Optimal operation conditions for a push-pull dual-ring silicon modulator from a viewpoint of dispersion engineering and linearity
Bibliographic record
Abstract
A silicon dual-ring modulator designed for chirp tuning in an intensity-modulated system is described and its performance is modelled. Previous experimental work using this device geometry partially demonstrates the advantages of the dual-ring approach. However, we provide here the first comprehensive theoretical treatment from which optimal operation parameters can be deduced. The device consists of two, over-coupled micro-ring resonators independently coupled to a MachZehnder interferometer and driven by a push-pull signal. Utilizing the interference effect provided by the Mach-Zehnder geometry, the device produces a large modulation depth and improved linearity, compared to single ring geometries, provided that the appropriate resonance detuning between the two micro-ring resonators and the correct phase condition are met. The differential drive configuration generates opposing signs of dispersion from the two rings leading to an adjustable modulation chirp that can be tuned into the negative or positive regime, or can be fixed at an essentially zero-chirp condition. System-level simulation is reported to validate the chirp tuning for a non-return-to-zero signal at a modulation rate of 28 Gb/s.
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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 | 0.001 |
| 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".