Depressed-clad large mode area amplifier fiber with selective doping yielding near diffraction-limited beam quality
Bibliographic record
Abstract
Large mode area (LMA) optical fibers are finding widespread use nowadays in high power fiber lasers and amplifiers. The lower numerical apertures allow for larger core diameters and therefore reduced intensity of guided lightwaves whilst preserving the near single-mode guidance. As the core diameter is made larger though, conventional LMA fibers support a growing number of modes and beam propagation factor - M2- gets worse unless provision is made to avoid the latter (even if bending-induced losses as a result of coiling the fiber to a prescribed diameter is assumed). Diverse strategies have been reported in the literature in the last decade or so to address the aforementioned issue. Selective doping [1-2] and multi-layer claddings with depressed index inner layer [3] are two such schemes. The former favors the amplification of the fundamental mode through confinement of rare-earth dopants to the central portion of the core whereas the latter results in increased differential bending losses as a result of the lower effective numerical aperture seen by higher-order modes (HOMs). Both of these methods are shown herein to be quite effective at suppressing HOMs for fibers with large core diameters when implemented all together.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".