Carlos Perez-Espigares, Alejandro B. Kolton, Jorge Kurchan
The probability distribution function for an out of equilibrium system may
sometimes be approximated by a physically motivated `trial' distribution. A
particularly interesting case is when a driven system (e.g. active matter) is
approximated by a thermodynamic one. We show here that every set of trial
distributions yields an inequality playing the role of a generalization of the
Second Law. The better the approximation, the more constraining the inequality
becomes: this suggests a criterion for its accuracy, as well as an optimization
procedure that may be implemented numerically and even experimentally. The
fluctuation relation behind this inequality --a natural and practical extension
of the Hatano-Sasa theorem-- does not rely on the a priori knowledge of the
stationary probability distribution.
View original:
http://arxiv.org/abs/1110.0967
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