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Record W4404140002 · doi:10.1088/1475-7516/2024/11/004

Bounds on the charge of the graviton using gravitational wave observations

2024· article· en· W4404140002 on OpenAlexaff
Sreejith Nair, A. Vijaykumar, Sourav Sarkar

Bibliographic record

VenueJournal of Cosmology and Astroparticle Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsGravitonGravitational waveCharge (physics)GravitationTheoretical physicsParticle physicsGravitational energyQuantum electrodynamicsAstronomy

Abstract

fetched live from OpenAlex

Abstract If the graviton possesses a non-zero charge qg , gravitational waves (GW) originating from astrophysical sources would experience an additional time delay due to intergalactic magnetic fields. This would result in a modification of the phase evolution of the observed GW signal similar to the effect induced by a massive graviton. As a result, we can reinterpret the most recent upper limits on the graviton's mass as constraints on the joint mass-charge parameter space, finding |qg |/e < 3 × 10-34 where e represents the charge of an electron. Additionally, we illustrate that a charged graviton would introduce a constant phase difference in the gravitational waves detected by two spatially separated GW detectors due to the Aharonov-Bohm effect. Using the non-observation of such a phase difference for the GW event GW190814, we establish a mass-independent constraint |qg |/e < 2 × 10-26. To the best of our knowledge, our results constitute the first-ever bounds on the charge of the graviton. We also discuss various caveats involved in our measurements and prospects for strengthening these bounds with future GW observations.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.338
Teacher spread0.280 · 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 designSimulation or modeling
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

Citations7
Published2024
Admission routes1
Has abstractyes

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