Comprehensive Radio Monitoring of the Black Hole X-Ray Binary Swift J1727.8−1613 during Its 2023–2024 Outburst
Bibliographic record
Abstract
Abstract This work presents comprehensive multifrequency radio monitoring of the black hole low-mass X-ray binary (LMXB) Swift J1727.8−1613, which underwent its first recorded outburst after its discovery in 2023 August. Through a considerable community effort, we have coalesced the data from multiple, distinct observing programs; the light curves include ∼10 months and 197 epochs of monitoring from seven radio facilities with observing frequencies ranging from (approximately) 0.3–230 GHz. The primary purpose of this work is to provide the broader astronomical community with these light curves to assist with the interpretation of other observing campaigns, particularly nonradio observing frequencies. We discuss the phenomenological evolution of the source, which included (i) multiple radio flares consistent with the launching of discrete jet ejections, the brightest of which reached ∼1 Jy; (ii) temporally evolving radio spectral indices ( α ), reaching values steeper than expected for optically thin synchrotron emission ( α < −1) and emission with significant radiative cooling ( α < −1.5). We have published a digital copy of the data and intend for this work to set a precedent for the community to continue releasing comprehensive radio light curves of future LMXB outbursts.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".