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The question of whether quantum coherence is a resource beneficial or detrimental to the performance of quantum heat engines has been thoroughly studied but remains undecided. To isolate the contribution of coherence, we analyze the…

Quantum Physics · Physics 2023-02-01 Stefan Aimet , Hyukjoon Kwon

The context of the present paper is stochastic thermodynamics - an approach to nonequilibrium thermodynamics rooted within the broader framework of stochastic control. In contrast to the classical paradigm of Carnot engines, we herein…

Systems and Control · Electrical Eng. & Systems 2021-01-08 Rui Fu , Olga Movilla Miangolarra , Amirhossein Taghvaei , Yongxin Chen , Tryphon T. Georgiou

Given a quantum heat engine that operates in a cycle that reaches maximal efficiency for a time-dependent Hamiltonian H(t) of the working substance, with overall controllable driving H(t) = g(t) H, we study the deviation of the efficiency…

We develop the laws of thermodynamics in terms of general exponential families. By casting learning (log-loss minimization) problems in max-entropy and statistical mechanics terms, we translate thermodynamics results to learning scenarios.…

Statistical Mechanics · Physics 2025-01-07 Akshay Balsubramani

One of the key objectives in investigating small stochastic systems is the development of micrometer-sized engines and the understanding of their thermodynamics. However, the primary mathematical tool used for this purpose, the overdamped…

Statistical Mechanics · Physics 2025-03-31 Shakul Awasthi , Hyunggyu Park , Jae Sung Lee

We develop an artificial neural network model to predict quantum heat engines working within the experimentally realized framework of electromagnetically induced transparency. We specifically focus on {\Lambda}-type alkali-based cold atomic…

Quantum Physics · Physics 2025-01-07 Manash Jyoti Sarmah , Himangshu Prabal Goswami

In this study, we advance the understanding of non-equilibrium systems by deriving thermodynamic relations for a heat engine operating under an exponentially decreasing temperature profile. Such thermal configurations closely mimic…

Statistical Mechanics · Physics 2025-04-01 Mesfin Taye

The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on…

Biological Physics · Physics 2014-10-08 Alex H. Lang , Charles K. Fisher , Thierry Mora , Pankaj Mehta

A central goal of thermodynamics is to identify optimal processes during which the least amount of energy is dissipated into the environment. Generally, even for simple systems, such as the parametric harmonic oscillator, optimal control…

Statistical Mechanics · Physics 2018-10-11 Marcus V. S. Bonança , Sebastian Deffner

Thermodynamic quantities, such as heat and work, are not functions of state, but rather of the process undergone by a physical system. Assessing them can therefore be difficult, since it requires probing the system at least twice. This is…

Quantum Physics · Physics 2022-03-14 Marcelo Janovitch , Gabriel T. Landi

The method of optimizing entropy is used to (i) conduct Asymptotic Hypothesis Testing and (ii) determine the particle distribution for which Entropy is maximized. This paper focuses on two related applications of Information Theory:…

Statistics Theory · Mathematics 2016-03-09 Khizar Qureshi

We design a heat engine with multi-heat-reservoir, ancillary system and quantum memory. We then derive an inequality related with the second law of thermodynamics, and give a new limitation about the work gain from the engine by analyzing…

Quantum Physics · Physics 2017-11-09 Li-Hang Ren , Heng Fan

Traditional machine learning relies on explicit models and domain assumptions, limiting flexibility and interpretability. We introduce a model-free framework using surprisal (information theoretic uncertainty) to directly analyze and…

In this work, we propose a theory of temperature estimation of quantum systems, which is applicable in the regime of non-negligible prior temperature uncertainty and limited measurement data. In this regime the problem of establishing a…

The study of thermal heat engines was pivotal to establishing the principles of equilibrium thermodynamics, with implications far wider than only engine optimization. For nonequilibrium systems, which by definition dissipate energy even at…

Statistical Mechanics · Physics 2021-05-18 Étienne Fodor , Michael E. Cates

Self-organizing systems consume energy to generate internal order. The concept of thermodynamic efficiency, drawing from statistical physics and information theory, has previously been proposed to characterise a change in control parameter…

Adaptation and Self-Organizing Systems · Physics 2025-12-12 Qianyang Chen , Nihat Ay , Mikhail Prokopenko

The optimal power performance of a first principle quantum heat engine model shows friction-like phenomena when the internal fluid Hamiltonian does not commute with the external control field. The model is based on interacting…

Chemical Physics · Physics 2009-11-07 Ronnie Kosloff , Tova Feldmann

Thermal engines have been one of the principal topics of thermodynamics ever since its beginning. Today, in the era of the second quantum revolution, although the thermal processes in constant temperatures are relatively well understood in…

Quantum Physics · Physics 2025-07-09 Jakub Czartowski , Rafał Bistroń

Information can improve heat engine performance, but the underlying principles are still not so clear. Here we introduce a Carnot information machine (CIE) and obtain a quantitative relationship between the engine performance and…

Statistical Mechanics · Physics 2025-07-21 Yang Xiao , Qian Zeng , Jin Wang

Information is central to thermodynamics, providing the grounds to the formulation of the theory in powerful abstract statistical terms. One must not forget, however, that, as put by Landauer, {\it information is physical}. This means that…

Quantum Physics · Physics 2019-05-01 T. Croucher , J. Wright , A. R. R. Carvalho , S. M. Barnett , J. A. Vaccaro
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