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Record W4388654360 · doi:10.1103/physrevd.108.104034

Observational aspects of a class of dark matter spacetimes

2023· article· en· W4388654360 on OpenAlexaff
Ashok B. Joshi, Divya Tahelyani, Dipanjan Dey, Pankaj S. Joshi

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhysicsDark matterSpacetimeAstrophysicsDark fluidUniverseScalar field dark matterDark matter haloEinstein field equationsTheoretical physicsEinsteinHaloMathematical physicsDark energyGalaxyCosmologyQuantum mechanics

Abstract

fetched live from OpenAlex

Various astrophysical and cosmological observations today serve as indirect evidence of the existence of dark matter in the Universe. In the present work, we propose a class of spacetimes that show some important characteristics relevant to the spacetime of a dark matter halo. These spacetimes are static and spherically symmetric solutions of the Einstein field equations. The proposed spacetimes satisfy the flat velocity profile of a galactic object far away from the center, they give good agreement to the astrometric data of the S2 star, and these also cast a central shadow. Using the Penrose diagram, we show that the causal nature of the central singularity here is null. This single spacetime model for galactic dark matter may therefore be used to explain some of the properties of galactic dynamics at different length scales.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.365
Teacher spread0.344 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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