1. Track extrapolation to TOF with Kalman filter F. Pierella for the TOF-Offline Group INFN & Bologna University PPR Meeting, January 2003

2. Summary Tracking efficiencies (HIJING, B=0.4T); Track Extrapolation to TOF in the Kalman filter framework; Matching Efficiency & Contamination results; TRD tracking included in the matching procedure; Track Length (rough) Estimate.

3. Tracking efficiencies Statistics: 250 HIJING central events at B=0.4T (no vertex smearing); Rapidity range: [-1,1] AliROOT v3-09-04; Tracking machinery: TPC digitization, clusterization, track finding; ITS digitization, rec. point (slow), clusterization and track finding; ITS and TPC back propagation; TRD digitization, clusterization, track finding with seed from TPC back-propagated tracks; TOF digitization and track extrapolation;

4. Tracking efficiency for pions

5. (Folded) Momentum spectra for pions

6. Tracking efficiency for kaons

7. (Folded) Momentum spectra for kaons

8. Tracking efficiency for protons

9. (Folded) Momentum spectra for protons

10. Tracking efficiency for electrons

11. (Folded) Momentum spectra for electrons

12. Track Extrapolation to TOF in the Kalman filter framework Tracks are back-propagated till the TOF surface from TRD last layer (then eventually recovered from TPC) taking into account the intermediate materials; Then they are matched with TOF signals (for each track its own error covariance matrix is taken into account according to a weighting algorithm) and TOF digits map is cleaned after each assignment (at least for TRD tracks); An iterative procedure is used to find TOF signals (in order to maximize the ratio Efficiency/Contamination)

13. Track Extrapolation to TOF in the Kalman filter frame Tracks are converted into TOF tracks which have the additional time-of-flight information; The output is stored into a TTree with all the track parameters given in the Master Reference Frame; Vertex parameters are obtained by propagation to the vertex; The output class is intermediate between AliKalmanTrack and AliEDG.

14. Main achievements Tracking in ITS-TPC-TRD is now included; Additional information on dE/dx in ITS-TPC (to be used for PID) is available; MC data and real data can be analyzed with the same code (for MC data a Comparison is possible for efficiencies et cetera); The algorithm starts from TOF digits (so, digitization time is saved); Results indicate an improvement in efficiency and contamination with respect to the past (5-10% in efficiency for each momentum bin).

15. Matching Efficiency & Contamination results for Pions

17. Matching Efficiency & Contamination results for Kaons

19. Matching Efficiency & Contamination results for Protons

20. Matching Efficiency & Contamination results for Electrons

22. TRD tracking TRD tracking has been included in the matching procedure with the same general strategy of the extrapolation on TOF sensitive pads; Even if the number of particles reaching TOF is affected by the presence of the TRD (in particular in the proton case) as reported in the following table

23. TRD tracking Subsets (%) of primary particles actually hitting the TOF With TRDWithout TRD Pions35%40% Kaons21%24% Protons38%51%

24. TRD tracking the spatial resolution of the TRD reconstructed tracks is excellent (even without the TRD tilted pad solution) In fact the back-propagated area on TOF surfaces corresponds approximatively to 1/40 of the TOF pad area; Consequently the matching procedure from TRD is really efficient (~90%)

25. TRD to TOF matching efficiency for Pions

26. TRD to TOF matching efficiency for Kaons

27. TRD to TOF matching efficiency for Protons

28. TRD to TOF matching efficiency for Electrons

29. Summary Matching efficiency from TRD:  90% Overall Matching efficiency (including the matching of the remaining tracks from TPC): 82-85% Probably “in medium stat virtus”

30. Track length (TOF group implementation) It is absolutely necessary (mass calculation, probability approach, “à priori” and “à posteriori” time-of-flight comparison et cetera) It needs vertex parameters of the track Current estimate is based on a sum of lengths of helix segments (according to track position in each entrance or end of a tracking detector, i.e. ITS, TPC and TRD)

34. Summary on Track Length results Assuming a gaussian fit of the distribution for the track length resolution (GEANT track length minus “reconstructed” track length), the sigma of the distribution is ~3 cm (2 cm without TRD); it corresponds to ~100ps which is larger than the intrinsic time resolution of the TOF-MRPC;

35. Summary on Track Length results Therefore the “paradox” is that space- time intervals are better measured with time-of-flight than with length-of-flight; Improvements of the track length resolution should be urgently faced.

36. Plans A priori times of flight integrated in the KF framework (track length) Lower multiplicity for matching (TOF for PPR Chap.5) Naive point: TTre Name expected in TRD (send to Peter) + exact sequence of overall reconstruction (TOF) Andrea Ghaeta (send request for volume) bogdan@cern.ch