Development of imaging techniques for scintillation light tracks in a novel neutron detector

Track imaging systems have been employed in nuclear, particle, and astroparticle physics to reconstruct particle interaction topologies. Early methods relied on bubble chambers and manual analysis, but modern techniques use advanced silicon detectors and scintillators to convert radiation into visible light. Sensitive photodetectors, such as SiPM matrices and CMOS cameras, capture this light, converting it into a digital signal, which is then processed to form an image. Coupled with sophisticated computational algorithms, these systems extract physical information from the images, eliminating the need for manual analysis. This work presents RIPTIDE, an innovative recoil-proton track imaging system designed for fast neutron detection, using the images generated from the detected light. RIPTIDE employs neutron-proton (n-p) elastic scattering in a plastic scintillator to produce scintillation light, which is captured in images to reconstruct scattering events in space and time. The primary objective is to develop novel track reconstruction techniques to determine the energy of incident neutrons using two orthogonal projections of the scintillator on the sensor. A hybrid approach combines the Hough transform with statistical moment-based methods to determine track direction and orientation, while deep-learning techniques are employed to remove optical aberrations from the tracks. This improves the accuracy of track length reconstruction. From the corrected images, proton energies are calculated, enabling the reconstruction of full neutron kinematics. Promising results are shown, highlighting the successful neutron energy reconstruction from both single and double scattering events.