Related papers: Detecting wide binaries using machine learning alg…
Recent studies of wide binary stars based on Gaia DR3 suggest that the relative orbital velocities of objects with separations s > 3'000 astronomical units are statistically larger than the standard Newtonian predictions. Obviously there is…
We have developed a general statistical procedure for analysis of 2D and 3D finite patterns, which is applied to the data from recently released Gaia-ESA catalogue DR2. The 2D analysis clearly confirms our former results on the presence of…
We devise a new method for the detection of double-lined binary stars in a sample of the Radial Velocity Experiment (RAVE) survey spectra. The method is both tested against extensive simulations based on synthetic spectra, and compared to…
A thorough search of the OGLE-III microlensing project has more than doubled the total sample of PNe known to have close binary central stars. These discoveries have enabled close binary induced morphological trends to be revealed for the…
We present the results of various automated classification methods, based on machine learning (ML), of objects from data releases 6 and 7 (DR6 and DR7) of the Sloan Digital Sky Survey (SDSS), primarily distinguishing stars from quasars. We…
With the advent of kernel methods, automating the task of specifying a suitable kernel has become increasingly important. In this context, the Multiple Kernel Learning (MKL) problem of finding a combination of pre-specified base kernels…
This note describes an effort to detect additional stellar sources in known transiting exoplanet (TEP) systems, which are unresolved or barely resolved in the Gaia Data Release 2 (DR2) catalogue. The presence of multiple unresolved stars in…
Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…
Classical Cepheids (CCs) and RR Lyrae stars (RRLs) are important classes of variable stars used as standard candles to estimate galactic and extragalactic distances. Their multiplicity is imperfectly known, particularly for RRLs.…
Orbital inclination is crucial in determining the mass of the binary. The astrometric excess noise contain the orbital motion information, which can be used to constrain the inclination. We aim to constrain the orbital inclination of a…
We utilize a hybrid approach that integrates the traditional cross-correlation function (CCF) and machine learning to detect spectroscopic multi-systems, specifically focusing on double-line spectroscopic binary (SB2). Based on the ninth…
We construct from Gaia eDR3 an extensive catalog of spatially resolved binary stars within $\approx$ 1 kpc of the Sun, with projected separations ranging from a few au to 1 pc. We estimate the probability that each pair is a chance…
Binarity plays a crucial role in star formation and evolution. Consequently, identifying binary stars is essential to deepen our understanding of these processes. We propose a method to investigate the observed radial velocity distribution…
We present a comprehensive kinematic analysis of the solar neighborhood (d < 50 pc) using high-precision astrometric data from the third Gaia Data Release (DR3). By leveraging the full six dimensional phase space information (positions and…
Young, intermediate-mass stars are experiencing renewed interest as targets for direct-imaging planet searches. However, these types of stars are part of multiple systems more often than not. Close stellar companions affect the formation…
The detection of gravitational waves (GWs) from binary neutron stars (BNSs) with possible telescope follow-ups opens a window to ground-breaking discoveries in the field of multi-messenger astronomy. With the improved sensitivity of current…
We have developed a new method for spectral analysis of binaries. Our method successfully identifies SB2 candidates from high-resolution Gaia-ESO spectra. Compared to the commonly used cross-correlation function analysis, it works for…
Disentangling techniques are often needed to obtain the spectra of the individual components of binary or multiple systems. A thorough analysis of the shift-and-add algorithm of Marchenko, Moffat, & Eenens (1998) reveals that in many cases…
Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance of machine learning (ML) merger detection methods. We…
Samples of reliably identified halo wide binaries are scarce. If reasonably free from selection effects and with a small degree of contamination by chance alignments, these wide binaries become a powerful dynamical tool, having provided one…