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Record W2021746758 · doi:10.5539/apr.v7n3p33

Fresnel vs. Einstein - a New Direct Test

2015· article· en· W2021746758 on OpenAlexvenueno aff
Dan Wagner

Bibliographic record

VenueApplied Physics Research · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRelativity and Gravitational Theory
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsOne-way speed of lightEinsteinTime dilationReference frameSpeed of light (cellular automaton)Moving frameSpecial relativityTheory of relativityOpticsClassical mechanicsGroup velocityFrame (networking)Principle of relativityComputer science

Abstract

fetched live from OpenAlex

When the phase velocity of light in a moving medium is used to predict the phase velocity of that light relative to a stationary observer then the Einstein low speed approximation to his velocity addition equation and the Fresnel drag equation both predict the exact same result. Therefore existing interference fringe shift experiments do not differentiate between the Fresnel and Einstein predictions. However, when the group velocity of light is used, the Fresnel prediction and the Einstein prediction are different. When Fresnel predictions based on group velocity are made for the proposed experiment, the difference in round trip arrival times for the two halves of a split laser pulse is substantial. When Einstein predictions based on group velocity are made the difference in round trip times is, of course, zero. Thus a positive result for the proposed experiment would violate Special Relativity Theory (SRT) with regards to the relativity of simultaneity and suggest that the Lorentz-Poincare’ physical viewpoint on the SRT equations is a better viewpoint. If the Einstein prediction for group velocity is not correct, then when positive data for the experiment configuration shown in Figure 1.0 is collected at various orientations at different times of the day it is possible to identify a local preferred reference frame in which the speed of light is actually (not just apparently) isotropic. This reference frame could be used in place of star reference frames for spacecraft navigation. Other implications of a local preferred reference frame are explained in the paper.

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)0.008
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.010
Scholarly communication0.0030.013
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.002

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 head0.112
GPT teacher head0.370
Teacher spread0.258 · 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 designBench or experimental
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

Citations4
Published2015
Admission routes1
Has abstractyes

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