Polarization management for silicon photonic integrated circuits
Bibliographic record
Abstract
Abstract Polarization management is very important for photonic integrated circuits (PICs) and their applications. Due to geometrical anisotropy and fabrication inaccuracies, the characteristics of the guided transverse‐electrical (TE) and transverse‐magnetic (TM) modes are generally different. Polarization‐dependent dispersion and polarization‐dependent loss are such manifestations in PICs. These issues become more severe in high index contrast structures such as nanophotonic waveguides made of silicon‐on‐insulator (SOI), which has been regarded as a good platform for optical interconnects because of the compatibility with CMOS processing. Recently, polarization division multiplexing (PDM) with coherent detection using silicon photonics has also attracted much attention. This trend further highlights the importance of polarization management in silicon PICs. The authors review their work on polarization management for silicon PICs using the polarization independence and polarization diversity methods. Polarization issues and solutions in PICs made of SOI nanowires and ridge waveguides are discussed.
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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 | 0.001 | 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".