Several Standard Model processes present electrons in the final state. Also, many signatures expected from physics beyond the Standard Model include one or more electrons. This paper describes the electron reconstruction along with some of the identification criteria used in the ATLAS detector. The expected performances at the start-up of the experiment are also presented

Arnaez, O

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ATL-PHYS-PROC-2009-11801October2009Electron Reconstruction and Identification withthe ATLAS DetectorO. Arnaez on behalf of the ATLAS collaborationLAPP, Université de Savoie, CNRS/IN2P3, Annecy-le-Vieux, FranceAbstract. Several Standard Model processes contain electrons in the final state. Also, many sig-natures expected from physics beyond the Standard Model include one or more electrons. Thispaper describes the electron reconstruction along with some of the identification criteria used in theATLAS detector. The expected performance at the start-up of the experiment are also presented.Keywords: ATLAS, LHC, electron, reconstruction, identification, track, shower, electromagneticPACS: 01.30.Cc, 29.40.Vj, 29.40.GxINTRODUCTIONThe LHC nominal center-of-mass energy being 14 TeV, a wide variety of known physicsprocesses -J/ψ , Y, W/Z, heavy flavour decays- and potentially new physics processeswill produce electrons in a wide energy range from a few GeV up to a few TeV. Atthe nominal luminosity (1034cm−2s−1) the inelastic event rate will be about 600 millionper second. Thus it is expected to see a huge number of jets and pile-up events fakingelectrons. Hence, it is important to have a robust method for the reconstruction andefficient criteria for the identification of the electrons.THE ELECTRON RECONSTRUCTIONThe reconstruction of the electrons in ATLAS relies on the signal produced by two sub-detectors : the inner detector tracker and the electromagnetic calorimeter[1].The former is composed of a pixel detector, a silicon microstrip (SCT) and a transitionradiation (TRT) trackers enclosed in a 2T magnetic field. The reconstruction of the trackscovers a large precision region in pseudo-rapidity, up to η < 2.5. The latter is a Pb/LArcalorimeter with accordion geometry segmented in three layers (“strips”, “middle” and“back”) allowing to measure the longitudinal extension of the electromagnetic shower,preceded by a thin presampler to estimate the energy loss in the upstream material.The reconstruction of electrons usually starts by the independent reconstructions oftracks from the hits in the inner detector and electromagnetic clusters from the cellsin the calorimeter.The tracks reconstruction involves the inside-out algorithm starting from seeds in thepixel/SCT layers and finding hits in the TRT and the back-tracking algorithm startingfrom hits in the TRT and extrapolating them to the SCT and the pixel layers. Both al-gorithms use track fitters taking into account the fraction of energy radiated in the innerdetector by bremsstrahlung process.The reconstruction of electromagnetic clusters uses a sliding-window algorithm. It con-sists of mapping the calorimeter cells into η = 0.025 towers and in moving a windowof 5x5 towers on this grid. A cluster seed is found when the transverse energy in thewindow is greater than 3 GeV. A cluster with a size corresponding to 3x7 cells in themiddle layer is then formed and its position is refined. Different corrections are appliedto the cluster position and energy in order to take into account the variation with the par-ticle impact position (S-shape and energy containment along η and accordion geometryeffect along φ ). Also, in the transition region between the barrel and end-cap parts of thecalorimeter (1.37 < η < 1.52), a specific correction is applied. Finally, the calibrationbetween the different calorimeter layers leads to the application of longitudinal weightsaccounting for the energy scale (λ ), loss of energy in the upstream/dead material (m andW0) and the longitudinal leakage (W3) as follows :Erec = λ (m+W0EPS+Estrips+Emiddle+W3Eback) (1)These coefficients are η-dependent (following the upstream material distribution) andare precisely determined from the full simulation of the detector. Such a reconstructionmechanism gives a linearity of the calorimeter response which is better than 1% over the20-500 GeV energy range with the energy resolution depicted in Figure 1.After their extrapolation to the strips and middle samplings of the calorimeter, tracks arematched to the cluster using |∆ηtrk/strips|< 0.05 and−0.1 < sign(q)∆φtrk/middle < 0.05,the asymmetry accounting for the bremsstrahlung. In a busy environment where multipletracks can be associated to one cluster, the association is done with the track giving theratio Ecluster/ptrk closest to 1.Energy (GeV)0 100 200 300 400 500Linearity-0.01-0.008-0.006-0.004-0.00200.0020.0040.0060.0080.01| = 0.3η|| = 2.0η|ATLAS|η|0 0.5 1 