Constraining the equation of state in neutron-star cores via the long-ringdown signal
Bibliographic record
Abstract
Multimessenger signals from binary neutron star (BNS) mergers are promising tools to infer the properties of nuclear matter at densities inaccessible to laboratory experiments. Gravitational waves (GWs) from BNS merger remnants can constrain the neutron-star equation of state (EOS) complementing constraints from late inspiral, direct mass-radius measurements, and ab-initio calculations. We perform a series of general-relativistic simulations of BNS systems with EOSs constructed to comprehensively cover the high-density regime. We identify a tight correlation between the ratio of the energy and angular-momentum losses in the late-time portion of the post-merger signal, called the long ringdown, and the EOS at the highest pressures and densities in neutron-star cores. Applying this correlation to post-merger GW signals significantly reduces EOS uncertainty at densities several times the nuclear saturation density, where no direct constraints are currently available. Hence, the long ringdown can provide stringent constraints on material properties of neutron stars cores.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".