Point Source Subtraction

Bart Pindor University of Melbourne

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

Importance of PS Subtraction

Liu et al. 2008

MWA Beam

> 1%

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€

D(x) = Aτ (x) + N(x)

Aest = ψ (x)D(x)dx 2∫ˆ ψ ∝ ˆ τ /P(k)

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

€

wl (k) = ψ lm

m

∑ (k)Dm (k)

Matrix Filters• MTXF applied to MAPS +

RTS 8s snapshot• Beam is a single simulated

position-independent point source

• Peak pixel is the inferred position

Matrix FiltersISSUES:• Centroiding• Efficient beam

reconstruction• Iteration• Diffuse sky model

Matrix Filters• Aim for frizz-free

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?

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

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!