The Next Generation Virgo Cluster Survey (NGVS). XXIV. The Red Sequence to ∼10<sup>6</sup> L<sub>⊙</sub> and Comparisons with Galaxy Formation Models
Bibliographic record
Abstract
Abstract We use deep optical photometry from the Next Generation Virgo Cluster Survey (NGVS) to investigate the color–magnitude diagram for the galaxies inhabiting the core of this cluster. The sensitivity of the NGVS imaging allows us to continuously probe galaxy colors over a factor of ∼2 × 105 in luminosity, from brightest cluster galaxies to scales overlapping classical satellites of the Milky Way ( M g ′ ∼ −9; M * ∼ 106 M ⊙), within a single environment. Remarkably, we find the first evidence that the red sequence (RS) flattens in all colors at the faint-magnitude end (starting between −14 ≤ M g ′ ≤ −13, around M * ∼ 4 × 107 M ⊙), with the slope decreasing to ∼60% or less of its value at brighter magnitudes. This could indicate that the stellar populations of faint dwarfs in Virgo’s core share similar characteristics (e.g., constant mean age) over ∼3 mag in luminosity, suggesting that these galaxies were quenched coevally, likely via pre-processing in smaller hosts. We also compare our results to galaxy formation models, finding that the RS in model clusters have slopes at intermediate magnitudes that are too shallow, and in the case of semianalytic models, do not reproduce the flattening seen at both extremes (bright/faint) of the Virgo RS. Deficiencies in the chemical evolution of model galaxies likely contribute to the model-data discrepancies at all masses, while overly efficient quenching may also be a factor at dwarf scales. Deep UV and near-IR photometry are required to unambiguously diagnose the cause of the faint-end flattening.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".