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Performance (linearity, resolution, tails) studied on: -- Rome data Many different samples

EtMiss in ATHENA: Status and Performance. Performance (linearity, resolution, tails) studied on: -- Rome data Many different samples -- CSC data Z   sample 5148 (25Kevts) J2/J4/J5/J6/J7 samples 5011/13/14/15/16 (89Kevts)

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Performance (linearity, resolution, tails) studied on: -- Rome data Many different samples

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  1. EtMiss in ATHENA: Status and Performance • Performance (linearity, resolution, tails) studied on: -- Rome data • Many different samples -- CSC data • Z   sample 5148 (25Kevts) • J2/J4/J5/J6/J7 samples 5011/13/14/15/16 (89Kevts) • J4/J6/J7 Herwig/Jimmy samples 5033/35/36 (85kevts) • W  en sample 5100 (22Kevts) • SU3 sample 5403 (19Kevts) • top sample 5200 (43Kevts) D. Cavalli – S. Resconi

  2. EtMiss Reconstruction and Calibration in ATHENA MissingET All Calorimeter cells in ||<5 |Ecell | > 2(noise) H1-weights from jets OR OR OR Estimated energy loss in cryostat between LAr and Tile from reco jets (kT) w*sqrt(EM3*TILE1) from MOORE muons in || < 2.7 BestMatch /good quality MET_Final = MET_Calib + MET_Cryo + MET_ Muon Calorimeter cells in topoclusters 4/2/0 H1-weights from jets from MuonBoy muons in || < 2.7 from reco jets (cone07) Calorimeter cells in topoclusters 4/2/0 Em/HadClassification/LocalHadCalib Dead material correction Topoclusters 4/2/0 Em/HadClass/LocalHadCalib Dead material correction Refinement of Calibration for cells in different objects (e/g, t, ,jets...) D. Cavalli – S. Resconi

  3. Linearity vs EtMiss in Rome and CSC data D. Cavalli – S. Resconi

  4. Resolution vs SumET in CSC data Resolution depends on Noise suppression, Calibration, Dead material correction … physics channel topology, presence of leptons, activity out of coverage... D. Cavalli – S. Resconi

  5. Comparing different CSC data samples Top,SU3, Jets Njets pT leading jet pT next-to-leading jet SumET electrons EtMissout SumET-SumETjets-SumETele D. Cavalli – S. Resconi

  6. s(Ex(y)miss) vs SumET in CSC Jets data (Pythia and Herwig) D. Cavalli – S. Resconi

  7. EtMiss tails in CSC jets (J6) • EtMiss compare Truth,TruthMu, Moore Mu, MuonBoy Mu • |h| of the leading jet and of the next-to-leading jet when |EtMissTruth–EtMissTruthMu|>100 see Naoko talk next session  A special production to study fake EtMiss: QCD Jets and Z+jets with jets pointing to cracks with Dead material hits Tails due to fake muons reduced respect to Rome: Events with EtMiss>100Gev: EtMissTruth:582, EtMissTruthMu:1197, EtMissMoore:1246, EtMissMuonBoy:1197 F. Paige is looking in detail to events in tail D. Cavalli – S. Resconi

  8. Missing ET in Athena: Conclusions and future plans Performance in CSC data for EtMiss calculated from Topocluster cells similar to Rome data: • Linearity and Resolution stable using H1-weights from jets (CellWeightToolG4hack) • Tails reduced: Muon term improved respect to Rome No pathological cells discovered up to now • A special production foreseen to study fake EtMiss: QCD Jets and Z+jets with jets pointing to cracks next: • Topocluster Local HadronCalibration + Dead material correction very preliminar results:see Silvia talk this session • Refined (object based) calibration: very first implementation foreseen for 12.0.0 • jet samples: starting from jets navigate back to Topo and back to cells - apply jet depending weights to cells belonging to Topo inside a jet • for more complex events: can do after Event View, same as before, but for various different objects (e/g, taus, jets…) see Silvia talk next session D. Cavalli – S. Resconi

  9. Backup slides D. Cavalli – S. Resconi

  10. s(Ex(y)miss) vs SumET in CSC datafrom ATLFAST At high energy worsening of Atlfast EtMiss resolution Jet smearing in Atlfast:s(E)/E=0.5*sqrt(E) + 0.03 |h|<3.2 s(E)/E=1.0*sqrt(E) + 0.07 |h|>3.2 in central region costant term dominant when jet energy> 300GeV D. Cavalli – S. Resconi

  11. ETmiss Performance in 10.0.1: Ex(y)Miss Resol from TopoCluster vs SumET for SU1 Rome evts SumET >0 Moore muons Final Ex(y)miss Resol = p0 *  SumET Final EtMiss Resol =  fit ( MET_Truth ( NonInt ) – MET_Final ) Calo EtMiss Resol =  fit ( MET_Truth ( Int ) – MET_Calib+cryo ) Dete EtMiss Resol =  fit ( MET_Truth ( Int+Muonspl ) – MET_Final ) D. Cavalli – S. Resconi In TDR: p0 for Final ~ 0.46 (Z°   , A° )

  12. CSC top events: compare s(EtMiss) for events with electrons, muons, Noelectron or muon No ele or muons Electrons Muons D. Cavalli – S. Resconi

  13. EtMiss Performance in 10.0.1 Rome data : Tails SumET cut • dead/noisy/hot cells in calorimeters In Rome data pathological cells in LArg strips with very large negative or positive energy (only some samples and <3%) - problem not understood.. • Muons fake or double or badly measured In Rome data some % mostly in high pT jets - use good quality combined muons for EtMiss calculation • energy lost in dead material, cracks: study with CSC special production see Naoko talk this session • Beam gas and machine background, displaced vertexes... D. Cavalli – S. Resconi

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