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Optimizing the W resonance in dijet mass

Optimizing the W resonance in dijet mass

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Optimizing the W resonance in dijet mass

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  1. Optimizing the W resonance in dijet mass Daniel Abercrombie Pennsylvania State University 8 August 2013 Advisors: Phil Harris and Andreas Hinzmann

  2. The Goal of the Project • Compare jet cone sizes and algorithms • Identify the algorithm and parameters that givesa stable W mass and narrowest resonance • Results will be used in talks with ATLAS to determine a common set of parameters for jet reconstruction between the experiments Daniel Abercrombie

  3. The Event Daniel Abercrombie

  4. Characterizing the W peak Searching for stable mean and smallest fractional width 200 GeV < pT < 225 GeV Daniel Abercrombie

  5. Comparing cone sizes • Using the anti-kT algorithm gives the most conic shape and is resistant to soft radiation • Scanned through cone sizes from ΔR = 0.4 to ΔR = 0.8 with a resolution of 0.1 Daniel Abercrombie

  6. Comparing cone sizes • Jump in larger cones probably due pT cut for single jets Daniel Abercrombie

  7. Comparing cone sizes • ΔR = 0.4 gives narrowest width Daniel Abercrombie

  8. Comparing cone sizes • Reasonably constant responses from each cone size Daniel Abercrombie

  9. Comparing cone sizes • Again, ΔR = 0.4 gives the narrowest width Daniel Abercrombie

  10. Comparing cone sizes • Again, ΔR = 0.4 gives the narrowest width Daniel Abercrombie

  11. Comparing algorithms Daniel Abercrombie

  12. Comparing algorithms ΔR = 0.5 • Grooming keeps mass relatively constant compared to anti-kT Daniel Abercrombie

  13. Comparing algorithms ΔR = 0.5 • Trimming and filtering compete for best resolution Daniel Abercrombie

  14. Comparing algorithms ΔR = 0.5 • Pruning may be too aggressive at low pileup Daniel Abercrombie

  15. Comparing algorithms ΔR = 0.5 • Trimming and filtering compete for best resolution Daniel Abercrombie

  16. Conclusions • Smaller cone sizes give the best mass resolution with a reasonably small response • Pruning looks like it might be too aggressive • Current plots should be improved by finding ways to increase the efficiency of picking the correct jets Daniel Abercrombie

  17. Future work • Explore additional parameter space of the algorithms • Look at the effects of jet reconstruction onthe top quark mass • Work on selection cuts and parameters to increase the efficiency of selecting the correct jet Daniel Abercrombie

  18. Thank you! Daniel Abercrombie

  19. Thank you! Daniel Abercrombie

  20. Backup Slides Daniel Abercrombie

  21. Selection criteria jets • Events must have at least two b tagged jets and one isolated muon with pT > 10 GeV and |η| < 2.4 • Two jets with pT > 20 GeV and the highest combined secondary vertex values were selected as the b jets • Other jets were in the opposite hemisphere from the muon, MET, and b tagged jet closer to the muon i.e. Daniel Abercrombie

  22. Selection criteria jets (cont.) • Single jets were picked with the following cuts:p > 200 GeV; mass > 60 GeV; MET > 30 GeV • MET cut helps ensure boosted tops • If there were no single jets, the dijet system with the highest pTjets with a invariant mass of 30 GeV < m < 250 GeV is picked Daniel Abercrombie

  23. Comparing algorithms • Pruningtight: nsubjets=2, zcut=0.1, dcut factor=0.5, algo = CAloose: nsubjets=2, zcut=0.1, dcut factor=0.2, algo = CA • Filteringtight: rfilt=0.2, nfilt=3, algo = CA loose: rfilt=0.3, nfilt=3, algo = CA • Trimmingtight: rtrim=0.2, pTfrac=0.05, algo = CA loose: rtrim=0.2, pTfrac=0.03, algo = CA Daniel Abercrombie

  24. Other measures of efficiency ΔR = 0.5 • All of the lines for each algorithm fall well withinthe uncertainties Daniel Abercrombie

  25. Other measures of efficiency ΔR = 0.5 • All of the lines for each algorithm fall well withinthe uncertainties Daniel Abercrombie

  26. Effects of PU ΔR = 0.4 • Pileup decreases efficiency • This is more prominent using larger cone sizes Daniel Abercrombie

  27. Effects of PU ΔR = 0.5 • Pileup decreases efficiency • This is more prominent using larger cone sizes Daniel Abercrombie

  28. Effects of PU ΔR = 0.7 • Pileup decreases efficiency • This is more prominent using larger cone sizes Daniel Abercrombie

  29. Effects of PU ΔR = 0.9 • Pileup decreases efficiency • This is more prominent using larger cone sizes Daniel Abercrombie

  30. PU jets simulation Weighting: Daniel Abercrombie

  31. PU jets simulation NPU = 10 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  32. PU jets simulation NPU = 15 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  33. PU jets simulation NPU = 20 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  34. PU jets simulation NPU = 25 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  35. PU jets simulation NPU = 30 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  36. PU jets simulation NPU = 35 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

  37. PU jets simulation NPU = 40 • Everything above 20 GeV can be mistakenfor a quark jet Daniel Abercrombie

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  42. ΔR = 0.3 Daniel Abercrombie

  43. ΔR = 0.4 Daniel Abercrombie

  44. ΔR = 0.5 Daniel Abercrombie

  45. ΔR = 0.6 Daniel Abercrombie

  46. ΔR = 0.7 Daniel Abercrombie

  47. ΔR = 0.8 Daniel Abercrombie

  48. ΔR = 0.9 Daniel Abercrombie

  49. ΔR = 1.0 Daniel Abercrombie

  50. ΔR = 0.7 175 GeV < pT < 200 GeV Daniel Abercrombie