1. Study of the semileptonic decays at 4170 MeV Koloina Randrianarivony Marina Artuso (Syracuse University)

2. 2 Motivations Apply our techniques to other semileptonic decays. Study the modes that haven’t been seen yet.

3. 3       K s            K + K - )  -  +  -  - K*K*(K s K -  +  - )  -  Analysis Techniques e+ e- (1 -- ) D s +* (D s + ) +...D s - (D s -* )  (K + K - ) e +, K* 0 (K +  - ) e +, K 0 (  +  - ) e + n SIGNAL SIDE TAGGED SIDE: + CC Event The same 8 modes as in D s + →  + CBX 06-36 And  '(  +  - ) e +

4. 4 Selection criteria Data sample ~310 pb -1 at ~4170 MeV Track Quality Cuts: Hit fraction > 0.5 Good fit |d0|<0.5cm and |Z0|<5.0cm |cosθ| < 0.93 |p| >0.04 GeV Particle ID Both dE/dX & RICH PID if |p| > 0.7GeV dE/dX PID if 0.2 < |p| < 0.7 GeV 4σ dE/DX consistency cut if |p| < 0.2 GeV, from Radia’s analysis (CBX 05-24).        PID for both Kaon and Pion. |    Mass-PDG|< Г=0.050 GeV e  electron ID. |p| > 0.2GeV. F RICH ≥ 0.8       PID for both Kaons. |  Mass-PDG|< 2x Г=0.01 GeV  '  Mass constrained fit for . Add 2 opposite charged PID Pions. K 0 Use standard VXFit Package.

5. 5 MM* 2 = (E cm – E D - E  ) 2 – (- p D – p  ) 2 Look for any extra photon and select events within ± 2.5 σ These are our number of tags MM* 2 (GeV 2 ) Signal MC KK  - K*e 50%  -tag 50%  -he Alpha and N are fixed from fully reconstructed D s - D s *+ events where one Ds is ignored (CBX 06-36) Cut on M bc Є [2.015, 2.067] Look at the invariant mass of the tags and cut on 2-2.5  depending on the modes

6. 6 MM* 2 per modes for D s → K* 0 e MM* 2 (GeV 2 ) SIGNAL MC Number of Events

7. 7 MM* 2 (Data) MM* 2 (GeV 2 ) The same number of tags as Nabil: 18645 ± 426 Number of events

8. 8 MM 2 MM 2 (GeV 2 ) Get ± 2.5 effective sigma  = f 1  1 + (1-f 1 )  2 # of semileptonic events, the effective sigma will be used for the rest of the modes to get the sum. Signal MC KK  - K*e 50%  -tag 50%  -he On the signal side Fit with a 2 gaussian Kinematic fitting is used on tag and signal sides

9. 9 Use of sideband subtraction MM 2 (GeV 2 ) From sidebands From signal side D s + → K* 0 e + GENERIC MC

10. 10 D s  K* 0 e Efficiencies We get the weighted average SL efficiency = (28.34 ± 0.27)%

11. 11 Using our efficiencies and Comparison with the generic MC for D s  K* 0 e With N Tags = 187158 ± 1052 N Signal = 35 ± 6 And  SL = (28.34 ± 0.27)%, we get Generic-MC Br (D s + → K* 0 (K  )e + ) = (8.6 ± 1.6)% Input Br MC (D s + → K* 0 (K  )e + ) = 7 x 10 -4 * The number of events are sideband subtracted

12. 12 MM 2 (GeV 2 ) MM 2 for D s + → K* 0 (K  )e + (Data) 7 signal events 0 background from the sidebands K +  - mass Є [0.846, 0.946] GeV Number of events

13. 13 Comparison ISGW2 model vs. Simple Pole Model ISGW2 SLPOL P  (GeV) D s  e Analysis

