Gravity-dominated Collisions: A Model for the Largest Remnant Masses with Treatment for “Hit and Run” and Density Stratification
Bibliographic record
Abstract
Abstract We develop empirical relationships for the accretion and erosion of colliding gravity-dominated bodies of various compositions under conditions expected in late-stage solar system formation. These are fast, easily coded relationships based on a large database of smoothed particle hydrodynamics (SPH) simulations of collisions between bodies of different compositions, including those that are water rich. The accuracy of these relations is also comparable to the deviations of results between different SPH codes and initial thermal/rotational conditions. We illustrate the paucity of disruptive collisions between major bodies, as compared to collisions between less massive planetesimals in late-stage planet formation, and thus focus on more probable, low-velocity collisions, though our relations remain relevant to disruptive collisions as well. We also pay particular attention to the transition zone between merging collisions and those where the impactor does not merge with the target, but continues downrange, a “hit-and-run” collision. We find that hit-and-run collisions likely occur more often in density-stratified bodies and across a wider range of impact angles than suggested by the most commonly used analytic approximation. We also identify a possible transitional zone in gravity-dominated collisions where larger bodies may undergo more disruptive collisions when the impact velocity exceeds the sound speed, though understanding this transition warrants further study. Our results are contrary to the commonly assumed invariance of total mass (scale), density structure, and material composition on the largest remnants of giant impacts. We provide an algorithm for adopting our model into N-body planet formation simulations, so that the mass of growing planets and debris can be tracked.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".