Scalable precision wide-field imaging in radio interferometry: I. uSARA validated on ASKAP data

Author:

Wilber A G1,Dabbech A1ORCID,Jackson A2ORCID,Wiaux Y1

Affiliation:

1. Institute of Sensors, Signals and Systems, Heriot-Watt University , Edinburgh EH14 4AS, UK

2. EPCC, The University of Edinburgh , Edinburgh EH8 9BT, UK

Abstract

ABSTRACT As Part I of a paper series showcasing a new imaging framework, we consider the recently proposed unconstrained Sparsity Averaging Reweighted Analysis (uSARA) optimization algorithm for wide-field, high-resolution, high-dynamic range, monochromatic intensity imaging. We reconstruct images from real radio-interferometric observations obtained with the Australian Square Kilometre Array Pathfinder (ASKAP) and present these results in comparison to the widely used, state-of-the-art imager WSClean . Selected fields come from the ASKAP Early Science and Evolutionary Map of the Universe (EMU) Pilot surveys and contain several complex radio sources: the merging cluster system Abell 3391-95, the merging cluster SPT-CL 2023-5535, and many extended, or bent-tail, radio galaxies, including the X-shaped radio galaxy PKS 2014-558 and ‘the dancing ghosts’, known collectively as PKS 2130-538. The modern framework behind uSARA utilizes parallelization and automation to solve for the w -effect and efficiently compute the measurement operator, allowing for wide-field reconstruction over the full field-of-view of individual ASKAP beams (up to ∼3.3° each). The precision capability of uSARA produces images with both super-resolution and enhanced sensitivity to diffuse components, surpassing traditional CLEAN algorithms that typically require a compromise between such yields. Our resulting monochromatic uSARA-ASKAP images of the selected data highlight both extended, diffuse emission and compact, filamentary emission at very high resolution (up to 2.2 arcsec), revealing never-before-seen structure. Here we present a validation of our uSARA-ASKAP images by comparing the morphology of reconstructed sources, measurements of diffuse flux, and spectral index maps with those obtained from images made with WSClean .

Funder

UK Research and Innovation

EPSRC

STFC

University of Edinburgh

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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1. The R2D2 Deep Neural Network Series Paradigm for Fast Precision Imaging in Radio Astronomy;The Astrophysical Journal Supplement Series;2024-06-20

2. CLEANing Cygnus A Deep and Fast with R2D2;The Astrophysical Journal Letters;2024-05-01

3. Identifying synergies between VLBI and STIX imaging;Astronomy & Astrophysics;2024-04

4. Scalable precision wide-field imaging in radio interferometry – II. AIRI validated on ASKAP data;Monthly Notices of the Royal Astronomical Society;2023-05-04

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