Speaker
Description
ALPAQUITA is the prototype of a new gamma-ray observatory, the Andes Large Particle Detector for Cosmic Ray Physics and Astronomy (ALPACA), currently under construction at an altitude of 4,740 meters above sea level on a wide plateau near Chacaltaya Mountain in Bolivia. ALPACA will be a hybrid detector comprising a large area of scintillator-based detectors and underground water Cherenkov muon detectors to observe cosmic rays and gamma rays in the energy range from TeV to PeV. Since April 2023, the ALPAQUITA surface detectors (SD) have been operating in situ with 97 plastic scintillators.
In this work, we explore the performance of a state-of-the-art method to discriminate between cosmic rays and gamma rays. For this purpose, we designed a graph convolutional neural network (GCN) model to process the signals from the ALPAQUITA surface array. Each air shower event will be characterized by a graph in which each node represents a plastic scintillator with a feature vector (density, timing, and position) associated with it. The training and evaluation dataset was generated using Monte Carlo simulations of extensive air showers and their interactions with the detector.
