Constraints on axion-like particles and nucleon pairing in dense matter from the hot neutron star in HESS J1731-347
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
If the thermal evolution of the hot young neutron star in the supernova remnant HESS J1731-347 is driven by neutrino emission, it provides a stringent constraint on the coupling of light (mass $\ensuremath{\ll}10\phantom{\rule{0.28em}{0ex}}\mathrm{keV}$) axion-like particles to neutrons. Using Markov-Chain Monte Carlo we find that for the values of axion-neutron coupling ${g}_{ann}^{2}>7.7\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}20}$ (90% c.l.) the axion cooling from the bremsstrahlung reaction $n+n\ensuremath{\rightarrow}n+n+a$ is too rapid to account for the high observed surface temperature. This implies that the Pecci-Quinn scale or axion decay constant ${f}_{a}>6.7\ifmmode\times\else\texttimes\fi{}{10}^{7}\phantom{\rule{0.28em}{0ex}}\mathrm{GeV}$ for KSVZ axions and ${f}_{a}>1.7\ifmmode\times\else\texttimes\fi{}{10}^{9}\phantom{\rule{0.28em}{0ex}}\mathrm{GeV}$ for DFSZ axions. The high temperature of this neutron star also allows us to tighten constraints on the size of the nucleon pairing gaps.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it