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Record W3199776331 · doi:10.1364/oe.435669

Low-loss broadband bi-layer edge couplers for visible light

2021· article· en· W3199776331 on OpenAlexaff

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoupling lossWaveguideBroadbandLithographyCoupling (piping)Photonic integrated circuitEnhanced Data Rates for GSM EvolutionVisible spectrumWavelengthFacet (psychology)

Abstract

fetched live from OpenAlex

Low-loss broadband fiber-to-chip coupling is currently challenging for visible-light photonic-integrated circuits (PICs) that need both high confinement waveguides for high-density integration and a minimum feature size above foundry lithographical limit. Here, we demonstrate bi-layer silicon nitride (SiN) edge couplers that have ≤ 4 dB/facet coupling loss with the Nufern S405-XP fiber over a broad optical wavelength range from 445 to 640 nm. The design uses a thin layer of SiN to expand the mode at the facet and adiabatically transfers the input light into a high-confinement single-mode waveguide (150-nm thick) for routing, while keeping the minimum nominal lithographic feature size at 150 nm. The achieved fiber-to-chip coupling loss is about 3 to 5 dB lower than that of single-layer designs with the same waveguide confinement and minimum feature size limitation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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.

Opus teacher head0.014
GPT teacher head0.238
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations51
Published2021
Admission routes1
Has abstractyes

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