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.
E., Allende Prieto , C., Holtzman , J
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
representative citing papers
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.
C/N/O abundance patterns indicate that some α-rich young red giants are merger or mass-transfer products rather than genuinely young stars with anomalous chemistry.
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.
-
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.
-
Origin of $\alpha$-rich young stars: clues from C, N and O
C/N/O abundance patterns indicate that some α-rich young red giants are merger or mass-transfer products rather than genuinely young stars with anomalous chemistry.
- Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference