Gamma-ray burst engine activity within the quark nova scenario: prompt emission, X-ray plateau and sharp drop-off
Bibliographic record
Abstract
Extending the three-stage model for long GRB inner engines suggested by Staff, Ouyed & Bagchi, we interpret recent Swift satellite observations of early X-ray afterglow plateaus followed by a sharp drop-off or a shallow power-law decay. The three stages involve a neutron star phase, a quark star (QS) and a black hole phase. We find that the QS stage allows for more energy to be extracted from neutron star to QS conversion as well as from ensuing accretion on to the QS. The QS accretion phase naturally extends the engine activity and can account for both the prompt emission and irregular early X-ray afterglow activity. Following the accretion phase, the QS can spin down by emission of a baryon-free outflow. The magnetar-like magnetic field strengths resulting from the NS to QS transition provide enough spin-down energy, for the correct amount of time, to account for the plateau in the X-ray afterglow. In our model, a sharp drop-off following the plateau occurs when the QS collapses to a BH during the spin-down, thus shutting off the secondary outflow. We applied our model to GRB 070110 and GRB 060607A and found that we can consistently account for the energetics and duration during the prompt and plateau phases.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".