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Record W4301606424 · doi:10.1364/oe.473018

Electrically reconfigurable waveguide Bragg grating filters

2022· article· en· W4301606424 on OpenAlexfundno aff
Mostafa Khalil, Hao Sun, Essam Berikaa, David V. Plant, Lawrence R. Chen

Bibliographic record

VenueOptics Express · 2022
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsMaterials scienceFiber Bragg gratingFree spectral rangeGratingOptical filterWaveguideMultiphysicsFilter (signal processing)OptoelectronicsWavelengthFinite element methodPhysicsComputer science

Abstract

fetched live from OpenAlex

We propose and demonstrate an electrically reconfigurable waveguide Bragg grating filters in silicon-on-insulator using a multiple-contact heater element. There are six electrical pads connected to the heater element in an equidistant manner. These electrical pads allow to create different heat, and corresponding refractive index, distributions across the grating so that the local Bragg wavelength corresponding to the heated segments can be controlled. In turn, this control over the heat distribution allows the device to be reconfigured to implement different filter spectral responses. These filters are applicable for both wavelength division multiplexing systems and optical signal processing applications. As a verification, we demonstrate the generation of two (or more) separate filter bands with a spacing up to 35 nm or a Fabry-Pérot cavity with a 1.6 nm free-spectral range. Moreover, we explain a firm and accurate simulation framework of the proposed device based on COMSOL Multiphysics and the transfer matrix method, which is in excellent agreement with our experimental measurements.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score0.607

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)0.0010.000

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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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