider the sum of the Dirac masses at points different from `x₀`, and `s = {x₀}`. For any Dirac mass `δ_x`, we have `δ_x (x₀) = 0`, so `∑' x, δ_x (x₀) = 0`. On the other hand, the measure `sum δ_x` gives mass one to each point different from `x₀`, so it gives infinite mass to any measurable set containing `x₀` (as such a set is uncountable), and by outer regularity one gets `sum δ_x {x₀} = ∞`. -/ theorem sum_apply_of_countable [Countable ι] (f : ι → Measure α) (s : Set α) : sum f s = ∑' i, f i s := by apply le_antisymm ?_ (le_sum_apply _ _) rcases exists_measurable_superset_forall_eq f s with ⟨t, hst, htm, ht⟩ calc sum f s ≤ sum f t := measure_mono hst _ = ∑' i, f i t := sum_apply _ htm _ = ∑' i, f i s := by simp [ht] theorem le_sum (μ : ι → Measure α) (i : ι) : μ i ≤ sum μ := le_iff.2 fun s hs ↦ by simpa only [sum_apply μ hs] using ENNReal.le_tsum i @[simp] theorem sum_apply_eq_zero [Countable ι] {μ : ι → Measure α} {s : Set α} : sum μ s = 0 ↔ ∀ i, μ i s = 0 := by simp [sum_apply_of_countable] theorem sum_apply_eq_zero' {μ : ι → Measure α} {s : Set α} (hs : MeasurableSet s) : sum μ s = 0 ↔ ∀ i, μ i s = 0 := by simp [hs] @[simp] lemma sum_eq_zero : sum f = 0 ↔ ∀ i, f i = 0 := by simp +contextual [Measure.ext_iff, forall_swap (α := ι)] @[simp] lemma sum_zero : Measure.sum (fun (_ : ι) ↦ (0 : Measure α)) = 0 := by ext s hs simp [Measure.sum_apply _ hs] theorem sum_sum {ι' : Type*} (μ : ι → ι' → Measure α) : (sum fun n => sum (μ n)) = sum (fun (p : ι × ι') ↦ μ p.1 p.2) := by ext1 s hs simp [sum_apply _ hs, ENNReal.tsum_prod'] theorem sum_comm {ι' : Type*} (μ : ι → ι' → Measure α) : (sum fun n => sum (μ n)) = sum fun m => sum fun n => μ n m := by ext1 s hs simp_rw [sum_apply _ hs] rw [ENNReal.tsum_comm] theorem ae_sum_iff [Countable ι] {μ : ι → Measure α} {p : α → Prop} : (∀ᵐ x ∂sum μ, p x) ↔ ∀ i, ∀ᵐ x ∂μ i, p x := sum_apply_eq_zero theorem ae_sum_iff' {μ : ι → Measure α} {p : α → Prop} (h : MeasurableSet { x | p x }) : (∀ᵐ x ∂sum μ, p x) ↔ ∀ i, ∀ᵐ x ∂μ i, p x := sum_apply_eq_zero' h.compl @[simp] theorem sum_fintype [Fintype ι] (μ : ι → Measure α) : sum μ = ∑ i, μ i := by ext1 s hs simp only [sum_apply, finset_sum_apply, hs, tsum_fintype] theorem sum_coe_finset (s : Finset ι) (μ : ι → Measure α) : (sum fun i : s => μ i) = ∑ i ∈ s, μ i := by rw [sum_fintype, Finset.sum_coe_sort s μ] @[simp] theorem ae_sum_eq [Countable ι] (μ : ι → Measure α) : ae (sum μ) = ⨆ i, ae (μ i) := Filter.ext fun _ => ae_sum_iff.trans mem_iSup.symm theorem sum_bool (f : Bool → Measure α) : sum f = f true + f false := by rw [sum_fintype, Fintype.sum_bool] theorem sum_cond (μ ν : Measure α) : (sum fun b => cond b μ ν) = μ + ν := sum_bool _ @[simp] theorem sum_of_isEmpty [IsEmpty ι] (μ : ι → Measure α) : sum μ = 0 := by rw [← measure_univ_eq_zero, sum_apply _ MeasurableSet.univ, tsum_empty] theorem sum_add_sum_compl (s : Set ι) (μ : ι → Measure α) : ((sum fun i : s => μ i) + sum fun i : ↥sᶜ => μ i) = sum μ := by ext1 t ht simp only [add_apply, sum_apply _ ht] exact ENNReal.summable.tsum_add_tsum_compl (f := fun i => μ i t) ENNReal.summable theorem sum_congr {μ ν : ℕ → Measure α} (h : ∀ n, μ n = ν n) : sum μ = sum ν := congr_arg sum (funext h) theorem sum_add_sum {ι : Type*} (μ ν : ι → Measure α) : sum μ + sum ν = sum fun n => μ n + ν n := by ext1 s hs simp only [add_apply, sum_apply _ hs, Pi.add_apply, coe_add, ENNReal.summable.tsum_add ENNReal.summable] @[simp] lemma sum_comp_equiv {ι ι' : Type*} (e : ι' ≃ ι) (m : ι → Measure α) : sum (m ∘ e) = sum m := by ext s hs simpa [hs, sum_apply] using e.tsum_eq (fun n ↦ m n s) @[simp] lemma sum_extend_zero {ι ι' : Type*} {f : ι → ι'} (hf : Injective f) (m : ι → Measure α) : sum (Function.extend f m 0) = sum m := by ext s hs simp [*, Function.apply_extend (fun μ : Measure α ↦ μ s)] end Sum /-! ### The `cofinite` filter -/ /-- The filter of sets `s` such that `sᶜ` has finite measure. -/ def cofinite {m0 : MeasurableSpace α} (μ : Measure α) : Filter α := comk (μ · < ∞) (by simp) (fun _ ht _ hs ↦ (measure_mono hs).trans_lt ht) fun s hs t ht ↦ (measure_union_le s t).trans_lt <| ENNReal.add_lt_top.2 ⟨hs, ht⟩ theorem mem_cofinite : s ∈ μ.cofinite ↔ μ sᶜ < ∞ := Iff.rfl theorem compl_mem_cofinite : sᶜ ∈ μ.cofinite ↔ μ s < ∞ := by rw [mem_cofinite, compl_compl] theorem eventually_cofinite {p : α → Prop} : (∀ᶠ x in μ.cofinite, p x) ↔ μ { x | ¬p x } < ∞ := Iff.rfl instance cofinite.instIsMeasurablyGenerated : IsMeasurablyGenerated μ.cofinite where exists_measurable_subset s hs := by refine ⟨(toMeasurable μ sᶜ)ᶜ, ?_, (measurableSet_toMeasurable _ _).compl, ?_⟩ · rwa [compl_mem_cofinite, measure_toMeasurable] · rw [compl_subset_comm] apply subset_toMeasurable end Measure open Measure open MeasureTheory protected theorem _root_.AEMeasurable.nullMeasurable {f : α → β} (h : AEMeasurable f μ) : NullMeasurable f μ := let ⟨_g, hgm, hg⟩ := h; hgm.nullMeasurable.congr hg.symm lemma _root_.AEMeasurable.nullMeasurableSet_preimage {f : α → β} {s : Set β} (hf : AEMeasurable f μ) (hs : MeasurableSet s) : NullMeasurableSet (f ⁻¹' s) μ := hf.nullMeasurable hs @[simp] theorem ae_eq_bot : ae μ = ⊥ ↔ μ = 0 := by rw [← empty_mem_iff_bot, mem_ae_iff, compl_empty, measure_univ_eq_zero] @[simp] theorem ae_neBot : (ae μ).NeBot ↔ μ ≠ 0 := neBot_iff.trans (not_congr ae_eq_bot) instance Measure.ae.neBot [NeZero μ] : (ae μ).NeBot := ae_neBot.2 <| NeZero.ne μ @[simp] theorem ae_zero {_m0 : MeasurableSpace α} : ae (0 : Measure α) = ⊥ := ae_eq_bot.2 rfl section Intervals theorem biSup_measure_Iic [Preorder α] {s : Set α} (hsc : s.Countable) (hst : ∀ x : α, ∃ y ∈ s, x ≤ y) (hdir : DirectedOn (· ≤ ·) s) : ⨆ x ∈ s, μ (Iic x) = μ univ := by rw [← measure_biUnion_eq_iSup hsc] · congr simp only [← bex_def] at hst exact iUnion₂_eq_univ_iff.2 hst · exact directedOn_iff_directed.2 (hdir.directed_val.mono_comp _ fun x y => Iic_subset_Iic.2) theorem tendsto_measure_Ico_atTop [Preorder α] [NoMaxOrder α] [(atTop : Filter α).IsCountablyGenerated] (μ : Measure α) (a : α) : Tendsto (fun x => μ (Ico a x)) atTop (𝓝 (μ (Ici a))) := by rw [← iUnion_Ico_right] exact tendsto_measure_iUnion_atTop (antitone_const.Ico monotone_id) theorem tendsto_measure_Ioc_atBot [Preorder α] [NoMinOrder α] [(atBot : Filter α).IsCountablyGenerated] (μ : Measure α) (a : α) : Tendsto (fun x => μ (Ioc x a)) atBot (𝓝 (μ (Iic a))) := by rw [← iUnion_Ioc_left] exact tendsto_measure_iUnion_atBot (monotone_id.Ioc antitone_const) theorem tendsto_measure_Iic_atTop [Preorder α] [(atTop : Filter α).IsCountablyGenerated] (μ : Measure α) : Tendsto (fun x => μ (Iic x)) atTop (𝓝 (μ univ)) := by rw [← iUnion_Iic] exact tendsto_measure_iUnion_atTop monotone_Iic theorem tendsto_measure_Ici_atBot [Preorder α] [(atBot : Filter α).IsCountablyGenerated] (μ : Measure α) : Tendsto (fun x => μ (Ici x)) atBot (𝓝 (μ univ)) := tendsto_measure_Iic_atTop (α := αᵒᵈ) μ variable [PartialOrder α] {a b : α} theorem Iio_ae_eq_Iic' (ha : μ {a} = 0) : Iio a =ᵐ[μ] Iic a := by rw [← Iic_diff_right, diff_ae_eq_self, measure_mono_null Set.inter_subset_right ha] theorem Ioi_ae_eq_Ici' (ha : μ {a} = 0) : Ioi a =ᵐ[μ] Ici a := Iio_ae_eq_Iic' (α := αᵒᵈ) ha theorem Ioo_ae_eq_Ioc' (hb : μ {b} = 0) : Ioo a b =ᵐ[μ] Ioc a b := (ae_eq_refl _).inter (Iio_ae_eq_Iic' hb) theorem Ioc_ae_eq_Icc' (ha : μ {a} = 0) : Ioc a b =ᵐ[μ] Icc a b := (Ioi_ae_eq_Ici' ha).inter (ae_eq_refl _) theorem Ioo_ae_eq_Ico' (ha : μ {a} = 0) : Ioo a b =ᵐ[μ] Ico a b := (Ioi_ae_eq_Ici' ha).inter (ae_eq_refl _) theorem Ioo_ae_eq_Icc' (ha : μ {a} = 0) (hb : μ {b} = 0) : Ioo a b =ᵐ[μ] Icc a b := (Ioi_ae_eq_Ici' ha).inter (Iio_ae_eq_Iic' hb) theorem Ico_ae_eq_Icc' (hb : μ {b} = 0) : Ico a b =ᵐ[μ] Icc a b := (ae_eq_refl _).inter (Iio_ae_eq_Iic' hb) theorem Ico_ae_eq_Ioc' (ha : μ {a} = 0) (hb : μ {b} = 0) : Ico a b =ᵐ[μ] Ioc a b := (Ioo_ae_eq_Ico' ha).symm.trans (Ioo_ae_eq_Ioc' hb) end Intervals end end MeasureTheory end
Mathlib/MeasureTheory/Measure/MeasureSpace.lean
1,568
1,569
/- Copyright (c) 2022 Damiano Testa. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Damiano Testa, Yuyang Zhao -/ import Mathlib.Algebra.Order.GroupWithZero.Unbundled.Basic import Mathlib.Algebra.Order.GroupWithZero.Unbundled.Defs import Mathlib.Tactic.Linter.DeprecatedModule deprecated_module (since := "2025-04-13")
Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean
517
523
/- Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn -/ import Mathlib.Data.Set.Prod import Mathlib.Logic.Equiv.Fin.Basic import Mathlib.ModelTheory.LanguageMap import Mathlib.Algebra.Order.Group.Nat /-! # Basics on First-Order Syntax This file defines first-order terms, formulas, sentences, and theories in a style inspired by the [Flypitch project](https://flypitch.github.io/). ## Main Definitions - A `FirstOrder.Language.Term` is defined so that `L.Term α` is the type of `L`-terms with free variables indexed by `α`. - A `FirstOrder.Language.Formula` is defined so that `L.Formula α` is the type of `L`-formulas with free variables indexed by `α`. - A `FirstOrder.Language.Sentence` is a formula with no free variables. - A `FirstOrder.Language.Theory` is a set of sentences. - The variables of terms and formulas can be relabelled with `FirstOrder.Language.Term.relabel`, `FirstOrder.Language.BoundedFormula.relabel`, and `FirstOrder.Language.Formula.relabel`. - Given an operation on terms and an operation on relations, `FirstOrder.Language.BoundedFormula.mapTermRel` gives an operation on formulas. - `FirstOrder.Language.BoundedFormula.castLE` adds more `Fin`-indexed variables. - `FirstOrder.Language.BoundedFormula.liftAt` raises the indexes of the `Fin`-indexed variables above a particular index. - `FirstOrder.Language.Term.subst` and `FirstOrder.Language.BoundedFormula.subst` substitute variables with given terms. - Language maps can act on syntactic objects with functions such as `FirstOrder.Language.LHom.onFormula`. - `FirstOrder.Language.Term.constantsVarsEquiv` and `FirstOrder.Language.BoundedFormula.constantsVarsEquiv` switch terms and formulas between having constants in the language and having extra variables indexed by the same type. ## Implementation Notes - Formulas use a modified version of de Bruijn variables. Specifically, a `L.BoundedFormula α n` is a formula with some variables indexed by a type `α`, which cannot be quantified over, and some indexed by `Fin n`, which can. For any `φ : L.BoundedFormula α (n + 1)`, we define the formula `∀' φ : L.BoundedFormula α n` by universally quantifying over the variable indexed by `n : Fin (n + 1)`. ## References For the Flypitch project: - [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*] [flypitch_cpp] - [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of the continuum hypothesis*][flypitch_itp] -/ universe u v w u' v' namespace FirstOrder namespace Language variable (L : Language.{u, v}) {L' : Language} variable {M : Type w} {α : Type u'} {β : Type v'} {γ : Type*} open FirstOrder open Structure Fin /-- A term on `α` is either a variable indexed by an element of `α` or a function symbol applied to simpler terms. -/ inductive Term (α : Type u') : Type max u u' | var : α → Term α | func : ∀ {l : ℕ} (_f : L.Functions l) (_ts : Fin l → Term α), Term α export Term (var func) variable {L} namespace Term instance instDecidableEq [DecidableEq α] [∀ n, DecidableEq (L.Functions n)] : DecidableEq (L.Term α) | .var a, .var b => decidable_of_iff (a = b) <| by simp | @Term.func _ _ m f xs, @Term.func _ _ n g ys => if h : m = n then letI : DecidableEq (L.Term α) := instDecidableEq decidable_of_iff (f = h ▸ g ∧ ∀ i : Fin m, xs i = ys (Fin.cast h i)) <| by subst h simp [funext_iff] else .isFalse <| by simp [h] | .var _, .func _ _ | .func _ _, .var _ => .isFalse <| by simp open Finset /-- The `Finset` of variables used in a given term. -/ @[simp] def varFinset [DecidableEq α] : L.Term α → Finset α | var i => {i} | func _f ts => univ.biUnion fun i => (ts i).varFinset /-- The `Finset` of variables from the left side of a sum used in a given term. -/ @[simp] def varFinsetLeft [DecidableEq α] : L.Term (α ⊕ β) → Finset α | var (Sum.inl i) => {i} | var (Sum.inr _i) => ∅
| func _f ts => univ.biUnion fun i => (ts i).varFinsetLeft /-- Relabels a term's variables along a particular function. -/ @[simp]
Mathlib/ModelTheory/Syntax.lean
107
110
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Abhimanyu Pallavi Sudhir -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Order.CauSeq.BigOperators import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Complex.BigOperators import Mathlib.Data.Complex.Norm import Mathlib.Data.Nat.Choose.Sum /-! # Exponential Function This file contains the definitions of the real and complex exponential function. ## Main definitions * `Complex.exp`: The complex exponential function, defined via its Taylor series * `Real.exp`: The real exponential function, defined as the real part of the complex exponential -/ open CauSeq Finset IsAbsoluteValue open scoped ComplexConjugate namespace Complex theorem isCauSeq_norm_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ := let ⟨n, hn⟩ := exists_nat_gt ‖z‖ have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0)) (by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div, norm_natCast] gcongr exact le_trans hm (Nat.le_succ _) @[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp noncomputable section theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial := (isCauSeq_norm_exp z).of_abv /-- The Cauchy sequence consisting of partial sums of the Taylor series of the complex exponential function -/ @[pp_nodot] def exp' (z : ℂ) : CauSeq ℂ (‖·‖) := ⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩ /-- The complex exponential function, defined via its Taylor series -/ @[pp_nodot] def exp (z : ℂ) : ℂ := CauSeq.lim (exp' z) /-- scoped notation for the complex exponential function -/ scoped notation "cexp" => Complex.exp end end Complex namespace Real open Complex noncomputable section /-- The real exponential function, defined as the real part of the complex exponential -/ @[pp_nodot] nonrec def exp (x : ℝ) : ℝ := (exp x).re /-- scoped notation for the real exponential function -/ scoped notation "rexp" => Real.exp end end Real namespace Complex variable (x y : ℂ) @[simp] theorem exp_zero : exp 0 = 1 := by rw [exp] refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩ convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε rcases j with - | j · exact absurd hj (not_le_of_gt zero_lt_one) · dsimp [exp'] induction' j with j ih · dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl] · rw [← ih (by simp [Nat.succ_le_succ])] simp only [sum_range_succ, pow_succ] simp theorem exp_add : exp (x + y) = exp x * exp y := by have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) = ∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial * (y ^ (i - k) / (i - k).factorial) := by intro j refine Finset.sum_congr rfl fun m _ => ?_ rw [add_pow, div_eq_mul_inv, sum_mul] refine Finset.sum_congr rfl fun I hi => ?_ have h₁ : (m.choose I : ℂ) ≠ 0 := Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi)))) have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi) rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv] simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹, mul_comm (m.choose I : ℂ)] rw [inv_mul_cancel₀ h₁] simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm] simp_rw [exp, exp', lim_mul_lim] apply (lim_eq_lim_of_equiv _).symm simp only [hj] exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y) /-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ := { toFun := fun z => exp z.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℂ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℂ) expMonoidHom f s lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _ theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n | 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero] | Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul] @[simp] theorem exp_ne_zero : exp x ≠ 0 := fun h => zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp theorem exp_neg : exp (-x) = (exp x)⁻¹ := by rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by cases n · simp [exp_nat_mul] · simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul] @[simp] theorem exp_conj : exp (conj x) = conj (exp x) := by dsimp [exp] rw [← lim_conj] refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_) dsimp [exp', Function.comp_def, cauSeqConj] rw [map_sum (starRingEnd _)] refine sum_congr rfl fun n _ => ?_ rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal] @[simp] theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x := conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal] @[simp, norm_cast] theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x := ofReal_exp_ofReal_re _ @[simp] theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im] theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x := rfl end Complex namespace Real open Complex variable (x y : ℝ) @[simp] theorem exp_zero : exp 0 = 1 := by simp [Real.exp] nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp] /-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ := { toFun := fun x => exp x.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℝ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℝ) expMonoidHom f s lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _ nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n := ofReal_injective (by simp [exp_nat_mul]) @[simp] nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h => exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ := ofReal_injective <| by simp [exp_neg] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] open IsAbsoluteValue Nat theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x := calc ∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp only [exp', const_apply, re_sum] norm_cast refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_ positivity _ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re] lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x := calc x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! := single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n) _ ≤ exp x := sum_le_exp_of_nonneg hx _ theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x := calc 1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one, ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one, cast_succ, add_right_inj] ring_nf _ ≤ exp x := sum_le_exp_of_nonneg hx 3 private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x := (by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le) private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by rcases eq_or_lt_of_le hx with (rfl | h) · simp exact (add_one_lt_exp_of_pos h).le theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx] @[bound] theorem exp_pos (x : ℝ) : 0 < exp x := (le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by rw [← neg_neg x, Real.exp_neg] exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h))) @[bound] lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le @[simp] theorem abs_exp (x : ℝ) : |exp x| = exp x := abs_of_pos (exp_pos _) lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *] @[mono] theorem exp_strictMono : StrictMono exp := fun x y h => by rw [← sub_add_cancel y x, Real.exp_add] exact (lt_mul_iff_one_lt_left (exp_pos _)).2 (lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith))) @[gcongr] theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h @[mono] theorem exp_monotone : Monotone exp := exp_strictMono.monotone @[gcongr, bound] theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h @[simp] theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y := exp_strictMono.lt_iff_lt @[simp] theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y := exp_strictMono.le_iff_le theorem exp_injective : Function.Injective exp := exp_strictMono.injective @[simp] theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y := exp_injective.eq_iff @[simp] theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 := exp_injective.eq_iff' exp_zero @[simp] theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp] @[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff @[simp] theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp] @[simp] theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 := exp_zero ▸ exp_le_exp @[simp] theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x := exp_zero ▸ exp_le_exp end Real namespace Complex theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α] (n j : ℕ) (hn : 0 < n) : (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) := calc (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) = ∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;> simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le] _ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by simp_rw [one_div] gcongr rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm] exact Nat.factorial_mul_pow_le_factorial _ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow] _ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by have h₁ : (n.succ : α) ≠ 1 := @Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn)) have h₂ : (n.succ : α) ≠ 0 := by positivity have h₃ : (n.factorial * n : α) ≠ 0 := by positivity have h₄ : (n.succ - 1 : α) = n := by simp rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α), ← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α), mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm] _ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr rw [Complex.norm_pow] exact pow_le_one₀ (norm_nonneg _) hx _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by simp [abs_mul, abv_pow abs, abs_div, ← mul_sum] _ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by gcongr exact sum_div_factorial_le _ _ hn theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 let k := j - n have hj : j = n + k := (add_tsub_cancel_of_le hj).symm rw [hj, sum_range_add_sub_sum_range] calc ‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤ ∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ := IsAbsoluteValue.abv_sum _ _ _ _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by simp [norm_natCast, Complex.norm_pow] _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_ _ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_ _ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_ · gcongr exact mod_cast Nat.factorial_mul_pow_le_factorial · refine Finset.sum_congr rfl fun _ _ => ?_ simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc] · rw [← mul_sum] gcongr simp_rw [← div_pow] rw [geom_sum_eq, div_le_iff_of_neg] · trans (-1 : ℝ) · linarith · simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left] positivity · linarith · linarith theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ := calc ‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ] _ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial] theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 := calc ‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial] _ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial] _ = ‖x‖ ^ 2 := by rw [mul_one] lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ _ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj] refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_ congr with i simp [Complex.norm_pow] _ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by gcongr exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _ lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _ rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr with i hi · rw [Complex.norm_pow] · simp _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by rw [← mul_sum] _ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by congr 1 refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm · intro a ha simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true] simp only [mem_range] at ha rwa [← lt_tsub_iff_right] · intro a ha b hb hab simpa using hab · intro b hb simp only [mem_range, exists_prop] simp only [mem_filter, mem_range] at hb refine ⟨b - n, ?_, ?_⟩ · rw [tsub_lt_tsub_iff_right hb.2] exact hb.1 · rw [tsub_add_cancel_of_le hb.2] · simp _ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by gcongr refine Real.sum_le_exp_of_nonneg ?_ _ exact norm_nonneg _ @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum := norm_exp_sub_sum_le_exp_norm_sub_sum @[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp := norm_exp_sub_sum_le_norm_mul_exp end Complex namespace Real open Complex Finset nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) : |exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx convert exp_bound hxc hn using 2 <;> norm_cast theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) : Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) + x ^ n * (n + 1) / (n.factorial * n) := by have h3 : |x| = x := by simpa have h4 : |x| ≤ 1 := by rwa [h3] have h' := Real.exp_bound h4 hn rw [h3] at h' have h'' := (abs_sub_le_iff.1 h').1 have t := sub_le_iff_le_add'.1 h'' simpa [mul_div_assoc] using t theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by rw [← sq_abs] have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_sub_id_le this /-- A finite initial segment of the exponential series, followed by an arbitrary tail. For fixed `n` this is just a linear map wrt `r`, and each map is a simple linear function of the previous (see `expNear_succ`), with `expNear n x r ⟶ exp x` as `n ⟶ ∞`, for any `r`. -/ noncomputable def expNear (n : ℕ) (x r : ℝ) : ℝ := (∑ m ∈ range n, x ^ m / m.factorial) + x ^ n / n.factorial * r @[simp] theorem expNear_zero (x r) : expNear 0 x r = r := by simp [expNear] @[simp] theorem expNear_succ (n x r) : expNear (n + 1) x r = expNear n x (1 + x / (n + 1) * r) := by simp [expNear, range_succ, mul_add, add_left_comm, add_assoc, pow_succ, div_eq_mul_inv, mul_inv, Nat.factorial] ac_rfl theorem expNear_sub (n x r₁ r₂) : expNear n x r₁ - expNear n x r₂ = x ^ n / n.factorial * (r₁ - r₂) := by simp [expNear, mul_sub] theorem exp_approx_end (n m : ℕ) (x : ℝ) (e₁ : n + 1 = m) (h : |x| ≤ 1) : |exp x - expNear m x 0| ≤ |x| ^ m / m.factorial * ((m + 1) / m) := by simp only [expNear, mul_zero, add_zero] convert exp_bound (n := m) h ?_ using 1 · field_simp [mul_comm] · omega theorem exp_approx_succ {n} {x a₁ b₁ : ℝ} (m : ℕ) (e₁ : n + 1 = m) (a₂ b₂ : ℝ) (e : |1 + x / m * a₂ - a₁| ≤ b₁ - |x| / m * b₂) (h : |exp x - expNear m x a₂| ≤ |x| ^ m / m.factorial * b₂) : |exp x - expNear n x a₁| ≤ |x| ^ n / n.factorial * b₁ := by refine (abs_sub_le _ _ _).trans ((add_le_add_right h _).trans ?_) subst e₁; rw [expNear_succ, expNear_sub, abs_mul] convert mul_le_mul_of_nonneg_left (a := |x| ^ n / ↑(Nat.factorial n)) (le_sub_iff_add_le'.1 e) ?_ using 1 · simp [mul_add, pow_succ', div_eq_mul_inv, abs_mul, abs_inv, ← pow_abs, mul_inv, Nat.factorial] ac_rfl · simp [div_nonneg, abs_nonneg] theorem exp_approx_end' {n} {x a b : ℝ} (m : ℕ) (e₁ : n + 1 = m) (rm : ℝ) (er : ↑m = rm) (h : |x| ≤ 1) (e : |1 - a| ≤ b - |x| / rm * ((rm + 1) / rm)) : |exp x - expNear n x a| ≤ |x| ^ n / n.factorial * b := by subst er exact exp_approx_succ _ e₁ _ _ (by simpa using e) (exp_approx_end _ _ _ e₁ h) theorem exp_1_approx_succ_eq {n} {a₁ b₁ : ℝ} {m : ℕ} (en : n + 1 = m) {rm : ℝ} (er : ↑m = rm) (h : |exp 1 - expNear m 1 ((a₁ - 1) * rm)| ≤ |1| ^ m / m.factorial * (b₁ * rm)) : |exp 1 - expNear n 1 a₁| ≤ |1| ^ n / n.factorial * b₁ := by subst er refine exp_approx_succ _ en _ _ ?_ h field_simp [show (m : ℝ) ≠ 0 by norm_cast; omega] theorem exp_approx_start (x a b : ℝ) (h : |exp x - expNear 0 x a| ≤ |x| ^ 0 / Nat.factorial 0 * b) : |exp x - a| ≤ b := by simpa using h theorem exp_bound_div_one_sub_of_interval' {x : ℝ} (h1 : 0 < x) (h2 : x < 1) : Real.exp x < 1 / (1 - x) := by have H : 0 < 1 - (1 + x + x ^ 2) * (1 - x) := calc 0 < x ^ 3 := by positivity _ = 1 - (1 + x + x ^ 2) * (1 - x) := by ring calc exp x ≤ _ := exp_bound' h1.le h2.le zero_lt_three _ ≤ 1 + x + x ^ 2 := by -- Porting note: was `norm_num [Finset.sum] <;> nlinarith` -- This proof should be restored after the norm_num plugin for big operators is ported. -- (It may also need the positivity extensions in https://github.com/leanprover-community/mathlib4/pull/3907.) rw [show 3 = 1 + 1 + 1 from rfl] repeat rw [Finset.sum_range_succ] norm_num [Nat.factorial] nlinarith _ < 1 / (1 - x) := by rw [lt_div_iff₀] <;> nlinarith theorem exp_bound_div_one_sub_of_interval {x : ℝ} (h1 : 0 ≤ x) (h2 : x < 1) : Real.exp x ≤ 1 / (1 - x) := by rcases eq_or_lt_of_le h1 with (rfl | h1) · simp · exact (exp_bound_div_one_sub_of_interval' h1 h2).le theorem add_one_lt_exp {x : ℝ} (hx : x ≠ 0) : x + 1 < Real.exp x := by obtain hx | hx := hx.symm.lt_or_lt · exact add_one_lt_exp_of_pos hx obtain h' | h' := le_or_lt 1 (-x) · linarith [x.exp_pos] have hx' : 0 < x + 1 := by linarith simpa [add_comm, exp_neg, inv_lt_inv₀ (exp_pos _) hx'] using exp_bound_div_one_sub_of_interval' (neg_pos.2 hx) h' theorem add_one_le_exp (x : ℝ) : x + 1 ≤ Real.exp x := by obtain rfl | hx := eq_or_ne x 0 · simp · exact (add_one_lt_exp hx).le lemma one_sub_lt_exp_neg {x : ℝ} (hx : x ≠ 0) : 1 - x < exp (-x) := (sub_eq_neg_add _ _).trans_lt <| add_one_lt_exp <| neg_ne_zero.2 hx lemma one_sub_le_exp_neg (x : ℝ) : 1 - x ≤ exp (-x) := (sub_eq_neg_add _ _).trans_le <| add_one_le_exp _ theorem one_sub_div_pow_le_exp_neg {n : ℕ} {t : ℝ} (ht' : t ≤ n) : (1 - t / n) ^ n ≤ exp (-t) := by rcases eq_or_ne n 0 with (rfl | hn) · simp rwa [Nat.cast_zero] at ht' calc (1 - t / n) ^ n ≤ rexp (-(t / n)) ^ n := by gcongr · exact sub_nonneg.2 <| div_le_one_of_le₀ ht' n.cast_nonneg · exact one_sub_le_exp_neg _ _ = rexp (-t) := by rw [← Real.exp_nat_mul, mul_neg, mul_comm, div_mul_cancel₀]; positivity lemma le_inv_mul_exp (x : ℝ) {c : ℝ} (hc : 0 < c) : x ≤ c⁻¹ * exp (c * x) := by rw [le_inv_mul_iff₀ hc] calc c * x _ ≤ c * x + 1 := le_add_of_nonneg_right zero_le_one _ ≤ _ := Real.add_one_le_exp (c * x) end Real namespace Mathlib.Meta.Positivity open Lean.Meta Qq /-- Extension for the `positivity` tactic: `Real.exp` is always positive. -/ @[positivity Real.exp _] def evalExp : PositivityExt where eval {u α} _ _ e := do match u, α, e with | 0, ~q(ℝ), ~q(Real.exp $a) => assertInstancesCommute pure (.positive q(Real.exp_pos $a)) | _, _, _ => throwError "not Real.exp" end Mathlib.Meta.Positivity namespace Complex @[simp] theorem norm_exp_ofReal (x : ℝ) : ‖exp x‖ = Real.exp x := by rw [← ofReal_exp] exact Complex.norm_of_nonneg (le_of_lt (Real.exp_pos _)) @[deprecated (since := "2025-02-16")] alias abs_exp_ofReal := norm_exp_ofReal end Complex
Mathlib/Data/Complex/Exponential.lean
1,509
1,538
/- Copyright (c) 2022 Paul A. Reichert. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Paul A. Reichert -/ import Mathlib.Analysis.Convex.Basic import Mathlib.Analysis.Normed.Module.Basic import Mathlib.Topology.MetricSpace.HausdorffDistance /-! # Convex bodies This file contains the definition of the type `ConvexBody V` consisting of convex, compact, nonempty subsets of a real topological vector space `V`. `ConvexBody V` is a module over the nonnegative reals (`NNReal`) and a pseudo-metric space. If `V` is a normed space, `ConvexBody V` is a metric space. ## TODO - define positive convex bodies, requiring the interior to be nonempty - introduce support sets - Characterise the interaction of the distance with algebraic operations, eg `dist (a • K) (a • L) = ‖a‖ * dist K L`, `dist (a +ᵥ K) (a +ᵥ L) = dist K L` ## Tags convex, convex body -/ open scoped Pointwise Topology NNReal variable {V : Type*} /-- Let `V` be a real topological vector space. A subset of `V` is a convex body if and only if it is convex, compact, and nonempty. -/ structure ConvexBody (V : Type*) [TopologicalSpace V] [AddCommMonoid V] [SMul ℝ V] where /-- The **carrier set** underlying a convex body: the set of points contained in it -/ carrier : Set V /-- A convex body has convex carrier set -/ convex' : Convex ℝ carrier /-- A convex body has compact carrier set -/ isCompact' : IsCompact carrier /-- A convex body has non-empty carrier set -/ nonempty' : carrier.Nonempty namespace ConvexBody section TVS variable [TopologicalSpace V] [AddCommGroup V] [Module ℝ V] instance : SetLike (ConvexBody V) V where coe := ConvexBody.carrier coe_injective' K L h := by cases K cases L congr protected theorem convex (K : ConvexBody V) : Convex ℝ (K : Set V) := K.convex' protected theorem isCompact (K : ConvexBody V) : IsCompact (K : Set V) := K.isCompact' protected theorem isClosed [T2Space V] (K : ConvexBody V) : IsClosed (K : Set V) := K.isCompact.isClosed protected theorem nonempty (K : ConvexBody V) : (K : Set V).Nonempty := K.nonempty' @[ext] protected theorem ext {K L : ConvexBody V} (h : (K : Set V) = L) : K = L := SetLike.ext' h @[simp] theorem coe_mk (s : Set V) (h₁ h₂ h₃) : (mk s h₁ h₂ h₃ : Set V) = s := rfl /-- A convex body that is symmetric contains `0`. -/ theorem zero_mem_of_symmetric (K : ConvexBody V) (h_symm : ∀ x ∈ K, -x ∈ K) : 0 ∈ K := by obtain ⟨x, hx⟩ := K.nonempty rw [show 0 = (1/2 : ℝ) • x + (1/2 : ℝ) • (- x) by field_simp] apply convex_iff_forall_pos.mp K.convex hx (h_symm x hx) all_goals linarith section ContinuousAdd instance : Zero (ConvexBody V) where zero := ⟨0, convex_singleton 0, isCompact_singleton, Set.singleton_nonempty 0⟩ @[simp] -- Porting note: add norm_cast; we leave it out for now to reproduce mathlib3 behavior. theorem coe_zero : (↑(0 : ConvexBody V) : Set V) = 0 := rfl instance : Inhabited (ConvexBody V) := ⟨0⟩ variable [ContinuousAdd V] instance : Add (ConvexBody V) where add K L := ⟨K + L, K.convex.add L.convex, K.isCompact.add L.isCompact, K.nonempty.add L.nonempty⟩ instance : SMul ℕ (ConvexBody V) where smul := nsmulRec -- Porting note: add @[simp, norm_cast]; we leave it out for now to reproduce mathlib3 behavior. theorem coe_nsmul : ∀ (n : ℕ) (K : ConvexBody V), ↑(n • K) = n • (K : Set V) | 0, _ => rfl | (n + 1), K => congr_arg₂ (Set.image2 (· + ·)) (coe_nsmul n K) rfl instance : AddMonoid (ConvexBody V) := SetLike.coe_injective.addMonoid _ rfl (fun _ _ ↦ rfl) fun _ _ ↦ coe_nsmul _ _ @[simp] -- Porting note: add norm_cast; we leave it out for now to reproduce mathlib3 behavior. theorem coe_add (K L : ConvexBody V) : (↑(K + L) : Set V) = (K : Set V) + L := rfl instance : AddCommMonoid (ConvexBody V) := SetLike.coe_injective.addCommMonoid _ rfl (fun _ _ ↦ rfl) fun _ _ ↦ coe_nsmul _ _ end ContinuousAdd variable [ContinuousSMul ℝ V] instance : SMul ℝ (ConvexBody V) where smul c K := ⟨c • (K : Set V), K.convex.smul _, K.isCompact.smul _, K.nonempty.smul_set⟩ @[simp] -- Porting note: add norm_cast; we leave it out for now to reproduce mathlib3 behavior. theorem coe_smul (c : ℝ) (K : ConvexBody V) : (↑(c • K) : Set V) = c • (K : Set V) := rfl variable [ContinuousAdd V] instance : DistribMulAction ℝ (ConvexBody V) := SetLike.coe_injective.distribMulAction ⟨⟨_, coe_zero⟩, coe_add⟩ coe_smul @[simp] -- Porting note: add norm_cast; we leave it out for now to reproduce mathlib3 behavior. theorem coe_smul' (c : ℝ≥0) (K : ConvexBody V) : (↑(c • K) : Set V) = c • (K : Set V) := rfl /-- The convex bodies in a fixed space $V$ form a module over the nonnegative reals. -/ instance : Module ℝ≥0 (ConvexBody V) where add_smul c d K := SetLike.ext' <| Convex.add_smul K.convex c.coe_nonneg d.coe_nonneg zero_smul K := SetLike.ext' <| Set.zero_smul_set K.nonempty theorem smul_le_of_le (K : ConvexBody V) (h_zero : 0 ∈ K) {a b : ℝ≥0} (h : a ≤ b) : a • K ≤ b • K := by rw [← SetLike.coe_subset_coe, coe_smul', coe_smul'] obtain rfl | ha := eq_zero_or_pos a · rw [Set.zero_smul_set K.nonempty, Set.zero_subset] exact Set.mem_smul_set.mpr ⟨0, h_zero, smul_zero _⟩ · intro x hx obtain ⟨y, hy, rfl⟩ := Set.mem_smul_set.mp hx rw [← Set.mem_inv_smul_set_iff₀ ha.ne', smul_smul] refine Convex.mem_smul_of_zero_mem K.convex h_zero hy (?_ : 1 ≤ a⁻¹ * b) rwa [le_inv_mul_iff₀ ha, mul_one] end TVS section SeminormedAddCommGroup variable [SeminormedAddCommGroup V] [NormedSpace ℝ V] (K L : ConvexBody V) protected theorem isBounded : Bornology.IsBounded (K : Set V) := K.isCompact.isBounded theorem hausdorffEdist_ne_top {K L : ConvexBody V} : EMetric.hausdorffEdist (K : Set V) L ≠ ⊤ := by apply_rules [Metric.hausdorffEdist_ne_top_of_nonempty_of_bounded, ConvexBody.nonempty, ConvexBody.isBounded] /-- Convex bodies in a fixed seminormed space $V$ form a pseudo-metric space under the Hausdorff metric. -/ noncomputable instance : PseudoMetricSpace (ConvexBody V) where dist K L := Metric.hausdorffDist (K : Set V) L dist_self _ := Metric.hausdorffDist_self_zero dist_comm _ _ := Metric.hausdorffDist_comm dist_triangle _ _ _ := Metric.hausdorffDist_triangle hausdorffEdist_ne_top @[simp, norm_cast] theorem hausdorffDist_coe : Metric.hausdorffDist (K : Set V) L = dist K L := rfl @[simp, norm_cast] theorem hausdorffEdist_coe : EMetric.hausdorffEdist (K : Set V) L = edist K L := by rw [edist_dist] exact (ENNReal.ofReal_toReal hausdorffEdist_ne_top).symm open Filter /-- Let `K` be a convex body that contains `0` and let `u n` be a sequence of nonnegative real numbers that tends to `0`. Then the intersection of the dilated bodies `(1 + u n) • K` is equal to `K`. -/ theorem iInter_smul_eq_self [T2Space V] {u : ℕ → ℝ≥0} (K : ConvexBody V) (h_zero : 0 ∈ K) (hu : Tendsto u atTop (𝓝 0)) : ⋂ n : ℕ, (1 + (u n : ℝ)) • (K : Set V) = K := by ext x refine ⟨fun h => ?_, fun h => ?_⟩ · obtain ⟨C, hC_pos, hC_bdd⟩ := K.isBounded.exists_pos_norm_le rw [← K.isClosed.closure_eq, SeminormedAddCommGroup.mem_closure_iff] rw [← NNReal.tendsto_coe, NormedAddCommGroup.tendsto_atTop] at hu intro ε hε obtain ⟨n, hn⟩ := hu (ε / C) (div_pos hε hC_pos) obtain ⟨y, hyK, rfl⟩ := Set.mem_smul_set.mp (Set.mem_iInter.mp h n) refine ⟨y, hyK, ?_⟩ rw [show (1 + u n : ℝ) • y - y = (u n : ℝ) • y by rw [add_smul, one_smul, add_sub_cancel_left], norm_smul, Real.norm_eq_abs] specialize hn n le_rfl rw [lt_div_iff₀' hC_pos, mul_comm, NNReal.coe_zero, sub_zero, Real.norm_eq_abs] at hn refine lt_of_le_of_lt ?_ hn
exact mul_le_mul_of_nonneg_left (hC_bdd _ hyK) (abs_nonneg _) · refine Set.mem_iInter.mpr (fun n => Convex.mem_smul_of_zero_mem K.convex h_zero h ?_) exact le_add_of_nonneg_right (by positivity) end SeminormedAddCommGroup section NormedAddCommGroup variable [NormedAddCommGroup V] [NormedSpace ℝ V] /-- Convex bodies in a fixed normed space `V` form a metric space under the Hausdorff metric. -/ noncomputable instance : MetricSpace (ConvexBody V) where eq_of_dist_eq_zero {K L} hd := ConvexBody.ext <| (K.isClosed.hausdorffDist_zero_iff_eq L.isClosed hausdorffEdist_ne_top).1 hd end NormedAddCommGroup end ConvexBody
Mathlib/Analysis/Convex/Body.lean
217
236
/- Copyright (c) 2019 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Yaël Dillies -/ import Mathlib.Algebra.Module.BigOperators import Mathlib.GroupTheory.Perm.Basic import Mathlib.GroupTheory.Perm.Finite import Mathlib.GroupTheory.Perm.List import Mathlib.GroupTheory.Perm.Sign /-! # Cycles of a permutation This file starts the theory of cycles in permutations. ## Main definitions In the following, `f : Equiv.Perm β`. * `Equiv.Perm.SameCycle`: `f.SameCycle x y` when `x` and `y` are in the same cycle of `f`. * `Equiv.Perm.IsCycle`: `f` is a cycle if any two nonfixed points of `f` are related by repeated applications of `f`, and `f` is not the identity. * `Equiv.Perm.IsCycleOn`: `f` is a cycle on a set `s` when any two points of `s` are related by repeated applications of `f`. ## Notes `Equiv.Perm.IsCycle` and `Equiv.Perm.IsCycleOn` are different in three ways: * `IsCycle` is about the entire type while `IsCycleOn` is restricted to a set. * `IsCycle` forbids the identity while `IsCycleOn` allows it (if `s` is a subsingleton). * `IsCycleOn` forbids fixed points on `s` (if `s` is nontrivial), while `IsCycle` allows them. -/ open Equiv Function Finset variable {ι α β : Type*} namespace Equiv.Perm /-! ### `SameCycle` -/ section SameCycle variable {f g : Perm α} {p : α → Prop} {x y z : α} /-- The equivalence relation indicating that two points are in the same cycle of a permutation. -/ def SameCycle (f : Perm α) (x y : α) : Prop := ∃ i : ℤ, (f ^ i) x = y @[refl] theorem SameCycle.refl (f : Perm α) (x : α) : SameCycle f x x := ⟨0, rfl⟩ theorem SameCycle.rfl : SameCycle f x x := SameCycle.refl _ _ protected theorem _root_.Eq.sameCycle (h : x = y) (f : Perm α) : f.SameCycle x y := by rw [h] @[symm] theorem SameCycle.symm : SameCycle f x y → SameCycle f y x := fun ⟨i, hi⟩ => ⟨-i, by rw [zpow_neg, ← hi, inv_apply_self]⟩ theorem sameCycle_comm : SameCycle f x y ↔ SameCycle f y x := ⟨SameCycle.symm, SameCycle.symm⟩ @[trans] theorem SameCycle.trans : SameCycle f x y → SameCycle f y z → SameCycle f x z := fun ⟨i, hi⟩ ⟨j, hj⟩ => ⟨j + i, by rw [zpow_add, mul_apply, hi, hj]⟩ variable (f) in theorem SameCycle.equivalence : Equivalence (SameCycle f) := ⟨SameCycle.refl f, SameCycle.symm, SameCycle.trans⟩ /-- The setoid defined by the `SameCycle` relation. -/ def SameCycle.setoid (f : Perm α) : Setoid α where r := f.SameCycle iseqv := SameCycle.equivalence f @[simp] theorem sameCycle_one : SameCycle 1 x y ↔ x = y := by simp [SameCycle] @[simp] theorem sameCycle_inv : SameCycle f⁻¹ x y ↔ SameCycle f x y := (Equiv.neg _).exists_congr_left.trans <| by simp [SameCycle] alias ⟨SameCycle.of_inv, SameCycle.inv⟩ := sameCycle_inv @[simp] theorem sameCycle_conj : SameCycle (g * f * g⁻¹) x y ↔ SameCycle f (g⁻¹ x) (g⁻¹ y) := exists_congr fun i => by simp [conj_zpow, eq_inv_iff_eq] theorem SameCycle.conj : SameCycle f x y → SameCycle (g * f * g⁻¹) (g x) (g y) := by simp [sameCycle_conj] theorem SameCycle.apply_eq_self_iff : SameCycle f x y → (f x = x ↔ f y = y) := fun ⟨i, hi⟩ => by rw [← hi, ← mul_apply, ← zpow_one_add, add_comm, zpow_add_one, mul_apply, (f ^ i).injective.eq_iff] theorem SameCycle.eq_of_left (h : SameCycle f x y) (hx : IsFixedPt f x) : x = y := let ⟨_, hn⟩ := h (hx.perm_zpow _).eq.symm.trans hn theorem SameCycle.eq_of_right (h : SameCycle f x y) (hy : IsFixedPt f y) : x = y := h.eq_of_left <| h.apply_eq_self_iff.2 hy @[simp] theorem sameCycle_apply_left : SameCycle f (f x) y ↔ SameCycle f x y := (Equiv.addRight 1).exists_congr_left.trans <| by simp [zpow_sub, SameCycle, Int.add_neg_one, Function.comp] @[simp] theorem sameCycle_apply_right : SameCycle f x (f y) ↔ SameCycle f x y := by rw [sameCycle_comm, sameCycle_apply_left, sameCycle_comm] @[simp] theorem sameCycle_inv_apply_left : SameCycle f (f⁻¹ x) y ↔ SameCycle f x y := by rw [← sameCycle_apply_left, apply_inv_self] @[simp] theorem sameCycle_inv_apply_right : SameCycle f x (f⁻¹ y) ↔ SameCycle f x y := by rw [← sameCycle_apply_right, apply_inv_self] @[simp] theorem sameCycle_zpow_left {n : ℤ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y := (Equiv.addRight (n : ℤ)).exists_congr_left.trans <| by simp [SameCycle, zpow_add] @[simp] theorem sameCycle_zpow_right {n : ℤ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by rw [sameCycle_comm, sameCycle_zpow_left, sameCycle_comm] @[simp] theorem sameCycle_pow_left {n : ℕ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y := by rw [← zpow_natCast, sameCycle_zpow_left] @[simp] theorem sameCycle_pow_right {n : ℕ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by rw [← zpow_natCast, sameCycle_zpow_right] alias ⟨SameCycle.of_apply_left, SameCycle.apply_left⟩ := sameCycle_apply_left alias ⟨SameCycle.of_apply_right, SameCycle.apply_right⟩ := sameCycle_apply_right alias ⟨SameCycle.of_inv_apply_left, SameCycle.inv_apply_left⟩ := sameCycle_inv_apply_left
alias ⟨SameCycle.of_inv_apply_right, SameCycle.inv_apply_right⟩ := sameCycle_inv_apply_right
Mathlib/GroupTheory/Perm/Cycle/Basic.lean
147
148
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro -/ import Mathlib.Data.ENNReal.Action import Mathlib.MeasureTheory.MeasurableSpace.Constructions import Mathlib.MeasureTheory.OuterMeasure.Caratheodory /-! # Induced Outer Measure We can extend a function defined on a subset of `Set α` to an outer measure. The underlying function is called `extend`, and the measure it induces is called `inducedOuterMeasure`. Some lemmas below are proven twice, once in the general case, and one where the function `m` is only defined on measurable sets (i.e. when `P = MeasurableSet`). In the latter cases, we can remove some hypotheses in the statement. The general version has the same name, but with a prime at the end. ## Tags outer measure -/ noncomputable section open Set Function Filter open scoped NNReal Topology ENNReal namespace MeasureTheory open OuterMeasure section Extend variable {α : Type*} {P : α → Prop} variable (m : ∀ s : α, P s → ℝ≥0∞) /-- We can trivially extend a function defined on a subclass of objects (with codomain `ℝ≥0∞`) to all objects by defining it to be `∞` on the objects not in the class. -/ def extend (s : α) : ℝ≥0∞ := ⨅ h : P s, m s h theorem extend_eq {s : α} (h : P s) : extend m s = m s h := by simp [extend, h]
Mathlib/MeasureTheory/OuterMeasure/Induced.lean
49
49
