Semi-analytical models to engineer a metalens composed of various meta-atoms
Bibliographic record
Abstract
We developed semi-analytical models to efficiently and rapidly obtain the propagation characteristics of square nanopillar and nanoring meta-atoms. We show that such analytical models can predict the output phase profile and chromatic behavior of a metasurface composed of various meta-atoms. We found that said models are accurate enough so that an optical designer can use them as a quick and pertinent alternative to tedious and time-consuming FDTD simulations. A mixed array of three different nanostructures combining square nanopillars, nanorings, and nanorods has been designed and compared to FDTD simulation with good conformity. Thus, we show the pertinence of the two semi-analytical models and the possibilities granted by the mixing of various meta-atoms. This work allows for more flexibility and design freedom for quick modeling of metasurface properties and adds to previous models developed in our research group.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".