Orbital analysis of small bodies in co-orbital motion with Jupiter through the torus structure
Bibliographic record
Abstract
ABSTRACT In this paper, based on the torus structure, we investigate the orbital characteristics of Jupiter Trojans and Jupiter-family comets (JFCs) in co-orbital motion with Jupiter. The motivation of this paper is to test whether the semi-analytical approach and conclusions of the torus structure proposed in the circular restricted three-body problem are still valid for real small bodies in the ephemeris model, and how long they follow the prediction of the semi-analytical approach. Based on the topological structure of the co-orbital motion in the torus space, we propose a method for estimating the libration amplitude for Trojans. 873 Jupiter Trojans with well-determined orbits are picked as examples to demonstrate the validity of our estimation method. Numerical analysis reveals that the difference between the osculating semimajor axes of the Trojan and Jupiter can influence the accuracy of our estimation method significantly. Based on the semi-analytical approach, we predict orbital behaviours of three JFCs, 85P/Boethin, P/2012 US27 (Siding Spring), and P/2019 A1 (PANSTARRS). Numerical integration in the ephemeris model indicates that their real orbital behaviours are consistent with our predictions. In particular, we find that the current quasi-satellite state of P/2012 US27 (Siding Spring) can remain for about 1.5 × 105 yr, much longer than those that correspond to other previously reported QS companions of Jupiter.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".