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Interior Domain at the Origin from a Lower Bound

Proved
FunctionalInequalities.Probability.MomentMeasure.origin_mem_interior_domain_of_lower_bound_readable

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

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This gives the normalization precursor for a convex potential.

Let μ\muμ be a finite Borel measure on a finite-dimensional real inner-product space. Assume:

  1. 000 lies in the interior of the convex hull of supp⁡μ\operatorname{supp}\musuppμ;
  2. the identity map is integrable with respect to μ\muμ;
  3. ccc is a convex potential that is potential-integrable with respect to μ\muμ;
  4. for some M∈RM\in\mathbb RM∈R, −M≤c(x)-M\leq c(x)−M≤c(x) for every xxx.

Then

0∈int⁡{x:c(x)≠+∞}.0\in\operatorname{int}\{x:c(x)\neq+\infty\}.0∈int{x:c(x)=+∞}.

The result converts a signed lower-bounded convex potential into the nonnegative setting needed for effective-domain interior arguments.

Original Lean declaration header

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

theorem origin_mem_interior_domain_of_lower_bound (μ : Measure E) [IsFiniteMeasure μ]
    (h0 : (0 : E) ∈ interior (convexHull ℝ μ.support))
    (hfirst : Integrable (fun x : E => x) μ)
    (c : E → EReal) (hc : ConvexPotential c) (hp : PotentialIntegrable c μ)
    (M : ℝ) (hlower : ∀ x, ((-M : ℝ) : EReal) ≤ c x) :
    (0 : E) ∈ interior {x | c x ≠ ⊤}

Module navigation

Module: Probability/MomentMeasure/Normalization.

Definition modules: Analysis/Convex/Legendre, Probability/MomentMeasure/Basic.

Supporting theorems: convex_epigraph_affineSubtract, affineSubtract_potentialIntegrable, mem_interior_setOf_ne_top_of_lintegral_ne_top.

Source excerpt, lines 30–35 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Probability_MomentMeasure_Normalization

open FunctionalInequalities.Analysis
open MeasureTheory Filter Set
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
  [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
Formal statement

theorem FunctionalInequalities.Probability.MomentMeasure.origin_mem_interior_domain_of_lower_bound_readable (μ : Measure E) [IsFiniteMeasure μ]
    (h0 : (0 : E) ∈ interior (convexHull ℝ μ.support))
    (hfirst : Integrable (fun x : E => x) μ)
    (c : E → EReal) (hc : ConvexPotential c) (hp : PotentialIntegrable c μ)
    (M : ℝ) (hlower : ∀ x, ((-M : ℝ) : EReal) ≤ c x) :
    (0 : E) ∈ interior {x | c x ≠ ⊤} := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Probability/MomentMeasure/Normalization.lean#L28-L57 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Probability.MomentMeasure.Normalization`, declaration `FunctionalInequalities.Probability.MomentMeasure.origin_mem_interior_domain_of_lower_bound`; the repository is private at upload time).

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