14. 14 D s  e Efficiencies Semileptonic efficiencies 

15. 15 Comparison with Generic MC for D s  e PP N SL * B i (D s →  e )(%) 0.0 – 0.240.66 ± 0.34 0.2 – 0.4540.54 ± 0.07 0.4 – 0.61440.41 ± 0.04 0.6 – 0.81280.39 ± 0.04 > 0.8440.47 ± 0.36 Total3742.49 ± 0.36 Using our efficiencies and With N Tags = 187158 ± 1052 Input Generic Br(D s →  e ) = 2.02 % * The number of events are sideband subtracted

16. 16 MM 2 (GeV 2 ) MM 2 for D s + →  (KK)e + (Data) 47 signal events 0 background from the sidebands K + K - mass Є [1.010, 1.030] GeV Number of events

17. 17 D s  K 0 e Efficiencies We get the weighted average SL efficiency  SL = (33.15 ± 0.24)%

18. 18 Comparison with the generic MC for D s  K 0 e With N Tags = 187158 ± 1052 N Signal = 52 ± 7 And  SL = (33.15 ± 0.24)%, we get Generic-MC Br (D s + → K 0 (  )e + ) = (0.23 ± 0.03)% Input Br MC (D s + → K 0 (  )e + ) = 0.2% Using our efficiencies and * The number of events are sideband subtracted

19. 19 MM 2 (GeV 2 ) MM 2 for D s + → K 0 (  )e + (Data) 10 signal events 8 background from the sidebands  +  - mass Є [0.48765, 0.50765] GeV Number of events

20. 20 D s  'e Efficiencies We get the weighted average SL efficiency  SL = (21.64 ± 0.26)%

21. 21 Comparison with the generic MC for D s  ' e With N Tags = 187158 ± 1052 N Signal = 56 ± 7 And  SL = (33.15 ± 0.24)%, we get Generic-MC Br (D s + →  ' (  )e + ) = (0.8 ± 0.1) % Input Br MC (D s + →  ' (  )e + ) = 0.9% Using our efficiencies and * The number of events are sideband subtracted

22. 22 MM 2 (GeV 2 ) MM 2 for D s + →  ' (  )e + (Data) 5 signal events 0 background from the sidebands K +  - mass Є [0.950, 0.964] GeV Number of events

23. 23 Branching Fractions from Data (1) PP N SL * B i (D s →  e )(%) 0.0 – 0.20 0 0.2 – 0.440.40 ± 0.20 0.4 – 0.6160.46 ± 0.12 0.6 – 0.8250.77 ± 0.16 > 0.820.22 ± 0.15 Total471.86 ± 0.32 With a number of tags = 18645 ± 425 Due to a very small efficiency at p  < 0.2 GeV, we modeled the partial branching fraction by taking the fraction of  yield in that range to  yield in the rest of the momentum intervals. We estimate it as: Br (p <0.2 GeV) (D s →  e ) = (0.8 ± 0.8 (syst))%  Br (D s →  e ) = (2.6 ± 0.3)% Compare to PDG 06 Br (D s →  e ) = (2.4 ± 0.4)%

24. 24 Branching Fractions from Data (2) SL DecaysN SL * Br (%)Br P.D.G 06 (%) D s + → K* 0 (K  )e + 70.19 ± 0.07 ─ D s + → K 0 (  )e + 100.47 ± 0.15 ─ D s + →  '(  )e + 50.71 ± 0.321.08 ± 0.35 With a number of tags = 18645 ± 425 and

25. 25 Summary and Predictions Br(Ds→  e ) = (2.6 ± 0.3)% Br(D s + → K* 0 (K  )e + ) = (0.19 ± 0.07)% Br(D s + → K 0 (  )e + ) = (0.47±0.15)% Br(D s + →  '(  )e + ) = (0.71±0.32)% And with Br(D s + →  e + ) = 3.3% We have Br(D s + →Xe + ) excl = (7.27 ± 0.84)% With a mean life τ = 0.5 ps, we get Г = 0.1294 ± 0.0169 ps -1 Г + = 0.1551 ps-1 x 0.5ps = 0.077  7.7%