Thermodynamics of information

物理 麦克斯韦的恶魔 概率逻辑 统计物理学 非平衡态热力学 热力学第二定律 热力学定律 理论物理学 热力学 计算机科学 人工智能
作者
Juan M. R. Parrondo,Jordan M. Horowitz,Takahiro Sagawa
出处
期刊:Nature Physics [Nature Portfolio]
卷期号:11 (2): 131-139 被引量:1272
标识
DOI:10.1038/nphys3230
摘要

By its very nature, the second law of thermodynamics is probabilistic, in that its formulation requires a probabilistic description of the state of a system. This raises questions about the objectivity of the second law: does it depend, for example, on what we know about the system? For over a century, much effort has been devoted to incorporating information into thermodynamics and assessing the entropic and energetic costs of manipulating information. More recently, this historically theoretical pursuit has become relevant in practical situations where information is manipulated at small scales, such as in molecular and cell biology, artificial nano-devices or quantum computation. Here we give an introduction to a novel theoretical framework for the thermodynamics of information based on stochastic thermodynamics and fluctuation theorems, review some recent experimental results, and present an overview of the state of the art in the field. The task of integrating information into the framework of thermodynamics dates back to Maxwell and his infamous demon. Recent advances have made these ideas rigorous—and brought them into the laboratory.
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