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Record W2773336022 · doi:10.1109/jqe.2017.2780448

Integrated Circularly Polarized OAM Generator and Multiplexer for Fiber Transmission

2017· article· en· W2773336022 on OpenAlexaff
Yuxuan Chen, Leslie A. Rusch, Wei Shi

Bibliographic record

VenueIEEE Journal of Quantum Electronics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMultiplexerMultiplexingOpticsPhysicsDemultiplexerSingle-mode optical fiberOptical fiberComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Unlike linearly polarized modes in fiber, modes exploiting orbital angular momentum (OAM) are circularly polarized when propagating in fiber. The use of OAM modes for spatial multiplexing requires efficient, low cost mode generators and multiplexers. We propose such a device based on the standard 220-nm silicon-on-insulator platform, taking multiple single-mode data-modulated signals, and imprinting these signals on right- and left-circularly polarized OAM channels on a single, multiplexed output. The device is designed to easily couple to an OAM fiber with a ring-shaped core. This approach treating circular polarization within the multiplexer allows us to avoid the losses associated with filtering out unwanted polarization to create a single polarization. Designing the device to have an output matched to the OAM fiber mode profile also avoids mode size conversion. We describe our design methodology and optimization techniques using a transfer-matrix model and the finite-difference time-domain method. A candidate design is simulated and modal crosstalk is examined, showing that low-crosstalk OAM multiplexing can be achieved through direct fiber-to-chip coupling.

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: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.658

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 head0.017
GPT teacher head0.269
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

Citations15
Published2017
Admission routes1
Has abstractyes

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