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Record W2061809286 · doi:10.1109/jqe.2004.841615

Photonic crystal waveguide analysis using interface boundary conditions

2005· article· en· W2061809286 on OpenAlexaff
Emanuel Istrate, Edward H. Sargent

Bibliographic record

VenueIEEE Journal of Quantum Electronics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotonic crystalWaveguideOpticsDispersion (optics)YablonovitePhotonicsCoupling (piping)Photonic integrated circuitReflection (computer programming)Boundary value problemMaterials scienceBoundary (topology)OptoelectronicsPhysicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

Devices based on combinations of photonic bandgap materials are understood intuitively in terms of the dispersion relations of the constituent periodic and locally homogeneous media. Quantitatively, though, photonic crystal-based devices are analyzed using numerical simulations which take no advantage of the a priori understanding of underlying periodic building-block materials. Here we unite the quantitative and qualitative pictures of photonic crystal devices and their design. We describe photonic crystals as effective media and impose boundary conditions between photonic crystals and homogeneous materials. We express optical field profiles as superpositions of plane waves in the homogeneous parts and propagating or decaying Bloch modes in the crystals, connected by transmission, reflection, and diffraction coefficients at the interfaces. We calculate waveguide modes, coupling lengths in directional couplers, and coupling between waveguides and point defects, achieving agreements of approximately 1% in frequencies and around 2% in quality factors. We use the new approach to optimize waveguide properties in a forward-going method, instead of the usual iterative optimizations.

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 score0.537
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.309
Teacher spread0.293 · 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

Citations15
Published2005
Admission routes1
Has abstractyes

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