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IC-22 Point Source Analysis with Unbinned Maximum Likelihood

IC-22 Point Source Analysis with Unbinned Maximum Likelihood. C. Finley, J. Dumm, T. Montaruli 2008 May 2. Overview. Basic Set of Cuts for point-source quality sample using Level 2 processing 14 days ( 12.6 days livetime) of Level 2 Filtered data

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IC-22 Point Source Analysis with Unbinned Maximum Likelihood

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  1. IC-22 Point Source Analysis with Unbinned Maximum Likelihood C. Finley, J. Dumm, T. Montaruli 2008 May 2

  2. Overview • Basic Set of Cuts for point-source quality sample using Level 2 processing • 14 days ( 12.6 days livetime) of Level 2 Filtered data • (Sept. 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 27, 28, 29) • 1000 files of Level 2, muon-filter Nugen E-1 (optimal for E-2 source sim.) • Dataset 753 • 1000 files of Level 2, muon-filter Nugen E-2(optimal for high statistics AtmNu) • Dataset 768 • First look at adding energy term to the likelihood in IC-22 (similar to method of J. Braun for AMANDA-II) C. Finley

  3. Muon Filter + Pandel Zenith>90 Cut C. Finley

  4. Paraboloid Sigma Cut C. Finley

  5. Pandel Reduced Log Likelihood Cut C. Finley

  6. Split Hit Series Cut: Pandel zen1>80 and zen2>80 C. Finley

  7. NDirC Cut C. Finley

  8. Pandel SDir Cut C. Finley

  9. Maximum Likelihood Analysis Part I: Point Spread Function • By now the maximum likelihood expression is familiar for point source searches: • where the source PDF is a Gaussian with width • given by the paraboloid sigma uncertainty estimate: • and the background PDF depends only on zenith angle: C. Finley

  10. Sensitivity with Analysis-Level Cuts Preliminary IC-22 Sensitivity for 250 d ( ~ 20 atmNu events per day ) E-2 average sensitivity 0 = 1.710-11 TeV-1 cm-2 s-1 C. Finley

  11. Sensitivity with Analysis-Level Cuts IC-9 Sensitivity IC22 Sensitivity E-2 average sensitivity 0 = 1.710-11 TeV-1 cm-2 s-1 C. Finley

  12. Sensitivity with Analysis-Level Cuts E-3 E-2 Sensitivity est. from Gent meeting, based on atmNu background simulation only C. Finley

  13. Maximum Likelihood Analysis Part II: Energy • Now, want to add energy term to the Likelihood function, to weight higher energy events with greater significance: C. Finley

  14. Maximum Likelihood Analysis Part II: Energy • Now, want to add energy term to the Likelihood function, to weight higher energy events with greater significance: C. Finley

  15. Energy PDFs • Start with simplest energy estimator: NChan P (Ei |=2) P (Ei |=3) Patm(Ei) C. Finley

  16. Maximum Likelihood fit to nSrc and Gamma: Examples gamma gamma + + nSrc nSrc Examples: Simulated E-2 source at declination +30° Left: 15 events injected (cross) Right: 30 events injected (cross) 1-sigma and 2-sigma contours are shown for best fit to number of source events nSrc and spectral index gamma gamma gamma + + nSrc nSrc C. Finley

  17. Maximum Likelihood fit to nSrc and Gamma: Examples gamma gamma + + nSrc nSrc gamma gamma + + nSrc nSrc Below: Simulated E-3 source at declination +30° Left: 15 events injected; Right: 30 events injected 1-sigma and 2-sigma contours are shown for best fit to number of source events nSrc and spectral index gamma C. Finley

  18. Effect of Energy Term on Discovery Potential • Simulated E-2 source at declination +30°: • 5-sigma Discovery potential (Power 50%): • without energy term in likelihood:6.1  10-8 GeV-1 cm-2 s-1 (E/GeV)-2 • (mean number of source events: 15) • with energy term in likelihood:4.2  10-8 GeV-1 cm-2 s-1 (E/GeV)-2 • (mean number of source events: 10.5) C. Finley

  19. Summary • Basic cuts on Level 2 parameters and basic maximum likelihood analysis • yield point source sensitivity ≈ 7x better from IC-9. • Many significant improvements coming soon: • Level 3 reconstructions • MPE reconstruction: better high energy efficiency, better angular resolution (see talk by J. Dumm) • Time residuals of MPE should improve efficiency of NDirect cut (or we may find an alternative cut for best high energy efficiency) • Adding energy term to likelihood: • Test with new energy estimators in level 3 (better than Nch estimate) • Reasonable to expect at least 30% improvement in discovery potential for hard spectra. C. Finley

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