Polymer Dynamics via Cliques: New Conditions for Approximations

Fuente: arXiv
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Main Authors: Friedrich, Tobias, Göbel, Andreas, Krejca, Martin S., Pappik, Marcus
Format: Preprint
Published: 2020
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author Friedrich, Tobias
Göbel, Andreas
Krejca, Martin S.
Pappik, Marcus
author_facet Friedrich, Tobias
Göbel, Andreas
Krejca, Martin S.
Pappik, Marcus
contents Abstract polymer models are systems of weighted objects, called polymers, equipped with an incompatibility relation. An important quantity associated with such models is the partition function, which is the weighted sum over all sets of compatible polymers. Various approximation problems reduce to approximating the partition function of a polymer model. Central to the existence of such approximation algorithms are weight conditions of the respective polymer model. Such conditions are derived either via complex analysis or via probabilistic arguments. We follow the latter path and establish a new condition -- the clique dynamics condition -- , which is less restrictive than the ones in the literature. We introduce a new Markov chain where the clique dynamics condition implies rapid mixing by utilizing cliques of incompatible polymers that naturally arise from the translation of algorithmic problems into polymer models. This leads to improved parameter ranges for several approximation algorithms, such as a factor of at least $2^{1/α}$ for the hard-core model on bipartite $α$-expanders.
format Preprint
id arxiv_https___arxiv_org_abs_2007_08293
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Polymer Dynamics via Cliques: New Conditions for Approximations
Friedrich, Tobias
Göbel, Andreas
Krejca, Martin S.
Pappik, Marcus
Probability
Discrete Mathematics
F.0; G.2.0; G.3
Abstract polymer models are systems of weighted objects, called polymers, equipped with an incompatibility relation. An important quantity associated with such models is the partition function, which is the weighted sum over all sets of compatible polymers. Various approximation problems reduce to approximating the partition function of a polymer model. Central to the existence of such approximation algorithms are weight conditions of the respective polymer model. Such conditions are derived either via complex analysis or via probabilistic arguments. We follow the latter path and establish a new condition -- the clique dynamics condition -- , which is less restrictive than the ones in the literature. We introduce a new Markov chain where the clique dynamics condition implies rapid mixing by utilizing cliques of incompatible polymers that naturally arise from the translation of algorithmic problems into polymer models. This leads to improved parameter ranges for several approximation algorithms, such as a factor of at least $2^{1/α}$ for the hard-core model on bipartite $α$-expanders.
title Polymer Dynamics via Cliques: New Conditions for Approximations
topic Probability
Discrete Mathematics
F.0; G.2.0; G.3
url https://arxiv.org/abs/2007.08293