LoCuSS: Testing hydrostatic equilibrium in galaxy clusters
Bibliographic record
Abstract
Abstract We test the assumption of hydrostatic equilibrium in an X-ray luminosity selected sample of 50 galaxy clusters at 0.15 < z < 0.3 from the Local Cluster Substructure Survey (LoCuSS). Our weak-lensing measurements of M500 control systematic biases to sub-4 per cent, and our hydrostatic measurements of the same achieve excellent agreement between XMM–Newton and Chandra. The mean ratio of X-ray to lensing mass for these 50 clusters is $\mathrel {\beta _{\rm X}}\;= 0.95\pm 0.05$, and for the 44 clusters also detected by Planck, the mean ratio of Planck mass estimate to LoCuSS lensing mass is $\mathrel {\beta _{\rm P}}\;= 0.95\pm 0.04$. Based on a careful like-for-like analysis, we find that LoCuSS, the Canadian Cluster Comparison Project, and Weighing the Giants agree on $\mathrel {\beta _{\rm P}}\;\simeq 0.9{\rm -}0.95$ at 0.15 < z < 0.3. This small level of hydrostatic bias disagrees at ∼5σ with the level required to reconcile Planck cosmology results from the cosmic microwave background and galaxy cluster counts.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".