Assessing Performance of Silicon Photonic Modulators for Pulse Amplitude Modulation
Bibliographic record
Abstract
Silicon photonic (SiP) electro-optic modulators are a key component in cost-efficient and integrated optical transmitters. Modulator design traditionally uses figure of merits (FOMs) that characterize modulation efficiency and propagation loss of light, which underestimate the modulator-induced power penalty due to intersymbol interference, as they do not consider the electro-optic bandwidth limitation. We show that in the presence of limited electro-optic bandwidth of the SiP modulator, the conventional FOMs, such as VπL and V παL, are unable to predict the minimum transmitter power penalty (TPP). Normalized optical modulation amplitude (OMAN) is proved through simulation to be a reliable tool to predict the minimal TPP point. Then, we introduce a new FOM that includes not only the efficiency of the modulator, but also the bandwidth limitation from the SiP electro-optic modulator. The new FOM that is derived from OMAN translates the system-level requirements of a PAM-M optical link to the device-level design parameters. This FOM can be hired to optimize driving voltage swing, bias voltage, and phase-shifter length or to simply choose a SiP modulator with minimal imposed TPP.
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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 | 0.002 |
| 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 | 0.001 | 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".