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The distribution of satellite galaxies: the great pancake

2005· article· en· W1975256542 on OpenAlexaff

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMilky WayDark matterSatelliteContext (archaeology)HaloSatellite galaxyGalaxyCold dark matter

Abstract

fetched live from OpenAlex

The 11 known satellite galaxies within 250 kpc of the Milky Way lie close to a great circle on the sky. We use high-resolution N-body simulations of galactic dark matter haloes to test if this remarkable property can be understood within the context of the cold dark matter (CDM) cosmology. We construct halo merger trees from the simulations and use a semi-analytic model to follow the formation of satellite galaxies. We find that in all six of our simulations, the 11 brightest satellites are indeed distributed along thin, disc-like structures analogous to that traced by the satellites of the Milky Way. This is in sharp contrast to the overall distributions of dark matter in the halo and of subhaloes within it, which, although triaxial, are not highly aspherical. We find that the spatial distribution of satellites is significantly different from that of the most massive subhaloes but is similar to that of the subset of subhaloes that had the most massive progenitors at earlier times. The elongated disc-like structure delineated by the satellites has its long axis aligned with the major axis of the dark matter halo. We interpret our results as reflecting the preferential infall of satellites along the spines of a few filaments of the cosmic web.

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 score0.008
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.191
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 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

Citations242
Published2005
Admission routes1
Has abstractyes

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