LoCuSS: A COMPARISON OF CLUSTER MASS MEASUREMENTS FROM<i>XMM-NEWTON</i>AND SUBARU—TESTING DEVIATION FROM HYDROSTATIC EQUILIBRIUM AND NON-THERMAL PRESSURE SUPPORT
Bibliographic record
Abstract
We compare X-ray hydrostatic and weak-lensing mass estimates for a sample of 12 clusters that have been observed with both XMM-Newton and Subaru. At an over-density of Δ = 500, we obtain 1 − M X / M WL = 0.01 ± 0.07 for the whole sample. We also divided the sample into undisturbed and disturbed sub-samples based on quantitative X-ray morphologies using asymmetry and fluctuation parameters, obtaining 1 − M X / M WL = 0.09 ± 0.06 and −0.06 ± 0.12 for the undisturbed and disturbed clusters, respectively. In addition to non-thermal pressure support, there may be a competing effect associated with adiabatic compression and/or shock heating which leads to overestimate of X-ray hydrostatic masses for disturbed clusters, for example, in the famous merging cluster A1914. Despite the modest statistical significance of the mass discrepancy, on average, in the undisturbed clusters, we detect a clear trend of improving agreement between M X and M WL as a function of increasing over-density, . We also examine the gas mass fractions, f gas = M gas / M WL , finding that they are an increasing function of cluster radius, with no dependence on dynamical state, in agreement with predictions from numerical simulations. Overall, our results demonstrate that XMM-Newton and Subaru are a powerful combination for calibrating systematic uncertainties in cluster mass measurements.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".