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Assembly of the Weak Generator Identity

Proved
FunctionalInequalities.Analysis.assemble_generator_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This is an assembly lemma for a weak inverse-Hessian generator identity.

Let u,V,a,fu,V,a,fu,V,a,f be functions on EuclideanSpace⁡ R (Fin⁡(n))\operatorname{EuclideanSpace}\,\mathbb R\,(\operatorname{Fin}(n))EuclideanSpaceR(Fin(n)). Assume u,Vu,Vu,V are C1C^1C1, ∇u\nabla u∇u is Lipschitz, the exponent −u+V∘∇u-u+V\circ\nabla u−u+V∘∇u is Lipschitz, and almost everywhere

det⁡(hessianMatrix⁡(u,x))=e−u(x)+V(∇u(x)).\det(\operatorname{hessianMatrix}(u,x))=e^{-u(x)+V(\nabla u(x))}.det(hessianMatrix(u,x))=e−u(x)+V(∇u(x)).

Assume also that each weighted coordinate test has a Lipschitz compactly supported representative, that its coordinate derivative satisfies the specified a.e. formula, and that the associated energyDensity u a f is integrable.

Then

∫generatorDensity⁡(u,V,a,f) dvol⁡=−∫energyDensity⁡(u,a,f) dvol⁡.\int \operatorname{generatorDensity}(u,V,a,f)\,d\operatorname{vol} =-\int \operatorname{energyDensity}(u,a,f)\,d\operatorname{vol}.∫generatorDensity(u,V,a,f)dvol=−∫energyDensity(u,a,f)dvol.

The statement is an internal analytic assembly interface: its hypotheses include the derivative and integrability inputs explicitly, and it does not itself assert the broader Monge–Ampère theorem.

Original Lean declaration header

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

private lemma assemble_generator {n : ℕ}
    {u V a f : EuclideanSpace ℝ (Fin n) → ℝ}
    (hu : ContDiff ℝ 1 u) {G : NNReal}
    (hG : LipschitzWith G (gradient u)) (hV : ContDiff ℝ 1 V)
    {LF : NNReal} (hF : LipschitzWith LF (fun x => -u x + V (gradient u x)))
    (hdet : ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))),
      (hessianMatrix u x).det = Real.exp (-u x + V (gradient u x)))
    (ht : ∀ i, ∃ L : NNReal,
      LipschitzWith L (weightedTest u a f i) ∧
        HasCompactSupport (weightedTest u a f i))
    (hd : ∀ i, ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))), ∀ j,
      coord (weightedTest u a f i) j x =
        Real.exp (-u x) *
          (coord a j x * coord f i x -
            a x * coord u j x * coord f i x +
            a x * hessianMatrix f x j i))
    (hE : Integrable (energyDensity u a f)
      (volume : Measure (EuclideanSpace ℝ (Fin n)))) :
    (∫ x, generatorDensity u V a f x
      ∂(volume : Measure (EuclideanSpace ℝ (Fin n)))) =
        -∫ x, energyDensity u a f x
          ∂(volume : Measure (EuclideanSpace ℝ (Fin n)))

Module navigation

Module: Analysis/BakryEmery/IntegrationByParts/InverseHessian/Weak.

Definition modules: Analysis/BakryEmery/HessianOperator.

Supporting theorems: ae_fderiv_mongeAmpere_exponent, integrable_inv_hessianMatrix_mul_of_bounded_compact, sum_integral_inv_hessianMatrix_mul_fderiv_eq, sum_inv_gradient_test_sub_chain_eq.

Previous: smooth_test_derivative · Next: integral_mul_generator_eq_neg_energy.

Source excerpt, lines 602–623 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_BakryEmery_IntegrationByParts_InverseHessian_Weak

open MeasureTheory Set Filter
open FunctionalInequalities.Probability.Stein
Formal statement
 lemma FunctionalInequalities.Analysis.assemble_generator_readable {n : ℕ}
    {u V a f : EuclideanSpace ℝ (Fin n) → ℝ}
    (hu : ContDiff ℝ 1 u) {G : NNReal}
    (hG : LipschitzWith G (gradient u)) (hV : ContDiff ℝ 1 V)
    {LF : NNReal} (hF : LipschitzWith LF (fun x => -u x + V (gradient u x)))
    (hdet : ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))),
      (hessianMatrix u x).det = Real.exp (-u x + V (gradient u x)))
    (ht : ∀ i, ∃ L : NNReal,
      LipschitzWith L (FunctionalInequalities.Analysis.weightedTest u a f i) ∧
        HasCompactSupport (FunctionalInequalities.Analysis.weightedTest u a f i))
    (hd : ∀ i, ∀ᵐ x ∂(volume : Measure (EuclideanSpace ℝ (Fin n))), ∀ j,
      FunctionalInequalities.Analysis.coord (FunctionalInequalities.Analysis.weightedTest u a f i) j x =
        Real.exp (-u x) *
          (FunctionalInequalities.Analysis.coord a j x * FunctionalInequalities.Analysis.coord f i x -
            a x * FunctionalInequalities.Analysis.coord u j x * FunctionalInequalities.Analysis.coord f i x +
            a x * hessianMatrix f x j i))
    (hE : Integrable (FunctionalInequalities.Analysis.energyDensity u a f)
      (volume : Measure (EuclideanSpace ℝ (Fin n)))) :
    (∫ x, FunctionalInequalities.Analysis.generatorDensity u V a f x
      ∂(volume : Measure (EuclideanSpace ℝ (Fin n)))) =
        -∫ x, FunctionalInequalities.Analysis.energyDensity u a f x
          ∂(volume : Measure (EuclideanSpace ℝ (Fin n))) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/BakryEmery/IntegrationByParts/InverseHessian/Weak.lean#L602-L742 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.BakryEmery.IntegrationByParts.InverseHessian.Weak`, declaration `_private.FunctionalInequalities.Analysis.BakryEmery.IntegrationByParts.InverseHessian.Weak.0.FunctionalInequalities.Analysis.assemble_generator`; the repository is private at upload time).

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