Zooniverse

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 quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications, the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of ‘smooth’ galaxies with parametric morphologies to select a sample of featureless discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs.