Search for a Black Hole Binary in Gaia DR3 Astrometric Binary Stars with Spectroscopic Data
Bibliographic record
Abstract
Abstract We report the discovery of a candidate binary system consisting of a black hole (BH) and a red giant branch star in Gaia DR3. This binary system was discovered from 64,108 binary solutions for which both astrometric and spectroscopic data are available. For this system, the astrometric and spectroscopic solutions are consistent with each other, making this system a confident candidate of a BH binary. The primary (visible) star in this system, Gaia DR3 5870569352746779008, is a red giant branch star whose mass is quite uncertain. Fortunately, despite the uncertainty of the primary’s mass, we can estimate the mass of the secondary (dark) object in this system to be >5.68 M ⊙ with a probability of 99%, based on the orbital parameters. The mass of the secondary object is much larger than the maximum neutron star mass (∼2.0 M ⊙ ), which indicates that the secondary object is likely a BH. We argue that, if this dark object is not a BH, this system must be a more exotic system, in which the primary red giant branch star orbits around a quadruple star system (or a higher-order multiple-star system) whose total mass is more than 5.68 M ⊙ . If this is a genuine BH binary, this has the longest period (1352.22 ± 45.81 days) among those discovered so far. As our conclusion entirely relies on Gaia DR3 data, independent confirmation with follow-up observations (e.g., long-term time-series spectra) is desired.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".