T2 Track Reconstruction and Classification 09/07/10 Matti Leinonen - PowerPoint PPT Presentation

T2 Track Reconstruction and Classification 09/07/10 Matti Leinonen 1

Overview of presentation  Track reconstruction  Measuring efficiency  Changes made  Efficiency plots  Track classification  Measuring efficiency  Cuts used  Efficiency table 09/07/10 Matti Leinonen 2

Information provided by Geant4  Geant4 provides information that can be used to classify reconstructed tracks into primary and secondary tracks.  Primary tracks originate from the vertex.  Secondary tracks originate from somewhere else.  Allows comparison of the number of simulated tracks against the number of reconstructed tracks.  It is possible to study the effect of different cuts to the classification of reconstructed tracks. 09/07/10 Matti Leinonen 3

Data used to generate plots  For the plots 10000 simulated 7 TeV MB pp events were used.  Digitizer added Gaussian noise to the data.  No dead vfats have been taken into account. 09/07/10 Matti Leinonen 4

Changes made to track reconstruction  Hit error  Moved from constant hit error to hit error based on the number of clusters used in forming the hit.  Methods to calculate hit errors  Simulated information  Leave-one-out method  Outlier point rejection  Previously no rejection for clearly erroneous hits in track fitting.  Based on Chi-square and leave-one-out calculations. 09/07/10 Matti Leinonen 5

Methods used for measuring the efficiency of track reconstruction  Chi-square distribution of reconstructed primary and secondary tracks.  For all tracks there should be clear peak of tracks near zero and constant number of tracks otherwise.  For reconstructed primary tracks the distribution should be uniformly distributed.  The number of reconstructed primary tracks as the function of simulated primary tracks.  The average number should be one with as small deviation as possible. 09/07/10 Matti Leinonen 6

Reconstructed track Chi-square distribution Before changes 09/07/10 Matti Leinonen 7

Reconstructed track Chi-square distribution After changes 09/07/10 Matti Leinonen 8

Efficiency of track reconstruction Before changes 09/07/10 Matti Leinonen 9

Efficiency of track reconstruction After changes 09/07/10 Matti Leinonen 10

Cuts used in track classification  Chi-square cut  Track Chi-square value less than 1 %.  Old eta cut  Absolute value of track eta between 4.9 and 7.0.  Old Z cut  Absolute value of track Z less than 4000 mm.  New eta + Z cut  Based on the number of hits in the track and the eta value of the track. 09/07/10 Matti Leinonen 11

Methods used in calculating the efficiency of track classification  Percentage of reconstructed primary and secondary tracks that pass all track classification cuts.  Function , where p is the number of p E  p , s =   s  reconstructed primary tracks that pass all classification cuts and s is the number of reconstructed secondary tracks that pass all classification cuts. 09/07/10 Matti Leinonen 12

Effect of different cut combinations on reconstructed track classification Chi-square Old Eta Old Z New eta + Z % of primary % of secondary E(p,s) tracks pass cut tracks pass cut 100.0 100.0 416 X 96.9 85.2 437 X 98.3 84.4 445 X 93.4 54.9 524 X 85.2 41.2 549 X X 93.4 54.9 524 X X 95.8 73.4 465 X X 91.8 52.0 530 X X X 91.8 52.0 530 X X 84.1 40.0 553 09/07/10 Matti Leinonen 13

Thank you for your attention 09/07/10 Matti Leinonen 14