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New TRD (&TOF) tracking algorithm. Marian Ivanov, Alice Offline week 23.02.2005. TRD tracking. TRD tracking changes - improvements Cluster search mechanism replaced with tracklet search mechanism Chi2 minimization for full tracklet not for separate clusters Advantage in high flux enviroment
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New TRD (&TOF) tracking algorithm Marian Ivanov, Alice Offline week 23.02.2005
TRD tracking • TRD tracking changes - improvements • Cluster search mechanism replaced with tracklet search mechanism • Chi2 minimization for full tracklet not for separate clusters • Advantage in high flux enviroment • New cluster error parameterization • Alignment using reconstructed tracklets • Kalman filter (Important for low momenta tracks): • Energy loss fluctuations taken to the account (covariance) • Increasing of the multiple scattering coefficient • Ongoing work on improvement for low momenta tracks – important for TOF matching
New cluster tracklet search mechanism • Previous version: • Cluster with minimal chi2 to predicted track position taken • Problem • Track possition uncertainty comparable with mean distance between clusters • Possibility to take non proper cluster
New cluster tracklet search mechanism (0) • New version • Looking for tracklets (set of clusters at given plane) with minimal chi2 • Tracklet position and angle taken to the account • Minimize the number of changes in pad-rows • Maximum 1 change possible (tan(theta)*3cm<padlength) • Problem: too many clusters in the road • Tree building too slow • Sollution – Iterative search
New cluster tracklet search mechanism (1) • Iterative search: • 1 approximation - closest clusters to the track taken • { • Tracklet position, angle and their uncertainty calculated • Weighted mean position calculated (tracklet+ track) • If chi2 of current tracklet smaller than chi2 of best previous and the number of pad-row changes less or equal of best previus – make current tracklet best • Closest clusters to the weighted mean taken • }
Cluster error parameterization • Base cluster position fluctuation • Estimated using RMS of tracklet clusters residuals • Sigmay2 = RMS • Uncertainty corresponding to collective shifts of tracklet added to all clusters • Correction for unisochronity and width of the Time Response Function • Sigmay2 += (sigma(dt)*tan(phi))^2*N(cluster) • Additional penalty factor for mean number of pads per cluster and number of pad-rows changes • Effective correction for unfolding
Cluster error parameterization • Left column - cluster residuals to the track-let interpolation • Right column – track-let residuals to the Kalman track extrapolation
Alignment • Following alignment coefficient extracted using tracklets • Effective drift velocity (factor ~1.07) • X0 (time 0) offset (~ 3 mm) • Y0 offset (~0.12 mm)
TRD tracking at high flux environment (central event dN/dy~5000)
TRD tracking at high flux environment (central event dN/dy~5000)
TOF matching • Key role of the TRD tracking • Goal improve space resolution for TOF • Provides probability information is track still alive • ~66 % of fake TOF information because the track not alive anymore (decayed or absorbed in material) • Information track still alive – current implementation • Given by the weighted chi2 of tracklets – weight increase close to the TOF
New TOF matching (0) • The pad “probability coverage” (probability that track cross given pad) in y and z direction as a function of the distance to the pad center • Integral of Gaussian distribution of possible track prolongations
New TOF matching (1) • Cut on probability coverage depends • Depending on the TRD information – track still alive • Cluster with biggest probability coverage taken by default • If the probability coverage for two cluster close each other –additional information about time distance (TOFtdc – TOFkalman) used • Better solution – TOF PID probability sum of conditional probabilities (under investigation) • TOF PID has to be assigned to the track during tracking when all possible prolongations are available
Conclusion • The pt resolution for high momenta tracks improved • Theoretical limit reached • critical for alignment TRD performance • Alignment better than 0.1 mm required • Ongoing work on tracking for low momenta tracks • Improve space point resolution in y • New development of cluster finder • Provides probability information – track still alive • TOF matching algorithm • Under development • Beta version – efficiency increase by 13 %, fake ratio decreased • Need another TOF PID schema • Don’t use AliTOFpidESD class – assign PID during tracking