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Kloe General Meeting University “La Sapienza” Rome 13-14/11/2003

Kloe General Meeting University “La Sapienza” Rome 13-14/11/2003. Preliminary results on Ks  3 p 0 search. M. Martini and S. Miscetti. Preliminary results on Ks  3 p 0 search. M. Martini and S. Miscetti. Analysis outlook: Comparison Data-MC, starting from DST dk0,mk0

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Kloe General Meeting University “La Sapienza” Rome 13-14/11/2003

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  1. Kloe General Meeting University “La Sapienza” Rome 13-14/11/2003 Preliminary results on Ks  3p0 search M. Martini and S. Miscetti

  2. Preliminary results on Ks  3p0 search...... M. Martini and S. Miscetti • Analysis outlook: • Comparison Data-MC, starting from DST dk0,mk0 • Data 450 pb-1 • MC 150 pb-1 (NewKaon) • Kinematic fit procedure • Definition of pseudo-c2 to improve S/B • c2 2p • c2 3p • Study of the background shape Data vs MC • Adjusted simulation to reproduce observed bkg rate • Track veto cut • E gamma cut and...first conclusions Kloe General Meeting 14/11/2003 M.Martini

  3. Events filter • Tuning of acceptance cuts (6 pb-1 Data, MC) looking for highest e while retaining 0 candidates in events with 6 neutral clusters: TW = 3.5 s ; Ecut = 7 MeV ;  = 22,5° 58% • Standard Kcrash Tag (100 MeV, large b* window ) • Kinematics fit (from S. Giovannella) applied using Ks momentum estimated by Kcrash (and ) by requiring 4-momentum conservation on the Ks side (c2 fit). • Major expected background: KS00 + 2 accidental (or splitted) clusters. • In order to improve S/B we defined two pseudo-c2 to look for KS20vs KS30 Kloe General Meeting 14/11/2003 M.Martini

  4. Application of Kinematic fit Constraining the Ks side with expected Ks momentum by Kcrash gives good rejection but leaves a sizeable quantity of bkg events!! Kloe General Meeting 14/11/2003 M.Martini

  5. Construction of the c2 2p • c2 2pis built selecting 4 out of 6 clusters which better satisfy the kinematics of KS into 2 pions decay • The kinematics parameters used are: • Mass distributions • Opening angle between pions in Kaon C.M. Frame • Four-momentum conservation KL KS All this is done using the reconstructed cluster parameters before applying the kinematic fit procedure Kloe General Meeting 14/11/2003 M.Martini

  6. Variables used in constructing c2 2p KS 2p with 4 gamma final state Red line MC Black dots DATA Kloe General Meeting 14/11/2003 M.Martini

  7. Definition of c2 2p c2 2p is the c2 that we build searching the best combination of 4 out of 6 clusters which represents a KS 2p0. The best combination is the one minimizing: Kloe General Meeting 14/11/2003 M.Martini

  8. c2 3p At the moment, the c2 3p is based only on the 3 reconstructed pion masses Data MC Comparison Data-Mc before splash filter Splash filter consists of: - Ngam = 6 Emean < 40 MeV Mmean < 40 MeV - Ngam = 4 Emean < 50 MeV Mmean < 50 MeV Kloe General Meeting 14/11/2003 M.Martini

  9. c2 3p Data MC Comparison Data-Mc after splash filter Kloe General Meeting 14/11/2003 M.Martini

  10. Data MC comparison of c2 2pvs c2 3p2001:a surprise! Data 2001 MC 2001 In the data, a new category of BKG events (not simulated by the “standard Gatti-Spadaro” Kcrash MC) appears. Their simulation takes into consideration only KL decaying after a cilinder bigger than DCH and smears the KL MC direction with the KL crash resolution observed in data. Kloe General Meeting 14/11/2003 M.Martini