/- 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, Yury Kudryashov -/ import Mathlib.Data.List.Forall2 import Mathlib.Data.List.Lex import Mathlib.Logic.Function.Iterate import Mathlib.Logic.Relation /-! # Relation chain This file provides basic results about `List.Chain` (definition in `Data.List.Defs`). A list `[a₂, ..., aₙ]` is a `Chain` starting at `a₁` with respect to the relation `r` if `r a₁ a₂` and `r a₂ a₃` and ... and `r aₙ₋₁ aₙ`. We write it `Chain r a₁ [a₂, ..., aₙ]`. A graph-specialized version is in development and will hopefully be added under `combinatorics.` sometime soon. -/ assert_not_imported Mathlib.Algebra.Order.Group.Nat universe u v open Nat namespace List variable {α : Type u} {β : Type v} {R r : α → α → Prop} {l l₁ l₂ : List α} {a b : α} mk_iff_of_inductive_prop List.Chain List.chain_iff theorem Chain.iff {S : α → α → Prop} (H : ∀ a b, R a b ↔ S a b) {a : α} {l : List α} : Chain R a l ↔ Chain S a l := ⟨Chain.imp fun a b => (H a b).1, Chain.imp fun a b => (H a b).2⟩ theorem Chain.iff_mem {a : α} {l : List α} : Chain R a l ↔ Chain (fun x y => x ∈ a :: l ∧ y ∈ l ∧ R x y) a l := ⟨fun p => by induction p with | nil => exact nil | @cons _ _ _ r _ IH => constructor · exact ⟨mem_cons_self, mem_cons_self, r⟩ · exact IH.imp fun a b ⟨am, bm, h⟩ => ⟨mem_cons_of_mem _ am, mem_cons_of_mem _ bm, h⟩, Chain.imp fun _ _ h => h.2.2⟩ theorem chain_singleton {a b : α} : Chain R a [b] ↔ R a b := by simp only [chain_cons, Chain.nil, and_true] theorem chain_split {a b : α} {l₁ l₂ : List α} : Chain R a (l₁ ++ b :: l₂) ↔ Chain R a (l₁ ++ [b]) ∧ Chain R b l₂ := by induction' l₁ with x l₁ IH generalizing a <;> simp only [*, nil_append, cons_append, Chain.nil, chain_cons, and_true, and_assoc] @[simp] theorem chain_append_cons_cons {a b c : α} {l₁ l₂ : List α} : Chain R a (l₁ ++ b :: c :: l₂) ↔ Chain R a (l₁ ++ [b]) ∧ R b c ∧ Chain R c l₂ := by rw [chain_split, chain_cons] theorem chain_iff_forall₂ : ∀ {a : α} {l : List α}, Chain R a l ↔ l = [] ∨ Forall₂ R (a :: dropLast l) l | a, [] => by simp | a, b :: l => by by_cases h : l = [] <;> simp [@chain_iff_forall₂ b l, dropLast, *] theorem chain_append_singleton_iff_forall₂ : Chain R a (l ++ [b]) ↔ Forall₂ R (a :: l) (l ++ [b]) := by simp [chain_iff_forall₂] theorem chain_map (f : β → α) {b : β} {l : List β} : Chain R (f b) (map f l) ↔ Chain (fun a b : β => R (f a) (f b)) b l := by induction l generalizing b <;> simp only [map, Chain.nil, chain_cons, *] theorem chain_of_chain_map {S : β → β → Prop} (f : α → β) (H : ∀ a b : α, S (f a) (f b) → R a b) {a : α} {l : List α} (p : Chain S (f a) (map f l)) : Chain R a l := ((chain_map f).1 p).imp H theorem chain_map_of_chain {S : β → β → Prop} (f : α → β) (H : ∀ a b : α, R a b → S (f a) (f b)) {a : α} {l : List α} (p : Chain R a l) : Chain S (f a) (map f l) := (chain_map f).2 <| p.imp H
theorem chain_pmap_of_chain {S : β → β → Prop} {p : α → Prop} {f : ∀ a, p a → β}
Mathlib/Data/List/Chain.lean
82
83
/- 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.Analysis.SpecialFunctions.Log.Deriv import Mathlib.Analysis.SpecialFunctions.Pow.Asymptotics import Mathlib.Analysis.Convex.Deriv /-! # The function `x ↦ - x * log x` The purpose of this file is to record basic analytic properties of the function `x ↦ - x * log x`, which is notably used in the theory of Shannon entropy. ## Main definitions * `negMulLog`: the function `x ↦ - x * log x` from `ℝ` to `ℝ`. -/ open scoped Topology namespace Real @[fun_prop] lemma continuous_mul_log : Continuous fun x ↦ x * log x := by rw [continuous_iff_continuousAt] intro x obtain hx | rfl := ne_or_eq x 0 · exact (continuous_id'.continuousAt).mul (continuousAt_log hx) rw [ContinuousAt, zero_mul] simp_rw [mul_comm _ (log _)] nth_rewrite 1 [← nhdsWithin_univ] have : (Set.univ : Set ℝ) = Set.Iio 0 ∪ Set.Ioi 0 ∪ {0} := by ext; simp [em] rw [this, nhdsWithin_union, nhdsWithin_union] simp only [nhdsWithin_singleton, sup_le_iff, Filter.nonpos_iff, Filter.tendsto_sup] refine ⟨⟨tendsto_log_mul_self_nhdsLT_zero, ?_⟩, ?_⟩ · simpa only [rpow_one] using tendsto_log_mul_rpow_nhdsGT_zero zero_lt_one · convert tendsto_pure_nhds (fun x ↦ log x * x) 0 simp @[fun_prop] lemma Continuous.mul_log {α : Type*} [TopologicalSpace α] {f : α → ℝ} (hf : Continuous f) : Continuous fun a ↦ f a * log (f a) := continuous_mul_log.comp hf lemma differentiableOn_mul_log : DifferentiableOn ℝ (fun x ↦ x * log x) {0}ᶜ := differentiable_id'.differentiableOn.mul differentiableOn_log @[simp] lemma deriv_mul_log {x : ℝ} (hx : x ≠ 0) : deriv (fun x ↦ x * log x) x = log x + 1 := by rw [deriv_mul differentiableAt_id' (differentiableAt_log hx)] simp only [deriv_id'', one_mul, deriv_log', ne_eq, add_right_inj] exact mul_inv_cancel₀ hx lemma hasDerivAt_mul_log {x : ℝ} (hx : x ≠ 0) : HasDerivAt (fun x ↦ x * log x) (log x + 1) x := by rw [← deriv_mul_log hx, hasDerivAt_deriv_iff] refine DifferentiableOn.differentiableAt differentiableOn_mul_log ?_ simp [hx] @[simp] lemma rightDeriv_mul_log {x : ℝ} (hx : x ≠ 0) : derivWithin (fun x ↦ x * log x) (Set.Ioi x) x = log x + 1 := (hasDerivAt_mul_log hx).hasDerivWithinAt.derivWithin (uniqueDiffWithinAt_Ioi x) @[simp] lemma leftDeriv_mul_log {x : ℝ} (hx : x ≠ 0) : derivWithin (fun x ↦ x * log x) (Set.Iio x) x = log x + 1 := (hasDerivAt_mul_log hx).hasDerivWithinAt.derivWithin (uniqueDiffWithinAt_Iio x) open Filter in private lemma tendsto_deriv_mul_log_nhdsWithin_zero : Tendsto (deriv (fun x ↦ x * log x)) (𝓝[>] 0) atBot := by have : (deriv (fun x ↦ x * log x)) =ᶠ[𝓝[>] 0] (fun x ↦ log x + 1) := by apply eventuallyEq_nhdsWithin_of_eqOn intro x hx rw [Set.mem_Ioi] at hx exact deriv_mul_log hx.ne' simp only [tendsto_congr' this, tendsto_atBot_add_const_right, tendsto_log_nhdsGT_zero] open Filter in lemma tendsto_deriv_mul_log_atTop : Tendsto (fun x ↦ deriv (fun x ↦ x * log x) x) atTop atTop := by refine (tendsto_congr' ?_).mpr (tendsto_log_atTop.atTop_add (tendsto_const_nhds (x := 1))) rw [EventuallyEq, eventually_atTop] exact ⟨1, fun _ hx ↦ deriv_mul_log (zero_lt_one.trans_le hx).ne'⟩ open Filter in lemma tendsto_rightDeriv_mul_log_atTop : Tendsto (fun x ↦ derivWithin (fun x ↦ x * log x) (Set.Ioi x) x) atTop atTop := by refine (tendsto_congr' ?_).mpr (tendsto_log_atTop.atTop_add (tendsto_const_nhds (x := 1))) rw [EventuallyEq, eventually_atTop] exact ⟨1, fun _ hx ↦ rightDeriv_mul_log (zero_lt_one.trans_le hx).ne'⟩ /-- At `x=0`, `(fun x ↦ x * log x)` is not differentiable (but note that it is continuous, see `continuous_mul_log`). -/ lemma not_DifferentiableAt_log_mul_zero : ¬ DifferentiableAt ℝ (fun x ↦ x * log x) 0 := fun h ↦ (not_differentiableWithinAt_of_deriv_tendsto_atBot_Ioi (fun x : ℝ ↦ x * log x) (a := 0)) tendsto_deriv_mul_log_nhdsWithin_zero (h.differentiableWithinAt (s := Set.Ioi 0)) /-- Not differentiable, hence `deriv` has junk value zero. -/ lemma deriv_mul_log_zero : deriv (fun x ↦ x * log x) 0 = 0 := deriv_zero_of_not_differentiableAt not_DifferentiableAt_log_mul_zero
lemma not_continuousAt_deriv_mul_log_zero :
Mathlib/Analysis/SpecialFunctions/Log/NegMulLog.lean
106
107
/- Copyright (c) 2022 Jujian Zhang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jujian Zhang, Andrew Yang -/ import Mathlib.AlgebraicGeometry.ProjectiveSpectrum.StructureSheaf import Mathlib.AlgebraicGeometry.GammaSpecAdjunction import Mathlib.RingTheory.GradedAlgebra.Radical /-! # Proj as a scheme This file is to prove that `Proj` is a scheme. ## Notation * `Proj` : `Proj` as a locally ringed space * `Proj.T` : the underlying topological space of `Proj` * `Proj| U` : `Proj` restricted to some open set `U` * `Proj.T| U` : the underlying topological space of `Proj` restricted to open set `U` * `pbo f` : basic open set at `f` in `Proj` * `Spec` : `Spec` as a locally ringed space * `Spec.T` : the underlying topological space of `Spec` * `sbo g` : basic open set at `g` in `Spec` * `A⁰_x` : the degree zero part of localized ring `Aₓ` ## Implementation In `AlgebraicGeometry/ProjectiveSpectrum/StructureSheaf.lean`, we have given `Proj` a structure sheaf so that `Proj` is a locally ringed space. In this file we will prove that `Proj` equipped with this structure sheaf is a scheme. We achieve this by using an affine cover by basic open sets in `Proj`, more specifically: 1. We prove that `Proj` can be covered by basic open sets at homogeneous element of positive degree. 2. We prove that for any homogeneous element `f : A` of positive degree `m`, `Proj.T | (pbo f)` is homeomorphic to `Spec.T A⁰_f`: - forward direction `toSpec`: for any `x : pbo f`, i.e. a relevant homogeneous prime ideal `x`, send it to `A⁰_f ∩ span {g / 1 | g ∈ x}` (see `ProjIsoSpecTopComponent.IoSpec.carrier`). This ideal is prime, the proof is in `ProjIsoSpecTopComponent.ToSpec.toFun`. The fact that this function is continuous is found in `ProjIsoSpecTopComponent.toSpec` - backward direction `fromSpec`: for any `q : Spec A⁰_f`, we send it to `{a | ∀ i, aᵢᵐ/fⁱ ∈ q}`; we need this to be a homogeneous prime ideal that is relevant. * This is in fact an ideal, the proof can be found in `ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal`; * This ideal is also homogeneous, the proof can be found in `ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal.homogeneous`; * This ideal is relevant, the proof can be found in `ProjIsoSpecTopComponent.FromSpec.carrier.relevant`; * This ideal is prime, the proof can be found in `ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal.prime`. Hence we have a well defined function `Spec.T A⁰_f → Proj.T | (pbo f)`, this function is called `ProjIsoSpecTopComponent.FromSpec.toFun`. But to prove the continuity of this function, we need to prove `fromSpec ∘ toSpec` and `toSpec ∘ fromSpec` are both identities; these are achieved in `ProjIsoSpecTopComponent.fromSpec_toSpec` and `ProjIsoSpecTopComponent.toSpec_fromSpec`. 3. Then we construct a morphism of locally ringed spaces `α : Proj| (pbo f) ⟶ Spec.T A⁰_f` as the following: by the Gamma-Spec adjunction, it is sufficient to construct a ring map `A⁰_f → Γ(Proj, pbo f)` from the ring of homogeneous localization of `A` away from `f` to the local sections of structure sheaf of projective spectrum on the basic open set around `f`. The map `A⁰_f → Γ(Proj, pbo f)` is constructed in `awayToΓ` and is defined by sending `s ∈ A⁰_f` to the section `x ↦ s` on `pbo f`. ## Main Definitions and Statements For a homogeneous element `f` of degree `m` * `ProjIsoSpecTopComponent.toSpec`: the continuous map between `Proj.T| pbo f` and `Spec.T A⁰_f` defined by sending `x : Proj| (pbo f)` to `A⁰_f ∩ span {g / 1 | g ∈ x}`. We also denote this map as `ψ`. * `ProjIsoSpecTopComponent.ToSpec.preimage_eq`: for any `a: A`, if `a/f^m` has degree zero, then the preimage of `sbo a/f^m` under `toSpec f` is `pbo f ∩ pbo a`. If we further assume `m` is positive * `ProjIsoSpecTopComponent.fromSpec`: the continuous map between `Spec.T A⁰_f` and `Proj.T| pbo f` defined by sending `q` to `{a | aᵢᵐ/fⁱ ∈ q}` where `aᵢ` is the `i`-th coordinate of `a`. We also denote this map as `φ` * `projIsoSpecTopComponent`: the homeomorphism `Proj.T| pbo f ≅ Spec.T A⁰_f` obtained by `φ` and `ψ`. * `ProjectiveSpectrum.Proj.toSpec`: the morphism of locally ringed spaces between `Proj| pbo f` and `Spec A⁰_f` corresponding to the ring map `A⁰_f → Γ(Proj, pbo f)` under the Gamma-Spec adjunction defined by sending `s` to the section `x ↦ s` on `pbo f`. Finally, * `AlgebraicGeometry.Proj`: for any `ℕ`-graded ring `A`, `Proj A` is locally affine, hence is a scheme. ## Reference * [Robin Hartshorne, *Algebraic Geometry*][Har77]: Chapter II.2 Proposition 2.5 -/ noncomputable section namespace AlgebraicGeometry open scoped DirectSum Pointwise open DirectSum SetLike.GradedMonoid Localization open Finset hiding mk_zero variable {R A : Type*} variable [CommRing R] [CommRing A] [Algebra R A] variable (𝒜 : ℕ → Submodule R A) variable [GradedAlgebra 𝒜] open TopCat TopologicalSpace open CategoryTheory Opposite open ProjectiveSpectrum.StructureSheaf -- Porting note: currently require lack of hygiene to use in variable declarations -- maybe all make into notation3? set_option hygiene false /-- `Proj` as a locally ringed space -/ local notation3 "Proj" => Proj.toLocallyRingedSpace 𝒜 /-- The underlying topological space of `Proj` -/ local notation3 "Proj.T" => PresheafedSpace.carrier <| SheafedSpace.toPresheafedSpace <| LocallyRingedSpace.toSheafedSpace <| Proj.toLocallyRingedSpace 𝒜 /-- `Proj` restrict to some open set -/ macro "Proj| " U:term : term => `((Proj.toLocallyRingedSpace 𝒜).restrict (Opens.isOpenEmbedding (X := Proj.T) ($U : Opens Proj.T))) /-- the underlying topological space of `Proj` restricted to some open set -/ local notation "Proj.T| " U => PresheafedSpace.carrier <| SheafedSpace.toPresheafedSpace <| LocallyRingedSpace.toSheafedSpace <| (LocallyRingedSpace.restrict Proj (Opens.isOpenEmbedding (X := Proj.T) (U : Opens Proj.T))) /-- basic open sets in `Proj` -/ local notation "pbo " x => ProjectiveSpectrum.basicOpen 𝒜 x /-- basic open sets in `Spec` -/ local notation "sbo " f => PrimeSpectrum.basicOpen f /-- `Spec` as a locally ringed space -/ local notation3 "Spec " ring => Spec.locallyRingedSpaceObj (CommRingCat.of ring) /-- the underlying topological space of `Spec` -/ local notation "Spec.T " ring => (Spec.locallyRingedSpaceObj (CommRingCat.of ring)).toSheafedSpace.toPresheafedSpace.1 local notation3 "A⁰_ " f => HomogeneousLocalization.Away 𝒜 f namespace ProjIsoSpecTopComponent /- This section is to construct the homeomorphism between `Proj` restricted at basic open set at a homogeneous element `x` and `Spec A⁰ₓ` where `A⁰ₓ` is the degree zero part of the localized ring `Aₓ`. -/ namespace ToSpec open Ideal -- This section is to construct the forward direction : -- So for any `x` in `Proj| (pbo f)`, we need some point in `Spec A⁰_f`, i.e. a prime ideal, -- and we need this correspondence to be continuous in their Zariski topology. variable {𝒜} variable {f : A} {m : ℕ} (x : Proj| (pbo f)) /-- For any `x` in `Proj| (pbo f)`, the corresponding ideal in `Spec A⁰_f`. This fact that this ideal is prime is proven in `TopComponent.Forward.toFun`. -/ def carrier : Ideal (A⁰_ f) := Ideal.comap (algebraMap (A⁰_ f) (Away f)) (x.val.asHomogeneousIdeal.toIdeal.map (algebraMap A (Away f))) @[simp] theorem mk_mem_carrier (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) : HomogeneousLocalization.mk z ∈ carrier x ↔ z.num.1 ∈ x.1.asHomogeneousIdeal := by rw [carrier, Ideal.mem_comap, HomogeneousLocalization.algebraMap_apply, HomogeneousLocalization.val_mk, Localization.mk_eq_mk', IsLocalization.mk'_eq_mul_mk'_one, mul_comm, Ideal.unit_mul_mem_iff_mem, ← Ideal.mem_comap, IsLocalization.comap_map_of_isPrime_disjoint (.powers f)] · rfl · infer_instance · exact (disjoint_powers_iff_not_mem _ (Ideal.IsPrime.isRadical inferInstance)).mpr x.2 · exact isUnit_of_invertible _ theorem isPrime_carrier : Ideal.IsPrime (carrier x) := by refine Ideal.IsPrime.comap _ (hK := ?_) exact IsLocalization.isPrime_of_isPrime_disjoint (Submonoid.powers f) _ _ inferInstance ((disjoint_powers_iff_not_mem _ (Ideal.IsPrime.isRadical inferInstance)).mpr x.2) variable (f) /-- The function between the basic open set `D(f)` in `Proj` to the corresponding basic open set in `Spec A⁰_f`. This is bundled into a continuous map in `TopComponent.forward`. -/ @[simps -isSimp] def toFun (x : Proj.T| pbo f) : Spec.T A⁰_ f := ⟨carrier x, isPrime_carrier x⟩ /- The preimage of basic open set `D(a/f^n)` in `Spec A⁰_f` under the forward map from `Proj A` to `Spec A⁰_f` is the basic open set `D(a) ∩ D(f)` in `Proj A`. This lemma is used to prove that the forward map is continuous. -/ theorem preimage_basicOpen (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) : toFun f ⁻¹' (sbo (HomogeneousLocalization.mk z) : Set (PrimeSpectrum (A⁰_ f))) = Subtype.val ⁻¹' (pbo z.num.1 : Set (ProjectiveSpectrum 𝒜)) := Set.ext fun y ↦ (mk_mem_carrier y z).not end ToSpec section /-- The continuous function from the basic open set `D(f)` in `Proj` to the corresponding basic open set in `Spec A⁰_f`. -/ @[simps! -isSimp hom_apply_asIdeal] def toSpec (f : A) : (Proj.T| pbo f) ⟶ Spec.T A⁰_ f := TopCat.ofHom { toFun := ToSpec.toFun f continuous_toFun := by rw [PrimeSpectrum.isTopologicalBasis_basic_opens.continuous_iff] rintro _ ⟨x, rfl⟩ obtain ⟨x, rfl⟩ := Quotient.mk''_surjective x rw [ToSpec.preimage_basicOpen] exact (pbo x.num).2.preimage continuous_subtype_val } variable {𝒜} in lemma toSpec_preimage_basicOpen {f} (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) : toSpec 𝒜 f ⁻¹' (sbo (HomogeneousLocalization.mk z) : Set (PrimeSpectrum (A⁰_ f))) = Subtype.val ⁻¹' (pbo z.num.1 : Set (ProjectiveSpectrum 𝒜)) := ToSpec.preimage_basicOpen f z end namespace FromSpec open GradedAlgebra SetLike open Finset hiding mk_zero open HomogeneousLocalization variable {𝒜} variable {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) open Lean Meta Elab Tactic macro "mem_tac_aux" : tactic => `(tactic| first | exact pow_mem_graded _ (Submodule.coe_mem _) | exact natCast_mem_graded _ _ | exact pow_mem_graded _ f_deg) macro "mem_tac" : tactic => `(tactic| first | mem_tac_aux | repeat (all_goals (apply SetLike.GradedMonoid.toGradedMul.mul_mem)); mem_tac_aux) /-- The function from `Spec A⁰_f` to `Proj|D(f)` is defined by `q ↦ {a | aᵢᵐ/fⁱ ∈ q}`, i.e. sending `q` a prime ideal in `A⁰_f` to the homogeneous prime relevant ideal containing only and all the elements `a : A` such that for every `i`, the degree 0 element formed by dividing the `m`-th power of the `i`-th projection of `a` by the `i`-th power of the degree-`m` homogeneous element `f`, lies in `q`. The set `{a | aᵢᵐ/fⁱ ∈ q}` * is an ideal, as proved in `carrier.asIdeal`; * is homogeneous, as proved in `carrier.asHomogeneousIdeal`; * is prime, as proved in `carrier.asIdeal.prime`; * is relevant, as proved in `carrier.relevant`. -/ def carrier (f_deg : f ∈ 𝒜 m) (q : Spec.T A⁰_ f) : Set A := {a | ∀ i, (HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ m, by rw [← smul_eq_mul]; mem_tac⟩, ⟨f ^ i, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.1} theorem mem_carrier_iff (q : Spec.T A⁰_ f) (a : A) : a ∈ carrier f_deg q ↔ ∀ i, (HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ m, by rw [← smul_eq_mul]; mem_tac⟩, ⟨f ^ i, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.1 := Iff.rfl theorem mem_carrier_iff' (q : Spec.T A⁰_ f) (a : A) : a ∈ carrier f_deg q ↔ ∀ i, (Localization.mk (proj 𝒜 i a ^ m) ⟨f ^ i, ⟨i, rfl⟩⟩ : Localization.Away f) ∈ algebraMap (HomogeneousLocalization.Away 𝒜 f) (Localization.Away f) '' { s | s ∈ q.1 } := (mem_carrier_iff f_deg q a).trans (by constructor <;> intro h i <;> specialize h i · rw [Set.mem_image]; refine ⟨_, h, rfl⟩ · rw [Set.mem_image] at h; rcases h with ⟨x, h, hx⟩ change x ∈ q.asIdeal at h convert h rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk] dsimp only [Subtype.coe_mk]; rw [← hx]; rfl) theorem mem_carrier_iff_of_mem (hm : 0 < m) (q : Spec.T A⁰_ f) (a : A) {n} (hn : a ∈ 𝒜 n) : a ∈ carrier f_deg q ↔ (HomogeneousLocalization.mk ⟨m * n, ⟨a ^ m, pow_mem_graded m hn⟩, ⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal := by trans (HomogeneousLocalization.mk ⟨m * n, ⟨proj 𝒜 n a ^ m, by rw [← smul_eq_mul]; mem_tac⟩, ⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal · refine ⟨fun h ↦ h n, fun h i ↦ if hi : i = n then hi ▸ h else ?_⟩ convert zero_mem q.asIdeal apply HomogeneousLocalization.val_injective simp only [proj_apply, decompose_of_mem_ne _ hn (Ne.symm hi), zero_pow hm.ne', HomogeneousLocalization.val_mk, Localization.mk_zero, HomogeneousLocalization.val_zero] · simp only [proj_apply, decompose_of_mem_same _ hn] theorem mem_carrier_iff_of_mem_mul (hm : 0 < m) (q : Spec.T A⁰_ f) (a : A) {n} (hn : a ∈ 𝒜 (n * m)) : a ∈ carrier f_deg q ↔ (HomogeneousLocalization.mk ⟨m * n, ⟨a, mul_comm n m ▸ hn⟩, ⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal := by rw [mem_carrier_iff_of_mem f_deg hm q a hn, iff_iff_eq, eq_comm, ← Ideal.IsPrime.pow_mem_iff_mem (α := A⁰_ f) inferInstance m hm] congr 1 apply HomogeneousLocalization.val_injective simp only [HomogeneousLocalization.val_mk, HomogeneousLocalization.val_pow, Localization.mk_pow, pow_mul] rfl theorem num_mem_carrier_iff (hm : 0 < m) (q : Spec.T A⁰_ f) (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) : z.num.1 ∈ carrier f_deg q ↔ HomogeneousLocalization.mk z ∈ q.asIdeal := by obtain ⟨n, hn : f ^ n = _⟩ := z.den_mem have : f ^ n ≠ 0 := fun e ↦ by have := HomogeneousLocalization.subsingleton 𝒜 (x := .powers f) ⟨n, e⟩ exact IsEmpty.elim (inferInstanceAs (IsEmpty (PrimeSpectrum (A⁰_ f)))) q convert mem_carrier_iff_of_mem_mul f_deg hm q z.num.1 (n := n) ?_ using 2 · apply HomogeneousLocalization.val_injective; simp only [hn, HomogeneousLocalization.val_mk] · have := degree_eq_of_mem_mem 𝒜 (SetLike.pow_mem_graded n f_deg) (hn.symm ▸ z.den.2) this rw [← smul_eq_mul, this]; exact z.num.2 theorem carrier.add_mem (q : Spec.T A⁰_ f) {a b : A} (ha : a ∈ carrier f_deg q) (hb : b ∈ carrier f_deg q) : a + b ∈ carrier f_deg q := by refine fun i => (q.2.mem_or_mem ?_).elim id id change (HomogeneousLocalization.mk ⟨_, _, _, _⟩ : A⁰_ f) ∈ q.1; dsimp only [Subtype.coe_mk] simp_rw [← pow_add, map_add, add_pow, mul_comm, ← nsmul_eq_mul] let g : ℕ → A⁰_ f := fun j => (m + m).choose j • if h2 : m + m < j then (0 : A⁰_ f) else -- Porting note: inlining `l`, `r` causes a "can't synth HMul A⁰_ f A⁰_ f ?" error if h1 : j ≤ m then letI l : A⁰_ f := HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ j * proj 𝒜 i b ^ (m - j), ?_⟩, ⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩ letI r : A⁰_ f := (HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i b ^ m, by rw [← smul_eq_mul]; mem_tac⟩, ⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩) l * r else letI l : A⁰_ f := HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ m, by rw [← smul_eq_mul]; mem_tac⟩, ⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩ letI r : A⁰_ f := HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ (j - m) * proj 𝒜 i b ^ (m + m - j), ?_⟩, ⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩ l * r rotate_left · rw [(_ : m * i = _)] apply GradedMonoid.toGradedMul.mul_mem <;> mem_tac_aux rw [← add_smul, Nat.add_sub_of_le h1]; rfl · rw [(_ : m * i = _)] apply GradedMonoid.toGradedMul.mul_mem (i := (j-m) • i) (j := (m + m - j) • i) <;> mem_tac_aux rw [← add_smul]; congr; zify [le_of_not_lt h2, le_of_not_le h1]; abel convert_to ∑ i ∈ range (m + m + 1), g i ∈ q.1; swap · refine q.1.sum_mem fun j _ => nsmul_mem ?_ _; split_ifs exacts [q.1.zero_mem, q.1.mul_mem_left _ (hb i), q.1.mul_mem_right _ (ha i)] rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk] change _ = (algebraMap (HomogeneousLocalization.Away 𝒜 f) (Localization.Away f)) _ dsimp only [Subtype.coe_mk]; rw [map_sum, mk_sum] apply Finset.sum_congr rfl fun j hj => _ intro j hj change _ = HomogeneousLocalization.val _ rw [HomogeneousLocalization.val_smul] split_ifs with h2 h1 · exact ((Finset.mem_range.1 hj).not_le h2).elim all_goals simp only [HomogeneousLocalization.val_mul, HomogeneousLocalization.val_zero, HomogeneousLocalization.val_mk, Subtype.coe_mk, Localization.mk_mul, ← smul_mk]; congr 2 · dsimp; rw [mul_assoc, ← pow_add, add_comm (m - j), Nat.add_sub_assoc h1] · simp_rw [pow_add]; rfl · dsimp; rw [← mul_assoc, ← pow_add, Nat.add_sub_of_le (le_of_not_le h1)] · simp_rw [pow_add]; rfl variable (hm : 0 < m) (q : Spec.T A⁰_ f) include hm theorem carrier.zero_mem : (0 : A) ∈ carrier f_deg q := fun i => by convert Submodule.zero_mem q.1 using 1 rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk, HomogeneousLocalization.val_zero]; simp_rw [map_zero, zero_pow hm.ne'] convert Localization.mk_zero (S := Submonoid.powers f) _ using 1 theorem carrier.smul_mem (c x : A) (hx : x ∈ carrier f_deg q) : c • x ∈ carrier f_deg q := by revert c refine DirectSum.Decomposition.inductionOn 𝒜 ?_ ?_ ?_ · rw [zero_smul]; exact carrier.zero_mem f_deg hm _ · rintro n ⟨a, ha⟩ i simp_rw [proj_apply, smul_eq_mul, coe_decompose_mul_of_left_mem 𝒜 i ha] let product : A⁰_ f := (HomogeneousLocalization.mk ⟨_, ⟨a ^ m, pow_mem_graded m ha⟩, ⟨_, ?_⟩, ⟨n, rfl⟩⟩ : A⁰_ f) * (HomogeneousLocalization.mk ⟨_, ⟨proj 𝒜 (i - n) x ^ m, by mem_tac⟩, ⟨_, ?_⟩, ⟨i - n, rfl⟩⟩ : A⁰_ f) · split_ifs with h · convert_to product ∈ q.1 · dsimp [product] rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk, HomogeneousLocalization.val_mul, HomogeneousLocalization.val_mk, HomogeneousLocalization.val_mk] · simp_rw [mul_pow]; rw [Localization.mk_mul] · congr; rw [← pow_add, Nat.add_sub_of_le h] · apply Ideal.mul_mem_left (α := A⁰_ f) _ _ (hx _) rw [(_ : m • n = _)] · mem_tac · simp only [smul_eq_mul, mul_comm] · simpa only [map_zero, zero_pow hm.ne'] using zero_mem f_deg hm q i rw [(_ : m • (i - n) = _)] · mem_tac · simp only [smul_eq_mul, mul_comm] · simp_rw [add_smul]; exact fun _ _ => carrier.add_mem f_deg q /-- For a prime ideal `q` in `A⁰_f`, the set `{a | aᵢᵐ/fⁱ ∈ q}` as an ideal. -/ def carrier.asIdeal : Ideal A where carrier := carrier f_deg q zero_mem' := carrier.zero_mem f_deg hm q add_mem' := carrier.add_mem f_deg q smul_mem' := carrier.smul_mem f_deg hm q theorem carrier.asIdeal.homogeneous : (carrier.asIdeal f_deg hm q).IsHomogeneous 𝒜 := fun i a ha j => (em (i = j)).elim (fun h => h ▸ by simpa only [proj_apply, decompose_coe, of_eq_same] using ha _) fun h => by simpa only [proj_apply, decompose_of_mem_ne 𝒜 (Submodule.coe_mem (decompose 𝒜 a i)) h, zero_pow hm.ne', map_zero] using carrier.zero_mem f_deg hm q j /-- For a prime ideal `q` in `A⁰_f`, the set `{a | aᵢᵐ/fⁱ ∈ q}` as a homogeneous ideal. -/ def carrier.asHomogeneousIdeal : HomogeneousIdeal 𝒜 := ⟨carrier.asIdeal f_deg hm q, carrier.asIdeal.homogeneous f_deg hm q⟩ theorem carrier.denom_not_mem : f ∉ carrier.asIdeal f_deg hm q := fun rid => q.isPrime.ne_top <| (Ideal.eq_top_iff_one _).mpr (by convert rid m rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_one, HomogeneousLocalization.val_mk] dsimp simp_rw [decompose_of_mem_same _ f_deg] simp only [mk_eq_monoidOf_mk', Submonoid.LocalizationMap.mk'_self]) theorem carrier.relevant : ¬HomogeneousIdeal.irrelevant 𝒜 ≤ carrier.asHomogeneousIdeal f_deg hm q := fun rid => carrier.denom_not_mem f_deg hm q <| rid <| DirectSum.decompose_of_mem_ne 𝒜 f_deg hm.ne' theorem carrier.asIdeal.ne_top : carrier.asIdeal f_deg hm q ≠ ⊤ := fun rid => carrier.denom_not_mem f_deg hm q (rid.symm ▸ Submodule.mem_top) theorem carrier.asIdeal.prime : (carrier.asIdeal f_deg hm q).IsPrime := (carrier.asIdeal.homogeneous f_deg hm q).isPrime_of_homogeneous_mem_or_mem (carrier.asIdeal.ne_top f_deg hm q) fun {x y} ⟨nx, hnx⟩ ⟨ny, hny⟩ hxy => show (∀ _, _ ∈ _) ∨ ∀ _, _ ∈ _ by rw [← and_forall_ne nx, and_iff_left, ← and_forall_ne ny, and_iff_left] · apply q.2.mem_or_mem; convert hxy (nx + ny) using 1 dsimp simp_rw [decompose_of_mem_same 𝒜 hnx, decompose_of_mem_same 𝒜 hny, decompose_of_mem_same 𝒜 (SetLike.GradedMonoid.toGradedMul.mul_mem hnx hny), mul_pow, pow_add] simp only [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk, HomogeneousLocalization.val_mul, Localization.mk_mul] simp only [Submonoid.mk_mul_mk, mk_eq_monoidOf_mk'] all_goals intro n hn; convert q.1.zero_mem using 1 rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk, HomogeneousLocalization.val_zero]; simp_rw [proj_apply] convert mk_zero (S := Submonoid.powers f) _ rw [decompose_of_mem_ne 𝒜 _ hn.symm, zero_pow hm.ne'] · first | exact hnx | exact hny /-- The function `Spec A⁰_f → Proj|D(f)` sending `q` to `{a | aᵢᵐ/fⁱ ∈ q}`. -/ def toFun : (Spec.T A⁰_ f) → Proj.T| pbo f := fun q => ⟨⟨carrier.asHomogeneousIdeal f_deg hm q, carrier.asIdeal.prime f_deg hm q, carrier.relevant f_deg hm q⟩, (ProjectiveSpectrum.mem_basicOpen _ f _).mp <| carrier.denom_not_mem f_deg hm q⟩ end FromSpec section toSpecFromSpec lemma toSpec_fromSpec {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) (x : Spec.T (A⁰_ f)) : toSpec 𝒜 f (FromSpec.toFun f_deg hm x) = x := by apply PrimeSpectrum.ext ext z obtain ⟨z, rfl⟩ := HomogeneousLocalization.mk_surjective z rw [← FromSpec.num_mem_carrier_iff f_deg hm x] exact ToSpec.mk_mem_carrier _ z end toSpecFromSpec section fromSpecToSpec lemma fromSpec_toSpec {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) (x : Proj.T| pbo f) : FromSpec.toFun f_deg hm (toSpec 𝒜 f x) = x := by refine Subtype.ext <| ProjectiveSpectrum.ext <| HomogeneousIdeal.ext' ?_ intros i z hzi refine (FromSpec.mem_carrier_iff_of_mem f_deg hm _ _ hzi).trans ?_ exact (ToSpec.mk_mem_carrier _ _).trans (x.1.2.pow_mem_iff_mem m hm) lemma toSpec_injective {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : Function.Injective (toSpec 𝒜 f) := by intro x₁ x₂ h have := congr_arg (FromSpec.toFun f_deg hm) h rwa [fromSpec_toSpec, fromSpec_toSpec] at this lemma toSpec_surjective {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : Function.Surjective (toSpec 𝒜 f) := Function.surjective_iff_hasRightInverse |>.mpr ⟨FromSpec.toFun f_deg hm, toSpec_fromSpec 𝒜 f_deg hm⟩ lemma toSpec_bijective {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : Function.Bijective (toSpec (𝒜 := 𝒜) (f := f)) := ⟨toSpec_injective 𝒜 f_deg hm, toSpec_surjective 𝒜 f_deg hm⟩ end fromSpecToSpec namespace toSpec variable {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) include hm f_deg variable {𝒜} in lemma image_basicOpen_eq_basicOpen (a : A) (i : ℕ) : toSpec 𝒜 f '' (Subtype.val ⁻¹' (pbo (decompose 𝒜 a i) : Set (ProjectiveSpectrum 𝒜))) = (PrimeSpectrum.basicOpen (R := A⁰_ f) <| HomogeneousLocalization.mk ⟨m * i, ⟨decompose 𝒜 a i ^ m, smul_eq_mul m i ▸ SetLike.pow_mem_graded _ (Submodule.coe_mem _)⟩, ⟨f^i, by rw [mul_comm]; exact SetLike.pow_mem_graded _ f_deg⟩, ⟨i, rfl⟩⟩).1 := Set.preimage_injective.mpr (toSpec_surjective 𝒜 f_deg hm) <| Set.preimage_image_eq _ (toSpec_injective 𝒜 f_deg hm) ▸ by rw [Opens.carrier_eq_coe, toSpec_preimage_basicOpen, ProjectiveSpectrum.basicOpen_pow 𝒜 _ m hm] end toSpec variable {𝒜} in /-- The continuous function `Spec A⁰_f → Proj|D(f)` sending `q` to `{a | aᵢᵐ/fⁱ ∈ q}` where `m` is the degree of `f` -/ def fromSpec {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : (Spec.T (A⁰_ f)) ⟶ (Proj.T| (pbo f)) := TopCat.ofHom { toFun := FromSpec.toFun f_deg hm continuous_toFun := by rw [isTopologicalBasis_subtype (ProjectiveSpectrum.isTopologicalBasis_basic_opens 𝒜) (pbo f).1 |>.continuous_iff] rintro s ⟨_, ⟨a, rfl⟩, rfl⟩ have h₁ : Subtype.val (p := (pbo f).1) ⁻¹' (pbo a) = ⋃ i : ℕ, Subtype.val (p := (pbo f).1) ⁻¹' (pbo (decompose 𝒜 a i)) := by simp [ProjectiveSpectrum.basicOpen_eq_union_of_projection 𝒜 a] let e : _ ≃ _ := ⟨FromSpec.toFun f_deg hm, ToSpec.toFun f, toSpec_fromSpec _ _ _, fromSpec_toSpec _ _ _⟩ change IsOpen <| e ⁻¹' _ rw [Set.preimage_equiv_eq_image_symm, h₁, Set.image_iUnion] exact isOpen_iUnion fun i ↦ toSpec.image_basicOpen_eq_basicOpen f_deg hm a i ▸ PrimeSpectrum.isOpen_basicOpen } end ProjIsoSpecTopComponent variable {𝒜} in /-- The homeomorphism `Proj|D(f) ≅ Spec A⁰_f` defined by - `φ : Proj|D(f) ⟶ Spec A⁰_f` by sending `x` to `A⁰_f ∩ span {g / 1 | g ∈ x}` - `ψ : Spec A⁰_f ⟶ Proj|D(f)` by sending `q` to `{a | aᵢᵐ/fⁱ ∈ q}`. -/ def projIsoSpecTopComponent {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : (Proj.T| (pbo f)) ≅ (Spec.T (A⁰_ f)) where hom := ProjIsoSpecTopComponent.toSpec 𝒜 f inv := ProjIsoSpecTopComponent.fromSpec f_deg hm hom_inv_id := ConcreteCategory.hom_ext _ _ (ProjIsoSpecTopComponent.fromSpec_toSpec 𝒜 f_deg hm) inv_hom_id := ConcreteCategory.hom_ext _ _ (ProjIsoSpecTopComponent.toSpec_fromSpec 𝒜 f_deg hm) namespace ProjectiveSpectrum.Proj /-- The ring map from `A⁰_ f` to the local sections of the structure sheaf of the projective spectrum of `A` on the basic open set `D(f)` defined by sending `s ∈ A⁰_f` to the section `x ↦ s` on `D(f)`. -/ def awayToSection (f) : CommRingCat.of (A⁰_ f) ⟶ (structureSheaf 𝒜).1.obj (op (pbo f)) := CommRingCat.ofHom -- Have to hint `S`, otherwise it gets unfolded to `structureSheafInType` -- causing `ext` to fail (S := (structureSheaf 𝒜).1.obj (op (pbo f))) { toFun s := ⟨fun x ↦ HomogeneousLocalization.mapId 𝒜 (Submonoid.powers_le.mpr x.2) s, fun x ↦ by obtain ⟨s, rfl⟩ := HomogeneousLocalization.mk_surjective s obtain ⟨n, hn : f ^ n = s.den.1⟩ := s.den_mem exact ⟨_, x.2, 𝟙 _, s.1, s.2, s.3, fun x hsx ↦ x.2 (Ideal.IsPrime.mem_of_pow_mem inferInstance n (hn ▸ hsx)), fun _ ↦ rfl⟩⟩ map_add' _ _ := by ext; simp only [map_add, HomogeneousLocalization.val_add, Proj.add_apply] map_mul' _ _ := by ext; simp only [map_mul, HomogeneousLocalization.val_mul, Proj.mul_apply] map_zero' := by ext; simp only [map_zero, HomogeneousLocalization.val_zero, Proj.zero_apply] map_one' := by ext; simp only [map_one, HomogeneousLocalization.val_one, Proj.one_apply] } lemma awayToSection_germ (f x hx) : awayToSection 𝒜 f ≫ (structureSheaf 𝒜).presheaf.germ _ x hx = CommRingCat.ofHom (HomogeneousLocalization.mapId 𝒜 (Submonoid.powers_le.mpr hx)) ≫ (Proj.stalkIso' 𝒜 x).toCommRingCatIso.inv := by ext z apply (Proj.stalkIso' 𝒜 x).eq_symm_apply.mpr apply Proj.stalkIso'_germ lemma awayToSection_apply (f : A) (x p) : (((ProjectiveSpectrum.Proj.awayToSection 𝒜 f).1 x).val p).val = IsLocalization.map (M := Submonoid.powers f) (T := p.1.1.toIdeal.primeCompl) _ (RingHom.id _) (Submonoid.powers_le.mpr p.2) x.val := by obtain ⟨x, rfl⟩ := HomogeneousLocalization.mk_surjective x show (HomogeneousLocalization.mapId 𝒜 _ _).val = _ dsimp [HomogeneousLocalization.mapId, HomogeneousLocalization.map] rw [Localization.mk_eq_mk', Localization.mk_eq_mk', IsLocalization.map_mk'] rfl /-- The ring map from `A⁰_ f` to the global sections of the structure sheaf of the projective spectrum of `A` restricted to the basic open set `D(f)`. Mathematically, the map is the same as `awayToSection`. -/ def awayToΓ (f) : CommRingCat.of (A⁰_ f) ⟶ LocallyRingedSpace.Γ.obj (op <| Proj| pbo f) := awayToSection 𝒜 f ≫ (ProjectiveSpectrum.Proj.structureSheaf 𝒜).1.map (homOfLE (Opens.isOpenEmbedding_obj_top _).le).op lemma awayToΓ_ΓToStalk (f) (x) : awayToΓ 𝒜 f ≫ (Proj| pbo f).presheaf.Γgerm x = CommRingCat.ofHom (HomogeneousLocalization.mapId 𝒜 (Submonoid.powers_le.mpr x.2)) ≫ (Proj.stalkIso' 𝒜 x.1).toCommRingCatIso.inv ≫ ((Proj.toLocallyRingedSpace 𝒜).restrictStalkIso (Opens.isOpenEmbedding _) x).inv := by rw [awayToΓ, Category.assoc, ← Category.assoc _ (Iso.inv _), Iso.eq_comp_inv, Category.assoc, Category.assoc, Presheaf.Γgerm] rw [LocallyRingedSpace.restrictStalkIso_hom_eq_germ] simp only [Proj.toLocallyRingedSpace, Proj.toSheafedSpace] rw [Presheaf.germ_res, awayToSection_germ] rfl /-- The morphism of locally ringed space from `Proj|D(f)` to `Spec A⁰_f` induced by the ring map `A⁰_ f → Γ(Proj, D(f))` under the gamma spec adjunction. -/ def toSpec (f) : (Proj| pbo f) ⟶ Spec (A⁰_ f) := ΓSpec.locallyRingedSpaceAdjunction.homEquiv (Proj| pbo f) (op (CommRingCat.of <| A⁰_ f)) (awayToΓ 𝒜 f).op open HomogeneousLocalization IsLocalRing lemma toSpec_base_apply_eq_comap {f} (x : Proj| pbo f) : (toSpec 𝒜 f).base x = PrimeSpectrum.comap (mapId 𝒜 (Submonoid.powers_le.mpr x.2)) (closedPoint (AtPrime 𝒜 x.1.asHomogeneousIdeal.toIdeal)) := by show PrimeSpectrum.comap (awayToΓ 𝒜 f ≫ (Proj| pbo f).presheaf.Γgerm x).hom (IsLocalRing.closedPoint ((Proj| pbo f).presheaf.stalk x)) = _ rw [awayToΓ_ΓToStalk, CommRingCat.hom_comp, PrimeSpectrum.comap_comp] exact congr(PrimeSpectrum.comap _ $(@IsLocalRing.comap_closedPoint (HomogeneousLocalization.AtPrime 𝒜 x.1.asHomogeneousIdeal.toIdeal) _ _ ((Proj| pbo f).presheaf.stalk x) _ _ _ (isLocalHom_of_isIso _))) lemma toSpec_base_apply_eq {f} (x : Proj| pbo f) : (toSpec 𝒜 f).base x = ProjIsoSpecTopComponent.toSpec 𝒜 f x := toSpec_base_apply_eq_comap 𝒜 x |>.trans <| PrimeSpectrum.ext <| Ideal.ext fun z => show ¬ IsUnit _ ↔ z ∈ ProjIsoSpecTopComponent.ToSpec.carrier _ by obtain ⟨z, rfl⟩ := z.mk_surjective rw [← HomogeneousLocalization.isUnit_iff_isUnit_val, ProjIsoSpecTopComponent.ToSpec.mk_mem_carrier, HomogeneousLocalization.map_mk, HomogeneousLocalization.val_mk, Localization.mk_eq_mk', IsLocalization.AtPrime.isUnit_mk'_iff] exact not_not lemma toSpec_base_isIso {f} {m} (f_deg : f ∈ 𝒜 m) (hm : 0 < m) : IsIso (toSpec 𝒜 f).base := by convert (projIsoSpecTopComponent f_deg hm).isIso_hom exact ConcreteCategory.hom_ext _ _ <| toSpec_base_apply_eq 𝒜 lemma mk_mem_toSpec_base_apply {f} (x : Proj| pbo f) (z : NumDenSameDeg 𝒜 (.powers f)) : HomogeneousLocalization.mk z ∈ ((toSpec 𝒜 f).base x).asIdeal ↔ z.num.1 ∈ x.1.asHomogeneousIdeal := (toSpec_base_apply_eq 𝒜 x).symm ▸ ProjIsoSpecTopComponent.ToSpec.mk_mem_carrier _ _ lemma toSpec_preimage_basicOpen {f} (t : NumDenSameDeg 𝒜 (.powers f)) : (Opens.map (toSpec 𝒜 f).base).obj (sbo (HomogeneousLocalization.mk t)) =
Opens.comap ⟨_, continuous_subtype_val⟩ (pbo t.num.1) := Opens.ext <| Opens.map_coe _ _ ▸ by convert (ProjIsoSpecTopComponent.ToSpec.preimage_basicOpen f t) exact funext fun _ => toSpec_base_apply_eq _ _ @[reassoc]
Mathlib/AlgebraicGeometry/ProjectiveSpectrum/Scheme.lean
687
692
/- 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.MeasureTheory.Integral.Lebesgue.Basic import Mathlib.MeasureTheory.Integral.Lebesgue.Countable import Mathlib.MeasureTheory.Integral.Lebesgue.MeasurePreserving import Mathlib.MeasureTheory.Integral.Lebesgue.Norm deprecated_module (since := "2025-04-13")
Mathlib/MeasureTheory/Integral/Lebesgue.lean
1,773
1,811
/- Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Bhavik Mehta -/ import Mathlib.Combinatorics.Additive.AP.Three.Defs import Mathlib.Combinatorics.Additive.Corner.Defs import Mathlib.Combinatorics.SimpleGraph.Triangle.Removal import Mathlib.Combinatorics.SimpleGraph.Triangle.Tripartite /-! # The corners theorem and Roth's theorem This file proves the corners theorem and Roth's theorem on arithmetic progressions of length three. ## References * [Yaël Dillies, Bhavik Mehta, *Formalising Szemerédi’s Regularity Lemma in Lean*][srl_itp] * [Wikipedia, *Corners theorem*](https://en.wikipedia.org/wiki/Corners_theorem) -/ open Finset SimpleGraph TripartiteFromTriangles open Function hiding graph open Fintype (card) variable {G : Type*} [AddCommGroup G] {A : Finset (G × G)} {a b c : G} {n : ℕ} {ε : ℝ} namespace Corners /-- The triangle indices for the proof of the corners theorem construction. -/ private def triangleIndices (A : Finset (G × G)) : Finset (G × G × G) := A.map ⟨fun (a, b) ↦ (a, b, a + b), by rintro ⟨x₁, x₂⟩ ⟨y₁, y₂⟩ ⟨⟩; rfl⟩ @[simp]
private lemma mk_mem_triangleIndices : (a, b, c) ∈ triangleIndices A ↔ (a, b) ∈ A ∧ c = a + b := by simp only [triangleIndices, Prod.ext_iff, mem_map, Embedding.coeFn_mk, exists_prop, Prod.exists, eq_comm] refine ⟨?_, fun h ↦ ⟨_, _, h.1, rfl, rfl, h.2⟩⟩ rintro ⟨_, _, h₁, rfl, rfl, h₂⟩ exact ⟨h₁, h₂⟩
Mathlib/Combinatorics/Additive/Corner/Roth.lean
35
41
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison -/ import Mathlib.Algebra.Category.ModuleCat.Adjunctions import Mathlib.Algebra.Category.ModuleCat.EpiMono import Mathlib.Algebra.Category.ModuleCat.Limits import Mathlib.Algebra.Category.ModuleCat.Colimits import Mathlib.Algebra.Category.ModuleCat.Monoidal.Symmetric import Mathlib.CategoryTheory.Elementwise import Mathlib.CategoryTheory.Action.Monoidal import Mathlib.RepresentationTheory.Basic /-! # `Rep k G` is the category of `k`-linear representations of `G`. If `V : Rep k G`, there is a coercion that allows you to treat `V` as a type, and this type comes equipped with a `Module k V` instance. Also `V.ρ` gives the homomorphism `G →* (V →ₗ[k] V)`. Conversely, given a homomorphism `ρ : G →* (V →ₗ[k] V)`, you can construct the bundled representation as `Rep.of ρ`. We construct the categorical equivalence `Rep k G ≌ ModuleCat (MonoidAlgebra k G)`. We verify that `Rep k G` is a `k`-linear abelian symmetric monoidal category with all (co)limits. -/ suppress_compilation universe u open CategoryTheory open CategoryTheory.Limits /-- The category of `k`-linear representations of a monoid `G`. -/ abbrev Rep (k G : Type u) [Ring k] [Monoid G] := Action (ModuleCat.{u} k) G instance (k G : Type u) [CommRing k] [Monoid G] : Linear k (Rep k G) := by infer_instance namespace Rep variable {k G : Type u} [CommRing k] section variable [Monoid G] instance : CoeSort (Rep k G) (Type u) := ⟨fun V => V.V⟩ instance (V : Rep k G) : AddCommGroup V := by change AddCommGroup ((forget₂ (Rep k G) (ModuleCat k)).obj V); infer_instance instance (V : Rep k G) : Module k V := by change Module k ((forget₂ (Rep k G) (ModuleCat k)).obj V) infer_instance /-- Specialize the existing `Action.ρ`, changing the type to `Representation k G V`. -/ def ρ (V : Rep k G) : Representation k G V := -- Porting note: was `V.ρ` (ModuleCat.endRingEquiv V.V).toMonoidHom.comp (Action.ρ V) /-- Lift an unbundled representation to `Rep`. -/ abbrev of {V : Type u} [AddCommGroup V] [Module k V] (ρ : G →* V →ₗ[k] V) : Rep k G := ⟨ModuleCat.of k V, (ModuleCat.endRingEquiv _).symm.toMonoidHom.comp ρ⟩ theorem coe_of {V : Type u} [AddCommGroup V] [Module k V] (ρ : G →* V →ₗ[k] V) : (of ρ : Type u) = V := rfl @[simp] theorem of_ρ {V : Type u} [AddCommGroup V] [Module k V] (ρ : G →* V →ₗ[k] V) : (of ρ).ρ = ρ := rfl theorem Action_ρ_eq_ρ {A : Rep k G} : Action.ρ A = (ModuleCat.endRingEquiv _).symm.toMonoidHom.comp A.ρ := rfl @[simp] lemma ρ_hom {X : Rep k G} (g : G) : (Action.ρ X g).hom = X.ρ g := rfl @[simp] lemma ofHom_ρ {X : Rep k G} (g : G) : ModuleCat.ofHom (X.ρ g) = Action.ρ X g := rfl @[simp] theorem ρ_inv_self_apply {G : Type u} [Group G] (A : Rep k G) (g : G) (x : A) : A.ρ g⁻¹ (A.ρ g x) = x := show (A.ρ g⁻¹ * A.ρ g) x = x by rw [← map_mul, inv_mul_cancel, map_one, Module.End.one_apply] @[simp] theorem ρ_self_inv_apply {G : Type u} [Group G] {A : Rep k G} (g : G) (x : A) : A.ρ g (A.ρ g⁻¹ x) = x := show (A.ρ g * A.ρ g⁻¹) x = x by rw [← map_mul, mul_inv_cancel, map_one, Module.End.one_apply] theorem hom_comm_apply {A B : Rep k G} (f : A ⟶ B) (g : G) (x : A) : f.hom (A.ρ g x) = B.ρ g (f.hom x) := LinearMap.ext_iff.1 (ModuleCat.hom_ext_iff.mp (f.comm g)) x variable (k G) /-- The trivial `k`-linear `G`-representation on a `k`-module `V.` -/ abbrev trivial (V : Type u) [AddCommGroup V] [Module k V] : Rep k G := Rep.of (Representation.trivial k G V) variable {k G} theorem trivial_def {V : Type u} [AddCommGroup V] [Module k V] (g : G) : (trivial k G V).ρ g = LinearMap.id := rfl /-- A predicate for representations that fix every element. -/ abbrev IsTrivial (A : Rep k G) := A.ρ.IsTrivial instance {V : Type u} [AddCommGroup V] [Module k V] : IsTrivial (Rep.trivial k G V) where instance {V : Type u} [AddCommGroup V] [Module k V] (ρ : Representation k G V) [ρ.IsTrivial] : IsTrivial (Rep.of ρ) where -- Porting note: the two following instances were found automatically in mathlib3 noncomputable instance : PreservesLimits (forget₂ (Rep k G) (ModuleCat.{u} k)) := Action.preservesLimits_forget.{u} _ _ noncomputable instance : PreservesColimits (forget₂ (Rep k G) (ModuleCat.{u} k)) := Action.preservesColimits_forget.{u} _ _ theorem epi_iff_surjective {A B : Rep k G} (f : A ⟶ B) : Epi f ↔ Function.Surjective f.hom := ⟨fun _ => (ModuleCat.epi_iff_surjective ((forget₂ _ _).map f)).1 inferInstance, fun h => (forget₂ _ _).epi_of_epi_map ((ModuleCat.epi_iff_surjective <| (forget₂ _ _).map f).2 h)⟩ theorem mono_iff_injective {A B : Rep k G} (f : A ⟶ B) : Mono f ↔ Function.Injective f.hom := ⟨fun _ => (ModuleCat.mono_iff_injective ((forget₂ _ _).map f)).1 inferInstance, fun h => (forget₂ _ _).mono_of_mono_map ((ModuleCat.mono_iff_injective <| (forget₂ _ _).map f).2 h)⟩ open MonoidalCategory in @[simp] theorem tensor_ρ {A B : Rep k G} : (A ⊗ B).ρ = A.ρ.tprod B.ρ := rfl @[simp] lemma res_obj_ρ {H : Type u} [Monoid H] (f : G →* H) (A : Rep k H) (g : G) : DFunLike.coe (F := G →* (A →ₗ[k] A)) (ρ ((Action.res _ f).obj A)) g = A.ρ (f g) := rfl section Linearization variable (k G) /-- The monoidal functor sending a type `H` with a `G`-action to the induced `k`-linear `G`-representation on `k[H].` -/ noncomputable def linearization : (Action (Type u) G) ⥤ (Rep k G) := (ModuleCat.free k).mapAction G instance : (linearization k G).Monoidal := by dsimp only [linearization] infer_instance variable {k G} @[simp] theorem linearization_obj_ρ (X : Action (Type u) G) (g : G) (x : X.V →₀ k) : ((linearization k G).obj X).ρ g x = Finsupp.lmapDomain k k (X.ρ g) x := rfl theorem linearization_of (X : Action (Type u) G) (g : G) (x : X.V) : ((linearization k G).obj X).ρ g (Finsupp.single x (1 : k)) = Finsupp.single (X.ρ g x) (1 : k) := by rw [linearization_obj_ρ, Finsupp.lmapDomain_apply, Finsupp.mapDomain_single] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11041): helps fixing `linearizationTrivialIso` since change in behaviour of `ext`. theorem linearization_single (X : Action (Type u) G) (g : G) (x : X.V) (r : k) : ((linearization k G).obj X).ρ g (Finsupp.single x r) = Finsupp.single (X.ρ g x) r := by rw [linearization_obj_ρ, Finsupp.lmapDomain_apply, Finsupp.mapDomain_single] variable {X Y : Action (Type u) G} (f : X ⟶ Y) @[simp] theorem linearization_map_hom : ((linearization k G).map f).hom = ModuleCat.ofHom (Finsupp.lmapDomain k k f.hom) := rfl theorem linearization_map_hom_single (x : X.V) (r : k) : ((linearization k G).map f).hom (Finsupp.single x r) = Finsupp.single (f.hom x) r := Finsupp.mapDomain_single open Functor.LaxMonoidal Functor.OplaxMonoidal Functor.Monoidal @[simp] theorem linearization_μ_hom (X Y : Action (Type u) G) : (μ (linearization k G) X Y).hom = ModuleCat.ofHom (finsuppTensorFinsupp' k X.V Y.V).toLinearMap := rfl @[simp] theorem linearization_δ_hom (X Y : Action (Type u) G) :
