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| 1 | +/- |
| 2 | +Copyright (c) 2026 Sébastien Gouëzel. All rights reserved. |
| 3 | +Released under Apache 2.0 license as described in the file LICENSE. |
| 4 | +Authors: Sébastien Gouëzel |
| 5 | +-/ |
| 6 | +module |
| 7 | + |
| 8 | +public import Mathlib.MeasureTheory.Integral.Prod |
| 9 | +public import Mathlib.MeasureTheory.VectorMeasure.SetIntegral |
| 10 | +public import Mathlib.MeasureTheory.VectorMeasure.Variation.Semivariation |
| 11 | + |
| 12 | +/-! |
| 13 | +# Product of vector measures |
| 14 | +
|
| 15 | +Given two vector measures, we define their product `μ.prod ν B` as the vector measure assigning |
| 16 | +to a measurable product `s × t` the mass `B (μ s) (ν t)`, if such a vector measure exists. |
| 17 | +We show that it exists when either `μ` or `ν` has finite variation. |
| 18 | +
|
| 19 | +The API is modelled on the one for the product of positive measures. |
| 20 | +-/ |
| 21 | + |
| 22 | +public section |
| 23 | + |
| 24 | +open Filter Function MeasureTheory RCLike Set TopologicalSpace Topology |
| 25 | +open scoped ENNReal NNReal Finset |
| 26 | + |
| 27 | +variable {ι X Y E F G H I J : Type*} {mX : MeasurableSpace X} {mY : MeasurableSpace Y} |
| 28 | + [NormedAddCommGroup E] [NormedSpace ℝ E] |
| 29 | + [NormedAddCommGroup F] [NormedSpace ℝ F] |
| 30 | + [NormedAddCommGroup G] [NormedSpace ℝ G] |
| 31 | + [NormedAddCommGroup H] [NormedSpace ℝ H] |
| 32 | + [NormedAddCommGroup I] [NormedSpace ℝ I] |
| 33 | + [NormedAddCommGroup J] [NormedSpace ℝ J] |
| 34 | + {μ : VectorMeasure X E} {ν : VectorMeasure Y F} {B : E →L[ℝ] F →L[ℝ] G} |
| 35 | + |
| 36 | +namespace MeasureTheory.VectorMeasure |
| 37 | + |
| 38 | +/-- Two vector measures `μ` and `ν` have a product with respect to `B` if there exists a |
| 39 | +measure giving mass `B (μ s) (ν t)` to any measurable product set `s × t`. |
| 40 | +This is satisfied whenever `μ` or `ν` has finite variation. -/ |
| 41 | +class HasProd (μ : VectorMeasure X E) (ν : VectorMeasure Y F) (B : E →L[ℝ] F →L[ℝ] G) : Prop where |
| 42 | + exists_prod : ∃ ρ : VectorMeasure (X × Y) G, ∀ (s : Set X) (t : Set Y), |
| 43 | + MeasurableSet s → MeasurableSet t → ρ (s ×ˢ t) = B (μ s) (ν t) |
| 44 | + |
| 45 | +/-- The product of two vector measures `μ` and `ν` with respect to a continuous bilinear map `B`, |
| 46 | +giving mass `B (μ s) (ν t)` to any measurable product set `s × t`. |
| 47 | +If such a measure does not exist, we use the junk value `0`. -/ |
| 48 | +noncomputable def prod (μ : VectorMeasure X E) (ν : VectorMeasure Y F) (B : E →L[ℝ] F →L[ℝ] G) : |
| 49 | + VectorMeasure (X × Y) G := |
| 50 | + open scoped Classical in if h : HasProd μ ν B then h.exists_prod.choose else 0 |
| 51 | + |
