Active gas features in three HSC-SSP CAMIRA clusters revealed by high angular resolution analysis of MUSTANG-2 SZE and XXL X-ray observations
Bibliographic record
Abstract
ABSTRACT We present results from simultaneous modelling of high angular resolution GBT/MUSTANG-2 90 GHz Sunyaev–Zel’dovich effect (SZE) measurements and XMM-XXL X-ray images of three rich galaxy clusters selected from the HSC-SSP Survey. The combination of high angular resolution SZE and X-ray imaging enables a spatially resolved multicomponent analysis, which is crucial to understand complex distributions of cluster gas properties. The targeted clusters have similar optical richnesses and redshifts, but exhibit different dynamical states in their member galaxy distributions: a single-peaked cluster, a double-peaked cluster, and a cluster belonging to a supercluster. A large-scale residual pattern in both regular Compton-parameter y and X-ray surface brightness distributions is found in the single-peaked cluster, indicating a sloshing mode. The double-peaked cluster shows an X-ray remnant cool core between two SZE peaks associated with galaxy concentrations. The temperatures of the two peaks reach ∼20–30 keV in contrast to the cool core component of ∼2 keV, indicating a violent merger. The main SZE signal for the supercluster is elongated along a direction perpendicular to the major axis of the X-ray core, suggesting a minor merger before core passage. The SX and y distributions are thus perturbed at some level, regardless of the optical properties. We find that the integrated Compton y parameter and the temperature for the major merger are boosted from those expected by the weak-lensing mass and those for the other two clusters show no significant deviations, which is consistent with predictions of numerical simulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".