Pulse shape analysis using subspace identification methods and particle identification using neural networks in CsI(Tl) scintillators

The problem considered in this work is the classification of the reaction products. The assumption made herein is that the shape of the pulse (which height corresponds to the energy lost by the reaction product) is the impulse response of a dynamic linear system and contains complete information on the ion. In this case the product classification can be done by pulse-shape analysis. The present contribution proposes a complete procedure for isotopic identification of light charged particles stopped in the CsI(Tl) scintillators. The main idea is to use the cascade of a state-space identification algorithm and a parametric non-linear map using the model parameters as input regressors. The algorithm has been tested on a large set of impulse-responses, and provides a fully-automatic accurate classification of the isotopes.