(δ (linearization k G) X Y).hom = ModuleCat.ofHom (finsuppTensorFinsupp' k X.V Y.V).symm.toLinearMap := rfl
Mathlib/RepresentationTheory/Rep.lean
200
202
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Johan Commelin, Andrew Yang, Joël Riou -/ import Mathlib.Algebra.Group.Basic import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero import Mathlib.CategoryTheory.Monoidal.End import Mathlib.CategoryTheory.Monoidal.Discrete /-! # Shift A `Shift` on a category `C` indexed by a monoid `A` is nothing more than a monoidal functor from `A` to `C ⥤ C`. A typical example to keep in mind might be the category of complexes `⋯ → C_{n-1} → C_n → C_{n+1} → ⋯`. It has a shift indexed by `ℤ`, where we assign to each `n : ℤ` the functor `C ⥤ C` that re-indexes the terms, so the degree `i` term of `Shift n C` would be the degree `i+n`-th term of `C`. ## Main definitions * `HasShift`: A typeclass asserting the existence of a shift functor. * `shiftEquiv`: When the indexing monoid is a group, then the functor indexed by `n` and `-n` forms a self-equivalence of `C`. * `shiftComm`: When the indexing monoid is commutative, then shifts commute as well. ## Implementation Notes `[HasShift C A]` is implemented using monoidal functors from `Discrete A` to `C ⥤ C`. However, the API of monoidal functors is used only internally: one should use the API of shifts functors which includes `shiftFunctor C a : C ⥤ C` for `a : A`, `shiftFunctorZero C A : shiftFunctor C (0 : A) ≅ 𝟭 C` and `shiftFunctorAdd C i j : shiftFunctor C (i + j) ≅ shiftFunctor C i ⋙ shiftFunctor C j` (and its variant `shiftFunctorAdd'`). These isomorphisms satisfy some coherence properties which are stated in lemmas like `shiftFunctorAdd'_assoc`, `shiftFunctorAdd'_zero_add` and `shiftFunctorAdd'_add_zero`. -/ namespace CategoryTheory noncomputable section universe v u variable (C : Type u) (A : Type*) [Category.{v} C] attribute [local instance] endofunctorMonoidalCategory variable {A C} section Defs variable (A C) [AddMonoid A] /-- A category has a shift indexed by an additive monoid `A` if there is a monoidal functor from `A` to `C ⥤ C`. -/ class HasShift (C : Type u) (A : Type*) [Category.{v} C] [AddMonoid A] where /-- a shift is a monoidal functor from `A` to `C ⥤ C` -/ shift : Discrete A ⥤ C ⥤ C /-- `shift` is monoidal -/ shiftMonoidal : shift.Monoidal := by infer_instance /-- A helper structure to construct the shift functor `(Discrete A) ⥤ (C ⥤ C)`. -/ structure ShiftMkCore where /-- the family of shift functors -/ F : A → C ⥤ C /-- the shift by 0 identifies to the identity functor -/ zero : F 0 ≅ 𝟭 C /-- the composition of shift functors identifies to the shift by the sum -/ add : ∀ n m : A, F (n + m) ≅ F n ⋙ F m /-- compatibility with the associativity -/ assoc_hom_app : ∀ (m₁ m₂ m₃ : A) (X : C), (add (m₁ + m₂) m₃).hom.app X ≫ (F m₃).map ((add m₁ m₂).hom.app X) = eqToHom (by rw [add_assoc]) ≫ (add m₁ (m₂ + m₃)).hom.app X ≫ (add m₂ m₃).hom.app ((F m₁).obj X) := by aesop_cat /-- compatibility with the left addition with 0 -/ zero_add_hom_app : ∀ (n : A) (X : C), (add 0 n).hom.app X = eqToHom (by dsimp; rw [zero_add]) ≫ (F n).map (zero.inv.app X) := by aesop_cat /-- compatibility with the right addition with 0 -/ add_zero_hom_app : ∀ (n : A) (X : C), (add n 0).hom.app X = eqToHom (by dsimp; rw [add_zero]) ≫ zero.inv.app ((F n).obj X) := by aesop_cat namespace ShiftMkCore variable {C A} attribute [reassoc] assoc_hom_app @[reassoc] lemma assoc_inv_app (h : ShiftMkCore C A) (m₁ m₂ m₃ : A) (X : C) : (h.F m₃).map ((h.add m₁ m₂).inv.app X) ≫ (h.add (m₁ + m₂) m₃).inv.app X = (h.add m₂ m₃).inv.app ((h.F m₁).obj X) ≫ (h.add m₁ (m₂ + m₃)).inv.app X ≫ eqToHom (by rw [add_assoc]) := by rw [← cancel_mono ((h.add (m₁ + m₂) m₃).hom.app X ≫ (h.F m₃).map ((h.add m₁ m₂).hom.app X)), Category.assoc, Category.assoc, Category.assoc, Iso.inv_hom_id_app_assoc, ← Functor.map_comp, Iso.inv_hom_id_app, Functor.map_id, h.assoc_hom_app, eqToHom_trans_assoc, eqToHom_refl, Category.id_comp, Iso.inv_hom_id_app_assoc, Iso.inv_hom_id_app] rfl lemma zero_add_inv_app (h : ShiftMkCore C A) (n : A) (X : C) : (h.add 0 n).inv.app X = (h.F n).map (h.zero.hom.app X) ≫ eqToHom (by dsimp; rw [zero_add]) := by rw [← cancel_epi ((h.add 0 n).hom.app X), Iso.hom_inv_id_app, h.zero_add_hom_app, Category.assoc, ← Functor.map_comp_assoc, Iso.inv_hom_id_app, Functor.map_id, Category.id_comp, eqToHom_trans, eqToHom_refl] lemma add_zero_inv_app (h : ShiftMkCore C A) (n : A) (X : C) : (h.add n 0).inv.app X = h.zero.hom.app ((h.F n).obj X) ≫ eqToHom (by dsimp; rw [add_zero]) := by rw [← cancel_epi ((h.add n 0).hom.app X), Iso.hom_inv_id_app, h.add_zero_hom_app, Category.assoc, Iso.inv_hom_id_app_assoc, eqToHom_trans, eqToHom_refl] end ShiftMkCore section attribute [local simp] eqToHom_map instance (h : ShiftMkCore C A) : (Discrete.functor h.F).Monoidal := Functor.CoreMonoidal.toMonoidal { εIso := h.zero.symm μIso := fun m n ↦ (h.add m.as n.as).symm μIso_hom_natural_left := by rintro ⟨X⟩ ⟨Y⟩ ⟨⟨⟨rfl⟩⟩⟩ ⟨X'⟩ ext dsimp simp μIso_hom_natural_right := by rintro ⟨X⟩ ⟨Y⟩ ⟨X'⟩ ⟨⟨⟨rfl⟩⟩⟩ ext dsimp simp associativity := by rintro ⟨m₁⟩ ⟨m₂⟩ ⟨m₃⟩ ext X simp [endofunctorMonoidalCategory, h.assoc_inv_app_assoc] left_unitality := by rintro ⟨n⟩ ext X simp [endofunctorMonoidalCategory, h.zero_add_inv_app, ← Functor.map_comp] right_unitality := by rintro ⟨n⟩ ext X simp [endofunctorMonoidalCategory, h.add_zero_inv_app] } /-- Constructs a `HasShift C A` instance from `ShiftMkCore`. -/ def hasShiftMk (h : ShiftMkCore C A) : HasShift C A where shift := Discrete.functor h.F end section variable [HasShift C A] /-- The monoidal functor from `A` to `C ⥤ C` given a `HasShift` instance. -/ def shiftMonoidalFunctor : Discrete A ⥤ C ⥤ C := HasShift.shift instance : (shiftMonoidalFunctor C A).Monoidal := HasShift.shiftMonoidal variable {A} open Functor.Monoidal /-- The shift autoequivalence, moving objects and morphisms 'up'. -/ def shiftFunctor (i : A) : C ⥤ C := (shiftMonoidalFunctor C A).obj ⟨i⟩ /-- Shifting by `i + j` is the same as shifting by `i` and then shifting by `j`. -/ def shiftFunctorAdd (i j : A) : shiftFunctor C (i + j) ≅ shiftFunctor C i ⋙ shiftFunctor C j := (μIso (shiftMonoidalFunctor C A) ⟨i⟩ ⟨j⟩).symm /-- When `k = i + j`, shifting by `k` is the same as shifting by `i` and then shifting by `j`. -/ def shiftFunctorAdd' (i j k : A) (h : i + j = k) : shiftFunctor C k ≅ shiftFunctor C i ⋙ shiftFunctor C j := eqToIso (by rw [h]) ≪≫ shiftFunctorAdd C i j lemma shiftFunctorAdd'_eq_shiftFunctorAdd (i j : A) : shiftFunctorAdd' C i j (i+j) rfl = shiftFunctorAdd C i j := by ext1 apply Category.id_comp variable (A) in /-- Shifting by zero is the identity functor. -/ def shiftFunctorZero : shiftFunctor C (0 : A) ≅ 𝟭 C := (εIso (shiftMonoidalFunctor C A)).symm /-- Shifting by `a` such that `a = 0` identifies to the identity functor. -/ def shiftFunctorZero' (a : A) (ha : a = 0) : shiftFunctor C a ≅ 𝟭 C := eqToIso (by rw [ha]) ≪≫ shiftFunctorZero C A end variable {C A} lemma ShiftMkCore.shiftFunctor_eq (h : ShiftMkCore C A) (a : A) : letI := hasShiftMk C A h shiftFunctor C a = h.F a := rfl lemma ShiftMkCore.shiftFunctorZero_eq (h : ShiftMkCore C A) : letI := hasShiftMk C A h shiftFunctorZero C A = h.zero := rfl lemma ShiftMkCore.shiftFunctorAdd_eq (h : ShiftMkCore C A) (a b : A) : letI := hasShiftMk C A h shiftFunctorAdd C a b = h.add a b := rfl set_option quotPrecheck false in /-- shifting an object `X` by `n` is obtained by the notation `X⟦n⟧` -/ notation -- Any better notational suggestions? X "⟦" n "⟧" => (shiftFunctor _ n).obj X set_option quotPrecheck false in /-- shifting a morphism `f` by `n` is obtained by the notation `f⟦n⟧'` -/ notation f "⟦" n "⟧'" => (shiftFunctor _ n).map f variable (C) variable [HasShift C A] lemma shiftFunctorAdd'_zero_add (a : A) : shiftFunctorAdd' C 0 a a (zero_add a) = (Functor.leftUnitor _).symm ≪≫ isoWhiskerRight (shiftFunctorZero C A).symm (shiftFunctor C a) := by ext X dsimp [shiftFunctorAdd', shiftFunctorZero, shiftFunctor] simp only [eqToHom_app, obj_ε_app, Discrete.addMonoidal_leftUnitor, eqToIso.inv, eqToHom_map, Category.id_comp] rfl lemma shiftFunctorAdd'_add_zero (a : A) : shiftFunctorAdd' C a 0 a (add_zero a) = (Functor.rightUnitor _).symm ≪≫ isoWhiskerLeft (shiftFunctor C a) (shiftFunctorZero C A).symm := by ext dsimp [shiftFunctorAdd', shiftFunctorZero, shiftFunctor] simp only [eqToHom_app, ε_app_obj, Discrete.addMonoidal_rightUnitor, eqToIso.inv, eqToHom_map, Category.id_comp] rfl lemma shiftFunctorAdd'_assoc (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) : shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃]) ≪≫ isoWhiskerRight (shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂) _ ≪≫ Functor.associator _ _ _ = shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃]) ≪≫ isoWhiskerLeft _ (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃) := by subst h₁₂ h₂₃ h₁₂₃ ext X dsimp simp only [shiftFunctorAdd'_eq_shiftFunctorAdd, Category.comp_id] dsimp [shiftFunctorAdd'] simp only [eqToHom_app] dsimp [shiftFunctorAdd, shiftFunctor] simp only [obj_μ_inv_app, Discrete.addMonoidal_associator, eqToIso.hom, eqToHom_map, eqToHom_app] erw [δ_μ_app_assoc, Category.assoc] rfl lemma shiftFunctorAdd_assoc (a₁ a₂ a₃ : A) : shiftFunctorAdd C (a₁ + a₂) a₃ ≪≫ isoWhiskerRight (shiftFunctorAdd C a₁ a₂) _ ≪≫ Functor.associator _ _ _ = shiftFunctorAdd' C a₁ (a₂ + a₃) _ (add_assoc a₁ a₂ a₃).symm ≪≫ isoWhiskerLeft _ (shiftFunctorAdd C a₂ a₃) := by ext X simpa [shiftFunctorAdd'_eq_shiftFunctorAdd] using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_assoc C a₁ a₂ a₃ _ _ _ rfl rfl rfl)) X variable {C} lemma shiftFunctorAdd'_zero_add_hom_app (a : A) (X : C) : (shiftFunctorAdd' C 0 a a (zero_add a)).hom.app X = ((shiftFunctorZero C A).inv.app X)⟦a⟧' := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_zero_add C a)) X lemma shiftFunctorAdd_zero_add_hom_app (a : A) (X : C) : (shiftFunctorAdd C 0 a).hom.app X = eqToHom (by dsimp; rw [zero_add]) ≫ ((shiftFunctorZero C A).inv.app X)⟦a⟧' := by simp [← shiftFunctorAdd'_zero_add_hom_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_zero_add_inv_app (a : A) (X : C) : (shiftFunctorAdd' C 0 a a (zero_add a)).inv.app X = ((shiftFunctorZero C A).hom.app X)⟦a⟧' := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_zero_add C a)) X lemma shiftFunctorAdd_zero_add_inv_app (a : A) (X : C) : (shiftFunctorAdd C 0 a).inv.app X = ((shiftFunctorZero C A).hom.app X)⟦a⟧' ≫ eqToHom (by dsimp; rw [zero_add]) := by simp [← shiftFunctorAdd'_zero_add_inv_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_add_zero_hom_app (a : A) (X : C) : (shiftFunctorAdd' C a 0 a (add_zero a)).hom.app X = (shiftFunctorZero C A).inv.app (X⟦a⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_add_zero C a)) X lemma shiftFunctorAdd_add_zero_hom_app (a : A) (X : C) : (shiftFunctorAdd C a 0).hom.app X = eqToHom (by dsimp; rw [add_zero]) ≫ (shiftFunctorZero C A).inv.app (X⟦a⟧) := by simp [← shiftFunctorAdd'_add_zero_hom_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_add_zero_inv_app (a : A) (X : C) : (shiftFunctorAdd' C a 0 a (add_zero a)).inv.app X = (shiftFunctorZero C A).hom.app (X⟦a⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_add_zero C a)) X lemma shiftFunctorAdd_add_zero_inv_app (a : A) (X : C) : (shiftFunctorAdd C a 0).inv.app X = (shiftFunctorZero C A).hom.app (X⟦a⟧) ≫ eqToHom (by dsimp; rw [add_zero]) := by simp [← shiftFunctorAdd'_add_zero_inv_app, shiftFunctorAdd'] @[reassoc] lemma shiftFunctorAdd'_assoc_hom_app (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) (X : C) : (shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃])).hom.app X ≫ ((shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂).hom.app X)⟦a₃⟧' = (shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃])).hom.app X ≫ (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃).hom.app (X⟦a₁⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_assoc C _ _ _ _ _ _ h₁₂ h₂₃ h₁₂₃)) X @[reassoc] lemma shiftFunctorAdd'_assoc_inv_app (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) (X : C) : ((shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂).inv.app X)⟦a₃⟧' ≫ (shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃])).inv.app X = (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃).inv.app (X⟦a₁⟧) ≫ (shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃])).inv.app X := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_assoc C _ _ _ _ _ _ h₁₂ h₂₃ h₁₂₃)) X @[reassoc] lemma shiftFunctorAdd_assoc_hom_app (a₁ a₂ a₃ : A) (X : C) : (shiftFunctorAdd C (a₁ + a₂) a₃).hom.app X ≫ ((shiftFunctorAdd C a₁ a₂).hom.app X)⟦a₃⟧' = (shiftFunctorAdd' C a₁ (a₂ + a₃) (a₁ + a₂ + a₃) (add_assoc _ _ _).symm).hom.app X ≫ (shiftFunctorAdd C a₂ a₃).hom.app (X⟦a₁⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd_assoc C a₁ a₂ a₃)) X @[reassoc] lemma shiftFunctorAdd_assoc_inv_app (a₁ a₂ a₃ : A) (X : C) : ((shiftFunctorAdd C a₁ a₂).inv.app X)⟦a₃⟧' ≫ (shiftFunctorAdd C (a₁ + a₂) a₃).inv.app X = (shiftFunctorAdd C a₂ a₃).inv.app (X⟦a₁⟧) ≫ (shiftFunctorAdd' C a₁ (a₂ + a₃) (a₁ + a₂ + a₃) (add_assoc _ _ _).symm).inv.app X := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd_assoc C a₁ a₂ a₃)) X end Defs section AddMonoid variable [AddMonoid A] [HasShift C A] (X Y : C) (f : X ⟶ Y) --@[simp] --theorem HasShift.shift_obj_obj (n : A) (X : C) : (HasShift.shift.obj ⟨n⟩).obj X = X⟦n⟧ := -- rfl /-- Shifting by `i + j` is the same as shifting by `i` and then shifting by `j`. -/ abbrev shiftAdd (i j : A) : X⟦i + j⟧ ≅ X⟦i⟧⟦j⟧ := (shiftFunctorAdd C i j).app _ theorem shift_shift' (i j : A) : f⟦i⟧'⟦j⟧' = (shiftAdd X i j).inv ≫ f⟦i + j⟧' ≫ (shiftAdd Y i j).hom := by symm rw [← Functor.comp_map, Iso.app_inv] apply NatIso.naturality_1 variable (A) /-- Shifting by zero is the identity functor. -/ abbrev shiftZero : X⟦(0 : A)⟧ ≅ X := (shiftFunctorZero C A).app _ theorem shiftZero' : f⟦(0 : A)⟧' = (shiftZero A X).hom ≫ f ≫ (shiftZero A Y).inv := by symm rw [Iso.app_inv, Iso.app_hom] apply NatIso.naturality_2 variable (C) {A} /-- When `i + j = 0`, shifting by `i` and by `j` gives the identity functor -/ def shiftFunctorCompIsoId (i j : A) (h : i + j = 0) : shiftFunctor C i ⋙ shiftFunctor C j ≅ 𝟭 C := (shiftFunctorAdd' C i j 0 h).symm ≪≫ shiftFunctorZero C A end AddMonoid section AddGroup variable (C) variable [AddGroup A] [HasShift C A] /-- Shifting by `i` and shifting by `j` forms an equivalence when `i + j = 0`. -/ @[simps] def shiftEquiv' (i j : A) (h : i + j = 0) : C ≌ C where functor := shiftFunctor C i inverse := shiftFunctor C j unitIso := (shiftFunctorCompIsoId C i j h).symm counitIso := shiftFunctorCompIsoId C j i (by rw [← add_left_inj j, add_assoc, h, zero_add, add_zero]) functor_unitIso_comp X := by convert (equivOfTensorIsoUnit (shiftMonoidalFunctor C A) ⟨i⟩ ⟨j⟩ (Discrete.eqToIso h) (Discrete.eqToIso (by dsimp; rw [← add_left_inj j, add_assoc, h, zero_add, add_zero])) (Subsingleton.elim _ _)).functor_unitIso_comp X all_goals ext X dsimp [shiftFunctorCompIsoId, unitOfTensorIsoUnit, shiftFunctorAdd'] simp only [Category.assoc, eqToHom_map] rfl /-- Shifting by `n` and shifting by `-n` forms an equivalence. -/ abbrev shiftEquiv (n : A) : C ≌ C := shiftEquiv' C n (-n) (add_neg_cancel n) variable (X Y : C) (f : X ⟶ Y) /-- Shifting by `i` is an equivalence. -/ instance (i : A) : (shiftFunctor C i).IsEquivalence := by change (shiftEquiv C i).functor.IsEquivalence infer_instance variable {C} /-- Shifting by `i` and then shifting by `-i` is the identity. -/ abbrev shiftShiftNeg (i : A) : X⟦i⟧⟦-i⟧ ≅ X := (shiftEquiv C i).unitIso.symm.app X /-- Shifting by `-i` and then shifting by `i` is the identity. -/ abbrev shiftNegShift (i : A) : X⟦-i⟧⟦i⟧ ≅ X := (shiftEquiv C i).counitIso.app X variable {X Y} theorem shift_shift_neg' (i : A) : f⟦i⟧'⟦-i⟧' = (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)).hom.app X ≫ f ≫ (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)).inv.app Y := (NatIso.naturality_2 (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)) f).symm theorem shift_neg_shift' (i : A) : f⟦-i⟧'⟦i⟧' = (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)).hom.app X ≫ f ≫ (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)).inv.app Y := (NatIso.naturality_2 (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)) f).symm theorem shift_equiv_triangle (n : A) (X : C) : (shiftShiftNeg X n).inv⟦n⟧' ≫ (shiftNegShift (X⟦n⟧) n).hom = 𝟙 (X⟦n⟧) := (shiftEquiv C n).functor_unitIso_comp X section theorem shift_shiftFunctorCompIsoId_hom_app (n m : A) (h : n + m = 0) (X : C) : ((shiftFunctorCompIsoId C n m h).hom.app X)⟦n⟧' = (shiftFunctorCompIsoId C m n (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel])).hom.app (X⟦n⟧) := by dsimp [shiftFunctorCompIsoId] simpa only [Functor.map_comp, ← shiftFunctorAdd'_zero_add_inv_app n X, ← shiftFunctorAdd'_add_zero_inv_app n X] using shiftFunctorAdd'_assoc_inv_app n m n 0 0 n h (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel]) (by rw [h, zero_add]) X theorem shift_shiftFunctorCompIsoId_inv_app (n m : A) (h : n + m = 0) (X : C) : ((shiftFunctorCompIsoId C n m h).inv.app X)⟦n⟧' = ((shiftFunctorCompIsoId C m n (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel])).inv.app (X⟦n⟧)) := by rw [← cancel_mono (((shiftFunctorCompIsoId C n m h).hom.app X)⟦n⟧'), ← Functor.map_comp, Iso.inv_hom_id_app, Functor.map_id, shift_shiftFunctorCompIsoId_hom_app, Iso.inv_hom_id_app] rfl theorem shift_shiftFunctorCompIsoId_add_neg_cancel_hom_app (n : A) (X : C) : ((shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).hom.app X)⟦n⟧' = (shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).hom.app (X⟦n⟧) := by apply shift_shiftFunctorCompIsoId_hom_app theorem shift_shiftFunctorCompIsoId_add_neg_cancel_inv_app (n : A) (X : C) : ((shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).inv.app X)⟦n⟧' = (shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).inv.app (X⟦n⟧) := by apply shift_shiftFunctorCompIsoId_inv_app theorem shift_shiftFunctorCompIsoId_neg_add_cancel_hom_app (n : A) (X : C) : ((shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).hom.app X)⟦-n⟧' = (shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).hom.app (X⟦-n⟧) := by apply shift_shiftFunctorCompIsoId_hom_app theorem shift_shiftFunctorCompIsoId_neg_add_cancel_inv_app (n : A) (X : C) : ((shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).inv.app X)⟦-n⟧' = (shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).inv.app (X⟦-n⟧) := by apply shift_shiftFunctorCompIsoId_inv_app end section variable (A) lemma shiftFunctorCompIsoId_zero_zero_hom_app (X : C) : (shiftFunctorCompIsoId C 0 0 (add_zero 0)).hom.app X = ((shiftFunctorZero C A).hom.app X)⟦0⟧' ≫ (shiftFunctorZero C A).hom.app X := by simp [shiftFunctorCompIsoId, shiftFunctorAdd'_zero_add_inv_app] lemma shiftFunctorCompIsoId_zero_zero_inv_app (X : C) : (shiftFunctorCompIsoId C 0 0 (add_zero 0)).inv.app X = (shiftFunctorZero C A).inv.app X ≫ ((shiftFunctorZero C A).inv.app X)⟦0⟧' := by simp [shiftFunctorCompIsoId, shiftFunctorAdd'_zero_add_hom_app] end section variable (m n p m' n' p' : A) (hm : m' + m = 0) (hn : n' + n = 0) (hp : p' + p = 0) (h : m + n = p) lemma shiftFunctorCompIsoId_add'_inv_app : (shiftFunctorCompIsoId C p' p hp).inv.app X = (shiftFunctorCompIsoId C n' n hn).inv.app X ≫ (shiftFunctorCompIsoId C m' m hm).inv.app (X⟦n'⟧)⟦n⟧' ≫ (shiftFunctorAdd' C m n p h).inv.app (X⟦n'⟧⟦m'⟧) ≫ ((shiftFunctorAdd' C n' m' p' (by rw [← add_left_inj p, hp, ← h, add_assoc, ← add_assoc m', hm, zero_add, hn])).inv.app X)⟦p⟧' := by dsimp [shiftFunctorCompIsoId] simp only [Functor.map_comp, Category.assoc] congr 1 rw [← NatTrans.naturality] dsimp rw [← cancel_mono ((shiftFunctorAdd' C p' p 0 hp).inv.app X), Iso.hom_inv_id_app,
Category.assoc, Category.assoc, Category.assoc, Category.assoc, ← shiftFunctorAdd'_assoc_inv_app p' m n n' p 0 (by rw [← add_left_inj n, hn, add_assoc, h, hp]) h (by rw [add_assoc, h, hp]), ← Functor.map_comp_assoc, ← Functor.map_comp_assoc, ← Functor.map_comp_assoc,
Mathlib/CategoryTheory/Shift/Basic.lean
520
523
/- 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.Algebra.Algebra.Hom.Rat import Mathlib.Analysis.Complex.Polynomial.Basic import Mathlib.NumberTheory.NumberField.Norm import Mathlib.RingTheory.RootsOfUnity.PrimitiveRoots import Mathlib.Topology.Instances.Complex /-! # 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 Finset namespace NumberField.Embeddings section Fintype open Module 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] instance : Nonempty (K →+* A) := by rw [← Fintype.card_pos_iff, NumberField.Embeddings.card K A] exact Module.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⟩⟩ end Roots section Bounded open Module 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 := Algebra.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 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. -/ theorem finite_of_norm_le (B : ℝ) : {x : K | IsIntegral ℤ x ∧ ∀ φ : K →+* A, ‖φ x‖ ≤ B}.Finite := by classical 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] /-- An algebraic integer whose conjugates are all of norm one is a root of unity. -/ theorem pow_eq_one_of_norm_eq_one {x : K} (hxi : IsIntegral ℤ x) (hx : ∀ φ : K →+* A, ‖φ x‖ = 1) : ∃ (n : ℕ) (_ : 0 < n), x ^ n = 1 := by obtain ⟨a, -, b, -, habne, h⟩ := @Set.Infinite.exists_ne_map_eq_of_mapsTo _ _ _ _ (x ^ · : ℕ → K) Set.infinite_univ (by exact fun a _ => ⟨hxi.pow a, fun φ => by simp [hx φ]⟩) (finite_of_norm_le K A (1 : ℝ)) wlog hlt : b < a · exact this K A hxi hx b a habne.symm h.symm (habne.lt_or_lt.resolve_right hlt) refine ⟨a - b, tsub_pos_of_lt hlt, ?_⟩ rw [← Nat.sub_add_cancel hlt.le, pow_add, mul_left_eq_self₀] at h refine h.resolve_right fun hp => ?_ specialize hx (IsAlgClosed.lift (R := ℚ)).toRingHom rw [pow_eq_zero hp, map_zero, norm_zero] at hx; norm_num at hx end Bounded end NumberField.Embeddings section Place variable {K : Type*} [Field K] {A : Type*} [NormedDivisionRing A] [Nontrivial A] (φ : K →+* A) /-- An embedding into a normed division ring defines a place of `K` -/ def NumberField.place : AbsoluteValue K ℝ := (IsAbsoluteValue.toAbsoluteValue (norm : A → ℝ)).comp φ.injective @[simp] theorem NumberField.place_apply (x : K) : (NumberField.place φ) x = norm (φ x) := rfl end Place namespace NumberField.ComplexEmbedding open Complex NumberField open scoped ComplexConjugate variable {K : Type*} [Field K] {k : Type*} [Field k] variable (K) in /-- A (random) lift of the complex embedding `φ : k →+* ℂ` to an extension `K` of `k`. -/ noncomputable def lift [Algebra k K] [Algebra.IsAlgebraic k K] (φ : k →+* ℂ) : K →+* ℂ := by letI := φ.toAlgebra exact (IsAlgClosed.lift (R := k)).toRingHom @[simp] theorem lift_comp_algebraMap [Algebra k K] [Algebra.IsAlgebraic k K] (φ : k →+* ℂ) : (lift K φ).comp (algebraMap k K) = φ := by unfold lift letI := φ.toAlgebra rw [AlgHom.toRingHom_eq_coe, AlgHom.comp_algebraMap_of_tower, RingHom.algebraMap_toAlgebra'] @[simp] theorem lift_algebraMap_apply [Algebra k K] [Algebra.IsAlgebraic k K] (φ : k →+* ℂ) (x : k) : lift K φ (algebraMap k K x) = φ x := RingHom.congr_fun (lift_comp_algebraMap φ) x /-- The conjugate of a complex embedding as a complex embedding. -/ abbrev conjugate (φ : K →+* ℂ) : K →+* ℂ := star φ @[simp] theorem conjugate_coe_eq (φ : K →+* ℂ) (x : K) : (conjugate φ) x = conj (φ x) := rfl theorem place_conjugate (φ : K →+* ℂ) : place (conjugate φ) = place φ := by ext; simp only [place_apply, norm_conj, conjugate_coe_eq] /-- An embedding into `ℂ` is real if it is fixed by complex conjugation. -/ abbrev IsReal (φ : K →+* ℂ) : Prop := IsSelfAdjoint φ theorem isReal_iff {φ : K →+* ℂ} : IsReal φ ↔ conjugate φ = φ := isSelfAdjoint_iff theorem isReal_conjugate_iff {φ : K →+* ℂ} : IsReal (conjugate φ) ↔ IsReal φ := IsSelfAdjoint.star_iff /-- A real embedding as a ring homomorphism from `K` to `ℝ` . -/ def IsReal.embedding {φ : K →+* ℂ} (hφ : IsReal φ) : K →+* ℝ where toFun x := (φ x).re map_one' := by simp only [map_one, one_re] map_mul' := by simp only [Complex.conj_eq_iff_im.mp (RingHom.congr_fun hφ _), map_mul, mul_re, mul_zero, tsub_zero, eq_self_iff_true, forall_const] map_zero' := by simp only [map_zero, zero_re] map_add' := by simp only [map_add, add_re, eq_self_iff_true, forall_const] @[simp] theorem IsReal.coe_embedding_apply {φ : K →+* ℂ} (hφ : IsReal φ) (x : K) : (hφ.embedding x : ℂ) = φ x := by apply Complex.ext · rfl · rw [ofReal_im, eq_comm, ← Complex.conj_eq_iff_im] exact RingHom.congr_fun hφ x lemma IsReal.comp (f : k →+* K) {φ : K →+* ℂ} (hφ : IsReal φ) : IsReal (φ.comp f) := by ext1 x; simpa using RingHom.congr_fun hφ (f x) lemma isReal_comp_iff {f : k ≃+* K} {φ : K →+* ℂ} : IsReal (φ.comp (f : k →+* K)) ↔ IsReal φ := ⟨fun H ↦ by convert H.comp f.symm.toRingHom; ext1; simp, IsReal.comp _⟩ lemma exists_comp_symm_eq_of_comp_eq [Algebra k K] [IsGalois k K] (φ ψ : K →+* ℂ) (h : φ.comp (algebraMap k K) = ψ.comp (algebraMap k K)) : ∃ σ : K ≃ₐ[k] K, φ.comp σ.symm = ψ := by letI := (φ.comp (algebraMap k K)).toAlgebra letI := φ.toAlgebra have : IsScalarTower k K ℂ := IsScalarTower.of_algebraMap_eq' rfl let ψ' : K →ₐ[k] ℂ := { ψ with commutes' := fun r ↦ (RingHom.congr_fun h r).symm } use (AlgHom.restrictNormal' ψ' K).symm ext1 x exact AlgHom.restrictNormal_commutes ψ' K x variable [Algebra k K] (φ : K →+* ℂ) (σ : K ≃ₐ[k] K) /-- `IsConj φ σ` states that `σ : K ≃ₐ[k] K` is the conjugation under the embedding `φ : K →+* ℂ`. -/ def IsConj : Prop := conjugate φ = φ.comp σ variable {φ σ} lemma IsConj.eq (h : IsConj φ σ) (x) : φ (σ x) = star (φ x) := RingHom.congr_fun h.symm x lemma IsConj.ext {σ₁ σ₂ : K ≃ₐ[k] K} (h₁ : IsConj φ σ₁) (h₂ : IsConj φ σ₂) : σ₁ = σ₂ := AlgEquiv.ext fun x ↦ φ.injective ((h₁.eq x).trans (h₂.eq x).symm) lemma IsConj.ext_iff {σ₁ σ₂ : K ≃ₐ[k] K} (h₁ : IsConj φ σ₁) : σ₁ = σ₂ ↔ IsConj φ σ₂ := ⟨fun e ↦ e ▸ h₁, h₁.ext⟩ lemma IsConj.isReal_comp (h : IsConj φ σ) : IsReal (φ.comp (algebraMap k K)) := by ext1 x simp only [conjugate_coe_eq, RingHom.coe_comp, Function.comp_apply, ← h.eq, starRingEnd_apply, AlgEquiv.commutes] lemma isConj_one_iff : IsConj φ (1 : K ≃ₐ[k] K) ↔ IsReal φ := Iff.rfl alias ⟨_, IsReal.isConjGal_one⟩ := ComplexEmbedding.isConj_one_iff lemma IsConj.symm (hσ : IsConj φ σ) : IsConj φ σ.symm := RingHom.ext fun x ↦ by simpa using congr_arg star (hσ.eq (σ.symm x)) lemma isConj_symm : IsConj φ σ.symm ↔ IsConj φ σ := ⟨IsConj.symm, IsConj.symm⟩ end NumberField.ComplexEmbedding section InfinitePlace open NumberField variable {k : Type*} [Field k] (K : Type*) [Field K] {F : Type*} [Field F] /-- An infinite place of a number field `K` is a place associated to a complex embedding. -/ def NumberField.InfinitePlace := { w : AbsoluteValue K ℝ // ∃ φ : K →+* ℂ, place φ = w } instance [NumberField K] : Nonempty (NumberField.InfinitePlace K) := Set.instNonemptyRange _ variable {K} /-- Return the infinite place defined by a complex embedding `φ`. -/ noncomputable def NumberField.InfinitePlace.mk (φ : K →+* ℂ) : NumberField.InfinitePlace K := ⟨place φ, ⟨φ, rfl⟩⟩ namespace NumberField.InfinitePlace open NumberField instance {K : Type*} [Field K] : FunLike (InfinitePlace K) K ℝ where coe w x := w.1 x coe_injective' _ _ h := Subtype.eq (AbsoluteValue.ext fun x => congr_fun h x) lemma coe_apply {K : Type*} [Field K] (v : InfinitePlace K) (x : K) : v x = v.1 x := rfl @[ext] lemma ext {K : Type*} [Field K] (v₁ v₂ : InfinitePlace K) (h : ∀ k, v₁ k = v₂ k) : v₁ = v₂ := Subtype.ext <| AbsoluteValue.ext h instance : MonoidWithZeroHomClass (InfinitePlace K) K ℝ where map_mul w _ _ := w.1.map_mul _ _ map_one w := w.1.map_one map_zero w := w.1.map_zero instance : NonnegHomClass (InfinitePlace K) K ℝ where apply_nonneg w _ := w.1.nonneg _ @[simp] theorem apply (φ : K →+* ℂ) (x : K) : (mk φ) x = ‖φ x‖ := rfl /-- For an infinite place `w`, return an embedding `φ` such that `w = infinite_place φ` . -/ noncomputable def embedding (w : InfinitePlace K) : K →+* ℂ := w.2.choose @[simp] theorem mk_embedding (w : InfinitePlace K) : mk (embedding w) = w := Subtype.ext w.2.choose_spec @[simp] theorem mk_conjugate_eq (φ : K →+* ℂ) : mk (ComplexEmbedding.conjugate φ) = mk φ := by refine DFunLike.ext _ _ (fun x => ?_) rw [apply, apply, ComplexEmbedding.conjugate_coe_eq, Complex.norm_conj] theorem norm_embedding_eq (w : InfinitePlace K) (x : K) : ‖(embedding w) x‖ = w x := by nth_rewrite 2 [← mk_embedding w] rfl theorem eq_iff_eq (x : K) (r : ℝ) : (∀ w : InfinitePlace K, w x = r) ↔ ∀ φ : K →+* ℂ, ‖φ x‖ = r := ⟨fun hw φ => hw (mk φ), by rintro hφ ⟨w, ⟨φ, rfl⟩⟩; exact hφ φ⟩ theorem le_iff_le (x : K) (r : ℝ) : (∀ w : InfinitePlace K, w x ≤ r) ↔ ∀ φ : K →+* ℂ, ‖φ x‖ ≤ r := ⟨fun hw φ => hw (mk φ), by rintro hφ ⟨w, ⟨φ, rfl⟩⟩; exact hφ φ⟩ theorem pos_iff {w : InfinitePlace K} {x : K} : 0 < w x ↔ x ≠ 0 := AbsoluteValue.pos_iff w.1 @[simp] theorem mk_eq_iff {φ ψ : K →+* ℂ} : mk φ = mk ψ ↔ φ = ψ ∨ ComplexEmbedding.conjugate φ = ψ := by constructor · -- We prove that the map ψ ∘ φ⁻¹ between φ(K) and ℂ is uniform continuous, thus it is either the -- inclusion or the complex conjugation using `Complex.uniformContinuous_ringHom_eq_id_or_conj` intro h₀ obtain ⟨j, hiφ⟩ := (φ.injective).hasLeftInverse let ι := RingEquiv.ofLeftInverse hiφ have hlip : LipschitzWith 1 (RingHom.comp ψ ι.symm.toRingHom) := by change LipschitzWith 1 (ψ ∘ ι.symm) apply LipschitzWith.of_dist_le_mul intro x y rw [NNReal.coe_one, one_mul, NormedField.dist_eq, Function.comp_apply, Function.comp_apply, ← map_sub, ← map_sub] apply le_of_eq suffices ‖φ (ι.symm (x - y))‖ = ‖ψ (ι.symm (x - y))‖ by rw [← this, ← RingEquiv.ofLeftInverse_apply hiφ _, RingEquiv.apply_symm_apply ι _] rfl exact congrFun (congrArg (↑) h₀) _ cases Complex.uniformContinuous_ringHom_eq_id_or_conj φ.fieldRange hlip.uniformContinuous with | inl h => left; ext1 x conv_rhs => rw [← hiφ x] exact (congrFun h (ι x)).symm | inr h => right; ext1 x conv_rhs => rw [← hiφ x] exact (congrFun h (ι x)).symm · rintro (⟨h⟩ | ⟨h⟩) · exact congr_arg mk h · rw [← mk_conjugate_eq] exact congr_arg mk h /-- An infinite place is real if it is defined by a real embedding. -/ def IsReal (w : InfinitePlace K) : Prop := ∃ φ : K →+* ℂ, ComplexEmbedding.IsReal φ ∧ mk φ = w /-- An infinite place is complex if it is defined by a complex (ie. not real) embedding. -/ def IsComplex (w : InfinitePlace K) : Prop := ∃ φ : K →+* ℂ, ¬ComplexEmbedding.IsReal φ ∧ mk φ = w theorem embedding_mk_eq (φ : K →+* ℂ) : embedding (mk φ) = φ ∨ embedding (mk φ) = ComplexEmbedding.conjugate φ := by rw [@eq_comm _ _ φ, @eq_comm _ _ (ComplexEmbedding.conjugate φ), ← mk_eq_iff, mk_embedding] @[simp] theorem embedding_mk_eq_of_isReal {φ : K →+* ℂ} (h : ComplexEmbedding.IsReal φ) : embedding (mk φ) = φ := by have := embedding_mk_eq φ rwa [ComplexEmbedding.isReal_iff.mp h, or_self] at this theorem isReal_iff {w : InfinitePlace K} : IsReal w ↔ ComplexEmbedding.IsReal (embedding w) := by refine ⟨?_, fun h => ⟨embedding w, h, mk_embedding w⟩⟩ rintro ⟨φ, ⟨hφ, rfl⟩⟩ rwa [embedding_mk_eq_of_isReal hφ] theorem isComplex_iff {w : InfinitePlace K} : IsComplex w ↔ ¬ComplexEmbedding.IsReal (embedding w) := by refine ⟨?_, fun h => ⟨embedding w, h, mk_embedding w⟩⟩ rintro ⟨φ, ⟨hφ, rfl⟩⟩ contrapose! hφ cases mk_eq_iff.mp (mk_embedding (mk φ)) with | inl h => rwa [h] at hφ | inr h => rwa [← ComplexEmbedding.isReal_conjugate_iff, h] at hφ @[simp] theorem conjugate_embedding_eq_of_isReal {w : InfinitePlace K} (h : IsReal w) : ComplexEmbedding.conjugate (embedding w) = embedding w := ComplexEmbedding.isReal_iff.mpr (isReal_iff.mp h) @[simp] theorem not_isReal_iff_isComplex {w : InfinitePlace K} : ¬IsReal w ↔ IsComplex w := by rw [isComplex_iff, isReal_iff] @[simp] theorem not_isComplex_iff_isReal {w : InfinitePlace K} : ¬IsComplex w ↔ IsReal w := by rw [isComplex_iff, isReal_iff, not_not] theorem isReal_or_isComplex (w : InfinitePlace K) : IsReal w ∨ IsComplex w := by rw [← not_isReal_iff_isComplex]; exact em _ theorem ne_of_isReal_isComplex {w w' : InfinitePlace K} (h : IsReal w) (h' : IsComplex w') : w ≠ w' := fun h_eq ↦ not_isReal_iff_isComplex.mpr h' (h_eq ▸ h) variable (K) in theorem disjoint_isReal_isComplex : Disjoint {(w : InfinitePlace K) | IsReal w} {(w : InfinitePlace K) | IsComplex w} := Set.disjoint_iff.2 <| fun _ hw ↦ not_isReal_iff_isComplex.2 hw.2 hw.1 /-- The real embedding associated to a real infinite place. -/ noncomputable def embedding_of_isReal {w : InfinitePlace K} (hw : IsReal w) : K →+* ℝ := ComplexEmbedding.IsReal.embedding (isReal_iff.mp hw) @[simp] theorem embedding_of_isReal_apply {w : InfinitePlace K} (hw : IsReal w) (x : K) : ((embedding_of_isReal hw) x : ℂ) = (embedding w) x := ComplexEmbedding.IsReal.coe_embedding_apply (isReal_iff.mp hw) x theorem norm_embedding_of_isReal {w : InfinitePlace K} (hw : IsReal w) (x : K) : ‖embedding_of_isReal hw x‖ = w x := by rw [← norm_embedding_eq, ← embedding_of_isReal_apply hw, Complex.norm_real] @[simp] theorem isReal_of_mk_isReal {φ : K →+* ℂ} (h : IsReal (mk φ)) : ComplexEmbedding.IsReal φ := by contrapose! h
rw [not_isReal_iff_isComplex] exact ⟨φ, h, rfl⟩
Mathlib/NumberTheory/NumberField/Embeddings.lean
431
433
/- Copyright (c) 2022 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Algebra.Polynomial.AlgebraMap import Mathlib.FieldTheory.Minpoly.IsIntegrallyClosed import Mathlib.RingTheory.PowerBasis /-! # A predicate on adjoining roots of polynomial This file defines a predicate `IsAdjoinRoot S f`, which states that the ring `S` can be constructed by adjoining a specified root of the polynomial `f : R[X]` to `R`. This predicate is useful when the same ring can be generated by adjoining the root of different polynomials, and you want to vary which polynomial you're considering. The results in this file are intended to mirror those in `RingTheory.AdjoinRoot`, in order to provide an easier way to translate results from one to the other. ## Motivation `AdjoinRoot` presents one construction of a ring `R[α]`. However, it is possible to obtain rings of this form in many ways, such as `NumberField.ringOfIntegers ℚ(√-5)`, or `Algebra.adjoin R {α, α^2}`, or `IntermediateField.adjoin R {α, 2 - α}`, or even if we want to view `ℂ` as adjoining a root of `X^2 + 1` to `ℝ`. ## Main definitions The two main predicates in this file are: * `IsAdjoinRoot S f`: `S` is generated by adjoining a specified root of `f : R[X]` to `R` * `IsAdjoinRootMonic S f`: `S` is generated by adjoining a root of the monic polynomial `f : R[X]` to `R` Using `IsAdjoinRoot` to map into `S`: * `IsAdjoinRoot.map`: inclusion from `R[X]` to `S` * `IsAdjoinRoot.root`: the specific root adjoined to `R` to give `S` Using `IsAdjoinRoot` to map out of `S`: * `IsAdjoinRoot.repr`: choose a non-unique representative in `R[X]` * `IsAdjoinRoot.lift`, `IsAdjoinRoot.liftHom`: lift a morphism `R →+* T` to `S →+* T` * `IsAdjoinRootMonic.modByMonicHom`: a unique representative in `R[X]` if `f` is monic ## Main results * `AdjoinRoot.isAdjoinRoot` and `AdjoinRoot.isAdjoinRootMonic`: `AdjoinRoot` satisfies the conditions on `IsAdjoinRoot`(`_monic`) * `IsAdjoinRootMonic.powerBasis`: the `root` generates a power basis on `S` over `R` * `IsAdjoinRoot.aequiv`: algebra isomorphism showing adjoining a root gives a unique ring up to isomorphism * `IsAdjoinRoot.ofEquiv`: transfer `IsAdjoinRoot` across an algebra isomorphism * `IsAdjoinRootMonic.minpoly_eq`: the minimal polynomial of the adjoined root of `f` is equal to `f`, if `f` is irreducible and monic, and `R` is a GCD domain -/ open scoped Polynomial open Polynomial noncomputable section universe u v -- Porting note: this looks like something that should not be here -- section MoveMe -- -- end MoveMe -- This class doesn't really make sense on a predicate /-- `IsAdjoinRoot S f` states that the ring `S` can be constructed by adjoining a specified root of the polynomial `f : R[X]` to `R`. Compare `PowerBasis R S`, which does not explicitly specify which polynomial we adjoin a root of (in particular `f` does not need to be the minimal polynomial of the root we adjoin), and `AdjoinRoot` which constructs a new type. This is not a typeclass because the choice of root given `S` and `f` is not unique. -/ structure IsAdjoinRoot {R : Type u} (S : Type v) [CommSemiring R] [Semiring S] [Algebra R S] (f : R[X]) : Type max u v where map : R[X] →+* S map_surjective : Function.Surjective map ker_map : RingHom.ker map = Ideal.span {f} algebraMap_eq : algebraMap R S = map.comp Polynomial.C -- This class doesn't really make sense on a predicate /-- `IsAdjoinRootMonic S f` states that the ring `S` can be constructed by adjoining a specified root of the monic polynomial `f : R[X]` to `R`. As long as `f` is monic, there is a well-defined representation of elements of `S` as polynomials in `R[X]` of degree lower than `deg f` (see `modByMonicHom` and `coeff`). In particular, we have `IsAdjoinRootMonic.powerBasis`. Bundling `Monic` into this structure is very useful when working with explicit `f`s such as `X^2 - C a * X - C b` since it saves you carrying around the proofs of monicity. -/ -- @[nolint has_nonempty_instance] -- Porting note: This linter does not exist yet. structure IsAdjoinRootMonic {R : Type u} (S : Type v) [CommSemiring R] [Semiring S] [Algebra R S] (f : R[X]) extends IsAdjoinRoot S f where Monic : Monic f section Ring variable {R : Type u} {S : Type v} [CommRing R] [Ring S] {f : R[X]} [Algebra R S] namespace IsAdjoinRoot /-- `(h : IsAdjoinRoot S f).root` is the root of `f` that can be adjoined to generate `S`. -/ def root (h : IsAdjoinRoot S f) : S := h.map X theorem subsingleton (h : IsAdjoinRoot S f) [Subsingleton R] : Subsingleton S := h.map_surjective.subsingleton theorem algebraMap_apply (h : IsAdjoinRoot S f) (x : R) : algebraMap R S x = h.map (Polynomial.C x) := by rw [h.algebraMap_eq, RingHom.comp_apply] theorem mem_ker_map (h : IsAdjoinRoot S f) {p} : p ∈ RingHom.ker h.map ↔ f ∣ p := by rw [h.ker_map, Ideal.mem_span_singleton] @[simp] theorem map_eq_zero_iff (h : IsAdjoinRoot S f) {p} : h.map p = 0 ↔ f ∣ p := by rw [← h.mem_ker_map, RingHom.mem_ker] @[simp] theorem map_X (h : IsAdjoinRoot S f) : h.map X = h.root := rfl @[simp] theorem map_self (h : IsAdjoinRoot S f) : h.map f = 0 := h.map_eq_zero_iff.mpr dvd_rfl @[simp] theorem aeval_eq (h : IsAdjoinRoot S f) (p : R[X]) : aeval h.root p = h.map p := Polynomial.induction_on p (fun x => by rw [aeval_C, h.algebraMap_apply]) (fun p q ihp ihq => by rw [map_add, RingHom.map_add, ihp, ihq]) fun n x _ => by rw [map_mul, aeval_C, map_pow, aeval_X, RingHom.map_mul, ← h.algebraMap_apply, RingHom.map_pow, map_X] theorem aeval_root (h : IsAdjoinRoot S f) : aeval h.root f = 0 := by rw [aeval_eq, map_self] /-- Choose an arbitrary representative so that `h.map (h.repr x) = x`. If `f` is monic, use `IsAdjoinRootMonic.modByMonicHom` for a unique choice of representative. -/ def repr (h : IsAdjoinRoot S f) (x : S) : R[X] := (h.map_surjective x).choose theorem map_repr (h : IsAdjoinRoot S f) (x : S) : h.map (h.repr x) = x := (h.map_surjective x).choose_spec /-- `repr` preserves zero, up to multiples of `f` -/ theorem repr_zero_mem_span (h : IsAdjoinRoot S f) : h.repr 0 ∈ Ideal.span ({f} : Set R[X]) := by rw [← h.ker_map, RingHom.mem_ker, h.map_repr] /-- `repr` preserves addition, up to multiples of `f` -/ theorem repr_add_sub_repr_add_repr_mem_span (h : IsAdjoinRoot S f) (x y : S) : h.repr (x + y) - (h.repr x + h.repr y) ∈ Ideal.span ({f} : Set R[X]) := by rw [← h.ker_map, RingHom.mem_ker, map_sub, h.map_repr, map_add, h.map_repr, h.map_repr, sub_self] /-- Extensionality of the `IsAdjoinRoot` structure itself. See `IsAdjoinRootMonic.ext_elem` for extensionality of the ring elements. -/ theorem ext_map (h h' : IsAdjoinRoot S f) (eq : ∀ x, h.map x = h'.map x) : h = h' := by cases h; cases h'; congr exact RingHom.ext eq /-- Extensionality of the `IsAdjoinRoot` structure itself. See `IsAdjoinRootMonic.ext_elem` for extensionality of the ring elements. -/ @[ext] theorem ext (h h' : IsAdjoinRoot S f) (eq : h.root = h'.root) : h = h' := h.ext_map h' fun x => by rw [← h.aeval_eq, ← h'.aeval_eq, eq] section lift variable {T : Type*} [CommRing T] {i : R →+* T} {x : T} section variable (hx : f.eval₂ i x = 0) include hx /-- Auxiliary lemma for `IsAdjoinRoot.lift` -/ theorem eval₂_repr_eq_eval₂_of_map_eq (h : IsAdjoinRoot S f) (z : S) (w : R[X]) (hzw : h.map w = z) : (h.repr z).eval₂ i x = w.eval₂ i x := by rw [eq_comm, ← sub_eq_zero, ← h.map_repr z, ← map_sub, h.map_eq_zero_iff] at hzw obtain ⟨y, hy⟩ := hzw rw [← sub_eq_zero, ← eval₂_sub, hy, eval₂_mul, hx, zero_mul] variable (i x) -- To match `AdjoinRoot.lift` /-- Lift a ring homomorphism `R →+* T` to `S →+* T` by specifying a root `x` of `f` in `T`, where `S` is given by adjoining a root of `f` to `R`. -/ def lift (h : IsAdjoinRoot S f) (hx : f.eval₂ i x = 0) : S →+* T where toFun z := (h.repr z).eval₂ i x map_zero' := by rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ (map_zero _), eval₂_zero] map_add' z w := by rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ (h.repr z + h.repr w), eval₂_add] rw [map_add, map_repr, map_repr] map_one' := by rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ (map_one _), eval₂_one] map_mul' z w := by rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ (h.repr z * h.repr w), eval₂_mul] rw [map_mul, map_repr, map_repr] variable {i x} @[simp] theorem lift_map (h : IsAdjoinRoot S f) (z : R[X]) : h.lift i x hx (h.map z) = z.eval₂ i x := by rw [lift, RingHom.coe_mk] dsimp rw [h.eval₂_repr_eq_eval₂_of_map_eq hx _ _ rfl] @[simp] theorem lift_root (h : IsAdjoinRoot S f) : h.lift i x hx h.root = x := by rw [← h.map_X, lift_map, eval₂_X] @[simp] theorem lift_algebraMap (h : IsAdjoinRoot S f) (a : R) : h.lift i x hx (algebraMap R S a) = i a := by rw [h.algebraMap_apply, lift_map, eval₂_C] /-- Auxiliary lemma for `apply_eq_lift` -/ theorem apply_eq_lift (h : IsAdjoinRoot S f) (g : S →+* T) (hmap : ∀ a, g (algebraMap R S a) = i a) (hroot : g h.root = x) (a : S) : g a = h.lift i x hx a := by rw [← h.map_repr a, Polynomial.as_sum_range_C_mul_X_pow (h.repr a)] simp only [map_sum, map_mul, map_pow, h.map_X, hroot, ← h.algebraMap_apply, hmap, lift_root, lift_algebraMap] /-- Unicity of `lift`: a map that agrees on `R` and `h.root` agrees with `lift` everywhere. -/ theorem eq_lift (h : IsAdjoinRoot S f) (g : S →+* T) (hmap : ∀ a, g (algebraMap R S a) = i a) (hroot : g h.root = x) : g = h.lift i x hx := RingHom.ext (h.apply_eq_lift hx g hmap hroot) end variable [Algebra R T] (hx' : aeval x f = 0) variable (x) in -- To match `AdjoinRoot.liftHom` /-- Lift the algebra map `R → T` to `S →ₐ[R] T` by specifying a root `x` of `f` in `T`, where `S` is given by adjoining a root of `f` to `R`. -/ def liftHom (h : IsAdjoinRoot S f) : S →ₐ[R] T := { h.lift (algebraMap R T) x hx' with commutes' := fun a => h.lift_algebraMap hx' a } @[simp] theorem coe_liftHom (h : IsAdjoinRoot S f) : (h.liftHom x hx' : S →+* T) = h.lift (algebraMap R T) x hx' := rfl theorem lift_algebraMap_apply (h : IsAdjoinRoot S f) (z : S) : h.lift (algebraMap R T) x hx' z = h.liftHom x hx' z := rfl @[simp] theorem liftHom_map (h : IsAdjoinRoot S f) (z : R[X]) : h.liftHom x hx' (h.map z) = aeval x z := by rw [← lift_algebraMap_apply, lift_map, aeval_def] @[simp] theorem liftHom_root (h : IsAdjoinRoot S f) : h.liftHom x hx' h.root = x := by rw [← lift_algebraMap_apply, lift_root] /-- Unicity of `liftHom`: a map that agrees on `h.root` agrees with `liftHom` everywhere. -/ theorem eq_liftHom (h : IsAdjoinRoot S f) (g : S →ₐ[R] T) (hroot : g h.root = x) : g = h.liftHom x hx' := AlgHom.ext (h.apply_eq_lift hx' g g.commutes hroot) end lift end IsAdjoinRoot namespace AdjoinRoot variable (f) /-- `AdjoinRoot f` is indeed given by adjoining a root of `f`. -/ protected def isAdjoinRoot : IsAdjoinRoot (AdjoinRoot f) f where map := AdjoinRoot.mk f map_surjective := Ideal.Quotient.mk_surjective ker_map := by ext rw [RingHom.mem_ker, ← @AdjoinRoot.mk_self _ _ f, AdjoinRoot.mk_eq_mk, Ideal.mem_span_singleton, ← dvd_add_left (dvd_refl f), sub_add_cancel] algebraMap_eq := AdjoinRoot.algebraMap_eq f /-- `AdjoinRoot f` is indeed given by adjoining a root of `f`. If `f` is monic this is more powerful than `AdjoinRoot.isAdjoinRoot`. -/ protected def isAdjoinRootMonic (hf : Monic f) : IsAdjoinRootMonic (AdjoinRoot f) f := { AdjoinRoot.isAdjoinRoot f with Monic := hf } @[simp] theorem isAdjoinRoot_map_eq_mk : (AdjoinRoot.isAdjoinRoot f).map = AdjoinRoot.mk f := rfl
@[simp]
Mathlib/RingTheory/IsAdjoinRoot.lean
