Dark matter halo properties of GAMA galaxy groups from 100 square degrees of KiDS weak lensing data

The Kilo-Degree Survey (KiDS) is an optical wide-field survey designed to map the matter distribution in the Universe using weak gravitational lensing. In this paper, we use these data to measure the density profiles and masses of a sample of $\sim \mathrm{1400}$ spectroscopically identified galaxy groups and clusters from the Galaxy And Mass Assembly (GAMA) survey. We detect a highly significant signal (signal-to-noise-ratio $\sim$ 120), allowing us to study the properties of dark matter haloes over one and a half order of magnitude in mass, from $M \sim 10^{13}-10^{14.5} h^{-1}\mathrm{M_{\odot}}$. We interpret the results for various subsamples of groups using a halo model framework which accounts for the mis-centring of the Brightest Cluster Galaxy (used as the tracer of the group centre) with respect to the centre of the group's dark matter halo. We find that the density profiles of the haloes are well described by an NFW profile with concentrations that agree with predictions from numerical simulations. In addition, we constrain scaling relations between the mass and a number of observable group properties. We find that the mass scales with the total r-band luminosity as a power-law with slope $1.16 \pm 0.13$ (1-sigma) and with the group velocity dispersion as a power-law with slope $1.89 \pm 0.27$ (1-sigma). Finally, we demonstrate the potential of weak lensing studies of groups to discriminate between models of baryonic feedback at group scales by comparing our results with the predictions from the Cosmo-OverWhelmingly Large Simulations (Cosmo-OWLS) project, ruling out models without AGN feedback

Phylotranscriptomics suggests the jawed vertebrate ancestor could generate diverse helper and regulatory T cell subsets

This study was supported by The Royal Society Research Grant RG130789 awarded to HD, as well as by a University of Aberdeen Centre for Genome-Enabled Biology and Medicine PhD studentship and Marine Alliance for Science and Technology for Scotland (MASTS) research grant SG363 awarded to AKR.Peer reviewedPublisher PD