TY - JOUR
T1 - Faceting for direction-dependent spectral deconvolution
AU - Tasse, C.
AU - Hugo, B.
AU - Mirmont, M.
AU - Smirnov, O.
AU - Atemkeng, M.
AU - Bester, L.
AU - Bonnassieux, E.
AU - Hardcastle, M. J.
AU - Lakhoo, R.
AU - Girard, J.H.V.
AU - Makhathini, S.
AU - Perkins, S.
AU - Shimwell, Timothy W.
N1 - Reproduced with permission from Astronomy & Astrophysics, © 2018 ESO.
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PY - 2018/3/1
Y1 - 2018/3/1
N2 - 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.
AB - 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.
KW - Instrumentation: adaptive optics
KW - Instrumentation: interferometers
KW - Methods: data analysis
KW - Techniques: interferometric
UR - http://www.scopus.com/inward/record.url?scp=85045518380&partnerID=8YFLogxK
U2 - 10.1051/0004-6361/201731474
DO - 10.1051/0004-6361/201731474
M3 - Article
SN - 0004-6361
VL - 611
JO - Astronomy & Astrophysics
JF - Astronomy & Astrophysics
M1 - A87
ER -