Real-time monitoring of the dynamics of Brillouin fiber lasers with random feedback
Bibliographic record
Abstract
Brillouin fiber lasers (BFLs) with random feedback have become multifunctional and programmable light sources. The evolution of intensity and frequency during lasing establishment can be controlled by varying the scattering pattern and the strength of the feedback. However, the buildup dynamics of BFLs with different feedback is not fully understood. Here, we present a method to measure the buildup dynamics of BFLs with Rayleigh scattering (RS) fiber and random fiber grating (RFG) feedback that exploits real-time intensity and frequency characterizations. A narrow pump pulse is used to observe intensity fluctuations at different round trips. Experimental results demonstrate three different states during the buildup process of random BFLs, including spontaneous noise, beating dynamics, and stable lasing. The BFL with RS fiber feedback exhibits a lower intensity noise and a shorter buildup time than the BFL with RFG feedback, while the cavity BFL exhibits the highest intensity noise. Furthermore, we investigate the high-resolution spectral evolution by combining the optical heterodyne method and a tunable narrow optical gate. We observe that the number of lasing spikes decreases with increasing round trips in random BFLs attributed by the optical filter effect from the RS fiber and the RFG, which reduces the lasing spikes with low gain, while the number of modes remains constant in the cavity BFL. The frequency evolution is similar to that in intensity dynamics. Understanding buildup dynamics will be beneficial for the design of complex lasers with specific features useful for various applications.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".