The XXL Survey – XLVIII. X-ray follow-up of distant XXL clusters: masses, scaling relations, and AGN contamination
Bibliographic record
Abstract
ABSTRACT We use deep follow-up XMM–Newton observations of six clusters discovered in the XXL Survey at z > 1 to gain robust measurements of their X-ray properties and to investigate the extent to which scaling relations at low redshift are valid at z > 1. This sample is unique as it has been investigated for active galactic nucleus (AGN) contamination, which ensures measurements are not undermined by systematic uncertainties, and pushes to lower mass at higher redshift than is usually possible, for example with Sunyaev–Zel’dovich (SZ) selected clusters. We determine the flux contribution of point sources to the XXL cluster flux in order to test for the presence of AGN in other high-redshift cluster candidates, and find 3XLSS J231626.8−533822 to be a point source misclassified as a cluster and 3XLSS J232737.3−541618 to be a genuine cluster. We present the first attempt to measure the hydrostatic masses in a bright subsample of z > 1 X-ray selected galaxy clusters with a known selection function. Periods of high particle background significantly reduced the effective exposure times of observations (losing >50 per cent in some cases) limiting the power of this study. When combined with complementary SZ selected cluster samples at higher masses, the data appear broadly consistent with the self-similar evolution of the low redshift scaling relations between intracluster medium properties and cluster mass, suggesting that properties such as the X-ray temperature, gas mass, and SZ signal remain reliable mass proxies even at high redshift.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".