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Record W2131527274 · doi:10.1109/tmtt.2003.809620

An efficient numerical interface between FDTD and haar MRTD-formulation and applications

2003· article· en· W2131527274 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 Microwave Theory and Techniques · 2003
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
FundersDeutscher Akademischer AustauschdienstU.S. Department of Defense
KeywordsFinite-difference time-domain methodFinite difference methodMathematicsBoundary value problemHaar waveletTime domainAlgorithmMathematical analysisWaveletComputer scienceElectronic engineeringWavelet transformOpticsPhysicsDiscrete wavelet transformEngineering

Abstract

fetched live from OpenAlex

A hybrid finite-difference time-domain (FDTD)/Haar multiresolution time-domain (MRTD) technique for the time-domain analysis of microwave structures is proposed in this paper. The salient features of the presented algorithm are, first, its inherent stability that stems from the matching of the dispersion properties of FDTD and Haar MRTD and, second, its applicability to arbitrarily high wavelet order MRTD schemes. Thus, the application of the MRTD technique to the modeling of open structures and inhomogeneous circuit geometries is facilitated. In particular, the straightforward implementation of perfectly matched layer type and Mur's absorbing boundary conditions is attained. The fact that the proposed interface involves no spatial or temporal interpolations or extrapolations indicates its potential to efficiently connect FDTD and Haar MRTD.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.765
Threshold uncertainty score0.587

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 head0.009
GPT teacher head0.274
Teacher spread0.265 · 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