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Record W2898683405 · doi:10.3847/1538-4357/ab3426

Pulsational Pair-instability Supernovae in Very Close Binaries

2019· article· en· W2898683405 on OpenAlexfundno aff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsnot available
FundersAstrophysics DivisionEuropean CommissionNederlandse Organisatie voor Wetenschappelijk OnderzoekCanadian Institute for Advanced ResearchNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsRoche lobeSupernovaBinary numberBinary black holeBinary starStarsHeliumStellar evolutionNeutron star

Abstract

fetched live from OpenAlex

Abstract Pair-instability and pulsational pair-instability supernovae (PPISNe) have not been unambiguously observed so far. They are, however, promising candidates for the progenitors of the heaviest binary black hole (BBH) mergers detected. If these BBHs are the product of binary evolution, then PPISNe could occur in very close binaries. Motivated by this, we discuss the implications of a PPISN happening with a close binary companion and what impact these events have on the formation of merging BBHs through binary evolution. For this, we have computed a set of models of metal-poor ( Z ⊙ /10) single helium stars using the MESA software instrument. For PPISN progenitors with pre-pulse masses >50 M ⊙ we find that, after a pulse, heat deposited throughout the layers of the star that remain bound causes it to expand to more than 100 R ⊙ for periods of 10 2 –10 4 yr depending on the mass of the progenitor. This results in long-lived phases of Roche lobe overflow or even common-envelope events if there is a close binary companion, leading to additional electromagnetic transients associated with PPISN eruptions. If we ignore the effect of these interactions, we find that mass loss from PPISNe reduces the final BH spin by ∼30%, induces eccentricities below the threshold of detectability of the LISA observatory, and can produce a double-peaked distribution of measured chirp masses in BBH mergers observed by ground-based detectors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.225
Teacher spread0.215 · 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 teacher head, not a consensus.

Study designObservational
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

Citations200
Published2019
Admission routes1
Has abstractyes

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