Parameter optimisation of pi-shifted distributed feedback fiber Bragg grating Raman lasers
Bibliographic record
Abstract
π-shifted distributed feedback (DFB) fiber Bragg grating (FBG) Raman lasers have been demonstrated in the last few years [1, 2] and many attempts at optimisation have been made using theoretical calculations [3]. However, due to the limitations of resolution of the coupled-mode equations, theoretical optimisation has been limited to a few case studies. By using a simple approximation, we demonstrate here in a detailed study, all possible cases for Raman generation in DFB lasers. DFB emission is approximated as single-frequency and solved in the Fourier Domain. The pump depletion equation is solved separately with an initial approximation of the fields which is then adjusted iteratively to fit the calculated fields until a solution is found. The control parameters during fabrication are the FBG coupling strength (ł <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ac</sub> ), its length and the value and position of the phase shift. Other parameters more difficult to control also include losses and non-linear coefficient. All these parameters have been varied to determine the threshold and slope efficiency of DFB lasers in typical high NA silica fiber. These calculations have been corroborated with complete resolution of the coupled-mode equations as previously reported in the literature.
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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 | 0.000 | 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 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".