<i>Planck</i>early results. X. Statistical analysis of Sunyaev-Zeldovich scaling relations for X-ray galaxy clusters
Bibliographic record
Abstract
All-sky data from the Planck survey and the Meta-Catalogue of X-ray detected Clusters of galaxies (MCXC) are combined to investigate the relationship between the thermal Sunyaev-Zeldovich (SZ) signal and X-ray luminosity. The sample comprises ~1600 X-ray clusters with redshifts up to ~1 and spans a wide range in X-ray luminosity. The SZ signal is extracted for each object individually, and the statistical significance of the measurement is maximised by averaging the SZ signal in bins of X-ray luminosity, total mass, or redshift. The SZ signal is detected at very high significance over more than two decades in X-ray luminosity (1043ergs-1 ≲ L500E(z)−7/3 ≲ 2 × 1045ergs-1). The relation between intrinsic SZ signal and X-ray luminosity is investigated and the measured SZ signal is compared to values predicted from X-ray data. Planck measurements and X-ray based predictions are found to be in excellent agreement over the whole explored luminosity range. No significant deviation from standard evolution of the scaling relations is detected. For the first time the intrinsic scatter in the scaling relation between SZ signal and X-ray luminosity is measured and found to be consistent with the one in the luminosity – mass relation from X-ray studies. There is no evidence of any deficit in SZ signal strength in Planck data relative to expectations from the X-ray properties of clusters, underlining the robustness and consistency of our overall view of intra-cluster medium properties.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".