An efficient approach to ab initio Monte Carlo simulation
Abstract
We present a Nested Markov chain Monte Carlo (NMC) scheme for building equilibrium averages based on accurate potentials such as density functional theory. Metropolis sampling of a reference system, defined by an inexpensive but approximate potential, was used to substantially decorrelate configurations at which the potential of interest was evaluated, thereby dramatically reducing the number needed to build ensemble averages at a given level of precision. The efficiency of this procedure was maximized onthefly through variation of the reference system thermodynamic state (characterized here by its inverse temperature β^{0}), which was otherwise unconstrained. Local density approximation results are presented for shocked states of argon at pressures from 4 to 60 GPa, where—depending on the quality of the reference system potential—acceptance probabilities were enhanced by factors of 1.228 relative to unoptimized NMC. The optimization procedure compensated strongly for reference potential shortcomings, as evidenced by significantly higher speedups when using a reference potential of lower quality. The efficiency of optimized NMC is shown to be competitive with that of standard ab initio molecular dynamics in the canonical ensemble.
 Publication:

Journal of Chemical Physics
 Pub Date:
 January 2014
 DOI:
 10.1063/1.4855755
 arXiv:
 arXiv:1309.0257
 Bibcode:
 2014JChPh.140c4106L
 Keywords:

 Physics  Chemical Physics;
 Physics  Computational Physics
 EPrint:
 The following article has been accepted by The Journal of Chemical Physics. After it is published, it will be found at http://scitation.aip.org/content/aip/journal/jcp