Optimization of experimental parameters for laser-slowing and magneto-optical trapping of MgF molecules

TL;DR

This paper uses Bayesian optimization to systematically enhance laser slowing and magneto-optical trapping of MgF molecules, achieving high capture velocities and trapping efficiencies crucial for quantum science applications.

Contribution

It introduces a comprehensive simulation and optimization framework for molecular laser cooling, specifically for MgF, combining laser slowing and MOT processes for improved experimental design.

Findings

Maximum MOT capture velocity of 82.5 m/s

28.6% of molecules trapped under optimal conditions

Framework applicable to similar molecules for quantum experiments

Abstract

Diatomic molecules are promising systems for quantum science applications due to their complex energy structures and strong dipole-dipole interactions. Achieving ultracold temperatures is essential for these applications, but the complexity of molecular energy levels requires precise optimization of experimental parameters for laser slowing and magneto-optical trapping (MOT). Here, we simulate and optimize the complete process of slowing and trapping MgF molecules, from a buffer-gas beam source to MOT capture, using Bayesian optimization. By combining laser slowing and MOT simulations, we identify parameters that maximize the capture velocity and the ratio of trapped molecules. Our results demonstrate a maximum MOT capture velocity of 82.5 m/s, and 28.6% of the molecules that reach the MOT region are trapped under optimal conditions. These findings provide insights into experimental setups for MgF and similar molecules, offering a framework for advancing molecular laser cooling and quantum experiments.