Pattern recognition algorithm for Dark Matter signals on pixel detectors DAMIC-M

Abstract

Scientific observations lead to postulate the existence of dark matter and great e↵orts are being carried out by the scientific community to prove its existence. For this aim, the DAMIC-M (DArk Matter In CCDs) Experiment was built. In this thesis, Deep Learning is applied to achieve particle identification, in particular, convolutional neural networks will be built. The main goal of these models is to determine whether a particle of the Standard Model has been detected or not, hence to discard this event as a dark matter signal.