Electron/pion separation with an Emulsion Cloud Chamber by using a Neural Network
摘要
We have studied the performance of a new algorithm for electron/pion separation in an Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The software for separation consists of two parts: a shower reconstruction algorithm and a Neural Network that assigns to each reconstructed shower the probability to be an electron or a pion. The performance has been studied for the ECC of the OPERA experiment [1]. The separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data taken at CERN (pion beams) and at DESY (electron beams). The algorithm allows to achieve a 90% electron identification efficiency with a pion misidentification smaller than 1% for energies higher than 2 GeV.
引用
@article{arxiv.physics/0701192,
title = {Electron/pion separation with an Emulsion Cloud Chamber by using a Neural Network},
author = {L. Arrabito and D. Autiero and C. Bozza and S. Buontempo and Y. Caffari and L. Consiglio and M. Cozzi and N. D'Ambrosio and G. De Lellis and M. De Serio and F. Di Capua and D. Di Ferdinando and N. Di Marco and A. Ereditato and L. S. Esposito and S. Gagnebin and G. Giacomelli and M. Giorgini and G. Grella and M. Hauger and M. Ieva and J. Janicsko Csathy and F. Juget and I. Kreslo and I. Laktineh and A. Longhin and G. Mandrioli and A. Marotta and J. Marteau and P. Migliozzi and P. Monacelli and U. Moser and M. T. Muciaccia and A. Pastore and L. Patrizii and C. Pistillo and M. Pozzato and G. Romano and G. Rosa and A. Russo and N. Savvinov and A. Schembri and L. Scotto Lavina and S. Simone and M. Sioli and C. Sirignano and G. Sirri and P. Strolin and V. Tioukov},
journal= {arXiv preprint arXiv:physics/0701192},
year = {2008}
}