Guided-Wave-Excited Binary Huygens’ Metasurfaces for Dynamic Beamforming
Bibliographic record
Abstract
This letter presents a simple, yet effective method for dynamic beamforming that can be readily realized by integrating a tunable binary Huygens’ metasurface with a leaky-waveguide antenna. Heretofore, dynamic beamforming has been difficult to achieve owing to the challenges in attaining full 360$^\circ$of dynamic phase tunability, while also independently controlling the local aperture amplitudes from zero to unity. In contrast, the hereby proposed method only requires$\pm 90^\circ$of dynamic phase tunability (with arbitrary transmission amplitudes), thereby significantly alleviating the stringent tuning requirements. In particular, the proposed method is obtained by leveraging the antenna-array and holography theories, and utilizing the idea of “virtual” electric line sources. Based on full-wave simulations, we demonstrate the versatility of the proposed method through the designs of a Huygens’-metasurface-assisted leaky-waveguide antenna that generates various complex far-field patterns such as sector beams and Dolph–Chebyshev patterns.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".