SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
Measuring the Resolved Star Formation Main Sequence in TNG100: Fitting Technique Matters
2 Pith papers cite this work. Polarity classification is still indexing.
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Machine-learning analysis of TNG100 galaxies finds global properties (black-hole mass, halo mass) control quenching while local stellar density controls ongoing star formation.
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Cosmological constraints from the small scale clustering of Emission Line Galaxies
SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
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Understanding the regulation of star formation within TNG100 galaxies on kpc-scales using machine learning I: Global versus local
Machine-learning analysis of TNG100 galaxies finds global properties (black-hole mass, halo mass) control quenching while local stellar density controls ongoing star formation.