Tracking performance in LHCb

1. Tracking performance in LHCb IV INTERNATIONAL SYMPOSIUM ON LHC PHYSICS AND DETECTORS FermiLab, Chicago May 1-3 2003 Tracking Performance Jeroen van Tilburg NIKHEF On behalf of the LHCb collaboration • Overview: • LHCb setup • Velo/ST/OT performance • Track finding • Track fitting Tracking Performance in LHCb, Jeroen van Tilburg

2. LHCb setup 21 stations R and φ sensors ~1.41.2 m2 ~65 m2 VELO Tracking Performance in LHCb, Jeroen van Tilburg

3. Vertex Locator • Vertex Locator: • 21 stations. • R/φ sensors (single sided, 45º sectors). • Pitch ranges from 37 μm to 103 μm. • 220 μm thin silicon. • Sensitive area starts at only 8 mm from beam axis. Tracking Performance in LHCb, Jeroen van Tilburg

4. Silicon Tracker T3 T2 T1 OT IT TT • Trigger Tracker: • 4 layers arranged in 2 stations. • 30 cm split. • 400/500 μm thin silicon. • Stereo views: 0°,+5°,-5°,0°. • 198 μm readout pitch. • 170k readout channels. • Used in L1 trigger. The Silicon Tracker: Two parts: 1. IT (Inner Tracker) 2. TT (Trigger Tracker) Tracking Performance in LHCb, Jeroen van Tilburg

5. Inner Tracker • Inner Tracker • 3 stations (T1-T3) with 4 layers each (0°,+5°,-5°,0°). • 320 μm thin silicon. • 198 μm readout pitch. • 130 k readout channels. After clustering: ~30% ~65% Tracking Performance in LHCb, Jeroen van Tilburg

6. Outer Tracker • Outer Tracker • 3 stations (T1-T3) with 4 double layers (0°,+5°,-5°,0°). • 5 mm straws. • Fast drift gas (Ar(75)/CF4(15)/CO2(10)) → Signal collection < 50 ns. • 25 ns beam crossing → spillover from previous and next spills. • Straws are 4.7 m with readout on top and below (long modules). • 50k readout channels. Short prototype module OT double layer cross section Track 5mm straws e- e- e- pitch 5.25 mm e- e- Tracking Performance in LHCb, Jeroen van Tilburg

7. Outer Tracker Average occupancy in OT ~ 4 % (hottest region ~ 7 %) Cross shape determined by restricting the OT occupancy: Core σ = 200 μm Resolution: Tails due to low momentum secondaries: p > 2 GeV Tracking Performance in LHCb, Jeroen van Tilburg

8. Track finding Geant3 LHCb event display • Track finding challenges in LHCb • High density of hits and tracks. • Track pattern recognition must be fast (in trigger and offline). • High track efficiency important (especially for many-prong decays). Tracking Performance in LHCb, Jeroen van Tilburg

9. Track finding Zoom of OT station (hits in red) • Track finding challenges in LHCb • High density of hits and tracks. • Track pattern recognition must be fast (in trigger and offline). • High track efficiency important (especially for many-prong decays). Tracking Performance in LHCb, Jeroen van Tilburg

10. Track finding algorithms • Velo tracks: • Find straight line segments in Velo. • Start search for triplets in R-z projection. • Then add φ hits and extend track to other sensors. • Important for finding primary vertex. • Efficiency ~ 97%, ghost rate < 5%. Velo tracks Tracking Performance in LHCb, Jeroen van Tilburg

11. Track finding algorithms • Forward tracks: • Starts with Velo track and find continuations in TT and T1-T3. • Uses optical model. • Accurate measurement of momentum. • Long track: important for most physics studies. B decay products. • Efficiency ~ 90%. • Afterwards the used hits are discarded for use in remaining algorithms. Velo tracks Forward tracks Tracking Performance in LHCb, Jeroen van Tilburg

12. Track finding algorithms • Seed tracks: • Stand-alone track finding in stations T1-T3. • Tracks almost straight lines (parameterized as parabola). • First search for x-hits then add stereo hits. • Improves RICH2 performance. Velo tracks Forward tracks Seed tracks Tracking Performance in LHCb, Jeroen van Tilburg

13. Track finding algorithms • Matched tracks: • Try to match Seed tracks with Velo tracks. • First, estimate momentum from deflection of Seed track. • Then extrapolate Seed track to Velo. Match with Velo track. • Finds remaining long tracks: additional to Forward tracks. • Adds ~ 2% to efficiency for long tracks. Velo tracks Forward tracks Seed tracks Matched tracks Tracking Performance in LHCb, Jeroen van Tilburg

14. Track finding algorithms • Velo  TT (VTT): • Finds tracks without hits after the magnet (momentum too low). • Start with unused Velo tracks. • Find a continuation of at least 3 hits in TT. • Magnetic deflection before TT: moderate momentum estimate Δp/p~20%. • Improve RICH1 performance, slow pions, kaon tagging. Efficiency ~75%. Velo tracks Forward tracks Seed tracks Matched tracks VTT tracks Tracking Performance in LHCb, Jeroen van Tilburg

15. Track finding algorithms • T  TT (or Upstream): • Find tracks without hits in Velo. • Start with unused Seed tracks and try to add hits in TT. • Estimate momentum from deflection Seed track. • Final momentum estimate Δp/p~0.4% • Enhance KS finding. Pion efficiency ~74%. Velo tracks Forward tracks Seed tracks Matched tracks VTT tracks T  TT tracks Tracking Performance in LHCb, Jeroen van Tilburg

