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Record W4286789987 · doi:10.1093/mnras/stac2003

Hidden cooling flows in clusters of galaxies

2022· article· en· W4286789987 on OpenAlexaff
A. C. Fabian, G. J. Ferland, J. S. Sanders, B. R. McNamara, C. Pinto, S A Walker

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Waterloo
FundersAkron Community Foundation
KeywordsPhysicsAstrophysicsRadiative coolingCooling flowGalaxyCentaurus ACluster (spacecraft)LuminosityGalaxy clusterAstronomyGalaxy groups and clustersStarsLow MassActive galactic nucleus

Abstract

fetched live from OpenAlex

ABSTRACT The radiative cooling time of the hot gas at the centres of cool cores in clusters of galaxies drops down to 10 Myr and below. The observed mass cooling rate of such gas is very low, suggesting that active galactic nucleus feedback is very tightly balanced or that the soft X-ray emission from cooling is somehow hidden from view. We use an intrinsic absorption model in which the cooling and coolest gas are closely interleaved to search for hidden cooling flows in the Centaurus, Perseus, and A1835 clusters of galaxies. We find hidden mass cooling rates of between 10 and $500\,{{\rm M_{\odot }}\,{\rm yr}^{-1}}$ as the cluster mass increases, with the absorbed emission emerging in the far-infrared (FIR) band. Good agreement is found between the hidden cooling rate and observed FIR luminosity in the Centaurus Cluster. The limits on the other two clusters allow for considerable hidden cooling. The implied total mass of cooled gas is much larger than the observed molecular masses. We discuss its fate including possible further cooling and collapse into undetected very cold clouds, low-mass stars, and substellar objects.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.007
GPT teacher head0.193
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 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

Citations35
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical Society→Same topicGalaxies: Formation, Evolution, Phenomena→French-language works237,207→