Matched, Low-Loss, and Wideband Graded-Index Flat Lenses for Millimeter-Wave Applications
Bibliographic record
Abstract
Low reflection, low-loss, and wideband graded-index (GRIN) flat artificial dielectric lenses utilizing GRIN antireflection (AR) layers are developed in this paper. The GRIN lens and the AR layers are realized by perforating regular microwave substrates. The resulting reflectance, transmittance, and dielectric losses of the designed lens are 0.06% (-32.2 dB), 96.7% (-0.14 dB), and 3.3% (-14.8 dB), respectively. This highly efficient lens is designed to collimate a commercial pyramidal horn at 34.3 GHz. Excellent agreement is observed between the simulated and measured results. The flat lens decreases the half-power beamwidth of the horn from 10° to 6° and increases the peak gain by an average of 5 dB within the frequency range of 26-39 GHz.
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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".