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Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization

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Cristian L. Cortes, Pascal Lefebvre, Nikolai Lauk, Michael J. Davis, Neil Sinclair, 5 Stephen K. Gray, and Daniel Oblak Center for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, USA… Click to show full abstract

Cristian L. Cortes, Pascal Lefebvre, Nikolai Lauk, Michael J. Davis, Neil Sinclair, 5 Stephen K. Gray, and Daniel Oblak Center for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, USA Institute for Quantum Science and Technology, and Department of Physics and Astronomy, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Division of Physics, Mathematics and Astronomy, and Alliance for Quantum Technologies (AQT), California Institute of Technology, 1200 E. California Boulevard, Pasadena, California 91125, USA Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, Illinois 60439, United States John A. Paulson School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, Massachusetts 02138, USA

Keywords: sample efficient; adaptive calibration; astronomy; efficient adaptive; physics; quantum

Journal Title: Physical Review Applied
Year Published: 2022

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