From Engine to Afterglow: Collapsars Naturally Produce Top-Heavy Jets\n and Early-Time Plateaus in Gamma Ray Burst Afterglows
Bibliographic record
Abstract
We demonstrate that the steep decay and long plateau in the early phases of\ngamma ray burst (GRB) X-ray afterglows are naturally produced in the collapsar\nmodel, by a means ultimately related to the dynamics of relativistic jet\npropagation through a massive star. We present two-dimensional axisymmetric\nhydrodynamical simulations which start from a collapsar engine and evolve all\nthe way through the late afterglow phase. The resultant outflow includes a jet\ncore which is highly relativistic after breaking out of the star, but becomes\nbaryon-loaded after colliding with a massive outer shell, corresponding to mass\nfrom the stellar atmosphere of the progenitor star which became trapped in\nfront of the jet core at breakout. The prompt emission produced before or\nduring this collision would then have the signature of a high Lorentz factor\njet, but the afterglow is produced by the amalgamated post-collision ejecta\nwhich has more inertia than the original highly relativistic jet core and thus\nhas a delayed deceleration. This naturally explains the early light curve\nbehavior discovered by Swift, including a steep decay and a long plateau,\nwithout invoking late-time energy injection from the central engine. The\nnumerical simulation is performed continuously from engine to afterglow,\ncovering a dynamic range of over ten orders of magnitude in radius. Light\ncurves calculated from the numerical output demonstrate that this mechanism\nreproduces basic features seen in early afterglow data. Initial steep decays\nare produced by internal shocks, and the plateau corresponds to the coasting\nphase of the outflow.\n
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".