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While there is extensive literature on approximation, deterministic as well as random, of general convex bodies $K$ in the symmetric difference metric, or other metrics arising from intrinsic volumes, very little is known for corresponding…

Metric Geometry · Mathematics 2025-08-25 Joscha Prochno , Carsten Schütt , Mathias Sonnleitner , Elisabeth M. Werner

The distance between convex bodies \(K, L \subseteq \R^n\) is defined as \[ d(K,L)= \inf \left\{ \lambda \ge 1: \ L-x \subseteq T (K-y) \subseteq \lambda (L-x) \right\}, \] where the infimum is taken over all \(x,y \in \R^n\) and all…

Functional Analysis · Mathematics 2026-02-27 Han Huang , Mark Rudelson

We study approximations of smooth convex bodies by random ball-polytopes. We examine the following probability model: let $K\subset{\bf R}^d$ be a convex body such that $K$ slides freely in a ball of radius $R>0$ and has $C^2$ smooth…

Metric Geometry · Mathematics 2020-08-07 Ferenc Fodor

A natural model for the approximation of a convex body $K$ in $\mathbb{R}^d$ by random polytopes is obtained as follows. Take a stationary Poisson hyperplane process in the space, and consider the random polytope $Z_K$ defined as the…

Probability · Mathematics 2019-08-27 Daniel Hug , Rolf Schneider

Approximate a smooth convex body $K$ with nonvanishing curvature by the convex hull of $n$ independent random points sampled from its boundary $\partial K$. In case the points are distributed according to the optimal density, we prove that…

Probability · Mathematics 2025-08-25 Mathias Sonnleitner

Let $K$ be a convex body in $\R^d$, let $j\in\{1, ..., d-1\}$, and let $\varrho$ be a positive and continuous probability density function with respect to the $(d-1)$-dimensional Hausdorff measure on the boundary $\partial K$ of $K$. Denote…

Metric Geometry · Mathematics 2014-10-07 Károly J. Böröczky , Ferenc Fodor , Daniel Hug

We prove that for every convex body $K$ with the center of mass at the origin and every $\varepsilon\in \left(0,\frac{1}{2}\right)$, there exists a convex polytope $P$ with at most $e^{O(d)}\varepsilon^{-\frac{d-1}{2}}$ vertices such that…

Classical Analysis and ODEs · Mathematics 2017-05-05 Márton Naszódi , Fedor Nazarov , Dmitry Ryabogin

In this paper, we give an overview of some results concerning best and random approximation of convex bodies by polytopes. We explain how both are linked and see that random approximation is almost as good as best approximation.

Metric Geometry · Mathematics 2021-11-16 Joscha Prochno , Carsten Schütt , Elisabeth M. Werner

The random polytope $K_n$, defined as the convex hull of $n$ points chosen uniformly at random on the boundary of a smooth convex body, is considered. Proofs for lower and upper variance bounds, strong laws of large numbers and central…

Probability · Mathematics 2017-06-12 Nicola Turchi , Florian Wespi

For a given convex body K in $R^d$, a random polytope $K^{(n)}$ is defined (essentially) as the intersection of $n$ independent closed halfspaces containing $K$ and having an isotropic and (in a specified sense) uniform distribution. We…

Metric Geometry · Mathematics 2009-01-22 Károly J. Böröczky , Rolf Schneider

Let $K$ be a convex body in $\mathbb{R}^d$ which slides freely in a ball. Let $K^{(n)}$ denote the intersection of $n$ closed half-spaces containing $K$ whose bounding hyperplanes are independent and identically distributed according to a…

Metric Geometry · Mathematics 2015-12-09 Ferenc Fodor , Daniel Hug , Ines Ziebarth

Let K be a d-dimensional convex body, and let $K^{(n)}$ be the intersection of n halfspaces containing $K$ whose bounding hyperplanes are independent and identically distributed. Under suitable distributional assumptions, we prove an…

Metric Geometry · Mathematics 2014-10-15 Károly J. Böröczky , Ferenc Fodor , Daniel Hug

Approximating convex bodies is a fundamental question in geometry, which has a wide variety of applications. Given a convex body $K$ in $\textbf{R}^d$ for fixed $d$, the objective is to minimize the number of facets of an approximating…

Computational Geometry · Computer Science 2026-01-26 Sunil Arya , David M. Mount

We present an alternative approach to some results of Koldobsky on measures of sections of symmetric convex bodies, which allows us to extend them to the not necessarily symmetric setting. We prove that if $K$ is a convex body in ${\mathbb…

Metric Geometry · Mathematics 2015-12-31 Giorgos Chasapis , Apostolos Giannopoulos , Dimitris-Marios Liakopoulos

Let K be a convex body in $R^d$. A random polytope is the convex hull $[x_1,...,x_n]$ of finitely many points chosen at random in K. $\Bbb E(K,n)$ is the expectation of the volume of a random polytope of n randomly chosen points. I.…

Metric Geometry · Mathematics 2016-09-06 Carsten Schütt

For an isotropic convex body $K\subset\mathbb{R}^n$ we consider the isotropic constant $L_{K_N}$ of the symmetric random polytope $K_N$ generated by $N$ independent random points which are distributed according to the cone probability…

Metric Geometry · Mathematics 2018-07-09 Joscha Prochno , Christoph Thäle , Nicola Turchi

This paper presents bounds for the best approximation, with respect to the Hausdorff metric, of a convex body $K$ by a circumscribed polytope $P$ with a given number of facets. These bounds are of particular interest if $K$ is elongated. To…

Metric Geometry · Mathematics 2016-12-15 Gilles Bonnet

We investigate the asymptotic best approximation of a smooth, strictly convex body $K$ in $\mathbb{R}^d$ by inscribed polytopes with a restricted number of vertices under the intrinsic volume difference. We prove rigidity phenomena in both…

Metric Geometry · Mathematics 2026-02-24 Steven Hoehner

Polytopes are the basic finite data structures for convex sets: they appear as feasible regions in linear optimization, as geometric summaries in algorithms, and as random objects in stochastic geometry. A natural geometric question is…

Metric Geometry · Mathematics 2026-03-10 Steven Hoehner

The isotropic constant $L_K$ is an affine-invariant measure of the spread of a convex body $K$. For a $d$-dimensional convex body $K$, $L_K$ can be defined by $L_K^{2d} = \det(A(K))/(\mathrm{vol}(K))^2$, where $A(K)$ is the covariance…

Functional Analysis · Mathematics 2015-12-09 Luis Rademacher
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