Cluster Cosmology Constraints from the 2500 deg<sup>2</sup> SPT-SZ Survey: Inclusion of Weak Gravitational Lensing Data from Magellan and the Hubble Space Telescope
Bibliographic record
Abstract
Abstract We derive cosmological constraints using a galaxy cluster sample selected from the 2500 deg 2 SPT-SZ survey. The sample spans the redshift range 0.25 < z < 1.75 and contains 343 clusters with SZ detection significance ξ > 5. The sample is supplemented with optical weak gravitational lensing measurements of 32 clusters with 0.29 < z < 1.13 (from Magellan and Hubble Space Telescope ) and X-ray measurements of 89 clusters with 0.25 < z < 1.75 (from Chandra ). We rely on minimal modeling assumptions: (i) weak lensing provides an accurate means of measuring halo masses, (ii) the mean SZ and X-ray observables are related to the true halo mass through power-law relations in mass and dimensionless Hubble parameter E ( z ) with a priori unknown parameters, and (iii) there is (correlated, lognormal) intrinsic scatter and measurement noise relating these observables to their mean relations. We simultaneously fit for these astrophysical modeling parameters and for cosmology. Assuming a flat ν ΛCDM model, in which the sum of neutrino masses is a free parameter, we measure Ω m = 0.276 ± 0.047, σ 8 = 0.781 ± 0.037, and σ 8 (Ω m /0.3) 0.2 = 0.766 ±0.025. The redshift evolutions of the X-ray Y X –mass and M gas –mass relations are both consistent with self-similar evolution to within 1 σ . The mass slope of the Y X –mass relation shows a 2.3 σ deviation from self-similarity. Similarly, the mass slope of the M gas –mass relation is steeper than self-similarity at the 2.5 σ level. In a νw CDM cosmology, we measure the dark energy equation-of-state parameter w = −1.55 ± 0.41 from the cluster data. We perform a measurement of the growth of structure since redshift z ∼ 1.7 and find no evidence for tension with the prediction from general relativity. This is the first analysis of the SPT cluster sample that uses direct weak-lensing mass calibration and is a step toward using the much larger weak-lensing data set from DES. We provide updated redshift and mass estimates for the SPT sample.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".