Optimization of signal gain and core composition for low photodegradation in Yb-doped fiber amplifiers
Bibliographic record
Abstract
Photodarkening and photobleaching processes affect the level of photodegradation of Yb-doped fibers. Characterization and modeling of each process is crucial to understand how to optimize the operating conditions of fiber amplifiers and lasers to obtain acceptable output power degradation. We show that photobleaching is a key factor in the modeling and simulation of a 10-ns pulsed Yb-doped LMA fiber amplifier. Each parameter of the model was separately determined from induced excess loss measurements under selective pump and wavelength excitations. The model was used to simulate accurately the measured fiber amplifier degradation. Optimized fiber length and gain were calculated to improve the output power stability over time and increase the fiber lifetime. Furthermore, eight fibers have been fabricated with various Yb, Al, and P content using the MCVD process to optimize the core composition. The level of photodarkening in each fiber was evaluated by measuring separately rate coefficient and excess loss. It was found that all fibers followed a similar inversion-dependent rate while the maximum excess loss was dependent on the ratios [Al]/[Yb] and [P]/[Yb]. The proposed model allows for rapid evaluation and optimization of fiber parameters and operation conditions to assist Yb-doped laser system design in achieving the desired performance with low photodegradation.
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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) | 0.000 | 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 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".