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Smooth-gradient tests and their L² relaxation

Definition
KLSModular_FunctionalInequalities_Energy_SmoothGradient_Basic

by Lazyfill · Oct 25, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitiesklskls-conjecturekls-modularlog-concavemodule-context

Energy.SmoothGradient.Test μ consists of globally C∞ real functions that belong to L²(μ) and whose squared canonical gradient norm is integrable. Its finite energy is the NNReal value represented by the real integral of ‖∇f‖², with no factor of 1/2, and toL2 is the represented L²(μ) class. preEnergy realizes these tests in L²(μ), while relaxation is their sequential L² relaxation as an ENNReal-valued functional. The module does not identify this relaxation with Cheeger energy or assert density or closedness beyond what is encoded by the imported relaxation construction.

Original module imports

import FunctionalInequalities.Energy.Relaxation.Basic
import Mathlib.Analysis.Calculus.ContDiff.Basic
import Mathlib.Analysis.Calculus.Gradient.Basic
import Mathlib.MeasureTheory.Function.L2Space
import Mathlib.MeasureTheory.Measure.ProbabilityMeasure

Original declaration excerpt

Shown in the original module context.

structure Test (μ : ProbabilityMeasure E) where
  /-- The real-valued test function. -/
  toFun : E → ℝ
  /-- The test is globally `C∞`.

  In Mathlib's differentiability index, `∞` denotes ordinary infinite differentiability;
  `⊤` is the stronger analytic regularity and is not required here.
  -/
  contDiff : ContDiff ℝ ∞ toFun
  /-- The test defines an element of real `L²(μ)`. -/
  memLp_two : MemLp toFun 2 (μ : Measure E)
  /-- The squared norm of the canonical Hilbert gradient is integrable. -/
  gradient_sq_integrable :
    Integrable (fun x ↦ ‖gradient toFun x‖ ^ 2) (μ : Measure E)

Module navigation

Direct project imports: Energy/Relaxation/Basic.

Project result: The KLS conjecture.

Original module · FunctionalInequalities.Energy.SmoothGradient.Basic · Frozen source 408915f.

Definition code
import Definitions.Def_KLSModular_FunctionalInequalities_Energy_Relaxation_Basic
import Mathlib.Analysis.Calculus.ContDiff.Basic
import Mathlib.Analysis.Calculus.Gradient.Basic
import Mathlib.MeasureTheory.Function.L2Space
import Mathlib.MeasureTheory.Measure.ProbabilityMeasure

noncomputable section
open MeasureTheory
open scoped ContDiff
namespace FunctionalInequalities
namespace Energy
namespace SmoothGradient
universe u
variable {E : Type u} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [CompleteSpace E]
  [MeasurableSpace E]
/-- A globally `C∞` real `L²(μ)` test with finite canonical gradient energy. -/
structure Test (μ : ProbabilityMeasure E) where
  /-- The real-valued test function. -/
  toFun : E → ℝ
  /-- The test is globally `C∞`.

  In Mathlib's differentiability index, `∞` denotes ordinary infinite differentiability;
  `⊤` is the stronger analytic regularity and is not required here.
  -/
  contDiff : ContDiff ℝ ∞ toFun
  /-- The test defines an element of real `L²(μ)`. -/
  memLp_two : MemLp toFun 2 (μ : Measure E)
  /-- The squared norm of the canonical Hilbert gradient is integrable. -/
  gradient_sq_integrable :
    Integrable (fun x ↦ ‖gradient toFun x‖ ^ 2) (μ : Measure E)
namespace Test
variable {μ : ProbabilityMeasure E}
instance : CoeFun (Test μ) (fun _ ↦ E → ℝ) :=
  ⟨toFun⟩
/-- The squared gradient norm is pointwise nonnegative. -/
theorem gradientSq_nonneg (f : Test μ) (x : E) :
    0 ≤ ‖gradient f.toFun x‖ ^ 2 :=
  sq_nonneg _
/-- The finite real integral underlying the smooth-gradient energy is nonnegative. -/
theorem gradientIntegral_nonneg (f : Test μ) :
    0 ≤ ∫ x, ‖gradient f.toFun x‖ ^ 2 ∂(μ : Measure E) :=
  integral_nonneg f.gradientSq_nonneg
/-- The finite canonical gradient integral, valued in `NNReal`. -/
def energy (f : Test μ) : NNReal :=
  ⟨∫ x, ‖gradient f.toFun x‖ ^ 2 ∂(μ : Measure E), f.gradientIntegral_nonneg⟩
/-- Coercing the finite energy to `ℝ` recovers its defining integral. -/
@[simp, norm_cast]
theorem coe_energy (f : Test μ) :
    (f.energy : ℝ) = ∫ x, ‖gradient f.toFun x‖ ^ 2 ∂(μ : Measure E) :=
  rfl
/-- The `L²(μ)` element represented by a smooth-gradient test. -/
def toL2 (f : Test μ) : Lp ℝ 2 (μ : Measure E) :=
  f.memLp_two.toLp f.toFun
end Test
/-- The finite smooth-gradient pre-energy, realized in real `L²(μ)`. -/
def preEnergy (μ : ProbabilityMeasure E) [FiniteDimensional ℝ E]
    [BorelSpace E] [SecondCountableTopology E] :
    PreEnergy (Lp ℝ 2 (μ : Measure E)) where
  Test := Test μ
  toAmbient := Test.toL2
  energy := Test.energy
/-- The ambient realization of the smooth-gradient pre-energy is the test's `L²` class. -/
@[simp]
theorem preEnergy_toAmbient (μ : ProbabilityMeasure E) [FiniteDimensional ℝ E]
    [BorelSpace E] [SecondCountableTopology E]
    (f : Test μ) :
    (preEnergy μ).toAmbient f = f.toL2 :=
  rfl
/-- The smooth-gradient pre-energy is exactly the finite squared-gradient integral. -/
@[simp]
theorem preEnergy_energy (μ : ProbabilityMeasure E) [FiniteDimensional ℝ E]
    [BorelSpace E] [SecondCountableTopology E]
    (f : Test μ) :
    (preEnergy μ).energy f = f.energy :=
  rfl
/-- The sequential `L²` relaxation of the smooth-gradient pre-energy.

This is the intended candidate for the standard canonical energy `2 Ch`. The equality with
`2 Ch`, and the required smooth-core density statement, are deliberately left as later
theorems rather than built into this name. -/
def relaxation (μ : ProbabilityMeasure E) [FiniteDimensional ℝ E]
    [BorelSpace E] [SecondCountableTopology E] :
    Functional (Lp ℝ 2 (μ : Measure E)) :=
  (preEnergy μ).sequentialRelaxation
end SmoothGradient
end Energy
end FunctionalInequalities
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Energy/SmoothGradient/Basic.lean#L35-L121 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Energy.SmoothGradient.Basic`, definition bundle `KLSModular_FunctionalInequalities_Energy_SmoothGradient_Basic`; the repository is private at upload time).

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