Adaptive Bayesian algorithm for achieving desired magneto-sensitive transition.

Efficiently and accurately determining a transition frequency is essential in precision spectroscopy. However, the exact relation between a desired transition frequency and the controllable experimental parameters is usually absent. Here, we propose an efficient scheme to search the suitable conditions for a desired magneto-sensitive transition via an adaptive Bayesian algorithm, and experimentally demonstrate it by using coherent population trapping (CPT) in an ensemble of laser-cooled $^{87}$Rb atoms. The transition frequency is controlled by an external magnetic field, which can be tuned in realtime by applying a d.c. voltage. Through an adaptive Bayesian algorithm, the voltage can automatically converge from a random initial value to the desired one only after few iterations. This work provides a simple and efficient way to determine a transition frequency, which can be widely applied in the fields of precision spectroscopy, such as atomic clocks, magnetometers, and nuclear magnetic resonance.