1. Recent KLOE results on rare K S K L processes M. Martini INFN, laboratori di Frascati on behalf of the KLOE collaboration Manchester, 19/07/2007

2. EPS 2007, Manchester M. Martini 19/07/2007 Dafne: the Frascati  -factory  e + e – collider with 2 separate rings  s  1020 MeV  M    peak  3  b  Best performances in: 2.5 fb  on tape @ √ s=M  ≈ 8×10 9  produced 250 pb  @ √ s=1000 MeV + 4 scan points around the   L peak = 1.4 × 10 32 cm  2 s  1  L int /day = 8.51 pb 

3. The KLOE experiment Superconducting coil B=0.6 T  Beryllium beam pipe   = 10 cm  0.5 mm thickness  lead/scint. fibers  barrel-endcap  15 X 0 thickness  4880 PM  98% coverage  E /E = 5.7% /  E(GeV)  t = 54 ps /  E(GeV)  140 ps  vtx (K L   0  0 ) ~ 1.5 cm   p /p = 0.4%   x/y = 150  m   z = 2 mm   vtx ~ 3 mm   (M  +  - )~1 MeV  (4 m   3.3 m)  90% He; 10% iC 4 H 10  Stereo geometry  52140 wires The KLOE design was driven by the measurement of direct CP violation through the double ratio: R =  (K L  +   )  (K S  0  0 ) /  (K S  +   )  (K L  0  0 ) and by the K L lifetime EPS 2007, Manchester M. Martini 19/07/2007

4. Kaon tagging K S tagged by K L interaction in EmC Efficiency ~ 30% (largely geometrical) K S angular resolution: ~ 1° (0.3  in  ) K S momentum resolution: ~ 2 MeV K L “crash”  = 0.22 (TOF) K S    e  K S    e  K L tagged by K S      vertex at IP Efficiency ~ 70% (mainly geometrical) K L angular resolution: ~ 1° K L momentum resolution: ~ 2 MeV KS  KS  KS  KS   KL  2KL  2KL  2KL  2 EPS 2007, Manchester M. Martini 19/07/2007

5. Talk layout EPS 2007, Manchester M. Martini 19/07/2007 Measurement of BR(K S  ) Direct search for K S  e + e - Measurement of BR(K L  e  CPT test with Bell-Steinberger relation QM test in K S K L system

6. NA48/1 Motivations for a new BR(K S  ) measurement It is a good test for ChPT (PRD 49 (1994) 2346) Experimental value of the BR changed along the years From 2003 it is known with a small error (3%) : BR(K S   ) = (2.71 ± 0.06 ± 0.04) x 10 -6 due to a measurement of NA48/1 collaboration Differs from ChPT O(p 4 ) by 30% (possible large O(p 6 ) contribution). In NA48, the K L  background is a relevant component of the fit. In KLOE, the background from K L is reduced to 0 (tagging). First measurement of this decay with a pure K S beam. EPS 2007, Manchester M. Martini 19/07/2007

7. * * * DATA BKG SIG cos(   ) * * * Strategy for BR(K S  ) measurement Data sample analyzed: 1.6fb -1 - K S tagged from K L interacting in EMC (122 x 10 6 events) - 2 prompt photons required (  496000 events) Background is made of K S  2  0 with 2 lost photons in the pipe or interacting in the calorimeter covering focusing quads (QCAL)QCAL  events with in time hits on QCAL vetoed. Background rejection from kinematic fitkinematic fit Event counting on the scatter plot M  vs  , where: -    Opening angle between the two photons in the K S cms -    Reconstructed  mass EPS 2007, Manchester M. Martini 19/07/2007

8. * FCN/Ndof = 1.2 K S  Fit results DATA -- MC all Signal Background To extract the number of signal, the 2D-plot in data is fit using signal and background shapes from MC N sig = 600.3 ± 34.8 (5.8% stat. error) EPS 2007, Manchester M. Martini 19/07/2007 cos(   ) *    (MeV)

