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arXiv · 1903.08387

Dynamic Geometric Data Structures via Shallow Cuttings

Timothy M. Chan
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Abstract

We present new results on a number of fundamental problems about dynamic geometric data structures: 1. We describe the first fully dynamic data structures with sublinear amortized update time for maintaining (i) the number of vertices or the volume of the convex hull of a 3D point set, (ii) the largest empty circle for a 2D point set, (iii) the Hausdorff distance between two 2D point sets, (iv) the discrete 1-center of a 2D point set, (v)the number of maximal (i.e., skyline) points in a 3D point set. The update times are near $n^{11/12}$ for (i) and (ii), $n^{7/8}$ for (iii) and (iv), and $n^{2/3}$ for (v). Previously, sublinear bounds were known only for restricted `semi-online' settings [Chan, SODA 2002]. 2. We slightly improve previous fully dynamic data structures for answering extreme point queries for the convex hull of a 3D point set and nearest neighbor search for a 2D point set. The query time is $O(\log^2n)$, and the amortized update time is $O(\log^4n)$ instead of $O(\log^5n)$ [Chan, SODA 2006; Kaplan et al., SODA 2017]. 3. We also improve previous fully dynamic data structures for maintaining the bichromatic closest pair between two 2D point sets and the diameter of a 2D point set. The amortized update time is $O(\log^4n)$ instead of $O(\log^7n)$ [Eppstein 1995; Chan, SODA 2006; Kaplan et al., SODA 2017].

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Timothy M. Chan. 2019-03-20. Dynamic Geometric Data Structures via Shallow Cuttings. https://arxiv.org/abs/1903.08387

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