2013MNRAS.433.1185M

In this paper we present a detailed study of the structures and morphologies of a sample of 1188 massive galaxies with M* ≥ 1010M☉ between redshifts z = 1 and 3 within the Ultra Deep Survey (UDS) region of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) field. Using this sample we determine how galaxy structure and morphology evolve with time, and investigate the nature of galaxy structure at high redshift. We visually classify our sample into discs, ellipticals and peculiar systems and correct for redshift effects on these classifications through simulations. We find significant evolution in the fractions of galaxies at a given visual classification as a function of redshift. The peculiar population is dominant at z > 2 with a substantial spheroid population, and a negligible disc population. We compute the transition redshift, ztrans, where the combined fraction of spheroidal and disc galaxies is equal to that of the peculiar population, as ztrans = 1.86±0.62 for galaxies in our stellar mass range. We find that this transition changes as a function of stellar mass, with Hubble-type galaxies becoming dominant at higher redshifts for higher mass galaxies (ztrans = 2.22±0.82), than for the lower mass galaxies (ztrans = 1.73±0.57). Higher mass galaxies become morphologically settled before their lower mass counterparts, a form of morphological downsizing. We furthermore compare our visual classifications with the Sérsic index, the concentration, asymmetry and clumpiness (CAS) parameters, star formation rate and rest-frame U - B colour. We find links between the colour of a galaxy, its star formation rate and how extended or peculiar it appears. Finally, we discuss the negligible z > 2 disc fraction based on visual morphologies and speculate that this is an effect of forming disc appearing peculiar through processes such as violent disc instabilities or mergers. We conclude that to properly define and measure high-redshift morphology and structure a new and more exact classification scheme is needed.