Bootstrap percolation and the geometry of complex networks

preprint2015arXivOpen access

Abstract

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 NN vertices, a dependent version of the Chung-Lu model. The process starts with infection rate p=p(N)p=p(N). Each uninfected vertex with at least r≥1\mathbf{r}\geq 1 infected neighbors becomes infected, remaining so forever. We identify a function pc(N)=o(1)p_c(N)=o(1) such that a.a.s.\ when p≫pc(N)p\gg p_c(N) the infection spreads to a positive fraction of vertices, whereas when p≪pc(N)p\ll p_c(N) the process cannot evolve. Moreover, this behavior is "robust" under random deletions of edges.

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