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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

A new Langevin-Verlet thermostat that preserves the fluctuation-dissipation relationship for discrete time steps, is applied to molecular modeling and tested against several popular suites (AMBER, GROMACS, LAMMPS) using a small molecule as…

Materials Science · Physics 2013-12-17 Niels Grønbech-Jensen , Natha Robert Hayre , Oded Farago

We investigate a simple model using the numerical simulation in the complex Langevin equation (CLE) and the analytical approximation with the Gaussian Ansatz. We find that the Gaussian Ansatz captures the essential and even quantitative…

High Energy Physics - Lattice · Physics 2016-12-07 Yuya Abe , Kenji Fukushima

A new configurational temperature thermostat suitable for molecules with holonomic constraints is derived. This thermostat has a simple set of motion equations, can generate the canonical ensemble in both position and momentum space, acts…

Statistical Mechanics · Physics 2009-11-13 Karl P. Travis , Carlos Braga

We initiate the study of utilizing Quantum Langevin Dynamics (QLD) to solve optimization problems, particularly those non-convex objective functions that present substantial obstacles for traditional gradient descent algorithms.…

Quantum Physics · Physics 2025-03-11 Zherui Chen , Yuchen Lu , Hao Wang , Yizhou Liu , Tongyang Li

The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points…

Atmospheric and Oceanic Physics · Physics 2011-09-06 Valerio Lucarini , Davide Faranda , Matteo Willeit

We study numerical methods for the generalized Langevin equation (GLE) with a positive Prony series memory kernel, in which case the GLE can be written in an extended variable Markovian formalism. We propose a new splitting method that is…

Computational Physics · Physics 2022-05-31 Manh Hong Duong , Xiaocheng Shang

When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon…

Computational Physics · Physics 2014-08-08 David A. Sivak , John D. Chodera , Gavin E. Crooks

We show that a recently introduced stochastic thermostat [J. Chem. Phys. 126 (2007) 014101] can be considered as a global version of the Langevin thermostat. We compare the global scheme and the local one (Langevin) from a formal point of…

Computational Physics · Physics 2008-06-06 Giovanni Bussi , Michele Parrinello

Dynamical equations describing physical systems at statistical equilibrium are commonly extended by mathematical tools called "thermostats". These tools are designed for sampling ensembles of statistical mechanics. We propose a dynamic…

Data Analysis, Statistics and Probability · Physics 2018-01-17 A. Samoletov , B. Vasiev

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

Monte Carlo sampling for Bayesian posterior inference is a common approach used in machine learning. The Markov Chain Monte Carlo procedures that are used are often discrete-time analogues of associated stochastic differential equations…

Machine Learning · Statistics 2020-02-14 Xiaocheng Shang , Zhanxing Zhu , Benedict Leimkuhler , Amos J. Storkey

We propose a Gaussian ensemble as a description of the long-time dynamics of isolated quantum integrable systems. Our approach extends the Generalized Gibbs Ensemble (GGE) by incorporating fluctuations of integrals of motion. It is…

Statistical Mechanics · Physics 2017-05-24 Hyungwon Kim , Anatoli Polkovnikov , Emil A. Yuzbashyan

We propose a generalized Langevin dynamics (GLD) technique to construct non-Markovian particle-based coarse-grained models from fine-grained reference simulations and to efficiently integrate them. The proposed GLD model has the form of a…

Soft Condensed Matter · Physics 2018-11-16 Gerhard Jung , Martin Hanke , Friederike Schmid

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

We compute the quantum Langevin equation (or quantum stochastic differential equation) representing the action of a quantum heat bath at thermal equilibrium on a simple quantum system. These equations are obtained by taking the continuous…

Mathematical Physics · Physics 2007-05-23 S. Attal , A. Joye

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

We investigate a novel type of Langevin model that describes the nonequilibrium dynamics of a classical particle interacting with a spatially extended environment. In this model, a particle, which interacts with the environment through the…

Statistical Mechanics · Physics 2015-10-20 Taiki Haga

We obtain the quantum Langevin equation (QLE) of a charged quantum particle moving in a harmonic potential in the presence of a uniform external magnetic field and linearly coupled to a quantum heat bath through momentum variables. The bath…

Statistical Mechanics · Physics 2013-12-04 Shamik Gupta , Malay Bandyopadhyay

Modeling a high-dimensional Hamiltonian system in reduced dimensions with respect to coarse-grained (CG) variables can greatly reduce computational cost and enable efficient bottom-up prediction of main features of the system for many…

Computational Engineering, Finance, and Science · Computer Science 2021-04-09 Shu Wang , Zhan Ma , Wenxiao Pan