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Scaling behavior of information entropy in explosive percolation transitions
Physical Review E ( IF 2.2 ) Pub Date : 2021-07-22 , DOI: 10.1103/physreve.104.014310
Yejun Kang 1 , Young Sul Cho 1, 2
Affiliation  

An explosive percolation transition is the abrupt emergence of a giant cluster at a threshold caused by a suppression of the growth of large clusters. In this paper, we consider the information entropy of the cluster-size distribution, which is the probability distribution for the size of a randomly chosen cluster. It has been reported that information entropy does not reach its maximum at the threshold in explosive percolation models, a result seemingly contrary to other previous results that the cluster-size distribution shows power-law behavior and the cluster-size diversity (number of distinct cluster sizes) is maximum at the threshold. Here, we show that this phenomenon is due to the fact that the scaling form of the cluster-size distribution is given differently below and above the threshold. We also establish the scaling behaviors of the first and second derivatives of the information entropy near the threshold to explain why the first derivative has a negative minimum at the threshold and the second derivative diverges negatively (positively) at the left (right) limit of the threshold, as predicted through previous simulation.

中文翻译:

爆炸性渗透转变中信息熵的标度行为

爆炸性的渗流转变是由于大型星团的生长受到抑制而在阈值处突然出现的巨型星团。在本文中,我们考虑簇大小分布的信息熵,它是随机选择的簇大小的概率分布。据报道,在爆炸性渗透模型中,信息熵在阈值处未达到最大值,这一结果似乎与其他先前的结果相反,即集群大小分布显示幂律行为和集群大小多样性(不同集群的数量)尺寸)在阈值处最大。在这里,我们表明这种现象是由于集群大小分布的缩放形式在阈值之下和之上给出的不同。
更新日期:2021-07-22
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