openAI-math-dataset / lean /OAI /Probability /LogConcave /Dynamics /ProbabilityFlowGrowth.lean
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Add lean source and binary files (part 125)
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import Mathlib
import OAI.Probability.LogConcave.Sampling.PairGauge
namespace OAI
section
noncomputable section
namespace LogConcaveSampling
open MeasureTheory ProbabilityTheory
open scoped Classical NNReal
variable {d : ℕ}
lemma probabilityFlow_growth {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam)
(x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1)
(hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) (z : Point d) :
‖fullProbabilityFlow hF x hr hl T z‖≤circuitGrowthConstant*(circuitD F x+‖z‖) := by
have hf := probabilityFlow_initial_displacement hF x hr hl z ⟨hT,hT1.le⟩
have hn := norm_le_norm_sub_add (fullProbabilityFlow hF x hr hl T z) z
rw [field_zero_eq_gradient] at hf
have hD : ‖gradient F x‖≤circuitD F x := le_add_of_nonneg_left (Real.sqrt_nonneg _)
have hd := sqrt_le_circuitD F x
have hc := circuitD_nonneg F x
have h₁ := mul_le_mul_of_nonneg_right hr1 (norm_nonneg (gradient F x))
have h₂ := mul_le_mul_of_nonneg_right (show (lam:ℝ)*r^2≤1 by linarith)
(show 0≤Real.pi*Real.sqrt d+‖z‖ by positivity)
have hp := mul_le_mul_of_nonneg_left hd Real.pi_pos.le
have hb : r*‖gradient F x‖+((lam:ℝ)*r^2)*(Real.pi*Real.sqrt d+‖z‖)≤
(Real.pi+1)*(circuitD F x+‖z‖) := by
nlinarith [mul_nonneg Real.pi_pos.le (norm_nonneg z)]
have hh := mul_le_mul_of_nonneg_left hb terminalTransportConstant_pos.le
have hz : ‖z‖≤(Real.pi+1)*(circuitD F x+‖z‖) := by
nlinarith [mul_nonneg Real.pi_pos.le (norm_nonneg z),mul_nonneg Real.pi_pos.le hc]
have hc' : terminalTransportConstant+1≤8*(terminalTransportConstant+1) := by
linarith [terminalTransportConstant_pos]
have hh' := mul_le_mul_of_nonneg_right hc' (show 0≤(Real.pi+1)*(circuitD F x+‖z‖) by positivity)
dsimp [circuitGrowthConstant]
nlinarith
lemma interpolationLaw_norm_sq {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam)
(x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1)
(hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) :
Integrable (fun z : Point d => ‖z‖^2) (interpolationLaw F x r T) ∧
(∫z : Point d,‖z‖^2 ∂interpolationLaw F x r T)≤4*circuitGrowthConstant^2*(circuitD F x)^2 := by
have hm := (fullProbabilityFlow_lipschitz hF x hr hl ⟨hT,hT1.le⟩).continuous.measurable
have hg := gaussian_growth_sq_moment (fullProbabilityFlow_lipschitz hF x hr hl ⟨hT,hT1.le⟩).continuous
circuitGrowthConstant_pos.le (circuitD_nonneg F x)
(probabilityFlow_growth hF x hr hr1 hl hT hT1)
rw [←fullProbabilityFlow_interpolation_closed hF x hr hl hT hT1]
refine ⟨(integrable_map_measure (by fun_prop) hm.aemeasurable).mpr hg.1,?_⟩
rw [integral_map hm.aemeasurable (by fun_prop)]
apply hg.2.trans
have hs := pow_le_pow_left₀ (Real.sqrt_nonneg (d:ℝ)) (sqrt_le_circuitD F x) 2
rw [Real.sq_sqrt (Nat.cast_nonneg d)] at hs
nlinarith [mul_le_mul_of_nonneg_left hs (sq_nonneg circuitGrowthConstant)]
lemma pairGauge_sq_bound {C : ℝ} (hC : 0≤C) (z : Point d × Point d) :
(pairGauge C z)^2≤4*(1+C)^2+4*‖z.1‖^2+4*‖z.2‖^2 := by
have hp : ‖z‖≤‖z.1‖+‖z.2‖ := by
change max ‖z.1‖ ‖z.2‖≤_
