最近邻矩阵上Gibbs测度的r -正性和零温度极限的存在性

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY Journal of Applied Probability Pub Date : 2023-09-25 DOI:10.1017/jpr.2023.59
Jorge Littin Curinao, Gerardo Corredor Rincón
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引用次数: 0

摘要

摘要研究了一组在原点反射的最近邻矩阵$(Q_{\beta})_{\beta \geq 0}$的无穷体积Gibbs测量序列$(\mu_{\beta}(\!\cdot\!))_{\beta \geq 0}$在逆温度$\beta$的$R_\beta$ -正性和零温度极限的存在性。我们使用了一种基于连续分数理论的概率方法,该理论先前在Ferrari和Martínez(1993)中引入,并在Littin和Martínez(2010)中得到了加强。给出了保证(1)对于大而有限值的$\beta$存在唯一的无限体积Gibbs测度和(2)弱极限$\beta \to \infty$存在的充分必要条件。修改了一些应用实例,以便将本工作的主要结果放在上下文中。
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R-positivity and the existence of zero-temperature limits of Gibbs measures on nearest-neighbor matrices
Abstract We study the $R_\beta$ -positivity and the existence of zero-temperature limits for a sequence of infinite-volume Gibbs measures $(\mu_{\beta}(\!\cdot\!))_{\beta \geq 0}$ at inverse temperature $\beta$ associated to a family of nearest-neighbor matrices $(Q_{\beta})_{\beta \geq 0}$ reflected at the origin. We use a probabilistic approach based on the continued fraction theory previously introduced in Ferrari and Martínez (1993) and sharpened in Littin and Martínez (2010). Some necessary and sufficient conditions are provided to ensure (i) the existence of a unique infinite-volume Gibbs measure for large but finite values of $\beta$ , and (ii) the existence of weak limits as $\beta \to \infty$ . Some application examples are revised to put in context the main results of this work.
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来源期刊
Journal of Applied Probability
Journal of Applied Probability 数学-统计学与概率论
CiteScore
1.50
自引率
10.00%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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