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Search for SM Higgs Boson Using Large Missing Transverse Energy and B-jets at DØ

Search for SM Higgs Boson Using Large Missing Transverse Energy and B-jets at DØ. Tim Scanlon Imperial College, London on behalf of the DØ Collaboration. Overview:. Introduction The D Ø Detector Previous Results Analysis Method Published Result Future Analysis Conclusion. n.

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Search for SM Higgs Boson Using Large Missing Transverse Energy and B-jets at DØ

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  1. Search for SM Higgs Boson Using Large Missing Transverse Energy and B-jets at DØ Tim Scanlon Imperial College, London on behalf of the DØ Collaboration Overview: • Introduction • The DØ Detector • Previous Results • Analysis Method • Published Result • Future Analysis • Conclusion

  2. n Z Z n b H b ET Jet1 Jet2 Introduction • Motivation • ZHbb is a very sensitive way to search for the SM Higgs at the Tevatron as we do not distinguish between the neutrino species • (qqZH)xBr(Z, Hbb) = 0.015 pb @ mH=115 GeV • (qqWH)xBr(Wl, Hbb) = 0.014 pb • Characteristic Signal • Large missing ET (ET) • 2 b-tagged jets with high pT • The leading jets are boosted and hence not back-to-back • Di-jet mass of b-jets • No isolated leptons Tim Scanlon (Imperial College London)

  3. The DØ Detector • Good calorimeter (ET) and tracking (b-tagging) essential • Uranium/Liquid-Argon Calorimeter • Central calorimeter provides coverage up to ||~1.1 • Two end calorimeters extend coverage up to ||~4.2 • Tracking • Silicon Microstrip Tracker (SMT) • New Layer 0 for Run IIb • Central Fibre Tracker (CFT) • Surrounded by 2T Solenoid • DØ detector • Efficiency above 85% • Recorded 1.5 fb-1 of data Tim Scanlon (Imperial College London)

  4. Previous Preliminary Result • 2005 Preliminary result • 95% C.L. limits on (ppZH) × Br(Hbb) = 8.5 ~ 12.2 pb @261pb-1 • Updated version of the analysis now accepted for publication: • Same dataset • Improved: • Optimized event selection • Added “exclusive” single b-tag channel to double b-tag channel • Inclusion of WH limits in ET+jets sample, when the lepton from the W is missed Tim Scanlon (Imperial College London)

  5. Analysis Issues • The signal is well defined although it has significant backgrounds: • “Physics” backgrounds • Well defined processes can be distinguished and accurately modeled • Some irreducible • Dominant physics backgrounds • W+jets, Z+jets, top, ZZ, and WZ • “Instrumental” backgrounds • Basically everything else • Mainly QCD multi-jet events with mismeasured jets • back to back jets events where one jet is grossly mis-measured • Large ET • presence of fake jets, etc. • Generally low acceptance, but cross-section much larger • Significant background • No easy way to estimate the magnitude and shape of this background • Instrumental background forced us to apply more stringent selection cuts • Needed to devise a way of estimating and simulating its contribution Tim Scanlon (Imperial College London)

  6. - HT = |pT(jets)| • PTtrk = |pT(tracks)| • - A(ET,HT) = (ET-HT)/(ET+HT) Event Selection • ET > 50 GeV(basic Higgs signal) • 2 or 3 jets with pT > 20 GeV, ||<2.5 (basic Higgs signal) • (dijet) < 165° (rejects QCD di-jet events) • Isolated EM and muon veto (rejects top, W/Z+jets) • HT < 240 GeV (rejects top) • PTtrk > 20 GeV (rejects instrumental) • -0.1 < A(ET,HT) < 0.2(rejects instrumental) • min (ET,jets) > 0.15 && ET > -40 * min (ET,jets) + 80 • (ET, PTtrk) < 90° for “signal” region > 90°for “sideband” region Determined by optimisation. (Used to measure instrumental background) Variables verified in W+jets sample. Tim Scanlon (Imperial College London)

