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Logarithmic Laplace Factorization at Integrable Joint Parameters

Proved
FunctionalInequalities.KLS.LogConcave.Suspension.logLaplace_jointLaw_factorization_readable

by Lazyfill · Oct 26, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This lemma states the logarithmic Laplace factorization at a parameter with integrable joint exponential.

Let n,N∈Nn,N\in\mathbb Nn,N∈N with N>0N>0N>0, E=RnE=\mathbb R^nE=Rn (EuclideanSpace ℝ (Fin n)), μ\muμ a probability measure on EEE, and f:E→Rf:E\to\mathbb Rf:E→R measurable. Let β>0\beta>0β>0, ηβ=\eta_\beta=ηβ​= laplaceMeasure β\betaβ, σβ=1+2/β2\sigma_\beta=\sqrt{1+2/\beta^2}σβ​=1+2/β2​ (sigma), and λ=\lambda=λ= jointLaw μ f β σβ N\mu\ f\ \beta\ \sigma_\beta\ Nμ f β σβ​ N. The target H=H=H= JointSpace N nN\ nN n has a scalar coordinate and NNN copy blocks. For z∈Hz\in Hz∈H, denote these by z0z_0z0​ and zi∈Ez_i\in Ezi​∈E.

Assume e⟨z,⋅⟩∈L1(λ)e^{\langle z,\cdot\rangle}\in L^1(\lambda)e⟨z,⋅⟩∈L1(λ). With Λλ(z)=log⁡∫e⟨z,p⟩ dλ(p)\Lambda_\lambda(z)=\log\int e^{\langle z,p\rangle}\,d\lambda(p)Λλ​(z)=log∫e⟨z,p⟩dλ(p) (logLaplace),

Λλ(z)=log⁡(∫e(z0/σβ)s dηβ(s))+∑i∈Fin⁡Nlog⁡(∫ez0σβNf(x)+⟨zi,x⟩ dμ(x)).\Lambda_\lambda(z)= \log\left(\int e^{(z_0/\sigma_\beta)s}\,d\eta_\beta(s)\right) +\sum_{i\in\operatorname{Fin}N}\log\left(\int e^{\frac{z_0}{\sigma_\beta\sqrt N}f(x)+\langle z_i,x\rangle}\,d\mu(x)\right).Λλ​(z)=log(∫e(z0​/σβ​)sdηβ​(s))+i∈FinN∑​log(∫eσβ​N​z0​​f(x)+⟨zi​,x⟩dμ(x)).

This gives the real logarithmic identity used in local derivative calculations, with joint integrability explicitly required.

Original Lean declaration header

Within namespace FunctionalInequalities.KLS.LogConcave.Suspension. Shown in its original module context. Proof omitted.

theorem logLaplace_jointLaw_factorization {n N : ℕ} (μ : Measure (EuclideanSpace ℝ (Fin n)))
    [IsProbabilityMeasure μ] {f : EuclideanSpace ℝ (Fin n) → ℝ} (hf : Measurable f)
    {β : ℝ} (hβ : 0 < β) (hN : 0 < N) (z : JointSpace N n)
    (hInt : Integrable (fun p => Real.exp ⟪z, p⟫) (jointLaw μ f β (sigma β) N)) :
    FunctionalInequalities.Analysis.BakryEmery.logLaplace (jointLaw μ f β (sigma β) N) z =
      Real.log (∫ s : ℝ, Real.exp (z none / sigma β * s) ∂laplaceMeasure β) +
        ∑ i : Fin N, Real.log (∫ x, Real.exp
          (z none / (sigma β * Real.sqrt N) * f x +
            ⟪(WithLp.toLp 2 fun j => z (some (i, j)) : EuclideanSpace ℝ (Fin n)), x⟫) ∂μ)

Module navigation

Module: KLS/BKL/Suspension/Cumulant.

Definition modules: Analysis/BakryEmery/Cumulant/Basic, KLS/BKL/Suspension/Law, Probability/Line/Laplace.

Supporting theorems: joint_integrability_factorization.

Previous: joint_integrability_factorization · Next: exists_f_abs_exponential_moment.

Source excerpt, lines 272–280 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_BKL_Suspension_Cumulant

open MeasureTheory FunctionalInequalities.Analysis.BakryEmery FunctionalInequalities.Analysis.Tensor
open FunctionalInequalities.Probability.Line
open scoped RealInnerProductSpace
Formal statement

theorem FunctionalInequalities.KLS.LogConcave.Suspension.logLaplace_jointLaw_factorization_readable {n N : ℕ} (μ : Measure (EuclideanSpace ℝ (Fin n)))
    [IsProbabilityMeasure μ] {f : EuclideanSpace ℝ (Fin n) → ℝ} (hf : Measurable f)
    {β : ℝ} (hβ : 0 < β) (hN : 0 < N) (z : JointSpace N n)
    (hInt : Integrable (fun p => Real.exp ⟪z, p⟫) (jointLaw μ f β (sigma β) N)) :
    FunctionalInequalities.Analysis.BakryEmery.logLaplace (jointLaw μ f β (sigma β) N) z =
      Real.log (∫ s : ℝ, Real.exp (z none / sigma β * s) ∂laplaceMeasure β) +
        ∑ i : Fin N, Real.log (∫ x, Real.exp
          (z none / (sigma β * Real.sqrt N) * f x +
            ⟪(WithLp.toLp 2 fun j => z (some (i, j)) : EuclideanSpace ℝ (Fin n)), x⟫) ∂μ) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/KLS/BKL/Suspension/Cumulant.lean#L271-L294 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.KLS.BKL.Suspension.Cumulant`, declaration `FunctionalInequalities.KLS.LogConcave.Suspension.logLaplace_jointLaw_factorization`; the repository is private at upload time).

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