Optimization of Scalar and Bianisotropic Electromagnetic Metasurface Parameters Satisfying Far-Field Criteria
Bibliographic record
Abstract
Electromagnetic metasurfaces offer the capability to realize almost arbitrary power conserving field transformations. These field transformations are governed by the generalized sheet transition conditions, which relate the tangential fields on each side of the surface through the surface parameters. Ideally, engineers would like to determine the surface parameters for transformations based on their application-specific far-field criteria. However, determining the surface parameters to satisfy these criteria is challenging without direct knowledge of the tangential fields on one side of the surface, which are not unique for a given far field pattern. As a result, current design is restricted to analytical examples where the tangential fields are solvable or other ad hoc methods. This paper presents a convex optimization-based scheme which determines surface parameters, such as surface impedance, admittance, and magneto-electric coupling, which satisfy far-field constraints such as beam magnitude, side lobe level, and null locations. The optimization is performed on a model constructed using the method of moments. This model incorporates edge effects and mutual coupling. The resulting non-convexity from this model is relaxed using the alternating direction method of multipliers. Examples of this optimization scheme performing multi-criteria pattern forming, extreme angle small surface refraction, and Chebyshev beamforming are presented.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".