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Random subgraphs of finite graphs: I. The scaling window under the triangle condition

Abstract

We study random subgraphs of an arbitrary finite connected transitive graph G\mathbb G obtained by independently deleting edges with probability 1p1-p. Let VV be the number of vertices in G\mathbb G, and let Ω\Omega be their degree. We define the critical threshold pc=pc(G,λ)p_c=p_c(\mathbb G,\lambda) to be the value of pp for which the expected cluster size of a fixed vertex attains the value λV1/3\lambda V^{1/3}, where λ\lambda is fixed and positive. We show that for any such model, there is a phase transition at pcp_c analogous to the phase transition for the random graph, provided that a quantity called the triangle diagram is sufficiently small at the threshold pcp_c. In particular, we show that the largest cluster inside a scaling window of size |p-p_c|=\Theta(\cn^{-1}V^{-1/3}) is of size Θ(V2/3)\Theta(V^{2/3}), while below this scaling window, it is much smaller, of order O(ϵ2log(Vϵ3))O(\epsilon^{-2}\log(V\epsilon^3)), with \epsilon=\cn(p_c-p). We also obtain an upper bound O(\cn(p-p_c)V) for the expected size of the largest cluster above the window. In addition, we define and analyze the percolation probability above the window and show that it is of order \Theta(\cn(p-p_c)). Among the models for which the triangle diagram is small enough to allow us to draw these conclusions are the random graph, the nn-cube and certain Hamming cubes, as well as the spread-out nn-dimensional torus for n>6n>6

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