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Langevin and Brownian simulations play a prominent role in computational research, and state of the art integration algorithms provide trajectories with different stability ranges and accuracy in reproducing statistical averages. The…

Computational Physics · Physics 2025-01-03 Bogdan Tanygin , Simone Melchionna

The integral equation coarse-graining (IECG) approach is a promising high-level coarse-graining (CG) method for polymer melts, with variable resolution from soft spheres to multi CG sites, which preserves the structural and thermodynamical…

Soft Condensed Matter · Physics 2018-07-24 Mohammadhasan Dinpajooh , Marina G. Guenza

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

In the coarse grained Brownian Dynamics simulation method the many solvent molecules are replaced by random thermal kicks and an effective friction acting on the particles of interest. For Brownian Dynamics the friction has to be so strong…

Biomolecules · Quantitative Biology 2015-05-13 Uwe Winter , Tihamer Geyer

We implement the statistically sound G-JF thermostat for Langevin Dynamics simulations into the ESPREesSo molecular package for large-scale simulations of soft matter systems. The implemented integration method is tested against the…

Computational Physics · Physics 2016-08-17 Evyatar Arad , Oded Farago , Niels Grønbech-Jensen

Two of the most widely used Langevin integrators for molecular dynamics simulations are the GROMACS Stochastic Dynamics (GSD) integrator and the splitting method BAOAB. In this letter, we show that the GROMACS Stochastic Dynamics integrator…

Computational Physics · Physics 2022-09-28 Stefanie Kieninger , Bettina G. Keller

Accelerated coarse-graining (CG) algorithms for simulating heterogeneous chemical reactions on surface systems have recently gained much attention. In the present paper, we consider such an issue by investigating the oscillation behavior of…

Statistical Mechanics · Physics 2011-04-18 Ting Rao , Zhen Zhang , Zhonghuai Hou , Houwen Xin

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

Conjugated organic molecules play a central role in a wide range of optoelectronic devices, including organic light-emitting diodes, organic field-effect transistors, and organic solar cells. A major bottleneck in the computational design…

We provide an analytical framework for analyzing the quality of stochastic Verlet-type integrators for simulating the Langevin equation. Focusing only on basic objective measures, we consider the ability of an integrator to correctly…

Computational Physics · Physics 2026-02-12 Niels Grønbech-Jensen

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

The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters. In particular, we focus on implicit-solvent CG modeling of…

Computational Engineering, Finance, and Science · Computer Science 2021-03-22 Zhan Ma , Shu Wang , Minhee Kim , Kaibo Liu , Chun-Long Chen , Wenxiao Pan

Coarse-grained (CG) models are simplified representations of soft matter systems that are commonly employed to overcome size and time limitations in computational studies. Many approaches have been developed to construct and parametrise…

Statistical Mechanics · Physics 2022-09-27 Piero Luchi , Roberto Menichetti , Gianluca Lattanzi , Raffaello Potestio

This work presents a systematic methodology for describing the transient dynamics of coarse-grained molecular systems inferred from all-atom simulated data. We suggest Langevin-type dynamics where the coarse-grained interaction potential…

Numerical Analysis · Mathematics 2023-09-22 G. Baxevani , V. Harmandaris , E. Kalligiannaki , I. Tsantili

We reformulate the algorithm of Gr{\o}nbech-Jensen and Farago (GJF) for Langevin dynamics simulations at constant temperature. The GJF algorithm has become increasingly popular in molecular dynamics simulations because it provides robust…

Statistical Mechanics · Physics 2019-08-14 Oded Farago

Several recently proposed semi--automatic and fully--automatic coarse--graining schemes for polymer simulations are discussed. All these techniques derive effective potentials for multi--atom units or super--atoms from atomistic…

Soft Condensed Matter · Physics 2007-05-23 Roland Faller

In the present article, novel Coarse-Graining (CG) algorithms for the Eulerian-Lagrangian (EL) simulation of particle-laden flows are proposed. These include different variants of Reproducing Kernel Particle Methods (RKPM) and an extended…

Fluid Dynamics · Physics 2025-11-12 H. Eshraghi , E. Amani , M. Saffar-Avval

In previous work, we introduced a method for determining convergence rates for integration methods for the kinetic Langevin equation for $M$-$\nabla$Lipschitz $m$-log-concave densities [arXiv:2302.10684, 2023]. In this article, we exploit…

Numerical Analysis · Mathematics 2023-06-16 Benedict Leimkuhler , Daniel Paulin , Peter A. Whalley

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

Coarse-graining (CG) accelerates molecular simulations of protein dynamics by simulating sets of atoms as singular beads. Backmapping is the opposite operation of bringing lost atomistic details back from the CG representation. While…

Machine Learning · Computer Science 2023-03-06 Soojung Yang , Rafael Gómez-Bombarelli
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