Light scalars in neutron star mergers
Bibliographic record
Abstract
Abstract Due to their unique set of multimessenger signals, neutron star mergers have emerged as a novel environment for studies of new physics beyond the Standard Model (SM). As a case study, we consider the simplest extension of the SM scalar sector involving a light CP-even scalar singlet S mixing with the SM Higgs boson. These S particles can be produced abundantly in neutron star mergers via the nucleon bremsstrahlung process. We show that the S particles may either be trapped in or stream freely out of the merger remnant, depending on the S mass, its mixing with the SM Higgs boson, and the temperature and baryon density in the merger. In the free-streaming region, the scalar S will provide an extra channel to cool down the merger remnant, with cooling timescales as small as 𝒪(ms). On the other hand, in the trapped region, the Bose gas of S particles could contribute a larger thermal conductivity than the trapped neutrinos in some parts of the parameter space, thus leading to faster thermal equilibration than expected. Therefore, future observations of the early postmerger phase of a neutron star merger could effectively probe a unique range of the S parameter space, largely complementary to the existing and future laboratory and supernova limits. In view of these results, we hope the merger simulation community will be motivated to implement the effects of light CP-even scalars into their simulations in both the free-streaming and trapped regimes.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".