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Discovering exotic AGN behind the Magellanic Clouds

Published online by Cambridge University Press:  29 January 2021

Clara M. Pennock
Lennard-Jones Laboratories, Keele University, Keele, ST5 5BG, UK email:
Jacco Th. van Loon
Lennard-Jones Laboratories, Keele University, Keele, ST5 5BG, UK email:
Cameron P. M. Bell
Leibniz Institute for Astrophysics Potsdam, Potsdam, Germany
Miroslav D. Filipović
Western Sydney University, Sydney, Australia
Tana D. Joseph
University of Manchester, Manchester, UK
Eleni Vardoulaki
Max-Planck-Institut für Radioastronomie, Bonn, Germany
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The nearby Magellanic Clouds system covers more than 200 square degrees on the sky. Much of it has been mapped across the electromagnetic spectrum at high angular resolution and sensitivity –X-ray (XMM-Newton), UV (UVIT), optical (SMASH), IR (VISTA, WISE, Spitzer, Herschel), radio (ATCA, ASKAP, MeerKAT). This provides us with an excellent dataset to explore the galaxy populations behind the stellar-rich Magellanic Clouds. We seek to identify and characterise AGN via machine learning algorithms on this exquisite data set. Our project focuses not on establishing sequences and distributions of common types of galaxies and active galactic nuclei (AGN), but seeks to identify extreme examples, building on the recent accidental discoveries of unique AGN behind the Magellanic Clouds.

Contributed Papers
© The Author(s), 2021. Published by Cambridge University Press on behalf of International Astronomical Union


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