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Record W4407639327 · doi:10.1109/tmtt.2025.3539939

Antenna-Circuit Modeling for Accelerated Simultaneous Co-Simulation Using Clustering Model-Order Reduction

2025· article· en· W4407639327 on OpenAlex
Jacob Martire, D.A. McNamara, Emad Gad

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2025
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReduction (mathematics)Model order reductionAntenna (radio)Cluster analysisEquivalent circuitComputer scienceElectronic engineeringRLC circuitElectrical engineeringEngineeringTelecommunicationsMathematicsAlgorithmVoltageCapacitorArtificial intelligence

Abstract

fetched live from OpenAlex

In this article, an approach for modeling radiation/scattering from antenna structures connected to a circuit is reported. This approach uses a single matrix formulation that combines a method of moments (MoMs) analysis of an antenna structure given that the antenna is being fed by a circuit represented using modified nodal analysis (MNA) equations. To reduce the computation time over some prescribed frequency bands, new cluster-based multiport model-order reduction (MOR) techniques are applied to the MoMs formulation. These techniques allow for a fast frequency sweep of the antenna-circuit model over a very large number of frequency points.

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.

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: none
Teacher disagreement score0.819
Threshold uncertainty score0.892

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 head0.041
GPT teacher head0.330
Teacher spread0.290 · 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