The Coevolution of Massive Quiescent Galaxies and Their Dark Matter Halos over the Last 6 Billion Years
Bibliographic record
Abstract
Abstract We investigate the growth of massive quiescent galaxies at z < 0.6 based on the Sloan Digital Sky Survey and the Smithsonian Hectospec Lensing Survey, two magnitude-limited spectroscopic surveys of high data quality and completeness. Our three-parameter model links quiescent galaxies across cosmic time by self-consistently evolving stellar mass, stellar population age-sensitive D n 4000 index, half-light radius, and stellar velocity dispersion. Stellar velocity dispersion is a robust proxy of dark matter halo mass; we use it to connect galaxies and dark matter halos and thus empirically constrain their coevolution. The typical rate of stellar mass growth is , and dark matter growth rates from our empirical model are remarkably consistent with N-body simulations. Massive quiescent galaxies grow by minor mergers with dark matter halos of mass and evolve parallel to the stellar mass–halo mass (SMHM) relation based on N-body simulations. Thus, the SMHM relation of massive galaxies apparently results primarily from dry minor merging.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".