| 52 | +lemma prod_eq_zero_of_not_hasProd (h : ¬HasProd μ ν B) : |
| 53 | + μ.prod ν B = 0 := by |
| 54 | + grind [HasProd, prod] |
| 55 | + |
| 56 | +@[simp] lemma prod_apply [h : HasProd μ ν B] {s : Set X} {t : Set Y} : |
| 57 | + μ.prod ν B (s ×ˢ t) = B (μ s) (ν t) := by |
| 58 | + rcases eq_or_ne s ∅ with rfl | hs |
| 59 | + · simp |
| 60 | + rcases eq_or_ne t ∅ with rfl | ht |
| 61 | + · simp |
| 62 | + by_cases h's : MeasurableSet s; swap |
| 63 | + · simp only [h's, not_false_eq_true, not_measurable, _root_.map_zero, _root_.zero_apply] |
| 64 | + rw [not_measurable] |
| 65 | + simp [measurableSet_prod, hs, ht, h's] |
| 66 | + by_cases h't : MeasurableSet t; swap |
| 67 | + · simp only [h't, not_false_eq_true, not_measurable, _root_.map_zero] |
| 68 | + rw [not_measurable] |
| 69 | + simp [measurableSet_prod, hs, ht, h't] |
| 70 | + simpa [prod, h] using h.exists_prod.choose_spec s t h's h't |
| 71 | + |
| 72 | +lemma HasProd.flip [HasProd μ ν B] : HasProd ν μ B.flip where |
| 73 | + exists_prod := by |
| 74 | + refine ⟨(μ.prod ν B).map Prod.swap, fun s t hs ht ↦ ?_⟩ |
| 75 | + rw [map_apply _ (by fun_prop) (hs.prod ht)] |
| 76 | + simp |
| 77 | + |
| 78 | +lemma hasProd_flip_iff : HasProd ν μ B.flip ↔ HasProd μ ν B := |
| 79 | + ⟨fun h ↦ by simpa using HasProd.flip (μ := ν) (ν := μ) (B := B.flip), fun h ↦ HasProd.flip⟩ |
| 80 | + |
| 81 | +omit [NormedSpace ℝ F] in |
| 82 | +/-- If `ν` is a vector measure, and `s ⊆ X × Y` is measurable, then `x ↦ ν { y | (x, y) ∈ s }` is |
| 83 | +a strongly measurable function. -/ |
| 84 | +theorem stronglyMeasurable_vectorMeasure_prodMk_left {s : Set (X × Y)} |
| 85 | + (hs : MeasurableSet s) : StronglyMeasurable fun x ↦ ν (Prod.mk x ⁻¹' s) := by |
| 86 | + induction s, hs |
| 87 | + using MeasurableSpace.induction_on_inter generateFrom_prod.symm isPiSystem_prod with |
| 88 | + | empty => simp [stronglyMeasurable_const] |
| 89 | + | basic s hs => |
| 90 | + obtain ⟨s, hs, t, -, rfl⟩ := hs |
| 91 | + classical |
| 92 | + simpa [mk_preimage_prod_right_eq_if, of_if] using stronglyMeasurable_const.indicator hs |
| 93 | + | compl s hs ihs => |
| 94 | + simp_rw [preimage_compl, VectorMeasure.of_compl (measurable_prodMk_left hs)] |
| 95 | + exact stronglyMeasurable_const.sub ihs |
| 96 | + | iUnion f hfd hfm ihf => |
| 97 | + have (a : X) : HasSum (fun i ↦ ν (Prod.mk a ⁻¹' f i)) (ν (Prod.mk a ⁻¹' ⋃ i, f i)) := by |
| 98 | + rw [preimage_iUnion] |
| 99 | + apply hasSum_of_disjoint_iUnion |
| 100 | + exacts [fun i ↦ measurable_prodMk_left (hfm i), hfd.mono fun _ _ ↦ .preimage _] |
| 101 | + exact StronglyMeasurable.hasSum ihf this |
| 102 | + |
| 103 | +omit [NormedSpace ℝ E] in |
| 104 | +theorem integrable_vectorMeasure_prodMk_left [IsFiniteMeasure μ.variation] |
| 105 | + {s : Set (X × Y)} (hs : MeasurableSet s) : |
