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Record W2092893866 · doi:10.1364/josaa.27.000703

A comparison of modeling methods for ring resonator circuits

2010· article· en· W2092893866 on OpenAlexaff
Michael Gad, David Yevick, P. E. Jessop

Bibliographic record

VenueJournal of the Optical Society of America A · 2010
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsResonatorBenchmark (surveying)Coupling (piping)Electronic circuitRing (chemistry)Finite-difference time-domain methodContext (archaeology)Split-ring resonatorCoupling coefficient of resonatorsPower (physics)Equivalent circuitElectronic engineeringPhysicsComputer scienceOpticsMaterials scienceEngineeringChemistryVoltage

Abstract

fetched live from OpenAlex

We have previously introduced a "compound ring resonator circuit," in which several ring resonator (RR) cavities are coupled in a loop, and analyzed the resulting configuration with the coupling of modes in space (CMS) technique. In this work we compare the accuracy, simplicity and calculation time of three standard procedures, namely the FDTD, and the methods of coupling of modes in time (CMT) and CMS in the context of a two-dimensional (2D) complex ring resonator circuit. This provides a far more effective benchmark of the relative advantages of the methods than the analysis of far simpler structures performed by other authors. As part of these calculations, we further discuss the relationship between the power loss coefficients in the CMS and the CMT models. We verify that the CMT yields accurate and rapid results for small coupling coefficients and losses even for large waveguide circuits containing multiple rings.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.351
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2010
Admission routes1
Has abstractyes

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