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一类分形网络中首次通过特性的精确结果。

Exact results for the first-passage properties in a class of fractal networks.

作者信息

Peng Junhao, Agliari Elena

机构信息

School of Math and Information Science, Guangzhou University, Guangzhou 510006, China.

Department of Mathematics, Sapienza Università di Roma, 00185 Rome, Italy.

出版信息

Chaos. 2019 Feb;29(2):023105. doi: 10.1063/1.5080481.

Abstract

In this work, we consider a class of recursively grown fractal networks G(t) whose topology is controlled by two integer parameters, t and n. We first analyse the structural properties of G(t) (including fractal dimension, modularity, and clustering coefficient), and then we move to its transport properties. The latter are studied in terms of first-passage quantities (including the mean trapping time, the global mean first-passage time, and Kemeny's constant), and we highlight that their asymptotic behavior is controlled by the network's size and diameter. Remarkably, if we tune n (or, analogously, t) while keeping the network size fixed, as n increases (t decreases) the network gets more and more clustered and modular while its diameter is reduced, implying, ultimately, a better transport performance. The connection between this class of networks and models for polymer architectures is also discussed.

摘要

在这项工作中,我们考虑一类通过递归生长的分形网络G(t),其拓扑结构由两个整数参数t和n控制。我们首先分析G(t)的结构特性(包括分形维数、模块性和聚类系数),然后转向其传输特性。后者是根据首次通过量(包括平均捕获时间、全局平均首次通过时间和凯梅尼常数)进行研究的,我们强调它们的渐近行为受网络大小和直径的控制。值得注意的是,如果在保持网络大小固定的同时调整n(或者类似地,调整t),随着n的增加(t的减小),网络变得越来越聚集和模块化,而其直径减小,最终意味着更好的传输性能。还讨论了这类网络与聚合物结构模型之间的联系。

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