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The thermodynamic formalism, which was first developed for dynamical systems and then applied to discrete Markov processes, turns out to be well suited for continuous time Markov processes as well, provided the definitions are interpreted…

Statistical Mechanics · Physics 2009-11-13 Vivien Lecomte , Cecile Appert-Rolland , Frederic Van-Wijland

Developing a thermodynamic theory of computation is a challenging task at the interface of non-equilibrium thermodynamics and computer science. In particular, this task requires dealing with difficulties such as stochastic halting times,…

Statistical Mechanics · Physics 2024-05-14 Gonzalo Manzano , Gülce Kardeş , Édgar Roldán , David Wolpert

Numerical simulation of steady-state heat conduction is common for thermal engineering. The simulation process usually involves mathematical formulation, numerical discretization and iteration of discretized ordinary or partial differential…

Applied Physics · Physics 2020-10-09 Jiang-Zhou Peng , Xianglei Liu , Nadine Aubry , Zhihua Chen , Wei-Tao Wu

Present-day thermodynamics has long outgrown the initial frames of the heat-engine theory and transmuted into a rather general macroscopic method for studying kinetics of various transfer processes in their inseparable connection with the…

General Physics · Physics 2014-04-02 V. A Etkin

We set up a framework for quantum stochastic thermodynamics based solely on experimentally controllable, but otherwise arbitrary interventions at discrete times. Using standard assumptions about the system-bath dynamics and insights from…

Quantum Physics · Physics 2019-08-22 Philipp Strasberg

Thermodynamics can be formulated in either of two approaches, the phenomenological approach, which refers to the macroscopic properties of systems, and the statistical approach, which describes systems in terms of their microscopic…

Quantum Physics · Physics 2019-05-01 Mirjam Weilenmann , Lea Krämer Gabriel , Philippe Faist , Renato Renner

Thermodynamics is accepted as a universal truth, encompassing all macroscopic objects. Therefore, it is surprising to find that, within our current understanding, the photovoltaic effect has so far eluded the first and second laws of…

Statistical Mechanics · Physics 2020-12-22 Ido Frenkel , Avi Niv

Knowledge distillation has proven effective for model compression by transferring knowledge from a larger network called the teacher to a smaller network called the student. Current knowledge distillation in time series is predominantly…

Machine Learning · Computer Science 2026-01-12 Nilushika Udayangani Hewa Dehigahawattage , Kishor Nandakishor , Marimuthu Palaniswami

Technical components are usually well optimized. However, simply combining these optimized components in a technical system does not necessarily lead to optimal systems. Therefore, focusing on a system perspective reveals new potential for…

Optimization and Control · Mathematics 2018-10-31 Jonas Benjamin Weber , Ulf Lorenz

I give a quick overview of some of the theoretical background necessary for using modern non-equilibrium statistical physics to investigate the thermodynamics of computation. I first present some of the necessary concepts from information…

Statistical Mechanics · Physics 2019-06-20 David H. Wolpert

Thermodynamic computing exploits fluctuations and dissipation in physical systems to efficiently solve various mathematical problems. For example, it was recently shown that certain linear algebra problems can be solved thermodynamically,…

Statistical Mechanics · Physics 2024-01-08 Samuel Duffield , Maxwell Aifer , Gavin Crooks , Thomas Ahle , Patrick J. Coles

An equation based reduced order model applicable to generalized heat equation and thermal simulations of power electronics systems developed in commercial CFD tools, is presented in this work. The model considers the physics of heat…

Numerical Analysis · Mathematics 2024-04-26 Neelakantan Padmanabhan

For the system with inhomogeneous distribution of macroscopic parameters we obtain thermodynamic relation which depends on the spatial point (coordinate). In our approach, to obtain such a relation we use the basic ideas of the method of…

Statistical Mechanics · Physics 2025-09-24 A. P. Rebesh , B. I. Lev , A. G. Zagorodny

Climate data science remains constrained by fragmented data sources, heterogeneous formats, and steep technical expertise requirements. These barriers slow discovery, limit participation, and undermine reproducibility. We present…

Artificial Intelligence · Computer Science 2026-03-16 Ahmed Jaber , Wangshu Zhu , Ayon Roy , Karthick Jayavelu , Justin Downes , Sameer Mohamed , Candace Agonafir , Linnia Hawkins , Tian Zheng

Nowadays, a huge amount of knowledge has been amassed in digital agriculture. This knowledge and know-how information are collected from various sources, hence the question is how to organise this knowledge so that it can be efficiently…

Databases · Computer Science 2020-11-24 Quoc Hung Ngo , Tahar Kechadi , Nhien-An Le-Khac

Concepts of everyday use like energy, heat, and temperature have acquired a precise meaning after the development of thermodynamics. Thermodynamics provides the basis for understanding how heat and work are related and with the general…

Statistical Mechanics · Physics 2007-05-23 D. Reguera , J. M. Rubi , J. M. G. Vilar

We develop KnowThyself, an agentic assistant that advances large language model (LLM) interpretability. Existing tools provide useful insights but remain fragmented and code-intensive. KnowThyself consolidates these capabilities into a…

Artificial Intelligence · Computer Science 2025-11-07 Suraj Prasai , Mengnan Du , Ying Zhang , Fan Yang

The fundamentals of a quantum heat engine are derived from first principles. The study is based on the equation of motion of a minimum set of operators which is then used to define the state of the system. The relation between the quantum…

Quantum Physics · Physics 2009-11-10 Tova Feldmann , Ronnie Kosloff

Knowledge distillation is a popular approach for enhancing the performance of ''student'' models, with lower representational capacity, by taking advantage of more powerful ''teacher'' models. Despite its apparent simplicity and widespread…

Machine Learning · Computer Science 2023-12-12 Mher Safaryan , Alexandra Peste , Dan Alistarh

In recent years, the unified theory of information and thermodynamics has been intensively discussed in the context of stochastic thermodynamics. The unified theory reveals that information theory would be useful to understand…

Statistical Mechanics · Physics 2018-07-23 Sosuke Ito
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