| 106 | + μ.Integrable fun x ↦ ν (Prod.mk x ⁻¹' s) := by |
| 107 | + refine Integrable.of_bound (μ := μ.variation) ?_ ν.bound ?_ |
| 108 | + · exact (stronglyMeasurable_vectorMeasure_prodMk_left hs).aestronglyMeasurable |
| 109 | + · exact Eventually.of_forall (fun x ↦ norm_apply_le_bound) |
| 110 | + |
| 111 | +/-- The product of two vector measures when the first one has finite variation, obtained by |
| 112 | +integrating the measure of the fibers, as in the definition of the product of positive measures. |
| 113 | +*Do not use*: This is only used to instantiate the typeclass `HasProd`. Instead, use `μ.prod ν B`, |
| 114 | +which uses the typeclass instance. -/ |
| 115 | +private noncomputable def prodOfIsFiniteMeasureLeft |
| 116 | + (μ : VectorMeasure X E) (ν : VectorMeasure Y F) (B : E →L[ℝ] F →L[ℝ] G) |
| 117 | + [IsFiniteMeasure μ.variation] : |
| 118 | + VectorMeasure (X × Y) G where |
| 119 | + measureOf' s := open scoped Classical in |
| 120 | + if MeasurableSet s then ∫ᵛ x, ν (Prod.mk x ⁻¹' s) ∂[B.flip; μ] else 0 |
| 121 | + empty' := by simp |
| 122 | + not_measurable' := by simp +contextual |
| 123 | + m_iUnion' f f_meas f_disj := by |
| 124 | + simp only [f_meas, ↓reduceIte, implies_true, MeasurableSet.iUnion, preimage_iUnion, |
| 125 | + HasSum, SummationFilter.unconditional_filter] |
| 126 | + have A (a : Finset ℕ) : ∑ y ∈ a, ∫ᵛ x, ν (Prod.mk x ⁻¹' f y) ∂[B.flip; μ] |
| 127 | + = ∫ᵛ x, ∑ y ∈ a, ν (Prod.mk x ⁻¹' f y) ∂[B.flip; μ] := by |
| 128 | + rw [integral_finsetSum _ (fun i hi ↦ integrable_vectorMeasure_prodMk_left (f_meas i))] |
| 129 | + simp_rw [A] |
| 130 | + apply tendsto_integral_filter_of_dominated_convergence (bound := fun x ↦ ν.bound) |
| 131 | + · apply Eventually.of_forall (fun a ↦ ?_) |
| 132 | + apply StronglyMeasurable.aestronglyMeasurable |
| 133 | + apply Finset.stronglyMeasurable_fun_sum _ (fun i hi ↦ ?_) |
| 134 | + apply stronglyMeasurable_vectorMeasure_prodMk_left (f_meas i) |
| 135 | + · filter_upwards with a |
| 136 | + filter_upwards with x |
| 137 | + rw [← VectorMeasure.of_biUnion_finset] |
| 138 | + · apply norm_apply_le_bound |
| 139 | + · exact fun i hi j hj hij ↦ (f_disj hij).preimage _ |
| 140 | + · exact fun i hi ↦ measurable_prodMk_left (f_meas i) |
| 141 | + · apply integrable_const |
| 142 | + · filter_upwards with x |
| 143 | + apply hasSum_of_disjoint_iUnion |
| 144 | + · exact fun i ↦ measurable_prodMk_left (f_meas i) |
| 145 | + · exact fun i j hij ↦ (f_disj hij).preimage _ |
| 146 | + |
| 147 | +instance [CompleteSpace G] [IsFiniteMeasure μ.variation] : HasProd μ ν B where |
| 148 | + exists_prod := by |
| 149 | + classical |
| 150 | + refine ⟨prodOfIsFiniteMeasureLeft μ ν B, fun s t hs ht ↦ ?_⟩ |
| 151 | + simp [prodOfIsFiniteMeasureLeft, hs.prod ht, ↓reduceIte, mk_preimage_prod_right_eq_if, |
