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经典信息传输的非平衡增强

Non-Equilibrium Enhancement of Classical Information Transmission.

作者信息

Zeng Qian, Wang Jin

机构信息

State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Changchun 130022, China.

Department of Chemistry and Physics, State University of New York, Stony Brook, NY 11794, USA.

出版信息

Entropy (Basel). 2024 Jul 8;26(7):581. doi: 10.3390/e26070581.

Abstract

Information transmission plays a crucial role across various fields, including physics, engineering, biology, and society. The efficiency of this transmission is quantified by mutual information and its associated information capacity. While studies in closed systems have yielded significant progress, understanding the impact of non-equilibrium effects on open systems remains a challenge. These effects, characterized by the exchange of energy, information, and materials with the external environment, can influence both mutual information and information capacity. Here, we delve into this challenge by exploring non-equilibrium effects using the memoryless channel model, a cornerstone of information channel coding theories and methodology development. Our findings reveal that mutual information exhibits a convex relationship with non-equilibriumness, quantified by the non-equilibrium strength in transmission probabilities. Notably, channel information capacity is enhanced by non-equilibrium effects. Furthermore, we demonstrate that non-equilibrium thermodynamic cost, characterized by the entropy production rate, can actually improve both mutual information and information channel capacity, leading to a boost in overall information transmission efficiency. Our numerical results support our conclusions.

摘要

信息传输在包括物理、工程、生物和社会等各个领域都起着至关重要的作用。这种传输的效率通过互信息及其相关的信息容量来量化。虽然在封闭系统中的研究已经取得了显著进展,但理解非平衡效应在开放系统中的影响仍然是一个挑战。这些效应的特征是与外部环境进行能量、信息和物质的交换,它们会影响互信息和信息容量。在这里,我们通过使用无记忆信道模型来探索非平衡效应,深入研究这一挑战,该模型是信息信道编码理论和方法发展的基石。我们的研究结果表明,互信息与非平衡性呈现出一种凸关系,通过传输概率中的非平衡强度来量化。值得注意的是,非平衡效应会增强信道信息容量。此外,我们证明了以熵产生率为特征的非平衡热力学成本实际上可以同时提高互信息和信息信道容量,从而提高整体信息传输效率。我们的数值结果支持我们的结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2f/11275859/d350ec674ad1/entropy-26-00581-g001.jpg

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