Realization and optimization of phase-shifted distributed feedback fiber Bragg grating Raman lasers
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Bibliographic record
Abstract
Single-frequency laser sources have found a great number of applications, but are difficult to implement and suffer from poor robustness, poor quality (linewidth and stability), and are generally expensive to fabricate. One solution for a cheaper and simpler single-frequency source is a π-phase-shifted distributed feedback (DFB) fiber Bragg grating (FBG) based laser. Typically, such a laser usually uses a fiber with rare-earth dopants as an active medium for gain. However, its operating wavelength is limited to the emission bandwidth of the rare-earth dopant in the fiber. A proposed solution to overcome this limitation is to use Raman gain. Raman DFB fiber lasers have been successfully demonstrated, and a few simulations have been undertaken and reported. However, a thorough study of parameters and careful optimization has not been reported due to the long computation time and difficulty in the fabrication of long FBGs with known parameters. We demonstrate here, with the aid of a fast but exact method, a detailed optimization study on phase-shifted Raman DFB fiber lasers. These theoretical results are compared with the experimental operation of many fabricated FBGs thanks to a newly developed fabrication technique for the replication of FBGs. We show that fabricated lasers have poor performance compared to simulations of ideal lasers. We also show that the difference in performance is due to the high internal optical intensity induced nonlinear thermal gradient along the FBG.
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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) | 0.000 | 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