openAI-math-dataset / lean /OAI /Probability /LogConcave /Complexity /HarmonicCorrectionBudget.lean
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import Mathlib
import OAI.Probability.LogConcave.Sampling.TransportCorrectionMajorant
namespace OAI
section
section
noncomputable section
namespace LogConcaveSampling
open Set MeasureTheory
open scoped Classical BigOperators NNReal RealInnerProductSpace
open TensorEnergy Quadrature
local instance : DecidableEq Unit := Classical.decEq _
lemma jointCorrectionArray_polySmooth {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0}
(hF : Primitive F lam) (x : Point d) {r R T : ℝ}
(hr : 0<r) (hlam : 0<lam) (hl : (lam:ℝ)*r^2≤1/2)
(hR : 0<R) (hRT : R^2≤1-T^2) (hT0 : 0≤T) (hT1 : T<1)
(s t : Icc (0:ℝ) T) (c : Unit → Fin (d+d)) :
PolySmooth (jointCorrectionArray
(fun z => probabilityTransport hF x hr.le hl hT0 hT1 s t z-z) c) :=
arrayCoordinateLift_polySmooth _ _ _
(probabilityCorrection_polySmooth hF x hr hlam hl hR hRT hT0 hT1 s t) c
def harmonicCorrectionBudget (n : ℕ) : ℝ :=
iterEnergyBudget harmonicGradientBound (fun _ => 2)
(fun k => 2+normalizedTensorMajorant (k+1) 1)
(fun k => (transportCorrectionMajorant k)^2) n 0
lemma harmonicCorrectionBudget_nonneg (n : ℕ) : 0≤harmonicCorrectionBudget n :=
iterEnergyBudget_nonneg harmonicGradientBound.2 _ _ (fun _ => sq_nonneg _) n 0
def harmonicMeanBudget (n : ℕ) : ℝ :=
iterEnergyBudget harmonicGradientBound (fun _ => 2)
(fun k => 2+normalizedTensorMajorant (k+1) 1)
(fun k => (normalizedTensorMajorant (k+1) 1)^2) n 0
lemma harmonicMeanBudget_nonneg (n : ℕ) : 0≤harmonicMeanBudget n :=
iterEnergyBudget_nonneg harmonicGradientBound.2 _ _ (fun _ => sq_nonneg _) n 0
theorem harmonic_correction_taylor_rms {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0}
(hF : Primitive F lam) (x : Point d) {r R T : ℝ}
(hr : 0<r) (hlam : 0<lam) (hl : (lam:ℝ)*r^2≤1/2)
(hR : 0<R) (hRT : R^2≤1-T^2) (hT0 : 0≤T) (hT1 : T<1)
(s t u : Icc (0:ℝ) T)
(Ξ : Point (d+d) → ℝ → Point (d+d))
(hder : ∀y v,v∈Icc (0:ℝ) 1 → HasDerivWithinAt (Ξ y)
(skewLieField (centeringPotential F x r u) (harmonicSkew d) (Ξ y v)) (Icc (0:ℝ) 1) v)
(hm : Measurable (fun p : ℝ × Point (d+d) => Ξ p.2 p.1))
(hlaw : ∀v∈Icc (0:ℝ) 1,(gibbs (centeringPotential F x r u)).map (fun y => Ξ y v)=
gibbs (centeringPotential F x r u)) :
let A := jointCorrectionArray (fun z => probabilityTransport hF x hr.le hl hT0 hT1 s t z-z)
∀n : ℕ,∀a b : ℝ,0≤a → a≤b → b≤1 →
Integrable (fun y => ‖tensorVector A (Ξ y b)-chainTaylor
(fun k v => tensorVector (iterTensorLie (centeringPotential F x r u)
(harmonicSkew d) A k) (Ξ y v)) n a b‖^2) (gibbs (centeringPotential F x r u)) ∧
(∫y,‖tensorVector A (Ξ y b)-chainTaylor
(fun k v => tensorVector (iterTensorLie (centeringPotential F x r u)
(harmonicSkew d) A k) (Ξ y v)) n a b‖^2 ∂gibbs (centeringPotential F x r u))≤
((b-a)^(n+1)/(n.factorial:ℝ))^2*
((d*((lam:ℝ)*r^2)^2)*(R⁻¹)^(4*(n+1))*harmonicCorrectionBudget (n+1)) := by
have hu1 := u.2.2.trans_lt hT1
have hRu : R^2≤1-(u:ℝ)^2 := by nlinarith [u.2.1,u.2.2]
have hR1 : R≤1 := by nlinarith [sq_nonneg T]
have hH : PolySmooth (centeringPotential F x r u) := productPotential_polySmooth
(interpolationPotential_polySmooth hF x hr hlam hl u.2.1 hu1) (gaussianPotential_polySmooth d)
have ht : HasGaussianLowerTail (centeringPotential F x r u) := productPotential_lowerTail
(interpolationPotential_lowerTail hF x hr.le (by linarith) u.2.1 hu1) (gaussianPotential_lowerTail d)
let := probability_gibbs_of_gaussianTail hH.smooth.continuous ht
