A Data-Driven M Dwarf Model and Detailed Abundances for $\sim$17,000 M Dwarfs in SDSS-V
Aida Behmard, Melissa K. Ness, Andrew R. Casey, Ruth Angus, Katia, Cunha, Diogo Souto, Yuxi (Lucy) Lu, Jennifer A. Johnson

TL;DR
This paper develops a data-driven model using The Cannon to accurately determine temperatures and detailed elemental abundances for approximately 17,000 M dwarfs from SDSS-V, overcoming previous modeling speed limitations.
Contribution
It introduces a new, efficient data-driven approach trained on binary star spectra to derive precise stellar parameters and abundances for a large sample of M dwarfs.
Findings
Model achieves median uncertainties of 13 K in temperature and 0.02 dex in abundances.
Successfully reproduces known abundance patterns and metallicity trends.
Provides detailed elemental abundances for 16,590 M dwarfs in SDSS-V.
Abstract
The cool temperatures of M dwarf atmospheres enable complex molecular chemistry, making robust characterization of M dwarf compositions a long-standing challenge. Recent modifications to spectral synthesis pipelines have enabled more accurate modeling of M dwarf atmospheres, but these methods are too slow for characterizing more than a handful of stars at a time. Data-driven methods such as The Cannon are viable alternatives, and can harness the information content of many M dwarfs from large spectroscopic surveys. Here, we train The Cannon on M dwarfs with FGK binary companions from the Sloan Digital Sky Survey-V/Milky Way Mapper (SDSS-V/MWM), with spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). The FGK-M pairs are assumed to be chemically homogeneous and span 0.56 [Fe/H] 0.31 dex. The resulting model is capable of inferring M dwarf…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Gamma-ray bursts and supernovae · Stellar, planetary, and galactic studies
