Flatness enhancement of multi-wavelength Brillouin-Raman fiber laser with 10 GHz spacing utilizing Raman pump power distribution
Bibliographic record
Abstract
A simple high flat amplitude multi-wavelength Brillouin-Raman fibre laser (MBRFL) with 10 GHz spacing and excellent optical signal-to-noise ratio (OSNR) in C-Band spectral region is demonstrated. The laser consists of a linear cavity in which 12 km dispersion compensating fiber (DCF) in addition to 49 cm Bismuth-oxide Erbium doped fiber (Bi-EDF) are employed as a gain medium for amplification. The impact of Raman pump power distribution through changes in coupling ratio on amplitude flatness is carried out by comparing the peak power discrepancy between odd- and even-order Brillouin Stoke lines. This is the main property that allows the efficient controlling of gain propagation between lasing lines that is vital for Stokes flattening initiation and other output spectra characteristics. The attainment of MBRFL with outstanding OSNR necessitates the utilizing of Bi-EDF as a noise suppressor. By utilizing a 50/50 coupler, 354 identical channels together with uniform Brillouin Stokes linewidth within only 0.3-dB maximum power difference between adjacent channels is generated. The average OSNR and Stokes power are 28 dB and -5 dBm respectively when the RPP is set at 1300 mW. To date, this is the highest flatness 10 GHz spacing MBRFL with outstanding OSNR attained in MBRFL that incorporate only a single Raman pump unit.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".