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One-Shot Trajectory Learning of Open Quantum Systems Dynamics
Ist Teil von
The journal of physical chemistry letters, 2022-07, Vol.13 (26), p.6037-6041
Ort / Verlag
American Chemical Society
Erscheinungsjahr
2022
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
Nonadiabatic quantum dynamics is important for understanding light-harvesting processes, but its propagation with traditional methods can be rather expensive. Here we present a one-shot trajectory learning approach that allows us to directly make an ultrafast 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 10-ps-long propagation takes 70 ms 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.