COSMOS-DASH: The Evolution of the Galaxy Size–Mass Relation since z ∼ 3 from New Wide-field WFC3 Imaging Combined with CANDELS/3D-HST
Bibliographic record
Abstract
Abstract We present COSMOS-Drift And SHift (DASH), a Hubble Space Telescope ( HST ) Wide Field Camera 3 (WFC3) imaging survey of the COSMOS field in the H 160 filter. The survey comprises 456 individual WFC3 pointings corresponding to an area of 0.49 deg 2 (0.66 deg 2 when including archival data) and reaches a 5 σ point-source limit of H 160 = 25.1 (0.″3 aperture). COSMOS-DASH is the widest HST /WFC3 imaging survey in the H 160 filter, tripling the extragalactic survey area in the near-infrared at HST resolution. We make the reduced H 160 mosaic available to the community. We use this data set to measure the sizes of 169 galaxies with at 1.5 < z < 3.0 and augment this sample with 749 galaxies at 0.1 < z < 1.5 using archival ACS imaging. We find that the median size of galaxies in this mass range changes with redshift as kpc. Separating the galaxies into star-forming and quiescent galaxies using their rest-frame U − V and V − J colors, we find no statistical difference between the median sizes of the most massive star-forming and quiescent galaxies at : they are 4.9 ± 0.9 kpc and 4.3 ± 0.3 kpc, respectively. However, we do find a significant difference in the Sèrsic index between the two samples, such that massive quiescent galaxies have higher central densities than star-forming galaxies. We extend the size−mass analysis to lower masses by combining it with the 3D- HST /CANDELS sample of van der Wel et al. and derive empirical relations between size, mass, and redshift. Fitting a relation of the form , with and r eff in kpc, we find log A = −0.25 log(1 + z ) + 0.80 and α = −0.13 log(1 + z ) + 0.27. We also provide relations for the subsamples of star-forming and quiescent galaxies. Our results confirm previous studies that were based on smaller samples or ground-based imaging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".