G
Glenn J. Martyna
Researcher at IBM
Publications - 157
Citations - 21104
Glenn J. Martyna is an academic researcher from IBM. The author has contributed to research in topics: Nanopore & Graphene. The author has an hindex of 45, co-authored 157 publications receiving 18636 citations. Previous affiliations of Glenn J. Martyna include University of Edinburgh & Indiana University.
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Constant pressure molecular dynamics algorithms
TL;DR: In this paper, a modularly invariant equations of motion are derived that generate the isothermal-isobaric ensemble as their phase space averages, and the resulting methods are tested on two problems, a particle in a one-dimensional periodic potential and a spherical model of C60 in the solid/fluid phase.
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Nosé-Hoover chains : the canonical ensemble via continuous dynamics
TL;DR: In this paper, a modification of the Nose-Hoover dynamics is proposed which includes not a single thermostat variable but a chain of variables, Nose chains, which gives the canonical distribution where the simple formalism fails.
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Reversible multiple time scale molecular dynamics
TL;DR: It is shown how the new RESPA methods are related to predictor–corrector integrators and how these methods can be used to accelerate the integration of the equations of motion of systems with Nose thermostats.
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Explicit reversible integrators for extended systems dynamics
TL;DR: Explicit reversible integrators, suitable for use in large-scale computer simulations, are derived for extended systems generating the canonical and isothermal-isobaric ensembles.
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A reciprocal space based method for treating long range interactions in ab initio and force-field-based calculations in clusters
TL;DR: In this paper, a new reciprocal space based formalism for treating long range forces in clusters is presented, which can be incorporated into plane-wave based density function theory calculations, standard Ewald summation calculations, and smooth particle-mesh Ewald calculations to yield accurate and numerically efficient descriptions of long range interactions in cluster systems.