9. K S  efficiencies and normalization After tagging, the events K S  2  0 events are used as normalization sample. The BR is then extracted as: For the signal:  SIG (tot| K L -crash) =  presel) x  (veto) x  (  2 ) =   = (50.8 ± 0.6)% For the normalization sample, K S  2  0 events counted selecting 4 prompt photons:  2  0 (tot | K L -crash) = (65.0 ± 0.2 stat ± 0.1 sys )% N 2  0 /  2  0 (tot | K L -crash) = 159.8 Mevts Systematics due to application of data-MC correction curve for cluster efficiency. Cross checked with counting (3-5) prompt photons (159.5 Mevts)  (presel) (83.2 ± 0.2)%  (veto) (96.5 ± 0.4)% (2)(2) (63.3 ± 0.7)% EPS 2007, Manchester M. Martini 19/07/2007

10.  PT O(p 4 ) O(p 6 )    KLOE  far from NA48 result - The NA48 measurement implied the existence of a sizeable O(p 6 ) counterterm in ChPT. Our number makes this contribution practically negligible K S  final BR result Source+Syst (%)-Syst (%) Signal acceptance0.12 QCAL0.880.51  2 cut 0.44  2,   scale from signal ---0.55 Fit procedure0.880.44 Energy scale---1.32 Norm sample0.15 Total+1.33-1.65 * EPS 2007, Manchester M. Martini 19/07/2007

11. K S   +  -   K S  +  -    +  -  0 K S  e + e - M inv [e  e  hypo] (MeV)  signal box Direct search for K S  e + e - ( ) event s election (1.32 fb -1 ) K S tagged by K L crash 2 tracks from IP to EmC with M inv [e+e- hypo] > 420 MeV  2 -like variable based on: - TOF of the 2 particles - E/p - distance between track impact point and cluster centroid P* (  hypo) in the K S rest frame  220 MeV M miss  380 MeV to reject residual       SM prediction is low but precise BR(K S  e + e - ) = 1.6  10 -15 [Ecker, Pich 91] EPS 2007, Manchester M. Martini 19/07/2007

12. Upper limit on K S  e + e -  Signal box MC optimization: (492  M inv  504) MeV and  2  20optimization N obs = 3 and  BKG = 7.1±3.6  we extract UL(  sig ) = 4.3 @ 90% CL using bayesian approachbayesian approach  sig =  presel  sel    -rad ( E*  < 6 MeV ) = 0.785  0.888  0.8 = 0.558   -rad   = 0.6, N  ~ 1.5  10 8 UL(BR) = UL(  sig )     sig BR  N    normalize to K S  (  ) counts in the same data set: BR(K S  e + e - (  )) < 2.1  10 -8 @ 90% CL KLOE preliminary: CPLEAR: < 1.4  10 -7 EPS 2007, Manchester M. Martini 19/07/2007

13. BR measurement of K L  e  - We measure R=BR(Ke3  ; E *  >30 MeV,  * lep-  >20°)/BR(Ke3(  )), using a 328 pb -1328 pb 2001-2002 data sample; - Both IB and DE emission contribute to R; - Separation between IB and DE never measured; for the first time the DE contribution is measured; - E *  -  * ele-  reconstructed by kinematic closure based on cluster position and tracking

14. BR(Ke3  ; E*   30 MeV,  * e-   20 0 ) BR(Ke3(  )) R = R = (0.924 ± 0.023 stat ± 0.016 syst )% theory [Gasser et al.,EPJ 40C (2005)205 ]: R = (0.96 ± 0.01)% (uncertainty mainly due to the DE term) Fit 2D plot of E*  and  * e-  with the MC shapes we measure:  * e-   deg) E*   (MeV) MC EPS 2007, Manchester M. Martini 19/07/2007 K L  e  final results According to Gasser et al. the spectrum can be parametrized as:

