Related papers: Identifying hot subdwarf stars from photometric da…

Wide-field photometric surveys enable searches of rare yet interesting objects, such as strongly lensed quasars or quasars with a bright host galaxy. Past searches for lensed quasars based on their optical and near infrared properties have…

Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…

High-contrast adaptive optics imaging is a powerful technique to probe the architectures of planetary systems from the outside-in and survey the atmospheres of self-luminous giant planets. Direct imaging has rapidly matured over the past…

The fraction of binary stars (fb) is one of most valuable tool to probe the star formation and evolution of multiple systems in the Galaxy. We focus on the relationship between fb and stellar metallicity ([Fe/H]) by employing the…

We used data from the HST UV Legacy Survey of Galactic Globular Clusters to select the Blue Straggler Star (BSS) population in four intermediate/high density systems (namely NGC 2808, NGC 6388, NGC 6541 and NGC 7078) through a "UV-guided…

Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian…

We report broadband UBV and/or BVRI CCD photometry for a total of 1857 stars in the thick-disk and halo populations of the Galaxy. The majority of our targets were selected as candidate field horizontal-branch or other A-type stars (FHB/A,…

Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra obtained by the LAMOST survey. The CNN is trained on a dataset…

Stellar infrared excesses can indicate various phenomena of interest, from protoplanetary disks to debris disks, or (more speculatively) techno-signatures along the lines of Dyson spheres. In this paper, we conduct a large search for such…

We present an automated statistical method that uses medium-resolution spectroscopic observations of a set of stars to select those that show evidence of possessing significant amounts of neutron-capture elements. Our tool was tested…

The results of a search for cool subdwarfs are presented. Kinematic (U, V, and W) and stellar parameters (Teff, log g, [Fe/H], and V_t) are derived for 134 candidate subdwarfs based on high resolution spectra. The observed stars span 4200K…

Context: Star formation takes place in giant molecular clouds, resulting in mass-segregated young stellar clusters composed of Sun-like stars, brown dwarves, and massive O-type(50-100\msun) stars. Aims: To identify candidate hub-filament…

Parallaxes, proper motions, and optical photometry are presented for 51 systems made up 37 cool subdwarf and 14 additional high proper motion systems. Thirty-seven systems have parallaxes reported for the first time, 15 of which have proper…

Having a need to perform differential photometry for tens of thousands stars in a several square degrees field, we developed Astrokit program. The software corrects the star brightness variations caused by variations of atmospheric…

The classification of galaxies as spirals or ellipticals is a crucial task in understanding their formation and evolution. With the arrival of large-scale astronomical surveys, such as the Sloan Digital Sky Survey (SDSS), astronomers now…

Photometric data from the Xuyi Schmidt Telescope Photometric Survey of the Galactic Anticentre (XSTPS-GAC) and the Sloan Digital Sky Survey (SDSS) are used to derive the global structure parameters of the smooth components of the Milky Way.…

We present a machine learning method to assign stellar parameters (temperature, surface gravity, metallicity) to the photometric data of large photometric surveys such as SDSS and SKYMAPPER. The method makes use of our previous effort in…

We use star counts from 13 deep HST fields imaged with the {\it Wide Field Camera - 2} in order to constrain the amount of dark matter in the Galaxy that can be in the form of low-mass main sequence stars or white-dwarfs. Based on the…

We present a new approach for the identification of ultra-high energy cosmic rays from sources using dynamic graph convolutional neural networks. These networks are designed to handle sparsely arranged objects and to exploit their short-…

Machine learning, algorithms to extract empirical knowledge from data, can be used to classify data, which is one of the most common tasks in observational astronomy. In this paper, we focus on Bayesian data classification algorithms using…