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arXiv 2102.02653math.PRmath.CO
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无限树上过程的典型性与熵

Typicality and entropy of processes on infinite trees

Ágnes Backhausz, Charles Bordenave, Balázs Szegedy

摘要:

考虑一个顶点为$n$的均匀抽样随机$d$ -正则图.如果$d$是固定的,并且$n$转到$\infty$,那么我们可以将这种随机图的典型(大概率)性质与无限$d$ -正则树$T_d$上的一族不变随机过程(称为“典型”过程)联系起来。$T_d$上的遍历论与随机正则图之间的这种对应关系已经被证明在两个方向上都是富有成效的。本文继续对典型过程的研究,特别强调熵。我们研究了$T_d$上不变过程的微观状态熵的自然概念。它作为典型性概念的定量细化,并与统计物理学中的渐近自由能紧密相连。利用熵不等式,给出了边马氏过程典型性的新的充分条件。我们还将这些概念和结果扩展到单模Galton-Watson随机树上的过程。

英文摘要:

Consider a uniformly sampled random $d$-regular graph on $n$ vertices. If $d$ is fixed and $n$ goes to $\infty$ then we can relate typical (large probability) properties of such random graph to a family of invariant random processes (called "typical" processes) on the infinite $d$-regular tree $T_d$. This correspondence between ergodic theory on $T_d$ and random regular graphs is already proven to be fruitful in both directions. This paper continues the investigation of typical processes with a special emphasis on entropy. We study a natural notion of micro-state entropy for invariant processes on $T_d$. It serves as a quantitative refinement of the notion of typicality and is tightly connected to the asymptotic free energy in statistical physics. Using entropy inequalities, we provide new sufficient conditions for typicality for edge Markov processes. We also extend these notions and results to processes on unimodular Galton-Watson random trees.

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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