Effectiveness of gain control in EDFAs against traffic with different levels of bursty behaviour
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous publications have addressed the impact of bursty, self-similar traffic on erbium-doped fibre amplifiers (EDFA). Several gain control techniques have been suggested to combat the gain fluctuations of EDFA with this type of traffic. The effectiveness of two such methods are investigated, namely highly inverted amplifiers and all-optical gain clamping, while varying the parameters characterising the burstiness of the sources. While previous publications have focused on the effect of the average load or activity factor, the paper further investigate the dependence on the relative variability of the packet burst lengths (ON times), and lengths of the interburst idle times (OFF times). Both gain control methods reduce the output power and signal-to-noise ratio excursions with respect to a standard amplifier chain. The authors find that, for an eight channel WDM system and a cascade of six EDFAs, all-optical gain clamping can reduce the variations by a factor of five, provided adequate power is present in the clamping laser, while highly inverted amplifiers have variations reduced by a factor of two. The authors find that, in a clamped chain, the source activity factor does not uniquely determine the required level of lasing power. The authors also deduce that information on the relative variability of ON and OFF times is essential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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 it