Radio Galaxy Zoo: New Giant Radio Galaxies in the RGZ DR1catalogue

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%. 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 centers of rich ($\sim 10^{14}$ M${}_{\odot }$) galaxy clusters and challenges the hypothesis that GRGs grow to such sizes only in locally under-dense environments.

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Cited by in corpus (13)

• Measuring the giant radio galaxy length distribution with the LoTSS
• The discovery of a radio galaxy of at least 5 Mpc
• MIGHTEE: Are giant radio galaxies more common than we thought?
• Decoding the giant extragalactic radio sources
• Constraining the giant radio galaxy population with machine learning and Bayesian inference
• VLA Radio Study of a Sample of Nearby X-ray and Optically Bright Early-Type Galaxies
• The contribution of magnetized galactic outflows to extragalactic Faraday rotation
• Discovery of X-shaped Morphology of the Giant Radio Galaxy GRG 0503-286
• A new distant Giant Radio Galaxy in the Boötes field serendipitously detected by Chandra
• Formation of giant radio sources in galaxy clusters
• A Machine Learning made Catalog of FR-II Radio Galaxies from the FIRST Survey
• Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation
• Radio Galaxy Zoo: Giant Radio Galaxy Classification using Multi-Domain Deep Learning