Related papers: Detection of extragalactic Ultra-Compact Dwarfs an…
Many recent observational and theoretical studies suggest that globular clusters (GCs) host compact object populations large enough to play dominant roles in their overall dynamical evolution. Yet direct detection, particularly of black…
We investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in conjunction with CNNs, by retraining networks first trained…
Traditionally globular clusters and dwarf spheroidal galaxies have been distinguished by using one or more of the following criteria: (1) mass, (2) luminosity, (3) size, (4) mass-to-light ratio and (5) spread in metallicity. However, a few…
The unprecedented volume and quality of data from space- and ground-based telescopes present an opportunity for machine learning to identify new classes of variable stars and peculiar systems that may have been overlooked by traditional…
Ultra-diffuse galaxies (UDGs) and compact dwarfs (CDs) occupy opposite extremes of the structural parameter space of dwarf galaxies, yet their spatial distributions in clusters suggest a possible evolutionary connection. Observational…
Automating classification of galaxy components is important for understanding the formation and evolution of galaxies. Traditionally, only the larger galaxy structures such as the spiral arms, bulge, and disc are classified. Here we use…
We present \textsc{Mathpop}, a novel method to infer the globular cluster (GC) counts in ultra-diffuse galaxies (UDGs) and low-surface brightness galaxies (LSBGs). Many known UDGs have a surprisingly high ratio of GC number to surface…
Globular clusters (GCs) provide one way of determining when the most important periods of star formation in dwarf elliptical (dE) galaxies occurred. Thus, they are also useful for comparing the star formation histories of dwarf and giant…
With the advent of future big-data surveys, automated tools for unsupervised discovery are becoming ever more necessary. In this work, we explore the ability of deep generative networks for detecting outliers in astronomical imaging…
We propose a novel set of Poisson Cluster Process (PCP) models to detect Ultra-Diffuse Galaxies (UDGs), a class of extremely faint, enigmatic galaxies of substantial interest in modern astrophysics. We model the unobserved UDG locations as…
Evolution of galaxies in dense environments can be affected by close encounters with neighbouring galaxies and interactions with the intracluster medium. Dwarf galaxies (dGs) are important as their low mass makes them more susceptible to…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
Globular Clusters (GCs) in the Milky Way are the primary laboratories for establishing the ages of the oldest stellar populations and for measuring the color-magnitude relation of stars. In infrared (IR) color-magnitude diagrams (CMDs), the…
We present ultraviolet (UV) integrated colors of 44 Galactic globular clusters (GGCs) observed with the Galaxy Evolution Explorer (GALEX) in both FUV and NUV bands. This data-base is the largest homogeneous catalog of UV colors ever…
We present Hubble Space Telescope ACS/WFC and WFC3/UVIS imaging for a sample of 50 low surface brightness (LSB) galaxies in the $\sim$10$^{15}$ M$_{\odot}$ Perseus cluster, which were originally identified in ground-based imaging. We…
To investigate the origin of elevated globular cluster abundances observed around Ultra-Diffuse Galaxies (UDGs), we simulate globular cluster populations hosted by UDGs formed through tidal heating. Specifically, globular cluster (GC)…
In deep, ground-based imaging, about 15%-30% of object detections are expected to correspond to two or more true objects - these are called ``unrecognized blends''. We use Machine Learning algorithms to detect unrecognized blends in deep…
We present a methodological framework for studying galaxy evolution by utilizing Graph Theory and network analysis tools. We study the evolutionary processes of local ultraluminous infrared galaxies (ULIRGs) and quasars and the underlying…
We measure the half-light radii of globular clusters (GCs) in 43 galaxies from the ACS Fornax Cluster Survey (ACSFCS). We use these data to extend previous work in which the environmental dependencies of the half-light radii of GCs in early…
Globular clusters (GCs) are bright objects that span a wide range of galactocentric distances, and are thus probes of the structure of dark matter (DM) haloes. In this work, we explore whether the projected radial profiles of GCs can be…