Pressure Profiles and Mass Estimates Using High-resolution Sunyaev–Zel’dovich Effect Observations of Zwicky 3146 with MUSTANG-2
Bibliographic record
Abstract
Abstract The galaxy cluster Zwicky 3146 is a sloshing cool core cluster at z = 0.291 that in X-ray imaging does not appear to exhibit significant pressure substructure in the intracluster medium (ICM). The published M 500 values range between to (22.50 ± 7.58) × 1014 M ⊙, where ICM-based estimates with reported errors <20% suggest that we should expect to find a mass between M ⊙ (from Planck, with an 8.4σ detection) and M ⊙ (from ACT, with a 14σ detection). We investigate the ability to estimate the mass of Zwicky 3146 via the Sunyaev–Zel’dovich (SZ) effect with data taken at 90 GHz by MUSTANG-2 to a noise level better than 15 μK at the center and a cluster detection of 61σ. We derive a pressure profile from our SZ data, which is in excellent agreement with that derived from X-ray data. From our SZ-derived pressure profiles, we infer M 500 and M 2500 via three methods—Y–M scaling relations, the virial theorem, and hydrostatic equilibrium (HE)—where we employ X-ray constraints from XMM-Newton on the electron density profile when assuming HE. Depending on the model and estimation method, our M 500 estimates range from 6.13 ± 0.69 to (10.6 ± 2.0) × 1014 M ⊙, where our estimate from HE is (±27% stat) (±7.9% sys, calibration) × 1014 M ⊙. Our fiducial mass, derived from a Y–M relation is (±7.9% stat) (±5.4% sys, Y–M) (±6.9% sys, cal.) × 1014 M ⊙.
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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 | 0.001 |
| 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".