Related papers: Image Classification Algorithm for Determining the…
Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. While there is a vast source of candidate systems in the light curve databases of survey missions such as Kepler and TESS, published…
We derive the absolute physical and orbital parameters for a sample of 18 detached eclipsing binaries from the \emph{All Sky Automated Survey} (ASAS) database based on the available photometry and our own radial velocity measurements. The…
Unsupervised learning algorithms are beginning to achieve accuracies comparable to their supervised counterparts on benchmark computer vision tasks, but their utility for practical applications has not yet been demonstrated. In this work,…
CCD light curves of the Algol type eclipsing binaries DP Cep, AL Gem, FG Gem, UU Leo, CF Tau and AW Vul were analysed using the Wilson-Deninney code and new geometric and absolute parameters were derived. Due to cyclic apparent orbital…
In this paper we discuss an application of machine learning based methods to the identification of candidate AGN from optical survey data and to the automatic classification of AGNs in broad classes. We applied four different machine…
The All-Sky Automated Survey for Supernovae (ASAS-SN) provides long baseline (${\sim}4$ yrs) light curves for sources brighter than V$\lesssim17$ mag across the whole sky. The Transiting Exoplanet Survey Satellite (TESS) has started to…
Binaries play key roles in determining stellar parameters and exploring stellar evolution models. We build a catalog of 88 eclipsing binaries with spectroscopic information, taking advantage of observations from both the Large Sky Area…
We present a machine learning package for the classification of periodic variable stars. Our package is intended to be general: it can classify any single band optical light curve comprising at least a few tens of observations covering…
In this work, six convolutional neural networks (CNNs) have been trained based on %different feature images and arrays from the database including 15,638 superflare candidates on solar-type stars, which are collected from the three-years…
In this work, we propose a novel method to classify close binary stars, derived from the dynamical structure inherent in their light curves. We apply the technique to light curves of binaries from the revised Kepler Eclipsing binary…
Abridged. Eclipsing spectroscopic double-lined binaries are the prime source of precise and accurate measurements of masses and radii of stars. These measurements provide a stringent test of models of stellar evolution that are persistently…
Eclipsing binaries (EBs) provide critical laboratories for empirically testing predictions of theoretical models of stellar structure and evolution. Pre-main-sequence (PMS) EBs are particularly valuable, both due to their rarity and the…
We present absolute physical and orbital parameters for three double-lined detached eclipsing binary systems from the All Sky Automated Survey (ASAS) catalogue with subgiant and giant components. These parameters were derived from archival…
This work is focused on the morphological classification of galaxies following the Hubble sequence in which the different classes are arranged in a hierarchy. The proposed method, BCNN, is composed of two main modules. First, a…
Twin binaries were identified among the eclipsing binaries with $\delta$>--30$^\circ$ listed in the ASAS catalog. In addition to the known twin binaries in the literature, 68 new systems have been identified, photometric and spectroscopic…
Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…
This study broadens our comprehensive investigation of total-eclipse W Ursae Majoris-type contact binaries by analyzing eight additional systems, continuing our previous research. Multiband $BVR_cI_c$ photometric data were obtained at an…
In the era of large all-sky surveys, there will be a need for rapid, automatic classifications of newly discovered transient objects. Our focus here is the classification of supernovae (SNe). We consider random forest machine learning…
We describe an automated method for assigning the most likely physical parameters to the components of an eclipsing binary (EB), using only its photometric light curve and combined color. In traditional methods (e.g. WD and EBOP) one…
The observed light curves of most eclipsing binaries and stars with transiting planets can be well described and interpreted by current advanced physical models which also allow for the determination of many physical parameters of eclipsing…