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Record W2262634738 · doi:10.1142/s0218271815420237

Evidence for event horizons: Long-lived modes in ultracompact objects

2015· article· en· W2262634738 on OpenAlexaff
Caio F. B. Macedo, Luís C. B. Crispino, Vítor Cardoso, H. Okawa, Paolo Pani

Bibliographic record

VenueInternational Journal of Modern Physics D · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsPerimeter Institute
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoEuropean Commission
KeywordsPhysicsWKB approximationGeneral relativityGeodesicAstrophysicsTheoretical physicsSupermassive black holeGalaxyGeodesics in general relativityInstabilityClassical mechanicsQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

Gravitational compact astrophysical objects are excellent laboratories to test the strong field regime of theories of gravity. Among these compact objects, lies the ultracompact class: stellar structures that possess a light ring (circular null geodesic). Such ultracompact stars were presented in literature in the earlier solutions of general relativity, and some are claimed to be good candidates to the supermassive objects present at the center of galaxies. In this paper, we present evidences for the claim that compact objects with a light ring should be black holes, based on the existence of long-lived modes obtained through a first-order perturbation theory. These first-order long-lived modes can source nonlinear terms which could turn the star unstable. We show, in particular, a comparison between modes computed through an exact direct integration and through the WKB approximation. Moreover, we present the time evolution of wavepackets for different field configurations. We conjecture some possible outcomes of the nonlinear instability. The discussion presented in this work complements our previous paper [Phys. Rev. D90 (2014) 044069].

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.554
Threshold uncertainty score0.533

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 communication0.0000.001
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 head0.080
GPT teacher head0.357
Teacher spread0.278 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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