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A generalization of fluctuation theorems in stochastic processes is proposed. The new theorem is written in terms of posterior probabilities, which are introduced via the Bayes theorem. In usual fluctuation theorems, a forward path and its…

Statistical Mechanics · Physics 2015-05-14 Jun Ohkubo

The fluctuation-dissipation relation is calculated for a class of stochastic models obeying a master equation. The transition rates are assumed to obey detailed balance also in the presence of a field. It is shown that in general the linear…

Statistical Mechanics · Physics 2016-08-31 Gregor Diezemann

The Doi-Peliti method is effective for investigating classical stochastic processes, and it has wide applications, including field theoretic approaches. Furthermore, it is applicable not only to master equations but also to stochastic…

Statistical Mechanics · Physics 2023-10-19 Shunta Takahashi , Jun Ohkubo

We review the density of states and related quantities of quasi one-dimensional disordered Peierls systems in which fluctuation effects of a backscattering potential play a crucial role. The low-energy behavior of non-interacting fermions…

Strongly Correlated Electrons · Physics 2017-09-27 Lorenz Bartosch

We present a theoretical approach to include dynamical aspects of molecular structural fluctuations, such as, for example, forming and breaking hydrogen bonds, isomerizations, and dynamical supramolecular structures, in nonequilibrium…

Mesoscale and Nanoscale Physics · Physics 2022-10-18 Daniel S. Kosov

Asymptotic fluctuation theorems are statements of a Gallavotti-Cohen symmetry in the rate function of either the time-averaged entropy production or heat dissipation of a process. Such theorems have been proved for various general classes…

Mathematical Physics · Physics 2010-01-23 Benjamin Hertz Shargel , Tom Chou

We present a novel and flexible data-driven framework for estimating the response of higher-order moments of nonlinear stochastic systems to small external perturbations. The classical Generalized Fluctuation--Dissipation Theorem (GFDT)…

Machine Learning · Statistics 2025-08-28 Ludovico T. Giorgini , Fabrizio Falasca , Andre N. Souza

Fluctuation-dissipation relations or "theorems" (FDTs) are fundamental for statistical physics and can be rigorously derived for equilibrium systems. Their applicability to non-equilibrium systems is, however, debated. Here, we simulate an…

Statistical Mechanics · Physics 2021-09-15 Gerhard Jung , Friederike Schmid

We present an exact functional formalism to deal with linear Langevin equations with arbitrary memory kernels and driven by any noise structure characterized through its characteristic functional. No others hypothesis are assumed over the…

Other Condensed Matter · Physics 2009-11-10 A. A. Budini , M. O. Caceres

The fluctuation-dissipation theorem (FDT) is a simple yet powerful consequence of the first-order differential equation governing the dynamics of systems subject simultaneously to dissipative and stochastic forces. The linear learning…

Machine Learning · Computer Science 2021-09-29 Manhyung Han , Jeonghyeok Park , Taewoong Lee , Jung Hoon Han

The irreversibility of trajectories in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. We consider stochastic maps resulting from a time discretization with interval \tau…

Data Analysis, Statistics and Probability · Physics 2018-03-15 Andrea Auconi , Andrea Giansanti , Edda Klipp

Fluctuation theorems are key to understanding both fundamental and applied aspects of non-equilibrium thermodynamics of small systems. We study the non-Markovian entropy production fluctuation theorem for the diffusion process of charged…

Statistical Mechanics · Physics 2026-05-06 K. S. Rodríguez-Vigil , M. A. Bastarrachea-Magnani , J. I. Jiménez-Aquino

The paper contributes to strengthening the relation between machine learning and the theory of differential equations. In this context, the inverse problem of fitting the parameters, and the initial condition of a differential equation to…

Machine Learning · Computer Science 2022-06-22 Imre Fekete , András Molnár , Péter L. Simon

Quantitative studies of irreversibility in statistical mechanics often involve the consideration of a reverse process, whose definition has been the object of many discussions, in particular for quantum mechanical systems. Here we show that…

Quantum Physics · Physics 2021-05-12 Francesco Buscemi , Valerio Scarani

Any decomposition of the total trajectory entropy production for Markovian systems has a joint probability distribution satisfying a generalized detailed fluctuation theorem, when all the contributing terms are odd with respect to time…

Statistical Mechanics · Physics 2010-10-26 Reinaldo Garcia-Garcia , Daniel Dominguez , Vivien Lecomte , Alejandro B. Kolton

Stochastic thermodynamics is an important development in the direction of finding general thermodynamic principles for non-equilibrium systems. We believe stochastic thermodynamics has the potential to benefit from the measure-theoretic…

Statistical Mechanics · Physics 2023-07-06 Annwesha Dutta , Saikat Sarkar

We study a connection between the algebraic probability and classical stochastic processes described by master equations. Introducing a definition of a state which has not been used for quantum cases, the classical stochastic processes can…

Statistical Mechanics · Physics 2013-07-10 Jun Ohkubo

Stochastic entropy production, which quantifies the difference between the probabilities of trajectories of a stochastic dynamics and its time reversals, has a central role in nonequilibrium thermodynamics. In the theory of probability, the…

Statistical Mechanics · Physics 2020-03-04 Ying-Jen Yang , Hong Qian

We establish the general framework of quantum fluctuation theorems by finding the symmetry between the forward and backward transitions of any given quantum channel. The Petz recovery map is adopted as the reverse quantum channel, and the…

Quantum Physics · Physics 2019-08-23 Hyukjoon Kwon , M. S. Kim

We show that the scaled cumulant generating and large deviation function, associated to a two-state Markov process involving two processes, obey a symmetry relation reminiscent of the fluctuation theorem, independent from any conditions on…

Statistical Mechanics · Physics 2015-06-19 Tim Willaert , Bart Cleuren , Christian Van den Broeck