The Next Generation Fornax Survey (NGFS). II. The Central Dwarf Galaxy Population
Bibliographic record
Abstract
Abstract We present a photometric study of the dwarf galaxy population in the core region (≲r vir/4) of the Fornax galaxy cluster based on deep u′g′i′ photometry from the Next Generation Fornax Cluster Survey. All imaging data were obtained with the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo Interamerican Observatory. We identify 258 dwarf galaxy candidates with luminosities −17 ≲ M g′ ≲ −8 mag, corresponding to typical stellar masses of , reaching ∼3 mag deeper in point-source luminosity and ∼4 mag deeper in surface brightness sensitivity compared to the classic Fornax Cluster Catalog. Morphological analysis shows that the dwarf galaxy surface-brightness profiles are well represented by single-component Sérsic models with average Sérsic indices of and average effective radii of . Color–magnitude relations indicate a flattening of the galaxy red sequence at faint galaxy luminosities, similar to the one recently discovered in the Virgo cluster. A comparison with population synthesis models and the galaxy mass–metallicity relation reveals that the average faint dwarf galaxy is likely older than ∼5 Gyr. We study galaxy scaling relations between stellar mass, effective radius, and stellar mass surface density over a stellar mass range covering six orders of magnitude. We find that over the sampled stellar mass range several distinct mechanisms of galaxy mass assembly can be identified: (1) dwarf galaxies assemble mass inside the half-mass radius up to , (2) isometric mass assembly occurs in the range , and (3) massive galaxies assemble stellar mass predominantly in their halos at and above.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.003 | 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".