Late-time Cooling of Neutron Star Transients and the Physics of the Inner Crust
Bibliographic record
Abstract
Abstract An accretion outburst onto a neutron star transient heats the neutron star’s crust out of thermal equilibrium with the core. After the outburst, the crust thermally relaxes toward equilibrium with the neutron star core, and the surface thermal emission powers the quiescent X-ray light curve. Crust cooling models predict that thermal equilibrium of the crust will be established into quiescence. Recent observations of the cooling neutron star transient MXB 1659-29, however, suggest that the crust did not reach thermal equilibrium with the core on the predicted timescale and continued to cool after into quiescence. Because the quiescent light curve reveals successively deeper layers of the crust, the observed late-time cooling of MXB 1659-29 depends on the thermal transport in the inner crust. In particular, the observed late-time cooling is consistent with a low thermal conductivity layer near the depth predicted for nuclear pasta that maintains a temperature gradient between the neutron star’s inner crust and core for thousands of days into quiescence. As a result, the temperature near the crust–core boundary remains above the critical temperature for neutron superfluidity, and a layer of normal neutrons forms in the inner crust. We find that the late-time cooling of MXB 1659-29 is consistent with heat release from a normal neutron layer near the crust–core boundary with a long thermal time. We also investigate the effect of inner crust physics on the predicted cooling curves of the accreting transient KS 1731-260 and the magnetar SGR 1627-41.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".