Nuclear burning in collapsar accretion discs
Bibliographic record
Abstract
ABSTRACT The core collapse of massive, rapidly-rotating stars are thought to be the progenitors of long-duration gamma-ray bursts (GRB) and their associated hyperenergetic supernovae (SNe). At early times after the collapse, relatively low angular momentum material from the infalling stellar envelope will circularize into an accretion disc located just outside the black hole horizon, resulting in high accretion rates necessary to power a GRB jet. Temperatures in the disc mid-plane at these small radii are sufficiently high to dissociate nuclei, while outflows from the disc can be neutron-rich and may synthesize r-process nuclei. However, at later times, and for high progenitor angular momentum, the outer layers of the stellar envelope can circularize at larger radii ≳ 107 cm, where nuclear reactions can take place in the disc mid-plane (e.g. 4He + 16O → 20Ne + γ). Here we explore the effects of nuclear burning on collapsar accretion discs and their outflows by means of hydrodynamical α-viscosity torus simulations coupled to a 19-isotope nuclear reaction network, which are designed to mimic the late infall epochs in collapsar evolution when the viscous time of the torus has become comparable to the envelope fall-back time. Our results address several key questions, such as the conditions for quiescent burning and accretion versus detonation and the generation of 56Ni in disc outflows, which we show could contribute significantly to powering GRB SNe. Being located in the slowest, innermost layers of the ejecta, the latter could provide the radioactive heating source necessary to make the spectral signatures of r-process elements visible in late-time GRB-SNe spectra.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".