We use the optical-infrared imaging in the UKIDSS Ultra Deep Survey field, in combination with the new deep radio map of Arumugam et al., to calculate the distribution of radio luminosities among galaxies as a function of stellar mass in two redshift bins across the interval 0.4 < z ≤ 1.2. This is done with the use of a new Bayesian method to classify stars and galaxies in surveys with multi-band photometry, and to derive photometric redshifts and stellar masses for those galaxies. We compare the distribution to that observed locally and find agreement if we consider only objects believed to be weak-lined radio-loud galaxies. Since the local distribution is believed to be the result of an energy balance between radiative cooling of the gaseous halo and mechanical AGN heating, we infer that this balance was also present as long ago as z ≈ 1. This supports the existence of a direct link between the presence of a low-luminosity ('hot-mode') radio-loud active galactic nucleus and the absence of ongoing star formation.

We present the results of an analysis of a well-selected sample of galaxies with active and inactive galactic nuclei from the Sloan Digital Sky Survey, in the range 0.01 < z < 0.16. The SDSS galaxy catalogue was split into two classes of active galaxies, Type 2 active galactic nuclei (AGN) and composites, and one set of inactive, star-forming/passive galaxies. For each active galaxy, two inactive control galaxies were selected by matching redshift, absolute magnitude, inclination, and radius. The sample of inactive galaxies naturally divides into a red and a blue sequence, while the vast majority of AGN hosts occur along the red sequence. In terms of Hα equivalent width (EW), the population of composite galaxies peaks in the valley between the two modes, suggesting a transition population. However, this effect is not observed in other properties such as the colour-magnitude space or colour-concentration plane. Active galaxies are seen to be generally bulge-dominated systems, but with enhanced Hα emission compared to inactive red-sequence galaxies. AGN and composites also occur in less dense environments than inactive red-sequence galaxies, implying that the fuelling of AGN is more restricted in high-density environments. These results are therefore inconsistent with theories in which AGN host galaxies are a 'transition' population. We also introduce a systematic 3D spectroscopic imaging survey, to quantify and compare the gaseous and stellar kinematics of a well-selected, distance-limited sample of up to 20 nearby Seyfert galaxies, and 20 inactive control galaxies with well-matched optical properties. The survey aims to search for dynamical triggers of nuclear activity and address outstanding controversies in optical/infrared imaging surveys.

Using the Inamori Magellan Areal Camera and Spectrograph (IMACS) integral-field unit (IFU) on the 6.5 m Magellan telescope, we have designed the first statistically significant investigation of the two-dimensional distribution and kinematics of ionised gas and stars in the central kiloparsec regions of a well-matched sample of Seyfert and inactive control galaxies selected from the Sloan Digital Sky Survey. The goals of the project are to use the fine spatial sampling (0.2 arcsec pixel −1 ) and large wavelength coverage (4000-7000Å) of the IMACS-IFU to search for dynamical triggers of nuclear activity in the central region where active galactic nucleus (AGN) activity and dynamical timescales become comparable, to identify and assess the impact of AGNdriven outflows on the host galaxy and to provide a definitive sample of local galaxy kinematics for comparison with future three-dimensional kinematic studies of high-redshift systems. In this paper, we provide the first detailed description of the procedure to reduce and calibrate data from the IMACS-IFU in 'long-mode' to obtain two-dimensional maps of the distribution and kinematics of ionised gas and stars. The sample selection criteria are presented, observing strategy described and resulting maps of the sample galaxies presented along with a description of the observed properties of each galaxy and the overall observed properties of the sample.

The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environment or employed simplistic obstacle avoidance, separate from the estimation procedure. In this paper, we explore the coupling of the path planning task for both source term estimation and obstacle avoidance in an adaptive framework. The proposed system intelligently produces potential gas sampling locations that will reliably inform the estimation engine by not sampling in the wake of buildings as frequently. Then a tree search is performed to generate paths toward the estimated source location that traverse around any obstacles and still allow for exploration of potentially superior sampling locations.The proposed informed tree planning algorithm is then tested against the standard Entrotaxis and Entrotaxis-Jump techniques in a series of high fidelity simulations. The proposed system is found to reduce source estimation error far more efficiently than its competitors in a feature rich environment, whilst also exhibiting vastly more consistent and robust results.