Issue |
A&A
Volume 611, March 2018
|
|
---|---|---|
Article Number | A87 | |
Number of page(s) | 15 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/201731474 | |
Published online | 12 April 2018 |
Faceting for direction-dependent spectral deconvolution
1
GEPI,
Observatoire de Paris,
Université PSL, CNRS,
5 place Jules Janssen,
92190 Meudon, France
e-mail: cyril.tasse@obspm.fr
2
Department of Physics & Electronics, Rhodes University,
PO Box 94,
Grahamstown 6140, South Africa
3
SKA South Africa,
3rd Floor,
The Park,
Park Road, Pinelands 7405, South Africa
4
Centre for Astrophysics Research,
School of Physics,
Astronomy and Mathematics, University of Hertfordshire, College Lane, Hatfield AL10 9AB,
UK
5
Oxford e-Research Centre, University of Oxford,
7 Keble Road,
Oxford OX1 3QG, UK
6
Wolfson College, University of Oxford,
Linton Road,
Oxford OX2 6UD, UK
7
Leiden Observatory, Leiden University,
PO Box 9513,
2300 RA Leiden, The Netherlands
8
Ampyx Power,
Lulofsstraat 55-13,
The Hague,
The Netherlands
Received:
29
June
2017
Accepted:
1
December
2017
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.
Key words: instrumentation: adaptive optics / instrumentation: interferometers / methods: data analysis / techniques: interferometric
© ESO 2018
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