English

Transport and Percolation Theory in Weighted Networks

Statistical Mechanics 2007-05-23 v3

Abstract

We study the distribution P(σ)P(\sigma) of the equivalent conductance σ\sigma for Erd\H{o}s-R\'enyi (ER) and scale-free (SF) weighted resistor networks with NN nodes. Each link has conductance geaxg\equiv e^{-ax}, where xx is a random number taken from a uniform distribution between 0 and 1 and the parameter aa represents the strength of the disorder. We provide an iterative fast algorithm to obtain P(σ)P(\sigma) and compare it with the traditional algorithm of solving Kirchhoff equations. We find, both analytically and numerically, that P(σ)P(\sigma) for ER networks exhibits two regimes. (i) A low conductance regime for σ<eapc\sigma < e^{-ap_c} where pc=1/\avkp_c=1/\av{k} is the critical percolation threshold of the network and \avk\av{k} is average degree of the network. In this regime P(σ)P(\sigma) is independent of NN and follows the power law P(σ)σαP(\sigma) \sim \sigma^{-\alpha}, where α=1\avk/a\alpha=1-\av{k}/a. (ii) A high conductance regime for σ>eapc\sigma >e^{-ap_c} in which we find that P(σ)P(\sigma) has strong NN dependence and scales as P(σ)f(σ,apc/N1/3)P(\sigma) \sim f(\sigma,ap_c/N^{1/3}). For SF networks with degree distribution P(k)kλP(k)\sim k^{-\lambda}, kminkkmaxk_{min} \le k \le k_{max}, we find numerically also two regimes, similar to those found for ER networks.

Keywords

Cite

@article{arxiv.cond-mat/0701526,
  title  = {Transport and Percolation Theory in Weighted Networks},
  author = {Guanliang Li and Lidia A. Braunstein and Sergey V. Buldyrev and Shlomo Havlin and H. Eugene Stanley},
  journal= {arXiv preprint arXiv:cond-mat/0701526},
  year   = {2007}
}

Comments

4 pages, 8 figures