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Related papers: DiffGLE: Differentiable Coarse-Grained Dynamics us…

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Langevin equations or generalized Langevin equations (GLEs) are popular models for describing the motion of a particle in a fluid medium in an effective manner. Here we examine particles immersed in an inherently nonequilibrium fluid, i.e.,…

Soft Condensed Matter · Physics 2024-05-03 Jeanine Shea , Gerhard Jung , Friederike Schmid

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

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

Applying an excess entropy scaling formalism to the coarse-grained (CG) dynamics of liquids, we discovered that missing rotational motions during the CG process are responsible for artificially accelerated CG dynamics. In the context of the…

Chemical Physics · Physics 2024-09-27 Jaehyeok Jin , Gregory A. Voth

We present a method to differentiate organisms solely by their motion based on the generalized Langevin equation (GLE) and use it to distinguish two different swimming modes of strongly confined unicellular microalgae Chlamydomonas…

Biological Physics · Physics 2024-05-24 Anton Klimek , Debasmita Mondal , Stephan Block , Prerna Sharma , Roland R. Netz

In statistical physics, the Nakajima-Mori-Zwanzig projection operator formalism is used to derive an integro-differential equation for observables in a Hilbert space, the generalized Langevin equation (GLE). This technique relies on the…

Mathematical Physics · Physics 2026-04-27 Christoph Widder , Johannes Zimmer , Tanja Schilling

The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) systems. Despite its universality, a more exact determination of…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

To investigate the impact of non-linear interactions on dynamic coarse graining, we study a simplified model system, featuring a tracer particle in a complex environment. Using a projection operator formalism and computer simulations, we…

Soft Condensed Matter · Physics 2023-07-18 Bernd Jung , Gerhard Jung

We describe in detail how to implement a coarse-grained hybrid Molecular Dynamics and Stochastic Rotation Dynamics simulation technique that captures the combined effects of Brownian and hydrodynamic forces in colloidal suspensions. The…

Soft Condensed Matter · Physics 2007-05-23 J. T. Padding , A. A. Louis

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

This paper series aims to establish a complete correspondence between fine-grained (FG) and coarse-grained (CG) dynamics by way of excess entropy scaling (introduced in Paper I). While Paper II successfully captured translational motions in…

Chemical Physics · Physics 2023-08-01 Jaehyeok Jin , Eok Kyun Lee , Gregory A. Voth

We derive generalized Langevin equations (GLEs) for single beads in linear elastic networks. In particular, the derivations of the GLEs are conducted without employing normal modes, resulting in two distinct representations in terms of…

Soft Condensed Matter · Physics 2024-10-23 Soya Shinkai , Shuichi Onami , Tomoshige Miyaguchi

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

A general scheme, which includes constructions of coarse-grained (CG) models, weighted ensemble dynamics (WED) simulations and cluster analyses (CA) of stable states, is presented to detect dynamical and thermodynamical properties in…

Soft Condensed Matter · Physics 2008-12-04 Xin Zhou

In this paper, the original discrete unified gas kinetic scheme (DUGKS) is extended to arbitrary Lagrangian-Eulerian (ALE) framework for simulating the low-speed continuum and rarefied flows with moving boundaries. For ALE method, the mesh…

Computational Physics · Physics 2020-01-08 Yong Wan , Chengwen Zhong

Coarse-grained (CG) models facilitate an efficient exploration of complex systems by reducing the unnecessary degrees of freedom of the fine-grained (FG) system while recapitulating major structural correlations. Unlike structural…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

Fourier acceleration has been successfully applied to the simulation of lattice field theories for more than a decade. In this paper, we extend the method to the dynamics of discrete particles moving in continuum. Although our method is…

Statistical Mechanics · Physics 2009-10-31 Francis J. Alexander , Bruce M. Boghosian , Richard C. Brower , S. Roy Kimura

We derive a $c-$number Generalised Langevin Equation (GLE) describing the evolution of the expectation values $\left\langle x_{i}\right\rangle_{t}$ of the atomic position operators $x_{i}$ of an open system. The latter is coupled linearly…

Statistical Mechanics · Physics 2016-11-15 L. Kantorovich , H. Ness , L. Stella , C. Lorenz

This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from non-equilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbulence. The mechanics of the generalized Langevin equation…

Fluid Dynamics · Physics 2017-02-01 Eric J. Parish , Karthik Duraisamy

Efficient sampling of the Boltzmann distribution of molecular systems is a long-standing challenge. Recently, instead of generating long molecular dynamics simulations, generative machine learning methods such as normalizing flows have been…

Machine Learning · Computer Science 2024-08-06 Henrik Schopmans , Pascal Friederich