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We propose a two-stage cycle for an optimized linear-irreversible heat engine that operates, in a finite time, between a hot (cold) reservoir and a finite auxiliary system acting as a sink (source) in the first (second) stage. Under the…

Statistical Mechanics · Physics 2019-08-02 I. Iyyappan , Ramandeep S. Johal

In the recent progress in nonequilibrium thermodynamics, information has been recognized as a kind of thermodynamic resource that can drive thermodynamic current without any direct energy injection. In this paper, we establish the framework…

Statistical Mechanics · Physics 2016-11-22 Shumpei Yamamoto , Sosuke Ito , Naoto Shiraishi , Takahiro Sagawa

We present a new outlook on the climate system thermodynamics, studying some of its macroscopic properties in terms of the 1st and 2nd laws of thermodynamics. We review and clarify the notion of efficiency of the climate system by…

Atmospheric and Oceanic Physics · Physics 2011-10-11 Valerio Lucarini

We analytically derive maximum efficiency at given cooling power for Carnot-type low-dissipation refrigerators. The corresponding optimal cycle duration depends on a single parameter, which is a specific combination of irreversibility…

Statistical Mechanics · Physics 2020-05-27 Viktor Holubec , Zhuolin Ye

It is known that an engine with ideal efficiency ($\eta =1$ for a chemical engine and $e = e_{\rm Carnot}$ for a thermal one) has zero power because a reversible cycle takes an infinite time. However, at least from a theoretical point of…

Chemical Physics · Physics 2016-11-22 Jesper Koning , Joseph O. Indekeu

The Carnot engine sets an upper limit to the efficiency of a practical heat engine. An arbitrary irreversible engine is sometimes believed to behave closely as the Curzon-Ahlborn engine. Efficiency of the latter is obtained commonly by…

Chemical Physics · Physics 2016-06-17 Kamal Bhattacharyya

We construct a generic model for a heat engine using information theory concepts, attributing irreversible energy dissipation to the information transmission channels. Using several forms for the channel capacity, classical and quantum, we…

Statistical Mechanics · Physics 2015-05-18 Yun Zhou , Dvira Segal

Thermodynamic length is a metric distance between equilibrium thermodynamic states that asymptotically bounds the dissipation induced by a finite time transformation of a thermodynamic system. By means of thermodynamic length, we first…

Statistical Mechanics · Physics 2022-01-27 Carlo Cafaro , Orlando Luongo , Stefano Mancini , Hernando Quevedo

The study of stochastic thermodynamic machines is one of the main topics in nonequilibrium thermodynamics. In this study, within the framework of Fokker-Planck equation, and using the method of characteristics of partial differential…

Statistical Mechanics · Physics 2020-04-03 Yunxin Zhang

The thermodynamic uncertainty relation expresses a universal trade-off between precision and entropy production, which applies in its original formulation to current observables in steady-state systems. We generalize this relation to…

Statistical Mechanics · Physics 2018-12-06 Timur Koyuk , Udo Seifert , Patrick Pietzonka

We establish a general lower bound for the entropy production rate (EPR) based on the Kullback-Leibler divergence and the Logarithmic-Sobolev constant that characterizes the time-scale of relaxation. This bound can be considered as an…

Statistical Mechanics · Physics 2025-10-31 Ruicheng Bao , Chaoqun Du , Zhiyu Cao , Zhonghuai Hou

We apply advanced methods of control theory to open quantum systems and we determine finite-time processes which are optimal with respect to thermodynamic performances. General properties and necessary conditions characterizing optimal…

Quantum Physics · Physics 2018-08-01 Vasco Cavina , Andrea Mari , Alberto Carlini , Vittorio Giovannetti

Producing useful electrical work in consuming chemical energy, the fuel cell have to reject heat to its surrounding. However, as it occurs for any other type of engine, this thermal energy cannot be exchanged in an isothermal way in finite…

Chemical Physics · Physics 2010-08-31 A. Vaudrey , P. Baucour , F. Lanzetta , R. Glises

Based on quantum thermodynamic processes, we make a quantum-mechanical (QM) extension of the typical heat engine cycles, such as the Carnot, Brayton, Otto, and Diesel cycles, etc. The temperature is not included in these QM engine cycles,…

Statistical Mechanics · Physics 2013-02-05 Jianhui Wang , Yongli Ma , Jizhou He

Irreversibility is a fundamental concept with important implications at many levels. It pinpoints the fundamental difference between the intrinsically reversible microscopic equations of motion and the unidirectional arrow of time that…

Quantum Physics · Physics 2019-05-01 T. B. Batalhao , S. Gherardini , J. P. Santos , G. T. Landi , M. Paternostro

Using the fluctuation theorem supplemented with geometric arguments, we derive universal features of the (long-time) efficiency fluctuations for thermal and isothermal machines operating under steady or periodic driving, close or far from…

Statistical Mechanics · Physics 2014-11-26 Gatien Verley , Tim Willaert , Christian Van den Broeck , Massimiliano Esposito

The reversible nature of thermodynamical cycles is an idealisation based on the assumption of perfect quasi-static dynamics. As a consequence of this assumption, ideal engines operate at the maximum efficiency but have zero power. Realistic…

Quantum Physics · Physics 2014-09-05 A. del Campo , J. Goold , M. Paternostro

In the thermodynamic analysis of thermoelectric devices, typical irreversibilities are for the processes of finite-rate heat transfer, heat leak and Joule heating. Approximate analyses often focus on either internal or external…

Statistical Mechanics · Physics 2025-08-07 Rajeshree Chakraborty , Ramandeep S. Johal

We demonstrate that irreversibility arises from the principle of microscopic reversibility and the presence of memory in the time evolution of a single copy of a system driven by a protocol. We introduce microscopic reversibility by using…

Statistical Mechanics · Physics 2015-11-30 J. Ricardo Arias-Gonzalez

The training algorithms for AI systems all introduce far-from-equilibrium dynamical processes, and understanding the irreversibility of these algorithms is a fundamental step towards understanding the learning dynamics of modern AI systems.…

Statistical Mechanics · Physics 2026-05-22 Liu Ziyin , Yuanjie Ren , Adam Levine , Isaac Chuang