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Record W1772677041 · doi:10.1088/0004-637x/805/1/35

X-RAY CAVITIES IN A SAMPLE OF 83 SPT-SELECTED CLUSTERS OF GALAXIES: TRACING THE EVOLUTION OF AGN FEEDBACK IN CLUSTERS OF GALAXIES OUT TO<i>z</i>= 1.2

2015· article· en· W1772677041 on OpenAlexaff
Julie Hlavacek-Larrondo, M. McDonald, B. A. Benson, W. Forman, S. W. Allen, L. E. Bleem, M. L. N. Ashby, S. Bocquet, M. Brodwin, J. P. Dietrich, C. Jones, C. L. Reichardt, B. R. Saliwanchik, A. Saro, T. Schrabback, Jie Song, B. Stalder, A. Vikhlinin, A. Zenteno

Bibliographic record

VenueThe Astrophysical Journal · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhysicsAstrophysicsSupermassive black holeIntracluster mediumActive galactic nucleusGalaxy clusterGalaxyRedshiftAstronomyAccretion (finance)Surface brightnessCluster (spacecraft)

Abstract

fetched live from OpenAlex

X-ray cavities are key tracers of mechanical (or radio mode) heating arising from the active galactic nuclei (AGN) in brightest cluster galaxies. We report on a survey for X-ray cavities in 83 massive, high-redshift (0.40.5) redshift. Despite these limitations, our results suggest that the power generated by AGN feedback in brightest cluster galaxies has remained unchanged for over half of the age of the Universe (&gt;7 Gyrs at z=0.8). On average, the detected X-ray cavities have powers of 0.8-5*10^45 erg/s, enthalpies of 3-6*10^59 erg, and radii of 17 kpc. Integrating over 7 Gyrs, we find that the supermassive black holes in the brightest cluster galaxies may have accreted 10^8 to several 10^9M_sun of material to power these outflows. This level of accretion indicates that significant supermassive black hole growth may occur not only at early times, in the quasar era, but at late times as well. We also find that X-ray cavities at high-redshift may inject an excess heat of 0.1-1.0 keV per particle into the hot intracluster medium above and beyond the energy needed to offset cooling. This value is similar to the energy needed to preheat clusters, break self-similarity, and explain the excess entropy in hot atmospheres.

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)0.001
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 score0.040
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.224
Teacher spread0.211 · 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

Citations162
Published2015
Admission routes1
Has abstractyes

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