The critical point of k-clique percolation in the Erdos-Renyi graph

Abstract

Motivated by the success of a k-clique percolation method for the identification of overlapping communities in large real networks, here we study the k-clique percolation problem in the Erdos-Renyi graph. When the probability p of two nodes being connected is above a certain threshold p_c(k), the complete subgraphs of size k (the k-cliques) are organized into a giant cluster. By making some assumptions that are expected to be valid below the threshold, we determine the average size of the k-clique percolation clusters, using a generating function formalism. From the divergence of this average size we then derive an analytic expression for the critical linking probability p_c(k).

arXiv comment12 pages, 2 figures

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• Localization transition in non-Hermitian systems depending on reciprocity and hopping asymmetry
• Triangle percolation in mean field random graphs -- with PDE
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