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Track extrapolation to TOF with Kalman filter. F. Pierella for the TOF-Offline Group INFN & Bologna University PPR Meeting, January 2003. Summary. Tracking efficiencies (HIJING, B=0.4T); Track Extrapolation to TOF in the Kalman filter framework; Matching Efficiency & Contamination results;
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Track extrapolation to TOF with Kalman filter F. Pierella for the TOF-Offline Group INFN & Bologna University PPR Meeting, January 2003
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.
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;
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)
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.
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).
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
TRD tracking • Subsets (%) of primary particles actually hitting the TOF
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%)
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”
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)
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;
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.
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
