arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1109.0839cond-mat.stat-mechcs.SIphysics.soc-ph
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相关随机网络上的渗流

Percolation on correlated random networks

Elena Agliari, Claudia Cioli, Enore Guadagnini

摘要:

我们考虑一类随机的,加权网络,通过重新定义的模式在Hopfield模型,并通过执行渗流过程,我们得到的信息的拓扑结构和弹性网络本身的属性。考虑到图的加权性质,可以研究不同类型的键渗流:随机(随机删除链接)和确定性(基于秩权重删除链接),每种都模仿不同的物理过程。网络的演化相应地是不同的,如由最大组件大小和集群大小的分布的行为所证明的。特别是,我们可以推导出弱联系对于保持图的连通性至关重要,而且当它们最容易失败时,巨联系的组成部分通常会收缩而不会突然分裂;这些结果最近在几种社交网络中得到了证明。

英文摘要:

We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in order to maintain the graph connected and that, when they are the most prone to failure, the giant component typically shrinks without abruptly breaking apart; these results have been recently evidenced in several kinds of social networks.

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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