A RADIO-SELECTED BLACK HOLE X-RAY BINARY CANDIDATE IN THE MILKY WAY GLOBULAR CLUSTER M62
Bibliographic record
Abstract
We report the discovery of a candidate stellar-mass black hole in the Milky Way globular cluster M62. We detected the black hole candidate, which we call M62-VLA1, in the core of the cluster using deep radio continuum imaging from the Karl G. Jansky Very Large Array. M62-VLA1 is a faint source with a flux density of 18.7 ± 1.9 μJy at 6.2 GHz and a flat radio spectrum (α = −0.24 ± 0.42, for S ν = ν α ). M62 is the second Milky Way cluster with a candidate stellar-mass black hole; unlike the two candidate black holes previously found in the cluster M22, M62-VLA1 is associated with a Chandra X-ray source, supporting its identification as a black hole X-ray binary. Measurements of its radio and X-ray luminosity, while not simultaneous, place M62-VLA1 squarely on the well-established radio–X-ray correlation for stellar-mass black holes. In archival Hubble Space Telescope imaging, M62-VLA1 is coincident with a star near the lower red giant branch. This possible optical counterpart shows a blue excess, Hα emission, and optical variability. The radio, X-ray, and optical properties of M62-VLA1 are very similar to those for V404 Cyg, one of the best-studied quiescent stellar-mass black holes. We cannot yet rule out alternative scenarios for the radio source, such as a flaring neutron star or background galaxy; future observations are necessary to determine whether M62-VLA1 is indeed an accreting stellar-mass black hole.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".