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Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

Aad, G; Abbott, B.; Abdallah, J; Abdinov, O; Aben, R; Åkesson, Torsten LU ; Bocchetta, Simona LU ; BRYNGEMARK, LENE LU ; Doglioni, Caterina LU and Floderus, Anders LU , et al. (2017) In European Physical Journal C 77(7).
Abstract
The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature... (More)
The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS. © 2017, CERN for the benefit of the ATLAS collaboration. (Less)
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publication status
published
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in
European Physical Journal C
volume
77
issue
7
publisher
Springer
external identifiers
  • scopus:85026307625
ISSN
1434-6044
DOI
10.1140/epjc/s10052-017-5004-5
language
English
LU publication?
yes
id
061eae6b-5e9d-4adf-a47a-4d2b421de373
date added to LUP
2017-09-05 09:46:54
date last changed
2018-09-16 04:49:27
@article{061eae6b-5e9d-4adf-a47a-4d2b421de373,
  abstract     = {The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS. © 2017, CERN for the benefit of the ATLAS collaboration.},
  articleno    = {490},
  author       = {Aad, G and Abbott, B. and Abdallah, J and Abdinov, O and Aben, R and Åkesson, Torsten and Bocchetta, Simona and BRYNGEMARK, LENE and Doglioni, Caterina and Floderus, Anders and Hawkins, Anthony and Hedberg, Vincent and Ivarsson, Jenny and Jarlskog, Göran and Lytken, Else and Mjörnmark, Ulf and Smirnova, Oxana and Viazlo, Oleksandr},
  issn         = {1434-6044},
  language     = {eng},
  number       = {7},
  publisher    = {Springer},
  series       = {European Physical Journal C},
  title        = {Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1},
  url          = {http://dx.doi.org/10.1140/epjc/s10052-017-5004-5},
  volume       = {77},
  year         = {2017},
}