Experimental demonstration of a low-loss low-reflectivity TM-pass polarizer based on tilted subwavelength metamaterials
Bibliographic record
Abstract
The silicon-on-insulator platform exhibits strong birefringence, often requiring single-polarization operation to ensure the optimal performance of integrated photonic systems. On-chip polarizers that suppress unwanted polarization states are key in this scenario. Achieving efficient TE-mode suppression with low-loss TM transmission is particularly challenging on the standard 220 nm silicon platform because of the stronger confinement of the TE mode compared to the TM mode. In this work, we experimentally demonstrate a TM-pass polarizer fabricated on a standard 220 nm silicon platform with a single etch step. By leveraging subwavelength metamaterials, we engineer a Bragg grating that reflects the fundamental TE mode into the first-order TE mode, which is radiated away, while allowing the TM mode to pass with minimal loss. The device achieves a measured extinction ratio exceeding 20 dB and insertion losses below 1 dB across a bandwidth of 170 nm, with a total footprint of 17.84 µm by 1.1 µm. We furthermore demonstrate, for the first time, to our knowledge, in Bragg–based polarizers, measured back-reflections for TE polarization below −18.9dB.
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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".