Percolation transition and distribution of connected components in generalized random network ensembles

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dc.creatorBradde, Serena
dc.creatorBianconi, Ginestra
dc.date2009-01-21
dc.date2009-05-15
dc.date.accessioned2026-07-07T13:14:49Z
dc.date.available2026-07-07T13:14:49Z
dc.descriptionIn this work, we study the percolation transition and large deviation properties of generalized canonical network ensembles. This new type of random networks might have a very rich complex structure, including high heterogeneous degree sequences, non-trivial community structure or specific spatial dependence of the link probability for networks embedded in a metric space. We find the cluster distribution of the networks in these ensembles by mapping the problem to a fully connected Potts model with heterogeneous couplings. We show that the nature of the Potts model phase transition, linked to the birth of a giant component, has a crossover from second to first order when the number of critical colors $q_c = 2$ in all the networks under study. These results shed light on the properties of dynamical processes defined on these network ensembles.
dc.description27 pages, 15 figures
dc.identifierhttps://arxiv.org/abs/0901.3225
dc.identifierhttp://arxiv.org/abs/0901.3225
dc.identifierJ. Phys. A: Math. and Theor. 42, 2009, 195007
dc.identifierdoi:10.1088/1751-8113/42/19/195007
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/230298
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titlePercolation transition and distribution of connected components in generalized random network ensembles
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