Four parameters suffice to describe dust attenuation curve diversity in TNG simulations, yielding a new symbolic-regression model that recovers curves and fluxes better than existing parameterizations while linking parameters to SFR surface density, metallicity, and geometry.
C., et al., 2024, @doi [arXiv] 10.48550/arXiv.2411.13960
3 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
years
2026 3roles
method 1polarities
background 1representative citing papers
A new overdensity-conditioned emulator trained on small subvolumes from Quijote recovers the global halo mass function via integration over the overdensity distribution at 0.026% of the simulation cost.
AI techniques for photometric redshift estimation have converged and are now limited by the size, systematics, and selection effects in spectroscopic training samples rather than by methodology.
citing papers explorer
-
Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations
Four parameters suffice to describe dust attenuation curve diversity in TNG simulations, yielding a new symbolic-regression model that recovers curves and fluxes better than existing parameterizations while linking parameters to SFR surface density, metallicity, and geometry.