Maximizing Free Energy Gain.

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Entropy Pub Date : 2025-01-20 DOI:10.3390/e27010091
Artemy Kolchinsky, Iman Marvian, Can Gokler, Zi-Wen Liu, Peter Shor, Oles Shtanko, Kevin Thompson, David Wolpert, Seth Lloyd
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Abstract

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy-and by extension, the maximum extractable work-that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
期刊最新文献
A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition. Discontinuous Structural Transitions in Fluids with Competing Interactions. Maximizing Free Energy Gain. Nonadditive Entropies and Nonextensive Statistical Mechanics. Novel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction.
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