Analysis of the nonlinear optical loop mirror with feedback and low-birefringence twisted fiber in the loop
Bibliographic record
Abstract
The dynamical behavior of the nonlinear optical loop mirror (NOLM) with feedback and low birefringence twisted fiber in the loop is examined. It is found that the output of the NOLM with feedback depends on many parameters, including the fiber beat length, the polarization state of the counter-propagating beams in the loop, as well as the length, twist rate, and nonlinearities of the loop fiber. The placement of a quarter-wave plate (QWP) asymmetrically in the loop allows for the tuning of the bistable and chaotic output from the optical resonator. As well, the output polarization state of the NOLM with feedback is shown to rely on the QWP angle as well as the input power, which is of importance when using the NOLM with feedback in optical systems that have polarization sensitivity. As all fibers exhibit some degree of twist and birefringence, the addition of a QWP in the NOLM with feedback allows for an easy and practical measure of control of the bistable and chaotic regions of the nonlinear optical resonator, which is important when implementing the device in an optical system.
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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 | 0.001 |
| 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) | 0.001 | 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".