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Silicon Tracking for Forward Electron Identification at CDF

Silicon Tracking for Forward Electron Identification at CDF. David Stuart, UC Santa Barbara Oct 30, 2002. Outline. Motivation and History CDF Run II upgrade Forward Tracking algorithm Physics Prospects. In Run 1, CDF had tracking only in central region.

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Silicon Tracking for Forward Electron Identification at CDF

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  1. Silicon Tracking for ForwardElectron Identificationat CDF David Stuart, UC Santa Barbara Oct 30, 2002

  2. Outline • Motivation and History • CDF Run II upgrade • Forward Tracking algorithm • Physics Prospects

  3. In Run 1, CDF had tracking only in central region

  4. Physics beyond |h|=1 e.g., look at h of e in Z  e+e- |h|<1 =50% |h|<2 = 83% …but what matters is finding both e+ and e-…

  5. What is h of maxh e in Z  e+e- |h|<1 =25% |h|<2 = 70% ET > 20 GeV

  6. More central at high mass, e.g. 800 GeV/c2 Z e+e- |h|<1 =53% |h|<2 = 90%

  7. Plug Electron ID in Run 1 • Some plug e ID • Had/EM < 0.05 • Isolation < 0.1 • VTX Occupancy

  8. …but poor purity even in di-electron case One electron with |h|<1 and one with |h|>1, S:B ~ 1 Two electrons with |h|<1, S:B ~ 20

  9. Silicon tracking coverage to higher h

  10. Using forward silicon hits in Run 1 • Stand-alone silicon pattern recognition • Fit for f0, d0, pT (curvature) • with 4 hits, <=1 dof. • It worked, but was limited by • lever arm (L2) • Too few hits • Poor curvature resolution degraded • impact parameter resolution • 4% relative increase in b-tagging for top

  11. Using forward silicon hits in Run 1 • Calorimeter-seeded tracking for electrons • Constrains pT and f0 • Adds 1 d.o.f. • Used same pattern recognition as standard outside-in tracking • But, lever arm still too small to measure curvature, just an initial direction so you have to rely on the calorimeter’s position measurement.

  12. eeggET event

  13. eeggET event

  14. Significant Improvements for Run II ISL SVXII L00 SVX’ (Run 1)

  15. Intermediate Silicon Layers for Run II 5 m2 of silicon

  16. Performance goals • 8 layers over 30cm lever arm • 3x the lever arm • At 30 cm occupancy is low enough to attach • single hits with minimal ambiguity because a • typical jet, ~10 tracks in a Df<0.2 cone, • covers 1000 channels

  17. Performance goals • 8 layers over 30cm lever arm • Sufficient pT resolution to • Determine d0 • Determine charge • over a large pT • range

  18. Performance goals 2trk COT res • 8 layers over 30cm lever arm • Sufficient pT resolution • Sufficient pointing resolution • into COT to pick up more hits • < 2 track resolution for ~ all pT • ~ hit resolution for pT>10 GeV • rz view is also comparable • This will allow stand-alone, • inside-out tracking once we • reach design resolution.

  19. Silicon Commissioning in progress

  20. Alignment in progress • Global ~finished • Internal starting But, even with a rough alignment we are now tracking forward electrons with a calorimeter seeded approach similar to the original Run 1 algorithm.

  21. Forward Electron Tracking Algorithm • Form 2 seed tracks, • one of each sign, • from calorimeter & beam spot

  22. Forward Electron Tracking Algorithm • Form 2 seed tracks, • one of each sign, • from calorimeter & beam spot • Project into silicon • and attach hits using • standard silicon pattern recognition

  23. Forward Electron Tracking Algorithm • Form 2 seed tracks, • one of each sign, • from calorimeter & beam spot • Project into silicon • and attach hits using • standard silicon pattern recognition • Select best c2match

  24. Plug Alignment Align plug to COT using the subset of COT tracks which match plug electrons just above |h|=1. Then align silicon to the COT. COT Plug

  25. Plug Alignment

  26. Plug Alignment

  27. Measured using Z -> e+e- with one “leg” in the central to reduce background and identify charge Performance • Efficiency • Fake Rate • Charge MisId

  28. Performance • Efficiency • ~80% in Monte Carlo • ~30% in data due to remaining • commissioning effects • Improvements coming.

  29. Performance • Efficiency • Fake Rate • …In progress… • In addition to the standard • techniques, we are pursuing • a silicon occupancy • measure.

  30. Performance • Efficiency • Fake Rate • Charge MisId • Comparable to COT for |h|<1 • because of CES resolution and • lever arm. • ~ 10% for 1<|h|<2 • Barely “non-random” • for |h|>2

  31. Future Improvements • Alignment • For |h|>2, need full • silicon and PES • resolution to determine • charge. • Meanwhile, can improve • with seed covariance pulls

  32. Future Improvements • Alignment • 3D hits

  33. Future Improvements • Alignment • 3D hits • Adding COT hits • 1 axial layer to |h|~1.6 • 1 stereo layer to |h|~2.0

  34. Future Improvements • Alignment • 3D hits • Adding COT hits • Muons • IMU coverage to |h|=1.5 • fully within ISL and >= 1 • axial COT superlayer • Momentum constraint becomes • asymmetric but still powerful.

  35. Future Improvements • Alignment • 3D hits • Adding COT hits • Muons • Level 3 Trigger • Silicon outside-in tracking • for L3 will be ready soon. • CAL seeded tracking • is then a small, fast, addition

  36. Impact on acceptance Single electron case Gain, |h|<3 v.s. |h|<1 With ~eff Ideal

  37. Impact on acceptance Multi electron modes Gain, |h|<3 v.s. |h|<1 With ~eff Ideal top Z WW ZZ WZ HWW Z (800)

  38. Our first step was using this for tracking Z  e+e- with both e± in the plug.

  39. Now measuring charge asymmetry in W ± e ±n

  40. ~30 pb-1 processed so far

  41. Cross-check to COT in the central

  42. Improvements beyond statistics At highest h, error currently dominated by charge ID Adding COT hits will significantly improve this.

  43. Conclusion Calorimeter seeded algorithm implemented Promising gains in acceptance W asymmetry despite low luminosity Electron ID is moving forward in Run II

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