DOE OSTI · 3366795
Predicting Open Quantum Dynamics with Data-Informed Quantum-Classical Dynamics
Abstract
We introduce a data-informed quantum-classical dynamics (DIQCD) approach for predicting the evolution of an open quantum system. The equation of motion in DIQCD is a Lindblad equation with a flexible, time-dependent Hamiltonian that can be optimized to fit sparse and noisy data from local observations of an extensive open quantum system. We demonstrate the accuracy and efficiency of DIQCD for both experimental and simulated quantum devices. We show that DIQCD can predict entanglement dynamics of ultracold molecules (calcium fluoride) in optical tweezer arrays. DIQCD also successfully predicts carrier mobility in organic semiconductors (rubrene) with accuracy comparable to nearly exact numerical methods.
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Xie, Pinchen [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000293304032), Wang, Ke [Pennsylvania State Univ., University Park, PA (United States)] (ORCID:000900013225887X), Mitra, Anupam [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0009000467112477), Zhu, Yuanran [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000168514161), Li, Xiantao [Pennsylvania State Univ., University Park, PA (United States)] (ORCID:0000000297607292), de Jong, Wibe Albert [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000271148315), Yang, Chao [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000171727539). 2026-01-09. Predicting Open Quantum Dynamics with Data-Informed Quantum-Classical Dynamics. https://doi.org/10.1103/7lsx-ssjl
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