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/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.SpecificLimits.Basic import Mathlib.Topology.MetricSpace.IsometricSMul /-! # Hausdorff distance The Hausdorff distance on subsets of a metric (or emetric) space. Given two subsets `s` and `t` of a metric space, their Hausdorff distance is the smallest `d` such that any point `s` is within `d` of a point in `t`, and conversely. This quantity is often infinite (think of `s` bounded and `t` unbounded), and therefore better expressed in the setting of emetric spaces. ## Main definitions This files introduces: * `EMetric.infEdist x s`, the infimum edistance of a point `x` to a set `s` in an emetric space * `EMetric.hausdorffEdist s t`, the Hausdorff edistance of two sets in an emetric space * Versions of these notions on metric spaces, called respectively `Metric.infDist` and `Metric.hausdorffDist` ## Main results * `infEdist_closure`: the edistance to a set and its closure coincide * `EMetric.mem_closure_iff_infEdist_zero`: a point `x` belongs to the closure of `s` iff `infEdist x s = 0` * `IsCompact.exists_infEdist_eq_edist`: if `s` is compact and non-empty, there exists a point `y` which attains this edistance * `IsOpen.exists_iUnion_isClosed`: every open set `U` can be written as the increasing union of countably many closed subsets of `U` * `hausdorffEdist_closure`: replacing a set by its closure does not change the Hausdorff edistance * `hausdorffEdist_zero_iff_closure_eq_closure`: two sets have Hausdorff edistance zero iff their closures coincide * the Hausdorff edistance is symmetric and satisfies the triangle inequality * in particular, closed sets in an emetric space are an emetric space (this is shown in `EMetricSpace.closeds.emetricspace`) * versions of these notions on metric spaces * `hausdorffEdist_ne_top_of_nonempty_of_bounded`: if two sets in a metric space are nonempty and bounded in a metric space, they are at finite Hausdorff edistance. ## Tags metric space, Hausdorff distance -/ noncomputable section open NNReal ENNReal Topology Set Filter Pointwise Bornology universe u v w variable {ι : Sort*} {α : Type u} {β : Type v} namespace EMetric section InfEdist variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x y : α} {s t : Set α} {Φ : α → β} /-! ### Distance of a point to a set as a function into `ℝ≥0∞`. -/ /-- The minimal edistance of a point to a set -/ def infEdist (x : α) (s : Set α) : ℝ≥0∞ := ⨅ y ∈ s, edist x y @[simp] theorem infEdist_empty : infEdist x ∅ = ∞ := iInf_emptyset theorem le_infEdist {d} : d ≤ infEdist x s ↔ ∀ y ∈ s, d ≤ edist x y := by simp only [infEdist, le_iInf_iff] /-- The edist to a union is the minimum of the edists -/ @[simp] theorem infEdist_union : infEdist x (s ∪ t) = infEdist x s ⊓ infEdist x t := iInf_union @[simp] theorem infEdist_iUnion (f : ι → Set α) (x : α) : infEdist x (⋃ i, f i) = ⨅ i, infEdist x (f i) := iInf_iUnion f _ lemma infEdist_biUnion {ι : Type*} (f : ι → Set α) (I : Set ι) (x : α) : infEdist x (⋃ i ∈ I, f i) = ⨅ i ∈ I, infEdist x (f i) := by simp only [infEdist_iUnion] /-- The edist to a singleton is the edistance to the single point of this singleton -/ @[simp] theorem infEdist_singleton : infEdist x {y} = edist x y := iInf_singleton /-- The edist to a set is bounded above by the edist to any of its points -/ theorem infEdist_le_edist_of_mem (h : y ∈ s) : infEdist x s ≤ edist x y := iInf₂_le y h /-- If a point `x` belongs to `s`, then its edist to `s` vanishes -/ theorem infEdist_zero_of_mem (h : x ∈ s) : infEdist x s = 0 := nonpos_iff_eq_zero.1 <| @edist_self _ _ x ▸ infEdist_le_edist_of_mem h /-- The edist is antitone with respect to inclusion. -/ theorem infEdist_anti (h : s ⊆ t) : infEdist x t ≤ infEdist x s := iInf_le_iInf_of_subset h /-- The edist to a set is `< r` iff there exists a point in the set at edistance `< r` -/ theorem infEdist_lt_iff {r : ℝ≥0∞} : infEdist x s < r ↔ ∃ y ∈ s, edist x y < r := by simp_rw [infEdist, iInf_lt_iff, exists_prop] /-- The edist of `x` to `s` is bounded by the sum of the edist of `y` to `s` and the edist from `x` to `y` -/ theorem infEdist_le_infEdist_add_edist : infEdist x s ≤ infEdist y s + edist x y := calc ⨅ z ∈ s, edist x z ≤ ⨅ z ∈ s, edist y z + edist x y := iInf₂_mono fun _ _ => (edist_triangle _ _ _).trans_eq (add_comm _ _) _ = (⨅ z ∈ s, edist y z) + edist x y := by simp only [ENNReal.iInf_add] theorem infEdist_le_edist_add_infEdist : infEdist x s ≤ edist x y + infEdist y s := by rw [add_comm] exact infEdist_le_infEdist_add_edist theorem edist_le_infEdist_add_ediam (hy : y ∈ s) : edist x y ≤ infEdist x s + diam s := by simp_rw [infEdist, ENNReal.iInf_add] refine le_iInf₂ fun i hi => ?_ calc edist x y ≤ edist x i + edist i y := edist_triangle _ _ _ _ ≤ edist x i + diam s := add_le_add le_rfl (edist_le_diam_of_mem hi hy) /-- The edist to a set depends continuously on the point -/ @[continuity] theorem continuous_infEdist : Continuous fun x => infEdist x s := continuous_of_le_add_edist 1 (by simp) <| by simp only [one_mul, infEdist_le_infEdist_add_edist, forall₂_true_iff] /-- The edist to a set and to its closure coincide -/ theorem infEdist_closure : infEdist x (closure s) = infEdist x s := by refine le_antisymm (infEdist_anti subset_closure) ?_ refine ENNReal.le_of_forall_pos_le_add fun ε εpos h => ?_ have ε0 : 0 < (ε / 2 : ℝ≥0∞) := by simpa [pos_iff_ne_zero] using εpos have : infEdist x (closure s) < infEdist x (closure s) + ε / 2 := ENNReal.lt_add_right h.ne ε0.ne' obtain ⟨y : α, ycs : y ∈ closure s, hy : edist x y < infEdist x (closure s) + ↑ε / 2⟩ := infEdist_lt_iff.mp this obtain ⟨z : α, zs : z ∈ s, dyz : edist y z < ↑ε / 2⟩ := EMetric.mem_closure_iff.1 ycs (ε / 2) ε0 calc infEdist x s ≤ edist x z := infEdist_le_edist_of_mem zs _ ≤ edist x y + edist y z := edist_triangle _ _ _ _ ≤ infEdist x (closure s) + ε / 2 + ε / 2 := add_le_add (le_of_lt hy) (le_of_lt dyz) _ = infEdist x (closure s) + ↑ε := by rw [add_assoc, ENNReal.add_halves] /-- A point belongs to the closure of `s` iff its infimum edistance to this set vanishes -/ theorem mem_closure_iff_infEdist_zero : x ∈ closure s ↔ infEdist x s = 0 := ⟨fun h => by rw [← infEdist_closure] exact infEdist_zero_of_mem h, fun h => EMetric.mem_closure_iff.2 fun ε εpos => infEdist_lt_iff.mp <| by rwa [h]⟩ /-- Given a closed set `s`, a point belongs to `s` iff its infimum edistance to this set vanishes -/ theorem mem_iff_infEdist_zero_of_closed (h : IsClosed s) : x ∈ s ↔ infEdist x s = 0 := by rw [← mem_closure_iff_infEdist_zero, h.closure_eq] /-- The infimum edistance of a point to a set is positive if and only if the point is not in the closure of the set. -/ theorem infEdist_pos_iff_not_mem_closure {x : α} {E : Set α} : 0 < infEdist x E ↔ x ∉ closure E := by rw [mem_closure_iff_infEdist_zero, pos_iff_ne_zero] theorem infEdist_closure_pos_iff_not_mem_closure {x : α} {E : Set α} : 0 < infEdist x (closure E) ↔ x ∉ closure E := by rw [infEdist_closure, infEdist_pos_iff_not_mem_closure] theorem exists_real_pos_lt_infEdist_of_not_mem_closure {x : α} {E : Set α} (h : x ∉ closure E) : ∃ ε : ℝ, 0 < ε ∧ ENNReal.ofReal ε < infEdist x E := by rw [← infEdist_pos_iff_not_mem_closure, ENNReal.lt_iff_exists_real_btwn] at h rcases h with ⟨ε, ⟨_, ⟨ε_pos, ε_lt⟩⟩⟩ exact ⟨ε, ⟨ENNReal.ofReal_pos.mp ε_pos, ε_lt⟩⟩ theorem disjoint_closedBall_of_lt_infEdist {r : ℝ≥0∞} (h : r < infEdist x s) : Disjoint (closedBall x r) s := by rw [disjoint_left] intro y hy h'y apply lt_irrefl (infEdist x s) calc infEdist x s ≤ edist x y := infEdist_le_edist_of_mem h'y _ ≤ r := by rwa [mem_closedBall, edist_comm] at hy _ < infEdist x s := h /-- The infimum edistance is invariant under isometries -/ theorem infEdist_image (hΦ : Isometry Φ) : infEdist (Φ x) (Φ '' t) = infEdist x t := by simp only [infEdist, iInf_image, hΦ.edist_eq] @[to_additive (attr := simp)] theorem infEdist_smul {M} [SMul M α] [IsIsometricSMul M α] (c : M) (x : α) (s : Set α) : infEdist (c • x) (c • s) = infEdist x s := infEdist_image (isometry_smul _ _) theorem _root_.IsOpen.exists_iUnion_isClosed {U : Set α} (hU : IsOpen U) : ∃ F : ℕ → Set α, (∀ n, IsClosed (F n)) ∧ (∀ n, F n ⊆ U) ∧ ⋃ n, F n = U ∧ Monotone F := by obtain ⟨a, a_pos, a_lt_one⟩ : ∃ a : ℝ≥0∞, 0 < a ∧ a < 1 := exists_between zero_lt_one let F := fun n : ℕ => (fun x => infEdist x Uᶜ) ⁻¹' Ici (a ^ n) have F_subset : ∀ n, F n ⊆ U := fun n x hx ↦ by by_contra h have : infEdist x Uᶜ ≠ 0 := ((ENNReal.pow_pos a_pos _).trans_le hx).ne' exact this (infEdist_zero_of_mem h) refine ⟨F, fun n => IsClosed.preimage continuous_infEdist isClosed_Ici, F_subset, ?_, ?_⟩ · show ⋃ n, F n = U refine Subset.antisymm (by simp only [iUnion_subset_iff, F_subset, forall_const]) fun x hx => ?_ have : ¬x ∈ Uᶜ := by simpa using hx rw [mem_iff_infEdist_zero_of_closed hU.isClosed_compl] at this have B : 0 < infEdist x Uᶜ := by simpa [pos_iff_ne_zero] using this have : Filter.Tendsto (fun n => a ^ n) atTop (𝓝 0) := ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one a_lt_one rcases ((tendsto_order.1 this).2 _ B).exists with ⟨n, hn⟩ simp only [mem_iUnion, mem_Ici, mem_preimage] exact ⟨n, hn.le⟩ show Monotone F intro m n hmn x hx simp only [F, mem_Ici, mem_preimage] at hx ⊢ apply le_trans (pow_le_pow_right_of_le_one' a_lt_one.le hmn) hx theorem _root_.IsCompact.exists_infEdist_eq_edist (hs : IsCompact s) (hne : s.Nonempty) (x : α) : ∃ y ∈ s, infEdist x s = edist x y := by have A : Continuous fun y => edist x y := continuous_const.edist continuous_id obtain ⟨y, ys, hy⟩ := hs.exists_isMinOn hne A.continuousOn exact ⟨y, ys, le_antisymm (infEdist_le_edist_of_mem ys) (by rwa [le_infEdist])⟩ theorem exists_pos_forall_lt_edist (hs : IsCompact s) (ht : IsClosed t) (hst : Disjoint s t) : ∃ r : ℝ≥0, 0 < r ∧ ∀ x ∈ s, ∀ y ∈ t, (r : ℝ≥0∞) < edist x y := by rcases s.eq_empty_or_nonempty with (rfl | hne) · use 1 simp obtain ⟨x, hx, h⟩ := hs.exists_isMinOn hne continuous_infEdist.continuousOn have : 0 < infEdist x t := pos_iff_ne_zero.2 fun H => hst.le_bot ⟨hx, (mem_iff_infEdist_zero_of_closed ht).mpr H⟩ rcases ENNReal.lt_iff_exists_nnreal_btwn.1 this with ⟨r, h₀, hr⟩ exact ⟨r, ENNReal.coe_pos.mp h₀, fun y hy z hz => hr.trans_le <| le_infEdist.1 (h hy) z hz⟩ end InfEdist /-! ### The Hausdorff distance as a function into `ℝ≥0∞`. -/ /-- The Hausdorff edistance between two sets is the smallest `r` such that each set is contained in the `r`-neighborhood of the other one -/ irreducible_def hausdorffEdist {α : Type u} [PseudoEMetricSpace α] (s t : Set α) : ℝ≥0∞ := (⨆ x ∈ s, infEdist x t) ⊔ ⨆ y ∈ t, infEdist y s section HausdorffEdist variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x : α} {s t u : Set α} {Φ : α → β} /-- The Hausdorff edistance of a set to itself vanishes. -/ @[simp] theorem hausdorffEdist_self : hausdorffEdist s s = 0 := by simp only [hausdorffEdist_def, sup_idem, ENNReal.iSup_eq_zero] exact fun x hx => infEdist_zero_of_mem hx /-- The Haudorff edistances of `s` to `t` and of `t` to `s` coincide. -/ theorem hausdorffEdist_comm : hausdorffEdist s t = hausdorffEdist t s := by simp only [hausdorffEdist_def]; apply sup_comm /-- Bounding the Hausdorff edistance by bounding the edistance of any point in each set to the other set -/ theorem hausdorffEdist_le_of_infEdist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, infEdist x t ≤ r) (H2 : ∀ x ∈ t, infEdist x s ≤ r) : hausdorffEdist s t ≤ r := by simp only [hausdorffEdist_def, sup_le_iff, iSup_le_iff] exact ⟨H1, H2⟩ /-- Bounding the Hausdorff edistance by exhibiting, for any point in each set, another point in the other set at controlled distance -/ theorem hausdorffEdist_le_of_mem_edist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, ∃ y ∈ t, edist x y ≤ r) (H2 : ∀ x ∈ t, ∃ y ∈ s, edist x y ≤ r) : hausdorffEdist s t ≤ r := by refine hausdorffEdist_le_of_infEdist (fun x xs ↦ ?_) (fun x xt ↦ ?_) · rcases H1 x xs with ⟨y, yt, hy⟩ exact le_trans (infEdist_le_edist_of_mem yt) hy · rcases H2 x xt with ⟨y, ys, hy⟩ exact le_trans (infEdist_le_edist_of_mem ys) hy /-- The distance to a set is controlled by the Hausdorff distance. -/ theorem infEdist_le_hausdorffEdist_of_mem (h : x ∈ s) : infEdist x t ≤ hausdorffEdist s t := by rw [hausdorffEdist_def] refine le_trans ?_ le_sup_left exact le_iSup₂ (α := ℝ≥0∞) x h /-- If the Hausdorff distance is `< r`, then any point in one of the sets has a corresponding point at distance `< r` in the other set. -/ theorem exists_edist_lt_of_hausdorffEdist_lt {r : ℝ≥0∞} (h : x ∈ s) (H : hausdorffEdist s t < r) : ∃ y ∈ t, edist x y < r := infEdist_lt_iff.mp <| calc infEdist x t ≤ hausdorffEdist s t := infEdist_le_hausdorffEdist_of_mem h _ < r := H /-- The distance from `x` to `s` or `t` is controlled in terms of the Hausdorff distance between `s` and `t`. -/ theorem infEdist_le_infEdist_add_hausdorffEdist : infEdist x t ≤ infEdist x s + hausdorffEdist s t := ENNReal.le_of_forall_pos_le_add fun ε εpos h => by have ε0 : (ε / 2 : ℝ≥0∞) ≠ 0 := by simpa [pos_iff_ne_zero] using εpos have : infEdist x s < infEdist x s + ε / 2 := ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).1.ne ε0 obtain ⟨y : α, ys : y ∈ s, dxy : edist x y < infEdist x s + ↑ε / 2⟩ := infEdist_lt_iff.mp this have : hausdorffEdist s t < hausdorffEdist s t + ε / 2 := ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).2.ne ε0 obtain ⟨z : α, zt : z ∈ t, dyz : edist y z < hausdorffEdist s t + ↑ε / 2⟩ := exists_edist_lt_of_hausdorffEdist_lt ys this calc infEdist x t ≤ edist x z := infEdist_le_edist_of_mem zt _ ≤ edist x y + edist y z := edist_triangle _ _ _ _ ≤ infEdist x s + ε / 2 + (hausdorffEdist s t + ε / 2) := add_le_add dxy.le dyz.le _ = infEdist x s + hausdorffEdist s t + ε := by simp [ENNReal.add_halves, add_comm, add_left_comm] /-- The Hausdorff edistance is invariant under isometries. -/ theorem hausdorffEdist_image (h : Isometry Φ) : hausdorffEdist (Φ '' s) (Φ '' t) = hausdorffEdist s t := by simp only [hausdorffEdist_def, iSup_image, infEdist_image h] /-- The Hausdorff distance is controlled by the diameter of the union. -/ theorem hausdorffEdist_le_ediam (hs : s.Nonempty) (ht : t.Nonempty) : hausdorffEdist s t ≤ diam (s ∪ t) := by rcases hs with ⟨x, xs⟩ rcases ht with ⟨y, yt⟩ refine hausdorffEdist_le_of_mem_edist ?_ ?_ · intro z hz exact ⟨y, yt, edist_le_diam_of_mem (subset_union_left hz) (subset_union_right yt)⟩ · intro z hz exact ⟨x, xs, edist_le_diam_of_mem (subset_union_right hz) (subset_union_left xs)⟩ /-- The Hausdorff distance satisfies the triangle inequality. -/ theorem hausdorffEdist_triangle : hausdorffEdist s u ≤ hausdorffEdist s t + hausdorffEdist t u := by rw [hausdorffEdist_def] simp only [sup_le_iff, iSup_le_iff] constructor · show ∀ x ∈ s, infEdist x u ≤ hausdorffEdist s t + hausdorffEdist t u exact fun x xs => calc infEdist x u ≤ infEdist x t + hausdorffEdist t u := infEdist_le_infEdist_add_hausdorffEdist _ ≤ hausdorffEdist s t + hausdorffEdist t u := add_le_add_right (infEdist_le_hausdorffEdist_of_mem xs) _ · show ∀ x ∈ u, infEdist x s ≤ hausdorffEdist s t + hausdorffEdist t u exact fun x xu => calc infEdist x s ≤ infEdist x t + hausdorffEdist t s := infEdist_le_infEdist_add_hausdorffEdist _ ≤ hausdorffEdist u t + hausdorffEdist t s := add_le_add_right (infEdist_le_hausdorffEdist_of_mem xu) _ _ = hausdorffEdist s t + hausdorffEdist t u := by simp [hausdorffEdist_comm, add_comm] /-- Two sets are at zero Hausdorff edistance if and only if they have the same closure. -/ theorem hausdorffEdist_zero_iff_closure_eq_closure : hausdorffEdist s t = 0 ↔ closure s = closure t := by simp only [hausdorffEdist_def, ENNReal.sup_eq_zero, ENNReal.iSup_eq_zero, ← subset_def, ← mem_closure_iff_infEdist_zero, subset_antisymm_iff, isClosed_closure.closure_subset_iff] /-- The Hausdorff edistance between a set and its closure vanishes. -/ @[simp] theorem hausdorffEdist_self_closure : hausdorffEdist s (closure s) = 0 := by rw [hausdorffEdist_zero_iff_closure_eq_closure, closure_closure] /-- Replacing a set by its closure does not change the Hausdorff edistance. -/ @[simp] theorem hausdorffEdist_closure₁ : hausdorffEdist (closure s) t = hausdorffEdist s t := by refine le_antisymm ?_ ?_ · calc _ ≤ hausdorffEdist (closure s) s + hausdorffEdist s t := hausdorffEdist_triangle _ = hausdorffEdist s t := by simp [hausdorffEdist_comm] · calc _ ≤ hausdorffEdist s (closure s) + hausdorffEdist (closure s) t := hausdorffEdist_triangle _ = hausdorffEdist (closure s) t := by simp /-- Replacing a set by its closure does not change the Hausdorff edistance. -/ @[simp] theorem hausdorffEdist_closure₂ : hausdorffEdist s (closure t) = hausdorffEdist s t := by simp [@hausdorffEdist_comm _ _ s _] /-- The Hausdorff edistance between sets or their closures is the same. -/ theorem hausdorffEdist_closure : hausdorffEdist (closure s) (closure t) = hausdorffEdist s t := by simp /-- Two closed sets are at zero Hausdorff edistance if and only if they coincide. -/ theorem hausdorffEdist_zero_iff_eq_of_closed (hs : IsClosed s) (ht : IsClosed t) : hausdorffEdist s t = 0 ↔ s = t := by rw [hausdorffEdist_zero_iff_closure_eq_closure, hs.closure_eq, ht.closure_eq] /-- The Haudorff edistance to the empty set is infinite. -/ theorem hausdorffEdist_empty (ne : s.Nonempty) : hausdorffEdist s ∅ = ∞ := by rcases ne with ⟨x, xs⟩ have : infEdist x ∅ ≤ hausdorffEdist s ∅ := infEdist_le_hausdorffEdist_of_mem xs simpa using this /-- If a set is at finite Hausdorff edistance of a nonempty set, it is nonempty. -/ theorem nonempty_of_hausdorffEdist_ne_top (hs : s.Nonempty) (fin : hausdorffEdist s t ≠ ⊤) : t.Nonempty := t.eq_empty_or_nonempty.resolve_left fun ht ↦ fin (ht.symm ▸ hausdorffEdist_empty hs) theorem empty_or_nonempty_of_hausdorffEdist_ne_top (fin : hausdorffEdist s t ≠ ⊤) : (s = ∅ ∧ t = ∅) ∨ (s.Nonempty ∧ t.Nonempty) := by rcases s.eq_empty_or_nonempty with hs | hs · rcases t.eq_empty_or_nonempty with ht | ht · exact Or.inl ⟨hs, ht⟩ · rw [hausdorffEdist_comm] at fin exact Or.inr ⟨nonempty_of_hausdorffEdist_ne_top ht fin, ht⟩ · exact Or.inr ⟨hs, nonempty_of_hausdorffEdist_ne_top hs fin⟩ end HausdorffEdist -- section end EMetric /-! Now, we turn to the same notions in metric spaces. To avoid the difficulties related to `sInf` and `sSup` on `ℝ` (which is only conditionally complete), we use the notions in `ℝ≥0∞` formulated in terms of the edistance, and coerce them to `ℝ`. Then their properties follow readily from the corresponding properties in `ℝ≥0∞`, modulo some tedious rewriting of inequalities from one to the other. -/ --namespace namespace Metric section variable [PseudoMetricSpace α] [PseudoMetricSpace β] {s t u : Set α} {x y : α} {Φ : α → β} open EMetric /-! ### Distance of a point to a set as a function into `ℝ`. -/ /-- The minimal distance of a point to a set -/ def infDist (x : α) (s : Set α) : ℝ := ENNReal.toReal (infEdist x s) theorem infDist_eq_iInf : infDist x s = ⨅ y : s, dist x y := by rw [infDist, infEdist, iInf_subtype', ENNReal.toReal_iInf] · simp only [dist_edist] · exact fun _ ↦ edist_ne_top _ _ /-- The minimal distance is always nonnegative -/ theorem infDist_nonneg : 0 ≤ infDist x s := toReal_nonneg /-- The minimal distance to the empty set is 0 (if you want to have the more reasonable value `∞` instead, use `EMetric.infEdist`, which takes values in `ℝ≥0∞`) -/ @[simp] theorem infDist_empty : infDist x ∅ = 0 := by simp [infDist] lemma isGLB_infDist (hs : s.Nonempty) : IsGLB ((dist x ·) '' s) (infDist x s) := by simpa [infDist_eq_iInf, sInf_image'] using isGLB_csInf (hs.image _) ⟨0, by simp [lowerBounds, dist_nonneg]⟩ /-- In a metric space, the minimal edistance to a nonempty set is finite. -/ theorem infEdist_ne_top (h : s.Nonempty) : infEdist x s ≠ ⊤ := by rcases h with ⟨y, hy⟩ exact ne_top_of_le_ne_top (edist_ne_top _ _) (infEdist_le_edist_of_mem hy) @[simp] theorem infEdist_eq_top_iff : infEdist x s = ∞ ↔ s = ∅ := by rcases s.eq_empty_or_nonempty with rfl | hs <;> simp [*, Nonempty.ne_empty, infEdist_ne_top] /-- The minimal distance of a point to a set containing it vanishes. -/ theorem infDist_zero_of_mem (h : x ∈ s) : infDist x s = 0 := by simp [infEdist_zero_of_mem h, infDist] /-- The minimal distance to a singleton is the distance to the unique point in this singleton. -/ @[simp] theorem infDist_singleton : infDist x {y} = dist x y := by simp [infDist, dist_edist] /-- The minimal distance to a set is bounded by the distance to any point in this set. -/ theorem infDist_le_dist_of_mem (h : y ∈ s) : infDist x s ≤ dist x y := by rw [dist_edist, infDist] exact ENNReal.toReal_mono (edist_ne_top _ _) (infEdist_le_edist_of_mem h) /-- The minimal distance is monotone with respect to inclusion. -/ theorem infDist_le_infDist_of_subset (h : s ⊆ t) (hs : s.Nonempty) : infDist x t ≤ infDist x s := ENNReal.toReal_mono (infEdist_ne_top hs) (infEdist_anti h) lemma le_infDist {r : ℝ} (hs : s.Nonempty) : r ≤ infDist x s ↔ ∀ ⦃y⦄, y ∈ s → r ≤ dist x y := by simp_rw [infDist, ← ENNReal.ofReal_le_iff_le_toReal (infEdist_ne_top hs), le_infEdist, ENNReal.ofReal_le_iff_le_toReal (edist_ne_top _ _), ← dist_edist] /-- The minimal distance to a set `s` is `< r` iff there exists a point in `s` at distance `< r`. -/ theorem infDist_lt_iff {r : ℝ} (hs : s.Nonempty) : infDist x s < r ↔ ∃ y ∈ s, dist x y < r := by simp [← not_le, le_infDist hs] /-- The minimal distance from `x` to `s` is bounded by the distance from `y` to `s`, modulo the distance between `x` and `y`. -/ theorem infDist_le_infDist_add_dist : infDist x s ≤ infDist y s + dist x y := by rw [infDist, infDist, dist_edist] refine ENNReal.toReal_le_add' infEdist_le_infEdist_add_edist ?_ (flip absurd (edist_ne_top _ _)) simp only [infEdist_eq_top_iff, imp_self] theorem not_mem_of_dist_lt_infDist (h : dist x y < infDist x s) : y ∉ s := fun hy => h.not_le <| infDist_le_dist_of_mem hy theorem disjoint_ball_infDist : Disjoint (ball x (infDist x s)) s := disjoint_left.2 fun _y hy => not_mem_of_dist_lt_infDist <| mem_ball'.1 hy theorem ball_infDist_subset_compl : ball x (infDist x s) ⊆ sᶜ := (disjoint_ball_infDist (s := s)).subset_compl_right theorem ball_infDist_compl_subset : ball x (infDist x sᶜ) ⊆ s := ball_infDist_subset_compl.trans_eq (compl_compl s) theorem disjoint_closedBall_of_lt_infDist {r : ℝ} (h : r < infDist x s) : Disjoint (closedBall x r) s := disjoint_ball_infDist.mono_left <| closedBall_subset_ball h theorem dist_le_infDist_add_diam (hs : IsBounded s) (hy : y ∈ s) : dist x y ≤ infDist x s + diam s := by rw [infDist, diam, dist_edist] exact toReal_le_add (edist_le_infEdist_add_ediam hy) (infEdist_ne_top ⟨y, hy⟩) hs.ediam_ne_top variable (s)
/-- The minimal distance to a set is Lipschitz in point with constant 1 -/
Mathlib/Topology/MetricSpace/HausdorffDistance.lean
515
516
/- Copyright (c) 2014 Parikshit Khanna. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Parikshit Khanna, Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Mario Carneiro -/ import Mathlib.Data.List.Lemmas import Mathlib.Data.Nat.Factorial.Basic import Mathlib.Data.List.Count import Mathlib.Data.List.Duplicate import Mathlib.Data.List.InsertIdx import Mathlib.Data.List.Induction import Batteries.Data.List.Perm import Mathlib.Data.List.Perm.Basic /-! # Permutations of a list In this file we prove properties about `List.Permutations`, a list of all permutations of a list. It is defined in `Data.List.Defs`. ## Order of the permutations Designed for performance, the order in which the permutations appear in `List.Permutations` is rather intricate and not very amenable to induction. That's why we also provide `List.Permutations'` as a less efficient but more straightforward way of listing permutations. ### `List.Permutations` TODO. In the meantime, you can try decrypting the docstrings. ### `List.Permutations'` The list of partitions is built by recursion. The permutations of `[]` are `[[]]`. Then, the permutations of `a :: l` are obtained by taking all permutations of `l` in order and adding `a` in all positions. Hence, to build `[0, 1, 2, 3].permutations'`, it does * `[[]]` * `[[3]]` * `[[2, 3], [3, 2]]]` * `[[1, 2, 3], [2, 1, 3], [2, 3, 1], [1, 3, 2], [3, 1, 2], [3, 2, 1]]` * `[[0, 1, 2, 3], [1, 0, 2, 3], [1, 2, 0, 3], [1, 2, 3, 0],` `[0, 2, 1, 3], [2, 0, 1, 3], [2, 1, 0, 3], [2, 1, 3, 0],` `[0, 2, 3, 1], [2, 0, 3, 1], [2, 3, 0, 1], [2, 3, 1, 0],` `[0, 1, 3, 2], [1, 0, 3, 2], [1, 3, 0, 2], [1, 3, 2, 0],` `[0, 3, 1, 2], [3, 0, 1, 2], [3, 1, 0, 2], [3, 1, 2, 0],` `[0, 3, 2, 1], [3, 0, 2, 1], [3, 2, 0, 1], [3, 2, 1, 0]]` -/ -- Make sure we don't import algebra assert_not_exists Monoid open Nat Function variable {α β : Type*} namespace List theorem permutationsAux2_fst (t : α) (ts : List α) (r : List β) : ∀ (ys : List α) (f : List α → β), (permutationsAux2 t ts r ys f).1 = ys ++ ts | [], _ => rfl | y :: ys, f => by simp [permutationsAux2, permutationsAux2_fst t _ _ ys] @[simp] theorem permutationsAux2_snd_nil (t : α) (ts : List α) (r : List β) (f : List α → β) : (permutationsAux2 t ts r [] f).2 = r := rfl @[simp] theorem permutationsAux2_snd_cons (t : α) (ts : List α) (r : List β) (y : α) (ys : List α) (f : List α → β) : (permutationsAux2 t ts r (y :: ys) f).2 = f (t :: y :: ys ++ ts) :: (permutationsAux2 t ts r ys fun x : List α => f (y :: x)).2 := by simp [permutationsAux2, permutationsAux2_fst t _ _ ys] /-- The `r` argument to `permutationsAux2` is the same as appending. -/ theorem permutationsAux2_append (t : α) (ts : List α) (r : List β) (ys : List α) (f : List α → β) : (permutationsAux2 t ts nil ys f).2 ++ r = (permutationsAux2 t ts r ys f).2 := by induction ys generalizing f <;> simp [*] /-- The `ts` argument to `permutationsAux2` can be folded into the `f` argument. -/ theorem permutationsAux2_comp_append {t : α} {ts ys : List α} {r : List β} (f : List α → β) : ((permutationsAux2 t [] r ys) fun x => f (x ++ ts)).2 = (permutationsAux2 t ts r ys f).2 := by induction' ys with ys_hd _ ys_ih generalizing f · simp · simp [ys_ih fun xs => f (ys_hd :: xs)] theorem map_permutationsAux2' {α' β'} (g : α → α') (g' : β → β') (t : α) (ts ys : List α) (r : List β) (f : List α → β) (f' : List α' → β') (H : ∀ a, g' (f a) = f' (map g a)) : map g' (permutationsAux2 t ts r ys f).2 = (permutationsAux2 (g t) (map g ts) (map g' r) (map g ys) f').2 := by induction' ys with ys_hd _ ys_ih generalizing f f' · simp · simp only [map, permutationsAux2_snd_cons, cons_append, cons.injEq] rw [ys_ih] · refine ⟨?_, rfl⟩ simp only [← map_cons, ← map_append]; apply H · intro a; apply H /-- The `f` argument to `permutationsAux2` when `r = []` can be eliminated. -/ theorem map_permutationsAux2 (t : α) (ts : List α) (ys : List α) (f : List α → β) : (permutationsAux2 t ts [] ys id).2.map f = (permutationsAux2 t ts [] ys f).2 := by rw [map_permutationsAux2' id, map_id, map_id] · rfl simp /-- An expository lemma to show how all of `ts`, `r`, and `f` can be eliminated from `permutationsAux2`. `(permutationsAux2 t [] [] ys id).2`, which appears on the RHS, is a list whose elements are produced by inserting `t` into every non-terminal position of `ys` in order. As an example: ```lean #eval permutationsAux2 1 [] [] [2, 3, 4] id -- [[1, 2, 3, 4], [2, 1, 3, 4], [2, 3, 1, 4]] ``` -/ theorem permutationsAux2_snd_eq (t : α) (ts : List α) (r : List β) (ys : List α) (f : List α → β) : (permutationsAux2 t ts r ys f).2 = ((permutationsAux2 t [] [] ys id).2.map fun x => f (x ++ ts)) ++ r := by rw [← permutationsAux2_append, map_permutationsAux2, permutationsAux2_comp_append] theorem map_map_permutationsAux2 {α'} (g : α → α') (t : α) (ts ys : List α) : map (map g) (permutationsAux2 t ts [] ys id).2 = (permutationsAux2 (g t) (map g ts) [] (map g ys) id).2 := map_permutationsAux2' _ _ _ _ _ _ _ _ fun _ => rfl theorem map_map_permutations'Aux (f : α → β) (t : α) (ts : List α) : map (map f) (permutations'Aux t ts) = permutations'Aux (f t) (map f ts) := by induction' ts with a ts ih · rfl · simp only [permutations'Aux, map_cons, map_map, ← ih, cons.injEq, true_and, Function.comp_def] theorem permutations'Aux_eq_permutationsAux2 (t : α) (ts : List α) : permutations'Aux t ts = (permutationsAux2 t [] [ts ++ [t]] ts id).2 := by induction' ts with a ts ih; · rfl simp only [permutations'Aux, ih, cons_append, permutationsAux2_snd_cons, append_nil, id_eq, cons.injEq, true_and] simp +singlePass only [← permutationsAux2_append] simp [map_permutationsAux2] theorem mem_permutationsAux2 {t : α} {ts : List α} {ys : List α} {l l' : List α} : l' ∈ (permutationsAux2 t ts [] ys (l ++ ·)).2 ↔ ∃ l₁ l₂, l₂ ≠ [] ∧ ys = l₁ ++ l₂ ∧ l' = l ++ l₁ ++ t :: l₂ ++ ts := by induction' ys with y ys ih generalizing l · simp +contextual rw [permutationsAux2_snd_cons, show (fun x : List α => l ++ y :: x) = (l ++ [y] ++ ·) by funext _; simp, mem_cons, ih] constructor · rintro (rfl | ⟨l₁, l₂, l0, rfl, rfl⟩) · exact ⟨[], y :: ys, by simp⟩ · exact ⟨y :: l₁, l₂, l0, by simp⟩ · rintro ⟨_ | ⟨y', l₁⟩, l₂, l0, ye, rfl⟩ · simp [ye] · simp only [cons_append] at ye rcases ye with ⟨rfl, rfl⟩ exact Or.inr ⟨l₁, l₂, l0, by simp⟩ theorem mem_permutationsAux2' {t : α} {ts : List α} {ys : List α} {l : List α} : l ∈ (permutationsAux2 t ts [] ys id).2 ↔ ∃ l₁ l₂, l₂ ≠ [] ∧ ys = l₁ ++ l₂ ∧ l = l₁ ++ t :: l₂ ++ ts := by rw [show @id (List α) = ([] ++ ·) by funext _; rfl]; apply mem_permutationsAux2 theorem length_permutationsAux2 (t : α) (ts : List α) (ys : List α) (f : List α → β) : length (permutationsAux2 t ts [] ys f).2 = length ys := by induction ys generalizing f <;> simp [*] theorem foldr_permutationsAux2 (t : α) (ts : List α) (r L : List (List α)) : foldr (fun y r => (permutationsAux2 t ts r y id).2) r L = (L.flatMap fun y => (permutationsAux2 t ts [] y id).2) ++ r := by induction' L with l L ih · rfl · simp_rw [foldr_cons, ih, flatMap_cons, append_assoc, permutationsAux2_append] theorem mem_foldr_permutationsAux2 {t : α} {ts : List α} {r L : List (List α)} {l' : List α} : l' ∈ foldr (fun y r => (permutationsAux2 t ts r y id).2) r L ↔ l' ∈ r ∨ ∃ l₁ l₂, l₁ ++ l₂ ∈ L ∧ l₂ ≠ [] ∧ l' = l₁ ++ t :: l₂ ++ ts := by have : (∃ a : List α, a ∈ L ∧ ∃ l₁ l₂ : List α, ¬l₂ = nil ∧ a = l₁ ++ l₂ ∧ l' = l₁ ++ t :: (l₂ ++ ts)) ↔ ∃ l₁ l₂ : List α, ¬l₂ = nil ∧ l₁ ++ l₂ ∈ L ∧ l' = l₁ ++ t :: (l₂ ++ ts) := ⟨fun ⟨_, aL, l₁, l₂, l0, e, h⟩ => ⟨l₁, l₂, l0, e ▸ aL, h⟩, fun ⟨l₁, l₂, l0, aL, h⟩ => ⟨_, aL, l₁, l₂, l0, rfl, h⟩⟩ rw [foldr_permutationsAux2] simp only [mem_permutationsAux2', ← this, or_comm, and_left_comm, mem_append, mem_flatMap, append_assoc, cons_append, exists_prop] theorem length_foldr_permutationsAux2 (t : α) (ts : List α) (r L : List (List α)) : length (foldr (fun y r => (permutationsAux2 t ts r y id).2) r L) = (map length L).sum + length r := by simp [foldr_permutationsAux2, Function.comp_def, length_permutationsAux2, length_flatMap] theorem length_foldr_permutationsAux2' (t : α) (ts : List α) (r L : List (List α)) (n) (H : ∀ l ∈ L, length l = n) : length (foldr (fun y r => (permutationsAux2 t ts r y id).2) r L) = n * length L + length r := by rw [length_foldr_permutationsAux2, (_ : (map length L).sum = n * length L)] induction' L with l L ih · simp have sum_map : (map length L).sum = n * length L := ih fun l m => H l (mem_cons_of_mem _ m) have length_l : length l = n := H _ mem_cons_self simp [sum_map, length_l, Nat.mul_add, Nat.add_comm, mul_succ] @[simp] theorem permutationsAux_nil (is : List α) : permutationsAux [] is = [] := by rw [permutationsAux, permutationsAux.rec] @[simp] theorem permutationsAux_cons (t : α) (ts is : List α) : permutationsAux (t :: ts) is = foldr (fun y r => (permutationsAux2 t ts r y id).2) (permutationsAux ts (t :: is)) (permutations is) := by rw [permutationsAux, permutationsAux.rec]; rfl @[simp] theorem permutations_nil : permutations ([] : List α) = [[]] := by rw [permutations, permutationsAux_nil] theorem map_permutationsAux (f : α → β) : ∀ ts is : List α, map (map f) (permutationsAux ts is) = permutationsAux (map f ts) (map f is) := by refine permutationsAux.rec (by simp) ?_ introv IH1 IH2; rw [map] at IH2 simp only [foldr_permutationsAux2, map_append, map, map_map_permutationsAux2, permutations, flatMap_map, IH1, append_assoc, permutationsAux_cons, flatMap_cons, ← IH2, map_flatMap] theorem map_permutations (f : α → β) (ts : List α) : map (map f) (permutations ts) = permutations (map f ts) := by rw [permutations, permutations, map, map_permutationsAux, map] theorem map_permutations' (f : α → β) (ts : List α) : map (map f) (permutations' ts) = permutations' (map f ts) := by induction' ts with t ts ih <;> [rfl; simp [← ih, map_flatMap, ← map_map_permutations'Aux, flatMap_map]]
theorem permutationsAux_append (is is' ts : List α) :
Mathlib/Data/List/Permutation.lean
231
232
/- Copyright (c) 2020 Johan Commelin, Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin, Robert Y. Lewis -/ import Mathlib.Algebra.MvPolynomial.Rename import Mathlib.Algebra.MvPolynomial.Variables /-! # Monad operations on `MvPolynomial` This file defines two monadic operations on `MvPolynomial`. Given `p : MvPolynomial σ R`, * `MvPolynomial.bind₁` and `MvPolynomial.join₁` operate on the variable type `σ`. * `MvPolynomial.bind₂` and `MvPolynomial.join₂` operate on the coefficient type `R`. - `MvPolynomial.bind₁ f φ` with `f : σ → MvPolynomial τ R` and `φ : MvPolynomial σ R`, is the polynomial `φ(f 1, ..., f i, ...) : MvPolynomial τ R`. - `MvPolynomial.join₁ φ` with `φ : MvPolynomial (MvPolynomial σ R) R` collapses `φ` to a `MvPolynomial σ R`, by evaluating `φ` under the map `X f ↦ f` for `f : MvPolynomial σ R`. In other words, if you have a polynomial `φ` in a set of variables indexed by a polynomial ring, you evaluate the polynomial in these indexing polynomials. - `MvPolynomial.bind₂ f φ` with `f : R →+* MvPolynomial σ S` and `φ : MvPolynomial σ R` is the `MvPolynomial σ S` obtained from `φ` by mapping the coefficients of `φ` through `f` and considering the resulting polynomial as polynomial expression in `MvPolynomial σ R`. - `MvPolynomial.join₂ φ` with `φ : MvPolynomial σ (MvPolynomial σ R)` collapses `φ` to a `MvPolynomial σ R`, by considering `φ` as polynomial expression in `MvPolynomial σ R`. These operations themselves have algebraic structure: `MvPolynomial.bind₁` and `MvPolynomial.join₁` are algebra homs and `MvPolynomial.bind₂` and `MvPolynomial.join₂` are ring homs. They interact in convenient ways with `MvPolynomial.rename`, `MvPolynomial.map`, `MvPolynomial.vars`, and other polynomial operations. Indeed, `MvPolynomial.rename` is the "map" operation for the (`bind₁`, `join₁`) pair, whereas `MvPolynomial.map` is the "map" operation for the other pair. ## Implementation notes We add a `LawfulMonad` instance for the (`bind₁`, `join₁`) pair. The second pair cannot be instantiated as a `Monad`, since it is not a monad in `Type` but in `CommRingCat` (or rather `CommSemiRingCat`). -/ noncomputable section namespace MvPolynomial open Finsupp variable {σ : Type*} {τ : Type*} variable {R S T : Type*} [CommSemiring R] [CommSemiring S] [CommSemiring T] /-- `bind₁` is the "left hand side" bind operation on `MvPolynomial`, operating on the variable type. Given a polynomial `p : MvPolynomial σ R` and a map `f : σ → MvPolynomial τ R` taking variables in `p` to polynomials in the variable type `τ`, `bind₁ f p` replaces each variable in `p` with its value under `f`, producing a new polynomial in `τ`. The coefficient type remains the same. This operation is an algebra hom. -/ def bind₁ (f : σ → MvPolynomial τ R) : MvPolynomial σ R →ₐ[R] MvPolynomial τ R := aeval f /-- `bind₂` is the "right hand side" bind operation on `MvPolynomial`, operating on the coefficient type. Given a polynomial `p : MvPolynomial σ R` and a map `f : R → MvPolynomial σ S` taking coefficients in `p` to polynomials over a new ring `S`, `bind₂ f p` replaces each coefficient in `p` with its value under `f`, producing a new polynomial over `S`. The variable type remains the same. This operation is a ring hom. -/ def bind₂ (f : R →+* MvPolynomial σ S) : MvPolynomial σ R →+* MvPolynomial σ S := eval₂Hom f X /-- `join₁` is the monadic join operation corresponding to `MvPolynomial.bind₁`. Given a polynomial `p` with coefficients in `R` whose variables are polynomials in `σ` with coefficients in `R`, `join₁ p` collapses `p` to a polynomial with variables in `σ` and coefficients in `R`. This operation is an algebra hom. -/ def join₁ : MvPolynomial (MvPolynomial σ R) R →ₐ[R] MvPolynomial σ R := aeval id /-- `join₂` is the monadic join operation corresponding to `MvPolynomial.bind₂`. Given a polynomial `p` with variables in `σ` whose coefficients are polynomials in `σ` with coefficients in `R`, `join₂ p` collapses `p` to a polynomial with variables in `σ` and coefficients in `R`. This operation is a ring hom. -/ def join₂ : MvPolynomial σ (MvPolynomial σ R) →+* MvPolynomial σ R := eval₂Hom (RingHom.id _) X @[simp] theorem aeval_eq_bind₁ (f : σ → MvPolynomial τ R) : aeval f = bind₁ f := rfl @[simp] theorem eval₂Hom_C_eq_bind₁ (f : σ → MvPolynomial τ R) : eval₂Hom C f = bind₁ f := rfl @[simp] theorem eval₂Hom_eq_bind₂ (f : R →+* MvPolynomial σ S) : eval₂Hom f X = bind₂ f := rfl section variable (σ R) @[simp] theorem aeval_id_eq_join₁ : aeval id = @join₁ σ R _ := rfl theorem eval₂Hom_C_id_eq_join₁ (φ : MvPolynomial (MvPolynomial σ R) R) : eval₂Hom C id φ = join₁ φ := rfl @[simp] theorem eval₂Hom_id_X_eq_join₂ : eval₂Hom (RingHom.id _) X = @join₂ σ R _ := rfl end -- In this file, we don't want to use these simp lemmas, -- because we first need to show how these new definitions interact -- and the proofs fall back on unfolding the definitions and call simp afterwards attribute [-simp] aeval_eq_bind₁ eval₂Hom_C_eq_bind₁ eval₂Hom_eq_bind₂ aeval_id_eq_join₁ eval₂Hom_id_X_eq_join₂ @[simp] theorem bind₁_X_right (f : σ → MvPolynomial τ R) (i : σ) : bind₁ f (X i) = f i := aeval_X f i @[simp] theorem bind₂_X_right (f : R →+* MvPolynomial σ S) (i : σ) : bind₂ f (X i) = X i := eval₂Hom_X' f X i @[simp] theorem bind₁_X_left : bind₁ (X : σ → MvPolynomial σ R) = AlgHom.id R _ := by ext1 i simp variable (f : σ → MvPolynomial τ R) theorem bind₁_C_right (f : σ → MvPolynomial τ R) (x) : bind₁ f (C x) = C x := algHom_C _ _ @[simp] theorem bind₂_C_right (f : R →+* MvPolynomial σ S) (r : R) : bind₂ f (C r) = f r := eval₂Hom_C f X r @[simp] theorem bind₂_C_left : bind₂ (C : R →+* MvPolynomial σ R) = RingHom.id _ := by ext : 2 <;> simp @[simp] theorem bind₂_comp_C (f : R →+* MvPolynomial σ S) : (bind₂ f).comp C = f := RingHom.ext <| bind₂_C_right _ @[simp] theorem join₂_map (f : R →+* MvPolynomial σ S) (φ : MvPolynomial σ R) : join₂ (map f φ) = bind₂ f φ := by simp only [join₂, bind₂, eval₂Hom_map_hom, RingHom.id_comp] @[simp] theorem join₂_comp_map (f : R →+* MvPolynomial σ S) : join₂.comp (map f) = bind₂ f := RingHom.ext <| join₂_map _ theorem aeval_id_rename (f : σ → MvPolynomial τ R) (p : MvPolynomial σ R) : aeval id (rename f p) = aeval f p := by rw [aeval_rename, Function.id_comp] @[simp] theorem join₁_rename (f : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) : join₁ (rename f φ) = bind₁ f φ := aeval_id_rename _ _ @[simp] theorem bind₁_id : bind₁ (@id (MvPolynomial σ R)) = join₁ := rfl @[simp] theorem bind₂_id : bind₂ (RingHom.id (MvPolynomial σ R)) = join₂ := rfl theorem bind₁_bind₁ {υ : Type*} (f : σ → MvPolynomial τ R) (g : τ → MvPolynomial υ R) (φ : MvPolynomial σ R) : (bind₁ g) (bind₁ f φ) = bind₁ (fun i => bind₁ g (f i)) φ := by simp [bind₁, ← comp_aeval] theorem bind₁_comp_bind₁ {υ : Type*} (f : σ → MvPolynomial τ R) (g : τ → MvPolynomial υ R) : (bind₁ g).comp (bind₁ f) = bind₁ fun i => bind₁ g (f i) := by ext1 apply bind₁_bind₁ theorem bind₂_comp_bind₂ (f : R →+* MvPolynomial σ S) (g : S →+* MvPolynomial σ T) : (bind₂ g).comp (bind₂ f) = bind₂ ((bind₂ g).comp f) := by ext : 2 <;> simp theorem bind₂_bind₂ (f : R →+* MvPolynomial σ S) (g : S →+* MvPolynomial σ T) (φ : MvPolynomial σ R) : (bind₂ g) (bind₂ f φ) = bind₂ ((bind₂ g).comp f) φ := RingHom.congr_fun (bind₂_comp_bind₂ f g) φ theorem rename_comp_bind₁ {υ : Type*} (f : σ → MvPolynomial τ R) (g : τ → υ) : (rename g).comp (bind₁ f) = bind₁ fun i => rename g <| f i := by ext1 i simp theorem rename_bind₁ {υ : Type*} (f : σ → MvPolynomial τ R) (g : τ → υ) (φ : MvPolynomial σ R) : rename g (bind₁ f φ) = bind₁ (fun i => rename g <| f i) φ := AlgHom.congr_fun (rename_comp_bind₁ f g) φ theorem map_bind₂ (f : R →+* MvPolynomial σ S) (g : S →+* T) (φ : MvPolynomial σ R) : map g (bind₂ f φ) = bind₂ ((map g).comp f) φ := by simp only [bind₂, eval₂_comp_right, coe_eval₂Hom, eval₂_map] congr 1 with : 1 simp only [Function.comp_apply, map_X] theorem bind₁_comp_rename {υ : Type*} (f : τ → MvPolynomial υ R) (g : σ → τ) : (bind₁ f).comp (rename g) = bind₁ (f ∘ g) := by ext1 i simp theorem bind₁_rename {υ : Type*} (f : τ → MvPolynomial υ R) (g : σ → τ) (φ : MvPolynomial σ R) : bind₁ f (rename g φ) = bind₁ (f ∘ g) φ := AlgHom.congr_fun (bind₁_comp_rename f g) φ theorem bind₂_map (f : S →+* MvPolynomial σ T) (g : R →+* S) (φ : MvPolynomial σ R) : bind₂ f (map g φ) = bind₂ (f.comp g) φ := by simp [bind₂] @[simp] theorem map_comp_C (f : R →+* S) : (map f).comp (C : R →+* MvPolynomial σ R) = C.comp f := by ext1 apply map_C -- mixing the two monad structures theorem hom_bind₁ (f : MvPolynomial τ R →+* S) (g : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) : f (bind₁ g φ) = eval₂Hom (f.comp C) (fun i => f (g i)) φ := by rw [bind₁, map_aeval, algebraMap_eq] theorem map_bind₁ (f : R →+* S) (g : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) : map f (bind₁ g φ) = bind₁ (fun i : σ => (map f) (g i)) (map f φ) := by rw [hom_bind₁, map_comp_C, ← eval₂Hom_map_hom] rfl @[simp] theorem eval₂Hom_comp_C (f : R →+* S) (g : σ → S) : (eval₂Hom f g).comp C = f := by ext1 r exact eval₂_C f g r theorem eval₂Hom_bind₁ (f : R →+* S) (g : τ → S) (h : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) : eval₂Hom f g (bind₁ h φ) = eval₂Hom f (fun i => eval₂Hom f g (h i)) φ := by rw [hom_bind₁, eval₂Hom_comp_C] theorem aeval_bind₁ [Algebra R S] (f : τ → S) (g : σ → MvPolynomial τ R) (φ : MvPolynomial σ R) : aeval f (bind₁ g φ) = aeval (fun i => aeval f (g i)) φ := eval₂Hom_bind₁ _ _ _ _ theorem aeval_comp_bind₁ [Algebra R S] (f : τ → S) (g : σ → MvPolynomial τ R) : (aeval f).comp (bind₁ g) = aeval fun i => aeval f (g i) := by ext1 apply aeval_bind₁ theorem eval₂Hom_comp_bind₂ (f : S →+* T) (g : σ → T) (h : R →+* MvPolynomial σ S) : (eval₂Hom f g).comp (bind₂ h) = eval₂Hom ((eval₂Hom f g).comp h) g := by ext : 2 <;> simp theorem eval₂Hom_bind₂ (f : S →+* T) (g : σ → T) (h : R →+* MvPolynomial σ S) (φ : MvPolynomial σ R) : eval₂Hom f g (bind₂ h φ) = eval₂Hom ((eval₂Hom f g).comp h) g φ := RingHom.congr_fun (eval₂Hom_comp_bind₂ f g h) φ theorem aeval_bind₂ [Algebra S T] (f : σ → T) (g : R →+* MvPolynomial σ S) (φ : MvPolynomial σ R) : aeval f (bind₂ g φ) = eval₂Hom ((↑(aeval f : _ →ₐ[S] _) : _ →+* _).comp g) f φ := eval₂Hom_bind₂ _ _ _ _ alias eval₂Hom_C_left := eval₂Hom_C_eq_bind₁ theorem bind₁_monomial (f : σ → MvPolynomial τ R) (d : σ →₀ ℕ) (r : R) : bind₁ f (monomial d r) = C r * ∏ i ∈ d.support, f i ^ d i := by simp only [monomial_eq, map_mul, bind₁_C_right, Finsupp.prod, map_prod, map_pow, bind₁_X_right] theorem bind₂_monomial (f : R →+* MvPolynomial σ S) (d : σ →₀ ℕ) (r : R) : bind₂ f (monomial d r) = f r * monomial d 1 := by
simp only [monomial_eq, RingHom.map_mul, bind₂_C_right, Finsupp.prod, map_prod, map_pow, bind₂_X_right, C_1, one_mul]
Mathlib/Algebra/MvPolynomial/Monad.lean
280
282
