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High-accuracy approximation of binary-state dynamics on networks

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dc.contributor.author Gleeson, James P.
dc.date.accessioned 2015-05-12T14:06:18Z
dc.date.available 2015-05-12T14:06:18Z
dc.date.issued 2011
dc.identifier.uri http://hdl.handle.net/10344/4463
dc.description peer-reviewed en_US
dc.description.abstract Binary-state dynamics (such as the susceptible-infected-susceptible (SIS) model of disease spread, or Glauber spin dynamics) on random networks are accurately approximated using master equations. Standard mean-field and pairwise theories are shown to result from seeking approximate solutions of the master equations. Applications to the calculation of SIS epidemic thresholds and critical points of nonequilibrium spin models are also demonstrated. en_US
dc.language.iso eng en_US
dc.publisher American Physical Society en_US
dc.relation.uri http://dx.doi.org/10.1103/PhysRevLett.107.068701
dc.subject contact process en_US
dc.subject model en_US
dc.subject epidemics en_US
dc.subject lattice en_US
dc.subject spread en_US
dc.title High-accuracy approximation of binary-state dynamics on 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 2015-05-12T13:15:38Z
dc.description.version PUBLISHED
dc.identifier.doi 10.1103/PhysRevLett.107.068701
dc.contributor.sponsor SFI en_US
dc.relation.projectid 06/IN1/I366
dc.relation.projectid 06/MI/005
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 1147989
dc.internal.copyrightchecked Yes
dc.description.status peer-reviewed


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