15. CPT test: Bell-Steinberger relation CPT test from unitarity based on K S -K L observables:      K S       00    K S            K S       kl3  S  L B(K L l3)  Re  Re y  i  Im x    S  L B(K L l3)  (A S +A L )/4  i Im x      S  L     K L           S  L     K L        EPS 2007, Manchester M. Martini 19/07/2007 SS 1 ff (1 + i tan  SW ) [Re  i Im  ]  A*(K S  f ) A(K L  f )   f  f before NA48 and KLOE measurement Im(  ) limited by  000 - trough main uncertainty now comes from  +- trough  +- KLOE contributionsKLOE contributions: K S semileptonic asymmetry, UL on BR(K S  0  0  0 )semileptonic asymmetry Im x  from a combined fit of KLOE + CPLEAR data

16. Re    Im   CPLEAR: Re    Im   KLOE result (JHEP 0612:011,2006) : Assuming  =0, i.e. no CPT in decay: -5.3  10 -19 GeV <  M < 6.3  10 -19 GeV at 95% C.L. EPS 2007, Manchester M. Martini 19/07/2007 CPT test: Bell-Steinberger relation

17. EPS 2007, Manchester M. Martini 19/07/2007 QM coherence  m  S,L The decay time difference distribution for K S     , K L       allows to measure  m and decoherence term  S,L. From CPLEAR data: In the B-meson system, BELLE: PLB 642(2006) 315

18. EPS 2007, Manchester M. Martini 19/07/2007 CPTV and quantum gravity |  | could be at most: In presence of decoherence and CPT violation induced by quantum gravity (CPT operator “ill- defined”) the definition of the particle-antiparticle states could be modified. This in turn could induce a breakdown of the correlations imposed by Bose statistics (EPR correlations) to the kaon state [Bernabeu, et al. PRL 92 (2004) 131601, NPB744 (2006) 180]:quantum gravity KLOE result (  measured for the first time) with L=2.5 fb -1 : Re  Im  PLB 642(2006) 315

19. EPS 2007, Manchester M. Martini 19/07/2007 CPTV and quantum gravity KLOE has now ~2.5 fb -1 data on disk Preliminary results based on 1fb -1 :  S,L = 0.009  0.022 STAT  0,0 = (0.03  0.12 STAT ) × 10 -5 1fb -1 Preliminary results on  based on 1fb -1 :  S,L = 0.018  0.040  0.007  0,0 =(0.10  0.21  0.04) × 10 -5 published result (380 pb -1 )  2 /dof=29/31

20. EPS 2007, Manchester M. Martini 19/07/2007 Conclusions KLOE has obtained new results on: - BR (K S   ) = (2.27 ± 0.14)  10 -6 - BR(K S  e + e - (  )) < 2.1  10 -8 @ 90% CL - K L   e  : R = (0.924± 0.023 stat ± 0.016 syst )% = (-2.3 ±1.3 stat ±1.4 syst ), Improved accuracy of CPT test with Bell-Steinberger relation Several parameters related to CPT and QM tests are measured at KLOE, Re(  ) and Im(  ) for the first time.

21. SPARES

22. - BR obtained by NA48 from a fit to the Z vertex distribution (K L   background is a relevant component in the fit) - In KLOE there is not background from K L   so we can perform the first measurement of this decay with a pure K S beam - We can reach an accuracy of about 5-6%, twice larger than NA48 but with completely different systematics and background.. Motivations..... II EPS 2007, Manchester M. Martini 19/07/2007

23. QCAL detector The QCAL tile calorimeters of KLOE are two compact detectors placed closed to the interaction point and surrounding the focalization quadrupoles. Their purpose is to increase the hermiticity of KLOE calorimeter. Each QCAL consists of a sampling structure of lead plates and 1mm scintillator tiles. EPS 2007, Manchester M. Martini 19/07/2007

24. QCAL veto  qcal distribution: Comparison between a K S     and a K S      sample EPS 2007, Manchester M. Martini 19/07/2007

25. QCAL data/MC efficiency - In each period, the event fractions with N  =2, 3, 4 have been fit with the following technique: we calculate the ratio: We found compatible value of R for the different DATA sample sample2001200220042005 R0.72 ±0.010.83 ±0.010.81 ±0.010.78 ±0.01 EPS 2007, Manchester M. Martini 19/07/2007

