Impact of the Collision Model on the Multi-messenger Emission from Gamma-Ray Burst Internal Shocks
Bibliographic record
Abstract
Abstract We discuss the production of multiple astrophysical messengers (neutrinos, cosmic rays, gamma-rays) in the Gamma-Ray Burst (GRB) internal shock scenario, focusing on the impact of the collision dynamics between two shells on the fireball evolution. In addition to the inelastic case, in which plasma shells merge when they collide, we study the Ultra Efficient Shock scenario, in which a fraction of the internal energy is re-converted into kinetic energy and, consequently, the two shells survive and remain in the system. We find that in all cases, a quasi-diffuse neutrino flux from GRBs at the level of 10−11– (per flavor) is expected for protons and a baryonic loading of 10, which is potentially within the reach of IceCube-Gen2. The highest impact of the collision model for multi-messenger production is observed for the Ultra Efficient Shock scenario, that promises high conversion efficiencies from kinetic to radiated energy. However, the assumption that the plasma shells separate after a collision and survive as separate shells within the fireball is found to be justified too rarely in a multicollision model that uses hydrodynamical simulations with the PLUTO code for individual shell collisions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".