2016/06/30 by Venkat Kapil, Jörg Behler, Michele Ceriotti · 1 citation
Physics and Astronomy · #physics.chem-ph
paper · pdf · doi:10.1063/1.4971438
published as J. Chem. Phys. 145, 234103 (2016)
arxiv created 2016/12/30 · arxiv updated 2017/03/23
The precise description of quantum nuclear fluctuations in atomistic modelling is possible by employing path integral techniques, which involve a considerable computational overhead due to the need of simulating multiple replicas of the system. Many approaches have been suggested to reduce the required number of replicas. Among these, high-order factorizations of the Boltzmann operator are particularly attractive for high-precision and low-temperature scenarios. Unfortunately, to date several technical challenges have prevented a widespread use of these approaches to study nuclear quantum effects in condensed-phase systems. Here we introduce an inexpensive molecular dynamics scheme that overcomes these limitations, thus making it possible to exploit the improved convergence of high-order path integrals without having to sacrifice the stability, convenience and flexibility of conventional second-order techniques. The capabilities of the method are demonstrated by simulations of liquid water and ice, as described by a neural-network potential fitted to dispersion-corrected hybrid density functional theory calculations.