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Impact of Dead LAr Calorimeter Cells and FEBs on Electron Trigger Efficiencies

Impact of Dead LAr Calorimeter Cells and FEBs on Electron Trigger Efficiencies. Andrew Lowe Royal Holloway, University of London. Overview. Benchmarking with single electrons First look at results with double-object trigger

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Impact of Dead LAr Calorimeter Cells and FEBs on Electron Trigger Efficiencies

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  1. Impact of Dead LAr Calorimeter Cells and FEBs onElectron Trigger Efficiencies Andrew Lowe Royal Holloway, University of London

  2. Overview • Benchmarking with single electrons • First look at results with double-object trigger • First look at impact of dead cells and FEBs on efficiency to trigger on H  ZZ(*)  4e Andrew Lowe, RHUL

  3. Introduction (1) • The effect of dead (unresponsive) cells and Front End Boards (FEBs) in the LAr calorimeter on electron selection efficiencies was studied • Expect that: dead cells/FEBs  incorrect reconstruction of cluster energies  e/ fail to pass cuts  trigger selection efficiency decreases  loss of events that would otherwise be part of subsequent physics analysis Right: granularity of EM calorimeter samplings Andrew Lowe, RHUL

  4. Introduction (2) Left: “exploded” view of Front End Crate Right: Front End Crates mounted on the end of the barrel cryostat Andrew Lowe, RHUL

  5. Method • Reconstruction using offline release 8.0.2 • Changes made to LAr reconstruction to randomly kill cells/FEBs • Assume dead cells to be uniformly distributed in LAr EM calorimeter (yields average of all possible configurations of dead cells) • 0, 0.1, 0.2, 0.5, 1.0, 2.0 and 5.0 percent dead cells/FEBs simulated (1% reflects estimates of dead cells/FEBs that may be expected) • No smart corrections (to correctly reconstruct energy) applied • All samplings treated equally • Configuration of dead cells/FEBs changes every event to avoid bias from “lucky/unlucky” distributions • Examine trigger efficiencies as a function of the percentage of dead cells/FEBs using (ROOT-based) e/ Analysis Framework • TrigEgammaAnalysis-00-00-04-13 (note: this is a branch of 00-00-04) Andrew Lowe, RHUL

  6. Electron trigger selection • The trigger efficiencies for single electrons were calculated for a geometrical and kinematical acceptance region defined as follows: • At least 1 electron with ||<2.5 (region of precision physics) • With 15.0 < PT < 50.0 GeV • Not in EMB-EMEC crack region (1.37-1.52) • No LVL2 tracking cuts applied • Problem with IDScan (missing tracks) • No TRT cuts are applied at Event Filter • TRT reconstruction known to have had problems Andrew Lowe, RHUL

  7. Results with single electrons • Trigger efficiencies ε for e25i and 2e15i trigger • First attempt at 2e15i • DC1 data • Comparison with published results in TDR and elsewhere (V. Perez-Reale, “Triggering Standard Model Higgs processes in the ATLAS Detector”, Czechoslovak Journal of Physics, Vol. 54 (2004), Suppl. A) • Close match for e25i • Not so good match for 2e15i • Comparison with results obtained using offline release 6.0.4 and 8.0.2 reconstructed events • Differences are due to changes in reconstruction between offline releases Andrew Lowe, RHUL

  8. Higgs trigger selection • The trigger efficiencies for Higgs samples were calculated for a geometrical and kinematical acceptance region defined as follows: • At least 2 electrons with ||<2.5 and PT>20GeV • At least 2 additional electrons with ||<2.5 and PT>7GeV • Assume discrepancy in results is due to geometrical and kinematical cuts • Expect geometrical acceptance (percentage of events that have 4 electrons with ||<2.5) = ~ 47% and overall trigger efficiency (no geometrical or kinematical requirement for events) = ~45.8% (Valeria Perez-Reale, “ATLAS: Triggering for Higgs”, Physics at LHC, 13-17 July 2004, Vienna) • Calculated geometrical acceptance: 91.2% • Calculated geometrical and kinematical acceptance: 72.8% • Calculated overall trigger efficiency: 88.7 ± 0.3% (c.f. 91.7%) Andrew Lowe, RHUL

  9. Results with Higgs events • HZZ(*)4e, MH=130GeV • Trigger efficiencies ε for e25i and 2e15i trigger • DC1 data • Note that LAr and tile calo noise was not switched during reconstruction of Higgs events with offline release 8.0.2 • Not expected to a large effect on results • Will shortly have data with noise on • Difference between new and published results that cannot be accounted for by statistical errors Andrew Lowe, RHUL

  10. Efficiency of e25i trigger to select HZZ4e (MH=130 GeV) vs. dead cell fraction Andrew Lowe, RHUL

  11. Efficiency of e25i trigger to select HZZ4e (MH=130 GeV) vs. dead FEB fraction Andrew Lowe, RHUL

  12. Efficiency of 2e15i trigger to select HZZ4e (MH=130 GeV) vs. dead cell fraction Andrew Lowe, RHUL

  13. Efficiency of 2e15i trigger to select HZZ4e (MH=130 GeV) vs. dead FEB fraction Andrew Lowe, RHUL

  14. Efficiency of e25i trigger to select HZZ4e vs. Higgs mass Andrew Lowe, RHUL

  15. Efficiency of 2e15i trigger to select HZZ4e vs. Higgs mass Andrew Lowe, RHUL

  16. Conclusions • e/ Analysis Framework • Single electrons • e25i trigger yields results that closely match published figures • 2e15i trigger needs honing to get better results • Higgs samples • Discrepancy between results and published figures for both triggers that cannot be accounted for by statistical errors • Suspect there is a problem with geometrical and/or kinematical cuts applied at Monte Carlo level • Observe expected increase in efficiency to trigger on Higgs events as the mass of the Higgs increases • Efficiency to trigger on Higgs events decreases linearly by ~1% per 1% increase in the fraction of unresponsive cells or FEBs • Future work • Improve 2e15i trigger • Determine source of discrepancy in results with Higgs data • Calculate results with e25i OR 2e15i • Obtain results using 180 and 300 GeV Higgs Andrew Lowe, RHUL

  17. Backup slide • Scan of 7-80 GeV single electrons, e25i trigger • Efficiency has a flat distribution for high PT Andrew Lowe, RHUL

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