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Jet reconstruction and performance using particle flow with the ATLAS Detector

, ; Åkesson, Torsten LU ; Bocchetta, Simona LU ; Bryngemark, Lene LU ; Doglioni, Caterina LU ; Hedberg, Vincent LU ; Jarlskog, Göran LU ; Kalderon, Charles LU ; Lytken, Else LU and Mjörnmark, Ulf LU , et al. (2017) In European Physical Journal C 77(7). p.277-280
Abstract
This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb- 1 of ATLAS data from 8 TeV proton–proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the... (More)
This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb- 1 of ATLAS data from 8 TeV proton–proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the calorimeter and the inner tracker, is compared to that of jets reconstructed from calorimeter energy deposits alone, demonstrating improvements in resolution and pile-up stability. © 2017, CERN for the benefit of the ATLAS collaboration. (Less)
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Contribution to journal
publication status
published
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in
European Physical Journal C
volume
77
issue
7
pages
277 - 280
publisher
Springer Berlin Heidelberg
external identifiers
  • scopus:85024369614
ISSN
1434-6044
DOI
10.1140/epjc/s10052-017-5031-2
language
English
LU publication?
yes
id
fc37ddc5-b075-494e-8451-a6727f54363b
date added to LUP
2018-09-27 09:27:36
date last changed
2019-07-16 03:56:24
@article{fc37ddc5-b075-494e-8451-a6727f54363b,
  abstract     = {This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb- 1 of ATLAS data from 8 TeV proton–proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the calorimeter and the inner tracker, is compared to that of jets reconstructed from calorimeter energy deposits alone, demonstrating improvements in resolution and pile-up stability. © 2017, CERN for the benefit of the ATLAS collaboration.},
  author       = {,  and Åkesson, Torsten and Bocchetta, Simona and Bryngemark, Lene and Doglioni, Caterina and Hedberg, Vincent and Jarlskog, Göran and Kalderon, Charles and Lytken, Else and Mjörnmark, Ulf and Smirnova, Oxana and Viazlo, Oleksandr},
  issn         = {1434-6044},
  language     = {eng},
  number       = {7},
  pages        = {277--280},
  publisher    = {Springer Berlin Heidelberg},
  series       = {European Physical Journal C},
  title        = {Jet reconstruction and performance using particle flow with the ATLAS Detector},
  url          = {http://dx.doi.org/10.1140/epjc/s10052-017-5031-2},
  volume       = {77},
  year         = {2017},
}