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 journalArticlepeer-review


    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 languageEnglish
    JournalEuropean Physical Journal C. Particles and Fields
    Publication statusPublished - 13 Jul 2017


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