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  • Electron/pion identificatio...
    Adler, C.; Andronic, A.; Angelov, V.; Appelshäuser, H.; Baumann, C.; Blume, C.; Braun-Munzinger, P.; Bucher, D.; Busch, O.; Cătănescu, V.; Chernenko, S.; Ciobanu, M.; Daues, H.; Emschermann, D.; Fateev, O.; Foka, Y.; Garabatos, C.; Glasow, R.; Gottschlag, H.; Gunji, T.; Hamagaki, H.; Hehner, J.; Heine, N.; Herrmann, N.; Inuzuka, M.; Kislov, E.; Lehmann, T.; Lindenstruth, V.; Lippmann, C.; Ludolphs, W.; Mahmoud, T.; Marin, A.; Miskowiec, D.; Oyama, K.; Panebratsev, Yu; Petracek, V.; Petrovici, M.; Radu, A.; Reygers, K.; Rusanov, I.; Sandoval, A.; Santo, R.; Schicker, R.; Simon, R.S.; Smykov, L.; Soltveit, H.K.; Stachel, J.; Stelzer, H.; Stockmeier, M.R.; Tsiledakis, G.; Verhoeven, W.; Vulpescu, B.; Wessels, J.P.; Wilk, A.; Windelband, B.; Yurevich, V.; Zanevsky, Yu; Zaudtke, O.

    Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment, 11/2005, Letnik: 552, Številka: 3
    Journal Article

    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 6 GeV/ c. An improvement in pion rejection by about a factor of 3 is obtained with NN compared to standard likelihood methods.