Support Vector Regression-Enabled Optimization Strategy of Dual Circularly-Polarized Shaped-Beam Reflectarray With Improved Cross- Polarization Performance
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Bibliographic record
Abstract
This work presents the optimization of a dual circular-polarized (CP) shaped-beam reflectarray with improved performance. To that end, the design methodology leverages surrogate models based on support vector regression (SVR) of the electromagnetic response of the constituent unit cell for a direct layout optimization of the antenna. The dual CP capability is achieved using a linear polarization (LP) Jerusalem cross integrated with an LP-to-CP polarization converter. A full description of the reflectarray analysis in CP is given. We also provide a missing demonstration in the literature of the fact that the direct coefficients in CP shape the copolar (CO) pattern of the corresponding polarization. This is applied to the optimization of a dual CP reflectarray with an isoflux pattern, achieving a reduction of more than 9 dB in the crosspolar (XP) pattern.
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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