Related papers: An adaptive algorithm for detecting double stars i…
With nearly two billion stars observed and their corresponding astrometric parameters evaluated in the recent Gaia mission, the number of astrometric binary candidates have risen significantly. Due to the surplus of astrometric data, the…
This paper reviews methods which can be used to detect binaries involving low- and intermediate-mass stars, with special emphasis on evolved systems. Besides the traditional methods involving radial-velocity or photometric monitoring, the…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
We focus on the automated classification of eclipsing binary stars using deep learning methods to handle the vast data generated by large-scale photometric sky surveys. These surveys produce extensive datasets that are impractical for…
We present a machine learning (ML) framework for the detection of wide binary star systems using Gaia DR3 data. By training supervised ML models on established wide binary catalogues, we efficiently classify wide binaries and employ…
Detecting binary stars in photometric time series is traditionally done by measuring eclipses. This requires the orbital plane to be aligned with the observer. A new method without that requirement uses stellar oscillations to measure…
I present a brief summary of three different types of binary star - astrometric, spectroscopic and eclipsing - and tabulate the properties of these systems that can be determined directly from observations. Eclipsing binary stars are the…
Rapidly growing catalogs of compact binary mergers from advanced gravitational-wave detectors allow us to explore the astrophysics of massive stellar binaries. Merger observations can constrain the uncertain parameters that describe the…
Binarity is often invoked to explain peculiarities that can not be explained by the standard theory of stellar evolution. Detecting orbital motion via the Doppler effect is the best method to test binarity when direct imaging is not…
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…
One of important aims of astronomical data mining is to systematically search for specific rare objects in a massive spectral dataset, given a small fraction of identified samples with the same type. Most existing methods are mainly based…
In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a…
The direct detection of binary systems in wide-field surveys is limited by the size of the stars' point-spread-functions (PSFs). A search for elongated objects can find closer companions, but is limited by the precision to which the PSF…
A technique is described for the detection and measurement of close binary systems whose images are unresolved. The method is based on analysis of the moment of inertia tensor of the image, from which the product of the binary flux ratio…
We present our models of the effect of binaries on high-resolution spectroscopic surveys. We want to determine how many binary stars will be observed, whether unresolved binaries will contaminate measurements of chemical abundances, and how…
Astronomical polarimetry is a powerful technique that can provide physical information sometimes difficult or impossible to obtain by any other type of observation. Almost every class of binary star can benefit from polarimetric…
We demonstrate that microlensing can be used for detecting planets in binary stellar systems. This is possible because in the geometry of planetary binary systems where the planet orbits one of the binary component and the other binary star…
In a previous article, we obtained the first-ever list of astrometric binary asteroid candidates. Some of these candidates have now been confirmed. In that previous work, however, the details of the statistical methods were not provided.…
Building on previous Bayesian approaches, we introduce a novel formulation of probabilistic cross-identification, where detections are directly associated to (hypothesized) astronomical objects in a globally optimal way. We show that this…
The results of an adaptive optics survey of exoplanet host stars for stellar companions is presented. We used the AEOS Telescope and its adaptive optics system to collect deep images of the stars in $I$-band. Sixty-two exoplanet host stars…