Online Monitoring using Machine Learning for the SpinQuest Experiment at Fermilab

The SpinQuest experiment (E1039) is a transversely polarized fixed target experiment at Fermi National Accelerator Laboratory that will measure the azimuthal asymmetry of dimuon pair production via scattering of unpolarized protons from transversely polarized NH3 and ND3 targets. By using neural network machine learning, we can quickly filter triggered events and reconstruct the kinematics of the detected muons on a spill-by-spill basis, letting us check the quality of incoming data, detect false asymmetries as they arise, and monitor the overall health of the experiment. This system will also be able to assist in off-line analysis by identifying data that merits examination, allowing us to better utilize existing tools. An overview of this system will be presented, as well as its context in the E1039 experiment.