期刊
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
卷 -, 期 -, 页码 6037-6041出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jpclett.2c012426037J
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资金
- National Natural Science Foundation of China [22003051]
- Fundamental Research Funds for the Central Universities [20720210092]
- Laboratory Project of the State Key Laboratory of Physical Chemistry of Solid Surfaces.
This study presents a one-shot trajectory learning approach that enables ultrafast prediction of the entire trajectory of the reduced density matrix. It also significantly reduces training time and memory requirements.
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.
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