The Temporal Requirements of Directly Observing Self-gravitating Spiral Waves in Protoplanetary Disks with ALMA
Bibliographic record
Abstract
Abstract We investigate how the detectability of signatures of self-gravity in a protoplanetary disk depends on its temporal evolution. We run a one-dimensional model for secular timescales to follow the disk mass as a function of time. We then combine this with three-dimensional global hydrodynamics simulations that employ a hybrid radiative transfer method to approximate realistic heating and cooling. We simulate ALMA continuum observations of these systems and find that structures induced by the gravitational instability (GI) are readily detectable when q = M disk/M * ≳ 0.25 and R outer ≲ 100 au. The high accretion rate generated by gravito-turbulence in such a massive disk drains its mass to below the detection threshold in ∼104 years, or approximately 1% of the typical disk lifetime. Therefore, disks with spiral arms detected in ALMA dust observations, if generated by self-gravity, must either be still receiving infall to maintain a high q value, or have just emerged from their natal envelope. Detection of substructure in systems with lower q is possible, but would require a specialist integration with the most extended configuration over several days. This disfavors the possibility of GI-caused spiral structure in systems with q < 0.25 being detected in relatively short integration times, such as those found in the DSHARP ALMA survey. We find no temporal dependence of detectability on dynamical timescales.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".