JOINT ANALYSIS OF CLUSTER OBSERVATIONS. II. CHANDRA/XMM-NEWTON X-RAY AND WEAK LENSING SCALING RELATIONS FOR A SAMPLE OF 50 RICH CLUSTERS OF GALAXIES
Bibliographic record
Abstract
We present a study of multiwavelength X-ray and weak lensing scaling relations for a sample of 50 clusters of galaxies. Our analysis combines Chandra and XMM-Newton data using an energy-dependent cross-calibration. After considering a number of scaling relations, we find that gas mass is the most robust estimator of weak lensing mass, yielding 15% ± 6% intrinsic scatter at (the pseudo-pressure Y X yields a consistent scatter of 22% ± 5%). The scatter does not change when measured within a fixed physical radius of 1 Mpc. Clusters with small brightest cluster galaxy (BCG) to X-ray peak offsets constitute a very regular population whose members have the same gas mass fractions and whose even smaller (<10%) deviations from regularity can be ascribed to line of sight geometrical effects alone. Cool-core clusters, while a somewhat different population, also show the same (<10%) scatter in the gas mass–lensing mass relation. There is a good correlation and a hint of bimodality in the plane defined by BCG offset and central entropy (or central cooling time). The pseudo-pressure Y X does not discriminate between the more relaxed and less relaxed populations, making it perhaps the more even-handed mass proxy for surveys. Overall, hydrostatic masses underestimate weak lensing masses by 10% on the average at ; but cool-core clusters are consistent with no bias, while non-cool-core clusters have a large and constant 15%–20% bias between and , in agreement with N -body simulations incorporating unthermalized gas. For non-cool-core clusters, the bias correlates well with BCG ellipticity. We also examine centroid shift variance and power ratios to quantify substructure; these quantities do not correlate with residuals in the scaling relations. Individual clusters have for the most part forgotten the source of their departures from self-similarity.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".