Faceting for direction-dependent spectral deconvolution

被引：209

作者：

Tasse C. ^{[1
,2
]}

Hugo B. ^{[2
,3
]}

Mirmont M. ^{[8
]}

Smirnov O. ^{[2
,3
]}

Atemkeng M. ^{[2
]}

Bester L. ^{[3
]}

Hardcastle M.J. ^{[4
]}

Lakhoo R. ^{[5
,6
]}

Perkins S. ^{[3
]}

Shimwell T. ^{[7
]}

机构：

[1] GEPI, Observatoire de Paris, Université PSL, CNRS, 5 place Jules Janssen, Meudon

[2] Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown

[3] SKA South Africa, Park, Park Road, Pinelands

[4] Centre for Astrophysics Research, School of Physics, Astronomy and Mathematics, University of Hertfordshire, College Lane, Hatfield

[5] Oxford E-Research Centre, University of Oxford, 7 Keble Road, Oxford

[6] Wolfson College, University of Oxford, Linton Road, Oxford

[7] Leiden Observatory, Leiden University, PO Box 9513, RA Leiden

[8] Ampyx Power, Lulofsstraat 55-13, The Hague

来源：

Astronomy and Astrophysics | 2018年 / 611卷

基金：

新加坡国家研究基金会; 英国科学技术设施理事会; 欧洲研究理事会;

关键词：

Instrumentation: adaptive optics; Instrumentation: interferometers; Methods: data analysis; Techniques: interferometric;

D O I：

10.1051/0004-6361/201731474

中图分类号：

学科分类号：

摘要：

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. © ESO 2018.

引用

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