26. QCAL data/MC efficiency results Using the results on R and the Ploss for the different DATA samples, we can correct the MC QCAL efficiency for the signal. Now we have also extract the efficiency on signal from MC: For the complete sample we found: EPS 2007, Manchester M. Martini 19/07/2007

27. Energy scale and efficiencies K L  control sample selected to further check the energy scale on data-MC Signal and normalization sample free of K L   Inclusive energy of the 2  photons background   (MeV) EPS 2007, Manchester M. Martini 19/07/2007

28. Inclusive photon energy barrelecap barrelecap Data -- MC 2  BKG 4  K S   EPS 2007, Manchester M. Martini 19/07/2007

29. Energy scale and efficiencies K L  control sample selected to further check the energy scale on data-MC Signal and normalization sample free of K L   K S   M KL (MeV)M KS (MeV) EPS 2007, Manchester M. Martini 19/07/2007

30. We fit the distribution of reconstructed mass for data and MC at the end of analysis chain to check the energy scale calibration. Rt (cm)M KL data (MeV)M KL MC (MeV) (before calib) M KL MC (MeV) (after calib)  M KL (MeV) (Data – MC) (1 – 30)496.2 ± 0.8488.7 ± 0.4495.4 ± 0.50.8 ± 0.9 (35 – 65)495.0 ± 0.9488.1 ± 0.5494.7± 0.50.3 ± 1.0 (65 – 95)494.0 ± 1.0487.1 ± 0.6493.8 ± 0.60.2 ± 1.2 (95 – 125)494.3 ± 1.2486.1 ± 0.7492.4 ± 0.71.9 ± 1.4 (125 – 155)492.5 ± 1.5483.3 ± 0.9490.2± 0.92.3 ± 1.8 (155 – 185)484.8 ± 4.6475.6 ± 1.9481.4 ± 1.93.0 ± 5.0 Energy scale calibration… results After our scale correction, the data-MC scale agrees at (0.2 ± 0.2)% EPS 2007, Manchester M. Martini 19/07/2007

31. Energy scale systematics Since we still have a difference of (0.2 ± 0.2)% between data and MC on energy scale, we can extract a systematics varying of 0.2% and 0.4% M  from MC (signal and bkg). VariationN sig BR Standard600.3 ± 34.82.27 ± 0.13 x 1.002 596.8 ± 35.42.26 ± 0.13 x 1.004 591.6 ± 35.72.24 ± 0.14 We have a systematics of -0.03 on BR value EPS 2007, Manchester M. Martini 19/07/2007

32. Systematics…. - From KSGG sample Ploss_mean = (3.51 ± 0.04)% - From KS00 sample: Ploss_mean = (3.55 ± 0.06)% -From KS+- sample: Ploss_mean = (3.29 ± 0.05)% Ploss_win = (3.31 ± 0.05)% Summarizing, we can extract 2 different systematics:  mean (KS00 vs KS+-) = 0.26  out-win (KS+- vs KS+-) = 0.02 Summing up, we obtain 0.26%  qcal distribution: Comparison between a K S     and a K S      sample EPS 2007, Manchester M. Martini 19/07/2007

33. CutN sig BR x 10 -6 Standard (-5:5)600.3 ± 34.82.27 ± 0.13 (-4:4)601.3 ± 35.12.26 ± 0.14 (-6:6)602.2 ± 35.02.29 ± 0.14 Try to move qcal win  qcal = 96.47%  qcal = 97.18%  qcal = 95.76% Systematics=+0.02, -0.01 on BR value To extract the systematics on QCAL cut, we varied the windows around the chosen cut EPS 2007, Manchester M. Martini 19/07/2007

