The build-up of the colour-magnitude relation in galaxy clusters since z 0.8
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
Using galaxy clusters from the ESO Distant Cluster Survey, we study how the distribution of galaxies along the colour–magnitude relation has evolved since z∼ 0.8. While red-sequence galaxies in all these clusters are well described by an old, passively evolving population, we confirm our previous finding of a significant evolution in their luminosity distribution as a function of redshift. When compared to galaxy clusters in the local Universe, the high-redshift EDisCS clusters exhibit a significant deficit of faint red galaxies. Combining clusters in three different redshift bins, and defining as ‘faint’ all galaxies in the range 0.4 ≳L/L*≳ 0.1, we find a clear decrease in the luminous-to-faint ratio of red galaxies from z∼ 0.8 to ∼0.4. The amount of such a decrease appears to be in qualitative agreement with predictions of a model where the blue bright galaxies that populate the colour–magnitude diagram of high-redshift clusters, have their star formation suppressed by the hostile cluster environment. Although model results need to be interpreted with caution, our findings clearly indicate that the red-sequence population of high-redshift clusters does not contain all progenitors of nearby red-sequence cluster galaxies. A significant fraction of these must have moved on to the red sequence below z∼ 0.8.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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