Related papers: Predicting Stellar Rotation Periods Using XGBoost
Among the available methods for dating stars, gyrochronology is a powerful one because it requires knowledge of only the star's mass and rotation period. Gyrochronology relations have previously been calibrated using young clusters, with…
Context. Understanding the Milky Way's formation and evolution across cosmic epochs necessitates precise stellar age determination across all Galactic components. Recent advancements in asteroseismology, spectroscopy, stellar modelling, and…
Ray tracing algorithms that compute pulse profiles from rotating neutron stars are essential tools for constraining neutron-star properties with data from missions such as NICER. However, the high computational cost of these simulations…
The second mission of the NASA Kepler satellite, K2, has collected hundreds of thousands of lightcurves for stars close to the ecliptic plane. This new sample could increase the number of known pulsating stars and then improve our…
In our previous work, we investigated the occurrence rate of super-flares on various types of stars and their statistical properties, with a particular focus on G-type dwarfs, using entire Kepler data. The said study also considered how the…
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…
A number of planet-host stars have been observed to rotate with a period equal to an integer multiple of the orbital period of their close planet. We expand this list by analyzing Kepler data of HAT-P-11 and finding a period ratio of 6:1.…
Most X-ray pulsars in high-mass X-ray binary (HMXB) systems exhibit both global and local trends of spin acceleration (spin-up) and deceleration (spin-down). Moreover, decades-long monitored objects display even more general spin-up trends…
Context. Kepler-17 is a G2V sun-like star accompanied by a transiting planet with a mass of ~2.5 Jupiter masses and an orbital period of 1.486 d, recently discovered by the Kepler space telescope. This star is highly interesting as a young…
The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structures they contain. In the realm of material informatics, employing machine learning (ML) techniques to classify…
Many stars, including those in binary or multiple systems, exhibit modified rotational evolution due to tidal interactions. While magnetic braking slows rotation in single stars, close binaries experience synchronization from tidal forces,…
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…
Solar flares are among the most powerful and dynamic events in the solar system, resulting from the sudden release of magnetic energy stored in the Sun's atmosphere. These energetic bursts of electromagnetic radiation can release up to…
In this work we propose a new algorithm for solving high-dimensional backward stochastic differential equations (BSDEs). Based on the general theta-discretization for the time-integrands, we show how to efficiently use eXtreme Gradient…
The efficiency of the transport of angular momentum and chemical elements inside intermediate-mass stars lacks proper calibration, thereby introducing uncertainties on a star's evolutionary pathway. Improvements require better estimation of…
Accurate short-term forecasting of air temperature and relative humidity is critical for urban management, especially in topographically complex cities such as Chongqing, China. This study compares seven machine learning models: eXtreme…
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify.…
Rotation estimation plays a fundamental role in many computer vision and robot tasks. However, efficiently estimating rotation in large inputs containing numerous outliers (i.e., mismatches) and noise is a recognized challenge. Many robust…
The rotation-mass-age relationship offers a promising avenue for measuring the ages of field stars, assuming the attendant uncertainties to this technique can be well characterized. We model stellar angular momentum evolution starting with…
Machine learning algorithms such as random forests or xgboost are gaining more importance and are increasingly incorporated into production processes in order to enable comprehensive digitization and, if possible, automation of processes.…