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In this article, we focus on the sampling of the configurational Gibbs-Boltzmann distribution, that is, the calculation of averages of functions of the position coordinates of a molecular $N$-body system modelled at constant temperature. We…

Numerical Analysis · Mathematics 2025-04-30 Benedict Leimkuhler , Charles Matthews

We discuss the design of an invariant measure-preserving transformed dynamics for the numerical treatment of Langevin dynamics based on rescaling of time, with the goal of sampling from an invariant measure. Given an appropriate monitor…

Numerical Analysis · Mathematics 2024-08-30 Alix Leroy , Benedict Leimkuhler , Jonas Latz , Desmond J. Higham

In this paper we introduce and analyse Langevin samplers that consist of perturbations of the standard underdamped Langevin dynamics. The perturbed dynamics is such that its invariant measure is the same as that of the unperturbed dynamics.…

Probability · Mathematics 2017-12-06 A. B. Duncan , N. Nuesken , G. A. Pavliotis

We develop an efficient sampling method by simulating Langevin dynamics with an artificial force rather than a natural force by using the gradient of the potential energy. The standard technique for sampling following the predetermined…

Statistical Mechanics · Physics 2015-09-30 M. Ohzeki , A. Ichiki

The Langevin dynamics is a diffusion process extensively used, in particular in molecular dynamics simulations, to sample Gibbs measures. Some alternatives based on (piecewise deterministic) kinetic velocity jump processes have gained…

Numerical Analysis · Mathematics 2025-05-27 Nicolaï Gouraud , Lucas Journel , Pierre Monmarché

We study the convergence to equilibrium of an underdamped Langevin equation that is controlled by a linear feedback force. Specifically, we are interested in sampling the possibly multimodal invariant probability distribution of a Langevin…

Optimization and Control · Mathematics 2022-01-12 Tobias Breiten , Carsten Hartmann , Lara Neureither , Upanshu Sharma

Adaptive Langevin dynamics is a method for sampling the Boltzmann-Gibbs distribution at prescribed temperature in cases where the potential gradient is subject to stochastic perturbation of unknown magnitude. The method replaces the…

Probability · Mathematics 2023-11-14 Benedict Leimkuhler , Matthias Sachs , Gabriel Stoltz

An improved method for driving a system into a desired distribution, for example, the Gibbs-Boltzmann distribution, is proposed, which makes use of an artificial relaxation process. The standard techniques for achieving the Gibbs-Boltzmann…

Statistical Mechanics · Physics 2015-06-18 Masayuki Ohzeki , Akihisa Ichiki

Langevin dynamics has become a popular tool to simulate the Boltzmann equilibrium distribution. When the repartition of the Langevin equation involves the exact realization of the Ornstein-Uhlenbeck noise, in addition to the conventional…

Chemical Physics · Physics 2017-11-15 Dezhang Li , Xu Han , Yichen Chai , Cong Wang , Zifei Chen , Zhijun Zhang , Jian Liu , Jiushu Shao

The measured time series from complex systems are renowned for their intricate stochastic behavior, characterized by random fluctuations stemming from external influences and nonlinear interactions. These fluctuations take diverse forms,…

Statistical Mechanics · Physics 2025-03-19 Pyei Phyo Lin , Matthias Wächter , Joachim Peinke , M. Reza Rahimi Tabar

We present a new method of conducting molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way,…

Statistical Mechanics · Physics 2016-04-28 Xingyu Gao , Jun Fang , Han Wang

We study numerical methods for sampling probability measures in high dimension where the underlying model is only approximately identified with a gradient system. Extended stochastic dynamical methods are discussed which have application to…

Numerical Analysis · Mathematics 2016-03-08 Benedict Leimkuhler , Xiaocheng Shang

Equilibrium properties in statistical physics are obtained by computing averages with respect to Boltzmann-Gibbs measures, sampled in practice using ergodic dynamics such as the Langevin dynamics. Some quantities however cannot be computed…

Numerical Analysis · Mathematics 2023-01-02 Gabriel Stoltz

We present a method for sampling microscopic configurations of a physical system distributed according to a canonical (Boltzmann-Gibbs) measure, with a constraint holding in average. Assuming that the constraint can be controlled by the…

Statistical Mechanics · Physics 2008-10-03 Jean-Bernard Maillet , Gabriel Stoltz

We study Langevin dynamics with a kinetic energy different from the standard, quadratic one in order to accelerate the sampling of Boltzmann-Gibbs distributions. In particular, this kinetic energy can be non-globally Lipschitz, which raises…

Statistical Mechanics · Physics 2018-05-15 Gabriel Stoltz , Zofia Trstanova

We introduce a method to sample the orientational distribution function in computer simulations. The method is based on the exact torque balance equation for classical many-body systems of interacting anisotropic particles in equilibrium.…

Soft Condensed Matter · Physics 2023-04-12 Johannes Renner , Matthias Schmidt , Daniel de las Heras

We present a novel methodology based on filtered data and moving averages for estimating effective dynamics from observations of multiscale systems. We show in a semi-parametric framework of the Langevin type that our approach is…

Numerical Analysis · Mathematics 2022-01-25 Giacomo Garegnani , Andrea Zanoni

Pervasive across diverse domains, stochastic systems exhibit fluctuations in processes ranging from molecular dynamics to climate phenomena. The Langevin equation has served as a common mathematical model for studying such systems, enabling…

Statistical Mechanics · Physics 2025-05-01 Youngkyoung Bae , Seungwoong Ha , Hawoong Jeong

Many complex systems operating far from the equilibrium exhibit stochastic dynamics that can be described by a Langevin equation. Inferring Langevin equations from data can reveal how transient dynamics of such systems give rise to their…

Machine Learning · Statistics 2021-11-01 Mikhail Genkin , Owen Hughes , Tatiana A. Engel

In this paper, we consider Langevin processes with mechanical constraints. The latter are a fundamental tool in molecular dynamics simulation for sampling purposes and for the computation of free energy differences. The results of this…

Statistical Mechanics · Physics 2011-04-19 Tony Lelievre , Mathias Rousset , Gabriel Stoltz
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