Observing Planet-driven Dust Spirals with ALMA
Bibliographic record
Abstract
Abstract Atacama Large Millimeter/submillimeter Array (ALMA) continuum observations of thermal emission from the dust component of protoplanetary disks have revealed an abundance of substructures that may be interpreted as evidence for embedded planets, but planet-driven spiral arms—perhaps one of the most compelling lines of evidence—have proven comparatively elusive. In this work, we test the capabilities of ALMA to detect the planet-driven spiral signal in continuum emission. Carrying out hydrodynamic simulations and radiative transfer calculations, we present synthetic Band 7 continuum images for a wide range of disk and observing conditions. We show that thermal mass planets at tens of astronomical units typically drive spirals detectable within a few hours of integration time, and the detectable planet mass may be as low as ∼Neptune mass (0.3 M th). The grains probed by ALMA form spirals morphologically identical to the underlying gas spiral. The temperature of the dust spiral is crucial in determining its contrast, and spirals are easier to detect in disks with an adiabatic equation of state and longer cooling times. Resolving the spiral is not necessary for its detection; with the help of residual maps, the optimal beam size is a few times the spiral width at a constant noise level. Finally, we show how the presence of gaps and rings can impair our ability to recognize colocated spirals. Our work demonstrates the planet-finding potential of the current design specification of ALMA, and suggests that observing capability is not the bottleneck in searching for spirals induced by thermal mass planets.
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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 | 0.000 | 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".