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Record W2121116537 · doi:10.1002/asna.201211864

The duty cycle of the radio mode feedback

2013· article· en· W2121116537 on OpenAlexaff
L. Bırzan, D. A. Rafferty, P. E. J. Nulsen, B. R. McNamara, H. J. A. Röttgering, M. W. Wise

Bibliographic record

VenueAstronomische Nachrichten · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsPerimeter InstituteUniversity of Waterloo
Fundersnot available
KeywordsCooling flowDuty cyclePhysicsIntracluster mediumAstrophysicsActive galactic nucleusCluster (spacecraft)BubbleLuminosityGalaxy clusterGalaxyObservatoryFlux (metallurgy)Flow (mathematics)AstronomyPower (physics)MechanicsThermodynamicsMaterials science

Abstract

fetched live from OpenAlex

Abstract The Chandra X‐ray Observatory has revealed X‐ray bubbles in the intracluster medium (ICM) of many nearby clusters, which are thought to be created by the central active galactic nucleus (AGN). However, the duty cycle of such AGN outbursts is not well understood. In order to further understand how cooling is balanced by bubble heating we studied complete samples of cooling flow clusters (from the Brightest 55 clusters of galaxies sample, B55, and the HIghest X‐ray FLUx Galaxy Cluster Sample, HIFLUGCS). We found that there is a radio luminosity cut‐off of 2.5×10 30 erg s –1 Hz –1 for the cooling flow clusters. Furthermore, we find a duty cycle for radio mode feedback, the fraction of time that a system possesses bubbles inflated by its central radio source, of ≳ 69 % for the B55 sample and ≳ 63 % for the HIFLUGCS sample. These duty cycles are lower limits since some bubbles are likely missed in existing images. We used simulations to constrain the bubble power that might be present and remain undetected in the cooling flow systems without detected bubbles. Among theses systems, almost all could have significant bubble power. Therefore, our results imply that the duty cycle of AGN outbursts with the potential to heat the gas significantly in cooling flow clusters is at least 60% and could approach 100 %. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.491

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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