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Record W4405834037 · doi:10.1103/physrevd.110.124066

Tidal forces in collapsing compact objects

2024· article· en· W4405834037 on OpenAlexafffund
Ashok B. Joshi, Dipanjan Dey, Pankaj S. Joshi, Vivekkumar R. Tank

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsDalhousie University
FundersAtlantic Association for Research in the Mathematical SciencesAhmedabad University
KeywordsTidal forceComputer scienceClassical mechanicsGeologyAeronauticsAerospace engineeringPhysicsEngineeringAstronomy

Abstract

fetched live from OpenAlex

In this work, we investigate tidal forces in the Lemaitre-Tolman-Bondi (LTB) metric, focusing on both hidden and locally visible singularities. We discuss the strength of these singularities in terms of deformationally strong singularities. Specifically, we analyze tidal forces in LTB spacetime, calculating radial and angular tidal forces and Jacobi fields for the radially comoving shell. To provide a comparative study, we consider both homogeneous and inhomogeneous cases. The matter field distribution at one-time slice can differ significantly from another, highlighting the potential for time-dependent tidal deformation as a distinct observational signature. We focus on a specific feature: the time-varying maximum of stretching in the radial tidal force, which we term the ``critical tidal boundary.'' In the inhomogeneous case, close to singularity time ($t<{t}_{s}$), the magnitudes of tidal forces vary substantially, with significant differences in compressive and stretching forces within a small physical radius $R(t,r)$. The resulting singularity in the LTB metrics at the end state of gravitational collapse appears to be an Ori-strong singularity, characterized by infinite tidal deformation.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.013
GPT teacher head0.403
Teacher spread0.389 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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