Related papers: Machine learning technique for morphological class…
Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated halos. In this work, we propose a widely applicable method for…
Ground-based optical surveys such as PanSTARRS, DES, and LSST, will produce large catalogs to limiting magnitudes of r > 24. Star-galaxy separation poses a major challenge to such surveys because galaxies---even very compact…
We present a method for automatic detection and classification of galaxies which includes a novel data-augmentation procedure to make trained models more robust against the data taken from different instruments and contrast-stretching…
We present a morphological analysis of distant field galaxies using the deep ACS images from the public parallel NICMOS observations of the Hubble Ultra Deep Field obtained in the F435W (B), F606W (V), F775W (i) and F850LP (z) filters. We…
Clusters of galaxies in most previous catalogs have redshifts z<0.3. Using the photometric redshifts of galaxies from the Sloan Digital Sky Survey Data Release 6 (SDSS DR6), we identify 39,668 clusters in the redshift range 0.05< z <0.6…
We perform a galaxy-galaxy lensing study by correlating the shapes of $\sim$2.7 $\times$ 10$^5$ galaxies selected from the VLA FIRST radio survey with the positions of $\sim$38.5 million SDSS galaxies, $\sim$132000 BCGs and $\sim$78000 SDSS…
Aims: This study aims to trace the chronological evolution of galaxy spectra over cosmic time. Focusing on the VIPERS dataset, we seek to understand the diverse population of galaxies within narrow redshift bins, comparing our findings with…
Using the TNG50 cosmological simulation and observations from the Kilo-Degree Survey (KiDS), we investigate the connection between galaxy mergers and optical morphology in the local Universe over a wide range of galaxy stellar masses…
We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 million morphological classifications of 304,122 galaxies drawn from the Sloan Digital Sky Survey. Morphology is a powerful probe for…
Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…
The aim of this study is to determine the fractions of different spiral galaxy types, especially bulgeless disks, from a complete and homogeneous sample of 15127 edge-on disk galaxies extracted from the sixth data release from the Sloan…
The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for…
The Sloan Digital Sky Survey (SDSS) was foundational to the study of galaxy evolution, having revealed the bimodality of galaxies and the relationship between their structure and star-forming activity. However, ground-based optical surveys…
The combination of galaxy-galaxy weak lensing and galaxy clustering is a powerful probe of the cosmological model, and exploration of how to best model and extract this information from the signals is essential. We present the measurement…
We use machine learning to classify galaxies according to their HI content, based on both their optical photometry and environmental properties. The data used for our analyses are the outputs in the range $z = 0-1$ from MUFASA cosmological…
Edge-on galaxies have many important applications in galactic astrophysics, but they can be difficult to identify in vast amounts of astronomical data. To facilitate the search for them, we have developed a deep learning algorithm designed…
We applied computational tools for automatic detection of peculiar galaxy pairs. We first detected in SDSS DR7 ~400,000 galaxy images with i magnitude <18 that had more than one point spread function, and then applied a machine learning…
Several UV and near-infrared color selection methods have identified galaxies at z = 1-3. Since each method suffers from selection biases, we have applied three leading techniques (Lyman break, BX/BM, and BzK selection) simultaneously in…
We examine morphology-separated color-mass diagrams to study the quenching of star formation in $\sim 100,000$ ($z\sim0$) Sloan Digital Sky Survey (SDSS) and $\sim 20,000$ ($z\sim1$) Cosmic Assembly Near-Infrared Deep Extragalactic Legacy…
Galaxy morphology is inextricably linked to environment. The morphology-density relation quantifies this relationship. However, optical morphology is only loosely related to the kinematic structure of galaxies, and about two thirds of…