THE ATACAMA COSMOLOGY TELESCOPE: DYNAMICAL MASSES AND SCALING RELATIONS FOR A SAMPLE OF MASSIVE SUNYAEV-ZEL'DOVICH EFFECT SELECTED GALAXY CLUSTERS $^,$
Bibliographic record
Abstract
We present the first dynamical mass estimates and scaling relations for a sample of Sunyaev–Zel'dovich effect (SZE) selected galaxy clusters. The sample consists of 16 massive clusters detected with the Atacama Cosmology Telescope (ACT) over a 455 deg 2 area of the southern sky. Deep multi-object spectroscopic observations were taken to secure intermediate-resolution ( R ∼ 700–800) spectra and redshifts for ≈60 member galaxies on average per cluster. The dynamical masses M 200 c of the clusters have been calculated using simulation-based scaling relations between velocity dispersion and mass. The sample has a median redshift z = 0.50 and a median mass with a lower limit , consistent with the expectations for the ACT southern sky survey. These masses are compared to the ACT SZE properties of the sample, specifically, the match-filtered central SZE amplitude , the central Compton parameter y 0 , and the integrated Compton signal Y 200 c , which we use to derive SZE–mass scaling relations. All SZE estimators correlate with dynamical mass with low intrinsic scatter (≲ 20%), in agreement with numerical simulations. We explore the effects of various systematic effects on these scaling relations, including the correlation between observables and the influence of dynamically disturbed clusters. Using the three-dimensional information available, we divide the sample into relaxed and disturbed clusters and find that ∼50% of the clusters are disturbed. There are hints that disturbed systems might bias the scaling relations, but given the current sample sizes, these differences are not significant; further studies including more clusters are required to assess the impact of these clusters on the scaling relations.
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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 | 0.002 |
| 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 | 0.000 |
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".