Imaging properties of dielectric photonic crystal slabs for large object distances
Bibliographic record
Abstract
We extend the understanding of the imaging properties of dielectric photonic crystal slabs to object distances that are larger than the slab thickness. We specifically consider hexagonal crystal lattices in the second band. For object distances smaller than the slab thickness, the image distance is a negative linear function of the object distance as expected for negative refractive index materials. The effective refractive index extracted from this linear object-image relation is close to the negative unity value calculated for infinite photonic crystal using the plane wave expansion method. In contrast to previous predictions, we find that a real image can still be formed for object distances up to twice the slab thickness. In this regime the image distance changes little as the object distance increases, and can thus be described as the saturated image regime. Sub-wavelength resolution performance can be approximately maintained even for these larger object distances. The full-width half-maximum spot size at the image is approximately (0.43-0.55)lambda up to object distances 1.5 times the slab thickness. By evaluating the image angular frequency spectrum we show that this sub-wavelength resolution imaging at larger object distances is due to evanescent waves that arise within the slab, rather than being directly transferred from the object. The eventual loss of image resolution is due to interference side lobes which enter the image plane.
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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 | 0.000 |
| 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 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".