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Virtual‐Move Parallel Tempering
Author(s) -
Coluzza Ivan,
Frenkel Daan
Publication year - 2005
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.200400629
Subject(s) - parallel tempering , tempering , sampling (signal processing) , umbrella sampling , energy landscape , computer science , computational science , parallel computing , energy (signal processing) , efficient energy use , scheme (mathematics) , algorithm , chemistry , biological system , computational chemistry , molecular dynamics , materials science , mathematics , artificial intelligence , computer vision , engineering , statistics , electrical engineering , metallurgy , filter (signal processing) , mathematical analysis , bayesian probability , monte carlo molecular modeling , biology , biochemistry , markov chain monte carlo
Efficient sampling: Free‐energy landscapes for the refolding of a model protein are computed with the conventional adaptive parallel‐tempering (APT) scheme and the virtual‐move parallel‐tempering (VMPT) algorithm (a and b, respectively, in the picture). There is a striking difference in the sampling efficiency of the two methods. VMPT generates a fairly complete free‐energy landscape, whereas APT only generates fragments.