1. Sinéad M. Farrington University of Liverpool for the CDF Collaboration ICHEP 28 th July 2006 Rare B Decays at CDF

2. 2 Outline Will show two analyses from CDF: B d,s      very rare decay (10 -9 in Standard Model) strong probe of new physics scenarios Briefly also show: B s  D s D s not so rare (10 -3 ) interesting CP properties 0 0

3. 3 B d,s   0

4. 4 B   in the Standard Model In Standard Model FCNC decay B   heavily suppressed Standard Model predicts A. Buras Phys. Lett. B 566,115 B d   further suppressed by CKM coupling (V td /V ts ) 2 Both are below sensitivity of Tevatron experiments SUSY scenarios (MSSM,RPV,mSUGRA) boost the BR by up to 100x Observe no events  set limits on new physics Observe events  clear evidence for new physics

5. 5 The Challenge Large combinatorial background Key elements are select discriminating variables determine efficiencies estimate background search region pp collider: trigger on dimuons   )~24MeV Mass resolution: separate B d, B s

6. Vertex muon pairs in B d /B s mass windows Unbiased optimisation, signal region blind Aim to measure BR or set limit: Reconstruct normalisation mode (B +  J/  K + ) Construct likelihood discriminant to select B signal and suppress dimuon background Measure remaining background Measure the acceptance and efficiency ratios 6 Methodology

7. Proper decay length ( ) Pointing (  ) |  B –  vtx | Isolation (Iso) 7 B   Selection Discriminating variables:

8. 8 Likelihood Ratio Discriminant Likelihood discriminant more powerful than cuts alone i: index over all discriminating variables P sig/bkg (x i ): probability for event to be signal or background for a given measured x i Obtain probably density functions of variables using background: Data sidebands signal: Pythia Monte Carlo sample

9. 9 Optimisation Likelihood ratio discriminant: Optimise likelihood for best 90% C.L. limit Bayesian approach include statistical and systematic errors Optimal cut: Likelihood ratio >0.99

10. 10 Unblinded Results 1 event found in B s search window (expected background: 0.88  0.30) 2 events found in B d search window (expected background: 1.86  0.34) (In central-central Muon sample only) BR(B s   ) < 1.0×10 -7 @ 95% CL < 8.0×10 -8 @ 90% CL BR(B d   ) < 3.0×10 -8 @ 95% CL < 2.3×10 -8 @ 90% CL central-central central-extension (These are currently world best limits)

11. 11 Bs  DsDsBs  DsDs 0

12. 12 B s  D s D s Results of B s mixing analysis at CDF have yielded measurement of  m s (see talk at this conference by Stefano Giagu)  gives complementary insight into CKM matrix 1/  (CP even) <1/  (CP odd) since the fast transition b  ccs is mostly CP even Biggest contribution to lifetime difference comes from B s  D s D s (pure CP even) Can constrain  by measuring branching fractions

13. 13 Relative BR Measurement BR (B s  D s D s ) measured relative to B 0  D s D - Control mode: B s  D s D s : 3 D s modes Reconstructed Total yield:23 3 D s modes Reconstructed Total yield:395

14. 14 Summary Made BR measurement of CP mode B s  D s D s B d,s     are a powerful probe of new physics Could give first hint of new physics at the Tevatron These are world best limits Impacting new physics scenarios’ phase space SO(10) Constrained MSSM hep-ph/0507233 Phys. Lett B624, 47, 2005

15. 15 Back-up

16. 16 Searching for New Physics Two ways to search for new physics: direct searches – seek e.g. Supersymmetric particles indirect searches – test for deviations from Standard Model predictions e.g. branching ratios In the absence of evidence for new physics set limits on model parameters BR(B   1x10 -7 Trileptons l+l+ l-l- l+l+ q q Z* W+W+ q   

17. 17 Expected Background Extrapolate from data sidebands to obtain expected events Scale by the expected rejection from the likelihood ratio cut Also include contributions from charmless B decays B  hh (h=K/  ) (use measured fake rates)

18. now 18 Limits on BR(B d,s   ) BR(B s   ) < 1.0×10 -7 @ 90% CL < 8.0×10 -8 @ 95% CL BR(B d   ) < 3.0×10 -8 @ 90% CL < 2.3×10 -8 @ 95% CL These are currently world best limits The future: Need to reoptimise after 1fb-1 for best results Assume linear background scaling

