Presentation is loading. Please wait.

Presentation is loading. Please wait.

Track reconstruction in TRD and MUCH Andrey Lebedev Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov Gennady Ososkov LIT JINR, Dubna.

Similar presentations


Presentation on theme: "Track reconstruction in TRD and MUCH Andrey Lebedev Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov Gennady Ososkov LIT JINR, Dubna."— Presentation transcript:

1 Track reconstruction in TRD and MUCH Andrey Lebedev Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov Gennady Ososkov LIT JINR, Dubna

2 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 2 Contents General scheme of the tracking Tracking procedure Performance of the TRD tracking Performance of the MuCh tracking Outlook

3 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 3 General scheme for the tracking -The successful application of the TRD tracking algorithms leads to the idea to generalize and optimize those algorithms in a flexible way in order to make them applicable for other, similar detectors. -Since both tracking detector setups (TRD and MuCh) are analogous in many details, the same approach can be used for tracking in these detectors. -The idea is to apply a general algorithm of track finding to different detectors and to adapt it to a specific one by changing tracking routing parameters. -This helps to decrease code duplication, making significantly easier the software support.

4 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 4 Tracking procedure It is based on the Kalman Filter and track following methods where the next track hit is searched in the area surrounding a predicted point. Tracking is accomplished in an iterative way. In each iteration, tracking parameters have to be specified, and hits belonging to tracks found in the current iteration are deleted from the hit array. One can specify the number of tracking iterations, the max number of allowed missing hits in a detector station, start and end station for the tracking and other parameters. The search region can be determined in two different ways: (1) using the covariance matrix of the predicted track parameters and position errors of the hits; (2) using MC, calculate the deviations between the predicted position and a hit.

5 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 5 Application to MuCh and TRD detectors Presented tracking scheme has been applied for the track-finding in the TRD and MuCh detectors. – TRD Standalone - CbmLitTrdTrackFinderS class; Track seed based algorithm: – STS track based - CbmLitTrdTrackFinderSts class; – MuCh track based - CbmLitTrdTrackFinderMuch class; – MuCh STS track based - CbmLitMuchTrackFinder class

6 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 6 Performance of the TRD tracking STS basedStandalone Simulation parameters: 500 central Au-Au events at 25 GeV; standard TRD geometry with 12 layers; L1 tracking in STS. All96.0 (387/403)90.6 (559/617) Vertex96.2 (352/366)94.9 (415/437) Reference96.4 (318/330)95.0 (366/385) Secondary94.3 (35/38)80.2 (145/180) Ghost3.2 (13/403)5.7 (35/617) * Efficiency in %; in brackets are number of reconstructed/number of accepted tracks; acc. tracks have at least 12 MC points.

7 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 7 Performance of the MuCh tracking Central Au-Au events at 25 GeV; omega signal; compact MuCh geometry with 3 and 2 layers between the absorbers; Performance 3 layers, only signal 3 layers, signal + UrQMD 2 layers, only signal 2layers, signal + UrQMD Muon tracks87% (2046/2357) 55% (327/593) 80% (4744/5931) 60% (366/606) Signal pairs74% (172/232) 29% (19/64) 60% (387/641) 29% (18/63) Nof events4k1k10k1k 10 stations, only signal10 stations, signal + UrQMD * Efficiency in %; in brackets are number of reconstructed/number of accepted tracks; acc. track has number of MC points equal to number of stations in MuCh and have to be reconstructed in the STS; pid is taken from matching rec. MuCh track with MC.

8 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 8 Performance of the MuCh tracking Central Au-Au events at 25 GeV; omega signal; Compact MuCh geometry with 3 and 2 layers between the absorbers; Performance 3 layers, only signal 3 layers, signal + UrQMD 2 layers, only signal 2layers, signal + UrQMD Muon tracks 26%16%27%17% Signal pairs 4.4%1.9%3.9%1.4% * Efficiency includes detector acceptance and full track reconstruction

9 A.Lebedev, G.Ososkov Track reconstruction in TRD and MuCh CBM collaboration meeting, GSI, 26 February 2008 9 Summary and outlook Program has been redesigned, which lead to easier support and optimization of the software; Tracking for the MuCh detector has been implemented; TRD and MuCh tracking performances have shown good results; Outlook: – Algorithm improvements (we have to think about it); – Problems, limitations of the tracking; – Software design improvements.


Download ppt "Track reconstruction in TRD and MUCH Andrey Lebedev Andrey Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov Gennady Ososkov LIT JINR, Dubna."

Similar presentations


Ads by Google