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Integrated Bochner Identity at Lipschitz Regularity

Proved
FunctionalInequalities.Analysis.BakryEmery.integral_weightedLaplacian_sq_eq_of_lipschitz_gradient_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readableletwin2026log-concave

This formalizes the integrated Bochner identity for a C1,1C^{1,1}C1,1 potential; it is related to Lemma A.6 of Letwin (2026), cited as “Brascamp–Lieb for ν\nuν.”

Let EEE be a complete finite-dimensional real inner-product space with its Borel structure. Let U:E→RU:E\to\mathbb RU:E→R be C1C^1C1, let ∇U\nabla U∇U be Lipschitz with constant G∈[0,∞)G\in[0,\infty)G∈[0,∞), and let UUU itself be Lipschitz with constant L∈[0,∞)L\in[0,\infty)L∈[0,∞). Assume

  1. e−Ue^{-U}e−U is integrable with respect to volume measure.
  2. f:E→Rf:E\to\mathbb Rf:E→R is C∞C^\inftyC∞.
  3. fff has compact support.

With ν=volume⁡.tilted⁡(−U)\nu=\operatorname{volume}.\operatorname{tilted}(-U)ν=volume.tilted(−U),

∫(LUf)2 dν=∫(HessSq⁡std(f)(x)+⟨D(∇U)(x)∇f(x),∇f(x)⟩)dν(x),\int (\mathcal L_U f)^2\,d\nu = \int\left(\operatorname{HessSq}_{\mathrm{std}}(f)(x)+ \left\langle D(\nabla U)(x)\nabla f(x),\nabla f(x)\right\rangle\right)d\nu(x),∫(LU​f)2dν=∫(HessSqstd​(f)(x)+⟨D(∇U)(x)∇f(x),∇f(x)⟩)dν(x),

where LUf=Δf−⟨∇U,∇f⟩\mathcal L_U f=\Delta f-\langle\nabla U,\nabla f\rangleLU​f=Δf−⟨∇U,∇f⟩. The derivative D(∇U)D(\nabla U)D(∇U) is the a.e. derivative fderiv ℝ (gradient U), and the Hessian square is hessianSqStdBasis.

Original Lean declaration header

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

theorem integral_weightedLaplacian_sq_eq_of_lipschitz_gradient {U : E → ℝ} (hU : ContDiff ℝ 1 U) {G : NNReal}
    (hG : LipschitzWith G (gradient U)) {L : NNReal} (hL : LipschitzWith L U)
    (hexp : Integrable (fun x => Real.exp (-U x)) (volume : Measure E))
    {f : E → ℝ} (hf : ContDiff ℝ ∞ f) (hfc : HasCompactSupport f) :
    ∫ x, weightedLaplacian U f x ^ 2 ∂((volume : Measure E).tilted (-U)) =
      ∫ x, (hessianSqStdBasis f x + ⟪fderiv ℝ (gradient U) x (gradient f x), gradient f x⟫)
        ∂((volume : Measure E).tilted (-U))

Module navigation

Module: Analysis/BakryEmery/Bochner/Lipschitz.

Definition modules: Analysis/BakryEmery/Bochner/Basic, Analysis/BakryEmery/Laplacian.

Supporting theorems: gammaTwo_eq_hessianSqStdBasis_add, exists_contDiff_approx_of_lipschitz_gradient.

Next: compact_ordinary_diffusion_coercivity_of_lipschitz_gradient.

Source excerpt, lines 131–137 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_BakryEmery_Bochner_Lipschitz

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

theorem FunctionalInequalities.Analysis.BakryEmery.integral_weightedLaplacian_sq_eq_of_lipschitz_gradient_readable {U : E → ℝ} (hU : ContDiff ℝ 1 U) {G : NNReal}
    (hG : LipschitzWith G (gradient U)) {L : NNReal} (hL : LipschitzWith L U)
    (hexp : Integrable (fun x => Real.exp (-U x)) (volume : Measure E))
    {f : E → ℝ} (hf : ContDiff ℝ ∞ f) (hfc : HasCompactSupport f) :
    ∫ x, weightedLaplacian U f x ^ 2 ∂((volume : Measure E).tilted (-U)) =
      ∫ x, (hessianSqStdBasis f x + ⟪fderiv ℝ (gradient U) x (gradient f x), gradient f x⟫)
        ∂((volume : Measure E).tilted (-U)) := by sorry
Source
Source: Letwin, The KLS constant is O(log^(1/4) n) (arXiv:2607.24164v1), Lemma A.6. Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/BakryEmery/Bochner/Lipschitz.lean#L127-L283 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.BakryEmery.Bochner.Lipschitz`, declaration `FunctionalInequalities.Analysis.BakryEmery.integral_weightedLaplacian_sq_eq_of_lipschitz_gradient`; the repository is private at upload time).

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