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Deep Realistic Extragalactic Model (DREaM) Galaxy Catalogs: Predictions for a Roman Ultra-Deep Field

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arxiv 2110.10703 v1 pith:ROL5TKHK submitted 2021-10-20 astro-ph.GA astro-ph.CO

classification astro-ph.GAastro-ph.CO
keywords galaxyromancatalogsdeepdreammodelsyntheticwill
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

In the next decade, deep galaxy surveys from telescopes such as the James Webb Space Telescope and Roman Space Telescope will provide transformational data sets that will greatly enhance the understanding of galaxy formation during the epoch of reionization (EoR). In this work, we present the Deep Realistic Extragalactic Model (DREaM) for creating synthetic galaxy catalogs. Our model combines dark matter simulations, subhalo abundance matching and empirical models, and includes galaxy positions, morphologies, and spectral energy distributions (SEDs). The resulting synthetic catalog extends to redshifts $z \sim 12 $, and galaxy masses $\log_{10}(M/M_{\odot}) = 5 $ covering an area of $1\, {\rm deg}^2$ on the sky. We use DREaM to explore the science returns of a $1\, {\rm deg}^2$ \emph{Roman} UDF, and to provide a resource for optimizing ultra-deep survey designs. We find that a \emph{Roman} UDF to $\sim 30\,m_{\rm AB}$ will potentially detect more than $10^6$ $M_{\rm UV}<-17$ galaxies, with more than $10^4$ at redshifts $z>7$, offering an unparalleled dataset for constraining galaxy properties during the EoR. Our synthetic catalogs and simulated images are made publicly available to provide the community with a tool to prepare for upcoming data.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. First Light and Assembly of GalaxieS (FLAGS) I: The JWST/NIRCam Number Counts and IGL as Constraints on Galaxy Formation Models

    astro-ph.GA 2026-08 conditional novelty 6.0 of 10

    FLAGS-I delivers the deepest JWST/NIRCam number counts to date, new 2.77 and 4.10 micron IGL constraints, and a model comparison that ranks SC-SAM first.

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