High Order Path Integrals Made Easy
arXiv:1606.00920 · doi:10.1063/1.4971438
Abstract
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.
References in corpus (13)
- Canonical sampling through velocity-rescaling
- How van der Waals interactions determine the unique properties of water
- Efficient stochastic thermostatting of path integral molecular dynamics
- How to remove the spurious resonances from ring polymer molecular dynamics
- Nuclear quantum effects in solids using a colored-noise thermostat
- Colored-noise thermostats à la carte
- Efficient first-principles calculation of the quantum kinetic energy and momentum distribution of nuclei
- Accelerating the convergence of path integral dynamics with a generalized Langevin equation
- Nuclear Quantum Effects and Nonlocal Exchange-Correlation Functionals Applied to Liquid Hydrogen at High Pressure
- On the Consistency of Approximate Quantum Dynamics Simulation Methods for Vibrational Spectra in the Condensed Phase
- Quantum fluctuations and isotope effects in ab initio descriptions of water
- Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: using density functional theory to accelerate wavefunction methods
- Direct path integral estimators for isotope fractionation ratios
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