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Record W4388733895 · doi:10.1002/mop.33954

Padé via Arnoldi with single‐size matrix simplification for electromagnetic fast frequency sweep

2023· article· en· W4388733895 on OpenAlexaff
Li Ma, Qi‐Jun Zhang, Jing Jin, Wei Liu, Jianan Zhang

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsCarleton University
FundersFundamental Research Funds for the Central UniversitiesCentral China Normal UniversityGovernment of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsLanczos resamplingMatrix (chemical analysis)AlgorithmMicrowaveLanczos algorithmMathematicsComputer scienceMathematical optimizationPhysicsEigenvalues and eigenvectorsMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

Abstract This paper proposes a new Padé via Arnoldi algorithm with single‐size matrix simplification for electromagnetic (EM) fast frequency sweep. New equations are derived to reduce the double‐size system matrix to single‐size system matrix. We also propose a systematic algorithm to calculate S‐parameters using the simplified single‐size system matrix. Using the proposed algorithm, the EM responses can be obtained with the same accuracy while consuming much less time compared with that using the existing double‐size matrix Padé via Lanczos. The proposed algorithm is demonstrated by two microwave examples.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.233
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

Citations0
Published2023
Admission routes1
Has abstractyes

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