Optimized finite-time information machine
arXiv:1406.1030 · doi:10.1088/1742-5468/2014/09/P09010
Abstract
We analyze a periodic optimal finite-time two-state information-driven machine that extracts work from a single heat bath exploring imperfect measurements. Two models are considered, a memory-less one that ignores past measurements and an optimized model for which the feedback scheme consists of a protocol depending on the whole history of measurements. Depending on the precision of the measurement and on the period length the optimized model displays a phase transition to a phase where measurements are judged as non-reliable. We obtain the critical line exactly and show that the optimized model leads to more work extraction in comparison to the memory-less model, with the gain parameter being larger in the region where the frequency of non-reliable measurements is higher. We also demonstrate that the model has two second law inequalities, with the extracted work being bounded by the change of the entropy of the system and by the mutual information.
16 pages, 5 figures
References in corpus (12)
- Efficiency at maximum power: An analytically solvable model for stochastic heat engines
- Optimal finite-time processes in stochastic thermodynamics
- Work and information processing in a solvable model of Maxwell's demon
- Thermodynamics of a physical model implementing a Maxwell demon
- Nonequilibrium Detailed Fluctuation Theorem for Repeated Discrete Feedback
- Extracting work from a single heat bath through feedback
- Thermodynamics of feedback controlled systems
- Optimal protocols for minimal work processes in underdamped stochastic thermodynamics
- Feedback control in a collective flashing ratchet
- Stochastic thermodynamics for "Maxwell demon" feedbacks
- Finite-time erasing of information stored in fermionic bits
- Computing the optimal protocol for finite-time processes in stochastic thermodynamics