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Determining Spatial Extendedness of GLAST Sources

Determining Spatial Extendedness of GLAST Sources. Adam Zok Science Undergraduate Laboratory Internship Program August 14, 2008. GLAST: Key Concepts. High energy: 30 MeV – 300 G eV Limited spatial resolution: 0.15° - 3.5° Resolution worsens at low photon energies

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Determining Spatial Extendedness of GLAST Sources

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  1. Determining Spatial Extendedness of GLAST Sources Adam Zok Science Undergraduate Laboratory Internship Program August 14, 2008

  2. GLAST: Key Concepts • High energy: 30 MeV – 300 GeV • Limited spatial resolution: 0.15° - 3.5° • Resolution worsens at low photon energies • Coulomb scattering from heavy nuclei • Targets of study: typically < 1°

  3. Identifying Sources • Many potential gamma-ray emitters may lie within GLAST’s spatial uncertainty • Some emitters are not point sources, but are spatially extended (they have a measurable angular size) • Spatially extended sources are much less common than point sources, so identifying one can narrow down the list of candidate objects significantly.

  4. Software Tools • gtobssim • Creates virtual gamma-ray emitters, outputs .fits file that represents how GLAST may view the source • sourcefit • Works backwards: subtracts background radiation, reconstructs source parameters and calculates confidence limits • Optimizes likelihood (probability that a given set of data came from a particular distribution) • Python modules: PyFITS, ROOT

  5. Gtobssim Simulation

  6. Testing Sourcefit Options • Sourcefitallows the user to specify certain fitting options, or simply use the defaults • In particular, I wanted to see how the energy binning and energy range used affected fit quality • To determine how to most effectively use the program, I ran fits on the same sources using several different combinations of settings

  7. Energy Ranges Red: default range Brown: 100 MeV – 100 GeV Green: 500 MeV – 100 GeV Blue: 1 GeV – 100 GeV

  8. Energy Binning Red: default binning (irregular) Brown: 2 bins per decade Green: 3 bins per decade Blue: 4 bins per decade Pink: 6 bins per decade

  9. Determining Sourcefit’s Limits • Needed to find out which kinds of sources could be accurately modeled by sourcefit • Used two different fitting algorithms: Minuit and Simplex • Generated 4 arrays of simulated sources obscured by background radiation • Different flux for each array, varied size and spectrum within the arrays • Investigated accuracy of fits in terms of size and position, as well as the calculated confidence limits

  10. Array Fit Results • Minuit and Simplex performed comparably • Both algorithms did a poor job of calculating reasonable confidence limits • Sources with a high flux and low spectral index (lots of energetic photons) were most successfully parameterized for both size and position

  11. Simplex Position Fitting ResultsFlux = 3 x 10-5 s-1m-2

  12. Simplex Position Fitting ResultsFlux = 10-4 s-1m-2

  13. Simplex Position Fitting ResultsFlux = 3 x 10-4 s-1m-2

  14. Simplex Position Fitting ResultsFlux = 10-3 s-1m-2

  15. TS Values, Flux = 10-3 s-1m-2

  16. Minuit Point Source Fitting Red = unacceptable fit ( > 0.01° ) Blue = good fit ( < 0.01° ) Green = very good fit ( < o.oo1° )

  17. Final Thoughts • Default energy range usually works best, but low flux, soft spectrum sources may be better fit with a wider energy range (including more low energy photons) • TS value correlates most strongly with source size and spectral index • More background (incorrectly) detected for large, soft-spectrum sources

  18. Future Work • Problems with error matrix calculated by sourcefit need to be fixed • Array plots that quantify error, instead of “yes” or “no” classification • Analyze sources with less regular spectra • Introduce background radiation from galactic sources • Additional simulations to rule out statistical irregularities

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