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Intrinsic colors (ICs) of stars are essential for the studies on both stellar physics and dust reddening. In this work, we developed an XGBoost model to predict the ICs with the atmospheric parameters $T_{\rm eff}$, ${\rm log}\,g$, and $\rm…

Solar and Stellar Astrophysics · Physics 2024-07-25 He Zhao , Shu Wang , Biwei Jiang , Jun Li , Dongwei Fan , Yi Ren , Xiaoxiao Ma

In an earlier work, we demonstrated the effectiveness of Bayesian neural networks in estimating the missing line-of-sight velocities of Gaia stars, and published an accompanying catalogue of blind predictions for the line-of-sight…

Astrophysics of Galaxies · Physics 2023-12-13 Aneesh P. Naik , Axel Widmark

We present a supervised, probabilistic taxonomic classification of asteroid reflectance spectra from Gaia Data Release 3 (DR3). Using high-quality Gaia DR3 spectra and a reference set of spectra from the literature consisting exclusively of…

Earth and Planetary Astrophysics · Physics 2026-03-02 Marco Delbo , Thomas Dyer , Ullas Bhat , Chrysa Avdellidou , Laurent Galluccio , Amelia Milton

Context. The study of the oldest and most metal-poor stars in our Galaxy promotes our understanding of the Galactic chemical evolution and the beginning of Galaxy and star formation. However, they are notoriously difficult to find, with…

Astrophysics of Galaxies · Physics 2022-08-04 Theodora Xylakis-Dornbusch , Norbert Christlieb , Karin Lind , Thomas Nordlander

Polycyclic aromatic hydrocarbons (PAHs) are recognized as the primary contributors to the aromatic infrared bands (AIBs) widely observed in space. However, analyzing these AIBs remains challenging because of the immense structural diversity…

Astrophysics of Galaxies · Physics 2026-02-16 Guoqing Tang , Jiang He , Zhao Wang , Dong Qiu

Carbon-enhanced metal-poor (CEMP) stars comprise almost a third of stars with [Fe/H] < --2, although their origins are still poorly understood. It is highly likely that one sub-class (CEMP-$s$ stars) is tied to mass-transfer events in…

Skin cancer is a serious worldwide health issue, precise and early detection is essential for better patient outcomes and effective treatment. In this research, we use modern deep learning methods and explainable artificial intelligence…

Image and Video Processing · Electrical Eng. & Systems 2023-12-19 Faysal Mahmud , Md. Mahin Mahfiz , Md. Zobayer Ibna Kabir , Yusha Abdullah

The recent release of 220+ million BP/RP spectra in $\textit{Gaia}$ DR3 presents an opportunity to apply deep learning models to an unprecedented number of stellar spectra, at extremely low-resolution. The BP/RP dataset is so massive that…

Instrumentation and Methods for Astrophysics · Physics 2023-07-14 Alexander Laroche , Joshua S. Speagle

Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusion detection, and much more. However, the lack of…

Machine Learning · Computer Science 2021-12-17 Khushnaseeb Roshan , Aasim Zafar

Classification of spectra (1) and anomaly detection (2) are fundamental steps to guarantee the highest accuracy in redshift measurements (3) in modern all-sky spectroscopic surveys. We introduce a new Galaxy Spectra Neural Network…

The original Kepler mission has delivered unprecedented high-quality photometry. These data have impacted numerous research fields (e.g., asteroseismology and exoplanets), and continue to be an astrophysical goldmine. Because of this,…

As part of a reanalysis of galactic Asymptotic Giant Branch (AGB) stars at infrared (IR) wavelengths, we discuss a sample (357) of carbon stars for which mass loss rates, near-IR photometry and distance estimates exist. For 252 sources we…

Astrophysics · Physics 2016-08-30 R. Guandalini , M. Busso , S. Ciprini , G. Silvestro , P. Persi

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

Symbiotic stars, binary pairs with a cool giant fueling accretion onto a hot compact companion, offer unique insights to our understanding of stellar evolution. Yet, only a few hundred symbiotic stars are confirmed. Here, we report on a new…

Solar and Stellar Astrophysics · Physics 2025-08-27 Samantha E. Ball , Benjamin C. Bromley , Scott J. Kenyon

We present AspGap, a new approach to infer stellar labels from low-resolution Gaia XP spectra, including precise [$\alpha$/M] estimates for the first time. AspGap is a neural-network based regression model trained on APOGEE spectra. In the…

Solar and Stellar Astrophysics · Physics 2023-09-26 Jiadong Li , Kaze W. K. Wong , David W. Hogg , Hans-Walter Rix , Vedant Chandra

Gaia will observe more than one billion objects brighter than V=20, including stars, asteroids, galaxies and quasars. As Gaia performs real time detection (i.e. without an input catalogue) the intrinsic properties of most of these objects…

Astrophysics · Physics 2007-05-23 C. A. L. Bailer-Jones

Carbon- and Oxygen-rich stars populating the Thermally-Pulsing Asymptotic Giant Branch (TP-AGB) phase of stellar evolution are relevant contributors to the spectra of ~1 Gyr old populations. Atmosphere models for these types are uncertain,…

This study performs a multi-wavelength astrometric and photometric examination of a high-confidence sample $(N = 120,418)$ derived from a parent population of 2.36 million unique WDSS-seeded systems. By establishing an empirical polynomial…

Solar and Stellar Astrophysics · Physics 2026-05-04 Andrew Soon

We describe a new catalog of accelerating star candidates with Gaia $G\le 17.5$ mag and distances $d\le 100$ pc. Designated as Gaia Nearby Accelerating Star Catalog (GNASC), it contains 29,684 members identified using a supervised…

Astrophysics of Galaxies · Physics 2023-04-19 Marc L. Whiting , Joshua B. Hill , Benjamin C. Bromley , Scott J. Kenyon