  7. Estimating the Instrumental Background Tim Scanlon (Imperial College London)

  8. Signal Region Sideband Region Instrumental Background • Fit of A(ET, HT) • Estimate physics background from MC: Triple Gaussian function • Instrumental background: 6th order polynomial function • Instrumental background = 696.1 ± 91.4 events (from fit) • Physics background = 2514.9 events (from MC) • Normalise sideband region instrumental background in A(ET, HT) bins • Model the instrumental background distributions in signal region Tim Scanlon (Imperial College London)

  9. b-tagging • Identifying a b-jet • Track Impact Parameters (JLIP and CSIP) • Secondary Vertex (SVT) • High pT Lepton • Neural Network Combination (more later) • Jet Lifetime Impact Parameter Tagger • JLIP identifies heavy flavour jets from large impact parameter tracks • JLIP calculates a probability (P) that the jet is a light-jet • Analysis split into two different b-tagging channels • One JLIP tag ‘Exclusive’ • Ultra Tight JLIP (P < 0.001) • Two (or more) JLIP tags • Loose JLIP (P < 0.01) • Extra Loose JLIP (P < 0.04) JLIP Performance in Data Tim Scanlon (Imperial College London) (~P)

  10. Distributions ET+jj Data : 3210 Exp : 3211 ET+jj (1 btag) Data : 592 Exp : 554.5 ET+jj (2 btags) Data : 25 Exp : 27.0 Tim Scanlon (Imperial College London)

  11. Background Composition and Acceptance Double (Single) Tagged Channel (within ±1.5 mass window) • Large contribution from WH decays • Single Tag Channel • Main background is Wj • Instrumental background is 26% • Double Tag Channel • Main background top decay • Instrumental background reduced to 13% • On same level as the W+jj and Z+bb • Systematics: Signal 19%, Background 19% • b-tagging (~14%) and Jet energy scale (~8%) Tim Scanlon (Imperial College London)

  12. (ppZH)xBr(Hbb) Limit • Significant progress since preliminary result • New limits are more than 2 times better • Limits set from combined double and exclusive single tag channels • Also measured limits for WH with escaped lepton • Results combined with other DØ and CDF result Tim Scanlon (Imperial College London)

  13. Future Analysis • Significant progress made on next generation of analysis • Several improvements expected to significantly improve the limit •  1 fb-1 of data • Full calibration of calorimeter • Lower systematic errors • New NN b-tagging • NN event selection • New preliminary limit expected by early 2007 Tim Scanlon (Imperial College London)

  14. New NN b-tagging (released summer 2006) • A new b-tagging tool • Combines various variables from the track based b-tagging tools in a Neural Network • Substantial improvement in performance over constituent input b-taggers • Trained on Monte Carlo • Certified on data • Performance measured on data • Increase of 1/3 in efficiency for a fixed fake rate of 0.5 % • Significantly increase Higgs sensitivity MC Fake-jets with a very loose tag Data Tim Scanlon (Imperial College London)

  15. Conclusions • Search for the Higgs boson with large missing transverse energy • Very important channel in search for the SM Higgs • Search for 2 b-tagged jets and large missing ET • Main difficulty predicting the instrumental background • 0.3 fb-1 analysis accepted for publication in PRL • Results were two times better than preliminary result • Also measured WH with escaped lepton • 1 fb-1 preliminary result expected early next year • Numerous improvements • Expect significantly improved limit • Current and future results • Vital role in combined SM Higgs search Tim Scanlon (Imperial College London)

  16. Backup Slides

  17. Systematic Errors • Each systematic source varied by ±1 • Analysis repeated • Uncertainties dominated by Jet Energy Scale and b-tagging Tim Scanlon (Imperial College London)

  18. Sensitivity Prospects • Largest improvement in sensitivity from • Increased luminosity • NN b-tagging Tim Scanlon (Imperial College London)

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