The Australian Square Kilometre Array Pathfinder: Performance of the Boolardy Engineering Test Array
D. McConnell, J.R. Allison, K. Bannister, M.E. Bell, H.E., Bignall, A.P. Chippendale, P.G. Edwards, L. Harvey-Smith, S., Hegarty, I. Heywood, A.W. Hotan, B.T. Indermuehle, E. Lenc, J., Marvil, A. Popping, W. Raja, J.E. Reynolds, R.J. Sault, P., Serra, M.A. Voronkov, M. Whiting

TL;DR
This paper evaluates the performance of BETA, a prototype radio telescope using phased array feeds, highlighting its capabilities in multi-beam formation, calibration, and imaging for future large-scale radio astronomy.
Contribution
It introduces the first aperture synthesis radio telescope with phased array feeds and details the methods for beam formation, calibration, and imaging, advancing radio telescope technology.
Findings
BETA achieved multiple simultaneous beams with phased array feeds.
The telescope demonstrated good sensitivity and beam quality.
Operational lessons inform the final ASKAP telescope's deployment.
Abstract
We describe the performance of the Boolardy Engineering Test Array (BETA), the prototype for the Australian Square Kilometre Array Pathfinder telescope ASKAP. BETA is the first aperture synthesis radio telescope to use phased array feed technology, giving it the ability to electronically form up to nine dual-polarization beams. We report the methods developed for forming and measuring the beams, and the adaptations that have been made to the traditional calibration and imaging procedures in order to allow BETA to function as a multi-beam aperture synthesis telescope. We describe the commissioning of the instrument and present details of BETA's performance: sensitivity, beam characteristics, polarimetric properties and image quality. We summarise the astronomical science that it has produced and draw lessons from operating BETA that will be relevant to the commissioning and operation of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
