GRAIN ALIGNMENT IN OMC1 AS DEDUCED FROM OBSERVED LARGE CIRCULAR POLARIZATION
Bibliographic record
Abstract
The properties of polarization in scattered light by aligned ellipsoidal grains are investigated with the Fredholm integral equation method and the T-matrix method, and the results are applied to the observed circular polarization in OMC1. We assume that the grains are composed of silicates and are ellipsoidal (oblate, prolate, or triaxial ellipsoid) in shape with a typical axial ratio of 2:1. The angular dependence of circular polarization p c on directions of incident and scattered light is investigated with spherical harmonics and associated Legendre polynomials. The degree of circular polarization p c also depends on the Rayleigh reduction factor R , which is a measure of imperfect alignment. We find that p c is approximately proportional to R for grains with | m | x eq ≲ 3 − 5, where x eq is the dimensionless size parameter and m is the refractive index of the grain. Models that include those grains can explain the observed large circular polarization in the near-infrared, ≈15%, in the southeast region of the BN object in OMC1, if the directions of incidence and scattering of light is optimal, and if grain alignment is strong, i.e., R ≳ 0.5. Such a strong alignment cannot be explained by the Davis–Greenstein mechanism; we prefer instead an alternative mechanism driven by radiative torques. If the grains are mixed with silicates and ice, the degree of circular polarization p c decreases in the 3 μm ice feature, while that of linear polarization increases. This wavelength dependence is different from that predicted in a process of dichroic extinction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".