Discovering exotic AGN behind the Magellanic Clouds. Issue Volume 15:Issue S356(2019) (October 2019)

• Record Type: Journal Article
• Authors: Pennock, Clara M.; van Loon, Jacco Th.; Bell, Cameron P. M.; Filipović, Miroslav D.; Joseph, Tana D.; Vardoulaki, Eleni
• Editors: Pović, Mirjana; Marziani, Paola; Masegosa, Josefa; Netzer, Hagai; Negu, Seblu H.; Tessema, Solomon B.
• Is Part Of: Proceedings of the International Astronomical Union. Volume 15:Issue S356(2019)
• Page Start: 335
• Page End: 338
• Publication Date: 2019-10
• Subjects: AGN, -- Machine-learning, -- Magellanic Clouds, -- Multi-wavelength; Astronomy -- Congresses; Astronomy -- Periodicals; 520
• DOI: 10.1017/S1743921320003270
• Languages: English
• ISSNs: 1743-9213

Abstract

Abstract: 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 â€"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.