The First High-contrast Images of X-Ray Binaries: Detection of Candidate Companions in the γ Cas Analog RX J1744.7-2713
Bibliographic record
Abstract
X-ray binaries provide exceptional laboratories for understanding the physics of matter under the most extreme conditions. Until recently, there were few, if any, observational constraints on the circumbinary environments of X-ray binaries at ∼100–5000 au scales. It remains unclear how the accretion onto the compact objects or the explosions giving rise to the compact objects interact with their immediate surroundings. Here, we present the first high-contrast adaptive optics images of X-ray binaries. These observations target all X-ray binaries within ∼3 kpc accessible with the Keck/NIRC2 vortex coronagraph. This paper focuses on one of the first key results from this campaign; our images reveal the presence of 21 sources potentially associated with the γ Cassiopeiae analog high-mass X-ray binary RX J1744.7−2713. By conducting different analyses—a preliminary proper motion analysis, a color–magnitude diagram, and a probability of chance alignment calculation—we found that three of these 21 sources have a high probability of being bound to the system. If confirmed, they would be in wide orbits (∼450 to 2500 au). While follow-up astrometric observations will be needed in ∼5–10 yr to confirm further the bound nature of these detections, these discoveries emphasize that such observations may provide a major breakthrough in the field. In fact, they would be useful not only for our understanding of stellar multiplicity, but also for our understanding of how planets, brown dwarfs, and stars can form even in the most extreme environments.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".