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Search for t  t n q

Search for t  t n q. Fermilab March 28-29, 2006 Sarah Demers. Outline. Motivation CDF and the Tevatron Event Selection Tau Identification Result. The Standard Model. Encompasses 3 of 4 fundamental forces Fundamental particles: 6 quarks 6 leptons

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Search for t  t n q

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  1. Search for t t nq Fermilab March 28-29, 2006 Sarah Demers

  2. Outline • Motivation • CDF and the Tevatron • Event Selection • Tau Identification • Result

  3. The Standard Model • Encompasses 3 of 4 fundamental forces • Fundamental particles: • 6 quarks • 6 leptons • Interactions mediated by force carriers

  4. The Standard Model: What’s Missing? • Why are there three generations? • Why the large variation in quark masses? • Why is there so little antimatter in the universe? • What about gravity?

  5. Top quarks and tau leptons • The Higgs Boson • Extensions to the standard model may be needed • MSSM Charged Higgs: t -> H+b, H+ ->t+ntgives identical final state • Result from CDF Run 1 (mid-1990s) • Expected 3.2 events (0.7 signal events) with theoretical cross section • Found four events with three b tagged events • Need to improve signal to noise

  6. Top quarks and tau leptons • Experience with tau leptons in the environment of a hadron collider • Room for new physics • The “recently” discovered top quark • The heavy third generation

  7. The Tevatron

  8. The Tevatron (and the LHC)

  9. Fermilab’s Accelerators • Cockroft-Walton • Hydrogen gas ionized • Ions accelerated to 750 keV • Linac • 500 ft long • Oscillating electric fields accelerate protons to 400 MeV • Booster • Circular accelerator • Protons make 20,000 laps • Accelerated to 8 GeV

  10. Fermilab’s Accelerators • Main Injector • Accelerates protons and anti-protons to 150 GeV • Injects the particles into the Tevatron • Anti-protons • From 120 GeV proton beam extracted from the Main Injector • Tevatron • Accelerates to almost 1 TeV • Particles move only 200 mph slower than speed of light

  11. Chicago  Booster CDF DØ Tevatron p source Main Injector Collisions

  12. Detectors

  13. Event Selection: Decay Chain t t • top, anti-top events needed for statistics W+ W- b b t nt e/m ne/nm jet jet

  14. t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong) Final State

  15. t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong) Strategy for this analysis • First CDF Run II top t-specific analysis • Closely follow {e+m} dilepton analysis (but) • admit only the lowest background categories with tight, central electron and muon requirements • place a premium on ensuring non-tau top final states are excluded

  16. Event Selection Tau decay modes • Reconstructed tau passing all ID cuts, Et > 15 GeV t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong) CMS CR 2005/018

  17. t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong) Event Selection • Tau identification requirements • No impact parameter

  18. Event Selection • Corrected Missing Et greater than 20 GeV • Opposite sign tau and electron (muon) t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong)

  19. t t W+ W- b b nt t e/m ne/nm jet jet nt hadrons (1 or 3 prong) Event Selection • >= 2 jets, |h| < 2.0 • 1st jet > 25 GeV • 2nd jet > 15 GeV • Ht > 205 GeV • Z Mass veto

  20. Optimization • The HT and lead jet ET cuts are chosen by a formal optimization procedure • 2D optimization with MC signal & data+MC bkgnd • Minimize S/sqrt(B), the stat. uncertainty in Gaussian limit in “no signal observed” case • Maximize likelihood ratio: LS+B/LB

  21. Acceptance • Pythia Monte Carlo • Before scale factors: • eth : 50% • mth : 42% • teth : 4% • tmth : 4%

  22. W+ nt t Acceptance • 35% t ID efficiency from Monte Carlo • With W->tn, compare data to Monte Carlo

  23. Acceptance Summary 0.076 ± 0.005 (stat) ± 0.013 (sys) % • BR ~ 3% with ~2.5% efficiency • Expected signal: • 1.00 ± 0.06 ± 0.16 events • Expected background: • 1.29 ± 0.14 ± 0.21 events

  24. Background Summary

  25. jet t fakes • We measure the jet to tau fake rate in 4 datasets: • 20 GeV jet • 50 GeV jet • 70 GeV jet • Large total event Energy • Rates from 0.1% to 10%

  26. e t fakes • Measure e  tau fake rate in data with Z  ee • Electron veto variable • (HadE/SumP) shown for loose leg Zee • We calculate a (1.2±0.3)% etau fake rate at our 0.15 cut

