Related papers: Automatic classification of eclipsing binaries lig…
Results of an archival survey are presented using B-band imaging of the eastern spiral arm of M31. Focusing on the eclipsing binary star population, a matched-filter technique has been used to identify 280 binary systems. Of these, 127…
We have discovered a class of eccentric binary systems within the Kepler data archive that have dynamic tidal distortions and tidally-induced pulsations. Each has a uniquely shaped light curve that is characterized by periodic brightening…
This paper presents an automatic method for data classification in nuclear physics experiments based on evolutionary computing and vector quantization. The major novelties of our approach are the fully automatic mechanism and the use of…
Binary classification is one of the most common problem in machine learning. It consists in predicting whether a given element belongs to a particular class. In this paper, a new algorithm for binary classification is proposed using a…
Over 2500 eclipsing binaries were identified and characterized from the ultra-precise photometric data provided by the Kepler space telescope. Kepler is now beginning its second mission, K2, which is proving to again provide ultra-precise…
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…
We present an automated classification of stars exhibiting periodic, non-periodic and irregular light variations. The Hipparcos catalogue of unsolved variables is employed to complement the training set of periodic variables of Dubath et…
Many moons have been detected around planets in our Solar System, but none has been detected unambiguously around any of the confirmed extrasolar planets. We test the feasibility of a supervised convolutional neural network to classify…
Thirty-three eclipsing binaries were selected for an analysis from a huge database of observations made by the INTEGRAL/OMC camera. The photometric data were processed and analyzed, resulting in a first light-curve study of these neglected…
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…
CBS is a new program for binary system light curve analysis, it generates synthetic light curves for a binary system, accounting for eclipses, tidal distortion, limb darkening, gravity darkening and reflection; it is also possible to…
Common variable star classifiers are built only with the goal of producing the correct class labels, leaving much of the multi-task capability of deep neural networks unexplored. We present a periodic light curve classifier that combines a…
A comparative analysis of the special shapes (patterns, profiles) of the eclipses applied for the phenomenological modeling of the light curves of eclipsing binary stars is conducted. Families of functions are considered, generalizing local…
Eclipsing Binaries (EBs) are known to be the source of most accurate stellar parameters, which are important for testing theories of stellar evolution. With improved quality and quantity of observations using space telescopes like {\it…
We present the first light curve solutions of the four binary systems observed and catalogued by the All Sky Automated Survey program. The light curves are analysed by using PHOEBE software, which is based on the Wilson-Devinney method. The…
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…
We demonstrate the eclipsing binary detection performance of the Gaia variability analysis and processing pipeline using Hipparcos data. The automated pipeline classifies 1,067 (0.9%) of the 118,204 Hipparcos sources as eclipsing binary…
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…
Modern astronomical surveys produce millions of light curves of variable sources. These massive data sets challenge the community to create automatic light-curve processing methods for detection, classification, and characterisation of…
We present a catalog of precise eclipse times and analysis of third body signals among 1279 close binaries in the latest Kepler Eclipsing Binary Catalog. For these short period binaries, Kepler's 30 minute exposure time causes significant…