Adam Zok Science Undergraduate Laboratory Internship Program August 14, 2008

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°

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.

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

Gtobssim Simulation

Testing Sourcefit Options

 Sourcefit allows 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

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

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

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

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

Simplex Position Fitting Results Flux = 3 x 10 -5 s -1 m -2

Simplex Position Fitting Results Flux = 10 -4 s -1 m -2

Simplex Position Fitting Results Flux = 3 x 10 -4 s -1 m -2

Simplex Position Fitting Results Flux = 10 -3 s -1 m -2

TS Values, Flux = 10

-3

s

-1

m

-2

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

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

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