Percolation transition in networks with degree-degree correlation

dc.creatorNoh, Jae Dong
dc.date2007-05-01
dc.date.accessioned2026-07-07T08:26:16Z
dc.date.available2026-07-07T08:26:16Z
dc.descriptionWe introduce an exponential random graph model for networks with a fixed degree distribution and with a tunable degree-degree correlation. We then investigate the nature of a percolation transition in the correlated network with the Poisson degree distribution. It is found that negative correlation is irrelevant in that the percolation transition in the disassortative network belongs to the same universality class of the uncorrelated network. Positive correlation turns out to be relevant. The percolation transition in the assortative network is characterized by the non-diverging mean size of finite clusters and power-law scalings of the density of the largest cluster and the cluster size distribution in the non-percolating phase as well as at the critical point. Our results suggest that the unusual type percolation transition in the growing network models reported recently may be inherited from the assortative degree-degree correlation.
dc.description7 pages, 11 figure
dc.identifierhttps://arxiv.org/abs/0705.0087
dc.identifierhttp://arxiv.org/abs/0705.0087
dc.identifierPhys. Rev. E 76, 026116 (2007).
dc.identifierdoi:10.1103/PhysRevE.76.026116
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/136881
dc.subjectStatistical Mechanics
dc.titlePercolation transition in networks with degree-degree correlation
dc.typetext

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