MUSTANG HIGH ANGULAR RESOLUTION SUNYAEV-ZEL'DOVICH EFFECT IMAGING OF SUBSTRUCTURE IN FOUR GALAXY CLUSTERS
Bibliographic record
Abstract
We present resolved images of four massive clusters of galaxies through the Sunyaev–Zel'dovich effect (SZE). These measurements, made at 90 GHz with the MUSTANG receiver on the Green Bank Telescope (GBT), reveal pressure substructure to the intracluster medium (ICM) in three of the four systems. The SZE and X-ray morphology of MACS0744.8+3927 are suggestive of the presence of a weak shock outside the cluster core. By fitting the Rankine–Hugoniot density jump conditions in a complementary SZE/X-ray analysis, we asses the feasibility of this interpretation. We conclude that a weak shock with a Mach number of and a shock velocity of 1827 +267 − 195 km s −1 adequately describes the observed phenomenology. Deeper Chandra data are needed for confirmation. In RXJ1347.5−1145, we present a new reduction of previously reported data and confirm the presence of a southeast SZE enhancement with a significance of 13.9σ when smoothed to 18'' resolution. This too is likely caused by shock-heated gas produced in a recent merger. In our highest redshift system, CL1226.9+3332, we detect substructure at a peak significance of 4.6σ in the form of a ridge oriented orthogonally to the vector connecting the main mass peak and a subclump revealed by weak lensing. We also conclude that the gas distribution is elongated in a southwest direction, consistent with a previously proposed merger scenario. The SZE image of the cool core cluster A1835 is, in contrast, consistent with azimuthally symmetric signal only. This pilot study demonstrates the potential of high-resolution SZE images to complement X-ray data and probe the dynamics of galaxy clusters.
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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 | 0.001 |
| 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".