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Record W2140691524 · doi:10.1093/mnras/stu1563

Jet–intracluster medium interaction in Hydra A – I. Estimates of jet velocity from inner knots

2014· article· en· W2140691524 on OpenAlexaff
M. A. Nawaz, A. Y. Wagner, G. V. Bicknell, Ralph S. Sutherland, B. R. McNamara

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhysicsAstrophysicsIntracluster mediumJet (fluid)Radio galaxyGalaxyGalaxy clusterAstronomyMechanics

Abstract

fetched live from OpenAlex

We present the first stage of an investigation of the interactions of the jets in the radio galaxy Hydra A with the intracluster medium. We consider the jet kinetic power, the galaxy and cluster atmosphere and the inner structure of the radio source. Analysing radio observations of the inner lobes of Hydra A by Taylor et al. we confirm the jet power estimates ∼1045舁erg舁s−1 derived by Wise et al. from dynamical analysis of the X-ray cavities. With this result and a model for the galaxy halo, we explore the jet–intracluster medium interactions occurring on a scale of 10舁kpc using two-dimensional, axisymmetric, relativistic pure hydrodynamic simulations. A key feature is that we identify the three bright knots in the northern jet as biconical reconfinement shocks, which result when an overpressured jet starts to come into equilibrium with the galactic atmosphere. Through an extensive parameter space study we deduce that the jet velocity is approximately 0.8c at a distance 0.5舁kpc from the black hole. The combined constraints of jet power, the observed jet radius profile along the jet and the estimated jet pressure and jet velocity imply a value of the jet density parameter χ ≈ 13 for the northern jet. We show that for a jet β = 0.8 and θ = 42°, an intrinsic asymmetry in the emissivity of the northern and southern jet is required for a consistent brightness ratio ≈7 estimated from the 6-cm Very Large Array image of Hydra A.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.669

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 head0.006
GPT teacher head0.206
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations14
Published2014
Admission routes1
Has abstractyes

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