High-mass X-ray binaries in nearby metal-poor galaxies: on the contribution to nebular He <scp>ii</scp> emission
Bibliographic record
Abstract
ABSTRACT Despite significant progress both observationally and theoretically, the origin of high-ionization nebular He ii emission in galaxies dominated by stellar photoionization remains unclear. Accretion-powered radiation from high-mass X-ray binaries (HMXBs) is still one of the leading proposed explanations for the missing He+-ionizing photons, but this scenario has yet to be conclusively tested. In this paper, we present nebular line predictions from a grid of photoionization models with input spectral energy distributions containing the joint contribution of both stellar atmospheres and a multicolour disc model for HMXBs. This grid demonstrates that HMXBs are inefficient producers of the photons necessary to power He ii, and can only boost this line substantially in galaxies with HMXB populations large enough to power X-ray luminosities of 1042 erg s−1 per unit star formation rate (SFR). To test this, we assemble a sample of 11 low-redshift star-forming galaxies with high-quality constraints on both X-ray emission from Chandra and He ii emission from deep optical spectra, including new observations with the MMT. These data reveal that the HMXB populations of these nearby systems are insufficient to account for the observed He ii strengths, with typical X-ray luminosities or upper limits thereon of only 1040–1041 erg s−1 per SFR. This indicates that HMXBs are not the dominant source of He+ ionization in these metal-poor star-forming galaxies. We suggest that the solution may instead reside in revisions to stellar wind predictions, softer X-ray sources, or very hot products of binary evolution at low metallicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".