/- 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, Sébastien Gouëzel, Rémy Degenne -/ import Mathlib.MeasureTheory.Integral.FinMeasAdditive /-! # Extension of a linear function from indicators to L1 Given `T : Set α → E →L[ℝ] F` with `DominatedFinMeasAdditive μ T C`, we construct an extension of `T` to integrable simple functions, which are finite sums of indicators of measurable sets with finite measure, then to integrable functions, which are limits of integrable simple functions. The main result is a continuous linear map `(α →₁[μ] E) →L[ℝ] F`. This extension process is used to define the Bochner integral in the `Mathlib.MeasureTheory.Integral.Bochner.Basic` file and the conditional expectation of an integrable function in `Mathlib.MeasureTheory.Function.ConditionalExpectation.CondexpL1`. ## Main definitions - `setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F`: the extension of `T` from indicators to L1. - `setToFun μ T (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F`: a version of the extension which applies to functions (with value 0 if the function is not integrable). ## Properties For most properties of `setToFun`, we provide two lemmas. One version uses hypotheses valid on all sets, like `T = T'`, and a second version which uses a primed name uses hypotheses on measurable sets with finite measure, like `∀ s, MeasurableSet s → μ s < ∞ → T s = T' s`. The lemmas listed here don't show all hypotheses. Refer to the actual lemmas for details. Linearity: - `setToFun_zero_left : setToFun μ 0 hT f = 0` - `setToFun_add_left : setToFun μ (T + T') _ f = setToFun μ T hT f + setToFun μ T' hT' f` - `setToFun_smul_left : setToFun μ (fun s ↦ c • (T s)) (hT.smul c) f = c • setToFun μ T hT f` - `setToFun_zero : setToFun μ T hT (0 : α → E) = 0` - `setToFun_neg : setToFun μ T hT (-f) = - setToFun μ T hT f` If `f` and `g` are integrable: - `setToFun_add : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g` - `setToFun_sub : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g` If `T` is verifies `∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x`: - `setToFun_smul : setToFun μ T hT (c • f) = c • setToFun μ T hT f` Other: - `setToFun_congr_ae (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g` - `setToFun_measure_zero (h : μ = 0) : setToFun μ T hT f = 0` If the space is also an ordered additive group with an order closed topology and `T` is such that `0 ≤ T s x` for `0 ≤ x`, we also prove order-related properties: - `setToFun_mono_left (h : ∀ s x, T s x ≤ T' s x) : setToFun μ T hT f ≤ setToFun μ T' hT' f` - `setToFun_nonneg (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f` - `setToFun_mono (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g` -/ noncomputable section open scoped Topology NNReal open Set Filter TopologicalSpace ENNReal namespace MeasureTheory variable {α E F F' G 𝕜 : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup F'] [NormedSpace ℝ F'] [NormedAddCommGroup G] {m : MeasurableSpace α} {μ : Measure α} namespace L1 open AEEqFun Lp.simpleFunc Lp namespace SimpleFunc theorem norm_eq_sum_mul (f : α →₁ₛ[μ] G) : ‖f‖ = ∑ x ∈ (toSimpleFunc f).range, μ.real (toSimpleFunc f ⁻¹' {x}) * ‖x‖ := by rw [norm_toSimpleFunc, eLpNorm_one_eq_lintegral_enorm] have h_eq := SimpleFunc.map_apply (‖·‖ₑ) (toSimpleFunc f) simp_rw [← h_eq, measureReal_def] rw [SimpleFunc.lintegral_eq_lintegral, SimpleFunc.map_lintegral, ENNReal.toReal_sum] · congr ext1 x rw [ENNReal.toReal_mul, mul_comm, ← ofReal_norm_eq_enorm, ENNReal.toReal_ofReal (norm_nonneg _)] · intro x _ by_cases hx0 : x = 0 · rw [hx0]; simp · exact ENNReal.mul_ne_top ENNReal.coe_ne_top (SimpleFunc.measure_preimage_lt_top_of_integrable _ (SimpleFunc.integrable f) hx0).ne section SetToL1S variable [NormedField 𝕜] [NormedSpace 𝕜 E] attribute [local instance] Lp.simpleFunc.module attribute [local instance] Lp.simpleFunc.normedSpace /-- Extend `Set α → (E →L[ℝ] F')` to `(α →₁ₛ[μ] E) → F'`. -/ def setToL1S (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : F := (toSimpleFunc f).setToSimpleFunc T theorem setToL1S_eq_setToSimpleFunc (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : setToL1S T f = (toSimpleFunc f).setToSimpleFunc T := rfl @[simp] theorem setToL1S_zero_left (f : α →₁ₛ[μ] E) : setToL1S (0 : Set α → E →L[ℝ] F) f = 0 := SimpleFunc.setToSimpleFunc_zero _ theorem setToL1S_zero_left' {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1S T f = 0 := SimpleFunc.setToSimpleFunc_zero' h_zero _ (SimpleFunc.integrable f) theorem setToL1S_congr (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) : setToL1S T f = setToL1S T g := SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) h theorem setToL1S_congr_left (T T' : Set α → E →L[ℝ] F) (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) : setToL1S T f = setToL1S T' f := SimpleFunc.setToSimpleFunc_congr_left T T' h (simpleFunc.toSimpleFunc f) (SimpleFunc.integrable f) /-- `setToL1S` does not change if we replace the measure `μ` by `μ'` with `μ ≪ μ'`. The statement uses two functions `f` and `f'` because they have to belong to different types, but morally these are the same function (we have `f =ᵐ[μ] f'`). -/ theorem setToL1S_congr_measure {μ' : Measure α} (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') : setToL1S T f = setToL1S T f' := by refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) ?_ refine (toSimpleFunc_eq_toFun f).trans ?_ suffices (f' : α → E) =ᵐ[μ] simpleFunc.toSimpleFunc f' from h.trans this have goal' : (f' : α → E) =ᵐ[μ'] simpleFunc.toSimpleFunc f' := (toSimpleFunc_eq_toFun f').symm exact hμ.ae_eq goal' theorem setToL1S_add_left (T T' : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : setToL1S (T + T') f = setToL1S T f + setToL1S T' f := SimpleFunc.setToSimpleFunc_add_left T T' theorem setToL1S_add_left' (T T' T'' : Set α → E →L[ℝ] F) (h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) : setToL1S T'' f = setToL1S T f + setToL1S T' f := SimpleFunc.setToSimpleFunc_add_left' T T' T'' h_add (SimpleFunc.integrable f) theorem setToL1S_smul_left (T : Set α → E →L[ℝ] F) (c : ℝ) (f : α →₁ₛ[μ] E) : setToL1S (fun s => c • T s) f = c • setToL1S T f := SimpleFunc.setToSimpleFunc_smul_left T c _ theorem setToL1S_smul_left' (T T' : Set α → E →L[ℝ] F) (c : ℝ) (h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) : setToL1S T' f = c • setToL1S T f := SimpleFunc.setToSimpleFunc_smul_left' T T' c h_smul (SimpleFunc.integrable f) theorem setToL1S_add (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) : setToL1S T (f + g) = setToL1S T f + setToL1S T g := by simp_rw [setToL1S] rw [← SimpleFunc.setToSimpleFunc_add T h_add (SimpleFunc.integrable f) (SimpleFunc.integrable g)] exact SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) (add_toSimpleFunc f g) theorem setToL1S_neg {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (f : α →₁ₛ[μ] E) : setToL1S T (-f) = -setToL1S T f := by simp_rw [setToL1S] have : simpleFunc.toSimpleFunc (-f) =ᵐ[μ] ⇑(-simpleFunc.toSimpleFunc f) := neg_toSimpleFunc f rw [SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) this] exact SimpleFunc.setToSimpleFunc_neg T h_add (SimpleFunc.integrable f) theorem setToL1S_sub {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) : setToL1S T (f - g) = setToL1S T f - setToL1S T g := by rw [sub_eq_add_neg, setToL1S_add T h_zero h_add, setToL1S_neg h_zero h_add, sub_eq_add_neg] theorem setToL1S_smul_real (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (c : ℝ) (f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by simp_rw [setToL1S] rw [← SimpleFunc.setToSimpleFunc_smul_real T h_add c (SimpleFunc.integrable f)] refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_ exact smul_toSimpleFunc c f theorem setToL1S_smul {E} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedSpace 𝕜 E] [DistribSMul 𝕜 F] (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by simp_rw [setToL1S] rw [← SimpleFunc.setToSimpleFunc_smul T h_add h_smul c (SimpleFunc.integrable f)] refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_ exact smul_toSimpleFunc c f theorem norm_setToL1S_le (T : Set α → E →L[ℝ] F) {C : ℝ} (hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * μ.real s) (f : α →₁ₛ[μ] E) : ‖setToL1S T f‖ ≤ C * ‖f‖ := by rw [setToL1S, norm_eq_sum_mul f] exact SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm _ (SimpleFunc.integrable f) theorem setToL1S_indicatorConst {T : Set α → E →L[ℝ] F} {s : Set α} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) : setToL1S T (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by have h_empty : T ∅ = 0 := h_zero _ MeasurableSet.empty measure_empty rw [setToL1S_eq_setToSimpleFunc] refine Eq.trans ?_ (SimpleFunc.setToSimpleFunc_indicator T h_empty hs x) refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_ exact toSimpleFunc_indicatorConst hs hμs.ne x theorem setToL1S_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (x : E) : setToL1S T (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x := setToL1S_indicatorConst h_zero h_add MeasurableSet.univ (measure_lt_top _ _) x section Order variable {G'' G' : Type*} [NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G'] [NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G''] {T : Set α → G'' →L[ℝ] G'} theorem setToL1S_mono_left {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f := SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _ theorem setToL1S_mono_left' {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f := SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f) omit [IsOrderedAddMonoid G''] in theorem setToL1S_nonneg (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G''} (hf : 0 ≤ f) : 0 ≤ setToL1S T f := by simp_rw [setToL1S] obtain ⟨f', hf', hff'⟩ := exists_simpleFunc_nonneg_ae_eq hf replace hff' : simpleFunc.toSimpleFunc f =ᵐ[μ] f' := (Lp.simpleFunc.toSimpleFunc_eq_toFun f).trans hff' rw [SimpleFunc.setToSimpleFunc_congr _ h_zero h_add (SimpleFunc.integrable _) hff'] exact SimpleFunc.setToSimpleFunc_nonneg' T hT_nonneg _ hf' ((SimpleFunc.integrable f).congr hff') theorem setToL1S_mono (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G''} (hfg : f ≤ g) : setToL1S T f ≤ setToL1S T g := by rw [← sub_nonneg] at hfg ⊢ rw [← setToL1S_sub h_zero h_add] exact setToL1S_nonneg h_zero h_add hT_nonneg hfg end Order variable [NormedSpace 𝕜 F] variable (α E μ 𝕜) /-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[𝕜] F`. -/ def setToL1SCLM' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁ₛ[μ] E) →L[𝕜] F := LinearMap.mkContinuous ⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩, setToL1S_smul T (fun _ => hT.eq_zero_of_measure_zero) hT.1 h_smul⟩ C fun f => norm_setToL1S_le T hT.2 f /-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[ℝ] F`. -/ def setToL1SCLM {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) : (α →₁ₛ[μ] E) →L[ℝ] F := LinearMap.mkContinuous ⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩, setToL1S_smul_real T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩ C fun f => norm_setToL1S_le T hT.2 f variable {α E μ 𝕜} variable {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} @[simp] theorem setToL1SCLM_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 := setToL1S_zero_left _ theorem setToL1SCLM_zero_left' (hT : DominatedFinMeasAdditive μ T C) (h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 := setToL1S_zero_left' h_zero f theorem setToL1SCLM_congr_left (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f := setToL1S_congr_left T T' (fun _ _ _ => by rw [h]) f theorem setToL1SCLM_congr_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f := setToL1S_congr_left T T' h f theorem setToL1SCLM_congr_measure {μ' : Measure α} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ' T C') (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') : setToL1SCLM α E μ hT f = setToL1SCLM α E μ' hT' f' := setToL1S_congr_measure T (fun _ => hT.eq_zero_of_measure_zero) hT.1 hμ _ _ h theorem setToL1SCLM_add_left (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ (hT.add hT') f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f := setToL1S_add_left T T' f theorem setToL1SCLM_add_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'') (h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT'' f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f := setToL1S_add_left' T T' T'' h_add f theorem setToL1SCLM_smul_left (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ (hT.smul c) f = c • setToL1SCLM α E μ hT f := setToL1S_smul_left T c f theorem setToL1SCLM_smul_left' (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT' f = c • setToL1SCLM α E μ hT f := setToL1S_smul_left' T T' c h_smul f theorem norm_setToL1SCLM_le {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1SCLM α E μ hT‖ ≤ C := LinearMap.mkContinuous_norm_le _ hC _ theorem norm_setToL1SCLM_le' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1SCLM α E μ hT‖ ≤ max C 0 := LinearMap.mkContinuous_norm_le' _ _ theorem setToL1SCLM_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (x : E) : setToL1SCLM α E μ hT (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x := setToL1S_const (fun _ => hT.eq_zero_of_measure_zero) hT.1 x section Order variable {G' G'' : Type*} [NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G''] [NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G'] theorem setToL1SCLM_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f := SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _ theorem setToL1SCLM_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f := SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f) omit [IsOrderedAddMonoid G'] in theorem setToL1SCLM_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G'} (hf : 0 ≤ f) : 0 ≤ setToL1SCLM α G' μ hT f := setToL1S_nonneg (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hf theorem setToL1SCLM_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G'} (hfg : f ≤ g) : setToL1SCLM α G' μ hT f ≤ setToL1SCLM α G' μ hT g := setToL1S_mono (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hfg end Order end SetToL1S end SimpleFunc open SimpleFunc section SetToL1 attribute [local instance] Lp.simpleFunc.module attribute [local instance] Lp.simpleFunc.normedSpace variable (𝕜) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} /-- Extend `Set α → (E →L[ℝ] F)` to `(α →₁[μ] E) →L[𝕜] F`. -/ def setToL1' (hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁[μ] E) →L[𝕜] F := (setToL1SCLM' α E 𝕜 μ hT h_smul).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top) simpleFunc.isUniformInducing variable {𝕜} /-- Extend `Set α → E →L[ℝ] F` to `(α →₁[μ] E) →L[ℝ] F`. -/ def setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F := (setToL1SCLM α E μ hT).extend (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top) simpleFunc.isUniformInducing theorem setToL1_eq_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) : setToL1 hT f = setToL1SCLM α E μ hT f := uniformly_extend_of_ind simpleFunc.isUniformInducing (simpleFunc.denseRange one_ne_top) (setToL1SCLM α E μ hT).uniformContinuous _ theorem setToL1_eq_setToL1' (hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (f : α →₁[μ] E) : setToL1 hT f = setToL1' 𝕜 hT h_smul f := rfl @[simp] theorem setToL1_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C) (f : α →₁[μ] E) : setToL1 hT f = 0 := by suffices setToL1 hT = 0 by rw [this]; simp refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_ ext1 f rw [setToL1SCLM_zero_left hT f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply] theorem setToL1_zero_left' (hT : DominatedFinMeasAdditive μ T C) (h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁[μ] E) : setToL1 hT f = 0 := by suffices setToL1 hT = 0 by rw [this]; simp refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_ ext1 f rw [setToL1SCLM_zero_left' hT h_zero f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply] theorem setToL1_congr_left (T T' : Set α → E →L[ℝ] F) {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by suffices setToL1 hT = setToL1 hT' by rw [this] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_ ext1 f suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM] exact setToL1SCLM_congr_left hT' hT h.symm f theorem setToL1_congr_left' (T T' : Set α → E →L[ℝ] F) {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by suffices setToL1 hT = setToL1 hT' by rw [this] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_ ext1 f suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM] exact (setToL1SCLM_congr_left' hT hT' h f).symm theorem setToL1_add_left (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁[μ] E) : setToL1 (hT.add hT') f = setToL1 hT f + setToL1 hT' f := by suffices setToL1 (hT.add hT') = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.add hT')) _ _ _ _ ?_ ext1 f suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ (hT.add hT') f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left hT hT'] theorem setToL1_add_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'') (h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁[μ] E) : setToL1 hT'' f = setToL1 hT f + setToL1 hT' f := by suffices setToL1 hT'' = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT'') _ _ _ _ ?_ ext1 f suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ hT'' f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left' hT hT' hT'' h_add] theorem setToL1_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α →₁[μ] E) : setToL1 (hT.smul c) f = c • setToL1 hT f := by suffices setToL1 (hT.smul c) = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.smul c)) _ _ _ _ ?_ ext1 f suffices c • setToL1 hT f = setToL1SCLM α E μ (hT.smul c) f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left c hT] theorem setToL1_smul_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ) (h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁[μ] E) : setToL1 hT' f = c • setToL1 hT f := by suffices setToL1 hT' = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply] refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT') _ _ _ _ ?_ ext1 f suffices c • setToL1 hT f = setToL1SCLM α E μ hT' f by rw [← this]; simp [coeToLp] rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left' c hT hT' h_smul] theorem setToL1_smul (hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁[μ] E) : setToL1 hT (c • f) = c • setToL1 hT f := by rw [setToL1_eq_setToL1' hT h_smul, setToL1_eq_setToL1' hT h_smul] exact ContinuousLinearMap.map_smul _ _ _ theorem setToL1_simpleFunc_indicatorConst (hT : DominatedFinMeasAdditive μ T C) {s : Set α} (hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) : setToL1 hT (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by rw [setToL1_eq_setToL1SCLM] exact setToL1S_indicatorConst (fun s => hT.eq_zero_of_measure_zero) hT.1 hs hμs x theorem setToL1_indicatorConstLp (hT : DominatedFinMeasAdditive μ T C) {s : Set α} (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) : setToL1 hT (indicatorConstLp 1 hs hμs x) = T s x := by rw [← Lp.simpleFunc.coe_indicatorConst hs hμs x] exact setToL1_simpleFunc_indicatorConst hT hs hμs.lt_top x theorem setToL1_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) : setToL1 hT (indicatorConstLp 1 MeasurableSet.univ (measure_ne_top _ _) x) = T univ x := setToL1_indicatorConstLp hT MeasurableSet.univ (measure_ne_top _ _) x section Order variable {G' G'' : Type*} [NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G''] [CompleteSpace G''] [NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G'] theorem setToL1_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f := by induction f using Lp.induction (hp_ne_top := one_ne_top) with | @indicatorConst c s hs hμs => rw [setToL1_simpleFunc_indicatorConst hT hs hμs, setToL1_simpleFunc_indicatorConst hT' hs hμs] exact hTT' s hs hμs c | @add f g hf hg _ hf_le hg_le => rw [(setToL1 hT).map_add, (setToL1 hT').map_add] exact add_le_add hf_le hg_le | isClosed => exact isClosed_le (setToL1 hT).continuous (setToL1 hT').continuous theorem setToL1_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f := setToL1_mono_left' hT hT' (fun s _ _ x => hTT' s x) f theorem setToL1_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁[μ] G'} (hf : 0 ≤ f) : 0 ≤ setToL1 hT f := by suffices ∀ f : { g : α →₁[μ] G' // 0 ≤ g }, 0 ≤ setToL1 hT f from this (⟨f, hf⟩ : { g : α →₁[μ] G' // 0 ≤ g }) refine fun g => @isClosed_property { g : α →₁ₛ[μ] G' // 0 ≤ g } { g : α →₁[μ] G' // 0 ≤ g } _ _ (fun g => 0 ≤ setToL1 hT g) (denseRange_coeSimpleFuncNonnegToLpNonneg 1 μ G' one_ne_top) ?_ ?_ g · exact isClosed_le continuous_zero ((setToL1 hT).continuous.comp continuous_induced_dom) · intro g have : (coeSimpleFuncNonnegToLpNonneg 1 μ G' g : α →₁[μ] G') = (g : α →₁ₛ[μ] G') := rfl rw [this, setToL1_eq_setToL1SCLM] exact setToL1S_nonneg (fun s => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg g.2 theorem setToL1_mono [IsOrderedAddMonoid G'] {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁[μ] G'} (hfg : f ≤ g) : setToL1 hT f ≤ setToL1 hT g := by rw [← sub_nonneg] at hfg ⊢ rw [← (setToL1 hT).map_sub] exact setToL1_nonneg hT hT_nonneg hfg end Order theorem norm_setToL1_le_norm_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ ‖setToL1SCLM α E μ hT‖ := calc ‖setToL1 hT‖ ≤ (1 : ℝ≥0) * ‖setToL1SCLM α E μ hT‖ := by refine ContinuousLinearMap.opNorm_extend_le (setToL1SCLM α E μ hT) (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top) fun x => le_of_eq ?_ rw [NNReal.coe_one, one_mul] simp [coeToLp] _ = ‖setToL1SCLM α E μ hT‖ := by rw [NNReal.coe_one, one_mul] theorem norm_setToL1_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) (f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ C * ‖f‖ := calc ‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ := ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _ _ ≤ C * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le hT hC) le_rfl (norm_nonneg _) hC theorem norm_setToL1_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ max C 0 * ‖f‖ := calc ‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ := ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _ _ ≤ max C 0 * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le' hT) le_rfl (norm_nonneg _) (le_max_right _ _) theorem norm_setToL1_le (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1 hT‖ ≤ C := ContinuousLinearMap.opNorm_le_bound _ hC (norm_setToL1_le_mul_norm hT hC) theorem norm_setToL1_le' (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ max C 0 := ContinuousLinearMap.opNorm_le_bound _ (le_max_right _ _) (norm_setToL1_le_mul_norm' hT) theorem setToL1_lipschitz (hT : DominatedFinMeasAdditive μ T C) : LipschitzWith (Real.toNNReal C) (setToL1 hT) := (setToL1 hT).lipschitz.weaken (norm_setToL1_le' hT) /-- If `fs i → f` in `L1`, then `setToL1 hT (fs i) → setToL1 hT f`. -/ theorem tendsto_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) {ι} (fs : ι → α →₁[μ] E) {l : Filter ι} (hfs : Tendsto fs l (𝓝 f)) : Tendsto (fun i => setToL1 hT (fs i)) l (𝓝 <| setToL1 hT f) := ((setToL1 hT).continuous.tendsto _).comp hfs end SetToL1 end L1 section Function variable [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} {f g : α → E} variable (μ T) open Classical in /-- Extend `T : Set α → E →L[ℝ] F` to `(α → E) → F` (for integrable functions `α → E`). We set it to 0 if the function is not integrable. -/ def setToFun (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F := if hf : Integrable f μ then L1.setToL1 hT (hf.toL1 f) else 0 variable {μ T} theorem setToFun_eq (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) : setToFun μ T hT f = L1.setToL1 hT (hf.toL1 f) := dif_pos hf theorem L1.setToFun_eq_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) : setToFun μ T hT f = L1.setToL1 hT f := by rw [setToFun_eq hT (L1.integrable_coeFn f), Integrable.toL1_coeFn] theorem setToFun_undef (hT : DominatedFinMeasAdditive μ T C) (hf : ¬Integrable f μ) : setToFun μ T hT f = 0 := dif_neg hf theorem setToFun_non_aestronglyMeasurable (hT : DominatedFinMeasAdditive μ T C) (hf : ¬AEStronglyMeasurable f μ) : setToFun μ T hT f = 0 := setToFun_undef hT (not_and_of_not_left _ hf) @[deprecated (since := "2025-04-09")] alias setToFun_non_aEStronglyMeasurable := setToFun_non_aestronglyMeasurable theorem setToFun_congr_left (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left T T' hT hT' h] · simp_rw [setToFun_undef _ hf] theorem setToFun_congr_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left' T T' hT hT' h] · simp_rw [setToFun_undef _ hf] theorem setToFun_add_left (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (f : α → E) : setToFun μ (T + T') (hT.add hT') f = setToFun μ T hT f + setToFun μ T' hT' f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_add_left hT hT'] · simp_rw [setToFun_undef _ hf, add_zero] theorem setToFun_add_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'') (h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α → E) : setToFun μ T'' hT'' f = setToFun μ T hT f + setToFun μ T' hT' f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_add_left' hT hT' hT'' h_add] · simp_rw [setToFun_undef _ hf, add_zero] theorem setToFun_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α → E) : setToFun μ (fun s => c • T s) (hT.smul c) f = c • setToFun μ T hT f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left hT c] · simp_rw [setToFun_undef _ hf, smul_zero] theorem setToFun_smul_left' (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ) (h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α → E) : setToFun μ T' hT' f = c • setToFun μ T hT f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left' hT hT' c h_smul] · simp_rw [setToFun_undef _ hf, smul_zero] @[simp] theorem setToFun_zero (hT : DominatedFinMeasAdditive μ T C) : setToFun μ T hT (0 : α → E) = 0 := by rw [Pi.zero_def, setToFun_eq hT (integrable_zero _ _ _)] simp only [← Pi.zero_def] rw [Integrable.toL1_zero, ContinuousLinearMap.map_zero] @[simp] theorem setToFun_zero_left {hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C} : setToFun μ 0 hT f = 0 := by by_cases hf : Integrable f μ · rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left hT _ · exact setToFun_undef hT hf theorem setToFun_zero_left' (hT : DominatedFinMeasAdditive μ T C) (h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) : setToFun μ T hT f = 0 := by by_cases hf : Integrable f μ · rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left' hT h_zero _ · exact setToFun_undef hT hf theorem setToFun_add (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) (hg : Integrable g μ) : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g := by rw [setToFun_eq hT (hf.add hg), setToFun_eq hT hf, setToFun_eq hT hg, Integrable.toL1_add, (L1.setToL1 hT).map_add] theorem setToFun_finset_sum' (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) : setToFun μ T hT (∑ i ∈ s, f i) = ∑ i ∈ s, setToFun μ T hT (f i) := by classical revert hf refine Finset.induction_on s ?_ ?_ · intro _ simp only [setToFun_zero, Finset.sum_empty] · intro i s his ih hf simp only [his, Finset.sum_insert, not_false_iff] rw [setToFun_add hT (hf i (Finset.mem_insert_self i s)) _] · rw [ih fun i hi => hf i (Finset.mem_insert_of_mem hi)] · convert integrable_finset_sum s fun i hi => hf i (Finset.mem_insert_of_mem hi) with x simp theorem setToFun_finset_sum (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) : (setToFun μ T hT fun a => ∑ i ∈ s, f i a) = ∑ i ∈ s, setToFun μ T hT (f i) := by convert setToFun_finset_sum' hT s hf with a; simp theorem setToFun_neg (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : setToFun μ T hT (-f) = -setToFun μ T hT f := by by_cases hf : Integrable f μ · rw [setToFun_eq hT hf, setToFun_eq hT hf.neg, Integrable.toL1_neg, (L1.setToL1 hT).map_neg] · rw [setToFun_undef hT hf, setToFun_undef hT, neg_zero] rwa [← integrable_neg_iff] at hf theorem setToFun_sub (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) (hg : Integrable g μ) : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g := by rw [sub_eq_add_neg, sub_eq_add_neg, setToFun_add hT hf hg.neg, setToFun_neg hT g] theorem setToFun_smul [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] (hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α → E) : setToFun μ T hT (c • f) = c • setToFun μ T hT f := by by_cases hf : Integrable f μ · rw [setToFun_eq hT hf, setToFun_eq hT, Integrable.toL1_smul', L1.setToL1_smul hT h_smul c _] · by_cases hr : c = 0 · rw [hr]; simp · have hf' : ¬Integrable (c • f) μ := by rwa [integrable_smul_iff hr f] rw [setToFun_undef hT hf, setToFun_undef hT hf', smul_zero] theorem setToFun_congr_ae (hT : DominatedFinMeasAdditive μ T C) (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g := by by_cases hfi : Integrable f μ · have hgi : Integrable g μ := hfi.congr h rw [setToFun_eq hT hfi, setToFun_eq hT hgi, (Integrable.toL1_eq_toL1_iff f g hfi hgi).2 h] · have hgi : ¬Integrable g μ := by rw [integrable_congr h] at hfi; exact hfi rw [setToFun_undef hT hfi, setToFun_undef hT hgi] theorem setToFun_measure_zero (hT : DominatedFinMeasAdditive μ T C) (h : μ = 0) : setToFun μ T hT f = 0 := by have : f =ᵐ[μ] 0 := by simp [h, EventuallyEq] rw [setToFun_congr_ae hT this, setToFun_zero] theorem setToFun_measure_zero' (hT : DominatedFinMeasAdditive μ T C) (h : ∀ s, MeasurableSet s → μ s < ∞ → μ s = 0) : setToFun μ T hT f = 0 := setToFun_zero_left' hT fun s hs hμs => hT.eq_zero_of_measure_zero hs (h s hs hμs) theorem setToFun_toL1 (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) : setToFun μ T hT (hf.toL1 f) = setToFun μ T hT f := setToFun_congr_ae hT hf.coeFn_toL1 theorem setToFun_indicator_const (hT : DominatedFinMeasAdditive μ T C) {s : Set α} (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) : setToFun μ T hT (s.indicator fun _ => x) = T s x := by rw [setToFun_congr_ae hT (@indicatorConstLp_coeFn _ _ _ 1 _ _ _ hs hμs x).symm] rw [L1.setToFun_eq_setToL1 hT] exact L1.setToL1_indicatorConstLp hT hs hμs x theorem setToFun_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) : (setToFun μ T hT fun _ => x) = T univ x := by have : (fun _ : α => x) = Set.indicator univ fun _ => x := (indicator_univ _).symm rw [this] exact setToFun_indicator_const hT MeasurableSet.univ (measure_ne_top _ _) x section Order variable {G' G'' : Type*} [NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G''] [CompleteSpace G''] [NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G'] theorem setToFun_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α → E) : setToFun μ T hT f ≤ setToFun μ T' hT' f := by by_cases hf : Integrable f μ · simp_rw [setToFun_eq _ hf]; exact L1.setToL1_mono_left' hT hT' hTT' _ · simp_rw [setToFun_undef _ hf, le_rfl] theorem setToFun_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToFun μ T hT f ≤ setToFun μ T' hT' f := setToFun_mono_left' hT hT' (fun s _ _ x => hTT' s x) f theorem setToFun_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α → G'} (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f := by by_cases hfi : Integrable f μ · simp_rw [setToFun_eq _ hfi] refine L1.setToL1_nonneg hT hT_nonneg ?_ rw [← Lp.coeFn_le] have h0 := Lp.coeFn_zero G' 1 μ have h := Integrable.coeFn_toL1 hfi filter_upwards [h0, h, hf] with _ h0a ha hfa rw [h0a, ha] exact hfa · simp_rw [setToFun_undef _ hfi, le_rfl] theorem setToFun_mono [IsOrderedAddMonoid G'] {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) (hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α → G'} (hf : Integrable f μ) (hg : Integrable g μ) (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g := by rw [← sub_nonneg, ← setToFun_sub hT hg hf] refine setToFun_nonneg hT hT_nonneg (hfg.mono fun a ha => ?_) rw [Pi.sub_apply, Pi.zero_apply, sub_nonneg] exact ha end Order @[continuity] theorem continuous_setToFun (hT : DominatedFinMeasAdditive μ T C) : Continuous fun f : α →₁[μ] E => setToFun μ T hT f := by simp_rw [L1.setToFun_eq_setToL1 hT]; exact ContinuousLinearMap.continuous _ /-- If `F i → f` in `L1`, then `setToFun μ T hT (F i) → setToFun μ T hT f`. -/ theorem tendsto_setToFun_of_L1 (hT : DominatedFinMeasAdditive μ T C) {ι} (f : α → E) (hfi : Integrable f μ) {fs : ι → α → E} {l : Filter ι} (hfsi : ∀ᶠ i in l, Integrable (fs i) μ) (hfs : Tendsto (fun i => ∫⁻ x, ‖fs i x - f x‖ₑ ∂μ) l (𝓝 0)) : Tendsto (fun i => setToFun μ T hT (fs i)) l (𝓝 <| setToFun μ T hT f) := by classical let f_lp := hfi.toL1 f let F_lp i := if hFi : Integrable (fs i) μ then hFi.toL1 (fs i) else 0 have tendsto_L1 : Tendsto F_lp l (𝓝 f_lp) := by rw [Lp.tendsto_Lp_iff_tendsto_eLpNorm'] simp_rw [eLpNorm_one_eq_lintegral_enorm, Pi.sub_apply] refine (tendsto_congr' ?_).mp hfs filter_upwards [hfsi] with i hi refine lintegral_congr_ae ?_ filter_upwards [hi.coeFn_toL1, hfi.coeFn_toL1] with x hxi hxf simp_rw [F_lp, dif_pos hi, hxi, f_lp, hxf] suffices Tendsto (fun i => setToFun μ T hT (F_lp i)) l (𝓝 (setToFun μ T hT f)) by refine (tendsto_congr' ?_).mp this filter_upwards [hfsi] with i hi suffices h_ae_eq : F_lp i =ᵐ[μ] fs i from setToFun_congr_ae hT h_ae_eq simp_rw [F_lp, dif_pos hi] exact hi.coeFn_toL1 rw [setToFun_congr_ae hT hfi.coeFn_toL1.symm] exact ((continuous_setToFun hT).tendsto f_lp).comp tendsto_L1 theorem tendsto_setToFun_approxOn_of_measurable (hT : DominatedFinMeasAdditive μ T C) [MeasurableSpace E] [BorelSpace E] {f : α → E} {s : Set E} [SeparableSpace s] (hfi : Integrable f μ) (hfm : Measurable f) (hs : ∀ᵐ x ∂μ, f x ∈ closure s) {y₀ : E} (h₀ : y₀ ∈ s) (h₀i : Integrable (fun _ => y₀) μ) : Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f hfm s y₀ h₀ n)) atTop (𝓝 <| setToFun μ T hT f) := tendsto_setToFun_of_L1 hT _ hfi (Eventually.of_forall (SimpleFunc.integrable_approxOn hfm hfi h₀ h₀i)) (SimpleFunc.tendsto_approxOn_L1_enorm hfm _ hs (hfi.sub h₀i).2) theorem tendsto_setToFun_approxOn_of_measurable_of_range_subset (hT : DominatedFinMeasAdditive μ T C) [MeasurableSpace E] [BorelSpace E] {f : α → E} (fmeas : Measurable f) (hf : Integrable f μ) (s : Set E) [SeparableSpace s] (hs : range f ∪ {0} ⊆ s) : Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f fmeas s 0 (hs <| by simp) n)) atTop (𝓝 <| setToFun μ T hT f) := by refine tendsto_setToFun_approxOn_of_measurable hT hf fmeas ?_ _ (integrable_zero _ _ _) exact Eventually.of_forall fun x => subset_closure (hs (Set.mem_union_left _ (mem_range_self _))) /-- Auxiliary lemma for `setToFun_congr_measure`: the function sending `f : α →₁[μ] G` to `f : α →₁[μ'] G` is continuous when `μ' ≤ c' • μ` for `c' ≠ ∞`. -/ theorem continuous_L1_toL1 {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞) (hμ'_le : μ' ≤ c' • μ) : Continuous fun f : α →₁[μ] G => (Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f := by by_cases hc'0 : c' = 0 · have hμ'0 : μ' = 0 := by rw [← Measure.nonpos_iff_eq_zero']; refine hμ'_le.trans ?_; simp [hc'0] have h_im_zero : (fun f : α →₁[μ] G => (Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f) = 0 := by ext1 f; ext1; simp_rw [hμ'0]; simp only [ae_zero, EventuallyEq, eventually_bot] rw [h_im_zero] exact continuous_zero rw [Metric.continuous_iff] intro f ε hε_pos use ε / 2 / c'.toReal refine ⟨div_pos (half_pos hε_pos) (toReal_pos hc'0 hc'), ?_⟩ intro g hfg rw [Lp.dist_def] at hfg ⊢ let h_int := fun f' : α →₁[μ] G => (L1.integrable_coeFn f').of_measure_le_smul hc' hμ'_le have : eLpNorm (⇑(Integrable.toL1 g (h_int g)) - ⇑(Integrable.toL1 f (h_int f))) 1 μ' = eLpNorm (⇑g - ⇑f) 1 μ' := eLpNorm_congr_ae ((Integrable.coeFn_toL1 _).sub (Integrable.coeFn_toL1 _)) rw [this] have h_eLpNorm_ne_top : eLpNorm (⇑g - ⇑f) 1 μ ≠ ∞ := by rw [← eLpNorm_congr_ae (Lp.coeFn_sub _ _)]; exact Lp.eLpNorm_ne_top _ calc (eLpNorm (⇑g - ⇑f) 1 μ').toReal ≤ (c' * eLpNorm (⇑g - ⇑f) 1 μ).toReal := by refine toReal_mono (ENNReal.mul_ne_top hc' h_eLpNorm_ne_top) ?_ refine (eLpNorm_mono_measure (⇑g - ⇑f) hμ'_le).trans_eq ?_ rw [eLpNorm_smul_measure_of_ne_zero hc'0, smul_eq_mul] simp _ = c'.toReal * (eLpNorm (⇑g - ⇑f) 1 μ).toReal := toReal_mul _ ≤ c'.toReal * (ε / 2 / c'.toReal) := by gcongr _ = ε / 2 := by refine mul_div_cancel₀ (ε / 2) ?_; rw [Ne, toReal_eq_zero_iff]; simp [hc', hc'0] _ < ε := half_lt_self hε_pos theorem setToFun_congr_measure_of_integrable {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞) (hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) (hfμ : Integrable f μ) : setToFun μ T hT f = setToFun μ' T hT' f := by -- integrability for `μ` implies integrability for `μ'`. have h_int : ∀ g : α → E, Integrable g μ → Integrable g μ' := fun g hg => Integrable.of_measure_le_smul hc' hμ'_le hg -- We use `Integrable.induction` apply hfμ.induction (P := fun f => setToFun μ T hT f = setToFun μ' T hT' f) · intro c s hs hμs have hμ's : μ' s ≠ ∞ := by refine ((hμ'_le s).trans_lt ?_).ne rw [Measure.smul_apply, smul_eq_mul] exact ENNReal.mul_lt_top hc'.lt_top hμs rw [setToFun_indicator_const hT hs hμs.ne, setToFun_indicator_const hT' hs hμ's] · intro f₂ g₂ _ hf₂ hg₂ h_eq_f h_eq_g rw [setToFun_add hT hf₂ hg₂, setToFun_add hT' (h_int f₂ hf₂) (h_int g₂ hg₂), h_eq_f, h_eq_g] · refine isClosed_eq (continuous_setToFun hT) ?_ have : (fun f : α →₁[μ] E => setToFun μ' T hT' f) = fun f : α →₁[μ] E => setToFun μ' T hT' ((h_int f (L1.integrable_coeFn f)).toL1 f) := by ext1 f; exact setToFun_congr_ae hT' (Integrable.coeFn_toL1 _).symm rw [this] exact (continuous_setToFun hT').comp (continuous_L1_toL1 c' hc' hμ'_le) · intro f₂ g₂ hfg _ hf_eq have hfg' : f₂ =ᵐ[μ'] g₂ := (Measure.absolutelyContinuous_of_le_smul hμ'_le).ae_eq hfg rw [← setToFun_congr_ae hT hfg, hf_eq, setToFun_congr_ae hT' hfg'] theorem setToFun_congr_measure {μ' : Measure α} (c c' : ℝ≥0∞) (hc : c ≠ ∞) (hc' : c' ≠ ∞) (hμ_le : μ ≤ c • μ') (hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) : setToFun μ T hT f = setToFun μ' T hT' f := by by_cases hf : Integrable f μ · exact setToFun_congr_measure_of_integrable c' hc' hμ'_le hT hT' f hf · -- if `f` is not integrable, both `setToFun` are 0. have h_int : ∀ g : α → E, ¬Integrable g μ → ¬Integrable g μ' := fun g => mt fun h => h.of_measure_le_smul hc hμ_le simp_rw [setToFun_undef _ hf, setToFun_undef _ (h_int f hf)] theorem setToFun_congr_measure_of_add_right {μ' : Measure α} (hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ T C) (f : α → E) (hf : Integrable f (μ + μ')) : setToFun (μ + μ') T hT_add f = setToFun μ T hT f := by refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf rw [one_smul] nth_rw 1 [← add_zero μ] exact add_le_add le_rfl bot_le theorem setToFun_congr_measure_of_add_left {μ' : Measure α} (hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ' T C) (f : α → E) (hf : Integrable f (μ + μ')) : setToFun (μ + μ') T hT_add f = setToFun μ' T hT f := by refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf rw [one_smul] nth_rw 1 [← zero_add μ'] exact add_le_add_right bot_le μ' theorem setToFun_top_smul_measure (hT : DominatedFinMeasAdditive (∞ • μ) T C) (f : α → E) : setToFun (∞ • μ) T hT f = 0 := by refine setToFun_measure_zero' hT fun s _ hμs => ?_ rw [lt_top_iff_ne_top] at hμs simp only [true_and, Measure.smul_apply, ENNReal.mul_eq_top, eq_self_iff_true, top_ne_zero, Ne, not_false_iff, not_or, Classical.not_not, smul_eq_mul] at hμs simp only [hμs.right, Measure.smul_apply, mul_zero, smul_eq_mul] theorem setToFun_congr_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞) (hT : DominatedFinMeasAdditive μ T C) (hT_smul : DominatedFinMeasAdditive (c • μ) T C') (f : α → E) : setToFun μ T hT f = setToFun (c • μ) T hT_smul f := by by_cases hc0 : c = 0 · simp [hc0] at hT_smul have h : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0 := fun s hs _ => hT_smul.eq_zero hs rw [setToFun_zero_left' _ h, setToFun_measure_zero] simp [hc0] refine setToFun_congr_measure c⁻¹ c ?_ hc_ne_top (le_of_eq ?_) le_rfl hT hT_smul f · simp [hc0] · rw [smul_smul, ENNReal.inv_mul_cancel hc0 hc_ne_top, one_smul] theorem norm_setToFun_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) (hC : 0 ≤ C) : ‖setToFun μ T hT f‖ ≤ C * ‖f‖ := by rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm hT hC f theorem norm_setToFun_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) : ‖setToFun μ T hT f‖ ≤ max C 0 * ‖f‖ := by rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm' hT f theorem norm_setToFun_le (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) (hC : 0 ≤ C) : ‖setToFun μ T hT f‖ ≤ C * ‖hf.toL1 f‖ := by rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm hT hC _ theorem norm_setToFun_le' (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) : ‖setToFun μ T hT f‖ ≤ max C 0 * ‖hf.toL1 f‖ := by rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm' hT _ /-- Lebesgue dominated convergence theorem provides sufficient conditions under which almost everywhere convergence of a sequence of functions implies the convergence of their image by `setToFun`. We could weaken the condition `bound_integrable` to require `HasFiniteIntegral bound μ` instead (i.e. not requiring that `bound` is measurable), but in all applications proving integrability is easier. -/ theorem tendsto_setToFun_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C) {fs : ℕ → α → E} {f : α → E} (bound : α → ℝ) (fs_measurable : ∀ n, AEStronglyMeasurable (fs n) μ) (bound_integrable : Integrable bound μ) (h_bound : ∀ n, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) (h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) atTop (𝓝 (f a))) : Tendsto (fun n => setToFun μ T hT (fs n)) atTop (𝓝 <| setToFun μ T hT f) := by -- `f` is a.e.-measurable, since it is the a.e.-pointwise limit of a.e.-measurable functions. have f_measurable : AEStronglyMeasurable f μ := aestronglyMeasurable_of_tendsto_ae _ fs_measurable h_lim -- all functions we consider are integrable have fs_int : ∀ n, Integrable (fs n) μ := fun n => bound_integrable.mono' (fs_measurable n) (h_bound _) have f_int : Integrable f μ := ⟨f_measurable, hasFiniteIntegral_of_dominated_convergence bound_integrable.hasFiniteIntegral h_bound h_lim⟩ -- it suffices to prove the result for the corresponding L1 functions suffices Tendsto (fun n => L1.setToL1 hT ((fs_int n).toL1 (fs n))) atTop (𝓝 (L1.setToL1 hT (f_int.toL1 f))) by convert this with n · exact setToFun_eq hT (fs_int n) · exact setToFun_eq hT f_int -- the convergence of setToL1 follows from the convergence of the L1 functions refine L1.tendsto_setToL1 hT _ _ ?_ -- up to some rewriting, what we need to prove is `h_lim` rw [tendsto_iff_norm_sub_tendsto_zero] have lintegral_norm_tendsto_zero : Tendsto (fun n => ENNReal.toReal <| ∫⁻ a, ENNReal.ofReal ‖fs n a - f a‖ ∂μ) atTop (𝓝 0) := (tendsto_toReal zero_ne_top).comp (tendsto_lintegral_norm_of_dominated_convergence fs_measurable bound_integrable.hasFiniteIntegral h_bound h_lim) convert lintegral_norm_tendsto_zero with n rw [L1.norm_def] congr 1 refine lintegral_congr_ae ?_ rw [← Integrable.toL1_sub] refine ((fs_int n).sub f_int).coeFn_toL1.mono fun x hx => ?_ dsimp only rw [hx, ofReal_norm_eq_enorm, Pi.sub_apply] /-- Lebesgue dominated convergence theorem for filters with a countable basis -/ theorem tendsto_setToFun_filter_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C) {ι} {l : Filter ι} [l.IsCountablyGenerated] {fs : ι → α → E} {f : α → E} (bound : α → ℝ) (hfs_meas : ∀ᶠ n in l, AEStronglyMeasurable (fs n) μ) (h_bound : ∀ᶠ n in l, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) (bound_integrable : Integrable bound μ) (h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) l (𝓝 (f a))) : Tendsto (fun n => setToFun μ T hT (fs n)) l (𝓝 <| setToFun μ T hT f) := by rw [tendsto_iff_seq_tendsto] intro x xl have hxl : ∀ s ∈ l, ∃ a, ∀ b ≥ a, x b ∈ s := by rwa [tendsto_atTop'] at xl have h : { x : ι | (fun n => AEStronglyMeasurable (fs n) μ) x } ∩ { x : ι | (fun n => ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) x } ∈ l := inter_mem hfs_meas h_bound obtain ⟨k, h⟩ := hxl _ h rw [← tendsto_add_atTop_iff_nat k] refine tendsto_setToFun_of_dominated_convergence hT bound ?_ bound_integrable ?_ ?_ · exact fun n => (h _ (self_le_add_left _ _)).1 · exact fun n => (h _ (self_le_add_left _ _)).2 · filter_upwards [h_lim] refine fun a h_lin => @Tendsto.comp _ _ _ (fun n => x (n + k)) (fun n => fs n a) _ _ _ h_lin ?_ rwa [tendsto_add_atTop_iff_nat] variable {X : Type*} [TopologicalSpace X] [FirstCountableTopology X] theorem continuousWithinAt_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E} {x₀ : X} {bound : α → ℝ} {s : Set X} (hfs_meas : ∀ᶠ x in 𝓝[s] x₀, AEStronglyMeasurable (fs x) μ) (h_bound : ∀ᶠ x in 𝓝[s] x₀, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ) (h_cont : ∀ᵐ a ∂μ, ContinuousWithinAt (fun x => fs x a) s x₀) : ContinuousWithinAt (fun x => setToFun μ T hT (fs x)) s x₀ := tendsto_setToFun_filter_of_dominated_convergence hT bound ‹_› ‹_› ‹_› ‹_› theorem continuousAt_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E} {x₀ : X} {bound : α → ℝ} (hfs_meas : ∀ᶠ x in 𝓝 x₀, AEStronglyMeasurable (fs x) μ) (h_bound : ∀ᶠ x in 𝓝 x₀, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ) (h_cont : ∀ᵐ a ∂μ, ContinuousAt (fun x => fs x a) x₀) : ContinuousAt (fun x => setToFun μ T hT (fs x)) x₀ := tendsto_setToFun_filter_of_dominated_convergence hT bound ‹_› ‹_› ‹_› ‹_› theorem continuousOn_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E} {bound : α → ℝ} {s : Set X} (hfs_meas : ∀ x ∈ s, AEStronglyMeasurable (fs x) μ) (h_bound : ∀ x ∈ s, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ) (h_cont : ∀ᵐ a ∂μ, ContinuousOn (fun x => fs x a) s) : ContinuousOn (fun x => setToFun μ T hT (fs x)) s := by intro x hx refine continuousWithinAt_setToFun_of_dominated hT ?_ ?_ bound_integrable ?_ · filter_upwards [self_mem_nhdsWithin] with x hx using hfs_meas x hx · filter_upwards [self_mem_nhdsWithin] with x hx using h_bound x hx · filter_upwards [h_cont] with a ha using ha x hx theorem continuous_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E} {bound : α → ℝ} (hfs_meas : ∀ x, AEStronglyMeasurable (fs x) μ) (h_bound : ∀ x, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ) (h_cont : ∀ᵐ a ∂μ, Continuous fun x => fs x a) : Continuous fun x => setToFun μ T hT (fs x) := continuous_iff_continuousAt.mpr fun _ => continuousAt_setToFun_of_dominated hT (Eventually.of_forall hfs_meas) (Eventually.of_forall h_bound) ‹_› <| h_cont.mono fun _ => Continuous.continuousAt end Function end MeasureTheory
Mathlib/MeasureTheory/Integral/SetToL1.lean
1,408
1,414
