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Limit Assembly for Logarithmic Mass Comparison

Proved
FunctionalInequalities.Probability.MomentMeasure.log_sub_ge_of_integral_limits_readable

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

corderoklartag2015functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This is an auxiliary limit-assembly statement related to Proposition 12 of Cordero–Klartag (arXiv:1304.0630v1).

Let a:N→[0,∞]a:\mathbb{N}\to[0,\infty]a:N→[0,∞], m:N→Rm:\mathbb{N}\to\mathbb{R}m:N→R, Z∈[0,∞]Z\in[0,\infty]Z∈[0,∞], and r,S,M∈Rr,S,M\in\mathbb{R}r,S,M∈R. Assume:

  1. 0≤mj0\le m_j0≤mj​ for every jjj.
  2. log⁡aj−mj\log a_j-m_jlogaj​−mj​ converges in the extended real line to SSS.
  3. mjm_jmj​ converges to MMM.
  4. ofReal⁡(r)≤lim inf⁡jofReal⁡(mj)\operatorname{ofReal}(r)\le\liminf_j\operatorname{ofReal}(m_j)ofReal(r)≤liminfj​ofReal(mj​) in [0,∞][0,\infty][0,∞].
  5. lim sup⁡jaj≤Z\limsup_j a_j\le Zlimsupj​aj​≤Z.

Then Z>0Z>0Z>0 and

S≤log⁡Z−r.S\le \log Z-r.S≤logZ−r.

The declaration is a technical assembly lemma for passing from sequence limits and liminf/limsup bounds to a functional comparison; it is not an attainment statement.

Formalization Note. The quantities involving aja_jaj​ and ZZZ use ENNReal.log, while the subtraction and the comparison with SSS and rrr take place in EReal; the conclusion is expressed with the corresponding coercions.

Original Lean declaration header

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

theorem log_sub_ge_of_integral_limits
    (a : ℕ → ℝ≥0∞) (m : ℕ → ℝ) (Z : ℝ≥0∞) (r S M : ℝ)
    (hnn : ∀ j, 0 ≤ m j)
    (hF : Tendsto (fun j => ENNReal.log (a j) - (m j : EReal)) atTop (𝓝 (S : EReal)))
    (hm : Tendsto m atTop (𝓝 M))
    (hfirst : ENNReal.ofReal r ≤ liminf (fun j => ENNReal.ofReal (m j)) atTop)
    (hsecond : limsup a atTop ≤ Z) :
    0 < Z ∧ (S : EReal) ≤ ENNReal.log Z - (r : EReal)

Module navigation

Module: Probability/MomentMeasure/ConjugateMass.

Previous: limsup_mass_legendre_le · Next: real_legendre_normalization.

Source excerpt, lines 211–218 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Probability_MomentMeasure_ConjugateMass

open scoped ENNReal Topology
set_option autoImplicit false
set_option relaxedAutoImplicit false
open Filter
Formal statement

theorem FunctionalInequalities.Probability.MomentMeasure.log_sub_ge_of_integral_limits_readable
    (a : ℕ → ℝ≥0∞) (m : ℕ → ℝ) (Z : ℝ≥0∞) (r S M : ℝ)
    (hnn : ∀ j, 0 ≤ m j)
    (hF : Tendsto (fun j => ENNReal.log (a j) - (m j : EReal)) atTop (𝓝 (S : EReal)))
    (hm : Tendsto m atTop (𝓝 M))
    (hfirst : ENNReal.ofReal r ≤ liminf (fun j => ENNReal.ofReal (m j)) atTop)
    (hsecond : limsup a atTop ≤ Z) :
    0 < Z ∧ (S : EReal) ≤ ENNReal.log Z - (r : EReal) := by sorry
Source
Source: Cordero-Erausquin–Klartag, Moment measures (arXiv:1304.0630v1), Proposition 12. Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Probability/MomentMeasure/ConjugateMass.lean#L206-L241 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Probability.MomentMeasure.ConjugateMass`, declaration `FunctionalInequalities.Probability.MomentMeasure.log_sub_ge_of_integral_limits`; the repository is private at upload time).

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