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        Faceting for direction-dependent spectral deconvolution

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        Author
        Tasse, C.
        Hugo, B.
        Mirmont, M.
        Smirnov, O.
        Atemkeng, M.
        Bester, L.
        Bonnassieux, E.
        Hardcastle, M. J.
        Lakhoo, R.
        Girard, J.H.V.
        Makhathini, S.
        Perkins, S.
        Shimwell, Timothy W.
        Attention
        2299/20160
        Abstract
        The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (ddfacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of ddfacet presented here can account for any externally defined Jones matrices and/or beam patterns.
        Publication date
        2018-03-01
        Published in
        Astronomy & Astrophysics
        Published version
        https://doi.org/10.1051/0004-6361/201731474
        Other links
        http://hdl.handle.net/2299/20160
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