Light-field microscopy with entangled photons
Bibliographic record
Abstract
Light-field microscopy (LFM) is a 3D microscopy technique whereby volumetric information of a sample is gained in a single shot by simultaneously capturing both position and angular information of light emanating from a sample. Classical LFM designs generally require a trade-off between position and momentum resolution, requiring one to sacrifice resolving power for increased depth of field (DOF). Here, I present a quantum based LFM design that utilizes the inherent correlation between position-momentum entangled photon pairs and does not require this position- momentum resolution trade-off. We demonstrate that a resolving power of 5<i>μ</i>m can be maintained with a DOF of 500<i>μ</i>m, approximately an order of magnitude to that of a classical LFM. In the extreme, at a resolving power of 100<i>μ</i>m, it is possible to achieve near infinite DOF.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".