Long Type I X-ray Bursts and Neutron Star Interior Physics
Bibliographic record
Abstract
Superbursts are very energetic Type I X-ray bursts discovered in recent years by long term monitoring of X-ray bursters, believed to be due to unstable ignition of carbon in the deep ocean of the neutron star. A number of "intermediate duration" bursts have also been observed, probably associated with ignition of a thick helium layer. We investigate the sensitivity of these long X-ray bursts to the thermal profile of the neutron star crust and core. We first compare cooling models of superburst lightcurves with observations, and derive constraints on the ignition mass and energy release, and then calculate ignition models for superbursts and pure helium bursts, and compare to observations. The superburst lightcurves and ignition models imply that the carbon mass fraction is approximately 20% or greater in the fuel layer, constraining models of carbon production. However, the most important result is that when Cooper pairing neutrino emission is included in the crust, the temperature is too low to support unstable carbon ignition at the observed column depths. Some additional heating mechanism is required in the accumulating fuel layer to explain the observed properties of superbursts. If Cooper pair emission is less efficient than currently thought, the observed ignition depths for superbursts imply that the crust is a poor conductor, and the core neutrino emission is not more efficient than modified URCA. The observed properties of helium bursts support these conclusions, requiring inefficient crust conductivity and core neutrino emission.
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 | 0.001 |
| 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 | 0.001 |
| 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".