The JWST Extragalactic Mock Catalog: Modeling Galaxy Populations from the UV through the Near-IR over 13 Billion Years of Cosmic History
Bibliographic record
Abstract
Abstract We present an original phenomenological model to describe the evolution of galaxy number counts, morphologies, and spectral energy distributions across a wide range of redshifts ( ) and stellar masses . Our model follows observed mass and luminosity functions of both star-forming and quiescent galaxies, and reproduces the redshift evolution of colors, sizes, star formation, and chemical properties of the observed galaxy population. Unlike other existing approaches, our model includes a self-consistent treatment of stellar and photoionized gas emission and dust attenuation based on the beagle tool. The mock galaxy catalogs generated with our new model can be used to simulate and optimize extragalactic surveys with future facilities such as the James Webb Space Telescope ( JWST ), and to enable critical assessments of analysis procedures, interpretation tools, and measurement systematics for both photometric and spectroscopic data. As a first application of this work, we make predictions for the upcoming JWST Advanced Deep Extragalactic Survey (JADES), a joint program of the JWST /NIRCam and NIRSpec Guaranteed Time Observations teams. We show that JADES will detect, with NIRCam imaging, 1000s of galaxies at z ≳ 6, and 10s at z ≳ 10 at (5 σ ) within the 236 arcmin 2 of the survey. The JADES data will enable accurate constraints on the evolution of the UV luminosity function at z > 8, and resolve the current debate about the rate of evolution of galaxies at z ≳ 8. Ready-to-use mock catalogs and software to generate new realizations are publicly available as the JAdes extraGalactic Ultradeep Artificial Realizations (JAGUAR) package.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".