Erbium-doped phosphosilicate fiber amplifiers: a comparison of configurations for the optimization of noise figure and conversion efficiency
Bibliographic record
Abstract
Extending the amplification bandwidth of erbium-doped fiber amplifiers (EDFAs) is one of the most cost-effective means of expanding the fiber transmission capacity. In conventional aluminosilicate EDFAs, gain drops sharply beyond 1605nm. Several new or modified erbium host materials have been used to extend the amplification band to beyond the conventional L-band, such as tellurite, bismuth-oxide, antimony silicate, P-doped aluminosilicate, and phosphosilicate EDFAs. Although tellurite and bismuth-oxide based EDFAs have wider bandwidths compared to that of demonstrated phosphosilicate (P-Si) EDFAs, P-Si EDFAs have been shown to provide better noise performance when the gain bandwidth is extended to 1620 nm. In addition, unlike tellurite or bismuth-oxide fibers, P-Si EDF does not exhibit increased nonlinearity or weakened reliability, compared to conventional aluminosilicate EDFs. Furthermore, phosphosilicate erbium fiber is compatible with other silica fibers and can be fusion spliced to the standard SMF silica fiber with high return loss and extremely low splice loss. These properties make the P-Si EDF a top contender for commercial extended L-band EDFAs. One key issue in the design of the extended L-band amplifiers is the optimization of power conversion efficiency while keeping the noise figure low. In this paper, we explore various amplifier configurations and compare their performances experimentally. We report high-power P-Si EDFAs with simultaneous improvement of PCE and NF by a combination of a single-pass low-noise stage with one or two double-pass high-efficiency stages. The best configuration yields high power (22dBm), low NF (5.5dB maximum over 1570-1620 nm band), and high efficiency (27% overall PCE after gain flattening).
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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 | 0.000 |
| 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) | 0.000 | 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".