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Record W2017260657 · doi:10.1086/521383

A Dark Core in Abell 520

2007· article· en· W2017260657 on OpenAlexaff
Andisheh Mahdavi, Henk Hoekstra, Arif Babul, D. D. Balam, P. Capak

Bibliographic record

VenueThe Astrophysical Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAstrophysicsPhysicsDark matterGalaxy clusterAbell 2744GalaxyAstronomyRam pressureDark galaxyGalaxy groupStar formation

Abstract

fetched live from OpenAlex

The rich cluster Abell 520 (z = 0.201) exhibits truly extreme and puzzling multi-wavelength characteristics. It may best be described as a “cosmic train wreck. ” It is a major merger showing abundant evidence for ram pressure stripping, with a clear offset in the gas distribution compared to the galaxies (as in the bullet cluster 1E 0657-558). However, the most striking feature is a massive dark core (721h70M⊙/L⊙B) in our weak lensing mass reconstruction. The core coincides with the central X-ray emission peak, but is largely devoid of galaxies. An unusually low mass to light ratio region lies 500 kpc to the East, and coincides with a shock feature visible in radio observations of the cluster. Although a displacement between the X-ray gas and the galaxy/dark matter distributions may be expected in a merger, a mass peak without galaxies cannot be easily explained within the current collisionless dark matter paradigm. Interestingly, the integrated gas mass fraction ( ≈ 0.15), mass-to-light ratio (220h70M⊙/L⊙B), and position on the X-ray luminosity-temperature and mass-temperature relations are unremarkable. Thus gross properties and scaling relations are not always useful indicators of the dynamical state of clusters. Subject headings: Galaxies: clusters: individual (Abell 520)—gravitational lensing—dark matter—Xrays: galaxies: clusters 1.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.418

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 integrity0.0000.001
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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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

Citations169
Published2007
Admission routes1
Has abstractyes

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