A novel Bayesian approach for decomposing the radio emission of quasars: I. Modelling the radio excess in red quasars

B -H Yue, P N Best, K J Duncan, G Calistro-Rivera, L K Morabito, J W Petley, I Prandoni, H. J. A. Rottgering, D J B Smith

Research output: Contribution to journalArticlepeer-review

Abstract

Studies show that both radio jets from the active galactic nuclei (AGNs) and the star formation (SF) activity in quasar host galaxies contribute to the quasar radio emission; yet their relative contributions across the population remain unclear. Here, we present an improved parametric model that allows us to statistically separate the SF and AGN components in observed quasar radio flux density distributions, and investigate how their relative contributions evolve with AGN bolometric luminosity (\L\mathrm\bol\\) and redshift (z) using a fully Bayesian method. Based on the newest data from LOw-Frequency ARray Two-metre Sky Survey data release 2, our model gives robust fitting results out to \z\\, showing a quasar host galaxy SF rate (SFR) evolution that increases with bolometric luminosity and with redshift out to \z\\. This differs from the global cosmic SFR density, perhaps due to the importance of galaxy mergers. The prevalence of radio AGN emissions increases with quasar luminosity, but has little dependence on redshift. Furthermore, our new methodology and large sample size allow us to subdivide our data set to investigate the role of other parameters. Specifically, in this paper, we explore quasar colour and demonstrate that the radio excess in red quasars is due to an enhancement in AGN-related emission, since the host galaxy SF contribution to the total radio emission is independent of quasar colour. We also find evidence that this radio enhancement occurs mostly in quasars with weak or intermediate radio power.
Original languageEnglish
Article numberstae725
Pages (from-to)3939-3957
Number of pages19
JournalMonthly Notices of the Royal Astronomical Society
Volume529
Issue number4
Early online date12 Mar 2024
DOIs
Publication statusE-pub ahead of print - 12 Mar 2024

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