Enhanced all-optical vector atomic magnetometer enabled by artificial neural network

Abstract

This paper reports an all-optical vector magnetometer enhanced by a machine learning model. Using a dual probing beam setup, spin projections in both probe directions are simultaneously detected. Vector information is directly obtained from the measured phases of spin projection signals. To enhance the measurement accuracy and mitigate the dead zone effect, we introduce an artificial neural network (ANN) to link the phase signals to the field direction. With the addition of amplitude information to the ANN input, the average angle error is reduced to less than 0.3° within a hemisphere. Furthermore, this configuration demonstrates a field angle sensitivity of better than 30 μ rad/Hz1/2.