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Electron/pion separation with an Emulsion Cloud Chamber by using a Neural Network

Abstract : 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 $e/\pi$ 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.
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http://hal.in2p3.fr/in2p3-00141769
Contributor : Dominique Girod <>
Submitted on : Monday, April 16, 2007 - 10:21:16 AM
Last modification on : Thursday, June 17, 2021 - 3:19:04 PM

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L. Arrabito, D. Autiero, C. Bozza, S. Buontempo, Y. Caffari, et al.. Electron/pion separation with an Emulsion Cloud Chamber by using a Neural Network. Journal of Instrumentation, IOP Publishing, 2007, 2, pp.P02001. ⟨10.1088/1748-0221/2/02/P02001⟩. ⟨in2p3-00141769⟩

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