Unified model for network dynamics exhibiting nonextensive statistics

Abstract

We introduce a dynamical network model which unifies a number of network families which are individually known to exhibit $q$-exponential degree distributions. The present model dynamics incorporates static (non-growing) self-organizing networks, preferentially growing networks, and (preferentially) rewiring networks. Further, it exhibits a natural random graph limit. The proposed model generalizes network dynamics to rewiring and growth modes which depend on internal topology as well as on a metric imposed by the space they are embedded in. In all of the networks emerging from the presented model we find q-exponential degree distributions over a large parameter space. We comment on the parameter dependence of the corresponding entropic index q for the degree distributions, and on the behavior of the clustering coefficients and neighboring connectivity distributions.

11 pages 8 figs

References in corpus (3)

• Scale free networks from a Hamiltonian dynamics
• Self Organized Scale-Free Networks from Merging and Regeneration
• Nonextensive information entropy for stochastic networks

Cited by in corpus (1)

• Inherent correlations between thermodynamics and statistic physics in extensive and nonextensive systems