Relativity as a Consequence of Quantum Entanglement: A Quantum Logic Gate Space Model for the Universe
Bibliographic record
Abstract
Everything in the Universe is assumed to be compromised of pure reversible quantum Toffoli gates, including empty space itself. Empty space can be configured into photon or matter gates simply by swapping logic input information with these entities through the phenomenon of quantum mechanical entanglement between photons and empty space Toffoli gates. The essential difference between empty space, photons and matter gates are the logic input values of their respective Toffoli gates. Empty space is characterized by an inability for the logic inputs to influence the internal logic state of its Toffoli gates since the control lines are set to logic 0. Photons and matter are characterized by Toffoli gates where the control lines are set to logic 1 enabling their logic inputs to control their internal logic states allowing for their interaction according to the laws of physics associated with reality. Photons swapping logic input information with empty space results in the propagation of light. Photons facilitating the swapping of information between matter and empty space gates leads to the laws of motion including relativity. This model enables the derivation of many physical laws from purely quantum mechanical considerations including the Heisenberg Uncertainty Principle, the Lorentz transformations of special relativity, and the relationship between relativistic energy and mass. The model provides a possible explanation for many physical phenomena including dark matter, anti-matter, and an inflationary Universe.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".