几何交图中的最大匹配。

IF 0.6 3区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS Discrete & Computational Geometry Pub Date : 2023-01-01 Epub Date: 2023-09-09 DOI:10.1007/s00454-023-00564-3
Édouard Bonnet, Sergio Cabello, Wolfgang Mulzer
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引用次数: 7

摘要

设G是平面上n个几何对象的交图。我们证明了G中的最大匹配可以在O(ρ3ω/2nω/2)时间内以高概率找到,其中ρ是几何对象的密度,ω>2是一个常数,使得n×n矩阵可以在0(nω)时间内相乘。同样的结果适用于G的任何子图,只要手头有几何表示。为此,我们将代数方法,即通过高斯消去计算矩阵的秩,与几何交集图具有小分隔符的事实相结合。我们还证明了在许多有趣的情况下,一般几何交集图中的最大匹配问题可以简化为有界密度的情况。特别地,在O(nω/2)时间内,可以高概率地在平面内凸对象的平移的任何族的交集图中找到最大匹配,并且在O(Ψ6log11n+Ψ12ωnω/2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Maximum Matchings in Geometric Intersection Graphs.

Let G be an intersection graph of n geometric objects in the plane. We show that a maximum matching in G can be found in O(ρ3ω/2nω/2) time with high probability, where ρ is the density of the geometric objects and ω>2 is a constant such that n×n matrices can be multiplied in O(nω) time. The same result holds for any subgraph of G, as long as a geometric representation is at hand. For this, we combine algebraic methods, namely computing the rank of a matrix via Gaussian elimination, with the fact that geometric intersection graphs have small separators. We also show that in many interesting cases, the maximum matching problem in a general geometric intersection graph can be reduced to the case of bounded density. In particular, a maximum matching in the intersection graph of any family of translates of a convex object in the plane can be found in O(nω/2) time with high probability, and a maximum matching in the intersection graph of a family of planar disks with radii in [1,Ψ] can be found in O(Ψ6log11n+Ψ12ωnω/2) time with high probability.

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来源期刊
Discrete & Computational Geometry
Discrete & Computational Geometry 数学-计算机:理论方法
CiteScore
1.80
自引率
12.50%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Discrete & Computational Geometry (DCG) is an international journal of mathematics and computer science, covering a broad range of topics in which geometry plays a fundamental role. It publishes papers on such topics as configurations and arrangements, spatial subdivision, packing, covering, and tiling, geometric complexity, polytopes, point location, geometric probability, geometric range searching, combinatorial and computational topology, probabilistic techniques in computational geometry, geometric graphs, geometry of numbers, and motion planning.
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