The Soft X-ray Spectrum of the High Mass X-Ray Binary V0332+53 in Quiescence
Bibliographic record
Abstract
The propeller effect should cut off accretion in fast-spinning neutron star high mass X-ray binaries (HMXBs) at low mass transfer rates. However, accretion continues in some HMXBs at $L_{x} < 10^{34}$ erg s$^{-1}$, as evidenced by continuing pulsations. Indications of spectral softening in systems in the propeller regime suggest that some HMXBs are undergoing fundamental changes in their accretion regime. A 39 ks \textit{XMM-Newton} observation of the transient HMXB V0332+53 found it at a very low X-ray luminosity ($L_{x} \sim 4\times 10^{32}$ erg s${^{-1}}$). A power-law spectral fit requires an unusually soft spectral index ($4.4^{+0.9}_{-0.6}$), while a magnetized neutron star atmosphere model, with temperature \lt\ 6.7$\pm 0.2$ K and inferred emitting radius of $\sim0.2-0.3$ km, gives a good fit. We suggest that the quiescent X-ray emission from V0332+53 is mainly from a hot spot on the surface of the neutron star. We could not detect pulsations from V0332+53, due to the low count rate. Due to the high $N_H$, thermal emission from the rest of the neutron star could be only weakly constrained, to \lt\ $
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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 | 0.000 | 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) | 0.002 | 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".