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Record W2113218666 · doi:10.1109/aps.1995.530098

An efficient higher order numerical convolution for modelling Nth-order Lorentz dispersion

2002· article· en· W2113218666 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsWestern University
Fundersnot available
KeywordsConvolution (computer science)Robustness (evolution)Recursion (computer science)Lorentz transformationApplied mathematicsComputational electromagneticsMathematicsMathematical analysisNumerical analysisHyperboloid modelComputer scienceElectromagnetic fieldAlgorithmPhysicsClassical mechanicsGeometry

Abstract

fetched live from OpenAlex

Results of using a higher order numerical convolution technique to model Nth-order, Lorentz type, dispersive media are presented. The convolution integral arising in the electromagnetic constitutive relation is approximated by the trapezoidal rule of numerical integration and implemented using a newly derived one time step recursion relation. This new method is compared to previously published techniques on the problem of a transient electromagnetic plane wave propagating in a dispersive media. All the methods considered solve the first order wave equations using the standard finite difference time domain technique. The results presented show that the new method performs the same or better than the other methods in terms of accuracy, robustness, and memory requirements.

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 categoriesInsufficient payload (model declined to judge)
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 score0.791
Threshold uncertainty score0.999

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)0.0020.000

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 head0.030
GPT teacher head0.267
Teacher spread0.238 · 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