Characterization of a driven two-level quantum system by Supervised
Learning
- URL: http://arxiv.org/abs/2212.11166v1
- Date: Wed, 21 Dec 2022 16:26:54 GMT
- Title: Characterization of a driven two-level quantum system by Supervised
Learning
- Authors: R. Couturier, E. Dionis, S. Gu\'erin, C. Guyeux, D. Sugny
- Abstract summary: 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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
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