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Record W2045162871 · doi:10.1103/physrevd.67.123513

Observational constraints on the curvaton model of inflation

2003· article· en· W2045162871 on OpenAlexaff
Chris Gordon, Antony Lewis

Bibliographic record

VenuePhysical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsCMB cold spotCosmic microwave backgroundPhysicsPlanckNon-GaussianityAdiabatic processCovariant transformationInflation (cosmology)Cosmological perturbation theoryParticle physicsAnisotropyPerturbation (astronomy)Statistical physicsTheoretical physicsAstrophysicsMathematical physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Simple curvaton models can generate a mixture of correlated primordial adiabatic and isocurvature perturbations. The baryon and cold dark matter isocurvature modes differ only by an observationally null mode in which the two perturbations almost exactly compensate, and therefore have proportional effects at linear order. We discuss the cosmic microwave background (CMB) anisotropy in general mixed models, and give a simple approximate analytic result for the large scale CMB anisotropy. Working numerically we use the latest Wilkinson Microwave Anisotropy Probe (WMAP) observations and a variety of other data to constrain the curvaton model. We find that models with an isocurvature contribution are not favored relative to simple purely adiabatic models. However a significant primordial totally correlated baryon isocurvature perturbation is not ruled out. Certain classes of curvaton model are thereby ruled out; other classes predict enough non-Gaussianity to be detectable by the Planck satellite. In the Appendixes we review the relevant equations in the covariant formulation and give series solutions for the radiation dominated era.

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)0.001
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 score0.038
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.341
Teacher spread0.306 · 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

Citations148
Published2003
Admission routes1
Has abstractyes

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