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The impact of laterally coupled grating microstructure on effective coupling coefficients

2010· article· en· W1966394584 on OpenAlexaff
Ronald Millett, Karin Hinzer, Abdessamad Benhsaien, Trevor J. Hall, Henry Schriemer

Bibliographic record

VenueNanotechnology · 2010
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGratingMaterials scienceOpticsDuty cycleCoupling (piping)FabricationCoupling coefficient of resonatorsLaserBlazed gratingRefractive indexWaveguideDiffraction gratingUltrasonic gratingMicrostructureOptoelectronicsPhysicsComposite material

Abstract

fetched live from OpenAlex

Lithographic fabrication may be used to define laterally coupled gratings of high refractive index contrast on waveguide ridges, eliminating the need for regrowth steps in such distributed feedback lasers. These may be made more amenable to fabrication by employing higher-order gratings. Reliable exploration of the laser design space requires that the radiating partial waves be accurately incorporated in numerical simulations. We modify the coupled-mode approach to fully consider the two-dimensional cross section, analyzing rectangular, sinusoidal, triangular and trapezoidal grating shapes. Effective coupling coefficients are determined for grating orders from first to third. We show that, by tailoring the grating microstructure, effective coupling coefficients up to double that of a 0.5 duty cycle rectangular grating can be achieved. The actual grating microstructure of an as-fabricated grating was analyzed and its effective coupling coefficient predicted as [Formula: see text]. This was found to be in excellent agreement with the value extracted from the amplified spontaneous emission spectrum, [Formula: see text].

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 score0.595
Threshold uncertainty score0.313

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 integrity0.0000.001
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 head0.003
GPT teacher head0.229
Teacher spread0.226 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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