Trajectory determination at Muon Impact Tracer and Observer (MITO) using artificial neural networks

• Published in: Advances in Space Research
• Main Authors: Regadío Carretero, Alberto, Blanco Ávalos, Juan José, García Tejedor, Juan Ignacio, Ayuso de Gregorio, Sindulfo, Vrublevskyy, Ivan, Sánchez Prieto, Sebastián
• Other Authors: Universidad de Alcalá. Departamento de Automática, Universidad de Alcalá. Departamento de Física y Matemáticas. Unidad docente Física
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2023
• Subjects: Digital pulse processing; Instrumentation; Muon detector; Scintillator; Neural network; Cosmic rays; Space weather; Física; Astronomía; Physics; Astronomy; Antarctic; Livingston Island; Antarc*; Antarctica; Orca
• Online Access: http://hdl.handle.net/10017/59250; https://doi.org/10.1016/j.asr.2023.07.046

We propose a method for the determination of the impact point of muons in each of the two detection planes of the Muon Impact Tracer and Observer (MITO) telescope, which is part of the ORCA (Antarctic Cosmic Ray Observatory). The method uses the relative pulse height obtained by the four photomultipliers associated to the scintillator with the Adaptable and Reconfigurable Acquisition Con- cept for Nuclear Electronics (ARACNE) data adquisition module. These pulses are processed with an Artificial Neural Network (ANN) previously trained with the GEANT4 model of the detector. With the impact point in both MITO planes, we estimate the angle of inci- dence of these particles with in order to evaluate the isotropy of the incident particles. To validate the method, real data from recorded by MITO in Livingston Island, Antarctica have been used to evaluate the feasibility of this method and its application to space weather. Agencia Estatal de Investigación