Prof. Matt Jarvis

Abstract:

We use three samples (3CRR, 6CE and 6C*) to investigate the radio luminosity function (RLF) for the 'most powerful' low-frequency selected radio sources. We find that the data are well fitted by a model with a constant ca-moving space density at high redshift as well as by one with a declining co-moving space density above some particular redshift. This behaviour is very similar to that inferred for steep-spectrum radio quasars by Willott et al (1998) in Line with the expectations of Unified Schemes. We conclude that there is as yet no evidence for a 'redshift cutoff' in the co-moving space densities of powerful classical double radio sources, and rule out a art-off at z less than or similar to 2.5.

Abstract:

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will observe several Deep Drilling Fields (DDFs) to a greater depth and with a more rapid cadence than the main survey. In this paper, we describe the ``DeepDrill'' survey, which used the Spitzer Space Telescope Infrared Array Camera (IRAC) to observe three of the four currently defined DDFs in two bands, centered on 3.6 $\mu$m and 4.5 $\mu$m. These observations expand the area which was covered by an earlier set of observations in these three fields by the Spitzer Extragalactic Representative Volume Survey (SERVS). The combined DeepDrill and SERVS data cover the footprints of the LSST DDFs in the Extended Chandra Deep Field-South field (ECDFS), the ELAIS-S1 field (ES1), and the XMM Large-Scale Structure Survey field (XMM-LSS). The observations reach an approximate $5\sigma$ point-source depth of 2 $\mu$Jy (corresponding to an AB magnitude of 23.1; sufficient to detect a 10$^{11} M_{\odot}$ galaxy out to $z\approx 5$) in each of the two bands over a total area of $\approx 29\,$deg$^2$. The dual-band catalogues contain a total of 2.35 million sources. In this paper we describe the observations and data products from the survey, and an overview of the properties of galaxies in the survey. We compare the source counts to predictions from the SHARK semi-analytic model of galaxy formation. We also identify a population of sources with extremely red ([3.6]$-$[4.5] $>1.2$) colours which we show mostly consists of highly-obscured active galactic nuclei.

Abstract:

U-band observations with the LSST have yet to be fully optimized in cadence. The straw man survey design is a simple coverage of the medium-deep-fast survey. Here we argue that deep coverage of the four deep drilling fields (XMM-LSS, ECDFS, ELAIS-S1 and COSMOS) has a much higher scientific return, given that these are also the target of the Southern Hemisphere's Square Kilometer Array Pathfinder, the MeerKAT specifically, deep radio observations.

Abstract:

We analyse the velocity dispersion properties of 472 z~0.9 star-forming galaxies observed as part of the KMOS Redshift One Spectroscopic Survey (KROSS). The majority of this sample is rotationally dominated (83 +/- 5% with v_C/sigma_0 > 1) but also dynamically hot and highly turbulent. After correcting for beam smearing effects, the median intrinsic velocity dispersion for the final sample is sigma_0 = 43.2 +/- 0.8 km/s with a rotational velocity to dispersion ratio of v_C/sigma_0 = 2.6 +/- 0.1. To explore the relationship between velocity dispersion, stellar mass, star formation rate and redshift we combine KROSS with data from the SAMI survey (z~0.05) and an intermediate redshift MUSE sample (z~0.5). While there is, at most, a weak trend between velocity dispersion and stellar mass, at fixed mass there is a strong increase with redshift. At all redshifts, galaxies appear to follow the same weak trend of increasing velocity dispersion with star formation rate. Our results are consistent with an evolution of galaxy dynamics driven by disks that are more gas rich, and increasingly gravitationally unstable, as a function of increasing redshift. Finally, we test two analytic models that predict turbulence is driven by either gravitational instabilities or stellar feedback. Both provide an adequate description of the data, and further observations are required to rule out either model.