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Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit Systems Cover

Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit Systems

Cybernetics and Information Technologies
Volume 20 (2020): Issue 6 (December 2020)
By: Violeta N. Ivanova-Rohling and  Niklas Rohling  
Open Access
|Dec 2020

Authors

Violeta N. Ivanova-Rohling

violeta.ivanova-rohling@uni-konstanz.de

Department of Physics and Zukunftskolleg, University of Konstanz, Department of Mathematical Foundations of Computer Sciences, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia

Niklas Rohling

niklas.rohling@uni-konstanz.de

Department of Physics, University of Konstanz, Germany
DOI: https://doi.org/10.2478/cait-2020-0061 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 61 - 73
Submitted on: Sep 15, 2020
Accepted on: Nov 4, 2020
Published on: Dec 31, 2020
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Quantum information,
optimization problem,
Widening,
reinforcement learning
Related subjects:
Computer sciences,
Information technology

© 2020 Violeta N. Ivanova-Rohling, Niklas Rohling, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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