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Lumi - spectrum impact on Top mass

Lumi - spectrum impact on Top mass. Stewart Boogert & David Miller University College London ALCPG, Top and QCD session, Victoria Thursday 29 th July 2004. Top threshold Aim: “realistic” systematic error on top mass from threshold scan Tool development Toppik (A. Hoang et al)

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Lumi - spectrum impact on Top mass

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  1. Lumi-spectrum impact on Top mass Stewart Boogert & David Miller University College London ALCPG, Top and QCD session, Victoria Thursday 29th July 2004

  2. Top threshold Aim: “realistic” systematic error on top mass from threshold scan Tool development Toppik (A. Hoang et al) Parameter (mt, t & s) maps Interpolation Convolution with energy loss Fitter Preliminary analysis, needs input from fellow top quark enthusiasts (who are you?) Next 20 mins • Talk outline • Luminosity spectra • Beamstrahlung and Bhabha scattering simulation • Top threshold simulation • Cross section interpolation • Threshold smearing • Fitting • Next steps • Beam spread • Beamstrahlung extraction • AFB and ppeak • Conclusion

  3. Beam energy loss • Three sources • Accelerator beam spread • Typically ~0.1% • Gaussian (?!) shape • Beamstrahlung • 0.7% at 350 GeV • 1.7% at 800 GeV • Initial state radiation • Calculable to high precision in QED • Complicates measurement of luminosity spectrum using Bhabha events

  4. Bhabha acollinearity • Monitor collision energy via Bhabha events • Acollinearity angle depends on the momentum mismatch between the beams • Kinematics • Calculate x using only scattering angles • Calorimeter energy resolution too large • Tracker/calorimeter angular resolution good enough?

  5. Simulation of luminosity spectrum • Beam simulation • Circe/Guinea-Pig (modified) • Accelerator simulation (G. White) + Beam collision simulation • E0=175 GeV, simple scaling of accelerator parameters. • Guinea-Pig • TESLA TDR parameters scaled appropriately by energy (500 350GeV) • Bhabha scattering • BHWIDE (350 GeV, >7)

  6. Top threshold simuation • Toppik (Hoang & Teubner) • Calculates R=(tt)/(+-) • Have wrapped Fortranin C++/Root for ease of use • Default parameters • mt=175 GeV • t=1.43 GeV • s(MZ) = 0.118 • Options and other parameters • NNLO, 1s mass scheme • MH=115 GeV •  = 15 GeV Example threshold from Toppik, without experimental effects

  7. Spectrum reconstruction • Reconstruction of luminosity spectrum (xm) • Reasonable agreement • Definition of xt problematic due to overlap between ISR/FSR • Mean shift <xm-xt> • 16.0510-4 • Large due to tails in xm-xt • See Luminosity spectrum talk in IPBI/IR/MDI session

  8. Top cross section interpolation • Toppik calculation slow • Interpolate • Evaluate cross section on grid • mt: 172178 GeV • s: 0.110 0.126 • t : 1.43 1.46 GeV • Interpolate cross section in 4D • Above parameters and s • Essential for convolution with energy loss and fitting problem • Direct use of toppik requires ~104 calls per fit iteration Example of mt steps s steps

  9. Interpolation grid node ((s)) mt t No problem Cross section interpolation (2) • Interpolation algorithm • Determine nearest neighbours (NN) • Linearly interpolate cross section function (s) • Problem due to maximum in cross section • Translate cross section so that maxima at same s • Linearly interpolate and translate back • Will apply same algorithm for smeared cross section ’(s) 1st 2nd

  10. Interpolation check • Check algorithm • Randomly select mt, s, t and s from within grid • Calculate toppik (toppik) and interpolated cross sections (interpol) • Right: plot of • (toppik- interpol)/ toppik • Working just fine • Bias : 0.0002 • RMS : 0.0015 << 1% (theoretical error) (toppik- interpol)/ toppik

  11. Threshold with energy loss • Fold top threshold with luminosity spectrum • p(x) – parameterisation or histogram • xi sampled from Bhabha sample (requires large number) Loss of luminosity

  12. Threshold fit • Fake threshold data (points) • True luminosity spectrum • 11 points (10 fb-1 per point) • 346<s<355 GeV • 41% efficiency (previous studies Martinez et al) • “Theoretical’’ cross section (solid line) • Generated using measured luminosity • Form usual 2 and minimise using Minuit • Correlation between top mass and strong coupling returns. 2(mt) 2(t)

  13. All parameters Free t fixed mt [GeV] mt [MeV] 174.952 0.013 -48 174.956  0.014 -44 s s 0.11627 0.00036 -0.0017 0.11639  0.00035 -0.0016 t [GeV] t [GeV] 1.417 0.018 -0.013 Fit summary • Summary of fit results • Data : mt=175 GeV, s=0.118 and t=1.43 • Shifts are between default values and fits using measured luminosity spectrum

  14. Scan strategy Number of points and luminosity per point Optimisation Simultaneous luminosity spectrum measurement Fundamental problems Is there a more efficient/consistent method to implement energy loss effects on the top threshold? Possibly, see next slides on linac energy spread and parameterisations of the luminosity spectrum Next steps • Luminosity spectrum • Different Guinea-Pig conditions • Linac energy spread • Track updates in beam-beam simulation / accelerator parameters • Analysis • Include AFB and ppeak • Top threshold event generator • Dialogue with accelerator people • Modifications of running for top threshold

  15. Accelerator beam spread • Problem in both warm and cold machines • E/Ewarm ~0.3% • E/Ecold ~0.1% • Smears out structures like the top peak (see right) • Analysis as presented will not cope with beam spread • Why: Bhabha events only sensitive to p, so xm1 • Find method to extract x>1 and apply to threshold. BS=0, 0.1, 0.2, 0.5, 1.0 %

  16. NLC beam spread shape • Beam spread different for cold/warm machines • TESLA – Gaussian shape • NLC – more complicated (see right) • Does NLC energy spread shape have impact on top mass measurements? • Clearly width and mean important • Parametrise NLC shape from accelerator simulations and scale to arbitrary mean and width

  17. Effect of energy spread • Convolute top cross section with energy spread only • Gaussian (TESLA) shape • Double peaked (NLC) shape • “Data” thresholds generated with some beam spread (true) • Then fitted with cross section convoluted with various measured energy spreads (meas)

  18. Result Systematic shifts observed mt = -48 MeV mt = -44 MeV (top width fixed) s = -0.0017 s = -0.0016 (top width fixed) Statistical errors compatible with previous analyses. Much more work to be done: Beam spread AFB and ppeak, theory input please! inclusion of ISR into top MC Different luminosity spectra! Conclusions • First analysis complete • “Realistic” (Guinea-pig) luminosity spectrum measurement • Interpolation of cross section in 4D parameter space • Cross section fitted using true and reconstructed luminosity spectra

  19. Backup slides

  20. Disadvantage • Must include ISR into top MC generation Parametrised beamstrahlung • Don’t use xm directly • Parameterise beamstrahlung f(a,b,c…) and fit for parameters. • For example CIRCE/Yokoya • Fit top threshold • Data is cross section smeared with true parameters • Theory is smeared with fit parameters • Advantage • Can extract beam spread!

  21. What about AFB and ppeak • How to include beam effects for • AFB • Similar to cross section • What about the boost (p 0) • Ppeak • Has similar problems • Interpolation? (5D) • Peak position not such a simple function of mt and s as cross section • Event generator based on toppik? • How about correlations between ptop and top

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