Literature DB >> 30934300

Generalization of core percolation on complex networks.

N Azimi-Tafreshi1, S Osat2, S N Dorogovtsev3.   

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.

Year:  2019        PMID: 30934300     DOI: 10.1103/PhysRevE.99.022312

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  1 in total

1.  Digital contact tracing and network theory to stop the spread of COVID-19 using big-data on human mobility geolocalization.

Authors:  Matteo Serafino; Higor S Monteiro; Shaojun Luo; Saulo D S Reis; Carles Igual; Antonio S Lima Neto; Matías Travizano; José S Andrade; Hernán A Makse
Journal:  PLoS Comput Biol       Date:  2022-04-11       Impact factor: 4.779

  1 in total

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