34. CutEffi anaN sig N bkg BR x 10 -6 1038.3 ± 0.7373.0 ± 25.9341.0 ± 35.62.29 ± 0.16 1656.2 ± 0.7530.1 ± 33.11079.9 ± 50.42.28 ± 0.14 1860.0 ± 0.7567.5 ± 35.11380.5 ± 55.42.26 ± 0.14 2063.3 ± 0.7600.3 ± 34.81678.7 ± 62.92.27 ± 0.13 2266.1 ± 0.7630.1 ± 35.31914.9 ± 70.42.28 ± 0.13 2468.2 ± 0.7650.5 ± 38.52295.4 ± 76.02.28 ± 0.14 Try to move  2 FIT cut To extract the systematics on  2 FIT, we slightly varied the value of the cut Systematics=±0.01 on BR value EPS 2007, Manchester M. Martini 19/07/2007

35. Try to move bins in scatter plot To extract a systematics on fit procedure, we slightly change the bins on the 2d distribution used in HMCLNL. Systematics= (+0.02 ; -0.01) on BR value M  bin Cos(    bin N sig N bkg BR x 10 -6 3050600.3 ± 34.81678.7 ± 62.92.27 ± 0.13 2545603.0 ± 35.01676.0 ± 63.12.28 ± 0.13 3555596.7 ± 33.91682.3 ± 62.52.26 ± 0.13 2555606.8 ± 35.11672.2 ± 62.82.29 ± 0.14 3545597.8 ± 34.61681.2 ± 61.52.26 ± 0.13 EPS 2007, Manchester M. Martini 19/07/2007

36. Cumulative …  2 FIT below DCH Using signal from K L , we can extract a systematics on  2 fit, building a cumulative for data and MC and checking the ratio. To reject the bkg we use a preliminary cut with  2 fit <50 and   <.998 Using the value at  2 fit =20, we obtain a systematics of -0.41% EPS 2007, Manchester M. Martini 19/07/2007

37. Cumulative …   below DCH Using the same technique developed for  2 fit, we can evaluate a systematics on   To reject the bkg we use a preliminary cut with  2 fit <50 and   <.998 Using the values at cos(   )=0.999, we obtain a systematics of -0.37% EPS 2007, Manchester M. Martini 19/07/2007

38. Fast simulation of Background To study the fit uncertainty as a function of MC statistics we have developed a method based on “hit or miss”. The procedure is only based on MC signal and background. Recipe for two components: Use the original 2d-distribution from signal and bkg, to create 2 smoothed distribution; Use hit or miss to create N different distributions for signal and background of different “fast” MC statistics; Create a fake data distribution using signal and bkg from hit or miss with statistics as in data sample; Repeat the fit procedure N times increasing the “fast” MC statistics. EPS 2007, Manchester M. Martini 19/07/2007

39. Fast simulation: M  vs   MC original distributions Fake DATA MC from hit or miss EPS 2007, Manchester M. Martini 19/07/2007

40. Hit or miss Signal and bkg statistical error as a function of the “fast” MC statistics When we performed this study, we had 0.5fb -1 of full MC. Now we have 1.1fb -1 and we obtained a lower uncertainty. We have already practically reached the plateau region.  (01-02) = 13.9%,  (04-05) = 7.5%  (01-02) = 12.0%,  (04-05) = 6.8% EPS 2007, Manchester M. Martini 19/07/2007

41. Background enriched sample Using HMCLNL we fit the 2D-plot for the bkg enriched sample (50 <  2 < 500). We obtain the bkg weight “  ”, that is used to estimate the bkg in the signal region. DATA -- MC all Signal Background EPS 2007, Manchester M. Martini 19/07/2007

42. Background enriched sample ProcedureN sig (upper band)BR x 10-6 Standard600.3 ± 34.82.27 ± 0.13 Bkg enriched sample608.2 ± 71.42.30 ± 0.27 Subtracting the obtained background to data, we obtain the expected number of signal events We obtain a results compatible with the number of signal events evaluated with the standard analysis. The larger error on N sig (upper band) is dominated by the poissonian uncertainty on the number of signal events. EPS 2007, Manchester M. Martini 19/07/2007

