The TNG50-SKIRT Atlas: Wavelength dependence of the effective radius
Bibliographic record
Abstract
Galaxy sizes correlate with many other important properties of galaxies, and the cosmic evolution of galaxy sizes is an important observational diagnostic for constraining galaxy evolution models. The effective radius is probably the most widely used indicator of galaxy size. We used the TNG50-SKIRT Atlas to investigate the wavelength dependence of the effective radius of galaxies at optical and near-infrared (NIR) wavelengths. We find that, on average, the effective radius in every band exceeds the stellar mass effective radius, and that this excess systematically decreases with increasing wavelength. The optical g -band (NIR K s -band) effective radius is on average 58% (13%) larger than the stellar mass effective radius. Effective radii measured from dust-obscured images are systematically larger than those measured from dust-free images, although the effect is limited (8.7% in the g -band, 2.1% in the K s -band). We find that stellar population gradients are the dominant factor (about 80%) in driving the wavelength dependence of the effective radius, and that differential dust attenuation is a secondary factor (20%). Comparing our results to recent observational data, we find offsets in the absolute values of the median effective radii, up to 50% for the population of blue galaxies. We find better agreement in the slope of the wavelength dependence of the effective radius, with red galaxies having a slightly steeper slope than green–blue galaxies. Comparing our effective radii with those of galaxies from the Siena Galaxy Atlas in separate bins in z -band absolute magnitude and g − z colour, we find excellent agreement for the reddest galaxies, but again significant offsets for the blue populations: up to 70% for galaxies around M z = −21.5. This difference in median effective radius for the bluer galaxies is most probably due to intrinsic differences in the morphological structure of observed and TNG50 simulated galaxies. Finally, we find that the median effective radius in any broadband filter increases systematically with decreasing u − r colour and with increasing galaxy stellar mass, total SFR, sSFR, and dust-to-stellar-mass ratio. For the slope of the wavelength dependence of R e , however, there does not seem to be a systematic, monotonic correlation with any of these global properties.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".