Related papers: Predicting Stellar Parameters of Massive Stars fro…

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…

Observational astronomy has undergone a significant transformation driven by large-scale surveys, such as the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) Survey, the Sloan Digital Sky Survey (SDSS), and the Gaia…

Light curves of 57 classical Be stars in TESS sectors 1 - 15 are examined. In most Be stars, the periodogram shows groups at a fundamental and one or more harmonics, which we attribute to rotation. In about 40 percent of the stars, the…

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…

In order to explore how the ubiquitous stochastic low-frequency (SLF) variability of O-type stars is related to various stellar characteristics, we compiled a sample of 150 O-type stars observed via ground-based spectroscopic surveys,…

The Hipparcos mission has made it possible to constrain the positions of nearby field stars in the colour-magnitude diagram with very high accuracy. These positions can be compared with the predictions of stellar evolutionary calculations…

In this paper, we investigate the photometric variability of magnetic O-type stars. Such stars possess oblique, predominantly dipolar magnetic fields that confine their winds roughly axisymmetrically about the magnetic equator, thus forming…

We have obtained HST and ground-based observations of a sample of 20 O-type stars in the LMC and SMC, including six of the hottest massive stars known (subtypes O2-3) in the R136 cluster. In general, these data include (a) the HST UV…

The TESS mission will survey ~85 % of the sky, giving us the opportunity of extracting high-precision light curves of millions of stars, including stellar cluster members. In this work, we present our project "A PSF-based Approach to TESS…

In recent years, high-precision high-cadence space photometry has revealed that stochastic low frequency (SLF) variability is common in the light curves of massive stars. We use the data from the Transiting Exoplanet Survey Satellite (TESS)…

The Transiting Exoplanet Survey Satellite (TESS) is a wide-field all-sky survey mission designed to detect Earth-sized exoplanets. After over four years photometric surveys, data from sectors 1-57, including approximately 1,050,000 light…

Eclipsing binaries are important benchmark objects to test and calibrate stellar structure and evolution models. This is especially true for binaries with a fully convective M-dwarf component for which direct measurements of these stars'…

Starspots are thought to be regions of locally strong magnetic fields, similar to sunspots, and they can generate photometric brightness modulations. To deduce stellar and spot properties, such as spot emergence and decay rates, we…

Spectroscopic data are necessary to break degeneracies in asteroseismic modelling of the interior structure in high- and intermediate-mass stars. We derive precise photospheric stellar parameters for a sample of 166 B-type stars with TESS…

We apply multi-algorithm machine learning models to TESS 2-minute survey data from Sectors 1-72 to identify stellar flares. Models trained with Deep Neural Network, Random Forest, and XGBoost algorithms, respectively, utilized four flare…

We report homogeneous spectroscopic determinations of the effective temperature, metallicity, and projected rotational velocity for the host stars of 56 transiting planets. Our analysis is based primarily on the Stellar Parameter…

The transit method allows the detection and characterization of planetary systems by analyzing stellar light curves. Convolutional neural networks appear to offer a viable solution for automating these analyses. In this research, two 1D…

We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the…

We discuss prospects of identifying and characterizing black hole (BH) companions to normal stars on tight but detached orbits, using photometric data from the Transiting Exoplanet Survey Satellite (TESS). We focus on the following two…

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…