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Record W2166119499 · doi:10.1109/apmc.1999.829891

Solving arbitrary resonant structures with an efficient eigen-based MRTD formulation

2003· article· en· W2166119499 on OpenAlexaff
Zhizhang Chen, J. Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputationMaxwell's equationsAlgorithmEigenvalues and eigenvectorsFinite-difference time-domain methodWaveletFast Fourier transformFourier transformTime domainGridSparse matrixMathematicsComputer scienceMathematical analysisApplied mathematicsGeometryPhysicsOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

Numerical computation of a high-Q resonant structure may pose as a challenge for its requirements computation time and memory. Circumvent the problem, we developed an eigen-based formulation, called the "Spatial Multi-Resolution Time-Domain (SPATIAL-MRTD) method, based on the recently developed MRTD method. In it, wavelets are used to expand the electromagnetic fields in spatial domain while the time differentials are kept with the Maxwell's equations. The final formulation is a sparse eigenvalue problem. By applying the sparse matrix techniques, resonant frequencies and modes are obtained effectively and efficiently. Like MRTD, low number of spatial grid points (as low as two points per wavelength) is required. Unlike MRTD, direct recursive time-marching calculations are not needed. As a result, the method is numerical-instability free. In addition, no post-simulation data-processing, such as discrete Fourier Transform, is required.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.390

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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 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

Citations0
Published2003
Admission routes1
Has abstractyes

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