MétaCan
Menu
Back to cohort
Record W2062839084 · doi:10.1088/0004-637x/697/2/1164

IMAGING THE BLACK HOLE SILHOUETTE OF M87: IMPLICATIONS FOR JET FORMATION AND BLACK HOLE SPIN

2009· article· en· W2062839084 on OpenAlexaff
Avery E. Broderick, Abraham Loeb

Bibliographic record

VenueThe Astrophysical Journal · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsSilhouetteBlack hole (networking)PhysicsSpin-flipSpin (aerodynamics)Jet (fluid)AstrophysicsCarbon blackGalaxyMaterials scienceComputer scienceArtificial intelligenceMechanics

Abstract

fetched live from OpenAlex

The silhouette cast by the horizon of the supermassive black hole in M87 can now be resolved with the emerging millimeter very-long baseline interferometry (VLBI) capability. Despite being ~2000 times farther away than SgrA* (the supermassive black hole at the center of the Milky-Way and the primary target for horizon-scale imaging), M87's much larger black hole mass results in a horizon angular scale roughly half that of SgrA*'s, providing another practical target for direct imaging. However, unlike SgrA*, M87 exhibits a powerful radio jet, providing an opportunity to study jet formation physics on horizon scales. We employ a simple, qualitatively correct force-free jet model to explore the expected high-resolution images of M87 at wavelengths of 1.3mm and 0.87mm (230GHz and 345GHz), for a variety of jet parameters. We show that future VLBI data will be able to constrain the size of the jet footprint, the jet collimation rate, and the black hole spin. Polarization will further probe the structure of the jet's magnetic field and its effect on the emitting gas. Horizon-scale imaging of M87 and SgrA* will enable for the first time the empirical exploration of the relationship between the mass and spin of a black hole and the characteristics of the gas inflow/outflow around it.

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 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 score0.511
Threshold uncertainty score0.385

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 integrity0.0000.000
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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.

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

Citations174
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe Astrophysical JournalSame topicAstrophysical Phenomena and ObservationsFrench-language works237,207