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Record W2148933735 · doi:10.1051/0004-6361:20041513

Dealing with systematics in cosmic shear studies: New results from the VIRMOS-Descart survey

2004· article· en· W2148933735 on OpenAlexaff

Bibliographic record

VenueAstronomy and Astrophysics · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsWeak gravitational lensingCosmic microwave backgroundRedshiftSpectral densityDark matterMatter power spectrumGalaxyCold dark matterStars

Abstract

fetched live from OpenAlex

We present a reanalysis of the VIRMOS-Descart weak lensing data, with a particular focus on different corrections for the variation of the point spread function anisotropy (PSF) across the CCDs. We show that the small scale systematics can be minimised, and eventually suppressed, using the B mode (curled shear component) measured in the corrected stars and galaxies. Updated cosmological constraints are obtained, free of systematics caused by PSF anisotropy. To facilitate general use of our results, we provide the two-points statistics data points with their covariance matrices up to a scale of one degree. For the normalisation of the mass power spectrum we obtain . The shape parameter Γ was marginalised over and the mean source redshift zs over . The latter is consistent with recent photometric redshifts obtained for the VIRMOS data and the preliminary spectroscopic redshifts from the VIRMOS-VVDS survey. The quoted contour level includes all identified sources of error. We discuss the possible sources of residual contamination in this result: the effect of the non-linear mass power spectrum and remaining issues concerning the PSF correction. Our result is compared with the first release of the Wilkinson Microwave Anisotropy Probe data. It is found that Cold Dark Matter models with a power law primordial power spectrum and high matter density are excluded at 3-σ.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.608

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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations131
Published2004
Admission routes1
Has abstractyes

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