Efficiency bounds for bipartite information-thermodynamic systems

In this paper, we introduce an approach to derive a lower bound for the entropy production rate of a subsystem by utilizing the Cauchy-Schwarz inequality. It extends to establishing comprehensive upper and lower bounds for the efficiency of two subsystems. These bounds are applicable to a wide range of Markovian stochastic processes, which enhances the accuracy in depicting the range of energy conversion efficiency between subsystems. Empirical validation is conducted using a two-quantum-dot system model, which serves to confirm the effectiveness of our inequality in refining the boundaries of efficiency.

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Publication Details

Journal
Physical review. E
Published
2024-09-03
DOI
https://doi.org/10.1103/physreve.110.034102
Citations
1
Primary Topic
Advanced Thermodynamics and Statistical Mechanics
Type
article
Field-Weighted Citation Impact
0.28

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article

Efficiency bounds for bipartite information-thermodynamic systems

Shanhe Su, Shihao Xia, Ousi Pan, Jincan Chen et al.
1 citations
Physical review. E
Advanced Thermodynamics and Statistical Mechanics
0.28
article

Efficiency bounds for bipartite information-thermodynamic systems

Shanhe Su, Shihao Xia, Ousi Pan, Jincan Chen, Yuzhuo Pan, Shuanglong Han
article en
1 citations

Abstract

In this paper, we introduce an approach to derive a lower bound for the entropy production rate of a subsystem by utilizing the Cauchy-Schwarz inequality. It extends to establishing comprehensive upper and lower bounds for the efficiency of two subsystems. These bounds are applicable to a wide range of Markovian stochastic processes, which enhances the accuracy in depicting the range of energy conversion efficiency between subsystems. Empirical validation is conducted using a two-quantum-dot system model, which serves to confirm the effectiveness of our inequality in refining the boundaries of efficiency.

Physical review. EVol. 110(3)
Quanzhou Normal University (CN), Xiamen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 46%
Advanced Thermodynamics and Statistical Mechanics
0.28
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