RAiSERed: radio continuum redshifts for lobed AGNs

TL;DR

This paper introduces RAiSERed, a novel radio-based method for estimating redshifts of lobed AGNs using radio imaging and photometry, achieving high accuracy without optical or infrared data.

Contribution

The authors develop a physically based model that accurately estimates AGN redshifts solely from radio data, outperforming traditional attribute-based methods.

Findings

Explains 70% of redshift variation in high-z AGNs.

Achieves <14% redshift error after calibration.

Accurate at z > 2 using unresolved source size bounds.

Abstract

Next-generation radio surveys are expected to detect tens of millions of active galactic nuclei (AGN) with a median redshift of z > 1. Beyond targeted surveys, the vast majority of these objects will not have spectroscopic redshifts, whilst photometric redshifts for high-redshift AGNs are of limited quality, and even then require optical and infrared photometry. We propose a new approach to measure the redshifts of lobed radio galaxies based exclusively on radio-frequency imaging and broadband radio photometry. Specifically, our algorithm uses the lobe flux density, angular size and width, and spectral shape to derive probability density functions for the most likely source redshift based on the Radio AGN in Semi-analytic Environments (RAiSE) dynamical model. The full physically based model explains 70% of the variation in the spectroscopic redshifts of a high-redshift (2 < z < 4) sample of radio AGNs, compared to at most 27% for any one of the observed attributes in isolation. We find that upper bounds on the angular size, as expected for unresolved sources, are sufficient to yield accurate redshift measurements at z > 2. The error in the model upon calibration using at least nine sources with known spectroscopic redshifts is <14% in redshift (as 1 + z) across all redshifts. We provide python code for the calculation and calibration of our radio continuum redshifts in an online library.