Modelling globular clusters in the TNG50 simulation: predictions from dwarfs to giant galaxies
Bibliographic record
Abstract
ABSTRACT We present a post-processing catalogue of globular clusters (GCs) for the 39 most massive groups and clusters in the TNG50 simulation of the IlllustrisTNG project (virial masses $M_{200} =[5\times 10^{12} \rm {\!-\!} 2 \times 10^{14}$] M⊙). We tag GC particles to all galaxies with stellar mass M* ≥ 5 × 106 M⊙, and we calibrate their masses to reproduce the observed power-law relation between GC mass and halo mass for galaxies with M200 ≥ 1011 M⊙ (corresponding to M* ∼ 109 M⊙). Here, we explore whether an extrapolation of this MGC–M200 relation to lower mass dwarfs is consistent with current observations. We find a good agreement between our predicted number and specific frequency of GCs in dwarfs with $\rm {\it M}_*=[5 \times 10^6 \rm {\!-\!} 10^9]$ M⊙ and observations. Moreover, we predict a steep decline in the GC occupation fraction for dwarfs with M* < 109 M⊙ that agrees well with current observational constraints. This declining occupation fraction is due to a combination of tidal stripping in all dwarfs plus a stochastic sampling of the GC mass function for dwarfs with M* < 107.5 M⊙. Our simulations also reproduce available constraints on the abundance of intracluster GCs in Virgo and Centaurus A. These successes provide support to the hypothesis that the MGC–M200 relation holds, albeit with more scatter, all the way down to the regime of classical dwarf spheroidals in these environments. Our GC catalogues are publicly available as part of the IllustrisTNG data release.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".