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Dynamics on modular networks with heterogeneous correlations

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dc.contributor.author Melnik, Sergey
dc.contributor.author Porter, Mason A
dc.contributor.author Mucha, Peter J
dc.contributor.author Gleeson, James P.
dc.date.accessioned 2015-05-13T08:47:33Z
dc.date.available 2015-05-13T08:47:33Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/10344/4466
dc.description peer-reviewed en_US
dc.description.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. en_US
dc.language.iso eng en_US
dc.publisher American Institute of Physics en_US
dc.relation 317614
dc.relation.ispartofseries Chaos;24, 023106
dc.relation.uri http://dx.doi.org/10.1063/1.4869983
dc.subject complex networks en_US
dc.subject interdependent networks en_US
dc.subject cascade en_US
dc.subject model en_US
dc.title Dynamics on modular networks with heterogeneous correlations en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.date.updated 2015-05-13T08:37:09Z
dc.description.version PUBLISHED
dc.contributor.sponsor IRC en_US
dc.contributor.sponsor SFI en_US
dc.contributor.sponsor ERC
dc.relation.projectid 11/PI/1026 en_US
dc.relation.projectid 317614 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 1574017
dc.internal.copyrightchecked Yes
dc.description.status peer-reviewed


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