Literature DB >> 28085444

Percolation in real multiplex networks.

Ginestra Bianconi1, Filippo Radicchi2.   

Abstract

We present an exact mathematical framework able to describe site-percolation transitions in real multiplex networks. Specifically, we consider the average percolation diagram valid over an infinite number of random configurations where nodes are present in the system with given probability. The approach relies on the locally treelike ansatz, so that it is expected to accurately reproduce the true percolation diagram of sparse multiplex networks with negligible number of short loops. The performance of our theory is tested in social, biological, and transportation multiplex graphs. When compared against previously introduced methods, we observe improvements in the prediction of the percolation diagrams in all networks analyzed. Results from our method confirm previous claims about the robustness of real multiplex networks, in the sense that the average connectedness of the system does not exhibit any significant abrupt change as its individual components are randomly destroyed.

Entities:  

Year:  2016        PMID: 28085444     DOI: 10.1103/PhysRevE.94.060301

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


  4 in total

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Authors:  David F Klosik; Anne Grimbs; Stefan Bornholdt; Marc-Thorsten Hütt
Journal:  Nat Commun       Date:  2017-09-14       Impact factor: 14.919

2.  Optimal percolation on multiplex networks.

Authors:  Saeed Osat; Ali Faqeeh; Filippo Radicchi
Journal:  Nat Commun       Date:  2017-11-16       Impact factor: 14.919

3.  Identification of COVID-19 Spreaders Using Multiplex Networks Approach.

Authors:  Edwin Montes-Orozco; Roman-Anselmo Mora-Gutierrez; Sergio-Gerardo De-Los-Cobos-Silva; Eric-Alfredo Rincon-Garcia; Gilberto-Sinuhe Torres-Cockrell; Jorge Juarez-Gomez; Bibiana Obregon-Quintana; Pedro Lara-Velazquez; Miguel-Angel Gutierrez-Andrade
Journal:  IEEE Access       Date:  2020-07-07       Impact factor: 3.367

4.  Hidden transition in multiplex networks.

Authors:  R A da Costa; G J Baxter; S N Dorogovtsev; J F F Mendes
Journal:  Sci Rep       Date:  2022-03-10       Impact factor: 4.379

  4 in total

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