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Simulating cosmic rays in clusters of galaxies – III. Non-thermal scaling relations and comparison to observations

2008· article· en· W2145269049 on OpenAlexaff
Christoph Pfrommer

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsAstrophysicsCosmic rayGalaxy clusterRadio haloGalaxyRadio galaxyAstronomy

Abstract

fetched live from OpenAlex

Complementary views of galaxy clusters in the radio synchrotron, hard X-ray inverse Compton, and high-energyγ-ray regimes are critical in calibrating them as high-precision cosmological probes. We present predictions for scaling relations between cluster mass and these non-thermal observables. To this end, we use high-resolution simulations of a sample of galaxy clusters spanning a mass range of almost two orders of magnitudes, and follow selfconsistent cosmic ray physics on top of the radiative hydrodynamics. We model relativistic electrons that are accelerated at cosmological structure formation shocks and those that are produced in hadronic interactions of cosmic rays with ambient gas protons. Calibrating the magnetic fields of our model with Faraday rotation measurements, the synchrotron emission of our relativistic electron populations matches the radio synchrotron luminosities and morphologies of observed giant radio halos and mini-halos surprisingly well. Using the complete sample of the brightest X-ray clusters observed by ROSAT in combination with ourγ-ray scaling relation, we predict GLAST that will detect about ten clusters allowing for Eddington bias due to the scatter in the scaling relation. The expected brightestγ-ray clusters are Ophiuchus,

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 score0.071
Threshold uncertainty score0.494

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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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

Citations83
Published2008
Admission routes1
Has abstractyes

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