43. K S  e + e - : preselection EPS 2007, Manchester M. Martini 19/07/2007

44. K S  e + e - :  2 (I) EPS 2007, Manchester M. Martini 19/07/2007

45. K S  e + e - :  2 (II) EPS 2007, Manchester M. Martini 19/07/2007

46. K S  e + e - :  2 (III) EPS 2007, Manchester M. Martini 19/07/2007

47. K S  e + e - : p* in region 1 EPS 2007, Manchester M. Martini 19/07/2007

48. K S  e + e - : cut on N prompt EPS 2007, Manchester M. Martini 19/07/2007

49. K S  e + e - : cut on missing mass EPS 2007, Manchester M. Martini 19/07/2007

50. K S  e + e - : analysis chain EPS 2007, Manchester M. Martini 19/07/2007

51. K S  e + e - : E crash vs  * in sidebands EPS 2007, Manchester M. Martini 19/07/2007

52. K S  e + e - : optimization EPS 2007, Manchester M. Martini 19/07/2007

53. K S  e + e - : UL evaluation EPS 2007, Manchester M. Martini 19/07/2007

54. SM prediction is small but precise: BR(K S  e + e - )=1.6x10 -15 (Ecker, Pich 91) leaving room for possible new physics effects to be detected. The most precise measurement up to now is done by CPLEAR using or Selection is done by performing a kinematical fit to the hypothesis: with 9 constraints. At the end: N(data)=0 N(MC)=0.22 ± 0.10 BR(K S  e + e - ) < 1.4 x 10 -7 (90% C.L.) K S  e + e - : CPLEAR result EPS 2007, Manchester M. Martini 19/07/2007

55. Compare Data with tuned MC sample after fit. Inclusive distribution of the photon polar angles. K S  checking angular distribution DATA -- MC all Signal Background EPS 2007, Manchester M. Martini 19/07/2007

56. Direct search of K S  e + e - SM prediction is small but precise: BR(K S  e + e - )=1.6 x 10 -15 [Nucl. Phys. B336, 189, 1991] leaving room for possible new physics effects to be detected. The most precise measurement done by CPLEAR: BR(K S  e + e - ) < 1.4 x 10 -7 (90% C.L.) In KLOE we can perform a direct search of this decay using a pure K S beam. Data sample analyzed: 1.32 fb -1 Starting normalization sample: 148 Mevts (K L -crash and K S   +  - ) Preselection: - K S tagged by K L -crash - 2 tracks from IP with opposite curvature - Invariant mass in e + e - hypothesis M inv > 420 MeV  (sig) =  sig (K L -crash) x  sig (presel. | K L -crash)  0.3 x 0.785 = 0.24 After preselection: 1.1 Mevts in Data sample EPS 2007, Manchester M. Martini 19/07/2007

57. For signal identification, the calorimeter information is used to build a  2 -like variable  2 -like based on: - Sum and difference of (T clu -ToF) of the 2 particles - E/p of both particles - Transverse distance between track impact point and the closest cluster We define a signal box in the plane: (  2 vs M inv ) M inv is evaluated in e + e - hypothesis Side-bands are defined in the invariant mass spectrum: - to define background normalization - to check Data/MC agreement after further cuts are applied K S  e + e - : Analysis strategy Signal box EPS 2007, Manchester M. Martini 19/07/2007

58. The sources of background from MC are: - K S background events enter preselection because of track resolution -  +  -  0 events are selected with an accidental cluster satisfying the K L -crash algorithm The relative fraction of background in each region is: K S  e + e - : Background composition From MC… A: K S   +  -  B: K S  +  - C    +  -  0 K S  e + e - Bkg typeRegion 1Region 2Region 3 K S      45.8%13.2%0.6% KSKS 53.9%65.1%2.2%  0.3%21.7%97.2% EPS 2007, Manchester M. Martini 19/07/2007

59. K S  e + e - : Background calibration in reg.3 The scale factor for        component (background C) is evaluated in region 3, where the other decay modes give a negligible contribution: 2001-20022005 fCfC 1.99 ± 0.062.24 ± 0.04 EPS 2007, Manchester M. Martini 19/07/2007

