Sub-wavelength passive single-shot computational super-oscillatory imaging
Bibliographic record
Abstract
Super-oscillatory (SO) imaging presents a passive solution to the sub-diffraction imaging challenge. The point spread functions (PSFs) of SO systems are band-limited and locally oscillate faster than their highest Fourier frequency. Because of this property, SO imaging systems are not bound by the Nyquist limit, allowing them to acquire details finer than the diffraction limit. In this work, we present a comprehensive theoretical analysis of passive incoherent SO imaging, leading to two key results. First, we show that the SO property of an imaging system is preserved when the system is combined with a general system of lenses. This opens the door for integrating SO imaging into existing microscopes and telescopes. Second, we show that incoherent SO imaging cannot resolve feature sizes below λ / 2 because of the inability to achieve incoherence at finer scales. This establishes the operational limits of the approach. We demonstrate our theory experimentally with a compound SO system that achieves sub-wavelength resolutions using high-NA lenses and Fourier spectrum modulation.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".