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Record W4386384618 · doi:10.48550/arxiv.2308.16604

Gravitational Lensing in Modified Gravity: A case study for Fast Radio Bursts

2023· preprint· en· W4386384618 on OpenAlexfundno aff
Surajit Kalita, Shruti Bhatporia, Amanda Weltman

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsnot available
FundersCurtin University of TechnologyAbdus Salam International Centre for Theoretical PhysicsMcGill UniversityUniversity of Cape TownMassachusetts Institute of TechnologyNational Research FoundationIndian Institute of Science
KeywordsPhysicsGravitational lensCosmologyGeneral relativityGravitationWeak gravitational lensingDark matterStrong gravitational lensingAstrophysicsAstronomyTheoretical physicsStrong gravityGalaxyRedshift

Abstract

fetched live from OpenAlex

Over the last few decades, a plethora of modifications to general relativity have been proposed to solve a host of cosmological and astrophysical problems. Many modified gravity models are now ruled out with further astrophysical observations; some theories are still viable, with, at best, bounds on their parameters set by observations to date. More recently, observations of Fast Radio Bursts have proven to be remarkably powerful tools to constrain cosmology and fundamental physics. In this work, we consider a generic modified gravity theory and consider the implications for gravitational lensing with Fast Radio Bursts. We use a set of Fast Radio Burst observations to constrain the fraction of dark matter made up of primordial black holes in such a theory. We further show that modified gravity adds a screening effect on gravitational lensing similar to the case when there is plasma in the path of the light ray acting as a scattering screen.

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)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.129
GPT teacher head0.295
Teacher spread0.166 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuearXiv (Cornell University)→Same topicPulsars and Gravitational Waves Research→French-language works237,207→