Literature DB >> 24483524

Percolation on random networks with arbitrary k-core structure.

Laurent Hébert-Dufresne1, Antoine Allard1, Jean-Gabriel Young1, Louis J Dubé1.   

Abstract

The k-core decomposition of a network has thus far mainly served as a powerful tool for the empirical study of complex networks. We now propose its explicit integration in a theoretical model. We introduce a hard-core random network (HRN) model that generates maximally random networks with arbitrary degree distribution and arbitrary k-core structure. We then solve exactly the bond percolation problem on the HRN model and produce fast and precise analytical estimates for the corresponding real networks. Extensive comparison with real databases reveals that our approach performs better than existing models, while requiring less input information.

Year:  2013        PMID: 24483524     DOI: 10.1103/PhysRevE.88.062820

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  Improving the accuracy of the k-shell method by removing redundant links: From a perspective of spreading dynamics.

Authors:  Ying Liu; Ming Tang; Tao Zhou; Younghae Do
Journal:  Sci Rep       Date:  2015-08-17       Impact factor: 4.379

2.  Predicting the evolution of spreading on complex networks.

Authors:  Duan-Bing Chen; Rui Xiao; An Zeng
Journal:  Sci Rep       Date:  2014-08-18       Impact factor: 4.379

3.  Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition.

Authors:  Laurent Hébert-Dufresne; Joshua A Grochow; Antoine Allard
Journal:  Sci Rep       Date:  2016-08-18       Impact factor: 4.379

4.  Core-like groups result in invalidation of identifying super-spreader by k-shell decomposition.

Authors:  Ying Liu; Ming Tang; Tao Zhou
Journal:  Sci Rep       Date:  2015-05-06       Impact factor: 4.379

  4 in total

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