Searching for compact hierarchical triple system candidates in astrometric binaries and accelerated solutions
Bibliographic record
Abstract
Context. Compact hierarchical triple (CHT) systems, where a tertiary component orbits an inner binary, provide critical insights into stellar formation and evolution. Despite their importance, the detection of such systems, especially compact ones, remains challenging due to the complexity of their orbital dynamics and the limitations of traditional observational methods. Aims. This study aims to identify new CHT star systems among Gaia astrometric binaries and accelerated solutions by analysing the radial velocity (RV) amplitude of these systems, thereby improving our understanding of stellar hierarchies. Methods. We selected a sample of bright astrometric binaries and accelerated solutions from the Gaia DR3 Non-Single Stars catalogue. The RV peak-to-peak amplitude was used as an estimator, and we applied a new method to detect potential triple systems by comparing the RV-based semi-amplitude with the astrometric semi-amplitude. We used available binary and triple star catalogues to identify and validate candidates, with a subset confirmed through further examination of the RV and astrometric data. Results. Our analysis resulted in the discovery of 956 CHT candidates among the orbital sources as well as another 3115 probable close binary sources in stars with accelerated solutions. Exploring the inclination, orbital period, and eccentricity of the outer companion in these CHT systems provides strong evidence of mutual orbit alignment, as well as a preference towards moderate outer eccentricities. Conclusions. Our novel approach has proven effective in identifying potential triple systems, thereby increasing their number in the catalogues. Our findings emphasise the importance of combined astrometric and RV data analysis in the study of multiple star systems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".