English

Generalization of core percolation on complex networks

Disordered Systems and Neural Networks 2019-02-26 v2 Physics and Society

Abstract

We introduce a kk-leaf removal algorithm as a generalization of the so-called leaf removal algorithm. In this pruning algorithm, vertices of degree smaller than kk, 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 kk-core (GkGk-core). Performing this pruning for the sequence of natural numbers kk, we decompose the network into a hierarchy of progressively nested GkGk-cores. We present an analytical framework for description of GkGk-core percolation for undirected uncorrelated networks with arbitrary degree distributions (configuration model). To confirm our results, we also derive rate equations for the kk-leaf removal algorithm which enable us to obtain the structural characteristics of the GkGk-cores in another way. Also we apply our algorithm to a number of real-world networks and perform the GkGk-core decomposition for them.

Keywords

Cite

@article{arxiv.1807.11695,
  title  = {Generalization of core percolation on complex networks},
  author = {N. Azimi-Tafreshi and S. Osat and S. N. Dorogovtsev},
  journal= {arXiv preprint arXiv:1807.11695},
  year   = {2019}
}

Comments

9 pages, 9 figures

R2 v1 2026-06-23T03:20:02.460Z