The Magnetic Keys to Massive Star Formation: The Western $η$ Carinae Giant Molecular Cloud
Bibliographic record
Abstract
We present SOFIA/HAWC+ continuum polarisation data on the magnetic fields threading 17 pc-scale massive molecular clumps at the western end of the $η$ Car GMC (Region 9 of CHaMP, representing all stages of star formation from pre-stellar to dispersing via feedback), revealing important details about the field morphology and role in the gas structures of this clump sample. We performed Davis-Chandrasekhar-Fermi and Histogram of Relative Orientation analyses tracing column densities 25.0 $<$ log($N$/m$^{-2}$) $<$ 27.2. With HRO, magnetic fields change from mostly parallel to column density structures to mostly perpendicular at a threshold $N_{\rm crit}$ = (3.7$\pm$0.6)$\times$10$^{26}$ m$^{-2}$, indicating that gravitational forces exceed magnetic forces above this value. The same analysis in 10 individual clumps gives similar results, with the same clear trend in field alignments and a threshold $N_{\rm crit}$ = (1.9$^{+1.5}_{-0.8}$)$\times$10$^{26}$ m$^{-2}$. In the other 7 clumps, the alignment trend with $N$ is much flatter or even reversed, inconsistent with the usual HRO pattern. Instead, these clumps' fields reflect external environmental forces, such as from the nearby HII region NGC 3324. DCF analysis reveals field strengths somewhat higher than typical of nearby clouds, with the $Bn$ data lying mostly above the Crutcher (2012) relation. The mass:flux ratio $λ$ across all clumps has a gaussian distribution, with log$λ_{\rm DCF}$ = -0.75$\pm$0.45 (mean$\pmσ$): only small areas are dominated by gravity. However, a significant trend of rising log$λ$ with falling $T_{\rm dust}$ parallels Pitts et al's (2019) result: $T_{\rm dust}$ falls as $N_{\rm H_2}$ rises towards clump centres. Thus, in this massive clump sample, magnetic fields provide enough support against gravity to explain their overall low star formation rate.
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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 | 0.000 |
| 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".