1. MICE TPG RECONSTRUCTION Tracking efficiency 29.09.2004 Olena Voloshyn Geneva University

2. In order to test the track reconstruction efficiency the test have been performed using events contained more than one track. In this case we have an appearance of the “fake points”. - strip - fake point - real point

3. Fake points Reconstructed points. View in YZ plan

4. Track recognition The first step is a determination of “good seeds” to start in search. It begins with a search for the pair of points in the region of the entrance of the upstream detector and in the region of the exit of the downstream one that corresponds to the nearest point condition. If at least 30% of possible points were successfully associated with the initial segment the search continues using helix extrapolation. The “window” inside which we look for a space point is defined. If there is more than one possible point in the “window” we choose the point which gives the smallest Chi2 value and attach it to the track. If at least half of the possible points between the initial ones were successfully associated with this track candidate they are saved and we continue to look for another pair of initial points. The global Chi2 of the track is used to assess the quality of the track

5. Reconstructed points in the case of 5 tracks per event

6. View in xz plan after track recognition The presence of holes and regions where two or more tracks overlap reduce the tracking efficiency

7. Tracking efficiency In order to determine the tracking efficiency the following quantities are used: “Generated good track” – a track which produces the hits in at least 40% samplings; “Found good track” – a track for which the number of assigned space points is larger than 50% of the total number of points per track; “Found fake track” – a track with the sufficient number but incorrect assignment of points. The tracking efficiency is then defined as the ratio of the number of “found good tracks” to the number of “generated good tracks”. The probability to find a “fake track” is expressed by number of “found fake track” normalized in the same way.

8. Dependence of the tracking efficiency on the number of muon tracks

9. The events with background have been used to test the Tpg reconstruction chain Reconstructed tracks. View in xz plan Muon tracks Electron track

10. Possibilities of the improvement of the track efficiency Using of the Kalman filter as a method for track recognition and fitting to reject incorrect points which can be due to noise or they can be points from other tracks accidentally captured in the list of points to be associated with the track under consideration Optimization of the track recognition algorithm (using of the second order extrapolation for the initial track segment building; inside the “window” finding all possible points for which Chi2<CutChi2 and consideration all possible branches of the given track )