Cold Gas and Star Formation in the Phoenix Cluster with JWST
Bibliographic record
Abstract
Abstract We present integral field unit observations of the Phoenix Cluster with the JWST Mid-infrared Instrument’s Medium Resolution Spectrometer. We focus this study on the molecular gas, dust, and star formation in the brightest cluster galaxy (BCG). We use precise spectral modeling to produce maps of the silicate dust, molecular gas, and polycyclic aromatic hydrocarbons (PAHs) in the inner ∼50 kpc of the cluster. We measure the optical depth from silicates by comparing the observed H2 line ratios to those predicted by excitation models. We provide updated measurements of the total molecular gas mass of 1 . 9 − 0.4 + 0.5 × 1 0 10 M ⊙, which agrees with CO-based estimates, providing an estimate of the CO-to-H2 conversion factor of α CO = 0.8 ± 0.2 M ⊙ pc − 2 ( K km s − 1 ) − 1 ; an updated stellar mass of M * = 2.6 ± 0.5 × 1010 M ⊙ ; and star formation rates (SFRs) averaged over 10 and 100 Myr of 〈SFR〉10 = 1340 ± 100 M ⊙ yr−1 and 〈SFR〉100 = 740 ± 80 M ⊙ yr−1, respectively. The H2 emission seems to be powered predominantly by shocks and star formation within the central ∼20 kpc, induced by stellar feedback and radio jets from the active galactic nucleus. Additionally, we find nearly an order-of-magnitude drop in the SFRs estimated by PAH fluxes in cool core BCGs compared to field galaxies, suggesting that hot particles from the intracluster medium are destroying PAH grains even in the central-most tens of kiloparsecs.
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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 | 0.000 | 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) | 0.002 | 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".