Design Analysis of OAM Fibers Using Particle Swarm Optimization Algorithm
Bibliographic record
Abstract
We study the design of ring core fibers (RCFs) supporting orbital angular momentum (OAM) modes for mode division multiplexing (MDM) transmission systems. We develop target criteria to optimize fiber designs using a particle swarm optimization (PSO) algorithm under fabrication constraints. Effective index separation Δneffand polarization purity of each OAM mode are known to determine modal crosstalk levels. To reduce the complexity of multiple-input multiple-output (MIMO) processing required to compensate for modal crosstalk, we define an objective function based on these quantities. Our design analysis focuses on four different concepts of step-index RCF leading to different modal and structural characteristics. The optimum design for each concept is derived using the PSO algorithm. We investigate the impact of hollow-core and/or higher-order radial modes on Δneffand polarization purity. Design strategies for increasing Δneffand polarization purity are discussed in light of robustness to fabrication errors. We finally discuss the scalability and potential limitations of this design.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".