Volume 576, April 2015
|Number of page(s)||16|
|Section||Numerical methods and codes|
|Published online||13 March 2015|
MORESANE: MOdel REconstruction by Synthesis-ANalysis Estimators
A sparse deconvolution algorithm for radio interferometric imaging
Laboratoire Lagrange, UMR 7293, Université Nice Sophia-Antipolis, CNRS,
Observatoire de la Côte d’Azur,
2 Centre for Radio Astronomy Techniques & Technologies (RATT), Department of Physics and Electronics, Rhodes University, PO Box 94, 6140 Grahamstown, South Africa
3 SKA South Africa, 3rd Floor, The Park, Park Road, 7405 Pinelands, South Africa
Received: 15 July 2014
Accepted: 13 December 2014
Context. Recent years have been seeing huge developments of radio telescopes and a tremendous increase in their capabilities (sensitivity, angular and spectral resolution, field of view, etc.). Such systems make designing more sophisticated techniques mandatory not only for transporting, storing, and processing this new generation of radio interferometric data, but also for restoring the astrophysical information contained in such data.
Aims.In this paper we present a new radio deconvolution algorithm named MORESANEand its application to fully realistic simulated data of MeerKAT, one of the SKA precursors. This method has been designed for the difficult case of restoring diffuse astronomical sources that are faint in brightness, complex in morphology, and possibly buried in the dirty beam’s side lobes of bright radio sources in the field.
Methods.MORESANE is a greedy algorithm that combines complementary types of sparse recovery methods in order to reconstruct the most appropriate sky model from observed radio visibilities. A synthesis approach is used for reconstructing images, in which the synthesis atoms representing the unknown sources are learned using analysis priors. We applied this new deconvolution method to fully realistic simulations of the radio observations of a galaxy cluster and of an HII region in M 31.
Results.We show that MORESANE is able to efficiently reconstruct images composed of a wide variety of sources (compact point-like objects, extended tailed radio galaxies, low-surface brightness emission) from radio interferometric data. Comparisons with the state of the art algorithms indicate that MORESANE provides competitive results in terms of both the total flux/surface brightness conservation and fidelity of the reconstructed model. MORESANE seems particularly well suited to recovering diffuse and extended sources, as well as bright and compact radio sources known to be hosted in galaxy clusters.
Key words: methods: numerical / methods: data analysis / techniques: image processing / techniques: interferometric
© ESO, 2015
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