Exit pupil expander with non-hexagonal 2D grating
Bibliographic record
Abstract
Recently, an increasing interest in utilizing 2D gratings on the waveguide for exit pupil expander (EPE) designs has been observed. However, to the best of author’s knowledge, most of these designs use only hexagonally arranged lattice for the 2D grating and do not investigate how varying lattice vector angle can help the optimization. In this paper, we will first discuss the consideration of non-orthogonal lattice vectors in Rigorous Coupled Wave Analysis (RCWA), provided by Ansys Lumerical RCWA. We will explain how a hexagonal 2D grating can be simulated with a set of orthogonal lattice vectors and why the same trick does not work for non-hexagonal 2D grating with arbitrary lattice vector angle. We will explain what it means when the grating is non-hexagonal in k-space and real space, and the consequent benefits. Based on the concept, initial simulation results, using dynamic link between Ansys Lumerical RCWA and Ansys Zemax OpticStudio, will be demonstrated. The simulation with different lattice vector angle are performed for understanding the system behavior. Finally, we set up an optimization workflow in Ansys optiSlang, considering lattice vector angles as one of variables. The optimization results will be discussed.
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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) | 0.002 | 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".