On the stability and collisions in triple stellar systems
Bibliographic record
Abstract
A significant fraction of main-sequence (MS) stars are part of a triple system. We study the long-term stability and dynamical outcomes of triple stellar systems using a large number of long-term direct N-body integrations with relativistic precession. We find that the previously proposed stability criteria by Eggleton & Kiseleva and Mardling & Aarseth predict the stability against ejections reasonably well for a wide range of parameters. Assuming that the triple stellar systems follow orbital and mass distributions from FGK binary stars in the field, we find that ∼ 1 per cent and ∼ 0.5 per cent of the triple systems lead to a direct head-on collision (impact velocity ∼ escape velocity) between MS stars and between a MS star and a stellar-mass compact object, respectively. We conclude that triple interactions are the dominant channel for direct collisions involving a MS star in the field with a rate of one event every ∼100 years in the Milky Way. We estimate that the fraction of triple systems that form short-period binaries is up to ∼ 23 per cent with only up to ∼ 13 per cent being the result of three-body interactions with tidal dissipation, which is consistent with previous work using a secular code.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".