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.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Reprojects abundances of 199k stars into 4 patterns, identifying enrichment pathways with strong chemo-spatial, age, and vertical correlations plus a transition at ~6 Gyr.
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
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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.
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Milky Way Mapper decoded abundances -- II: From patterns to paths
Reprojects abundances of 199k stars into 4 patterns, identifying enrichment pathways with strong chemo-spatial, age, and vertical correlations plus a transition at ~6 Gyr.
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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.