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

By G. Aad, B. Abbott, J. Abdallah, O. Abdinov, R. Aben, M. Abolins, O. AbouZeid, H. Abramowicz, H. Abreu, R. Abreu and 2,837 more. European Physical Journal C: Particles and Fields, 2016

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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.

Subfields: Nuclear and High Energy Physics

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Citations in the corpus

Evidence for the associated production of the Higgs boson and a top quark pair with the ATLAS detector (2017, neutral): “[82] ATLAS Collaboration, Topological cell clustering in the”
Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at √s=13 TeV with the ATLAS detector (2017, neutral): “A collection of three-dimensional, massless, positive-energy topological clusters (topo-clusters) [12, 13] made of calorimeter cell energies are used as input to the anti-kt algorithm.”
Combined measurements of Higgs boson production and decay using up to $80$ fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=$ 13 TeV collected with the ATLAS experiment (2019, neutral): “The only significant change concerns the reconstruction of the calorimeter energy clusters associated with the photons; a dynamical, topological cell clusteringbased algorithm [124,125] is now used instead of a slidingwindow technique [123,126].”
Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report (2017, neutral): “2 Pile-up mitigation in jet reconstruction The jet reconstruction in the two multi-purpose experiments at the LHC uses particle-flow objects in CMS [969] and clusters of topologically connected calorimeter cell signals (topoclusters) in ATLAS [970].”
Jet reconstruction and performance using particle flow with the ATLAS Detector (2017, positive): “2 is related to the worse performance of the particle flow algorithm in the transition region between the barrel and extended barrel of the Tile calorimeter, which is significantly affected by pile-up contributions [3].”
Measurement of the Inelastic Proton-Proton Cross Section at root s=13 TeV with the ATLAS Detector at the LHC (2016, positive): “Over the full coverage of the MBTS counters, the calorimeter is used to measure the counter efficiency with respect to particles that deposit sufficient energy in the calorimeter to seed a topological energy cluster [38].”
Measurements of Higgs boson properties in the diphoton decay channel with 36 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 13$ TeV with the ATLAS detector (2018, positive): “The calorimeter isolation is computed as the sum of the transverse energies of positive-energy topological clusters [74] in the calorimeter within a cone of ∆R = 0.”
Jet substructure at the Large Hadron Collider (2018, positive): “ATLAS and CMS combine calorimeter cells using topological clusters [53, 55].”
Performance of the ATLAS muon triggers in Run 2 (2020, positive): “Jets are reconstructed from topological clusters of energy deposits in calorimeter cells [29] with the anti-kt algorithm [30] with a radius parameter of 0.”