English

Self-avoiding walks and connective constants in small-world networks

Disordered Systems and Neural Networks 2009-11-10 v1

Abstract

Long-distance characteristics of small-world networks have been studied by means of self-avoiding walks (SAW's). We consider networks generated by rewiring links in one- and two-dimensional regular lattices. The number of SAW's unu_n was obtained from numerical simulations as a function of the number of steps nn on the considered networks. The so-called connective constant, μ=limnun/un1\mu = \lim_{n \to \infty} u_n/u_{n-1}, which characterizes the long-distance behavior of the walks, increases continuously with disorder strength (or rewiring probability, pp). For small pp, one has a linear relation μ=μ0+ap\mu = \mu_0 + a p, μ0\mu_0 and aa being constants dependent on the underlying lattice. Close to p=1p = 1 one finds the behavior expected for random graphs. An analytical approach is given to account for the results derived from numerical simulations. Both methods yield results agreeing with each other for small pp, and differ for pp close to 1, because of the different connectivity distributions resulting in both cases.

Keywords

Cite

@article{arxiv.cond-mat/0303415,
  title  = {Self-avoiding walks and connective constants in small-world networks},
  author = {Carlos P. Herrero and Martha Saboya},
  journal= {arXiv preprint arXiv:cond-mat/0303415},
  year   = {2009}
}

Comments

7 pages, 5 figures

R2 v1 2026-07-22T10:47:56.372Z