Testing jet geometries and disc–jet coupling in the neutron star LMXB 4U 0614 + 091 with the internal shocks model
Bibliographic record
Abstract
ABSTRACT Multiwavelength spectral energy distributions of low-mass X-ray binaries (LMXBs) in the hard state are determined by the emission from a jet, for frequencies up to mid-infrared, and emission from the accretion flow in the optical to X-ray range. In the last years, the flat radio-to-mid-IR spectra of black hole (BH) X-ray binaries was described using the internal shocks model, which assumes that the fluctuations in the velocity of the ejecta along the jet are driven by the fluctuations in the accretion flow, described by the X-ray power density spectrum (PDS). In this work, we attempt to apply this model for the first time to a neutron star (NS) LMXB, i.e. 4U 0614 + 091. We used the multiwavelength data set obtained in 2006, comprising data from radio to X-ray, and applied a model that includes an irradiated disc model for the accretion flow and an updated version of the internal shocks code for the ejection. The new version of the code allows to change the geometry of the jet for the case of non-conical jets. Only two alternative scenarios provide a satisfactory description of the data: using the X-ray PDS but in a non-conical geometry for the jet, or either using a conical geometry but with a ‘flicker-noise’ PDS. Both scenarios would imply some differences with the results obtained with similar models on BH X-ray binaries, shedding light on the possibility that jets in NS and BH binaries might somehow have a different geometry or a different coupling with the accretion flow.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".