Details

Autor(en) / Beteiligte

• Ullah, Arif
• Dral, Pavlo O.

Titel

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

Link zum Volltext

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.