Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model

摘要

We show how appropriate rewiring with the aid of Metropolis Monte Carlocomputational experiments can be exploited to create network topologiespossessing prescribed values of the average path length (APL) while keeping thesame connectivity degree and clustering coefficient distributions. Using theproposed rewiring rules we illustrate how the emergent dynamics of thecelebrated majority-rule model are shaped by the distinct impact of the APLattesting the need for developing efficient algorithms for tuning such networkcharacteristics.