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

ATLAS Collaboration , Fabrice Balli, Sarah Barnes, Brian Cox, Cinzia Da Via, Alessandra Forti, Julia Iturbe Ponce, Kiran Joshi, Houry Keoshkerian, Xingguo Li, Frederick Loebinger, Stephen Marsden, Jiri Masik, Francisca Munoz Sanchez, Thomas Neep, Alexander Oh, Rustem Ospanov, Joleen Pater, Yvonne Peters, Andrew PilkingtonArnaud Pin, Darren Price, Yang Qin, Michaela Queitsch-Maitland, Christian Schwanenberger, H. Schweiger, Savanna Shaw, R. Thompson, Lee Tomlinson, Stephen Watts, Samuel Webb, Martin Woudstra, Terence Wyatt

    Research output: Contribution to journalArticlepeer-review

    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.
    Original languageEnglish
    JournalEuropean Physical Journal C. Particles and Fields
    Early online date24 Jul 2017
    DOIs
    Publication statusPublished - 2017

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