Literature DB >> 26133413

Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations.

Fabian Gottwald1, Sven Karsten1, Sergei D Ivanov1, Oliver Kühn1.   

Abstract

Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

Year:  2015        PMID: 26133413     DOI: 10.1063/1.4922941

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  3 in total

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Authors:  Julian Kappler; Victor B Hinrichsen; Roland R Netz
Journal:  Eur Phys J E Soft Matter       Date:  2019-09-10       Impact factor: 1.890

2.  Coarse-graining molecular dynamics: stochastic models with non-Gaussian force distributions.

Authors:  Radek Erban
Journal:  J Math Biol       Date:  2019-09-21       Impact factor: 2.259

3.  Likelihood-based non-Markovian models from molecular dynamics.

Authors:  Hadrien Vroylandt; Ludovic Goudenège; Pierre Monmarché; Fabio Pietrucci; Benjamin Rotenberg
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-23       Impact factor: 12.779

  3 in total

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