839 citations · 7.4k across the 178 of their papers we have counts for
71 papers · 1 filter
Stellar Parameters of BOSS M dwarfs in SDSS-V DR19
Dan Qiu, Jennifer A. Johnson, Chao Liu +15
We utilized the Stellar LAbel Machine (SLAM), a data-driven model based on Support Vector Regression, to derive stellar parameters ([Fe/H], , and ) for SDSS-V…
Millions of Main-Sequence Binary Stars from Gaia BP/RP Spectra
Jiadong Li, Hans-Walter Rix, Yuan-Sen Ting +6
We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a f…
Differentiable Stellar Atmospheres with Physics-Informed Neural Networks
Jiadong Li, Mingjie Jian, Yuan-Sen Ting +1
We present Kurucz-a1, a physics-informed neural network (PINN) that emulates 1D stellar atmosphere models under Local Thermodynamic Equilibrium (LTE), addressing a critical bottlen…
Anchoring Stellar Age Indicators: A Cross-Calibration of [C/N] and Gyrochronology Ages via the Age-Velocity-Dispersion Relation
Yuxi Lu, Marc H. Pinsonneault, Yuan-Sen Ting +4
Determining stellar ages is challenging, as it depends on other stellar parameters in a non-linear way and often relies on stellar evolution models to infer the underlying relation…
Homogeneous Stellar Atmospheric Parameters and 22 Elemental Abundances for FGK Stars Derived From LAMOST Low-resolution Spectra with DD-Payne
Meng Zhang, Maosheng Xiang, Yuan-Sen Ting +11
A deep understanding of our Galaxy desires detailed decomposition of its stellar populations via their chemical fingerprints. This requires precise stellar abundances of many eleme…
Deriving Stellar Properties, Distances, and Reddenings using Photometry and Astrometry with BRUTUS
Joshua S. Speagle, Catherine Zucker, Angus Beane +18
We present brutus, an open source Python package for quickly deriving stellar properties, distances, and reddenings to stars based on grids of stellar models constrained by photome…