Reactive Monte Carlo sampling with an ab initio potential

Jeff Leiding; Joshua D Coe

doi:10.1063/1.4948303

Reactive Monte Carlo sampling with an ab initio potential

J Chem Phys. 2016 May 7;144(17):174109. doi: 10.1063/1.4948303.

Authors

Jeff Leiding¹, Joshua D Coe¹

Affiliation

¹ Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

PMID: 27155627
DOI: 10.1063/1.4948303

Abstract

We present the first application of reactive Monte Carlo in a first-principles context. The algorithm samples in a modified NVT ensemble in which the volume, temperature, and total number of atoms of a given type are held fixed, but molecular composition is allowed to evolve through stochastic variation of chemical connectivity. We discuss general features of the method, as well as techniques needed to enhance the efficiency of Boltzmann sampling. Finally, we compare the results of simulation of NH3 to those of ab initio molecular dynamics (AIMD). We find that there are regions of state space for which RxMC sampling is much more efficient than AIMD due to the "rare-event" character of chemical reactions.