Entanglement-enhanced measurement of a completely unknown optical phase
Why this work is in the frame
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Bibliographic record
Abstract
Precise interferometric measurement is vital to many scientific and technological applications. Using quantum entanglement allows interferometric sensitivity that surpasses the shot-noise limit (SNL)1,2. To date, experiments demonstrating entanglement-enhanced sub-SNL interferometry3,4,5,6, and most theoretical treatments7,8,9,10,11,12,13, have addressed the goal of increasing signal-to-noise ratios. This is suitable for phase-sensing—detecting small variations about an already known phase. However, it is not sufficient for ab initio phase-estimation—making a self-contained determination of a phase that is initially completely unknown within the interval [0, 2π). Both tasks are important2, but not equivalent. To move from the sensing regime to the ab initio estimation regime requires a non-trivial phase-estimation algorithm14,15,16,17. Here, we implement a ‘bottom-up’ approach, optimally utilizing the available entangled photon states, obtained by post-selection5,6. This enables us to demonstrate sub-SNL ab initio estimation of an unknown phase by entanglement-enhanced optical interferometry. Entangled photon states, obtained by post selection, are used to perform interferometric phase measurement with a sensitivity beyond the shot-noise limit.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it