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Record W4321486968 · doi:10.1093/mnrasl/slad016

Absence of the predicted 2022 October outburst of OJ 287 and implications for binary SMBH scenarios

2023· article· en· W4321486968 on OpenAlexaff
S. Komossa, D. Grupe, A. Kraus, Mark Gurwell, Zoltán Haiman, F K Liu, Alexander Tchekhovskoy, Luigi Gallo, M. Berton, R. D. Blandford, José L. Gómez, A G Gonzalez

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsSaint Mary's University
FundersSmithsonian Astrophysical ObservatoryNuclear Safety and Security CommissionUniversity of LeicesterAcademia SinicaNational Aeronautics and Space AdministrationSmithsonian InstitutionNational Science Foundation
KeywordsPhysicsAstrophysicsBinary numberAstronomy

Abstract

fetched live from OpenAlex

ABSTRACT The project MOMO (Multiwavelength Observations and Modelling of OJ 287) was set up to test predictions of binary supermassive black hole (SMBH) scenarios and to understand disc–jet physics of the blazar OJ 287. After a correction, the precessing binary (PB) SMBH model predicted the next main outburst of OJ 287 in 2022 October, making the outburst well observable and the model testable. We have densely covered this period in our ongoing multifrequency radio, optical, ultraviolet (UV), and X-ray monitoring. The predicted outburst was not detected. Instead, OJ 287 was at low optical–UV emission levels, declining further into November. The predicted thermal bremsstrahlung spectrum was not observed either, at any epoch. Further, applying scaling relations, we estimate an SMBH mass of OJ 287 of 108 M⊙. The latest in a sequence of deep low states that recur every 1–2 yr is used to determine an upper limit on the Eddington ratio and on the accretion-disc luminosity. This limit is at least a factor of 10 lower than required by the PB model with its massive primary SMBH of >1010 M⊙. All these results favour alternative binary SMBH models of OJ 287 that require neither strong orbital precession nor a very large mass of the primary SMBH.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.414

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 science0.0010.000
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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 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

Citations34
Published2023
Admission routes1
Has abstractyes

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