Tests of the nuclear equation of state and superfluid and superconducting gaps using the Cassiopeia A neutron star
Bibliographic record
Abstract
The observed rapid cooling of the Cassiopeia A neutron star can be interpreted as being caused by neutron and proton transitions from normal to superfluid and superconducting states in the stellar core. Here we present two new Chandra ACIS-S Graded observations of this neutron star and measurements of the neutron star mass $M$ and radius $R$ found from consistent fitting of both the x-ray spectra and cooling behavior. This comparison is only possible for individual nuclear equations of state. We test phenomenological superfluid and superconducting gap models which mimic many of the known theoretical models against the cooling behavior. Our best-fit solution to the Cassiopeia A data is one in which the $(M,R)=(1.44\phantom{\rule{0.16em}{0ex}}{M}_{\mathrm{Sun}},12.6\phantom{\rule{4.pt}{0ex}}\text{km})$ neutron star is built with the BSk21 equation of state, strong proton superconductor and moderate neutron triplet superfluid gap models, and a pure iron envelope or a thin carbon layer on top of an iron envelope, although there are still large observational and theoretical uncertainties.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".