Percolation and epidemic thresholds in clustered networks

被引:150
作者
Serrano, M. Angeles
Boguna, Marian
机构
[1] Indiana Univ, Sch Informat, Bloomington, IN 47406 USA
[2] Univ Barcelona, Dept Fis Fonamental, E-08028 Barcelona, Spain
关键词
D O I
10.1103/PhysRevLett.97.088701
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks, thus extending this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.
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页数:4
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