The GALAH Survey: Neutron-Capture Elemental Abundances for 350 000 Gaia-RVS spectra and the Chemodynamics of Accreted Structures

We present a comprehensive data-driven spectroscopic analysis of 357 415 red giant stars using Gaia DR3 Radial Velocity Spectrometer (RVS) spectra (8460–8700 Å; (Formula presented) ), aimed at deriving homogenous stellar parameters and elemental abundances (collectively referred to as stellar labels). We employ The Cannon, a generative model based on 2747 giants in common with GALactic Archaeology with HERMES (GALAH) DR4, adopting GALAH labels ((Formula presented) ) for training. The resulting model predicts 11 stellar labels for RVS giants: effective temperature ((Formula presented) ), surface gravity ((Formula presented) ), projected rotational velocity ((Formula presented) ), and abundances of [Fe/H], [Ca/Fe], [Si/Fe], [Ni/Fe], [Ti/Fe], as well as the neutron-capture elements [Zr/Fe], [Ce/Fe], and [Nd/Fe]. Building on these results, we develop a probabilistic framework to chemically identify debris from the Gaia–Sausage–Enceladus (GSE) accretion event. A logistic regression classifier, optimized via Markov chain Monte Carlo sampling and trained on a small reference sample of GSE members and comparison stars, identifies stars with high GSE membership probabilities based solely on their chemical abundances, with the resulting candidates exhibiting distinctive abundance-ratio patterns, including [Ca/Ti], [Ti/Ce], and [Nd/Zr]. Applying independent kinematic constraints yields a robust sample of GSE candidates, demonstrating that the characteristic chemical signatures remain consistent after applying these constraints. This work demonstrates the potential of data-driven analysis techniques to extract detailed chemical information from medium-resolution spectra and establishes a framework for tracing Galactic accretion events using chemical abundances.