Computing the Polarimetric and Photometric Variability of Be Stars
Bibliographic record
Abstract
Abstract We investigate variations in the linear polarization as well as in theV-band andB-band color–magnitudes for classical Be star disks. We present two models: disks with enhanced disk density and disks that are tilted or warped from the stellar equatorial plane. In both cases, we predict variation in observable properties of the system as the disk rotates. We use a non-LTE radiative transfer codebedisk(Sigut & Jones) in combination with a Monte Carlo routine that includes multiple scattering (Halonen et al.) to model classical Be star systems. We find that a disk with an enhanced density region that is one order of magnitude denser than the disk’s base density shows as much as variability in the polarization while the polarization position angle varies by . The ΔVmagnitude for the same system shows variations of up to mag while the Δ(B–V) color varies by at most mag. We find that disks tilted from the equatorial plane at small angles of more strongly reflect the values of polarization and color–magnitudes reported in the literature than disks tilted at larger angles. For this model, the linear polarization varies by , the polarization position angle varies by , the ΔVmagnitude varies up to 0.35 mag, and the Δ(B–V) color varies by up to 0.1 mag. We find that the enhanced disk density models show ranges of polarization and color–magnitudes that are commensurate with what is reported in the literature for all sizes of the density-enhanced regions. From this, we cannot determine any preference for small or large density-enhanced regions.
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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 | 0.002 |
| 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 | 0.001 | 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".