import OAI.Analysis.Brenier.CompactMeasure import OAI.Analysis.Brenier.Wasserstein namespace OAI noncomputable section open MeasureTheory open scoped ENNReal namespace Problem358 /-- A coupling inherits almost-everywhere support from each marginal. -/ theorem IsCoupling.ae_mem {d : ℕ} {μ ν : Measure (E d)} {π : Measure (E d × E d)} {K Y : Set (E d)} (hπ : IsCoupling μ ν π) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : ∀ᵐ p ∂π, p.1 ∈ K ∧ p.2 ∈ Y := by have hμae : ∀ᵐ x ∂μ, x ∈ K := by rw [ae_iff] exact hμ have hνae : ∀ᵐ y ∂ν, y ∈ Y := by rw [ae_iff] exact hν have hfst : ∀ᵐ p ∂π, p.1 ∈ K := by apply ae_of_ae_map measurable_fst.aemeasurable simpa only [hπ.2.1] using hμae have hsnd : ∀ᵐ p ∂π, p.2 ∈ Y := by apply ae_of_ae_map measurable_snd.aemeasurable simpa only [hπ.2.2] using hνae exact hfst.and hsnd /-- Finite second cost for a coupling whose two marginals have compact support. -/ theorem IsCoupling.integrable_sqDist_of_compact {d : ℕ} {μ ν : Measure (E d)} {π : Measure (E d × E d)} {K Y : Set (E d)} (hπ : IsCoupling μ ν π) (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : Integrable (fun p : E d × E d => ‖p.1 - p.2‖ ^ 2) π := by let : IsProbabilityMeasure π := hπ.1 obtain ⟨R, hR, hRK⟩ := hK.isBounded.exists_pos_norm_le obtain ⟨S, hS, hSY⟩ := hY.isBounded.exists_pos_norm_le have hmeas : AEStronglyMeasurable (fun p : E d × E d => ‖p.1 - p.2‖ ^ 2) π := ((continuous_fst.sub continuous_snd).norm.pow 2).aestronglyMeasurable apply (integrable_const ((R + S) ^ 2)).mono' hmeas filter_upwards [hπ.ae_mem hμ hν] with p hp rw [Real.norm_eq_abs, abs_of_nonneg (sq_nonneg _)] exact pow_le_pow_left₀ (norm_nonneg _) ((norm_sub_le _ _).trans (add_le_add (hRK _ hp.1) (hSY _ hp.2))) 2 /-- On compact marginal supports every coupling has finite ENNReal quadratic cost. -/ theorem IsCoupling.quadraticPlanCost_ne_top_of_compact {d : ℕ} {μ ν : Measure (E d)} {π : Measure (E d × E d)} {K Y : Set (E d)} (hπ : IsCoupling μ ν π) (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : quadraticPlanCost π ≠ ∞ := by have hi := hπ.integrable_sqDist_of_compact hK hY hμ hν exact (lintegral_ofReal_ne_top_iff_integrable hi.aestronglyMeasurable (Filter.Eventually.of_forall (fun p => sq_nonneg ‖p.1 - p.2‖))).2 hi /-- An explicit uniform cost bound from bounds on the marginal supports. -/ theorem IsCoupling.quadraticPlanCost_le_of_norm_le {d : ℕ} {μ ν : Measure (E d)} {π : Measure (E d × E d)} {K Y : Set (E d)} {R S : ℝ} (hπ : IsCoupling μ ν π) (hμ : IsSupported μ K) (hν : IsSupported ν Y) (hK : ∀ x ∈ K, ‖x‖ ≤ R) (hY : ∀ y ∈ Y, ‖y‖ ≤ S) : quadraticPlanCost π ≤ ENNReal.ofReal ((R + S) ^ 2) := by let : IsProbabilityMeasure π := hπ.1 calc quadraticPlanCost π ≤ ∫⁻ _ : E d × E d, ENNReal.ofReal ((R + S) ^ 2) ∂π := by apply lintegral_mono_ae filter_upwards [hπ.ae_mem hμ hν] with p hp apply ENNReal.ofReal_le_ofReal exact pow_le_pow_left₀ (norm_nonneg _) ((norm_sub_le _ _).trans (add_le_add (hK _ hp.1) (hY _ hp.2))) 2 _ = ENNReal.ofReal ((R + S) ^ 2) := by simp end Problem358 end noncomputable section open MeasureTheory open scoped