Article
Version 2
Preserved in Portico This version is not peer-reviewed
Science Pipelines for the Square Kilometre Array
Version 1
: Received: 5 October 2018 / Approved: 7 October 2018 / Online: 7 October 2018 (08:13:42 CEST)
Version 2 : Received: 20 November 2018 / Approved: 21 November 2018 / Online: 21 November 2018 (07:19:33 CET)
Version 2 : Received: 20 November 2018 / Approved: 21 November 2018 / Online: 21 November 2018 (07:19:33 CET)
A peer-reviewed article of this Preprint also exists.
Farnes, J.; Mort, B.; Dulwich, F.; Salvini, S.; Armour, W. Science Pipelines for the Square Kilometre Array. Galaxies 2018, 6, 120. Farnes, J.; Mort, B.; Dulwich, F.; Salvini, S.; Armour, W. Science Pipelines for the Square Kilometre Array. Galaxies 2018, 6, 120.
Abstract
The Square Kilometre Array (SKA) will be both the largest radio telescope ever constructed and the largest Big Data project in the known Universe. The first phase of the project will generate on the order of 5 zettabytes of data per year. A critical task for the SKA will be its ability to process data for science, which will need to be conducted by science pipelines. Together with polarization data from the LOFAR Multifrequency Snapshot Sky Survey (MSSS), we have been developing a realistic SKA-like science pipeline that can handle the large data volumes generated by LOFAR at 150 MHz. The pipeline uses task-based parallelism to image, detect sources, and perform Faraday Tomography across the entire LOFAR sky. The project thereby provides a unique opportunity to contribute to the technological development of the SKA telescope, while simultaneously enabling cutting-edge scientific results. In this paper, we provide an update on current efforts to develop a science pipeline that can enable tight constraints on the magnetised large-scale structure of the Universe.
Keywords
radio astronomy; interferometry; square kilometre array; big data; faraday tomography
Subject
Physical Sciences, Astronomy and Astrophysics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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