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Combinatorial criteria for uniqueness of Gibbs measures
Author(s) -
Weitz Dror
Publication year - 2005
Publication title -
random structures and algorithms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.314
H-Index - 69
eISSN - 1098-2418
pISSN - 1042-9832
DOI - 10.1002/rsa.20073
Subject(s) - uniqueness , markov chain , gibbs measure , mathematical proof , mathematics , mixing (physics) , measure (data warehouse) , statistical physics , graph , markov process , computer science , discrete mathematics , statistics , physics , data mining , mathematical analysis , geometry , quantum mechanics
We generalize previously known conditions for uniqueness of the Gibbs measure in statistical physics models by presenting conditions of any finite size for models on any underlying graph. We give two dual conditions, one requiring that the total influence on a site is small, and the other that the total influence of a site is small. Our proofs are combinatorial in nature and use tools from the analysis of discrete Markov chains, in particular the path coupling method. The implications of our conditions for the mixing time of natural Markov chains associated with the models are discussed as well. We also present some examples of models for which the conditions hold. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2005