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Record W4416101272 · doi:10.48550/arxiv.2507.06298

Bouncing Grains Keep Protoplanetary Disks Bright

2025· preprint· en· W4416101272 on OpenAlexaff
Yansong Qian, Yanqin Wu

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsPlanetesimalStreaming instabilityPlanetInstabilityGrain sizeInterpretation (philosophy)Circumstellar disk

Abstract

fetched live from OpenAlex

Proto-planetary disks display the so-called size-luminosity relation, where their mm-wavelength fluxes scale linearly with their emitting areas. This suggests that these disks are optically thick in mm-band, an interpretation further supported by their near-black-body spectral indexes. Such characteristics are seen not only among disks in very young star-forming regions like Lupus (1-3 Myrs), but, as we demonstrate here, also among disks in the much older Upper Scorpius region (5-11 Myrs). How can disks shine brightly for so long, when grain growth and subsequent radial drift should have quickly depleted their solid reservoir? Here, we suggest that the "bouncing barrier" provides the answer. Even colliding at very low speeds (below 1cm/s), grains already fail to stick to each other but instead bounce off in-elastically. This barrier stalls grain growth at a near-universal size of 100 micron. These small grains experience much reduced radial drift, and so are able to keep the disks bright for millions of years. They are also tightly coupled to gas, offering poor prospects for processes like streaming instability or pebble accretion. We speculate briefly on how planetesimals can arise in such a bath of 100-micron grains.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.027
GPT teacher head0.265
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueArXiv.orgSame topicAstrophysics and Star Formation StudiesFrench-language works237,207