Output Optical Power Enhancement of Push-Pull Modulated DFB Laser With Asymmetric Structure
Bibliographic record
Abstract
Conventional push-pull modulated (PPM) distributed feedback (DFB) lasers exploit structures with symmetry, which wastes a significant amount of the optical power output from the rear facet. To improve the power efficiency, PPM DFB lasers with asymmetrically coated facets can be considered. However, the resulted imbalanced push-pull modulation causes a dip in device small-signal intensity modulation response near the carrier-photon resonance (CPR) frequency, which distorts the waveform and even cuts off the bandwidth. This work proposes an asymmetric section length design in conjunction with the asymmetric facet coating to offset the aforementioned effect on device intensity modulation response. With a delayed push-pull modulation (DPPM) scheme further incorporated, our simulation result shows that the PPM DFB laser with optimized asymmetric structure can enhance the power efficiency and maintain a smooth modulation bandwidth up to around 50 GHz.
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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".