Year: 2026
Type: preprint
Abstract: Quantum nuclear effects on the statistical properties of position-dependent operators can be rigorously captured by molecular dynamics on the learnt potential of mean force of a single path-integral replica. However, the primitive mean-force averages obtained from path integral molecular dynamics with that replica held fixed are noisy. We derive a "scaled gradient" estimator with zero variance for a one-dimensional harmonic oscillator. On our molecular benchmark systems, the Zundel cation at 100 K and 300 K and bulk water at 300 K we observe nearly 5 to 50 times reduction in sampling time. The resulting potentials can be trained on these forces like standard machine learning interatomic potentials and yield stable production simulations from which quantum expectation values of position-dependent observables are obtained as classical ensemble averages.
Source: arXiv (Cornell University)
Author: Kapil, Venkat
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funder: University College London
OpenAlex ID: W7223665731