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Record W3196886767 · doi:10.1109/jlt.2021.3110505

Analytical Expressions for Power Coupling Coefficients Into Graded-Index Fibers With Generalized Beam Launch Conditions

2021· article· en· W3196886767 on OpenAlexafffund
Shanglin Li, Mohammadreza Sanadgol Nezami, Odile Liboiron-Ladouceur

Bibliographic record

VenueJournal of Lightwave Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOffset (computer science)ComputationOpticsMulti-mode optical fiberMathematical analysisCoupling coefficient of resonatorsGaussianMathematicsPhysicsCoupling (piping)Optical fiberMaterials scienceComputer scienceAlgorithmResonator

Abstract

fetched live from OpenAlex

In this paper, we derive the closed-form analytical expressions of the power coupling coefficients for a Laguerre-Gaussian beam coupled into a graded-index fiber with either central, offset, or tilted launch. We further generalize to an arbitrary launching condition with the radial offset and the three-dimension angular tilt simultaneously occurring. The analytical results are in good agreement with the numerical ones and can be applied to manufactured graded-index multimode fibers with an index exponent parameter from 1.8 to 2.2. Using the derived analytical expressions, the computation time shortens by at least a four-order of magnitude compared to conventional numerical methods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.262
Teacher spread0.252 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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