Dust Growth in ALMA Rings. II. Dusty Rossby Wave Instability
Bibliographic record
Abstract
Abstract Annular substructures serve as ideal venues for planetesimal formation. In this series, we investigate the linear stage of dust growth within rings. The first paper in this series examines the global streaming instability, while this study focuses on the dusty Rossby wave instability (DRWI). To this end, we perform a linear analysis of the two-fluid equations on a background pressure bump, representing annular substructures. The spectral code Dedalus is used to solve the linear eigenvalue problem. We identify two distinct DRWI modes: Type I, which originates from dust-modified gas RWI, and Type II, which results from dust-gas coupling. Type I and Type II modes never coexist for a given azimuthal wavenumber k y , but transition between each other as k y varies. Type I modes are driven by the advection of background vorticity, and Type II modes possess two waves: Rossby waves, driven by advection, and thin waves, driven by dust-gas drag. Finally, we assess the relevance of DRWI in Atacama Large Millimeter/submillimeter Array (ALMA) rings using DSHARP sources. Our findings suggest that Type I modes could explain the absence of azimuthal asymmetries in many ALMA disks, whereas Type II modes are entirely absent in all eight observed rings, implying that unresolved narrow rings or alternative mechanisms may play a role in dust growth within annular substructures.
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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 | 0.000 | 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) | 0.001 | 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".