Precision relaxation rate measurement in SERF atomic magnetometers through FoPSO algorithm

The advancement of data processing algorithms is crucial for enhancing the performance of quantum sensing platforms. Despite remarkable progress, the application of advanced data-driven methods in spin-exchange relaxation-free (SERF) atomic magnetometers (AMs) still requires further exploration. In this study, we propose a fractional-order particle swarm optimization (FoPSO) approach for measuring the transverse relaxation rates in SERF AMs, aiming to address issues related to convergence consistency and measurement robustness. By leveraging FoPSO's superior capability to capture complex nonlinear dynamics, this study achieves improved accuracy and robustness under both well-shielded and residual magnetic field conditions. Experiments conducted with both simulated and experimental measured data validate the efficacy of the FoPSO framework. In addition to determining transverse relaxation rates, the corresponding spin polarization rates are also calculated. The results indicate that FoPSO is a reliable and effective tool for optimizing high-precision quantum sensing systems.