1. Status of K S   e analysis C. GattiT. Spadaro Selection on data Selection on MC Efficiencies from data, K L   e, K S    ,      , bhabha Efficiencies from MC, K L   e, K S    ,      , bhabha Efficiencies from MC, K S    , single-particle method for 2001  Efficiencies from MC, K S    , single-particle method for 2002  Dedicated MC for the signal, on a period-by-period basis  Efficiencies from MC, KS  e, single-particle method HONEST time scale: weeks Present status of analysis: × × ×

2. Fitting with “old” or “new” MC Different shape of the background distribution Fit residuals are not flat in the signal region

3. Fitting with “new” MC Different shape of the background distribution Fit residuals are not flat in the signal region

4. What is new in the “new” MC Many methodological differences between “new” and “old”: NEW analysis: K L crash algorithm now applied in the MC exactly as in data Different treatment of split tracks NEW MC production: DC Wire sags HW wire efficiency simulated Different s-t relations EMC Muon cluster energy rescaled Pion nuclear interactions revised K L nuclear interactions revised GENERATION: K Se3 now available on a run-by-run basis OLD MC scratched from tapes, we can study it only using selected evts

5. Comparing “old” vs “new” MC Background composition: “  ” K S       with      before the DC “  ” K S      with bad reconstruction, tracking and/or T CL ’s “  ” K S       with an hard , tails of T CL resolution K S   K S      Not K S K L events: , K  K  with a fake K L crash

6. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

7. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

8. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

9. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

10. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

11. Comparing “old” vs “new” MC Checking shape of Background components identified as e     E miss  cP miss (MeV)

12. Comparing “old” vs “new” MC Background composition: compare #(selected evts)/#(K S    10 4 K S   K S   KSKLKSKL OLD e    8.38(5)3.80(3)1.01(2)0.067(4) NEW e    2.02(3)10.50(7)3.83(4)0.78(1)0.076(6) 0.19(7) OLD e    8.16(5)3.48(3)0.94(2)0.065(4) NEW e    2.07(3)9.43(7)3.22(4)0.53(2)0.064(5)0.068(6)0.19(7)

13. Comparing “old” vs “new” MC Core of the tracking resolution, compare K S   samples from: Home-made production for 25 pb  downscaled 100 The same production reconstructed with the old s-t rel. P t (MeV)  P (MeV) P t (MeV)  of correction (MeV) 0.2 To endcap To barrel

14. Comparing “old” vs “new” MC Core of the tracking resolution, check gaussian smearing comparing new MC, new MC smeared, and data M  (MeV) Core of M 

15. Comparing “old” vs “new” MC Core of the tracking resolution, check gaussian smearing comparing new MC, new MC smeared, and data M  (MeV) Left tail of M  : resolution tail +  early decays + radiation

16. Comparing “old” vs “new” MC Core of the tracking resolution, check gaussian smearing comparing new MC, new MC smeared, and data M  (MeV) Right tail of M  : resolution tails

17. Comparing data vs “new” MC K Le3 sample used to check the distribution for the signal: K S  tight selection, 490<M  <500 MeV, 100<p * <120 MeV K S  auto-triggering Separation between K S and K L hemispheres Estimate K L momentum from K S (different than the K L crash estimate) Correct position of the K L vertex sampling from the KS lifetime, moves KL cluster positions accordingly Apply the same cuts used for the K S analysis

18. Comparing data vs “new” MC Data:  2.9 MeV MC:  2.8 MeV  (E miss  P miss ) (MeV) Check standard deviation of the E miss  P miss distribution: Y2001Y2002 Y2001Y2002Y2001Y2002 Y2001Y2002

19. Conclusions 1.Checking selection on NEW MC + track momentum smearing: a)Background component distributions b)Selection efficiency on the background 2.Understand in depth  tail below the signal 3.Resolution check MC old vs MC new 4.K L crash contribution to the E miss  P miss sample: repeat with the NEW MC smeared, using a sample with Kcrash + 1 trk (P*p cut) 5.We are checking many other variables, able to separate between background components: vertex quality, PID, Pmiss