  27. mt fakes • Zmm MC predicts background • Cross-check in data • Fakes are extremely rare, so data statistics only allow a cross-check • Agreement at level of 30%

  28. Ztt • First require f of missing energy, “taus”consistent with Ztt • Then reconstruct mass by assigning MET to “taus”

  29. Ztt • 65 GeV < Mass < 115 GeV • 88% reduction of BG, 4% reduction of signal

  30. The Result • We could report this result as a cross-section, as is done with other rate analyses • However, clearly this analysis has little to contribute to a cross-section average • The motivation for the analysis is a universality test • We quote:

  31. Conclusions • We predict 2.3 events and see 2 events. • We set a limit on: • rt < 5.2 at the 95% confidence level • Frequentist Method: profile likelihood (Rolke et al)

  32. Acknowledgements • Thank you to the Fermilab group for inviting me! • www-cdf.fnal.gov • www.fnal.gov • www.particleadventure.org • lhc.web.cern.ch/lhc/

  33. backup slides

  34. CDF (and CMS) • CMS Tracker • 25,000 Silicon Strip Censors • Total Area of 210 m2 • 9600000 readout channels • Crystal Electromagnetic Calorimeter • Sampling Hadronic Calorimeter with • copper Absorbing Plates • Trigger • Store ~100 events per second (out of 40 million +) • CDF Tracker • 405,504 silicon readout channels • Open cell drift chamber (30,240 readout channels) • Lead/Scintillator Sampling Electromagnetic Calorimeter • Iron/Scintillator Sampling Hadronic Calorimeter • Trigger • Three level system • ~8 ms decision time at Level 1

  35. Systematics

  36. Data • Fake t background from jets and electrons. • Electrons pass isolation cuts but fail electron veto (lower left corner) • Jets fill plot but tend to fail the track and p0 isolation

  37. Candidate events • Two events survive all cuts. • Jet 1 of Candidate 1 is tagged as a b quark jet.

  38. Jet Multiplicity • We have background predictions in hand • As an a priori test: • predict rates in 0 and 1 jet multiplicity bins(no HT or Z Mass cut) • did not look at 2+ jet bin until satisfied • result more likely than 41% of pseudoexperiments

  39. t identification cuts • Our t ID cuts are similar to other tau analysis • We have tighter a tighter calorimeter isolation cut • Our electron veto is bracketed by cuts in other analyses • Our W+jets background is reduced at the expense of reduced tau ID efficiency

  40. Optimization (cont’d) • 1D version, fixing ET(1) cut… HT Signal/Bkgnd HT HT HT Signal/SQRT(Bkgnd) Likelihood Ratio

  41. Optimization (cont’d) • HT and lead jet ET cuts can distinguish signal from background • Integral distributions above cuts shown HT HT Background Signal ET(1)

  42. Data Our cut CDF 6010 cut MC Wtn analysis t identification cuts • Tightening the calorimeter isolation cut is a concern because it is the worst modeled • Using the “tightt” sample fromCDF 6010, thisis a 5%(relative) scalefactor effect

  43. Acceptance • Pythia ttopei MC • N(tcand) includes jet fakes • Before scale factors: • eth : 50% • mth : 42% • teth : 4% • tmth : 4%

  44. Efficiencies and Scale Factors value CDF Note

  45. Systematics: Techniques • Jet Energy Corrections: • Level 5, half of difference between +1s and –1s • Monte Carlo Generator Dependence (half of difference): • ttop2e (pythia) with no QED FSR • weighted for BR ttopli (herwig) • ISR: ttopei (ISR on) compared to ttop0e (ISR off) • FSR: ttopei (tune A) compared to ttop5e (tune B) • Statistical uncertainty dominates

  46. Systematics • PDFs: Compare # expected events in ttopei with: • ttop3e(MRST PDFs) • ttop4e (MRST PDFs, lower ISR) • ttop6e (MRST PDFs, lower FSR) • For ttop2e and ttop4e comparisons our systematics are limited by statistics

  47. jet t fakes • Cross-checking samples yeilds a maximum difference of 26%, which we take as our systematic error • jet50 is closest in Et to spectrum in data fakes so we use jet50 to determine our backgrounds

  48. Candidate Event • Run 167229 • Event 2376337

  49. Candidate Event

  50. Optimization • Plot optimization variable in 2D vs cuts • Choose cuts at lower left corner of “mouth” • highest acceptance for same optimization Signal/SQRT(Bkgnd) Likelihood Ratio HT 1.0 HT 3.2 0.9 2.4 ET(1) ET(1)

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