Observation as Field Participation: Reinterpreting the Double-Slit Experiment through Energetic Coherence
Bibliographic record
Abstract
This article presents a conceptual and experimentally illustrated reinterpretation of the double-slit experiment based on energetic coherence and Δφ-modulation within the Ilefos Model. Using a classical optical setup—including a 532 nm laser, multi-aperture plates, and photodiode detectors—the study investigates how interference patterns transform under different geometrical and observational conditions. Three coherence regimes are documented: (1) baseline interference, (2) complex multi-aperture diffraction, and (3) speckle-pattern coherence under polarization. The results demonstrate how small structural changes in the optical path lead to significant reorganizations of the field’s coherence distribution, supporting the hypothesis that measurement effects may be interpreted as field participation rather than particle-path detection. While the experiment operates in the classical regime (milliwatt intensities, not single photons), the illustrated coherence transitions align with the theoretical Δφ-framework describing how structured energy patterns respond to constraints and observation. This publication serves as a pilot study for future work involving higher-sensitivity detectors and single-photon sources, and provides a conceptual bridge between classical interference behavior and coherence-based interpretations of quantum measurement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.002 |
| 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".