I. A. Luchnikov, E. O. Kiktenko, M. A. Gavreev, H. Ouerdane, S. N. Filippov, A. K. Fedorov, “Probing non-Markovian quantum dynamics with data-driven analysis: Beyond “black-box” machine-learning models”, Physical Review Research, 2022, Volume 4, Pages 43002

Funding agency	Grant number
Russian Science Foundation	19-71-10092
Russian Quantum Center	014/20
Priority 2030 Program	K1-2022-027
Foundation for the Development of Theoretical Physics and Mathematics BASIS	19-1-2-66-1
The development of the data processing scheme, analysis of the spin-boson model, and analysis of the damped Jaynes-Cummings model are supported by the Russian Science Foundation (Grant No. 19-71-10092), by the Leading Research Center on Quantum Computing (Agreement No. 014/20; analysis of non-Markovian processes for NISQ devices), and by the Priority 2030 program at the National University of Science and Technology “MISIS” under the project K1-2022-027 (applications to various quantum models). The analysis of the finite-environment-induced non-Markovian quantum dynamics is supported by the Foundation for the Advancement of Theoretical Physics and Mathematics “BASIS” for support under Project No. 19-1-2-66-1. The authors thank Alexander Ryzhov and Georgiy Semin for fruitful discussions.

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