Related papers: An adaptive algorithm for detecting double stars i…
The combination of HIPPARCOS measurements with suitable ground-based astrometric data improves significantly the accuracy of the proper motions of bright stars. The comparison of both types of data allows us also to identify and to…
The comparison of quasi-instantaneously measured HIPPARCOS proper motions with long-term averaged proper motions, derived from ground-based data, allows the identification of many stellar objects as Delta_mu binaries (Wielen et al., 1999,…
We present the results of our study of astrometric stability of 200-in Hale (Mt. Palomar) and 10-m Keck II (Mauna Kea) telescopes, both with Adaptive Optics (AO) facilities. A group of nearby visual binaries and multiples was observed in…
Using an extended set of multi-epoch high-resolution high signal-to-noise ratio optical spectra, we readdress the multiplicity properties of the O-type stars in IC 2944 and in the Cen OB2 association. We present new evidence of binarity for…
Modern astronomy relies on massive databases collected by robotic telescopes and digital sky surveys, acquiring data in a much faster pace than what manual analysis can support. Among other data, these sky surveys collect information about…
Catalogs of stellar-mass compact binary systems detected by ground-based gravitational-wave instruments (such as Advanced LIGO and Advanced Virgo) will offer insights into the demographics of progenitor systems and the physics guiding…
We describe a method for determining the limb polarization and limb darkening of stars in eclipsing binary systems, by inverting photometric and polarimetric light curves. Because of the ill-conditioning of the problem, we use the…
Multi-epoch radial velocity measurements of stars can be used to identify stellar, sub-stellar, and planetary-mass companions. Even a small number of observation epochs can be informative about companions, though there can be multiple…
We propose a new pattern-matching algorithm for matching CCD images to a stellar catalogue based statistical method in this paper. The method of constructing star pairs can greatly reduce the computational complexity compared with the…
We study the detectability of gravitational-wave signals from sub-solar mass binary neutron star systems by the current generation of ground-based gravitational-wave detectors. We find that finite size effects from large tidal…
We estimate the observed distribution of chirp masses of compact object binaries for the gravitational wave detectors. The stellar binary evolution is modeled using the {\em StarTrack} population synthesis code. The distribution of the…
This work brings together some of the most common machine learning (ML) algorithms, and the objective is to make a comparison at the level of obtained results from a set of unbalanced data. This dataset is composed of almost 17 thousand…
We present a robust and fast algorithm for performing astrometry and source cross-identification on two dimensional point lists, such as between a catalogue and an astronomical image, or between two images. The method is based on minimal…
We present results of using a basic binary classification neural network model to identify likely catastrophic outlier photometric redshift estimates of individual galaxies, based only on the galaxies' measured photometric band magnitude…
We discuss a possible method for detection of dark companions of galactic objects of stellar mass. Such binary systems are likely to occur in the galactic disk and possibly also in the halo. The high incidence of binary and…
We present an image classification algorithm using deep learning convolutional neural network architecture, which classifies the morphologies of eclipsing binary systems based on their light curves. The algorithm trains the machine with…
Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars…
We present an application of Deep Learning for the image recognition of asteroid trails in single-exposure photos taken by the Hubble Space Telescope. Using algorithms based on multi-layered deep Convolutional Neural Networks, we report…
We use an updated method for the detection of double-lined spectroscopic binaries (SB2) using $v \sin{i}$ values from spectral fits. The method is applied to all spectra from LAMOST-MRS. Using this method, we detect 12426 SB2 candidates,…
Orbital solutions for binary or multiple stellar systems that combine astrometry (e.g., position angles and angular separations) with spectroscopy (radial velocities) have important advantages over astrometric-only or spectroscopic-only…