X-ray and Radio Monitoring of the Neutron Star Low Mass X-ray Binary 1A 1744-361: Quasi Periodic Oscillations, Transient Ejections, and a Disk Atmosphere
Bibliographic record
Abstract
We report on X-ray (NICER/NuSTAR/MAXI/Swift) and radio (MeerKAT) timing and spectroscopic analysis from a three-month monitoring campaign in 2022 of a high-intensity outburst of the dipping neutron star low-mass X-ray binary 1A 1744-361. The 0.5-6.8 keV NICER X-ray hardness-intensity and color-color diagrams of the observations throughout the outburst suggests that 1A 1744-361 spent most of its outburst in an atoll-state, but we show that the source exhibited Z-state-like properties at the peak of the outburst, similar to a small sample of other atoll-state sources. A timing analysis with NICER data revealed several instances of an $\approx8$ Hz quasi-periodic oscillation (QPO; fractional rms amplitudes of ~5%) around the peak of the outburst, the first from this source, which we connect to the normal branch QPOs (NBOs) seen in the Z-state. Our observations of 1A 1744-361 are fully consistent with the idea of the mass accretion rate being the main distinguishing parameter between atoll- and Z-states. Radio monitoring data by MeerKAT suggests that the source was at its radio-brightest during the outburst peak, and that the source transitioned from the 'island' spectral state to the 'banana' state within ~3 days of the outburst onset, launching transient jet ejecta. The observations present the strongest evidence for radio flaring, including jet ejecta, during the island-to-banana spectral state transition at low accretion rates (atoll-state). The source also exhibited Fe XXV, Fe XXVI K$α$, and K$β$ X-ray absorption lines, whose origins likely lie in an accretion disk atmosphere.
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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) | 0.000 | 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 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".