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Weak Source Stein Identity

Proved
FunctionalInequalities.KLS.LogConcave.source_stein_identity_of_bounded_lipschitz_test_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readableletwin2026log-concave

This statement formalizes the weak source Stein identity associated with a normalized potential.

Let n∈Nn\in\mathbb Nn∈N. Let u,f:Rn→Ru,f:\mathbb R^n\to\mathbb Ru,f:Rn→R be C1C^1C1, let uuu and ∇u∇u∇u be globally Lipschitz, and assume

∫Rne−u(y) dy=1.\int_{\mathbb R^n}e^{-u(y)}\,dy=1.∫Rn​e−u(y)dy=1.

Let fff be globally Lipschitz and bounded by CCC. For every coordinate i∈Fin⁡(n)i\in\operatorname{Fin}(n)i∈Fin(n), both displayed integrands are integrable with respect to the tilted measure volume.tilted (-u), and

∫(∇u(y))if(∇u(y)) dν(y)=∫∑j(∇2u(y))ij(∇f(∇u(y)))j dν(y),\int (∇u(y))_i f(∇u(y))\,dν(y) = \int \sum_j (\nabla^2u(y))_{ij}(∇f(∇u(y)))_j\,dν(y),∫(∇u(y))i​f(∇u(y))dν(y)=∫j∑​(∇2u(y))ij​(∇f(∇u(y)))j​dν(y),

where ν=volume⁡.tilted⁡(−u)ν=\operatorname{volume}.\operatorname{tilted}(-u)ν=volume.tilted(−u). This is an analytic identity; it does not assert existence of an inverse gradient map or a target Stein kernel.

Original Lean declaration header

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

theorem source_stein_identity_of_bounded_lipschitz_test {n : ℕ}
    {u f : EuclideanSpace ℝ (Fin n) → ℝ} {L G Lf : NNReal}
    (hu : ContDiff ℝ 1 u) (hL : LipschitzWith L u)
    (hG : LipschitzWith G (gradient u))
    (hnorm : (∫ y, Real.exp (-u y) ∂volume) = 1)
    (hf : ContDiff ℝ 1 f) (hfLip : LipschitzWith Lf f)
    (C : ℝ) (hbound : ∀ x, ‖f x‖ ≤ C) (i : Fin n) :
    Integrable (fun y => gradient u y i * f (gradient u y))
      ((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u)) ∧
    Integrable (fun y => ∑ j, hessianMatrix u y i j * gradient f (gradient u y) j)
      ((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u)) ∧
    (∫ y, gradient u y i * f (gradient u y)
      ∂((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u))) =
      ∫ y, (∑ j, hessianMatrix u y i j * gradient f (gradient u y) j)
        ∂((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u))

Module navigation

Module: KLS/LogConcave/HessianStein.

Definition modules: Analysis/BakryEmery/HessianOperator.

Supporting theorems: integral_fderiv_tilted_eq_integral_mul_fderiv_of_bounded_lipschitz, chain_coordinate_of_differentiableAt_gradient.

Next: source_affine_stein_identity_of_bounded_lipschitz_test.

Source excerpt, lines 234–248 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_HessianStein

open MeasureTheory Filter
open FunctionalInequalities.Probability.Stein
set_option maxHeartbeats 600000
Formal statement

theorem FunctionalInequalities.KLS.LogConcave.source_stein_identity_of_bounded_lipschitz_test_readable {n : ℕ}
    {u f : EuclideanSpace ℝ (Fin n) → ℝ} {L G Lf : NNReal}
    (hu : ContDiff ℝ 1 u) (hL : LipschitzWith L u)
    (hG : LipschitzWith G (gradient u))
    (hnorm : (∫ y, Real.exp (-u y) ∂volume) = 1)
    (hf : ContDiff ℝ 1 f) (hfLip : LipschitzWith Lf f)
    (C : ℝ) (hbound : ∀ x, ‖f x‖ ≤ C) (i : Fin n) :
    Integrable (fun y => gradient u y i * f (gradient u y))
      ((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u)) ∧
    Integrable (fun y => ∑ j, hessianMatrix u y i j * gradient f (gradient u y) j)
      ((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u)) ∧
    (∫ y, gradient u y i * f (gradient u y)
      ∂((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u))) =
      ∫ y, (∑ j, hessianMatrix u y i j * gradient f (gradient u y) j)
        ∂((volume : Measure (EuclideanSpace ℝ (Fin n))).tilted (-u)) := by sorry
Source
Source: Letwin, The KLS constant is O(log^(1/4) n) (arXiv:2607.24164v1), Lemma 2.7 (Fathi [29, Theorem 2.3]). Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/KLS/LogConcave/HessianStein.lean#L230-L272 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.KLS.LogConcave.HessianStein`, declaration `FunctionalInequalities.KLS.LogConcave.source_stein_identity_of_bounded_lipschitz_test`; the repository is private at upload time).

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