track extrapolation to tof with kalman filter

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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

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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; - PowerPoint PPT Presentation

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Page 1: Track extrapolation to TOF with Kalman filter

Track extrapolation to TOF with Kalman filter

F. Pierella for the TOF-Offline GroupINFN & Bologna UniversityPPR Meeting, January 2003

Page 2: Track extrapolation to TOF with Kalman filter

SummaryTracking 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.

Page 3: Track extrapolation to TOF with Kalman filter

Tracking efficienciesStatistics: 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;

Page 4: Track extrapolation to TOF with Kalman filter

Tracking efficiency for pions

Page 5: Track extrapolation to TOF with Kalman filter

(Folded) Momentum spectra for pions

Page 6: Track extrapolation to TOF with Kalman filter

Tracking efficiency for kaons

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(Folded) Momentum spectra for kaons

Page 8: Track extrapolation to TOF with Kalman filter

Tracking efficiency for protons

Page 9: Track extrapolation to TOF with Kalman filter

(Folded) Momentum spectra for protons

Page 10: Track extrapolation to TOF with Kalman filter

Tracking efficiency for electrons

Page 11: Track extrapolation to TOF with Kalman filter

(Folded) Momentum spectra for electrons

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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)

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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.

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Main achievementsTracking 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).

Page 15: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Pions

Page 16: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Pions

Page 17: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Kaons

Page 18: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Kaons

Page 19: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Protons

Page 20: Track extrapolation to TOF with Kalman filter

Matching Efficiency & Contamination results for Electrons

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TRD trackingTRD 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

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TRD trackingSubsets (%) of primary particles actually hitting the TOF

With TRD Without TRD

Pions 35% 40%Kaons 21% 24%Protons 38% 51%

Page 24: Track extrapolation to TOF with Kalman filter

TRD trackingthe 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%)

Page 25: Track extrapolation to TOF with Kalman filter

TRD to TOF matching efficiency for Pions

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TRD to TOF matching efficiency for Kaons

Page 27: Track extrapolation to TOF with Kalman filter

TRD to TOF matching efficiency for Protons

Page 28: Track extrapolation to TOF with Kalman filter

TRD to TOF matching efficiency for Electrons

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

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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 trackCurrent 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)

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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;

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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.

Page 36: Track extrapolation to TOF with Kalman filter

PlansA 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)[email protected]