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In molecular dynamics simulations, dynamically consistent coarse-grained (CG) models commonly use stochastic thermostats to model friction and fluctuations that are lost in a CG description. While Markovian, i.e., time-local, formulations…

Statistical Mechanics · Physics 2024-06-24 V. Klippenstein , N. Wolf , N. F. A. van der Vegt

We present a data-driven approach to determine the memory kernel and random noise in generalized Langevin equations. To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function,…

Computational Physics · Physics 2022-06-08 Huan Lei , Nathan Baker , Xiantao Li

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

Memory effects emerge as a fundamental consequence of dimensionality reduction when low-dimensional observables are used to describe the dynamics of complex many-body systems. In the context of molecular dynamics (MD) data analysis,…

Data Analysis, Statistics and Probability · Physics 2024-05-01 Lucas Tepper , Benjamin Dalton , Roland R. Netz

We obtain the memory kernel of the generalized Langevin equation, describing a particle interacting with longitudinal phonons in a liquid. The kernel is obtained analytically at T=0 Kelvin and numerically at T>0 Kelvin. We find that it…

Statistical Mechanics · Physics 2009-10-31 Gady Frenkel , Moshe Schwartz

We introduce a new method to accurately and efficiently estimate the effective dynamics of collective variables in molecular simulations. Such reduced dynamics play an essential role in the study of a broad class of processes, ranging from…

Statistical Mechanics · Physics 2022-03-28 Hadrien Vroylandt , Ludovic Goudenège , Pierre Monmarché , Fabio Pietrucci , Benjamin Rotenberg

Generalized Langevin Equation (GLE) thermostats have been used very effectively as a tool to manipulate and optimize the sampling of thermodynamic ensembles and the associated static properties. Here we show that a similar, exquisite level…

Chemical Physics · Physics 2017-09-06 Mariana Rossi , Venkat Kapil , Michele Ceriotti

In this paper, we study the diffusive limit of solutions to the generalized Langevin equation (GLE) in a periodic potential. Under the assumption of quasi-Markovianity, we obtain sharp longtime equilibration estimates for the GLE using…

Mathematical Physics · Physics 2021-02-03 G. A. Pavliotis , G. Stoltz , U. Vaes

The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic…

Soft Condensed Matter · Physics 2021-05-26 Niklas Bockius , Jeanine Shea , Gerhard Jung , Friederike Schmid , Martin Hanke

Memory effects in the dynamics of open systems have been the subject of significant interest in the last decades. The methods involved in quantifying this effect, however, are often difficult to compute and may lack analytical insight. With…

Quantum Physics · Physics 2021-02-10 Rolando Ramirez Camasca , Gabriel T. Landi

We recently showed that the dynamics of coarse-grained observables in systems out of thermal equilibrium are governed by the non-stationary generalized Langevin equation [J. Chem. Phys. 147, 214110 (2017), J. Chem. Phys. 150, 174118…

Statistical Mechanics · Physics 2021-05-21 Fabian Glatzel , Tanja Schilling

Recent rapid advances in single particle tracking and supercomputing techniques resulted in an unprecedented abundance of diffusion data exhibiting complex behaviours, such the presence of power law tails of the msd and memory functions,…

Statistical Mechanics · Physics 2018-10-08 Jakub Ślęzak

The Generalised Langevin Equation (GLE) method, as developed in Ref. [Phys. Rev. B 89, 134303 (2014)], is used to calculate the dissipative dynamics of systems described at the atomic level. The GLE scheme goes beyond the commonly used…

Statistical Mechanics · Physics 2015-01-06 H. Ness , L. Stella , C. D. Lorenz , L. Kantorovich

Memory effects are a key feature in the description of the dynamical systems governed by the generalized Langevin equation, which presents an exact reformulation of the equation of motion. A simple measure for the estimation of memory…

Disordered Systems and Neural Networks · Physics 2007-05-23 Anatolii V. Mokshin , Renat M. Yulmetyev , Peter Hänggi

Capturing the correct dynamics at the Coarse-Grained (CG) scale remains a central challenge in the advancement of systematic CG models for soft matter simulations. The Generalized Langevin Equation (GLE), rooted in the Mori-Zwanzig…

Soft Condensed Matter · Physics 2024-10-14 Jinu Jeong , Ishan Nadkarni , Narayana. R. Aluru

We propose a sampling method based on an ensemble approximation of second order Langevin dynamics. The log target density is appended with a quadratic term in an auxiliary momentum variable and damped-driven Hamiltonian dynamics introduced;…

Dynamical Systems · Mathematics 2025-06-06 Ziming Liu , Andrew M. Stuart , Yixuan Wang

We provide a general construction of quantum generalized master equations with memory kernel leading to well defined, that is completely positive and trace preserving, time evolutions. The approach builds on an operator generalization of…

Quantum Physics · Physics 2016-12-15 Bassano Vacchini

Analysis of non-Markovian systems and memory induced phenomena poses an everlasting challenge for physics. As a paradigmatic example we consider a classical Brownian particle of mass $M$ subjected to an external force and exposed to…

Statistical Mechanics · Physics 2024-05-21 Mateusz Wiśniewski , Jerzy Łuczka , Jakub Spiechowicz

We present a new method to approximate the Mori-Zwanzig (MZ) memory integral in generalized Langevin equations (GLEs) describing the evolution of smooth observables in high-dimensional nonlinear systems with local interactions. Building…

Numerical Analysis · Mathematics 2020-03-18 Yuanran Zhu , Daniele Venturi

Agent-based models typically treat systems in isolation, discarding environmental coupling as either computationally prohibitive or dynamically irrelevant. We demonstrate that this neglect misses essential physics: environmental degrees of…

Physics and Society · Physics 2026-02-12 Semra Gunduc , David J. Butts , Michael S. Murillo