Maximum entropy approach to power-law distributions in coupled dynamic-stochastic systems
Statistical Mechanics
2009-11-11 v1 Disordered Systems and Neural Networks
Abstract
Statistical properties of coupled dynamic-stochastic systems are studied within a combination of the maximum information principle and the superstatistical approach. The conditions at which the Shannon entropy functional leads to a power-law statistics are investigated. It is demonstrated that, from a quite general point of view, the power-law dependencies may appear as a consequence of "global" constraints restricting both the dynamic phase space and the stochastic fluctuations. As a result, at sufficiently long observation times the dynamic counterpart is driven into a non-equilibrium steady state whose deviation from the usual exponential statistics is given by the distance from the conventional equilibrium.
Keywords
Cite
@article{arxiv.cond-mat/0604573,
title = {Maximum entropy approach to power-law distributions in coupled dynamic-stochastic systems},
author = {E. V. Vakarin and J. P. Badiali},
journal= {arXiv preprint arXiv:cond-mat/0604573},
year = {2009}
}