A Systematic Circuit-based Approach to Efficiently Realize Singleand Dual-band Circular Polarizers
Bibliographic record
Abstract
This paper describes a systematic circuit-based approach which streamlines the realization of linear-to-circular polarizers. Two demonstrative designs are presented and the related challenges and opportunities are discussed. The first design is a low-loss polarizer, composed of two identical frequency selective surfaces (FSSs). The reduced number of layers yields a total profile of one-tenth of a wavelength, while providing high polarization purity and high transparency. This design features axial ratio of less than 3 dB (1 dB) over 10% (4%) fractional bandwidth, with low insertion loss of 0.5 dB (0.36 dB). The second design is a dual-band polarizer comprised of five FSS layers, which demonstrates low insertion loss of 0.6 dB and 4 / 2.7% bandwidth at 20 / 30 GHz. The unit cell used to realize the equivalent circuit elements of the polarizers is based on a subwavelength FSS grid, the so-called modified Jerusalem cross, recently introduced in the literature. The low profile and compactness of this cell (0.17λ 0 ×0.17λ 0 ×0.11λ 0 ) enhance the accuracy of the circuit-driven approach, relax the computational analysis, and could potentially reduce the sensitivity to the angle of incidence. In particular, the low insertion loss of such designs makes them appealing for a variety of terrestrial and satellite applications.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".