A Deep Redshift Survey of the Perseus Cluster: Spatial Distribution and Kinematics of Galaxies
Bibliographic record
Abstract
We study the global kinematics of the Perseus galaxy cluster (Abell 426) at redshift z = 0.017 using a large sample of galaxies from our new MMT/Hectospec spectroscopic observation for this cluster. The sample includes 1447 galaxies with measured redshifts within 60' from the cluster center (1148 from this MMT/Hectospec program and 299 from the literature). The resulting spectroscopic completeness is 67% at r-band apparent magnitude $r_{\rm{Petro, 0}}\leq 18.0$ within 60' from the cluster center. To identify cluster member galaxies in this sample, we develop a new open-source Python package, CausticSNUpy. This code implements the algorithm of the caustic technique and yields 418 member galaxies within 60' of the cluster. We study the cluster using this sample of member galaxies. The cluster shows no significant signal of global rotation. A statistical test shows that the cluster does not have a noticeable substructure within 30'. We find two central regions where the X-ray emitting intracluster medium and galaxies show significant velocity differences ($>7σ$). On a large scale, however, the overall morphology and kinematics between the intracluster medium and galaxies agree well. Our results suggest that the Perseus cluster is a relaxed system and has not experienced a recent merger.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".