Applying machine learning optimization methods to the production of a quantum gas

We apply three machine learning strategies to optimize the atomic cooling processes utilized in the production of a Bose-Einstein condensate (BEC). For the first time, we optimize both laser cooling and evaporative cooling mechanisms simultaneously. We present the results of an evolutionary optimiza...

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Veröffentlicht in:	Machine learning: science and technology Jg. 1; H. 1; S. 15007 - 15019
Hauptverfasser:	Barker, A J, Style, H, Luksch, K, Sunami, S, Garrick, D, Hill, F, Foot, C J, Bentine, E
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 01.03.2020
Schlagworte:	Artificial neural networks Bose-Einstein condensates Cooling Evaporative cooling Evolutionary computation Gaussian process Laser cooling Machine learning Optimization Process parameters Production methods ultracold quantum matter
ISSN:	2632-2153, 2632-2153
Online-Zugang:	Volltext
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