相关论文: Identifying Ring Galaxies in DESI Legacy Imaging S…

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next five years. The aim of this work is to validate the quasar selection by studying the impact of imaging…

We investigate how well the redshift distributions of galaxies sorted into photometric redshift bins can be determined from the galaxy angular two-point correlation functions. We find that the uncertainty in the reconstructed redshift…

Classification of galactic morphologies is a crucial task in galactic astronomy, and identifying fine structures of galaxies (e.g., spiral arms, bars, and clumps) is an essential ingredient in such a classification task. However, seeing…

Using deep machine learning we show that the internal velocities of galaxies can be retrieved from optical images trained using 4596 systems observed with the SDSS-MaNGA survey. Using only $i$-band images we show that the velocity…

We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({\theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by…

In this paper we present photometric redshift (photo-$z$) estimates for the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, currently the most sensitive optical survey covering the majority of the extra-galactic sky. Our…

To understand the processes that build up galaxies we investigate the stellar structure and gas kinematics of spiral and irregular galaxies out to redshift 1. We target 92 galaxies in four cluster (z = 0.3 & 0.5) fields to study the…

The rapid advancements in computer graphics have greatly enhanced the quality of computer-generated images (CGI), making them increasingly indistinguishable from authentic images captured by digital cameras (ADI). This indistinguishability…

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…

Galaxy morphology encodes key information about formation and evolution. Large imaging surveys require automated, reproducible methods beyond visual inspection. Non--parametric indices provide an useful framework, but their performance must…

The distinction between stars and galaxies is a fundamental problem in the field of celestial classification. This issue has become challenging for these ongoing and upcoming digital surveys, which will produce terabytes and even petabytes…

Quantitative characterization of galaxy morphology is vital in enabling comparison of observations to predictions from galaxy formation theory. However, without significant overlap between the observational footprints of deep and shallow…

Current methods for medical image segmentation primarily focus on extracting contextual feature information from the perspective of the whole image. While these methods have shown effective performance, none of them take into account the…

Ring galaxies are an uncommon class of galaxies whose morphology is closely related to dynamical processes that govern galaxy evolution. Some ring galaxies, known as "collisional ring galaxies", are thought to form as a consequence of…

Dust-lane spheroidal galaxies (DLSGs) are unique astrophysical systems that exhibit the morphology of early-type galaxies (ETGs) but are distinguished by prominent dust lanes. Recent studies propose that they form through minor mergers…

The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS, were cross-matched by Bilicki et al. (2016) (B16) to construct a novel photometric redshift catalogue on 70% of the sky. Galaxies were therein separated from…

We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…

The DEEP2 project will obtain redshifts for ~60,000 galaxies between z~0.7-1.5 in a comoving volume of 7 10^6 Mpc/h^3 for an LCDM universe. The survey will map four separate 2 by 0.5 degree strips of the sky. To study the expected…

We present a catalog and imaging atlas of classical (collisional) RING galaxies distilled from the Arp-Madore Atlas of Southern Peculiar Galaxies and Associations and supplemented with other known RING galaxies from the published…

Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…