Acoustic Wave Coupling in Dual-Wavelength Orthogonal Polarized Brillouin Random Fiber Laser Using Polarization-Maintaining Fiber
Bibliographic record
Abstract
Acoustic wave coupling in dual-wavelength orthogonal polarized Brillouin random fiber laser (BRFL) based on polarization-maintaining (PM) fiber is characterized experimentally for the first time. Dual-wavelength BRFL is generated when the pump light is injected to the Brillouin gain PM fiber at 45 degrees from the slow axis. The dynamics of intensity and frequency of dual-wavelength and single-wavelength BRFLs are investigated. The spectrum of Pearson’s correlation coefficient between different frequencies of the dual-wavelength BRFL shows several correlation peaks due to gain competition of two spatially overlapped coupled modes induced by acoustic wave coupling. The dual-wavelength BRFL presents a lower laser frequency drift with a standard deviation of 2.55 MHz and a larger relative intensity fluctuation with a standard deviation of 0.54 compared with that of single-wavelength BRFL (3.68 MHz and 0.32), which is attributed by increased photon-phonon coupling over the Brillouin gain fiber resulting from the coupling of acoustic waves in fast and slow axis due to 45 degrees pumping. In addition, replica symmetry breaking (RSB) is observed in dual-wavelength BRFL due to the increased gain competition of more random modes from acoustic wave coupling, which leads to correlated intensity fluctuations from trace to trace. The exploration of the internal spectral correlation, intensity fluctuation, RSB and frequency drift exposes the acoustic wave coupling in the dual-wavelength Brillouin random lasing process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".