English

On the maximal perimeter of isotropic log-concave probability measures

Metric Geometry 2026-02-04 v1 Functional Analysis Probability

Abstract

We study the maximal perimeter constant of isotropic log-concave probability measures on Rn\mathbb{R}^n. For a measure μ\mu, this quantity, denoted by Γ(μ)\Gamma(\mu), is defined as the supremum of the μ\mu-perimeter over all convex bodies and measures the largest possible boundary contribution of convex sets with respect to μ\mu. Let Γn:=sup{Γ(μ):μ is an isotropic log-concave probability measure on Rn}.\Gamma_n := \sup\{\Gamma(\mu) : \mu \text{ is an isotropic log-concave probability measure on } \mathbb{R}^n\}. We prove that ΓnCn3/2\Gamma_n \leqslant Cn^{3/2}, where C>0C>0 is an absolute constant. This result improves the previously known O(n2)O(n^2) upper bound. Under additional structural assumptions, we obtain sharp linear bounds of order O(n)O(n).

Keywords

Cite

@article{arxiv.2602.03831,
  title  = {On the maximal perimeter of isotropic log-concave probability measures},
  author = {Silouanos Brazitikos and Apostolos Giannopoulos and Antonios Hmadi and Natalia Tziotziou},
  journal= {arXiv preprint arXiv:2602.03831},
  year   = {2026}
}

Comments

20 pages