Displaying similar documents to “Molecular Simulation in the Canonical Ensemble and Beyond”

A Metropolis adjusted Nosé-Hoover thermostat

Benedict Leimkuhler, Sebastian Reich (2009)

ESAIM: Mathematical Modelling and Numerical Analysis

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We present a Monte Carlo technique for sampling from the canonical distribution in molecular dynamics. The method is built upon the Nosé-Hoover constant temperature formulation and the generalized hybrid Monte Carlo method. In contrast to standard hybrid Monte Carlo methods only the thermostat degree of freedom is stochastically resampled during a Monte Carlo step.

Combining stochastic and deterministic approaches within high efficiency molecular simulations

Bruno Escribano, Elena Akhmatskaya, Jon Mujika (2013)

Open Mathematics

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Generalized Shadow Hybrid Monte Carlo (GSHMC) is a method for molecular simulations that rigorously alternates Monte Carlo sampling from a canonical ensemble with integration of trajectories using Molecular Dynamics (MD). While conventional hybrid Monte Carlo methods completely re-sample particle’s velocities between MD trajectories, our method suggests a partial velocity update procedure which keeps a part of the dynamic information throughout the simulation. We use shadow (modified)...

Theoretical and numerical comparison of some sampling methods for molecular dynamics

Eric Cancès, Frédéric Legoll, Gabriel Stoltz (2007)

ESAIM: Mathematical Modelling and Numerical Analysis

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The purpose of the present article is to compare different phase-space sampling methods, such as purely stochastic methods (Rejection method, Metropolized independence sampler, Importance Sampling), stochastically perturbed Molecular Dynamics methods (Hybrid Monte Carlo, Langevin Dynamics, Biased Random Walk), and purely deterministic methods (Nosé-Hoover chains, Nosé-Poincaré and Recursive Multiple Thermostats (RMT) methods). After recalling some theoretical convergence properties...