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We introduce an online outlier detection algorithm to detect outliers in a sequentially observed data stream. For this purpose, we use a two-stage filtering and hedging approach. In the first stage, we construct a multi-modal probability…

We investigate the rate of false planetary transit detection due to blending with eclipsing binaries. Our approach is purely empirical and is based on the analysis of the artificially blended light curves of the eclipsing binary stars in…

We describe a new neural-net based light curve classifier and provide it with documentation as a ready-to-use tool for the community. While optimized for identification and classification of eclipsing binary stars, the classifier is general…

We present a new few-parameter phenomenological model of light curves of eclipsing binaries and stars with transiting planets that is able to fit the observed light curves with the accuracy better than 1\% of their amplitudes. The model can…

The discovery of habitable exoplanets has long been a heated topic in astronomy. Traditional methods for exoplanet identification include the wobble method, direct imaging, gravitational microlensing, etc., which not only require a…

The detection of exoplanets through direct imaging has produced numerous new positive identifications in recent years. The technique is biased towards planets at wide separations due to the difficulty in removing the stellar signature at…

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…

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…

We present a detailed V-band photometric light curve modeling of 30 eclipsing binaries using the data from Pietrukowicz et al. (2009) collected with the European Southern Observatory Very Large Telescope (ESO VLT) of diameter 8-m. The light…

Eclipsing binary systems with a Delta (${\delta}$) Scuti component serve a vital role in deriving precise fundamental stellar parameters and testing stellar evolution models. This study mainly focuses on the Kepler target KIC 8569819, a…

We investigate the possibility of exoplanet detection orbiting source stars in microlensing events through WFIRST observations. We perform a Monto Carlo simulation on the detection rate of exoplanets via microlensing, assuming that each…

The new generation of observatories and instruments (VLT/ERIS, JWST, ELT) motivate the development of robust methods to detect and characterise faint and close-in exoplanets. Molecular mapping and cross-correlation for spectroscopy use…

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…

We introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. We aim to exploit…

The next generation of telescopes will yield a substantial increase in the availability of high-resolution spectroscopic data for thousands of exoplanets. The sheer volume of data and number of planets to be analyzed greatly motivate the…

Anomaly detection aims at identifying data points that show systematic deviations from the majority of data in an unlabeled dataset. A common assumption is that clean training data (free of anomalies) is available, which is often violated…

We present a method for detection of weak continuous signals from sources in binary systems via the incoherent combination of many "short" coherently-analyzed segments. The main focus of the work is on the construction of a metric on the…

In the present era of large scale surveys, big data presents new challenges to the discovery process for anomalous data. Such data can be indicative of systematic errors, extreme (or rare) forms of known phenomena, or most interestingly,…

This study presents a multi-task machine learning framework for simultaneous morphology classification and physical parameter estimation of eclipsing binaries using photometric light curves. We train Random Forest and XGBoost ensemble…

Many short-period binary stars have distant orbiting companions that have played a role in driving the binary components into close separation. Indirect detection of a tertiary star is possible by measuring apparent changes in eclipse times…