TY - JOUR
T1 - Random subgraphs of finite graphs
T2 - I. The scaling window under the triangle condition
AU - Borgs, Christian
AU - Chayes, Jennifer T.
AU - Van Der Hofstad, Remco
AU - Slade, Gordon
AU - Spencer, Joel
PY - 2005/9
Y1 - 2005/9
N2 - We study random subgraphs of an arbitrary finite connected transitive graph G obtained by independently deleting edges with probability 1 - p. Let V be the number of vertices in G, and let Ω be their degree. We define the critical threshold p c = p c(G, λ) to be the value of p for which the expected cluster size of a fixed vertex attains the value λV 1/3, where λ is fixed and positive. We show that, for any such model, there is a phase transition at p c analogous to the phase transition for the random graph, provided that a quantity called the triangle diagram is sufficiently small at the threshold p c. In particular, we show that the largest cluster inside a scaling window of size |p-p c| = Θ(Ω -1 V -1/3) is of size Θ(V 2/3), while, below this scaling window, it is much smaller, of order O(ε 2 log(Vε -3)), with ε = Ω(p c - p). We also obtain an upper bound O(Ω(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 Θ(Ω(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 n-cube and certain Hamming cubes, as well as the spread-out n-dimensional torus for n > 6.
AB - We study random subgraphs of an arbitrary finite connected transitive graph G obtained by independently deleting edges with probability 1 - p. Let V be the number of vertices in G, and let Ω be their degree. We define the critical threshold p c = p c(G, λ) to be the value of p for which the expected cluster size of a fixed vertex attains the value λV 1/3, where λ is fixed and positive. We show that, for any such model, there is a phase transition at p c analogous to the phase transition for the random graph, provided that a quantity called the triangle diagram is sufficiently small at the threshold p c. In particular, we show that the largest cluster inside a scaling window of size |p-p c| = Θ(Ω -1 V -1/3) is of size Θ(V 2/3), while, below this scaling window, it is much smaller, of order O(ε 2 log(Vε -3)), with ε = Ω(p c - p). We also obtain an upper bound O(Ω(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 Θ(Ω(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 n-cube and certain Hamming cubes, as well as the spread-out n-dimensional torus for n > 6.
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U2 - 10.1002/rsa.20051
DO - 10.1002/rsa.20051
M3 - Article
AN - SCOPUS:26944446964
SN - 1042-9832
VL - 27
SP - 137
EP - 184
JO - Random Structures and Algorithms
JF - Random Structures and Algorithms
IS - 2
ER -