Constraints on the Galactic centre environment from <i>Gaia</i> hypervelocity stars III: insights on a possible companion to Sgr A*
Bibliographic record
Abstract
ABSTRACT We consider a scenario in which Sgr A* is in a massive black hole binary (MBHB) with an as-of-yet undetected supermassive or intermediate-mass black hole companion. Dynamical encounters between this MBHB and single stars in its immediate vicinity would eject hypervelocity stars (HVSs) with velocities beyond the Galactic escape velocity of the Galaxy. In this work, we use existing HVS observations to constrain for the first time the existence of a companion to Sgr A*. We simulate the ejection of HVSs via the ‘MBHB slingshot’ scenario and show that the population of HVSs detectable today depends strongly on the companion mass and the separation of the MBHB. We demonstrate that the lack of uncontroversial HVS candidates in Gaia Data Release 3 places a firm upper limit on the mass of a possible Sgr A* companion. Within one milliparsec of Sgr A*, our results exclude a companion more massive than $2000 \, \mathrm{M_\odot }$. If Sgr A* recently merged with a companion black hole, our findings indicate that unless this companion was less massive than $500 \, \mathrm{M_\odot }$, this merger must have occurred at least 10 Myr ago. These results complement and improve upon existing independent constraints on a companion to Sgr A* and show that large regions of its parameter space can now be ruled out.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".