SUNYAEV–ZEL’DOVICH CLUSTER PROFILES MEASURED WITH THE SOUTH POLE TELESCOPE
Bibliographic record
Abstract
ABSTRACT We present Sunyaev–Zel'dovich (SZ) measurements of 15 massive X-ray-selected galaxy clusters obtained with the South Pole Telescope (SPT). The SZ cluster signals are measured at 150 GHz, and concurrent 220 GHz data are used to reduce astrophysical contamination. Radial profiles are computed using a technique that takes into account the effects of the beams and filtering. In several clusters, significant SZ decrements are detected out to a substantial fraction of the virial radius. The profiles are fit to the β-model and to a generalized Navarro–Frenk–White (NFW) pressure profile, and are scaled and stacked to probe their average behavior. We find model parameters that are consistent with previous studies: β = 0.86 and r core/r 500 = 0.20 for the β-model, and (αn, βn, γn, c 500) = (1.0, 5.5, 0.5, 1.0) for the generalized NFW model. Both models fit the SPT data comparably well, and both are consistent with the average SZ profile out to beyond r 500. The integrated Compton-y parameter Y SZ is computed for each cluster using both model-dependent and model-independent techniques, and the results are compared to X-ray estimates of cluster parameters. We find that Y SZ scales with YX and gas mass with low scatter. Since these observables have been found to scale with total mass, our results point to a tight mass–observable relation for the SPT cluster survey.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".