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Electron Identification in CBM

Electron Identification in CBM. Semeon Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov LIT JINR, Dubna. Electron Identification in RICH Electron Identification in TRD Global Electron Identification. Outline. Electron Identification in RICH.

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Electron Identification in CBM

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  1. Electron Identification in CBM Semeon Lebedev GSI, Darmstadt and LIT JINR, Dubna Gennady Ososkov LIT JINR, Dubna

  2. Electron Identification in RICH Electron Identification in TRD Global Electron Identification Outline

  3. Electron Identification in RICH

  4. Hough Transform ring finder was improved especially for high ring density environment. Algorithm for electron identification in RICH based on ANN was implemented Improvements

  5. Standard and Compact RICH geometry • The length of the compact RICH radiator was calculated in order to keep mean number of hits in electron ring equals to 22. This is a requirement of the ring reconstruction algorithm. See talk by E. Belolaptikova in RICH session.

  6. Hit density normalized to one event Standard RICH Compact RICH

  7. High ring density test for ring finder (1) 120 e+ and 120 e- in each event

  8. 500 events histogram cell size is 10x10 cm2 1) RD < 70 cm 350 rings/500 events/100 cm2 -> 0.7 rings/event/100 cm2 -> 0.93rings/event/ring area 2) 70 < RD < 110 cm 250 rings/500 events/100 cm2 -> 0.5 rings/event/100 cm2 -> 0.67rings/event/ring area 3) RD > 110 cm < 150 rings/500 events/100 cm2 -> 0.3 rings/event/100 cm2 -> 0.40rings/event/ring area High ring density test for ring finder (2) 3 1 RD 2 For the red area in the histogram majority of rings are overlapped. RD = radial position

  9. High ring density test for ring finder (3) Old version of ring finder showed only 78%

  10. 70% collection efficiency might be realistic because of the H8500 construction PMT collection efficiency 240 e+ and e- in each events 100 % CE -> Mean efficiency = 91.07 % 70% CE -> Mean efficiency = 88.10% Mean number of hits in electron ring: 100 % CE =21.14 hits/ring 70% CE = 15.8 hits/ring

  11. Efficiency vs. number of hits 100 % Collective efficiency 70% Collective efficiency 240 e+ and e- in each event

  12. Efficiency vs. B/A A B 100 % Collective efficiency 70% Collective efficiency In 1% ellipse fitter goes wrong. B/A distribution for e+ and e- Important parameter for Compact RICH design.

  13. Input parameters for ANN: A axis B axis Ring-track distance Chi2 Number of hits Momentum Radial position Ellipse rotation angle Azimuthal angle Electron Identification in RICH based on ANN (1) Ring-track distance B axis Chi 2

  14. Electron Identification in RICH based on ANN (2) pions electrons

  15. Electron Identification in TRD

  16. Two different TRD geometries Munster-Bucharest 0.3 Mev Standard 0.15 Mev Standard Gas layers Sum of energy loss for pions (solid line) and electrons (dashed line). Munster-Bucharest

  17. Different geometries Detector inefficiency Track passes through not all layers Improvements in Electron Identification algorithm 4-4-4 Standard setup 4-2-2 34%saving • Electron Identification algorithm based on ANN allows to identify electrons which have from 6 to 12 hits in TRD. Two different TRD geometries are supported.

  18. Pion suppression vs. # of hits in track • Electron efficiency 90% • Algorithm based on ANN was used • Integrated pion suppression for all momentum range • (1-10 GeV/c) is shown

  19. Pion suppression in dependence on momentum Standard TRD geometry is used Electron efficiency 90% • To keep 90% of electron efficiency one need to chose cut in dependence on momentum according to plot. • Fitted with fractionally rational function • Model: y = a+b/(x-c) • a = 0.955; b = -0.379; c = 0.663;

  20. Global Electron Identification

  21. Matching efficiency (1)

  22. Matching efficiency (2) Compact RICH Standard RICH Note: besides “true” matching losses also losses due to geometry come in (tracks not accepted in TRD)

  23. Recall, Electron Identification in CBM A axis B axis Ring-track distance RICH • RICH: • ring-track distance < 1 cm; • A and B +- 3sigma around • mean value; • Artificial Neural Network • TRD: • ANN output > 0.8 TRD Dashed line – pi Solid line - el

  24. Electron identification, standard RICH (1) Cuts: ring-track distance < 1 cm; A and B +- 3sigma; TRD ANN > 0.8

  25. Electron identification, standard RICH (2) RICH ANN > -0.3; TRD ANN > 0.8

  26. Electron identification, compact RICH (1) Cuts: ring-track distance < 1 cm; A and B +- 4sigma; TRD ANN > 0.8

  27. Electron identification, compact RICH (2) RICH ANN > -0.3; TRD ANN > 0.8

  28. Summary table *ring-track distance < 1 cm; A and B +- 3sigma around mean value;

  29. Summary • Hough Transform ring finder was improved especially for high ring density environment. Efficiency for the standard RICH is more than 95%, for the Compact RICH about 90.5% • Algorithm for electron identification in RICH based on ANN was implemented. It has shown better results in comparison to standard cuts. • Electron Identification algorithm in TRD allows to identify electrons which have from 6 to 12 hits in TRD. Two different TRD geometries are supported (Munster-Bucharest and standard). • Routines for electron identification and quality check were implemented. Standard and Compact RICH layout were tested. • Results are very good: • for standard RICH geometry pion suppression factor of 10k can be reached at 83.3% electron efficiency using RICH and TRD. • for compact RICH geometry pion suppression factor of 13k can be reached at 74.6% electron efficiency using RICH and TRD.

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