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Record W3154650849 · doi:10.1364/oe.420696

Complex spectral filters in silicon waveguides based on cladding-modulated Bragg gratings

2021· article· en· W3154650849 on OpenAlexafffund
Daniel Pereira-Martín, José Manuel Luque‐González, J. Gonzalo Wangüemert‐Pérez, Abdelfettah Hadij‐ElHouati, Íñigo Molina‐Fernández, Pavel Cheben, Jens H. Schmid, Shurui Wang, Winnie N. Ye, Jiřı́ Čtyroký, Alejandro Ortega‐Moñux

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsCarleton UniversityNational Research Council Canada
FundersNational Research Council CanadaMinisterio de Economía y CompetitividadJunta de AndalucíaGrantová Agentura České RepublikyMinisterio de Educación, Cultura y DeporteUniversidad de Málaga
KeywordsMaterials scienceCladding (metalworking)OpticsFiber Bragg gratingSilicon on insulatorOptical filterFree spectral rangeWaveguidePhotonicsCoupled mode theoryFabricationSilicon photonicsOptoelectronicsGratingLaser linewidthRefractive indexSiliconLaserWavelengthPhysics

Abstract

fetched live from OpenAlex

Spectral filters are important building blocks for many applications in integrated photonics, including datacom and telecom, optical signal processing and astrophotonics. Sidewall-corrugated waveguide grating is typically the preferred option to implement spectral filters in integrated photonic devices. However, in the high-index contrast silicon-on-insulator (SOI) platform, designs with corrugation sizes of only a few tens of nanometers are often required, which hinders their fabrication. In this work, we propose a novel geometry to design complex Bragg filters with an arbitrary spectral response in silicon waveguides with laterally coupled Bragg loading segments. The waveguide core is designed to operate with a delocalized mode field, which helps reduce sensitivity to fabrication errors and increase accuracy on synthesized coupling coefficients and the corresponding spectral shape control. We present an efficient design strategy, based on the layer-peeling and layer-adding algorithms, that allows to readily synthesize an arbitrary target spectrum for our cladding-modulated Bragg gratings. The proposed filter concept and design methodology are validated by designing and experimentally demonstrating a complex spectral filter in an SOI platform, with 20 non-uniformly spaced spectral notches with a 3-dB linewidth as small as 210 pm.

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 score0.321
Threshold uncertainty score0.775

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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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

Citations33
Published2021
Admission routes2
Has abstractyes

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