Maximizing the capture velocity of molecular magneto-optical traps with Bayesian optimization

Abstract

Magneto-optical trapping (MOT) is a key technique on the route towards ultracold molecular ensembles. However, the realization and optimization of magneto-optical traps with their wide parameter space is particularly difficult. Here, we present a very general method for the optimization of molecular magneto-optical trap operation by means of Bayesian optimization (BO). As an example for a possible application, we consider the optimization of a calcium fluoride (CaF) MOT for maximum capture velocity. We find that both the $X^2{\Sigma }^{+}$ to $A^2{\Pi }_{1/2}$ and the $X^2{\Sigma }^{+}$ to $B^2{\Sigma }^{+}$ transition to allow for capture velocities larger than $20$ m/s with $24$ m/s and $23$ m/s respectively at a total laser power of $200$ mW. In our simulation, the optimized capture velocity depends logarithmically on the beam power within the simulated power range of $25$ to $400$ mW. Applied to heavy molecules such as BaH and BaF with their low capture velocity MOTs it might offer a route to far more robust magneto-optical trapping.

15 pages, 9 figures

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Cited by in corpus (3)

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• Hyperfine structure of the ${\mathbf{A}}^1\mathbf{\Pi }$ state of AlCl and its relevance to laser cooling and trapping