动态复杂网络中长距离行走的统计力学:多样化选择的统计论证

D. Volchenkov, C. Suh
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引用次数: 1

摘要

我们研究了在有限,连通,非随机图上的超长行走的热力学极限,该图受可能的随机修改和运输能力噪声的影响。由于行走可能代表了系统单元之间的相互作用链,所以很长行走的统计力学可以用来量化网络中定义的过程动力学的重要结构特性。在行走的大正则系综框架下,开放随机结构修改的网络具有节点逸度的费米-狄拉克分布特征。同样的分布表现为描述网络中随机过程概率分布的时间演化的离散Fokker-Planck方程的唯一平稳解。中心性较差的节点是未来网络结构变化的最有可能的候选者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Mechanics of Long Walks in Dynamic Complex Networks: Statistical Arguments for Diversifying Selection
We study the thermodynamic limit of very long walks on finite, connected, non-random graphs subject to possible random modifications and transportation capacity noise. As walks might represent the chains of interactions between system units, statistical mechanics of very long walks may be used to quantify the structural properties important for the dynamics of processes defined in networks. Networks open to random structural modifications are characterized by a Fermi–Dirac distribution of node’s fugacity in the framework of grand canonical ensemble of walks. The same distribution appears as the unique stationary solution of a discrete Fokker–Planck equation describing the time evolution of probability distribution of stochastic processes in networks. Nodes of inferior centrality are the most likely candidates for the future structural changes in the network.
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