Fast machine-learning online optimization of ultra-cold-atom experiments
Wigley, Paul; Everitt, Patrick; van den Hengel, Anton; Bastian, J. W.; Sooriyabandara, Mahasen; McDonald, Gordon; Hardman, Kyle; Quinlivan, Ciaron; Perumbil, Manju; Noschang Kuhn, Carlos; Petersen, Ian; Luiten, Andre; Hope, Joseph; Robins, Nicholas; Hush, Michael R
We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ‘learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous...[Show more]
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