Literature DB >> 27908121

The derivation and approximation of coarse-grained dynamics from Langevin dynamics.

Lina Ma1, Xiantao Li1, Chun Liu1.   

Abstract

We present a derivation of a coarse-grained description, in the form of a generalized Langevin equation, from the Langevin dynamics model that describes the dynamics of bio-molecules. The focus is placed on the form of the memory kernel function, the colored noise, and the second fluctuation-dissipation theorem that connects them. Also presented is a hierarchy of approximations for the memory and random noise terms, using rational approximations in the Laplace domain. These approximations offer increasing accuracy. More importantly, they eliminate the need to evaluate the integral associated with the memory term at each time step. Direct sampling of the colored noise can also be avoided within this framework. Therefore, the numerical implementation of the generalized Langevin equation is much more efficient.

Mesh:

Year:  2016        PMID: 27908121     DOI: 10.1063/1.4967936

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


  2 in total

1.  Data-driven molecular modeling with the generalized Langevin equation.

Authors:  Francesca Grogan; Huan Lei; Xiantao Li; Nathan A Baker
Journal:  J Comput Phys       Date:  2020-06-03       Impact factor: 3.553

2.  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

  2 in total

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