2025ApJ...982...13B

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. 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 T_eff and elemental abundances for Fe, Mg, Al, Si, C, N, O, Ca, Ti, Cr, and Ni with median uncertainties of 13 K and 0.018-0.029 dex, respectively. We test the model by verifying that it reproduces the reported abundance values of M dwarfs in open clusters and benchmark M dwarf data sets, as well as the expected metallicity trends from stellar evolution. We apply the model to 16,590 M dwarfs in SDSS-V/MWM and provide their detailed abundances in our accompanying catalog.