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   https://doi.org/10.1093/mnras/staa832  

   Gupta, N ; Pannella, M ; Mohr, J J ; Klein, M ; Rykoff, E S ; Annis, J ; Avila, S ; Bianchini, F ; Brooks, D ; Buckley-Geer, E ; et al ( May 2020 , Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We study the properties of the Sydney University Molonglo Sky Survey (SUMSS) 843 MHz radio active galactic nuclei (AGNs) population in galaxy clusters from two large catalogues created using the Dark Energy Survey (DES): ∼11 800 optically selected RM-Y3 and ∼1000 X-ray selected MARD-Y3 clusters. We show that cluster radio loud AGNs are highly concentrated around cluster centres to $z$ ∼ 1. We measure the halo occupation number for cluster radio AGNs above a threshold luminosity, finding that the number of radio AGNs per cluster increases with cluster halo mass as N ∝ M1.2 ± 0.1 (N ∝ M0.68 ± 0.34) for the RM-Y3 (MARD-Y3) sample. Together, these results indicate that radio mode feedback is favoured in more massive galaxy clusters. Using optical counterparts for these sources, we demonstrate weak redshift evolution in the host broad-band colours and the radio luminosity at fixed host galaxy stellar mass. We use the redshift evolution in radio luminosity to break the degeneracy between density and luminosity evolution scenarios in the redshift trend of the radio AGNs luminosity function (LF). The LF exhibits a redshift trend of the form (1 + $z$)γ in density and luminosity, respectively, of γD = 3.0 ± 0.4 and γP = 0.21 ± 0.15 in the RM-Y3 sample, and γD = 2.6 ± 0.7 and γP = 0.31 ± 0.15 in MARD-Y3. We discuss the physical drivers of radio mode feedback in cluster AGNs, and we use the cluster radio galaxy LF to estimate the average radio-mode feedback energy as a function of cluster mass and redshift and compare it to the core (<0.1R500) X-ray radiative losses for clusters at $z$ < 1. 

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   https://doi.org/10.1093/mnras/sty3070  

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   https://doi.org/10.1093/mnras/staa2805  

   Tang, H ; Scaife, A M ; Wong, O I ; Kapińska, A D ; Rudnick, L ; Shabala, S S ; Seymour, N ; Norris, R P ( October 2020 , Monthly Notices of the Royal Astronomical Society)

   null (Ed.)

   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 $\gt 60$ 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. 

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4. Radio Galaxy Zoo: Claran – a deep learning classifier for radio morphologies

   https://doi.org/10.1093/mnras/sty2646  

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   https://doi.org/10.1088/1538-3873/ab213d  

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