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Record W1646544457 · doi:10.1051/0004-6361:20010058

Cosmic shear analysis in 50 uncorrelated VLT fields. Implications for $\Omega_0$, $\sigma_8$

2001· article· en· W1646544457 on OpenAlexaff

Bibliographic record

VenueAstronomy and Astrophysics · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical Astrophysics
FundersDeutscher Akademischer Austauschdienst
KeywordsCOSMIC cancer databaseRedshiftGalaxySpectral densityAmplitudeGaussianShear (geology)Matter power spectrumCosmic varianceDark matter

Abstract

fetched live from OpenAlex

We observed with the camera FORS1 on the VLT (UT1, ANTU) 50 randomly selected fields and analyzed the cosmic shear inside circular apertures with diameter ranging from 0.5 to 5.0 arcmin. The images were obtained in optimal conditions using the Service Observing proposed by ESO on the VLT, which enabled us to a well-defined and homogeneous set of data. The 50 fields cover a 0.64 square-degrees area spread over more than 1000 square-degrees obtain which provides a sample ideal for minimizing the cosmic variance. Using the same techniques as in Van Waerbeke et al. ([CITE]), we measured the cosmic shear signal and investigated the systematics of the VLT sample. We find a significant excess of correlations between galaxy ellipticities on those angular scales. The amplitude and the shape of the correlation as function of angular scale are remarkably similar to those reported so far. Using our combined VLT and CFHT data and adding the results published by other teams we put the first joint constraints on and using cosmic shear surveys. From a deduced average of the redshift of the sources the combined data are consistent with (for a CDM power spectrum and ), in excellent agreement with the cosmological constraints obtained from the local cluster abundance. This is consistent with theoretical expectations if the density field grew from initial Gaussian conditions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.216
Teacher spread0.208 · 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.

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

Citations133
Published2001
Admission routes1
Has abstractyes

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