EMU/GAMA: A new approach to characterising radio luminosity functions

TL;DR

This paper introduces a statistical method to estimate radio luminosity functions for galaxies and AGN using survey data without spectroscopic redshifts, enabling better understanding of faint radio source populations.

Contribution

It presents a novel approach to characterise radio luminosity functions by applying statistical redshift estimation techniques to large radio surveys lacking comprehensive spectroscopic data.

Findings

RLFs match well with existing studies at low redshift

High redshift RLFs are accurately modeled using realistic distributions

Statistical classification effectively distinguishes SFGs and AGN

Abstract

This study characterises the radio luminosity functions (RLFs) for SFGs and AGN using statistical redshift estimation in the absence of comprehensive spectroscopic data. Sensitive radio surveys over large areas detect many sources with faint optical and infrared counterparts, for which redshifts and spectra are unavailable. This challenges our attempt to understand the population of radio sources. Statistical tools are often used to model parameters (such as redshift) as an alternative to observational data. Using the data from GAMA G23 and EMU early science observations, we explore simple statistical techniques to estimate the redshifts in order to measure the RLFs of the G23 radio sources as a whole and for SFGs and AGN separately. Redshifts and AGN/SFG classifications are assigned statistically for those radio sources without spectroscopic data. The calculated RLFs are compared with existing studies, and the results suggest that the RLFs match remarkably well for low redshift galaxies with an optical counterpart. We use a more realistic high redshift distribution to model the redshifts of (most likely) high redshift radio sources and find that the LFs from our approach match well with measured LFs. We also look at strategies to compare the RLFs of radio sources without an optical counterpart to existing studies.