title: Universality in complex networks: random matrix analysis.
abstract: We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory. Second, we show an analogy between the onset of small-world behavior, quantified by the structural properties of networks, and the transition from Poisson to Gaussian orthogonal ensemble statistics, quantified by Brody parameter characterizing a spectral property. We also present our analysis for a protein-protein interaction network in budding yeast.
authors.affiliation: Max-Planck Institute for the Physics of Complex Systems, Nöthnitzerstrasse 38, D-01187 Dresden, Germany.
authors.forename: Jayendra N
authors.initials: JN
authors.lastname: Bandyopadhyay
authors.forename: Sarika
authors.initials: S
authors.lastname: Jalan