Open AccessA simple method to accelerate configurational sampling for a generalized hybrid Monte Carlo method
Author(s) -
D Suzuki,
T Hori,
S. Miura
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2207/1/012018
Subject(s) - monte carlo method , simple (philosophy) , sampling (signal processing) , hybrid monte carlo , monte carlo method in statistical physics , monte carlo integration , rejection sampling , monte carlo molecular modeling , dynamic monte carlo method , importance sampling , statistical physics , mathematics , computer science , quasi monte carlo method , algorithm , mathematical optimization , markov chain monte carlo , statistics , physics , philosophy , epistemology , computer vision , filter (signal processing)
In this paper, a simple method to improve sampling efficiency of the generalized hybrid Monte Carlo (GHMC) method is presented. Compared to the standard GHMC method, our method is found to allow us to safely increase the time increment for solving an equation-of-motion in the GHMC calculations by a factor of 4. We have demonstrated various algorithmic parameter dependence on the sampling efficiency of a hydrated alanine dipeptide.