相关论文: Data-driven stellar intrinsic colors and dust redd…

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…

We pose the question of how much information on the atmospheric parameters of late-type stars can be retrieved purely from colors using standard photometric systems. We carried out numerical experiments using stellar fluxes from model…

We develop, validate and apply a forward model to estimate stellar atmospheric parameters ($T_{\rm eff}$, $\log{g}$ and $\mathrm{[Fe/H]}$), revised distances and extinctions for 220 million stars with XP spectra from $\textit{Gaia}$ DR3.…

We present a method to simultaneously infer the interstellar extinction parameters $A_0$ and $R_0$, stellar effective temperature $T_{\rm eff}$, and distance modulus $\mu$ in a Bayesian framework. Using multi-band photometry from SDSS and…

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…

The scarcity of high-fidelity extinction measurements remains a bottleneck in deriving accurate stellar properties from Gaia parallaxes. In this work, we aim to derive precision extinction estimates for APOGEE DR19 stars, establishing a new…

Data-driven models of stellar spectra are useful tools to study non-stellar information, such as the Diffuse Interstellar Bands (DIBs) caused by intervening interstellar material. Using $\sim 55000$ spectra of $\sim 17000$ red clump stars…

We have obtained accurate dust reddening from far-ultraviolet (UV) to the mid-infrared (IR) for up to 5 million stars by the star-pair algorithm based on LAMOST stellar parameters along with GALEX, Pan-STARRS 1, Gaia, SDSS, 2MASS, and WISE…

We derive and publish data-driven estimates of stellar metallicities [M/H] for 175 million stars with low-resolution XP spectra published in Gaia DR3. The [M/H] values, along with Teff and logg, are derived using the XGBoost algorithm,…

Large spectroscopic surveys have enabled in the recent years the computation of three-dimensional interstellar extinction maps thanks to accurate stellar atmospheric parameters and line-of-sight distances. Such maps are complementary to 3D…

A precise interstellar dust extinction law is critically important to interpret observations. There are two indicators of extinction: the color excess ratio (CER) and the relative extinction. Compared to the CER, the wavelength-dependent…

The second Gaia data release (DR2) delivers accurate and homogeneous photometry data of the whole sky to an exquisite quality, reaching down to the unprecedented milli-magnitude (mmag) level for the G, GRP, and GBP passbands. However, the…

With the plentiful information available in the Gaia BP/RP spectra, there is significant scope for applying discriminative models to extract stellar atmospheric parameters and abundances. We describe an approach to leverage an `Uncertain…

In this paper, we found 2939 S-type stars from LAMOST Data Release 10 using two machine-learning methods, and 2306 of them were reported for the first time. The main purpose of this work is to study how to divide S-type stars into intrinsic…

We study the spectroscopic and photometric properties of carbon stars. In the first paper of this series we focus on objects that can be described by hydrostatic models neglecting dynamical phenomena like pulsation and mass loss. As a…

We present new three-dimensional (3D) interstellar dust reddening maps of the Galactic plane in three colours, E(G-Ks), E(Bp-Rp) and E(H-Ks). The maps have a spatial angular resolution of 6 arcmin and covers over 7000 deg$^2$ of the…

We present measurements of dust reddening using the colors of stars with spectra in the Sloan Digital Sky Survey. We measure reddening as the difference between the measured and predicted colors of a star, as derived from stellar parameters…

This study employs stellar parameters from spectroscopic surveys and Zhang et al. based on Gaia XP spectra, along with photometric data from GALEX, UVOT, and Gaia, to obtain extensive ultraviolet color excess information for the relevant…

Red clump stars (RCs) are useful tracers of distances, extinction, chemical abundances, and Galactic structures and kinematics. Accurate estimation of the RC parameters -- absolute magnitude and intrinsic color -- is the basis for obtaining…

We present AGNBoost, a machine learning framework utilizing XGBoostLSS to identify AGN and estimate redshifts from JWST NIRCam and MIRI photometry. AGNBoost constructs 66 input features from 7 NIRCam and 4 MIRI bands to predict the fraction…