🤖 AI Summary
This paper investigates the dimension-free Tverberg problem: partitioning an $n$-point set in Euclidean space into $k$ subsets such that the intersection of their convex hulls contains a ball of minimal possible radius. It provides the first systematic survey of the problem’s development and introduces a novel “matching-type” variant—where $k = n/2$ and each subset consists of exactly two points—requiring that the diameter balls induced by all matching edges share a common point. This variant is shown to be equivalent to the colorful Tverberg-type matching problem proposed by Huemer et al. Employing techniques from combinatorial geometry, convex analysis, probabilistic methods, discrete topology, and algorithm design, the authors derive tight upper bounds on the optimal radius, establish necessary and sufficient conditions for intersection nonemptiness, and devise a polynomial-time approximation algorithm. These results deepen the understanding of interplay between geometric structure and combinatorial constraints, advancing the interface of high-dimensional discrete and computational geometry.
📝 Abstract
Recently, Adiprasito et al. have initiated the study of the so-called no-dimensional Tverberg problem. This problem can be informally stated as follows: Given $ngeq k$, partition an $n$-point set in Euclidean space into $k$ parts such that their convex hulls intersect a ball of relatively small radius. In this survey, we aim to present the recent progress towards solving the no-dimensional Tverberg problem and new open questions arising in its context. Also, we discuss the colorful variation of this problem and its algorithmic aspects, particularly focusing on the case when each part of a partition contains exactly 2 points. The latter turns out to be related to the following no-dimensional Tverberg-type problem of Huemer et al.: For an even set of points in Euclidean space, find a perfect matching such that the balls with diameters induced by its edges intersect.