THE NEXT GENERATION VIRGO CLUSTER SURVEY. VII. THE INTRINSIC SHAPES OF LOW-LUMINOSITY GALAXIES IN THE CORE OF THE VIRGO CLUSTER, AND A COMPARISON WITH THE LOCAL GROUP
Bibliographic record
Abstract
ABSTRACT We investigate the intrinsic shapes of low-luminosity galaxies in the central 300 kpc of the Virgo Cluster using deep imaging obtained as part of the Next Generation Virgo Cluster Survey (NGVS). We build a sample of nearly 300 red-sequence cluster members in the yet-unexplored −14 < M g < −8 mag range, and we measure their apparent axis ratios, q, through Sérsic fits to their two-dimensional light distribution, which is well described by a constant ellipticity parameter. The resulting distribution of apparent axis ratios is then fit by families of triaxial models with normally distributed intrinsic ellipticities, E = 1 − C/A, and triaxialities, T = (A 2 − B 2)/(A 2 − C 2). We develop a Bayesian framework to explore the posterior distribution of the model parameters, which allows us to work directly on discrete data, and to account for individual, surface-brightness-dependent axis ratio uncertainties. For this population we infer a mean intrinsic ellipticity = and a mean triaxiality = . This implies that faint Virgo galaxies are best described as a family of thick, nearly oblate spheroids with mean intrinsic axis ratios 1:0.94:0.57. The core of Virgo lacks highly elongated low-luminosity galaxies, with 95% of the population having q > 0.45. We additionally attempt a study of the intrinsic shapes of Local Group (LG) satellites of similar luminosities. For the LG population we infer a slightly larger mean intrinsic ellipticity = , and the paucity of objects with round apparent shapes translates into more triaxial mean shapes, 1:0.76:0.49. Numerical studies that follow the tidal evolution of satellites within LG-sized halos are in good agreement with the inferred shape distributions, but the mismatch for faint galaxies in Virgo highlights the need for more adequate simulations of this population in the cluster environment. We finally compare the intrinsic shapes of NGVS low-mass galaxies with samples of more massive quiescent systems, and with field, star-forming galaxies of similar luminosities. We find that the intrinsic flattening in this low-luminosity regime is almost independent of the environment in which the galaxy resides, but there is a hint that objects may be slightly rounder in denser environments. The comparable flattening distributions of low-luminosity galaxies that have experienced very different degrees of environmental effects suggest that internal processes are the main drivers of galaxy structure at low masses, with external mechanisms playing a secondary role.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".