TESLA - The TEV-Energy Superconducting Linear Accelerator Towards a measurement of the two photon width of the Higgs boson at the Tesla Photon.
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TESLA - The TEV-Energy Superconducting Linear Accelerator Towards a measurement of the two photon width of the Higgs boson at the Tesla Photon Collider Aura Rosca West University, Timişoara, Romania Durham, U.K., 1-4 September 2004 TESLA - The TeV-Energy Superconducting Linear Accelerator Motivation • Measure the two-photon partial width: – Contribution to the two photon decay width from any kind of massive charged particles. Deviation of the partial width from Standard Model prediction: • Evidence for new physics; • Can be directly compared to predictions of alternative models (MSSM, NMSSM, general 2HDM). September 2004 Aura Rosca West University Timisoara 2 TESLA - The TeV-Energy Superconducting Linear Accelerator How to Get Widths? • The Higgs mass peak gives Γ(h γγ) BR(h bb) (mh 140 GeV) • Taking BR(h bb) and BR(h γγ) from LHC or LC, Γ γγ Γ(h γγ) BR(h b b ) BR(h b b ) Γ γγ Γ tot BR(h γγ) • This is proposed as way to get the total Higgs width. Model-independent result. September 2004 Aura Rosca West University Timisoara 3 TESLA - The TeV-Energy Superconducting Linear Accelerator Results of Amsterdam ‘03 • Realistic photon spectrum for ++ and +- photon helicities simulated with CIRCE 2.0; • Signal MC generated with PYTHIA and passed through the TESLA fast simulation, Simdet 4.02; • Background MC generated with PYTHIA and passed through the TESLA fast simulation: – s γγ 80 GeV – Convolution with the realistic photon spectrum for ++ and +photon helicities – Events weighted by the NLO (Jikia, Tkabladze) cross sections for ++ and +- photon helicities • B-tagging based on NN September 2004 Aura Rosca West University Timisoara 4 TESLA - The TeV-Energy Superconducting Linear Accelerator Invariant Mass Spectrum • Possible to isolate the signal from the background. N sig 6018 events N bkg 7111 events Δ Γ (h γγ )BR(h bb Γ (h γγ )BR(h bb) N obs 1.9% N obs N b September 2004 Aura Rosca West University Timisoara 5 TESLA - The TeV-Energy Superconducting Linear Accelerator New Results • Background MC generated with SHERPA (CERN-TH/2003-284) and passed through the TESLA fast simulation: – s γγ 80 GeV – Convolution with the realistic photon spectrum for ++ and +- photon helicities • Selection: – – – – N jet 2,3 cosθ T 0.7 E vis 95 GeV, E long/E vis 0.1 jet 2nd fast jet NNfastest 0.95, NN 0.2 out out September 2004 Aura Rosca New! West University Timisoara 6 TESLA - The TeV-Energy Superconducting Linear Accelerator Background Cross Sections 1000 100 0.99 10 0.9 2.8 Jikia bbg ++ Jikia bbg +Jikia jjg ++ Jikia jjg +Sherpa bbg ++ Sherpa bbg +Sherpa ccg ++ Sherpa ccg +- 1 1.9 0.1 September 2004 80 80 100 100 120 120 Aura Rosca 140 140 160 160 West University Timisoara 7 TESLA - The TeV-Energy Superconducting Linear Accelerator Sherpa versus Pythia Pythia ++ Pythia +- Sherpa ++ Sherpa +- N jet September 2004 Aura Rosca West University Timisoara 8 TESLA - The TeV-Energy Superconducting Linear Accelerator Sherpa versus Pythia Pythia ++ Pythia +- Sherpa ++ Sherpa +- cos θ T September 2004 Aura Rosca West University Timisoara 9 TESLA - The TeV-Energy Superconducting Linear Accelerator Sherpa versus Pythia Pythia ++ Pythia +- Sherpa ++ Sherpa +- E vis September 2004 Aura Rosca West University Timisoara 10 TESLA - The TeV-Energy Superconducting Linear Accelerator Sherpa versus Pythia Pythia ++ Pythia +- Sherpa ++ Sherpa +- E long/E vis September 2004 Aura Rosca West University Timisoara 11 TESLA - The TeV-Energy Superconducting Linear Accelerator Invariant Mass Spectrum N sig 3207 events N bkg 1229 events Δ Γ (h γγ )BR(h bb Γ (h γγ )BR(h bb) N obs 1.5% N obs N b (However, more statistics required!) September 2004 Aura Rosca West University Timisoara 12 TESLA - The TeV-Energy Superconducting Linear Accelerator Summary • Measure Γ(h γγ) BR(h bb) with a precision below 2% by: – Taking into account the QCD radiative corrections to the background process γγ qq ; – Adapting a b-quark tagging algorithm based on a neural network. September 2004 Aura Rosca West University Timisoara 13