Spectral ageing in the era of big data: Integrated versus resolved models

Abstract

Continuous injection models of spectral ageing have long been used to determine the age of radio galaxies from their integrated spectrum; however, many questions about their reliability remain unanswered. With various large area surveys imminent (e.g. LOw Frequency ARray, MeerKAT, MurchisonWidefield Array) and planning for the next generation of radio interferometers are well underway (e.g. next generationVLA, SquareKilometreArray), investigations of radio galaxy physics are set to shift away from studies of individual sources to the population as a whole. Determining if and how integrated models of spectral ageing can be applied in the era of big data is therefore crucial. In this paper, I compare classical integrated models of spectral ageing to recent well-resolved studies that use modern analysis techniques on small spatial scales to determine their robustness and validity as a source selection method. I find that integrated models are unable to recover key parameters and, even when known a priori, provide a poor, frequency-dependent description of a source's spectrum. I show a disparity of up to a factor of 6 in age between the integrated and resolved methods but suggest, even with these inconsistencies, such models still provide a potential method of candidate selection in the search for remnant radio galaxies and in providing a cleaner selection of high redshift radio galaxies in z - α selected samples.