Different Accretion Heating of the Neutron Star Crust during Multiple Outbursts in MAXI J0556–332
Bibliographic record
Abstract
Abstract The transient neutron star (NS) low-mass X-ray binary MAXI J0556−332 provides a rare opportunity to study NS crust heating and subsequent cooling for multiple outbursts of the same source. We examine MAXI, Swift, Chandra, and XMM-Newton data of MAXI J0556−332 obtained during and after three accretion outbursts of different durations and brightnesses. We report on new data obtained after outburst III. The source has been tracked up to ∼1800 days after the end of outburst I. Outburst I heated the crust strongly, but no significant reheating was observed during outburst II. Cooling from ∼333 eV to ∼146 eV was observed during the first ∼1200 days. Outburst III reheated the crust up to ∼167 eV, after which the crust cooled again to ∼131 eV in ∼350 days. We model the thermal evolution of the crust and find that this source required a different strength and depth of shallow heating during each of the three outbursts. The shallow heating released during outburst I was ∼17 MeV nucleon−1 and outburst III required ∼0.3 MeV nucleon−1. These cooling observations could not be explained without shallow heating. The shallow heating for outburst II was not well constrained and could vary from ∼0 to 2.2 MeV nucleon−1, i.e., this outburst could in principle be explained without invoking shallow heating. We discuss the nature of the shallow heating and why it may occur at different strengths and depths during different outbursts.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".