Energy dissipation and information flow in coupled Markovian systems
arXiv:1807.00116 · 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.
arXiv comment10 pages, 6 figures
References in corpus (6)
- High-precision test of Landauer's principle in a feedback trap
- The thermodynamics of prediction
- The Energetic Costs of Cellular Computation
- Efficiency of cellular information processing
- Sensory capacity: an information theoretical measure of the performance of a sensor
- What we learn from the learning rate