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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…
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…
Modeling binary star populations is critical to linking the theories of star formation and stellar evolution with observations. In order to test these theories, we need accurate models of observable binary populations. The Kepler Eclipsing…
Detached eclipsing binaries (DEBs) enable direct inference of stellar and orbital properties across diverse stellar populations. However, inference typically requires computationally intensive forward modeling and radial velocity (RV)…
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…
Stellar light curves contain valuable information about oscillations and granulation, offering insights into stars' internal structures and evolutionary states. Traditional asteroseismic techniques, primarily focused on power spectral…
Based on the eclipsing binary catalog provided by \cite{2022ApJS..258...16P}, 84 totally eclipsing contact binaries with stable light curves were selected. The TESS light curves of these 84 targets were studied using the Physics Of…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
We used a convolutional neural network to infer stellar rotation periods from a set of synthetic light curves simulated with realistic spot evolution patterns. We convolved these simulated light curves with real TESS light curves containing…
With the release of a large amount of astronomical data, an increasing number of close-in hot Jupiters have been discovered. Calculating their evolutionary curves using star-planet interaction models presents a challenge. To expedite the…
We exploit high quality photometry from the EVEREST pipeline to evaluate false-positive exoplanet candidates from the K2 mission. We compare the practical capabilities of EVEREST's pixel-level decorrelation scheme to the data analysis…
The Transiting Exoplanet Survey Satellite (TESS) will observe $\sim$150~million stars brighter than $T_{\rm mag} \approx 16$, with photometric precision from 60~ppm to 3~percent, enabling an array of exoplanet and stellar astrophysics…
Vast amounts of astronomical photometric data are generated from various projects, requiring significant effort to identify variable stars and other object classes. In light of this, a general, widely applicable classification framework…
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 introduce a special class of functions for mathematical modeling of periodic signals of special shape with irregularly spaced arguments. This method was developed for determination of phenomenological characteristics of the light curves,…
Totally eclipsing contact binaries provide a unique opportunity to accurately determine mass ratios through photometric methods alone, eliminating the need for spectroscopic data. Studying low mass ratio (LMR) contact binaries is crucial…
In the era of exploding survey volumes, traditional methods of spectroscopic analysis are being pushed to their limits. In response, we develop deep-REMAP, a novel deep learning framework that utilizes a regularized, multi-task approach to…
Eclipsing binaries (EBs) play an important astrophysical role in studying stellar properties and evolution. By analyzing photometric data in the LAMOST Medium-Resolution Survey field, RA: $23^h$$01^m$$51.00^s$, Dec:…
We design a convolutional neural network (CNN) incorporating channel attention and spatial attention mechanisms to predict atmospheric parameters of hot subdwarfs. The experimental dataset comprises spectra at nine distinct signal-to-noise…
Abridged. Our aim is to measure the masses and radii of the stars in a newly-discovered detached eclipsing binary system to a high precision ($\approx$1%), enabling the system to be used for the calibration of free parameters in stellar…