Related papers: Detecting wide binaries using machine learning alg…
We use a self-consistent Monte Carlo treatment of stellar dynamics to investigate black hole binaries that are dynamically ejected from globular clusters to determine if they will be gravitational wave sources. We find that many of the…
RR Lyrae stars (RRLs) are classical tracers of old stellar populations, yet growing evidence suggests the presence of a metal-rich ([Fe/H]>-0.5), intermediate-age (2-7 Gyr) sub-population in the Milky Way disc. Binary evolution,…
We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…
Machine learning (ML) and deep learning (DL) models have been employed to significantly improve analyses of medical imagery, with these approaches used to enhance the accuracy of prediction and classification. Model predictions and…
The aim of this paper is, making use of the Gaia DR3 catalogue and Virtual Observatory tools, to confirm and characterize 428 binary and multiple stellar systems classified as neglected (only one observation) in the Washington Double Star…
Open clusters are groups of stars that form at the same time, making them an ideal laboratory to test theories of star formation, stellar evolution, and dynamics in the Milky Way disk. However, the utility of an open cluster can be limited…
Rapidly spinning neutron stars are promising sources of persistent, continuous gravitational waves. Detecting such a signal would allow probing of the physical properties of matter under extreme conditions. A significant fraction of the…
Black hole-main sequence star (BH-MS) binaries are one of the targets of the future data releases of the astrometric satellite {\it Gaia}. They are supposed to be formed in two main sites: a galactic field and star clusters. However,…
The frequency of planets in binaries is an important issue in the field of extrasolar planet studies because of its relevance in the estimation of the global planet population of our galaxy and the clues it can give to our understanding of…
We present a wavelet-based algorithm to identify dwarf galaxies in the Milky Way in ${\it Gaia}$ DR2 data. Our algorithm detects overdensities in 4D position--proper motion space, making it the first search to explicitly use velocity…
The publication of the \emph{Gaia} catalogue and improvements in methods to determine memberships and fundamental parameters of open clusters has led to major advances in recent years. However, important parameters such as the masses of…
Identifying sources exhibiting ellipsoidal variability in large photometric surveys is becoming a promising method to search for candidate detached black holes in binaries. This technique aims to exploit the orbital-phase dependent…
Metal absorption line systems in distant quasar spectra probe of the history of gas content in the universe. The MgII $\lambda \lambda$ 2796, 2803 doublet is one of the most important absorption lines since it is a proxy of the star…
Context. Gaia Early Data Release 3 (EDR3), published in December 2020, features improved photometry and astrometry over that published in the previous DR2 file, and includes a substantially larger number of sources, of the order of 2,000…
We describe a homogeneous catalog compilation of common proper motion stars based on Gaia DR2. A preliminary list of all pairs of stars within the radius of 100 pc around the Sun with a separation less than a parsec was compiled. Also, a…
Eccentricity of wide binaries is difficult to measure due to their long orbital periods. With Gaia's high-precision astrometric measurements, eccentricity of a wide binary can be constrained by the angle between the separation vector and…
We explore the detection limits of the phase modulation (PM) method of finding binary systems among multi-periodic pulsating stars. The method is an attractive way of finding non-transiting planets in the habitable zones of intermediate…
Machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We apply the machine learning classification to 85,613,922 objects in the…
NGC 5139 ($\omega$ Cen), is the closest candidate of a Nuclear Star Cluster that has been stripped of its host galaxy in the Milky Way. Despite extensive studies through the last decades, many open questions about the cluster remain,…
Data-driven stellar classification has a long and important history in astronomy, dating as far back as Annie Jump Cannon's "by eye" classifications of stars into spectral types still used today. In recent years, data-driven spectroscopy…