Energy calibration and particle recognition by a neural network

In this work a neural network has been used to reconstruct the energy and classify the atomic number of the particles detected in a silicon–CsI, ΔE−E telescope. The adopted net is described and the whole procedure has been compared with the standard calibration methods for the E stage.