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 -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.
Cite
@article{arxiv.cond-mat/0701037,
title = {Unified model for network dynamics exhibiting nonextensive statistics},
author = {Stefan Thurner and Fragiskos Kyriakopoulos and Constantino Tsallis},
journal= {arXiv preprint arXiv:cond-mat/0701037},
year = {2009}
}
Comments
11 pages 8 figs