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arXiv math-ph/0501002math-phmath.MP
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无限图上q>0的随机簇模型的收敛展开

Convergent expansions for Random Cluster Model with q>0 on infinite graphs

Aldo Procacci, Benedetto Scoppola

摘要:

在本文中,我们扩展了我们以前的结果的连通性函数和压力的随机集团模型在高次临界相和高超临界相,原来只证明了立方格子$\Z^d$,更广泛的一类无限图形。特别是,关于亚临界政权,我们表明,连接功能是解析和指数衰减在任何有界度图。在超临界阶段,我们能够证明在一个较小的类图,即有界度图的有限连通函数的解析性与所谓的最小割集属性,并满足(非常温和的)等周不等式。另一方面,我们表明,在超临界状态下的有限连通性的大距离衰减可以多项式慢依赖于图的拓扑结构。对无限图上的随机簇模型的压力,在进一步假设图的顺从性和拟传递性的条件下,得到了类似的解析性结果。

英文摘要:

In this paper we extend our previous results on the connectivity functions and pressure of the Random Cluster Model in the highly subcritical phase and in the highly supercritical phase, originally proved only on the cubic lattice $\Z^d$, to a much wider class of infinite graphs. In particular, concerning the subcritical regime, we show that the connectivity functions are analytic and decay exponentially in any bounded degree graph. In the supercritical phase, we are able to prove the analyticity of finite connectivity functions in a smaller class of graphs, namely, bounded degree graphs with the so called minimal cut-set property and satisfying a (very mild) isoperimetric inequality. On the other hand we show that the large distances decay of finite connectivity in the supercritical regime can be polynomially slow depending on the topological structure of the graph. Analogous analyticity results are obtained for the pressure of the Random Cluster Model on an infinite graph, but with the further assumptions of amenability and quasi-transitivity of the graph.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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