FAINT X-RAY BINARIES AND THEIR OPTICAL COUNTERPARTS IN M31
Bibliographic record
Abstract
X-ray binaries (XRBs) are probes of both star formation and stellar mass, but more importantly remain one of the only direct tracers of the compact object population. To investigate the XRB population in M31, we utilized all 121 publicly available observations of M31 totalling over 1 Ms from Chandra's ACIS instrument. We studied 83 star clusters in the bulge using the year 1 star cluster catalogue from the Panchromatic Hubble Andromeda Treasury Survey. We found 15 unique star clusters that matched to 17 X-ray point sources within 1'' (3.8 pc). This population is composed predominantly of globular cluster low-mass XRBs, with one previously unidentified star cluster X-ray source. Star clusters that were brighter and more compact preferentially hosted an X-ray source. Specifically, logistic regression showed that the F475W magnitude was the most important predictor followed by the effective radius, while color (F475W−F814W) was not statistically significant. We also completed a matching analysis of 1566 H ii regions and found 10 unique matches to 9 X-ray point sources within 3'' (11 pc). The H ii regions hosting X-ray point sources were on average more compact than unmatched H ii regions, but logistic regression concluded that neither the radius nor Hα luminosity was a significant predictor. Four matches have no previous classification and thus are high-mass XRB candidates. A stacking analysis of both star clusters and H ii regions resulted in non-detections, giving typical upper limits of ≈10 32 erg s −1 , which probes the quiescent XRB regime.
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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 | 0.001 | 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".