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Dynamics on modular networks with heterogeneous correlations

Date
2014
Abstract
We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module, and the inter-module connections are defined by the joint degree-degree distribution of nodes for each pair of modules. We present an analytical approach that allows one to analyze several types of binary dynamics operating on such networks, and we illustrate our approach using bond percolation, site percolation, and the Watts threshold model. The new network ensemble generalizes existing models (e. g., the well-known configuration model and Lancichinetti-Fortunato-Radicchi networks) by allowing a heterogeneous distribution of degree-degree correlations across modules, which is important for the consideration of nonidentical interacting networks. (C) 2014 AIP Publishing LLC.
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Description
peer-reviewed
Publisher
American Institute of Physics
Citation
Chaos;24, 023106
Collections
Mathematics & Statistics
MACSI - Mathematics Application Consortium for Science & Industry
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Gleeson_2014_dynamics.pdf
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Keywords
complex networks, interdependent networks, cascade, model
ULRR Identifiers
https://researchrepository.ul.ie/handle/10344/4466
 https://doi.org/10.34961/4436
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Funding Information
Irish Research Council (IRC), Science Foundation Ireland (SFI), European Research Council (ERC)
Sustainable Development Goals
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Type
Article
Rights
https://creativecommons.org/licenses/by-nc-sa/1.0/
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