Jet reconstruction and performance using particle flow with the ATLAS Detector

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dc.contributor.authorAaboud, M.
dc.contributor.authorAlbert, Justin
dc.contributor.authorChiu, Y. H.
dc.contributor.authorElliot, Alison A.
dc.contributor.authorFincke-Keeler, J.
dc.contributor.authorHamano, Kenji
dc.contributor.authorHill, Ewan Chin
dc.contributor.authorKeeler, Richard
dc.contributor.authorKowalewski, Robert
dc.contributor.authorKuwertz, E. S.
dc.contributor.authorKwan, Tony
dc.contributor.authorLeBlanc, Matthew Edgar
dc.contributor.authorLefebvre, Michel
dc.contributor.authorMcPherson, Robert A.
dc.contributor.authorPearce, James D.
dc.contributor.authorSeuster, Rolf
dc.contributor.authorSobie, Randall J.
dc.contributor.authorTrovatelli, M.
dc.contributor.authorVenturi, M.
dc.contributor.authorATLAS Collaboration
dc.date.accessioned2020-02-14T01:00:51Z
dc.date.available2020-02-14T01:00:51Z
dc.date.copyright2017en_US
dc.date.issued2017
dc.description.abstractThis 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.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipWe thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; SRNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, UK. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [66].en_US
dc.identifier.citationAaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; … & Zwalinski, L. (2017). Jet reconstruction and performance using particle flow with the ATLAS Detector. The European Physical Journal C, 77(7), article 466. DOI: 10.1140/epjc/s10052-017-5031-2en_US
dc.identifier.urihttps://doi.org/10.1140/epjc/s10052-017-5031-2
dc.identifier.urihttp://hdl.handle.net/1828/11556
dc.language.isoenen_US
dc.publisherThe European Physical Journal Cen_US
dc.titleJet reconstruction and performance using particle flow with the ATLAS Detectoren_US
dc.typeArticleen_US

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