A new radio census of neutron star X-ray binaries
Bibliographic record
Abstract
ABSTRACT We report new radio observations of a sample of 36 neutron star (NS) X-ray binaries, more than doubling the sample in the literature observed at current-day sensitivities. These sources include 13 weakly magnetized (B < 1010 G) and 23 strongly magnetized (B ≥ 1010 G) NSs. 16 of the latter category reside in high-mass X-ray binaries, of which only two systems were radio-detected previously. We detect four weakly and nine strongly magnetized NSs; the latter are systematically radio fainter than the former and do not exceed LR ≈ 3 × 1028 erg s−1. In turn, we confirm the earlier finding that the weakly magnetized NSs are typically radio fainter than accreting stellar-mass black holes. While an unambiguous identification of the origin of radio emission in high-mass X-ray binaries is challenging, we find that in all but two detected sources (Vela X-1 and 4U 1700-37) the radio emission appears more likely attributable to a jet than the donor star wind. The strongly magnetized NS sample does not reveal a global correlation between X-ray and radio luminosity, which may be a result of sensitivity limits. Furthermore, we discuss the effect of NS spin and magnetic field on radio luminosity and jet power in our sample. No current model can account for all observed properties, necessitating the development and refinement of NS jet models to include magnetic field strengths up to 1013 G. Finally, we discuss jet quenching in soft states of NS low-mass X-ray binaries, the radio non-detections of all observed very-faint X-ray binaries in our sample, and future radio campaigns of accreting NSs.
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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 | 0.002 | 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".