Machine Learning in LabVIEW to target NMR signals

Constant current continuous wave Nuclear Magnetic Resonance (NMR) has been an essential tool for polarized target experiments in Nuclear and High-energy physics. Q-meter based phase-sensitive detection can provide accurate monitoring of the polarization over the course of a scattering experiment; however it can only function reliably within a very strict set of electronic operational parameters. In this talk, we present recent studies of improved signal to noise in polarization measurements as well as reliable measurements outside of the designated range of the Q-meter's operational parameters with the use of machine learning (ML).