Iterative Spin Reclassification of Neutron Resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections, the probability for certain neutron interactions, for materials used in these systems. These cross sections exhibit resonant structure whose shape is determined in part by the angular-momentum quantum numbers of the resonances. In this project, conducted at the National Nuclear Data Center at Brookhaven National Laboratory, we apply machine learning to automate the quantum number assignments using only the resonances' energies and widths and not relying on detailed transmission or capture measurements. Current work is moving towards an iterative method of reclassifying the quantum numbers for flagged resonances.