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GENERALIZED K-CORE PERCOLATION IN NETWORKS WITH COMMUNITY STRUCTURE

机译:社区结构网络中的广义k核渗透

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Community structure underpins many complex networked systems and plays a vital role when components in some modules of the network come under attack or failure. Here, we study the generalized k-core (Gk-core) percolation over a modular random network model. Unlike the archetypal giant component based quantities, Gk-core can be viewed as a resilience metric tailored to gauge the network robustness subject to spreading virus or epidemics paralyzing weak nodes, i.e., nodes of degree less than k, and their nearest neighbors. We develop two complementary frameworks, namely, the generating function formalism and the rate equation approach, to characterize the Gk-core of modular networks. Through extensive numerical calculations and simulations, it is found that G2-core percolation undergoes a continuous phase transition while Gk-core percolation for k >= 3 displays a first-order phase transition for any fraction of interconnecting nodes. The influence of interconnecting nodes tends to be more visible nearer the percolation threshold. We find by studying modular networks with two Erdos-Renyi modules that the interconnections between modules affect the G2-core percolation phase transition in a way similar to an external field in a spin system, where Widom's identity regulating the critical exponents of the system is fulfilled. However, this analogy does not seem to exist for Gk-core with k >= 3 in general.
机译:社区结构基于许多复杂的网络系统,并且当网络的某些模块中的组件受到攻击或失败时,扮演至关重要的作用。在这里,我们研究了模块化随机网络模型的广义k核(GK核心)渗滤。与基于原型巨型组件的数量不同,GK-核心可以被视为定制的弹性度量,以便衡量以扩散病毒或流行病毒瘫痪的弱节点,即程度小于K的节点,以及其最近邻居的网络鲁棒性。我们开发了两个互补框架,即发电功能形式主义和速率方程方法,以表征模块化网络的GK核心。通过广泛的数值计算和仿真,发现G2芯渗滤经历连续相变,而K> = 3的GK芯渗透显示用于互连节点的任何一部分的一阶相转变。互连节点的影响趋于更容易看到近渗透阈值。通过研究具有两个ERDOS-renyi模块的模块化网络,模块之间的互连以类似于自旋系统中的外部字段的方式影响G2核心的渗透相转变,其中氟多多多多多多斯规范系统的临界指数的身份。然而,这一类比似乎没有K> = 3的GK核。

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