Radiative Torques on Interstellar Grains. III. Dynamics with Thermal Relaxation
Bibliographic record
Abstract
In the previous papers in this series, we found that radiative torques can play a major role in the alignment of grains with the interstellar magnetic field. Since the radiative torques can drive the grains to suprathermal rotational speeds, in previous work we made the simplifying assumption that the grain principal axis of greatest moment of inertia is always parallel to the grain angular momentum. This enabled us to describe many of the features of the grain dynamics. However, this assumption fails when the grains enter periods of thermal rotation, which occur naturally in the radiative torque alignment scenario. In the present paper we relax this assumption and explore the consequences for the grain dynamics. We develop a treatment to follow the grain dynamics, including thermal fluctuations and "thermal flipping," and show results for one illustrative example. By comparing with a treatment without thermal fluctuations, we see that inclusion of thermal fluctuations can lead to qualitative changes in the grain dynamics. In future installments in this series, we will use the more complete dynamical treatment developed here to perform a systematic study of grain alignment by radiative torques and test the model against observations of starlight polarization and polarized thermal emission from dust.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".