1.5 2 2.5Relative resolution00.010.020.030.040.050.060.070.080.093x7 Barrel 5x5 Ecap 100GeV eγ3x5 Barrel 5x5 Ecap 100GeV ATLASFIGURE 1. Left: Linearity of the energy response of the calorimeter vs energy of the incoming electron.Right: Relative energy resolution vs pseudorapidity η for 100 GeV electrons (black).ELECTRON IDENTIFICATIONAt the LHC, QCD processes will dominate and jets -as they produce tracks and depositenergy in the electromagnetic calorimeter- will fake electrons. At this stage, the trueelectron fraction (purity) is expected to be O(10−5). Variables reflecting the showershape in the calorimeter, the track quality, tight constraints on the track-cluster matchingand identification techniques using the TRT capabilities are needed to separate the trueelectrons from the fakes.The electron and jet showers exhibit significant differences. Using the segmentation andthe thin granularity of the calorimeter, jets will be seen broader (see Figure 2, left) andhave more leakage in the hadronic calorimeter than electrons.Width(S1)0 1 2 3 4 5 6a.u.00.010.020.030.040.050.060.07SignalBackgroundATLAS|η|0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2Pion efficiency-310-210-110190% Electron efficiency95% Electron efficiencyATLASFIGURE 2. Left: Distributions representing the shower width in the strip layer for the signal electrons(red) and the QCD fakes background (black). Right: Pion efficiency vs η for 90% and 95% efficiency on25 GeV electrons.With the ratio of high-threshold hits and the time-over-threshold, the TRT also pro-vides capabilities to separate pions and electrons as shown in Figure 2 (right).Finally, the quality of the track (number of hits in the pixel, SCT and TRT layers) and ofthe track-cluster association can be used to further reduce the background.Based on these variables, different sets of cuts -“Loose”, “Medium” and “Tight”- used toidentify electrons are defined with gradual rejection power. The expected efficiencies forelectrons for the different sets and the level of expected contamination by fakes after theTight cuts are shown in Figure 3. A rejection factor of 105 is achieved and for ET > 30GeV, the signal-over-background ratio for isolated electron is about 1.EFFICIENCY MEASUREMENTSIt is important to measure the electron efficiencies from data in order not to rely on MCpredictions for the detector response. The reconstruction and identification efficienciescan be measured using the so-called “tag-and-probe” method with Z→ ee events.The idea is to select electron pairs with invariant mass close to MZ and tight cuts on thefirst electron (called tag electron) in order to have high signal-to-background ratio in thesample. The efficiency of various cuts can be measured on the second electron (calledprobe electron). The ratio of probes passing the cuts over the total number of probesconsidered directly provides the efficiency of the tested cuts.Figure 4 shows a good agreement between identification efficiencies obtained from theMonte Carlo truth and the ones measured using tag-and-probe.|η|0 0.5 1 1.5 2 2.5Electron-ID efficiency00.20.40.60.811.2TightMediumLooseATLAS (GeV)TE0 20 40 60 80 100 per GeV-1Events per 100 pb310410510610Jets W,Z->eb,c->eATLASFIGURE 3. Left: Electron identification efficiency as a function of eta for electrons with ET > 5 GeVfrom H → eeee decays. Right: Differential cross-sections as a function of ET after tight cuts, shownseparately for various sources of isolated electrons, non-isolated electrons and residual jet background,for an integrated luminosity of 100 pb−1 and for the simulated with ET > 17 GeV di-jet sample.FIGURE 4. Efficiency of the electron reconstruction as a function of |η | (left) and ET (right) for Z→ eedecays, using the tag-and-probe method and the Monte Carlo truth information. Errors are statistical andcorrespond to an integrated luminosity of 100 pb−1.CONCLUSIONGood performance can be achieved with the ATLAS detector using robust reconstructionand identification methods. First collisions will soon be used to measure efficiencies, toimprove the performance and to tune the Monte Carlo before using electrons to performprecision measurements and (re-)discoveries.REFERENCES1. The ATLAS Collaboration, Expected Performance of the ATLAS Experiment - Detector, Trigger andPhysics, arXiv:0901.0512, 2009

Electron Reconstruction and Identification with the ATLAS Detector

International audienceSeveral Standard Model processes present electrons in the final state. Also, many signatures expected from physics beyond the Standard Model include one or more electrons. This paper describes the electron reconstruction along with some of the identification criteria used in the ATLAS detector. The expected performances at the start-up of the experiment are also presented

Electron Reconstruction and Identification with the ATLAS Detector

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