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arXiv 0909.4832cond-mat.dis-nncond-mat.stat-mech
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复杂网络中的小世界-分形转换:重整化群方法

Small world-Fractal Transition in Complex Networks: Renormalization Group Approach

Hernán D. Rozenfeld, Chaoming Song, Hernán A. Makse

摘要:

我们表明,重整化群(RG)理论应用于复杂网络是有用的分类网络拓扑结构的配置空间中的普适类。RG流很容易识别一个小世界/分形过渡,通过找到(i)一个平凡的稳定不动点的完整图,(ii)一个非平凡点的纯分形拓扑是稳定的或不稳定的,根据网络中的长程链接的数量,和(iii)另一个稳定的点的分形与捷径,正好存在于小世界/分形过渡。作为抵押品,RG技术解释了看似矛盾的分形和小世界阶段的共存,并允许提取信息的分布在现实世界的网络中的捷径,一个重要的问题,在系统中的信息流。

英文摘要:

We show that renormalization group (RG) theory applied to complex networks are useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world/fractal transition by finding (i) a trivial stable fixed point of a complete graph, (ii) a non-trivial point of a pure fractal topology that is stable or unstable according to the amount of long-range links in the network, and (iii) another stable point of a fractal with short-cuts that exists exactly at the small-world/fractal transition. As a collateral, the RG technique explains the coexistence of the seemingly contradicting fractal and small-world phases and allows to extract information on the distribution of short-cuts in real-world networks, a problem of importance for information flow in the system.

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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