Search for Narrow Resonance Decaying to Muon Pairs in 2.3 fb -1

1. Search for Narrow Resonance Decaying to Muon Pairs in 2.3 fb-1 Chris Hays1, Ashutosh Kotwal2, Ye Li3, Oliver Stelzer-Chilton1 1 Oxford University 2 Duke University 3 University of Wisconsin-Madison

2. Motivation • Theory Driven • Standard Model successful but incomplete • Strong discovery potential in dimuon channel • New models predict narrow neutral resonance, e.g. • additional U(1) symmetry: Z’ • extra space-time dimension: Randall-Sundrum graviton • The present analysis focuses on Z’ →  channel APS April Meeting, St. Louis - 14 April 2008

3. Motivation • Experiment Driven • Last CDF and DØ dimuon resonance searches performed with integrated luminosity 200 pb-1 → Our search: L ≈ 2.3 fb-1 of CDF Run II data • Significant increase of sensitivity to dielectron and diphoton channels • Excellent tracking resolution (Central Outer Tracker, Drift Chamber) APS April Meeting, St. Louis - 14 April 2008

4. Methodology • Model Drell-Yan background and signal resonance with PYTHIA + fast simulation for W mass measurement • Use Z region for normalization • Remove uncertainty on luminosity • Easy accounting • Compare CDF fast simulation (FastSim) to full Geant simulation (CDFSim) and data for acceptance and efficiency study APS April Meeting, St. Louis - 14 April 2008

5. Methodology • Inverse Mass (1/m) Scan • Excellent angular resolution → negligible • Track curvature (~1/PT) resolution constant for high PT → constant 1/m resonance width 1/m ≈ 0.16/TeV APS April Meeting, St. Louis - 14 April 2008

6. Methodology • Fit for NZ’ (number of Z’ candidate) • Calculate Binned Poisson likelihood L(NZ’;MZ’) for region 1/m < 10/TeV • Construct the narrowest possible interval in NZ’ at 95% C.L. • Scan 1/m spectrum for Z’ resonance • Use Monte-Carlo Pseudo-experiments to determine the significance APS April Meeting, St. Louis - 14 April 2008

7. Dataset & Selection • Dataset from high PT muon trigger • The dimuon event selection • The muon identification requirement • EM energy cut tuned for high efficiency of Z • High identification efficiency ~ 95% APS April Meeting, St. Louis - 14 April 2008

8. Efficiency • Mass dependence • Assume track and muon-hit cuts independent of mass • Momentum dependence • Only consider P dependence, due to the normalization of background expectation • Assume no P dependence of trigger efficiency for PT > 30 GeV • Separate the sample into signal and normalization (Z-pole) regions APS April Meeting, St. Louis - 14 April 2008

9. Efficiency • EM and Hadronic Cut Efficiency • Signal region: constant ratio between FastSim and CDFSim (no inefficiency of Had cut for FastSim → 2% const. offset) • Z-pole region: ratio between FastSim and Data drops at low P (due to incomplete modeling) • insufficient data for signal region • compute uncertainty from data-simulation difference APS April Meeting, St. Louis - 14 April 2008

10. Acceptance • Implement detector Geometric information on FastSim • Map angular distribution of CDFSim to FastSim; • W →  data and FastSim agree reasonably Muon  for || < 0.6 (CMUP) Muon  for 0.6 < || < 1.0 (CMX) APS April Meeting, St. Louis - 14 April 2008

11. Acceptance • Mass-dependent Acceptance • Larger mass → Lower boost → More central events → Larger acceptance • Constant Ratio between FastSim and CDFSim → Validate acceptance calculation from FastSim • Uncertainty from the small slope of the ratio APS April Meeting, St. Louis - 14 April 2008

12. Background • Drell-Yan */Z →  • PYTHIA + FastSim • WW and tt-bar • CDF Simulation (PYTHIA + CDFSim) • Cosmic Rays • Identified Cosmic-ray samples • QCD Jets and Decays-in-Flight • Data APS April Meeting, St. Louis - 14 April 2008

13. Drell-Yan • Dominant source for background • Mass spectrum affected by higher-order corrections • Calculate up to next-to-next-to leading order (NNLO) correction → k-factor • Different Calculations give different k-factors • Average k-factor; Difference as uncertainty APS April Meeting, St. Louis - 14 April 2008

14. Drell-Yan • The Stirling and Hamburg, van Neervan and Matsuura (HNM) calculations of the k-factor • About 6% difference ( ~3% systematic uncertainty) APS April Meeting, St. Louis - 14 April 2008

15. WW tt & Cosmic Ray • WW, tt →  + missing ET : Simulate PYTHIA samples using CDFSim to compute background • Cosmic Ray : Use timing information of Drift Chamber to estimate • Background fraction ~ 1.2 X 10-6 APS April Meeting, St. Louis - 14 April 2008

16. QCD & DIF • Assumtions • QCD jets faking muons: same-sign dimuon (SS) and Opposite-sign dimuon background (OS) distribution have similar shape, i.e. constant OS/SS ratio • Decay-in-flight muons: flat distribution of DIF muons at small curvature (high PT → small 1/m) • Track 2 cut reduces DIF events • Same-sign samples contains both jet fakes and decays-in-flight APS April Meeting, St. Louis - 14 April 2008

17. QCD & DIF • SS dimuon obtained from jet triggered data • SS dimuon obtained from signal dataset, with 2 cut removed • SS dimuon obtained from signal dataset, with 2 cut on APS April Meeting, St. Louis - 14 April 2008

18. Other Issues • Momentum Scale & Resolution • Momentum scale measurement done by fitting Z peak using templates made with FastSim • Resolution tuned on the width of the Z peak • Systematic Uncertainties • Dominant uncertainties: • Parton distribution functions • Mass-dependent of the NNLO k-factor • Other uncertainties: • Arise from PT-dependent acceptance and efficiency • Affect the signal and background prediction at high mass APS April Meeting, St. Louis - 14 April 2008

19. Signal Scan • Pseudo-experiment: Standard Model process APS April Meeting, St. Louis - 14 April 2008

20. Signal Scan • Pseudo-experiment: MZ’ = 250 GeV APS April Meeting, St. Louis - 14 April 2008

21. Signal Scan • Expected limits on NZ’ from 1000 pseudo-experiments on 50 Z’ masses • Data: to be implemented … APS April Meeting, St. Louis - 14 April 2008

22. Summary • Use 1/m distribution for constant resolution • Fitter and Simulation in place to study signal acceptance and identification efficiency • Analysis on different background fractions • Systematic uncertainties to be determined • Signal scan performed on pseudo-experiments APS April Meeting, St. Louis - 14 April 2008