Speaker
Mr
Alex Rua Herrera
(DS4DS, La Salle, Universitat Ramon Llull)
Description
Based on the fact that showers in calorimeters depend on the type of particle, this note attempts to perform a particle classifier for electromagnetic and hadronic particles on an electromagnetic calorimeter, based on the energy deposit of individual cells. Using data from a Geant4 simulation of a proposal of a Crystal Fiber Calorimeter (SPACAL), foreseen for a future upgrade of the LHCb detector, a classifier is built using Convolutional Neural Networks. Results obtained demonstrate that the higher resolution of this ECAL allows to attain over 95% precision in some classifications such as photons against neutrons.
Primary authors
Mr
Alex Rua Herrera
(DS4DS, La Salle, Universitat Ramon Llull)
Dr
Míriam Calvo Gómez
(DS4DS, La Salle, Universitat Ramon Llull)
Dr
Xavier Vilasís-Cardona
(DS4DS, La Salle, Universitat Ramon Llull)