60. With f C fixed, we can check MC prediction for A (K S        ) and B (K S      ) background components. Fitting M inv spectra in region 1: 2001-20022005 fAfA 0.59 ± 0.010.67 ± 0.01 fBfB 1.80 ± 0.012.39 ± 0.01 K S  e + e - : Background calibration in reg.1 EPS 2007, Manchester M. Martini 19/07/2007

61. To reject  +  - and  background events, we require : P*(  hyp) P*(  hyp) in K S rest frame > 220 MeV   = 0.014  sig = 0.962 K S  e + e - : Background rejection in reg. 2 EPS 2007, Manchester M. Martini 19/07/2007

62. To reject  +  - and  background events, we require : P*(  hyp) P*(  hyp) in K S rest frame > 220 MeV   = 0.014  sig = 0.962 To reject  +  -  0 contamination we require: M miss > 380 MeV M miss > 380 MeV and N prompt < 2N prompt < 2 Where M miss is evaluated from  momentum and tracks momentum (  hyp.)   = 0.001  sig = 0.998 K S  e + e - : Background rejection in reg. 2 EPS 2007, Manchester M. Martini 19/07/2007

63. - Optimization of signal box definition on Monte Carlo:Optimization (492 < M inv < 504) MeV and  2 < 20 obtained varying simultaneously M inv (± n  m ) and  2. The “optimized values” are chosen looking at:  bkg,  sig and signal efficiency. - In the signal box: N obs = 3  bkg = 7.1 ± 3.6 - UL(  sig ) evaluated numerically with bayesian approach, taking into accountbayesian approach background fluctuation (NIM 212 (1983) 319-322) UL (  sig ) = 4.3 @ 90% CL K S  e + e - : Sbox Optimization and UL Only simulation of 2001-2002 runs used so far for optimization EPS 2007, Manchester M. Martini 19/07/2007

64. Considering radiative corrections, there are two possible processes contributing to photon emission (not interfering): 1) K S  e + e - + IB photon emission 2) K S   *   e + e - Given the M inv cut, we actually measure the upper limit on: BR(K S  e + e - (  ) with E *  < 6 MeV) A limit on the second process is spoiled out in this M inv range by a factor of 10 -8. The cut used in M inv corresponds to an efficiency correction of: This factor must be included in  SIG. K S  e + e - : Radiative corrections EPS 2007, Manchester M. Martini 19/07/2007

65. Normalizing signal counts to K S   counts in the same data set:  sig (tot | K L -crash)=  sig (presel.|K L -crash) x  cut x   -rad = 0.785 x 0.888 x 0.8 = 0.558   -rad acceptance of the radiated photons for E *  < 6 MeV   (tot | K L -crash)= 0.6 N   1.5 x 10 8 K S  e + e - : Upper limit on BR KLOE preliminary EPS 2007, Manchester M. Martini 19/07/2007

66.     before NA48 and KLOE measuremnt Im(  ) limited by  000  +- trough  +- main uncertainty now comes from  +- trough  +-        kl3 (K S ) Main improvements: K S semileptonic asymmetry, UL K S  0  0  0 Im x  from a combined fit of KLOE + CPLEAR data EPS 2007, Manchester M. Martini 19/07/2007 CPT test: Bell-Steinberger relation

67. EPS 2007, Manchester M. Martini 19/07/2007 Decoherence and CPT violation Model of decoherence for neutral kaons => 3 new CPTV param.  ( NP B241 (1984) ) extra term inducing decoherence: pure state => mixed state At most: Deviations from QM could be due to Quantum Gravity effects which could cause pure state to evolve into mixed states: loss of quantum coherence. Modified Liouville – von Neumann equation for the density matrix of the kaon system: CPLEAR and KLOE have tested this model in single kaon and entangled kaon pair systems, respectively

68. EPS 2007, Manchester M. Martini 19/07/2007 Decoherence and CPT violation at 90% CL Using single kaons from, Fit simultaneously PLB 364, 239 (1999)

