Capturing an Asteroid via Triangular Libration Points
Bibliographic record
Abstract
This paper develops a new asteroid capture mechanism via triangular libration points based on their stable structure and chaotic motion nearby. Different from collinear libration points, the triangular libration points are linearly stable surrounded by long- and short-period orbit families in the planar case. First, their dynamical structure is explored by the Lie series method and an analytical approximation of long-period orbits is proposed. Then, massive escaping trajectories from the parking orbits are generated by a chaotic-assisted method on the finite time Lyapunov exponent map. The trajectories from the asteroid’s natural orbit to the Earth–moon system are constructed by modified Lambert transfers. Next, the fuel consumption for all potential near-Earth asteroids is evaluated ergodically in both perihelion and aphelion cases based on their initial condition, which guides the selection of the target. Finally, it is applied to 20 asteroids, and the minimum fuel consumption appears capturing asteroid 2015DU. Furthermore, a postcapture maneuver strategy based on a Poincaré section is proposed using long-period orbits to adjust the parking orbits and to satisfy the mission requirements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".