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Status of K s  3  0 analysis

M. Martini, S. Miscetti. Status of K s  3  0 analysis. Summary of work in progress Data-MC calibration of c 2 2 p and c 2 3 p New fit procedure for bkg Systematics on bkg determination time-scale for the paper. Summary of work in progress.

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Status of K s  3  0 analysis

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  1. M. Martini, S. Miscetti Status of Ks 3  0 analysis • Summary of work in progress • Data-MC calibration of c22p and c23p • New fit procedure for bkg • Systematics on bkg determination • time-scale for the paper

  2. Summary of work in progress • Almost all the questions posed by Matt have been attached • The MC production 2004 have been successfully used after calibration of the • energy scale as shown in the past meeting. • We now refer as: • -- OLDMC the production AllPhys+NeuKaon 2003 • -- NEWMC the poduction AllPhys+NeuKaon 2004 • For a whole MC Luminosity of 450x2 pb-1. • Considering the ekcra (MC/data)= 50% vs 30% we gain another factor 5/3. • Whole MC eff.Lumi 1500 pb-1 • We have modified/added some steps in our analysis to simplify • and improve the procedure for the bkg calibration. • We believe that the background studies is now COMPLETE • Tomorrow we will have a private meeting with the referees to show in further • details the analysis status and if we agree in all points we start immediately to • update the memo.

  3. Calibration of c22p and c23p DATA MC Mp Mp MC DATA DE DE In the construction of the c2 we have used, up to now, the values of sE and sM observed in a golden sample of KS2p0 events. We have now modified this in the analysis using a different sigma for each sample. DATA and MC (OLDMC, NEWMC) (2001 ,2002 ).

  4. New calibration procedure for fakes One of the criticized step of our analysis is the determination of the quantity of fake KCRASH. Two questions were posed: 1) Quantify the statistical error connected to the calibration: Instead of using our old standalone recipe we move to fitting the 1D-plots with HMCMLL inserted in a standalone Minuit program. Statistics of data and MC sample are now considered in the fitting procedure and an error is assigned to the resulting fake content. 2) Evaluate the systematic on fake determination due to the range used for fit. Instead of trying all possible cuts we decided to use a 2D-Fit. We have translated a 2d-Histogram of 20x40 bins in 1D-Histogram of 800 bins and used the standard HMCMLL procedure.

  5. New fake-calibration procedure c22p c23p In the new calibration we use 2D histogram with an almost entire scale Old SBox definition: 14<c22p<40 c23p<3.5

  6. New Fake-Acci-Split calibration procedure • To better calibrate DATA and MC, we have also questioned how well the MC reproduces the amount of double shower fragments and double accidental clusters. To understand and calibrate this we have divided the MC Kcrash events into 2 further classes: • 2A: events of Ks2p0 in overlap with 2 accidental (~ 60% ) • 2S: events of Ks2p0 with 2 splitted clusters or 1 accidental + 1 splitted cluster (~ 35%) To do this, we perform a 3 components fit (2S, 2A and fake events)

  7. New Fake-Acci-Split calibration procedure c22p c22p ALL 2 S c23p c23p c22p c22p Fake 2 A c23p c23p

  8. New Fake-Acci-Split calibration procedure ALL 2 S Bin Number Bin Number Fake 2 A Bin Number Bin Number

  9. New Fake-Acci-Split calibration procedure Bin Number Bin Number Bin Number Bin Number • Data • FIT • We remind that the calibration • is carried out separately • for the different samples: • NEW 2001 • NEW 2002 • OLD 2001 • OLD 2002 • For each sample we now have • 3 weights with a whole • correlation matrix

  10. New Fake-Acci-Split calibration procedure sample Correlation matrix dij Weights Wi with errors eWi Events of each type Ni with errors eNi Ndata with error expected from MC For a single sample this is a typical fit result

  11. Result of Fake-Acci-Split calibration  DATA -- MC ALL c22p<14 c23p c23p 14<c22p<40 c22p>40 c23p c23p A good agreement is observed in each scatter plot region

  12. DATA-MC comparison at beginning of ana Sbox CSbox UP Cup Down CDown Summing up 2001-2002 for each MC, we can compare DATA with the two different MC productions. NEW OLD A reasonable data-MC comparison is found for both samples.

  13. Result of Fake-Acci-Split calibration CUP UP Sbox CSbox Cdown Down

  14. Review of the analysis chain OLD counting Track Veto DECUT c2fit Sbox optimization NEW Track Veto Optimiz counting DE/sE c2fit Sbox DE DE/sE Since we have observed a little difference on sE between DATA and MC (and we have correct this effect into c2 definition), we have changed DE_CUT into DE_CUT/sE.

  15. Events rejected by Track veto  DATA -- MC DE/sE

  16. Events retained afterTrack veto  DATA -- MC DE/sE

  17. Optimization The optimization is done with the usual technique with a factor two improvement on the MC statistics thus reducing the Discretization problem. In this case we obtain the best ratio between surviving background and signal efficiency with the following set of cuts: c23p< 4.64 12.07 < c22p< 60 c2fit < 40.43 DE/sE > 1.69 In this way we have a signal efficiency esig = (24.8 ± 0.8stat )% and we found2 eventswith3.1 ± 1.6statexpected by MC

  18. Data-MC comparison after optimization ALL c22p<14 c23p c23p 14<c22p<40 c22p<40 c23p c23p  DATA -- MC

  19. Data-MC comparison after optimization Comparison between DATA and MC after the optimization procedure.

  20. Evaluation of Systematic errors on bkg To evaluate systematic error, we perform our analysis changing the most relevant parameters • Increase sE and sM to sE+dsE and sM+dsM • Decrease sE and sM to sE-dsE and sM-dsM • We correct in the MC the little data-MC shift on the average • MC values found in the control sample Ks2p0. • 5) Use the fit parameters calculated including also the signal box • 6) Use the fit parameters calculated not distinguishing between 2S - 2A

  21. Evaluation of Systematic errors on bkg c2fit -- DATA -- MC c2fit From optimization we obtain: c2fit < 40.5 We search the value for MC cut which gives the some retain integral observed in DATA. We obtain a variation of +5%.

  22. Systematic error 11,63 9,57 0,00 24,86 12,28 6,98 We have evaluated the events shift in each box:

  23. Time scale for paper … • From our side the evaluation of the bkg has been completed and • all suggestions/critiques of referees have been taken into • consideration. However, tomorrow we will have a long meeting • to go much further in detail on each item with the referees. • We have another week of work to do in addressing the questions • related to the systematics on the efficiency for the signal and the • normalization. • We expect to complete the revision of the analysis for first week • of December. • next week we start updating the memo for the background side. • and then we will give it back to the referees for final approval. • Plan is to have a complete memo for mid-Dicember and a first PLB • for x-mas

  24. Conclusions • We have successfully calibrated and used the whole new and • old MC production so doubling the statistics for the BKG evaluation. • Most of the referees comments on the bkg determination pushed us • to improve and clean our technique which now seems to us to be • very stable showing satisfactory data-MC comparisons. • We have other two weeks of hard work to complete the syst. on • the evaluation of signal efficiency and normalization • Planning to have a paper as a x-mass gift.

  25. OLD calibration procedure Normalization 1 c22pwith c23p<3.5 MC KcraMC Fake Both calibration done excluding signal box. We use the mean value of weights. MC KcraMC Fake Normalization 2 c22pwith c23p<8.8

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