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Admissibility of Cutoff Localization Coefficients

Proved
FunctionalInequalities.KLS.BKL.Localization.cutoffCoefficients_admissible_readable

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

bkl2026functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This statement formalizes the regularity and support properties of cutoff coefficients from Equation (67), p. 19, of Bizeul–Klartag–Lehec (arXiv:2610.05474v1).

Let n∈Nn\in\mathbb Nn∈N, let μ\muμ be a probability measure on EuclideanSpace ℝ (Fin n), assume that its support is compact and that μ\muμ is isotropic, and let γ\gammaγ be an admissible cutoff, expressed by IsCutoff γ. Then the cutoff drift and every cutoff noise column satisfy:

  1. There is one K∈[0,∞)K\in[0,\infty)K∈[0,∞) such that the cutoff drift and every cutoff noise column are globally KKK-Lipschitz.
  2. There is one B∈RB\in\mathbb RB∈R uniformly bounding the norms of the cutoff drift and all cutoff noise columns at every parameter.
  3. The cutoff drift has compact support.
  4. Every cutoff noise column has compact support.

Equivalently, the conclusion is the conjunction of the corresponding global Lipschitz, boundedness, and compact-support assertions. This is an admissibility result for the cutoff coefficients, not a statement about a stochastic process.

Original Lean declaration header

Within namespace FunctionalInequalities.KLS.BKL.Localization. Shown in its original module context. Proof omitted.

theorem cutoffCoefficients_admissible (hiso : KLS.Isotropic μ) {γ : Param n → ℝ} (hγ : IsCutoff γ) :
    (∃ K : ℝ≥0, LipschitzWith K (cutoffDrift μ hc γ) ∧
        ∀ k, LipschitzWith K fun p => cutoffNoise μ hc γ p k) ∧
      (∃ B : ℝ, ∀ p, ‖cutoffDrift μ hc γ p‖ ≤ B ∧ ∀ k, ‖cutoffNoise μ hc γ p k‖ ≤ B) ∧
      HasCompactSupport (cutoffDrift μ hc γ) ∧
      ∀ k, HasCompactSupport fun p => cutoffNoise μ hc γ p k

Module navigation

Module: KLS/BKL/Localization/Coefficients.

Definition modules: KLS/Isotropic.

Selected supporting theorems: Covariance.inner_operator_self_pos_of_affineSupport_eq_top, locallyLipschitz_noise, Isotropic.locallyLipschitz_inverseSqrt_covariance_joint, exists_lipschitzWith_smul_of_locallyLipschitz, contDiff_posteriorCovariance_joint.

Previous: locallyLipschitz_noise.

Source excerpt, lines 153–158 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_BKL_Localization_Coefficients

open scoped NNReal RealInnerProductSpace
variable {n : ℕ} (μ : MeasureTheory.ProbabilityMeasure (EuclideanSpace ℝ (Fin n)))
  (hc : IsCompact (μ : MeasureTheory.Measure (EuclideanSpace ℝ (Fin n))).support)
Formal statement

theorem FunctionalInequalities.KLS.BKL.Localization.cutoffCoefficients_admissible_readable (hiso : KLS.Isotropic μ) {γ : Param n → ℝ} (hγ : IsCutoff γ) :
    (∃ K : ℝ≥0, LipschitzWith K (cutoffDrift μ hc γ) ∧
        ∀ k, LipschitzWith K fun p => cutoffNoise μ hc γ p k) ∧
      (∃ B : ℝ, ∀ p, ‖cutoffDrift μ hc γ p‖ ≤ B ∧ ∀ k, ‖cutoffNoise μ hc γ p k‖ ≤ B) ∧
      HasCompactSupport (cutoffDrift μ hc γ) ∧
      ∀ k, HasCompactSupport fun p => cutoffNoise μ hc γ p k := by sorry
Source
Source: Bizeul–Klartag–Lehec, Presenting a proof of the Kannan–Lovász–Simonovits conjecture (arXiv:2610.05474v1), Equation (67), p. 19 (unnumbered display) and the compact stage before it. Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/KLS/BKL/Localization/Coefficients.lean#L151-L173 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.KLS.BKL.Localization.Coefficients`, declaration `FunctionalInequalities.KLS.BKL.Localization.cutoffCoefficients_admissible`; the repository is private at upload time).

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