Couturier, R.; Dionis, E.; Guérin, S.; Guyeux, C.; Sugny, D. Characterization of a Driven Two-Level Quantum System by Supervised Learning. Entropy2023, 25, 446.
Couturier, R.; Dionis, E.; Guérin, S.; Guyeux, C.; Sugny, D. Characterization of a Driven Two-Level Quantum System by Supervised Learning. Entropy 2023, 25, 446.
Couturier, R.; Dionis, E.; Guérin, S.; Guyeux, C.; Sugny, D. Characterization of a Driven Two-Level Quantum System by Supervised Learning. Entropy2023, 25, 446.
Couturier, R.; Dionis, E.; Guérin, S.; Guyeux, C.; Sugny, D. Characterization of a Driven Two-Level Quantum System by Supervised Learning. Entropy 2023, 25, 446.
Abstract
We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. The estimate is global in the sense that no a priori knowledge is required on the parameters to be determined. Different neural network algorithms are tested on a series of data sets. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.
Keywords
Optimal control; supervised learning; system characterization; two-level quantum systems
Subject
Physical Sciences, Quantum Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
