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Using Muon Removed files to assess the purity of the nubar-PID selection

Using Muon Removed files to assess the purity of the nubar-PID selection. Pedro Ochoa MINOS Collaboration Meeting September 2006. all. Prob( , ndf) > 0.1. NC. / ndf < 20. Introduction.

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Using Muon Removed files to assess the purity of the nubar-PID selection

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  1. Using Muon Removed files to assess the purity of the nubar-PID selection Pedro Ochoa MINOS Collaboration Meeting September 2006

  2. all Prob( , ndf) > 0.1 NC / ndf < 20 Introduction • Nubar-PID selection allows to separate antineutrinos with very high purity and reasonable efficiency: + + Basic cuts: fiducial volume track quality fit probability 1m < Zvtx < 5m track fit pass rvtx < 1m UVasym < 6 then apply nubar-PID: For a cut at nubar-PID=1.0, MC shows: L010185 MC Overall purity: 99.75% Overall efficiency: 45.98% • Do we believe this high purity?

  3. m- m+ p p+ K+ • Can separate the background • into two categories: • Category 1: m- is reconstructed as m+ due to hard scattering and/or pattern recognition problems = misidentified • Category 2: tracker fooled by positive particle (decay in flight, proton, pion, kaon… ) = fake Background (124 events total) trkIdHEP=13  Category 1 • Use IdHEP of tracked particle: trkIdHEP!=13  Category 2 About ~1/3 of the background pertains to category 2: 124 background events of nubarPID > 1.0 selection *Note: Category 1 contains a small component of misidentified negative stuff from hadronic shower.

  4. Category 2 example – NC (p decay in flight) tracked particle

  5. Category 2 example – NC (proton)

  6. Category 2 example – n CC (Λc+)

  7. Category 2 example – n CC (K+)

  8. True_y of CC n, category 2 • CC subcategory of Category 2 events seem to be highy Can use MRCC files to answer whether category 2 events are reasonably well modeled. • “Good” MRCC selection: best_purity > 0.8 best_complete > 0.8 best_purity_phw > 0.8 best_complete_phw > 0.8 (see Anna H. talk, minos-doc 2164) Event has to be best match to original data MC scaled to POT data MC scaled to POT Purity= Completeness= Means: Data: 0.975 MC: 0.973 Means: Data: 0.952 MC: 0.958

  9. Run MRCC Data and MC though selection data/MC data MC scaled to # events data/MC data MC scaled to POT

  10. Looking at the signal region: • Scaled to # events: data MC scaled to # events • nubar-PID > 1.0 region: MC: 38.8 ± 10.4 Data: 30 ± 5.5 • nubar-PID > 0.5 region: MC: 88.8 ± 9.4 Data: 96 ± 9.8 • Scaled to POT: data MC scaled to POT • nubar-PID > 1.0 region: MC: 34.2 ± 9.1 Data: 30 ± 5.5 • nubar-PID > 0.5 region: MC: 78.1 ± 8.8 Data: 96 ± 9.8

  11. What about energy dependence? data MC scaled to # events data/MC nubar-PID > 1.0 selection data/MC data MC scaled to # events nubar-PID > 0.5 selection

  12. Summary • Nothing crazy. Lack statistics… • Analysis shows so far that “category 2” background in our nubar-PID > 1.0 selection can be scaled overall by a factor of 0.77 ± 0.25 • Ultimately also need to: • Account for MRCC efficiency and purity • Compare subcategories in MRCC and in MC • What to do if more statistics reveal a considerable energy dependence? One possibility: use ratios in previous slides to scale backgroundbinned in reco energy (removing primary CC n energy if applicable).

  13. BACKUP

  14. NC - Pion decay in flight

  15. CC - Pion

  16. data MC scaled to # events nubar-PID > 0.0 signal: MC: 1895 ± 72 Data: 2123 ± 46 data MC scaled to POT nubar-PID > 0.0 signal: MC: 1666 ± 64 Data: 2123 ± 46

  17. nubarPID>1.0 nubarPID>0.5 nubarPID>0.0

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