GalCatDiff applies category embeddings and a novel Astro-RAB block inside diffusion models to produce galaxy images whose color and size distributions match observations more closely than prior generative approaches.
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A GAN framework is trained on EAGLE simulation merger trees to generate new realistic trees for semi-analytic galaxy models at modest computational cost.
Multiple galaxy formation simulations show that low-mass quenched galaxies at z>3 are predominantly environmentally quenched satellites, often only temporarily so, and match JWST observations.
citing papers explorer
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Category-based Galaxy Image Generation via Diffusion Models
GalCatDiff applies category embeddings and a novel Astro-RAB block inside diffusion models to produce galaxy images whose color and size distributions match observations more closely than prior generative approaches.
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A Halo Merger Tree Generation and Evaluation Framework
A GAN framework is trained on EAGLE simulation merger trees to generate new realistic trees for semi-analytic galaxy models at modest computational cost.
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Environmental Quenching of High-Redshift Galaxies: Interpreting JWST Observations with Simulations
Multiple galaxy formation simulations show that low-mass quenched galaxies at z>3 are predominantly environmentally quenched satellites, often only temporarily so, and match JWST observations.