Identifying active galactic nuclei via brightness temperature with sub-arcsecond international LOFAR telescope observations. Issue 4 (29th July 2022) - Morabito, Leah K; Sweijen, F; Radcliffe, J F; Best, P N; Kondapally, Rohit; Bondi, Marco; Bonato, Matteo; Duncan, K J; Prandoni, Isabella; Shimwell, T W; Williams, W L; van Weeren, R J; et al.
ABSTRACT: Identifying active galactic nuclei (AGNs) and isolating their contribution to a galaxy's energy budget is crucial for studying the co-evolution of AGNs and their host galaxies. Brightness temperature ( Tb ) measurements from high-resolution radio observations at GHz frequencies are widely used to identify AGNs. Here, we investigate using new sub-arcsecond imaging at 144 MHz with the International LOFAR Telescope to identify AGNs using Tb in the Lockman Hole field. We use ancillary data to validate the 940 AGN identifications, finding 83 percent of sources have AGN classifications from SED fitting and/or photometric identifications, yielding 160 new AGN identifications. Considering the multiwavelength classifications, brightness temperature criteria select over half of radio-excess sources, 32 percent of sources classified as radio-quiet AGNs, and 20 percent of sources classified as star-forming galaxies. Infrared colour–colour plots and comparison with what we would expect to detect based on peak brightness in 6 arcsec LOFAR maps imply that the star-forming galaxies and sources at low flux densities have a mixture of star-formation and AGN activity. We separate the radio emission from star-formation and AGN in unresolved, Tb -identified AGNs with no significant radio excess and find the AGN comprises 0.49 ± 0.16 of the radio luminosity. Overall, the non-radio excess AGNs show evidence for having a variety of different radio emission mechanisms, which can provide different pathways for AGNs and galaxy co-evolution. This validation of AGN identification using brightness temperature at low frequencies opens the possibility for securely selecting AGN samples where ancillary data are inadequate.