Trigger-Level Electron Counting in the Light Dark Matter eXperiment using Artificial Neural Networks
The Light Dark Matter eXperiment is a fixed target missing-momentum experiment that searches for light dark matter production via the process of Dark Bremsstrahlung by analysing the energy of beam electrons after they hit a tungsten target. Electron counting is an important part of the experiment as this forms one of the two components of the missing energy trigger. The thesis looks into viability