First author: Dominic Smith
Galaxies broadly fall into two categories: star-forming (blue) galaxies and quiescent (red) galaxies. In between, one finds the less populated ``green valley". Some of these galaxies are suspected to be in the process of ceasing their star-formation through a gradual exhaustion of gas supply or already dead and are experiencing a rejuvenation of star-formation through fuel injection. We use the Galaxy And Mass Assembly database and the Galaxy Zoo citizen science morphological estimates to compare the morphology of galaxies in the green valley against those in the red sequence and blue cloud.
First author: Atsuhisa Ota
The nonlinear Lagrangian displacement field and initial linear density field are highly correlated. Therefore, reconstructing the nonlinear displacement field could better extract the primordial cosmological information from the late time density field. Continuing from Ref. [1], we investigate to what extent the iterative displacement reconstruction in Ref. [2] can recover the true displacement field with a particular emphasis on improving the numerical discreteness effect and improving the perturbation theory model for the postreconstructed field.
First author: Siddharth Chaini
We present MargNet, a deep learning-based classifier for identifying stars, quasars and compact galaxies using photometric parameters and images from the Sloan Digital Sky Survey (SDSS) Data Release 16 (DR16) catalogue. MargNet consists of a combination of Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) architectures. Using a carefully curated dataset consisting of 240,000 compact objects and an additional 150,000 faint objects, the machine learns classification directly from the data, minimising the need for human intervention.
First author: Josh Borrow
All modern galaxy formation models employ stochastic elements in their sub-grid prescriptions to discretise continuous equations across the time domain. In this paper, we investigate how the stochastic nature of these models, notably star formation, black hole accretion, and their associated feedback, that act on small ($<$ kpc) scales, can back-react on macroscopic galaxy properties (e.g. stellar mass and size) across long ($>$ Gyr) timescales. We find that the scatter in scaling relations predicted by the EAGLE model implemented in the SWIFT code can be significantly impacted by random variability between re-simulations of the same object, even when galaxies are resolved by tens of thousands of particles.
First author: L. Bassini
Recent observations indicate that galactic outflows are ubiquitous in high redshift galaxies, including normal star forming galaxies, quasar hosts, and dusty star forming galaxies (DSFGs). However, the impact of outflows on the evolution of their hosts is still an open question. Here, we analyse the star formation histories (SFH) and galactic outflow properties of galaxies in massive haloes ($10^{12}M_{\odot}<M_{\rm vir} <5\times 10^{12}M_{\odot}$) at $z\gtrsim5.5$ in three zoom-in cosmological simulations from the MassiveFIRE suite, as part of the Feedback In Realistic Environments (FIRE) project.
First author: Suhail Dhawan
The local distance ladder estimate of the Hubble constant ($H_0$) is important in cosmology, given the recent tension with the early universe inference. We estimate $H_0$ from the Type Ia supernova (SN Ia) distance ladder, inferring SN Ia distances with the hierarchical Bayesian SED model, BayeSN. This method has a notable advantage of being able to continuously model the optical and near-infrared (NIR) SN Ia light curves simultaneously.
First author: Camila de Sá-Freitas
The epoch in which galactic discs settle is a major benchmark to test models of galaxy formation and evolution but is as yet largely unknown. Once discs settle and become self-gravitating enough, stellar bars are able to form; therefore, determining the ages of bars can shed light on the epoch of disc settling, and on the onset of secular evolution. Nevertheless, until now, timing when the bar formed has proven challenging.
First author: Christopher J. Agostino
In this work, we use ~500 low-redshift (z ~ 0.1) X-ray AGNs observed by XMM-Newton and SDSS to investigate the prevalence and nature of AGNs that apparently lack optical emission lines (optically dull AGNs''). Although 1/4 of spectra appear absorption-line dominated in visual assessment, line extraction with robust continuum subtraction from the MPA/JHU catalog reveals usable [OIII] measurements in 98% of the sample, allowing us to study [OIII]-underluminous AGNs together with more typical AGNs in the context of the L$_{\mathrm{[OIII]}}$--L$_{X}$ relation.
Geraint F. Lewis
Based upon a metallicity selection, we identify a significant sub-population of the inner halo globular clusters in the Andromeda Galaxy which we name the Dulais Structure. It is distinguished as a co-rotating group of 10-20 globular clusters which appear to be kinematically distinct from, and on average more metal-poor than, the majority of the inner halo population. Intriguingly, the orbital axis of this Dulais Structure is closely aligned with that of the younger accretion event recently identified using a sub-population of globular clusters in the outer halo of Andromeda, and this is strongly suggestive of a causal relationship between the two.
First author: Evangelos S. Papaefthymiou
We present a new diagnostic diagram for local ultraluminous infrared galaxies (ULIRGs) and quasars, analysing particularly the Spitzer Space Telescope’s Infrared Spectrograph (IRS) spectra of 102 local ULIRGs and 37 Palomar Green quasars. Our diagram is based on a special non-linear mapping of these data, employing the Kernel Principal Component Analysis method. The novelty of this map lies in the fact that it distributes the galaxies under study on the surface of a well-defined ellipsoid, which, in turn, links basic concepts from geometry to physical properties of the galaxies.
