Search and identification of transient and variable radio sources using MeerKAT observations: a case study on the MAXI J1820+070 field
(2022)
21 new long-term variables in the GX 339-4 field: two years of MeerKAT monitoring
(2022)
MIGHTEE-H I: the H I size–mass relation over the last billion years
Monthly Notices of the Royal Astronomical Society Oxford University Press 512:2 (2022) 2697-2706
Abstract:
We present the observed H I size–mass relation of 204 galaxies from the MIGHTEE Survey Early Science data. The high sensitivity of MeerKAT allows us to detect galaxies spanning more than 4 orders of magnitude in H I mass, ranging from dwarf galaxies to massive spirals, and including all morphological types. This is the first time the relation has been explored on a blind homogeneous data set that extends over a previously unexplored redshift range of 0 < z < 0.084, i.e. a period of around one billion years in cosmic time. The sample follows the same tight logarithmic relation derived from previous work, between the diameter (DHI) and the mass (MHI) of H I discs. We measure a slope of 0.501 ± 0.008, an intercept of −3.252+0.073−0.074, and an observed scatter of 0.057 dex. For the first time, we quantify the intrinsic scatter of 0.054 ± 0.003 dex (∼10 per cent), which provides a constraint for cosmological simulations of galaxy formation and evolution. We derive the relation as a function of galaxy type and find that their intrinsic scatters and slopes are consistent within the errors. We also calculate the DHI−MHI relation for two redshift bins and do not find any evidence for evolution with redshift. These results suggest that over a period of one billion years in look-back time, galaxy discs have not undergone significant evolution in their gas distribution and mean surface mass density, indicating a lack of dependence on both morphological type and redshift.Evidence for X-Ray Emission in Excess to the Jet-afterglow Decay 3.5 yr after the Binary Neutron Star Merger GW 170817: A New Emission Component
The Astrophysical Journal Letters American Astronomical Society 927:1 (2022) l17
Quantifying uncertainty in deep learning approaches to radio galaxy classification
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 511:3 (2022) 3722-3740