X-Ray Properties of SPT-selected Galaxy Clusters at 0.2 < z < 1.5 Observed with XMM-Newton
Bibliographic record
Abstract
Abstract We present measurements of the X-ray observables of the intracluster medium (ICM), including luminosity L X , ICM mass M ICM, emission-weighted mean temperature T X , and integrated pressure Y X , that are derived from XMM-Newton X-ray observations of a Sunyaev–Zel’dovich effect (SZE) selected sample of 59 galaxy clusters from the South Pole Telescope SPT-SZ survey that span the redshift range 0.20 < z < 1.5. We constrain the best-fit power-law scaling relations between X-ray observables, redshift, and halo mass. The halo masses are estimated based on previously published SZE observable-to-mass scaling relations, calibrated using information that includes the halo mass function. Employing SZE-based masses in this sample enables us to constrain these scaling relations for massive galaxy clusters (M 500 ≥ 3 × 1014 M ⊙) to the highest redshifts where these clusters exist without concern for X-ray selection biases. We find that the mass trends are steeper than self-similarity in all cases, and with ≥2.5σ significance in the case of L X and M ICM. The redshift trends are consistent with the self-similar expectation, but the uncertainties remain large. Core-included scaling relations tend to have steeper mass trends for L X . There is no convincing evidence for a redshift-dependent mass trend in any observable. The constraints on the amplitudes of the fitted scaling relations are currently limited by the systematic uncertainties on the SZE-based halo masses, but the redshift and mass trends are limited by the X-ray sample size and the measurement uncertainties of the X-ray observables.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".