/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Calculus.FDeriv.Add import Mathlib.Analysis.Calculus.FDeriv.Equiv import Mathlib.Analysis.Calculus.FDeriv.Prod import Mathlib.Analysis.Calculus.Monotone import Mathlib.Topology.EMetricSpace.BoundedVariation /-! # Almost everywhere differentiability of functions with locally bounded variation In this file we show that a bounded variation function is differentiable almost everywhere. This implies that Lipschitz functions from the real line into finite-dimensional vector space are also differentiable almost everywhere. ## Main definitions and results * `LocallyBoundedVariationOn.ae_differentiableWithinAt` shows that a bounded variation function into a finite dimensional real vector space is differentiable almost everywhere. * `LipschitzOnWith.ae_differentiableWithinAt` is the same result for Lipschitz functions. We also give several variations around these results. -/ open scoped NNReal ENNReal Topology open Set MeasureTheory Filter variable {α : Type*} [LinearOrder α] {E : Type*} [PseudoEMetricSpace E] /-! ## -/ variable {V : Type*} [NormedAddCommGroup V] [NormedSpace ℝ V] [FiniteDimensional ℝ V] namespace LocallyBoundedVariationOn /-- A bounded variation function into `ℝ` is differentiable almost everywhere. Superseded by `ae_differentiableWithinAt_of_mem`. -/ theorem ae_differentiableWithinAt_of_mem_real {f : ℝ → ℝ} {s : Set ℝ} (h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by obtain ⟨p, q, hp, hq, rfl⟩ : ∃ p q, MonotoneOn p s ∧ MonotoneOn q s ∧ f = p - q := h.exists_monotoneOn_sub_monotoneOn filter_upwards [hp.ae_differentiableWithinAt_of_mem, hq.ae_differentiableWithinAt_of_mem] with x hxp hxq xs exact (hxp xs).sub (hxq xs) /-- A bounded variation function into a finite dimensional product vector space is differentiable almost everywhere. Superseded by `ae_differentiableWithinAt_of_mem`. -/ theorem ae_differentiableWithinAt_of_mem_pi {ι : Type*} [Fintype ι] {f : ℝ → ι → ℝ} {s : Set ℝ} (h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by have A : ∀ i : ι, LipschitzWith 1 fun x : ι → ℝ => x i := fun i => LipschitzWith.eval i have : ∀ i : ι, ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (fun x : ℝ => f x i) s x := fun i ↦ by apply ae_differentiableWithinAt_of_mem_real exact LipschitzWith.comp_locallyBoundedVariationOn (A i) h filter_upwards [ae_all_iff.2 this] with x hx xs exact differentiableWithinAt_pi.2 fun i => hx i xs /-- A real function into a finite dimensional real vector space with bounded variation on a set is differentiable almost everywhere in this set. -/ theorem ae_differentiableWithinAt_of_mem {f : ℝ → V} {s : Set ℝ} (h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by let A := (Basis.ofVectorSpace ℝ V).equivFun.toContinuousLinearEquiv suffices H : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (A ∘ f) s x by filter_upwards [H] with x hx xs have : f = (A.symm ∘ A) ∘ f := by simp only [ContinuousLinearEquiv.symm_comp_self, Function.id_comp] rw [this] exact A.symm.differentiableAt.comp_differentiableWithinAt x (hx xs) apply ae_differentiableWithinAt_of_mem_pi exact A.lipschitz.comp_locallyBoundedVariationOn h /-- A real function into a finite dimensional real vector space with bounded variation on a set is differentiable almost everywhere in this set. -/ theorem ae_differentiableWithinAt {f : ℝ → V} {s : Set ℝ} (h : LocallyBoundedVariationOn f s) (hs : MeasurableSet s) : ∀ᵐ x ∂volume.restrict s, DifferentiableWithinAt ℝ f s x := by rw [ae_restrict_iff' hs] exact h.ae_differentiableWithinAt_of_mem /-- A real function into a finite dimensional real vector space with bounded variation
is differentiable almost everywhere. -/ theorem ae_differentiableAt {f : ℝ → V} (h : LocallyBoundedVariationOn f univ) : ∀ᵐ x, DifferentiableAt ℝ f x := by filter_upwards [h.ae_differentiableWithinAt_of_mem] with x hx
Mathlib/Analysis/BoundedVariation.lean
83
86
/- Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel -/ import Mathlib.Data.ENNReal.Real import Mathlib.Tactic.Bound.Attribute import Mathlib.Topology.Bornology.Basic import Mathlib.Topology.EMetricSpace.Defs import Mathlib.Topology.UniformSpace.Basic /-! ## Pseudo-metric spaces This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the condition `dist x y = 0 → x = y`. Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform spaces and topological spaces. For example: open and closed sets, compactness, completeness, continuity and uniform continuity. ## Main definitions * `Dist α`: Endows a space `α` with a function `dist a b`. * `PseudoMetricSpace α`: A space endowed with a distance function, which can be zero even if the two elements are non-equal. * `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`. * `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded. * `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`. Additional useful definitions: * `nndist a b`: `dist` as a function to the non-negative reals. * `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`. * `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`. TODO (anyone): Add "Main results" section. ## Tags pseudo_metric, dist -/ assert_not_exists compactSpace_uniformity open Set Filter TopologicalSpace Bornology open scoped ENNReal NNReal Uniformity Topology universe u v w variable {α : Type u} {β : Type v} {X ι : Type*} theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε := ⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩ /-- Construct a uniform structure from a distance function and metric space axioms -/ def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α := .ofFun dist dist_self dist_comm dist_triangle ofDist_aux /-- Construct a bornology from a distance function and metric space axioms. -/ abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x) (dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α := Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C } ⟨0, fun _ hx _ => hx.elim⟩ (fun _ ⟨c, hc⟩ _ h => ⟨c, fun _ hx _ hy => hc (h hx) (h hy)⟩) (fun s hs t ht => by rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩ · rwa [empty_union] rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩ · rwa [union_empty] rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C · refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩ simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb) rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩ refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim (fun hz => (hs hx hz).trans (le_max_left _ _)) (fun hz => (dist_triangle x y z).trans <| (add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩) fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩ /-- The distance function (given an ambient metric space on `α`), which returns a nonnegative real number `dist x y` given `x y : α`. -/ @[ext] class Dist (α : Type*) where /-- Distance between two points -/ dist : α → α → ℝ export Dist (dist) -- the uniform structure and the emetric space structure are embedded in the metric space structure -- to avoid instance diamond issues. See Note [forgetful inheritance]. /-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/ private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y := have : 0 ≤ 2 * dist x y := calc 0 = dist x x := (dist_self _).symm _ ≤ dist x y + dist y x := dist_triangle _ _ _ _ = 2 * dist x y := by rw [two_mul, dist_comm] nonneg_of_mul_nonneg_right this two_pos /-- A pseudometric space is a type endowed with a `ℝ`-valued distance `dist` satisfying reflexivity `dist x x = 0`, commutativity `dist x y = dist y x`, and the triangle inequality `dist x z ≤ dist x y + dist y z`. Note that we do not require `dist x y = 0 → x = y`. See metric spaces (`MetricSpace`) for the similar class with that stronger assumption. Any pseudometric space is a topological space and a uniform space (see `TopologicalSpace`, `UniformSpace`), where the topology and uniformity come from the metric. Note that a T1 pseudometric space is just a metric space. We make the uniformity/topology part of the data instead of deriving it from the metric. This eg ensures that we do not get a diamond when doing `[PseudoMetricSpace α] [PseudoMetricSpace β] : TopologicalSpace (α × β)`: The product metric and product topology agree, but not definitionally so. See Note [forgetful inheritance]. -/ class PseudoMetricSpace (α : Type u) : Type u extends Dist α where dist_self : ∀ x : α, dist x x = 0 dist_comm : ∀ x y : α, dist x y = dist y x dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z /-- Extended distance between two points -/ edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩ edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y) := by intros x y; exact ENNReal.coe_nnreal_eq _ toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets : (Bornology.cobounded α).sets = { s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl /-- Two pseudo metric space structures with the same distance function coincide. -/ @[ext] theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α} (h : m.toDist = m'.toDist) : m = m' := by let d := m.toDist obtain ⟨_, _, _, _, hed, _, hU, _, hB⟩ := m let d' := m'.toDist obtain ⟨_, _, _, _, hed', _, hU', _, hB'⟩ := m' obtain rfl : d = d' := h congr · ext x y : 2 rw [hed, hed'] · exact UniformSpace.ext (hU.trans hU'.symm) · ext : 2 rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB'] variable [PseudoMetricSpace α] attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology -- see Note [lower instance priority] instance (priority := 200) PseudoMetricSpace.toEDist : EDist α := ⟨PseudoMetricSpace.edist⟩ /-- Construct a pseudo-metric space structure whose underlying topological space structure (definitionally) agrees which a pre-existing topology which is compatible with a given distance function. -/ def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) (H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) : PseudoMetricSpace α := { dist := dist dist_self := dist_self dist_comm := dist_comm dist_triangle := dist_triangle toUniformSpace := (UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <| TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦ ((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm uniformity_dist := rfl toBornology := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets := rfl } @[simp] theorem dist_self (x : α) : dist x x = 0 := PseudoMetricSpace.dist_self x theorem dist_comm (x y : α) : dist x y = dist y x := PseudoMetricSpace.dist_comm x y theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) := PseudoMetricSpace.edist_dist x y @[bound] theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z := PseudoMetricSpace.dist_triangle x y z theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by rw [dist_comm z]; apply dist_triangle theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by rw [dist_comm y]; apply dist_triangle theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w := calc dist x w ≤ dist x z + dist z w := dist_triangle x z w _ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _ theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) : dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by rw [add_left_comm, dist_comm x₁, ← add_assoc] apply dist_triangle4 theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) : dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by rw [add_right_comm, dist_comm y₁] apply dist_triangle4 theorem dist_triangle8 (a b c d e f g h : α) : dist a h ≤ dist a b + dist b c + dist c d + dist d e + dist e f + dist f g + dist g h := by apply le_trans (dist_triangle4 a f g h) apply add_le_add_right (add_le_add_right _ (dist f g)) (dist g h) apply le_trans (dist_triangle4 a d e f) apply add_le_add_right (add_le_add_right _ (dist d e)) (dist e f) exact dist_triangle4 a b c d theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _ theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y := abs_sub_le_iff.2 ⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩ @[bound] theorem dist_nonneg {x y : α} : 0 ≤ dist x y := dist_nonneg' dist dist_self dist_comm dist_triangle namespace Mathlib.Meta.Positivity open Lean Meta Qq Function /-- Extension for the `positivity` tactic: distances are nonnegative. -/ @[positivity Dist.dist _ _] def evalDist : PositivityExt where eval {u α} _zα _pα e := do match u, α, e with | 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) => let _inst ← synthInstanceQ q(PseudoMetricSpace $β) assertInstancesCommute pure (.nonnegative q(dist_nonneg)) | _, _, _ => throwError "not dist" end Mathlib.Meta.Positivity example {x y : α} : 0 ≤ dist x y := by positivity @[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg /-- A version of `Dist` that takes value in `ℝ≥0`. -/ class NNDist (α : Type*) where /-- Nonnegative distance between two points -/ nndist : α → α → ℝ≥0 export NNDist (nndist) -- see Note [lower instance priority] /-- Distance as a nonnegative real number. -/ instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α := ⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩ /-- Express `dist` in terms of `nndist` -/ theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl @[simp, norm_cast] theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl /-- Express `edist` in terms of `nndist` -/ theorem edist_nndist (x y : α) : edist x y = nndist x y := by rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal] /-- Express `nndist` in terms of `edist` -/ theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by simp [edist_nndist] @[simp, norm_cast] theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y := (edist_nndist x y).symm @[simp, norm_cast] theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by rw [edist_nndist, ENNReal.coe_lt_coe] @[simp, norm_cast] theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by rw [edist_nndist, ENNReal.coe_le_coe] /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ := (edist_dist x y).symm ▸ ENNReal.ofReal_lt_top /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ := (edist_lt_top x y).ne /-- `nndist x x` vanishes -/ @[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a) @[simp, norm_cast] theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c := Iff.rfl @[simp, norm_cast] theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c := Iff.rfl @[simp] theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg] @[simp] theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) : edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr] /-- Express `nndist` in terms of `dist` -/ theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by rw [dist_nndist, Real.toNNReal_coe] theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y /-- Triangle inequality for the nonnegative distance -/ theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z := dist_triangle _ _ _ theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y := dist_triangle_left _ _ _ theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z := dist_triangle_right _ _ _ /-- Express `dist` in terms of `edist` -/ theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg] namespace Metric -- instantiate pseudometric space as a topology variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α} /-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/ def ball (x : α) (ε : ℝ) : Set α := { y | dist y x < ε } @[simp] theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε := Iff.rfl theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball] theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε := dist_nonneg.trans_lt hy theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by rwa [mem_ball, dist_self] @[simp] theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε := ⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩ @[simp] theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt] @[simp] theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty] /-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also contains it. See also `exists_lt_subset_ball`. -/ theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by simp only [mem_ball] at h ⊢ exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩ theorem ball_eq_ball (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε := rfl theorem ball_eq_ball' (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.1 p.2 < ε } = Metric.ball x ε := by ext simp [dist_comm, UniformSpace.ball] @[simp] theorem iUnion_ball_nat (x : α) : ⋃ n : ℕ, ball x n = univ := iUnion_eq_univ_iff.2 fun y => exists_nat_gt (dist y x) @[simp] theorem iUnion_ball_nat_succ (x : α) : ⋃ n : ℕ, ball x (n + 1) = univ := iUnion_eq_univ_iff.2 fun y => (exists_nat_gt (dist y x)).imp fun _ h => h.trans (lt_add_one _) /-- `closedBall x ε` is the set of all points `y` with `dist y x ≤ ε` -/ def closedBall (x : α) (ε : ℝ) := { y | dist y x ≤ ε } @[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall] /-- `sphere x ε` is the set of all points `y` with `dist y x = ε` -/ def sphere (x : α) (ε : ℝ) := { y | dist y x = ε } @[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere] theorem ne_of_mem_sphere (h : y ∈ sphere x ε) (hε : ε ≠ 0) : y ≠ x := ne_of_mem_of_not_mem h <| by simpa using hε.symm theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε := dist_nonneg.trans_eq hy @[simp] theorem sphere_eq_empty_of_neg (hε : ε < 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _y hy => (nonneg_of_mem_sphere hy).not_lt hε theorem sphere_eq_empty_of_subsingleton [Subsingleton α] (hε : ε ≠ 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _ h => ne_of_mem_sphere h hε (Subsingleton.elim _ _) instance sphere_isEmpty_of_subsingleton [Subsingleton α] [NeZero ε] : IsEmpty (sphere x ε) := by rw [sphere_eq_empty_of_subsingleton (NeZero.ne ε)]; infer_instance theorem closedBall_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 ≤ ε) : closedBall x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem ball_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 < ε) : ball x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by rwa [mem_closedBall, dist_self] @[simp]
theorem nonempty_closedBall : (closedBall x ε).Nonempty ↔ 0 ≤ ε := ⟨fun ⟨_x, hx⟩ => dist_nonneg.trans hx, fun h => ⟨x, mem_closedBall_self h⟩⟩
Mathlib/Topology/MetricSpace/Pseudo/Defs.lean
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/- Copyright (c) 2020 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.Deriv.Basic import Mathlib.Analysis.Calculus.Deriv.Slope import Mathlib.Analysis.Normed.Operator.BoundedLinearMaps import Mathlib.Analysis.Normed.Module.FiniteDimension import Mathlib.MeasureTheory.Constructions.BorelSpace.ContinuousLinearMap import Mathlib.MeasureTheory.Function.StronglyMeasurable.AEStronglyMeasurable /-! # Derivative is measurable In this file we prove that the derivative of any function with complete codomain is a measurable function. Namely, we prove: * `measurableSet_of_differentiableAt`: the set `{x | DifferentiableAt 𝕜 f x}` is measurable; * `measurable_fderiv`: the function `fderiv 𝕜 f` is measurable; * `measurable_fderiv_apply_const`: for a fixed vector `y`, the function `fun x ↦ fderiv 𝕜 f x y` is measurable; * `measurable_deriv`: the function `deriv f` is measurable (for `f : 𝕜 → F`). We also show the same results for the right derivative on the real line (see `measurable_derivWithin_Ici` and `measurable_derivWithin_Ioi`), following the same proof strategy. We also prove measurability statements for functions depending on a parameter: for `f : α → E → F`, we show the measurability of `(p : α × E) ↦ fderiv 𝕜 (f p.1) p.2`. This requires additional assumptions. We give versions of the above statements (appending `with_param` to their names) when `f` is continuous and `E` is locally compact. ## Implementation We give a proof that avoids second-countability issues, by expressing the differentiability set as a function of open sets in the following way. Define `A (L, r, ε)` to be the set of points where, on a ball of radius roughly `r` around `x`, the function is uniformly approximated by the linear map `L`, up to `ε r`. It is an open set. Let also `B (L, r, s, ε) = A (L, r, ε) ∩ A (L, s, ε)`: we require that at two possibly different scales `r` and `s`, the function is well approximated by the linear map `L`. It is also open. We claim that the differentiability set of `f` is exactly `D = ⋂ ε > 0, ⋃ δ > 0, ⋂ r, s < δ, ⋃ L, B (L, r, s, ε)`. In other words, for any `ε > 0`, we require that there is a size `δ` such that, for any two scales below this size, the function is well approximated by a linear map, common to the two scales. The set `⋃ L, B (L, r, s, ε)` is open, as a union of open sets. Converting the intersections and unions to countable ones (using real numbers of the form `2 ^ (-n)`), it follows that the differentiability set is measurable. To prove the claim, there are two inclusions. One is trivial: if the function is differentiable at `x`, then `x` belongs to `D` (just take `L` to be the derivative, and use that the differentiability exactly says that the map is well approximated by `L`). This is proved in `mem_A_of_differentiable` and `differentiable_set_subset_D`. For the other direction, the difficulty is that `L` in the union may depend on `ε, r, s`. The key point is that, in fact, it doesn't depend too much on them. First, if `x` belongs both to `A (L, r, ε)` and `A (L', r, ε)`, then `L` and `L'` have to be close on a shell, and thus `‖L - L'‖` is bounded by `ε` (see `norm_sub_le_of_mem_A`). Assume now `x ∈ D`. If one has two maps `L` and `L'` such that `x` belongs to `A (L, r, ε)` and to `A (L', r', ε')`, one deduces that `L` is close to `L'` by arguing as follows. Consider another scale `s` smaller than `r` and `r'`. Take a linear map `L₁` that approximates `f` around `x` both at scales `r` and `s` w.r.t. `ε` (it exists as `x` belongs to `D`). Take also `L₂` that approximates `f` around `x` both at scales `r'` and `s` w.r.t. `ε'`. Then `L₁` is close to `L` (as they are close on a shell of radius `r`), and `L₂` is close to `L₁` (as they are close on a shell of radius `s`), and `L'` is close to `L₂` (as they are close on a shell of radius `r'`). It follows that `L` is close to `L'`, as we claimed. It follows that the different approximating linear maps that show up form a Cauchy sequence when `ε` tends to `0`. When the target space is complete, this sequence converges, to a limit `f'`. With the same kind of arguments, one checks that `f` is differentiable with derivative `f'`. To show that the derivative itself is measurable, add in the definition of `B` and `D` a set `K` of continuous linear maps to which `L` should belong. Then, when `K` is complete, the set `D K` is exactly the set of points where `f` is differentiable with a derivative in `K`. ## Tags derivative, measurable function, Borel σ-algebra -/ noncomputable section open Set Metric Asymptotics Filter ContinuousLinearMap MeasureTheory TopologicalSpace open scoped Topology namespace ContinuousLinearMap variable {𝕜 E F : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [NormedSpace 𝕜 F] theorem measurable_apply₂ [MeasurableSpace E] [OpensMeasurableSpace E] [SecondCountableTopologyEither (E →L[𝕜] F) E] [MeasurableSpace F] [BorelSpace F] : Measurable fun p : (E →L[𝕜] F) × E => p.1 p.2 := isBoundedBilinearMap_apply.continuous.measurable end ContinuousLinearMap section fderiv variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F] variable {f : E → F} (K : Set (E →L[𝕜] F)) namespace FDerivMeasurableAux /-- The set `A f L r ε` is the set of points `x` around which the function `f` is well approximated at scale `r` by the linear map `L`, up to an error `ε`. We tweak the definition to make sure that this is an open set. -/ def A (f : E → F) (L : E →L[𝕜] F) (r ε : ℝ) : Set E := { x | ∃ r' ∈ Ioc (r / 2) r, ∀ y ∈ ball x r', ∀ z ∈ ball x r', ‖f z - f y - L (z - y)‖ < ε * r } /-- The set `B f K r s ε` is the set of points `x` around which there exists a continuous linear map `L` belonging to `K` (a given set of continuous linear maps) that approximates well the function `f` (up to an error `ε`), simultaneously at scales `r` and `s`. -/ def B (f : E → F) (K : Set (E →L[𝕜] F)) (r s ε : ℝ) : Set E := ⋃ L ∈ K, A f L r ε ∩ A f L s ε /-- The set `D f K` is a complicated set constructed using countable intersections and unions. Its main use is that, when `K` is complete, it is exactly the set of points where `f` is differentiable, with a derivative in `K`. -/ def D (f : E → F) (K : Set (E →L[𝕜] F)) : Set E := ⋂ e : ℕ, ⋃ n : ℕ, ⋂ (p ≥ n) (q ≥ n), B f K ((1 / 2) ^ p) ((1 / 2) ^ q) ((1 / 2) ^ e) theorem isOpen_A (L : E →L[𝕜] F) (r ε : ℝ) : IsOpen (A f L r ε) := by rw [Metric.isOpen_iff] rintro x ⟨r', r'_mem, hr'⟩ obtain ⟨s, s_gt, s_lt⟩ : ∃ s : ℝ, r / 2 < s ∧ s < r' := exists_between r'_mem.1 have : s ∈ Ioc (r / 2) r := ⟨s_gt, le_of_lt (s_lt.trans_le r'_mem.2)⟩ refine ⟨r' - s, by linarith, fun x' hx' => ⟨s, this, ?_⟩⟩ have B : ball x' s ⊆ ball x r' := ball_subset (le_of_lt hx') intro y hy z hz exact hr' y (B hy) z (B hz) theorem isOpen_B {K : Set (E →L[𝕜] F)} {r s ε : ℝ} : IsOpen (B f K r s ε) := by simp [B, isOpen_biUnion, IsOpen.inter, isOpen_A] theorem A_mono (L : E →L[𝕜] F) (r : ℝ) {ε δ : ℝ} (h : ε ≤ δ) : A f L r ε ⊆ A f L r δ := by rintro x ⟨r', r'r, hr'⟩ refine ⟨r', r'r, fun y hy z hz => (hr' y hy z hz).trans_le (mul_le_mul_of_nonneg_right h ?_)⟩ linarith [mem_ball.1 hy, r'r.2, @dist_nonneg _ _ y x] theorem le_of_mem_A {r ε : ℝ} {L : E →L[𝕜] F} {x : E} (hx : x ∈ A f L r ε) {y z : E} (hy : y ∈ closedBall x (r / 2)) (hz : z ∈ closedBall x (r / 2)) : ‖f z - f y - L (z - y)‖ ≤ ε * r := by rcases hx with ⟨r', r'mem, hr'⟩ apply le_of_lt exact hr' _ ((mem_closedBall.1 hy).trans_lt r'mem.1) _ ((mem_closedBall.1 hz).trans_lt r'mem.1) theorem mem_A_of_differentiable {ε : ℝ} (hε : 0 < ε) {x : E} (hx : DifferentiableAt 𝕜 f x) : ∃ R > 0, ∀ r ∈ Ioo (0 : ℝ) R, x ∈ A f (fderiv 𝕜 f x) r ε := by let δ := (ε / 2) / 2 obtain ⟨R, R_pos, hR⟩ : ∃ R > 0, ∀ y ∈ ball x R, ‖f y - f x - fderiv 𝕜 f x (y - x)‖ ≤ δ * ‖y - x‖ := eventually_nhds_iff_ball.1 <| hx.hasFDerivAt.isLittleO.bound <| by positivity refine ⟨R, R_pos, fun r hr => ?_⟩ have : r ∈ Ioc (r / 2) r := right_mem_Ioc.2 <| half_lt_self hr.1 refine ⟨r, this, fun y hy z hz => ?_⟩ calc ‖f z - f y - (fderiv 𝕜 f x) (z - y)‖ = ‖f z - f x - (fderiv 𝕜 f x) (z - x) - (f y - f x - (fderiv 𝕜 f x) (y - x))‖ := by simp only [map_sub]; abel_nf _ ≤ ‖f z - f x - (fderiv 𝕜 f x) (z - x)‖ + ‖f y - f x - (fderiv 𝕜 f x) (y - x)‖ := norm_sub_le _ _ _ ≤ δ * ‖z - x‖ + δ * ‖y - x‖ := add_le_add (hR _ (ball_subset_ball hr.2.le hz)) (hR _ (ball_subset_ball hr.2.le hy)) _ ≤ δ * r + δ * r := by rw [mem_ball_iff_norm] at hz hy; gcongr _ = (ε / 2) * r := by ring _ < ε * r := by gcongr; exacts [hr.1, half_lt_self hε] theorem norm_sub_le_of_mem_A {c : 𝕜} (hc : 1 < ‖c‖) {r ε : ℝ} (hε : 0 < ε) (hr : 0 < r) {x : E} {L₁ L₂ : E →L[𝕜] F} (h₁ : x ∈ A f L₁ r ε) (h₂ : x ∈ A f L₂ r ε) : ‖L₁ - L₂‖ ≤ 4 * ‖c‖ * ε := by refine opNorm_le_of_shell (half_pos hr) (by positivity) hc ?_ intro y ley ylt rw [div_div, div_le_iff₀' (mul_pos (by norm_num : (0 : ℝ) < 2) (zero_lt_one.trans hc))] at ley calc ‖(L₁ - L₂) y‖ = ‖f (x + y) - f x - L₂ (x + y - x) - (f (x + y) - f x - L₁ (x + y - x))‖ := by simp _ ≤ ‖f (x + y) - f x - L₂ (x + y - x)‖ + ‖f (x + y) - f x - L₁ (x + y - x)‖ := norm_sub_le _ _ _ ≤ ε * r + ε * r := by apply add_le_add · apply le_of_mem_A h₂ · simp only [le_of_lt (half_pos hr), mem_closedBall, dist_self] · simp only [dist_eq_norm, add_sub_cancel_left, mem_closedBall, ylt.le] · apply le_of_mem_A h₁ · simp only [le_of_lt (half_pos hr), mem_closedBall, dist_self] · simp only [dist_eq_norm, add_sub_cancel_left, mem_closedBall, ylt.le] _ = 2 * ε * r := by ring _ ≤ 2 * ε * (2 * ‖c‖ * ‖y‖) := by gcongr _ = 4 * ‖c‖ * ε * ‖y‖ := by ring /-- Easy inclusion: a differentiability point with derivative in `K` belongs to `D f K`. -/ theorem differentiable_set_subset_D : { x | DifferentiableAt 𝕜 f x ∧ fderiv 𝕜 f x ∈ K } ⊆ D f K := by intro x hx rw [D, mem_iInter] intro e have : (0 : ℝ) < (1 / 2) ^ e := by positivity rcases mem_A_of_differentiable this hx.1 with ⟨R, R_pos, hR⟩ obtain ⟨n, hn⟩ : ∃ n : ℕ, (1 / 2) ^ n < R := exists_pow_lt_of_lt_one R_pos (by norm_num : (1 : ℝ) / 2 < 1) simp only [mem_iUnion, mem_iInter, B, mem_inter_iff] refine ⟨n, fun p hp q hq => ⟨fderiv 𝕜 f x, hx.2, ⟨?_, ?_⟩⟩⟩ <;> · refine hR _ ⟨pow_pos (by norm_num) _, lt_of_le_of_lt ?_ hn⟩ exact pow_le_pow_of_le_one (by norm_num) (by norm_num) (by assumption) /-- Harder inclusion: at a point in `D f K`, the function `f` has a derivative, in `K`. -/ theorem D_subset_differentiable_set {K : Set (E →L[𝕜] F)} (hK : IsComplete K) : D f K ⊆ { x | DifferentiableAt 𝕜 f x ∧ fderiv 𝕜 f x ∈ K } := by have P : ∀ {n : ℕ}, (0 : ℝ) < (1 / 2) ^ n := fun {n} => pow_pos (by norm_num) n rcases NormedField.exists_one_lt_norm 𝕜 with ⟨c, hc⟩ intro x hx have : ∀ e : ℕ, ∃ n : ℕ, ∀ p q, n ≤ p → n ≤ q → ∃ L ∈ K, x ∈ A f L ((1 / 2) ^ p) ((1 / 2) ^ e) ∩ A f L ((1 / 2) ^ q) ((1 / 2) ^ e) := by intro e have := mem_iInter.1 hx e rcases mem_iUnion.1 this with ⟨n, hn⟩ refine ⟨n, fun p q hp hq => ?_⟩ simp only [mem_iInter] at hn rcases mem_iUnion.1 (hn p hp q hq) with ⟨L, hL⟩ exact ⟨L, exists_prop.mp <| mem_iUnion.1 hL⟩ /- Recast the assumptions: for each `e`, there exist `n e` and linear maps `L e p q` in `K` such that, for `p, q ≥ n e`, then `f` is well approximated by `L e p q` at scale `2 ^ (-p)` and `2 ^ (-q)`, with an error `2 ^ (-e)`. -/ choose! n L hn using this /- All the operators `L e p q` that show up are close to each other. To prove this, we argue that `L e p q` is close to `L e p r` (where `r` is large enough), as both approximate `f` at scale `2 ^(- p)`. And `L e p r` is close to `L e' p' r` as both approximate `f` at scale `2 ^ (- r)`. And `L e' p' r` is close to `L e' p' q'` as both approximate `f` at scale `2 ^ (- p')`. -/ have M : ∀ e p q e' p' q', n e ≤ p → n e ≤ q → n e' ≤ p' → n e' ≤ q' → e ≤ e' → ‖L e p q - L e' p' q'‖ ≤ 12 * ‖c‖ * (1 / 2) ^ e := by intro e p q e' p' q' hp hq hp' hq' he' let r := max (n e) (n e') have I : ((1 : ℝ) / 2) ^ e' ≤ (1 / 2) ^ e := pow_le_pow_of_le_one (by norm_num) (by norm_num) he' have J1 : ‖L e p q - L e p r‖ ≤ 4 * ‖c‖ * (1 / 2) ^ e := by have I1 : x ∈ A f (L e p q) ((1 / 2) ^ p) ((1 / 2) ^ e) := (hn e p q hp hq).2.1 have I2 : x ∈ A f (L e p r) ((1 / 2) ^ p) ((1 / 2) ^ e) := (hn e p r hp (le_max_left _ _)).2.1 exact norm_sub_le_of_mem_A hc P P I1 I2 have J2 : ‖L e p r - L e' p' r‖ ≤ 4 * ‖c‖ * (1 / 2) ^ e := by have I1 : x ∈ A f (L e p r) ((1 / 2) ^ r) ((1 / 2) ^ e) := (hn e p r hp (le_max_left _ _)).2.2 have I2 : x ∈ A f (L e' p' r) ((1 / 2) ^ r) ((1 / 2) ^ e') := (hn e' p' r hp' (le_max_right _ _)).2.2 exact norm_sub_le_of_mem_A hc P P I1 (A_mono _ _ I I2) have J3 : ‖L e' p' r - L e' p' q'‖ ≤ 4 * ‖c‖ * (1 / 2) ^ e := by have I1 : x ∈ A f (L e' p' r) ((1 / 2) ^ p') ((1 / 2) ^ e') := (hn e' p' r hp' (le_max_right _ _)).2.1 have I2 : x ∈ A f (L e' p' q') ((1 / 2) ^ p') ((1 / 2) ^ e') := (hn e' p' q' hp' hq').2.1 exact norm_sub_le_of_mem_A hc P P (A_mono _ _ I I1) (A_mono _ _ I I2) calc ‖L e p q - L e' p' q'‖ = ‖L e p q - L e p r + (L e p r - L e' p' r) + (L e' p' r - L e' p' q')‖ := by congr 1; abel _ ≤ ‖L e p q - L e p r‖ + ‖L e p r - L e' p' r‖ + ‖L e' p' r - L e' p' q'‖ := norm_add₃_le _ ≤ 4 * ‖c‖ * (1 / 2) ^ e + 4 * ‖c‖ * (1 / 2) ^ e + 4 * ‖c‖ * (1 / 2) ^ e := by gcongr _ = 12 * ‖c‖ * (1 / 2) ^ e := by ring /- For definiteness, use `L0 e = L e (n e) (n e)`, to have a single sequence. We claim that this is a Cauchy sequence. -/ let L0 : ℕ → E →L[𝕜] F := fun e => L e (n e) (n e) have : CauchySeq L0 := by rw [Metric.cauchySeq_iff'] intro ε εpos obtain ⟨e, he⟩ : ∃ e : ℕ, (1 / 2) ^ e < ε / (12 * ‖c‖) := exists_pow_lt_of_lt_one (by positivity) (by norm_num) refine ⟨e, fun e' he' => ?_⟩ rw [dist_comm, dist_eq_norm] calc ‖L0 e - L0 e'‖ ≤ 12 * ‖c‖ * (1 / 2) ^ e := M _ _ _ _ _ _ le_rfl le_rfl le_rfl le_rfl he' _ < 12 * ‖c‖ * (ε / (12 * ‖c‖)) := by gcongr _ = ε := by field_simp -- As it is Cauchy, the sequence `L0` converges, to a limit `f'` in `K`. obtain ⟨f', f'K, hf'⟩ : ∃ f' ∈ K, Tendsto L0 atTop (𝓝 f') := cauchySeq_tendsto_of_isComplete hK (fun e => (hn e (n e) (n e) le_rfl le_rfl).1) this have Lf' : ∀ e p, n e ≤ p → ‖L e (n e) p - f'‖ ≤ 12 * ‖c‖ * (1 / 2) ^ e := by intro e p hp apply le_of_tendsto (tendsto_const_nhds.sub hf').norm rw [eventually_atTop] exact ⟨e, fun e' he' => M _ _ _ _ _ _ le_rfl hp le_rfl le_rfl he'⟩ -- Let us show that `f` has derivative `f'` at `x`. have : HasFDerivAt f f' x := by simp only [hasFDerivAt_iff_isLittleO_nhds_zero, isLittleO_iff] /- to get an approximation with a precision `ε`, we will replace `f` with `L e (n e) m` for some large enough `e` (yielding a small error by uniform approximation). As one can vary `m`, this makes it possible to cover all scales, and thus to obtain a good linear approximation in the whole ball of radius `(1/2)^(n e)`. -/ intro ε εpos have pos : 0 < 4 + 12 * ‖c‖ := by positivity obtain ⟨e, he⟩ : ∃ e : ℕ, (1 / 2) ^ e < ε / (4 + 12 * ‖c‖) := exists_pow_lt_of_lt_one (div_pos εpos pos) (by norm_num) rw [eventually_nhds_iff_ball] refine ⟨(1 / 2) ^ (n e + 1), P, fun y hy => ?_⟩ -- We need to show that `f (x + y) - f x - f' y` is small. For this, we will work at scale -- `k` where `k` is chosen with `‖y‖ ∼ 2 ^ (-k)`. by_cases y_pos : y = 0 · simp [y_pos] have yzero : 0 < ‖y‖ := norm_pos_iff.mpr y_pos have y_lt : ‖y‖ < (1 / 2) ^ (n e + 1) := by simpa using mem_ball_iff_norm.1 hy have yone : ‖y‖ ≤ 1 := le_trans y_lt.le (pow_le_one₀ (by norm_num) (by norm_num)) -- define the scale `k`. obtain ⟨k, hk, h'k⟩ : ∃ k : ℕ, (1 / 2) ^ (k + 1) < ‖y‖ ∧ ‖y‖ ≤ (1 / 2) ^ k := exists_nat_pow_near_of_lt_one yzero yone (by norm_num : (0 : ℝ) < 1 / 2) (by norm_num : (1 : ℝ) / 2 < 1) -- the scale is large enough (as `y` is small enough) have k_gt : n e < k := by have : ((1 : ℝ) / 2) ^ (k + 1) < (1 / 2) ^ (n e + 1) := lt_trans hk y_lt rw [pow_lt_pow_iff_right_of_lt_one₀ (by norm_num : (0 : ℝ) < 1 / 2) (by norm_num)] at this omega set m := k - 1 have m_ge : n e ≤ m := Nat.le_sub_one_of_lt k_gt have km : k = m + 1 := (Nat.succ_pred_eq_of_pos (lt_of_le_of_lt (zero_le _) k_gt)).symm rw [km] at hk h'k -- `f` is well approximated by `L e (n e) k` at the relevant scale -- (in fact, we use `m = k - 1` instead of `k` because of the precise definition of `A`). have J1 : ‖f (x + y) - f x - L e (n e) m (x + y - x)‖ ≤ (1 / 2) ^ e * (1 / 2) ^ m := by apply le_of_mem_A (hn e (n e) m le_rfl m_ge).2.2 · simp only [mem_closedBall, dist_self] positivity · simpa only [dist_eq_norm, add_sub_cancel_left, mem_closedBall, pow_succ, mul_one_div] using h'k have J2 : ‖f (x + y) - f x - L e (n e) m y‖ ≤ 4 * (1 / 2) ^ e * ‖y‖ := calc ‖f (x + y) - f x - L e (n e) m y‖ ≤ (1 / 2) ^ e * (1 / 2) ^ m := by simpa only [add_sub_cancel_left] using J1 _ = 4 * (1 / 2) ^ e * (1 / 2) ^ (m + 2) := by field_simp; ring _ ≤ 4 * (1 / 2) ^ e * ‖y‖ := by gcongr -- use the previous estimates to see that `f (x + y) - f x - f' y` is small. calc ‖f (x + y) - f x - f' y‖ = ‖f (x + y) - f x - L e (n e) m y + (L e (n e) m - f') y‖ := congr_arg _ (by simp) _ ≤ 4 * (1 / 2) ^ e * ‖y‖ + 12 * ‖c‖ * (1 / 2) ^ e * ‖y‖ := norm_add_le_of_le J2 <| (le_opNorm _ _).trans <| by gcongr; exact Lf' _ _ m_ge _ = (4 + 12 * ‖c‖) * ‖y‖ * (1 / 2) ^ e := by ring _ ≤ (4 + 12 * ‖c‖) * ‖y‖ * (ε / (4 + 12 * ‖c‖)) := by gcongr _ = ε * ‖y‖ := by field_simp [ne_of_gt pos]; ring rw [← this.fderiv] at f'K exact ⟨this.differentiableAt, f'K⟩ theorem differentiable_set_eq_D (hK : IsComplete K) : { x | DifferentiableAt 𝕜 f x ∧ fderiv 𝕜 f x ∈ K } = D f K := Subset.antisymm (differentiable_set_subset_D _) (D_subset_differentiable_set hK) end FDerivMeasurableAux open FDerivMeasurableAux variable [MeasurableSpace E] [OpensMeasurableSpace E] variable (𝕜 f) /-- The set of differentiability points of a function, with derivative in a given complete set, is Borel-measurable. -/ theorem measurableSet_of_differentiableAt_of_isComplete {K : Set (E →L[𝕜] F)} (hK : IsComplete K) : MeasurableSet { x | DifferentiableAt 𝕜 f x ∧ fderiv 𝕜 f x ∈ K } := by -- Porting note: was -- simp [differentiable_set_eq_D K hK, D, isOpen_B.measurableSet, MeasurableSet.iInter, -- MeasurableSet.iUnion] simp only [D, differentiable_set_eq_D K hK] repeat apply_rules [MeasurableSet.iUnion, MeasurableSet.iInter] <;> intro exact isOpen_B.measurableSet variable [CompleteSpace F] /-- The set of differentiability points of a function taking values in a complete space is Borel-measurable. -/ theorem measurableSet_of_differentiableAt : MeasurableSet { x | DifferentiableAt 𝕜 f x } := by have : IsComplete (univ : Set (E →L[𝕜] F)) := complete_univ convert measurableSet_of_differentiableAt_of_isComplete 𝕜 f this simp @[measurability, fun_prop] theorem measurable_fderiv : Measurable (fderiv 𝕜 f) := by refine measurable_of_isClosed fun s hs => ?_ have : fderiv 𝕜 f ⁻¹' s = { x | DifferentiableAt 𝕜 f x ∧ fderiv 𝕜 f x ∈ s } ∪ { x | ¬DifferentiableAt 𝕜 f x } ∩ { _x | (0 : E →L[𝕜] F) ∈ s } := Set.ext fun x => mem_preimage.trans fderiv_mem_iff rw [this] exact (measurableSet_of_differentiableAt_of_isComplete _ _ hs.isComplete).union ((measurableSet_of_differentiableAt _ _).compl.inter (MeasurableSet.const _)) @[measurability, fun_prop] theorem measurable_fderiv_apply_const [MeasurableSpace F] [BorelSpace F] (y : E) : Measurable fun x => fderiv 𝕜 f x y := (ContinuousLinearMap.measurable_apply y).comp (measurable_fderiv 𝕜 f) variable {𝕜} @[measurability, fun_prop] theorem measurable_deriv [MeasurableSpace 𝕜] [OpensMeasurableSpace 𝕜] [MeasurableSpace F] [BorelSpace F] (f : 𝕜 → F) : Measurable (deriv f) := by simpa only [fderiv_deriv] using measurable_fderiv_apply_const 𝕜 f 1 theorem stronglyMeasurable_deriv [MeasurableSpace 𝕜] [OpensMeasurableSpace 𝕜] [h : SecondCountableTopologyEither 𝕜 F] (f : 𝕜 → F) : StronglyMeasurable (deriv f) := by borelize F rcases h.out with h𝕜|hF · exact stronglyMeasurable_iff_measurable_separable.2 ⟨measurable_deriv f, isSeparable_range_deriv _⟩ · exact (measurable_deriv f).stronglyMeasurable theorem aemeasurable_deriv [MeasurableSpace 𝕜] [OpensMeasurableSpace 𝕜] [MeasurableSpace F] [BorelSpace F] (f : 𝕜 → F) (μ : Measure 𝕜) : AEMeasurable (deriv f) μ := (measurable_deriv f).aemeasurable theorem aestronglyMeasurable_deriv [MeasurableSpace 𝕜] [OpensMeasurableSpace 𝕜] [SecondCountableTopologyEither 𝕜 F] (f : 𝕜 → F) (μ : Measure 𝕜) : AEStronglyMeasurable (deriv f) μ := (stronglyMeasurable_deriv f).aestronglyMeasurable end fderiv section RightDeriv variable {F : Type*} [NormedAddCommGroup F] [NormedSpace ℝ F] variable {f : ℝ → F} (K : Set F) namespace RightDerivMeasurableAux /-- The set `A f L r ε` is the set of points `x` around which the function `f` is well approximated at scale `r` by the linear map `h ↦ h • L`, up to an error `ε`. We tweak the definition to make sure that this is open on the right. -/ def A (f : ℝ → F) (L : F) (r ε : ℝ) : Set ℝ := { x | ∃ r' ∈ Ioc (r / 2) r, ∀ᵉ (y ∈ Icc x (x + r')) (z ∈ Icc x (x + r')), ‖f z - f y - (z - y) • L‖ ≤ ε * r } /-- The set `B f K r s ε` is the set of points `x` around which there exists a vector `L` belonging to `K` (a given set of vectors) such that `h • L` approximates well `f (x + h)` (up to an error `ε`), simultaneously at scales `r` and `s`. -/ def B (f : ℝ → F) (K : Set F) (r s ε : ℝ) : Set ℝ := ⋃ L ∈ K, A f L r ε ∩ A f L s ε /-- The set `D f K` is a complicated set constructed using countable intersections and unions. Its main use is that, when `K` is complete, it is exactly the set of points where `f` is differentiable, with a derivative in `K`. -/ def D (f : ℝ → F) (K : Set F) : Set ℝ := ⋂ e : ℕ, ⋃ n : ℕ, ⋂ (p ≥ n) (q ≥ n), B f K ((1 / 2) ^ p) ((1 / 2) ^ q) ((1 / 2) ^ e) theorem A_mem_nhdsGT {L : F} {r ε x : ℝ} (hx : x ∈ A f L r ε) : A f L r ε ∈ 𝓝[>] x := by rcases hx with ⟨r', rr', hr'⟩ obtain ⟨s, s_gt, s_lt⟩ : ∃ s : ℝ, r / 2 < s ∧ s < r' := exists_between rr'.1 have : s ∈ Ioc (r / 2) r := ⟨s_gt, le_of_lt (s_lt.trans_le rr'.2)⟩ filter_upwards [Ioo_mem_nhdsGT <| show x < x + r' - s by linarith] with x' hx' use s, this have A : Icc x' (x' + s) ⊆ Icc x (x + r') := by apply Icc_subset_Icc hx'.1.le linarith [hx'.2] intro y hy z hz exact hr' y (A hy) z (A hz) theorem B_mem_nhdsGT {K : Set F} {r s ε x : ℝ} (hx : x ∈ B f K r s ε) : B f K r s ε ∈ 𝓝[>] x := by obtain ⟨L, LK, hL₁, hL₂⟩ : ∃ L : F, L ∈ K ∧ x ∈ A f L r ε ∧ x ∈ A f L s ε := by simpa only [B, mem_iUnion, mem_inter_iff, exists_prop] using hx filter_upwards [A_mem_nhdsGT hL₁, A_mem_nhdsGT hL₂] with y hy₁ hy₂ simp only [B, mem_iUnion, mem_inter_iff, exists_prop] exact ⟨L, LK, hy₁, hy₂⟩ theorem measurableSet_B {K : Set F} {r s ε : ℝ} : MeasurableSet (B f K r s ε) := .of_mem_nhdsGT fun _ hx => B_mem_nhdsGT hx theorem A_mono (L : F) (r : ℝ) {ε δ : ℝ} (h : ε ≤ δ) : A f L r ε ⊆ A f L r δ := by rintro x ⟨r', r'r, hr'⟩ refine ⟨r', r'r, fun y hy z hz => (hr' y hy z hz).trans (mul_le_mul_of_nonneg_right h ?_)⟩ linarith [hy.1, hy.2, r'r.2] theorem le_of_mem_A {r ε : ℝ} {L : F} {x : ℝ} (hx : x ∈ A f L r ε) {y z : ℝ} (hy : y ∈ Icc x (x + r / 2)) (hz : z ∈ Icc x (x + r / 2)) : ‖f z - f y - (z - y) • L‖ ≤ ε * r := by rcases hx with ⟨r', r'mem, hr'⟩ have A : x + r / 2 ≤ x + r' := by linarith [r'mem.1] exact hr' _ ((Icc_subset_Icc le_rfl A) hy) _ ((Icc_subset_Icc le_rfl A) hz) theorem mem_A_of_differentiable {ε : ℝ} (hε : 0 < ε) {x : ℝ} (hx : DifferentiableWithinAt ℝ f (Ici x) x) : ∃ R > 0, ∀ r ∈ Ioo (0 : ℝ) R, x ∈ A f (derivWithin f (Ici x) x) r ε := by have := hx.hasDerivWithinAt simp_rw [hasDerivWithinAt_iff_isLittleO, isLittleO_iff] at this rcases mem_nhdsGE_iff_exists_Ico_subset.1 (this (half_pos hε)) with ⟨m, xm, hm⟩ refine ⟨m - x, by linarith [show x < m from xm], fun r hr => ?_⟩ have : r ∈ Ioc (r / 2) r := ⟨half_lt_self hr.1, le_rfl⟩ refine ⟨r, this, fun y hy z hz => ?_⟩ calc ‖f z - f y - (z - y) • derivWithin f (Ici x) x‖ = ‖f z - f x - (z - x) • derivWithin f (Ici x) x - (f y - f x - (y - x) • derivWithin f (Ici x) x)‖ := by congr 1; simp only [sub_smul]; abel _ ≤ ‖f z - f x - (z - x) • derivWithin f (Ici x) x‖ + ‖f y - f x - (y - x) • derivWithin f (Ici x) x‖ := (norm_sub_le _ _) _ ≤ ε / 2 * ‖z - x‖ + ε / 2 * ‖y - x‖ := (add_le_add (hm ⟨hz.1, hz.2.trans_lt (by linarith [hr.2])⟩) (hm ⟨hy.1, hy.2.trans_lt (by linarith [hr.2])⟩)) _ ≤ ε / 2 * r + ε / 2 * r := by gcongr · rw [Real.norm_of_nonneg] <;> linarith [hz.1, hz.2] · rw [Real.norm_of_nonneg] <;> linarith [hy.1, hy.2] _ = ε * r := by ring theorem norm_sub_le_of_mem_A {r x : ℝ} (hr : 0 < r) (ε : ℝ) {L₁ L₂ : F} (h₁ : x ∈ A f L₁ r ε) (h₂ : x ∈ A f L₂ r ε) : ‖L₁ - L₂‖ ≤ 4 * ε := by suffices H : ‖(r / 2) • (L₁ - L₂)‖ ≤ r / 2 * (4 * ε) by rwa [norm_smul, Real.norm_of_nonneg (half_pos hr).le, mul_le_mul_left (half_pos hr)] at H calc ‖(r / 2) • (L₁ - L₂)‖ = ‖f (x + r / 2) - f x - (x + r / 2 - x) • L₂ - (f (x + r / 2) - f x - (x + r / 2 - x) • L₁)‖ := by simp [smul_sub] _ ≤ ‖f (x + r / 2) - f x - (x + r / 2 - x) • L₂‖ + ‖f (x + r / 2) - f x - (x + r / 2 - x) • L₁‖ := norm_sub_le _ _ _ ≤ ε * r + ε * r := by apply add_le_add · apply le_of_mem_A h₂ <;> simp [(half_pos hr).le] · apply le_of_mem_A h₁ <;> simp [(half_pos hr).le] _ = r / 2 * (4 * ε) := by ring /-- Easy inclusion: a differentiability point with derivative in `K` belongs to `D f K`. -/ theorem differentiable_set_subset_D : { x | DifferentiableWithinAt ℝ f (Ici x) x ∧ derivWithin f (Ici x) x ∈ K } ⊆ D f K := by intro x hx rw [D, mem_iInter] intro e have : (0 : ℝ) < (1 / 2) ^ e := pow_pos (by norm_num) _ rcases mem_A_of_differentiable this hx.1 with ⟨R, R_pos, hR⟩ obtain ⟨n, hn⟩ : ∃ n : ℕ, (1 / 2) ^ n < R := exists_pow_lt_of_lt_one R_pos (by norm_num : (1 : ℝ) / 2 < 1) simp only [mem_iUnion, mem_iInter, B, mem_inter_iff] refine ⟨n, fun p hp q hq => ⟨derivWithin f (Ici x) x, hx.2, ⟨?_, ?_⟩⟩⟩ <;> · refine hR _ ⟨pow_pos (by norm_num) _, lt_of_le_of_lt ?_ hn⟩ exact pow_le_pow_of_le_one (by norm_num) (by norm_num) (by assumption) /-- Harder inclusion: at a point in `D f K`, the function `f` has a derivative, in `K`. -/ theorem D_subset_differentiable_set {K : Set F} (hK : IsComplete K) : D f K ⊆ { x | DifferentiableWithinAt ℝ f (Ici x) x ∧ derivWithin f (Ici x) x ∈ K } := by have P : ∀ {n : ℕ}, (0 : ℝ) < (1 / 2) ^ n := fun {n} => pow_pos (by norm_num) n intro x hx have : ∀ e : ℕ, ∃ n : ℕ, ∀ p q, n ≤ p → n ≤ q → ∃ L ∈ K, x ∈ A f L ((1 / 2) ^ p) ((1 / 2) ^ e) ∩ A f L ((1 / 2) ^ q) ((1 / 2) ^ e) := by intro e have := mem_iInter.1 hx e rcases mem_iUnion.1 this with ⟨n, hn⟩ refine ⟨n, fun p q hp hq => ?