A STRONG SHALLOW HEAT SOURCE IN THE ACCRETING NEUTRON STAR MAXI J0556-332
Bibliographic record
Abstract
An accretion outburst in an X-ray transient deposits material onto the neutron star primary; this accumulation of matter induces reactions in the neutron star's crust. During the accretion outburst these reactions heat the crust out of thermal equilibrium with the core. When accretion halts, the crust cools to its long-term equilibrium temperature on observable timescales. Here we examine the accreting neutron star transient MAXI J0556-332, which is the hottest transient, at the start of quiescence, observed to date. Models of the quiescent light curve require a large deposition of heat in the shallow outer crust from an unknown source. The additional heat injected is ≈4–10 MeV per accreted nucleon; when the observed decline in accretion rate at the end of the outburst is accounted for, the required heating increases to ≈6–16 MeV. This shallow heating is still required to fit the light curve even after taking into account a second accretion episode, uncertainties in distance, and different surface gravities. The amount of shallow heating is larger than that inferred for other neutron star transients and is larger than can be supplied by nuclear reactions or compositionally driven convection; but it is consistent with stored mechanical energy in the accretion disk. The high crust temperature ( ) makes its cooling behavior in quiescence largely independent of the crust composition and envelope properties, so that future observations will probe the gravity of the source. Fits to the light curve disfavor the presence of Urca cooling pairs in the crust.
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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) | 0.001 | 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".