Variational approximations for stochastic dynamics on graphs
Statistical Mechanics
2017-07-31 v2
Abstract
We investigate different mean-field-like approximations for stochastic dynamics on graphs, within the framework of a cluster-variational approach. In analogy with its equilibrium counterpart, this approach allows one to give a unified view of various (previously known) approximation schemes, and suggests quite a systematic way to improve the level of accuracy. We compare the different approximations with Monte Carlo simulations on a reversible (susceptible-infected-susceptible) discrete-time epidemic-spreading model on random graphs.
Cite
@article{arxiv.1702.06822,
title = {Variational approximations for stochastic dynamics on graphs},
author = {Alessandro Pelizzola and Marco Pretti},
journal= {arXiv preprint arXiv:1702.06822},
year = {2017}
}
Comments
29 pages, 5 figures. Minor revisions. IOP-styled