Analysis of gain transients in cascades of discrete fiber Raman amplifiers
Bibliographic record
Abstract
Discrete fiber Raman amplifiers (DFRAs) are a candidate technology for extending the transmission capacity of dynamic optical networks such as agile all-photonic networks. However, as with conventional doped fiber amplifiers, they suffer from power transients following the addition or removal of channels which results in system penalties due to degradation in optical signal-to-noise-ratio or nonlinear effects. Recently, several groups have investigated all-optical gain-clamping, which consists in introducing a lasing feedback signal in the amplifier, as a means for gain control and mitigating the power transients. In this paper, we theoretically analyse the dynamic response of DFRA cascades in the worst possible case of power transients. In particular, we consider a 64-channel system in which all of the channels except one (i.e. the surviving channel) are cut from and subsequently added to the first amplifier of the cascade. While previous studies have focused on the transient response of the surviving channel when all of the amplifiers in the cascade are either unclamped or gain-clamped, we consider here cascades involving combinations of unclamped and gain-clamped DFRAs. We vary the number and the position of the gain-clamped DFRAs in the cascade to determine whether a cascade in which only a few amplifiers are gain-clamped can be effective for controlling the power transients within tolerable limits. To simulate the dynamic response of the DFRAs, we have developed a new technique, based on a temporal average power analysis. In our simulations, we also take into account the location of the surviving channel and the operational regime of the amplifiers. Our results show that the location of the gain-clamped DFRAs in a mixed cascade is not important when the amplifiers are operated in small-signal regime; on the other hand, as the input signal power is increased, it becomes more preferable to place the gain-clamped amplifiers at the beginning of the cascade.
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.
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".