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arXiv 1201.0212cond-mat.stat-mechphysics.soc-ph
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具有多重陷阱的模块化无标度网络中的随机游动

Random walks in modular scale-free networks with multiple traps

Zhongzhi Zhang, Yihang Yang, Yuan Lin

摘要:

大量的实证研究表明,大量的真实网络同时具有无标度和模块化结构,揭示这两个显著性质对网络中各种动力学过程的影响具有重要意义。在本文中,我们研究了两种情况下的随机游动进行的一类模块化无标度网络的多个陷阱位于几个给定的节点。我们首先推导出一般网络的平均首次通过时间(MFPT)的公式,它是从特定节点开始的吸收的预期时间的平均值,在所有非陷阱起始节点上平均。虽然计算复杂,但公式的表达是精确的,而且计算方法和步骤与陷阱的数量和位置无关。然后,我们确定分析的MFPT被认为是两个随机游动。所得解析结果与数值结果完全一致。我们的研究结果表明,陷阱的数量和位置在MFPT的行为中起着重要的作用,因为对于这两种情况下的MFPT增长作为幂律函数的节点数,但它们的指数是完全不同的。我们证明了MFPT的行为差异的根源是由于网络的模块化和无标度拓扑结构。这一工作可以加深对模块化和无标度网络上扩散的理解,并促进对多陷阱复杂随机网络上随机游动的相关研究。

英文摘要:

Extensive empirical investigation has shown that a plethora of real networks synchronously exhibit scale-free and modular structure, and it is thus of great importance to uncover the effects of these two striking properties on various dynamical processes occurring on such networks. In this paper, we examine two cases of random walks performed on a class of modular scale-free networks with multiple traps located at several given nodes. We first derive a formula of the mean first-passage time (MFPT) for a general network, which is the mean of the expected time to absorption originating from a specific node, averaged over all non-trap starting nodes. Although the computation is complex, the expression of the formula is exact; moreover, the computational approach and procedure are independent of the number and position of the traps. We then determine analytically the MFPT for the two random walks being considered. The obtained analytical results are in complete agreement with the numerical ones. Our results show that the number and location of traps play an important role in the behavior of the MFPT, since for both cases the MFPT grows as a power-law function of the number of nodes, but their exponents are quite different. We demonstrate that the root of the difference in the behavior of MFPT is attributed to the modular and scale-free topologies of the networks. This work can deepen the understanding of diffusion on networks with modular and scale-free architecture and motivate relevant studies for random walks running on complex random networks with multiple traps.

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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