The near-IR luminosity function and bimodal surface brightness distributions of Virgo cluster galaxies
Bibliographic record
Abstract
We have acquired deep, H-band imaging for a sample of 286 Virgo cluster galaxies with BT≤ 16 mag and extracted surface photometry from optical g, r, i, z Sloan Digital Sky Survey images of 742 Virgo Cluster Catalogue galaxies, including those with H-band images. We confirm the detection of a dip in the luminosity function indicative of a discontinuity in the cluster galaxy population; the dip is more pronounced at redder wavelengths. We find, in agreement with earlier works of Tully and Verheijen and ours for Ursa Major cluster galaxies, a clear dichotomy between high and low surface brightness (HSB and LSB) galaxy discs. The difference between the low and high brightness peaks of Virgo disc galaxies is ∼2 H-mag arcsec−2, significantly larger than any systematic errors. The high surface brightness disc galaxies have two distinct classes of high and low concentration bulges, while LSB galaxies have only low concentration bulges. Early-type galaxies exhibit a similar structural bimodality though offset from that of the spiral galaxies towards higher surface brightnesses. Both the early- and late-type structural bimodalities are uncorrelated with colour or any other structural parameter except, possibly, circular velocity. Random realizations of realistic surface brightness profiles suggest that a bimodal distribution of effective surface brightness is unexpected based on normal distributions of bulge and disc parameters. Rather, the structural bimodality may be linked to dynamic properties of galaxies. Low angular momentum systems may collapse to form dynamically important discs with high surface brightness, while high angular momentum systems would end up as low surface brightness galaxies dominated by the dark halo at all radii. The confirmation of structural bimodality for gas-rich and gas-poor galaxies in the high-density Virgo cluster as well as the low-density UMa cluster suggests that this phenomenon is independent of environment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".