Caractérisation des pertes dépendant de la polarisation (PDL) dans les composants optiques tout-fibre (Biconiques)
Bibliographic record
Abstract
L'insertion des composants tout-fibre dans les reseaux de transmission optique a provoque une revolution complete dans les debits de transmission et dans l'architecture des reseaux de transmission. Les facteurs de degradation affectant le signal transmis dans ces reseaux sont devenus tres importants a etudier et a caracteriser. La polarisation de la lumiere et ses effets, telle que la perte dependant de la polarisation (PDL - Polarization Dependant Loss) et la dispersion de la polarisation (PMD - Polarization Mode Dispersion), sont les facteurs de degradation les plus etudies. Ce travail de these s'interesse a l'effet de la perte lie a l'etat de polarisation a l'entree d'un composant tout-fibre (biconique). L'objectif est de connaitre la sensibilite a la perte dependant de la polarisation (PDL) de ce composant. Plusieurs methodes de simulation de la PDL sont proposees. Ces methodes utilisent la forme geometrique de la structure du composant biconique comme une base de calcul. Une methode est basee sur la formalisme de Jones. Les autres methodes dependent de la PDL a partir de la theorie du couplage de modes associee a des perturbations aleatoires sur la forme geometrique de la structure biconique. Ces methodes ont ete appliquees sur des structures biconiques theoriques (creees par le programme de simulation) et sur des structures reelles (realisees par le banc de fabrication et de caracterisation). La realisation de plusieurs composants biconiques et la mesure de la PDL permettent de confronter ces methodes aux mesures experimentales.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".