Tunable Fabry-Perot filter using hollow-core photonic bandgap fiber and micro-fiber for a narrow-linewidth laser
Bibliographic record
Abstract
A novel tunable fiber Fabry-Perot (FP) filter is proposed and demonstrated by using a hollow-core photonic bandgap fiber (HC-PBF) and a micro-fiber. The interference cavity is a hollow core of HC-PBF. One of the reflection mirrors is the splicing point between a section of HC-PBF and a single mode fiber. The other reflection mirror is a gold-coated end of micro-fiber that uses chemical etching process to obtain the similar diameter as the core of HC-PBF. Hence the movable mirror can be adjusted with long distance inside the hollow core of HC-PBF. Tunable FP filter is used as a mode selecting component in the reflection mode to implement stable single longitudinal mode (SLM) operation in a ring laser. With FP cavity length of 0.25 ± 0.14 mm, the wavelength of SLM laser can be tuned over 1554-1562 nm with a tuning step of 0.2-0.3 nm, a side-mode suppression ratio (SMSR) of 32-36 dB and a linewidth of 3.0-5.1 kHz. With FP cavity length of 2.37 ± 0.37 mm, the SLM laser can be tuned over 1557.3-1560.2 nm with a tuning step of 0.06-0.1 nm, a SMSR of 44-51 dB and a linewidth of 1.8-3.0 kHz.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".