Observing Quantum Entanglement: Interference Patterns and Breaking Bell's Inequality
Bibliographic record
Abstract
In this two-part experiment, we studied the interference pattern of a laser pointer interfering with itself through a Mach-Zehnder interferometer as well as tested Bell’s Inequality for entangled particles via parametric down conversion. The predicted results were a fringe pattern that was purely circular with distinct fringes, however, the results of the laser pointer interference were inconclusive due to significant error in the alignment of the interferometer. In reference to the second part of our lab, due to COVID-19 restrictions, time ran out for us to complete data collection of the coincidence counts between the down converted beams of our Gallium Nitride laser. We attributed the lack of coincidence counts to error in the precision of the alignment of the optical apparatus. Thus, we used reference data instead to calculate the statistic, S=2.31 ± 0.04, to compare with Bell’s Inequality of |S| ≤ 2. Our result using the reference data did exceed Bell’s Inequality, as was expected of quantum mechanics, being non-local.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".