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Random Structures and Algorithms
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Matchings on trees and the adjacency matrix: A determinantal viewpoint

Matchings on trees and the adjacency matrix: a determinantal viewpoint
Authors: András Mészáros;

Matchings on trees and the adjacency matrix: A determinantal viewpoint

Abstract

AbstractLet be a finite tree. For any matching of , let be the set of vertices uncovered by . Let be a uniform random maximum size matching of . In this paper, we analyze the structure of . We first show that is a determinantal process. We also show that for most vertices of , the process in a small neighborhood of that vertex can be well approximated based on a somewhat larger neighborhood of the same vertex. Then we show that the normalized Shannon entropy of can be also well approximated using the local structure of . In other words, in the realm of trees, the normalized Shannon entropy of —that is, the normalized logarithm of the number of maximum size matchings of —is a Benjamini‐Schramm continuous parameter.

Country
Hungary
Keywords

QA Mathematics / matematika, Measures of information, entropy, Graphs and linear algebra (matrices, eigenvalues, etc.), Probability (math.PR), 510, local weak convergence, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), determinantal measure, Mathematics - Probability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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