Predicting instabilities of a tunable ring laser with an iterative map model
Bibliographic record
Abstract
Simple mathematical models have been unable to predict the conditions leading to instabilities in a tunable ring laser. Here we propose a nonlinear iterative map model for tunable ring lasers. Solving a reduced nonlinear Schrödinger equation for each component in the laser cavity, we obtain an algebraic map for each component. Iterating through the maps gives the total effect of one round trip. By neglecting the nonlinearity, we find a linearly chirped Gaussian to be the analytic fixed point solution, which we analyze asymptotically. We then numerically solve the full nonlinear model, allowing us to probe the underlying interplay of dispersion, modulation, and nonlinearity as the pulse evolves over hundreds of round trips of the cavity. In the nonlinear case, we find that the chirp saturates and the Fourier transform of the pulse becomes more rectangular in shape. Finally, for a nominal plane in the parameter space, we uncover a rich, sharp boundary separating the stable region and the unstable region where instabilities degrade the pulse into an unsustainable state.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".