Topology namespace Problem358 section MeasurableSpaces variable {X Y : Type*} [MeasurableSpace X] [MeasurableSpace Y] /-- The closed set of probability measures with two specified marginals. -/ def probabilityCouplings (μ : ProbabilityMeasure X) (ν : ProbabilityMeasure Y) : Set (ProbabilityMeasure (X × Y)) := {π | π.map Prod.fst = μ ∧ π.map Prod.snd = ν} theorem probabilityCouplings_nonempty (μ : ProbabilityMeasure X) (ν : ProbabilityMeasure Y) : (probabilityCouplings μ ν).Nonempty := by let π : ProbabilityMeasure (X × Y) := ⟨(μ : Measure X).prod (ν : Measure Y), inferInstance⟩ refine ⟨π, ?_, ?_⟩ · apply ProbabilityMeasure.toMeasure_injective change Measure.map Prod.fst ((μ : Measure X).prod (ν : Measure Y)) = μ simp · apply ProbabilityMeasure.toMeasure_injective change Measure.map Prod.snd ((μ : Measure X).prod (ν : Measure Y)) = ν simp end MeasurableSpaces section MetricSpaces variable {X Y : Type*} [MetricSpace X] [MetricSpace Y] [SecondCountableTopology Y] [MeasurableSpace X] [MeasurableSpace Y] [BorelSpace X] [BorelSpace Y] theorem isClosed_probabilityCouplings (μ : ProbabilityMeasure X) (ν : ProbabilityMeasure Y) : IsClosed (probabilityCouplings μ ν) := (isClosed_eq (ProbabilityMeasure.continuous_map continuous_fst) continuous_const).inter (isClosed_eq (ProbabilityMeasure.continuous_map continuous_snd) continuous_const) end MetricSpaces variable {X Y : Type*} [MetricSpace X] [MetricSpace Y] [CompactSpace X] [CompactSpace Y] [MeasurableSpace X] [MeasurableSpace Y] [BorelSpace X] [BorelSpace Y] theorem isCompact_probabilityCouplings (μ : ProbabilityMeasure X) (ν : ProbabilityMeasure Y) : IsCompact (probabilityCouplings μ ν) := (isClosed_probabilityCouplings μ ν).isCompact /-- Every continuous real cost attains its minimum over compact-space probability couplings. -/ theorem exists_probabilityCoupling_minimizer (μ : ProbabilityMeasure X) (ν : ProbabilityMeasure Y) (c : X × Y → ℝ) (hc : Continuous c) : ∃ π ∈ probabilityCouplings μ ν, ∀ η ∈ probabilityCouplings μ ν, (∫ p, c p ∂(π : Measure (X × Y))) ≤ ∫ p, c p ∂(η : Measure (X × Y)) := by have hcost : Continuous (fun π : ProbabilityMeasure (X × Y) => ∫ p, c p ∂(π : Measure (X × Y))) := ProbabilityMeasure.continuous_integral_continuousMap (⟨c, hc⟩ : ContinuousMap (X × Y) ℝ) exact (isCompact_probabilityCouplings μ ν).exists_isMinOn (probabilityCouplings_nonempty μ ν) hcost.continuousOn /-- Unbundled continuous-cost minimization, for direct use with measure-valued plans. -/ theorem exists_compact_coupling_minimizer (μ : Measure X) (ν : Measure Y) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] (c : X × Y → ℝ) (hc : Continuous c) : ∃ π : Measure (X × Y), IsProbabilityMeasure π ∧ Measure.map Prod.fst π = μ ∧ Measure.map Prod.snd π = ν ∧ ∀ η : Measure (X × Y), IsProbabilityMeasure η → Measure.map Prod.fst η = μ → Measure.map Prod.snd η = ν → (∫ p, c p ∂π) ≤ ∫ p, c p ∂η := by let μp : ProbabilityMeasure X := ⟨μ, inferInstance⟩ let νp : ProbabilityMeasure Y := ⟨ν, inferInstance⟩ obtain ⟨π, hπ, hmin⟩ := exists_probabilityCoupling_minimizer μp νp c hc refine ⟨π, inferInstance, ?