1. Search for Top Flavor Changing Neutral Current Decay t → qZ Ingyin Zaw DOE Review August 21, 2006

2. 2 Why? BR(t → qZ) ≈ O(10 -14 ) in the Standard Model No tree level, only higher order diagrams, e.g. penguin diagrams New Physics models predict branching ratios up to O(10 -2 ) SUSY, Higgs doublet, Warped extra dimensions, etc. Any observation at the Tevatron → New Physics Have large sample of top pairs ~1 fb -1 of data ~7k top pairs produced Penguin Diagram New Physics?

3. 3 Signature One top decays via FCNC (t → qZ), the other via SM (t → Wb) Z  ℓ + ℓ - / νν / qq, W  ℓ ν / qq (ℓ=e/μ)

4. 4 Signal tt  Wb qZ  ℓ + ℓ - + ≥4 jets Reconstruct Z from e + e - or μ + μ - 76 GeV/c 2 <M Z <106 GeV/c 2 Require ≥ 4 jets Jet Et ≥ 15 GeV, corrected Jet |η| < 2.4 One jet is a b jet → can have a secondary vertex tag Blind analysis Signal region: Z+≥4jets Use both b tagged sample and anti- b tagged sample BR  Acceptance  Efficiency (before tagging): 0.95% Event tagging efficiency (≥ 1 tag): 52% jet l l tagged b jet jet 72%28% Pythia MCEvents with a Z Number of Jets Signal Region Control Region jet

5. 5 Backgrounds Z+Jets Standard Model Top Others (small) Dibosons (WW, WZ, ZZ) From MC 3.5 events before tagging, 0.5 tagged Fake Zs Estimate from same-sign Zs

6. 6 Z+Jets, Pretag Use both data (700 pb -1 ) and Monte Carlo to estimate background Leading order Alpgen+Pythia Monte Carlo Correctly models the Z+njet distribution Absolute Z cross-section is low Normalize to inclusive Zs in data Expected background before tagging for 1 fb -1 of data: Zs in data (scaled from 700 pb -1 ): 79500 Z+≥4j fraction in MC: 0.156% ~ 125 events in signal region Number of Jets

7. 7 Z+Jets, Tagged Z+Heavy Flavor Measure heavy flavor fractions and tagging efficiencies in MC Z+bb: Fraction: ~9.5% Tagging efficiency: ~48% Z+cc: Fraction: ~17% Tagging efficiency: ~14% Predicted tag rates checked in control region in data HF fractions may be higher in data than MC See Joao’s talk on W+HF and K- factor Z+Light Flavor (Mistags) Apply mistag templates from data to MC Mistag rate: ~6% Expected background: ~6 events Expected tagged background: ~18 events

8. 8 Standard Model Top Estimated from Monte Carlo simulation with Pythia tt → WbWb → lν lν bb events with dilepton mass in Z mass window tt → WbWb → lν jj bb events where a jet fakes a lepton Expected background in 1fb -1 : ~ 4 events before tagging ~ 3 events after tagging Dilepton Mass (GeV) SM top MC (170 fb -1 ) 9% 91% Events with a Z Candidate With ≥ 4jets

9. 9 Limits and Optimization Limit Calculation: Assume no signal Expected upper limit for signal: i = number of observed events n b = number of expected background events Optimization: Optimize cuts for best limit Variables: jet E T s H T = Masses  FCNC top mass  W mass  SM top mass Feldman-Cousins Expected Limit vs. H T H T (GeV)

10. 10 Sensitivity Still optimizing for best limit No systematic uncertainties yet Expected limit at 95% C.L. (assuming no signal): Anti-tagged sample: 23% Dominant background: Z+Jets Tagged sample: 18% Dominant background: Z+Jets, SM top Combined: 10% Previous limits: 33% (CDF Run I), direct search  Same channel as our search  No b-tagging 13.7% (LEP), indirect search  Single top production via flavor changing neutral current

11. 11 Plans Optimize event selection Finish cross-checks with data Incorporate systematic uncertainties Results! (hopefully, very soon)