Near-infrared counterparts of ultraluminous X-ray sources
Bibliographic record
Abstract
In this paper, we present the results of the first systematic search for counterparts to nearby ultraluminous X-ray sources (ULXs) in the near-infrared (NIR). We observed 62 ULXs in 37 galaxies within 10 Mpc and discovered 17 candidate NIR counterparts. The detection of 17 out of 62 ULX candidates points to intrinsic differences between systems that show and those that do not show infrared emission. For six counterparts, we conclude from the absolute magnitudes and – in some cases – additional information such as morphology and previously reported photometric or spectroscopic observations, that they are likely background active galactic nuclei or ULXs residing in star clusters. 11 counterparts have absolute magnitudes consistent with them being single red supergiant stars. Alternatively, these systems may have larger accretion discs that emit more NIR light than the systems that we do not detect. Other scenarios such as emission from a surrounding nebula or from a compact radio jet are also possible, although for Holmberg II X-1 the NIR luminosity far exceeds the expected jet contribution. The 11 possible red supergiant counterparts are excellent candidates for spectroscopic follow-up observations. This may enable us to measure the mass function in these systems if they are indeed red supergiant donor stars where we can observe absorption lines.
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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 | 0.001 | 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) | 0.002 | 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".