fast-resolve: Fast Bayesian radio interferometric imaging

Context. The aim of this paper is to reduce the computational complexity of the Bayesian imaging algorithm resolve , enabling the application of Bayesian imaging for larger datasets. Aims. By combining computational shortcuts of the CLEAN algorithm with the Bayesian imaging algorithm resolve we developed an accurate and fast imaging algorithm that we named fast-resolve . Methods. We validate the accuracy of the presented fast-resolve algorithm by comparing it with results from resolve on VLA Cygnus A data. Furthermore, we demonstrate the computational advantages of fast-resolve on a large MeerKAT ESO 137-006 dataset, which is computationally out of reach for resolve . Results. The presented algorithm is significantly faster than previous Bayesian imaging algorithms, broadening the applicability of Bayesian interferometric imaging. Specifically, for the single channel VLA Cygnus A datasets fast-resolve is about 144 times faster than resolve . For the MeerKAT dataset with multiple channels the computational increase in speed of fast-resolve is even greater.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2024-09-26
DOI
https://doi.org/10.1051/0004-6361/202451107
Citations
6
Primary Topic
Radio Astronomy Observations and Technology
Type
article
Field-Weighted Citation Impact
1.99

Funders

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article

fast-resolve: Fast Bayesian radio interferometric imaging

Hertzog L. Bester, Jakob Roth, Rüdiger Westermann, Philipp Frank et al.
6 citations
Astronomy and Astrophysics
Radio Astronomy Observations and Technology
1.99
article

fast-resolve: Fast Bayesian radio interferometric imaging

Hertzog L. Bester, Jakob Roth, Rüdiger Westermann, Philipp Frank, T. A. Enßlin, O. Smirnov
article en
6 citations

Abstract

Context. The aim of this paper is to reduce the computational complexity of the Bayesian imaging algorithm resolve , enabling the application of Bayesian imaging for larger datasets. Aims. By combining computational shortcuts of the CLEAN algorithm with the Bayesian imaging algorithm resolve we developed an accurate and fast imaging algorithm that we named fast-resolve . Methods. We validate the accuracy of the presented fast-resolve algorithm by comparing it with results from resolve on VLA Cygnus A data. Furthermore, we demonstrate the computational advantages of fast-resolve on a large MeerKAT ESO 137-006 dataset, which is computationally out of reach for resolve . Results. The presented algorithm is significantly faster than previous Bayesian imaging algorithms, broadening the applicability of Bayesian interferometric imaging. Specifically, for the single channel VLA Cygnus A datasets fast-resolve is about 144 times faster than resolve . For the MeerKAT dataset with multiple channels the computational increase in speed of fast-resolve is even greater.

Astronomy and AstrophysicsVol. 690
Rhodes University (ZA), Max Planck Institute for Astrophysics (DE), Istituto di Radioastronomia di Bologna (IT), South African Radio Astronomy Observatory (ZA), Technical University of Munich (DE), Ludwig-Maximilians-Universität München (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 14%
Radio Astronomy Observations and Technology
1.99
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