High-speed polarization-independent plasmonic modulator on a silicon waveguide
Bibliographic record
Abstract
The electrical bandwidth of an electro-optic modulator plays a vital role in determining the throughput of an optical communications link. We propose a broadband plasmonic electro-optic modulator operating at telecommunications wavelengths (λ 0 ∼ 1550 nm), based on free carrier dispersion in indium tin oxide (ITO). The ITO is driven through its epsilon-near-zero point within the accumulation layers of metal-oxide-semiconductor (MOS) structures. The MOS structures are integrated into a pair of coupled metal-insulator-metal (MIM) waveguides aligned on a planarized silicon waveguide. The coupled MIM waveguides support symmetric and asymmetric plasmonic supermodes, excited adiabatically using mode transformation tapers, by the fundamental TM 0 and TE 0 modes of the underlying silicon waveguide, respectively, such that the modulator can operate in either mode as selected by the input polarisation to the silicon waveguide. The modulator has an active section 1.5 to 2 µm long, enabling the modulator to operate as a lumped element to bandwidths exceeding 200 GHz (3 dB electrical, RC-limited). The modulators produce an extinction ratio in the range of 3.5 to 6 dB, and an insertion loss in the range of 4 to 7.5 dB including input/output mode conversion losses. The AC drive voltage is ±1.75 V. The devices comprise only inorganic materials and are realisable using standard deposition, etching and nanolithography techniques.
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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".