_, ?_, ?_⟩ · exact congrArg (fun p : ProbabilityMeasure X => (p : Measure X)) hπ.1 · exact congrArg (fun p : ProbabilityMeasure Y => (p : Measure Y)) hπ.2 · intro η hη hfst hsnd exact hmin ⟨η, hη⟩ ⟨ProbabilityMeasure.toMeasure_injective hfst, ProbabilityMeasure.toMeasure_injective hsnd⟩ end Problem358 end noncomputable section open MeasureTheory Filter open scoped Topology ENNReal NNReal namespace Problem358 /-- Fixed compact support determines a compact set of probability measures. -/ theorem isCompact_probability_supported {X : Type*} [MetricSpace X] [MeasurableSpace X] [BorelSpace X] {K : Set X} (hK : IsCompact K) : IsCompact {μ : ProbabilityMeasure X | (μ : Measure X) Kᶜ = 0} := by have h := isCompact_setOfPred_probabilityMeasure_mass_eq_compl_isCompact_le (K := fun _ : ℕ => K) (u := fun _ : ℕ => (0 : ℝ≥0)) tendsto_const_nhds (fun _ => hK) (Or.inl inferInstance) simpa only [Set.mem_ofPred_eq, le_zero_iff, forall_const, ProbabilityMeasure.null_iff_toMeasure_null] using h /-- Couplings of supported marginals are concentrated on the product of their supports. -/ theorem probabilityCouplings_ae_mem_prod {d : ℕ} {μ ν : ProbabilityMeasure (E d)} {K Y : Set (E d)} (hμ : (μ : Measure (E d)) Kᶜ = 0) (hν : (ν : Measure (E d)) Yᶜ = 0) {π : ProbabilityMeasure (E d × E d)} (hπ : π ∈ probabilityCouplings μ ν) : ∀ᵐ p ∂(π : Measure (E d × E d)), p ∈ K ×ˢ Y := by have hfst : Measure.map Prod.fst (π : Measure (E d × E d)) = μ := congrArg (fun p : ProbabilityMeasure (E d) => (p : Measure (E d))) hπ.1 have hsnd : Measure.map Prod.snd (π : Measure (E d × E d)) = ν := congrArg (fun p : ProbabilityMeasure (E d) => (p : Measure (E d))) hπ.2 have hμae : ∀ᵐ x ∂(μ : Measure (E d)), x ∈ K := ae_iff.mpr hμ have hνae : ∀ᵐ x ∂(ν : Measure (E d)), x ∈ Y := ae_iff.mpr hν have ha := ae_of_ae_map measurable_fst.aemeasurable (hfst.symm ▸ hμae) have hb := ae_of_ae_map measurable_snd.aemeasurable (hsnd.symm ▸ hνae) filter_upwards [ha, hb] with p hp hq exact ⟨hp, hq⟩ /-- Compactly supported marginals have a compact set of couplings in the weak topology. -/ theorem isCompact_probabilityCouplings_of_supported {d : ℕ} {μ ν : ProbabilityMeasure (E d)} {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : (μ : Measure (E d)) Kᶜ = 0) (hν : (ν : Measure (E d)) Yᶜ = 0) : IsCompact (probabilityCouplings μ ν) := by apply (isCompact_probability_supported (hK.prod hY)).of_isClosed_subset (isClosed_probabilityCouplings μ ν) intro π hπ exact ae_iff.mp (probabilityCouplings_ae_mem_prod hμ hν hπ) /-- A conveniently clipped quadratic cost, bounded and continuous on the full product space. -/ def boundedQuadraticCost (d : ℕ) (M : ℝ) (hM : 0 ≤ M) : BoundedContinuousFunction (E d × E d) ℝ where toFun p := min M (‖p.1 - p.2‖ ^ 2) continuous_toFun := by fun_prop map_bounded' := by refine ⟨2 * M, fun p q => ?