The Influence of Central Body Tides on Catastrophic Disruptions of Close-in Planetary Satellites
Bibliographic record
Abstract
We model the outcomes of catastrophic disruptions on small, gravity-dominated natural satellites, accounting for the tidal potential of the central body, which is neglected in classical disruption scaling laws. We introduce the concept of $Q^\star_\text{TD}$, the specific energy required to disperse half of the total mass involved in a collision, accounting for the tidal potential of a central body. We derive a simple scaling relation for $Q^\star_\text{TD}$ and demonstrate that for close-in planetary or asteroidal satellites, the tides from the central body can significantly reduce their catastrophic disruption threshold. We show that many satellites in the Solar System are in such a regime, where their disruption threshold should be much lower than that predicted by classical scaling laws which neglect tidal effects. Some notable examples include Mars' Phobos, Jupiter's Metis and Adrastea, Saturn's ring moons, Uranus' Ophelia, and Neptune's Naiad and Thalassa, among others. We argue that traditional impact scaling laws should be modified to account for tides when modeling the formation and evolution of these close-in satellites. Our derivation for $Q^\star_\text{TD}$ can easily be used in existing $N$-body and collisional evolution codes.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".