Performance of algorithms that reconstruct missing transverse momentum in \(\sqrt{s}\) = 8 TeV proton–proton collisions in the ATLAS detector

The European Physical Journal C, Apr 2017

The reconstruction and calibration algorithms used to calculate missing transverse momentum (\(E_{\text {T}}^{\text {miss}}\) ) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the \(E_{\text {T}}^{\text {miss}}\) reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisions at a centre-of-mass energy of 8 \(\text {TeV}\) during 2012, and results are shown for a data sample corresponding to an integrated luminosity of \(20.3\, \mathrm{fb}^{-1}\). The simulation and modelling of \(E_{\text {T}}^{\text {miss}}\)  in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for \(E_{\text {T}}^{\text {miss}}\) , and estimates of the systematic uncertainties in the \(E_{\text {T}}^{\text {miss}}\)  measurements are presented.

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Performance of algorithms that reconstruct missing transverse momentum in \(\sqrt{s}\) = 8 TeV proton–proton collisions in the ATLAS detector

Eur. Phys. J. C Performance of algorithms that reconstruct missing transverse √ momentum in s = 8 TeV proton-proton collisions in the ATLAS detector ATLAS Collaboration 0 0 CERN , 1211 Geneva 23 , Switzerland 1 Also at Department of Physics, California State University , Fresno, CA , USA 2 Also at TRIUMF , Vancouver, BC , Canada 3 Also at Department of Physics and Astronomy, University of Louisville , Louisville, KY , USA 4 Also at Institute of Physics, Azerbaijan Academy of Sciences , Baku , Azerbaijan 5 Also at Novosibirsk State University , Novosibirsk , Russia 6 Also at Department of Physics, King's College London , London , UK The reconstruction and calibration algorithms used to calculate missing transverse momentum (ETmiss) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton-proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the E miss reconT struction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton-proton collisions at a centre-of-mass energy of 8 TeV during 2012, and results are shown for a data sample corresponding to an integrated luminosity of 20.3 fb−1. The simulation and modelling of E miss in events containing a Z boson decaying T to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for E miss, and estimates of T the systematic uncertainties in the E miss measurements are T presented. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . 2 ATLAS detector . . . . . . . . . . . . . . . . . . . . 3 Data samples and event selection . . . . . . . . . . . 3.1 Track and vertex selection . . . . . . . . . . . . . 3.2 Event selection for Z → . . . . . . . . . . . . 3.3 Event selection for W → ν . . . . . . . . . . . 3.4 Monte Carlo simulation samples . . . . . . . . . 4 Reconstruction and calibration of the E miss . . . . . . T 4.1 Reconstruction of the E miss . . . . . . . . . . . . T 4.1.1 Reconstruction and calibration of the E miss T hard terms . . . . . . . . . . . . . . . . . . 4.1.2 Reconstruction and calibration of the E miss soft T term . . . . . . . . . . . . . . . . . . . . . 4.1.3 Jet pT threshold and JVF selection . . . . 4.2 Track E miss . . . . . . . . . . . . . . . . . . . . T 5 Comparison of E miss distributions in data and MC T simulation . . . . . . . . . . . . . . . . . . . . . . . 5.1 Modelling of Z → events . . . . . . . . . . . 5.2 Modelling of W → ν events . . . . . . . . . . 6 Performance of the E miss in data and MC simulation . T 6.1 Resolution of E miss . . . . . . . . . . . . . . . . T 6.1.1 Resolution of the E miss as a function of T the number of reconstructed vertices . . . . 6.1.2 Resolution of the ETmiss as a function of ET 6.2 The E miss response . . . . . . . . . . . . . . . . T 6.2.1 Measuring E miss recoil versus pTZ . . . . . T 6.2.2 Measuring E miss response in simulated T W → ν events . . . . . . . . . . . . . . 6.3 The E miss angular resolution . . . . . . . . . . . T 6.4 Transverse mass in W → ν events . . . . . . . 6.5 Proxy for ETmiss significance . . . . . . . . . . . 6.6 Tails of E miss distributions . . . . . . . . . . . . T 6.7 Correlation of fake E miss between algorithms . . T 7 Jet- pT threshold and vertex association selection . . . 8 Systematic uncertainties of the soft term . . . . . . . 8.1 Methodology for CST . . . . . . . . . . . . . . . 8.1.1 Evaluation of balance between the soft term and the hard term . . . . . . . . . . . 8.1.2 Cross-check method for the CST system atic uncertainties . . . . . . . . . . . . . . 8.2 Methodology for TST and Track E miss . . . . . . T 8.2.1 Propagation of systematic uncertainties . . 8.2.2 Closure of systematic uncertainties . . . . . 8.2.3 Systematic uncertainties from tracks inside jets . . . . . . . . . . . . . . . . . . . . . 9 Conclusions . . . . . . . . . . . . . . . . . . . . . . Appendix . . . . . . . . . . . . . . . . . . . . . . . . . A. Calculation of EJAF . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . 1 Introduction 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle ar (...truncated)


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Campana, M. Campanelli. Performance of algorithms that reconstruct missing transverse momentum in \(\sqrt{s}\) = 8 TeV proton–proton collisions in the ATLAS detector, The European Physical Journal C, 2017, pp. 241, Volume 77, Issue 4, DOI: 10.1140/epjc/s10052-017-4780-2