Cluster properties as a function of dynamical state in the DESI Legacy x UNIONS surveys
Bibliographic record
Abstract
We investigate how the dynamical state of galaxy clusters influences their galaxy populations and mass distributions. Using photometrically selected clusters from the DESI Legacy Imaging Survey cross-matched with the UNIONS galaxy shear catalogue, we classify clusters as evolved or evolving based on their rest-frame r-band magnitude gaps and stellar mass ratios between the brightest cluster galaxies (BCGs) and bright satellites. We measure the stellar mass functions, weak-lensing profiles, and radial number density and red-fraction profiles of stacked clusters in both subsamples. Evolved clusters exhibit more concentrated lensing profiles, bimodal stellar mass functions dominated by massive BCGs, and a deficit of intermediate-mass satellites, while evolving clusters show flatter central lensing signals and an excess of massive satellites. Applying the same selection to IllustrisTNG clusters reproduces these trends and links the observed differences to distinct mass accretion histories. These results demonstrate the close link between cluster galaxy populations and the overall dynamical state of their underlying dark matter halo.
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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 | 0.002 |
| 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 | 0.001 | 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".