1978
DOI: 10.1080/00268977800100471
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Multiple time-step methods in molecular dynamics

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Cited by 203 publications
(84 citation statements)
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“…Multiple time scale methods can be used to exploit this separation in time scales by updating the slow interactions less frequently than the fast interactions, in principle, allowing significant computational savings to be achieved. [1][2][3][4] However, the maximum outer time step which can be obtained is in practice limited by the resonance between the slow and fast modes. 5,6 This results in energy building up in the high frequency modes, raising the temperature of the system and leading to unstable trajectories and incorrect sampling.…”
Section: Introductionmentioning
confidence: 99%
“…Multiple time scale methods can be used to exploit this separation in time scales by updating the slow interactions less frequently than the fast interactions, in principle, allowing significant computational savings to be achieved. [1][2][3][4] However, the maximum outer time step which can be obtained is in practice limited by the resonance between the slow and fast modes. 5,6 This results in energy building up in the high frequency modes, raising the temperature of the system and leading to unstable trajectories and incorrect sampling.…”
Section: Introductionmentioning
confidence: 99%
“…However, recent improvements to the spatial decomposition have enabled good scaling behavior down to a few hundred atoms per processor as well as about 10% improvement in performance for the spatial decomposition for some systems [59]. Another group of researchers implemented a version of the decomposition which employs a multiple time-step method [60] and three-body interactions [14,61,62] and then applied to several problems in porous silica [63,64].…”
Section: Spatial Parallel Molecular Dvnamics Algorithmmentioning
confidence: 99%
“…In spite of the rarity of interactions at low density, the inherent time step in SMD simulations cannot be increased beyond some small threshold without loss of stability and accuracy of trajectories, since there is nearly always a small fraction of particles interacting at any given time. Several adaptive integration methods exist, typically based on either separating rapidly and slowly-varying components of the potential in a multiple time step approach [3], or on time re-parametrization of the Hamiltonian equations to a new system that is integrated with a fixed step size [4]. Both methods have inherent drawbacks making them unsuitable for arbitrary potentials.…”
Section: Introductionmentioning
confidence: 99%