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Jet identification based on probability calculations using Bayes' theorem

Jacobsson, C.; Jönsson, L.; Lindgren, Georg LU and Nyberg-Werther, M. (1995) In Physical Review D (Particles and Fields) 52(1). p.162-174
Abstract
The problem of identifying jets at CERN LEP and DESY HERA is studied. Identification using jet energies and fragmentation properties is treated separately in order to investigate the degree of quark-gluon separation that can be achieved by either of these approaches. In the case of the fragmentation-based identification, a neural network is used, and a test of the dependence on the jet production process and the fragmentation model is done. Instead of working with the separation variables directly, these are used to calculate probabilities of having a specific type of jet, according to Bayes’ theorem. This offers a direct interpretation of the performance of the jet identification and provides a simple means of combining the results of the... (More)
The problem of identifying jets at CERN LEP and DESY HERA is studied. Identification using jet energies and fragmentation properties is treated separately in order to investigate the degree of quark-gluon separation that can be achieved by either of these approaches. In the case of the fragmentation-based identification, a neural network is used, and a test of the dependence on the jet production process and the fragmentation model is done. Instead of working with the separation variables directly, these are used to calculate probabilities of having a specific type of jet, according to Bayes’ theorem. This offers a direct interpretation of the performance of the jet identification and provides a simple means of combining the results of the energy- and fragmentation-based identifications. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
LUND MONTE-CARLO, E+E-ANNIHILATION, GLUON BREMSSTRAHLUNG, HIGH-ENERGIES, FRAGMENTATION, QUARK, NETWORKS, PHYSICS, EVENTS
in
Physical Review D (Particles and Fields)
volume
52
issue
1
pages
162 - 174
publisher
American Physical Society
external identifiers
  • scopus:35949006179
ISSN
0556-2821
DOI
10.1103/PhysRevD.52.162
language
English
LU publication?
yes
id
43dbf51a-a1d5-462c-82c8-5c3f60e1f65c (old id 1210436)
alternative location
http://link.aps.org/abstract/PRD/v52/p162
date added to LUP
2008-08-14 16:30:45
date last changed
2017-03-15 13:27:00
@article{43dbf51a-a1d5-462c-82c8-5c3f60e1f65c,
  abstract     = {The problem of identifying jets at CERN LEP and DESY HERA is studied. Identification using jet energies and fragmentation properties is treated separately in order to investigate the degree of quark-gluon separation that can be achieved by either of these approaches. In the case of the fragmentation-based identification, a neural network is used, and a test of the dependence on the jet production process and the fragmentation model is done. Instead of working with the separation variables directly, these are used to calculate probabilities of having a specific type of jet, according to Bayes’ theorem. This offers a direct interpretation of the performance of the jet identification and provides a simple means of combining the results of the energy- and fragmentation-based identifications.},
  author       = {Jacobsson, C. and Jönsson, L. and Lindgren, Georg and Nyberg-Werther, M.},
  issn         = {0556-2821},
  keyword      = {LUND MONTE-CARLO,E+E-ANNIHILATION,GLUON BREMSSTRAHLUNG,HIGH-ENERGIES,FRAGMENTATION,QUARK,NETWORKS,PHYSICS,EVENTS},
  language     = {eng},
  number       = {1},
  pages        = {162--174},
  publisher    = {American Physical Society},
  series       = {Physical Review D (Particles and Fields)},
  title        = {Jet identification based on probability calculations using Bayes' theorem},
  url          = {http://dx.doi.org/10.1103/PhysRevD.52.162},
  volume       = {52},
  year         = {1995},
}