493 research outputs found

    Finite-size effects for anisotropic bootstrap percolation: logarithmic corrections

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    In this note we analyze an anisotropic, two-dimensional bootstrap percolation model introduced by Gravner and Griffeath. We present upper and lower bounds on the finite-size effects. We discuss the similarities with the semi-oriented model introduced by Duarte.Comment: Key words: Bootstrap percolation, anisotropy, finite-size effect

    The time of graph bootstrap percolation

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    Graph bootstrap percolation, introduced by Bollob\'as in 1968, is a cellular automaton defined as follows. Given a "small" graph HH and a "large" graph G=G0KnG = G_0 \subseteq K_n, in consecutive steps we obtain Gt+1G_{t+1} from GtG_t by adding to it all new edges ee such that GteG_t \cup e contains a new copy of HH. We say that GG percolates if for some t0t \geq 0, we have Gt=KnG_t = K_n. For H=KrH = K_r, the question about the size of the smallest percolating graphs was independently answered by Alon, Frankl and Kalai in the 1980's. Recently, Balogh, Bollob\'as and Morris considered graph bootstrap percolation for G=G(n,p)G = G(n,p) and studied the critical probability pc(n,Kr)p_c(n,K_r), for the event that the graph percolates with high probability. In this paper, using the same setup, we determine, up to a logarithmic factor, the critical probability for percolation by time tt for all 1tCloglogn1 \leq t \leq C \log\log n.Comment: 18 pages, 3 figure

    Strong-majority bootstrap percolation on regular graphs with low dissemination threshold

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    International audienceConsider the following model of strong-majority bootstrap percolation on a graph. Let r ≥ 1 be some integer, and p ∈ [0, 1]. Initially, every vertex is active with probability p, independently from all other vertices. Then, at every step of the process, each vertex v of degree deg(v) becomes active if at least (deg(v) + r)/2 of its neighbours are active. Given any arbitrarily small p > 0 and any integer r, we construct a family of d = d(p, r)-regular graphs such that with high probability all vertices become active in the end. In particular, the case r = 1 answers a question and disproves a conjecture of Rapaport, Suchan, Todinca and Verstraëte [38]
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