69. EPS 2007, Manchester M. Martini 19/07/2007 Decoherence and CPT violation  is measured for the first time in the entangled kaon system KLOE 380 pb -1 Fit I(  t;          ) (complete positivity assumption) KLOE fit I(  t;         ) under the assumptions of complete positive (it holds for entangled systems) i.e.  and  only  is fitted

70. EPS 2007, Manchester M. Martini 19/07/2007 QM coherence From CPLEAR data: KLOE result: In the B-meson system, BELLE coll.: PLB 642(2006) 315 Fit including  t resolution and efficiency effects + regeneration  S,  L  m fixed from PDG with 2.5 fb -1 ±0.8  10 -6

71. CPT test using K S,L   e EPS 2007, Manchester M. Martini 19/07/2007 Semileptonic charge asymmetries provide CPT tests If CPT holds, A S =A L =2Re  A S  A L signals CPT violation in mixing and/or decay with  S  Q  (K S,L   - e + )  (K S,L   + e - )  (K S,L   - e + )  (K S,L   + e - ) _ _ A S,L = from KLOE (450 pb -1 ): A S = (  1.5  9.6  2.9 )  10  3 A L = (3.322  0.058  0.047) 10  3 [KTeV 2002] A L = (3.317  0.070  0.072) 10  3 [NA48 2003] With 2.5 fb ,  A S  3×10  Using A L = (3.34 ± 0.07) x 10 -3 from KTEV, from A S -A L : Use Re(  ) from CPLEAR, x 5 improvement for error on Re(x - ) From A S +A L : First determination of Re(y) independently of B-S relation

72. E clu (MeV) E clu -E  eval (MeV) inclusive selection (328 pb -1 ): K L tagged by K S      (E miss -|P miss |) in different mass hypothesis to remove ~90% of bck ToF to separate e/  (after PID ~ 0.7% contamination)  2  10 6 K e3 K L  vtx -> comparing ToF of K L and the  - cluster time cluster position to close the kinematic and evaluate E  ->  p   = 0 = (p K -p  -p e -p  ) 2 Signal Ke3  out of acceptance not radiative K e3   +  -  0 K  3 measurement of BR and the Direct Emission term in the  spectrum radiative sample selection: this cut to remove not radiative K e3 E clu  25 MeV to remove accidentals NN trained with EmC infos to remove K  3 and       bck reduction: K L        control sample to check  efficiency, energy and vertex resolutions MC EPS 2007, Manchester M. Martini 19/07/2007 Analysis of K L  e 

73.  PT O(p 4 ) O(p 6 )    KLOE K S  final BR result Source+Syst (%)-Syst (%) Signal acceptance0.12 QCAL0.880.51  2 cut 0.44  2,   scale from signal ---0.55 Fit procedure0.880.44 Energy scale---1.32 Norm sample0.15 Total+1.33-1.65 * Various sources of systematics have been considered: -QCAL: - Change Qcal veto definitionQCAL - P loss comparison with: K S     and K S     samples. -  2 cut: change  2 cut definition  2 cut -  2,   scale: check data-MC scale difference using K L   2,   scale - Fit procedure: change bins size in 2D distributionFit procedure - Energy scale: correct data-MC energy scaleEnergy scale calibration using K L  * 3  far from NA48 result, but confirming ChPT prediction - The NA48 measurement implied the existence of a sizeable O(p 6 ) counterterm in ChPT. Our number makes this contribution practically negligible EPS 2007, Manchester M. Martini 19/07/2007

74. K S  kinematic fit EPS 2007, Manchester M. Martini 19/07/2007 To further reduce background a Kinematic fit is used with the following constraints: - P KS (K L -crash) = P KS (2  ) - M  = M KL - T = Rc for the two photons N DOF = 7 DATA -- MC signal + background MC Signal Before QCAL cut

75. K S  kinematic fit EPS 2007, Manchester M. Martini 19/07/2007 To further reduce background a Kinematic fit is used with the following constraints: - P KS (K L -crash) = P KS (2  ) - M  = M KL - T = Rc for the two photons N DOF = 7 DATA -- MC signal + background MC Signal After QCAL cut