  11. A NEW SIMULATION OF Klcrash (AcciK) To understand these events whenever no Kcrash is found by the standard Kcrash MC we add the possibility to find a Kcrash applying the standard data cuts (E and b*) Running this new Kcrash simulation on 2002 MC we find other 1320 entries with respect of to the 9657 events already simulated in the 6 prompt clusters sample. • There are three different sources of these new BKG events: • AcciKcrash  K crash by accidental (1) • T0stolen  Golden cluster by accidentals (2) • Klpipe  K crash by KL daughters inside Rt = 25 cm (3) Kloe General Meeting 14/11/2003 M.Martini

  12. c2 2pvs c2 3p 2002sample MC Ks3pi Data MC Ks2pi Kloe General Meeting 14/11/2003 M.Martini

  13. Comparison “Data-MC” c22p, no c2cut All c23p c23p > 80 Normalization with 6 g rate reasonable in the overall plot but missing to reproduce the observed rate in these regions c23p < 80 c23p < 200 Kloe General Meeting 14/11/2003 M.Martini

  14. Adjusted simulation Data MC KcraMC AcciK Normalization kk1 c23p<80 Normalization kk2 c23p<200 MC KcraMC AcciK Data Kloe General Meeting 14/11/2003 M.Martini

  15. Adjusted normalization Normalization: ID1 = Data ; ID2 = MC(Kcrash) ; ID3 = MC(AcciK) ID1 = a1ID2 + a2ID3 Where: Ndata = Number of entries of the c2 fit plot for data Nmc = Number of entries of the c2 fit plot for mc • Normalization from two different plots: • kk1  Coefficients calculated from c2 2p with c2 3p less then 80 • kk2  Coefficients calculated from c2 2p with c2 3p less then 200 • kkm  The average value between kk1 and kk2 Kloe General Meeting 14/11/2003 M.Martini

  16. Comparison “Data-MC” c22p, no c2cut All c23p c23p > 80 Normalization with kk1 values c23p < 80 c23p < 200 Kloe General Meeting 14/11/2003 M.Martini

  17. Comparison “Data-MC” c22p, no c2cut All c23p c23p > 80 Normalization with kk2 values c23p < 80 c23p < 200 Kloe General Meeting 14/11/2003 M.Martini

  18. Comparison “Data-MC” c22p, no c2cut All c23p c23p > 80 Normalization with kkm values c23p < 80 c23p < 200 Kloe General Meeting 14/11/2003 M.Martini

  19. Comparison “Data-MC” c2fit, no c2 cut Result of normalization FIT: KK1 KK2 Kmed Kcra MC  1.120 1.129 1.123 AcciKcra  2.881 2.406 2.643 Kloe General Meeting 14/11/2003 M.Martini

  20. Comparison “Data-MC” c23p, no c2cut All c22p c22p > 40 Normalization with 6 g rate 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  21. Comparison “Data-MC” c23p, no c2cut All c22p c22p > 40 Normalization with kk1 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  22. Comparison “Data-MC” c23p, no c2cut All c22p c22p > 40 Normalization with kk2 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  23. Comparison “Data-MC” c23p, no c2cut All c22p c22p > 40 Normalization with kkm values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  24. Definition of the Signal box Up Cup Sbox CSbox Down Cdown Kloe General Meeting 14/11/2003 M.Martini

  25. Comparison Data-MC As explained before we use this sample without any cFITto check the reliability of the “adjusted” simulation on reproducing the rate in the signal and control boxes. NO CUTS on c2fit. Kloe General Meeting 14/11/2003 M.Martini

  26. Comparison “Data-MC” c2fit, c2<30 Kloe General Meeting 14/11/2003 M.Martini

  27. Comparison “Data-MC” c23p, c2<30 All c22p c22p > 40 Normalization with kk1 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  28. Comparison “Data-MC” c23p, c2<30 All c22p c22p > 40 Normalization with kk2 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  29. Comparison “Data-MC” c23p, c2<30 All c22p c22p > 40 Normalization with kkm values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  30. Comparison Data-MC Check reliability of the “adjusted” simulation when a c2<30 cut is applied. Kloe General Meeting 14/11/2003 M.Martini

