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Switching Between the NVT and NpT Ensembles Using the Reweighting and Reconstruction Scheme
Author(s) -
Ahmad Kadoura,
Amgad Salama,
Shuyu Sun
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.05.309
Subject(s) - computer science , markov chain , range (aeronautics) , scheme (mathematics) , algorithm , extension (predicate logic) , set (abstract data type) , monte carlo method , markov chain monte carlo , statistical physics , mathematical optimization , artificial intelligence , machine learning , mathematics , physics , materials science , bayesian probability , mathematical analysis , statistics , composite material , programming language
Recently, we have developed several techniques in order to accelerate Monte Carlo (MC) molec- ular simulations. For that purpose, two strategies were followed. In the first, new algorithms were proposed as a set of early rejection schemes performing faster than the conventional al- gorithm while preserving the accuracy of the method. On the other hand, a reweighting and reconstruction scheme was introduced that is capable of retrieving primary quantities and sec- ond derivative properties at several thermodynamic conditions from a single MC Markov chain. The latter scheme, was first developed to extrapolate quantities in NV T ensemble for struc- tureless Lennard-Jones particles. However, it is evident that for most real life applications the NpT ensemble is more convenient, as pressure and temperature are usually known. Therefore, in this paper we present an extension to the reweighting and reconstruction method to solve NpT problems utilizing the same Markov chains generated by the NV T ensemble simulations. Eventually, the new approach allows elegant switching between the two ensembles for several quantities at a wide range of neighboring thermodynamic conditions

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