Systematic Series Expansions for Processes on Networks

TL;DR

This paper introduces a series expansion method to analyze the dynamics of processes on networks, accurately capturing effects of network structure and improving upon existing analytical results, including real-world applications.

Contribution

The paper develops a systematic series expansion approach that incorporates detailed network effects and improves the accuracy of critical point predictions on complex networks.

Findings

Series expansions match numerical simulations accurately.

Disassortativity affects critical point estimates, requiring modifications.

Method successfully applied to real-world network data.

Abstract

We use series expansions to study dynamics of equilibrium and non-equilibrium systems on networks. This analytical method enables us to include detailed non-universal effects of the network structure. We show that even low order calculations produce results which compare accurately to numerical simulation, while the results can be systematically improved. We show that certain commonly accepted analytical results for the critical point on networks with a broad degree distribution need to be modified in certain cases due to disassortativity; the present method is able to take into account the assortativity at sufficiently high order, while previous results correspond to leading and second order approximations in this method. Finally, we apply this method to real-world data.