_⟩ simp only [mem_iInter] at hn rcases mem_iUnion.1 (hn p hp q hq) with ⟨L, hL⟩ exact ⟨L, exists_prop.mp <| mem_iUnion.1 hL⟩ /- Recast the assumptions: for each `e`, there exist `n e` and linear maps `L e p q` in `K` such that, for `p, q ≥ n e`, then `f` is well approximated by `L e p q` at scale `2 ^ (-p)` and `2 ^ (-q)`, with an error `2 ^ (-e)`. -/ choose! n L hn using this /- All the operators `L e p q` that show up are close to each other. To prove this, we argue that `L e p q` is close to `L e p r` (where `r` is large enough), as both approximate `f` at scale `2 ^(- p)`. And `L e p r` is close to `L e' p' r` as both approximate `f` at scale `2 ^ (- r)`. And `L e' p' r` is close to `L e' p' q'` as both approximate `f` at scale `2 ^ (- p')`. -/ have M : ∀ e p q e' p' q', n e ≤ p → n e ≤ q → n e' ≤ p' → n e' ≤ q' → e ≤ e' → ‖L e p q - L e' p' q'‖ ≤ 12 * (1 / 2) ^ e := by intro e p q e' p' q' hp hq hp' hq' he' let r := max (n e) (n e') have I : ((1 : ℝ) / 2) ^ e' ≤ (1 / 2) ^ e := pow_le_pow_of_le_one (by norm_num) (by norm_num) he' have J1 : ‖L e p q - L e p r‖ ≤ 4 * (1 / 2) ^ e := by have I1 : x ∈ A f (L e p q) ((1 / 2) ^ p) ((1 / 2) ^ e) := (hn e p q hp hq).2.1 have I2 : x ∈ A f (L e p r) ((1 / 2) ^ p) ((1 / 2) ^ e) := (hn e p r hp (le_max_left _ _)).2.1 exact norm_sub_le_of_mem_A P _ I1 I2 have J2 : ‖L e p r - L e' p' r‖ ≤ 4 * (1 / 2) ^ e := by have I1 : x ∈ A f (L e p r) ((1 / 2) ^ r) ((1 / 2) ^ e) := (hn e p r hp (le_max_left _ _)).2.2 have I2 : x ∈ A f (L e' p' r) ((1 / 2) ^ r) ((1 / 2) ^ e') := (hn e' p' r hp' (le_max_right _ _)).2.2 exact norm_sub_le_of_mem_A P _ I1 (A_mono _ _ I I2) have J3 : ‖L e' p' r - L e' p' q'‖ ≤ 4 * (1 / 2) ^ e := by have I1 : x ∈ A f (L e' p' r) ((1 / 2) ^ p') ((1 / 2) ^ e') := (hn e' p' r hp' (le_max_right _ _)).2.1 have I2 : x ∈ A f (L e' p' q') ((1 / 2) ^ p') ((1 / 2) ^ e') := (hn e' p' q' hp' hq').2.1 exact norm_sub_le_of_mem_A P _ (A_mono _ _ I I1) (A_mono _ _ I I2) calc ‖L e p q - L e' p' q'‖ = ‖L e p q - L e p r + (L e p r - L e' p' r) + (L e' p' r - L e' p' q')‖ := by congr 1; abel _ ≤ ‖L e p q - L e p r‖ + ‖L e p r - L e' p' r‖ + ‖L e' p' r - L e' p' q'‖ := (le_trans (norm_add_le _ _) (add_le_add_right (norm_add_le _ _) _)) _ ≤ 4 * (1 / 2) ^ e + 4 * (1 / 2) ^ e + 4 * (1 / 2) ^ e := by gcongr _ = 12 * (1 / 2) ^ e := by ring /- For definiteness, use `L0 e = L e (n e) (n e)`, to have a single sequence. We claim that this is a Cauchy sequence. -/ let L0 : ℕ → F := fun e => L e (n e) (n e) have : CauchySeq L0 := by rw [Metric.cauchySeq_iff'] intro ε εpos obtain ⟨e, he⟩ : ∃ e : ℕ, (1 / 2) ^ e < ε / 12 := exists_pow_lt_of_lt_one (div_pos εpos (by norm_num)) (by norm_num) refine ⟨e, fun e' he' => ?_⟩ rw [dist_comm, dist_eq_norm] calc ‖L0 e - L0 e'‖ ≤ 12 * (1 / 2) ^ e := M _ _ _ _ _ _ le_rfl le_rfl le_rfl le_rfl he' _ < 12 * (ε / 12) := mul_lt_mul' le_rfl he (le_of_lt P) (by norm_num) _ = ε := by field_simp [(by norm_num : (12 : ℝ) ≠ 0)] -- As it is Cauchy, the sequence `L0` converges, to a limit `f'` in `K`. obtain ⟨f', f'K, hf'⟩ : ∃ f' ∈ K, Tendsto L0 atTop (𝓝 f') := cauchySeq_tendsto_of_isComplete hK (fun e => (hn e (n e) (n e) le_rfl le_rfl).1) this have Lf' : ∀ e p, n e ≤ p → ‖L e (n e) p - f'‖ ≤ 12 * (1 / 2) ^ e := by intro e p hp apply le_of_tendsto (tendsto_const_nhds.sub hf').norm rw [eventually_atTop] exact ⟨e, fun e' he' => M _ _ _ _ _ _ le_rfl hp le_rfl le_rfl he'⟩ -- Let us show that `f` has right derivative `f'` at `x`. have : HasDerivWithinAt f f' (Ici x) x := by simp only [hasDerivWithinAt_iff_isLittleO, isLittleO_iff] /- to get an approximation with a precision `ε`, we will replace `f` with `L e (n e) m` for some large enough `e` (yielding a small error by uniform approximation). As one can vary `m`, this makes it possible to cover all scales, and thus to obtain a good linear approximation in the whole interval of length `(1/2)^(n e)`. -/ intro ε εpos obtain ⟨e, he⟩ : ∃ e : ℕ, (1 / 2) ^ e < ε / 16 := exists_pow_lt_of_lt_one (div_pos εpos (by norm_num)) (by norm_num) filter_upwards [Icc_mem_nhdsGE <| show x < x + (1 / 2) ^ (n e + 1) by simp] with y hy -- We need to show that `f y - f x - f' (y - x)` is small. For this, we will work at scale -- `k` where `k` is chosen with `‖y - x‖ ∼ 2 ^ (-k)`. rcases eq_or_lt_of_le hy.1 with (rfl | xy) · simp only [sub_self, zero_smul, norm_zero, mul_zero, le_rfl] have yzero : 0 < y - x := sub_pos.2 xy have y_le : y - x ≤ (1 / 2) ^ (n e + 1) := by linarith [hy.2] have yone : y - x ≤ 1 := le_trans y_le (pow_le_one₀ (by norm_num) (by norm_num)) -- define the scale `k`. obtain ⟨k, hk, h'k⟩ : ∃ k : ℕ, (1 / 2) ^ (k + 1) < y - x ∧ y - x ≤ (1 / 2) ^ k := exists_nat_pow_near_of_lt_one yzero yone (by norm_num : (0 : ℝ) < 1 / 2) (by norm_num : (1 : ℝ) / 2 < 1) -- the scale is large enough (as `y - x` is small enough) have k_gt : n e < k := by have : ((1 : ℝ) / 2) ^ (k + 1) < (1 / 2) ^ (n e + 1) := lt_of_lt_of_le hk y_le rw [pow_lt_pow_iff_right_of_lt_one₀ (by norm_num : (0 : ℝ) < 1 / 2) (by norm_num)] at this omega set m := k - 1 have m_ge : n e ≤ m := Nat.le_sub_one_of_lt k_gt have km : k = m + 1 := (Nat.succ_pred_eq_of_pos (lt_of_le_of_lt (zero_le _) k_gt)).symm rw [km] at hk h'k -- `f` is well approximated by `L e (n e) k` at the relevant scale -- (in fact, we use `m = k - 1` instead of `k` because of the precise definition of `A`). have J : ‖f y - f x - (y - x) • L e (n e) m‖ ≤ 4 * (1 / 2) ^ e * ‖y - x‖ := calc ‖f y - f x - (y - x) • L e (n e) m‖ ≤ (1 / 2) ^ e * (1 / 2) ^ m := by apply le_of_mem_A (hn e (n e) m le_rfl m_ge).2.2 · simp only [one_div, inv_pow, left_mem_Icc, le_add_iff_nonneg_right] positivity · simp only [pow_add, tsub_le_iff_left] at h'k simpa only [hy.1, mem_Icc, true_and, one_div, pow_one] using h'k _ = 4 * (1 / 2) ^ e * (1 / 2) ^ (m + 2) := by field_simp; ring _ ≤ 4 * (1 / 2) ^ e * (y - x) := by gcongr _ = 4 * (1 / 2) ^ e * ‖y - x‖ := by rw [Real.norm_of_nonneg yzero.le] calc ‖f y - f x - (y - x) • f'‖ = ‖f y - f x - (y - x) • L e (n e) m + (y - x) • (L e (n e) m - f')‖ := by simp only [smul_sub, sub_add_sub_cancel] _ ≤ 4 * (1 / 2) ^ e * ‖y - x‖ + ‖y - x‖ * (12 * (1 / 2) ^ e) := norm_add_le_of_le J <| by rw [norm_smul]; gcongr; exact Lf' _ _ m_ge _ = 16 * ‖y - x‖ * (1 / 2) ^ e := by ring _ ≤ 16 * ‖y - x‖ * (ε / 16) := by gcongr _ = ε * ‖y - x‖ := by ring rw [← this.derivWithin (uniqueDiffOn_Ici x x Set.left_mem_Ici)] at f'K exact ⟨this.differentiableWithinAt, f'K⟩ theorem differentiable_set_eq_D (hK : IsComplete K) : { x | DifferentiableWithinAt ℝ f (Ici x) x ∧ derivWithin f (Ici x) x ∈ K } = D f K := Subset.antisymm (differentiable_set_subset_D _) (D_subset_differentiable_set hK) end RightDerivMeasurableAux open RightDerivMeasurableAux variable (f) /-- The set of right differentiability points of a function, with derivative in a given complete set, is Borel-measurable. -/ theorem measurableSet_of_differentiableWithinAt_Ici_of_isComplete {K : Set F} (hK : IsComplete K) : MeasurableSet { x | DifferentiableWithinAt ℝ f (Ici x) x ∧ derivWithin f (Ici x) x ∈ K } := by -- simp [differentiable_set_eq_d K hK, D, measurableSet_b, MeasurableSet.iInter, -- MeasurableSet.iUnion] simp only [differentiable_set_eq_D K hK, D] repeat apply_rules [MeasurableSet.iUnion, MeasurableSet.iInter] <;> intro exact measurableSet_B variable [CompleteSpace F] /-- The set of right differentiability points of a function taking values in a complete space is Borel-measurable. -/ theorem measurableSet_of_differentiableWithinAt_Ici : MeasurableSet { x | DifferentiableWithinAt ℝ f (Ici x) x } := by have : IsComplete (univ : Set F) := complete_univ convert measurableSet_of_differentiableWithinAt_Ici_of_isComplete f this simp @[measurability, fun_prop] theorem measurable_derivWithin_Ici [MeasurableSpace F] [BorelSpace F] : Measurable fun x => derivWithin f (Ici x) x := by refine measurable_of_isClosed fun s hs => ?_ have : (fun x => derivWithin f (Ici x) x) ⁻¹' s = { x | DifferentiableWithinAt ℝ f (Ici x) x ∧ derivWithin f (Ici x) x ∈ s } ∪ { x | ¬DifferentiableWithinAt ℝ f (Ici x) x } ∩ { _x | (0 : F) ∈ s } := Set.ext fun x => mem_preimage.trans derivWithin_mem_iff rw [this] exact (measurableSet_of_differentiableWithinAt_Ici_of_isComplete _ hs.isComplete).union ((measurableSet_of_differentiableWithinAt_Ici _).compl.inter (MeasurableSet.const _)) theorem stronglyMeasurable_derivWithin_Ici : StronglyMeasurable (fun x ↦ derivWithin f (Ici x) x) := by borelize F apply stronglyMeasurable_iff_measurable_separable.2 ⟨measurable_derivWithin_Ici f, ?_⟩ obtain ⟨t, t_count, ht⟩ : ∃ t : Set ℝ, t.Countable ∧ Dense t := exists_countable_dense ℝ suffices H : range (fun x ↦ derivWithin f (Ici x) x) ⊆ closure (Submodule.span ℝ (f '' t)) from IsSeparable.mono (t_count.image f).isSeparable.span.closure H rintro - ⟨x, rfl⟩ suffices H' : range (fun y ↦ derivWithin f (Ici x) y) ⊆ closure (Submodule.span ℝ (f '' t)) from H' (mem_range_self _) apply range_derivWithin_subset_closure_span_image calc Ici x = closure (Ioi x ∩ closure t) := by simp [dense_iff_closure_eq.1 ht] _ ⊆ closure (closure (Ioi x ∩ t)) := by apply closure_mono simpa [inter_comm] using (isOpen_Ioi (a := x)).closure_inter (s := t) _ ⊆ closure (Ici x ∩ t) := by rw [closure_closure] exact closure_mono (inter_subset_inter_left _ Ioi_subset_Ici_self) theorem aemeasurable_derivWithin_Ici [MeasurableSpace F] [BorelSpace F] (μ : Measure ℝ) : AEMeasurable (fun x => derivWithin f (Ici x) x) μ := (measurable_derivWithin_Ici f).aemeasurable theorem aestronglyMeasurable_derivWithin_Ici (μ : Measure ℝ) : AEStronglyMeasurable (fun x => derivWithin f (Ici x) x) μ := (stronglyMeasurable_derivWithin_Ici f).aestronglyMeasurable /-- The set of right differentiability points of a function taking values in a complete space is Borel-measurable. -/
theorem measurableSet_of_differentiableWithinAt_Ioi : MeasurableSet { x | DifferentiableWithinAt ℝ f (Ioi x) x } := by simpa [differentiableWithinAt_Ioi_iff_Ici] using measurableSet_of_differentiableWithinAt_Ici f @[measurability, fun_prop] theorem measurable_derivWithin_Ioi [MeasurableSpace F] [BorelSpace F] : Measurable fun x => derivWithin f (Ioi x) x := by simpa [derivWithin_Ioi_eq_Ici] using measurable_derivWithin_Ici f theorem stronglyMeasurable_derivWithin_Ioi : StronglyMeasurable (fun x ↦ derivWithin f (Ioi x) x) := by simpa [derivWithin_Ioi_eq_Ici] using stronglyMeasurable_derivWithin_Ici f
Mathlib/Analysis/Calculus/FDeriv/Measurable.lean
751
762
/- Copyright (c) 2021 Kexing Ying. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kexing Ying -/ import Mathlib.MeasureTheory.Measure.Decomposition.RadonNikodym import Mathlib.MeasureTheory.Measure.Haar.OfBasis import Mathlib.Probability.Independence.Basic /-! # Probability density function This file defines the probability density function of random variables, by which we mean measurable functions taking values in a Borel space. The probability density function is defined as the Radon–Nikodym derivative of the law of `X`. In particular, a measurable function `f` is said to the probability density function of a random variable `X` if for all measurable sets `S`, `ℙ(X ∈ S) = ∫ x in S, f x dx`. Probability density functions are one way of describing the distribution of a random variable, and are useful for calculating probabilities and finding moments (although the latter is better achieved with moment generating functions). This file also defines the continuous uniform distribution and proves some properties about random variables with this distribution. ## Main definitions * `MeasureTheory.HasPDF` : A random variable `X : Ω → E` is said to `HasPDF` with respect to the measure `ℙ` on `Ω` and `μ` on `E` if the push-forward measure of `ℙ` along `X` is absolutely continuous with respect to `μ` and they `HaveLebesgueDecomposition`. * `MeasureTheory.pdf` : If `X` is a random variable that `HasPDF X ℙ μ`, then `pdf X` is the Radon–Nikodym derivative of the push-forward measure of `ℙ` along `X` with respect to `μ`. * `MeasureTheory.pdf.IsUniform` : A random variable `X` is said to follow the uniform distribution if it has a constant probability density function with a compact, non-null support. ## Main results * `MeasureTheory.pdf.integral_pdf_smul` : Law of the unconscious statistician, i.e. if a random variable `X : Ω → E` has pdf `f`, then `𝔼(g(X)) = ∫ x, f x • g x dx` for all measurable `g : E → F`. * `MeasureTheory.pdf.integral_mul_eq_integral` : A real-valued random variable `X` with pdf `f` has expectation `∫ x, x * f x dx`. * `MeasureTheory.pdf.IsUniform.integral_eq` : If `X` follows the uniform distribution with its pdf having support `s`, then `X` has expectation `(λ s)⁻¹ * ∫ x in s, x dx` where `λ` is the Lebesgue measure. ## TODO Ultimately, we would also like to define characteristic functions to describe distributions as it exists for all random variables. However, to define this, we will need Fourier transforms which we currently do not have. -/ open scoped MeasureTheory NNReal ENNReal open TopologicalSpace MeasureTheory.Measure noncomputable section namespace MeasureTheory variable {Ω E : Type*} [MeasurableSpace E] /-- A random variable `X : Ω → E` is said to have a probability density function (`HasPDF`) with respect to the measure `ℙ` on `Ω` and `μ` on `E` if the push-forward measure of `ℙ` along `X` is absolutely continuous with respect to `μ` and they have a Lebesgue decomposition (`HaveLebesgueDecomposition`). -/ class HasPDF {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) : Prop where protected aemeasurable' : AEMeasurable X ℙ protected haveLebesgueDecomposition' : (map X ℙ).HaveLebesgueDecomposition μ protected absolutelyContinuous' : map X ℙ ≪ μ section HasPDF variable {_ : MeasurableSpace Ω} {X Y : Ω → E} {ℙ : Measure Ω} {μ : Measure E} theorem hasPDF_iff : HasPDF X ℙ μ ↔ AEMeasurable X ℙ ∧ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ := ⟨fun ⟨h₁, h₂, h₃⟩ ↦ ⟨h₁, h₂, h₃⟩, fun ⟨h₁, h₂, h₃⟩ ↦ ⟨h₁, h₂, h₃⟩⟩ theorem hasPDF_iff_of_aemeasurable (hX : AEMeasurable X ℙ) : HasPDF X ℙ μ ↔ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ := by rw [hasPDF_iff] simp only [hX, true_and] variable (X ℙ μ) in @[measurability] theorem HasPDF.aemeasurable [HasPDF X ℙ μ] : AEMeasurable X ℙ := HasPDF.aemeasurable' μ instance HasPDF.haveLebesgueDecomposition [HasPDF X ℙ μ] : (map X ℙ).HaveLebesgueDecomposition μ := HasPDF.haveLebesgueDecomposition' theorem HasPDF.absolutelyContinuous [HasPDF X ℙ μ] : map X ℙ ≪ μ := HasPDF.absolutelyContinuous' /-- A random variable that `HasPDF` is quasi-measure preserving. -/ theorem HasPDF.quasiMeasurePreserving_of_measurable (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E) [HasPDF X ℙ μ] (h : Measurable X) : QuasiMeasurePreserving X ℙ μ := { measurable := h absolutelyContinuous := HasPDF.absolutelyContinuous .. } theorem HasPDF.congr (hXY : X =ᵐ[ℙ] Y) [hX : HasPDF X ℙ μ] : HasPDF Y ℙ μ := ⟨(HasPDF.aemeasurable X ℙ μ).congr hXY, ℙ.map_congr hXY ▸ hX.haveLebesgueDecomposition, ℙ.map_congr hXY ▸ hX.absolutelyContinuous⟩ theorem HasPDF.congr_iff (hXY : X =ᵐ[ℙ] Y) : HasPDF X ℙ μ ↔ HasPDF Y ℙ μ := ⟨fun _ ↦ HasPDF.congr hXY, fun _ ↦ HasPDF.congr hXY.symm⟩ @[deprecated (since := "2024-10-28")] alias HasPDF.congr' := HasPDF.congr_iff /-- X `HasPDF` if there is a pdf `f` such that `map X ℙ = μ.withDensity f`. -/ theorem hasPDF_of_map_eq_withDensity (hX : AEMeasurable X ℙ) (f : E → ℝ≥0∞) (hf : AEMeasurable f μ) (h : map X ℙ = μ.withDensity f) : HasPDF X ℙ μ := by refine ⟨hX, ?_, ?_⟩ <;> rw [h] · rw [withDensity_congr_ae hf.ae_eq_mk] exact haveLebesgueDecomposition_withDensity μ hf.measurable_mk · exact withDensity_absolutelyContinuous μ f end HasPDF /-- If `X` is a random variable, then `pdf X ℙ μ` is the Radon–Nikodym derivative of the push-forward measure of `ℙ` along `X` with respect to `μ`. -/ def pdf {_ : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) : E → ℝ≥0∞ := (map X ℙ).rnDeriv μ theorem pdf_def {_ : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E} : pdf X ℙ μ = (map X ℙ).rnDeriv μ := rfl theorem pdf_of_not_aemeasurable {_ : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E} (hX : ¬AEMeasurable X ℙ) : pdf X ℙ μ =ᵐ[μ] 0 := by rw [pdf_def, map_of_not_aemeasurable hX] exact rnDeriv_zero μ theorem pdf_of_not_haveLebesgueDecomposition {_ : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E} (h : ¬(map X ℙ).HaveLebesgueDecomposition μ) : pdf X ℙ μ = 0 := rnDeriv_of_not_haveLebesgueDecomposition h theorem aemeasurable_of_pdf_ne_zero {m : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} (X : Ω → E) (h : ¬pdf X ℙ μ =ᵐ[μ] 0) : AEMeasurable X ℙ := by contrapose! h exact pdf_of_not_aemeasurable h theorem hasPDF_of_pdf_ne_zero {m : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} {X : Ω → E} (hac : map X ℙ ≪ μ) (hpdf : ¬pdf X ℙ μ =ᵐ[μ] 0) : HasPDF X ℙ μ := by refine ⟨?_, ?_, hac⟩ · exact aemeasurable_of_pdf_ne_zero X hpdf · contrapose! hpdf have := pdf_of_not_haveLebesgueDecomposition hpdf filter_upwards using congrFun this @[measurability] theorem measurable_pdf {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) : Measurable (pdf X ℙ μ) := by exact measurable_rnDeriv _ _ theorem withDensity_pdf_le_map {_ : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) : μ.withDensity (pdf X ℙ μ) ≤ map X ℙ := withDensity_rnDeriv_le _ _ theorem setLIntegral_pdf_le_map {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) (s : Set E) : ∫⁻ x in s, pdf X ℙ μ x ∂μ ≤ map X ℙ s := by apply (withDensity_apply_le _ s).trans exact withDensity_pdf_le_map _ _ _ s theorem map_eq_withDensity_pdf {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) [hX : HasPDF X ℙ μ] : map X ℙ = μ.withDensity (pdf X ℙ μ) := by rw [pdf_def, withDensity_rnDeriv_eq _ _ hX.absolutelyContinuous] theorem map_eq_setLIntegral_pdf {m : MeasurableSpace Ω} (X : Ω → E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) [hX : HasPDF X ℙ μ] {s : Set E} (hs : MeasurableSet s) : map X ℙ s = ∫⁻ x in s, pdf X ℙ μ x ∂μ := by rw [← withDensity_apply _ hs, map_eq_withDensity_pdf X ℙ μ] namespace pdf variable {m : MeasurableSpace Ω} {ℙ : Measure Ω} {μ : Measure E} protected theorem congr {X Y : Ω → E} (hXY : X =ᵐ[ℙ] Y) : pdf X ℙ μ = pdf Y ℙ μ := by rw [pdf_def, pdf_def, map_congr hXY] theorem lintegral_eq_measure_univ {X : Ω → E} [HasPDF X ℙ μ] : ∫⁻ x, pdf X ℙ μ x ∂μ = ℙ Set.univ := by rw [← setLIntegral_univ, ← map_eq_setLIntegral_pdf X ℙ μ MeasurableSet.univ, map_apply_of_aemeasurable (HasPDF.aemeasurable X ℙ μ) MeasurableSet.univ, Set.preimage_univ] theorem eq_of_map_eq_withDensity [IsFiniteMeasure ℙ] {X : Ω → E} [HasPDF X ℙ μ] (f : E → ℝ≥0∞) (hmf : AEMeasurable f μ) : map X ℙ = μ.withDensity f ↔ pdf X ℙ μ =ᵐ[μ] f := by rw [map_eq_withDensity_pdf X ℙ μ] apply withDensity_eq_iff (measurable_pdf X ℙ μ).aemeasurable hmf rw [lintegral_eq_measure_univ] exact measure_ne_top _ _ theorem eq_of_map_eq_withDensity' [SigmaFinite μ] {X : Ω → E} [HasPDF X ℙ μ] (f : E → ℝ≥0∞) (hmf : AEMeasurable f μ) : map X ℙ = μ.withDensity f ↔ pdf X ℙ μ =ᵐ[μ] f := map_eq_withDensity_pdf X ℙ μ ▸ withDensity_eq_iff_of_sigmaFinite (measurable_pdf X ℙ μ).aemeasurable hmf nonrec theorem ae_lt_top [IsFiniteMeasure ℙ] {μ : Measure E} {X : Ω → E} : ∀ᵐ x ∂μ, pdf X ℙ μ x < ∞ := rnDeriv_lt_top (map X ℙ) μ nonrec theorem ofReal_toReal_ae_eq [IsFiniteMeasure ℙ] {X : Ω → E} : (fun x => ENNReal.ofReal (pdf X ℙ μ x).toReal) =ᵐ[μ] pdf X ℙ μ := ofReal_toReal_ae_eq ae_lt_top section IntegralPDFMul /-- **The Law of the Unconscious Statistician** for nonnegative random variables. -/ theorem lintegral_pdf_mul {X : Ω → E} [HasPDF X ℙ μ] {f : E → ℝ≥0∞} (hf : AEMeasurable f μ) : ∫⁻ x, pdf X ℙ μ x * f x ∂μ = ∫⁻ x, f (X x) ∂ℙ := by rw [pdf_def, ← lintegral_map' (hf.mono_ac HasPDF.absolutelyContinuous) (HasPDF.aemeasurable X ℙ μ), lintegral_rnDeriv_mul HasPDF.absolutelyContinuous hf] variable {F : Type*} [NormedAddCommGroup F] [NormedSpace ℝ F] theorem integrable_pdf_smul_iff [IsFiniteMeasure ℙ] {X : Ω → E} [HasPDF X ℙ μ] {f : E → F} (hf : AEStronglyMeasurable f μ) : Integrable (fun x => (pdf X ℙ μ x).toReal • f x) μ ↔ Integrable (fun x => f (X x)) ℙ := by rw [← Function.comp_def, ← integrable_map_measure (hf.mono_ac HasPDF.absolutelyContinuous) (HasPDF.aemeasurable X ℙ μ), map_eq_withDensity_pdf X ℙ μ, pdf_def, integrable_rnDeriv_smul_iff HasPDF.absolutelyContinuous] rw [withDensity_rnDeriv_eq _ _ HasPDF.absolutelyContinuous] /-- **The Law of the Unconscious Statistician**: Given a random variable `X` and a measurable function `f`, `f ∘ X` is a random variable with expectation `∫ x, pdf X x • f x ∂μ` where `μ` is a measure on the codomain of `X`. -/ theorem integral_pdf_smul [IsFiniteMeasure ℙ] {X : Ω → E} [HasPDF X ℙ μ] {f : E → F} (hf : AEStronglyMeasurable f μ) : ∫ x, (pdf X ℙ μ x).toReal • f x ∂μ = ∫ x, f (X x) ∂ℙ := by rw [← integral_map (HasPDF.aemeasurable X ℙ μ) (hf.mono_ac HasPDF.absolutelyContinuous), map_eq_withDensity_pdf X ℙ μ, pdf_def, integral_rnDeriv_smul HasPDF.absolutelyContinuous, withDensity_rnDeriv_eq _ _ HasPDF.absolutelyContinuous] end IntegralPDFMul section variable {F : Type*} [MeasurableSpace F] {ν : Measure F} (X : Ω → E) [HasPDF X ℙ μ] {g : E → F} /-- A random variable that `HasPDF` transformed under a `QuasiMeasurePreserving` map also `HasPDF` if `(map g (map X ℙ)).HaveLebesgueDecomposition μ`. `quasiMeasurePreserving_hasPDF` is more useful in the case we are working with a probability measure and a real-valued random variable. -/
theorem quasiMeasurePreserving_hasPDF (hg : QuasiMeasurePreserving g μ ν) (hmap : (map g (map X ℙ)).HaveLebesgueDecomposition ν) : HasPDF (g ∘ X) ℙ ν := by have hgm : AEMeasurable g (map X ℙ) := hg.aemeasurable.mono_ac HasPDF.absolutelyContinuous rw [hasPDF_iff, ← AEMeasurable.map_map_of_aemeasurable hgm (HasPDF.aemeasurable X ℙ μ)] refine ⟨hg.measurable.comp_aemeasurable (HasPDF.aemeasurable _ _ μ), hmap, ?_⟩ exact (HasPDF.absolutelyContinuous.map hg.1).trans hg.2 theorem quasiMeasurePreserving_hasPDF' [SFinite ℙ] [SigmaFinite ν] (hg : QuasiMeasurePreserving g μ ν) : HasPDF (g ∘ X) ℙ ν :=
Mathlib/Probability/Density.lean
247
255
/- Copyright (c) 2021 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn, Sébastien Gouëzel -/ import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric import Mathlib.MeasureTheory.Group.Pointwise import Mathlib.MeasureTheory.Measure.Doubling import Mathlib.MeasureTheory.Measure.Haar.Basic import Mathlib.MeasureTheory.Measure.Lebesgue.Basic /-! # Relationship between the Haar and Lebesgue measures We prove that the Haar measure and Lebesgue measure are equal on `ℝ` and on `ℝ^ι`, in `MeasureTheory.addHaarMeasure_eq_volume` and `MeasureTheory.addHaarMeasure_eq_volume_pi`. We deduce basic properties of any Haar measure on a finite dimensional real vector space: * `map_linearMap_addHaar_eq_smul_addHaar`: a linear map rescales the Haar measure by the absolute value of its determinant. * `addHaar_preimage_linearMap` : when `f` is a linear map with nonzero determinant, the measure of `f ⁻¹' s` is the measure of `s` multiplied by the absolute value of the inverse of the determinant of `f`. * `addHaar_image_linearMap` : when `f` is a linear map, the measure of `f '' s` is the measure of `s` multiplied by the absolute value of the determinant of `f`. * `addHaar_submodule` : a strict submodule has measure `0`. * `addHaar_smul` : the measure of `r • s` is `|r| ^ dim * μ s`. * `addHaar_ball`: the measure of `ball x r` is `r ^ dim * μ (ball 0 1)`. * `addHaar_closedBall`: the measure of `closedBall x r` is `r ^ dim * μ (ball 0 1)`. * `addHaar_sphere`: spheres have zero measure. This makes it possible to associate a Lebesgue measure to an `n`-alternating map in dimension `n`. This measure is called `AlternatingMap.measure`. Its main property is `ω.measure_parallelepiped v`, stating that the associated measure of the parallelepiped spanned by vectors `v₁, ..., vₙ` is given by `|ω v|`. We also show that a Lebesgue density point `x` of a set `s` (with respect to closed balls) has density one for the rescaled copies `{x} + r • t` of a given set `t` with positive measure, in `tendsto_addHaar_inter_smul_one_of_density_one`. In particular, `s` intersects `{x} + r • t` for small `r`, see `eventually_nonempty_inter_smul_of_density_one`. Statements on integrals of functions with respect to an additive Haar measure can be found in `MeasureTheory.Measure.Haar.NormedSpace`. -/ assert_not_exists MeasureTheory.integral open TopologicalSpace Set Filter Metric Bornology open scoped ENNReal Pointwise Topology NNReal /-- The interval `[0,1]` as a compact set with non-empty interior. -/ def TopologicalSpace.PositiveCompacts.Icc01 : PositiveCompacts ℝ where carrier := Icc 0 1 isCompact' := isCompact_Icc interior_nonempty' := by simp_rw [interior_Icc, nonempty_Ioo, zero_lt_one] universe u /-- The set `[0,1]^ι` as a compact set with non-empty interior. -/ def TopologicalSpace.PositiveCompacts.piIcc01 (ι : Type*) [Finite ι] : PositiveCompacts (ι → ℝ) where carrier := pi univ fun _ => Icc 0 1 isCompact' := isCompact_univ_pi fun _ => isCompact_Icc interior_nonempty' := by simp only [interior_pi_set, Set.toFinite, interior_Icc, univ_pi_nonempty_iff, nonempty_Ioo, imp_true_iff, zero_lt_one] /-- The parallelepiped formed from the standard basis for `ι → ℝ` is `[0,1]^ι` -/ theorem Basis.parallelepiped_basisFun (ι : Type*) [Fintype ι] : (Pi.basisFun ℝ ι).parallelepiped = TopologicalSpace.PositiveCompacts.piIcc01 ι := SetLike.coe_injective <| by refine Eq.trans ?_ ((uIcc_of_le ?_).trans (Set.pi_univ_Icc _ _).symm) · classical convert parallelepiped_single (ι := ι) 1 · exact zero_le_one /-- A parallelepiped can be expressed on the standard basis. -/ theorem Basis.parallelepiped_eq_map {ι E : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedSpace ℝ E] (b : Basis ι ℝ E) : b.parallelepiped = (PositiveCompacts.piIcc01 ι).map b.equivFun.symm b.equivFunL.symm.continuous b.equivFunL.symm.isOpenMap := by classical rw [← Basis.parallelepiped_basisFun, ← Basis.parallelepiped_map] congr with x simp [Pi.single_apply] open MeasureTheory MeasureTheory.Measure theorem Basis.map_addHaar {ι E F : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedAddCommGroup F] [NormedSpace ℝ E] [NormedSpace ℝ F] [MeasurableSpace E] [MeasurableSpace F] [BorelSpace E] [BorelSpace F] [SecondCountableTopology F] [SigmaCompactSpace F] (b : Basis ι ℝ E) (f : E ≃L[ℝ] F) : map f b.addHaar = (b.map f.toLinearEquiv).addHaar := by have : IsAddHaarMeasure (map f b.addHaar) := AddEquiv.isAddHaarMeasure_map b.addHaar f.toAddEquiv f.continuous f.symm.continuous rw [eq_comm, Basis.addHaar_eq_iff, Measure.map_apply f.continuous.measurable (PositiveCompacts.isCompact _).measurableSet, Basis.coe_parallelepiped, Basis.coe_map] erw [← image_parallelepiped, f.toEquiv.preimage_image, addHaar_self] namespace MeasureTheory open Measure TopologicalSpace.PositiveCompacts Module /-! ### The Lebesgue measure is a Haar measure on `ℝ` and on `ℝ^ι`. -/ /-- The Haar measure equals the Lebesgue measure on `ℝ`. -/ theorem addHaarMeasure_eq_volume : addHaarMeasure Icc01 = volume := by convert (addHaarMeasure_unique volume Icc01).symm; simp [Icc01] /-- The Haar measure equals the Lebesgue measure on `ℝ^ι`. -/ theorem addHaarMeasure_eq_volume_pi (ι : Type*) [Fintype ι] : addHaarMeasure (piIcc01 ι) = volume := by convert (addHaarMeasure_unique volume (piIcc01 ι)).symm simp only [piIcc01, volume_pi_pi fun _ => Icc (0 : ℝ) 1, PositiveCompacts.coe_mk, Compacts.coe_mk, Finset.prod_const_one, ENNReal.ofReal_one, Real.volume_Icc, one_smul, sub_zero] theorem isAddHaarMeasure_volume_pi (ι : Type*) [Fintype ι] : IsAddHaarMeasure (volume : Measure (ι → ℝ)) := inferInstance namespace Measure /-! ### Strict subspaces have zero measure -/ open scoped Function -- required for scoped `on` notation /-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure zero. This auxiliary lemma proves this assuming additionally that the set is bounded. -/ theorem addHaar_eq_zero_of_disjoint_translates_aux {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (sb : IsBounded s) (hu : IsBounded (range u)) (hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by by_contra h apply lt_irrefl ∞ calc ∞ = ∑' _ : ℕ, μ s := (ENNReal.tsum_const_eq_top_of_ne_zero h).symm _ = ∑' n : ℕ, μ ({u n} + s) := by congr 1; ext1 n; simp only [image_add_left, measure_preimage_add, singleton_add] _ = μ (⋃ n, {u n} + s) := Eq.symm <| measure_iUnion hs fun n => by simpa only [image_add_left, singleton_add] using measurable_id.const_add _ h's _ = μ (range u + s) := by rw [← iUnion_add, iUnion_singleton_eq_range] _ < ∞ := (hu.add sb).measure_lt_top /-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure zero. -/ theorem addHaar_eq_zero_of_disjoint_translates {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (hu : IsBounded (range u)) (hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by suffices H : ∀ R, μ (s ∩ closedBall 0 R) = 0 by apply le_antisymm _ (zero_le _) calc μ s ≤ ∑' n : ℕ, μ (s ∩ closedBall 0 n) := by conv_lhs => rw [← iUnion_inter_closedBall_nat s 0] exact measure_iUnion_le _ _ = 0 := by simp only [H, tsum_zero] intro R apply addHaar_eq_zero_of_disjoint_translates_aux μ u (isBounded_closedBall.subset inter_subset_right) hu _ (h's.inter measurableSet_closedBall) refine pairwise_disjoint_mono hs fun n => ?_ exact add_subset_add Subset.rfl inter_subset_left /-- A strict vector subspace has measure zero. -/ theorem addHaar_submodule {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] (s : Submodule ℝ E) (hs : s ≠ ⊤) : μ s = 0 := by obtain ⟨x, hx⟩ : ∃ x, x ∉ s := by simpa only [Submodule.eq_top_iff', not_exists, Ne, not_forall] using hs obtain ⟨c, cpos, cone⟩ : ∃ c : ℝ, 0 < c ∧ c < 1 := ⟨1 / 2, by norm_num, by norm_num⟩ have A : IsBounded (range fun n : ℕ => c ^ n • x) := have : Tendsto (fun n : ℕ => c ^ n • x) atTop (𝓝 ((0 : ℝ) • x)) := (tendsto_pow_atTop_nhds_zero_of_lt_one cpos.le cone).smul_const x isBounded_range_of_tendsto _ this apply addHaar_eq_zero_of_disjoint_translates μ _ A _ (Submodule.closed_of_finiteDimensional s).measurableSet intro m n hmn simp only [Function.onFun, image_add_left, singleton_add, disjoint_left, mem_preimage, SetLike.mem_coe] intro y hym hyn have A : (c ^ n - c ^ m) • x ∈ s := by convert s.sub_mem hym hyn using 1 simp only [sub_smul, neg_sub_neg, add_sub_add_right_eq_sub] have H : c ^ n - c ^ m ≠ 0 := by simpa only [sub_eq_zero, Ne] using (pow_right_strictAnti₀ cpos cone).injective.ne hmn.symm have : x ∈ s := by convert s.smul_mem (c ^ n - c ^ m)⁻¹ A rw [smul_smul, inv_mul_cancel₀ H, one_smul] exact hx this /-- A strict affine subspace has measure zero. -/ theorem addHaar_affineSubspace {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] (s : AffineSubspace ℝ E) (hs : s ≠ ⊤) : μ s = 0 := by rcases s.eq_bot_or_nonempty with (rfl | hne) · rw [AffineSubspace.bot_coe, measure_empty] rw [Ne, ← AffineSubspace.direction_eq_top_iff_of_nonempty hne] at hs rcases hne with ⟨x, hx : x ∈ s⟩ simpa only [AffineSubspace.coe_direction_eq_vsub_set_right hx, vsub_eq_sub, sub_eq_add_neg, image_add_right, neg_neg, measure_preimage_add_right] using addHaar_submodule μ s.direction hs /-! ### Applying a linear map rescales Haar measure by the determinant We first prove this on `ι → ℝ`, using that this is already known for the product Lebesgue measure (thanks to matrices computations). Then, we extend this to any finite-dimensional real vector space by using a linear equiv with a space of the form `ι → ℝ`, and arguing that such a linear equiv maps Haar measure to Haar measure. -/ theorem map_linearMap_addHaar_pi_eq_smul_addHaar {ι : Type*} [Finite ι] {f : (ι → ℝ) →ₗ[ℝ] ι → ℝ} (hf : LinearMap.det f ≠ 0) (μ : Measure (ι → ℝ)) [IsAddHaarMeasure μ] : Measure.map f μ = ENNReal.ofReal (abs (LinearMap.det f)⁻¹) • μ := by cases nonempty_fintype ι /- We have already proved the result for the Lebesgue product measure, using matrices. We deduce it for any Haar measure by uniqueness (up to scalar multiplication). -/ have := addHaarMeasure_unique μ (piIcc01 ι) rw [this, addHaarMeasure_eq_volume_pi, Measure.map_smul, Real.map_linearMap_volume_pi_eq_smul_volume_pi hf, smul_comm] variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] theorem map_linearMap_addHaar_eq_smul_addHaar {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) : Measure.map f μ = ENNReal.ofReal |(LinearMap.det f)⁻¹| • μ := by -- we reduce to the case of `E = ι → ℝ`, for which we have already proved the result using -- matrices in `map_linearMap_addHaar_pi_eq_smul_addHaar`. let ι := Fin (finrank ℝ E) haveI : FiniteDimensional ℝ (ι → ℝ) := by infer_instance have : finrank ℝ E = finrank ℝ (ι → ℝ) := by simp [ι] have e : E ≃ₗ[ℝ] ι → ℝ := LinearEquiv.ofFinrankEq E (ι → ℝ) this -- next line is to avoid `g` getting reduced by `simp`. obtain ⟨g, hg⟩ : ∃ g, g = (e : E →ₗ[ℝ] ι → ℝ).comp (f.comp (e.symm : (ι → ℝ) →ₗ[ℝ] E)) := ⟨_, rfl⟩ have gdet : LinearMap.det g = LinearMap.det f := by rw [hg]; exact LinearMap.det_conj f e rw [← gdet] at hf ⊢ have fg : f = (e.symm : (ι → ℝ) →ₗ[ℝ] E).comp (g.comp (e : E →ₗ[ℝ] ι → ℝ)) := by ext x simp only [LinearEquiv.coe_coe, Function.comp_apply, LinearMap.coe_comp, LinearEquiv.symm_apply_apply, hg] simp only [fg, LinearEquiv.coe_coe, LinearMap.coe_comp] have Ce : Continuous e := (e : E →ₗ[ℝ] ι → ℝ).continuous_of_finiteDimensional have Cg : Continuous g := LinearMap.continuous_of_finiteDimensional g have Cesymm : Continuous e.symm := (e.symm : (ι → ℝ) →ₗ[ℝ] E).continuous_of_finiteDimensional rw [← map_map Cesymm.measurable (Cg.comp Ce).measurable, ← map_map Cg.measurable Ce.measurable] haveI : IsAddHaarMeasure (map e μ) := (e : E ≃+ (ι → ℝ)).isAddHaarMeasure_map μ Ce Cesymm have ecomp : e.symm ∘ e = id := by ext x; simp only [id, Function.comp_apply, LinearEquiv.symm_apply_apply] rw [map_linearMap_addHaar_pi_eq_smul_addHaar hf (map e μ), Measure.map_smul, map_map Cesymm.measurable Ce.measurable, ecomp, Measure.map_id] /-- The preimage of a set `s` under a linear map `f` with nonzero determinant has measure equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/ @[simp] theorem addHaar_preimage_linearMap {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) (s : Set E) : μ (f ⁻¹' s) = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s := calc μ (f ⁻¹' s) = Measure.map f μ s := ((f.equivOfDetNeZero hf).toContinuousLinearEquiv.toHomeomorph.toMeasurableEquiv.map_apply s).symm _ = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s := by rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]; rfl /-- The preimage of a set `s` under a continuous linear map `f` with nonzero determinant has measure equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/ @[simp] theorem addHaar_preimage_continuousLinearMap {f : E →L[ℝ] E} (hf : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0) (s : Set E) : μ (f ⁻¹' s) = ENNReal.ofReal (abs (LinearMap.det (f : E →ₗ[ℝ] E))⁻¹) * μ s := addHaar_preimage_linearMap μ hf s /-- The preimage of a set `s` under a linear equiv `f` has measure equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/ @[simp] theorem addHaar_preimage_linearEquiv (f : E ≃ₗ[ℝ] E) (s : Set E) : μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s := by have A : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0 := (LinearEquiv.isUnit_det' f).ne_zero convert addHaar_preimage_linearMap μ A s simp only [LinearEquiv.det_coe_symm] /-- The preimage of a set `s` under a continuous linear equiv `f` has measure equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/ @[simp] theorem addHaar_preimage_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) : μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s := addHaar_preimage_linearEquiv μ _ s /-- The image of a set `s` under a linear map `f` has measure equal to `μ s` times the absolute value of the determinant of `f`. -/ @[simp] theorem addHaar_image_linearMap (f : E →ₗ[ℝ] E) (s : Set E) : μ (f '' s) = ENNReal.ofReal |LinearMap.det f| * μ s := by rcases ne_or_eq (LinearMap.det f) 0 with (hf | hf) · let g := (f.equivOfDetNeZero hf).toContinuousLinearEquiv change μ (g '' s) = _ rw [ContinuousLinearEquiv.image_eq_preimage g s, addHaar_preimage_continuousLinearEquiv] congr · simp only [hf, zero_mul, ENNReal.ofReal_zero, abs_zero] have : μ (LinearMap.range f) = 0 := addHaar_submodule μ _ (LinearMap.range_lt_top_of_det_eq_zero hf).ne exact le_antisymm (le_trans (measure_mono (image_subset_range _ _)) this.le) (zero_le _) /-- The image of a set `s` under a continuous linear map `f` has measure equal to `μ s` times the absolute value of the determinant of `f`. -/ @[simp] theorem addHaar_image_continuousLinearMap (f : E →L[ℝ] E) (s : Set E) : μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s := addHaar_image_linearMap μ _ s /-- The image of a set `s` under a continuous linear equiv `f` has measure equal to `μ s` times the absolute value of the determinant of `f`. -/ @[simp] theorem addHaar_image_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) : μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s := μ.addHaar_image_linearMap (f : E →ₗ[ℝ] E) s theorem LinearMap.quasiMeasurePreserving (f : E →ₗ[ℝ] E) (hf : LinearMap.det f ≠ 0) : QuasiMeasurePreserving f μ μ := by refine ⟨f.continuous_of_finiteDimensional.measurable, ?_⟩ rw [map_linearMap_addHaar_eq_smul_addHaar μ hf] exact smul_absolutelyContinuous theorem ContinuousLinearMap.quasiMeasurePreserving (f : E →L[ℝ] E) (hf : f.det ≠ 0) : QuasiMeasurePreserving f μ μ := LinearMap.quasiMeasurePreserving μ (f : E →ₗ[ℝ] E) hf /-! ### Basic properties of Haar measures on real vector spaces -/ theorem map_addHaar_smul {r : ℝ} (hr : r ≠ 0) : Measure.map (r • ·) μ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) • μ := by let f : E →ₗ[ℝ] E := r • (1 : E →ₗ[ℝ] E) change Measure.map f μ = _ have hf : LinearMap.det f ≠ 0 := by simp only [f, mul_one, LinearMap.det_smul, Ne, MonoidHom.map_one] intro h exact hr (pow_eq_zero h) simp only [f, map_linearMap_addHaar_eq_smul_addHaar μ hf, mul_one, LinearMap.det_smul, map_one] theorem quasiMeasurePreserving_smul {r : ℝ} (hr : r ≠ 0) : QuasiMeasurePreserving (r • ·) μ μ := by refine ⟨measurable_const_smul r, ?_⟩ rw [map_addHaar_smul μ hr] exact smul_absolutelyContinuous @[simp] theorem addHaar_preimage_smul {r : ℝ} (hr : r ≠ 0) (s : Set E) : μ ((r • ·) ⁻¹' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s := calc μ ((r • ·) ⁻¹' s) = Measure.map (r • ·) μ s := ((Homeomorph.smul (isUnit_iff_ne_zero.2 hr).unit).toMeasurableEquiv.map_apply s).symm _ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s := by rw [map_addHaar_smul μ hr, coe_smul, Pi.smul_apply, smul_eq_mul] /-- Rescaling a set by a factor `r` multiplies its measure by `abs (r ^ dim)`. -/ @[simp] theorem addHaar_smul (r : ℝ) (s : Set E) : μ (r • s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by rcases ne_or_eq r 0 with (h | rfl) · rw [← preimage_smul_inv₀ h, addHaar_preimage_smul μ (inv_ne_zero h), inv_pow, inv_inv] rcases eq_empty_or_nonempty s with (rfl | hs) · simp only [measure_empty, mul_zero, smul_set_empty] rw [zero_smul_set hs, ← singleton_zero] by_cases h : finrank ℝ E = 0 · haveI : Subsingleton E := finrank_zero_iff.1 h simp only [h, one_mul, ENNReal.ofReal_one, abs_one, Subsingleton.eq_univ_of_nonempty hs, pow_zero, Subsingleton.eq_univ_of_nonempty (singleton_nonempty (0 : E))] · haveI : Nontrivial E := nontrivial_of_finrank_pos (bot_lt_iff_ne_bot.2 h) simp only [h, zero_mul, ENNReal.ofReal_zero, abs_zero, Ne, not_false_iff, zero_pow, measure_singleton] theorem addHaar_smul_of_nonneg {r : ℝ} (hr : 0 ≤ r) (s : Set E) : μ (r • s) = ENNReal.ofReal (r ^ finrank ℝ E) * μ s := by rw [addHaar_smul, abs_pow, abs_of_nonneg hr] variable {μ} {s : Set E} -- Note: We might want to rename this once we acquire the lemma corresponding to -- `MeasurableSet.const_smul` theorem NullMeasurableSet.const_smul (hs : NullMeasurableSet s μ) (r : ℝ) : NullMeasurableSet (r • s) μ := by obtain rfl | hs' := s.eq_empty_or_nonempty · simp obtain rfl | hr := eq_or_ne r 0 · simpa [zero_smul_set hs'] using nullMeasurableSet_singleton _ obtain ⟨t, ht, hst⟩ := hs refine ⟨_, ht.const_smul_of_ne_zero hr, ?_⟩ rw [← measure_symmDiff_eq_zero_iff] at hst ⊢ rw [← smul_set_symmDiff₀ hr, addHaar_smul μ, hst, mul_zero] variable (μ) @[simp] theorem addHaar_image_homothety (x : E) (r : ℝ) (s : Set E) : μ (AffineMap.homothety x r '' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := calc μ (AffineMap.homothety x r '' s) = μ ((fun y => y + x) '' (r • (fun y => y + -x) '' s)) := by simp only [← image_smul, image_image, ← sub_eq_add_neg]; rfl _ = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by simp only [image_add_right, measure_preimage_add_right, addHaar_smul] /-! We don't need to state `map_addHaar_neg` here, because it has already been proved for general Haar measures on general commutative groups. -/ /-! ### Measure of balls -/ theorem addHaar_ball_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ (ball x r) = μ (ball (0 : E) r) := by have : ball (0 : E) r = (x + ·) ⁻¹' ball x r := by simp [preimage_add_ball] rw [this, measure_preimage_add] theorem addHaar_real_ball_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ.real (ball x r) = μ.real (ball (0 : E) r) := by simp [measureReal_def, addHaar_ball_center] theorem addHaar_closedBall_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ (closedBall x r) = μ (closedBall (0 : E) r) := by have : closedBall (0 : E) r = (x + ·) ⁻¹' closedBall x r := by simp [preimage_add_closedBall] rw [this, measure_preimage_add] theorem addHaar_real_closedBall_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ.real (closedBall x r) = μ.real (closedBall (0 : E) r) := by simp [measureReal_def, addHaar_closedBall_center] theorem addHaar_ball_mul_of_pos (x : E) {r : ℝ} (hr : 0 < r) (s : ℝ) : μ (ball x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 s) := by have : ball (0 : E) (r * s) = r • ball (0 : E) s := by simp only [_root_.smul_ball hr.ne' (0 : E) s, Real.norm_eq_abs, abs_of_nonneg hr.le, smul_zero] simp only [this, addHaar_smul, abs_of_nonneg hr.le, addHaar_ball_center, abs_pow] theorem addHaar_ball_of_pos (x : E) {r : ℝ} (hr : 0 < r) : μ (ball x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 1) := by rw [← addHaar_ball_mul_of_pos μ x hr, mul_one] theorem addHaar_ball_mul [Nontrivial E] (x : E) {r : ℝ} (hr : 0 ≤ r) (s : ℝ) : μ (ball x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 s) := by rcases hr.eq_or_lt with (rfl | h) · simp only [zero_pow (finrank_pos (R := ℝ) (M := E)).ne', measure_empty, zero_mul, ENNReal.ofReal_zero, ball_zero] · exact addHaar_ball_mul_of_pos μ x h s theorem addHaar_ball [Nontrivial E] (x : E) {r : ℝ} (hr : 0 ≤ r) : μ (ball x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 1) := by rw [← addHaar_ball_mul μ x hr, mul_one] theorem addHaar_closedBall_mul_of_pos (x : E) {r : ℝ} (hr : 0 < r) (s : ℝ) : μ (closedBall x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 s) := by have : closedBall (0 : E) (r * s) = r • closedBall (0 : E) s := by simp [smul_closedBall' hr.ne' (0 : E), abs_of_nonneg hr.le] simp only [this, addHaar_smul, abs_of_nonneg hr.le, addHaar_closedBall_center, abs_pow] theorem addHaar_closedBall_mul (x : E) {r : ℝ} (hr : 0 ≤ r) {s : ℝ} (hs : 0 ≤ s) : μ (closedBall x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 s) := by have : closedBall (0 : E) (r * s) = r • closedBall (0 : E) s := by simp [smul_closedBall r (0 : E) hs, abs_of_nonneg hr] simp only [this, addHaar_smul, abs_of_nonneg hr, addHaar_closedBall_center, abs_pow]
/-- The measure of a closed ball can be expressed in terms of the measure of the closed unit ball. Use instead `addHaar_closedBall`, which uses the measure of the open unit ball as a standard form. -/ theorem addHaar_closedBall' (x : E) {r : ℝ} (hr : 0 ≤ r) : μ (closedBall x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 1) := by
Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean
466
471
/- Copyright (c) 2021 Riccardo Brasca. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Riccardo Brasca -/ import Mathlib.RingTheory.IntegralClosure.IntegrallyClosed import Mathlib.RingTheory.Trace.Basic import Mathlib.RingTheory.Norm.Basic /-! # Discriminant of a family of vectors Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define the *discriminant* of `b` as the determinant of the matrix whose `(i j)`-th element is the trace of `b i * b j`. ## Main definition * `Algebra.discr A b` : the discriminant of `b : ι → B`. ## Main results * `Algebra.discr_zero_of_not_linearIndependent` : if `b` is not linear independent, then `Algebra.discr A b = 0`. * `Algebra.discr_of_matrix_vecMul` and `Algebra.discr_of_matrix_mulVec` : formulas relating `Algebra.discr A ι b` with `Algebra.discr A (b ᵥ* P.map (algebraMap A B))` and `Algebra.discr A (P.map (algebraMap A B) *ᵥ b)`. * `Algebra.discr_not_zero_of_basis` : over a field, if `b` is a basis, then `Algebra.discr K b ≠ 0`. * `Algebra.discr_eq_det_embeddingsMatrixReindex_pow_two` : if `L/K` is a field extension and `b : ι → L`, then `discr K b` is the square of the determinant of the matrix whose `(i, j)` coefficient is `σⱼ (b i)`, where `σⱼ : L →ₐ[K] E` is the embedding in an algebraically closed field `E` corresponding to `j : ι` via a bijection `e : ι ≃ (L →ₐ[K] E)`. * `Algebra.discr_powerBasis_eq_prod` : the discriminant of a power basis. * `Algebra.discr_isIntegral` : if `K` and `L` are fields and `IsScalarTower R K L`, if `b : ι → L` satisfies `∀ i, IsIntegral R (b i)`, then `IsIntegral R (discr K b)`. * `Algebra.discr_mul_isIntegral_mem_adjoin` : let `K` be the fraction field of an integrally closed domain `R` and let `L` be a finite separable extension of `K`. Let `B : PowerBasis K L` be such that `IsIntegral R B.gen`. Then for all, `z : L` we have `(discr K B.basis) • z ∈ adjoin R ({B.gen} : Set L)`. ## Implementation details Our definition works for any `A`-algebra `B`, but note that if `B` is not free as an `A`-module, then `trace A B = 0` by definition, so `discr A b = 0` for any `b`. -/ universe u v w z open scoped Matrix open Matrix Module Fintype Polynomial Finset IntermediateField namespace Algebra variable (A : Type u) {B : Type v} (C : Type z) {ι : Type w} [DecidableEq ι] variable [CommRing A] [CommRing B] [Algebra A B] [CommRing C] [Algebra A C] section Discr /-- Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define `discr A ι b` as the determinant of `traceMatrix A ι b`. -/ -- Porting note: using `[DecidableEq ι]` instead of `by classical...` did not work in -- mathlib3. noncomputable def discr (A : Type u) {B : Type v} [CommRing A] [CommRing B] [Algebra A B] [Fintype ι] (b : ι → B) := (traceMatrix A b).det theorem discr_def [Fintype ι] (b : ι → B) : discr A b = (traceMatrix A b).det := rfl variable {A C} in /-- Mapping a family of vectors along an `AlgEquiv` preserves the discriminant. -/ theorem discr_eq_discr_of_algEquiv [Fintype ι] (b : ι → B) (f : B ≃ₐ[A] C) : Algebra.discr A b = Algebra.discr A (f ∘ b) := by rw [discr_def]; congr; ext
