A compact 100 GHz femtojoule silicon-organic hybrid modulator based on a novel Mach–Zehnder interferometer design
Bibliographic record
Abstract
Abstract In this paper, a high-speed, low-power and compact silicon-organic hybrid (SOH) modulator operating at the telecom wavelength is presented. The modulator is based on the mature and widespread silicon-on-insulator technology with a device layer of 220 nm. The proposed design utilizes a slot waveguide in a loop-terminated Mach–Zehnder interferometer (LT-MZI) configuration. The LT-MZI is twice as compact as the conventional MZI. Accordingly, the LT-MZI modulator exhibits a reduction in capacitance by a factor of two, which subsequently enhances the modulator speed and power consumption by a factor of two. An electro-optic polymer is used as it exhibits fast and strong electro-optic effects. Finite element and finite difference simulations show that for a driving voltage of only 0.5 V our modulator arms’ length is as low as 167 µ m resulting in a V π × L product of only 0.084 V mm, 10.41 fF capacitance and up to 100 GHz speed with corresponding energy consumption of only 6.755 fJ bit −1 . Results based on 3D finite difference time domain simulation show that our modulator can work over a large optical bandwidth of 60 nm with an extinction ratio (ER) greater than 23 dB and insertion loss (IL) less than 1.7 dB, reaching ER = 40 dB and IL = 1.15 dB at λ = 1.55 µ m.
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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".