16. Track finding algorithms • Finally apply clone killing algorithm. • Select the best candidate among tracks that share many hits. Velo tracks Forward tracks Seed tracks Matched tracks VTT tracks T  TT tracks Many track types, many algorithms Tracking Performance in LHCb, Jeroen van Tilburg

17. Event display Average number of tracks per event: 27 Long (Forward + Matched), 23 Velo, 10 VTT, 10 T  TT 4 Seed tracks + Total 74 Average efficiency = 92 % Efficiency for B daughters ~ 95% Event withaverage occupancy: Red: measurements (hits) Blue: reconstructed tracks Tracking Performance in LHCb, Jeroen van Tilburg

18. Tracking performance Efficiency vs p Ghost rate vs pcut Ghost rate vs pTcut Long tracks Long tracks 95% 8% 8% Long tracks Total ghost rate = 16% Ghost rate pT>0.5 GeV ~ 8%. Large event to event fluctuations. Average efficiency = 92 % Efficiency for p>5GeV > 95% Tracking Performance in LHCb, Jeroen van Tilburg

19. Robustness tests Ninteractions Ninteractions Tracking is robust against number of interactions • Tracking is also robust against: • Lower hit efficiencies, • Decreased hit resolutions, • More noise hits. • Note: • Luminosity adjusted to have the maximum number of single interactions. • Pile-up veto trigger (L0) rejects multiple interaction events. Tracking Performance in LHCb, Jeroen van Tilburg

20. Track fit The tracks are fitted using the Kalman Filter. • The Kalman Fit: • The prediction step. • The filter step. Adds measurements one-by-one. • The smoother step. direction of the filter track prediction filtered track • The Kalman Fit properties: • Adds measurements recursively. • Mathematically equivalent to least χ2 method. • Needs as input initial track estimate. • Multiple scattering and energy loss are naturally included. Tracking Performance in LHCb, Jeroen van Tilburg

21. Track fit resolution LHCb provides an excellent momentum estimate at the vertex. Momentum resolution core σ = 0.35% 2nd σ = 1.0% (fraction 0.1) Note: Fitted with single Gaussian in each bin. percent Δp/p Tracking Performance in LHCb, Jeroen van Tilburg

22. Mass and vertex resolutions Good tracking performance essential input for physics analysis: • 4-prong prompt decay  all long tracks. • Total tracking efficiency 84.6±0.5 % (= 95.6 % per track) • Good resolutions: Decay channel: Bs Ds-(KKπ) π+ Tracking Performance in LHCb, Jeroen van Tilburg

23. Ks reconstruction • Reconstruction of Ks( π+π-) challenging: • Long decay lengths (~ 1 m); many decay outside Velo. • Tracks don’t point to interaction point. • Leave less hits in detector. Where does the Ksdecay? ~25 % in Velo  Long tracks ~50 % between Velo and TT  TTT tracks ~25 % after TT  Lost π+π- mass of selected B  J/ψ Ks • Example: B  J/ψ Ks • Combine oppositely charged TTT tracks. • pT > 250 MeV. • Common vertex. • Tracking efficiency for Ks: 54% (74% per track). σ=10.9±0.6 MeV/c2 Tracking Performance in LHCb, Jeroen van Tilburg

24. Conclusions • Tracking system provides good spatial and momentum resolutions.: Vertex IP resolution (17+32/pT) μm, Cluster resolutions 45 μm (ST), 200 μm (OT), • Momentum resolution 0.35%. • Many algorithms developed for finding tracks in optimised setup. Tracking efficiency ~ 95% for B-daughters, For pions from Ks~ 74%. (~54% both tracks), Ghost rate ~ 8% (for pT>0.5GeV). • Tracking is robust against worse conditions. • Provides excellent input for physics analysis: e.g. Bs Ds-π+: Mass resolution 13 MeV/c2 Proper time resolution 42 fs. Tracking Performance in LHCb, Jeroen van Tilburg

25. Tracking Performance in LHCb, Jeroen van Tilburg

26. BACKUP SLIDES Tracking Performance in LHCb, Jeroen van Tilburg

27. Event display Average number of tracks per event: 27 Long (Forward + Matched), 23 Velo, 10 VTT, 10 T  TT 4 Seed tracks + Total 74 Average efficiency = 90.6 % Efficiency for B daughters ~ 95% Event with average occupancy: Red: measurements (hits) Blue: reconstructed tracks Tracking Performance in LHCb, Jeroen van Tilburg

28. Tracking performance Long tracks: Mean momentum 13 GeV On average 37 measurements (Velo, IT, OT) Tracking Performance in LHCb, Jeroen van Tilburg

29. Efficiency definition • Efficiencies are normalised to a sample of “reconstructable” particles: • in VELO at least 3 r and 3 φ hits, • in T stations at least 1 x and 1 stereo hit in each station T1-T3. • Long tracks must be reconstructable in VELO and T. • VTT tracks must be reconstructable VELO and at least 3 TT hits. • TTT tracks must be reconstructable in T and have at least 1 hit in TT. • Successfully reconstructed track: at least 70% of hits from one MC particle. • Long tracks must be successfully reconstructed in VELO and T, • VTT tracks must be successfully reconstructed in VELO and have at least correct 1 hit in TT, • TTT tracks must be successfully reconstructed in T and have at least 1 correct hit in TT. Tracking Performance in LHCb, Jeroen van Tilburg

30. LHCb classic setup LHCb light setup VELO Tracking Performance in LHCb, Jeroen van Tilburg