Matthew Reid 1 st Year PhD University of Warwick 1.

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Presentation transcript:

Matthew Reid 1 st Year PhD University of Warwick 1

 Interested in pattern recognition for pixel detectors  New techniques that could be applicable to the upgrade  Aim– Increase the reconstruction efficiency of tracks in the Timepix test beam  Any questions just interrupt me! 2

3 Reference cluster Cluster in detector i

Tree structure of the kNN algorithm 4

5 SEED HIT Candidate hits after 1 st iteration Candidate hits after 2 nd iteration

 Example for k=3, projections in both xz- plane and yz-plane: (Note degeneracy) xz-plane yz-plane 6 z z y x SEED HIT Candidate hits 1 st iter Candidate hits 2 nd iter

 Kalman Filter gives best estimates for a linear system (see backup slides for detail)  Allows you to take into account multiple scattering based on Moliere formula for thick material to find better track fit  Measurement uncertainty based on pitch of pixel ~ 55µm 7

Example taken using: bin/tpanal –c cond/Alignment507.dat –z /afs/cern.ch/lhcb/group/vertex/vol7/Timepix/ZSData/Run507.root –n 9 MAX number of tracks with current algorithm is the plane with the lowest number of clusters? ? WRONG!! Detector PlaneNumber of Clusters C03W K05W D09W M06W I02W E05W DUT D04W0015 Bias the data set so ignore 8

 The maximum number of clusters depends on the alignment of detectors  Since the alignment is not perfect we are required to look in area shown in graph  Hence not all clusters can be used in the reconstruction. 9

10 Detector PlaneNumber of ClustersNumber of Aligned Clusters C03W K05W D09W M06W I02W E05W TOTAL676571

Original AlgorithmNew Algorithm Number of Tracks5175 Number of rejected tracks-16 Efficiency54%79% ?? ( ) Projection of Tracks in xz 11 z x z x y

 Residuals are of a comparable order to the original code giving ~6µm, over all planes (unfortunately) 12

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