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Scientific Article
unige:96017 
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Jet reconstruction and performance using particle flow with the ATLAS Detector |
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| Collaboration | With : Ancu, Lucian Stefan / Benoit, Mathieu / Bilbao De Mendizabal, Javier / Calace, Noemi / Chatterjee, Avishek / Clark, Allan Geoffrey / Coccaro, Andrea / Delitzsch, Chris Malena / Della Volpe, Domenico / Ferrere, Didier / Golling, Tobias / Gonzalez Sevilla, Sergio / Gramling, Johanna Léna / Iacobucci, Giuseppe / Katre, Akshay / Khoo, Teng Jian / Lanfermann, Marie Christine / Lionti, Anthony Eric / March Ruiz, Luis / Mermod, Philippe / Nackenhorst, Olaf / Paolozzi, Lorenzo / Ristic, Branislav / Schramm, Steven / Sfyrla, Anna / Wu, Xin | |
| Published in | The European Physical Journal. C, Particles and Fields. 2017, vol. 77, no. 7, 466 | |
| Collection |
Open Access - SCOAP3 |
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| 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. | |
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| Citation (ISO format) | ATLAS COLLABORATION. Jet reconstruction and performance using particle flow with the ATLAS Detector. In: The European Physical Journal. C, Particles and Fields, 2017, vol. 77, n° 7, p. 466. doi: 10.1140/epjc/s10052-017-5031-2 https://archive-ouverte.unige.ch/unige:96017 |
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