title: Maximum entropy approach to power-law distributions in coupled dynamic-stochastic systems.
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 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 nonequilibrium steady state whose deviation from the usual exponential statistics is given by the distance from the conventional equilibrium.
authors.affiliation: UMR 7575 LECA ENSCP-UPMC-CNRS, 11 rue P. et M. Curie, 75231 Cedex 05, Paris, France.
authors.forename: E V
authors.initials: EV
authors.lastname: Vakarin
authors.forename: J P
authors.initials: JP
authors.lastname: Badiali