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Record W6910602228 · doi:10.48550/arxiv.0910.3207

Structure Formation by Fifth Force: Power Spectrum from N-Body Simulations

2009· preprint· en· W6910602228 on OpenAlexaff

Bibliographic record

VenueMax Planck Institute for Plasma Physics · 2009
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsStructure formationScalar fieldDark matterMatter power spectrumScalar field dark matterDark energyCosmic microwave backgroundCold dark matterScalar (mathematics)

Abstract

fetched live from OpenAlex

We lay out the framework to numerically study nonlinear structure formation in the context of scalar-field-coupled cold dark matter models (phiCDM models) where the scalar field phi serves as dynamical dark energy. Adopting parameters for the scalar field which yield a realistic CMB spectrum, we generate the initial conditions for our Nbody simulations, which follow the spatial distributions of dark matter and the scalar field, by solving their equations of motion using the multilevel adaptive grid technique. We show that the spatial configuration of the scalar field tracks both the voids and clusters of dark matter. The phiCDM model differs from standard LCDM at small scales with observable modifications of, e.g., the mass function of halos as well as the matter power spectrum. Nevertheless, the predictions of both models for the Hubble expansion and the CMB spectrum are virtually indistinguishable. Hence, galaxy cluster counts and weak lensing observations, which probe structure formation at small scales, are needed to falsify this class of models.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.244
Teacher spread0.236 · 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 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

Citations0
Published2009
Admission routes1
Has abstractyes

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