exact max_le (le_add_of_nonneg_right (norm_nonneg _)) (le_add_of_nonneg_left (norm_nonneg _))
have hq : 0≤pairGauge C z := by unfold pairGauge; positivity
have hb : pairGauge C z≤1+C+‖z.1‖+‖z.2‖ := by dsimp [pairGauge]; linarith
have hh := pow_le_pow_left₀ hq hb 2
nlinarith [sq_nonneg (1+C-‖z.1‖-‖z.2‖),sq_nonneg (‖z.1‖-‖z.2‖)]
lemma pairGauge_moment (μ : Measure (Point d)) [IsProbabilityMeasure μ]
(hi : Integrable (fun z : Point d => ‖z‖^2) μ) {C : ℝ} (hC : 0≤C) :
Integrable (fun z => (pairGauge C z)^2) (μ.prod (stdGaussian (Point d))) ∧
(∫z,(pairGauge C z)^2 ∂μ.prod (stdGaussian (Point d)))≤
4*(1+C)^2+4*(∫z,‖z‖^2 ∂μ)+4*d := by
have hj : Integrable (fun z : Point d => ‖z‖^2) (stdGaussian (Point d)) := by
simpa only [id_eq] using (IsGaussian.memLp_two_id (μ:=stdGaussian (Point d))).norm.integrable_sq
have hdom : Integrable (fun z : Point d × Point d => 4*(1+C)^2+4*‖z.1‖^2+4*‖z.2‖^2)
(μ.prod (stdGaussian (Point d))) := ((integrable_const (4*(1+C)^2)).add ((hi.comp_fst (stdGaussian (Point d))).const_mul 4)).add
((hj.comp_snd μ).const_mul 4)
have hgi : Integrable (fun z => (pairGauge C z)^2) (μ.prod (stdGaussian (Point d))) := by
apply hdom.mono' ((pairGauge_measurable C).pow_const 2).aestronglyMeasurable
exact Filter.Eventually.of_forall (fun z => by simpa only [Real.norm_eq_abs,abs_sq,Pi.add_apply] using pairGauge_sq_bound hC z)
refine ⟨hgi,?_⟩
apply (integral_mono hgi hdom (pairGauge_sq_bound hC)).trans_eq
have hf : Integrable (fun z : Point d × Point d => 4*‖z.1‖^2) (μ.prod (stdGaussian (Point d))) := (hi.comp_fst _).const_mul _
have hs : Integrable (fun z : Point d × Point d => 4*‖z.2‖^2) (μ.prod (stdGaussian (Point d))) := (hj.comp_snd _).const_mul _
have hl : Integrable (fun z : Point d × Point d => 4*(1+C)^2+4*‖z.1‖^2) (μ.prod (stdGaussian (Point d))) := (integrable_const _).add hf
rw [integral_add hl hs,integral_add (integrable_const _) hf,integral_const,probReal_univ,one_smul,
integral_const_mul,integral_const_mul]
rw [integral_fun_fst (fun z : Point d => ‖z‖^2),integral_fun_snd (fun z : Point d => ‖z‖^2)]
simp only [probReal_univ,one_smul,stdGaussian_sq_norm]
lemma pairGauge_interpolation_moment {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam)
(x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1)
(hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) (hd : 1≤d) :
Integrable (fun z => (pairGauge (circuitD F x) z)^2)
((interpolationLaw F x r T).prod (stdGaussian (Point d))) ∧
(∫z,(pairGauge (circuitD F x) z)^2 ∂(interpolationLaw F x r T).prod (stdGaussian (Point d)))≤
(20+16*circuitGrowthConstant^2)*(circuitD F x)^2 := by
let := interpolationLaw_probability hF x hr (by linarith only [hl]) T
have hm := interpolationLaw_norm_sq hF x hr hr1 hl hT hT1
have hg := pairGauge_moment _ hm.1 (circuitD_nonneg F x)
refine ⟨hg.1,hg.2.trans ?_⟩
have hs : (1:ℝ)≤Real.sqrt d := by
exact (by norm_num : (1:ℝ)=Real.sqrt 1).trans_le (Real.sqrt_le_sqrt (by exact_mod_cast hd))
have hD := hs.trans (sqrt_le_circuitD F x)
have hd2 := pow_le_pow_left₀ (Real.sqrt_nonneg (d:ℝ)) (sqrt_le_circuitD F x) 2
rw [Real.sq_sqrt (Nat.cast_nonneg d)] at hd2
have hs2 := pow_le_pow_left₀ (show 0≤1+circuitD F x by positivity [circuitD_nonneg F x])
(show 1+circuitD F x≤2*circuitD F x by linarith) 2
nlinarith [hm.2]
end LogConcaveSampling
end
end
end OAI