Output power excursions in a cascade of EDFAs fed by multichannel burst-mode packet traffic: experimentation and modeling
Bibliographic record
Abstract
A serious problem facing wavelength-division multiplexed (WDM) networks with fiber amplifier cascades is transient cross-gain saturation or gain dynamics of fiber amplifiers. Attention has been focused primarily on circuit-switched scenarios. When the number of WDM channels transmitted through a circuit-switching network varies, channel addition/removal will tend to perturb signals at the surviving channels that share all or part of the route. Even more serious bit error rate deterioration can arise in WDM packet switched burst mode networks. In this paper, we present experimental and theoretical results demonstrating the effect of fast power transients in erbium-doped fiber amplifiers (EDFAs) on packetized traffic transmitted through a chain of five EDFAs. Traffic of a local-area network has been transmitted over three channels. The effect of EDFA cross-gain saturation due to the burstiness of the traffic has been observed in a continuous-wave monitoring channel. The stabilizing effect of gain clamping of the first EDFA in the cascade has been investigated. The experimental results are extended to eight-channel WDM system using a large signal numerical analysis.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".