_⟩ have hp : 0 ≤ min M (‖p.1 - p.2‖ ^ 2) := le_min hM (sq_nonneg _) have hq : 0 ≤ min M (‖q.1 - q.2‖ ^ 2) := le_min hM (sq_nonneg _) calc dist (min M (‖p.1 - p.2‖ ^ 2)) (min M (‖q.1 - q.2‖ ^ 2)) ≤ |min M (‖p.1 - p.2‖ ^ 2)| + |min M (‖q.1 - q.2‖ ^ 2)| := by simpa only [Real.dist_eq, sub_zero, zero_sub, abs_neg] using abs_sub_le (min M (‖p.1 - p.2‖ ^ 2)) 0 (min M (‖q.1 - q.2‖ ^ 2)) _ ≤ M + M := by rw [abs_of_nonneg hp, abs_of_nonneg hq] exact add_le_add (min_le_left _ _) (min_le_left _ _) _ = 2 * M := by ring /-- Compactly supported probabilities have a minimizing quadratic transport plan. -/ theorem exists_quadraticOptimalPlan_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : ∃ π : Measure (E d × E d), IsCoupling μ ν π ∧ quadraticPlanCost π ≠ ∞ ∧ ∀ η : Measure (E d × E d), IsCoupling μ ν η → quadraticPlanCost π ≤ quadraticPlanCost η := by let μp : ProbabilityMeasure (E d) := ⟨μ, inferInstance⟩ let νp : ProbabilityMeasure (E d) := ⟨ν, inferInstance⟩ obtain ⟨B, hB⟩ := (hK.prod hY).exists_bound_of_continuousOn (show ContinuousOn (fun p : E d × E d => ‖p.1 - p.2‖ ^ 2) (K ×ˢ Y) by fun_prop) let M := max B 0 let c := boundedQuadraticCost d M (le_max_right B 0) have heq (π : ProbabilityMeasure (E d × E d)) (hπ : π ∈ probabilityCouplings μp νp) : ∀ᵐ p ∂(π : Measure (E d × E d)), c p = ‖p.1 - p.2‖ ^ 2 := by filter_upwards [probabilityCouplings_ae_mem_prod (μ := μp) (ν := νp) (K := K) (Y := Y) hμ hν hπ] with p hp have hbp : ‖p.1 - p.2‖ ^ 2 ≤ B := by simpa only [Real.norm_of_nonneg (sq_nonneg _)] using hB p hp exact min_eq_right (hbp.trans (le_max_left B 0)) have hcost (π : ProbabilityMeasure (E d × E d)) (hπ : π ∈ probabilityCouplings μp νp) : quadraticPlanCost (π : Measure (E d × E d)) = ENNReal.ofReal (∫ p, c p ∂(π : Measure (E d × E d))) := by have hc : Integrable (fun p : E d × E d => ‖p.1 - p.2‖ ^ 2) (π : Measure (E d × E d)) := (c.integrable (μ := (π : Measure (E d × E d)))).congr (heq π hπ) rw [quadraticPlanCost_eq_ofReal_integral hc] congr 1 exact integral_congr_ae (Filter.EventuallyEq.symm (heq π hπ)) have hcompact := isCompact_probabilityCouplings_of_supported (μ := μp) (ν := νp) hK hY hμ hν have hccont : Continuous (fun π : ProbabilityMeasure (E d × E d) => ∫ p, c p ∂(π : Measure (E d × E d))) := ProbabilityMeasure.continuous_integral_boundedContinuousFunction c obtain ⟨π, hπ, hmin⟩ := hcompact.exists_isMinOn (probabilityCouplings_nonempty μp νp) hccont.continuousOn refine ⟨π, ⟨inferInstance, ?_, ?_⟩, ?_, ?_⟩ · exact congrArg (fun p : ProbabilityMeasure (E d) => (p : Measure (E d))) hπ.1 · exact congrArg (fun p : ProbabilityMeasure (E d) => (p : Measure (E d))) hπ.2 · rw [hcost π hπ] exact ENNReal.ofReal_ne_top · intro η hη let ηp : ProbabilityMeasure (E d × E d) := ⟨η, hη.1⟩ have hηp : ηp ∈ probabilityCouplings μp νp := ⟨ProbabilityMeasure.toMeasure_injective hη.2.1, ProbabilityMeasure.toMeasure_injective hη.2.2⟩ change quadraticPlanCost (π : Measure (E d × E d)) ≤ quadraticPlanCost (ηp : Measure (E d × E d)) rw [hcost π hπ, hcost ηp hηp] exact ENNReal.ofReal_le_ofReal (hmin hηp) /-- In particular, a finite-cost plan is available for any compactly supported probabilities. -/ theorem exists_finite_cost_coupling_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : ∃ π : Measure (E d × E d), IsCoupling