The Far-infrared Polarization Spectrum of <i>ρ</i> Ophiuchi A from HAWC+/SOFIA Observations
Bibliographic record
Abstract
We report on polarimetric maps made with HAWC + /SOFIA toward ρ Oph A, the densest portion of the ρ Ophiuchi molecular complex. We employed HAWC + bands C (89 μ m) and D (154 μ m). The slope of the polarization spectrum was investigated by defining the quantity , where p C and p D represent polarization degrees in bands C and D , respectively. We find a clear correlation between and the molecular hydrogen column density across the cloud. A positive slope ( > 1) dominates the lower-density and well-illuminated portions of the cloud, which are heated by the high-mass star Oph S1, whereas a transition to a negative slope ( < 1) is observed toward the denser and less evenly illuminated cloud core. We interpret the trends as due to a combination of (1) warm grains at the cloud outskirts, which are efficiently aligned by the abundant exposure to radiation from Oph S1, as proposed in the radiative torques theory; and (2) cold grains deep in the cloud core, which are poorly aligned owing to shielding from external radiation. To assess this interpretation, we developed a very simple toy model using a spherically symmetric cloud core based on Herschel data and verified that the predicted variation of is consistent with the observations. This result introduces a new method that can be used to probe the grain alignment efficiency in molecular clouds, based on the analysis of trends in the far-infrared polarization spectrum.
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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 | 0.000 |
| 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".