Properties of Random Graphs via Boltzmann Samplers

This work is devoted to the understanding of properties of random graphs from graph classes with structural constraints. We propose a method that is based on the analysis of the behaviour of Boltzmann sampler algorithms, and may be used to obtain precise estimates for the maximum degree and maximum...

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Main Authors: Konstantinos Panagiotou, Andreas Weißl
Format: Article
Language:English
Published: Discrete Mathematics & Theoretical Computer Science 2007-01-01
Series:Discrete Mathematics & Theoretical Computer Science
Subjects:
Online Access:https://dmtcs.episciences.org/3552/pdf
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author Konstantinos Panagiotou
Andreas Weißl
author_facet Konstantinos Panagiotou
Andreas Weißl
author_sort Konstantinos Panagiotou
collection DOAJ
description This work is devoted to the understanding of properties of random graphs from graph classes with structural constraints. We propose a method that is based on the analysis of the behaviour of Boltzmann sampler algorithms, and may be used to obtain precise estimates for the maximum degree and maximum size of a biconnected block of a "typical'' member of the class in question. We illustrate how our method works on several graph classes, namely dissections and triangulations of convex polygons, embedded trees, and block and cactus graphs.
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spelling doaj.art-523351b79064460b8e308f3e370ded902024-03-07T14:34:52ZengDiscrete Mathematics & Theoretical Computer ScienceDiscrete Mathematics & Theoretical Computer Science1365-80502007-01-01DMTCS Proceedings vol. AH,...Proceedings10.46298/dmtcs.35523552Properties of Random Graphs via Boltzmann SamplersKonstantinos Panagiotou0Andreas WeißlInstitute of Theoretical Computer Science [Zurich]This work is devoted to the understanding of properties of random graphs from graph classes with structural constraints. We propose a method that is based on the analysis of the behaviour of Boltzmann sampler algorithms, and may be used to obtain precise estimates for the maximum degree and maximum size of a biconnected block of a "typical'' member of the class in question. We illustrate how our method works on several graph classes, namely dissections and triangulations of convex polygons, embedded trees, and block and cactus graphs.https://dmtcs.episciences.org/3552/pdfrandom graphs with structural constraintsgenerating functionssampling algorithms[info.info-ds] computer science [cs]/data structures and algorithms [cs.ds][info.info-dm] computer science [cs]/discrete mathematics [cs.dm][math.math-co] mathematics [math]/combinatorics [math.co][info.info-cg] computer science [cs]/computational geometry [cs.cg]
spellingShingle Konstantinos Panagiotou
Andreas Weißl
Properties of Random Graphs via Boltzmann Samplers
Discrete Mathematics & Theoretical Computer Science
random graphs with structural constraints
generating functions
sampling algorithms
[info.info-ds] computer science [cs]/data structures and algorithms [cs.ds]
[info.info-dm] computer science [cs]/discrete mathematics [cs.dm]
[math.math-co] mathematics [math]/combinatorics [math.co]
[info.info-cg] computer science [cs]/computational geometry [cs.cg]
title Properties of Random Graphs via Boltzmann Samplers
title_full Properties of Random Graphs via Boltzmann Samplers
title_fullStr Properties of Random Graphs via Boltzmann Samplers
title_full_unstemmed Properties of Random Graphs via Boltzmann Samplers
title_short Properties of Random Graphs via Boltzmann Samplers
title_sort properties of random graphs via boltzmann samplers
topic random graphs with structural constraints
generating functions
sampling algorithms
[info.info-ds] computer science [cs]/data structures and algorithms [cs.ds]
[info.info-dm] computer science [cs]/discrete mathematics [cs.dm]
[math.math-co] mathematics [math]/combinatorics [math.co]
[info.info-cg] computer science [cs]/computational geometry [cs.cg]
url https://dmtcs.episciences.org/3552/pdf
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