Track Reconstruction for the EMPHATIC Spectrometer

Neutrinos are among the most abundant fundamental particles in the universe, but because they interact with other matter primarily through the weak nuclear force, we know very little about them. Although the weak interaction decay itself is well understood, the process of creating the hadrons which decay into 1-10 GeV neutrinos in accelerators and in the upper atmosphere is only understood at the 10-20% level, resulting in an uncertainty in the neutrino flux at the level of 10%. More precise measurements of the hadron interactions that create neutrinos can help researchers reduce the uncertainty on the neutrino flux and will enhance the capabilities of neutrino experiments like NOvA and DUNE in a variety of measurements such as neutrino cross-sections, sterile neutrino searches, and other BSM physics searches. The EMPHATIC collaboration's goal is to measure these hadron production probabilities (cross sections) using a compact, table-top sized spectrometer. This talk describes the development of a machine learning algorithm trained to reconstruct particle trajectories and momenta in the EMPHATIC spectrometer.