Milky Way Mapper decoded abundances -- I. Shared disc enrichment patterns
Melissa K. Ness, Sarah Aquilina, Jennifer Mead, Emily Griffith, Catherine Manea, Jonathan Bird, Andrew R. Casey, Lucy (Yuxi) Lu, Kathryn V. Johnston, Michael R. Blanton, James W. Johnson, Maja Jablonska, Leticia Carigi, Jos\'e G. Fern\'andez-Trincado, Ricardo L\'opez Valdivia

TL;DR
This study models elemental abundances in 70,057 Milky Way disc stars using latent nucleosynthetic patterns, revealing insights into Galactic chemical evolution and enrichment sources.
Contribution
Introduces a data-driven generative model that captures shared nucleosynthetic patterns across stars, linking them to specific enrichment sources and Galactic evolution.
Findings
Model accurately reproduces star abundances with high precision.
Identifies distinct enrichment sources like supernovae and AGB stars.
Reveals how enrichment patterns vary with age, metallicity, and orbital properties.
Abstract
Elemental abundances in the Milky Way disc trace its star-formation and enrichment history, but predicting these abundances from theory is limited by uncertain nucleosynthetic yields and poorly constrained chemical evolution models. Large surveys provide many abundances that enable multi-dimensional insight. However, having so much data available complicates joint visualisation and physical interpretation. Here, we examine the element abundances of 70,057 red giant stars from the Milky Way Mapper survey ([Fe/H] ), using 16 elements (O,~Mg,~Al,~Si,~S,~K,~Ca,~Ti,~V, ~Cr, Mn,~Fe,~Co,~Ni,~Ce,~Nd). To tackle the challenges of joint-interpretation of these elements, we build a generative data-driven model, expressing each star's abundance vector as a linear combination of a few () latent nucleosynthetic patterns. These patterns are shared among the population but vary in fraction…
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