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Record W1966890928 · doi:10.1364/oe.16.017616

Demultiplexer with blazed waveguide sidewall grating and sub-wavelength grating structure

2008· article· en· W1966890928 on OpenAlexaff
Przemek J. Bock, Pavel Cheben, A. Delâge, Jens H. Schmid, Dan‐Xia Xu, Siegfried Janz, Trevor J. Hall

Bibliographic record

VenueOptics Express · 2008
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOpticsGratingBlazed gratingMaterials scienceDiffractionDiffraction gratingUltrasonic gratingDiffraction efficiencyHolographic gratingWaveguideDemultiplexerWavelengthOptoelectronicsMultiplexerPhysicsMultiplexingTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

We propose an original diffraction grating demultiplexer device with a very small footprint, designed for the silicon-on-insulator waveguide platform. The wavelength dispersive properties are provided by a second-order diffraction grating designed to be lithographically defined and etched in the sidewall of a curved Si waveguide. The grating is blazed to maximize the -1st order diffraction efficiency. The diffracted light is coupled into the silicon slab waveguide via an impedance matching subwavelength grating gradient index antireflective interface. The waveguide is curved in order to focus the light onto the Rowland circle, where different wavelengths are intercepted by different receiver waveguides. The phase errors were substantially reduced using an apodized design with a chirped grating, which assures a constant effective index along the grating length. The simulated crosstalk is -30 dB. The device has 15 channels with a spacing of 25 nm, thus a broadband operational bandwidth of 375 nm. Its performance approaches the diffraction limit. The layout size is 90 microm x 140 microm, which is the smallest footprint yet reported for a mux/dmux device of a similar performance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.813

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 head0.010
GPT teacher head0.195
Teacher spread0.184 · 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 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

Citations24
Published2008
Admission routes1
Has abstractyes

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