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Proceedings Paper

Identification of gluon jets with a neural network technique
Author(s): Olof Barring; Torsten Akesson; Vincent Hedberg
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Paper Abstract

The separation of jets originating from quarks and gluons in three-jet events at LEP by using a neural network program has been studied. The analysis has been done in two steps, one in which only the jet-energy is used for the identification and a second step in which jet fragmentation variables are used as well. A new training procedure of the neural network combined with a new normalization of the fragmentation variables gives a method of identifying gluon jets from their fragmentation properties without distorting the energy spectrum of the identified jets. Since the fragmentation process can only be studied with phenomenological models it is important that the identification procedure is to a large extent model independent and the study has been made with two different jet fragmentation models.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205109
Show Author Affiliations
Olof Barring, CERN (Switzerland)
Torsten Akesson, Univ. of Lund (Sweden)
Vincent Hedberg, Univ. of Lund (Sweden)


Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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