Y.F. Zolotarev, I.A. Luchnikov, J.A. López-Saldívar, A.K. Fedorov, E.O. Kiktenko, “Continuous Monitoring for Noisy Intermediate-Scale Quantum Processors”, Phys. Rev. Applied, 19:1 (2023)
Sergei Fedotov, Daniel Han, “Population heterogeneity in the fractional master equation, ensemble self-reinforcement, and strong memory effects”, Phys. Rev. E, 107:3 (2023)
Jia-Liang Tang, Gabriel Alvarado Barrios, Enrique Solano, Francisco Albarrán-Arriagada, “Tunable Non-Markovianity for Bosonic Quantum Memristors”, Entropy, 25:5 (2023), 756
V. N. Petruhanov, A. N. Pechen, “GRAPE optimization for open quantum systems with time-dependent decoherence rates driven by coherent and incoherent controls”, J. Phys. A, 56:30 (2023), 305303–26
G. A. L. White, K. Modi, C. D. Hill, “Filtering Crosstalk from Bath Non-Markovianity via Spacetime Classical Shadows”, Phys. Rev. Lett., 130:16 (2023)
S. V. Vintskevich, N. Bao, A. Nomerotski, P. Stankus, D. A. Grigoriev, “Classification of four-qubit entangled states via machine learning”, Phys. Rev. A, 107:3 (2023)
I.A. Aloisio, G.A.L. White, C.D. Hill, K. Modi, “Sampling Complexity of Open Quantum Systems”, PRX Quantum, 4:2 (2023)
Akram Youssry, Hendra I Nurdin, “Multi-axis control of a qubit in the presence of unknown non-Markovian quantum noise”, Quantum Sci. Technol., 8:1 (2023), 015018
María Laura Olivera-Atencio, Lucas Lamata, Manuel Morillo, Jesús Casado-Pascual, “Quantum reinforcement learning in the presence of thermal dissipation”, Phys. Rev. E, 108:1 (2023)
Valentin Gebhart, Raffaele Santagati, Antonio Andrea Gentile, Erik M. Gauger, David Craig, Natalia Ares, Leonardo Banchi, Florian Marquardt, Luca Pezzè, Cristian Bonato, “Learning quantum systems”, Nat Rev Phys, 5:3 (2023), 141