Progress in angular acceptance study

1. Progress in angular acceptance study Yuehong Xie University of Edinburgh 12 March 2009

2. Reminder of previous talk • Talk in bs meeting 22 January 2009 • Proposed a event-by-event method to include effects on angular distributions from • detector geometry • kinematic cuts • particle efficiencies • Discussed the possibility to calibrate particle efficiencies using control channels

3. This talk • How well does our model work with fully simulated data? • Predict Bs→J/yf average acceptance functions • Develop methods to calibrate particle efficiencies

4. Full simulation test • Test if the following factors can explain the observed angular acceptance • detector geometry • cuts on particle P and/or Pt • dependence of particle reconstruction efficiency on kinematics (P and Pt) • Use B+→J/yK+ • cosqm in J/y rest frame w.r.t. B direction in this frame • cosqK in B rest frame w.r.t. (0,0,1)

5. Detector geometry • Only explicitly require charged tracks are inside Velo acceptance • Pt/Pz >0.02 • Pt/Pz <0.4 • Effects of other detector geometrical acceptance enter the momentum-dependent particle efficiency

6. Explicit cuts • Use standard DC06 selection • Kaons: Pt > 1.3 GeV, P > 10 GeV • Muons: Pt > 500 MeV • J/y: Pt > 1 GeV

7. Particle efficiency e(P) • Obtain efficiency as a function of P for muons and kaons respectively from MC truth muon kaon P (GeV) P (GeV)

8. Test method • Get reconstructed distribution of an angle • Follow steps in my previous talk to construct conditional pdf for each event • Use known theoretical distributions • Use per event angular acceptance function • Sum of conditional pdf should match the reconstructed distribution if the considered factors in the per event angular acceptance model are adequate

9. cosqm known theoretical distribution: 1- cos2qm reconstructed sum of conditional pdf cosqm

10. Average efficiency of cosqm Relative difference from MC truth from conditional pdf cosqm cosqm

11. cosqK known theoretical distribution: flat reconstructed sum of conditional pdf cosqK

12. Average efficiency of cosqK from MC truth Relative difference from conditional pdf cosqK cosqK

13. Part I summary • Our model describes the basic trend of the angular acceptance functions • has prediction power • Some fine tunings of the model are needed to reduce the ~10% relative difference • e.g. consider particle efficiency as a function of P and Pt

14. Average acceptance in Bs →J/yf ~ 20% variation cosqtr ftr cosy

15. Effects of Pt/Pz>0.02 ~ 5% relative variation ftr cosqtr cosy

16. Effects of Pt/Pz<0.4 ~ 5% relative variation cosqtr cosy ftr

17. Effects of particle efficiencies < 5% relative variation cosqtr cosy ftr

18. Effects of Kinematic cuts ~20% relative variation cosqtr cosy ftr

19. Part II summary • Shapes of angular acceptance functions in Bs→J/yf roadmap document are confirmed • Decreasing order of importance • Kinematic cuts • Velo geometry • Particle efficiencies

20. Obtain particle efficiency e(P) from B+→J/yK+ • Assume an initial form of e(P) • The P distribution of a certain particle can be predicted and compared with the reconstructed P distribution • If the predicted and reconstructed P distributions don’t match, update e(P) • Iterate until a perfect match

21. Iteration 0: start with em(P)=1 reconstructed predicted with em(P)=1 updated eff. muon P distributions in GeV em(P) for muons

22. Part III summary • Have found a simple way to check consistency of assumed e(P) with data • Aim to obtain e(P) • w/o using MC truth • w/o any assumption of B momentum spectrum • A few steps away from success • Still have some technical problems to get e(P) converged to the right form • Non-trivial to deal with background