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Record W1710783611 · doi:10.1103/physrevd.91.124021

Post-merger evolution of a neutron star-black hole binary with neutrino transport

2015· article· en· W1710783611 on OpenAlexafffund
François Foucart, Evan O’Connor, Luke F. Roberts, Matthew Duez, Roland Haas, Christian D. Ott, Harald Pfeiffer, Mark Scheel, Béla Szilágyi

Bibliographic record

VenuePhysical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Advanced ResearchCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersFonds de recherche du Québec – Nature et technologiesSmithsonian Astrophysical ObservatoryUniversité de MontréalSpace Telescope Science InstituteMinistère de l'Économie, de l’Innovation et des Exportations du QuébecNational Aeronautics and Space AdministrationCanada Foundation for InnovationNational Science FoundationCompute CanadaSherman Fairchild FoundationMcGill UniversityCalifornia Institute of TechnologyNatural Sciences and Engineering Research Council of CanadaSmithsonian Institution
KeywordsPhysicsNeutron starNeutrinoAstrophysicsBlack hole (networking)NucleosynthesisStellar black holeNuclear physicsGalaxySupernova

Abstract

fetched live from OpenAlex

We present a first simulation of the post-merger evolution of a black hole-neutron star binary in full general relativity using an energy-integrated general-relativistic truncated moment formalism for neutrino transport. We describe our implementation of the moment formalism and important tests of our code, before studying the formation phase of an accretion disk after a black hole-neutron star merger. We use as initial data an existing general-relativistic simulation of the merger of a neutron star of mass $1.4{M}_{\ensuremath{\bigodot}}$ with a black hole of mass $7{M}_{\ensuremath{\bigodot}}$ and dimensionless spin ${\ensuremath{\chi}}_{\mathrm{BH}}=0.8$. Comparing with a simpler leakage scheme for the treatment of the neutrinos, we find noticeable differences in the neutron-to-proton ratio in and around the disk, and in the neutrino luminosity. We find that the electron neutrino luminosity is much lower in the transport simulations, and that both the disk and the disk outflows are less neutron rich. The spatial distribution of the neutrinos is significantly affected by relativistic effects, due to large velocities and curvature in the regions of strongest emission. Over the short time scale evolved, we do not observe purely neutrino-driven outflows. However, a small amount of material ($3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}{M}_{\ensuremath{\bigodot}}$) is ejected in the polar region during the circularization of the disk. Most of that material is ejected early in the formation of the disk, and is fairly neutron rich (electron fraction ${Y}_{e}\ensuremath{\sim}0.15--0.25$). Through r-process nucleosynthesis, that material should produce high-opacity lanthanides in the polar region, and could thus affect the light curve of radioactively powered electromagnetic transients. We also show that by the end of the simulation, while the bulk of the disk remains neutron rich (${Y}_{e}\ensuremath{\sim}0.15--0.2$ and decreasing), its outer layers have a higher electron fraction: 10% of the remaining mass has ${Y}_{e}>0.3$. As that material would be the first to be unbound by disk outflows on longer time scales, and as composition evolution is slower at later times, the changes in ${Y}_{e}$ experienced during the formation phase of the disk could have an impact on nucleosynthesis outputs from neutrino-driven and viscously driven outflows. Finally, we find that the effective viscosity due to momentum transport by neutrinos is unlikely to have a strong effect on the growth of the magnetorotational instability in the post-merger accretion disk.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.338
Teacher spread0.318 · 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 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

Citations175
Published2015
Admission routes2
Has abstractyes

Explore more

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