Optimal Area-Sensitive Bounds for Polytope Approximation

Approximating convex bodies is a fundamental question in geometry and has a wide variety of applications. Given a convex body $K$ of diameter $\Delta$ in $\mathbb{R}^d$ for fixed $d$, the objective is to minimize the number of vertices (alternatively, the number of facets) of an approximating polytope for a given Hausdorff error $\varepsilon$. The best known uniform bound, due to Dudley (1974), shows that $O((\Delta/\varepsilon)^{(d-1)/2})$ facets suffice. While this bound is optimal in the case of a Euclidean ball, it is far from optimal for ``skinny'' convex bodies. A natural way to characterize a convex object's skinniness is in terms of its relationship to the Euclidean ball. Given a convex body $K$, define its surface diameter $\Delta{d-1}$ to be the diameter of a Euclidean ball of the same surface area as $K$. It follows from generalizations of the isoperimetric inequality that $\Delta \geq \Delta{d-1}$. We show that, under the assumption that the width of the body in any direction is at least $\varepsilon$, it is possible to approximate a convex body using $O((\Delta{d-1}/\varepsilon)^{(d-1)/2})$ facets. This bound is never worse than the previous bound and may be significantly better for skinny bodies. The bound is tight, in the sense that for any value of $\Delta{d-1}$, there exist convex bodies that, up to constant factors, require this many facets. The improvement arises from a novel approach to sampling points on the boundary of a convex body. We employ a classical concept from convexity, called Macbeath regions. We demonstrate that Macbeath regions in $K$ and $K$'s polar behave much like polar pairs. We then apply known results on the Mahler volume to bound their number.