Stable room-temperature multiwavelength erbium-doped fiber ring laser
Bibliographic record
Abstract
Erbium-doped fiber lasers can find many applications such as WDM systems, fiber-optic sensors and microwave photonics, thanks to their high power, narrow linewidth and low noise. The key factor that limits the number of stable lasing wavelengths achieved at room temperature is the strong gain homogenous broadening of erbium-doped fiber. Different approaches have been approached. These approaches include the use of a phase shifter in the fiber ring cavity to reduce the homogenous broadening, and the use of Nitrogen to cool the erbium-doped fiber with a reduced homogenous broadening. Clearly, the approach using a phase shifter increases the system cost and the approach using Nitrogen is not suitable for practical applications. In this paper, we propose a novel approach to achieving stable multiwavelength lasing at room temperature using a semiconductor optical amplifier in the fiber ring laser cavity. In the fiber laser, the erbium-doped fiber is used as a gain medium. The semiconductor optical amplifier is used as a phase shifter. The semiconductor optical amplifier is driven by a sinusoidal wave. The refractive index change of the semiconductor optical amplifier leads to a phase shift, which effectively suppresses the homogenous broadening and cross-gain saturation. In addition, since the semiconductor optical amplifier is biased at the transparent point, no insertion loss is introduced. In the experiment, the modulation voltage to the semiconductor optical amplifier can be as low as 10 mV, which is much lower than that used in a phase modulator (10 V). Experiment is being carried out and more experimental results will be reported.
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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 | 0.001 |
| Open science | 0.001 | 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".