Light coupling model for a photonic crystal fiber with air holes collapsed at the fiber end
Bibliographic record
Abstract
The air holes structured in a Photonic crystal fiber’s cladding are easily contaminated by dust and moisture. For some applications, the fibers need to be in contact with fluids. The capillary effect will then draw the fluid into the air holes and change the optical properties of the fiber. A simple solution to avoid this effect is to collapse these air holes near the fiber end face. This, however, will in turn significantly affect the optical properties in such a way that they will need to be specifically investigated. In this paper we present a theoretical model of light transmission in the area of a collapsed fiber end face. We demonstrate that the air hole collapsed PCF could be represented by an equivalent PCF fiber with complete holes. A shorter collapsed segment will lead to a higher accuracy of this model and to a higher power coupling efficiency than a longer collapsed segment. Error distributions are calculated for different incident angles and for different core sizes. A 0.7 m length of a PM-1550-01 polarization maintaining PCF fiber is experimentally investigated. The setup uses an optical fiber splicer to couple light from another PM-1550-01 PCF fiber to the investigated PCF fiber. A SLD is used as a light source. The transmitted light is measured by a EXFO Fibre-Optic Tester. By adjusting the distance between the launching fiber and the receiving PCF fiber (10 mm per step), the intensity-distance curves are generated for 3 different collapsed distances: 1. Air holes of PCF fiber are not collapsed; 2. Air holes are collapsed at about ~1/5 OD and 3. Air holes are collapsed at about ~1 OD. The analysis of these curves confirms the validity of the developed theoretical model.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".