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Record W4388274479 · doi:10.1103/physrevd.109.044006

Tidal effects up to next-to-next-to-leading post-Newtonian order in massless scalar-tensor theories

2024· article· en· W4388274479 on OpenAlexfundno aff
Laura Bernard, Stavros Mougiakakos

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsHorizon 2020 Framework ProgrammeMinistry of Colleges and UniversitiesGovernment of CanadaAgence Nationale de la RechercheInnovation, Science and Economic Development CanadaInstitut Périmètre de physique théoriqueSimons Foundation
KeywordsPhysicsMassless particleScalar theories of gravitationScalar fieldClassical mechanicsNewtonian fluidScalar (mathematics)GravitationNewtonian potentialTheoretical physicsScalar–tensor theoryMathematical physicsGravitational waveGeneral relativityEinstein tensorEinsteinClassical field theoryRiemann curvature tensorMathematicsQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

In this paper, we study the tidal effects in the gravitationally bound two-body system at next-to-next-to leading post-Newtonian order for spinless sources in massless scalar-tensor theories. We compute the conservative dynamics, using both a Fokker Lagrangian approach and effective field theory with the post-Newtonian effective field theory formalism. We also compute the ten conserved quantities at the same next-to-next-to leading order. Finally, we extend our results from simple scalar-tensor theories to Einstein-scalar-Gauss-Bonnet gravity. Such results are important in preparation of the science case of the next generation of gravitational wave detectors.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0010.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.463
Teacher spread0.448 · 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

Citations26
Published2024
Admission routes1
Has abstractyes

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