Prof. Matt Jarvis

Abstract:

We present cosmological (30−400 Mpc) distributions of neutral hydrogen (H i) in the intergalactic medium (IGM) traced by Lyα emitters (LAEs) and QSOs at z = 2.1–2.5, selected with the data of the ongoing Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) and the eBOSS survey. Motivated by a previous study of Mukae et al., we investigate spatial correlations of LAEs and QSOs with H i tomography maps reconstructed from H i Lyα forest absorption in the spectra of background galaxies and QSOs obtained by the CLAMATO survey and this study, respectively. In the cosmological volume far from QSOs, we find that LAEs reside in regions of strong H i absorption, i.e., H i rich, which is consistent with results of previous galaxy−background QSO pair studies. Moreover, there is an anisotropy in the H i distribution plot of transverse and line-of-sight distances; on average the H i absorption peak is blueshifted by ~200 km s−1 from the LAE Lyα redshift, reproducing the known average velocity offset between the Lyα emission redshift and the galaxy systemic redshift. We have identified a ~40 Mpc scale volume of H i underdensity that is a candidate for a giant H ii bubble, where six QSOs and an LAE overdensity exist at $\left\langle z\right\rangle =2.16$. The coincidence of the QSO and LAE overdensities with the H i underdensity indicates that the ionizing photon radiation of the QSOs has created a highly ionized volume of multiple proximity zones in a matter overdensity. Our results suggest an evolutionary picture where H i gas in an overdensity of galaxies becomes highly photoionized when QSOs emerge in the galaxies.

Abstract:

Context. Distant galaxy clusters provide an effective laboratory in which to study galaxy evolution in dense environments and at early cosmic times. Aims. We aim to identify distant galaxy clusters as extended X-ray sources that are coincident with overdensities of characteristically bright galaxies. Methods. We used optical and near-infrared data from the Hyper Suprime-Cam and VISTA Deep Extragalactic Observations (VIDEO) surveys to identify distant galaxy clusters as overdensities of bright, zphot = 0:8 galaxies associated with extended X-ray sources detected in the ultimate XMM extragalactic survey (XXL). Results. We identify a sample of 35 candidate clusters at 0:80 = z = 1:93 from an approximately 4.5 deg2 sky area. This sample includes 15 newly discovered candidate clusters, ten previously detected but unconfirmed clusters, and ten spectroscopically confirmed clusters. Although these clusters host galaxy populations that display a wide variety of quenching levels, they exhibit well-defined relations between quenching, cluster-centric distance, and galaxy luminosity. The brightest cluster galaxies (BCGs) within our sample display colours that are consistent with a bimodal population composed of an old and red sub-sample together with a bluer, more diverse sub-sample. Conclusions The relation between galaxy masses and quenching seem to already be in place at z ~ 1, although there is no significant variation in the quenching fraction with the cluster-centric radius. The BCG bimodality might be explained by the presence of a younger stellar component in some BCGs, but additional data are needed to confirm this scenario.

Abstract:

Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing 12 photo-z algorithms applied to mock data produced for The Rubin Observatory Legacy Survey of Space and Time Dark Energy Science Collaboration. By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/underbreadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics.

Abstract:

Wide-area imaging surveys are one of the key ways of advancing our understanding of cosmology, galaxy formation physics, and the large-scale structure of the Universe in the coming years. These surveys typically require calculating redshifts for huge numbers (hundreds of millions to billions) of galaxies – almost all of which must be derived from photometry rather than spectroscopy. In this paper, we investigate how using statistical models to understand the populations that make up the colour–magnitude distribution of galaxies can be combined with machine learning photometric redshift codes to improve redshift estimates. In particular, we combine the use of Gaussian mixture models with the high-performing machine-learning photo-z algorithm GPz and show that modelling and accounting for the different colour–magnitude distributions of training and test data separately can give improved redshift estimates, reduce the bias on estimates by up to a half, and speed up the run-time of the algorithm. These methods are illustrated using data from deep optical and near-infrared data in two separate deep fields, where training and test data of different colour–magnitude distributions are constructed from the galaxies with known spectroscopic redshifts, derived from several heterogeneous surveys.