Related papers: Star-Galaxy Classification in Deep LSST Data with …

We discuss the statistical foundations of morphological star-galaxy separation. We show that many of the star-galaxy separation metrics in common use today (e.g. by SDSS or SExtractor) are closely related both to each other, and to the…

We present the results of a photometric redshift analysis designed to identify z>6 galaxies from the near-IR HST imaging in three deep fields (HUDF, HUDF09-2 & ERS). By adopting a rigorous set of criteria for rejecting low-z interlopers,…

The search for fast optical transients, such as the expected electromagnetic counterparts to binary neutron star mergers, is riddled with false positives ranging from asteroids to stellar flares. While moving objects are readily rejected…

I review a technique for interpreting faint galaxy data which traces the evolution with cosmic time of the galaxy luminosity density, as determined from several deep spectroscopic samples and the HDF. The method relies on the rest frame UV…

We aim to study the statistical properties of dusty star-forming galaxies, such as their number counts, luminosity functions (LF) and dust-obscured star-formation rate density (SFRD). We use state-of-the-art de-blended Herschel catalogue in…

Over the last few years, both ALMA and Spitzer/IRAC observations have revealed a population of likely massive galaxies at $z>3$ that was too faint to be detected in HST rest-frame ultraviolet imaging. However, due to the very limited…

Cosmological constraints from galaxy clusters rely on accurate measurements of the mass and internal structure of clusters. An important source of systematic uncertainty in cluster mass and structure measurements is the secure selection of…

We analyse the joint distribution of dust attenuation and projected axis ratios, together with galaxy size and surface brightness profile information, to infer lessons on the dust content and star/dust geometry within star-forming galaxies…

We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in HST UV-optical imaging of nearby spiral galaxies…

The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multi-band wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of…

We present the first large, unbiased sample of Lyman Break Galaxies (LBGs) at z ~ 1. Far ultraviolet-dropout (1530 A) galaxies in the Chandra Deep Field South have been selected using GALEX data. This first large sample in the z ~ 1…

We combine a semi-analytic model of galaxy formation with simple analytic recipes describing the absorption and re-emission of starlight by dust in the interstellar medium of galaxies. We use the resulting models to predict galaxy counts…

We use the deep ground-based optical photometry of the Lyman Break Galaxy (LBG) Survey to derive robust measurements of the faint-end slope (alpha) of the UV LF at redshifts 1.9<z<3.4. Our sample includes >2000 spectroscopic redshifts and…

At present, the precision of deep ultraviolet photometry is somewhat limited by the dearth of faint ultraviolet standard stars. In an effort to improve this situation, we present a uniform catalog of eleven new faint (u sim17) ultraviolet…

Lopsided galaxies are late-type galaxies with a non-axisymmetric disk due to an uneven distribution of their stellar mass. Despite being a relatively common perturbation, several questions regarding its origin and the information that can…

Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supervised machine learning method (GoogLeNet) to automatically…

We analyze the clustering of galaxies using the z=1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Large Synoptic Survey Telescope (LSST). We present…

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will observe several Deep Drilling Fields (DDFs) to a greater depth and with a more rapid cadence than the main survey. In this paper, we describe the ``DeepDrill''…

Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…

Understanding the formation and evolution of low surface brightness galaxies (LSBGs) is critical for explaining their wide-ranging properties. However, studies of LSBGs in deep photometric surveys are often hindered by a lack of distance…