Aprajita Verma

Abstract:

In these proceedings we highlight the primary scientific goals and design of the WEAVE-LOFAR survey, which will use the new WEAVE spectrograph on the 4.2m William Herschel Telescope to provide the primary source of spectroscopic information for the LOFAR Surveys Key Science Project. Beginning in 2018, WEAVE-LOFAR will generate more than 10$^6$ R=5000 365-960 nm spectra of low-frequency selected radio sources, across three tiers designed to efficiently sample the redshift-luminosity plane, and produce a data set of enormous legacy value. The radio frequency selection, combined with the high multiplex and throughput of the WEAVE spectrograph, make obtaining redshifts in this way very efficient, and we expect that the redshift success rate will approach 100 per cent at $z < 1$. This unprecedented spectroscopic sample - which will be complemented by an integral field component - will be transformational in key areas, including studying the star formation history of the Universe, the role of accretion and AGN-driven feedback, properties of the epoch of reionisation, cosmology, cluster haloes and relics, as well as the nature of radio galaxies and protoclusters. Each topic will be addressed in unprecedented detail, and with the most reliable source classifications and redshift information in existence.

Abstract:

We present a series of results from a clustering analysis of the first data release of the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey. VIDEO is the only survey currently capable of probing the bulk of stellar mass in galaxies at redshifts corresponding to the peak of star formation on degree scales. Galaxy clustering is measured with the two-point correlation function, which is calculated using a non-parametric kernel-based density estimator. We use our measurements to investigate the connection between the galaxies and the host dark matter halo using a halo occupation distribution methodology, deriving bias, satellite fractions, and typical host halo masses for stellar masses between 10 9.35 and 10 10.85 M ⊙ , at redshifts 0.5 < z < 1.7. Our results show typical halo mass increasing with stellar mass (with moderate scatter) and bias increasing with stellar mass and redshift consistent with previous studies. We find that the satellite fraction increased towards low redshifts, from ~5 per cent at z ~ 1.5 to ~20 per cent at z ~ 0.6. We combine our results to derive the stellar mass-to-halo mass ratio for both satellites and centrals over a range of halo masses and find the peak corresponding to the halo mass with maximum star formation efficiency to be ~2 × 10 12 M ⊙ , finding no evidence for evolution.

Abstract:

We report the discovery of 29 promising (and 59 total) new lens candidates from the CFHT Legacy Survey (CFHTLS) based on about 11 million classifications performed by citizen scientists as part of the first Space Warps lens search. The goal of the blind lens search was to identify lens candidates missed by robots (the RingFinder on galaxy scales and ArcFinder on group/cluster scales) which had been previously used to mine the CFHTLS for lenses. We compare some properties of the samples detected by these algorithms to the Space Warps sample and find them to be broadly similar. The image separation distribution calculated from the Space Warps sample shows that previous constraints on the average density profile of lens galaxies are robust. SpaceWarps recovers about 65% of known lenses, while the new candidates show a richer variety compared to those found by the two robots. This detection rate could be increased to 80% by only using classifications performed by expert volunteers (albeit at the cost of a lower purity), indicating that the training and performance calibration of the citizen scientists is very important for the success of Space Warps. In this work we present the SIMCT pipeline, used for generating in situ a sample of realistic simulated lensed images. This training sample, along with the false positives identified during the search, has a legacy value for testing future lens finding algorithms. We make the pipeline and the training set publicly available.