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arXiv 0705.1547cond-mat.dis-nncond-mat.stat-mech
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无标度网络中渗流上临界维数的数值计算

Numerical evaluation of the upper critical dimension of percolation in scale-free networks

Zhenhua Wu, Cecilia Lagorio, Lidia A. Braunstein, Reuven Cohen, Shlomo Havlin, H. Eugene Stanley

摘要:

提出了一种数值方法来计算Erdens-Rényi网络和度分布为${\cal P}(k) \sim k^{-λ}$的无标度网络中随机渗流团簇的上临界维数$d_c$,其中$k$是节点的度,$λ$是度分布的宽度.我们的结果报告的理论预测,$d_c = 2(λ- 1)/(λ- 3)$的无标度网络与$3 < λ< 4$和$d_c = 6$的Erdens-Rényi网络和无标度网络与$λ> 4$。当节点的移除不是随机的而是针对移除最高度节点时,我们获得所有$λ> 2$的$d_c = 6$。我们的方法也产生了一个更好的数值评估的临界渗流阈值,$p_c$,无标度网络。我们的研究结果表明,当$λ$从上面接近3时,有限尺寸效应增加。

英文摘要:

We propose a numerical method to evaluate the upper critical dimension $d_c$ of random percolation clusters in Erdős-Rényi networks and in scale-free networks with degree distribution ${\cal P}(k) \sim k^{-λ}$, where $k$ is the degree of a node and $λ$ is the broadness of the degree distribution. Our results report the theoretical prediction, $d_c = 2(λ- 1)/(λ- 3)$ for scale-free networks with $3 < λ< 4$ and $d_c = 6$ for Erdős-Rényi networks and scale-free networks with $λ> 4$. When the removal of nodes is not random but targeted on removing the highest degree nodes we obtain $d_c = 6$ for all $λ> 2$. Our method also yields a better numerical evaluation of the critical percolation threshold, $p_c$, for scale-free networks. Our results suggest that the finite size effects increases when $λ$ approaches 3 from above.

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