Paolo P. Mazza, Dominik Zietlow, Federico Carollo, Sabine Andergassen, Georg Martius, Igor Lesanovsky, “Machine learning time-local generators of open quantum dynamics”, Phys. Rev. Research, 3:2 (2021)
Ilya A. Luchnikov, Mikhail E. Krechetov, Sergey N. Filippov, “Riemannian geometry and automatic differentiation for optimization problems of quantum physics and quantum technologies”, New J. Phys., 23 (2021), 73006–25
Oliver Kaestle, Regina Finsterhoelzl, Andreas Knorr, Alexander Carmele, “Continuous and time-discrete non-Markovian system-reservoir interactions: Dissipative coherent quantum feedback in Liouville space”, Phys. Rev. Research, 3:2 (2021)
Mikhail Altaisky, Natalia Kaputkina, 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 2021, 10
Chu Guo, Kavan Modi, Dario Poletti, “Tensor-network-based machine learning of non-Markovian quantum processes”, Phys. Rev. A, 102:6 (2020)
O. V. Morzhin, A. N. Pechen, “Machine learning for finding suboptimal final times and coherent and incoherent controls for an open two-level quantum system”, Lobachevskii J. Math., 41:12 (2020), 2353–2368
Jiří Svozilík, Raúl Hidalgo-Sacoto, Ievgen I. Arkhipov, “Universal non-Markovianity detection in hybrid open quantum systems”, Sci Rep, 10:1 (2020)
S. N. Filippov, A. N. Glinov, L. Leppäjärvi, “Phase covariant qubit dynamics and divisibility”, Lobachevskii J. Math., 41:4 (2020), 617–630
A. E. Teretenkov, “Non-Markovian evolution of multi-level system interacting with several reservoirs. Exact and approximate”, Lobachevskii J. Math., 40:10 (2019), 1587–1605
Ilia A. Luchnikov, Alexander Ryzhov, Pieter-Jan Stas, Sergey N. Filippov, Henni Ouerdane, “Variational autoencoder reconstruction of complex many-body physics”, Entropy, 21 (2019), 1091–22