• Corpus ID: 248834255

Machine-learning-accelerated Bose-Einstein condensation

@inproceedings{Vendeiro2022MachinelearningacceleratedBC,
  title={Machine-learning-accelerated Bose-Einstein condensation},
  author={Zachary Vendeiro and Joshua Ramette and Alyssa Rudelis and Michelle Chong and Josiah Sinclair and Luke Stewart and Alban Urvoy and Vladan Vuleti'c},
  year={2022}
}
Machine learning is emerging as a technology that can enhance physics experiment execution and data analysis. Here, we apply machine learning to accelerate the production of a Bose-Einstein Condensate (BEC) of 87 Rb atoms by Bayesian optimization of up to 55 control parameters. This approach enables us to prepare BECs of 2 . 8 × 10 3 optically trapped 87 Rb atoms from a room-temperature gas in 575 ms. The algorithm achieves the fast BEC preparation by applying highly efficient Raman cooling to… 

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