Description
A magneto-optical trap (MOT) is the first step to take various atoms and molecules to the ultracold temperature. For molecules, because of their complex energy structure, there are too many parameters to be adjusted in the MOT and the preceding laser slowing stage. It is difficult to experimentally optimize all the parameters one by one. Motion simulation of particle can provide the optimized parameters more efficiently, and also can give us the motional trace to check if parameters are valid for MOT and laser slowing.
We optimize the parameters for MOT and laser slowing of Magnesium monofluoride (MgF) via motion simulation, to maximize the capture velocity ($v_c$) and the ratio of trapped molecules to the total molecules from a cold buffer-gas beam source ($R_{trap}$). We simulate the motion of MgF in two stages, MOT region and laser slowing region, using rate equation model. In the MOT region, we optimized various parameters of lasers and magnetic field to maximize $v_c$, using Bayesian optimization method. Using the optimized experimental parameters, we set a capture condition of initial positions and velocities which determines if molecules are trapped or not, when they enter the stage. In laser slowing stage, we optimize the parameters of slowing lasers to maximize $R_{trap}$ using the capture condition of the MOT. In the poster, we further discuss the overall structure, initial conditions and optimization result of the simulation.
| Presenter name | Dongkyu Lim |
|---|---|
| How will you attend ICAP-27? | I am planning on in-person attendance |
