Enhanced Modulation Bandwidth by Delayed Push–Pull Modulated DFB Lasers
Bibliographic record
Abstract
The bandwidth of a distributed feedback (DFB) directly modulated laser (DML) is limited by its carrier-photon resonance (CPR) frequency. A viable approach to break the bottleneck is to introduce a photon-photon resonance (PPR), since the PPR can happen at a much higher frequency than the CPR. Among the many structures that can possibly generate the PPR, the dual-sectional push-pull modulated (PPM) DFB is of particular interest for its fabrication cost-effectiveness as no regrowth is required. The PPR in the PPM DFB, however, usually shows a rapid roll-off on both edges, which brings in an indentation on the lower frequency side of the PPR peak and, consequently, cuts off the bandwidth. To compensate for this dip, we introduce a detuned PPR and restart the CPR response by exploiting a time delay between the differential signals applied to the PPM DFB. Our simulation result shows that the broadened PPR peak and the restarted CPR response indeed mitigate the dip and effectively expand the PPM-DFB's bandwidth to approximately 50 GHz, a value double that of the conventional (single-sectional) DFB DML.
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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 | 0.001 | 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".