Impact of residual dispersion and ASE noise on the performance optimization of all-optical regenerators utilizing self-phase modulation in a highly nonlinear fiber
Bibliographic record
Abstract
The performance of an all-optical regenerator utilizing self-phase modulation in a highly nonlinear fiber and offset optical filtering is assessed using computer simulation. By varying the bandwidth and offset of the optical filter, the Q-factor performance of the regenerator is near-optimized for systems impaired by amplified spontaneous emission (ASE) noise and systems impaired by both residual dispersion (RD) and ASE noise. Generally, the near-optimum bandwidth and offset of the optical filter differs for these two types of systems. It is found that the selection of the bandwidth and offset is more stringent for systems with ASE noise only. For systems with RD and ASE noise, the selection of the filter bandwidth and offset depends on the amount of RD with quite different trends being observed. The regenerator is more effective when the RD is negative. The implication that the dispersion of the highly nonlinear fiber has on the regenerator performance is examined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".