A data-driven decomposition of stellar abundance vectors into four latent patterns identifies distinct contributions from core-collapse supernovae, Type Ia supernovae, and AGB stars across the Milky Way disc.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
Milky Way abundance trends act as effective empirical proxies for nucleosynthetic yields, recovering alpha and Fe-peak abundances in quiescent galaxies with 0.05 dex median offset versus 0.23 dex for theory, indicating largely universal yields.
A blind 12D chemo-dynamical clustering analysis with UMAP and HDBSCAN on SDSS-V DR19 and Gaia DR3 data recovers seven known halo substructures and reports five new tightly bound candidates FO1-FO5.
PISP projects high-dimensional spectra into optimized subspaces using PCA or active subspaces plus L1 selection to raise accuracy and speed of stellar parameter inference over standard methods.
citing papers explorer
-
Milky Way Mapper decoded abundances -- I. Shared disc enrichment patterns
A data-driven decomposition of stellar abundance vectors into four latent patterns identifies distinct contributions from core-collapse supernovae, Type Ia supernovae, and AGB stars across the Milky Way disc.
-
Are Nucleosynthetic Yields Universal? Interpreting the Multi-Elemental Abundances of Quiescent Galaxies over Cosmic Time Using Milky Way Stars
Milky Way abundance trends act as effective empirical proxies for nucleosynthetic yields, recovering alpha and Fe-peak abundances in quiescent galaxies with 0.05 dex median offset versus 0.23 dex for theory, indicating largely universal yields.
-
Unsupervised Chemo-Dynamical Dissection of the Inner Galactic Halo: Discovery of Five Accreted Substructures with SDSS-V and Gaia
A blind 12D chemo-dynamical clustering analysis with UMAP and HDBSCAN on SDSS-V DR19 and Gaia DR3 data recovers seven known halo substructures and reports five new tightly bound candidates FO1-FO5.
-
PISP: Projected-Space Inference of Stellar Parameters
PISP projects high-dimensional spectra into optimized subspaces using PCA or active subspaces plus L1 selection to raise accuracy and speed of stellar parameter inference over standard methods.