Color Gradients and Half-mass Radii of Galaxies Out to z = 2 in the CANDELS/3D-HST Fields: Further Evidence for Important Differences in the Evolution of Mass-weighted and Light-weighted Sizes
Bibliographic record
Abstract
Abstract Recent studies have indicated that the ratio between half-mass and half-light radii, r mass/r light, varies significantly as a function of stellar mass and redshift, complicating the interpretation of the ubiquitous r light − M * relation. To investigate, in this study we construct the light and color profiles of ∼3000 galaxies at 1 < z < 2 with log M * / M ⊙ > 10.25 using imcascade, a Bayesian implementation of the Multi-Gaussian Expansion (MGE) technique. imcascade flexibly represents galaxy profiles using a series of Gaussians, free of any a priori parameterization. We find that both star-forming and quiescent galaxies have, on average, negative color gradients. For star-forming galaxies, we find steeper gradients that evolve with redshift and correlate with dust content. Using the color gradients as a proxy for gradients in the M/L ratio, we measure half-mass radii for our sample of galaxies. There is significant scatter in individual r mass/r light ratios, which is correlated with variation in the color gradients. We find that the median r mass/r light ratio evolves from 0.75 at z = 2 to 0.5 at z = 1, consistent with previous results. We characterize the r mass − M * relation, and we find that it has a shallower slope and shows less redshift evolution than the r light − M * relation. This applies both to star-forming and quiescent galaxies. We discuss some of the implications of using r mass instead of r light, including an investigation of the size−inclination bias and a comparison to numerical simulations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".