import Mathlib import OAI.Probability.LogConcave.Sampling.TerminalBackward import OAI.Probability.LogConcave.Numerics.ParametricFDeriv import OAI.Probability.LogConcave.Sampling.JointU import OAI.Probability.LogConcave.Sampling.ConditionalPositionMoment import OAI.Probability.LogConcave.Sampling.JointConditionalLawProperties import OAI.Probability.LogConcave.JetEstimates.JetNormalizedLaplaceMoments namespace OAI section section noncomputable section namespace LogConcaveSampling open MeasureTheory ProbabilityTheory Filter open scoped Topology Classical BigOperators NNReal RealInnerProductSpace lemma conditionalU_moments_sq {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0 conditionalPositionMoment F x r v t (ρ,y)) s* conditionalMixedMoment F x r u v (l.toFinset\s) (ρ,y) := by let := conditionalLaw_probability_sq hF x hr.le hl hρ y rw [conditionalU_normalized_jet_sq hF x hr hlam hl hρ] rw [Appell.jet_normalizedLaplace_zero_moments (conditionalLaw_hasExpMoments_sq hF x hr.le hl hρ y) (continuous_const.inner (primitiveField_contDiff hF x r).continuous) (primitiveField_inner_growth hF x u hr.le) v l hlN] rfl theorem conditionalU_joint_smooth {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r : ℝ} (hr : 0 conditionalU F x r q.1 q.2 u ((lam:ℝ)*r) v l) p := by have hl' : (lam:ℝ)*r^2<1 := by linarith have hM (s : Finset ι) := conditionalPositionMoment_smooth hF x hr.le hl' v s p hp have hI (s : Finset ι) := Appell.inverseMoment_contDiffAt hM s have hX (s : Finset ι) := conditionalMixedMoment_smooth hF x hr.le hl' u v s p hp have hS : ContDiffAt ℝ (⊤:ℕ∞) (fun q => ∑s∈l.toFinset.powerset, Appell.inverseMoment (fun t => conditionalPositionMoment F x r v t q) s* conditionalMixedMoment F x r u v (l.toFinset\s) q) p := ContDiffAt.sum (fun s _ => (hI s).mul (hX _)) have hA : ContDiffAt ℝ (⊤:ℕ∞) (fun q : ℝ × Point d => ((1-q.1^2)^l.length)⁻¹) p := ((contDiffAt_const.sub (contDiffAt_fst.pow 2)).pow _).inv (pow_ne_zero _ (by linarith)) apply (hA.mul hS).congr_of_eventuallyEq filter_upwards [(isOpen_lt (continuous_fst.pow 2) continuous_const).mem_nhds hp] with q hq exact conditionalU_moments_sq hF x hr hlam hl hq v l hlN u q.2 lemma jointU_timeSmooth {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r : ℝ} (hr : 0 EuclideanSpace.basisFun (Fin d) ℝ j) [()] • coordinateRankOne d i j variable {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r T : ℝ} (hr : 0 EuclideanSpace.basisFun (Fin d) ℝ j) [()] (by simp) (EuclideanSpace.basisFun (Fin d) ℝ i) p hp).smul contDiffAt_const def terminalJacobian (p : ℝ × Point d) : Point d →L[ℝ] Point d := (fderiv ℝ (terminalForward hF x hr.le hl hT0 hT1) (smoothTimeClip hT0 hT1 p.1,terminalBackward hF x hr.le hl hT0 hT1 p)).comp (ContinuousLinearMap.inr ℝ ℝ (Point d)) lemma terminalJacobian_smooth : ContDiff ℝ (⊤:ℕ∞) (terminalJacobian hF x hr hl hT0 hT1) := by have hclip : ContDiff ℝ (⊤:ℕ∞) (smoothTimeClip hT0 hT1) := contDiff_infty.mpr (smoothTimeClip_contDiff hT0 hT1) exact (((terminalForward_smooth hF x hr.le hl hT0 hT1).fderiv_right (by simp)).comp ((hclip.comp contDiff_fst).prodMk (terminalBackward_smooth hF x hr.le hl hT0 hT1))).clm_comp contDiff_const def steinIntegrand (p : ℝ × Point d) : Point d →L[ℝ] Point d := (terminalJacobian hF x hr hl hT0 hT1 p).comp (conditionalFirstJet F x r ((lam:ℝ)*r) (smoothTimeClip hT0 hT1 p.1,terminalBackward hF x hr.le hl hT0 hT1 p)) include hlam in lemma steinIntegrand_smooth : ContDiff ℝ (⊤:ℕ∞) (steinIntegrand hF x hr hl hT0 hT1) := by have hclip : ContDiff ℝ (⊤:ℕ∞) (smoothTimeClip hT0 hT1) := contDiff_infty.mpr (smoothTimeClip_contDiff hT0 hT1) have hU : ContDiff ℝ (⊤:ℕ∞) (fun p => conditionalFirstJet F x r ((lam:ℝ)*r) (smoothTimeClip hT0 hT1 p.1,terminalBackward hF x hr.le hl hT0 hT1 p)) := by apply contDiff_iff_contDiffAt.mpr intro p exact (conditionalFirstJet_smooth hF x hr hlam hl _ (smoothTimeClip_sq_lt hT0 hT1 p.1)).comp p ((hclip.comp contDiff_fst).prodMk (terminalBackward_smooth hF x hr.le hl hT0 hT1)).contDiffAt exact (terminalJacobian_smooth hF x hr hl hT0 hT1).clm_comp hU def centeringKernel (y : Point d) : Point d →L[ℝ] Point d := (∫ρ in Icc 0 T,steinIntegrand hF x hr hl hT0 hT1 (ρ,y)).adjoint include hlam in lemma centeringKernel_smooth : ContDiff ℝ (⊤:ℕ∞) (centeringKernel hF x hr hl hT0 hT1) := by let : CompleteSpace (Point d →L[ℝ] Point d) := ContinuousLinearMap.instCompleteSpace have hs := CompactIntegral.smooth_parametric ((steinIntegrand_smooth hF x hr hlam hl hT0 hT1).comp (contDiff_snd.prodMk contDiff_fst)) (s:=Icc (0:ℝ) T) isCompact_Icc exact ContinuousLinearMap.adjoint.contDiff.comp hs end LogConcaveSampling end end section noncomputable section namespace LogConcaveSampling open MeasureTheory ProbabilityTheory Set open scoped Classical BigOperators NNReal RealInnerProductSpace lemma covariance_field_synthesis {d : ℕ} {μ : Measure (Point d)} [IsProbabilityMeasure μ] {f : Point d → ℝ} {g : Point d → Point d} (hf : MemLp f 2 μ) (hg : ∀u,MemLp (fun z => inner ℝ u (g z)) 2 μ) (v : Point d) : (∑i : Fin d,inner ℝ v ((EuclideanSpace.basisFun (Fin d) ℝ) i)* cov[f,(fun z => inner ℝ ((EuclideanSpace.basisFun (Fin d) ℝ) i) (g z));μ])= cov[f,(fun z => inner ℝ v (g z));μ] := by let b := EuclideanSpace.basisFun (Fin d) ℝ have hh := covariance_fun_sum_right (fun i : Fin d => (hg (b i)).const_mul (inner ℝ v (b i))) hf simp only [covariance_const_mul_right] at hh simpa only [b.sum_inner_mul_inner v] using hh.symm variable {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0 inner ℝ v z), (fun z => inner ℝ u (primitiveField F x r z));gibbs (conditionalPotential F x r ρ y)] := by let b := EuclideanSpace.basisFun (Fin d) ℝ let μ := gibbs (conditionalPotential F x r ρ y) let := conditionalLaw_probability hF x hr.le hl hρ0 hρ1 y have hm := conditionalLaw_hasExpMoments hF x hr.le hl hρ0 hρ1 y have hi (v : Point d) : MemLp (fun z => inner ℝ v z) 2 μ := (Appell.HasGrowth.linear (innerSL ℝ v)).memLp (by fun_prop) hm.hasMoments have hg (u : Point d) : MemLp (fun z => inner ℝ u (primitiveField F x r z)) 2 μ := (primitiveField_inner_growth hF x u hr.le).memLp (continuous_const.inner (primitiveField_contDiff hF x r).continuous).aestronglyMeasurable hm.hasMoments simp only [conditionalFirstJet,sum_apply,smul_apply, inner_sum,inner_smul_right,coordinateRankOne,ContinuousLinearMap.smulRight_apply, innerSL_apply_apply,conditionalU_one_cov hF x hr hlam hl hρ0 hρ1] change (∑i,∑j,(1/(1-ρ^2))*cov[(fun z => inner ℝ (b j) z), (fun z => inner ℝ (b i) (primitiveField F x r z));μ]*(inner ℝ (b j) v*inner ℝ u (b i)))=_ calc _=(1/(1-ρ^2))*(∑i,inner ℝ u (b i)*(∑j,inner ℝ v (b j)* cov[(fun z => inner ℝ (b j) z),(fun z => inner ℝ (b i) (primitiveField F x r z));μ])) := by simp only [Finset.mul_sum] apply Finset.sum_congr rfl intro i _ apply Finset.sum_congr rfl intro j _ rw [real_inner_comm (b j) v] ring _=_ := by have hs (i : Fin d) := covariance_inner_synthesis hm (hg (b i)) v dsimp [μ,b] at hs ⊢ simp only [hs] rw [covariance_field_synthesis (hi v) hg u] include hF hr hlam hl hρ0 hρ1 in lemma conditionalFirstJet_norm_le (y : Point d) : ‖conditionalFirstJet F x r ((lam:ℝ)*r) (ρ,y)‖≤(Real.pi^2/2)*((lam:ℝ)*r) := by have ha := (probability_time hρ0 hρ1).1 apply ContinuousLinearMap.opNorm_le_bound _ (by positivity) intro v let w := conditionalFirstJet F x r ((lam:ℝ)*r) (ρ,y) v have he := conditionalFirstJet_inner hF x hr hlam hl hρ0 hρ1 w v y have hb := mul_le_mul_of_nonneg_left (conditional_covariance_le hF x hr.le hl hρ0 hρ1 w v y) (by positivity : 0≤1/(1-ρ^2)) have hh : ‖w‖^2≤((Real.pi^2/2)*((lam:ℝ)*r))*‖w‖*‖v‖ := by rw [←real_inner_self_eq_norm_sq w,he] calc _≤(1/(1-ρ^2))*|cov[(fun z => inner ℝ v z), (fun z => inner ℝ w (primitiveField F x r z));gibbs (conditionalPotential F x r ρ y)]| := mul_le_mul_of_nonneg_left (le_abs_self _) (by positivity) _≤_ := by convert! hb using 1; field_simp [ha.ne'] change ‖w‖≤_ by_cases hw : ‖w‖=0 · rw [hw]; positivity · apply (mul_le_mul_iff_left₀ (lt_of_le_of_ne (norm_nonneg w) (Ne.symm hw))).mp convert! hh using 1 <;> ring include hF hr hlam hl hρ0 hρ1 in lemma conditionalFirstJet_deriv (y : Point d) : fderiv ℝ (conditionalFieldMean F x r ρ) y= ρ • conditionalFirstJet F x r ((lam:ℝ)*r) (ρ,y) := by apply ContinuousLinearMap.ext intro v apply ext_inner_left ℝ intro u simp only [smul_apply,inner_smul_right, conditionalFieldMean_inner_deriv hF x hr.le hl hρ0 hρ1, conditionalFirstJet_inner hF x hr hlam hl hρ0 hρ1] ring end LogConcaveSampling end end section noncomputable section namespace LogConcaveSampling open MeasureTheory Set Function open scoped NNReal Topology variable {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r T : ℝ} (hr : 0 terminalForward hF x hr.le hl hT0 hT1 (t,z))= probabilityTransport hF x hr.le hl hT0 hT1 t ⟨T,hT0,le_rfl⟩ := funext (terminalForward_eq hF x hr.le hl hT0 hT1 t) change HasFDerivAt (fun z => terminalForward hF x hr.le hl hT0 hT1 (t,z)) _ _ at hh rw [he] at hh change HasFDerivAt _ ((fderiv ℝ (terminalForward hF x hr.le hl hT0 hT1) ((t:ℝ),terminalBackward hF x hr.le hl hT0 hT1 (t,y))).comp (ContinuousLinearMap.inr ℝ ℝ (Point d))) _ at hh simpa only [terminalJacobian,smoothTimeClip_eq hT0 hT1 t.2] using hh.fderiv.symm lemma terminalJacobian_norm_le (t : Icc (0:ℝ) T) (y : Point d) : ‖terminalJacobian hF x hr hl hT0 hT1 (t,y)‖≤Real.exp (Real.pi^2/4) := by rw [terminalJacobian_eq] have hb := norm_fderiv_le_of_lipschitz ℝ (x₀:=terminalBackward hF x hr.le hl hT0 hT1 (t,y)) (GlobalODE.flow_lipschitz (fun u (_ : u∈Icc 0 T) => clampedProbabilityVelocity_lipschitz hF x hr.le hl hT0 hT1 u) (clampedProbabilityVelocity_continuous hF x hr.le hl hT0 hT1) t ⟨T,hT0,le_rfl⟩) apply hb.trans apply Real.exp_le_exp.mpr have ht : 0≤T-(t:ℝ) := sub_nonneg.mpr t.2.2 rw [abs_of_nonneg ht] have htt : T-(t:ℝ)≤1 := by linarith [t.2.1] have hbase : (Real.pi^2/2)*(lam:ℝ)*r^2≤Real.pi^2/4 := by nlinarith [sq_nonneg Real.pi] exact (mul_le_of_le_one_right (by positivity : 0≤(Real.pi^2/2)*(lam:ℝ)*r^2) htt).trans hbase include hlam in lemma steinIntegrand_norm_le (t : Icc (0:ℝ) T) (y : Point d) : ‖steinIntegrand hF x hr hl hT0 hT1 (t,y)‖≤ (Real.exp (Real.pi^2/4)*(Real.pi^2/2))*((lam:ℝ)*r) := by unfold steinIntegrand calc _≤‖terminalJacobian hF x hr hl hT0 hT1 (t,y)‖* ‖conditionalFirstJet F x r ((lam:ℝ)*r) (smoothTimeClip hT0 hT1 t,terminalBackward hF x hr.le hl hT0 hT1 (t,y))‖ := ContinuousLinearMap.opNorm_comp_le _ _ _≤Real.exp (Real.pi^2/4)*((Real.pi^2/2)*((lam:ℝ)*r)) := by rw [smoothTimeClip_eq hT0 hT1 t.2] exact mul_le_mul (terminalJacobian_norm_le hF x hr hl hT0 hT1 t y) (conditionalFirstJet_norm_le hF x hr hlam hl t.2.1 (t.2.2.trans_lt hT1) _) (norm_nonneg _) (Real.exp_pos _).le _=_ := by ring include hlam in theorem centeringKernel_norm_le (y : Point d) : ‖centeringKernel hF x hr hl hT0 hT1 y‖≤ (Real.exp (Real.pi^2/4)*(Real.pi^2/2))*((lam:ℝ)*r) := by unfold centeringKernel rw [ContinuousLinearMap.adjoint.norm_map] have hb := norm_setIntegral_le_of_norm_le_const (μ:=volume) (s:=Icc (0:ℝ) T) (f:=fun t => steinIntegrand hF x hr hl hT0 hT1 (t,y)) isCompact_Icc.measure_lt_top (fun t ht => steinIntegrand_norm_le hF x hr hlam hl hT0 hT1 ⟨t,ht⟩ y) apply hb.trans simp only [Measure.real,Real.volume_Icc,sub_zero,ENNReal.toReal_ofReal hT0] exact mul_le_of_le_one_right (by positivity) hT1.le end LogConcaveSampling end end section noncomputable section namespace LogConcaveSampling open Filter open scoped Topology Classical BigOperators lemma eq_zero_of_continuous_pos {f g : ℝ → ℝ} (hf : ContinuousAt f 0) (hg : ContinuousAt g 0) (he : ∀t,0 smooth_cadj_at (b i) (hs i) (hV i)) end JetCalculus lemma extra_list_nodup {ι : Type*} {l : List ι} (hl : l.Nodup) : (Sum.inr ()::l.map (Sum.inl (β:=Unit))).Nodup := by simp only [List.nodup_cons] refine ⟨?_,hl.map Sum.inl_injective⟩ simp end LogConcaveSampling end end section noncomputable section namespace LogConcaveSampling open Filter open scoped Topology Classical BigOperators NNReal RealInnerProductSpace theorem material_jointU {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0 jointU F x r ((lam:ℝ)*r) (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::l.map Sum.inl) i) (ρ,y)+ 2*r*ρ*∑s∈l.toFinset.powerset.erase ∅,∑k, jointU F x r ((lam:ℝ)*r) v (l.filter (fun j => j∈s)) k (ρ,y)* jointU F x r ((lam:ℝ)*r) (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::(l.filter (fun j => j∉s)).map Sum.inl) i (ρ,y) := by let U := jointU F x r ((lam:ℝ)*r) v l i let V := fun k => jointU F x r ((lam:ℝ)*r) (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::l.map Sum.inl) i let A := JetCalculus.mdir (1,0) jointSpace r (jointMean F x r) U let B := fun p : ℝ × Point d => JetCalculus.gadj jointSpace (jointScore F x r) V p+ 2*r*p.1*∑s∈l.toFinset.powerset.erase ∅,∑k, jointU F x r ((lam:ℝ)*r) v (l.filter (fun j => j∈s)) k p* jointU F x r ((lam:ℝ)*r) (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::(l.filter (fun j => j∉s)).map Sum.inl) i p change A (ρ,y)=B (ρ,y) have hU := jointU_timeSmooth hF x hr hlam hl v l hlN i have hV (k : Fin d) := jointU_timeSmooth hF x hr hlam hl (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::l.map