Cool and data-driven: an exploration of optical cool dwarf chemistry with both data-driven and physical models

Abstract

Detailed chemical studies of F/G/K - or solar-type - stars have long been routine in stellar astrophysics, enabling studies in both Galactic chemodynamics and exoplanet demographics. However, similar understanding of the chemistry of M and late-K dwarfs - the most common stars in the Galaxy - has been greatly hampered both observationally and theoretically by the complex molecular chemistry of their atmospheres. Here, we present a new implementation of the data-driven Cannon model, modelling T_eff, log g, [Fe/H], and [Ti/Fe] trained on low-medium resolution optical spectra (4000-7000 Å) from 103 cool dwarf benchmarks. Alongside this, we also investigate the sensitivity of optical wavelengths to various atomic and molecular species using both data-driven and theoretical means via a custom grid of MARCS synthetic spectra, and make recommendations for where MARCS struggles to reproduce cool dwarf fluxes. Under leave-one-out cross-validation, our Cannon model is capable of recovering T_eff, log g, [Fe/H], and [Ti/Fe] with precisions of 1.4 per cent, $\pm 0.04\,$ dex, $\pm 0.10\,$ dex, and $\pm 0.06\,$ dex respectively, with the recovery of [Ti/Fe] pointing to the as-yet mostly untapped potential of exploiting the abundant - but complex - chemical information within optical spectra of cool stars.