Path-integral approach to the dynamics in sparse random network
Disordered Systems and Neural Networks
2009-11-11 v1 Adaptation and Self-Organizing Systems
Abstract
We study the dynamics involved in a sparse random network model. We extend the standard mean-field approximation for the dynamics of a random network by employing the path-integral approach. The result indicates that the distribution of the variable is essentially identical to that obtained from globally coupled oscillators with random Gaussian interaction. We present the results of a numerical simulation of the Kuramoto transition in a random network, which is found to be consistent with this analysis.
Cite
@article{arxiv.cond-mat/0507285,
title = {Path-integral approach to the dynamics in sparse random network},
author = {Takashi Ichinomiya},
journal= {arXiv preprint arXiv:cond-mat/0507285},
year = {2009}
}