Full Characterization of Circularly Polarized Orthomode Transducers Using Short-Circuit Termination
Bibliographic record
Abstract
A straightforward retrieval algorithm for the circularly polarized (CP) orthomode transducer (OMT) scattering matrix is proposed, utilizing three offsets short-circuited Common Port terminations. Leveraging equivalent voltage theory, a detailed, systematic mathematical analysis is presented to characterize the impedance matching of all ports, isolation, transmission, co-polarization, and cross-polarization without requiring the back-to-back (BTB) configuration or additional load terminations. Moreover, the scattering matrix of dissimilar BTB OMTs is predicted by fully identifying a single CP OMT. All mathematical analyses are first validated through full-wave simulations of various CP OMTs, thereby obviating the uncertainties introduced by fabrication tolerances. Experimental validation using a novel OMT with an irregular hexagonal cross section also assures the algorithm’s robustness and broad applicability. The retrieved phase constant shows strong agreement due to minimal fabrication tolerances in the Common Port opening, while the retrieved scattering parameters exhibit satisfactory agreement with minor deviations influenced by fine structural dimensions. Therefore, the proposed analysis establishes a robust, low-cost framework using only a standard two-port vector network analyzer (VNA), offering key advantages over existing far-field and BTB approaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".