1. Possibility of tan  measurement with in CMS Majid Hashemi CERN, CMS IPM,Tehran,Iran QCD and Hadronic Interactions, 12-19 March 2005, La Thuile, Italy

2.  tan(  is one of the most important parameters in MSSM,  It enters in all parts of the theory,  Value of tan  can be measured at LHC in different ways depending on its real value,  At large tan(  (>10) there is a possibility to measure this quantity with the Higgs sector using event rates, in this study. In MSSM at large tan , cross section exceeds that of for almost all the mass values. NLO Motivation M. Hashemi CERN,CMS (IPM, Iran)

3. At large tan  dominant parts of the total cross section are proportional to which I call tan  hereafter. Branching ratio is almost constant as a function of tan  keeping tan  dependence of the cross section, tan  measurement uncertainty half of uncertainty of rate measurement. SUSY parameters are chosen according to the LEP benchmark scenario: PPHTT+HDECAY Cross section and branching ratios for the signal events M. Hashemi CERN,CMS (IPM, Iran)

4. Events are generated by pythia6,toprex,tauola, signal cross section with PPHTT and Higgs branching ratios with HDECAY, Studies with parameterized fast simulation, partly with full simulation. Signal events are : Main Backgrounds are : Background events are rejected by : Lepton isolation, Tau-jet identification, Tau impact parameter, b-tagging, Jet veto. Signal and background identification and simulation tools M. Hashemi CERN,CMS (IPM, Iran)

5. Event trigger is done with L1&HLT package for each channel: Single muon trigger, eff.=0.85 Single muon trigger or di-electron, eff.=0.82 Single muon trigger or Di-tau trigger, eff.=0.38 e+tau trigger, eff.=0.73 When having a tau-jet : L1&HLT tau trigger thresholds are applied: 1  jet:86GeV, 2  jet:59GeV, e-  jet:45GeV Offline selection: Leading track pt cut: pt>40GeV, 1 or 3 tracks in cone 0.04 around the leading track, No other track with pt>2GeV in the isolation cone 0.4 Efficient against QCD, bb, W+jets Since b-jets are soft and distributed over the whole rapidity range, b-tagging efficiency is low and single b-tagged jet has been requested for each event, with impact parameter significance method (3 tracks with  ip >2) Signal event selection M. Hashemi CERN,CMS (IPM, Iran)

6. e+  lepton+lepton lepton+jetjet+jet Reconstructed Higgs boson mass M. Hashemi CERN,CMS (IPM, Iran)

7. With at low luminosity ( ) with SUSY parameters values listed, the 5  contour shows that this channel is the most promising channel for heavy neutral MSSM Higgs boson discovery. 5  discovery contours M. Hashemi CERN,CMS (IPM, Iran)

8. The number of signal events that we get after all experimental selection cuts is : For production cross section we have statistical and systematic uncertainties: Systematic uncertainty comes from:  luminosity,  experimental selection,  background uncertainties, The total uncertainty is the quadratic sum of statistical and systematic errors: Calculation of statistical and systematic uncertainties M. Hashemi CERN,CMS (IPM, Iran)

9.  Statistical uncertainty of the signal events is calculated with standard weighted least squares procedure by summing over all final states, assuming uncorrelated measurements:  The uncertainty on the luminosity measurement is assumed to be ~5% Statistical and luminosity uncertainty M. Hashemi CERN,CMS (IPM, Iran)

10. The uncertainty on the signal selection efficiency comes from :  The calorimeter energy scale (since jets and missing Et thresholds are required) : Full simulation of di-  jet final states shows that we have 2.9% uncertainty on the signal selection efficiency assuming 1% uncertainty on the calorimeter energy scale.  b-tagging efficiency: Using two samples of semileptonic ttbar events, single btagging eff. is calculated as the ratio of double vs single b-tagged events. The statistical uncertainty is 1% which leads to 2% assumption on the total b-tagging uncertainty considering b-jet purity and background contribution.   tagging efficiency: Using two samples of and the measured ratio of events selected after applying tau tagging algorithm and Z mass constraint gives 2.5% uncertainty on tau tagging efficiency. The total selection efficiency error is 4.3%. Signal selection uncertainty M. Hashemi CERN,CMS (IPM, Iran)

11. The background contribution to the signal selection efficiency is estimated by fitting the distribution. The extrapolation of the background fit to the Higgs mass window gives the background contribution. By varying the Higgs mass and tan(  the background contribution uncertainty is obtained. Choosing and tan  which is close to 5  to estimate the highest uncertainty, the background uncertainty is estimated to be The total systematic uncertainty is 12% comparable with statistical uncertainty. Now assuming fixed values for SUSY parameters, the production cross section can be written as: Such that the error on tan(beta) measurement is : Where consists of:  theoretical uncertainties of the production cross section and the branching ratio  cross section uncertainty due to the uncertainty on the Higgs boson mass measurement. Background uncertainty M. Hashemi CERN,CMS (IPM, Iran)

12.  The NLO cross section uncertainty for the signal has been shown to be 20-30% for the total rate.(Dittmaier, Kramer, Spira, hep-ph/0309204) If a pt cut on both b quarks is applied the theoretical error is smaller (10-15%), but since 1-btagging is done the error is taken to be 20%.  The branching ratio uncertainty is ~3% which is due to SM parameters uncertainties. ~22%~17% Theoretical uncertainty on the signal cross section M. Hashemi CERN,CMS (IPM, Iran)

13. Production cross section depends on the Higgs mass which is measured with some accuracy. This induces some error on the cross section. The gaussian fit to the mass distribution is used to estimate the error in the cross section related to the Higgs mass reconstruction, The error induced to the cross section is estimated by varying the cross section for the Higgs masses and : At 5  limit when the signal statistics is lowest, the mass measurement uncertainty brings 5-6% uncertainty on the tan  measurement. Uncertainty of the mass measurement M. Hashemi CERN,CMS (IPM, Iran)

14. The Higgs sector is sensitive to SUSY parameters as well as and tan , The SUSY parameters uncertainties are unknown. To give an estimation of the rate sensitivity on the SUSY parameters, those were varied by 20% around the nominal values. The variation of the rate within the discovery region is about 11%, which leads to at most 6% uncertainty on tan  measurement. SUSY parameters uncertainty effects M. Hashemi CERN,CMS (IPM, Iran)

15. The statistical uncertainty and the uncertainty due to the mass measurement is shown in the table, The total uncertainty includes: Statistics, mass measurement, cross section and branching ratio, luminosity, experimental selection, background uncertainties. Uncertainty of tan  measurement, M. Hashemi CERN,CMS (IPM, Iran)

16. Small gray errors: statistical Large errors: total errors Uncertainty of tan  measurement, M. Hashemi CERN,CMS (IPM, Iran)

17.  The precision of a tan  measurement is estimated using in CMS with  The uncertainty includes:  Statistical error  Error of the Higgs mass measurement  Theoretical error (cross section and branching ratio)  Luminosity error  Signal selection uncertainty  SUSY parameters uncertainties with 20% assumption for each  What is still to be investigated in more detail:  Uncertainty of the SUSY parameters measurement  Uncertainty of the signal plus background selection and background determination With signal significance >5  the study gives better than 35% accuracy on the tan  determination at the benchmark point considered. Errors are dominated by the theoretical errors. conclusions M. Hashemi CERN,CMS (IPM, Iran)