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arXiv 1202.4903cond-mat.stat-mech
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递归网络首达量的精确计算

Exact calculations of first-passage quantities on recursive networks

B. Meyer, E. Agliari, O. Bénichou, R. Voituriez

摘要:

我们提出了一般的方法来精确计算递归定义的自相似网络上的平均首次通过量。特别地,我们计算与源和一个或多个目标相关联的平均首次通过时间和分裂概率;给定源集合上的平均量(例如,相同连接性节点)也被导出。这些数量的准确估计突出了第一次通过过程相对于源-目标距离的依赖性,最近发现这是一个关键参数,以描述复杂介质中的传输。我们显式地执行计算任意大小的递归网络的不同类别(cirramified分形,无标度(反)分形,非分形,分形和非分形之间的混合物,不可抽取的层次图)。我们的方法统一并显著扩展了该领域的可用结果。

英文摘要:

We present general methods to exactly calculate mean-first passage quantities on self-similar networks defined recursively. In particular, we calculate the mean first-passage time and the splitting probabilities associated to a source and one or several targets; averaged quantities over a given set of sources (e.g., same-connectivity nodes) are also derived. The exact estimate of such quantities highlights the dependency of first-passage processes with respect to the source-target distance, which has recently revealed to be a key parameter to characterize transport in complex media. We explicitly perform calculations for different classes of recursive networks (finitely ramified fractals, scale-free (trans)fractals, non-fractals, mixtures between fractals and non-fractals, non-decimable hierarchical graphs) of arbitrary size. Our approach unifies and significantly extends the available results in the field.

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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