simp_rw [traceMatrix_apply, traceForm_apply, Function.comp, ← map_mul f, trace_eq_of_algEquiv] variable {ι' : Type*} [Fintype ι'] [Fintype ι] [DecidableEq ι']
Mathlib/RingTheory/Discriminant.lean
76
79
/- Copyright (c) 2021 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison -/ import Mathlib.Algebra.Group.Hom.Defs import Mathlib.Algebra.Group.Pi.Basic /-! # Dependent-typed matrices -/ universe u u' v w z /-- `DMatrix m n` is the type of dependently typed matrices whose rows are indexed by the type `m` and whose columns are indexed by the type `n`. In most applications `m` and `n` are finite types. -/ def DMatrix (m : Type u) (n : Type u') (α : m → n → Type v) : Type max u u' v := ∀ i j, α i j variable {m n : Type*} variable {α : m → n → Type v} namespace DMatrix section Ext variable {M N : DMatrix m n α} theorem ext_iff : (∀ i j, M i j = N i j) ↔ M = N := ⟨fun h => funext fun i => funext <| h i, fun h => by simp [h]⟩
@[ext]
Mathlib/Data/Matrix/DMatrix.lean
35
36
/- Copyright (c) 2021 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash, Yury Kudryashov -/ import Mathlib.Topology.CompactOpen import Mathlib.Topology.LocallyFinite import Mathlib.Topology.Maps.Proper.Basic import Mathlib.Topology.UniformSpace.UniformConvergenceTopology import Mathlib.Topology.UniformSpace.Compact /-! # Compact convergence (uniform convergence on compact sets) Given a topological space `α` and a uniform space `β` (e.g., a metric space or a topological group), the space of continuous maps `C(α, β)` carries a natural uniform space structure. We define this uniform space structure in this file and also prove its basic properties. ## Main definitions - `ContinuousMap.toUniformOnFunIsCompact`: natural embedding of `C(α, β)` into the space `α →ᵤ[{K | IsCompact K}] β` of all maps `α → β` with the uniform space structure of uniform convergence on compacts. - `ContinuousMap.compactConvergenceUniformSpace`: the `UniformSpace` structure on `C(α, β)` induced by the map above. ## Main results * `ContinuousMap.mem_compactConvergence_entourage_iff`: a characterisation of the entourages of `C(α, β)`. The entourages are generated by the following sets. Given `K : Set α` and `V : Set (β × β)`, let `E(K, V) : Set (C(α, β) × C(α, β))` be the set of pairs of continuous functions `α → β` which are `V`-close on `K`: $$ E(K, V) = \{ (f, g) | ∀ (x ∈ K), (f x, g x) ∈ V \}. $$ Then the sets `E(K, V)` for all compact sets `K` and all entourages `V` form a basis of entourages of `C(α, β)`. As usual, this basis of entourages provides a basis of neighbourhoods by fixing `f`, see `nhds_basis_uniformity'`. * `Filter.HasBasis.compactConvergenceUniformity`: a similar statement that uses a basis of entourages of `β` instead of all entourages. It is useful, e.g., if `β` is a metric space. * `ContinuousMap.tendsto_iff_forall_isCompact_tendstoUniformlyOn`: a sequence of functions `Fₙ` in `C(α, β)` converges in the compact-open topology to some `f` iff `Fₙ` converges to `f` uniformly on each compact subset `K` of `α`. * Topology induced by the uniformity described above agrees with the compact-open topology. This is essentially the same as `ContinuousMap.tendsto_iff_forall_isCompact_tendstoUniformlyOn`. This fact is not available as a separate theorem. Instead, we override the projection of `ContinuousMap.compactConvergenceUniformity` to `TopologicalSpace` to be `ContinuousMap.compactOpen` and prove that they agree, see Note [forgetful inheritance] and implementation notes below. * `ContinuousMap.tendsto_iff_tendstoLocallyUniformly`: on a weakly locally compact space, a sequence of functions `Fₙ` in `C(α, β)` converges to some `f` iff `Fₙ` converges to `f` locally uniformly. * `ContinuousMap.tendsto_iff_tendstoUniformly`: on a compact space, a sequence of functions `Fₙ` in `C(α, β)` converges to some `f` iff `Fₙ` converges to `f` uniformly. ## Implementation details For technical reasons (see Note [forgetful inheritance]), instead of defining a `UniformSpace C(α, β)` structure and proving in a theorem that it agrees with the compact-open topology, we override the projection right in the definition, so that the resulting instance uses the compact-open topology. ## TODO * Results about uniformly continuous functions `γ → C(α, β)` and uniform limits of sequences `ι → γ → C(α, β)`. -/ open Filter Set Topology UniformSpace open scoped Uniformity UniformConvergence universe u₁ u₂ u₃ variable {α : Type u₁} {β : Type u₂} [TopologicalSpace α] [UniformSpace β] variable (K : Set α) (V : Set (β × β)) (f : C(α, β)) namespace ContinuousMap /-- Compact-open topology on `C(α, β)` agrees with the topology of uniform convergence on compacts: a family of continuous functions `F i` tends to `f` in the compact-open topology if and only if the `F i` tends to `f` uniformly on all compact sets. -/ theorem tendsto_iff_forall_isCompact_tendstoUniformlyOn {ι : Type u₃} {p : Filter ι} {F : ι → C(α, β)} {f} : Tendsto F p (𝓝 f) ↔ ∀ K, IsCompact K → TendstoUniformlyOn (fun i a => F i a) f p K := by rw [tendsto_nhds_compactOpen] constructor · -- Let us prove that convergence in the compact-open topology -- implies uniform convergence on compacts. -- Consider a compact set `K` intro h K hK -- Since `K` is compact, it suffices to prove locally uniform convergence rw [← tendstoLocallyUniformlyOn_iff_tendstoUniformlyOn_of_compact hK] -- Now choose an entourage `U` in the codomain and a point `x ∈ K`. intro U hU x _ -- Choose an open symmetric entourage `V` such that `V ○ V ⊆ U`. rcases comp_open_symm_mem_uniformity_sets hU with ⟨V, hV, hVo, hVsymm, hVU⟩ -- Then choose a closed entourage `W ⊆ V` rcases mem_uniformity_isClosed hV with ⟨W, hW, hWc, hWU⟩ -- Consider `s = {y ∈ K | (f x, f y) ∈ W}` set s := K ∩ f ⁻¹' ball (f x) W -- This is a neighbourhood of `x` within `K`, because `W` is an entourage. have hnhds : s ∈ 𝓝[K] x := inter_mem_nhdsWithin _ <| f.continuousAt _ (ball_mem_nhds _ hW) -- This set is compact because it is an intersection of `K` -- with a closed set `{y | (f x, f y) ∈ W} = f ⁻¹' UniformSpace.ball (f x) W` have hcomp : IsCompact s := hK.inter_right <| (isClosed_ball _ hWc).preimage f.continuous -- `f` maps `s` to the open set `ball (f x) V = {z | (f x, z) ∈ V}` have hmaps : MapsTo f s (ball (f x) V) := fun x hx ↦ hWU hx.2 use s, hnhds -- Continuous maps `F i` in a neighbourhood of `f` map `s` to `ball (f x) V` as well. refine (h s hcomp _ (isOpen_ball _ hVo) hmaps).mono fun g hg y hy ↦ ?_ -- Then for `y ∈ s` we have `(f y, f x) ∈ V` and `(f x, F i y) ∈ V`, thus `(f y, F i y) ∈ U` exact hVU ⟨f x, hVsymm.mk_mem_comm.2 <| hmaps hy, hg hy⟩ · -- Now we prove that uniform convergence on compacts -- implies convergence in the compact-open topology -- Consider a compact set `K`, an open set `U`, and a continuous map `f` that maps `K` to `U` intro h K hK U hU hf -- Due to Lebesgue number lemma, there exists an entourage `V` -- such that `U` includes the `V`-thickening of `f '' K`. rcases lebesgue_number_of_compact_open (hK.image (map_continuous f)) hU hf.image_subset with ⟨V, hV, -, hVf⟩ -- Then any continuous map that is uniformly `V`-close to `f` on `K` -- maps `K` to `U` as well filter_upwards [h K hK V hV] with g hg x hx using hVf _ (mem_image_of_mem f hx) (hg x hx) @[deprecated (since := "2024-11-19")] alias tendsto_iff_forall_compact_tendstoUniformlyOn := tendsto_iff_forall_isCompact_tendstoUniformlyOn /-- Interpret a bundled continuous map as an element of `α →ᵤ[{K | IsCompact K}] β`. We use this map to induce the `UniformSpace` structure on `C(α, β)`. -/ def toUniformOnFunIsCompact (f : C(α, β)) : α →ᵤ[{K | IsCompact K}] β := UniformOnFun.ofFun {K | IsCompact K} f @[simp] theorem toUniformOnFun_toFun (f : C(α, β)) : UniformOnFun.toFun _ f.toUniformOnFunIsCompact = f := rfl theorem range_toUniformOnFunIsCompact : range (toUniformOnFunIsCompact) = {f : UniformOnFun α β {K | IsCompact K} | Continuous f} := Set.ext fun f ↦ ⟨fun g ↦ g.choose_spec ▸ g.choose.2, fun hf ↦ ⟨⟨f, hf⟩, rfl⟩⟩ open UniformSpace in /-- Uniform space structure on `C(α, β)`. The uniformity comes from `α →ᵤ[{K | IsCompact K}] β` (i.e., `UniformOnFun α β {K | IsCompact K}`) which defines topology of uniform convergence on compact sets. We use `ContinuousMap.tendsto_iff_forall_isCompact_tendstoUniformlyOn` to show that the induced topology agrees with the compact-open topology and replace the topology with `compactOpen` to avoid non-defeq diamonds, see Note [forgetful inheritance]. -/ instance compactConvergenceUniformSpace : UniformSpace C(α, β) := .replaceTopology (.comap toUniformOnFunIsCompact inferInstance) <| by refine TopologicalSpace.ext_nhds fun f ↦ eq_of_forall_le_iff fun l ↦ ?_ simp_rw [← tendsto_id', tendsto_iff_forall_isCompact_tendstoUniformlyOn, nhds_induced, tendsto_comap_iff, UniformOnFun.tendsto_iff_tendstoUniformlyOn] rfl theorem isUniformEmbedding_toUniformOnFunIsCompact : IsUniformEmbedding (toUniformOnFunIsCompact : C(α, β) → α →ᵤ[{K | IsCompact K}] β) where comap_uniformity := rfl injective := DFunLike.coe_injective -- The following definitions and theorems -- used to be a part of the construction of the `UniformSpace C(α, β)` structure -- before it was migrated to `UniformOnFun` theorem _root_.Filter.HasBasis.compactConvergenceUniformity {ι : Type*} {pi : ι → Prop} {s : ι → Set (β × β)} (h : (𝓤 β).HasBasis pi s) : HasBasis (𝓤 C(α, β)) (fun p : Set α × ι => IsCompact p.1 ∧ pi p.2) fun p => { fg : C(α, β) × C(α, β) | ∀ x ∈ p.1, (fg.1 x, fg.2 x) ∈ s p.2 } := by rw [← isUniformEmbedding_toUniformOnFunIsCompact.comap_uniformity] exact .comap _ <| UniformOnFun.hasBasis_uniformity_of_basis _ _ {K | IsCompact K} ⟨∅, isCompact_empty⟩ (directedOn_of_sup_mem fun _ _ ↦ IsCompact.union) h theorem hasBasis_compactConvergenceUniformity : HasBasis (𝓤 C(α, β)) (fun p : Set α × Set (β × β) => IsCompact p.1 ∧ p.2 ∈ 𝓤 β) fun p => { fg : C(α, β) × C(α, β) | ∀ x ∈ p.1, (fg.1 x, fg.2 x) ∈ p.2 } := (basis_sets _).compactConvergenceUniformity theorem mem_compactConvergence_entourage_iff (X : Set (C(α, β) × C(α, β))) : X ∈ 𝓤 C(α, β) ↔ ∃ (K : Set α) (V : Set (β × β)), IsCompact K ∧ V ∈ 𝓤 β ∧ { fg : C(α, β) × C(α, β) | ∀ x ∈ K, (fg.1 x, fg.2 x) ∈ V } ⊆ X := by simp [hasBasis_compactConvergenceUniformity.mem_iff, and_assoc]
/-- If `K` is a compact exhaustion of `α` and `V i` bounded by `p i` is a basis of entourages of `β`, then `fun (n, i) ↦ {(f, g) | ∀ x ∈ K n, (f x, g x) ∈ V i}` bounded by `p i` is a basis of entourages of `C(α, β)`. -/ theorem _root_.CompactExhaustion.hasBasis_compactConvergenceUniformity {ι : Type*} {p : ι → Prop} {V : ι → Set (β × β)} (K : CompactExhaustion α) (hb : (𝓤 β).HasBasis p V) : HasBasis (𝓤 C(α, β)) (fun i : ℕ × ι ↦ p i.2) fun i ↦
Mathlib/Topology/UniformSpace/CompactConvergence.lean
203
209
/- 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.FieldTheory.Finiteness import Mathlib.LinearAlgebra.AffineSpace.Basis import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas /-! # Finite-dimensional subspaces of affine spaces. This file provides a few results relating to finite-dimensional subspaces of affine spaces. ## Main definitions * `Collinear` defines collinear sets of points as those that span a subspace of dimension at most 1. -/ noncomputable section open Affine open scoped Finset section AffineSpace' variable (k : Type*) {V : Type*} {P : Type*} variable {ι : Type*} open AffineSubspace Module variable [DivisionRing k] [AddCommGroup V] [Module k V] [AffineSpace V P] /-- The `vectorSpan` of a finite set is finite-dimensional. -/ theorem finiteDimensional_vectorSpan_of_finite {s : Set P} (h : Set.Finite s) : FiniteDimensional k (vectorSpan k s) := .span_of_finite k <| h.vsub h /-- The vector span of a singleton is finite-dimensional. -/ instance finiteDimensional_vectorSpan_singleton (p : P) : FiniteDimensional k (vectorSpan k {p}) := finiteDimensional_vectorSpan_of_finite _ (Set.finite_singleton p) /-- The `vectorSpan` of a family indexed by a `Fintype` is finite-dimensional. -/ instance finiteDimensional_vectorSpan_range [Finite ι] (p : ι → P) : FiniteDimensional k (vectorSpan k (Set.range p)) := finiteDimensional_vectorSpan_of_finite k (Set.finite_range _) /-- The `vectorSpan` of a subset of a family indexed by a `Fintype` is finite-dimensional. -/ instance finiteDimensional_vectorSpan_image_of_finite [Finite ι] (p : ι → P) (s : Set ι) : FiniteDimensional k (vectorSpan k (p '' s)) := finiteDimensional_vectorSpan_of_finite k (Set.toFinite _) /-- The direction of the affine span of a finite set is finite-dimensional. -/ theorem finiteDimensional_direction_affineSpan_of_finite {s : Set P} (h : Set.Finite s) : FiniteDimensional k (affineSpan k s).direction := (direction_affineSpan k s).symm ▸ finiteDimensional_vectorSpan_of_finite k h /-- The direction of the affine span of a singleton is finite-dimensional. -/ instance finiteDimensional_direction_affineSpan_singleton (p : P) : FiniteDimensional k (affineSpan k {p}).direction := by rw [direction_affineSpan] infer_instance /-- The direction of the affine span of a family indexed by a `Fintype` is finite-dimensional. -/ instance finiteDimensional_direction_affineSpan_range [Finite ι] (p : ι → P) : FiniteDimensional k (affineSpan k (Set.range p)).direction := finiteDimensional_direction_affineSpan_of_finite k (Set.finite_range _) /-- The direction of the affine span of a subset of a family indexed by a `Fintype` is finite-dimensional. -/ instance finiteDimensional_direction_affineSpan_image_of_finite [Finite ι] (p : ι → P) (s : Set ι) : FiniteDimensional k (affineSpan k (p '' s)).direction := finiteDimensional_direction_affineSpan_of_finite k (Set.toFinite _) /-- An affine-independent family of points in a finite-dimensional affine space is finite. -/ theorem finite_of_fin_dim_affineIndependent [FiniteDimensional k V] {p : ι → P} (hi : AffineIndependent k p) : Finite ι := by nontriviality ι; inhabit ι rw [affineIndependent_iff_linearIndependent_vsub k p default] at hi letI : IsNoetherian k V := IsNoetherian.iff_fg.2 inferInstance exact (Set.finite_singleton default).finite_of_compl (Set.finite_coe_iff.1 hi.finite_of_isNoetherian) /-- An affine-independent subset of a finite-dimensional affine space is finite. -/ theorem finite_set_of_fin_dim_affineIndependent [FiniteDimensional k V] {s : Set ι} {f : s → P} (hi : AffineIndependent k f) : s.Finite := @Set.toFinite _ s (finite_of_fin_dim_affineIndependent k hi) variable {k} /-- The `vectorSpan` of a finite subset of an affinely independent family has dimension one less than its cardinality. -/ theorem AffineIndependent.finrank_vectorSpan_image_finset [DecidableEq P] {p : ι → P} (hi : AffineIndependent k p) {s : Finset ι} {n : ℕ} (hc : #s = n + 1) : finrank k (vectorSpan k (s.image p : Set P)) = n := by classical have hi' := hi.range.mono (Set.image_subset_range p ↑s) have hc' : #(s.image p) = n + 1 := by rwa [s.card_image_of_injective hi.injective] have hn : (s.image p).Nonempty := by simp [hc', ← Finset.card_pos] rcases hn with ⟨p₁, hp₁⟩ have hp₁' : p₁ ∈ p '' s := by simpa using hp₁ rw [affineIndependent_set_iff_linearIndependent_vsub k hp₁', ← Finset.coe_singleton, ← Finset.coe_image, ← Finset.coe_sdiff, Finset.sdiff_singleton_eq_erase, ← Finset.coe_image] at hi' have hc : #(((s.image p).erase p₁).image (· -ᵥ p₁)) = n := by rw [Finset.card_image_of_injective _ (vsub_left_injective _), Finset.card_erase_of_mem hp₁] exact Nat.pred_eq_of_eq_succ hc' rwa [vectorSpan_eq_span_vsub_finset_right_ne k hp₁, finrank_span_finset_eq_card, hc] /-- The `vectorSpan` of a finite affinely independent family has dimension one less than its cardinality. -/ theorem AffineIndependent.finrank_vectorSpan [Fintype ι] {p : ι → P} (hi : AffineIndependent k p) {n : ℕ} (hc : Fintype.card ι = n + 1) : finrank k (vectorSpan k (Set.range p)) = n := by classical rw [← Finset.card_univ] at hc rw [← Set.image_univ, ← Finset.coe_univ, ← Finset.coe_image] exact hi.finrank_vectorSpan_image_finset hc /-- The `vectorSpan` of a finite affinely independent family has dimension one less than its cardinality. -/ lemma AffineIndependent.finrank_vectorSpan_add_one [Fintype ι] [Nonempty ι] {p : ι → P} (hi : AffineIndependent k p) : finrank k (vectorSpan k (Set.range p)) + 1 = Fintype.card ι := by rw [hi.finrank_vectorSpan (tsub_add_cancel_of_le _).symm, tsub_add_cancel_of_le] <;> exact Fintype.card_pos /-- The `vectorSpan` of a finite affinely independent family whose cardinality is one more than that of the finite-dimensional space is `⊤`. -/ theorem AffineIndependent.vectorSpan_eq_top_of_card_eq_finrank_add_one [FiniteDimensional k V] [Fintype ι] {p : ι → P} (hi : AffineIndependent k p) (hc : Fintype.card ι = finrank k V + 1) : vectorSpan k (Set.range p) = ⊤ := Submodule.eq_top_of_finrank_eq <| hi.finrank_vectorSpan hc variable (k) /-- The `vectorSpan` of `n + 1` points in an indexed family has dimension at most `n`. -/ theorem finrank_vectorSpan_image_finset_le [DecidableEq P] (p : ι → P) (s : Finset ι) {n : ℕ} (hc : #s = n + 1) : finrank k (vectorSpan k (s.image p : Set P)) ≤ n := by classical have hn : (s.image p).Nonempty := by rw [Finset.image_nonempty, ← Finset.card_pos, hc] apply Nat.succ_pos rcases hn with ⟨p₁, hp₁⟩ rw [vectorSpan_eq_span_vsub_finset_right_ne k hp₁] refine le_trans (finrank_span_finset_le_card (((s.image p).erase p₁).image fun p => p -ᵥ p₁)) ?_ rw [Finset.card_image_of_injective _ (vsub_left_injective p₁), Finset.card_erase_of_mem hp₁, tsub_le_iff_right, ← hc] apply Finset.card_image_le /-- The `vectorSpan` of an indexed family of `n + 1` points has dimension at most `n`. -/ theorem finrank_vectorSpan_range_le [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 1) : finrank k (vectorSpan k (Set.range p)) ≤ n := by classical rw [← Set.image_univ, ← Finset.coe_univ, ← Finset.coe_image] rw [← Finset.card_univ] at hc exact finrank_vectorSpan_image_finset_le _ _ _ hc /-- The `vectorSpan` of an indexed family of `n + 1` points has dimension at most `n`. -/ lemma finrank_vectorSpan_range_add_one_le [Fintype ι] [Nonempty ι] (p : ι → P) : finrank k (vectorSpan k (Set.range p)) + 1 ≤ Fintype.card ι := (le_tsub_iff_right <| Nat.succ_le_iff.2 Fintype.card_pos).1 <| finrank_vectorSpan_range_le _ _ (tsub_add_cancel_of_le <| Nat.succ_le_iff.2 Fintype.card_pos).symm /-- `n + 1` points are affinely independent if and only if their `vectorSpan` has dimension `n`. -/ theorem affineIndependent_iff_finrank_vectorSpan_eq [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 1) : AffineIndependent k p ↔ finrank k (vectorSpan k (Set.range p)) = n := by classical have hn : Nonempty ι := by simp [← Fintype.card_pos_iff, hc] obtain ⟨i₁⟩ := hn rw [affineIndependent_iff_linearIndependent_vsub _ _ i₁, linearIndependent_iff_card_eq_finrank_span, eq_comm, vectorSpan_range_eq_span_range_vsub_right_ne k p i₁, Set.finrank] rw [← Finset.card_univ] at hc rw [Fintype.subtype_card] simp [Finset.filter_ne', Finset.card_erase_of_mem, hc] /-- `n + 1` points are affinely independent if and only if their `vectorSpan` has dimension at least `n`. -/ theorem affineIndependent_iff_le_finrank_vectorSpan [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 1) : AffineIndependent k p ↔ n ≤ finrank k (vectorSpan k (Set.range p)) := by rw [affineIndependent_iff_finrank_vectorSpan_eq k p hc] constructor · rintro rfl rfl · exact fun hle => le_antisymm (finrank_vectorSpan_range_le k p hc) hle /-- `n + 2` points are affinely independent if and only if their `vectorSpan` does not have dimension at most `n`. -/ theorem affineIndependent_iff_not_finrank_vectorSpan_le [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 2) : AffineIndependent k p ↔ ¬finrank k (vectorSpan k (Set.range p)) ≤ n := by rw [affineIndependent_iff_le_finrank_vectorSpan k p hc, ← Nat.lt_iff_add_one_le, lt_iff_not_ge] /-- `n + 2` points have a `vectorSpan` with dimension at most `n` if and only if they are not affinely independent. -/ theorem finrank_vectorSpan_le_iff_not_affineIndependent [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 2) : finrank k (vectorSpan k (Set.range p)) ≤ n ↔ ¬AffineIndependent k p := (not_iff_comm.1 (affineIndependent_iff_not_finrank_vectorSpan_le k p hc).symm).symm variable {k} lemma AffineIndependent.card_le_finrank_succ [Fintype ι] {p : ι → P} (hp : AffineIndependent k p) : Fintype.card ι ≤ Module.finrank k (vectorSpan k (Set.range p)) + 1 := by cases isEmpty_or_nonempty ι · simp [Fintype.card_eq_zero] rw [← tsub_le_iff_right] exact (affineIndependent_iff_le_finrank_vectorSpan _ _ (tsub_add_cancel_of_le <| Nat.one_le_iff_ne_zero.2 Fintype.card_ne_zero).symm).1 hp open Finset in /-- If an affine independent finset is contained in the affine span of another finset, then its cardinality is at most the cardinality of that finset. -/ lemma AffineIndependent.card_le_card_of_subset_affineSpan {s t : Finset V} (hs : AffineIndependent k ((↑) : s → V)) (hst : (s : Set V) ⊆ affineSpan k (t : Set V)) : #s ≤ #t := by obtain rfl | hs' := s.eq_empty_or_nonempty · simp obtain rfl | ht' := t.eq_empty_or_nonempty · simpa [Set.subset_empty_iff] using hst have := hs'.to_subtype have := ht'.to_set.to_subtype have direction_le := AffineSubspace.direction_le (affineSpan_mono k hst) rw [AffineSubspace.affineSpan_coe, direction_affineSpan, direction_affineSpan, ← @Subtype.range_coe _ (s : Set V), ← @Subtype.range_coe _ (t : Set V)] at direction_le have finrank_le := add_le_add_right (Submodule.finrank_mono direction_le) 1 -- We use `erw` to elide the difference between `↥s` and `↥(s : Set V)}` erw [hs.finrank_vectorSpan_add_one] at finrank_le simpa using finrank_le.trans <| finrank_vectorSpan_range_add_one_le _ _ open Finset in /-- If the affine span of an affine independent finset is strictly contained in the affine span of another finset, then its cardinality is strictly less than the cardinality of that finset. -/ lemma AffineIndependent.card_lt_card_of_affineSpan_lt_affineSpan {s t : Finset V} (hs : AffineIndependent k ((↑) : s → V)) (hst : affineSpan k (s : Set V) < affineSpan k (t : Set V)) : #s < #t := by obtain rfl | hs' := s.eq_empty_or_nonempty · simpa [card_pos] using hst obtain rfl | ht' := t.eq_empty_or_nonempty · simp [Set.subset_empty_iff] at hst have := hs'.to_subtype have := ht'.to_set.to_subtype have dir_lt := AffineSubspace.direction_lt_of_nonempty (k := k) hst <| hs'.to_set.affineSpan k rw [direction_affineSpan, direction_affineSpan, ← @Subtype.range_coe _ (s : Set V), ← @Subtype.range_coe _ (t : Set V)] at dir_lt have finrank_lt := add_lt_add_right (Submodule.finrank_lt_finrank_of_lt dir_lt) 1 -- We use `erw` to elide the difference between `↥s` and `↥(s : Set V)}` erw [hs.finrank_vectorSpan_add_one] at finrank_lt simpa using finrank_lt.trans_le <| finrank_vectorSpan_range_add_one_le _ _ /-- If the `vectorSpan` of a finite subset of an affinely independent family lies in a submodule with dimension one less than its cardinality, it equals that submodule. -/ theorem AffineIndependent.vectorSpan_image_finset_eq_of_le_of_card_eq_finrank_add_one [DecidableEq P] {p : ι → P} (hi : AffineIndependent k p) {s : Finset ι} {sm : Submodule k V} [FiniteDimensional k sm] (hle : vectorSpan k (s.image p : Set P) ≤ sm) (hc : #s = finrank k sm + 1) : vectorSpan k (s.image p : Set P) = sm := Submodule.eq_of_le_of_finrank_eq hle <| hi.finrank_vectorSpan_image_finset hc /-- If the `vectorSpan` of a finite affinely independent family lies in a submodule with dimension one less than its cardinality, it equals that submodule. -/ theorem AffineIndependent.vectorSpan_eq_of_le_of_card_eq_finrank_add_one [Fintype ι] {p : ι → P} (hi : AffineIndependent k p) {sm : Submodule k V} [FiniteDimensional k sm] (hle : vectorSpan k (Set.range p) ≤ sm) (hc : Fintype.card ι = finrank k sm + 1) : vectorSpan k (Set.range p) = sm := Submodule.eq_of_le_of_finrank_eq hle <| hi.finrank_vectorSpan hc /-- If the `affineSpan` of a finite subset of an affinely independent family lies in an affine subspace whose direction has dimension one less than its cardinality, it equals that subspace. -/ theorem AffineIndependent.affineSpan_image_finset_eq_of_le_of_card_eq_finrank_add_one [DecidableEq P] {p : ι → P} (hi : AffineIndependent k p) {s : Finset ι} {sp : AffineSubspace k P} [FiniteDimensional k sp.direction] (hle : affineSpan k (s.image p : Set P) ≤ sp) (hc : #s = finrank k sp.direction + 1) : affineSpan k (s.image p : Set P) = sp := by have hn : s.Nonempty := by rw [← Finset.card_pos, hc] apply Nat.succ_pos refine eq_of_direction_eq_of_nonempty_of_le ?_ ((hn.image p).to_set.affineSpan k) hle have hd := direction_le hle rw [direction_affineSpan] at hd ⊢ exact hi.vectorSpan_image_finset_eq_of_le_of_card_eq_finrank_add_one hd hc /-- If the `affineSpan` of a finite affinely independent family lies in an affine subspace whose direction has dimension one less than its cardinality, it equals that subspace. -/ theorem AffineIndependent.affineSpan_eq_of_le_of_card_eq_finrank_add_one [Fintype ι] {p : ι → P} (hi : AffineIndependent k p) {sp : AffineSubspace k P} [FiniteDimensional k sp.direction] (hle : affineSpan k (Set.range p) ≤ sp) (hc : Fintype.card ι = finrank k sp.direction + 1) : affineSpan k (Set.range p) = sp := by classical rw [← Finset.card_univ] at hc rw [← Set.image_univ, ← Finset.coe_univ, ← Finset.coe_image] at hle ⊢ exact hi.affineSpan_image_finset_eq_of_le_of_card_eq_finrank_add_one hle hc /-- The `affineSpan` of a finite affinely independent family is `⊤` iff the family's cardinality is one more than that of the finite-dimensional space. -/ theorem AffineIndependent.affineSpan_eq_top_iff_card_eq_finrank_add_one [FiniteDimensional k V] [Fintype ι] {p : ι → P} (hi : AffineIndependent k p) : affineSpan k (Set.range p) = ⊤ ↔ Fintype.card ι = finrank k V + 1 := by constructor · intro h_tot let n := Fintype.card ι - 1 have hn : Fintype.card ι = n + 1 := (Nat.succ_pred_eq_of_pos (card_pos_of_affineSpan_eq_top k V P h_tot)).symm rw [hn, ← finrank_top, ← (vectorSpan_eq_top_of_affineSpan_eq_top k V P) h_tot, ← hi.finrank_vectorSpan hn] · intro hc rw [← finrank_top, ← direction_top k V P] at hc exact hi.affineSpan_eq_of_le_of_card_eq_finrank_add_one le_top hc theorem Affine.Simplex.span_eq_top [FiniteDimensional k V] {n : ℕ} (T : Affine.Simplex k V n) (hrank : finrank k V = n) : affineSpan k (Set.range T.points) = ⊤ := by rw [AffineIndependent.affineSpan_eq_top_iff_card_eq_finrank_add_one T.independent, Fintype.card_fin, hrank] /-- The `vectorSpan` of adding a point to a finite-dimensional subspace is finite-dimensional. -/ instance finiteDimensional_vectorSpan_insert (s : AffineSubspace k P) [FiniteDimensional k s.direction] (p : P) : FiniteDimensional k (vectorSpan k (insert p (s : Set P))) := by rw [← direction_affineSpan, ← affineSpan_insert_affineSpan] rcases (s : Set P).eq_empty_or_nonempty with (hs | ⟨p₀, hp₀⟩) · rw [coe_eq_bot_iff] at hs rw [hs, bot_coe, span_empty, bot_coe, direction_affineSpan] convert finiteDimensional_bot k V <;> simp · rw [affineSpan_coe, direction_affineSpan_insert hp₀] infer_instance /-- The direction of the affine span of adding a point to a finite-dimensional subspace is finite-dimensional. -/ instance finiteDimensional_direction_affineSpan_insert (s : AffineSubspace k P) [FiniteDimensional k s.direction] (p : P) : FiniteDimensional k (affineSpan k (insert p (s : Set P))).direction := (direction_affineSpan k (insert p (s : Set P))).symm ▸ finiteDimensional_vectorSpan_insert s p variable (k) /-- The `vectorSpan` of adding a point to a set with a finite-dimensional `vectorSpan` is finite-dimensional. -/ instance finiteDimensional_vectorSpan_insert_set (s : Set P) [FiniteDimensional k (vectorSpan k s)] (p : P) : FiniteDimensional k (vectorSpan k (insert p s)) := by haveI : FiniteDimensional k (affineSpan k s).direction := (direction_affineSpan k s).symm ▸ inferInstance rw [← direction_affineSpan, ← affineSpan_insert_affineSpan, direction_affineSpan] exact finiteDimensional_vectorSpan_insert (affineSpan k s) p /-- A set of points is collinear if their `vectorSpan` has dimension at most `1`. -/ def Collinear (s : Set P) : Prop := Module.rank k (vectorSpan k s) ≤ 1 /-- The definition of `Collinear`. -/ theorem collinear_iff_rank_le_one (s : Set P) : Collinear k s ↔ Module.rank k (vectorSpan k s) ≤ 1 := Iff.rfl variable {k} /-- A set of points, whose `vectorSpan` is finite-dimensional, is collinear if and only if their `vectorSpan` has dimension at most `1`. -/ theorem collinear_iff_finrank_le_one {s : Set P} [FiniteDimensional k (vectorSpan k s)] : Collinear k s ↔ finrank k (vectorSpan k s) ≤ 1 := by have h := collinear_iff_rank_le_one k s rw [← finrank_eq_rank] at h exact mod_cast h alias ⟨Collinear.finrank_le_one, _⟩ := collinear_iff_finrank_le_one /-- A subset of a collinear set is collinear. -/ theorem Collinear.subset {s₁ s₂ : Set P} (hs : s₁ ⊆ s₂) (h : Collinear k s₂) : Collinear k s₁ := (Submodule.rank_mono (vectorSpan_mono k hs)).trans h /-- The `vectorSpan` of collinear points is finite-dimensional. -/ theorem Collinear.finiteDimensional_vectorSpan {s : Set P} (h : Collinear k s) : FiniteDimensional k (vectorSpan k s) := IsNoetherian.iff_fg.1 (IsNoetherian.iff_rank_lt_aleph0.2 (lt_of_le_of_lt h Cardinal.one_lt_aleph0)) /-- The direction of the affine span of collinear points is finite-dimensional. -/ theorem Collinear.finiteDimensional_direction_affineSpan {s : Set P} (h : Collinear k s) : FiniteDimensional k (affineSpan k s).direction := (direction_affineSpan k s).symm ▸ h.finiteDimensional_vectorSpan variable (k P) /-- The empty set is collinear. -/ theorem collinear_empty : Collinear k (∅ : Set P) := by rw [collinear_iff_rank_le_one, vectorSpan_empty] simp variable {P} /-- A single point is collinear. -/ theorem collinear_singleton (p : P) : Collinear k ({p} : Set P) := by rw [collinear_iff_rank_le_one, vectorSpan_singleton] simp variable {k} /-- Given a point `p₀` in a set of points, that set is collinear if and only if the points can all be expressed as multiples of the same vector, added to `p₀`. -/ theorem collinear_iff_of_mem {s : Set P} {p₀ : P} (h : p₀ ∈ s) : Collinear k s ↔ ∃ v : V, ∀ p ∈ s, ∃ r : k, p = r • v +ᵥ p₀ := by simp_rw [collinear_iff_rank_le_one, rank_submodule_le_one_iff', Submodule.le_span_singleton_iff] constructor · rintro ⟨v₀, hv⟩ use v₀ intro p hp obtain ⟨r, hr⟩ := hv (p -ᵥ p₀) (vsub_mem_vectorSpan k hp h) use r rw [eq_vadd_iff_vsub_eq] exact hr.symm · rintro ⟨v, hp₀v⟩ use v intro w hw have hs : vectorSpan k s ≤ k ∙ v := by rw [vectorSpan_eq_span_vsub_set_right k h, Submodule.span_le, Set.subset_def] intro x hx rw [SetLike.mem_coe, Submodule.mem_span_singleton] rw [Set.mem_image] at hx rcases hx with ⟨p, hp, rfl⟩ rcases hp₀v p hp with ⟨r, rfl⟩ use r simp have hw' := SetLike.le_def.1 hs hw rwa [Submodule.mem_span_singleton] at hw' /-- A set of points is collinear if and only if they can all be expressed as multiples of the same vector, added to the same base point. -/ theorem collinear_iff_exists_forall_eq_smul_vadd (s : Set P) : Collinear k s ↔ ∃ (p₀ : P) (v : V), ∀ p ∈ s, ∃ r : k, p = r • v +ᵥ p₀ := by rcases Set.eq_empty_or_nonempty s with (rfl | ⟨⟨p₁, hp₁⟩⟩) · simp [collinear_empty] · rw [collinear_iff_of_mem hp₁] constructor · exact fun h => ⟨p₁, h⟩ · rintro ⟨p, v, hv⟩ use v intro p₂ hp₂ rcases hv p₂ hp₂ with ⟨r, rfl⟩ rcases hv p₁ hp₁ with ⟨r₁, rfl⟩ use r - r₁ simp [vadd_vadd, ← add_smul] variable (k) in /-- Two points are collinear. -/ theorem collinear_pair (p₁ p₂ : P) : Collinear k ({p₁, p₂} : Set P) := by rw [collinear_iff_exists_forall_eq_smul_vadd] use p₁, p₂ -ᵥ p₁ intro p hp rw [Set.mem_insert_iff, Set.mem_singleton_iff] at hp rcases hp with hp | hp · use 0 simp [hp] · use 1 simp [hp] /-- Three points are affinely independent if and only if they are not collinear. -/ theorem affineIndependent_iff_not_collinear {p : Fin 3 → P} : AffineIndependent k p ↔ ¬Collinear k (Set.range p) := by rw [collinear_iff_finrank_le_one, affineIndependent_iff_not_finrank_vectorSpan_le k p (Fintype.card_fin 3)] /-- Three points are collinear if and only if they are not affinely independent. -/ theorem collinear_iff_not_affineIndependent {p : Fin 3 → P} : Collinear k (Set.range p) ↔ ¬AffineIndependent k p := by rw [collinear_iff_finrank_le_one, finrank_vectorSpan_le_iff_not_affineIndependent k p (Fintype.card_fin 3)] /-- Three points are affinely independent if and only if they are not collinear. -/ theorem affineIndependent_iff_not_collinear_set {p₁ p₂ p₃ : P} : AffineIndependent k ![p₁, p₂, p₃] ↔ ¬Collinear k ({p₁, p₂, p₃} : Set P) := by rw [affineIndependent_iff_not_collinear] simp_rw [Matrix.range_cons, Matrix.range_empty, Set.singleton_union, insert_empty_eq] /-- Three points are collinear if and only if they are not affinely independent. -/ theorem collinear_iff_not_affineIndependent_set {p₁ p₂ p₃ : P} : Collinear k ({p₁, p₂, p₃} : Set P) ↔ ¬AffineIndependent k ![p₁, p₂, p₃] := affineIndependent_iff_not_collinear_set.not_left.symm /-- Three points are affinely independent if and only if they are not collinear. -/ theorem affineIndependent_iff_not_collinear_of_ne {p : Fin 3 → P} {i₁ i₂ i₃ : Fin 3} (h₁₂ : i₁ ≠ i₂) (h₁₃ : i₁ ≠ i₃) (h₂₃ : i₂ ≠ i₃) : AffineIndependent k p ↔ ¬Collinear k ({p i₁, p i₂, p i₃} : Set P) := by have hu : (Finset.univ : Finset (Fin 3)) = {i₁, i₂, i₃} := by decide +revert rw [affineIndependent_iff_not_collinear, ← Set.image_univ, ← Finset.coe_univ, hu, Finset.coe_insert, Finset.coe_insert, Finset.coe_singleton, Set.image_insert_eq, Set.image_pair] /-- Three points are collinear if and only if they are not affinely independent. -/ theorem collinear_iff_not_affineIndependent_of_ne {p : Fin 3 → P} {i₁ i₂ i₃ : Fin 3} (h₁₂ : i₁ ≠ i₂) (h₁₃ : i₁ ≠ i₃) (h₂₃ : i₂ ≠ i₃) : Collinear k ({p i₁, p i₂, p i₃} : Set P) ↔ ¬AffineIndependent k p := (affineIndependent_iff_not_collinear_of_ne h₁₂ h₁₃ h₂₃).not_left.symm /-- If three points are not collinear, the first and second are different. -/ theorem ne₁₂_of_not_collinear {p₁ p₂ p₃ : P} (h : ¬Collinear k ({p₁, p₂, p₃} : Set P)) : p₁ ≠ p₂ := by rintro rfl simp [collinear_pair] at h /-- If three points are not collinear, the first and third are different. -/ theorem ne₁₃_of_not_collinear {p₁ p₂ p₃ : P} (h : ¬Collinear k ({p₁, p₂, p₃} : Set P)) : p₁ ≠ p₃ := by rintro rfl simp [collinear_pair] at h /-- If three points are not collinear, the second and third are different. -/ theorem ne₂₃_of_not_collinear {p₁ p₂ p₃ : P} (h : ¬Collinear k ({p₁, p₂, p₃} : Set P)) : p₂ ≠ p₃ := by rintro rfl simp [collinear_pair] at h /-- A point in a collinear set of points lies in the affine span of any two distinct points of that set. -/ theorem Collinear.mem_affineSpan_of_mem_of_ne {s : Set P} (h : Collinear k s) {p₁ p₂ p₃ : P} (hp₁ : p₁ ∈ s) (hp₂ : p₂ ∈ s) (hp₃ : p₃ ∈ s) (hp₁p₂ : p₁ ≠ p₂) : p₃ ∈ line[k, p₁, p₂] := by rw [collinear_iff_of_mem hp₁] at h rcases h with ⟨v, h⟩ rcases h p₂ hp₂ with ⟨r₂, rfl⟩ rcases h p₃ hp₃ with ⟨r₃, rfl⟩ rw [vadd_left_mem_affineSpan_pair] refine ⟨r₃ / r₂, ?_⟩ have h₂ : r₂ ≠ 0 := by rintro rfl simp at hp₁p₂ simp [smul_smul, h₂] /-- The affine span of any two distinct points of a collinear set of points equals the affine span of the whole set. -/ theorem Collinear.affineSpan_eq_of_ne {s : Set P} (h : Collinear k s) {p₁ p₂ : P} (hp₁ : p₁ ∈ s) (hp₂ : p₂ ∈ s) (hp₁p₂ : p₁ ≠ p₂) : line[k, p₁, p₂] = affineSpan k s := le_antisymm (affineSpan_mono _ (Set.insert_subset_iff.2 ⟨hp₁, Set.singleton_subset_iff.2 hp₂⟩)) (affineSpan_le.2 fun _ hp => h.mem_affineSpan_of_mem_of_ne hp₁ hp₂ hp hp₁p₂) /-- Given a collinear set of points, and two distinct points `p₂` and `p₃` in it, a point `p₁` is collinear with the set if and only if it is collinear with `p₂` and `p₃`. -/ theorem Collinear.collinear_insert_iff_of_ne {s : Set P} (h : Collinear k s) {p₁ p₂ p₃ : P} (hp₂ : p₂ ∈ s) (hp₃ : p₃ ∈ s) (hp₂p₃ : p₂ ≠ p₃) : Collinear k (insert p₁ s) ↔ Collinear k ({p₁, p₂, p₃} : Set P) := by have hv : vectorSpan k (insert p₁ s) = vectorSpan k ({p₁, p₂, p₃} : Set P) := by conv_rhs => rw [← direction_affineSpan, ← affineSpan_insert_affineSpan] rw [← direction_affineSpan, ← affineSpan_insert_affineSpan, h.affineSpan_eq_of_ne hp₂ hp₃ hp₂p₃] rw [Collinear, Collinear, hv] /-- Adding a point in the affine span of a set does not change whether that set is collinear. -/ theorem collinear_insert_iff_of_mem_affineSpan {s : Set P} {p : P} (h : p ∈ affineSpan k s) : Collinear k (insert p s) ↔ Collinear k s := by rw [Collinear, Collinear, vectorSpan_insert_eq_vectorSpan h]
/-- If a point lies in the affine span of two points, those three points are collinear. -/ theorem collinear_insert_of_mem_affineSpan_pair {p₁ p₂ p₃ : P} (h : p₁ ∈ line[k, p₂, p₃]) : Collinear k ({p₁, p₂, p₃} : Set P) := by rw [collinear_insert_iff_of_mem_affineSpan h]
Mathlib/LinearAlgebra/AffineSpace/FiniteDimensional.lean
570
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/- 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.LinearAlgebra.Basis.Basic import Mathlib.LinearAlgebra.BilinearMap import Mathlib.LinearAlgebra.LinearIndependent.Lemmas /-! # Sesquilinear maps This files provides properties about sesquilinear maps and forms. The maps considered are of the form `M₁ →ₛₗ[I₁] M₂ →ₛₗ[I₂] M`, where `I₁ : R₁ →+* R` and `I₂ : R₂ →+* R` are ring homomorphisms and `M₁` is a module over `R₁`, `M₂` is a module over `R₂` and `M` is a module over `R`. Sesquilinear forms are the special case that `M₁ = M₂`, `M = R₁ = R₂ = R`, and `I₁ = RingHom.id R`. Taking additionally `I₂ = RingHom.id R`, then one obtains bilinear forms. Sesquilinear maps are a special case of the bilinear maps defined in `BilinearMap.lean` and `many` basic lemmas about construction and elementary calculations are found there. ## Main declarations * `IsOrtho`: states that two vectors are orthogonal with respect to a sesquilinear map * `IsSymm`, `IsAlt`: states that a sesquilinear form is symmetric and alternating, respectively * `orthogonalBilin`: provides the orthogonal complement with respect to sesquilinear form ## References * <https://en.wikipedia.org/wiki/Sesquilinear_form#Over_arbitrary_rings> ## Tags Sesquilinear form, Sesquilinear map, -/ variable {R R₁ R₂ R₃ M M₁ M₂ M₃ Mₗ₁ Mₗ₁' Mₗ₂ Mₗ₂' K K₁ K₂ V V₁ V₂ n : Type*} namespace LinearMap /-! ### Orthogonal vectors -/ section CommRing -- the `ₗ` subscript variables are for special cases about linear (as opposed to semilinear) maps variable [CommSemiring R] [CommSemiring R₁] [AddCommMonoid M₁] [Module R₁ M₁] [CommSemiring R₂] [AddCommMonoid M₂] [Module R₂ M₂] [AddCommMonoid M] [Module R M] {I₁ : R₁ →+* R} {I₂ : R₂ →+* R} {I₁' : R₁ →+* R} /-- The proposition that two elements of a sesquilinear map space are orthogonal -/ def IsOrtho (B : M₁ →ₛₗ[I₁] M₂ →ₛₗ[I₂] M) (x : M₁) (y : M₂) : Prop := B x y = 0 theorem isOrtho_def {B : M₁ →ₛₗ[I₁] M₂ →ₛₗ[I₂] M} {x y} : B.IsOrtho x y ↔ B x y = 0 := Iff.rfl theorem isOrtho_zero_left (B : M₁ →ₛₗ[I₁] M₂ →ₛₗ[I₂] M) (x) : IsOrtho B (0 : M₁) x := by dsimp only [IsOrtho] rw [map_zero B, zero_apply] theorem isOrtho_zero_right (B : M₁ →ₛₗ[I₁] M₂ →ₛₗ[I₂] M) (x) : IsOrtho B x (0 : M₂) := map_zero (B x) theorem isOrtho_flip {B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₁'] M} {x y} : B.IsOrtho x y ↔ B.flip.IsOrtho y x := by simp_rw [isOrtho_def, flip_apply] open scoped Function in -- required for scoped `on` notation /-- A set of vectors `v` is orthogonal with respect to some bilinear map `B` if and only if for all `i ≠ j`, `B (v i) (v j) = 0`. For orthogonality between two elements, use `BilinForm.isOrtho` -/ def IsOrthoᵢ (B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₁'] M) (v : n → M₁) : Prop := Pairwise (B.IsOrtho on v) theorem isOrthoᵢ_def {B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₁'] M} {v : n → M₁} : B.IsOrthoᵢ v ↔ ∀ i j : n, i ≠ j → B (v i) (v j) = 0 := Iff.rfl theorem isOrthoᵢ_flip (B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₁'] M) {v : n → M₁} : B.IsOrthoᵢ v ↔ B.flip.IsOrthoᵢ v := by simp_rw [isOrthoᵢ_def] constructor <;> exact fun h i j hij ↦ h j i hij.symm end CommRing section Field variable [Field K] [AddCommGroup V] [Module K V] [Field K₁] [AddCommGroup V₁] [Module K₁ V₁] [Field K₂] [AddCommGroup V₂] [Module K₂ V₂] {I₁ : K₁ →+* K} {I₂ : K₂ →+* K} {I₁' : K₁ →+* K} {J₁ : K →+* K} {J₂ : K →+* K} -- todo: this also holds for [CommRing R] [IsDomain R] when J₁ is invertible theorem ortho_smul_left {B : V₁ →ₛₗ[I₁] V₂ →ₛₗ[I₂] V} {x y} {a : K₁} (ha : a ≠ 0) : IsOrtho B x y ↔ IsOrtho B (a • x) y := by dsimp only [IsOrtho] constructor <;> intro H · rw [map_smulₛₗ₂, H, smul_zero] · rw [map_smulₛₗ₂, smul_eq_zero] at H rcases H with H | H · rw [map_eq_zero I₁] at H trivial · exact H -- todo: this also holds for [CommRing R] [IsDomain R] when J₂ is invertible theorem ortho_smul_right {B : V₁ →ₛₗ[I₁] V₂ →ₛₗ[I₂] V} {x y} {a : K₂} {ha : a ≠ 0} : IsOrtho B x y ↔ IsOrtho B x (a • y) := by dsimp only [IsOrtho] constructor <;> intro H · rw [map_smulₛₗ, H, smul_zero] · rw [map_smulₛₗ, smul_eq_zero] at H rcases H with H | H · simp only [map_eq_zero] at H exfalso exact ha H · exact H /-- A set of orthogonal vectors `v` with respect to some sesquilinear map `B` is linearly independent if for all `i`, `B (v i) (v i) ≠ 0`. -/ theorem linearIndependent_of_isOrthoᵢ {B : V₁ →ₛₗ[I₁] V₁ →ₛₗ[I₁'] V} {v : n → V₁} (hv₁ : B.IsOrthoᵢ v) (hv₂ : ∀ i, ¬B.IsOrtho (v i) (v i)) : LinearIndependent K₁ v := by classical rw [linearIndependent_iff'] intro s w hs i hi have : B (s.sum fun i : n ↦ w i • v i) (v i) = 0 := by rw [hs, map_zero, zero_apply] have hsum : (s.sum fun j : n ↦ I₁ (w j) • B (v j) (v i)) = I₁ (w i) • B (v i) (v i) := by apply Finset.sum_eq_single_of_mem i hi intro j _hj hij rw [isOrthoᵢ_def.1 hv₁ _ _ hij, smul_zero] simp_rw [B.map_sum₂, map_smulₛₗ₂, hsum] at this apply (map_eq_zero I₁).mp exact (smul_eq_zero.mp this).elim _root_.id (hv₂ i · |>.elim) end Field /-! ### Reflexive bilinear maps -/ section Reflexive variable [CommSemiring R] [AddCommMonoid M] [Module R M] [CommSemiring R₁] [AddCommMonoid M₁] [Module R₁ M₁] {I₁ : R₁ →+* R} {I₂ : R₁ →+* R} {B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₂] M} /-- The proposition that a sesquilinear map is reflexive -/ def IsRefl (B : M₁ →ₛₗ[I₁] M₁ →ₛₗ[I₂] M) : Prop := ∀ x y, B x y = 0 → B y x = 0 namespace IsRefl section variable (H : B.IsRefl) include H theorem eq_zero : ∀ {x y}, B x y = 0 → B y x = 0 := fun {x y} ↦ H x y theorem eq_iff {x y} : B x y = 0 ↔ B y x = 0 := ⟨H x y, H y x⟩ theorem ortho_comm {x y} : IsOrtho B x y ↔ IsOrtho B y x := ⟨eq_zero H, eq_zero H⟩ theorem domRestrict (p : Submodule R₁ M₁) : (B.domRestrict₁₂ p p).IsRefl := fun _ _ ↦ by simp_rw [domRestrict₁₂_apply] exact H _ _ end @[simp] theorem flip_isRefl_iff : B.flip.IsRefl ↔ B.IsRefl := ⟨fun h x y H ↦ h y x ((B.flip_apply _ _).trans H), fun h x y ↦ h y x⟩ theorem ker_flip_eq_bot (H : B.IsRefl) (h : LinearMap.ker B = ⊥) : LinearMap.ker B.flip = ⊥ := by refine ker_eq_bot'.mpr fun _ hx ↦ ker_eq_bot'.mp h _ ?_ ext exact H _ _ (LinearMap.congr_fun hx _) theorem ker_eq_bot_iff_ker_flip_eq_bot (H : B.IsRefl) : LinearMap.ker B = ⊥ ↔ LinearMap.ker B.flip = ⊥ := by refine ⟨ker_flip_eq_bot H, fun h ↦ ?_⟩ exact (congr_arg _ B.flip_flip.symm).trans (ker_flip_eq_bot (flip_isRefl_iff.mpr H) h) end IsRefl end Reflexive /-! ### Symmetric bilinear forms -/ section Symmetric variable [CommSemiring R] [AddCommMonoid M] [Module R M] {I : R →+* R} {B : M →ₛₗ[I] M →ₗ[R] R} /-- The proposition that a sesquilinear form is symmetric -/ def IsSymm (B : M →ₛₗ[I] M →ₗ[R] R) : Prop := ∀ x y, I (B x y) = B y x namespace IsSymm protected theorem eq (H : B.IsSymm) (x y) : I (B x y) = B y x := H x y theorem isRefl (H : B.IsSymm) : B.IsRefl := fun x y H1 ↦ by rw [← H.eq] simp [H1] theorem ortho_comm (H : B.IsSymm) {x y} : IsOrtho B x y ↔ IsOrtho B y x := H.isRefl.ortho_comm theorem domRestrict (H : B.IsSymm) (p : Submodule R M) : (B.domRestrict₁₂ p p).IsSymm := fun _ _ ↦ by simp_rw [domRestrict₁₂_apply] exact H _ _ end IsSymm @[simp] theorem isSymm_zero : (0 : M →ₛₗ[I] M →ₗ[R] R).IsSymm := fun _ _ => map_zero _ theorem BilinMap.isSymm_iff_eq_flip {N : Type*} [AddCommMonoid N] [Module R N] {B : LinearMap.BilinMap R M N} : (∀ x y, B x y = B y x) ↔ B = B.flip := by simp [LinearMap.ext_iff₂] theorem isSymm_iff_eq_flip {B : LinearMap.BilinForm R M} : B.IsSymm ↔ B = B.flip := BilinMap.isSymm_iff_eq_flip
end Symmetric /-! ### Alternating bilinear maps -/
Mathlib/LinearAlgebra/SesquilinearForm.lean
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