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New Experiment Demonstrates Transformation of Visible Photons into Other Visible Photons with Different Energy and Momentum

2022· article· en· W4307508601 on OpenAlexaff
Dan Wagner

Bibliographic record

VenueEuropean Journal of Applied Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPhotonPhysicsWavelengthPhoton entanglementMomentum (technical analysis)OpticsQuantumQuantum mechanicsQuantum entanglement

Abstract

fetched live from OpenAlex

A new experiment demonstrates that although mixed red and green wavelength photons may be perceived by the human eye as yellow, actual yellow wavelength photons are also produced. The experiment is easily repeatable and provides a basis for additional experimentation. The results raise a question as to the accuracy of element percentage predictions based on the intensity of spectrum lines. Other experiments with results supporting the transformation of photons with a given wavelength to photons with a different wavelength, such as the Compton Effect, are discussed. Also, Markarian 501 along with other Gamma-Ray Burst (GRB) data are shown to perhaps be the first evidence that photons, like other particles, do not all travel at the same speed in a vacuum. If true, then photons can be treated as other quantum objects whose wavelengths are associated with both rest mass and speed. This possibility provided the motivation to conduct the new experiment.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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