Weighing the Darkness: Astrometric Mass Measurement of Hidden Stellar Companions Using Gaia
Bibliographic record
Abstract
Abstract In astrometric binaries, the presence of a dark, unseen star can be inferred from the gravitational pull it induces on its luminous binary companion. While the orbit of such binaries can be characterized with precise astrometric measurements, constraints made from astrometry alone are not enough to measure the component masses. In this work, we determine the precision with which Gaia can astrometrically measure the orbits and—with additional observations—the component masses, for luminous stars hosting hidden companions. Using realistic mock Gaia observations, we find that Gaia can precisely measure the orbits of binaries hosting hidden brown dwarfs out to tens of parsecs and hidden white dwarf and neutron star companions at distances as far as several hundred parsecs. Heavier black hole companions may be measured out to 1 kpc or farther. We further determine how orbital period affects this precision, finding that Gaia can characterize orbits with periods as short as 10 days and as long as a few 103 days, with the best measured orbits having periods just short of Gaia’s mission lifetime. Extending Gaia’s nominal five-year mission lifetime by an additional five years not only allows for the measurement of longer period orbits, but those longer period binaries can be seen at even greater distances.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".