Statistics of cycles in large networks

Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Feb;73(2 Pt 2):025101. doi: 10.1103/PhysRevE.73.025101. Epub 2006 Feb 3.

Abstract

The occurrence of self-avoiding closed paths (cycles) in networks is studied under varying rules of wiring. As a main result, we find that the dependence between network size and typical cycle length is algebraic, (h) proportional to Nalpha, with distinct values of for different wiring rules. The Barabasi-Albert model has alpha=1. Different preferential and nonpreferential attachment rules and the growing Internet graph yield alpha<1. Computation of the statistics of cycles at arbitrary length is made possible by the introduction of an efficient sampling algorithm.