The stellar chemical abundances of simulated massive galaxies at <i>z</i> = 2
Bibliographic record
Abstract
ABSTRACT We analyse the stellar abundances of massive galaxies (log M*/M⊙ > 10.5) at redshift, z = 2, in the IllustrisTNG simulation with the goal of guiding the interpretation of current and future observations, particularly from JWST. We find that the effective size, Re, of galaxies strongly affects the abundance measurements: both [Mg/H] and [Fe/H] are anticorrelated with Re, while the relative abundance [Mg/Fe] slightly increases with Re. The α enhancement as tracked by [Mg/Fe] traces the formation time-scale of a galaxy weakly, and mostly depends on Re. Aperture effects are important: measuring the stellar abundances within 1 kpc instead of within Re can make a large difference. These results are all due to a nearly universal, steeply declining stellar abundance profile that does not scale with galaxy size – Small galaxies appear metal-rich because their stars live in the inner part of the profile where abundances are high. The slope of this profile is mostly set by the gas-phase abundance profile and not substantially modified by stellar age gradients. The gas-phase abundance profile, in turn, is determined by the strong radial dependence of the gas fraction and star-formation efficiency. We develop a simple model to describe the chemical enrichment, in which each radial bin of a galaxy is treated as an independent closed-box system. This model reproduces the gas-phase abundance profile of simulated galaxies, but not the detailed distribution of their stellar abundances, for which gas and/or metal transport are likely needed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".