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Quantum estimation, control and learning: opportunities and challenges (2201.05835v1)
Published 15 Jan 2022 in quant-ph, cs.SY, and eess.SY
Abstract: The development of estimation and control theories for quantum systems is a fundamental task for practical quantum technology. This vision article presents a brief introduction to challenging problems and potential opportunities in the emerging areas of quantum estimation, control and learning. The topics cover quantum state estimation, quantum parameter identification, quantum filtering, quantum open-loop control, quantum feedback control, machine learning for estimation and control of quantum systems, and quantum machine learning.