arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0905.4455cond-mat.dis-nncond-mat.stat-mech
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关联超图中的渗流转移

Percolation transition in correlated hypergraphs

Serena Bradde, Ginestra Bianconi

摘要:

已知相关性在确定复杂网络的结构中起着至关重要的作用。在这里,我们研究它们的存在如何影响随机超图的渗流阈值的计算。为了模拟真实网络中的相关性,我们从广义隐变量系综构建超图,并通过将此问题映射到具有异质耦合的全连接Potts模型来研究渗流过渡。

英文摘要:

Correlations are known to play a crucial role in determining the structure of complex networks. Here we study how their presence affects the computation of the percolation threshold in random hypergraphs. In order to mimic the correlation in real network, we build hypergraphs from a generalized hidden variable ensembles and we study the percolation transition by mapping this problem to the fully connected Potts model with heterogeneous couplings.

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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