Structure of Disk‐dominated Galaxies. II. Color Gradients and Stellar Population Models
Bibliographic record
Abstract
We investigate optical and near-IR color gradients in a sample of 172 low-inclination galaxies spanning Hubble types S0-Irr. The colors are compared with stellar population synthesis models from which luminosity-weighted average ages and metallicities are determined. We explore the effects of different underlying star formation histories and additional bursts of star formation. Our results are robust in a relative sense under the assumption that our galaxies shared a similar underlying star formation history and that no bursts involving more than ∼10% of the galaxy mass have occurred in the past 1-2 Gyr. Because the observed gradients show radial structure, we measure "inner" and "outer" disk age and metallicity gradients. Trends in age and metallicity and their gradients are explored as a function of Hubble type, rotational velocity, total near-IR galaxy magnitude, central surface brightness, and scale length. We find strong correlations in age and metallicity with Hubble type, rotational velocity, total magnitude, and central surface brightness in the sense that earlier-type, faster rotating, more luminous, and higher surface brightness galaxies are older and more metal-rich, suggesting an early and more rapid star formation history for these galaxies. The increasing trends with rotational velocity and total magnitude level off for V rot ≳ 120 km s -1 and M K ≲ -23 mag, respectively. This effect is stronger for metallicity (than age), which could reflect a threshold potential above which all metals are retained and thus metallicity saturates at the yield. Outer disk gradients are found to be weaker than the inner gradients as expected for a slower variation of the potential and surface brightness in the outer parts. We find that stronger age gradients are associated with weaker metallicity gradients. Trends in gradients with galaxy parameters are compared with model predictions: these trends do not agree with predictions of semianalytic models of hierarchical galaxy formation, possibly owing to the effect of bar-induced radial flows. The observed trends are in agreement with chemo-spectrophotometric models of spiral galaxy evolution based on CDM-motivated scaling laws but none of the hierarchical merging characteristics, implying a strong dependence of the star formation history of spiral galaxies on the galaxy potential and halo spin parameter.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".