GAINN: The Galaxy Assembly and Interaction Neural Networks for High-redshift JWST Observations

GAINN: The Galaxy Assembly and Interaction Neural Networks for High-redshift JWST Observations

We present the Galaxy Assembly and Interaction Neural Networks ( Gainn ), a series of artificial neural networks for predicting the redshift, stellar mass, halo mass, and mass-weighted age of simulated galaxies based on James Webb Space Telescope (JWST) photometry. Our goal is to determine the best...

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Detalhes bibliográficos
Principais autores: Lillian Santos-Olmsted, Kirk S. S. Barrow, Tilman Hartwig
Formato: Artigo
Idioma:English
Publicado em: IOP Publishing 2024-01-01
coleção:The Astrophysical Journal
Assuntos:
Hydrodynamical simulations
High-redshift galaxies
James Webb Space Telescope
Galaxy properties
Neural networks
Acesso em linha:https://doi.org/10.3847/1538-4357/ad46fd

Internet

https://doi.org/10.3847/1538-4357/ad46fd

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