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Grouped Cumulant Expansion for Inverse Covariance

Proved
FunctionalInequalities.Analysis.BakryEmery.iteratedFDeriv_inner_centeredGradient_zero_grouped_of_compact_readable

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

bkl2026functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This formalizes the grouped expansion in Equations (72)–(74) of Bizeul–Klartag–Lehec (arXiv:2610.05474v1), cited for the spatial step of Lemma 4.3.

Let μ\muμ be a compactly supported probability measure on a finite-dimensional real inner-product space EEE. Assume the covariance operator A=Cov⁡(μ)A=\operatorname{Cov}(\mu)A=Cov(μ) is invertible. For m≥3m\ge3m≥3, directions h:Fin⁡(m)→Eh:\operatorname{Fin}(m)\to Eh:Fin(m)→E, and a fixed index i0∈Fin⁡(m)i_0\in\operatorname{Fin}(m)i0​∈Fin(m), define v(z)=∇Λμ(z)−∇Λμ(0)v(z)=\nabla\Lambda_\mu(z)-\nabla\Lambda_\mu(0)v(z)=∇Λμ​(z)−∇Λμ​(0). Then

Dm⟨v,A−1v⟩(0)[h]=2m κm(h)+2∑q: q(i0)=true2≤∣q∣≤m−2, 2≤∣¬q∣≤m−2⟨κ∣q∣+1(hq,⋅),A−1κm−∣q∣+1(h¬q,⋅)⟩.D^m\langle v,A^{-1}v\rangle(0)[h] =2m\,\kappa_m(h)+2\sum_{q:\,q(i_0)=\mathrm{true}\atop 2\le |q|\le m-2,\ 2\le |\neg q|\le m-2} \left\langle\kappa_{|q|+1}(h_q,\cdot),A^{-1}\kappa_{m-|q|+1}(h_{\neg q},\cdot)\right\rangle.Dm⟨v,A−1v⟩(0)[h]=2mκm​(h)+22≤∣q∣≤m−2, 2≤∣¬q∣≤m−2q:q(i0​)=true​∑​⟨κ∣q∣+1​(hq​,⋅),A−1κm−∣q∣+1​(h¬q​,⋅)⟩.

The singleton and complementary-singleton allocations contribute 2m κm(h)2m\,\kappa_m(h)2mκm​(h), while the remaining allocations are paired by complementation. This is a deterministic fixed-measure identity, not a stochastic evolution statement.

Original Lean declaration header

Within namespace FunctionalInequalities.Analysis.BakryEmery. Shown in its original module context. Proof omitted.

theorem iteratedFDeriv_inner_centeredGradient_zero_grouped_of_compact
    (mu : ProbabilityMeasure E)
    (hc : IsCompact (mu : Measure E).support)
    (hA : IsUnit (Covariance.operator (mu : Measure E)))
    {m : ℕ} (hm : 3 ≤ m) (h : Fin m → E) (i0 : Fin m) :
    iteratedFDeriv ℝ m (fun z : E =>
        ⟪gradient (logLaplace (mu : Measure E)) z - gradient (logLaplace (mu : Measure E)) 0,
          Ring.inverse (Covariance.operator (mu : Measure E))
            (gradient (logLaplace (mu : Measure E)) z -
              gradient (logLaplace (mu : Measure E)) 0)⟫) 0 h =
      (2 * (m : ℝ)) * cumulant (mu : Measure E) m h +
        2 * ∑ q ∈ Finset.univ.filter (fun q : Fin m → Bool =>
          q i0 = true ∧
          2 ≤ (selected h q).length ∧
          2 ≤ (selected h (fun i => !(q i))).length),
          ⟪cumulantVector (mu : Measure E) (selected h q),
            Ring.inverse (Covariance.operator (mu : Measure E))
              (cumulantVector (mu : Measure E)
                (selected h (fun i => !(q i))))⟫

Module navigation

Module: Analysis/BakryEmery/Cumulant/Leibniz.

Definition modules: Analysis/BakryEmery/Cumulant/Basic, Probability/Covariance/Basic, Analysis/BakryEmery/Cumulant/Local, Analysis/IteratedDerivative/Bilinear.

Supporting theorems: inner_cumulantVector_single_ringInverse_cumulantVector, iteratedFDeriv_inner_centeredGradient_zero_of_compact, selected_mask_partition, sum_filter_eq_two_mul_sum_filter_of_compl_invariant.

Previous: iteratedFDeriv_inner_centeredGradient_zero_of_compact.

Source excerpt, lines 153–171 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_BakryEmery_Cumulant_Leibniz

open MeasureTheory
open scoped RealInnerProductSpace ContDiff
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
  [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
Formal statement

theorem FunctionalInequalities.Analysis.BakryEmery.iteratedFDeriv_inner_centeredGradient_zero_grouped_of_compact_readable
    (mu : ProbabilityMeasure E)
    (hc : IsCompact (mu : Measure E).support)
    (hA : IsUnit (Covariance.operator (mu : Measure E)))
    {m : ℕ} (hm : 3 ≤ m) (h : Fin m → E) (i0 : Fin m) :
    iteratedFDeriv ℝ m (fun z : E =>
        ⟪gradient (logLaplace (mu : Measure E)) z - gradient (logLaplace (mu : Measure E)) 0,
          Ring.inverse (Covariance.operator (mu : Measure E))
            (gradient (logLaplace (mu : Measure E)) z -
              gradient (logLaplace (mu : Measure E)) 0)⟫) 0 h =
      (2 * (m : ℝ)) * cumulant (mu : Measure E) m h +
        2 * ∑ q ∈ Finset.univ.filter (fun q : Fin m → Bool =>
          q i0 = true ∧
          2 ≤ (selected h q).length ∧
          2 ≤ (selected h (fun i => !(q i))).length),
          ⟪cumulantVector (mu : Measure E) (selected h q),
            Ring.inverse (Covariance.operator (mu : Measure E))
              (cumulantVector (mu : Measure E)
                (selected h (fun i => !(q i))))⟫ := by sorry
Source
Source: Bizeul–Klartag–Lehec, Presenting a proof of the Kannan–Lovász–Simonovits conjecture (arXiv:2610.05474v1), Lemma 4.3, p. 20; Bizeul–Klartag–Lehec, Presenting a proof of the Kannan–Lovász–Simonovits conjecture (arXiv:2610.05474v1), Equations (72) and (74), pp. 20–21 (spatial step of the proof of Lemma 4.3). Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/BakryEmery/Cumulant/Leibniz.lean#L148-L465 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.BakryEmery.Cumulant.Leibniz`, declaration `FunctionalInequalities.Analysis.BakryEmery.iteratedFDeriv_inner_centeredGradient_zero_grouped_of_compact`; the repository is private at upload time).

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