The 2020 superburst of 4U 1608–522 and its impact on the accretion disc
Bibliographic record
Abstract
ABSTRACT Superbursts are rare events observed from bursting neutron star low-mass X-ray binaries. They are thought to originate from unstable burning of the thick layer of Carbon on the surface of the neutron star, causing the observed X-ray flashes to last several hours. Given their fluence it has long been thought that superbursts may have significant effects on the accretion flow around the neutron star. In this paper, we first present evidence for a new superburst observed from 4U 1608–522 by Monitor of All-sky X-ray Image (MAXI) during the 2020 outburst, around 00:45 utc on 2020 July 16. We compare some of the properties of this superburst and the underlying outburst with the events recorded on 2005 May 5 by Rossi X-ray Timing Explorer (RXTE) and most recently in 2025 by MAXI. We then present our spectral analysis of Neutron star Interior Composition Explorer (NICER) and Insight–HXMT data obtained before and after the 2020 superburst event. Our results indicate that the inner disc temperature and the radius show a systematic evolution in the following few days, which may be related to the superburst. We show that the time-scale of the observed evolution can not be governed by viscous time-scales unless the viscosity parameter is unrealistically low.
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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 | 0.000 | 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".