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First Taylor Tensor as a Centered Moment

Proved
FunctionalInequalities.Analysis.BakryEmery.taylorTensor_one_apply_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This formalizes the centered first-moment formula for the first Taylor tensor.

Let EEE be a finite-dimensional real inner-product space with its Borel measurable structure, and let μ\muμ be a probability measure on EEE. Assume:

  1. For every r∈Rr\in\mathbb Rr∈R, x↦er∥x∥x\mapsto e^{r\|x\|}x↦er∥x∥ is integrable with respect to μ\muμ.
  2. f:E→Rf:E\to\mathbb Rf:E→R belongs to L2(μ)L^2(\mu)L2(μ).
  3. w∈Ew\in Ew∈E.

Writing TdfT_d fTd​f for taylorTensor μ f d, the first tensor evaluated at www satisfies

T1f(w)=∫⟨w,x⟩f(x) dμ(x)−(∫f dμ)(∫⟨w,x⟩ dμ(x)).T_1f(w)=\int \langle w,x\rangle f(x)\,d\mu(x) -\left(\int f\,d\mu\right)\left(\int \langle w,x\rangle\,d\mu(x)\right).T1​f(w)=∫⟨w,x⟩f(x)dμ(x)−(∫fdμ)(∫⟨w,x⟩dμ(x)).

This identifies the first Taylor tensor with the centered first moment and provides the degree-one case used in tensor and cumulant calculations.

Formalization Note The measure is a probability measure, and all displayed integrals are ordinary real-valued integrals under the stated integrability consequences of the hypotheses.

Original Lean declaration header

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

theorem taylorTensor_one_apply (μ : Measure E) [IsProbabilityMeasure μ]
    (hexp : ∀ r : ℝ, Integrable (fun x => Real.exp (r * ‖x‖)) μ) {f : E → ℝ}
    (hf : MemLp f 2 μ) (w : E) :
    taylorTensor μ f 1 (fun _ => w) =
      (∫ x, ⟪w, x⟫ * f x ∂μ) - (∫ x, f x ∂μ) * ∫ x, ⟪w, x⟫ ∂μ

Module navigation

Module: Analysis/BakryEmery/Tilt/LocalDerivatives.

Definition modules: Analysis/BakryEmery/Tilt/Basic.

Supporting theorems: contDiff_tiltAverage_of_memLp, integrable_exp_mul_norm_of_memLp.

Source excerpt, lines 168–172 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_BakryEmery_Tilt_LocalDerivatives

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

theorem FunctionalInequalities.Analysis.BakryEmery.taylorTensor_one_apply_readable (μ : Measure E) [IsProbabilityMeasure μ]
    (hexp : ∀ r : ℝ, Integrable (fun x => Real.exp (r * ‖x‖)) μ) {f : E → ℝ}
    (hf : MemLp f 2 μ) (w : E) :
    taylorTensor μ f 1 (fun _ => w) =
      (∫ x, ⟪w, x⟫ * f x ∂μ) - (∫ x, f x ∂μ) * ∫ x, ⟪w, x⟫ ∂μ := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/BakryEmery/Tilt/LocalDerivatives.lean#L166-L257 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.BakryEmery.Tilt.LocalDerivatives`, declaration `FunctionalInequalities.Analysis.BakryEmery.taylorTensor_one_apply`; the repository is private at upload time).

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