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This study focuses on large deviation principles for fully coupled multiscale multivalued stochastic systems, in which the slow component is governed by a multivalued stochastic differential equation and the fast component is described by a…

Probability · Mathematics 2025-12-12 Huijie Qiao

We study the convergence of statistical estimators used in the estimation of large deviation functions describing the fluctuations of equilibrium, nonequilibrium, and manmade stochastic systems. We give conditions for the convergence of…

Statistical Mechanics · Physics 2015-11-09 Christian M. Rohwer , Florian Angeletti , Hugo Touchette

It is shown that under a certain condition on a semimartingale and a time-change, any stochastic integral driven by the time-changed semimartingale is a time-changed stochastic integral driven by the original semimartingale. As a direct…

Probability · Mathematics 2010-10-26 Kei Kobayashi

We discuss the stochastic thermodynamics of systems that are described by a time-dependent density field, for example simple liquids and colloidal suspensions. For a time-dependent change of external parameters, we show that the Jarzynski…

Statistical Mechanics · Physics 2014-03-18 T. Leonard , B. Lander , U. Seifert , T. Speck

We consider a general d-dimensional quantum system of non-interacting particles, with suitable statistics, in a very large (formally infinite) container. We prove that, in equilibrium, the fluctuations in the density of particles in a…

Mathematical Physics · Physics 2007-05-23 Joel L. Lebowitz , Marco Lenci , Herbert Spohn

Green-Kubo and Einstein expressions for the transport coefficients of a fluid in a nonequilibrium steady state can be derived using the Fluctuation Theorem and by assuming the probability distribution of the time-averaged dissipative flux…

Statistical Mechanics · Physics 2009-10-31 Debra J. Searles , Denis J. Evans

We prove a large deviation principle for stochastic differential equations driven by semimartingales, with additive controls. Conditions are given in terms of characteristics of driven semimartingales, so that if the noise-control pairs…

Probability · Mathematics 2024-08-13 Qiao Huang , Wei Wei , Jinqiao Duan

We study a discrete stochastic model of a molecular motor. This discrete model can be viewed as a \emph{minimal} ratchet model. We extend our previous work on this model, by further investigating the constraints imposed by the Fluctuation…

Statistical Mechanics · Physics 2009-11-13 D. Lacoste , A. W. C. Lau , K. Mallick

Surface sensitive electric current measurements are important experimental tools poorly corroborated by theoretical models. We show that the drift-diffusion equations offer a framework for a consistent description of such experiments. The…

Mesoscale and Nanoscale Physics · Physics 2017-06-15 Jakub Lis

We analyse large deviations of the dynamical activity in one-dimensional systems of diffusing hard particles. Using an optimal-control representation of the large-deviation problem, we analyse effective interaction forces which can be added…

Statistical Mechanics · Physics 2020-01-22 Jakub Dolezal , Robert L. Jack

We present a class of stochastic processes in which the large deviation functions of time-integrated observables exhibit singularities that relate to dynamical phase transitions of trajectories. These illustrative examples include Brownian…

Statistical Mechanics · Physics 2025-12-24 Yogeesh Reddy Yerrababu , Satya N. Majumdar , Benjamin Guiselin , Tridib Sadhu

Using the information current, we develop a Lorentz-covariant framework for modeling equilibrium fluctuations in relativistic kinetic theory in the grand-canonical ensemble. The resulting stochastic theory is proven to be causal and…

Nuclear Theory · Physics 2024-07-24 Gabriel Soares Rocha , Lorenzo Gavassino , Nicki Mullins

We analyse the statistics of the shear stress in a one dimensional \emph{model fluid}, that exhibits a rich phase behaviour akin to real complex fluids under shear. We show that the energy flux satisfies the Gallavotti-Cohen FT across all…

Statistical Mechanics · Physics 2016-09-06 Pritha Dolai , Aditi Simha

We show that a substantial portion of stochastic calculus can be developed along similar lines to ordinary calculus, with derivative-based concepts driving the development. We define a notion of stopping derivative, which is a form of right…

Probability · Mathematics 2026-02-06 Alex Simpson

Motivated by the occurrence in rate functions of time-dependent large-deviation principles, we study a class of non-negative functions $\mathscr L$ that induce a flow, given by $\mathscr L(\rho_t,\dot\rho_t)=0$. We derive necessary and…

Functional Analysis · Mathematics 2018-01-17 Alexander Mielke , D. R. Michiel Renger , Mark A. Peletier

In this work we elaborate on two recently discovered invariance principles, according to which transport coefficients are, to a large extent, independent of the microscopic definition of the densities and currents of the conserved…

Statistical Mechanics · Physics 2021-07-20 Federico Grasselli , Stefano Baroni

It is known that the distribution of nonreversible Markov processes breaking the detailed balance condition converges faster to the stationary distribution compared to reversible processes having the same stationary distribution. This is…

Statistical Mechanics · Physics 2021-06-30 Francesco Coghi , Raphael Chetrite , Hugo Touchette

Vanishing of the equilibrium Green-Kubo fluctuation expression for the friction coefficient of a massive particle moving in a finite-volume liquid is usually interpreted as an unphysical consequence of the finite volume. Here I show that it…

Chemical Physics · Physics 2009-11-13 Janka Petravic

Presently, the main methods for describing a non-equilibrium charge-transporting steady state are based on time-evolving it from the initial zero-current situation. An alternative class of theories would give the statistical non-equilibrium…

Materials Science · Physics 2007-05-23 P. Bokes , H. Mera , R. W. Godby

Biological machines like molecular motors and enzymes operate in dynamic cycles representable as stochastic flows on networks. Current stochastic dynamics describes such flows on fixed networks. Here, we develop a scalable approach to…

Statistical Mechanics · Physics 2026-03-02 Ying-Jen Yang , Ken A. Dill