LMA fibers modal decomposition using image factor analysis
Bibliographic record
Abstract
A new method is presented for the analysis of the modal content of a beam travelling in a waveguide. This method uses a simple optical set up to record beam images. Depending on the application, the source can be broad band (BBS) or a tunable laser. The method uses the eigenmode profiles of the waveguide under test, either theoretical or experimental ones. In this case, the technique is applied to characterize the modal content of few moded large mode area (LMA) fibers. Such LMA fibers are typically used in high power fiber lasers and amplifiers to reduce sensitivity to non-linear effects. By calculating the scalar products of the unfolded experimental and theoretical 2D profiles, the modal content is obtained. Access to such cost effective and easy to implement diagnosis tool will greatly help improving modal quality preservation in components and systems based on the fundamental mode operation of few moded LMA fibers. The high precision and performance of the method is evaluated using both computer generated and experimental data sets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".