Linewidth Narrowing of a Dual Wavelength-Selectable, Ring Cavity Erbium-Doped Fiber Laser Using a Saturable Absorber
Bibliographic record
Abstract
The narrow linewidth fiber laser is useful in applications such as fiber sensing, optical communications, and spectroscopy. This paper presents an investigation of the model and an experiment of a stable, wavelength-selective, narrow linewidth, ring cavity erbium-doped fiber laser incorporating two fiber Bragg gratings (FBG) at 1530.18 nm and 1550.08 nm, respectively. An F-P tunable filter was used to select a specific wavelength after optimizing the spectral output from the two FBGs to measure their respective linewidths. The erbium-doped ring fiber laser was optimized by adjusting the optical cavity loss using a variable optical coupler at a coupling ratio of 95%. The variable coupler was set to an optimal coupling ratio of 95%, where the spectral output powers of 3.4 mW at 1530.18 nm and 3.1 mW at 1550.08 nm were achieved as the optimal fiber laser output powers. The balanced output power had an optical signal-to-noise ratio of (OSNR) of 61 dB for each wavelength. The linewidth was measured for both wavelengths without saturable absorbers, and 27.7 kHz and 28.3 kHz for 1530.18 nm and 1550.08 nm were obtained. Using the saturable absorber, the linewidths were narrowed to 25.3 KHz and 21.1 kHz for 1530.18 nm and 1550.08 nm, respectively.
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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 | 0.000 |
| Open science | 0.001 | 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 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".