Ultra–High‐Energy Cosmic Rays from Hypothetical Quark Novae
Bibliographic record
Abstract
We explore the acceleration of ions in the quark nova (QN) scenario, in which a neutron star experiences an explosive phase transition into a quark star (born in the propeller regime). In this picture, two cosmic-ray components are isolated: one related to the randomized pulsar wind and the other to the propelled wind, both boosted by the ultrarelativistic QN shock. The latter component acquires energies 10 15 eV < E < 10 18 eV, while the former, boosted pulsar wind, achieves ultrahigh energies E > 10 18.6 eV. The composition is dominated by ions present in the pulsar wind in the energy range above 10 18.6 eV, while at energies below 10 18 eV the propelled ejecta, consisting of the fallback neutron star crust material from the explosion, is the dominant one. Added to these two components, the propeller injects relativistic particles with Lorentz factors Γ prop ~ 1-1000, later to be accelerated by galactic supernova shocks. The QN model appears to be able to account for the extragalactic cosmic rays above the ankle shown in the figure in this paper and to contribute a few percent of the galactic cosmic rays below the ankle. We predict a few hundred ultra-high-energy cosmic-ray events above 10 19 eV for the Pierre Auger detector per distant QN, while some thousands are predicted for the proposed Extreme Universe Space Observatory (EUSO) and Orbiting Wide-angle Light collectors ( OWL ) detectors.
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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) | 0.000 | 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".