import Mathlib import OAI.Probability.LogConcave.Sampling.TiltedExpectation import OAI.Probability.LogConcave.JetEstimates.Bound namespace OAI section section noncomputable section open MeasureTheory Filter open scoped ENNReal NNReal Topology section UpperProof open MeasureTheory ProbabilityTheory Filter open scoped ENNReal NNReal RealInnerProductSpace Topology namespace LogConcaveSampling open MeasureTheory lemma HasGaussianLowerTail.hasExpMoments {d : ℕ} {H : Point d → ℝ} (ht : HasGaussianLowerTail H) (hc : Continuous H) : Appell.HasExpMoments (gibbs H) := by have hi := integrable_tilted H hc continuous_const ht (growth_const (1:ℝ)) 0 simp only [inner_zero_left,zero_sub,smul_eq_mul,mul_one] at hi obtain ⟨m,hm,C,ht⟩ := ht intro R apply integrable_gibbs_of_weighted hc hi have hct : Continuous (fun x => Real.exp (-H x)*Real.exp (R*‖x‖)) := hc.neg.rexp.mul ((continuous_const.mul continuous_norm).rexp) apply ((integrable_gaussian_envelope d (b := m/2) (by positivity)).const_mul (Real.exp (C+R^2/(2*m)))).mono' hct.aestronglyMeasurable filter_upwards [] with x rw [norm_mul,Real.norm_eq_abs,abs_of_pos (Real.exp_pos _),Real.norm_eq_abs, abs_of_pos (Real.exp_pos _),← Real.exp_add,← Real.exp_add] apply Real.exp_le_exp.mpr have hyp : R*‖x‖ ≤ (m/2)*‖x‖^2+R^2/(2*m) := by have hh := sq_nonneg (m*‖x‖-R) have hd : R^2/(2*m)*(2*m)=R^2 := by field_simp nlinarith linarith [ht x] lemma Primitive.hasExpMoments {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r : ℝ} (hr : 0 ≤ r) (hl : (lam:ℝ)*r^2 < 1) : Appell.HasExpMoments (gibbs (primitivePotential F x r)) := (hF.hasGaussianLowerTail x hr hl).hasExpMoments (hF.continuous_potential x r) namespace Appell lemma HasExpMoments.map_lipschitz {E F : Type} [NormedAddCommGroup E] [NormedAddCommGroup F] [MeasurableSpace E] [BorelSpace E] [MeasurableSpace F] [BorelSpace F] {μ : Measure E} (hμ : HasExpMoments μ) {S : E → F} {K : ℝ≥0} (hS : LipschitzWith K S) : HasExpMoments (μ.map S) := by intro R apply (integrable_map_measure ((continuous_const.mul continuous_norm).rexp).aestronglyMeasurable hS.continuous.aemeasurable).2 apply ((hμ (|R| *K)).const_mul (Real.exp (|R| *‖S 0‖))).mono' ((continuous_const.mul hS.continuous.norm).rexp).aestronglyMeasurable filter_upwards [] with x change ‖Real.exp (R*‖S x‖)‖ ≤ _ rw [Real.norm_eq_abs,abs_of_pos (Real.exp_pos _),← Real.exp_add] apply Real.exp_le_exp.mpr have hb : ‖S x‖ ≤ K*‖x‖+‖S 0‖ := by have hh := hS.dist_le_mul x 0 simp only [dist_eq_norm,sub_zero] at hh have hh' := norm_add_le (S x-S 0) (S 0) rw [sub_add_cancel] at hh' linarith have ht := mul_le_mul_of_nonneg_left hb (abs_nonneg R) have hr := mul_le_mul_of_nonneg_right (le_abs_self R) (norm_nonneg (S x)) nlinarith end Appell end LogConcaveSampling namespace LogConcaveSampling open MeasureTheory open scoped ENNReal theorem gibbs_map_equiv {d : ℕ} {H : Point d → ℝ} (hH : Continuous H) (e : Point d ≃ᵐ Point d) {c : ℝ≥0∞} (hc0 : c≠0) (hct : c≠⊤) (he : (volume : Measure (Point d)).map e=c • volume) : (gibbs H).map e=gibbs (fun y => H (e.symm y)) := by have hm : ((volume : Measure (Point d)).withDensity (gibbsDensity H)).map e = c • volume.withDensity (gibbsDensity (fun y => H (e.symm y))) := by rw [EulerDensity.map_withDensity_equiv volume e (by unfold gibbsDensity; fun_prop), he,withDensity_smul_measure] rfl have hp : partition H=c*partition (fun y => H (e.symm y)) := by have hh := congrArg (fun μ : Measure (Point d) => μ Set.univ) hm simpa only [Measure.map_apply e.measurable MeasurableSet.univ,Set.preimage_univ, Measure.smul_apply,smul_eq_mul,withDensity_apply _ MeasurableSet.univ, Measure.restrict_univ,partition] using hh unfold gibbs rw [Measure.map_smul _ e.measurable.aemeasurable,hm,hp,smul_smul, ENNReal.mul_inv (Or.inl hc0) (Or.inl hct)] congr 1 calc (c⁻¹*(partition (fun y => H (e.symm y)))⁻¹)*c = (c⁻¹*c)*(partition (fun y => H (e.symm y)))⁻¹ := by ac_rfl _ = _ := by rw [ENNReal.inv_mul_cancel hc0 hct,one_mul] lemma gibbs_map_smul {d : ℕ} {H : Point d → ℝ} (hH : Continuous H) {s : ℝ} (hs : s≠0) : (gibbs H).map (fun z => s • z)=gibbs (fun z => H (s⁻¹ • z)) := by let e := (Homeomorph.smulOfNeZero (α := Point d) s hs).toMeasurableEquiv have he : (volume : Measure (Point d)).map e = ENNReal.ofReal |(s^d)⁻¹| • volume := by convert! Measure.map_addHaar_smul (volume : Measure (Point d)) hs using 1 simp [Point] have h := gibbs_map_equiv hH e (by positivity : ENNReal.ofReal |(s^d)⁻¹| ≠ 0) ENNReal.ofReal_ne_top he change (gibbs H).map e = _ rw [h] congr 1 lemma gibbs_map_add {d : ℕ} {H : Point d → ℝ} (hH : Continuous H) (v : Point d) : (gibbs H).map (fun z => v+z)=gibbs (fun z => H (z-v)) := by let e := (Homeomorph.addLeft v).toMeasurableEquiv have he : (volume : Measure (Point d)).map e = (1:ℝ≥0∞) • volume := by change (volume : Measure (Point d)).map (fun z => v+z) = _ simpa only [one_smul] using (measurePreserving_add_left (volume : Measure (Point d)) v).map_eq change (gibbs H).map e = _ rw [gibbs_map_equiv hH e (by norm_num) (by norm_num) he] congr 1 funext z apply congrArg H change -v+z=z-v abel lemma gibbs_map_affine {d : ℕ} {H : Point d → ℝ} (hH : Continuous H) (v : Point d) {s : ℝ} (hs : s≠0) : (gibbs H).map (fun z => v+s • z)=gibbs (fun z => H (s⁻¹ • (z-v))) := by change (gibbs H).map ((fun z => v+z) ∘ (fun z => s • z)) = _ rw [← Measure.map_map (show Measurable (fun z : Point d => v+z) by fun_prop) (show Measurable (fun z : Point d => s • z) by fun_prop),gibbs_map_smul hH hs] exact gibbs_map_add (show Continuous (fun z : Point d => H (s⁻¹ • z)) by fun_prop) v end LogConcaveSampling namespace LogConcaveSampling open MeasureTheory open scoped NNReal RealInnerProductSpace def conditionalPotential {d : ℕ} (F : Point d → ℝ) (x : Point d) (r ρ : ℝ) (y z : Point d) : ℝ := ‖z-ρ • y‖^2/(2*(1-ρ^2)) + F (x+r • z) lemma probability_time {ρ : ℝ} (hρ0 : 0≤ρ) (hρ1 : ρ<1) : 0 < 1-ρ^2 ∧ 1-ρ^2 ≤ 1 := by constructor · nlinarith · nlinarith [sq_nonneg ρ] lemma conditionalPotential_pullback {d : ℕ} (F : Point d → ℝ) (x : Point d) (r ρ : ℝ) (y z : Point d) (ha : 0<1-ρ^2) : primitivePotential F (x+r • (ρ • y)) (r*Real.sqrt (1-ρ^2)) ((Real.sqrt (1-ρ^2))⁻¹ • (z-ρ • y)) = conditionalPotential F x r ρ y z := by have hs : Real.sqrt (1-ρ^2) ≠ 0 := (Real.sqrt_pos.mpr ha).ne' have hv : x+r • (ρ • y)+(r*Real.sqrt (1-ρ^2)) • ((Real.sqrt (1-ρ^2))⁻¹ • (z-ρ • y))=x+r • z := by rw [← mul_smul r ρ y,smul_smul,mul_assoc,mul_inv_cancel₀ hs,mul_one,smul_sub] rw [smul_smul] abel unfold primitivePotential conditionalPotential rw [hv,norm_smul,Real.norm_eq_abs,mul_pow,sq_abs,inv_pow,Real.sq_sqrt ha.le] congr 1 field_simp lemma conditionalLaw_map {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) (r ρ : ℝ) (y : Point d) (ha : 0<1-ρ^2) : (gibbs (primitivePotential F (x+r • (ρ • y)) (r*Real.sqrt (1-ρ^2)))).map (fun z => ρ • y+Real.sqrt (1-ρ^2) • z) = gibbs (conditionalPotential F x r ρ y) := by rw [gibbs_map_affine (hF.continuous_potential _ _) _ (Real.sqrt_pos.mpr ha).ne'] congr 1 funext z exact conditionalPotential_pullback F x r ρ y z ha lemma conditional_smallness {lam : ℝ≥0} {r ρ : ℝ} (hl : (lam:ℝ)*r^2 ≤ 1/2) (ha : 0<1-ρ^2) (ha1 : 1-ρ^2≤1) : (lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2 ≤ 1/2 := by rw [mul_pow,Real.sq_sqrt ha.le] have hn : 0≤(lam:ℝ)*r^2 := mul_nonneg lam.coe_nonneg (sq_nonneg r) calc (lam:ℝ)*(r^2*(1-ρ^2))=((lam:ℝ)*r^2)*(1-ρ^2) := by ring _ ≤ ((lam:ℝ)*r^2)*1 := mul_le_mul_of_nonneg_left ha1 hn _ ≤ 1/2 := by simpa using hl lemma conditionalLaw_probability {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0≤r) (hl : (lam:ℝ)*r^2 ≤ 1/2) (hρ0 : 0≤ρ) (hρ1 : ρ<1) (y : Point d) : IsProbabilityMeasure (gibbs (conditionalPotential F x r ρ y)) := by obtain ⟨ha,ha1⟩ := probability_time hρ0 hρ1 have hs := conditional_smallness hl ha ha1 have hsmall : (lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2 < 1 := by linarith have hrad : 0≤r*Real.sqrt (1-ρ^2) := mul_nonneg hr (Real.sqrt_nonneg _) have : IsProbabilityMeasure (gibbs (primitivePotential F (x+r • (ρ • y)) (r*Real.sqrt (1-ρ^2)))) := probability_gibbs_of_partition (partition_pos_of_continuous (hF.continuous_potential _ _)).ne' (partition_ne_top_of_integrable (hF.integrable_exp_neg_potential _ hrad hsmall)) rw [← conditionalLaw_map hF x r ρ y ha] infer_instance lemma conditionalLaw_hasPoincare {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) (x : Point d) {r ρ : ℝ} (hr : 0≤r) (hl : (lam:ℝ)*r^2 ≤ 1/2) (hρ0 : 0≤ρ) (hρ1 : ρ<1) (y : Point d) : HasPoincare (gibbs (conditionalPotential F x r ρ y)) ((Real.pi^2/2)*(1-ρ^2)) := by obtain ⟨ha,ha1⟩ := probability_time hρ0 hρ1 have hs := conditional_smallness hl ha ha1 have hsmall : (lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2 < 1 := by linarith have hrad : 0≤r*Real.sqrt (1-ρ^2) := mul_nonneg hr (Real.sqrt_nonneg _) have : IsProbabilityMeasure (gibbs (primitivePotential F (x+r • (ρ • y)) (r*Real.sqrt (1-ρ^2)))) := probability_gibbs_of_partition (partition_pos_of_continuous (hF.continuous_potential _ _)).ne' (partition_ne_top_of_integrable (hF.integrable_exp_neg_potential _ hrad hsmall)) let K : ℝ≥0 := ⟨Real.sqrt (1-ρ^2),Real.sqrt_nonneg _⟩ have hK : LipschitzWith K (fun z : Point d => ρ • y+Real.sqrt (1-ρ^2) • z) := by apply LipschitzWith.of_dist_le_mul intro u v simp only [dist_eq_norm,add_sub_add_left_eq_sub,← smul_sub,norm_smul, Real.norm_eq_abs,abs_of_nonneg (Real.sqrt_nonneg _)] rfl have hB : 0≤(Real.pi^2/8)*(2/(1-(lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2)) := by positivity have hp := (hF.hasPoincare (x+r • (ρ • y)) hrad hsmall).map hB (show ContDiff ℝ 1 (fun z : Point d => ρ • y+Real.sqrt (1-ρ^2) • z) by fun_prop) hK rw [conditionalLaw_map hF x r ρ y ha] at hp apply hp.mono change (Real.pi^2/8)*(2/(1-(lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2)) * (Real.sqrt (1-ρ^2))^2 ≤ _ rw [Real.sq_sqrt ha.le] apply mul_le_mul_of_nonneg_right _ ha.le have hd : 0<1-(lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2 := sub_pos.mpr hsmall have hb : 2/(1-(lam:ℝ)*(r*Real.sqrt (1-ρ^2))^2) ≤ 4 := by apply (div_le_iff₀ hd).mpr linarith nlinarith [mul_le_mul_of_nonneg_left hb (by positivity : (0:ℝ)≤Real.pi^2/8)] end LogConcaveSampling end UpperProof end end end end OAI