Parasitic Mode Conversion in $Z$- Propagating Lithium-Niobate Waveguides
Bibliographic record
Abstract
The propagation characteristics of near-Z-axis lithium-niobate waveguides are investigated, considering the finite crystallographic-alignment tolerances. We expand on the previous models that have considered only the departures from the Z-axis in the plane of the substrate ("yaw") to include the effects of "pitch" and "roll." We find that a combination of yaw and pitch couples the major electric-field components of the fundamental quasi-TE and quasi-TM modes through off-diagonal permittivity components. When these two rotations are both larger than ~0.1deg, the imaginary coupling coefficient associated with the overlap of the major field components becomes larger than the real coefficient, associated with the coupling of the longitudinal TM component to the transverse TE component, that results from yaw alone. We show numerically, as well as experimentally, that unintentional crystallographic-alignment errors can result in substantial mode conversion, affecting the extinction ratio and linearity of Z-propagating modulators. The results also indicate that waveguides with intentional yaw will have mode-conversion characteristics that are highly sensitive to any unintentional pitch resulting from the boule slicing/polishing process. We highlight the importance of crystallographic alignment as well as the role of modal birefringence in suppressing undesired mode conversion
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".