Track reconstruction and physics analysis in LHCb

1. Track reconstruction and physics analysis in LHCb • Outline • Introduction to the LHCb experiment • Track reconstruction → finding and fitting • Physics analysis → event selection and sensitivity study • More details in my thesis: Track simulation and reconstruction in LHCb Seminar: Particle and Astrophysics U Zürich, Physik Institut 07 December 2005, Jeroen van Tilburg, NIKHEF

2. Reminder: CP violation CKM matrix connects the quark mass eigenstates with the weak interaction eigenstates ~ e-iγ CKM matrix ~ e-iβ ~ eiχ Complex phases in matrix elements → CP violation

3. The Large Hadron Collider The LHCb detector The LHC tunnel CERN, Geneva

4. 21 stations R and φ sensors The LHCb detector ~1.41.3 m2 ~65 m2 VELO

5. Track types Velo tracks: used to find primary vertex. Long tracks: used for most physics studies: B decay products. T tracks: improve RICH2 performance. Upstream tracks: improve RICH1 performance, moderate p estimate Downstream tracks: enhance KS finding. Different track types, different algorithms

6. Track event display Average # of tracks in b-events: 34 VELO, 33 long, 19 T tracks, 6 upstream, 14 downstream + Total 106 reconstructed tracks Outer tracker station VELO TT T1 T2 T3

7. Example: Matching algorithm Matches T tracks with VELO tracks to find long tracks: → estimate momentum of T track → extrapolate T track through magnet to the VELO → find best match (based on χ2 cut). → add TT hits

8. Matching algorithm: estimate p δp/p=0.7% Estimate momentum of the T track with p-kick method: → Magnetic field is ~ an instant kick at focal plane z=zmagnet. → Assume track originates from interaction point. → Re-evaluate center of magnet (zc). p-kick method p-kick zc zmagnet VELO T seed T stations Bdl ~ 4.2 Tm

9. Matching χ2 Efficiency = 91.2% Wrong combinations = 4.8% p > 5 GeV

10. Adding TT hits for matched tracks → Extrapolate matched tracks to TT stations. → Group the hits depending on distance to track. → Find best group of TT hits. Group the hits: Distance d to track < 10 mm Δd in same station < 1 mm Δd in other station < 2 mm Group has at least 3 hits Hit can belong > 1 group

11. Adding TT hits Tune wspread Select the group with the lowest q2. q2 = d2 + w2spread sd2 Distance deviation of group Average distance of group

12. Long track performance Average number of hits: 12.7 VELO, 3.0 TT, 2.4 IT, 17.5 OT + Total 35.6

13. Long track performance ghost rate efficiency g = 7.7% (p>5 GeV) ε = 94.3% (p>5 GeV)

14. Tracking robustness relative multiplicity Tracking is robust against number of interactions

15. Track fit prediction step filter step The tracks are fitted using the Kalman Filter. • The Kalman Fit properties: • Adds measurements recursively. • Mathematically equivalent to least χ2 method. • Multiple scattering and energy loss can be naturally included.

16. Outlier removal Outliers (hits with high χ2 contribution) can be removed. → requires a refit → remove only 1 hit per iteration

17. Outlier removal (long tracks) Number of iterations Improves χ2 distribution

18. Fit quality (long tracks)

19. Momentum resolution LHCb provides an excellent momentum estimate at the vertex. Reconstructed tracks Ideal tracks Note: Fitted with single Gaussian in each bin.

20. Impact parameter @ vertex

21. Physics analysis • Two benchmark decay channels of LHCb: • Bs→ Dsπ measures Δms(Bsoscillation frequency) • Bs→ Ds K measures γ-2χ (CP violation) • For my thesis I studied the • event selection for these decays, and the • final sensitivity on Δms and γ-2χ

22. Branching fractions Decay channel Branching fraction Annual production Bs→ Ds±π± 1.2 * 10-4 26 M events Bs→ Ds± K± 1.0 * 10-5 2.1 M events Event topology

23. Bs→ Ds* K and Bs→ Ds K* Bs→ Ds* K and Bs→ Ds K* Included two similar channels: K*± → K0π± (67%) → half decays to Ks0 K± π0(33%) Ds*± → Ds± γ (94%) Event topology

24. Selection strategy • Preselection to reduce background→ using standard LHCb applications (DaVinci and LoKi) • Remove specific backgrounds→ using a single cut • Tune remaining cuts against generic background→ using an optimisation tool

25. 1. Preselection Loose cuts

26. 2. Specific background Bs→Dsπ background in Bs→DsK selection → cut on RICH likelihood

27. 2. Specific background For instance, cut at ΔlnLKπ=3 gives: Fit both mass distributions simultaneously to find the number of signal events (S) and its error (σS). ±50 MeV

28. 2. Specific background Vary ΔlnLKπ cut to find the optimum with respect to the statistical significance of the signal:

29. 3. Generic background • Optimisation tool: • Optimise remaining cuts simultaneously • Divide each selection variable into equidistant bins. • Scan the total selection space. • Find the combination of cuts for which is maximal.

30. Final selection cuts

31. Efficiencies and yield Efficiencies quoted in %. Lower detection efficiency Low yield Need to cut harder due to high background

32. Decay time resolution and pull Resolution Pull distribution

33. Acceptance function Selection and trigger cuts reduce efficiency at zero decay time After selection and trigger

34. Sensitivity study Matter Antimatter

35. Sensitivity study • Use Toy Monte Carlo and Fitting Program: • Generate events according to expected annual yield and with realistic time errors from full simulation. • Account for acceptance function. • Perform an unbinned likelihood fit to “observed” decay time distribution. • Fit both Bs→Dsπ and Bs→DsK events simultaneously.

36. “Observed” decay times Bs→DsK 3 years

37. Default parameters

38. Computing power Submitted ~10k jobs (=experiments) on the DataGrid:

39. Oscillation frequency Sensitivity on Δms Δms deviation for 100 “experiments”: Amplitude method: After 1 year

40. Sensitivity on weak phase Weak phase: γ-2χ Error bars represent RMS fluctuation. Sensitivity for 100 “experiments” after 3 years. 1 year: σ = 15.2º

41. Conclusions • Different track reconstruction algorithms developed for the different track types (e.g. the matching algorithm). • The LHCb experiment provides an efficient track reconstruction of 94% with a ghost rate of 8% (p>5 GeV). • LHCb has an excellent spatial (42 um) and momentum resolutions (0.35%) at the interaction point. • Three-step event selection for Bs→Dsπ and Bs→DsK provides a sufficient background reduction. • After 1 year of running LHCb can measure Δmsup to 88 ps-1 and γ-2χ with an error of 15.2º.