Bs →J/ Ψ (µ + µ - ) φ (K + K - )

1. Bs→J/Ψ(µ+µ-)φ(K+K-) Jan Amoraal Sander Klous

2. Introduction • Reconstruction and Selection • Cuts (Before/After and Combined) • Signal efficiency • Yield • S/B • MC data: • Signal 611300 (30000 events) • Background 370000 (~23000 events >10 M events) • LoKi for analysis

3. LoKi • Offline analysis package • Uses DaVinci • Algorithms in plain English e.g. φ Range kaons = select(“kaons”… Range kplus = select(“K+”… Range kminus = select(“K-” … For (Loop phi = loop(“K+ K-” … { phi->save(“phi”)}

4. Finding Optimal Cuts • Eliminate background from signal data • No Cuts (signal) • ΔM cut on φ,Ψ (signal) • VΧ2 on φ,Ψ (signal) • ΔM and VΧ2 on Bs (signal) • Run on background data and “hope” to find nothing

5. No Cuts: M (Signal) ΔMφ= 20 MeV and ΔMΨ= 50 MeV

6. No Cuts: VΧ2 (Signal) VΧ2φ < 5 and VΧ2Ψ < 5

7. ΔM cut on φ,Ψ (Signal)

8. VΧ2 on φ,Ψ (Signal)

9. ΔMV + VΧ2 on φ,Ψ (Signal)

10. Reconstructed Bs (Signal) No cuts VΧ2 ΔM

11. ΔM + VΧ2 on Bs (Signal) ΔM = 30 MeV and VΧ2 < 12

12. Finally Signal Data Background Data Nbkg=Lint*σbb*ε* εθ*(76/10M) = 3M

13. Oops Background • Use Pt > 500 MeV cut on muons and kaons • Nbkg = 500 k

14. Summary, Efficiency and Yield • See a reduction in background (combinatorics) • #Bs = 2534 (2246/3128 MC) after: • Pt cuts on muons and kaons • ΔM + VΧ2 on φ,Ψ • ΔM + VΧ2 on Bs • εoff = Nsel/Nevents* εθ= 2534/30k*0.34 = .029 (TDR 2003 0.0162) • Nprod= Lint * σbb * 2 * Prob(b→Bs) * BRvis = 2e15 * 500e-6 * 2 * 0.1 * 31e-6 = 6.2M • Noff = Nprod * εoff =178 k (TDR 2003 100k) • S/B = 178 k/ 500 k = 0.36 for 13 bkg

15. To Do • Still need to work on the background • CL on kaons and muons • IP parameter cut • Propertime • Maybe look at S/(S + B) to find optimal cuts