Sum.inl) (extra_list_nodup hlN) i have hpos (t : ℝ) (h0 : 0 (hV k (t,y) (by dsimp; linarith) h1).differentiableAt (by simp)) change JetCalculus.gadj jointSpace (jointScore F x r) V (t,y)=_ at hs change JetCalculus.mdir (1,0) jointSpace r (jointMean F x r) (jointU F x r ((lam:ℝ)*r) v l i) (t,y)=_ rw [he] exact congrArg (fun a => a+2*r*t*∑s∈l.toFinset.powerset.erase ∅,∑k, jointU F x r ((lam:ℝ)*r) v (l.filter (fun j => j∈s)) k (t,y)* jointU F x r ((lam:ℝ)*r) (Sum.elim v (fun _ : Unit => JetCalculus.spaceBasis d k)) (Sum.inr ()::(l.filter (fun j => j∉s)).map Sum.inl) i (t,y)) hs.symm rcases hρ0.eq_or_lt with hzero|hposρ · subst ρ have hz : (0:ℝ)^2<1 := by norm_num have hA : ContDiffAt ℝ (⊤:ℕ∞) A (0,y) := JetCalculus.smooth_mdir_at (1,0) jointSpace r (jointMean_smooth_at hF x hr.le hl hz) (hU (0,y) (by norm_num) (by norm_num)) have hB : ContDiffAt ℝ (⊤:ℕ∞) B (0,y) := by apply ContDiffAt.add · exact JetCalculus.smooth_gadj_at jointSpace (jointScore_smooth_at hF x hr.le hl hz) (fun k => hV k (0,y) (by norm_num) (by norm_num)) · apply ContDiffAt.mul (contDiffAt_const.mul contDiffAt_fst) apply ContDiffAt.sum intro s _ apply ContDiffAt.sum intro k _ exact (jointU_timeSmooth hF x hr hlam hl v _ (hlN.filter _) k (0,y) (by norm_num) (by norm_num)).mul (jointU_timeSmooth hF x hr hlam hl _ _ (extra_list_nodup (hlN.filter _)) i (0,y) (by norm_num) (by norm_num)) have hc : ContinuousAt (fun t : ℝ => (t,y)) 0 := continuousAt_id.prodMk continuousAt_const exact eq_zero_of_continuous_pos (hA.continuousAt.comp (f:=fun t : ℝ => (t,y)) hc) (hB.continuousAt.comp (f:=fun t : ℝ => (t,y)) hc) hpos · exact hpos ρ hposρ hρ1 end LogConcaveSampling end end section noncomputable section namespace LogConcaveSampling open scoped Classical BigOperators NNReal RealInnerProductSpace lemma joint_score_transport_nonneg {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0 JetCalculus.dir (jointSpace i) (jointMean F x r k)) (ρ,y) := by rcases hρ0.eq_or_lt with hz|hpos · subst ρ have hM := jointMean_smooth_at hF x hr.le hl (p:=(0,y)) (by norm_num) have hS := jointScore_smooth_at hF x hr.le hl (p:=(0,y)) (by norm_num) have ha := JetCalculus.smooth_mdir_at (1,0) jointSpace r hM (hS i) have hb := (contDiffAt_const (c:=r)).mul (JetCalculus.smooth_gadj_at jointSpace hS (fun k => JetCalculus.smooth_dir_at (hM k) (jointSpace i))) have hc : ContinuousAt (fun t : ℝ => (t,y)) 0 := continuousAt_id.prodMk continuousAt_const exact eq_zero_of_continuous_pos (ha.continuousAt.comp (f:=fun t : ℝ => (t,y)) hc) (hb.continuousAt.comp (f:=fun t : ℝ => (t,y)) hc) (fun t h0 h1 => joint_score_transport hF x hr hlam hl h0 h1 y i) · exact joint_score_transport hF x hr hlam hl hpos hρ1 y i theorem physical_material_adjoint_nonneg {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0 JetCalculus.mdir (1,0) jointSpace r (jointMean F x r) (V i)) (ρ,y)+ r*JetCalculus.gadj jointSpace (jointScore F x r) (fun k p => ∑i,JetCalculus.dir (jointSpace i) (jointMean F x r k) p*V i p) (ρ,y) := by have hp : ρ^2<1 := by have := (probability_time hρ0 hρ1).1; linarith exact JetCalculus.mdir_gadj_at _ _ _ (jointMean_smooth_at hF x hr.le hl hp) (jointScore_smooth_at hF x hr.le hl hp) hV (joint_score_transport_nonneg hF x hr hlam hl hρ0 hρ1 y) end LogConcaveSampling end end end end OAI