Spectral ageing in the era of big data: integrated vs resolved models
Jeremy J. Harwood

TL;DR
This paper evaluates the reliability of classical integrated spectral ageing models for radio galaxies in the context of big data, comparing them to modern resolved studies and highlighting their limitations and potential uses.
Contribution
It demonstrates that integrated models are unreliable for key parameters but can still aid in candidate selection for remnant and high-redshift radio galaxies.
Findings
Integrated models cannot accurately recover key spectral parameters.
There is up to a sixfold age discrepancy between integrated and resolved methods.
Integrated models may still be useful for source selection in large surveys.
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. LOFAR, MeerKAT, MWA) and planning for the next generation of radio interferometer well underway (e.g. ngVLA, SKA), 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…
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