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Record W3112817786 · doi:10.1364/oe.411348

Spectral-dependent electronic-photonic modeling of high-speed VCSEL-MMF links for optimized launch conditions

2020· article· en· W3112817786 on OpenAlexafffund
Shanglin Li, Mohammadreza Sanadgol Nezami, Shubhankar Mishra, Odile Liboiron-Ladouceur

Bibliographic record

VenueOptics Express · 2020
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsVertical-cavity surface-emitting laserMulti-mode optical fiberOpticsBeam propagation methodBandwidth (computing)PhotonicsMaterials scienceModal dispersionAttenuationTransmission (telecommunications)OptoelectronicsOptical fiberPhysicsLaserDispersion-shifted fiberComputer scienceFiber optic sensorRefractive indexTelecommunications

Abstract

fetched live from OpenAlex

We present spectral-dependent electronic-photonic modeling of vertical-cavity surface-emitting laser (VCSEL)-multimode fiber (MMF) links for next-generation high-speed interconnects. The beam coupling processes, between the VCSEL and the MMF and between the MMF and the photodetector (PD), are discussed, with spectral-dependent three-dimensional launch conditions analyzed. The model accounts for fiber effects on the transmission performance, specifically modal attenuation, dispersion, mode mixing, and mode partition noise. An advanced split-step small-segment (4-S) method simulates the signal evolution over the MMF with high accuracy and high efficiency. Experimental validation at 25 Gbps confirms the high accuracy of the VCSEL-MMF link model. The model reveals that larger radial offsets can further excite lower-order mode groups reducing the power distributed to higher-order groups when a tilted beam couples to the input fiber facet. With an optimized misalignment launch, the modal bandwidth is greatly improved by 3.8-fold compared to the conventional center launch. The model helps determine the optimum launch condition to improve link performance metrics such as transmission reach.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.950

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 head0.020
GPT teacher head0.237
Teacher spread0.217 · 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 designSimulation or modeling
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

Citations12
Published2020
Admission routes2
Has abstractyes

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