Influences of ASE on the performances of Q-switched ytterbium-doped fiber lasers
Bibliographic record
Abstract
The output characteristics of actively Q-switched ytterbium-doped fiber lasers (YDFL) are investigated in this paper. Our experimental results show that, the combined effect between the short switching time and the gain transient property of doped fiber causes the initial amplified spontaneous emission (ASE) power fluctuation, forming the multi-peak structure in the output pulse for either ring or linear cavity Q-switched YDFL. The pulse buildup time decreases with the rising of the pump. Moreover, since the broad-band ASE generated in the YDF is very high, it may saturate the doped fiber once the switch has been opened, making it difficult to achieve Q-switched laser oscillation for both fiber lasers. By using ASE filter to suppress the initial ASE, the gain supplied by the YDF can be greatly enhanced, which can not only decrease the threshold, but also greatly decrease the duration, and enhance the peak power of the Q-switched laser pulse as well. By using such an ASE filter, the Q-switched laser pulse with the peak power of 40.7 W and the duration of 30 ns has been achieved for the linear cavity YDFL pumped with 160 mW.
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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 | 0.002 |
| 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 | 0.001 |
| 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".