import Mathlib import OAI.Probability.LogConcave.Dynamics.Squared namespace OAI section noncomputable section namespace LogConcaveSampling.Coupling open MeasureTheory ProbabilityTheory Function open scoped Classical variable {Ω Γ W : Type*} [MeasurableSpace Ω] [MeasurableSpace Γ] [MeasurableSpace W] {d e : ℕ} theorem SquaredAt.shared_lipschitz {μ : Measure Ω} {ν : Measure Γ} [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] (η : Measure W) [IsProbabilityMeasure η] {f : Ω → Point d} {g : Γ → Point d} (hf : Measurable f) (hg : Measurable g) {B K : ℝ} (hK : 0≤K) (hc : SquaredAt μ ν f g B) (H : Point d → W → Point e) (hH : Measurable (uncurry H)) (hLip : ∀x y w,‖H x w-H y w‖≤K*‖x-y‖) : SquaredAt (μ.prod η) (ν.prod η) (fun z => H (f z.1) z.2) (fun z => H (g z.1) z.2) (K^2*B) := by obtain ⟨κ,hκ,hl,hr,hi,he⟩ := hc let := hκ let Λ := κ.prod η have hΛf : Λ.map (fun z => (z.1.1,z.2))=μ.prod η := by rw [show (fun z : (Ω × Γ) × W => (z.1.1,z.2))=Prod.map Prod.fst id from rfl] rw [←Measure.map_prod_map _ _ measurable_fst measurable_id,Measure.map_id] exact congrArg (fun m => m.prod η) hl have hΛg : Λ.map (fun z => (z.1.2,z.2))=ν.prod η := by rw [show (fun z : (Ω × Γ) × W => (z.1.2,z.2))=Prod.map Prod.snd id from rfl] rw [←Measure.map_prod_map _ _ measurable_snd measurable_id,Measure.map_id] exact congrArg (fun m => m.prod η) hr have hm : Measurable (fun z : Ω × Γ => ‖f z.1-g z.2‖^2) := by fun_prop have hi' : Integrable (fun z : (Ω × Γ) × W => ‖f z.1.1-g z.1.2‖^2) Λ := hi.comp_fst η have hp (z : (Ω × Γ) × W) : ‖H (f z.1.1) z.2-H (g z.1.2) z.2‖^2≤ K^2*‖f z.1.1-g z.1.2‖^2 := by simpa only [mul_pow] using pow_le_pow_left₀ (norm_nonneg _) (hLip _ _ _) 2 have hcmeas : Measurable (fun z : (Ω × Γ) × W => ‖H (f z.1.1) z.2-H (g z.1.2) z.2‖^2) := by have h₁ : Measurable (fun z : (Ω × Γ) × W => H (f z.1.1) z.2) := hH.comp ((hf.comp (measurable_fst.comp measurable_fst)).prodMk measurable_snd) have h₂ : Measurable (fun z : (Ω × Γ) × W => H (g z.1.2) z.2) := hH.comp ((hg.comp (measurable_snd.comp measurable_fst)).prodMk measurable_snd) exact (h₁.sub h₂).norm.pow_const 2 have hdom := hi'.const_mul (K^2) have hIi := hdom.mono' hcmeas.aestronglyMeasurable (Filter.Eventually.of_forall fun z => by simpa only [Real.norm_eq_abs,abs_sq] using hp z) refine SquaredAt.of_joint Λ (μ.prod η) (ν.prod η) (fun z => (z.1.1,z.2)) (fun z => (z.1.2,z.2)) (by fun_prop) (by fun_prop) hΛf hΛg _ _ ?_ ?_ hIi ?_ · exact hH.comp ((hf.comp measurable_fst).prodMk measurable_snd) · exact hH.comp ((hg.comp measurable_fst).prodMk measurable_snd) · apply (integral_mono hIi hdom hp).trans rw [integral_const_mul] have hfst : ∫z : (Ω × Γ) × W, ‖f z.1.1-g z.1.2‖^2 ∂Λ = ∫z, ‖f z.1-g z.2‖^2 ∂κ := by exact (measurePreserving_fst (μ:=κ) (ν:=η)).hasLaw.integral_comp hm.aestronglyMeasurable rw [hfst] exact mul_le_mul_of_nonneg_left he (pow_nonneg hK 2) lemma SquaredAt.add_shared {μ : Measure Ω} {ν : Measure Γ} [IsProbabilityMeasure μ] [IsProbabilityMeasure ν] (η : Measure W) [IsProbabilityMeasure η] {f : Ω → Point d} {g : Γ → Point d} (hf : Measurable f) (hg : Measurable g) {B : ℝ} (hc : SquaredAt μ ν f g B) (h : W → Point d) (hh : Measurable h) : SquaredAt (μ.prod η) (ν.prod η) (fun z => f z.1+h z.2) (fun z => g z.1+h z.2) B := by simpa only [one_pow,one_mul] using hc.shared_lipschitz η hf hg (by norm_num : (0:ℝ)≤1) (fun x w => x+h w) (by fun_prop) (fun x y w => by rw [add_sub_add_right_eq_sub,one_mul]) end LogConcaveSampling.Coupling end end section noncomputable section namespace LogConcaveSampling.Coupling open MeasureTheory ProbabilityTheory Function open scoped Classical variable {X Ω Γ : Type*} [MeasurableSpace X] [MeasurableSpace