Statistical Properties of Galactic Starlight Polarization
Bibliographic record
Abstract
We present a statistical analysis of Galactic interstellar polarization from the largest compilation available of starlight data. The data comprises ~ 9300 stars of which we have selected ~ 5500 for our analysis. We find a nearly linear growth of mean polarization degree with extinction. The amplitude of this correlation shows that interstellar grains are not fully aligned with the Galactic magnetic field, which can be interpreted as the effect of a large random component of the field. In agreement with earlier studies of more limited scope,we estimate the ratio of the uniform to the random plane-of-the-sky components of the magnetic field to be Bu/Br ~ 0.8. Moreover, a clear correlation exists between polarization degree and polarization angle what provides evidence that the magnetic field geometry follows Galactic structures on large-scales. The angular power spectrum C_l of the starlight polarization degree for Galactic plane data (|b| < 10 degrees) is consistent with a power-law, C_l ~ l^{-1.5} (where l ~ 180/\\theta degrees is the multipole order), for all angular scales \\theta > 10 arcmin. An investigation of sparse and inhomogeneous sampling of the data indicates that, in the entire range of scales probed, the starlight data analyzed traces an underlying continuum polarized emission in the visible with the same angular power spectrum. Our findings suggest that starlight data can be safely used for the modeling of Galactic polarized continuum emission at other wavelengths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".