Next-Generation Neutron Detector: Study of Position Resolution via Machine Learning

The MoNA Collaboration is designing the Next-Generation Neutron Detector (NGn) to improve the position resolution of neutron detection in invariant-mass spectroscopy experiments. More accurate position resolution of neutrons improves the overall reconstructed decay energy of unbound states, which leads to better understanding of exotic nuclei near the neutron dripline. A small scale prototype of the future NGn was fabricated out of scintillating plastic and a modular array of Silicon Photomultipliers (SiPMs) with DAQ based on a Front-End Readout System (FERS). Davidson College conducted tests on the prototype board by moving a UV laser across the face of the scintillator in a grid pattern. At Hope College, we have been analyzing this laser data, along with additional data collected at Hope College using a collimated ⁹⁰Sr source. The currently predicted position resolution using the machine learning algorithm is ~3mm. Preliminary results of these ongoing tests will be presented.