Related papers: Eclipsing binary classification with machine learn…
I present an overview of the techniques used for detecting and following up binaries in nearby galaxies and present the current census of extragalactic binaries, with a focus on eclipsing systems. The motivation for looking in other…
Large repositories of high precision light curve data, such as the Kepler data set, provide the opportunity to identify astrophysically important eclipsing binary (EB) systems in large quantities. However, the rate of classical "by eye"…
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…
Next-generation synoptic photometric surveys will yield unprecedented (for the astronomical community) volumes of data and the processes of discovery and rare-object identification are, by necessity, becoming more autonomous. Such…
Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. Within the light curve databases of survey missions such as Kepler and TESS are a wealth of new systems awaiting characterisation. We aim to…
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…
Very high quality light curves are now available for thousands of detached eclipsing binary stars and transiting exoplanet systems as a result of surveys for transiting exoplanets and other large-scale photometric surveys. I have developed…
A significant degree of misclassification of variable stars through the application of machine learning methods to survey data motivates a search for more reliable and accurate machine learning procedures, especially in light of the very…
Exoplanet transit and Doppler surveys discover many binary stars during their operation that can be used to conduct a variety of ancillary science. Specifically, eclipsing binary stars can be used to study the stellar mass-radius…
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…
Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure…
Eclipsing binary stars have long served as benchmark systems to measure fundamental stellar properties. In the past few decades, asteroseismology - the study of stellar pulsations - has emerged as a new powerful tool to study the structure…
The Kepler Mission has provided unprecedented, nearly continuous photometric data of $\sim$200,000 objects in the $\sim$105 deg$^{2}$ field of view from the beginning of science operations in May of 2009 until the loss of the second…
We describe an automated method for assigning the most probable physical parameters to the components of an eclipsing binary, using only its photometric light curve and combined colors. With traditional methods, one attempts to optimize a…
In this paper, we determine the detectability of eclipsing binary star companions from eclipse timing variations using the Kepler mission dataset. Extensive and precise stellar time-series photometry from space-based missions enable…
We report on the properties of eclipsing binaries from the Kepler mission with a newly developed photometric modeling code, which uses the light curve, spectral energy distribution of each binary, and stellar evolution models to infer…
Pulsations and binarity are both common features of massive stars. The study of pulsating massive stars in eclipsing binary systems hold great potential for constraining stellar structure and evolution theory. However, prior to the all-sky…
Recent developments in computational power and machine learning techniques motivate their use in many different astrophysical research areas. Consequently, many machine learning models have been trained to classify exoplanet transit signals…
The expected distributions of eclipse-depth versus period for eclipsing binaries of different luminosities are derived from large-scale population synthesis experiments. Using the rapid Hurley et al. BSE binary evolution code, we have…
Research into light curves from stars (temporal variation of brightness) has completely changed how exoplanets are discovered or characterised. This study including star light curves from the Kepler dataset as a way to discover exoplanets…