Low Metallicities and Old Ages for Three Ultra-diffuse Galaxies in the Coma Cluster
Bibliographic record
Abstract
Abstract A large population of ultra-diffuse galaxies (UDGs) was recently discovered in the Coma cluster. Here we present optical spectra of three such UDGs, DF 7, DF 44, and DF 17, which have central surface brightnesses of μ g ≈ 24.4–25.1 mag arcsec−2. The spectra were acquired as part of an ancillary program within the SDSS-IV MaNGA Survey. We stacked 19 fibers in the central regions from larger integral field units (IFUs) per source. With over 13.5 hr of on-source integration, we achieved a mean signal-to-noise ratio in the optical of 9.5 Å−1, 7.9 Å−1, and 5.0 Å−1, respectively, for DF 7, DF 44, and DF 17. Stellar population models applied to these spectra enable measurements of recession velocities, ages, and metallicities. The recession velocities of DF 7, DF 44, and DF 17 are km s−1, km s−1, and km s−1, spectroscopically confirming that all of them reside in the Coma cluster. The stellar populations of these three galaxies are old and metal-poor, with ages of Gyr, Gyr, and Gyr, and iron abundances of [Fe/H] , , and , respectively. Their stellar masses are (3–6) × 108 M ⊙. The UDGs in our sample are as old or older than galaxies at similar stellar mass or velocity dispersion (only DF 44 has an independently measured dispersion). They all follow the well-established stellar mass–stellar metallicity relation, while DF 44 lies below the velocity dispersion-metallicity relation. These results, combined with the fact that UDGs are unusually large for their stellar masses, suggest that stellar mass plays a more important role in setting stellar population properties for these galaxies than either size or surface brightness.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".