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• W3106127907 abstract "In recent decades, cold atom experiments have become increasingly complex. While computers control most parameters, optimization is mostly done manually. This is a time-consuming task for a high-dimensional parameter space with unknown correlations. Here we automate this process using a genetic algorithm based on Differential Evolution. We demonstrate that this algorithm optimizes 21 correlated parameters and that it is robust against local maxima and experimental noise. The algorithm is flexible and easy to implement. Thus, the presented scheme can be applied to a wide range of experimental optimization tasks." @default.
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• W3106127907 date "2013-05-27" @default.
• W3106127907 modified "2023-09-25" @default.
• W3106127907 title "Evolutionary optimization of an experimental apparatus" @default.
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• W3106127907 doi "https://doi.org/10.1063/1.4808213" @default.
• W3106127907 hasPublicationYear "2013" @default.
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