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Record W4321602567 · doi:10.3847/1538-4357/acaf71

MOMO. VI. Multifrequency Radio Variability of the Blazar OJ 287 from 2015 to 2022, Absence of Predicted 2021 Precursor-flare Activity, and a New Binary Interpretation of the 2016/2017 Outburst

2023· article· en· W4321602567 on OpenAlexaff
S. Komossa, A. Kraus, D. Grupe, A G Gonzalez, Mark Gurwell, Luigi Gallo, F. K. Liu, I. Myserlis, T. P. Krichbaum, Seppo Laine, U. Bach, José L. Gómez, M. L. Parker, Su Yao, M. Berton

Bibliographic record

VenueThe Astrophysical Journal · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPhysicsFlareBlazarAstrophysicsBinary numberAstronomyGamma ray

Abstract

fetched live from OpenAlex

Abstract Based on our dedicated Swift monitoring program, MOMO, OJ 287 is one of the best-monitored blazars in the X-ray–UV–optical regime. Here, we report results from our accompanying, dense, multifrequency (1.4–44 GHz) radio monitoring of OJ 287 between 2015 and 2022 covering a broad range of activity states. Fermi γ -ray observations were added. We characterize the radio flux and spectral variability in detail, including discrete correlation function and other variability analyses, and discuss its connection with the multiwavelength emission. Deep fades of the radio and optical–UV fluxes are found to occur every 1–2 yr. Further, it is shown that a precursor flare of thermal bremsstrahlung predicted by one of the binary supermassive black hole (SMBH) models of OJ 287 was absent. We then focus on the nature of the extraordinary, nonthermal, 2016/2017 outburst that we initially discovered with Swift. We interpret it as the latest of the famous optical double-peaked outbursts of OJ 287, favoring binary scenarios that do not require a highly precessing secondary 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.486

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 integrity0.0000.001
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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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 designBench or experimental
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

Citations24
Published2023
Admission routes1
Has abstractyes

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