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Record W2008069379 · doi:10.1364/oe.21.019624

Nanowires and sidewall Bragg gratings in silicon as enabling technologies for microwave photonic filters

2013· article· en· W2008069379 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsMcGill University
FundersCMC MicrosystemsNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaFonds de recherche du Québec – Nature et technologiesUniversity of WashingtonNational Science Foundation
KeywordsFiber Bragg gratingMaterials scienceOpticsSilicon photonicsSiliconOptoelectronicsGratingPhotonicsMicrowaveOptical filterWaveguidePhysicsWavelengthTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

We describe the use of various silicon photonic device technologies to implement microwave photonic filters (MPFs). We demonstrate four-wave mixing in a silicon nanowire waveguide (SNW) to increase the number of taps for MPFs based on finite impulse response filter designs. Using a 12 mm long SNW reduces the footprint by five orders of magnitude compared to silica highly nonlinear fiber while only requiring approximately two times more input power. We also demonstrate optical delays based on serial sidewall Bragg grating arrays and step-chirped sidewall Bragg gratings in silicon waveguides. We obtain up to 63 ps delay in discrete steps from 15 ps to 32 ps over a wide bandwidth range from 33 nm to at least 62 nm. These components can be integrated with other silicon-based components such as integrated spectral shapers and modulators to realize a fully integrated MPF.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.683

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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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