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17 October 2023 Efficient machine-learning approach to optimize trapped cold atom ensembles for quantum memory applications
Ivan Sekulic, Philipp-Immanuel Schneider, Oliver Anton, Elisa Da Ros, Victoria Henderson, Markus Krutzik
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Proceedings Volume 12740, Emerging Imaging and Sensing Technologies for Security and Defence VIII; 127400F (2023) https://doi.org/10.1117/12.2684406
Event: SPIE Security + Defence, 2023, Amsterdam, Netherlands
Abstract
Efficient guidance of physical experiments involving many control parameters presents a challenging optimization problem. In this work, we investigate how machine learning methods can be utilized to dramatically speed up the parameter tuning process pertinent to cold-atom sources with applications in quantum memories and atom interferometry. We compare the capabilities of several machine learning strategies in controlling the experimental process and report on the superior performance of the scalable Bayesian optimization algorithm, specifically tailored for this task.
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Ivan Sekulic, Philipp-Immanuel Schneider, Oliver Anton, Elisa Da Ros, Victoria Henderson, and Markus Krutzik "Efficient machine-learning approach to optimize trapped cold atom ensembles for quantum memory applications", Proc. SPIE 12740, Emerging Imaging and Sensing Technologies for Security and Defence VIII, 127400F (17 October 2023); https://doi.org/10.1117/12.2684406
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KEYWORDS
Chemical species
Quantum memory applications
Clouds
Data modeling
Education and training
Mathematical optimization
Process modeling
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