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

This study analyzes linearity, resolution, and tails of performance in different data samples in ATHENA. It includes analysis on Rome and CSC data, assessment of missing ET reconstruction and calibration, and comparison of various CSC data samples. Notable focus is on performance stability in CSC data, reduction of tails, calibration refinements, and future plans for improvement.

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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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