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Standard-Basis Bochner Identity

Proved
FunctionalInequalities.Analysis.BakryEmery.gammaTwo_eq_hessianSqStdBasis_add_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This formalizes the pointwise Bochner identity in the fixed standard orthonormal basis.

Let EEE be a complete finite-dimensional real inner-product space, let U:E→RU:E\to\mathbb RU:E→R be C2C^2C2, let f:E→Rf:E\to\mathbb Rf:E→R be C3C^3C3, and let x∈Ex\in Ex∈E. Then

Γ2(U,f)(x)=HessSq⁡std(f)(x)+D2U(x)(∇f(x),∇f(x)).\Gamma_2(U,f)(x) = \operatorname{HessSq}_{\mathrm{std}}(f)(x) +D^2U(x)(\nabla f(x),\nabla f(x)).Γ2​(U,f)(x)=HessSqstd​(f)(x)+D2U(x)(∇f(x),∇f(x)).

Here gammaTwo U f is the pointwise carré-du-champ iteration, and hessianSqStdBasis f x is the sum of squares of the Hessian entries in the fixed basis (ei)(e_i)(ei​): HessSq⁡std(f)=∑i,j(D2f(ei,ej))2\operatorname{HessSq}_{\mathrm{std}}(f)=\sum_{i,j}(D^2f(e_i,e_j))^2HessSqstd​(f)=∑i,j​(D2f(ei​,ej​))2.

This is the central local identity used to derive nonnegativity and curvature estimates; it asserts a standard-basis formula, not basis independence.

Original Lean declaration header

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

theorem gammaTwo_eq_hessianSqStdBasis_add {U f : E → ℝ} (hU : ContDiff ℝ 2 U)
    (hf : ContDiff ℝ 3 f) (x : E) :
    gammaTwo U f x =
      hessianSqStdBasis f x +
        bilinearIteratedFDerivTwo ℝ U x (gradient f x) (gradient f x)

Module navigation

Module: Analysis/BakryEmery/Bochner/Basic.

Definition modules: Analysis/BakryEmery/Gamma.

Supporting theorems: inner_gradient_gradient_inner, inner_gradient_gradient_laplacian, laplacian_norm_gradient_sq.

Previous: inner_gradient_gradient_inner.

Source excerpt, lines 298–302 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_BakryEmery_Bochner_Basic

universe u
variable {E : Type u} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
variable [CompleteSpace E] [FiniteDimensional ℝ E]
Formal statement

theorem FunctionalInequalities.Analysis.BakryEmery.gammaTwo_eq_hessianSqStdBasis_add_readable {U f : E → ℝ} (hU : ContDiff ℝ 2 U)
    (hf : ContDiff ℝ 3 f) (x : E) :
    gammaTwo U f x =
      hessianSqStdBasis f x +
        bilinearIteratedFDerivTwo ℝ U x (gradient f x) (gradient f x) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/BakryEmery/Bochner/Basic.lean#L296-L313 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.BakryEmery.Bochner.Basic`, declaration `FunctionalInequalities.Analysis.BakryEmery.gammaTwo_eq_hessianSqStdBasis_add`; the repository is private at upload time).

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