Evanescent-to-propagating wave conversion in sub-wavelength metal-strip gratings
Bibliographic record
Abstract
Transmitting sub-wavelength information to the far-zone is of great interest for various electromagnetics and optics applications, e.g., for overcoming the diffraction limit in imaging or enabling multiple-input/multiple-output operation in closely spaced antennas. The common phenomenon in these applications is the conversion of evanescent to propagating waves. In this paper, we rigorously analyze and study evanescent-to-propagating wave conversion based on sub-wavelength metallic strip gratings. A theory is provided, which fully captures all diffracted fields and clearly highlights this conversion phenomenon. The Green's function of the strip gratings is constructed by introducing the spectral impulse response. This method solves the problem of the aperiodic excitation of the periodic grating and along the way provides insight and clear explanation of the evanescent-to-propagating wave conversion that takes place. All proposed results are validated against full-wave electromagnetic simulations. The theory is used to highlight and explain “extraordinary” transmission through a sub-wavelength metal strip grating when excited by a current source. Finally, an interesting application is presented where a nonradiating arrangement of sources is made to radiate by converting and diffracting its reactive near-field spectrum into the propagating regime using a simple metal strip grating.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".