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Record W4388825418 · doi:10.1103/physrevd.108.095033

Phantom fluid cosmology: Impact of a phantom hidden sector on cosmological observables

2023· article· en· W4388825418 on OpenAlexafffund
James M. Cline, Matteo Puel, Takashi Toma, Qiu Shi Wang

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaJapan Society for the Promotion of ScienceAlliance de recherche numérique du Canada
KeywordsPhysicsDark energyParticle physicsCosmologyMassless particleDark matterImaging phantomHubble's lawVacuum energyObservableScalar (mathematics)Theoretical physicsAstrophysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Phantom scalar theories are widely considered in cosmology, but rarely at the quantum level, where they give rise to negative-energy ghost particles. These cause decay of the vacuum into gravitons and photons, violating observational gamma-ray limits unless the ghosts are effective degrees of freedom with a cutoff $\mathrm{\ensuremath{\Lambda}}$ at the few-MeV scale. We update the constraints on this scale, finding that $\mathrm{\ensuremath{\Lambda}}\ensuremath{\lesssim}19\text{ }\text{ }\mathrm{MeV}$. We further explore the possible coupling of ghosts to a light, possibly massless, hidden sector particle, such as a sterile neutrino. Vacuum decays can then cause the dark matter density of the universe to grow at late times. The combined phantom plus dark matter fluid has an effective equation of state $w<\ensuremath{-}1$, and functions as a new source of dark energy. We derive constraints from cosmological observables on the rate of vacuum decay into such a phantom fluid. We find a mild preference for the ghost model over the standard cosmological one, and a modest amelioration of the Hubble and ${S}_{8}$ tensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.442
Teacher spread0.410 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2023
Admission routes2
Has abstractyes

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