Galaxy formation and evolution

Abstract:

<jats:title>Abstract</jats:title> <jats:p>We investigate the evolution of the gas mass fraction for galaxies in the COSMOS field using submillimetre emission from dust at 850μm. We use stacking methodologies on the 850 μm S2COSMOS map to derive the gas mass fraction of galaxies out to high redshifts, 0 ≤ z ≤ 5, for galaxies with stellar masses of $10^{9.5} &amp;lt; M_* ~(\rm M_{\odot }) &amp;lt; 10^{11.75}$. In comparison to previous literature studies we extend to higher redshifts, include more normal star-forming galaxies (on the main sequence), and also investigate the evolution of the gas mass fraction split by star-forming and passive galaxy populations. We find our stacking results broadly agree with scaling relations in the literature. We find tentative evidence for a peak in the gas mass fraction of galaxies at around z ∼ 2.5 − 3, just before the peak of the star formation history of the Universe. We find that passive galaxies are particularly devoid of gas, compared to the star-forming population. We find that even at high redshifts, high stellar mass galaxies still contain significant amounts of gas.</jats:p>

Abstract:

© 2020. The Astronomical Society of the Pacific. The Very Large Array Sky Survey (VLASS) is a synoptic, all-sky radio sky survey with a unique combination of high angular resolution (≈2.″5), sensitivity (a 1σ goal of 70 μJy/beam in the coadded data), full linear Stokes polarimetry, time domain coverage, and wide bandwidth (2–4 GHz). The first observations began in 2017 September, and observing for the survey will finish in 2024. VLASS will use approximately 5500 hr of time on the Karl G. Jansky Very Large Array (VLA) to cover the whole sky visible to the VLA (decl. > −40°), a total of 33 885 deg2. The data will be taken in three epochs to allow the discovery of variable and transient radio sources. The survey is designed to engage radio astronomy experts, multi-wavelength astronomers, and citizen scientists alike. By utilizing an “on the fly” interferometry mode, the observing overheads are much reduced compared to a conventional pointed survey. In this paper, we present the science case and observational strategy for the survey, and also results from early survey observations.

Abstract:

Observations of the early Universe suggest that reionization was complete by z ∼ 6, however, the exact history of this process is still unknown. One method for measuring the evolution of the neutral fraction throughout this epoch is via observing the Lyα damping wings of high-redshift quasars. In order to constrain the neutral fraction from quasar observations, one needs an accurate model of the quasar spectrum around Lyα, after the spectrum has been processed by its host galaxy but before it is altered by absorption and damping in the intervening IGM. In this paper, we present a novel machine learning approach, using artificial neural networks, to reconstruct quasar continua around Lyα. Our QSANNDRA algorithm improves the error in this reconstruction compared to the state-of-the-art PCA-based model in the literature by 14.2% on average, and provides an improvement of 6.1% on average when compared to an extension thereof. In comparison with the extended PCA model, QSANNDRA further achieves an improvement of 22.1% and 16.8% when evaluated on low-redshift quasars most similar to the two high-redshift quasars under consideration, ULAS J1120+0641 at z = 7.0851 and ULAS J1342+0928 at z = 7.5413, respectively. Using our more accurate reconstructions of these two z > 7 quasars, we estimate the neutral fraction of the IGM using a homogeneous reionization model and find x¯H1=0.25+0.05−0.05 at z = 7.0851 and x¯H1=0.60+0.11−0.11 at z = 7.5413. Our results are consistent with the literature and favour a rapid end to reionization.