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The generalized Langevin equation (GLE) is a stochastic integro-differential equation that has been used to describe the velocity of microparticles in viscoelastic fluids. In this work, we consider the large-time asymptotic properties of a…

Probability · Mathematics 2020-01-30 Nathan Glatt-Holtz , David Herzog , Scott McKinley , Hung Nguyen

Various qualitative properties of solutions to the generalized Langevin equation (GLE) in a periodic or a confining potential are studied in this paper. We consider a class of quasi-Markovian GLEs, similar to the model that was introduced…

Mathematical Physics · Physics 2015-05-18 M. Ottobre , G. A. Pavliotis

We study the design and implementation of numerical methods to solve the generalized Langevin equation (GLE) focusing on canonical sampling properties of numerical integrators. For this purpose, we cast the GLE in an extended phase space…

Numerical Analysis · Mathematics 2020-12-09 Benedict Leimkuhler , Matthias Sachs

Finding the dynamical law of observable quantities lies at the core of physics. Within the particular field of statistical mechanics, the generalized Langevin equation (GLE) comprises a general model for the evolution of observables…

Statistical Mechanics · Physics 2022-11-22 Antonio Russo , Miguel A. Duran-Olivencia , Ioannis G. Kevrekidis , Serafim Kalliadasis

In this paper, we study a non-Markovian generalized relativistic Langevin equation (GRLE). We show that when the memory kernel is a sum of exponentials, the GRLE is equivalent to a Markovian system with added variables. We establish the…

Probability · Mathematics 2026-03-17 Ethan Baker , Manh Hong Duong , Hung Dang Nguyen

The Generalized Langevin Equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general non-equilibrium processes. In this approach, a part of the whole system (an…

Statistical Mechanics · Physics 2014-04-23 L. Stella , C. D. Lorenz , L. Kantorovich

We consider different Markovian embedding schemes of non-Markovian stochastic processes that are described by generalized Langevin equations (GLE) and obey thermal detailed balance under equilibrium conditions. At thermal equilibrium…

Statistical Mechanics · Physics 2010-02-08 Peter Siegle , Igor Goychuk , Peter Talkner , Peter Hanggi

Dynamics of non-Markovian systems is a classic problem yet it attracts an everlasting activity in physics and beyond. A powerful tool for modeling such setups is the Generalized Langevin Equation, however, its analysis typically poses a…

Statistical Mechanics · Physics 2024-10-29 Mateusz Wiśniewski , Jakub Spiechowicz

Piecewise-deterministic Markov processes (PDMPs) offer a powerful stochastic modeling framework that combines deterministic trajectories with random perturbations at random times. Estimating their local characteristics (particularly the…

Methodology · Statistics 2025-12-29 Romain Azaïs , Solune Denis

We develop the thermodynamics of non-Markovian generalized Langevin equations by embedding them in a high-dimensional Markovian representation involving auxiliary degrees of freedom. If the memory is linear and satisfies detailed balance…

Statistical Mechanics · Physics 2026-04-29 Andreas Dechant , Kiyoshi Kanazawa

We consider a system of interacting particles governed by the generalized Langevin equation (GLE) in the presence of external confining potentials, singular repulsive forces, as well as memory kernels. Using a Mori-Zwanzig approach, we…

Probability · Mathematics 2024-03-15 Manh Hong Duong , Hung D. Nguyen

The Generalized Langevin Equation (GLE) is a Stochastic Integro-Differential Equation that is commonly used to describe the velocity of microparticles that move randomly in viscoelastic fluids. Such particles commonly exhibit what is known…

Probability · Mathematics 2017-11-03 Scott A McKinley , Hung D Nguyen

The Fractional Langevin Equation (FLE) describes a non-Markovian Generalized Brownian Motion with long time persistence (superdiffusion), or anti-persistence (subdiffusion) of both velocity-velocity correlations, and position increments. It…

Statistical Mechanics · Physics 2011-07-11 P. Siegle , I. Goychuk , P. Hanggi

We introduce a hybrid projection scheme that combines linear Mori projection and conditional Zwanzig projection techniques and use it to derive a Generalized Langevin Equation (GLE) for a general interacting many-body system. The resulting…

Chemical Physics · Physics 2022-08-31 Cihan Ayaz , Benjamin A. Dalton , Roland R. Netz

Modeling non-Markovian time series is a recent topic of research in many fields such as climate modeling, biophysics, molecular dynamics, or finance. The generalized Langevin equation (GLE), given naturally by the Mori-Zwanzig projection…

Data Analysis, Statistics and Probability · Physics 2022-07-25 Clemens Willers , Oliver Kamps

The Monte Carlo wave function method or the quantum trajectory/jump approach is a powerful tool to study dissipative dynamics governed by the Markovian master equation, in particular for high-dimensional systems and when it is difficult to…

Quantum Physics · Physics 2009-11-13 X. L. Huang , H. Y. Sun , X. X. Yi

Recent pioneering experiments on non-Markovian dynamics done e.g. for active matter have demonstrated that our theoretical understanding of this challenging yet hot topic is rather incomplete and there is a wealth of phenomena still…

Statistical Mechanics · Physics 2024-02-27 M. Wiśniewski , J. Łuczka , J. Spiechowicz

We study asymptotic properties of the Generalized Langevin Equation (GLE) in the presence of a wide class of external potential wells with a power-law decay memory kernel. When the memory can be expressed as a sum of exponentials, a class…

Probability · Mathematics 2021-03-10 Hung D. Nguyen

We consider the asymptotics of the invariant measure for the process of the empirical spatial distribution of $N$ coupled Markov chains in the limit of a large number of chains. Each chain reflects the stochastic evolution of one particle.…

Probability · Mathematics 2013-01-25 Vivek S. Borkar , Rajesh Sundaresan

This paper proposes a novel exact maximum likelihood (ML) estimation method for general Gaussian processes, where all parameters are estimated jointly. The exact ML estimator (MLE) is consistent and asymptotically normally distributed. We…

Statistics Theory · Mathematics 2025-09-08 Tetsuya Takabatake , Jun Yu , Chen Zhang
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