Visualizing MoNA/LISA data to aid in event classification

Neutron-unbound systems are a special type of exotic nucleus that immediately decays by emitting one or more neutrons. Studying these systems can provide insights important to understanding nucleon-nucleon interactions inside the atomic nucleus. The Modular Neutron Array (MoNA) Collaboration uses the invariant mass spectroscopy technique to study these nuclei. Decays involving more than one neutron are challenging to analyze because care must be taken to identify events in which all emitted neutrons are detected. A current effort within the Collaboration is underway to explore new computational tools and techniques to address these challenges. The present work focuses on ways to visualize recorded data with the goal of enabling the development of a labelled event library for use in training machine learning algorithms to classify neutron hit patterns measured with the MoNA/LISA neutron detector array.