On the importance of disc chemistry in the formation of protoplanetary disc rings
Bibliographic record
Abstract
ABSTRACT Radial substructures have now been observed in a wide range of protoplanetary discs (PPDs), from young to old systems; however, their formation is still an area of vigorous debate. Recent magnetohydrodynamic (MHD) simulations have shown that rings and gaps can form naturally in PPDs when non-ideal MHD effects are included. However, these simulations employ ad hoc approximations to the magnitudes of the magnetic diffusivities in order to facilitate ring growth. We replace the parametrization of these terms with a simple chemical network and grain distribution model to calculate the non-ideal effects in a more self-consistent way. We use a range of grain distributions to simulate grain formation for different disc conditions. Including ambipolar diffusion, we find that large grain populations (>1 $\mu$m), and those including a population of very small polyaromatic hydrocarbons (PAHs) facilitate the growth of periodic, stable rings, while intermediate-sized grains suppress ring formation. Including Ohmic diffusion removes the positive influence of PAHs, with only large grain populations still producing periodic ring and gap structures. These results relate closely to the degree of coupling between the magnetic field and the neutral disc material, quantified by the non-dimensional Elsasser number Λ (the ratio of magnetic forces to Coriolis force). For both the ambipolar-only and ambipolar-ohmic cases, if the total Elsasser number is initially of the order of unity along the disc mid-plane, ring and gap structures may develop.
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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 | 0.000 | 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".