1. MUC Reconstruction status and GDML Management You Zhengyun School of Physics, PKU 2005.11.2

2. Outline Muc Reco. Algorithm; Muc Reco. Efficiency; GDML Detector Description in boss; Conclusion;

3. Detector Description – GDML management in boss Geometry Data Flow MucReconstructionSimulation Event Display MucSim GDML Manage ment Detector Description G4 Geo ROOT Geo Data bes.gdml Muc.gdml Emc.gdml … GDML Generator GDML Schema link ( to where BesGDML installed) BOOST MucGeom Svc MucRec Alg ROOT Geometry SimUtil Data (Ascii, DB) Data TrkExt Alg Alignment data

4. Muc Reco. Alg. Use Ext Track from Mdc as seed; Searching hits gap by gap; Searching on Barrel first, then EndCap; Also Searching on neighboring segments; Line Fit with hits on track; Ext track Fired strips Window Barrel End Cap Compare with Mc truth;

5. Muc Reco. Efficiency @ 1.0GeV 1.0 GeV mu- cos θ (-0.9~0.9) 10,000 single mu- input event, 94.78% perfect tracks; (all hits found) 3.91% tracks lost a few (1~3) hits; 1.07% tracks lost more than half (4~9) hits; 0.19% tracks not constructed by Mdc; Muc tracks Reco. Efficiency@1.0GeV is (94.78 % + 3.91 %) / (1-0.19%-0.05%) = ~98.93 % btw : Mdc reconstructed 2 ghost tracks Track over Barrel and EndCap Track over 2 segments Ext track error too much Ext track Muc pos to layer>0 √ √ ~9 hits / track 0.05% Ext tracks have no Muc intersection; (all hits lost)

6. Muc Reco. Efficiency @ 0.5GeV 0.5 GeV mu- cos θ (-0.9~0.9) 10,000 single mu- input event, 2.29 % Ext tracks have no Muc intersecton; (all hits lost) 90.81% perfect tracks; (all hits found) 0.65% tracks lost >= 3 hits; 0.41% tracks not constructed by Mdc; Muc tracks Reco. Efficiency@0.5GeV is > 90.81% / (1-0.41%-2.29%) = > 93.33 % btw : Mdc reconstructed 36 ghost tracks 4.44% tracks lost 1 hit, 1.40% lost 2 hits; √ ~2 hits / track lost hits Ratio : 1249 / 24004 = 5.20%

7. 10000 mu- @ 0.5GeV 24004 MC hits generated. Material Ext lost 1249 hits : Of which 271 by Ext no muc Intersection. Vacuum Ext lost 757 hits. Vacuum Ext always has muc intersection and gives less deviation. Using a random process to reproduce previous random process sometimes gets worse result Reco. Ext track try to reproduce MC track ? Material effects on Track Ext. In material In vacuum MC track In material In vacuum maybe Better In material In vacuum maybe Worse In material In vacuum maybe Stopped

8. A simple test on Random Process 1000 random float [ 0, 1]; a1 = 0.290 a2 = 0.413 a3 = 0.889 …. Average = 0.494, Sigma = 0.2963; Another 1000 random float [ 0, 1]; b1 = 0.562 b2 = 0.498 b3 = 0.077 …. Average = 0.50009, Sigma = 0.2985; RMS of (an - bn) = 0.4086

9. Conclusion Muc Track Reco. Efficiency is ~ 99% @ 1.0GeV >93.3% @ 0.5GeV Could be enhanced even more; Consistent GDML Detector Description management realized;

10. Thank you !

11. Muc Reco. Efficiency 1.0 GeV mu cos θ (-0.9~0.9) 10,000 single track total: 10018 mc primary tracks = 10000 + 18 (3*6event) mdc lost: 37 = 7+12+18 tracks, 57 hits in 7 events, 12 no hit events ext lost: 5 tracks (in the 10000), no hits lost 0 : 9513 (include 18 tracks, 12 no mdc tracks,5 ext tracks with no hits) 1: 234 2: 90 -(nomdc1) 3: 68 4: 46 5: 27 6: 13 7: 5 8: 6 -(nomdc1) 9: 15 -(nomdc4) 11: 1 -(nomdc1)

12. Muc Reco. Efficiency 0.5 GeV mu cos θ (-0.9~0.9) 10,000 single track total: 10054 mc primary tracks = 10000 + 54 (3*18event) mdc lost: 95 = 9+32+54 tracks, 41 hits in 9 events, 32 no hit events ext lost: 229 = 92 no hits + 137 with hits lost 0 : 9259 (include 54 tracks, 32 no mdc tracks, 92 ext tracks with no hits) 1: 496 - 1 - 51 2: 194 - 1 - 53 3: 74 – 0 - 26 4: 20 – 0 - 5 5: 7 – 5 - 1 6: 2 – 1 - 1 7: 1 – 1 - 0 8: 0 9: 1