The XXL Survey. XLII. The <i>LX</i> − σ<i>v</i> relation of galaxy groups and clusters detected in the <i>XXL</i> and <i>GAMA</i> surveys
Bibliographic record
Abstract
ABSTRACT The XXL Survey is the largest homogeneous survey carried out with XMM-Newton. Covering an area of 50 deg2, the survey contains several hundred galaxy clusters out to a redshift of ≈2, above an X-ray flux limit of ∼6 × 10−15 er g cm−2 s−1. The GAMA spectroscopic survey of ∼300 000 galaxies covers ≈286 deg2, down to an r-band magnitude of r < 19.8 mag. The region of overlap of these two surveys (covering 14.6 deg2) represents an ideal opportunity to study clusters selected via two independent selection criteria. Generating two independently selected samples of clusters, one drawn from XXL (spanning a redshift range 0.05 ≤ z ≤ 0.3) and another from GAMA (0.05 ≤ z ≤ 0.2), both spanning 0.2 ≲ M500 ≲ 5 × 1014 M⊙, we investigate the relationship between X-ray luminosity and velocity dispersion (LX − σv relation). Comparing the LX − σv relation between the X-ray selected and optically selected samples, when not accounting for the X-ray selection, we find that the scatter of the X-ray selected sample is 2.7 times higher than the optically selected sample (at the 3.7σ level). Accounting for the X-ray selection to model the LX − σv relation, we find that the difference in the scatter increases (with the X-ray selected sample having a scatter 3.4 times larger than the optically selected sample). Although the scatter of the optically selected sample is lower, we find 13 optically selected GAMA groups undetected in X-rays. Inspection of the difference in magnitude between the first and second brightest galaxies in the cluster, and a stacked X-ray image of these 13 groups, suggests that these are young systems still in the process of forming.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.018 | 0.010 |
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".