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Record W2377458668

Vectorial Effective Index Method for Photonic Crystal Fibers

2004· article· en· W2377458668 on OpenAlexaff
Yan Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsPhotonic-crystal fiberCladding (metalworking)Photonic crystalMaterials scienceIndex methodRefractive indexOptical fiberModalDispersion (optics)Bessel functionOpticsPhysicsOptoelectronicsComposite material
DOInot available

Abstract

fetched live from OpenAlex

The complex refractive index distribution of photonic crystal fibers makes a numerical algorithm necessary. An effective index method based on weak guidance approximation is often used to study the modal properties of such fibers including their dispersion properties. In this paper, a fully vectorial effective index method is formulated for photonic crystal fibers based on the solution of the vectorial characteristic equation and is used to compute the dispersion parameters of photonic crystal fibers. In analogy with step index fibers, the effective index of the photonic crystal fiber cladding can be calculated simply by substituting the appropriate Bessel functions of the electromagnetic field into the vectorial characteristic equation for step index fibers. The result obtained by the vectorial effective index method is in better agreement with those by the finite element methods and measured data.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.234
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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