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Status of CC Analysis

Status of CC Analysis. J.Thomas for CC working group. Everything looks reasonable as function of pot and time. NUMI performance. Set of standard cuts agreed upon to select runs with ‘good’ beam. Set of loose cuts to get into MC/Data ball park. Data Preselection. Efficiency about 90%

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Status of CC Analysis

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  1. Status of CC Analysis J.Thomas for CC working group

  2. Everything looks reasonable as function of pot and time NUMI performance

  3. Set of standard cuts agreed upon to select runs with ‘good’ beam Set of loose cuts to get into MC/Data ball park Data Preselection

  4. Efficiency about 90% Purity about 80% Data Preselection

  5. 5 special runs were taken to check out beam modelling MC/Data disagreement changes with beam energy Points to beam modelling, not detector modelling LE-10(170,185,200) pME pHE

  6. Different beams map out different areas of pT and xF. Attempt to learn about secondary hadron production as well as beam settings from this information Based on BMPT parametrization, try to fit it PTxF

  7. SKZP Parametrization

  8. First done for simple additional cuts on top of preselection The results depend on the event selection. The results shown are for the CC event selection described later SKZP Parametrization

  9. Investigate the low level quantities: problem is always to make sure MC and Data are both apples before you compare them Make assumption that CC events better modelled/understood than NC Event selection relies more heavily on muon modelling than shower modelling SR fitter is used to track muons MC/Data Comparisons

  10. SR Fitter Efficiency

  11. Muon Tracking

  12. Variables for CC selection

  13. Agreement between MC and Data is not perfect at this stage These variables are put into a PDF to select a high purity sample of CC events Variables for CC Selection

  14. Cut is imposed at –0.2 for ND and –0.1 for FD PDF MC

  15. Now that data and MC resemble each other, it is possible to compare low level quantities Shower Ph/plane is NOT well modelled. We have not seen this level of ‘dirty laundry’ from Super-K or K2K EM modelling, reconstruction effects….. MC/Data comparisons

  16. Muon and Shower Energy

  17. y and Total E Distribution

  18. Special runs were carried out to study the effect of intensity on event selection No non-linearities were observed Very low intensity data proved this Intensity Studies

  19. The main worry is that the modelling agreement between Data and MC differs between ND and FD There is no evidence that this is the case, even when MC and Data do not agree Since Oxford, agreement between Data and MC has been significantly improved at low y by a reconstruction fix An important cross check for all parameter measurement methods is to assume all ND data/MC difference is due to such problems Summary of data checks

  20. There are 4 methods currently being used to study our sensitivity Fixing MC Generator parameters and systematics in the ND (DP) F/N MC ratio to extrapolate ND data to FD predicted spectrum (TV) GNUMI flux matrix to relate neutrinos of energy Ef in FD to neutrinos of energy En in near detector multiplies ND data to give predicted FD spectrum (NS) Fitting of systematics, generator parameters in grid of E and y in ND (MI) Oscillation Parameter Measurements

  21. DP Fit

  22. This approach uses reconstructed energy dependent F/N to multiply contents of ND data energy bin to produce FD predicted spectrum Oscillations are applied to Etrue in each bin of Ereco MINUIT fitting allows exhaustive systematic studies to be carried out by means of 100s of ‘pseudo runs’ to estimate the combination of systematics at 1e20 statistics F/N extrapolation (TV)

  23. F/N Pseudo Run : vanilla

  24. F/N systematic checks

  25. F/N Systematic Error

  26. This method uses the GNUMI flux files to generate a matrix which relates a neutrino of energy Ef in FD to one of energy En in ND Ereco to Etrue in ND, cross section matrices cancel, efficiency of ND selection, matrix,FD efficiency,Etrue to Ereco via oscillations Matrix Method (NS)

  27. Matrix Method Extrapolation

  28. Systematic studies have been carried out on the sensitivity of this method Particular systematics are applied to the FD or ND and FD spectra and then the fits carried out Matrix Method (NS)

  29. Data has 9% more events than MC in ND Matrix Method (NS)

  30. A new MDC was carried out last week. 100 sub-runs of 1e20 were generated 100e20 data set was used to measure possible statistical biases in fit methods All four methods were in agreement within errors Second batch of MDC has been generated with combinations of systematics. Some analysis have analised this too, but not all, not enough time Systematics have been studied exhaustively in any case 2006 MDC

  31. F/N 2006 MDC

  32. Difference between pseudo runs and 100e20 is negligible in Dm2 Difference of 0.04 in sin22q F/N 2006 MDC

  33. Right plots indicate the statistical fluctuations one might expect with 1e20 p.o.t Left plot for 200e20 Matrix 2006 MDC

  34. DP method Dm2 = 0.00225 sin22q = 0.940 c2=33.1/18 2006 MDC results • F/N • Dm2 = 0.0023+/-0.00006 • sin22q = 0.950 +/-0.027 • c2=64/57 • Matrix • Dm2 = 0.00220+0.00005-0.00002 • sin22q = 0.96-0.025 • c2=43/12 • Masaki • Dm2 = 0.00236 • sin22q = 0.933 • c2=33.1/18

  35. F/N has been checked out by Niki Matrix is being studied by Chris David has been cross checked by Brian and Alycia Masaki has not been cross checked We will hear from Brian and Chris at this meeting These cross checks will be completed before we go public Status of Cross Checks

  36. Exhaustive checks on data have been carried out 10% statistical error suggests we are in a region of diminishing gains Systematics are understood to be well below the statistical error cc group proposal is to open the box tonight Results will be available tomorrow morning Programme of cross-checks has to be put in place for the run up to the W&C Proposal is for W&C to be on Thursday of Collaboration meeting What now?

  37. I’ve given a brief overview of where we are to put it all in context Now we will listen in detail to the analyses Questions should be addressed to the speaker as we go along But first……

  38. From ND data, predict the FD spectrum for no oscillation case 4 different methods give 4 different answers ND selection the obvious culprit… And finally, the FD spectrum

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