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首页> 外文期刊>Physical review, E >Disassortativity of percolating clusters in random networks
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Disassortativity of percolating clusters in random networks

机译:随机网络中渗透簇的抵消

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摘要

We provide arguments for the property of the degree-degree correlations of giant components formed by the percolation process on uncorrelated random networks. Using the generating functions, we derive a general expression for the assortativity of a giant component, r, which is defined as Pearson's correlation coefficient for degrees of directly connected nodes. For uncorrelated random networks in which the third moment for the degree distribution is finite, we prove the following two points: (1) Assortativity r satisfies the relation r≤0 for p≥p_c. (2) The average degree of nodes adjacent to degree k nodes at the percolation threshold is proportional to k~(-1) independently of the degree distribution function. These results claim that disassortativity emerges in giant components near the percolation threshold. The accuracy of the analytical treatment is confirmed by extensive Monte Carlo simulations.
机译:我们为在不相关的随机网络上的渗滤过程中形成的巨型组件的程度相关性提供论据。 使用生成函数,我们导出了巨大分量r的assortativity的一般表达式,该r,它被定义为Pearson的直接连接节点的相关系数。 对于所属的随机网络,其中第三时刻为程度分布是有限的,我们证明了以下两点:(1)assortativity r满足p≥p_c的关系r≤0。 (2)在渗透阈值下与程度k节点相邻的节点的平均度数与程度分布函数的k〜(-1)成比例。 这些结果声明了在渗透阈值附近的巨型组件中出现的抗衡性。 通过广泛的蒙特卡罗模拟证实了分析治疗的准确性。

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