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Sphericity

Lee Pondrom June 13, 2011. Sphericity. Unravelling two jet20 events taken together. Use the jet clustering algorithm from the event reconstruction code to analyze the towers into separate jets in the two event overlap. Check with single events to see if it works. TCalOneEventModule.cc.

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Sphericity

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  1. Lee Pondrom June 13, 2011 Sphericity

  2. Unravelling two jet20 events taken together • Use the jet clustering algorithm from the event reconstruction code to analyze the towers into separate jets in the two event overlap. • Check with single events to see if it works

  3. TCalOneEventModule.cc • Implement code adapted from Ken Hatakeyama to do the real clustering on the towers. • Run on single events to compare the jetblock data to the results from jetclu.

  4. Parameters of the jetclu algorithmsame as JetCluAlgorithm.cc • Seedthreshold=1 GeV, mintowerET=0.1GeV • Coneradius = 0.7 in η-φ space • Adjacency cut = 2. Towers are added to the jet if in a 2Rx2R square in η and φ • Overlapthreshold = 0.75. Ovelapping jets are merged if their shared ET>0.75*ET2, the ET of the smaller jet. Otherwise two jets are formed and common towers are assigned to the nearest jet.

  5. Correct for event vertex • Tower ET and η assume zvertex=0. • Write simple correction code, different for barrel |η|<1 and plug |η|>1. • Match Δφ<.15 to select jet-cluster pair. • Read 1000 events: 478 jet1->clu1 match • 42 jet2->clu1 match • 13 clu1 matches neither jet.

  6. Run on jet20 single events compare jet1η to cluster η

  7. Jet2 η cluster2 η

  8. Compare jet1ET to clu1 ET

  9. And jet2 ET to clu2 ET

  10. Δη jet1-clu1

  11. ΔET jet1-clu1

  12. Conclusions from jetclu • Comparison of jet data in the jetblock and reclustered jets using the towers and jetclu shows that the agreement is good, but not perfect. • JetCluAlgorithm.cc is the default code. • Φ agreement is the best. That is why it was used as a key for the other comparisons.

  13. Application to the two event module • Add events in pairs such that each one has at least one jet with ET>15 GeV. • This gives at least 4 jets in the combined event. • Run the cluster algorithm on the combined towers. Leave all towers at z = 0. • Compare lego plots of the jet block and the cluster block

  14. Lego plots jets vs clusters event #1

  15. Comments on event #1 • Here the leading jet in the first event and the second jet in the second event are merged by jetclualgorithm to form a single jet in the second lego plot. • However, jetclualgorithm produces a fourth jet in the region where the original jet resided.

  16. Event #2

  17. Event #3

  18. Event #4

  19. Event #5

  20. Event #6

  21. Event #7

  22. Event #8

  23. Event #9

  24. Event #10 (last one)

  25. Conclusions from the lego plots • Jets move around. Lower ET jets are easier to move. • Generally the re-clustered energy is larger than in the original jets. • If the original jets are close together jetclualgo merges them into one superjet. • On the whole, the original jets and the reclustered jets agree well for these 10 events.

  26. Run on jet20 data to look for 4 jets in one event • Require jet4 ET>3 GeV (same as JetCluParams for minimum ET jet formation). • Require no second vertex outside ±1 cm. • 50,000 events gives 20,209 4 jet candidates.

  27. Compare 1 trigger 4 jets to 2 triggers 4 jets

  28. Compare 1 trigger ET2 to 2 triggers ET3 and ET4

  29. Compare number of towers and total cm energy

  30. Jet20 single and double triggers • Double triggers have more of everything – more towers, more energy, higher ET in every jet category. • Of course the double triggers have two trigger jets by definition, while the single trigger 4 jet events have only one. • The second jet in the single triggers looks like the fourth jet in the double trigger sample. • A surprisingly large number of events (40%) have 4 or more jets with ET>3 GeV.

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