Electron/pion identification with ALICE TRD prototypes using a neural network algorithm

Article ID	Journal	Published Year	Pages	File Type
10716129	Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment	2005	8 Pages	PDF

Abstract

We study the electron/pion identification performance of the ALICE Transition Radiation Detector (TRD) prototypes using a neural network (NN) algorithm. Measurements were carried out for particle momenta from 2 to 6Â GeV/c. An improvement in pion rejection by about a factor of 3 is obtained with NN compared to standard likelihood methods.

Keywords

29.40.Gx 29.40.Cs Transition Radiation Detector Drift chamber Neural network Electron/pion identification

Related Topics

Physical Sciences and Engineering Physics and Astronomy Instrumentation

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Electron/pion identification with ALICE TRD prototypes using a neural network algorithm

Authors

C. Adler, A. Andronic, V. Angelov, H. Appelshäuser, C. Baumann, C. Blume, P. Braun-Munzinger, D. Bucher, O. Busch, V. CÄtÄnescu, S. Chernenko, M. Ciobanu, H. Daues, D. Emschermann, O. Fateev, Y. Foka, C. Garabatos, R. Glasow, O. Zaudtke,