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Record W4393924702 · doi:10.3847/2041-8213/ad7e1f

Monster Shocks, Gamma-Ray Bursts, and Black Hole Quasi-normal Modes from Neutron-star Collapse

2024· preprint· en· W4393924702 on OpenAlexafffund
Elias R. Most, Andrei M. Beloborodov, Bart Ripperda

Bibliographic record

VenueThe Astrophysical Journal Letters · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of TorontoPerimeter Institute
FundersOffice of Advanced CyberinfrastructureNatural Sciences and Engineering Research Council of CanadaNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Centre for Supercomputing ApplicationsSimons FoundationNational Science Foundation
KeywordsNeutron starAstrophysicsPhysicsMonsterBlack hole (networking)Star (game theory)AstronomyGamma-ray burstComputer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract We perform the first magnetohydrodynamic simulation tracking the magnetosphere of a collapsing magnetar. The collapse is expected for massive rotating magnetars formed in merger events and may occur many hours after the merger. Our simulation suggests a novel mechanism for a gamma-ray burst (GRB), which is uncollimated and forms a delayed high-energy counterpart of the merger gravitational waves. The simulation shows that the collapse launches an outgoing magnetospheric shock, and a hot magnetized outflow forms behind the shock. The outflow is baryon free and uncollimated, and its power peaks on a millisecond timescale. Then, the outflow becomes modulated by the ring-down of the nascent black hole, imprinting its kilohertz quasi-normal modes on the GRB tail.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.010
GPT teacher head0.222
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2024
Admission routes2
Has abstractyes

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