Spreading on a complex network avoiding certain motifs
Disordered Systems and Neural Networks
2009-03-09 v1 Statistical Mechanics
Abstract
Spreading of either information or matter can often be treated as a network problem. It can be of great importance to be able to estimate the likelihood that spreading through a network reaches essentially the entire network while still not reaching certain sub-classes of the network. We show that excluding nodes and edges from the network has a subtle effect on the percolation. We study two specific examples of degree distributions (exponential and scale free) for which analytical solutions can be obtained. The two cases exhibit qualitatively different behavior.
Cite
@article{arxiv.0903.1199,
title = {Spreading on a complex network avoiding certain motifs},
author = {Tomas Alarcon and Henrik Jeldtoft Jensen},
journal= {arXiv preprint arXiv:0903.1199},
year = {2009}
}
Comments
4 pages, 3 figures