Literature DB >> 20886921

Efficient stochastic thermostatting of path integral molecular dynamics.

Michele Ceriotti1, Michele Parrinello, Thomas E Markland, David E Manolopoulos.   

Abstract

The path integral molecular dynamics (PIMD) method provides a convenient way to compute the quantum mechanical structural and thermodynamic properties of condensed phase systems at the expense of introducing an additional set of high frequency normal modes on top of the physical vibrations of the system. Efficiently sampling such a wide range of frequencies provides a considerable thermostatting challenge. Here we introduce a simple stochastic path integral Langevin equation (PILE) thermostat which exploits an analytic knowledge of the free path integral normal mode frequencies. We also apply a recently developed colored noise thermostat based on a generalized Langevin equation (GLE), which automatically achieves a similar, frequency-optimized sampling. The sampling efficiencies of these thermostats are compared with that of the more conventional Nosé-Hoover chain (NHC) thermostat for a number of physically relevant properties of the liquid water and hydrogen-in-palladium systems. In nearly every case, the new PILE thermostat is found to perform just as well as the NHC thermostat while allowing for a computationally more efficient implementation. The GLE thermostat also proves to be very robust delivering a near-optimum sampling efficiency in all of the cases considered. We suspect that these simple stochastic thermostats will therefore find useful application in many future PIMD simulations.

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Year:  2010        PMID: 20886921     DOI: 10.1063/1.3489925

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


  15 in total

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9.  Nuclear quantum effects on the thermodynamic, structural, and dynamical properties of water.

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Journal:  Phys Chem Chem Phys       Date:  2021-03-17       Impact factor: 3.945

Review 10.  Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review.

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