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Preapproval update: EXO-11-038. John Paul Chou, Greg Landsberg, Duong Nguyen (Brown). Exotica Meeting July 5, 2011. MC Photon Efficiency (I). 60 < E T < 100. 350 < E T < 400. 60 < E T < 100. PU reweighting is applied. Combined efficiency estimated in MC: 90.0 ± 2.5 (syst)%
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Preapproval update: EXO-11-038 John Paul Chou, Greg Landsberg, Duong Nguyen (Brown) Exotica Meeting July 5, 2011
MC Photon Efficiency (I) 60 < ET < 100 350 < ET < 400 60 < ET < 100 PU reweighting is applied • Combined efficiency estimated in MC: 90.0 ± 2.5 (syst)% • Pixel seed veto efficiency 96.6±0.5 (syst)% • Adding 4% systematic uncertainty to cover pile-up effect
Data/MC Scale Factor (II) • Total photon efficiency: (88.7 ± 5.5)% • Diphoton efficiency: (78.7 ± 9.6)%
Limits for ADD 95% CL cross section limit (Mgg>800 and |eta|<1.44): 4.53 fb
Conclusions • Searches for extra dimensions in the diphoton channel are updated to 2011 data • With 881 pb-1 data, the 95% CL limits are • LED: cross section limit is 4.53 fb (M>800 GeV and |eta| < 1.4442), Ms limits from 2.41 to 3.61 TeV
Background k-factor • Background k-factor (EB-EB only) • Invariant mass dependence • Calculated by DIPHOX. • Box process is included in the LO and its corresponding higher order is estimated by gamma2MC Mγγ 6
Signal k-factor k-factors are from M.C. Kumar, P. Mathews, V. Ravindran, and A. Tripathi Note: K-factors are higher than what we have used in 2010 (1.3) For the RS: The background K-factor doesn’t directly effect the result. However, the signal K-factors have a large impact on the model limits ADD RS 7
Data/MC Scale Factor (I) R. Yohay eff = 0.857 ± 0.014 eff = 0.876 ± 0.033 Data MC • Z Tag and Probe to measure photon efficiency in data-driven way • Data/MC scale factor: 1.02 ± 0.04 • Total photon efficiency: (88.7 ± 4.2)% • Diphoton efficiency: (78.7 +- 7.5)% 8
Fake Rate at High pT ET (GeV)
Invariant Mass Optimization for LED Perform pseudo-experiments on the SM background and ADD signal Maximize the z-score of the Pes for Mgg cut (EB-EB) Optimize cut at 800 GeV (for 1/fb scenario) Eta optimization from expected limit suggests EB-EB is optimal ADD 10
Systematic Uncertainties ADD (EB-EB) Signal efficiency (data/MC SF, PU): 12.2% relative Background estimate: 12% relative Signal K-factor: 6.3% relative Luminosity: 6% relative Fake Rate: 20% 11
Limit setting • Perform limit setting for a counting experiment with > 500 GeV • Apply Bayesian procedure • Use Poisson likelihood for model • Lognormal prior for nuisance parameter • Flat prior for cross section • 95% upper bound • Upper bound on the <0.11 pb at 95% C.L.