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Session 112 - Radio Galaxies and Jets: VLBI.
Oral session, Thursday, January 18
1st Floor, La Villita Assembly Building
Robust weighting is a new form of visibility weighting that varies smoothly from natural to uniform weighting as a function of a single real parameter, the robustness. Intermediate values of the robustness can produce images with moderately improved thermal noise characteristics compared to uniform weighting at very little cost in resolution. Alternatively, an image can be produced with nearly the sensitivity of the naturally weighted map, and resolution intermediate between that of uniform and natural weighting. This latter weighting often produces extremely low sidelobes and a particularly good match between the dirty beam and its fitted Gaussian, making it an excellent choice for imaging faint extended emission. A new deconvolver has been developed which greatly outperforms CLEAN or MEM on compact sources. It is based on a preexisting Non Negative Least Squares matrix solution algorithm. NNLS deconvolution is somewhat slower than existing algorithms for slightly resolved sources, and very much slower for extended objects. The solution degrades with increasing source size and at the present computational limit (\sim 6000 pixels of significant emission) it is roughly comparable in deconvolution fidelity to existing algorithms. NNLS deconvolution is particularly well suited for use in the self-calibration loop. For this reason it may prove particularly useful for Very Long Baseline Interferometry, even on size scales where the solution has degraded below those of conventional algorithms.
