Bootstrap percolation and the geometry of complex networks
Bootstrap percolation and the geometry of complex networks
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DOI：
10.1016/j.spa.2015.08.005
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发表时间：
2016-01-01
影响因子：
1.4
通讯作者：
Fountoulakis, Nikolaos
中科院分区：
文献类型：
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作者：
Candellero, Elisabetta;Fountoulakis, Nikolaos
在复杂网络的几何模型（由 Krioukov 等人提出）上，我们研究了引导渗透过程。该模型由具有 N 个顶点的双曲平面上的随机几何图组成，是 Chung-Lu 模型的从属版本。该过程从感染率 p = p(N) 开始。至少有 r >= 1 个受感染邻居的每个未受感染的顶点都会被感染，并永远保持这种状态。我们确定一个函数 p(c)(N) = o(1) 使得 a.a.s.当 p >> p(c)(N) 时，感染传播到正分数的顶点，而当 p
On a geometric model for complex networks (introduced by Krioukov et al.) we investigate the bootstrap percolation process. This model consists of random geometric graphs on the hyperbolic plane having N vertices, a dependent version of the Chung-Lu model. The process starts with infection rate p = p(N). Each uninfected vertex with at least r >= 1 infected neighbors becomes infected, remaining so forever. We identify a function p(c)(N) = o(1) such that a.a.s. when p >> p(c)(N) the infection spreads to a positive fraction of vertices, whereas when p