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In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest…

The information contained in the Gaia Second Data Release (DR2) allows to search for the unusual objects with the pre-selected properties, literally constructing the stars with the desired characteristics. This work describes the idea of…

Solar and Stellar Astrophysics · Physics 2018-07-13 D. V. Denisenko , I. Larin

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our…

Astrophysics · Physics 2012-08-30 C. A. L. Bailer-Jones , K. W. Smith , C. Tiede , R. Sordo , A. Vallenari

We construct from Gaia eDR3 an extensive catalog of spatially resolved binary stars within $\approx$ 1 kpc of the Sun, with projected separations ranging from a few au to 1 pc. We estimate the probability that each pair is a chance…

Solar and Stellar Astrophysics · Physics 2021-02-17 Kareem El-Badry , Hans-Walter Rix , Tyler M. Heintz

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…

Solar and Stellar Astrophysics · Physics 2015-02-27 Zdeněk Mikulášek , Miloslav Zejda , Theodor Pribulla , Martin Vaňko , Shen-Bang Qian , Li-Ying Zhu

Double-close-binary quadruples (2+2 systems) are hierarchical systems of four stars where two short-period binary systems move around their common center of mass on a wider orbit. Using Gaia Early Data Release 3, we search for comoving…

Solar and Stellar Astrophysics · Physics 2022-03-02 Gavin B. Fezenko , Hsiang-Chih Hwang , Nadia L. Zakamska

Spectroscopic Eclipsing Binaries (SEBs) are fundamental benchmarks in stellar astrophysics and today are observed in breathtaking detail by missions like TESS, Kepler, and APOGEE. We develop a methodology for simultaneous analysis of high…

Eccentricity of wide binaries is difficult to measure due to their long orbital periods. With Gaia's high-precision astrometric measurements, eccentricity of a wide binary can be constrained by the angle between the separation vector and…

Solar and Stellar Astrophysics · Physics 2022-03-30 Hsiang-Chih Hwang , Yuan-Sen Ting , Nadia L. Zakamska

In this study we investigate the calibration of surface brightness--color (SBC) relations based solely on eclipsing binary stars. We selected a sample of 35 detached eclipsing binaries with trigonometric parallaxes from Gaia DR1 or…

This note describes an effort to detect additional stellar sources in known transiting exoplanet (TEP) systems, which are unresolved or barely resolved in the Gaia Data Release 2 (DR2) catalogue. The presence of multiple unresolved stars in…

Earth and Planetary Astrophysics · Physics 2018-05-01 Daniel Evans

We present a catalog of 99,203 wide binary systems, initially identified as common proper motion (CPM) pairs from a subset of ~5.2 million stars with proper motions $\mu > 40$ mas/year, selected from Gaia data release 2 (DR2) and the…

Solar and Stellar Astrophysics · Physics 2020-04-15 Zachary Hartman , Sébastien Lépine

There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a…

Instrumentation and Methods for Astrophysics · Physics 2015-08-20 Edward J. Kim , Robert J. Brunner , Matias Carrasco Kind

Gaia is an astrometric space experiment that is measuring positions, proper motions as well as parallaxes for a huge number of stars. It operates a medium-dispersion spectrometer, the RVS, that provides spectra and thus radial velocity…

Solar and Stellar Astrophysics · Physics 2025-01-24 E. Gosset , Y. Damerdji , T. Morel , L. Delchambre , J. -L. Halbwachs , G. Sadowski , D. Pourbaix , A. Sozzetti , P. Panuzzo , F. Arenou

Context: The space telescope Gaia is dedicated mainly to performing high-precision astrometry, but also spectroscopy and epoch photometry which can be used to study various types of photometric variability. One such variability type is…

Hot sub-luminous stars represent a population of stripped and evolved red giants that is located on the extreme horizontal branch. Since they exhibit a wide range of variability due to pulsations or binary interactions, it is crucial to…

Solar and Stellar Astrophysics · Physics 2025-01-29 P. Ranaivomanana , M. Uzundag , C. Johnston , P. J. Groot , T. Kupfer , C. Aerts

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…

Solar and Stellar Astrophysics · Physics 2025-02-18 Stephen Overall , John Southworth

The classification of time series from photometric large scale surveys into variability types and the description of their properties is difficult for various reasons including but not limited to the irregular sampling, the usually few…

Instrumentation and Methods for Astrophysics · Physics 2010-12-13 L. Eyer , A. Jan , P. Dubath , K. Nienartowicz , J. Blomme , J. Debosscher , J. De Ridder , M. Lopez , L. Sarro

The Super Wide Angle Search for Planets (SuperWASP) is a whole-sky high-cadence optical survey which has searched for exoplanetary transit signatures since 2004. Its archive contains long-term light curves for ~30 million 8-15 V magnitude…

Solar and Stellar Astrophysics · Physics 2015-04-28 M. E. Lohr

Classification of datasets into two or more distinct classes is an important machine learning task. Many methods are able to classify binary classification tasks with a very high accuracy on test data, but cannot provide any easily…

Machine Learning · Computer Science 2020-08-26 Yashesh Dhebar , Sparsh Gupta , Kalyanmoy Deb

Classical machine learning algorithms often face scalability bottlenecks when they are applied to large-scale data. Such algorithms were designed to work with small data that is assumed to fit in the memory of one machine. In this report,…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-14 Tarek Elgamal , Mohamed Hefeeda
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