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Deconvolution /source subtraction via forward modeling ( Pindor et al., 2011, PASA, 28, 46)

Deconvolution /source subtraction via forward modeling ( Pindor et al., 2011, PASA, 28, 46) (GB et al., 2011, MNRAS, 413, 411) It can now run on the instrumental polarization -> speed increases proportional to the length of the integration It accounts for the pixel noise statistics.

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Deconvolution /source subtraction via forward modeling ( Pindor et al., 2011, PASA, 28, 46)

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  1. Deconvolution/source subtraction via forward modeling • (Pindor et al., 2011, PASA, 28, 46) (GB et al., 2011, MNRAS, 413, 411) • It can now run on the instrumental polarization -> speed increases proportional to the length of the integration • It accounts for the pixel noise statistics

  2. Deconvolving real data: an example Source J0523-36 is modeled in the same way that the pointing is processed via the RTS (beams, cadence, frequency) Convergence after 2 iterations. Positional error ~ 15’, flux error ~ 10%

  3. Primary beam measurements • the sky drifts overhead while the tiles point at zenith; • ~30 bandwidth centered @ 185 MHz; • snapshot images (one every 5 min) are used to measure the beam response towards the J0444-2905 (which is ~ 37 Jy @ 185 MHz);

  4. Primary beam measurements J0444-2905

  5. Fitting a simple primary beam model The beam is accurate at a 2% level and predicts the source fluxex with 5% rms accuracy

  6. Stokes I The rms is 0.63 Jy/beam

  7. Stokes Q The rms is 41 mJy/beam

  8. Stokes U The rms is 28 mJy/beam

  9. Extending the beam work: zooming in to HydA field HydA Observations span slightly more than 5 hours (total) over 110-200 MHz: 21 tiles available HydA provides the direction independent calibration of the array Snapshot images co-added Multi-frequency synthesis (but in the image plane)

  10. to be continued with existing data with X16

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