The abundance of ultra-diffuse galaxies from groups to clusters UDGs are relatively more common in more massive haloes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent years, multiple studies have reported substantial populations of large, low-surface-brightness galaxies in local galaxy clusters. Various theories that aim to explain the presence of such ultra-diffuse galaxies (UDGs) have since been proposed. A key question that will help to differentiate between models is whether UDGs have counterparts in lower-mass host haloes, and what their abundance as a function of halo mass is. In this study we extend our previous study of UDGs in galaxy clusters to galaxy groups. We measure the abundance of UDGs in 325 spectroscopically-selected groups from the Galaxy And Mass Assembly (GAMA) survey. We make use of the overlapping imaging from the ESO Kilo-Degree Survey (KiDS), from which we can identify galaxies with mean surface brightnesses within their effective radii down to ~25.5 mag arcsec$^{-2}$ in the r-band. We are able to measure a significant overdensity of UDGs (with sizes r_eff > 1.5 kpc) in galaxy groups down to M200=10^12 Msun, a regime where approximately only 1 in 10 groups contains a UDG that we can detect. We combine measurements of the abundance of UDGs in haloes that cover three orders of magnitude in halo mass, finding that their numbers scale quite steeply with halo mass; N_UDG (R
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it