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Record W2613357406 · doi:10.1109/jphot.2017.2703857

A CMOS Compatible Ultracompact Silicon Photonic Optical Add-Drop Multiplexer with Misaligned Sidewall Bragg Gratings

2017· article· en· W2613357406 on OpenAlexafffund
Md. Ghulam Saber, Zhenping Xing, David Patel, Eslam El‐Fiky, Nicolás Abadía, Yun Wang, Maxime Jacques, Mohamed Morsy-Osman, David V. Plant

Bibliographic record

VenueIEEE photonics journal · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcGill University
FundersCMC MicrosystemsNatural Sciences and Engineering Research Council of CanadaMcGill UniversityUniversity of Washington
KeywordsExtinction ratioMultiplexerSilicon on insulatorOpticsMaterials scienceFiber Bragg gratingLithographyOptoelectronicsSilicon photonicsInterferometryElectron-beam lithographyPhotonicsSiliconWavelengthMultiplexingPhysicsResistElectronic engineering

Abstract

fetched live from OpenAlex

We experimentally and via simulations demonstrate ultracompact single-stage and cascaded optical add-drop multiplexers using misaligned sidewall Bragg grating in a Mach-Zehnder interferometer for the silicon-on-insulator platform. The single-stage configuration has a device footprint of 400 μm × 90 μm, and the cascaded configuration has a footprint of 400 μm × 125 μm. The proposed designs have 3-dB bandwidths of 6 nm and extinction ratios of 25 dB and 51 dB, respectively, and have been fabricated for the transverse electric mode. A minimum lithographic feature size of 80 nm is used in our design, which is within the limitation of 193 nm deep ultraviolet lithography.

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 score0.004

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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

Citations45
Published2017
Admission routes2
Has abstractyes

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