Energy Dissipation and Information Flow in Coupled Markovian Systems

Entropy (Basel). 2018 Sep 14;20(9):707. doi: 10.3390/e20090707.

Abstract

A stochastic system under the influence of a stochastic environment is correlated with both present and future states of the environment. Such a system can be seen as implicitly implementing a predictive model of future environmental states. The non-predictive model complexity has been shown to lower-bound the thermodynamic dissipation. Here we explore these statistical and physical quantities at steady state in simple models. We show that under quasi-static driving this model complexity saturates the dissipation. Beyond the quasi-static limit, we demonstrate a lower bound on the ratio of this model complexity to total dissipation, that is realized in the limit of weak driving.

Keywords: dissipation; information; learning; nostalgia; prediction; quasi-static; work.