Selecting and Modelling Remnant AGNs with Limited Spectral Coverage

TL;DR

This paper introduces a new method to estimate the remnant phase duration of radio-loud AGNs using backflow brightness, validated against spectral modelling, and applicable to large radio surveys with limited spectral coverage.

Contribution

The authors develop and validate a novel technique combining backflow brightness with the RAiSE model to measure remnant AGN lifetimes, reducing reliance on high-frequency spectral data.

Findings

The new method produces remnant lifetime estimates consistent with spectral modelling.

It can classify active and remnant AGNs effectively, especially for long-lived and higher redshift sources.

The technique is robust against intrinsic properties of radio AGNs and suitable for large surveys.

Abstract

Quantifying the energetics and lifetimes of remnant radio-loud active galactic nuclei (AGNs) is much more challenging than for active sources due to the added complexity of accurately determining the time since the central black hole switched off. Independent spectral modelling of remnant lobes enables the derivation of the remnant ratio, $R_\mathrm{rem}$, (i.e. `off-time/source age'), thus reducing this complexity back to that of active sources however, the requirement of high-frequency ($\gtrsim5\,$GHz) coverage makes the application of this technique over large-area radio surveys difficult. In this work we propose a new method, which relies on the observed brightness of backflow of Fanaroff-Riley type~II lobes, combined with the \emph{Radio AGN in Semi-Analytic Environments} (RAiSE) code, to measure the duration of the remnant phase. Sensitive radio observations of the remnant radio galaxy J2253-34 are obtained to provide a robust comparison of this technique with the canonical spectral analysis and modelling methods. We find that the remnant lifetimes modelled by each method are consistent; spectral modelling yields $R_\mathrm{rem} = 0.23\pm0.02$, compared to $R_\mathrm{rem} = 0.26\pm0.02$ from our new method. We examine the viability of applying our proposed technique to low-frequency radio surveys using mock radio source populations, and examine whether the technique is sensitive to any intrinsic properties of radio AGNs. Our results show that the technique can be used to robustly classify active and remnant populations, with the most confident predictions for the remnant ratio, and thus off-time, in the longest-lived radio sources ($>50~$Myr) and those at higher redshifts ($z > 0.1$).