High-resolution calculations of merging neutron stars - II. Neutrino emission
Bibliographic record
Abstract
The remnant resulting from the merger of two neutron stars produces neutrinos in copious amounts. In this paper we present the neutrino emission results obtained via Newtonian, high-resolution simulations of the coalescence event. These simulations use three-dimensional smoothed particle hydrodynamics together with a nuclear, temperature-dependent equation of state and a multiflavour neutrino leakage scheme. We present the details of our scheme, discuss the neutrino emission results from a neutron star coalescence and compare them with the core-collapse supernova case where neutrino emission has been studied for several decades. The average neutrino energies are similar to those in the supernova case, but contrary to the latter, the luminosities are dominated by electron-type antineutrinos that are produced in the hot, neutron-rich, thick disc of the merger remnant. The cooler parts of this disc contain substantial fractions of heavy nuclei, which, however, do not influence the overall neutrino emission results significantly. Our total neutrino luminosities from the merger event are considerably lower than those found in previous investigations. This imposes constraints on the ability of neutron star mergers to produce a gamma-ray burst via neutrino annihilation. The neutrinos are emitted preferentially along the initial binary rotation axis, an event seen ‘pole-on’ would appear much brighter in neutrinos than a similar event seen ‘edge-on’.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".