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

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

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IVANOVA-ROHLING, Violeta N., Niklas ROHLING, 2020. Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit Systems. In: Cybernetics and Information Technologies. De Gruyter. 20(6), pp. 61-73. ISSN 1311-9702. eISSN 1314-4081. Available under: doi: 10.2478/cait-2020-0061

@article{IvanovaRohling2020Evalu-52415, title={Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit Systems}, year={2020}, doi={10.2478/cait-2020-0061}, number={6}, volume={20}, issn={1311-9702}, journal={Cybernetics and Information Technologies}, pages={61--73}, author={Ivanova-Rohling, Violeta N. and Rohling, Niklas} }

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