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

Authors :
Ken Oyama
Johanna Stachel
M. R. Stockmeier
N. Heine
C. Lippmann
A. Radu
H. Daues
W. Ludolphs
V. I. Yurevich
L. Smykov
T. Lehmann
O. Zaudtke
M. Inuzuka
Hideki Hamagaki
O. Busch
R. Santo
C. Adler
R.S. Simon
A. Sandoval
B. Vulpescu
D. Emschermann
W. Verhoeven
T. Mahmoud
Anton Andronic
A. Wilk
D. Bucher
Taku Gunji
I. Rusanov
Christoph Blume
Mihai Petrovici
G. Tsiledakis
Bernd Stefan Windelband
H. K. Soltveit
S. P. Chernenko
V. Angelov
Yu.V. Zanevsky
H. Appelshäuser
Rainer Martin Schicker
Y. Foka
Klaus Johannes Reygers
H. Gottschlag
Volker Lindenstruth
R. Glasow
D. Miskowiec
V. Catanescu
E. Kislov
N. Herrmann
O. V. Fateev
Peter Braun-Munzinger
C. Garabatos
Yu. Panebratsev
M. Ciobanu
A. Marin
H. Stelzer
V. Petracek
J. Hehner
Johannes Peter Wessels
C. Baumann
Source :
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 552:364-371
Publication Year :
2005
Publisher :
Elsevier BV, 2005.

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

Details

ISSN :
01689002
Volume :
552
Database :
OpenAIRE
Journal :
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Accession number :
edsair.doi...........8e73eed9e7318c5869859e66a4e3d6ca