Proved
Conditional mathematical implication in the cited source ↗
Observed Oct 13, 2026
Theorem · version 1
If every isotropic log-concave probability measure has Poincaré constant at most C, then every full-dimensional log-concave probability measure μ with covariance Σ satisfies C_P(μ) ≤ C ‖Σ‖op.
This affine-transfer implication does not establish the premise or a numerical value of C. Singular covariance requires a formulation on its affine support.
Proved
Observed Oct 13, 2026
In this problem · publication v3 · Selected context
Conditional implication · Proved
Relationship not independently reviewed. This concerns its use in this problem.
In this problem · publication v5
Conditional implication · Proved
Relationship not independently reviewed. This concerns its use in this problem.
Proposes a dimension-free Poincaré bound for isotropic log-concave measures through cumulant estimates, localization and suspension.
paraphrase · OpenMath supplies its own mathematical paraphrases and links; proof text is not republished.
Pierre Bizeul · Boaz Klartag · Joseph Lehec · Preprint · Publication date Oct 4, 2026
Source revision: 2026-10-04. Observed Oct 13, 2026.
The authors credit ChatGPT with many proof ideas and arguments, and credit the suspension idea and exposition to the human authors. Their approach uses a criterion of Song and Zhang; these are distinct papers with a mathematical dependency, not wholly independent proofs.
Statement versions and problem publication versions are separate. A new publication can update context or sources while retaining the same statement.
Assessments retained in these publication records. Earlier statement versions retain their own source histories.
Proved
Observed Oct 13, 2026 · Source passage →