Dwarf Galaxy Discoveries from the KMTNet Supernova Program. II. The NGC 3585 Group and Its Dynamical State*
Bibliographic record
Abstract
Abstract We present our discovery and analysis of dwarf galaxies in the NGC 3585 galaxy group by the Korea Microlensing Telescope Network (KMTNet) Supernova Program. Using deep stack images reaching ≃28 mag arcsec−2 in BVI, we discovered 46 dwarf galaxy candidates distributed in a field of 7 square degrees. The dwarf galaxy candidates exhibit a central surface brightness as faint as μ 0,V = 26.2 mag arcsec−2, with effective radii larger than 150 pc and total absolute magnitudes brighter than M V ≈ −10 mag, if at the distance of NGC 3585. The dwarf galaxy surface number density decreases with projected distance from NGC 3585. We estimate the background contamination to be about 20% based both on the number density profile and on diffuse galaxy counts in a control field. The dwarf galaxy colors and Sérsic structural parameters are consistent with those found for other dwarf galaxies. Unusually, there is no indication of a change in color or brightness in the dwarf galaxy candidates with projected distance from the group center. Approximately 20% of the candidates contain an unresolved nucleus. The nucleated fraction is larger for brighter (and redder) galaxies, but is independent of distance from the group center. We identify four ultra-diffuse galaxy candidates, all near the group center. We interpret these spatial properties as suggesting that the NGC 3585 group might be dynamically younger than the typical group. The galaxy luminosity function of the NGC 3585 group has a faint-end slope of α ≈ −1.39, which is roughly consistent with the slopes found for other nearby groups. The possible dependence of the slope on global group properties is still unclear and continues to motivate our homogeneous deep survey of dozens of nearby groups.
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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) | 0.000 | 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".