Nonadiabatic quantum dynamics are important for understanding light-harvesting processes, but their propagation with traditional methods can be rather expensive. Here we present a one-shot trajectory learning approach that allows to directly make ultra-fast prediction of the entire trajectory of the reduced density matrix for a new set of such simulation parameters as temperature and reorganization energy. The whole 10ps long propagation takes 70 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.
@article{arxiv.2204.12661,
title = {One-shot trajectory learning of open quantum systems dynamics},
author = {Arif Ullah and Pavlo O. Dral},
journal= {arXiv preprint arXiv:2204.12661},
year = {2022}
}