Ω] [MeasurableSpace Γ] {d : ℕ} theorem SquaredAt.mixture (μ : Measure X) [IsProbabilityMeasure μ] (ν : Measure Ω) [IsProbabilityMeasure ν] (θ : Measure Γ) [IsProbabilityMeasure θ] (K : Kernel X (Ω × Γ)) [IsMarkovKernel K] (hl : ∀x,(K x).fst=ν) (hr : ∀x,(K x).snd=θ) (f : X → Ω → Point d) (g : X → Γ → Point d) (hf : Measurable (uncurry f)) (hg : Measurable (uncurry g)) (B : X → ℝ) (hB : Integrable B μ) (hi : ∀x,Integrable (fun z => ‖f x z.1-g x z.2‖^2) (K x)) (he : ∀x,(∫z,‖f x z.1-g x z.2‖^2 ∂K x)≤B x) : SquaredAt (μ.prod ν) (μ.prod θ) (uncurry f) (uncurry g) (∫x,B x ∂μ) := by let Λ := μ ⊗ₘ K let F : X × (Ω × Γ) → ℝ := fun z => ‖f z.1 z.2.1-g z.1 z.2.2‖^2 have hF : Measurable F := by unfold F; fun_prop have hFi : Integrable (fun x => ∫z,F (x,z) ∂K x) μ := by apply hB.mono' hF.stronglyMeasurable.integral_kernel_prod_right'.aestronglyMeasurable exact Filter.Eventually.of_forall (fun x => by rw [Real.norm_of_nonneg (integral_nonneg fun _ => sq_nonneg _)] exact he x) have hI : Integrable F Λ := by apply (Measure.integrable_compProd_iff hF.aestronglyMeasurable).mpr refine ⟨Filter.Eventually.of_forall hi,?_⟩ simpa only [F,Real.norm_eq_abs,abs_sq] using hFi have hleft : K.map Prod.fst=Kernel.const X ν := by ext x s hs rw [Kernel.map_apply _ measurable_fst] exact congrArg (fun m : Measure Ω => m s) (hl x) have hright : K.map Prod.snd=Kernel.const X θ := by ext x s hs rw [Kernel.map_apply _ measurable_snd] exact congrArg (fun m : Measure Γ => m s) (hr x) apply SquaredAt.of_joint Λ (μ.prod ν) (μ.prod θ) (fun z => (z.1,z.2.1)) (fun z => (z.1,z.2.2)) (by fun_prop) (by fun_prop) ?_ ?_ (uncurry f) (uncurry g) hf hg hI · change (∫z,F z ∂Λ)≤_ rw [Measure.integral_compProd hI] exact integral_mono hFi hB he · change Λ.map (Prod.map id Prod.fst)=_ dsimp only [Λ] rw [←Measure.compProd_map measurable_fst,hleft,Measure.compProd_const] · change Λ.map (Prod.map id Prod.snd)=_ dsimp only [Λ] rw [←Measure.compProd_map measurable_snd,hright,Measure.compProd_const] end LogConcaveSampling.Coupling end end section noncomputable section namespace LogConcaveSampling.Coupling open MeasureTheory ProbabilityTheory Function Set TopologicalSpace open scoped Classical variable {X Ω Γ : Type*} [PseudoMetricSpace X] [SeparableSpace X] [Nonempty X] [MeasurableSpace X] [BorelSpace X] [MeasurableSpace Ω] [MeasurableSpace Γ] {d : ℕ} theorem SquaredAt.random_anchor (μ : Measure X) [IsProbabilityMeasure μ] (ν : Measure Ω) [IsProbabilityMeasure ν] (θ : Measure Γ) [IsProbabilityMeasure θ] (f : X → Ω → Point d) (g : X → Γ → Point d) (hf : Measurable (uncurry f)) (hg : Measurable (uncurry g)) (ρ : X → ℝ) (hρ : ∀x,1≤ρ x) (hρlip : ∀x y,ρ y≤ρ x+dist x y) (hρi : Integrable (fun x => (ρ x)^2) μ) {Lf Lg E : ℝ} (hLf : 0≤Lf) (hLg : 0≤Lg) (hE : 0 E^2*(ρ x)^2) hLf hLg he hfl hgl hc let := hK have hb (x) : 2*(E^2*(ρ (denseSeq X (q x)))^2)+2*((Lf+Lg)*e)^2≤10*E^2*(ρ x)^2 := by have hh : ρ (denseSeq X (q x)) ≤ ρ x + e := by calc _ ≤ ρ x + dist x (denseSeq X (q x)) := hρlip _ _ _ ≤ ρ x + e := by gcongr; exact (hqe x).le have hρx := hρ x have hρy := hρ (denseSeq X (q x)) have hy : (ρ (denseSeq X (q x)))^2≤4*(ρ x)^2 := by nlinarith have hys := mul_le_mul_of_nonneg_left hy (sq_nonneg E) have hz : ((Lf+Lg)*e)^2≤E^2 := pow_le_pow_left₀ (by positivity) heE 2 nlinarith [sq_nonneg E,mul_nonneg (sq_nonneg E) (show 0≤(ρ x)^2-1 by nlinarith)] have hm := SquaredAt.mixture μ ν θ K (fun x => (hcouple x).1) (fun x => (hcouple x).2.1) f g hf hg (fun x => 10*E^2*(ρ x)^2) (hρi.const_mul _) (fun x => (hcouple x).2.2.1) (fun x => (hcouple x).2.2.2.trans (hb x)) simpa only [integral_const_mul] using hm end LogConcaveSampling.Coupling end end end OAI