Working around the edges of Chemical Abundance Surveys using MOOG

Measuring chemical abundances for hundreds of thousands of stars across the entire HR diagram is a very difficult thing to do in a way that is systematic-free. There are a wide-range of LTE/NLTE/plane-parallel/spherically symmetric codes that can all introduce their own systematic uncertainties. The choices made to optimize analysis time for the goals of the survey can impact the derived abundances of stars with very different stellar parameters, e.g., a survey tuned for MW disk stars may have biases for MW halo stars or a survey tuned for G dwarfs may produce poor results for M giants.

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) DR17 abundances results are available from both the Synspec and Turbospectrum spectral synthesis codes. Despite having a large synthetic 8D grid with 442,260 synthetic spectra to cover more than 657,000 stars, there are more than 15,000 of high S/N DR17 APOGEE spectra for stars which are labeled as “BAD” because the APOGEE Stellar Parameter and Abundance Pipeline (ASPCAP) analysis places them close to the spectral grid edges. Exploring those edge stars could potentially bear fruit, but does the choice of spectral synthesis code matter for such an analysis? In this talk, I describe how the tools used for measuring stellar abundances in spectroscopic surveys of stars impact the chemical abundance measurements; and how and when one can use other spectral synthesis tools, such as MOOG to further interpret those results. We show some exemplar cases using MOOG and what problems this might cause. I’ll conclude with a review of a boutique abundance analysis for the most metal-poor stars in the APOGEE dSph samples for Ursa Minor, Fornax, Sextans and Bootes. All these dSph stars are at the grid edges and were therefore not analyzed until now.