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New exact results about the nonequilibrium thermodynamics of open quantum systems at arbitrary timescales are obtained by considering all possible variations of initial conditions of a system, its environment, and correlations between them.…

Statistical Mechanics · Physics 2021-05-05 Paul M. Riechers , Mile Gu

Diffusive motion in an externally driven potential is considered. It is shown that the distribution of work required to drive the system from an initial equilibrium state to another is Gaussian for slow but finite driving. Our result is…

Statistical Mechanics · Physics 2007-05-23 Thomas Speck , Udo Seifert

The study of thermodynamic fluctuations allows one to relate the free energy difference between two equilibrium states with the work done on a system through processes far from equilibrium. This finding plays a crucial role in the quantum…

The problem of estimating entropy production from incomplete information in stochastic thermodynamics is essential for theory and experiments. Whereas a considerable amount of work has been done on this topic, arguably, most of it is…

Statistical Mechanics · Physics 2024-12-17 Pedro E. Harunari , Carlos E. Fiore , Andre C. Barato

We propose a novel approach to define and measure the statistics of work, internal energy and dissipated heat in a driven quantum system. In our framework the presence of a physical detector arises naturally and work and its statistics can…

Quantum Physics · Physics 2015-10-28 P. Solinas , S. Gasparinetti

One of the major resource requirements of computers - ranging from biological cells to human brains to high-performance (engineered) computers - is the energy used to run them. Those costs of performing a computation have long been a focus…

Statistical Mechanics · Physics 2025-08-06 David H. Wolpert

Traditionally, it is understood that fluctuations in the equilibrium distribution are not evident in thermodynamic systems of large $N$ (the number of particles in the system) \cite{Huang1}. In this paper we examine the validity of this…

Mathematical Physics · Physics 2007-10-03 Kieran Kelly , Przemysław Repetowicz , Seosamh macRéamoinn

Returning a system to a desired state under a force field involves a thermodynamic cost, i.e., {\it work}. This cost fluctuates for a small-scale system from one experimental realization to another. We introduce a general framework to…

Statistical Mechanics · Physics 2022-12-07 Deepak Gupta , Carlos A. Plata

We extend the canonical Gibbs distribution, originally formulated for systems at equilibrium, to systems driven out of equilibrium. The stochastic dynamics of a small system are described by a probability distribution over discrete energy…

Statistical Mechanics · Physics 2026-03-31 Jean-Luc Garden

Consider a particle diffusing in a confined volume which is divided into two equal regions. In one region the diffusion coefficient is twice the value of the diffusion coefficient in the other region. Will the particle spend equal…

Dynamical Systems · Mathematics 2015-06-04 P. F. Tupper , Xin Yang

The fluctuation-dissipation theorem is a fundamental result in statistical physics that establishes a connection between the response of a system subject to a perturbation and the fluctuations associated with observables in equilibrium.…

Quantum Physics · Physics 2022-08-03 Tanmoy Biswas , A. de Oliveira Junior , Michał Horodecki , Kamil Korzekwa

Reducing work fluctuation and dissipation in heat engines or, more generally, information heat engines that perform feedback control is vital to maximize their efficiency. The same problem arises when we attempt to maximize the efficiency…

Statistical Mechanics · Physics 2016-01-06 Ken Funo , Masahito Ueda

Near equilibrium, thermodynamic intuition suggests that fast, irreversible processes will dissipate more energy and entropy than slow, quasistatic processes connecting the same initial and final states. Here, we test the hypothesis that…

Statistical Mechanics · Physics 2022-12-07 Rebecca A. Bone , Daniel J. Sharpe , David J. Wales , Jason R. Green

Irreversible information processing cannot be carried out without some inevitable thermodynamical work cost. This fundamental restriction, known as Landauer's principle, is increasingly relevant today, as the energy dissipation of computing…

Quantum Physics · Physics 2015-07-08 Philippe Faist , Frédéric Dupuis , Jonathan Oppenheim , Renato Renner

There are many functional contexts where it is desirable to maintain a mesoscopic system in a nonequilibrium state. However, such control requires an inherent energy dissipation. In this article, we unify and extend a number of works on the…

Statistical Mechanics · Physics 2017-11-07 Jordan M. Horowitz , Jeremy L. England

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

We derive a relation between the dissipation in a stochastic dynamics and the Wasserstein distance. We show that the minimal amount of dissipation required to transform an initial state to a final state during a diffusion process is given…

Statistical Mechanics · Physics 2019-12-19 Andreas Dechant , Yohei Sakurai

In this study, the minimum amount of work needed to drive a thermodynamic system from one initial distribution to another in a given time duration is discussed. Equivalently, for given amount of work, the minimum time duration required to…

Statistical Mechanics · Physics 2020-02-17 Yunxin Zhang

Physical systems driven away from equilibrium by an external controller dissipate heat to the environment; the excess entropy production in the thermal reservoir can be interpreted as a "cost" to transform the system in a finite time. The…

Statistical Mechanics · Physics 2024-12-31 Jérémie Klinger , Grant M. Rotskoff

Computing the distribution of trajectories from a Gaussian Process model of a dynamical system is an important challenge in utilizing such models. Motivated by the computational cost of sampling-based approaches, we consider approximations…

Machine Learning · Statistics 2023-05-16 Steffen Ridderbusch , Sina Ober-Blöbaum , Paul Goulart
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