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Record W3037139860 · doi:10.35848/1347-4065/aba073

Efficient coupling to slow light in a silicon slot waveguide with internal corrugations

2020· article· en· W3037139860 on OpenAlexafffund
Deepak V. Simili, Michael Čada, Jaromı́r Pištora

Bibliographic record

VenueJapanese Journal of Applied Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsDalhousie University
FundersEuropean Regional Development FundNatural Sciences and Engineering Research Council of Canada
KeywordsSlow lightMaterials scienceWaveguideCoupling lossOpticsGratingInsertion lossOptoelectronicsStopbandCoupling (piping)Slot-waveguideSiliconSilicon on insulatorOptical fiberSilicon photonicsPhysicsPhotonic crystalResonator

Abstract

fetched live from OpenAlex

Abstract We modeled, simulated and experimentally observed efficient slow light coupling to internally corrugated slot Bragg grating (ICSBG) waveguide on a silicon-on-insulator platform. A short step taper is utilized to evanescently couple to the slow light mode near the stopband edge, resulting in minimization of Fabry–Perot reflections due to group index mismatch and a minimum slow light coupling enhancement of ∼1 dB. This is important as it results in a lower insertion loss ICSBG waveguide, which is capable of low loss slow light propagation and therefore is an attractive option as a phase shifter structure for an on-chip slow light enhanced electro-optic modulator or integrated optic sensor 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 score0.118
Threshold uncertainty score0.378

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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