Maximal surface area of polytopes with respect to log-concave rotation invariant measures

It was shown in \cite{GL} that the maximal surface area of a convex set in $\mathbb{R}^n$ with respect to a rotation invariant log-concave probability measure $γ$ is of order $\frac{\sqrt{n}}{\sqrt[4]{Var|X|} \sqrt{\mathbb{E}|X|}}$, where $X$ is a random vector in $\mathbb{R}^n$ distributed with respect to $γ$. In the present paper we discuss surface area of convex polytopes $P_K$ with $K$ facets. We find tight bounds on the maximal surface area of $P_K$ in terms of $K$. We show that $γ(\partial P_K)\lesssim \frac{\sqrt{n}}{\mathbb{E}|X|}\cdot\sqrt{\log K}\cdot\log n$ for all $K$. This bound is better then the general bound for all $K\in [2,e^{\frac{c}{\sqrt{Var|X|}}}]$. Moreover, for all $K$ in that range the bound is exact up to a factor of $\log n$: for each $K\in [2,e^{\frac{c}{\sqrt{Var|X|}}}]$ there exists a polytope $P_K$ with at most $K$ facets such that $γ(\partial P_K)\gtrsim \frac{\sqrt{n}}{\mathbb{E}|X|}\sqrt{\log K}.$ %For the measures $γ_p$ with densities $C_{n,p} e^{-\frac{|y|^p}{p}}$ (where $p>0$) we obtain: $γ_p(\partial P_K)\lesssim \frac{\sqrt{n}}{\mathbb{E}X}\sqrt{\log K},$ which was obtained for the standard Gaussian measure $γ_2$ by F. Nazarov.

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