2016
DOI: 10.1002/rsa.20671
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Fuzzy transformations and extremality of Gibbs measures for the potts model on a Cayley tree

Abstract: Abstract. We continue our study of the full set of translation-invariant splitting Gibbs measures (TISGMs, translation-invariant tree-indexed Markov chains) for the qstate Potts model on a Cayley tree. In our previous work [14] we gave a full description of the TISGMs, and showed in particular that at sufficiently low temperatures their number is 2 q − 1. In this paper we find some regions for the temperature parameter ensuring that a given TISGM is (non-)extreme in the set of all Gibbs measures. In particular… Show more

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Cited by 55 publications
(27 citation statements)
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“…Interesting sources of non-Gibbsian behavior include time evolutions or deterministic transformations which reduce the complexity of the local state space. A prototypical example of a system of the second type is the fuzzy Potts model (fuzzy PM) [20,28,26,22,19,1]. It is obtained from the ordinary PM by partitioning the local state space {1, 2, .…”
Section: Introductionmentioning
confidence: 99%
“…Interesting sources of non-Gibbsian behavior include time evolutions or deterministic transformations which reduce the complexity of the local state space. A prototypical example of a system of the second type is the fuzzy Potts model (fuzzy PM) [20,28,26,22,19,1]. It is obtained from the ordinary PM by partitioning the local state space {1, 2, .…”
Section: Introductionmentioning
confidence: 99%
“…Мы используем методы из работы [9] (см. также Лемму 5.7 из [10]). Рассмотрим цепь Маркова с состояниями {0, 1} и матрицу P µ * вероятностных переходов P ij , определенную данной ТИМГ µ * следующим образом:…”
Section: определения и известные фактыunclassified
“…We then turn to the question of their extremality. Analogous questions has been studied by the authors for all TISGMs of the Potts model in [6], [7] and we will draw from our experience to treat the present situation, incorporating the non-symmetric states. As we will see, our classification for the SOS-model leaves fewer gaps than for the Potts model.…”
Section: Introductionmentioning
confidence: 99%