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arXiv · 2204.12661

One-shot trajectory learning of open quantum systems dynamics

Arif Ullah·Pavlo O. Dral
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Abstract

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.

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Arif Ullah, Pavlo O. Dral. 2022-04-27. One-shot trajectory learning of open quantum systems dynamics. https://doi.org/10.1021/acs.jpclett.2c01242

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