Point Source Subtraction

1. Point Source Subtraction Bart Pindor University of Melbourne

2. Objectives • Remove Bright EG point sources prior to polynomial EOR FG subtraction • Issue: Mode-mixing / ‘Frizz’ • RTS will Peel some bright sources as part of CML • It will be possible/necessary to remove further sources after imaging • Characterize residuals/effect on (the other) PS

3. Importance of PS Subtraction Liu et al. 2008

4. MWA Beam > 1%

5. Matched Filters • Generally; positions, fluxes, spectra unknown • Matched filter is the optimal linear S/N estimator of source amplitudes • Peaks in filtered maps used to identify PS

6. Matrix Filters • Extension of Matched Filters to multi-channel • Developed for Planck CMB maps (Herranz et al. astro-ph/08082884 • Incorporates cross-channel correlations but allows for independent spectral slopes • Each filtered image estimates source fluxes

7. Matrix Filters • MTXF applied to MAPS + RTS 8s snapshot • Beam is a single simulated position-independent point source • Peak pixel is the inferred position

8. Matrix Filters ISSUES: • Centroiding • Efficient beam reconstruction • Iteration • Diffuse sky model

9. Matrix Filters • Aim for frizz-free

10. OOB – oh oh? • Sidelobes will appear from sources outside of the primary beam • Can we detect/locate sources in combined maps? • Use of MWA survey or other (GMRT?) data to locate relevant source? • What is the accuracy of calibration solution in that direction?

11. Open Issues / Simulation To-Do: • Ionosphere • HEALPIX pixelization • Integration, co-addition, registration • Rotation synthesis • Peeling levels and residuals • Calibration / Beam Accuracy • OOB • 8 minutes * 200 Channels * 5000 images

12. Open Issues / Simulation To-Do: • Ionosphere • HEALPIX pixelization • Integration, co-addition, registration • Rotation synthesis • Peeling levels and residuals • Calibration / Beam Accuracy • OOB • 8 minutes * 200 Channels * 5000 images = 136 years!