The peculiar hard state behaviour of the black hole X-ray binary Swift J1727.8−1613
Bibliographic record
Abstract
ABSTRACT Tracking the correlation between radio and X-ray luminosities during black hole X-ray binary outbursts is a key diagnostic of the coupling between accretion inflows (traced by X-rays) and relativistic jet outflows (traced by radio). We present the radio–X-ray correlation of the black hole low-mass X-ray binary Swift J1727.8–1613 during its 2023–2024 outburst. Our observations span a broad dynamic range, covering $\sim$4 orders of magnitude in radio luminosity and $\sim$6.5 in X-ray luminosity. This source follows an unusually radio-quiet track, exhibiting significantly lower radio luminosities at a given X-ray luminosity than both the standard (radio-loud) track and most previously known radio-quiet systems. Across most of the considered distance range ($D\, {\sim }\, 1.5$–4.3 kpc), Swift J1727.8–1613 appears to be the most radio-quiet black hole binary identified to date. For distances ${\ge }\, 4$ kpc, while Swift J1727 becomes comparable to one other extremely radio-quiet system, its peak X-ray luminosity (${\gtrsim }\, 5{\times }10^{38}$ erg s$^{-1}$) exceeds that of any previously reported hard-state black hole low-mass X-ray binary, emphasizing the extremity of this outburst. Additionally, for the first time in a radio-quiet system, we identify the onset of X-ray spectral softening to coincide with a change in trajectory through the radio–X-ray plane. We assess several proposed explanations for radio-quiet behaviour in black hole systems in light of this data set. As with other such sources, however, no single mechanism fully accounts for the observed properties, highlighting the importance of regular monitoring and the value of comprehensive (quasi-)simultaneous data-sets.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".