Tracing birth properties of stars with abundance clustering

To understand the formation and evolution of the Milky Way disk, we must connect its current properties to its past. We explore hydrodynamical cosmological simulations to investigate how the chemical abundances of stars might be linked to their origins. Using hierarchical clustering of abundance measurements in two Milky Way-like simulations with distributed and steady star formation histories, we find that abundance clusters of stars comprise different groups in birth place ($R_text{birth}$) and time (age). Simulating observational abundance errors (0.05 dex), we find that to trace discrete groups of ($R_text{birth}$, age) requires a large vector of abundances. Using 15-element abundances (Fe, O, Mg, S, Si, C, P, Mn, Ne, Al, N, V, Ba, Cr, Co), up to $approx$ 10 clusters can be defined with $approx$ 25% overlap in ($R_text{birth}$, age). We build a simple model to show that it is possible to infer a stars age and $R_text{birth}$ from abundances with precisions of $pm$0.06 Gyr and $pm$1.17 kpc respectively. We find that abundance clustering is ineffective for a third simulation, where low-$alpha$ stars form distributed in the disc and early high-$alpha$ stars form more rapidly in clumps that sink towards the galactic center as their constituent stars evolve to enrich the interstellar medium. However, this formation path leads to large age-dispersions across the [$alpha$/Fe]-[Fe/H] plane, which is inconsistent with the Milky Ways observed properties. We conclude that abundance clustering is a promising approach toward charting the history of our Galaxy.