Leaky Dust Traps in Planet-embedded Protoplanetary Disks
Bibliographic record
Abstract
Abstract From the survival of dust disks for a few Myr to the establishment of chemical dichotomy, dust traps are expected to play a pivotal role in sculpting protoplanetary disks and the early planet formation process. These traps may not be perfect, as evidenced by both numerical simulations and the observations of disks with gaps and cavities, inside which we detect some amounts of both gas and dust. Using two-fluid hydrodynamic global simulations in both 2D and 3D, we directly compute the dynamics of dust grains as they aerodynamically interact with the disk gas that is being perturbed by an embedded planet. In both 2D and 3D, we find the dust trap to be more leaky for a lower-mass planet and for a more turbulent disk. More crucially, we find that the fraction of dust mass that remains trapped within the pressure bump can be up to an order of magnitude more reduced in 3D compared to 2D, with all else being equal. Our simulations show a complex behavior of dust radial motion that is both azimuthally and poloidally nonuniform, with the overall dynamics dominated by the dust coupling to the gas flow even for Stokes number 0.1. The leaky traps we find suggest that the pebble isolation mass is likely not truly isolating and that gap-opening planets do not establish an unconditional impermeable barrier. Our findings have implications for recent JWST MINDS results, which show that volatiles, including water, are present in the inner regions of disks hosting outer dust rings.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".