intro A n a b ha hab hb
have hsub : uIcc a b⊆Icc (0:ℝ) 1 := by
rw [uIcc_of_le hab]
intro v h; exact ⟨ha.trans h.1,h.2.trans hb⟩
have h := stationary_lie_taylor_rms (S:=Unit) (d:=d+d) hH ht
(centeringPotential_gradient_uniform hF x hr hl u.2.1 hu1)
(harmonicSkew d) A (harmonicSkew_polySmooth d)
(jointCorrectionArray_polySmooth hF x hr hlam hl hR hRT hT0 hT1 s t)
(jointSkew_skew _ 1) (fun _ => 2)
(fun k => 2+normalizedTensorMajorant (k+1) 1)
(fun k => (transportCorrectionMajorant k)^2)
(α:=1) (κ:=d*((lam:ℝ)*r^2)^2) (ρ:=R⁻¹) (by positivity) ((one_le_inv₀ hR).mpr hR1)
(fun _ => sq_nonneg _) (harmonicSkew_inv_scaled hR hR1)
(centeringScore_inv_scaled hF x hr hlam hl hR hRu u.2.1 hu1)
(jointCorrection_inv_scaled hF x hr hlam hl hR hRT hT0 hT1 s t u)
Ξ hder hm hlaw hab hsub n
simpa only [one_pow,one_mul,←pow_mul,harmonicCorrectionBudget] using h
theorem harmonic_mean_taylor_uniform {d : ℕ} {F : Point d → ℝ} {lam : ℝ≥0}
(hF : Primitive F lam) (x : Point d) {r R T : ℝ}
(hr : 0<r) (hlam : 0<lam) (hl : (lam:ℝ)*r^2≤1/2)
(hR : 0<R) (hRT : R^2≤1-T^2) (hT0 : 0≤T) (hT1 : T<1)
(Ξ : Point (d+d) → ℝ → Point (d+d))
(hder : ∀y t,t∈Icc (0:ℝ) 1 → HasDerivWithinAt (Ξ y)
(skewLieField (centeringPotential F x r T) (harmonicSkew d) (Ξ y t)) (Icc (0:ℝ) 1) t)
(hm : Measurable (fun p : ℝ × Point (d+d) => Ξ p.2 p.1))
(hlaw : ∀t∈Icc (0:ℝ) 1,(gibbs (centeringPotential F x r T)).map (fun y => Ξ y t)=
gibbs (centeringPotential F x r T)) :
∀n : ℕ,∀a b : ℝ,0≤a → a≤b → b≤1 →
Integrable (fun y => ‖tensorVector (centeringMeanArray F x r T) (Ξ y b)-chainTaylor
(fun k t => tensorVector (iterTensorLie (centeringPotential F x r T)
(harmonicSkew d) (centeringMeanArray F x r T) k) (Ξ y t)) n a b‖^2)
(gibbs (centeringPotential F x r T)) ∧
(∫y,‖tensorVector (centeringMeanArray F x r T) (Ξ y b)-chainTaylor
(fun k t => tensorVector (iterTensorLie (centeringPotential F x r T)
(harmonicSkew d) (centeringMeanArray F x r T) k) (Ξ y t)) n a b‖^2
∂gibbs (centeringPotential F x r T))≤
((b-a)^(n+1)/(n.factorial:ℝ))^2*
((d*((lam:ℝ)*r)^2)*(R⁻¹)^(4*(n+1))*harmonicMeanBudget (n+1)) := by
have hR1 : R≤1 := by nlinarith [sq_nonneg T]
have hH : PolySmooth (centeringPotential F x r T) := productPotential_polySmooth
(interpolationPotential_polySmooth hF x hr hlam hl hT0 hT1) (gaussianPotential_polySmooth d)
have ht : HasGaussianLowerTail (centeringPotential F x r T) := productPotential_lowerTail
(interpolationPotential_lowerTail hF x hr.le (by linarith) hT0 hT1) (gaussianPotential_lowerTail d)
let := probability_gibbs_of_gaussianTail hH.smooth.continuous ht
intro n a b ha hab hb
have hsub : uIcc a b⊆Icc (0:ℝ) 1 := by
rw [uIcc_of_le hab]
intro t h; exact ⟨ha.trans h.1,h.2.trans hb⟩
have h := stationary_lie_taylor_rms (S:=Unit) (d:=d+d) hH ht
(centeringPotential_gradient_uniform hF x hr hl hT0 hT1)
(harmonicSkew d) (centeringMeanArray F x r T)
(harmonicSkew_polySmooth d) (centeringMeanArray_polySmooth hF x hr hlam hl hT0 hT1)
(jointSkew_skew _ 1) (fun _ => 2)
(fun k => 2+normalizedTensorMajorant (k+1) 1)
(fun k => (normalizedTensorMajorant (k+1) 1)^2)
(α:=1) (κ:=d*((lam:ℝ)*r)^2) (ρ:=R⁻¹) (by positivity) ((one_le_inv₀ hR).mpr hR1)
(fun _ => sq_nonneg _) (harmonicSkew_inv_scaled hR hR1)
(centeringScore_inv_scaled hF x hr hlam hl hR hRT hT0 hT1)
(centeringMean_inv_scaled hF x hr hlam hl hR hRT hT0 hT1)
Ξ hder hm hlaw hab hsub n
simpa only [one_pow,one_mul,←pow_mul,harmonicMeanBudget] using h
end LogConcaveSampling
end
end
end
end OAI