Jet reconstruction and performance using particle flow with the ATLAS Detector

Agni Bethani; Steven Connelly; Rafal Bielski; Brian Cox; Cinzia Da Via; Nicholas Dann; Giulio Forcolin; Alessandra Forti; Julia Iturbe Ponce; Stephen Marsden; Jiri Masik; Stephen Menary; Francisca Munoz Sanchez; Alexander Oh; Rustem Ospanov; Andrew Pilkington; Arnaud Pin; Darren Price; John Raine; Jacob Rawling; Rhys Roberts; H. Schweiger; Savanna Shaw; Lee Tomlinson; Stephen Watts; Fabian Wilk; Martin Woudstra; Terence Wyatt; ATLAS Collaboration

doi:10.1140/epjc/s10052-017-5031-2

Jet reconstruction and performance using particle flow with the ATLAS Detector

Agni Bethani, Steven Connelly, Rafal Bielski, Brian Cox, Cinzia Da Via, Nicholas Dann, Giulio Forcolin, Alessandra Forti, Julia Iturbe Ponce, Stephen Marsden, Jiri Masik, Stephen Menary, Francisca Munoz Sanchez, Alexander Oh, Rustem Ospanov, Andrew Pilkington, Arnaud Pin, Darren Price, John Raine, Jacob RawlingRhys Roberts, H. Schweiger, Savanna Shaw, Lee Tomlinson, Stephen Watts, Fabian Wilk, Martin Woudstra, Terence Wyatt, ATLAS Collaboration

Research output: Contribution to journal › Article › peer-review

Abstract

This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb −1−1 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

Original language	English
Journal	European Physical Journal C. Particles and Fields
Volume	77
DOIs	https://doi.org/10.1140/epjc/s10052-017-5031-2
Publication status	Published - 13 Jul 2017

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Bethani, A., Connelly, S., Bielski, R., Cox, B., Da Via, C., Dann, N., Forcolin, G., Forti, A., Iturbe Ponce, J., Marsden, S., Masik, J., Menary, S., Munoz Sanchez, F., Oh, A., Ospanov, R., Pilkington, A., Pin, A., Price, D., Raine, J., ... ATLAS Collaboration (2017). Jet reconstruction and performance using particle flow with the ATLAS Detector. European Physical Journal C. Particles and Fields, 77. https://doi.org/10.1140/epjc/s10052-017-5031-2

@article{295767cfb2d04b63a8650d9873e60d72,

title = "Jet reconstruction and performance using particle flow with the ATLAS Detector",

abstract = "This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb −1−1 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",

author = "Agni Bethani and Steven Connelly and Rafal Bielski and Brian Cox and {Da Via}, Cinzia and Nicholas Dann and Giulio Forcolin and Alessandra Forti and {Iturbe Ponce}, Julia and Frederick Loebinger and Stephen Marsden and Jiri Masik and Stephen Menary and {Munoz Sanchez}, Francisca and Alexander Oh and Rustem Ospanov and Yvonne Peters and Andrew Pilkington and Arnaud Pin and Darren Price and John Raine and Jacob Rawling and Rhys Roberts and H. Schweiger and Savanna Shaw and Lee Tomlinson and Stephen Watts and Fabian Wilk and Martin Woudstra and Terence Wyatt and {ATLAS Collaboration}",

year = "2017",

month = jul,

day = "13",

doi = "10.1140/epjc/s10052-017-5031-2",

language = "English",

volume = "77",

journal = "European Physical Journal C. Particles and Fields",

issn = "1434-6044",

publisher = "Springer Nature",

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Bethani, A, Connelly, S, Bielski, R, Cox, B, Da Via, C, Dann, N, Forcolin, G, Forti, A, Iturbe Ponce, J, Marsden, S, Masik, J, Menary, S, Munoz Sanchez, F , Oh, A, Ospanov, R, Pilkington, A, Pin, A, Price, D, Raine, J, Rawling, J, Roberts, R, Schweiger, H, Shaw, S, Tomlinson, L, Watts, S, Wilk, F, Woudstra, M, Wyatt, T & ATLAS Collaboration 2017, 'Jet reconstruction and performance using particle flow with the ATLAS Detector', European Physical Journal C. Particles and Fields, vol. 77. https://doi.org/10.1140/epjc/s10052-017-5031-2

TY - JOUR

T1 - Jet reconstruction and performance using particle flow with the ATLAS Detector

AU - Bethani, Agni

AU - Connelly, Steven

AU - Bielski, Rafal

AU - Cox, Brian

AU - Da Via, Cinzia

AU - Dann, Nicholas

AU - Forcolin, Giulio

AU - Forti, Alessandra

AU - Iturbe Ponce, Julia

AU - Loebinger, Frederick

AU - Marsden, Stephen

AU - Masik, Jiri

AU - Menary, Stephen

AU - Munoz Sanchez, Francisca

AU - Oh, Alexander

AU - Ospanov, Rustem

AU - Peters, Yvonne

AU - Pilkington, Andrew

AU - Pin, Arnaud

AU - Price, Darren

AU - Raine, John

AU - Rawling, Jacob

AU - Roberts, Rhys

AU - Schweiger, H.

AU - Shaw, Savanna

AU - Tomlinson, Lee

AU - Watts, Stephen

AU - Wilk, Fabian

AU - Woudstra, Martin

AU - Wyatt, Terence

AU - ATLAS Collaboration

PY - 2017/7/13

Y1 - 2017/7/13

N2 - This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb −1−1 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

AB - This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb −1−1 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

U2 - 10.1140/epjc/s10052-017-5031-2

DO - 10.1140/epjc/s10052-017-5031-2

M3 - Article

SN - 1434-6044

VL - 77

JO - European Physical Journal C. Particles and Fields

JF - European Physical Journal C. Particles and Fields

ER -

Jet reconstruction and performance using particle flow with the ATLAS Detector

Abstract

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