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Temperate Functions Belong To The Closed Gradient Domain

Proved
FunctionalInequalities.KLS.LogConcave.exists_toLp_mem_closedWeightedOperator_domain_of_hasTemperateGrowth_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This is a classical-to-L2L^2L2 domain bridge for the closed weighted gradient.

Let VVV be a finite-dimensional real inner-product space with the stated topological and measurable structures. Let ν\nuν be log-concave, let mmm be an additive Haar measure, and assume that the interior of the support of ν\nuν is nonempty. Assume every exponential moment of ν\nuν is integrable. For every function f:V→Rf:V\to\mathbb Rf:V→R of temperate growth, there exist

  1. a proof that f∈L2(ν)f\in L^2(\nu)f∈L2(ν);
  2. a proof that its gradient ∇f∈L2(ν)\nabla f\in L^2(\nu)∇f∈L2(ν); and
  3. a proof that the L2L^2L2 class of fff lies in the domain of the closed weighted operator.

If these objects are denoted by [f][f][f] and [∇f][\nabla f][∇f], then

∇‾[f]=[∇f].\overline{\nabla}[f]=[\nabla f].∇[f]=[∇f].

This result supplies operator-domain membership for temperate test functions and is useful for transferring classical differential identities to L2L^2L2 classes.

Formalization Note. The witnesses are MemLp proofs and a domain-membership proof; toLp denotes the corresponding L2(ν)L^2(\nu)L2(ν) representatives.

Original Lean declaration header

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

theorem exists_toLp_mem_closedWeightedOperator_domain_of_hasTemperateGrowth {f : V → ℝ}
    (hf : f.HasTemperateGrowth) :
    ∃ (hf2 : MemLp f 2 (ν : Measure V)) (hg2 : MemLp (gradient f) 2 (ν : Measure V))
      (hmem : hf2.toLp f ∈ (hν.closedWeightedOperator m (ContinuousLinearMap.id ℝ V) hi).domain),
      hν.closedWeightedOperator m (ContinuousLinearMap.id ℝ V) hi ⟨_, hmem⟩ = hg2.toLp (gradient f)

Module navigation

Module: KLS/LogConcave/HeatSemigroup/Temperate.

Definition modules: KLS/LogConcave/WeightedGradient/Closure, Probability/LogConcave.

Supporting theorems: cutoff_eq_one, hasCompactSupport_cutoff, integrable_of_norm_le_pow, norm_iteratedFDeriv_cutoff_le.

Source excerpt, lines 124–128 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_KLS_LogConcave_HeatSemigroup_Temperate

open MeasureTheory
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [CompleteSpace V]
  [MeasurableSpace V] [BorelSpace V] [SecondCountableTopology V] [FiniteDimensional ℝ V]
  {ν : MeasureTheory.ProbabilityMeasure V} (m : MeasureTheory.Measure V) [m.IsAddHaarMeasure] (hν : FunctionalInequalities.KLS.LogConcave ν)
  (hi : (interior (ν : MeasureTheory.Measure V).support).Nonempty) {U : V → ℝ}
  (hνU : (ν : MeasureTheory.Measure V) = m.tilted (-U)) (hU : U.HasTemperateGrowth)
  (hexp : ∀ r : ℝ, MeasureTheory.Integrable (fun x => Real.exp (r * ‖x‖)) (ν : MeasureTheory.Measure V))
include hexp
Formal statement

theorem FunctionalInequalities.KLS.LogConcave.exists_toLp_mem_closedWeightedOperator_domain_of_hasTemperateGrowth_readable {f : V → ℝ}
    (hf : f.HasTemperateGrowth) :
    ∃ (hf2 : MemLp f 2 (ν : Measure V)) (hg2 : MemLp (gradient f) 2 (ν : Measure V))
      (hmem : hf2.toLp f ∈ (hν.closedWeightedOperator m (ContinuousLinearMap.id ℝ V) hi).domain),
      hν.closedWeightedOperator m (ContinuousLinearMap.id ℝ V) hi ⟨_, hmem⟩ = hg2.toLp (gradient f) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/KLS/LogConcave/HeatSemigroup/Temperate.lean#L121-L221 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.KLS.LogConcave.HeatSemigroup.Temperate`, declaration `FunctionalInequalities.KLS.LogConcave.exists_toLp_mem_closedWeightedOperator_domain_of_hasTemperateGrowth`; the repository is private at upload time).

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