Literature DB >> 33727572

Renormalization group theory of molecular dynamics.

Daiji Ichishima1, Yuya Matsumura2.   

Abstract

Large scale computation by molecular dynamics (MD) method is often challenging or even impractical due to its computational cost, in spite of its wide applications in a variety of fields. Although the recent advancement in parallel computing and introduction of coarse-graining methods have enabled large scale calculations, macroscopic analyses are still not realizable. Here, we present renormalized molecular dynamics (RMD), a renormalization group of MD in thermal equilibrium derived by using the Migdal-Kadanoff approximation. The RMD method improves the computational efficiency drastically while retaining the advantage of MD. The computational efficiency is improved by a factor of [Formula: see text] over conventional MD where D is the spatial dimension and n is the number of applied renormalization transforms. We verify RMD by conducting two simulations; melting of an aluminum slab and collision of aluminum spheres. Both problems show that the expectation values of physical quantities are in good agreement after the renormalization, whereas the consumption time is reduced as expected. To observe behavior of RMD near the critical point, the critical exponent of the Lennard-Jones potential is extracted by calculating specific heat on the mesoscale. The critical exponent is obtained as [Formula: see text]. In addition, the renormalization group of dissipative particle dynamics (DPD) is derived. Renormalized DPD is equivalent to RMD in isothermal systems under the condition such that Deborah number [Formula: see text].

Entities:  

Year:  2021        PMID: 33727572      PMCID: PMC7966406          DOI: 10.1038/s41598-021-85286-3

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  14 in total

Review 1.  Molecular dynamics simulations of biomolecules.

Authors:  Martin Karplus; J Andrew McCammon
Journal:  Nat Struct Biol       Date:  2002-09

2.  Phase diagram and universality of the Lennard-Jones gas-liquid system.

Authors:  Hiroshi Watanabe; Nobuyasu Ito; Chin-Kun Hu
Journal:  J Chem Phys       Date:  2012-05-28       Impact factor: 3.488

3.  Simulating stochastic dynamics using large time steps.

Authors:  O Corradini; P Faccioli; H Orland
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-12-09

4.  Molecular dynamics at low time resolution.

Authors:  P Faccioli
Journal:  J Chem Phys       Date:  2010-10-28       Impact factor: 3.488

5.  Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald.

Authors:  Romelia Salomon-Ferrer; Andreas W Götz; Duncan Poole; Scott Le Grand; Ross C Walker
Journal:  J Chem Theory Comput       Date:  2013-08-20       Impact factor: 6.006

6.  Critical point estimation of the Lennard-Jones pure fluid and binary mixtures.

Authors:  Javier Pérez-Pellitero; Philippe Ungerer; Gerassimos Orkoulas; Allan D Mackie
Journal:  J Chem Phys       Date:  2006-08-07       Impact factor: 3.488

Review 7.  Force-field parameters from the SAFT-γ equation of state for use in coarse-grained molecular simulations.

Authors:  Erich A Müller; George Jackson
Journal:  Annu Rev Chem Biomol Eng       Date:  2014-03-31       Impact factor: 11.059

8.  Coarse-Grained Molecular Models of Water: A Review.

Authors:  Kevin R Hadley; Clare McCabe
Journal:  Mol Simul       Date:  2012-07-04       Impact factor: 2.178

9.  Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born.

Authors:  Andreas W Götz; Mark J Williamson; Dong Xu; Duncan Poole; Scott Le Grand; Ross C Walker
Journal:  J Chem Theory Comput       Date:  2012-03-26       Impact factor: 6.006

10.  Bayesian selection for coarse-grained models of liquid water.

Authors:  Julija Zavadlav; Georgios Arampatzis; Petros Koumoutsakos
Journal:  Sci Rep       Date:  2019-01-14       Impact factor: 4.379

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