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最大化自由能增益。

Maximizing Free Energy Gain.

作者信息

Kolchinsky Artemy, Marvian Iman, Gokler Can, Liu Zi-Wen, Shor Peter, Shtanko Oles, Thompson Kevin, Wolpert David, Lloyd Seth

机构信息

Department of Medicine and Life Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain.

Physics and Electrical Engineering, Duke University, Durham, NC 27708, USA.

出版信息

Entropy (Basel). 2025 Jan 20;27(1):91. doi: 10.3390/e27010091.

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.

摘要

对于从光合作用等能量收集过程到燃料和电池等能量存储系统的各种生物和技术过程而言,最大化从环境中收获的功的量至关重要。在此,我们考虑自由能的最大化——进而考虑可从受其环境驱动的经典或量子系统中获得的最大可提取功。我们研究自由能增益如何依赖于系统的初始状态,同时考虑制备系统的成本。我们给出了通过改变初始状态来增加自由能增益的简单充要条件。我们还推导了简单公式,这些公式将使用最优初始状态而非另一个次优初始状态所获得的自由能联系起来。最后,我们证明,根据用于制备和功提取的温度,寻找最优初始状态的问题可能有两种不同的情况,一种容易,一种困难。我们在一个信息引擎的简单模型上阐述我们的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13db/11765171/8fc1e0bb1c5c/entropy-27-00091-g001.jpg

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