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Record W2763648230 · doi:10.1364/oe.25.025310

Spectral engineering of subwavelength-grating-based contradirectional couplers

2017· article· en· W2763648230 on OpenAlexafffund
Behnam Naghdi, Lawrence R. Chen

Bibliographic record

VenueOptics Express · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsExtinction ratioOpticsGratingMultiplexerMaterials scienceTaperingWaveguideCladding (metalworking)Power dividers and directional couplersOptoelectronicsInsertion lossPhysicsMultiplexingTelecommunicationsWavelength

Abstract

fetched live from OpenAlex

We tailor the spectral characteristics of silicon photonic contradirectional couplers (Contra-DCs), where the design of the coupler is based on placing a subwavelength grating (SWG) waveguide next to a strip waveguide. By tapering the gap distance between the SWG and strip waveguides, we demonstrate a compromise between sidelobe suppression and pass-band/stop-band extinction ratio such that the performance of the device as a potential optical (de)multiplexer is improved. The designs with different pass-band bandwidths of 12 nm, 9 nm, and 6 nm show 10 dB to 20 dB sidelobe suppression ratio and 15 dB to 35 dB extinction ratio. We also obtain a resonant transmission peak in the stop-band of the spectral response of the device by introducing a π phase shift into the gratings of the SWG waveguide. The resonant peak has 1 nm bandwidth and 7 dB extinction ratio, where the use of the SWG waveguide in the structure of such coupler allows the characteristics of the resonant peak to be highly sensitive to the cladding material, which is of strong desire in integrated sensing applications.

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 score0.181
Threshold uncertainty score0.542

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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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

Citations21
Published2017
Admission routes2
Has abstractyes

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