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Record W4410737580 · doi:10.1051/0004-6361/202451216

The phase-space of tailed radio galaxies in massive clusters

2025· article· en· W4410737580 on OpenAlexafffund
S. van der Jagt, E. Osinga, R. J. van Weeren, G.K. Miley, Ian Roberts, A. Botteon, A. Ignesti

Bibliographic record

VenueAstronomy and Astrophysics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of WaterlooUniversity of Toronto
FundersLos Alamos National LaboratoryDST-NRF Centre Of Excellence In Tree Health BiotechnologySmithsonian Astrophysical ObservatoryYork UniversityMinistério da Ciência, Tecnologia e InovaçãoScience and Technology Facilities CouncilHorizon 2020 Framework ProgrammeUniversity of Colorado BoulderLawrence Berkeley National LaboratoryJet Propulsion LaboratoryCarnegie Institution for ScienceInstituto de Astrofísica de CanariasPlanetary Science DivisionCarnegie Institution of WashingtonGauss Centre for SupercomputingMax-Planck-Institut für AstronomieMax-Planck-Institut für AstrophysikEötvös Loránd TudományegyetemObservatoire de Paris, Université de Recherche Paris Sciences et LettresMinisterium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-WestfalenNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversité d'OrléansBundesministerium für Bildung und ForschungNational Central UniversityCentre National de la Recherche ScientifiqueMax-Planck-GesellschaftUniversity of HertfordshireQueen's UniversityGordon and Betty Moore FoundationQueen's University BelfastUniversity of OxfordUniversidad Nacional Autónoma de MéxicoIstituto Nazionale di AstrofisicaDurham UniversitySpace Telescope Science InstituteNew Mexico State UniversityUniversity of PortsmouthUniversity of Notre DameCarnegie Mellon UniversityUniversity of WashingtonJohns Hopkins UniversityScience Foundation IrelandNational Science FoundationOhio State UniversityVanderbilt UniversityLeibniz-GemeinschaftScience Mission DirectorateYale UniversityEuropean CommissionCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationSmithsonian Institution
KeywordsPhysicsAstrophysicsRadio galaxyAstronomyGalaxy clusterGalaxyGalaxy groups and clusters

Abstract

fetched live from OpenAlex

The radio jets of radio galaxies in galaxy clusters are often bent due to the ram pressure of the intracluster medium. Most studies of bent radio tails initially identified tailed sources and then attempted to characterise their environments. In this paper we take an alternative approach, by starting with a well-defined sample of galaxy clusters and subsequently identifying tailed radio sources in these known environments. Our sample consists of 81 galaxy clusters from the Planck ESZ cluster sample. We present a catalogue of 127 extended cluster radio sources, including brightest cluster galaxies, obtained by visually inspecting Karl G. Jansky Very Large Array (1–2 GHz) observations. We have determined the bending angle of 109 well-structured sources, and classified them accordingly: 84 narrow-angle tailed sources (NATs), 16 wide-angle tailed sources (WATs), and 9 non-bent radio sources (i.e. with bending angles of less than 15°). We find a negative correlation between the bending angle and the distance to the cluster centre (impact radius), and we observe that NATs generally have smaller impact radii than the regular galaxy population and WATs. We present a phase-space diagram of tailed radio galaxy velocities and impact radii and find that NATs have a significant excess in the high-velocity and low-impact radius region of phase space, indicating they undergo the largest amount of ram pressure bending. We compared the results from our sample with those for jellyfish galaxies, and suggest that the mechanism responsible for bending the radio tails is similar to the stripping of gas in jellyfish galaxies, although tailed radio galaxies are more concentrated in the centre of the phase space. Finally, we find that NATs and WATs have the same occurrence ratio in merging and relaxed clusters. However, their distribution in the phase-space is significantly different. We report an excess of NATs in the high-velocity and low-impact-radius phase-space region in merging clusters, and an excess of NATs in relaxed clusters in the low-velocity and low-impact-radius region.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.653

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 science0.0000.000
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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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