Skip navigation
Skip navigation

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]

CollectionsANU Research Publications
Date published: 2016
Type: Journal article
Source: Scientific Reports
DOI: 10.1038/srep25890
Access Rights: Open Access


File Description SizeFormat Image
01_Wigley_Fast_machine-learning_online_2016.pdf663.45 kBAdobe PDFThumbnail

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  22 January 2019/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator