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Log-Laplace Formula for Compact Posteriors

Proved
FunctionalInequalities.Probability.Posterior.logLaplace_compactPosterior_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This statement gives the log-Laplace identity for a compactly supported linear–quadratic posterior.

Let EEE be a complete finite-dimensional real inner-product space, let μ\muμ be a probability law with compact support, let c,z∈Ec,z\in Ec,z∈E, and let Q:E→EQ:E\to EQ:E→E be continuous linear. For the compact posterior μc,Q\mu_{c,Q}μc,Q​ and the log-partition function ψ=logPartition μ\psi=\texttt{logPartition}\,\muψ=logPartitionμ, one has

Λμc,Q(z)=ψ(c+z,Q)−ψ(c,Q),\Lambda_{\mu_{c,Q}}(z) =\psi(c+z,Q)-\psi(c,Q),Λμc,Q​​(z)=ψ(c+z,Q)−ψ(c,Q),

where Λ\LambdaΛ is Analysis.BakryEmery.logLaplace. The identity is a direct formula for the posterior log-Laplace transform and is reusable in derivative and cumulant calculations.

Original Lean declaration header

Within namespace FunctionalInequalities.Probability.Posterior. Shown in its original module context. Proof omitted.

omit [CompleteSpace E] [FiniteDimensional ℝ E]
  [MeasurableSpace E] [BorelSpace E] in
theorem logLaplace_compactPosterior
    [CompleteSpace E] [FiniteDimensional ℝ E]
    [MeasurableSpace E] [BorelSpace E]
    (μ : ProbabilityMeasure E)
    (hc : IsCompact (μ : Measure E).support) (c : E) (Q : E →L[ℝ] E) (z : E) :
    Analysis.BakryEmery.logLaplace (compactPosterior μ hc c Q : Measure E) z =
      logPartition μ (c + z) Q - logPartition μ c Q

Module navigation

Module: Probability/Posterior/LogPartition.

Definition modules: Analysis/BakryEmery/Cumulant/Basic, Probability/Posterior/CompactDomain.

Previous: contDiff_logPartition_joint · Next: cumulant_compactPosterior.

Source excerpt, lines 204–212 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Probability_Posterior_LogPartition

open MeasureTheory ProbabilityTheory
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [CompleteSpace E]
  [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
omit [CompleteSpace E] [FiniteDimensional ℝ E]
  [MeasurableSpace E] [BorelSpace E]
Formal statement
theorem FunctionalInequalities.Probability.Posterior.logLaplace_compactPosterior_readable
    [CompleteSpace E] [FiniteDimensional ℝ E]
    [MeasurableSpace E] [BorelSpace E]
    (μ : ProbabilityMeasure E)
    (hc : IsCompact (μ : Measure E).support) (c : E) (Q : E →L[ℝ] E) (z : E) :
    Analysis.BakryEmery.logLaplace (compactPosterior μ hc c Q : Measure E) z =
      logPartition μ (c + z) Q - logPartition μ c Q := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Probability/Posterior/LogPartition.lean#L204-L238 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Probability.Posterior.LogPartition`, declaration `FunctionalInequalities.Probability.Posterior.logLaplace_compactPosterior`; the repository is private at upload time).

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