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Piola Identity for Smooth Hessian Adjugates

Proved
FunctionalInequalities.Analysis.sum_fderiv_adjugate_hessianMatrix_eq_zero_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This is the smooth Piola identity for Hessian adjugates.

Let n∈Nn\in\mathbb Nn∈N, let u:EuclideanSpace⁡(R,Fin⁡(n))→Ru:\operatorname{EuclideanSpace}(\mathbb R,\operatorname{Fin}(n))\to\mathbb Ru:EuclideanSpace(R,Fin(n))→R be C3C^3C3, and let xxx be a point and i<ni<ni<n a row index. If H(y)=hessianMatrix⁡(u,y)H(y)=\operatorname{hessianMatrix}(u,y)H(y)=hessianMatrix(u,y), then

∑j<nD[y↦adj⁡(H(y))ij](x)ej=0,\sum_{j<n}D\bigl[y\mapsto \operatorname{adj}(H(y))_{ij}\bigr](x)e_j=0,j<n∑​D[y↦adj(H(y))ij​](x)ej​=0,

where eje_jej​ is the standard coordinate vector. The declaration sum_fderiv_adjugate_hessianMatrix_eq_zero_readable states that each row of the adjugate Hessian is divergence-free. It is the smooth input for later weak Piola identities.

Original Lean declaration header

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

theorem sum_fderiv_adjugate_hessianMatrix_eq_zero {n : ℕ} {u : EuclideanSpace ℝ (Fin n) → ℝ}
    (hu : ContDiff ℝ 3 u) (x : EuclideanSpace ℝ (Fin n)) (i : Fin n) :
    ∑ j, fderiv ℝ (fun y => (hessianMatrix u y).adjugate i j) x
      (EuclideanSpace.basisFun (Fin n) ℝ j) = 0

Module navigation

Module: Analysis/Matrix/Piola.

Definition modules: Analysis/BakryEmery/HessianOperator.

Supporting theorems: fderiv_det_updateRow.

Previous: fderiv_det_updateRow · Next: sum_integral_adjugate_hessianMatrix_mul_fderiv_eq_zero_of_lipschitz.

Source excerpt, lines 135–138 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Matrix_Piola

open FunctionalInequalities.Probability.Stein
Formal statement

theorem FunctionalInequalities.Analysis.sum_fderiv_adjugate_hessianMatrix_eq_zero_readable {n : ℕ} {u : EuclideanSpace ℝ (Fin n) → ℝ}
    (hu : ContDiff ℝ 3 u) (x : EuclideanSpace ℝ (Fin n)) (i : Fin n) :
    ∑ j, fderiv ℝ (fun y => (hessianMatrix u y).adjugate i j) x
      (EuclideanSpace.basisFun (Fin n) ℝ j) = 0 := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Matrix/Piola.lean#L131-L270 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Matrix.Piola`, declaration `FunctionalInequalities.Analysis.sum_fderiv_adjugate_hessianMatrix_eq_zero`; the repository is private at upload time).

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