Weak lensing analysis of SZ-selected clusters of galaxies from the SPT and Planck surveys
Bibliographic record
Abstract
We present the weak lensing analysis of the Wide-Field Imager Sunyaev–Zel'dovich Cluster of Galaxy (WISCy) sample, a set of 12 clusters of galaxies selected for their Sunyaev–Zel'dovich (SZ) effect. After developing new and improved methods for background selection and determination of geometric lensing scaling factors from absolute multiband photometry in cluster fields, we compare the weak lensing mass estimate with public X-ray and SZ data. We find consistency with hydrostatic X-ray masses with no significant bias, no mass dependent bias and less than 20 per cent intrinsic scatter and constrain |$f_{\rm{gas},500c}=0.128^{+0.029}_{-0.023}$|. We independently calibrate the South Pole Telescope significance–mass relation and find consistency with previous results. The comparison of weak lensing mass and Planck Compton parameters, whether extracted self-consistently with a mass–observable relation (MOR) or using X-ray prior information on cluster size, shows significant discrepancies. The deviations from the MOR strongly correlate with cluster mass and redshift. This could be explained either by a significantly shallower than expected slope of Compton decrement versus mass and a corresponding problem in the previous X-ray based mass calibration, or a size or redshift dependent bias in SZ signal extraction.
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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 | 0.001 | 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".