Bootstrap percolation on the random graph $G_{n,p}
Bootstrap percolation on the random graph G... is a process of spread of "activation" on a given realization of the graph with a given number of initially active nodes. At each step those vertices which have not been active but have at least r≥2 active neighbors become active as well. We s...
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Veröffentlicht in: | The Annals of applied probability 2012-10, Vol.22 (5), p.1989-2047 |
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container_end_page | 2047 |
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container_issue | 5 |
container_start_page | 1989 |
container_title | The Annals of applied probability |
container_volume | 22 |
creator | Janson, Svante Łuczak, Tomasz Turova, Tatyana Vallier, Thomas |
description | Bootstrap percolation on the random graph G... is a process of spread of "activation" on a given realization of the graph with a given number of initially active nodes. At each step those vertices which have not been active but have at least r≥2 active neighbors become active as well. We study the size A... of the final active set. The parameters of the model are, besides r (fixed) and n (tending to ...), the size a=a(n) of the initially active set and the probability p=p(n) of the edges in the graph. We show that the model exhibits a sharp phase transition: depending on the parameters of the model, the final size of activation with a high probability is either n-o(n) or it is o(n). We provide a complete description of the phase diagram on the space of the parameters of the model. In particular, we find the phase transition and compute the asymptotics (in probability) for A...; we also prove a central limit theorem for A... in some ranges. Furthermore, we provide the asymptotics for the number of steps until the process stops. (ProQuest: ... denotes formulae/symbols omitted.) |
doi_str_mv | 10.1214/11-AAP822 |
format | Article |
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At each step those vertices which have not been active but have at least r≥2 active neighbors become active as well. We study the size A... of the final active set. The parameters of the model are, besides r (fixed) and n (tending to ...), the size a=a(n) of the initially active set and the probability p=p(n) of the edges in the graph. We show that the model exhibits a sharp phase transition: depending on the parameters of the model, the final size of activation with a high probability is either n-o(n) or it is o(n). We provide a complete description of the phase diagram on the space of the parameters of the model. In particular, we find the phase transition and compute the asymptotics (in probability) for A...; we also prove a central limit theorem for A... in some ranges. Furthermore, we provide the asymptotics for the number of steps until the process stops. 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source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; Project Euclid Complete |
subjects | 05C80 60C05 60K35 Asymptotic methods Bootstrap method Bootstrap percolation Phase transitions Probability distribution random graph sharp threshold |
title | Bootstrap percolation on the random graph $G_{n,p} |
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