%0 Journal Article %1 Bandyopadhyay2013341 %A Bandyopadhyay, Pradipta %D 2013 %J Chemical Physics Letters %K Carlo Monte chemistry mechanics physics statistical %N 1 %P 341 - 345 %R 10.1016/j.cplett.2012.11.047 %T Increasing the efficiency of Monte Carlo simulation with sampling from an approximate potential %U http://www.sciencedirect.com/science/article/pii/S000926141201353X %V 556 %X Nested Markov Chain Monte Carlo (MCMC) simulation using two potential functions, where the move for MCMC with one potential function (primary chain) is given by a short MCMC run with the other potential function (auxiliary chain) is well known. However, generally the acceptance of these moves is low. In this work, a scheme has been developed to increase the acceptance rate and applied to (H2O)20 and (H2O)25, where the primary and auxiliary chains are represented by a quantum mechanical (QM) and a classical potential respectively. A comparison between standard and nested MC simulation for (H2O)4 showed impressive results.

@article{Bandyopadhyay2013341, abstract = {Nested Markov Chain Monte Carlo (MCMC) simulation using two potential functions, where the move for MCMC with one potential function (primary chain) is given by a short MCMC run with the other potential function (auxiliary chain) is well known. However, generally the acceptance of these moves is low. In this work, a scheme has been developed to increase the acceptance rate and applied to (H2O)20 and (H2O)25, where the primary and auxiliary chains are represented by a quantum mechanical (QM) and a classical potential respectively. A comparison between standard and nested MC simulation for (H2O)4 showed impressive results.}, added-at = {2013-01-25T17:43:43.000+0100}, author = {Bandyopadhyay, Pradipta}, biburl = {https://www.bibsonomy.org/bibtex/2054b269ca925c666c87fb5e0cc8297aa/drmatusek}, doi = {10.1016/j.cplett.2012.11.047}, interhash = {c59dfc2aa9afe74f1b9e66545b75dc1d}, intrahash = {054b269ca925c666c87fb5e0cc8297aa}, issn = {0009-2614}, journal = {Chemical Physics Letters}, keywords = {Carlo Monte chemistry mechanics physics statistical}, month = jan, number = 1, pages = {341 - 345}, timestamp = {2013-02-04T12:55:23.000+0100}, title = {Increasing the efficiency of Monte Carlo simulation with sampling from an approximate potential}, url = {http://www.sciencedirect.com/science/article/pii/S000926141201353X}, volume = 556, year = 2013 }