One-shot trajectory learning of open quantum systems dynamics

Abstract

Nonadiabatic quantum dynamics are important for understanding lightharvesting processes, but their propagation with tradition methods can be rather expensive. Here we present a one-short trajectory learning approach that allows to directly make ultra-fast prediction of the entire trajectory for a new set of such simulation parameters as temperature and reorganization energy. The whole 2.5 ps long propagation takes 50 milliseconds as we demonstrate on the comparatively large quantum system, the Fenna–Matthews–Olsen (FMO) complex. Our approach also significantly reduces time and memory requirements for training.