The <i>XMM</i>-LSS survey: the Class 1 cluster sample over the initial 5 deg2 and its cosmological modelling
Bibliographic record
Abstract
Abstract We present a sample of 29 galaxy clusters from the XMM-LSS survey over an area of some 5 deg2 out to a redshift of z= 1.05. The sample clusters, which represent about half of the X-ray clusters identified in the region, follow well-defined X-ray selection criteria and are all spectroscopically confirmed. For all clusters, we provide X-ray luminosities and temperatures as well as masses, obtained from dedicated spatial and spectral fitting. The cluster distribution peaks around z= 0.3 and T= 1.5 keV, half of the objects being groups with a temperature below 2 keV. Our LX–T(z) relation points towards self-similar evolution, but does not exclude other physically plausible models. Assuming that cluster scaling laws follow self-similar evolution, our number density estimates up to z= 1 are compatible with the predictions of the concordance cosmology and with the findings of previous ROSAT surveys. Our well-monitored selection function allowed us to demonstrate that the inclusion of selection effects is essential for the correct determination of the evolution of the LX–T relation, which may explain the contradictory results from previous studies. Extensive simulations show that extending the survey area to 10 deg2 has the potential to exclude the non-evolution hypothesis, but those constraints on more refined intracluster medium models will probably be limited by the large intrinsic dispersion of the LX–T relation, whatever be the sample size. We further demonstrate that increasing the dispersion in the scaling laws increases the number of detectable clusters, hence generating further degeneracy [in addition to σ8, Ωm, LX–T(z)] in the cosmological interpretation of the cluster number counts. We provide useful empirical formulae for the cluster mass–flux and mass–count rate relations as well as a comparison between the XMM-LSS mass sensitivity and that of forthcoming Sunyaev–Zel'dovich surveys.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".