Determination of jet calibration and energy resolution in proton–proton collisions at √ s = 8 TeV using the ATLAS detector

• Author(s): Santos, S. P. Amor dos ; Fiolhais, M. C. N. ; Veloso, F. ; Galhardo, B. ; Wolters, H. ; ATLAS Collaboration
• Date: 2020
• Persistent ID: https://hdl.handle.net/10316/106068
• Origin: Estudo Geral - Universidade de Coimbra
• Document Type: Journal article
• Language: English

Description

The jet energy scale, jet energy resolution, and their systematic uncertainties are measured for jets reconstructed with the ATLAS detector in 2012 using proton– proton data produced at a centre-of-mass energy of 8 TeV with an integrated luminosity of 20 fb−1. Jets are reconstructed from clusters of energy depositions in the ATLAS calorimeters using the anti-kt algorithm. A jet calibration scheme is applied in multiple steps, each addressing specific effects including mitigation of contributions from additional proton–proton collisions, loss of energy in dead material, calorimeter non-compensation, angular biases and other global jet effects. The final calibration step uses several in situ techniques and corrects for residual effects not captured by the initial calibration. These analyses measure both the jet energy scale and resolution by exploiting the transverse momentum balance in γ +jet, Z +jet, dijet, and multijet events.Astatistical combination of thesemeasurements is performed. In the central detector region, the derived calibration has a precision better than 1% for jets with transverse momentum 150 GeV < pT < 1500 GeV, and the relative energy resolution is (8.4 ± 0.6)% for pT = 100 GeV and (23 ± 2)% for pT = 20 GeV. The calibration scheme for jets with radius parameter R = 1.0, for which jets receive a dedicated calibration of the jet mass, is also discussed.

We 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 and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR, China; ISF 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, Russia 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, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; ERC, ERDF, Horizon 2020, Marie Skłodowska-Curie Actions and COST, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR,France;DFGandAvHFoundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya and PROMETEOProgramme GeneralitatValenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. 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), CCIN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NLT1 (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. [73].