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Record W4386555677 · doi:10.48550/arxiv.2309.02454

Kerr-Newman Black Holes in Weyl-Cartan Theory: Shadows and EHT constraints

2023· preprint· en· W4386555677 on OpenAlexaff
Khadije Jafarzade, S. H. Hendi, Mubasher Jamil, Sebastián Bahamonde

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsCanadian Quantum Research Center
FundersAgencia Nacional de Investigación y DesarrolloJapan Society for the Promotion of ScienceIran Science Elites FederationShiraz University
KeywordsPhysicsBlack hole (networking)Supermassive black holeShadow (psychology)General relativityEvent horizonGravitationHorizonRotating black holeAstrophysicsFuzzballTheoretical physicsSchwarzschild radiusAstronomyCharged black holeGalaxy

Abstract

fetched live from OpenAlex

With the recent release of the black hole image of Sgr A* alongside the earlier image of M87*, one can achieve an in-depth understanding of gravitational physics at the horizon scale. According to the Event Horizon Telescope (EHT) collaboration, the observed image is consistent with the expected appearance of a Kerr black hole. In the present work, we consider Kerr-Newman black holes in Weyl-Cartan theory as a supermassive black hole (BH) and evaluate the parameters of the model with shadow size estimates done by the observations of M87* and Sgr A* from EHT. Such a study can be a possible way to distinguish Weyl-Cartan theory from general relativity and ensure the validity of the idea. Besides, we calculate the energy emission rate for the corresponding BH and discuss how the model's parameters affect the emission of particles around the black hole. With this investigation, we are able to examine the time evolution and lifetime of the black hole in such a theory of gravity.

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)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.195
Teacher spread0.128 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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