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Scientific discovery can be framed as a thermodynamic process in which an agent invests physical work to acquire information about an environment under a finite work budget. Using established results about the thermodynamics of computing,…

Information Theory · Computer Science 2025-11-20 Mihir Rao

One of the important challenges facing high resolution molecular dynamics calculations is to reproduce biological functions that occur in the macroscopic world and involve macroscopic variables. Some of these functions can be well described…

Biomolecules · Quantitative Biology 2008-02-18 Bob Eisenberg

The thermodynamic limit of the internal energy and the entropy of the system of quantum interacting particles in random medium is shown to exist under the crucial requirements of stability and temperedness of interactions. The energy turns…

Mathematical Physics · Physics 2012-01-24 Nikolaj A. Veniaminov

The thermodynamics is studied with the thermodynamic parameter of the lifetime, first-passage time, generalizing the equilibrium thermodynamics. Various ways of describing several stationary nonequilibrium states in the system are…

Statistical Mechanics · Physics 2019-10-21 V. V. Ryazanov

In these decades, it has been revealed that there is rich information-theoretic structure in thermodynamics of out-of-equilibrium systems in both the classical and quantum regimes. This has led to the fruitful interplay among statistical…

Quantum Physics · Physics 2020-09-29 Takahiro Sagawa

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

The high accuracy exhibited by biological information transcription processes is due to kinetic proofreading, i.e., by a mechanism which reduces the error rate of the information-handling process by driving it out of equilibrium. We provide…

Statistical Mechanics · Physics 2015-06-18 Riccardo Rao , Luca Peliti

In this work, we suggest a parameterized statistical model (the gamma distribution) for the frequency of word occurrences in long strings of English text and use this model to build a corresponding thermodynamic picture by constructing the…

Information Theory · Computer Science 2011-03-01 Kostadin Koroutchev , Jian Shen , Elka Koroutcheva , Manuel Cebrian

We present the design for a thermodynamic computer that can perform arbitrary nonlinear calculations in or out of equilibrium. Simple thermodynamic circuits, fluctuating degrees of freedom in contact with a thermal bath and confined by a…

Statistical Mechanics · Physics 2026-01-08 Stephen Whitelam , Corneel Casert

We introduce an algorithmic model of heat conduction, the thermodynamic graph. The thermodynamic graph is analogous to meshes in the finite difference method in the sense that the calculation of temperature is carried out at the vertices of…

Computational Engineering, Finance, and Science · Computer Science 2018-02-02 O. Kurganskyy , A. J. Maksimova

We consider stochastic thermodynamics as a theory of statistical inference for experimentally observed fluctuating time-series. To that end, we introduce a general framework for quantifying the knowledge about the dynamical state of the…

Statistical Mechanics · Physics 2015-05-19 Bernhard Altaner , Jürgen Vollmer

We present three different neural network algorithms to calculate thermodynamic properties as well as dynamic correlation functions at finite temperatures for quantum lattice models. The first method is based on purification, which allows…

Statistical Mechanics · Physics 2024-04-16 D. Wagner , A. Klümper , J. Sirker

We consider continuously monitored quantum systems and introduce definitions of work and heat along individual quantum trajectories that are valid for coherent superpositions of energy eigenstates. We use these quantities to extend the…

Quantum Physics · Physics 2016-03-22 Jose Joaquin Alonso , Eric Lutz , Alessandro Romito

We develop the stochastic approach to thermodynamics based on the stochastic dynamics, which can be discrete (master equation) continuous (Fokker-Planck equation), and on two assumptions concerning entropy. The first is the definition of…

Statistical Mechanics · Physics 2015-06-11 Tânia Tomé , Mário J. de Oliveira

An unified thermodynamical framework based in the use of a generalized Massieu-Planck thermodynamic potential is proposed and a new formulation of Boltzmann-Gibbs Statistical Mechanics is established. Under this philosophy a generalization…

Mathematical Physics · Physics 2007-05-23 V. Garcia-Morales , J. Pellicer

Cellular signaling is essential in information processing and decision making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. Single-cell measurements of signaling…

Quantitative Methods · Quantitative Biology 2019-04-18 Carolin Loos , Jan Hasenauer

In this article, we review a general theoretical framework of thermodynamics of information on the basis of Bayesian networks. This framework can describe a broad class of nonequilibrium dynamics of multiple interacting systems with complex…

Statistical Mechanics · Physics 2018-07-23 Sosuke Ito , Takahiro Sagawa

The purpose of this work is to discuss recent progress in deriving the fundamental laws of thermodynamics (0th, 1st and 2nd-law) from nonequilibrium quantum statistical mechanics. Basic thermodynamic notions are clarified and different…

Mathematical Physics · Physics 2007-05-23 Walid K. Abou Salem

In the real world, one almost never knows the parameters of a thermodynamic process to infinite precision. Reflecting this, here we investigate how to extend stochastic thermodynamics to systems with uncertain parameters, including…

Statistical Mechanics · Physics 2021-03-17 Jan Korbel , David H. Wolpert

We use a formal correspondence between thermodynamics and inference, where the number of samples can be thought of as the inverse temperature, to study a quantity called ``learning capacity'' which is a measure of the effective…

Machine Learning · Computer Science 2024-10-22 Daiwei Chen , Wei-Kai Chang , Pratik Chaudhari