Hintze Centre for Astrophysical Surveys

Abstract:

In this work, we extend the catalog of low-surface brightness (LSB) galaxies, including ultra-diffuse galaxy (UDG) candidates, within ≈0.4 Rvir of the Hydra I cluster of galaxies based on deep images from the VST Early-type GAlaxy Survey (VEGAS). The new galaxies were found by applying an automatic detection tool and carrying out additional visual inspections of g and r band images. This led to the detection of 11 UDGs and 8 more LSB galaxies. For all of them, we assessed the cluster membership using the color- magnitude relation derived for early-type giant and dwarf galaxies in Hydra I. The UDGs and new LSB galaxies found in Hydra I span a wide range of central surface brightness (22.7 ≤ μ0,g ≤ 26.5 mag arcsec-2), effective radius (0.6 ≤ Re ≤ 4.0 kpc), and color (0.4 ≤ g-r ≤ 0.9 mag), and have stellar masses in the range ∼5 × 106-2 × 108 MO. The 2D projected distribution of both galaxy types is similar to the spatial distribution of dwarf galaxies, with over-densities in the cluster core and north of the cluster center. They have similar color distribution and comparable stellar masses to the red dwarf galaxies. Based on photometric selection, we identify a total of nine globular cluster (GC) candidates associated to the UDGs and four to the LSB galaxies, with the highest number of candidates in an individual UDG being three.We find that there are no relevant differences between dwarfs, LSB galaxies, and UDGs: the structural parameters (i.e., surface brightness, size, color, and n-index) and GC content of the three classes have similar properties and trends. This finding is consistent with UDGs being the extreme LSB tail of the size-luminosity distribution of dwarfs in this environment

Abstract:

In this work we present a novel compute framework for reconstructing Faraday depth signals from noisy and incomplete spectro-polarimetric radio datasets. This framework is based on a compressed-sensing approach that addresses a number of outstanding issues in Faraday depth reconstruction in a systematic and scaleable manner. We apply this framework to early-release data from the MeerKAT MIGHTEE polarisation survey.