English

Bounding the norm of a log-concave vector via thin-shell estimates

Functional Analysis 2015-05-06 v2 Metric Geometry Probability

Abstract

Chaining techniques show that if X is an isotropic log-concave random vector in R^n and Gamma is a standard Gaussian vector then E |X| < C n^{1/4} E |Gamma| for any norm |*|, where C is a universal constant. Using a completely different argument we establish a similar inequality relying on the thin-shell constant sigma_n = sup ((var|X|^){1/2} ; X isotropic and log-concave on R^n). In particular, we show that if the thin-shell conjecture sigma_n = O(1) holds, then n^{1/4} can be replaced by log (n) in the inequality. As a consequence, we obtain certain bounds for the mean-width, the dual mean-width and the isotropic constant of an isotropic convex body. In particular, we give an alternative proof of the fact that a positive answer to the thin-shell conjecture implies a positive answer to the slicing problem, up to a logarithmic factor.

Keywords

Cite

@article{arxiv.1306.3696,
  title  = {Bounding the norm of a log-concave vector via thin-shell estimates},
  author = {Ronen Eldan and Joseph Lehec},
  journal= {arXiv preprint arXiv:1306.3696},
  year   = {2015}
}

Comments

preliminary version, 13 pages

R2 v1 2026-06-22T00:34:35.612Z