  31. Next cuts ... TRKOK All c22p c22p > 40 Counting only tracks with: r(PCA)<4 cm Z(PCA)<10 cm To reject tracks from qcal. Veto events with TRKOK>0 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  32. Kinematic distributions after c22p,c23p • Another byproduct of • the c22p variable is that • we can test if the energy associated to the four selected photons looks like • coming from KS 2p0 • This is a really good discriminating variable between the two processes as shown here. • Cutting at the level of the blue arrow reduces the background to ½ without touching the signal. • A little harder cut can also be very useful to max. the UpperLimit ( study will follow by MC) --- Data no 2 cut • Data 2 < 30 • --- MCBG no 2 cut • MCBG 2 < 30 •  MCSIG K meeting 14/10/2003 M.Martini

  33. Study of EgCUT • --- MCBG no 2 cut • MCBG 2 < 30 • MCGG 2 + TRKOK • MCSIG • At the end of analysis: • 2 < 30 • TRKOK • Signal Box Applying EgCUT<9 only AcciK remain in Signal Region KcraMC AcciK Kloe General Meeting 14/11/2003 M.Martini

  34. Next cuts ... EgCUT TRKOK TRKOK+EgCUT TRKOK+EgCUT+c2 All c22p c22p > 40 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  35. Candidates... • At the end of analysis we have: • 5 candidates from “Data” @ 450 pb-1 • 3 expected from “MC” @ 150 pb-1 Nrun: 24051 Nev: 7110735 NTracks: 0---------------------------------------------- Reconstructed pions masses: M1 = 114.5806 MeV M2 = 125.6421 MeV M3 = 108.1511 MeV ---------------------------------------------- Chi2 fit: 17.32738 Chi2 pair: 17.72474Chi3 pair: 73.09442 Number of kcrash: 1Ekcra: 210.6075 MeV Beta Kcra: .2319278Number of clusters: 9---------------------------------------------- Clusters parameters: Cluster Energy (MeV) Nsigma Angle 1 122.7134 .3378006 1.265235 2 112.8406 1.413125 .7238826 3 87.42661 1.504362 2.373147 4 39.42066 1.709174 2.366150 5 118.7905 1.757564 2.336169 6 35.05759 1.826631 2.369749----------------------------------------------- Kloe General Meeting 14/11/2003 M.Martini

  36. Preliminary calculation of the Upper Limit... The efficiencies are: The number of events with 4 g from data are: To calculate the BR we can use: Only suppose the Kcrash is the same in 2p and 3p Kloe General Meeting 14/11/2003 M.Martini

  37. Preliminary calculation of the Upper Limit... From P.D.G. 2002: Assuming Poissonian statistics and using the upper end of confidence interval we found: Substituting the values: Mean expected background = 3 Events observed = 5 Very Preliminary Very Preliminary Kloe General Meeting 14/11/2003 M.Martini

  38. Conclusions • After MC adjustment reasonable agreement Data-Mc • Next weeks • Run all Newkaon statistics (400 pb-1) • Estimate MC errors • Search the best signal box • Definitive Upper limit Kloe General Meeting 14/11/2003 M.Martini

  39. c2 2p vs c2 3p MC 2001 MC 2002 Kloe General Meeting 14/11/2003 M.Martini

  40. Comparison “Data-MC” c2fit, c2<100 kkm Norm. 6g Norm. kk2 Norm. kk1 Norm. Kloe General Meeting 14/11/2003 M.Martini

  41. Comparison Data-MC Check reliability of the “adjusted” simulation when a c2<100 cut is applied. Kloe General Meeting 14/11/2003 M.Martini

  42. Comparison “Data-MC” c23p, c2<100 All c22p c22p > 40 Normalization with 6 g rate 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  43. Comparison “Data-MC” c23p, c2<100 All c22p c22p > 40 Normalization with kk1 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  44. Comparison “Data-MC” c23p, c2<100 All c22p c22p > 40 Normalization with kk2 values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

  45. Comparison “Data-MC” c23p, c2<100 All c22p c22p > 40 Normalization with kkm values 14<c22p < 40 c22p < 14 Kloe General Meeting 14/11/2003 M.Martini

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