Adam Zok Science Undergraduate Laboratory Internship Program August 14, 2008.

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Determining Spatial Extendedness of GLAST Sources

Adam ZokScience Undergraduate Laboratory Internship Program

August 14, 2008

GLAST: Key ConceptsHigh energy: 30 MeV – 300 GeVLimited spatial resolution: 0.15° - 3.5°Resolution worsens at low photon energies

Coulomb scattering from heavy nucleiTargets 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 Toolsgtobssim

Creates virtual gamma-ray emitters, outputs .fits file that represents how GLAST may view the source

sourcefitWorks 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 LimitsNeeded to find out which kinds of sources could be

accurately modeled by sourcefitUsed two different fitting algorithms: Minuit and SimplexGenerated 4 arrays of simulated sources obscured by

background radiationDifferent flux for each array, varied size and spectrum

within the arraysInvestigated accuracy of fits in terms of size and position,

as well as the calculated confidence limits

Array Fit Results

Minuit and Simplex performed comparablyBoth algorithms did a poor job of calculating reasonable

confidence limitsSources with a high flux and low spectral index (lots of

energetic photons) were most successfully parameterized for both size and position

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

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

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

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

TS Values, Flux = 10-3 s-1m-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 indexMore 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 spectraIntroduce background radiation from galactic sourcesAdditional simulations to rule out statistical irregularities