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Title: 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 groups of chemically similar stars comprise different groups in birth place (Rbirth) and time (age). Simulating observational abundance errors (0.05 dex), we find that to trace distinct groups of (Rbirth, 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 ≈10 groups can be defined with ≈25% overlap in (Rbirth, age). We build a simple model to show that in the context of these simulations, it is possible to infer a star’s age andRbirthfrom abundances with precisions of ±0.06 Gyr and ±1.17 kpc, respectively. We find that abundance clustering is ineffective for a third simulation, where low-αstars form distributed in the disk and early high-αstars form more rapidly in clumps that sink toward the Galactic center as their constituent stars evolve more » to enrich the interstellar medium. However, this formation path leads to large age dispersions across the [α/Fe]–[Fe/H] plane, which is inconsistent with the Milky Way’s observed properties. We conclude that abundance clustering is a promising approach toward charting the history of our Galaxy.

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The Astrophysical Journal
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Article No. 60
DOI PREFIX: 10.3847
Sponsoring Org:
National Science Foundation
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