Engineered <inline-formula> <tex-math notation="LaTeX">$\pi$ </tex-math> </inline-formula>-Phase-Shifted Fiber Bragg Gratings for Efficient Distributed Feedback Raman Fiber Lasers
Bibliographic record
Abstract
Distributed feedback Raman fiber lasers with π-phase-shifted uniform gratings are modeled and simulated in the steady state, to optimize their performance. Using the parameters of realistic devices, it is found that the position change of the π-phase-shift in a constant-strength uniform grating has a significant impact on the laser performance including right and left-hand-side output power and emission frequency, and linewidth. Also, it is shown that the optimum phase-shift position to maximize the laser uni-directionality is dependent on pump power and fiber loss value. A new design approach based on an engineered π-phase-shifted step-like-strength uniform grating is presented demonstrating that even for a high-loss fiber (0.1 dB/m), the laser power and linewidth can be efficiently increased and decreased by ~25% and ~15%, respectively, for the same total device length and pumping condition, just by the proper choices of the phase-shift position and two coupling coefficients.
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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".