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Record W2604340262 · doi:10.1093/mnras/stx2082

Precision calculations of the cosmic shear power spectrum projection

2017· article· en· W2604340262 on OpenAlexafffundabout
M. Kilbinger, Catherine Heymans, Marika Asgari, Shahab Joudaki, Peter Schneider, P. Šimon, Ludovic Van Waerbeke, Joachim Harnois-Déraps, H. Hildebrandt, F. Köhlinger, Konrad Kuijken, Massimo Viola

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of British Columbia
FundersARC Centre of Excellence for All-Sky AstrophysicsMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Wirtschaft und EnergieEuropean Research Consortium for Informatics and MathematicsDeutsche ForschungsgemeinschaftScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaEuropean CommissionNederlandse Organisatie voor Wetenschappelijk OnderzoekAlexander von Humboldt-Stiftung
KeywordsPhysicsCosmic microwave backgroundWeak gravitational lensingPlanckSpectral densityCosmic varianceCOSMIC cancer databaseSkyMatter power spectrumProjection (relational algebra)Dark energyAstrophysicsComputational physicsAnisotropyRedshiftCosmologyOpticsAlgorithmGalaxy

Abstract

fetched live from OpenAlex

We compute the spherical-sky weak-lensing power spectrum of the shear and convergence. We discuss various approximations, such as flat-sky, and first- and second-order Limber equations for the projection. We find that the impact of adopting these approximations is negligible when constraining cosmological parameters from current weak-lensing surveys. This is demonstrated using data from the Canada–France–Hawaii Telescope Lensing Survey. We find that the reported tension with Planck cosmic microwave background temperature anisotropy results cannot be alleviated. For future large-scale surveys with unprecedented precision, we show that the spherical second-order Limber approximation will provide sufficient accuracy. In this case, the cosmic-shear power spectrum is shown to be in agreement with the full projection at the sub-percent level for ℓ > 3, with the corresponding errors an order of magnitude below cosmic variance for all ℓ. When computing the two-point shear correlation function, we show that the flat-sky fast Hankel transformation results in errors below two percent compared to the full spherical transformation. In the spirit of reproducible research, our numerical implementation of all approximations and the full projection are publicly available within the package nicaea at http://www.cosmostat.org/software/nicaea.

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 score0.030
Threshold uncertainty score0.571

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 studies0.0010.000
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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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

Citations138
Published2017
Admission routes3
Has abstractyes

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