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WSCLEAN: an implementation of a fast, generic wide-field imager for radio astronomy

Authors :
Offringa, Andre
McKinley, Benjamin
Hurley-Walker, Natasha
Briggs, Franklin
Wayth, Randall
Kaplan, D L
Bell, M. E.
Feng, Lu
Neben, A R
Hughes, J D
Rhee, Jonghwan
Murphy, Tara
Bhat, N.D.R.
Bernardi, Gianni
Bowman, J D
Deshpande, Avinash
Ewall-Wice, Aaron
Offringa, Andre
McKinley, Benjamin
Hurley-Walker, Natasha
Briggs, Franklin
Wayth, Randall
Kaplan, D L
Bell, M. E.
Feng, Lu
Neben, A R
Hughes, J D
Rhee, Jonghwan
Murphy, Tara
Bhat, N.D.R.
Bernardi, Gianni
Bowman, J D
Deshpande, Avinash
Ewall-Wice, Aaron
Source :
Monthly Notices of the Royal Astronomical Society
Publication Year :
2014

Abstract

Astronomical wide-field imaging of interferometric radio data is computationally expensive, especially for the large data volumes created by modern non-coplanar many-element arrays. We present a new wide-field interferometric imager that uses the w-stacking algorithm and can make use of the w-snapshot algorithm. The performance dependences of CASA's w-projection and our new imager are analysed and analytical functions are derived that describe the required computing cost for both imagers. On data from the Murchison Widefield Array, we find our new method to be an order of magnitude faster than w-projection, as well as being capable of full-sky imaging at full resolution and with correct polarization correction. We predict the computing costs for several other arrays and estimate that our imager is a factor of 2-12 faster, depending on the array configuration. We estimate the computing cost for imaging the lowfrequency Square Kilometre Array observations to be 60 PetaFLOPS with current techniques. We find that combining w-stacking with the w-snapshot algorithm does not significantly improve computing requirements over pure w-stacking. The source code of our new imager is publicly released.

Details

Database :
OAIster
Journal :
Monthly Notices of the Royal Astronomical Society
Publication Type :
Electronic Resource
Accession number :
edsoai.on1291762970
Document Type :
Electronic Resource