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On the uniqueness of the non-minimal matter coupling in massive gravity and bigravity

2015· article· en· W1607851137 on OpenAlexfundno aff
Qing-Guo Huang, Raquel H. Ribeiro, Yu-Hang Xing, Kechao Zhang, Shuang-Yong Zhou

Bibliographic record

VenuePhysics Letters B · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilInstitut Périmètre de physique théoriqueChinese Academy of SciencesKavli Institute for Theoretical Physics, University of California, Santa BarbaraIndustry CanadaOntario Ministry of Economic Development and InnovationNational Natural Science Foundation of ChinaGovernment of CanadaU.S. Department of Energy
KeywordsPhysicsDecoupling (probability)Coupling (piping)SpacetimeMetric (unit)UniquenessMassive gravityMathematical physicsTheoretical physicsDark matterMinimal couplingClassical mechanicsGravitationQuantum mechanicsAstrophysicsMathematical analysisGraviton

Abstract

fetched live from OpenAlex

In de Rham–Gabadadze–Tolley (dRGT) massive gravity and bi-gravity, a non-minimal matter coupling involving both metrics generically reintroduces the Boulware–Deser (BD) ghost. A non-minimal matter coupling via a simple, yet specific composite metric has been proposed, which eliminates the BD ghost below the strong coupling scale. Working explicitly in the metric formulation and for arbitrary spacetime dimensions, we show that this composite metric is the unique consistent non-minimal matter coupling below the strong coupling scale, which emerges out of two diagnostics, namely, the absence of Ostrogradski ghosts in the decoupling limit and the absence of the BD ghost from matter quantum loop corrections.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.219

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations33
Published2015
Admission routes1
Has abstractyes

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