Reducing frequency fluctuation in a Brillouin random fiber laser by a random fiber grating ring resonator
Bibliographic record
Abstract
Frequency fluctuation is a major problem in high-precision metrology as real-time optical frequency measurement is not available with commercial photodetectors; alternatively, frequency-stabilized lasers as a reference are also not accessible in most laboratories. In this study, we propose and demonstrate a polarization-maintaining random fiber grating ring (PM-RFGR) resonator in a PM Brillouin random fiber laser (BRFL) to achieve sub-MHz frequency drift, which is measured by the optical beat of the random laser and the pump laser. Experimental results show that longitudinal modes are suppressed in the BRFL owing to the feedback of the RFGR resonating with one longitudinal mode of the random laser. The BRFL shows mode-hopping-free operation over 14.9 s due to the self-adjustment of random modes with small frequency difference to thermal and acoustic variations and self-injection locking through RFGR. As a result, a small frequency drift of ∼340 kHz with single-longitudinal mode is achieved in the BRFL enabled by the RFGR, which offers an all optical locking mechanism for optical frequency stabilization.
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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 | 0.001 |
| 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".