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Matching Random Colored Points with Rectangles

Matching random colored points with rectangles
Authors: Corujo, Josué; Flores-Peñaloza, David; Huemer, Clemens; Pérez-Lantero, Pablo; Seara, Carlos;

Matching Random Colored Points with Rectangles

Abstract

Let S[0,1]2 be a set of n points, randomly and uniformly selected. Let RB be a random partition, or coloring, of S in which each point of S is included in R uniformly at random with probability 1/2. We study the random variable M(n) equal to the number of points of S that are covered by the rectangles of a maximum strong matching of S with axis-aligned rectangles. The matching consists of closed rectangles that cover exactly two points of S of the same color. A matching is strong if all its rectangles are pairwise disjoint. We prove that almost surely M(n)=0.83n for n large enough. Our approach is based on modeling a deterministic greedy matching algorithm, that runs over the random point set, as a Markov chain. Research supported by projects MTM2015-63791-R MINECO/FEDER and Gen. Cat. DGR 2017SGR1640

Countries
Spain, France
Keywords

[MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Combinatorial optimization, geometric matchings, Computational geometry, Geometria computacional, random colored points, Grafs, Random colored points, Geometric matchings, Computer graphics; computational geometry (digital and algorithmic aspects), Computational methods in Markov chains, Analysis of algorithms, :Matemàtiques i estadística::Geometria::Geometria computacional [Àrees temàtiques de la UPC], Combinatorial probability, Teoria de, Markov chains, Grafs, Teoria de, Discrete mathematics, Markov chains (discrete-time Markov processes on discrete state spaces), Graph theory, [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica discreta::Combinatòria, Àrees temàtiques de la UPC::Matemàtiques i estadística::Geometria::Geometria computacional, Anàlisi combinatòria

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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