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

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, ±0.04 dex, ±0.10 dex, and ±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.