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How clustering affects the bond percolation threshold in complex networks

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dc.contributor.author Gleeson, James P.
dc.contributor.author Melnik, Sergey
dc.contributor.author Hackett, Adam W.
dc.date.accessioned 2015-05-13T11:21:21Z
dc.date.available 2015-05-13T11:21:21Z
dc.date.issued 2010
dc.identifier.uri http://hdl.handle.net/10344/4468
dc.description peer-reviewed en_US
dc.description.abstract The question of how clustering (nonzero density of triangles) in networks affects their bond percolation threshold has important applications in a variety of disciplines. Recent advances in modeling highly clustered networks are employed here to analytically study the bond percolation threshold. In comparison to the threshold in an unclustered network with the same degree distribution and correlation structure, the presence of triangles in these model networks is shown to lead to a larger bond percolation threshold (i.e. clustering increases the epidemic threshold or decreases resilience of the network to random edge deletion) en_US
dc.language.iso eng en_US
dc.publisher American Physical Society en_US
dc.relation.ispartofseries Physical Review E;81, 066114
dc.relation.uri http://dx.doi.org/10.1103/PhysRevE.81.066114
dc.subject random graphs en_US
dc.subject populations en_US
dc.subject epidemics en_US
dc.subject disease en_US
dc.subject spread en_US
dc.title How clustering affects the bond percolation threshold in complex networks 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 2015-05-13T11:10:16Z
dc.description.version PUBLISHED
dc.contributor.sponsor SFI en_US
dc.relation.projectid 06/IN.1/I366 en_US
dc.relation.projectid 06/MI/005 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 1132571
dc.internal.copyrightchecked Yes
dc.description.status peer-reviewed


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