19. 19 B   in New Physics Models SUSY could enhance BR by orders of magnitude MSSM: BR(B   )  tan 6  may be 100x Standard Model R-parity violating SUSY: tree level diagram via sneutrino observe decay for low tan  mSUGRA: B   search complements direct SUSY searches Low tan   observation of trilepton events High tan   observation of B   Or something else!  ’ i23  i22   b s RPV SUSY A. Dedes et al, hep-ph/0207026

20. 20 Expected Background Tested background prediction in several control regions and find good agreement OS-: opposite sign muon, negative lifetime SS+: same sign muon, positive lifetime SS-: same sign muon, negative lifetime FM+: fake muon, positive lifetime

21. 21 Likelihood p.d.f.s Input p.d.f.s: Isolation Pointing angle Ct significance New plots***

22. six dedicated rare B triggers using all muon chambers to |  |  1.1 Tracking capability leads to good mass resolution Use two types of muon pairs: central-central central-extension 22 CDF Central Muon Extension (0.6< |  | < 1.0) Central Muon Chambers (|  | < 0.6)

23. 23 B d,s   K + /K*/  B Rare Decays B +   K + B 0    B s     b   FCNC b  s  * Penguin or box processes in the Standard Model: Rare processes: Latest Belle measurement observed at Babar, Belle hep-ex/0109026, hep-ex/0308042, hep-ex/0503044 x10 -7  

24. 24 Motivations 1) Would be first observations in B s and  b channels 2) Tests of Standard Model branching ratios kinematic distributions (with enough statistics) Effective field theory for b  s (Operator Product Expansion) Rare decay channels are sensitive to Wilson coefficients which are calculable for many models (several new physics scenarios e.g. SUSY, technicolor) Decay amplitude: C 9 Dilepton mass distribution: C 7, C 9 Forward-backward asymmetry: C 10

25. 25 Samples (CDF) Dedicated rare B triggers in total six Level 3 paths Two muons + other cuts using all chambers to |  |  1.1 Use two types of dimuons: CMU-CMU CMU-CMX Additional cuts in some triggers:  p t (  )>5 GeV L xy >100  m mass(  )<6 GeV mass(  )>2.7 GeV

26. Signal and Side-band Regions Use events from same triggers for B + and Bs(d)   reconstruction. Search region: - 5.169 < M  < 5.469 GeV - Signal region not used in optimization procedure Sideband regions: - 500MeV on either side of search region - For background estimate and analysis optimization. Search region Monte Carlo   )~24MeV

27. MC Samples Pythia MC Tune A default cdfSim tcl realistic silicon and beamline pT(B) from Mary Bishai pT(b)>3 GeV && |y(b)|<1.5 – B s    (signal efficiencies) – B+  JK+   K+ (nrmlztn efncy and xchks) – B+  J  +    (nrmlztn correction)

28. R. Dermisek et al., hep-ph/0304101 SO(10) Unification Model tan(  )~50 constrained by unification of Yukawa coupling All previously allowed regions (white) are excluded by this new measurement Unification valid for small M 1/2 (~500GeV) New Br(Bs   limit strongly disfavors this solution for m A = 500 GeV Red regions are excluded by either theory or experiments Green region is the WMAP preferred region Blue dashed line is the Br(Bs   ) contour Light blue region excluded by old Bs   analysis   h 2 >0.13 m  + <104GeV m h <111GeV Excluded by this new result

29. Method: Likelihood Variable Choice Prob( ) = probability of B s   yields > obs (ie. the integral of the cumulative distribution) Prob( ) = exp(- /438  m) yields flat distribution reduces sensitivity to MC modeling inaccuracies (e.g. L00, SVX-z)

30. Step 4: Compute Acceptance and Efficiencies Most efficiencies are determined directly from data using inclusive J/    events. The rest are taken from Pythia MC.  (B+/Bs) = 0.297 +/- 0.008 (CMU-CMU) = 0.191 +/- 0.006 (CMU-CMX)  LH (Bs): ranges from 70% for LH>0.9 to 40% for LH>0.99  trig (B+/Bs) = 0.9997 +/- 0.0016 (CMU-CMU) = 0.9986 +/- 0.0014 (CMU-CMX)  reco-  (B+/Bs) = 1.00 +/- 0.03 (CMU-CMU/X)  vtx (B+/Bs) = 0.986 +/- 0.013 (CMU-CMU/X)  reco-K (B+) = 0.938 +/- 0.016 (CMU-CMU/X) Red = From MC Green = From Data Blue = combination of MC and Data