The Evolution of Population Gradients in Galaxy Clusters: The Butcher‐Oemler Effect and Cluster Infall
Bibliographic record
Abstract
We present photometric and spectroscopic measurements of the galaxy populations in clusters from the CNOC1 sample of rich, X-ray-luminous clusters at 0.18 < z < 0.55. A classical measure of the galaxy blue fraction for spectroscopically confirmed cluster members shows a significant Butcher-Oemler effect for the sample, but only when radii larger than 0.5 r 200 are considered. We perform a principal component analysis of galaxy spectra to divide the total cluster light into contributions from stellar populations of different ages. Composite radial distributions of different stellar populations show strong gradients as a function of clustercentric radius. The composite population is dominated by evolved populations in the core, and gradually changes at radii greater than the virial radius to one which is similar to coeval field galaxies. We do not see evidence at any radius within the clusters for an excess of star formation over that seen in the coeval field. Within this redshift range, significant evolution in the fractional population gradient is seen. Both low- and high-redshift clusters have similar populations in the cluster cores, but higher redshift clusters have steeper gradients and more star-forming galaxies at radii outside of the core region—in effect, a restatement of the Butcher-Oemler effect. Luminosity density profiles are consistent with a scenario where this phenomenon is due to a decline over time in the infall rate of field galaxies into clusters. Depending on how long galaxies reside in clusters before their star formation rates are diminished, this suggests a decrease in the infall into clusters of a factor of ~3 between z > 0.8 and z ~ 0.5. We also discuss alternative scenarios for the evolution of cluster populations.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".