Ternary optimization for designing metasurfaces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A fully automated approach for designing metasurfaces whose unit cell may include metallic vias is proposed. Towards this aim, a ternary version of the particle swarm optimization (PSO) algorithm is employed in order to find the optimal metallic pattern and via-hole positions simultaneously. In the proposed design method, the upper surface of the unit cell is first pixelated. One of the possible three states of a metallic covered pixel, an uncovered etched pixel and a pixel containing a centered metalized via-hole is assigned to each pixel. The optimal state of each pixel is then determined by utilizing a ternary PSO algorithm to achieve favorable design goals. This method can be used for designing various metasurfaces as well as other via-assisted electromagnetic structures. As a proof of concept, the proposed method was applied to design two surfaces: a frequency selective surface with a minimum resonance frequency, and a linear-to-circular polarization converter with a maximum polarization conversion bandwidth. Comparison of the results with previous works confirms the efficiency and capability of the proposed method to design diverse metasurfaces in an automated fashion without the need for any theoretical or physical model.
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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 it