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

Autor:	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
Rok vydání:	2005
Předmět:	Physics Nuclear and High Energy Physics Particle physics Artificial neural network Physics::Instrumentation and Detectors Nuclear Theory Electron Nuclear physics Transition radiation detector Identification (information) Pion High Energy Physics::Experiment Nuclear Experiment Alice (programming language) Instrumentation computer computer.programming_language
Zdroj:	Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 552:364-371
ISSN:	0168-9002
DOI:	10.1016/j.nima.2005.07.006
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8e73eed9e7318c5869859e66a4e3d6ca https://doi.org/10.1016/j.nima.2005.07.006 Zobrazit plný text záznamu Full Text from ScienceDirect