Presentation on theme: "On the Trail of the Higgs Boson Meenakshi Narain."— Presentation transcript:
On the Trail of the Higgs Boson Meenakshi Narain
Outline Higgs Primer Overview of Higgs Searches Search Strategies: –Standard Model Higgs Low and High Mass regions –SUSY Higgs –ttbarH production –Diffractive Production Future Prospects Conclusions
Constraints on the Higgs Mass Direct Searches at LEP Fits to Precision Electroweak Data Fit for the Higgs Mass (LEP EWWG 2001)
SM Higgs Production at Tevatron [pb] (m H =100 GeV) typical production cross-sections gg H WH ZH 1.0 0.3 0.18 WZ Wbb 3.2 11 tt tb+tq+tbq 7.5 3.4 QCDO(10 6 ) Gluon fusionAssociated Production WZ/ZH production is cleanest
SM Higgs Decays and BRs Divide into two regions Low Mass –H-.bb domintaes –gg->H precluded by QCD background High Mass –Gauge Boson decays dominate –H->WW becomes promising Less sensitivity in cross over region
Low Mass Higgs Search Higgs couples most strongly to massive particles: Focus on associated production (WH/ZH) – Best Prospects: leptonic W/Z decays – QCD background large for hadronic channels SM Background processes: Sensitivity will depend on –b-jet tagging – dijet mass resolution 1 32
SM Higgs: Leptonic Channel (1) Typical Selection: Main backgrounds: Event selection optimized to maximize S/B
Expected Events and Sensitivity Sensitivity crucially depends on dijet mass resolutions
Mass Resolutions: cont’d Signal significance depends on bb mass resolution –For RunII aim for 10% mass resolution –30% better than in the previous Run WH l bb CDF RunI “Calibration for Higgs Search
Mass Resolutions: cont’d Run I Jet ET resolution vs Fast MC Optimize b-jet reconstruction and corrections corrections (partly for b’s): –b/light-q jet calibration Improvement due to increased +jets statistics Significant sample of Z bb –Correct for in b l –Correct for in jets Can get 12% at M=120 GeV –If only 12% mass resolution Required luminosity increases by 20% WH l bb
Mass resolution issues Problem is not intrinsic jet resolution –In 2 jet WH events, Mjj is close to gaussian Mass resolution is about 10% (but, costs 30-70% in efficiency) –With 2 jet requirement relaxed, Mass resolution is about 15% 3rd jet must be judiciously used!
More improvements – b-tagging b-jet tagging: Will it be good enough? –Displaced Vertices 3-D vs 2D vertexing possible Improved impact parameter resolution (Extrapolation from CDF Run I eff.) –Semileptonic tags dodo primary vtx secondary vtx L xy e or in jet b secondary vtx 2 tracks tagged if L xy / Lxy
can we improve? b-tagging LEP2, S.Jin PHENO2000 For bb backgrounds: Relative Luminosity goes as Eff increase from 60% 65% would result in the same signal significance for 20% less integrated luminosity.
Multivariate Analysis techniques Further Improvements from use of Neural Networks, Grid Search, likelihood methods. – Significant gains, compare S/ B with and without neural nets
SM Higgs: Leptonic Channel (2) Main backgrounds: Event selection optimized to maximize S/B Typical Selection:
Use Neural Networks to optimize analysis: – use different networks one for signal 4 different ones for bkg
SM Higgs: Leptonic Channel (3) Small rate but good S/B Main backgrounds: Typical Selection:
Neural Network Analysis: signal Backgrounds (4 different networks) Kinematic fit may enhance sensitivity Add Taus?
Low Mass Higgs Search It’s going to be challenging… A 120 GeV Higgs signal Total Background
Conclusion Thanks to CDF and DØ collaborations Tevatron Run II precision studies of top quark properties LHC… `top factory’ open possibilities of new measurements e.g. Yukawa coupling, rare decays, CP violation etc.
bb mass reconstruction the extracted signal significance depends on input dijet mass resolution WH l bb improvement from use of tracking and preshower in jet reconstruction? (also, different algorithms?) corrections (partly specific to b’s): - corrections for into jets (b l ) - corrections for into jets - b/light-q jet calibration - b/light-q parton corrections and... -effect of extra interactions on jet reconstruction optimized b-jet reconstruction+corrections E. Barberis
b-tagging displaced vertices: RunI SVX algorithms on RunII detector (3D Si, large ) + soft lepton tagging (~10%) ~55-60% fakes: dodo primary vtx secondary vtx L xy secondary vtx 2 tracks tagged if L xy / Lxy e or in jet b DØ used only ‘s in top analyses M.Roco