On the Combinatorial Complexity of Approximating Polytopes
Sunil Arya, Guilherme D. da Fonseca, David M. Mount

TL;DR
This paper improves bounds on the total combinatorial complexity of convex polytope approximations in fixed dimensions, using novel geometric and combinatorial techniques to achieve near-optimal results.
Contribution
It introduces a new method combining Macbeath regions, stratified placement, and a refined cap covering analysis to bound polytope complexity.
Findings
Achieves a polylogarithmic factor improvement over previous bounds.
Provides a tight analysis of a width-based cap covering method.
Uses a deterministic witness-collector technique in convex approximation.
Abstract
Approximating convex bodies succinctly by convex polytopes is a fundamental problem in discrete geometry. A convex body of diameter is given in Euclidean -dimensional space, where is a constant. Given an error parameter , the objective is to determine a polytope of minimum combinatorial complexity whose Hausdorff distance from is at most . By combinatorial complexity we mean the total number of faces of all dimensions of the polytope. A well-known result by Dudley implies that facets suffice, and a dual result by Bronshteyn and Ivanov similarly bounds the number of vertices, but neither result bounds the total combinatorial complexity. We show that there exists an approximating polytope whose total combinatorial complexity is , where…
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