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2D binned likelihood source detection

This study aims to develop a fast method for obtaining sufficient source fluxes and positions using a 2D binned likelihood approach. By comparing the results with current unbinned likelihood performances, we utilize the EGRET program LIKE (Mattox et al., 1994) to analyze data from energy bands (100 MeV to 200 GeV, 300 MeV to 1 GeV, and 1 GeV to 200 GeV) using 0.5° x 0.5° binning. We identify extended and soft sources, addressing an offset issue caused by binning misinterpretations. This optimized method estimates a running time of approximately 12 hours on a small CPU cluster.

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2D binned likelihood source detection

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  1. 2D binned likelihoodsource detection Jean-Marc Casandjian CEA Saclay

  2. 2D binned likelihood with DC2 • GOAL: find a fast way to get good enough source fluxes and positions • in particular a good position • compare with the current unbinned likelihood performance • use of the EGRET program LIKE (fortran, Mattox et al. 1994) • not fast !!! • binning 0.5° x 0.5° • energy bands: • 100MeV - 200GeV • 300MeV - 1GeV • 1GeV - 200GeV • input generated with gtcntsmap, gtmodelmap and exposure_map • LAT PSF assuming E-2.3 sources • counts and exposure maps for the whole period • Galactic interstellar emission maps

  3. sky tesselation 40 47 46 45 44 43 42 41 48 37 36 35 34 33 32 31 30 38 27 26 25 24 23 22 21 20 28 17 16 15 14 13 12 11 10 18 7 6 5 4 3 2 1 0 8 • 45 regions of interest in (l,b) and (,) • for each RoI and energy band: 4 likelihood maps iteratively computed

  4. iterations 1 & 2

  5. interations 3 & 4

  6. DC2 sources • extended sources detected • soft sources detected twice

  7. coordinate problem • offset problem between the gtmodelmap binning and LIKE’s interpretation of it • all sources along Gal. plane shifted by 0.25°

  8. df resulting from binning d < 1 bin typically 0.5° binning ill-adapted at high-energy will be updated soon catalogue vs. 2D results distance (deg) Flux difference (%)

  9. conclusions • running time estimate of ~ 12 hours with a small 10 cpu cluster for an optimized program • energy-dependent binning to get precise fluxes and positions for a large range of spectral indices • 0.5° x 0.5° binning enough for a quick-look search for potential source candidates  reasonably bright transient search

  10. g=Sqhi.HI + Sqco.WCO + qicIC + qsou.Sources + Cst SqhiHI =qhi01.HI_01 + qh2i.HI_2 + qhi3.HI_3 + qhi4.HI_4 + qhi5.HI_5 + qhi6.HI_6 + qhi78.HI_78 IC still low

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