Generation of arbitrarily two-point correlated random networks

dc.creatorWeber, Sebastian
dc.creatorPorto, Markus
dc.date2007-08-30
dc.date.accessioned2026-07-07T08:37:14Z
dc.date.available2026-07-07T08:37:14Z
dc.descriptionRandom networks are intensively used as null models to investigate properties of complex networks. We describe an efficient and accurate algorithm to generate arbitrarily two-point correlated undirected random networks without self- or multiple-edges among vertices. With the goal to systematically investigate the influence of two-point correlations, we furthermore develop a formalism to construct a joint degree distribution $P(j,k)$ which allows to fix an arbitrary degree distribution $P(k)$ and an arbitrary average nearest neighbor function $\knn(k)$ simultaneously. Using the presented algorithm, this formalism is demonstrated with scale-free networks ($P(k) \propto k^{-γ}$) and empirical complex networks ($P(k)$ taken from network) as examples. Finally, we generalize our algorithm to annealed networks which allows networks to be represented in a mean-field like manner.
dc.description10 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/0708.4161
dc.identifierhttp://arxiv.org/abs/0708.4161
dc.identifierPhys. Rev. E 76, 046111 (2007)
dc.identifierdoi:10.1103/PhysRevE.76.046111
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/140332
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titleGeneration of arbitrarily two-point correlated random networks
dc.typetext

Files

Collections