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Bond percolation on multiplex networks

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posted on 2023-03-03, 11:57 authored by Adam W. Hackett, Davide Cellai, S. Gomez, Alex Arenas, James GleesonJames Gleeson
We present an analytical approach for bond percolation on multiplex networks and use it to determine the expected size of the giant connected component and the value of the critical bond occupation probability in these networks. We advocate the relevance of these tools to the modeling of multilayer robustness and contribute to the debate on whether any benefit is to be yielded from studying a full multiplex structure as opposed to its monoplex projection, especially in the seemingly irrelevant case of a bond occupation probability that does not depend on the layer. Although we find that in many cases the predictions of our theory for multiplex networks coincide with previously derived results for monoplex networks, we also uncover the remarkable result that for a certain class of multiplex networks, well described by our theory, new critical phenomena occur as multiple percolation phase transitions are present. We provide an instance of this phenomenon in a multiplex network constructed from London rail and European air transportation data sets.

Funding

PI: MARK LEISING/CLEMSON UNIVERSITY U.S. INTEGRAL USERS GROUP CHAIR SUMMARY: TO SUPPORT MY WORK AND TRAVEL AS CHAIR OF THE U.S. INTEGRAL USERS GROUP (US-IUG). ORGANIZE AND ATTEND 2 US-LUG MEETINGS AT GODDARD SPACE FLIGHT CENTER WORK WITH THE PROJECT TO EN

National Aeronautics and Space Administration

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History

Publication

Physical Review X;6, 021002

Publisher

American Physical Society

Note

peer-reviewed

Other Funding information

ERC, ICREA Academia, Generalitat de Catalunya, James S. McDonnell Foundation, SFI

Rights

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the publised article’s title, journal citation, and DOI

Language

English

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  • MACSI - Mathematics Application Consortium for Science & Industry

Department or School

  • Mathematics & Statistics

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