Displaying similar documents to “Combining stochastic and deterministic approaches within high efficiency molecular simulations”

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.

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...

Molecular Simulation in the Canonical Ensemble and Beyond

Zhidong Jia, Ben Leimkuhler (2007)

ESAIM: Mathematical Modelling and Numerical Analysis

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In this paper, we discuss advanced thermostatting techniques for sampling molecular systems in the canonical ensemble. We first survey work on dynamical thermostatting methods, including the Nosé-Poincaré method, and generalized bath methods which introduce a more complicated extended model to obtain better ergodicity. We describe a general controlled temperature model, () and demonstrate that it flexibly accommodates existing alternative thermostatting methods, such as Nosé-Poincaré,...

A generalised approach to the use of sampling for rapid object location

E. R. Davies (2008)

International Journal of Applied Mathematics and Computer Science

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This paper has developed a generalised sampling strategy for the rapid location of objects in digital images. In this strategy a priori information on the possible locations of objects is used to guide the sampling process, and earlier body-based and edge-based approaches emerge automatically on applying the right a priori probability maps. In addition, the limitations of the earlier regular sampling technique have been clarified and eased - with the result that sampling patterns are...