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Abstract

In this paper, we present the identification of five previously unknown giant radio galaxies (GRGs) using Data Release 1 of the Radio Galaxy Zoo citizen science project and a selection method appropriate to the training and validation of deep learning algorithms for new radio surveys. We associate one of these new GRGs with the brightest cluster galaxy (BCG) in the galaxy cluster GMBCG J251.67741+36.45295 and use literature data to identify a further 13 previously known GRGs as BCG candidates, increasing the number of known BCG GRGs by >60 per cent. By examining local galaxy number densities for the number of all known BCG GRGs, we suggest that the existence of this growing number implies that GRGs are able to reside in the centres of rich (∼1014 M⊙) galaxy clusters and challenges the hypothesis that GRGs grow to such sizes only in locally underdense environments.

Item Type:	Article
Authors/Creators:	Tang, H and Scaife, AMM and Wong, OI and Kapinska, AD and Rudnick, L and Shabala, SS and Seymour, N and Norris, RP
Keywords:	methods: data analysis – catalogues – radio continuum: galaxies
Journal or Publication Title:	Monthly Notices of the Royal Astronomical Society
Publisher:	Blackwell Publishing Ltd
ISSN:	0035-8711
DOI / ID Number:	10.1093/mnras/staa2805
Copyright Information:	This article has been accepted for publication in Monthly notices of the Royal Astronomical Society ©: 2020 the authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
Related URLs:	Google Scholar: Shabala, SS UTAS Profile: Shabala, SS
Item Statistics:	View statistics for this item

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