MétaCan
Menu
Back to cohort
Record W4417168843 · doi:10.1109/lawp.2025.3641967

Toward a Fast and Accurate SFDTD Method Based on Eigenmode Analysis and Artificial Anisotropy

2025· article· W4417168843 on OpenAlexaff
Junfeng Wang, Hao Huang, Zhizhang Chen

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2025
Typearticle
Language
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsDalhousie University
FundersNational Natural Science Foundation of ChinaChongqing Postdoctoral Science Foundation
KeywordsNormal modeEigenmode expansionAnisotropyMode (computer interface)Numerical analysisDispersion (optics)Differential (mechanical device)

Abstract

fetched live from OpenAlex

This letter presented a fast and accurate spatial finite-difference temporal differential (SFDTD) method for time-domain electromagnetic modeling. First, the eigenmode analysis reveals that only a limited number of eigenmodes located at the top of the eigen-spectrum make significant contributions to the numerical solution. Then, by introducing artificial anisotropy (AA) parameters, an AA-SFDTD method characterized by low dispersion is proposed. Based on eigenmode analysis and by truncating the mode expansion order in the AA-SFDTD method, we develop a novel SFDTD approach that considers both speed and accuracy. Numerical simulation experiments validate the high efficiency and precision of the proposed method.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.018
GPT teacher head0.288
Teacher spread0.271 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Antennas and Wireless Propagation LettersSame topicElectromagnetic Simulation and Numerical MethodsFrench-language works237,207