Approximations of convex bodies by measure-generated sets

Abstract: Given a Borel measure $\mu$ on ${\mathbb R}^{n}$, we define a convex set by [ M({\mu})=\bigcup_{\substack{0\le f\le1,\ \int_{{\mathbb R}^{n}}f\,{\rm d}{\mu}=1 } }\left{ \int_{{\mathbb R}^{n}}yf\left(y\right)\,{\rm d}{\mu}\left(y\right)\right} , ] where the union is taken over all $\mu$-measurable functions $f:{\mathbb R}^{n}\to\left[0,1\right]$ with $\int_{{\mathbb R}^{n}}f\,{\rm d}{\mu}=1$. We study the properties of these measure-generated sets, and use them to investigate natural variations of problems of approximation of general convex bodies by polytopes with as few vertices as possible. In particular, we study an extension of the vertex index which was introduced by Bezdek and Litvak. As an application, we provide a lower bound for certain average norms of centroid bodies of non-degenerate probability measures.