μ ν π ∧ quadraticPlanCost π ≠ ∞ := by obtain ⟨π, hπ, hfinite, _⟩ := exists_quadraticOptimalPlan_of_compact_support μ ν hK hY hμ hν exact ⟨π, hπ, hfinite⟩ end Problem358 end noncomputable section open MeasureTheory open scoped ENNReal NNReal open Filter open scoped Topology namespace Problem358 /-- The infimum in the exact Wasserstein definition is attained for compact supports. -/ theorem wasserstein2_attained_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : ∃ π : Measure (E d × E d), IsCoupling μ ν π ∧ quadraticPlanCost π ≠ ∞ ∧ wasserstein2 μ ν = Real.sqrt (quadraticPlanCost π).toReal := by obtain ⟨π, hπ, hfin, hopt⟩ := exists_quadraticOptimalPlan_of_compact_support μ ν hK hY hμ hν exact ⟨π, hπ, hfin, wasserstein2_eq_of_minimizing_coupling hπ hopt⟩ /-- Zero distance separates compactly supported probabilities. -/ theorem wasserstein2_eq_zero_iff_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : wasserstein2 μ ν = 0 ↔ μ = ν := by constructor · exact measure_eq_of_wasserstein2_eq_zero (exists_finite_cost_coupling_of_compact_support μ ν hK hY hμ hν) · rintro rfl exact wasserstein2_self μ /-- Distinct compactly supported probabilities have strictly positive distance. -/ theorem wasserstein2_pos_iff_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) : 0 < wasserstein2 μ ν ↔ μ ≠ ν := by rw [lt_iff_le_and_ne, and_iff_right (wasserstein2_nonneg μ ν), ne_comm] exact not_congr (wasserstein2_eq_zero_iff_of_compact_support μ ν hK hY hμ hν) /-- Compact support discharges both the finite-cost and integrability hypotheses in the Lipschitz testing inequality. -/ theorem integral_test_le_wasserstein2_of_compact_support {d : ℕ} (μ ν : Measure (E d)) [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] {K Y : Set (E d)} (hK : IsCompact K) (hY : IsCompact Y) (hμ : IsSupported μ K) (hν : IsSupported ν Y) {L : ℝ≥0} {f : E d → ℝ} (hf : LipschitzWith L f) : |(∫ x, f x ∂μ) - ∫ y, f y ∂ν| ≤ L * wasserstein2 μ ν := by exact integral_test_le_wasserstein2 (exists_finite_cost_coupling_of_compact_support μ ν hK hY hμ hν) hf (hμ.integrable_continuousOn hK hf.continuous.continuousOn) (hν.integrable_continuousOn hY hf.continuous.continuousOn) /-- On compact supports, Wasserstein convergence implies weak convergence without an additional finite-cost hypothesis; the compact supports may vary with the index. -/ theorem tendsto_probabilityMeasure_of_compact_wasserstein2_tendsto_zero {d : ℕ} {ι : Type*} {l : Filter ι} [l.IsCountablyGenerated] {μs : ι → ProbabilityMeasure (E d)} {ν : ProbabilityMeasure (E d)} {Ks : ι → Set (E d)} {Y : Set (E d)} (hKs : ∀ i, IsCompact (Ks i)) (hY : IsCompact Y) (hμs : ∀ i, IsSupported (μs i : Measure (E d)) (Ks i)) (hν : IsSupported (ν : Measure (E d)) Y) (hW : Tendsto (fun i => wasserstein2 (μs i : Measure (E d)) (ν : Measure (E d))) l (𝓝 0)) : Tendsto μs l (𝓝 ν) := by exact tendsto_probabilityMeasure_of_wasserstein2_tendsto_zero (fun i => exists_finite_cost_coupling_of_compact_support (μs i : Measure (E d)) (ν : Measure (E d)) (hKs i) hY (hμs i) hν) hW end Problem358 end end OAI