The MillenniumTNG project: the galaxy population at <i>z</i> ≥ 8
Bibliographic record
Abstract
ABSTRACT The early release science results from JWST have yielded an unexpected abundance of high-redshift luminous galaxies that seems to be in tension with current theories of galaxy formation. However, it is currently difficult to draw definitive conclusions form these results as the sources have not yet been spectroscopically confirmed. It is in any case important to establish baseline predictions from current state-of-the-art galaxy formation models that can be compared and contrasted with these new measurements. In this work, we use the new large-volume ($L_\mathrm{box}\sim 740 \, \mathrm{cMpc}$) hydrodynamic simulation of the MillenniumTNG project, suitably scaled to match results from higher resolution – smaller volume simulations, to make predictions for the high-redshift (z ≳ 8) galaxy population and compare them to recent JWST observations. We show that the simulated galaxy population is broadly consistent with observations until z ∼ 10. From z ≈ 10–12, the observations indicate a preference for a galaxy population that is largely dust-free, but is still consistent with the simulations. Beyond z ≳ 12, however, our simulation results underpredict the abundance of luminous galaxies and their star-formation rates by almost an order of magnitude. This indicates either an incomplete understanding of the new JWST data or a need for more sophisticated galaxy formation models that account for additional physical processes such as Population III stars, variable stellar initial mass functions, or even deviations from the standard ΛCDM model. We emphasize that any new process invoked to explain this tension should only significantly influence the galaxy population beyond z ≳ 10, while leaving the successful galaxy formation predictions of the fiducial model intact below this redshift.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".