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Record W4396612154 · doi:10.3847/1538-4357/ad343c

Unveiling the Small-scale Jets in the Rapidly Growing Supermassive Black Hole IZw1

2024· article· en· W4396612154 on OpenAlexaff
Xiaolong Yang, Su Yao, Luigi Gallo, Jun Yang, Luis C. Ho, Minfeng Gu, Willem A. Baan, Jiří Svoboda, Ran Wang, Xiang Liu, Xiaoyu Hong, Xue-Bing Wu, Wei Zhao

Bibliographic record

VenueThe Astrophysical Journal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsSaint Mary's University
FundersNational Key Research and Development Program of ChinaScience and Technology Facilities CouncilChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaEuropean Space AgencyGrantová Agentura České RepublikyAlexander von Humboldt-StiftungNational Science Foundation
KeywordsPhysicsAstrophysicsSupermassive black holeActive galactic nucleusAccretion (finance)AstronomyBlack hole (networking)Astrophysical jetBrightnessJet (fluid)Very-long-baseline interferometryGalaxy

Abstract

fetched live from OpenAlex

Abstract Accretion of black holes at near-Eddington or super-Eddington rates represents the most powerful episode driving black hole growth, potentially occurring across various types of objects. However, the physics governing accretion and jet–disk coupling in such states remains unclear, primarily due to the difficulty in detecting associated jets, which may emit extremely weakly or exhibit episodic behavior. Only a few near/super-Eddington systems have demonstrated radio activity, and it remains uncertain whether jets exist and what their properties are in super-Eddington active galactic nuclei (AGNs) and ultraluminous X-ray sources. This uncertainty stems mainly from the complex radio emission mix, which includes contributions from jets, star formation activity, photoionized gas, accretion disk wind, and coronal activity. In this work, we conducted high-resolution, very long baseline interferometry observations to investigate jets in the highly accreting narrow-line Seyfert I system I Zw 1. Our observations successfully revealed small-scale jets (with a linear size of ∼45 pc) at both 1.5 and 5 GHz, based on the high radio brightness temperature, radio morphology, and spectral index distribution. Additionally, the parsec-scale jet observed in I Zw 1 displays a knotted morphology reminiscent of other sources accreting at similar rates. In summary, the high accretion rates and jet properties observed in the AGN I Zw 1 may support the AGN/X-ray binary analogy in this extreme state.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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