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Record W2142446369 · doi:10.1109/20.952596

Iterative solvers for hierarchal vector finite element analysis of microwave problems

2001· article· en· W2142446369 on OpenAlex

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.

Bibliographic record

VenueIEEE Transactions on Magnetics · 2001
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsPreconditionerConjugate gradient methodFinite element methodIterative methodMatrix (chemical analysis)Dimension (graph theory)Sparse matrixApplied mathematicsMicrowaveComputer scienceEnhanced Data Rates for GSM EvolutionAlgorithmMathematical analysisMathematical optimizationMathematicsMaterials sciencePhysicsPure mathematics

Abstract

fetched live from OpenAlex

The finite element analysis of microwave devices reduces to the solution of a large, sparse matrix equation. Several iterative solution methods were tested on the matrices arising when high-order, hierarchical edge elements are used. The best algorithm tested was the conjugate gradient method, with a preconditioner based on symmetric successive overrelaxation. The number of iterations needed was found to increase only slowly with element order for the first three orders, despite the corresponding large increase in the matrix dimension. In all cases there was a rapid deterioration in performance when the element size exceeded about a tenth of a wavelength.

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: Methods · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.645

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 head0.022
GPT teacher head0.269
Teacher spread0.247 · 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