Astronomy Tea Talk
The field of Galactic Archaeology has made several promising discoveries, from the Gaia Enceladus merger to the inside-out growth of the Galactic disc. Recently, the analysis of spectra, photometry and stellar populations has relied on individual numerical codes incorporating Bayesian interference analysis. However, the increasing amount of information from stellar surveys requires a more self-consistent analysis of the diverse data. For this reason, we have developed SAPP(Stellar Abundances and atmospheric Parameters Pipeline), a fully parallelised efficient python code which determines fundamental stellar parameters using Bayesian inference. The pipeline simultaneously combines information from different sources of observations: photometry, astrometry, spectroscopy as well as asteroseismology. The SAPP will provide parameters such as effective temperature, surface gravity, metallicity and abundances for the core programme of the PLATO space mission planned for 2026, as well as the 4MOST and WEAVE. Outside of the mission, the code provides masses, radii and ages of stars suited for wider application of other space and ground-based telescopes. I will present the SAPP's analysis of the Gaia-ESO DR4 survey by using NLTE abundances combined with Gaia DR3 in the context of the Milky Way's disc history.