Conical Double-Core Structure LP<sub>mn</sub> Mode Converter
Bibliographic record
Abstract
In this work, a LPmnmode converter is proposed based on a tapered double-core structure. With opposite changes of the two cores in radius dimension, matching the effective refractive index between the fundamental mode (LP01) in one core and one desired high-order mode in the other core is obtained, and the fundamental mode power is gradually converted to the high-order mode. The simulation results show that the mode conversion of LP01to any high-order mode of LP11, LP21, LP31, LP12, LP41, LP22, LP32, LP42and LP23modes can be obtained with a conversion efficiency of ~99%, ~96%, ~92%, ~93%, ~82%, ~92%, ~84%, ~85% and ~81% at the working wavelength of 1550 nm, respectively, and also conversion bandwidth (>80% conversion efficiency) is 265, 125, 130, 130, 100, 35 and 30 nm, respectively. Compared to the previously reported works, the proposed mode converter structure is more universal to support any of higher-order mode conversions with wider bandwidth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".