Hintze Centre for Astrophysical Surveys

Abstract:

We present a complete structural analysis of the ellipticals (E), diffuse bulges (dB), compact bulges (cB), and discs (D) within a redshift range 0 < z < 1, and stellar mass log10(M∗/M⊙) ≥ 9.5 volume-limited sample drawn from the combined DEVILS and HST-COSMOS region. We use the profit code to profile over ∼35 000 galaxies for which visual classification into single or double component was pre-defined in Paper-I. Over this redshift range, we see a growth in the total stellar mass density (SMD) of a factor of 1.5. At all epochs we find that the dominant structure, contributing to the total SMD, is the disc, and holds a fairly constant share of ∼ 60 per cent of the total SMD from z = 0.8 to z = 0.2, dropping to ∼ 30 per cent at z = 0.0 (representing ∼ 33 per cent decline in the total disc SMD). Other classes (E, dB, and cB) show steady growth in their numbers and integrated stellar mass densities. By number, the most dramatic change across the full mass range is in the growth of diffuse bulges. In terms of total SMD, the biggest gain is an increase in massive elliptical systems, rising from 20 per cent at z = 0.8 to equal that of discs at z = 0.0 (30 per cent) representing an absolute mass growth of a factor of 2.5. Overall, we see a clear picture of the emergence and growth of all three classes of spheroids over the past 8 Gyr, and infer that in the later half of the Universe's timeline spheroid-forming processes and pathways (secular evolution, mass-accretion, and mergers) appear to dominate mass transformation over quiescent disc growth.

Abstract:

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: (i) where the spectroscopic training set has a very different distribution in color–magnitude space to the test set, and (ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular, we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ∼1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogs.

Abstract:

In this paper we present photometric redshifts for 2.7 million galaxies in the XMM-LSS and COSMOS fields, both with rich optical and near-infrared data from VISTA and HyperSuprimeCam. Both template fitting (using galaxy and Active Galactic Nuclei templates within LePhare) and machine learning (using GPz) methods are run on the aperture photometry of sources selected in the Ks-band. The resulting predictions are then combined using a Hierarchical Bayesian model, to produce consensus photometric redshift point estimates and probability distribution functions that outperform each method individually. Our point estimates have a root mean square error of ∼0.08 − 0.09, and an outlier fraction of ∼3 − 4 percent when compared to spectroscopic redshifts. We also compare our results to the COSMOS2020 photometric redshifts, which contains fewer sources, but had access to a larger number of bands and greater wavelength coverage, finding that comparable photo-z quality can be achieved (for bright and intermediate luminosity sources where a direct comparison can be made). Our resulting redshifts represent the most accurate set of photometric redshifts (for a catalogue this large) for these deep multi-square degree multi-wavelength fields to date.