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Generalization of core percolation on complex networks

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arxiv 1807.11695 v2 pith:GL5OC37F submitted 2018-07-31 cond-mat.dis-nn physics.soc-ph

classification cond-mat.dis-nnphysics.soc-ph
keywords algorithmcoreleafnetworknetworkspruningremovalcores
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abstract

We introduce a $k$-leaf removal algorithm as a generalization of the so-called leaf removal algorithm. In this pruning algorithm, vertices of degree smaller than $k$, together with their first nearest neighbors and all incident edges are progressively removed from a random network. As the result of this pruning the network is reduced to a subgraph which we call the Generalized $k$-core ($Gk$-core). Performing this pruning for the sequence of natural numbers $k$, we decompose the network into a hierarchy of progressively nested $Gk$-cores. We present an analytical framework for description of $Gk$-core percolation for undirected uncorrelated networks with arbitrary degree distributions (configuration model). To confirm our results, we also derive rate equations for the $k$-leaf removal algorithm which enable us to obtain the structural characteristics of the $Gk$-cores in another way. Also we apply our algorithm to a number of real-world networks and perform the $Gk$-core decomposition for them.

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  1. Statistical mechanics of the minimum vertex cover problem in stochastic block models

    cond-mat.stat-mech 2019-08 conditional novelty 7.0 of 10

    For two-community stochastic block models, the minimum vertex cover problem becomes hard when in-degree plus out-degree exceeds e, but becomes easy again when cross-community degree is large enough.

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