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Record W2153140855 · doi:10.1109/aps.1994.408053

Spectral preconditioned CG-FFT method in electromagnetics analysis

2002· article· en· W2153140855 on OpenAlexaff
Yuan Zhuang, Allan D. Pierce, J. Litva

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPreconditionerFast Fourier transformConjugate gradient methodComputer scienceElectromagneticsMethod of moments (probability theory)AlgorithmMathematicsIterative methodElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

Presents an efficient spectral preconditioned conjugate gradient fast Fourier (SPCG-FFT) method for EM analysis. This technique takes full advantage of the FFT by carrying out the CG operation, constructing the preconditioner and operating the preconditioning in the frequency domain. It also has the additional advantage that no additional memory and only O(NlogN) additional operations are needed for constructing and storing the preconditioner. At the same time it has superior convergence properties compared with the conventional CG-FFT method. Two numerical examples, a long wire antenna and a planar microstrip dipole array, are given to show the great potential of this technique in solving 1D and 2D large EM problems.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.968

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)0.0320.000

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 head0.243
Teacher spread0.236 · 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.

Study designObservational
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
Published2002
Admission routes1
Has abstractyes

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