1. Pattern Recognition in OPERA Tracking A.Chukanov, S.Dmitrievsky, Yu.Gornushkin OPERA collaboration meeting, Mizunami, Japan, 20-22 of January 2009 JINR, Dubna

2. Outline Problem of pattern recognition in standard OPERA tracking Method of Hough transform for straight track recognition Simple tracing method for curved track reconstruction Method of spanning tree tracing for curved track candidate selection Status of proposed pattern recognition package.

3. Standard track Mushower extrap Pictures are taken from Dario’s report of 29/10/2008 Problem of standard OPERA tracking originates in fact from incorrect pattern recognition. Mushower procedure doesn’t eliminate the reason of the problem but just serves as a patch for tracking algorithm. It simply makes a linear extrapolation of found track direction through a shower without taking into account hit positions in the beginning part of an event.

4. Hence the OPERA pattern recognition needs to be improved. The effective pattern recognition method widely used in HEP experiments (e.g. MINOS, ALICE, CBM, etc) is Hough transform (HT).

5. For each of given point iteration through different angles gives us corresponding values of. Points are saved in a 2D histogram. If there are some straight tracks (or parts of tracks) in an event there should exist distinct pikes in the histogram. By determining of centers of gravity of that pikes it is possible to reconstruct parameters of track lines by the following formulas: Hough transform uses representation of a line in normal form: This equation specifies a line passing through point. That line is perpendicular to the line drawn from the origin to point in polar space. It can be shown that in case of points belonging to the same line and are constants. Hough Transform for Straight Track Recognition

6. Example of HT Track Recognition: event 234948251 and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

7. Example of HT Track Recognition: event 234643825 OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation. and give track parameters: Proposed HT track finding Found

8. Example of HT Track Recognition: event 234655944 and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

9. Example of HT Track Recognition: event 234862308 and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

10. Example of HT Track Recognition: event 234917207 and give track parameters: Proposed HT track finding Found OpRelease tracking: solid line - Kalman extrapolation, dash line - Mushower extrapolation.

11. As shown in the given examples the muon track is easily distinguished by a pike in HT histogram. Moreover, the result of HT recognition coincides with Mushower extrapolation while Hough transform can be performed just at the stage of pattern recognition.

12. Simple Tracing Method for Curved Track Finding After the initial straight part of a track is determined by a Hough transform in the beginning of an event it is possible to find the rest tail part of the track with help of proposed tracing method (which in fact is a simplified kind of a Kalman filter): 1) Finding a search direction Linear fit on 7 last found hits of a track; 2) Setting of search angle range Its own angle range for each detector is used taking into account its geometry and uncertainties. 3) Finding hits in the following detector planes inside the search angle range Inefficiency of detectors (2 empty TT planes, 8 empty RPC planes) is taken into account. If there are more than 1 candidates to track hits only the hit accepted that is the nearest to the search direction. 4) Including found hit to the TrackElement and iterating steps 1-3 for next planes or stop procedure in case of no hits found

13. Example of Forward Tracing Procedure Event 23356121 TT1TT2 RPC1 RPC2 Y, cm Z, cm Simple tracing along the beam direction works easily (as shown on the picture) because there are no background hits far away of the vertex.

14. Backward Tracing with Background When particle’s momentum is small the track can be curved already in its beginning part. The curved tracks are difficult for HT reconstruction and even the simple tracing method can fail within the shower environment. On the picture below such a specific case is shown. Y, cm Z, cm T T planes Line found by a Hough transform wrong hits track hits There are no more sequential hits in the search area Event 217982179

15. To solve such a problem it is useful to iterate on all possible chains of the hits to select among them the best chain. It can be done with help of method of spanning tree tracing. It finds different reliable track trajectories and than consider the longest and most smooth chain of hits to be the best track candidate. Spanning Tree Tracing Method for Track Selection Event 217982179 Y, cm Z, cm T T planes As a result the longest and most smooth track will be selected

16. Resolution of Tracking Preliminary Preliminary results of tracking resolution for XZ and YZ projections have been obtained with help of tracks found in CS. is comparable with standard tracking resolution.

17. Status of Proposed Pattern Recognition Package 1)Event cleaning (removing of CT and isolated hits): done 2) Method of Hough Transform to find straight part of a track: done 3) Tracing method to find curved tail part of a track: under test 4) Method of Spanning Tree Tracing to select the best track candidate within a shower: not yet in OPERA release