Surviving the heat: multiwavelength analysis of V883 Ori reveals that dust aggregates survive the sublimation of their ice mantles
Bibliographic record
Abstract
ABSTRACT Investigating the response of icy dust aggregates to water ice sublimation is essential for understanding the formation and properties of planetesimals in protoplanetary discs. However, their fate remains unclear, as previous studies suggest that aggregates could either survive or completely fall apart to (sub)μm-sized grains. Protoplanetary discs around stars undergoing accretion outbursts represent a unique laboratory to study the ice sublimation process, as the water snowline is pushed outward to regions accessible to current observatories. In this work, we aim to understand the aggregates’ response to ice sublimation by focusing on V883 Ori, a system currently undergoing a powerful accretion outburst. We present new analysis of archival high-resolution ALMA observations of the protoplanetary disc of V883 Ori at 0.88, 1.3, 2.0, and 3.1 mm, and derive new radial spectral index profiles, which we compare with predictions from one-dimensional dust evolution simulations. In the region of V883 Ori where water ice has sublimated, we find lower spectral indices than previously obtained, indicating the presence of cm-sized particles. Coupled with our dust evolution models, we find that the only way to explain their presence is to assume that they formed before the outburst and survived the sublimation process. The resilience of dust aggregates to such intense events leads us to speculate that it may extend to other environments with more gentle heating, such as pebbles drifting through the water snowline in quiescent protoplanetary discs. In that case, it may alter the formation pathway of dry planetesimals interior to the snowline.
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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) | 0.000 | 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".