| 152 | + of_if, integral_indicator hs, ContinuousLinearMap.flip_apply, hs, restrict_apply] |
| 153 | + |
| 154 | +instance [CompleteSpace G] [h : IsFiniteMeasure ν.variation] : HasProd μ ν B := |
| 155 | + hasProd_flip_iff.1 inferInstance |
| 156 | + |
| 157 | +lemma prod_eq_of_forall_apply_prod {ρ : VectorMeasure (X × Y) G} (hρ : ∀ (s : Set X) (t : Set Y), |
| 158 | + MeasurableSet s → MeasurableSet t → ρ (s ×ˢ t) = B (μ s) (ν t)) : |
| 159 | + μ.prod ν B = ρ := by |
| 160 | + have : HasProd μ ν B := ⟨ρ, hρ⟩ |
| 161 | + apply ext_of_generateFrom _ _ generateFrom_prod.symm isPiSystem_prod |
| 162 | + · rw [← univ_prod_univ, hρ _ _ MeasurableSet.univ MeasurableSet.univ, prod_apply] |
| 163 | + · rintro - ⟨s, hs, t, ht, rfl⟩ |
| 164 | + rw [prod_apply, hρ _ _ hs ht] |
| 165 | + |
| 166 | +lemma prod_apply_eq_integral [CompleteSpace G] [IsFiniteMeasure μ.variation] |
| 167 | + {s : Set (X × Y)} (hs : MeasurableSet s) : |
| 168 | + μ.prod ν B s = ∫ᵛ x, ν (Prod.mk x ⁻¹' s) ∂[B.flip; μ] := by |
| 169 | + have : μ.prod ν B = prodOfIsFiniteMeasureLeft μ ν B := by |
| 170 | + classical |
| 171 | + apply prod_eq_of_forall_apply_prod (fun s t hs ht ↦ ?_) |
| 172 | + simp [prodOfIsFiniteMeasureLeft, hs.prod ht, ↓reduceIte, mk_preimage_prod_right_eq_if, |
| 173 | + of_if, integral_indicator hs, ContinuousLinearMap.flip_apply, restrict_apply, hs] |
| 174 | + rw [this] |
| 175 | + simp [prodOfIsFiniteMeasureLeft, hs] |
| 176 | + |
| 177 | +lemma prod_flip_apply_eq_integral [CompleteSpace G] [IsFiniteMeasure μ.variation] |
| 178 | + {B : F →L[ℝ] E →L[ℝ] G} {s : Set (X × Y)} (hs : MeasurableSet s) : |
| 179 | + μ.prod ν B.flip s = ∫ᵛ x, ν (Prod.mk x ⁻¹' s) ∂[B; μ] := by |
| 180 | + simp [prod_apply_eq_integral hs] |
| 181 | + |
| 182 | +lemma variation_prod_le [CompleteSpace G] [IsFiniteMeasure μ.variation] [SFinite ν.variation] : |
| 183 | + (μ.prod ν B).variation ≤ ‖B‖ₑ • μ.variation.prod ν.variation := by |
| 184 | + apply variation_le_of_forall_enorm_le (fun s hs ↦ ?_) |
| 185 | + rw [prod_apply_eq_integral hs] |
| 186 | + simp only [Measure.smul_apply, smul_eq_mul, Measure.prod_apply hs] |
| 187 | + grw [enorm_integral_le_lintegral_enorm, ContinuousLinearMap.opENorm_flip, |
| 188 | + enorm_measure_le_variation] |
| 189 | + |
| 190 | +instance [CompleteSpace G] [IsFiniteMeasure μ.variation] [IsFiniteMeasure ν.variation] : |
| 191 | + IsFiniteMeasure (μ.prod ν B).variation := by |
| 192 | + have : IsFiniteMeasure (‖B‖ₑ • μ.variation.prod ν.variation) := by |
| 193 | + simp only [enorm_eq_nnnorm, Measure.coe_nnreal_smul] |
| 194 | + infer_instance |
| 195 | + exact isFiniteMeasure_of_le _ variation_prod_le |
| 196 | + |
| 197 | +end MeasureTheory.VectorMeasure |
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