MNRAS-2016-Mingo-2631-67.pdf (11.21 MB)
The MIXR sample: AGN activity versus star formation across the cross-correlation of WISE, 3XMM, and FIRST/NVSS
journal contributionposted on 2016-11-18, 14:50 authored by B. Mingo, M. G. Watson, S. R. Rosen, M. J. Hardcastle, A. Ruiz, A. Blain, F. J. Carrera, S. Mateos, F. X. Pineau, G. C. Stewart
We cross-correlate the largest available mid-infrared (Wide-field Infrared Survey Explorer - WISE), X-ray (3XMM) and radio (Faint Images of the Radio Sky at Twenty centimetres+NRAO VLA Sky Survey) catalogues to define the MIXR sample of AGN and star-forming galaxies. We pre-classify the sources based on their positions on the WISE colour/colour plot, showing that the MIXR triple selection is extremely effective to diagnose the star formation and AGN activity of individual populations, even on a flux/magnitude basis, extending the diagnostics to objects with luminosities and redshifts from SDSS DR12. We recover the radio/mid-IR star formation correlation with great accuracy, and use it to classify our sources, based on their activity, as radio-loud and radio-quiet active galactic nuclei (AGN), low excitation radio galaxies/low ionization nuclear emission line regions, and non-AGN galaxies. These diagnostics can prove extremely useful for large AGN and galaxy samples, and help develop ways to efficiently triage sources when data from the next generation of instruments becomes available. We study bias in detail, and show that while the widely used WISE colour selections for AGN are very successful at cleanly selecting samples of luminous AGN, they miss or misclassify a substantial fraction of AGN at lower luminosities and/or higher redshifts. MIXR also allows us to test the relation between radiative and kinetic (jet) power in radio-loud AGN, for which a tight correlation is expected due to a mutual dependence on accretion. Our results highlight that long-term AGN variability, jet regulation, and other factors affecting the Q/Lbol relation, are introducing a vast amount of scatter in this relation, with dramatic potential consequences on our current understanding of AGN feedback and its effect on star formation.
This work has made use of data/facilities and financial support from the ARCHES project (7th Framework of the European Union no. 313146). SM, FJC and AR acknowledge financial support by the Spanish Ministry of Economy and Competitiveness through grant AYA2012-31447, which is partly funded by the FEDER programme. FJC also acknowledges financial support through grant AYA2015-64346-C2-1-P (MINECO/FEDER). This work is based on observations obtained with XMM–Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. It also makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. We acknowledge the use of the FIRST and NVSS catalogues, provided by the NRAO. Optical magnitudes and redshifts were obtained from the SDSS Data Release 12. Funding for the SDSS IV has been provided by the Alfred P. Sloan Foundation and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org.
CitationMonthly Notices of the Royal Astronomical Society, (November 01, 2016) 462 (3): 2631-2667.
Author affiliation/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and Astronomy
- VoR (Version of Record)