We describe Hubble Space Telescope (HST ) imaging of 10 of the 20 ESO Distant Cluster Survey (EDisCS) fields. Each $40 arcmin 2 field was imaged in the F814W filter with the Advanced Camera for Surveys Wide Field Camera. Based on these data, we present visual morphological classifications for the $920 sources per field that are brighter than I auto ¼ 23 mag. We use these classifications to quantify the morphological content of 10 intermediate-redshift (0:5 < z < 0:8) galaxy clusters within the HST survey region. The EDisCS results, combined with previously published data from seven higher redshift clusters, show no statistically significant evidence for evolution in the mean fractions of elliptical, S0, and late-type (Sp+Irr) galaxies in clusters over the redshift range 0:5 < z < 1:2. In contrast, existing studies of lower redshift clusters have revealed a factor of $2 increase in the typical S0 fraction between z ¼ 0:4 and 0, accompanied by a commensurate decrease in the Sp+Irr fraction and no evolution in the elliptical fraction. The EDisCS clusters demonstrate that cluster morphological fractions plateau beyond z % 0:4. They also exhibit a mild correlation between morphological content and cluster velocity dispersion, highlighting the importance of careful sample selection in evaluating evolution. We discuss these findings in the context of a recently proposed scenario in which the fractions of passive (E, S0) and star-forming (Sp, Irr) galaxies are determined primarily by the growth history of clusters.

In this paper we describe the first data release of the the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey. VIDEO is a ∼ 12 degree 2 survey in the near-infrared Z,Y ,J,H and K s bands, specifically designed to enable the evolution of galaxies and large structures to be traced as a function of both epoch and environment from the present day out to z=4, and active galactic nuclei (AGN) and the most massive galaxies up to and into the epoch of reionization. With its depth and area, VIDEO will be able to fully explore the period in the Universe where AGN and starburst activity were at their peak and the first galaxy clusters were beginning to virialize. VIDEO therefore offers a unique data set with which to investigate the interplay between AGN, starbursts and environment, and the role of feedback at a time when it was potentially most crucial.We provide data over the VIDEO-XMM3 tile, which also covers the Canada-France-Hawaii-Telescope Legacy Survey Deep-1 field (CFHTLS-D1). The released VIDEO data reach a 5σ AB-magnitude depth of Z = 25.7, Y = 24.5, J = 24.4, H = 24.1 and K s = 23.8 in 2 arcsec diameter apertures (the full depth of Y = 24.6 will be reached within the full integration time in future releases). The data are compared to previous surveys over this field and we find good astrometric agreement with the Two-Micron All Sky Survey, and source counts in agreement with the recently released UltraVISTA survey data. The addition of the VIDEO data to the CFHTLS-D1 optical data increases the accuracy of photometric redshifts and significantly reduces the fraction of catastrophic outliers over the redshift range 0 < z < 1 from 5.8 to 3.1 per cent in the absence of an i−band luminosity prior. However, we expect the main improvement in photometric redshifts will come in the redshift range 1 < z < 4 due to the sensitivity to the Balmer and 4000 Å breaks provided by the near-infrared VISTA filters. All images and catalogues presented in this paper are publicly available through ESO's phase 3 archive and the VISTA Science Archive.

The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification through visual inspection unfeasible. We present ClaRAN -Classifying Radio sources Automatically with Neural networks -a proof-of-concept radio source morphology classifier based upon the Faster Region-based Convolutional Neutral Networks (Faster R-CNN) method. Specifically, we train and test ClaRAN on the FIRST and WISE images from the Radio Galaxy Zoo Data Release 1 catalogue. ClaRAN provides end users with automated identification of radio source morphology classifications from a simple input of a radio image and a counterpart infrared image of the same region. ClaRAN is the first open-source, end-to-end radio source morphology classifier that is capable of locating and associating discrete and extended components of radio sources in a fast (< 200 milliseconds per image) and accurate (≥ 90%) fashion. Future work will improve ClaRAN's relatively lower success rates in dealing with multi-source fields and will enable ClaRAN to identify sources on much larger fields without loss in classification accuracy.

Understanding the interplay between black-hole accretion and star formation, and how to disentangle the two, is crucial to our understanding of galaxy formation and evolution. To investigate, we use a combination of optical and near-infrared photometry to select a sample of 74 quasars from the VISTA Deep Extragalactic Observations (VIDEO) Survey, over 1 deg 2 . The depth of VIDEO allows us to study very low accretion rates and/or lower-mass black holes, and 26 per cent of the candidate quasar sample has been spectroscopically confirmed. We use a radio-stacking technique to sample below the nominal flux-density threshold using data from the Very Large Array at 1.4 GHz and find, in agreement with other work, that a power-law fit to the quasar-related radio source counts is inadequate at low flux density. By comparing with a control sample of galaxies (where we match in terms of stellar mass), and by estimating the star formation rate, we suggest that this radio emission is predominantly caused by accretion activity rather than star-formation activity.